2026-05-16T04:42:31+02:00 https://library.wur.nl/oai

oai:library.wur.nl:wurpubs/31fbe623-d2f3-4df2-be7a-c75c458e9723 2026-05-13 dataset edurep openaire public

Acevedo-Siaca, Liana Javadi Asayesh, Elahe Dataset Dataset for: Using ΦPSII and leaf temperature as indicators of non-steady-state photosynthesis and stomatal conductance during stepwise changes in light intensity 2026 Publication Title: Using ΦPSII and leaf temperature as indicators of non-steady-state photosynthesis and stomatal conductance during stepwise changes in light intensity Authors: Elahe Javadi Asayesh, Leo F.M. Marcelis, Liana G. Acevedo-Siaca, Elias Kaiser. Study objectives: to determine whether variations in non-steady-state values of chlorophyll fluorescence and leaf temperature reflect differences in key gas exchange traits under fluctuating light conditions. The dataset consists of 9 files containing raw gas exchange and chlorophyll fluorescence measurements collected using an infra-red gas analyzer (LI-6800). Data were obtained from 9 species, each represented by 9 biological replicates, under stepwise changes in light intensity. Each file is named according to the corresponding species, and replicates are identified as “Rep X” in separate sheets within each file. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-for-using-φpsii-and-leaf-temperature-as-indicators-of-non 10.17887/wur01-tmwyjn https://edepot.wur.nl/716096 CO2 assimilation Natural Sciences - Biological sciences (1.6) chlorophyll fluorescence leaf temperature non-steady-state photosynthesis photosynthetic induction stomatal conductance Wageningen University & Research

oai:library.wur.nl:wurpubs/9170ce9d-6f31-4c2f-9285-e9ef4ba51fdc 2026-05-12 dataset edurep openaire public

Bäthge, Annemarie Ruz Vargas, Claudia Lischeid, Gunnar Collenteur, Raoul Cuthbert, Mark Fleckenstein, Jan H. Floerke, Martina De Graaf, Inge Gnann, Sebastian Hartmann, Andreas Huggins, Xander Moosdorf, Nils Wada, Yoshihide Wagener, Thorsten Reinecke, Robert Dataset GROW: A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System 2026 GROW (the global-scale integrated GROundWater package) is a global-scale, analysis-ready, quality-controlled dataset that combines groundwater depth or level time series from around the world with associated Earth system variables. The dataset contains > 200,000 time series from 55 countries, 91% from North America, India, Europe, and Australia, in a daily, monthly, or yearly temporal resolution, accompanied by 36 time series or static attributes of meteorological, hydrological, geophysical, vegetation, and anthropogenic variables (e.g., precipitation, drainage density, rock type, NDVI, land use). 34 data flags regarding well features (e.g., coordinates and country), as well as time series characteristics (e.g., gap fraction or autocorrelation), facilitate quick data filtering. The dataset is organized in two files: A table containing time series (grow_timeseries.csv/ .parquet) and one table with static attributes (grow_attributes.csv/.parquet). The columns of the attributes and time series table are described in Table 1 & 2 in the Readme file. Additionally, the attributes are given as json-file (grow_attributes.json) with well locations as geometry. This file can be opened directly in GIS programs. The time series with different temporal resolutions are stored in a single table. Time-resolved variables with unit of quantity are all given in mm/year regardless of the temporal resolution of the time series. This enables the straightforward derivation of further aggregations across different time series resolutions, subsets, and statistics. When the user wants to use only daily or monthly data, GROW can be easily subset and the unit can be transferred to the target resolution. An example of use that demonstrates how the data is subset and prepared is given on GitHub (https://github.com/EarthSystemModelling/GROW/blob/main/usage_example.py) and Zenodo (python_scripts). Citation This dataset is licensed under Creative Commons Attribution Non-Commercial ShareAlike 4.0 International License (CC-BY-NC-SA 4.0; https://creativecommons.org/licenses/by-nc-sa/4.0/) When using the data, please cite Bäthge et al. “GROW: A Global-Scale Time Series Dataset for Groundwater Studies within the Earth System” (full citation available on Zenodo) Johannes Gutenberg University text/html https://research.wur.nl/en/datasets/grow-a-global-scale-time-series-dataset-for-groundwater-studies-w 10.5281/zenodo.15149479 https://edepot.wur.nl/715937 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/42f6ff26-06b8-495a-a821-d6b954eb811f 2026-05-12 dataset edurep openaire public

Broekhuizen, H. Elkhuizen, S. Wagemakers, A. Dataset Data onderliggend aan de publicatie: Samen Werken aan Sterke Wijken 2026 Research dataset supporting the publication “Samen Werken aan Sterke Wijken,” containing qualitative materials including policy documents (n=25), interviews (n=23), ripple effect mapping sessions (n=3), observations (n=113), and supporting research documentation across three municipalities. The objective was to explore which mechanisms promote or hinder cross-sector collaboration with citizen participation in priority neighborhoods. Sensitive data underlying this datapackage are archived internally at WUR and not present in this published data package. Contact our department secretariat for information about retention periods at office.hso@wur.nl. Arrangements have been made to allow continued access to sensitive data when requested and formal agreements between parties have been made. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-onderliggend-aan-de-publicatie-samen-werken-aan-sterke-wijke 10.17026/ss/dkwish https://edepot.wur.nl/715769 Social Sciences citizen participation community engagement health inequalities health promotion healthy living environment Wageningen University & Research

oai:library.wur.nl:wurpubs/44322247-d1da-48e2-9d2e-abf06bae2a8e 2026-05-06 dataset edurep openaire public

Bouwmeester, Hein Heuvelink, Gerard Msami, Jessey Legg, James Dataset Data underlying the publication: Spatial prediction of cassava seed market performance in Tanzania's Lake Zone 2026 This dataset contains the data, code, and outputs supporting a spatial analysis of cassava seed market performance among Commercial Seed Entrepreneurs (CSEs) in Tanzania's Lake Zone. It includes anonymised survey data from 66 CSEs (2022 IITA-Tanzania phone survey, after quality control), a 25-band raster stack of environmental, agricultural, and infrastructural predictors at 5-arcminute resolution, R scripts that reproduce the published Random Forest model and Structural Potential Index analyses, and the full set of figures and summary outputs. The materials enable independent verification of the published numerical results and figures, and provide a starting point for similar analyses elsewhere. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-spatial-prediction-of-cassava-see 10.4121/17d90a7c-e097-409c-b650-7834e535795b https://edepot.wur.nl/715437 Lake Zone SPAM Tanzania Time: 1970-2022 agricultural mapping cassava random forest seed systems smallholder agriculture spatial prediction structural potential index Wageningen University & Research

oai:library.wur.nl:wurpubs/b62b858a-9df8-4340-adfd-edf3e632b0f0 2026-04-23 dataset edurep openaire public

van Dijk, J. Kamermans, P. Poos, J.J. Jansen, H.M. Dataset Data underlying the publication: Co-cultivating sugar kelp and blue mussel in a mesocosm experiment 2026 Low trophic aquaculture (LTA) is receiving increasing interest, this includes the cultivation of seaweed and shellfish. This study explores any potential benefits or disadvantages of co-cultivating two LTA species, sugar kelp (Saccharina latissima) and the blue mussel (Mytilus edulis), in a mesocosm experiment. The experimental setup comprised 4 treatments divided over 24 tanks: either seaweed or mussels, both in co-cultivation, and a control with neither. The aim was to assess the growth and performance of S. latissima and M. edulis in the different treatments during the production cycle of seaweed (November to April). Wageningen University & Research text/html https://research.wur.nl/en/datasets/b62b858a-9df8-4340-adfd-edf3e632b0f0 10.4121/1e71dec4-ffd0-40f9-8005-161cfa823c7d https://edepot.wur.nl/714784 Clearance rate Mesocosm Mussel filtration Mytilus edulis Nitrogen dynamics Phytoplankton Saccharina latissima Wageningen University & Research

oai:library.wur.nl:wurpubs/fa6cc6df-50a4-4a6e-a923-04ff6ae616c8 2026-04-21 dataset edurep openaire public

Huijsmans, Jan Goedhart, Paul Dataset Supplementary material for the paper: Revisiting 414 experiments to evaluate ammonia emission and mitigation measures for field-applied manure in The Netherlands 2026 This repository contains the data and data processing scripts for ammonia losses from field-applied manure as presented in the paper “Revisiting 414 experiments to evaluate ammonia emission and mitigation measures for field-applied manure in The Netherlands” by Jan F.M. Huijsmans & Paul W. Goedhart. It describes selected data and scripts for the statistical analyses to create Figures, Tables and Model regression coefficients for a regression model on ammonia losses model for field-applied manure. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-material-for-the-paper-revisiting-414-experiments-t 10.4121/c420dba5-5e39-4306-adfe-f7e8c56b7582 https://edepot.wur.nl/714619 ammonia application technique arable land bare soil emission factor field-applied manure grassland manure treatment mitigation measures wheat Wageningen University & Research

oai:library.wur.nl:wurpubs/1db2a382-f54c-4110-923c-e1fc9dfdd38a 2026-04-21 dataset edurep openaire public

Kalumbilo, Mubonda Mwaba, Mukuka Banda, Agripina Chuba, David van Mastrigt, Oscar Schoustra, Sijmen E. Smid, Eddy J. De Deyn, Gerlinde Dataset Data supporting the publication: How plant species origin, identity and cereal type shape the microbial composition and functional properties of Munkoyo, a traditional fermented beverage 2026 This dataset supports a study on the microbial and functional diversity of Munkoyo, a traditional non-alcoholic fermented cereal beverage widely consumed in Zambia and neighbouring countries. Munkoyo is produced through spontaneous fermentation of cooked cereals inoculated with roots from specific wild plant species, locally referred to as “Munkoyo plants.” The dataset comprises three complementary experiments designed to evaluate the effects of (i) plant species identity, (ii) geographic origin, and (iii) cereal substrate (maize or sorghum) on bacterial community composition and functional properties of the beverage.Results show that Munkoyo produced using roots from different co-occurring plant species exhibits distinct fermentation dynamics. Final pH values after 72 hours ranged from 3.5 to 4.5, with Rhynchosia insignis-derived beverages showing the lowest pH, while Eminia holubii-derived Munkoyo exhibited faster acidification, reaching minimum pH within 24 hours. In addition, primary metabolite profiles, aroma composition, and bacterial community structure differed significantly between these plant species. Geographic origin effects were assessed using R. insignis roots collected from three districts. The origin significantly influenced titratable acidity, aroma profiles, and bacterial community composition, indicating strong terroir effects.Cereal substrate (maize versus sorghum) did not significantly affect final pH but did influence bacterial community composition.Overall, the dataset demonstrates that plant species identity, geographic origin, and substrate type are key drivers of microbial community assembly and functional characteristics in Munkoyo fermentation. These findings contribute to understanding the role of indigenous microbial resources in traditional fermentation systems and support future efforts in product standardisation and valorisation. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-supporting-the-publication-how-plant-species-origin-identity 10.4121/1d03823f-22fa-47b2-b060-e057d878992a https://edepot.wur.nl/714520 Biological sciences Munkoyo bacterial microbiome fermented cereal beverage plant root endosphere Wageningen University & Research

oai:library.wur.nl:wurpubs/093db0ec-cfd1-4596-8ab5-5522079fc807 2026-04-20 dataset edurep openaire public

Nieuwland, Maaike Zigon, Uros de Wijk, Rene de Rosa Spierings, Karen Vingerhoeds, Monique Dataset Data underlying the publication: Plant-based patties – towards understanding texture and taste 2026 Meat replacers are one of the options to nudge consumers towards a more sustainable, more healthy diet. Unfortunately, quality of meat replacers is usually not up to the standards of their animal counterparts. In this study the effects of five ingredient variations (total fat content, type of fat, type of texturized protein, methylcellulose content and citrus fibre content) for a vegan patty were investigated for their effect on flavour and texture. A sensory QDA panel was applied, supplemented with analytical measurements quantifying serum loss and texture. Most variation in the patties was observed in the texture parameters, that also correlated well with the analytical texture parameters. At the same time, smaller but significant changes were observed in flavour perception, despite all patties having the same flavour type and concentration. This shows the importance of matrix effects and textural effects on flavour perception. From the applied variations, methyl cellulose content and type of texturized protein were found to have the largest impact on the sensory perception of the patties. The data for the sensory evaluation described in paragraph 2.4 and 3.1 can be found in Sensory data.xlsx. Their correlations are presented in the tab 'correlation on averaged data' in that same file.The analytical data described in paragraph 2.5 and 3.2 can be found in Analytical data.xlsxThe mixed model analysis of the sensory data can be found in MixedModelSensory.xlsxThe mixed model analysis of the analytical data can be found in MixedModelAnalytical.xlsxThe data of the partial least square regression of the analytical vs the sensory data can be found in PLS_TAvsSensory.xlsx Wageningen University & Research text/html https://research.wur.nl/en/datasets/093db0ec-cfd1-4596-8ab5-5522079fc807 10.4121/10804ad3-7b87-44f6-b9c6-05d060f8e91c https://edepot.wur.nl/714443 Design of Experiment Health sciences Plant based patties Sensory evaluation juiciness texture analysis Wageningen University & Research

oai:library.wur.nl:wurpubs/322dc6b9-b444-4bb7-b74a-a92825fa1a59 2026-04-20 dataset edurep openaire public

Bovio, Marcella Dataset Data from: "Wild relatives of Chrysanthemum as sources of resistance against the thrips Frankliniella occidentalis" 2026 Chrysanthemum is one of the most important ornamental crops worldwide. Cultivation of Chrysanthemum is affected by infestations of thrips, of which in Europe Frankliniella occidentalis is the most important species. Although genetic variation for thrips resistance in Chrysanthemum cultivars has been observed, no strong thrips resistance has been successfully introduced in breeding programmes. Crop wild relatives can be sources of resistance traits, but information on the thrips-resistance level of wild species in the Chrysanthemum genus or of species in the related genus Artemisia is not yet available. Therefore, we screened 47 accessions from 23 Chrysanthemum species and related genera in whole plant assays for thrips population build-up and in leaf-disc assays for larval development and survival. We identified several wild Chrysanthemum and Artemisia accessions on which population build-up was reduced, survival was low, and development of larvae was inhibited. On five highly resistant accessions, larvae were impaired in their development at the first larval stage (L1), effectively interrupting the life cycle of thrips. Next, we investigated the possible role of T-shaped and glandular trichomes in thrips resistance and found a positive correlation between arrested development in the L2 stage and higher density of T-shaped trichomes. However, not all the resistant accessions showed higher trichome density, suggesting that the latter accessions contain other resistance mechanisms. The identified resistant and susceptible wild relatives of Chrysanthemum may be used in further studies to elucidate the mechanism and the genetics of thrips resistance, and resistant accessions could be used as sources of thrips resistance in Chrysanthemum breeding programmes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-wild-relatives-of-chrysanthemum-as-sources-of-resistanc 10.5281/zenodo.14049714 https://edepot.wur.nl/714424 chrysanthemum frankliniella occidentalis host plant resistance insect resistance thrips larval development western flower thrips wild relatives Wageningen University & Research

oai:library.wur.nl:wurpubs/450d8864-8ca7-423a-b2e9-fbc6ee4d42da 2026-04-22 dataset edurep openaire public

Kapembwa, Chindi Shitumbanuma, Victor Yengwe, Jones Schoustra, Sijmen E. De Deyn, Gerlinde Dataset Determination of N mineralization of Tropical soils amended with compost and bokashi generated from water hyacinth and hippo grass 2026 The spread of aquatic weeds, notably water hyacinth and hippo grass, in rivers of tropical regions cause serious problems. Using these weeds as soil amendments could promote their utilization and help reduce their spread. We investigated their use when dried, composted, and fermented (bokashi), to supply nitrogen (N) to tropical soils and to improve sorghum N uptake and dry matter yield (DMY). Our objectives were to determine: (i) the N mineralization rates for the different aquatic weed amendments; (ii) the correlation between N mineralization rates and sorghum N uptake; and (iii) the correlation between N mineralization rate and sorghum DMY. In an incubation greenhouse experiment, we used a Typic Kandiustalf and applied: (i) dried, (ii) fermented, and (iii) composted water hyacinth or hippo grass, (iv) mineral fertilizer, and (v) no amendment. Nitrogen application in treatments i-iv was standardized to rates equivalent to 90 kg N ha-1. Overall, N mineralization rates were highest for compost (0.412 mg kg⁻¹ day⁻¹), intermediate for bokashi (0.265 mg kg⁻¹ day⁻¹), and lowest for dried weeds (0.211 mg kg⁻¹ day⁻¹). Across amendments, N mineralization rates were strongly correlated to sorghum N uptake (r = 0.808) and to sorghum DMY (r = 0.844). Relative agronomic effectiveness for sorghum biomass production was 163% for compost, 97% for bokashi, and 2% for dried weeds. Both aquatic weeds can supply sufficient N for sorghum when processed into compost or bokashi, with compost providing faster mineral N release. Wageningen University & Research text/html https://research.wur.nl/en/datasets/determination-of-n-mineralization-of-tropical-soils-amended-with- 10.4121/f0539cee-c288-42ff-872d-af11320e183c https://edepot.wur.nl/714244 Bokashi Nitrogen Mineralization rate Relative agronomic efficiency compost Wageningen University & Research

oai:library.wur.nl:wurpubs/606b4ce6-0fe8-4a08-b41c-757813e1c769 2026-04-22 dataset edurep openaire public

Arfman, Kasper Janssen, Bas Romein, Robin van den Boom, Sophie van der Woude, Maarten Jansen, Lucas Rademaker, Maartje Hernandez-Garcia, Jorge de Amil da Costa Jacob Ramalho, João Dipp-Alvarez, Melissa Dataset Data underlying the publication: Nanoclustering of a plant transcription factor enables strong yet specific DNA binding 2026 This dataset features centrifugation assay (CENTR), confocal microscopy (CLSM), Dynamic Light Scattering (DLS), Electrophoretic Mobility Shift Assay (EMSA), quantitative PCR (qPCR), Size-Exclusion Chromatography (SEC), Single-Molecule Imaging (SMI), and Single-Particle Tracking (SPT), and furthermore includes manually provided annotations of the data needed to perform analyses as presented in the publications. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-nanoclustering-of-a-plant-transcr 10.4121/b659246a-b866-4043-b0bf-a9b96cb236cf https://edepot.wur.nl/714044 Confocal microscopy DNA-protein interactions Light Scattering Single-molecule microscopy Transcription factors phase separation Wageningen University & Research

oai:library.wur.nl:wurpubs/92634790-746a-46ad-8f2c-5fd80a1e2631 2026-04-14 dataset edurep openaire public

Croijmans, Luuk Waenink, Rik Faber, Hilde van der Werf, Wopke de Jonge, Berend Lenders, Roos Lekkerkerk, Nienke Hofmeijer, Merel Bianchi, Felix Dataset Data underlying the publication: Strip cropping in practice: higher slug abundance despite higher number of slug-predating carabid species 2026 This data belongs to a manuscript, with the title: Strip cropping in practice: higher slug abundance despite higher number of slug-predating carabid species. See the readme files for information on methods, techniques and other relevant information. Abstract: Strip cropping involves growing multiple crops in adjacent strips in a field, which facilitates existing management routines while promoting ecological interactions. While strip cropping can promote in-field biodiversity and biological control of insect pests, it is unclear how strip cropping affects in-field slugs, which can cause considerable crop damage. We selected 20 farms across the Netherlands with paired monoculture and strip cropping fields. The strip cropping fields varied in strip width (3-33m), number of crop species grown (2-9 crops) and farming system (conventional or organic). We used a combination of shelter and pitfall traps to quantify populations of slugs and their arthropod predators in cereals. Slug abundance was low at most farms, but was 3-5 times higher in strip cropping than in monocultures. Slug abundance in strip cropping increased with increasing strip width. Farming system, cereal type, soil type, or the number of crop species did not mediate the effect of strip cropping on slug abundances. Natural enemy diversity was around 25% higher in strip cropping, and this effect of strip cropping was mediated by cereal type and soil type. Farming system, strip width or number of crops did not mediate the effect of strip cropping on natural enemy diversity. Most farmers reported similar levels of slug damage in cereals in strip cropping and monoculture. However, some farmers reported increased slug damage in other crops within the strip cropping arrangement, especially at farms with relatively high slug abundances. Synthesis and applications. To avoid increased slug damage in strip cropping fields in slug-prone areas, potential slug-source crops should be spatially separated from slug-sensitive crops. However, an increase in slug abundance should not deter the adoption of strip cropping as higher slug damage in strip cropping systems was rarely observed by farmers. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-strip-cropping-in-practice-higher 10.4121/f7553b0c-620b-4a79-a3bf-5646117d5b7a https://edepot.wur.nl/714014 Agriculture, forestry and fisheries Biological sciences Carabidae Conservation biological control Crop diversification Earth and related environmental sciences Ecological intensification Gastropod Intercropping Pest management Time: 2024 Wageningen University & Research

oai:library.wur.nl:wurpubs/a988079c-1176-4b97-b970-323acbe0aa9a 2026-05-07 dataset

Reniers, Yente L. Helfenstein, J. van Rijssel, S.Q. Dataset Data belonging with MSc thesis "Understanding soil fungal diversity across agricultural soils in Europe: Exploring relationships with farm management and environmental gradients" 2026 Soil fungi play a key role in ecosystem functioning and soil multifunctionality in agricultural systems but are negatively affected by agricultural intensification, leading to species loss and biotic homogenization. Despite results from field and experimental studies showing low-intensity management positively influences fungal communities, these findings are often context-dependent and limited to small spatial scales. At larger scales, responses to farm management thus remain unexplored, and functional composition is frequently overlooked. This study investigated fungal diversity and functional composition across agricultural soils of seven European countries (681 sites), linking these patterns to climate, soil, and farm management drivers. As no large-scale datasets currently combine fungal DNA and farm management information, this was achieved by matching aggregated farm management data from FADN to soil and sequencing data from the SoilCare project (AgroCares), based on NUTS2 region, elevation, and crop type. Random forest models identified climate and geographic factors as the dominant drivers of fungal alpha diversity, with farm management having a significant secondary contribution in the case of OTU richness. Key management drivers included cropping intensity, fertilization, and tillage intensity. Crop type was found to affect taxonomic and functional turnover, rather than overall diversity patterns. Furthermore, communities were dominated by saprotrophs, although grassland and low-intensity crops showed higher relative abundances of symbiotrophs and lower abundances of pathotrophs compared to higher-intensity arable crops. Together, these findings demonstrate that farm management is a key driver of fungal communities at large spatial scales and further highlights the positive influence of low-intensity management. This underscores the need for farm management that conserves fungal diversity and promotes beneficial functional groups to sustain soil health and functioning in agricultural soils. Wageningen University & Research Soil microbial communities soil fungi soil health https://research.wur.nl/en/datasets/data-belonging-with-msc-thesis-understanding-soil-fungal-diversit Wageningen University & Research

oai:library.wur.nl:wurpubs/339e41ba-1452-47dc-84ae-d462ca2c2e06 2026-04-14 dataset edurep openaire public

Bos, Peter van Amerongen, Herbert Wientjes, Emilie Dataset Dataset underlying: Wavelength-dependent Excitation Ratio of Photosystem I and II in Arabidopsis thaliana 2026 We recorded streak camera images of WT and mutant Arabidopsis thaliana leaves to resolve the fluorescence contributions of PSI and PSII to the total fluorescence. The mutants are lhcb2 RNAi and lhca knockout. For correction and interpretation of the data, we recorded the IRF of the streak camera set-up and the decay spectra of isolated LHCII and freshly isolated grana. Next to that, we performed pulse-amplitude measurements to determine the quantum yield of PSI and PSII at increasing light intensities. We used the same technique to monitor the ability for state transitions of the Arabidopsis leaves. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-underlying-wavelength-dependent-excitation-ratio-of-photo 10.4121/919acc8f-ae53-4988-8f5e-d67f0063b8e3 https://edepot.wur.nl/713985 Biological sciences Photosynthesis Photosystem Photosystem I Photosystem II Time-resolved spectroscopy state transitions Wageningen University & Research

oai:library.wur.nl:wurpubs/e7b2fdcd-ac76-48c2-9340-63314ca2dbdf 2026-04-20 dataset edurep openaire public

Beemster, Joris Talke, Stefan van Maren, Bas Giloy, Nathalie Wünsche, Anna Wei, Zhang Grasso, Florent Hoitink, Ton Dataset Data Supporting "Human footprint on estuarine tidal hydrodynamics" 2026 Description for the Dataset: "Data for 'Human footprint on estuarine tidal hydrodynamics'"This dataset supports the research presented in the paper "Human Footprint on Tides in Estuaries" by Joris G.W. Beemster et al. (2026). The study investigates the impact of human interventions on tidal dynamics in 25 estuaries worldwide, comparing historical and modern conditions over timescales of decades to centuries. The dataset includes comprehensive data on tidal characteristics, estuarine geometries, and human activities influencing tidal changes. Methodology: The research employs a global-scale comparative analysis of tidal hydrodynamics, examining changes in tidal range, high and low water levels, tidal propagation speed, and tidal asymmetry. The study leverages newly digitized historical datasets and existing studies to link observed changes to specific human activities. Data were compiled from agency databases, scientific literature, maps, and reports, encompassing tidal range, wave celerity, tidal asymmetry, channel depth, planform areas, and discharge. Techniques Used:Digitization of Historical Data: Water level records, bathymetric charts, and nautical maps were digitized to construct along-channel profiles of tidal range and wave propagation.Interpolation and Analysis: Tidal range changes were analyzed by interpolating along-estuary profiles and identifying key parameters such as maximum tidal range and location of maximum change. Data Availability:Previously Published Data: Researchers interested in these datasets should refer to the sources listed in the paper and contact the respective data holders for access. Digitized & Derived Data is available in this repository. Acknowledgments: This work was funded by the Netherlands Organization for Scientific Research (NWO) within the Vici project “Deltas out of Shape: Regime Changes of Sediment Dynamics in Tide-Influenced Deltas” (Grant NWO-TTW 17062). Financial support for this research was also provided by the U.S. Departmentof Defense’s Strategic Environmental Research and Development Program (SERDP) under Project RC12-3456. The authors thank all individuals and institutions who contributed to the collection, preservation, and digitization of these datasets. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-supporting-human-footprint-on-estuarine-tidal-hydrodynamics 10.4121/54bf59a6-a827-4d50-a7ad-9f990b5aff89 https://edepot.wur.nl/713775 Earth and related environmental sciences Human Interventions Tidal Amplication Tidal Change Time: 1821-2024 Wageningen University & Research

oai:library.wur.nl:wurpubs/f7dede96-d2aa-48fe-acd5-5c5b8aa37eb8 2026-04-09 dataset edurep openaire public

Hartono, Sylviani Meijerink, Marlisa F.A. Abee, Tjakko Smid, Eddy J. van Mastrigt, Oscar Dataset Metagenome of stressostat cultivation 2026 Lactococcus lactis FM03 was grown in 2 independent stressostat cultivations (a novel adaptive laboratory evolution method) with increasing lactate concentration. We used metagenomic to study the population dynamic and changes in alleles frequency during stressostat cultivation. Wageningen University & Research text/html https://research.wur.nl/en/datasets/metagenome-of-stressostat-cultivation https://edepot.wur.nl/713739 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/6aee8c20-354c-4679-bf53-59ea69b7086e 2026-04-09 dataset edurep openaire public

Hartono, Sylviani Meijerink, Marlisa F.A. Abee, Tjakko Smid, Eddy J. van Mastrigt, Oscar Dataset Lactate resistant L. lactis isolated from stresssostat cultivation 2026 Lactococcus lactis FM03 was grown in 2 independent stressostat cultivations (a novel adaptive laboratory evolution method) with increasing lactate concentration for 35 days. Evolved L. lactis was isolated from several time points throughout the evolution experiment and was shown to have increased lactate resistance compared to the wild type Wageningen University & Research text/html https://research.wur.nl/en/datasets/lactate-resistant-l-lactis-isolated-from-stresssostat-cultivation https://edepot.wur.nl/713735 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/251eabdb-a8e4-4326-981b-a6197885bb59 2026-04-20 dataset edurep openaire public

van Gelder, A.H. Sousa, D.Z. Rijpstra, W.I. Damsté, J.S. Stams, A.J.M. Sanchez Andrea, I. Dataset A novel anaerobic succinate-producing bacterium, strain ZWBT, was isolated from sludge collected from a biogas desulfurization bioreactor (Eerbeek, the Netherlands). 2026 A novel anaerobic succinate-producing bacterium, strain ZWBT, was isolated from sludge collected from a biogas desulfurization bioreactor (Eerbeek, the Netherlands). Cells were non- spore-forming, motile, slightly curved rods (0.4–0.5 mm in diameter and 2–3 mm in length), and stained Gram-negative. The temperature range for growth was 25–40 6C, with an optimum at 37 6C. The pH range for growth was 7.0–9.0, with an optimum at pH 7.5. Strain ZWBT was able to ferment glycerol and several carbohydrates mainly to H2, succinate and acetate. Sulfur and fumarate could be used as electron acceptors by strain ZWBT. The G+C content of the genomic DNA was 37.6 mol%. The most abundant fatty acids were iso-C14 : 0 and so-C16 : 0 DMA. On the basis of 16S rRNA gene sequence similarity, strain ZWBT belongs to the family Ruminococcaceae and it is distantly related to Saccharofermentans acetigenes JCM 14006T (92.1 %). Based on the physiological features and phylogenetic analysis, strain ZWBT represents a novel species of a new genus, for which the name Ercella succinigenes gen. nov., sp. nov. is proposed. The type strain of Ercella succinigenes is ZWBT (5DSM 27333T5JCM 19283T). Wageningen University & Research text/html https://research.wur.nl/en/datasets/a-novel-anaerobic-succinate-producing-bacterium-strain-zwbt-was-i https://edepot.wur.nl/713732 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/357615ab-382f-4613-bbe9-efb03dc3a988 2026-04-09 dataset edurep openaire public

van de Ruitenbeek, Stefan J.S. Willemsen, Ids Dataset Databases for the EZpore pipeline 2026 This repository is meant for sharing databases that can be used in the ezpore pipeline: https://github.com/ids-willemsen/ezpore The pr2 database (v5.1.1) is downloaded from: https://github.com/pr2database/pr2database and transformed to vsearch input using a custom R script. The eukaryome general fasta database (v2.0) is downloaded from: https://eukaryome.org/generalfasta and transformed to vsearch input using a custom R script. The 16S bacteria database is from SILVA (https://www.arb-silva.de/current-release) The 18S nematoda database is from van Himbeeck et. al 2024 (10.1016/j.soilbio.2023.109263) The ITS fungus database is from UNITE (https://unite.ut.ee/repository.php) Wageningen University & Research text/html https://research.wur.nl/en/datasets/databases-for-the-ezpore-pipeline 10.17887/wur01-6m915t https://edepot.wur.nl/713666 16S 18S 28S ITS Natural Sciences - Biological sciences (1.6) database eukaryome pr2 reference Wageningen University & Research

oai:library.wur.nl:wurpubs/6425e899-2bc5-49f1-932c-672ed72ce1b4 2026-04-20 dataset edurep openaire public

Schrijver, L.L. Vliegenthart, R. Dykstra, Pearl Dataset Data package for publication "in search of truth" 2026 This is the data package for the following project: 'In search of truth: A refined approach to data collection and annotation for BERT-based misinformation detection'. For this project, we developed a codebook to classify misinformation and other content-related characteristics, such as incivility, in Tweets, and elaborately trained four student assistants to classify 3400 Tweets using this codebook. The paper and codebook are published in Computational Communication Research. More information about data collection and annotation can be found there. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-package-for-publication-in-search-of-truth 10.17887/WUR01-UZ2JNO https://edepot.wur.nl/713665 BERT conspiracy theories covid pandemic crises machine learning mis- and disinformation Wageningen University & Research

oai:library.wur.nl:wurpubs/00ed2a3d-71ea-4347-af78-58b4f6d2bc28 2026-04-08 dataset edurep openaire public

Kurm, Viola Brinkman, Pella Visser, Johnny Korthals, Gerard Dataset Data underlying the publication: Positive effects of various organic amendments on soil life in a multi-year field experiment 2026 In this study we investigated the microbial and nematode soil life, indicators for overall soil health, after application of different organic products, and compared this to the use of different dosages of artificial fertilizers and an conventional treatment over three years. In the fourth year we studied the dynamics of the same parameters over one growing season. Although crop yield was lower compared to the conventional treatment, several products, especially a bokashi and fresh clippings, enhanced soil bacterial and fungal abundance as well as the abundance of nematodes. These effects were stable over several years. Moreover, we could demonstrate that timepoint of measurement over the growing season did not affect the observed effect of the treatment in spite of strong temporal fluctuations. Two datatsets were used in this study. One contains the phospholipid fatty acid (PLFA) measurements and soil nematode counts and indices of one sampling timepoint each in 2021, 2022, and 2023. Four randomized blocks of plots treated with one of the 11 products were sampled and product treatment was the same for each block over the years. All treatment details and timepoint of sampling are described in the publication. The other dataset contains the PLFA measurements and nematode counts and indices of several sampling timepoints in 2024. Samples for PLFA were taken at 7 timepoints. Samples for nematodes were taken at 4 timepoints. Moreover, in 2024, only a subset of 4 product treatments was sampled. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-positive-effects-of-various-organ 10.4121/d57a9d1a-1a20-4a8a-be1f-8246e6946e57 https://edepot.wur.nl/713629 PLFA bokashi compost long-term field experiment soil nematodes Wageningen University & Research

oai:library.wur.nl:wurpubs/b82417b0-2fdf-4f66-9cfb-e02382d17fe7 2026-04-02 dataset edurep openaire public

Mwale, Cyprian Bastiaans, Lammert Rodenburg, Jonne Bakker, E.J. (Evert Jan) Dataset Data underlying the publication: Striga hermonthica resistance in maize also warrants low Striga asiatica infections and contributes to yield stability across environments 2026 Data refer to a range of maize genotypes derived from the Malawian public research system and private seed sector and genotypes derived from an international non-profit organization, IITA, based in Nigeria. A total of 22 genotypes were grown on S. hermonthica infested soils at four sites in Kenya (2017), and on S. asiatica infested soils at three sites in Malawi, during two cropping seasons (2017, 2018). Maximum aboveground Striga plant numbers and maize grain yields (in Malawi only) were assessed from fields and strigolactone profiling of root exudates of these genotypes was done in the lab. Details can be found in the published paper and in the meta data sheet of the dataset. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-striga-hermonthica-resistance-in- 10.4121/34acdb88-8588-4c5f-b183-6ec6e09b2ff9 https://edepot.wur.nl/713478 Africa Cultivars Maize Striga Yield Wageningen University & Research

oai:library.wur.nl:wurpubs/8eb3770a-66f0-45f3-bdfb-a0c399dfeae2 2026-04-01 dataset edurep openaire public

Pampoukis, George Dataset Supplementary material for Chapter 6: General Discussion 2026 This dataset contains the supplementary material associated with Chapter 6 of the PhD thesis From data to insight: Assessing the decontamination efficacy of mild food processing technologies using data-driven approaches. It contains the supplementary Excel workbook supporting the cross-technology benchmarking discussed in the General Discussion. The workbook includes data and model-output tables for thermal processing (TP), high-pressure processing (HPP), and pulsed electric field (PEF), and supports the comparison of decontamination efficacy, energy use, and greenhouse gas emissions across technologies. Wageningen University & Research text/html https://research.wur.nl/en/datasets/8eb3770a-66f0-45f3-bdfb-a0c399dfeae2 10.4121/08c650c5-82be-468f-a878-b6ccbf93b7ca https://edepot.wur.nl/713395 benchmarking energy use food microbiology greenhouse gas emissions high-pressure processing pulsed electric field thermal processing Wageningen University & Research

oai:library.wur.nl:wurpubs/1fbe40f5-c24b-43e4-955e-2b22a41cc2d5 2026-04-20 dataset edurep openaire public

Pampoukis, George Ham, Jan Zwietering, Marcel H. den Besten, Heidy M.W. Dataset Supplementary material for Chapter 4: The decontamination efficacy of pulsed electric field in food: Establishing global kinetic parameters 2026 This dataset contains the supplementary material associated with Chapter 4 of the PhD thesis From data to insight: Assessing the decontamination efficacy of mild food processing technologies using data-driven approaches. It includes the supplementary material supporting the published article on pulsed electric field (PEF) decontamination efficacy and global kinetic parameters. The dataset contains the literature search strategy, PRISMA flow diagram and eligibility criteria, the protocol for the parameters included in the PEF database, a worked example of the inverse-prediction procedure for estimating the volumetric energy input required to achieve a 5-log10 reduction, and the supplementary Excel file containing the filtered PEF database and regression/stratification outputs. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-material-for-chapter-4-the-decontamination-efficacy 10.4121/1ab51010-9b1c-4ad7-a86e-142bb16ae2e5 https://edepot.wur.nl/713394 Inactivation Microbiology Modeling Modelling Pulsed electric fields StrainVariability Wageningen University & Research

oai:library.wur.nl:wurpubs/ce98c967-f401-4cce-833b-6904fdab4804 2026-04-01 dataset edurep openaire public

Pampoukis, George Zwietering, Marcel H. den Besten, Heidy M.W. Dataset Supplementary material for Chapter 2: Ranking factors affecting the decontamination efficacy of non-thermal plasma: The approach of dissipated power per plasma volume through machine learning modeling 2026 This dataset contains the supplementary material associated with Chapter 2 of the PhD thesis From data to insight: Assessing the decontamination efficacy of mild food processing technologies using data-driven approaches. It includes search keywords used for the literature search, the reference list of included studies, methodological details on regularized regression, supplementary figures, and supplementary tables. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-material-for-chapter-2-ranking-factors-affecting-th 10.4121/aa957c13-9748-4af9-b8fc-b05986759034 https://edepot.wur.nl/713393 Active learning Biological sciences Cold plasma Elastic net Gradient boosting Inactivation Kinetics Other engineering and technologies Wageningen University & Research

oai:library.wur.nl:wurpubs/0ae86397-cd9c-4b5f-9b8d-61e39d7a58fc 2026-04-20 dataset edurep openaire public

Yeak, Claire Pampoukis, George Serra I Castelló, Cristina Bover-Cid, Sara den Besten, Heidy M.W. Zwietering, Marcel H. Dataset Supplementary material for Chapter 5: High-pressure processing inactivation of foodborne bacteria and viruses in foods 2026 This dataset contains the supplementary material associated with Chapter 5 of the PhD thesis From data to insight: Assessing the decontamination efficacy of mild food processing technologies using data-driven approaches. It includes the supplementary material supporting the chapter on high-pressure processing (HPP) inactivation of foodborne bacteria and viruses in foods. The dataset contains the statistical background and equations used in the chapter, the full curated HPP database, pressure-based resistance ranking outputs, the comparison with EFSA-derived estimates, and the background multiple linear regression models. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-material-for-chapter-5-high-pressure-processing-ina 10.4121/3cab8862-d524-4bcd-bee1-3318525a7311 https://edepot.wur.nl/713392 Biological sciences Decontamination, pathogen HHP HPP Hazard Hydrostatic pressure Mild processing Non-thermal Other engineering and technologies Wageningen University & Research

oai:library.wur.nl:wurpubs/6311449f-4b6e-4784-89ed-c6a726ab6fa4 2026-04-20 dataset edurep openaire public

Tagle Freire, D.S. Kuiper, J.J.A. Ohms, M.A.W. Chiang, Yuanfu Stieger, M.A. Forde, C.G. Schutyser, M.A.I. Dataset Data underlying the research on "Processing history shapes in vitro digestibility of protein and starch within oat protein ingredients: Influence of fractionation and thermal treatment." 2026 This dataset was generated as part of a research project investigating how fractionation route and post-heat treatment influence the in vitro digestibility of protein and starch in oat protein ingredients. The overarching aim of the project is to understand how processing history shapes ingredient composition, structure, and physicochemical properties, and how these factors relate to enzyme accessibility and digestion behavior. The dataset includes multiple types of data collected to characterize oat ingredients produced through different processing routes, including dry fractionation, alkaline extraction–isoelectric precipitation, and water-only extraction, as well as oat flour and two commercial oat protein ingredients. It contains compositional data (protein, starch, lipid, ash, and moisture), ingredient solubility and color measurements, microstructural observations obtained by scanning electron microscopy (SEM), and thermal properties determined by differential scanning calorimetry (DSC), including protein denaturation and starch gelatinization. In addition, the dataset includes in vitro digestion data generated using the INFOGEST static protocol, with protein and starch digestibility quantified as degree of hydrolysis using the OPA and DNS assays, respectively, as well as the corresponding statistical analyses. Potential users of this dataset include food scientists, cereal chemists, and researchers working on plant protein ingredients, food processing, and digestion. The dataset can be used to examine how processing-induced differences in composition, microstructure, and thermal behavior influence nutrient digestibility, to support comparative studies on plant-based protein ingredients, and to further investigate relationships between processing conditions and digestion outcomes. For any questions, comments, or access requests, please contact Danny Tagle-Freire at dannntagle@gmail.com. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-research-on-processing-history-shapes-in-vitr 10.17887/WUR01-UT435V https://edepot.wur.nl/713258 Dry fractionation INFOGEST In vitro digestion Oat protein Oat starch Thermal treatment Wet extraction Wageningen University & Research

oai:library.wur.nl:wurpubs/6e578186-76c9-449a-9408-17eb5a851123 2026-04-20 dataset edurep openaire public

Moyano, Marta Blanco, Edurne Ortega, Aurelio De la Gándara, Fernando Armengol, Laia Peck, Myron A. Reglero, Patricia Dataset Thermal tolerance of Atlantic bluefin tuna larvae 2026 This dataset includes raw data on CTmin and CTmax estimates on Atlantic bluefin tuna larvae included in the scientific article "Critical thermal limits of Atlantic bluefin tuna (Thunnus thynnus) larvae" published in Journal of Thermal Biology (https://doi.org/10.1016/j.jtherbio.2026.104410). This version includes the updated version of the R script. NIVA text/html https://research.wur.nl/en/datasets/thermal-tolerance-of-atlantic-bluefin-tuna-larvae 10.5281/zenodo.16883630 https://edepot.wur.nl/712922 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/57cf9b51-d037-4c7e-b914-4076ce0ba92c 2026-04-20 dataset edurep openaire public

Boeschoten, Laura E. Guillemot, Joannès van Melis, Juliano Poorter, Lourens Rodrigues, Ricardo R. Bongers, Frans Molin, Paulo G. Peña-Claros, Marielos Souza, Vinicius C. Toledo, Cássio A.P. Fernandes, Patrick Faria Ferreira, Marcelo P. Resende, Angélica F. Simões, Laura H.P. Torres de Almeida, Catherine Uriarte, María Brancalion, Pedro H.S. Dataset Dataset Accompanying the Study by Boeschoten et al. 'All reforestation methods can support tropical tree diversity recovery, but drivers and species composition vary' 2026 This Zenodo repository contains the processed dataset used in the research paper titled "All reforestation methods can support tropical tree diversity recovery, but drivers and species composition vary" Global Change biology (2026) (https://doi.org/10.1111/gcb.70721). In this study, we present the first comprehensive comparison of tree diversity restoration and the drivers of recovery across five main reforestation methods (naturally regenerating forests, biodiverse restoration plantings, short- and long-rotation tree monocultures, agroforests) relative to three reference systems (agropastoral lands, degraded and conserved forest remnants). Key Finding: Tree diversity levels comparable to those in conserved and degraded forest remnants occur across most reforestation methods; however, similar species composition was observed only in naturally regenerating forests. Ghent University text/html https://research.wur.nl/en/datasets/dataset-accompanying-the-study-by-boeschoten-et-al-all-reforestat 10.5281/zenodo.18244527 https://edepot.wur.nl/712919 Active restoration Agroforests Atlantic forest Biodiversity crisis Forest restoration Habitat fragmentation Natural regeneration Passive restoration Reforestation Tropical forest Wageningen University & Research

oai:library.wur.nl:wurpubs/0ef4a10c-67dc-4c00-8eda-823b0de0681e 2026-03-25 dataset

oai:library.wur.nl:wurpubs/e7120f0a-7c08-4568-9407-51b8387da6a1 2026-03-19 dataset edurep openaire public

Soykan, Gürkan Babur, Önder Liu, Qingzhi Tekinerdogan, Bedir Dataset Data and Model Checkpoints from: ExoPrompt: Transformer-based greenhouse climate forecasting with structured conditioning and physics-based simulation 2026 Data and model checkpoints accompanying the paper: Soykan et al. (2026). ExoPrompt: Transformer-based greenhouse climate forecasting with structured conditioning and physics-based simulation. Computers and Electronics in Agriculture, 246, 111673. https://doi.org/10.1016/j.compag.2026.111673 --- Data --- new_world_sim.zipSynthetic GreenLight simulation outputs used for pretraining. Covers 9 parameter scenarios across 15 geographic locations and 2 lighting modes (LED/HPS). Each runincludes paired .csv time-series and .json exogenous parameter files. gt.zipGround-truth climate measurements from a tomato greenhouse trial (Bleiswijk, 2009-2010) under LED and HPS lighting, reorganised into CSV format for use withthe ExoPrompt training pipeline. c_leakage_gt_led_conditions_csv.zipSimulation sweeps varying a single exogenous parameter (cLeakage) with aligned ground-truth subsets, used for the controlled robustness experiment in Section 3.3. --- Model Checkpoints --- ckpts_pretrained_main.zipPretrained ExoPrompt and Vanilla backbones evaluated zero-shot on ground truth (Table 4). ckpts_200k_main.zipFine-tuned checkpoints for mixed, LED-only, and HPS-only splits (Figure 5). ckpts_cleakage.zipPretrained and fine-tuned checkpoints for the controlled cLeakage study (Section 3.3-3.4). Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-and-model-checkpoints-from-exoprompt-transformer-based-green 10.4121/73060077-ec7c-4ad5-ab03-339a3430b6b5 https://edepot.wur.nl/712593 Computer and information sciences Conditioning Digital twins Forecasting Greenhouse Microclimate Simulation Transformers Wageningen University & Research

oai:library.wur.nl:wurpubs/654d894f-8ce1-4f1c-8baa-814755c9658b 2026-04-20 dataset edurep openaire public

de Boer, A.M. Pearson, Stuart van der Spek, Ad van Prooijen, Bram Wallinga, J. Dataset Data underlying the publication Luminescence as a tool to reconstruct sediment transport pathways in a tidal inlet 2026 This dataset contains single-grain feldspar luminescence measurements from modern seafloor sediments collected across the Ameland tidal inlet (Dutch Wadden Sea) to investigate sediment transport pathways using luminescence tracing. Samples were obtained by boxcoring during multiple research cruises, prepared under controlled laboratory conditions, and processed to isolate the 212–250 µm K-feldspar-rich fraction. Infrared stimulated luminescence (IRSL50) and multiple elevated-temperature post-IR IRSL (pIRIR110, pIRIR170, pIRIR230) signals were measured at the single-grain level using an EMCCD-based imaging system mounted on a Risø DA-20 reader. Equivalent dose (De) distributions were analyzed using the Central Age Model (CAM) and bootstrapped Minimum and Maximum Age Models (bMAM, bMAX). The dataset includes raw luminescence signals, dose–response curves, grain acceptance metrics, De values, and spatial metadata, enabling assessment of bleaching variability, inherited dose patterns, and pathway-integrated sediment transport behavior. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-luminescence-as-a-tool-to-reconst 10.17887/WUR01-LWMSLD https://edepot.wur.nl/712284 coastal sediment transport luminescence tracing single-grain feldspar luminescence tidal inlet dynamics wadden sea, ameland Wageningen University & Research

oai:library.wur.nl:wurpubs/a2770708-fd4a-4f00-a681-6c64d616af7d 2026-03-17 dataset edurep openaire public

Righini, Isabella Hemming, Silke Stanghellini, Cecilia Graamans, Luuk Marcelis, Leo Dataset Dwarf tomato trials in a research vertical farm facility: climate, yield and crop related data 2026 Data underlying the publication: A validated climate-crop model for the prediction of yield of dwarf tomatoes in Controlled Environment Agriculture.Full details of the experimental setup, treatments, and data collection procedures are described in the linked publication. The dataset was generated from two trials conducted in 2021 and 2022 in two climate-controlled chambers of the experimental vertical farm facility at Wageningen University & Research (Bleiswijk, the Netherlands). The dataset comprises 14 individual datasets. Each individual dataset is identified by a number and cultivar and it is considered as a unique combination of cultivation system, day light integral, temperature and year. Every dataset includes the following parameters: IndoorClimate.csv: realized climate control settings. CropParameters.csv: crop-related parameters obtained from destructive measurements. Production.csv: fruit yield data and fruit dry matter content. Two cultivars of dwarf tomato (Solanum lycopersicum L.) were used in the experiments: ‘F12414’ (producing red, plum-type tomatoes) and ‘F13469B’ (producing orange, cherry-type tomatoes). In the dataset, these cultivars are referred to as Red and Orange, respectively. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dwarf-tomato-trials-in-a-research-vertical-farm-facility-climate- 10.4121/1ab846cb-c590-4220-9da7-f17e2217f96c https://edepot.wur.nl/712279 Agriculture, forestry and fisheries Horticultural production Indoor farming LED lights dwarf tomato vertical farm Wageningen University & Research

oai:library.wur.nl:wurpubs/9cd9e4ec-8b98-4e7a-baae-1e8d3fe7777a 2026-04-20 dataset edurep openaire public

Abdel Hamid, Muzamil Mahdi Abdelraheem, Mohamed Hassan Acheampong, Desmond Omane Adam, Ishag Aide, Pedro Ajibaye, Olusola Ali, Mozam Almagro-Garcia, Jacob Amambua-Ngwa, Alfred Amenga-Etego, Lucas Aniebo, Ifeyinwa Aninagyei, Enoch Ansah, Felix Apinjoh, Tobias O. Ariani, Cristina V. Auburn, Sarah Awandare, Gordon A. Balmer, Andrew Bejon, Philip Boene, Simone Bwire, George Candrinho, Baltazar Chidimatembue, Arlindo Chindavongsa, Keobouphaphone Comiche, Kiba Conway, David Dara, Antoine Diakite, Mahamadou Djimde, Abdoulaye Dondorp, Arjen Doumbia, Seydou Drury, Eleanor Fanello, Caterina A. Ferdig, Mike Figueroa, Katherine Gamboa, Dionicia Golassa, Lemu Gonçalves, Sónia dite Agnes Guindo, Merepen Hamaluba, Mainga Hanboonkunupakarn, Borimas Howe, Kevin Hussien, Maazza Imwong, Mallika Ishengoma, Deus Jeans, Julia Kabaghe, Alinune Kamuhabwa, Appolinary Kindermans, Jean Marie Pearson, Richard D. Takken, Willem Dataset Pf8: an open dataset of Plasmodium falciparum genome variation in 33,325 worldwide samples 2026 The Pf8 data release includes 33,325 parasite samples collected in 34 different countries in Africa, Asia, South America and Oceania. From these, 24,409 are high-quality samples with complete metadata. In total, we identified more than 12 million variant positions (SNPs and indels). This record includes metadata and drug-resistance inference for samples contributed to MalariaGEN. To encourage specialised analyses, we additionally include the genetic distance matrix (full and SNP-only versions), measures of sample clonality (Fws), copy number variation (CNV) calls, and drug resistance inferences and rules files. Sequence alignment and genomic variant files (CRAM and VCF files) are not included in this record but will be made publicly available under approriate repositories ENA / EVA. Further information on files may be accessed in the Pf8_README.txt file. These data are available open access under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Publications using these data should acknowledge and cite the source of the data. For more information on MalariaGEN P. falciparum projects, please visit: https://www.malariagen.net/parasite-observatory/ The methods used to generate the data are described in detail in "Pf8: an open dataset of Plasmodium falciparum genome variation in 33,325 worldwide samples", MalariaGEN et al., 2025, DOI: 10.12688/wellcomeopenres.24031.1 Wageningen University & Research text/html https://research.wur.nl/en/datasets/pf8-an-open-dataset-of-plasmodium-falciparum-genome-variation-in- 10.5281/zenodo.18681979 https://edepot.wur.nl/712014 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/4d78a1c9-bdc5-4a36-ae4a-ebfc65c0dbc1 2026-05-07 dataset

Robben, Annika Helfenstein, J. Schoorl, J.M. Dataset Data and R scripts with MSc thesis "Analysis of abiotic drivers of land abandonment in mountainous Mediterranean areas through a case study in Álora, Spain" 2026 Agricultural land abandonment is a widespread and significant land use change process in Europe, defined as the discontinuation of farming activities and the return of the land to natural vegetation. This phenomenon is particularly widespread in mountainous, remote, and semi-arid areas, often driven by unfavourable natural constraints. However, detailed spatial analysis that integrates long-term land use change with detailed local soil and topographic data remains limited in mountainous Mediterranean regions. The Álora region in Andalusia, Spain, serves as a representative case study for many mountainous areas in the Mediterranean facing land abandonment. This research used high-resolution orthophotos from 2022, 2000, and 1977 to quantify land use and land abandonment rates for two time intervals. From 1977 to 2022, 20.02 km2 of agricultural land was abandoned in the study area, with olive and almond accounting for nearly half of the total abandoned area. Bivariate statistics and random forest was used to identify the most important abiotic properties for explaining land abandonment. In the study area, land abandonment is driven primarily by topographic properties, such as elevation and slope, and soil properties, such as parent material and effective soil and rooting depth. This research provides spatially explicit and high-resolution insights into the abiotic properties driving land abandonment in Mediterranean agricultural landscapes. Wageningen University agriculture land abandonment land use https://research.wur.nl/en/datasets/data-and-r-scripts-with-msc-thesis-analysis-of-abiotic-drivers-of Wageningen University & Research

oai:library.wur.nl:wurpubs/d3eeab89-c58d-45e1-8fd8-fd4a0c08b162 2026-04-29 dataset edurep openaire public

Bagchus, Cleo Ramakers, Lennart Verhoeven, Dana Beraldo, Claudia Alboresi, Alessandro Morosinotto, Tomas van Amerongen, Herbert Wientjes, Emilie Dataset Data Underlying: Quantitative decomposition of non-photochemical quenching in Physcomitrium patens highlights synergistic roles of LhcSR and zeaxanthin 2026 In this work, we used quantitative decomposion to determine the contributions of PsbS, LhcSR and Zeaxanthin to NPQ in the moss physcomitrium patens. This dataset contains the data underlying the publication entitled "Quantitative decomposition of non-photochemical quenching in Physcomitrium patens highlights synergistic roles of LhcSR and zeaxanthin". In the README file, an overview is given of the presented data and Python codes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-quantitative-decomposition-of-non-photochemical-q 10.4121/5417e149-4c9c-4a44-8424-bfd4a8ecdd07 https://edepot.wur.nl/711560 LhcSR NPQ Photosynthesis Physcomitrium patens PsbS Zeaxanthin non-photochemical quenching Wageningen University & Research

oai:library.wur.nl:wurpubs/e94d9b79-d4b7-465d-948c-63d8685457d5 2026-03-05 dataset edurep openaire public

Selin Norén, Isabella Trip, Martine de Wit, David Simonse, Daniël de Haan, Janjo Korthals, Gerard Elena Jiménez, Georgina van der Hout, Annemariet Saarloos, Ardy Dataset Beter Bodembeheer Contentkalender voor communicatie versie 1.0 2026 Dit is de output van het project: https://research.wur.nl/en/projects/kom24007-beter-bodembeheer-op-de-kalender-bo-56-001-103/. Het betreft een contentkalender voor jaarronde, vraaggerichte communicatie over bodembeheer in de akkerbouw en vollegrondsgroenteteelt. De communicatie-items zijn bedoeld voor herhaald gebruik, zodat veelvoorkomende vragen van (toekomstige) boeren en erfbetreders kunnen worden beantwoord met kennis uit onderzoek. De contentkalender wordt periodiek aangevuld en opnieuw gepubliceerd in een geactualiseerde versie. Dit is de output van het project: https://research.wur.nl/en/projects/kom24007-beter-bodembeheer-op-de-kalender-bo-56-001-103/.Het betreft een contentkalender voor jaarronde, vraaggerichte communicatie over bodembeheer in de akkerbouw en vollegrondsgroenteteelt. De communicatie-items zijn bedoeld voor herhaald gebruik, zodat veelvoorkomende vragen van (toekomstige) boeren en erfbetreders kunnen worden beantwoord met kennis uit onderzoek. De contentkalender wordt periodiek aangevuld en opnieuw gepubliceerd in een geactualiseerde versie. Wageningen University & Research text/html https://research.wur.nl/en/datasets/beter-bodembeheer-contentkalender-voor-communicatie-versie-10 10.5281/zenodo.18873425 https://edepot.wur.nl/711548 Akkerbouw en vollegrondsgroenteteelt Communicatie Contentkalender Duurzaam bodembeheer Wageningen University & Research

oai:library.wur.nl:wurpubs/edec9472-ccc7-4251-89e8-1d94b26b723e 2026-04-20 dataset edurep openaire public

Berhe, Gebremeskel Berhane Grum Ritsema, Coen Baartman, J.E.M. (Jantiene) Dataset Data on: Effects of soil and water conservation measures on event-based hydrological responses and sediment yield at semi-arid catchments of Tigray, Northern Ethiopia 2026 This data set was collected from two adjacent small catchments of Korir reservoir in Tigray, Northern Ethiopia. The reservoir was built in 1996 to harvest flash floods during the rainy season and irrigate about 100 ha of land during the dry season. The reservoir has paired adjacent small agricultural catchments: Korir and Eyamat with an area of 12.9 and 3.4 km^2 respectively. The input parameters for OpenLISEM were collected for the study catchments during 2023 and 2024. This data contains rainfall data measured using two tipping bucket data loggers (one rain gauge per catchment) at five minutes time interval, catchment characteristic measure from 36 sampling points within the two adjacent catchments and flow discharges and suspended sediment concentration measures at the outlets of the two catchments. The data set is presented in three excel spreadsheets. The first spreadsheet (Catchment_data) contains the catchment characteristics collected from 36 sampling points. These parameters were collected during the 2023 and 2024 rainy seasons from 36 sampling points to prepare input data sets for the event based hydrological and erosion model, OpenLISEM. The catchment characteristics spreadsheet includes the location of the sampling points (in UTM), aggregate stability of soils (aggstab in drop no.), soil cohesion (Coh in KPa), Addional cohesion by roots (AddCoh in KPa), Soil particle median size (D50 in µm), Saturated hydraulic conductivity (Ksat in mm/h), Manning's n (-), Wetting fron soil water potential (PSI in Cm), Random Roughness (RR in cm), ston fraction (stonFrac in %), Saturated soil moisture content (ThetaS in %), Initial soil moisture content (ThetaI in %, in two weeks interval), Soil texture (USDA textural classes) and the land use type. The second spreadsheet (Eyamat_Summary and Korir_Summary) contains datasets measure at the outlet of the Eyamat and Korir catchments respectively. The first spreadsheet includes the measured precipitation (PPT in mm/hr), observed discharge (Qobs in l/s), observed suspended sediment concentration (SSC obs in g/l), model simulated discharge (Qsim (in l/s) and model simulated suspended sediment concentration (SSCsim in g/l). The rainfall runoff hydrographs for each event are also included in this spreadsheet. The rainfall runoff dates are expresses as YYMMDD. The second and third spreadsheets are the sensitivity of runoff discharge and suspended sediment concentration to the model input parameters. The model sensitivity analysis was done for the first event of the 2023 rainy season (230721) for both catchments. The fourth spreadsheet contains the effects of Stone buds and check dams on runoff discharge and suspended sediment concentration. This includes the base line scenario (SC1), the implementation of stone bunds in the hillslopes and check dams along the gullies (SC2), implementation of only stone bunds in the hillslope areas (SC3) and implementation of only check dams along the gullies (SC4). The last spreadsheet contains the discharge-suspended sediment concentration (Q-SSC) hysteresis and flushing indexes. Spatial coverage:Data was collected from two adjacent small agricultural catchments located upstream of a reservoir based irrigation scheme in Tigray region, northern Ethiopian highlands. The location of sampling points and catchment outlets are indicated in the first excel sheet. Methods, materials and software:The data was collected from two small adjacent catchment of a reservoir at a field and laboratory following standard procedure. Data sets and variable included in the spreadsheets are as explained above. The event based hydrological and soil erosion model, OpenLISEM was used to simulate the runoff discharge and suspended sediment concentration at the outlets of both catchments. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-on-effects-of-soil-and-water-conservation-measures-on-event- 10.4121/4bed0b1d-abc6-4d12-a0d2-3e8678337373 https://edepot.wur.nl/711416 Earth and related environmental sciences Event-based OpenLISEM hysteresis soil erosion Wageningen University & Research

oai:library.wur.nl:wurpubs/103a1079-8a8b-49bd-9203-e2ee498a58e8 2026-04-20 dataset edurep openaire public

Korving, Leon Dias, Daniel Panteleaki Tourkodimitri, Kallirroi Rafecas, Rosa Plana, Queralt De la Torre, Teresa Dataset Research data: Does Resource Recovery Pay Off? A Techno-Economic Evaluation of Circular Wastewater Treatment Concepts 2026 This dataset contains data that was produced for the techno-economic assessment. The dataset consists of 2 CSV files (UTF-8, semi-colon delimited). Each files contains information for a reference scenario (REF) and four alternative scenarios 1, 2, 3 and 4. All data in all files is organised in columns. The first column describes the nature of the data, the second column the measurement unit and the following columns the scenarios. The corresponding publication describes how the data was produced. Wageningen University & Research text/html https://research.wur.nl/en/datasets/research-data-does-resource-recovery-pay-off-a-techno-economic-ev 10.4121/10c96516-38ef-4a22-832c-7d33ac5d832f https://edepot.wur.nl/711243 Chemical oxygen demand FOS: Chemical engineering FOS: Environmental engineering Mass balance Nitrogen Phosphorus Scenario analysis Wastewater resource recovery sewage treatment technical economic assesment Wageningen University & Research

oai:library.wur.nl:wurpubs/ed32a8eb-cbfb-47fc-ba54-5ecc9f80a295 2026-04-02 dataset edurep openaire public

Stoffers, Twan Dataset Data from: A collaborative research agenda for restoring free-flowing rivers 2026 This dataset supports a collaborative expert-driven research agenda to identify and prioritise research needs for restoring free-flowing rivers under the EU Nature Restoration Regulation (NRR), which targets restoring at least 25,000 km of rivers to free-flowing condition by 2030. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-removing-barriers-a-collaborative-research-agenda-for-r 10.4121/36b75ce9-3a6d-4076-9f33-3c53e9f74df5 https://edepot.wur.nl/711233 EU Nature Restoration Regulation Freshwater biodiversity Migratory fishes Research agenda River morphology River restoration free-flowing rivers Wageningen University & Research

oai:library.wur.nl:wurpubs/f89163e4-7ae6-4105-911b-ecb86320aacf 2026-04-20 dataset edurep openaire public

Micella, I.M. Bak, M.P. Dürr, H.H. Jones, E.R. Kumar, R. Nkwasa, Albert Suresh, Keerthana Tang, Ting Van Vliet, Michelle T.H. Wang, M. Strokal, M. Dataset Data from Uneven distribution of multi-pollutant hotspots worldwide: river exports to seas and their global change drivers in the future 2026 The study aims to identify future multi-pollutant hotspots of coastal waters and analyse their spatial distribution patterns linked to socio-economic drivers across global income levels. The research applies the established MARINA-Multi to quantify river exports of nutrients (nitrogen & phosphorus), plastics (micro & macro), and chemicals (triclosan & diclofenac) by sub-basin and source for 2010 and 2050. The study shows that global river exports of pollutants to coastal waters are projected to increase by 2050, though not uniformly across sub-basins or pollutant types, leading to unevenly distributed future multi-pollutant hotspots. Rapid urbanization drives plastics pollution hotspots in high-income basins, and over 75% of the population in low-income basins is projected to live in future hotspots. These findings underscore the need to address income-based disparities in pollution management and to support basin-based policies for equitable and sustainable water governance. The csv files "Fig2_PDFs_2010_2050", "Fig3_Fig4_hotspot_approaches", "Fig5_hotspot_classified", and "Fig6_hotspot_D_values_per_driver" contain the main results of Micella et al. (XX). The model results are presented by river sub-basin for the years 2010 and 2050. These results are obtained by the VIC-MARINA-Multi modelling framework using forcing data from 5 global climate models for 2010 and 2050 under an economy-driven and high global warming scenario (SSP5-RCP8.5), following the methodology as described in the "Methods" section of the paper and in the "Supplementary Information" of the paper. The folder contains the "Fig2_codebook.csv", "Fig3_Fig4_codebook.csv", "Fig5_codebook.csv", and "Fig6_codebook.csv" files, which provide further descriptions of the parameters. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-uneven-distribution-of-multi-pollutant-hotspots-worldwi 10.17026/PT/WVRTGX https://edepot.wur.nl/711228 Coastal waters pollution VIC-MARINA modeling multi-pollutant pollution river export water quality Wageningen University & Research

oai:library.wur.nl:wurpubs/57b7012a-0bdc-4fd0-ae9c-68b3a5598074 2026-04-02 dataset edurep openaire public

de Jong, Anjo de Vries, Wim Dataset Data from: Decades of high nitrogen deposition mainly enhanced eutrophication rather than acidification of Dutch forest soils 2026 Element concentrations in organic layer (LFH) and topsoil (0-30 cm) in forest soils in the Netherlands in 127 plots with 7 tree species in 1990 and 2023. Data are used to calculate changes in element stock in forest on sandy soil under high nitrogen deposition loads. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-decades-of-high-nitrogen-deposition-mainly-enhanced-eut 10.4121/a2104ec9-2970-46d0-bc0a-15d9e8c1c9c0 https://edepot.wur.nl/711140 aluminium base cations carbon accumulation forest soil nitrogen saturation soil acidification soil inventory Wageningen University & Research

oai:library.wur.nl:wurpubs/7300127d-403d-4caa-907b-125abd627427 2026-04-02 dataset edurep openaire public

Berentsen, Jarne Hogeveen, Erwin Wientjes, Emilie Dataset Data underlying: Ionic regulation of thylakoid membrane architecture: Mg²⁺-driven destacking and restacking visualised 2026 In our research, we investigated the Mg²⁺-driven destacking and restacking of the thylakoid membrane. For this research, we employed fluorescence spectroscopy and microscopy to understand these changes upon depletion and re-addition of Mg²⁺. This dataset contains the data underlying the publication "Ionic regulation of thylakoid membrane architecture: Mg²⁺-driven destacking and restacking visualised". In the README file, an overview is given of the presented data and Python codes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-ionic-regulation-of-thylakoid-membrane-architectu 10.4121/449bac03-b291-4226-8484-944670081432 https://edepot.wur.nl/711129 Biological sciences Expansion Microscopy Mg²⁺ Photosynthesis Spillover Thylakoid Destacking Thylakoid Membrane Wageningen University & Research

oai:library.wur.nl:wurpubs/65d8a506-5232-4fb2-ae76-03d471be6104 2026-04-20 dataset edurep openaire public

Sytsma, M. Mulders, Ton Kamal, N. van der Werf, Andries Musters, Maikel Meesters, Lydia Dataset Dataset underlying the NXTGEN - Ready Made Meals project: Market overview of robot arms and end-effectors 2026 As part of the NXTGEN Ready Made Meals project, an overview of robot arms and end-effectors currently available on the market was compiled, with the latest update for the end-effectors gathered in 2024 and for the robotic arm in 2025. The research involved an extensive web search to identify the systems on offer, and, in some cases, companies were contacted for further insights. This overview can be continuously updated by others and serves as a valuable resource for both researchers and industry professionals looking for the right robot arm and end-effector to suit their specific needs. The initial list of robot arms was published in February 2026 and consisted of 10 robot arms.The initial list of end-effectors was published in February 2026 and consisted of 20 end-effectors. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-underlying-the-nxtgen-ready-made-meals-project-market-ove-2 10.4121/a1a18a14-70b5-4a59-9115-15eed82d469b https://edepot.wur.nl/711008 end-effectors food processing grasping methods market overview robotic arms Wageningen University & Research

oai:library.wur.nl:wurpubs/5228f760-0c9e-4b52-90e1-cf27bd9344da 2026-04-02 dataset edurep openaire public

Tielen, Toon Sytsma, M. Meesters, Lydia Dataset Dataset underlying the NXTGEN - Ready Made Meals project: Market overview of depth cameras 2026 As part of the NXTGEN Ready Made Meals project, an overview of depth cameras currently available on the market was compiled, with the latest update gathered in 2024. The research involved an extensive web search to identify the systems on offer, and, in some cases, companies were contacted for further insights. This overview can be continuously updated by others and serves as a valuable resource for both researchers and industry professionals looking for the right depth camera to suit their specific needs. The initial list of depth cameras was published in February 2026 and consisted of 55 devices. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-underlying-the-nxtgen-ready-made-meals-project-market-ove 10.4121/2e3eca4f-e765-4b7c-b6fc-5cd190cd6cd6 https://edepot.wur.nl/711006 3D vision Color Depth Point cloud Sensor comparison Wageningen University & Research

oai:library.wur.nl:wurpubs/1e2165d9-a498-40d6-94ef-d726a9c571d0 2026-04-20 dataset edurep openaire public

Stoffers, Twan van Rijn, Jimmy Winter, Hendrik V. Needle, Matt Papageorgiou, Georgios Bervoets, Tadzio Y. Bond, Mark E. Duinmeijer, Chris C. de Graaf, Martin Heithaus, Michael Poos, J.J. Schep, Stijn Tieskens, Koen Nagelkerke, L.A.J. Dataset Data from: Anthropogenic disturbance modifies spatial patterns of reef sharks 2026 This repository contains data and R scripts used to model elasmobranch relative abundance (count data per BRUV deployment) throughout the Dutch Caribbean. The workflow focuses on testing how habitat and depth relate to observed counts for focal taxa, while accounting for broad spatial structure using a categorical “Location” term (treated as a random effect). Models are fitted with Bayesian inference using the INLA framework, followed by diagnostic checks (overdispersion, residual plots) and exploratory assessment of spatial autocorrelation in residuals (mapping + variograms). Posterior predictive simulations are used to evaluate dispersion and whether the fitted Poisson models can reproduce the observed proportion of zeros. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-anthropogenic-disturbance-modifies-spatial-patterns-of- 10.4121/55d6d2ab-73fc-41c4-beb6-3aa787808a54 https://edepot.wur.nl/710944 Anthropogenic pressure BRUV Dutch Caribbean Elasmobranch FOS: Economics and business Reefs Sharks Species abundance Tourism Wageningen University & Research

oai:library.wur.nl:wurpubs/c3c2b181-0b32-492d-8e1d-f3109305ada1 2026-04-02 dataset edurep openaire public

Huijsmans, Jan Goedhart, Paul Dataset Ammonia emission experiments field-applied manure conducted in The Netherlands in 1989-2021 2026 Data repository and R programs for 414 Ammonia emission experiments with field-applied manure conducted in The Netherlands in 1989-2021 with details on application techniques, manure, field en weather conditions. Details are reported in https://doi.org/10.18174/637101 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ammonia-emission-experiments-field-applied-manure-conducted-in-th 10.4121/a5ec3e90-b25e-4ac0-9f18-4ea559cd2abb https://edepot.wur.nl/710662 Ammonia application technique arable land emission field-applied manure grassland treatment weather wheat Wageningen University & Research

oai:library.wur.nl:wurpubs/595b44e9-2bef-4504-b5fa-78452f31df9d 2026-04-02 dataset edurep openaire public

Tosto, A. Morales Sierra, A. Anten, N.P.R. Zuidema, P.A. Evers, J.B. Dataset Data underlying the publication "Quantifying the impact of pruning on young cocoa trees using a functional-structural plant model" 2026 Pruning affects tree functioning by removing biomass and triggering compensatory responses. Functional-structural plant (FSP) models, combining three-dimensional plant architecture with physiological processes, are suitable tools to study pruning effects. We present and evaluate the first FSP model for cocoa trees and we simulate pruning impact on young cocoa tree functioning. We performed two experiments: a parametrization experiment, assessing branching responses to pruning treatments (heading and thinning); and an evaluation experiment measuring the pruning effects on stem radius, leaf number and crown diameter of cocoa trees. We developed a FSP model that simulates tree growth as a result of the interaction between physiological processes, tree architecture and pruning-induced changes in branching patterns. Bud break is simulated stochastically, based on bud position and pruning interventions, and was parameterized with field observations. The evaluation experiment was replicated in silico to evaluate model predictions and quantify the effect of pruning on tree functioning. Our model captured the immediate effects of pruning on tree structure and partially simulated the compensatory response in leaf production observed in the experiment. In the simulations, pruning reduced total light interception. The simulated mean light interception per unit leaf area was increased only by the thinning treatment. However, this advantage was quickly lost due to induced branch production. Our model is a novel tool to study the short-term impact of pruning, as it explicitly simulates tree architecture and pruning-induced responses. Results highlight the necessity of dynamic simulations to understand the long-term impact of pruning in cocoa, even though long-term evaluation data is still necessary. Detailed description of the material and methods to produced the data described here can be found in the Material and Methods sections of Tosto et al 2025. Addition information on experimental and model design can be found in supplementary material Methods S1 Methods S2. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-quantifying-the-impact-of-pruning 10.17026/LS/7PQIBR https://edepot.wur.nl/710231 Agricultural Sciences Wageningen University & Research

oai:library.wur.nl:wurpubs/0f5b17ad-00d5-448c-aa77-5204d82e2c28 2026-04-20 dataset edurep openaire public

Elozeiri, Alaaeldin Spasov, Dean Rijnaarts, Huub Lammertink, Rob G.H. Dykstra, J.E. (Jouke) Dataset Data underlying the publication: On-site affordable acid and base production from seawater using bipolar membrane electrodialysis: ion transport and polyelectrolyte multilayer coating 2026 This dataset was collected at the Laboratory of Environmental Technology, Wageningen University & Research in 2024/2025. It is supplementary data for the PhD thesis of A.A.E. Elozeiri and the publication of " On-site affordable acid and base production from seawater using bipolar membrane electrodialysis: ion transport and polyelectrolyte multilayer coating". We investigated the direct use of seawater in a bipolar membrane electrodialysis (BMED) process to produce acids and bases. The current and energy efficiency of a bipolar membrane electrodialysis stack were analyzed, where the starting salt stream was 0.5 M NaCl or synthetic seawater. Moreover, the current-voltage responses of the used membranes were characterized in a 6-compartment electrodialysis cell via cyclic voltammetry. Using synthetic seawater as the salt stream in a conventional BMED stack resulted in inorganic scaling inside the BMED stack. To mitigate the inorganic scaling, we coated the cation-exchange membranes with a polyelectrolyte multilayer (i.e., PAH/PSS) to limit the transport of multivalent cations from the salt to the base compartment. This research was performed within the framework of the research program AquaConnect, funded by the Dutch Research Council (NWO, grant-ID P19-45) and public and private partners of the AquaConnect consortium and coordinated by Wageningen University and Research. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-on-site-affordable-acid-and-base- 10.4121/93d63993-6224-494f-b215-0af3fd7196a2 https://edepot.wur.nl/710219 Chemical engineering Chemical sciences Environmental engineering bipolar membrane electrodialysis polyelectrolyte multilayer scaling prevention Wageningen University & Research

oai:library.wur.nl:wurpubs/0a833b8d-bedb-42e7-b6fc-8ec6c6a585f6 2026-04-02 dataset edurep openaire public

Roelofsen, Hans Vellekoop, Sam Feist, Jan Dataset Data voor de publicatie: Scenarioopbouw en modellering MESN 2026 This report concerns scenario-design and analysis using the Model for Nature Policy (MNP), as intended for the exante evaluation of the Program for Nitrogen-reduction an Nature-restoration. We developed four scenarios which were analysed with MNP: the currect situation as reference-frame, a ‘standing-policy’ scenario incorporating current policies and finally the ‘as-planned‘ and ‘as-executed’ scenarios, which carry the full and partial implementation of the intended policies respectively. Dit rapport beschrijft scenarioontwikkeling en analyses met het Model for Nature Policy (MNP) zoals bedoeld voor de exante evaluatie van het Programa Stikstofreductie en Natuurverbetering. We ontwikkelen vier scenarios die met MNP worden geevalueerd: de huidige situatie als referentiekader, het ‘basispad 2030’ situatie waarin staand beleid is geimplmenteerd en tenslotte de plan- en uitvoeringspotentieel scenarios. Hierin zijn de maatregelen van het Programma volledig respectievelijk deels gerealiseerd. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-voor-de-publicatie-scenarioopbouw-en-modellering-mesn 10.4121/6c328085-bb0e-4e53-9eb2-6264426e53f9 https://edepot.wur.nl/710001 MESN MNP ex-ante monitoring evaluatie stikstof natuur programma natuur stikstof Wageningen University & Research

oai:library.wur.nl:wurpubs/0cc1fb3d-690c-4e6c-b264-c3a190dee1b2 2026-04-20 dataset edurep openaire public

Mendoza, Raul van Verseveld, Willem Sperna Weiland, Frederiek Bhagwat, Anjali Seijger, Chris Weerts, Albrecht Dataset Data and model underlying publication: Assessing hydrological model representation of irrigation and subsurface flow in a heavily anthropogenic influenced catchment 2026 Dataset underlying the research article on assessing the representation of irrigation and subsurface flow in a distributed hydrological model (wflow_sbm) applied to the Hindon River Basin, India. Dataset includes wflow_sbm model input, settings, and output files. Input files were generated using the wflow_sbm model building tool HydroMT-Wflow using mostly open global datasets. Output files are the simulated hydrological fluxes and states resulting from the implementations of three different irrigation schemes and two subsurface flow model concepts (total of six model runs). Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-and-model-underlying-publication-assessing-hydrological-mode 10.4121/8183bcd1-f5a8-4923-b82b-c2696a0ab550 https://edepot.wur.nl/709860 Hindon River Basin Hydrological model anthropogenic impacts wflow_sbm Wageningen University & Research

oai:library.wur.nl:wurpubs/31c0ff46-0a1b-4692-93e0-5555dfef2b36 2026-04-02 dataset edurep openaire public

van der Molen, M.K. Barten, J.G.M. Ganzeveld, L.N. Snellen, H. Dataset Atmospheric ozone concentration and flux observations over a pine forest in the Netherlands (Loobos, NL-Loo), 2025. 2026 Since March 2025 ozone concentration and flux observations have been collected at Loobos, NL (52.166446 degN, 5.743575 degE). A fast Eddy-Correlation system measuring at 20 Hz has been installed at the top of the tower (38m), well above the forest canopy. Simultaneously, a slow Thermo Model 49C O3 Analyzer has been installed to measure ozone concentrations at a 1-minute interval. Both instruments are cross-calibrated. F65: 5-minute concentration data to perform the calibration L06_F62: 30-minute ozone fluxes, without application of the calibration, the flux is given in m s-1. F63: Calibration of Fast Ozone Sensor (30 minute time base) Contact information: observations.maq@wur.nl Wageningen University & Research text/html https://research.wur.nl/en/datasets/atmospheric-ozone-concentration-and-flux-observations-over-a-pine 10.17887/WUR01-6UGU9F https://edepot.wur.nl/709752 Air Quality Concentrations Ecosystem Fluxes Forest Loobos Ozone Wageningen University & Research

oai:library.wur.nl:wurpubs/66cb0b37-186c-42bf-b912-0943e50e4d2f 2026-04-02 dataset

van Tol, R.S. Dataset Data underlying the PhD thesis: Wilding pedagogies - Exploring more-than-human ecologies of learning 2026 Data in this folder supports my dissertation entitled "Wilding pedagogies - Exploring more-than-human ecologies of learning". My thesis explores a suggested rewilding of pedagogies for a relational becoming with the world and eventually deep environmental care. Wild pedagogies (WP) concern learning in, with, trough and for nature by means of relational outdoor learning approaches. In my study I explored (1) How WP can be understood from a posthuman feminist theoretical perspective and in a context of socio-ecological crises (2) How WP can inform formal higher education and (3) whether and how WP contribute to relational being and becoming with the world among young adults in formal higher education. I worked with narrative literature review, participatory immersion, reflective questionnaires, walking interviews and document analysis as methodological appraoches. Atlas.ti was used for qualitative analysis of the data. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-phd-thesis-wilding-pedagogies-exploring-more- 10.17887/WUR01-OAETKJ https://edepot.wur.nl/709751 environmental care posthuman feminist theory relational becoming relational outdoor learning wild pedagogies Wageningen University & Research

oai:library.wur.nl:wurpubs/6be783e0-da10-4ae8-afd0-3f2c631e99ec 2026-04-20 dataset edurep openaire public

Bindt, F.P. Ocké, M.C. Toxopeus, Ido de Jonge, Rob Fensel, A. Dataset NICE-Food: An RDF knowledge graph incorporating nutritional, contaminant, and environmental characteristics of food and branded food ingredients 2026 NICE-Food: To support food experts in complex interdisciplinary information retrieval we developed NICE-Food, a knowledge graph and data pipeline combining subgraphs on Nutrition, Ingredients, Contaminants and Environmental impact for the Netherlands. Through data annotation and mapping employing food related ontologies and Resource Description Framework (RDF), NICE-Food enhances the FAIR (Findable, Accessible, Interoperable, Reusable) principles of food data. We used NICE-Food 1) to assess the data overlap between the different NICE domains 2) for the identification of communal food groups across the integrated data 3) to provide food recommendation based on specific food preferences 4) to infer knowledge on contemporary branded products such as meat and fish alternatives. NICE-Food is a knowledge graph consisting of four subgraphs covering data from: 1) N: Dutch Food Composition Database (NEVO) 2) I: Branded Food Database (LEDA) 3) C: Quality Programme for Agricultural Products (KAP) 4) E: The environmental impact of food products. Food data was harmonized using FoodOn and modelled using the food item ontology (Wageningen University & Research) and food safety monitoring ontology (Maastricht University). Wageningen University & Research text/html https://research.wur.nl/en/datasets/nice-food-an-rdf-knowledge-graph-incorporating-nutritional-contam 10.5281/zenodo.15837270 https://edepot.wur.nl/709746 Environmental Impact FAIR data Food Contaminants Knowledge Graph Nutrients Wageningen University & Research

oai:library.wur.nl:wurpubs/05a04d98-c102-4e53-a9dc-766fedd33929 2026-04-02 dataset edurep openaire public

Alpizar Rodriguez, Francisco Dataset ECIN Replication Package for "Suggested Donation or Social Information? Evidence from a Field Experiment" 2026 The data and code in this package allow for reproducing the results from the paper ‘Suggested Donation or Social Information? Evidence from a Field Experiment.’ Which fundraising strategy is more effective, and how donation behavior changes with different monetary amounts are still open questions. This study compares the effectiveness of two fundraising strategies, suggested donation and social information, and examines how different monetary amounts impact donation behavior. We implemented a field experiment on voluntary donations among visitors to a national park. Both fundraising strategies affect donation behavior. However, the donation pattern differs significantly depending on the monetary amounts shown. Our findings provide important insights for designing fundraising campaigns and show us how suggested donation and social information affect economic behavior. Wageningen University & Research text/html https://research.wur.nl/en/datasets/ecin-replication-package-for-suggested-donation-or-social-informa 10.3886/e239752 https://edepot.wur.nl/709718 donation field experiment natural park public goods Wageningen University & Research

oai:library.wur.nl:wurpubs/cb8d21af-0031-4131-af9b-f571cc8031f9 2026-04-02 dataset edurep openaire public

van den Brink, Mark van Dam, Jos Mulder, Martin Ritsema, Coen J. Bartholomeus, Ruud Dataset Data underlying the publication: Effect of increasing the level of detail in modelling the relation between agricultural yield and the drainage base 2026 This dataset contains the model in- and output and scripts describing the methodology of the study "Effect of increasing the level of detail in modelling the relation between agricultural yield and the drainage base". The aim of this research was to investigate the effect of the use of different levels of model detail within the SWAP model and their standard parametrisation, which are the result of scientific development since the 1980s, on the relation between agricultural yield and the drainage base. This was done for a representative field on the sandy uplands of the Netherlands between 1923 and 2024. The methodology of this study consists of two steps. The first step demonstrates the relation between yield and the drainage base for five base models, which differ in the level of model detail, for a maize crop simulated from 1923 to 2024. The base models have common parameters but simulate potential evapotranspiration, crop growth and oxygen and drought stress in an increasingly more detailed manner. For each of these base models, the drainage base was varied. To evaluate the effect of changing meteorological conditions, results were aggregated for the 30-year periods 1925-1954, 1960-1989 and 1995-2024. Using the resultant relationships between yield and the drainage base, feasible ranges of the drainage base required to achieve a minimum relative yield of 80 and 90% were determined. These ranges can be used for adaptation of the drainage system in the Netherlands to both wet and dry extremes. The second step applies the methodology of the first step to different soil profiles, crops, bottom boundary condition configurations and drainage resistances to check if differences between the base models found in step one are consistent across contexts. A shorter period was simulated (1995-2024) and feasible ranges of the drainage base were determined for a minimum relative yield of 85%. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-effect-of-increasing-the-level-of 10.4121/78749828-6401-4065-828b-87c05663c566 https://edepot.wur.nl/709687 Agriculture, forestry and fisheries Crop modelling SWAP drainage base evapotranspiration root water uptake soil hydrology water management Wageningen University & Research

oai:library.wur.nl:wurpubs/075b628c-6476-4ed4-aa02-0a72417279a7 2026-04-02 dataset edurep openaire public

Arts, Gertie Huang, Anna Josemans, Meike Dataset Data underlying the publication: Characterisation of communities of terrestrial non-target plants (NTTPs) in field margins through a review of literature and databases 2026 The study has collected data about the species composition of plant communities and traits of non-target terrestrial plants (NTTPs) in the off-field area in arable land. The species composition of plant communities of non-target plants from the literature was compared to that of the EVA database (European Vegetation Archive). Based on the conclusion that the overlap was 75 %, the list of species in field margins from the EVA database with an occurrence of 5% and higher was taken as the list for which 12 traits were collected from databases and literature sources. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-characterisation-of-communities-o 10.4121/10ffe478-bf1f-4fdd-b4be-ab3e2e95586c https://edepot.wur.nl/709616 Biological sciences European Vegetation Archive TRY-database field margin non-target terrestrial plant species off-field areas plant traits species composition Wageningen University & Research

oai:library.wur.nl:wurpubs/0da30c7b-c613-42d6-8612-7b7918c8653d 2026-04-20 dataset edurep openaire public

Barneveld, Hermjan Frings, Roy Hoitink, Ton Melsen, Lieke Dataset Data set belonging to paper "Hungry rivers—Insights from a sediment budget" 2026 Objective of the study was to assess the sediment load in the Meuse river under normal conditions and during a flood period. For normal conditions the period 2011-2019 was used, for which consistent data were available. This provided an average annual sediment load for that period. For the flood event, the extreme event of July 2021 was used, providing an assessment of the sediment load during the event.The study was performed using available data on bed level changes in the main river channel and on the floodplains, dredging data, bank erosion data as well as numerical hydrodynamic simulations to assess shear stresses. Data were collected from management files of Rijkswaterstaat (river manager), fieldwork (floodplain deposition) and national bed elevation data. In a desk study these data were combined into volumes and mass of alluvial sediment (sand and gravel). Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-set-belonging-to-paper-hungry-riversinsights-from-a-sediment 10.4121/4f5acb1b-9828-4cbe-bbf4-79d36ec9a697 https://edepot.wur.nl/708926 Agriculture, forestry and fisheries Anthropogenic effect Civil engineering Earth and related environmental sciences Environmental engineering Floods Meuse River sediment budget tectonics Wageningen University & Research

oai:library.wur.nl:wurpubs/97534e34-446e-4c00-9585-b819b6061746 2026-04-02 dataset edurep openaire public

Seeger, Katharina Minderhoud, Philip S.J. Dataset DeltaDTM v1.1 referenced to mean sea level (MDT HYBRID-CNES-CLS2022) 2026 The impacts of sea-level rise and other hazards on the world's coasts are determined by coastal sea-level height and land elevation. Their correct alignment is crucial for reliable impact assessments. However, we found that over 99% of the evaluated assessments handled sea-level and land elevation data inadequately and substantially misjudged sea level relative to coastal elevation. To facilitate proper, future (re)assessments of coastal hazard impacts, we provide several state-of-the-art and ready-to-use global Digital Elevation Models (DEM) properly converted to latest coastal sea-level height for a 500km-wide coastal zone. This dataset is one of those. Wageningen University & Research text/html https://research.wur.nl/en/datasets/deltadtm-v11-referenced-to-mean-sea-level-mdt-hybrid-cnes-cls2022 10.17887/wur01-gx7s1b https://edepot.wur.nl/708800 Digital Elevation Model Natural Sciences - Earth and related environmental sciences (1.5) Sea level Wageningen University & Research

oai:library.wur.nl:wurpubs/9ccee982-1c67-445e-a285-9cefcfab818d 2026-04-02 dataset edurep openaire public

Seeger, Katharina Minderhoud, Philip S.J. Dataset FABDEM v1.0 referenced to mean sea level (MDT HYBRID-CNES-CLS2022) 2026 The impacts of sea-level rise and other hazards on the world's coasts are determined by coastal sea-level height and land elevation. Their correct alignment is crucial for reliable impact assessments. However, we found that over 99% of the evaluated assessments handled sea-level and land elevation data inadequately and substantially misjudged sea level relative to coastal elevation. To facilitate proper, future (re)assessments of coastal hazard impacts, we provide several state-of-the-art and ready-to-use global Digital Elevation Models (DEM) properly converted to latest coastal sea-level height for a 500km-wide coastal zone. This dataset is one of those. Wageningen University & Research text/html https://research.wur.nl/en/datasets/fabdem-v10-referenced-to-mean-sea-level-mdt-hybrid-cnes-cls2022 10.17887/wur01-6l9d2x https://edepot.wur.nl/708799 Digital Elevation Model Natural Sciences - Earth and related environmental sciences (1.5) Sea level Wageningen University & Research

oai:library.wur.nl:wurpubs/0de75531-263e-470b-8cf7-15e732cbbd09 2026-04-02 dataset edurep openaire public

Klein, R.C. Hageraats, S. Jansen, G.A. Ruizendaal, J.L. Dataset Data underlying the project: LWV23041 Detectie en behandeling van bladluis in het gewas (Detection and treatment of aphids in crops). 2026 This dataset contains high resolution images of aphids on bell pepper plants. It was collected as part of the project "LWV23041 Detectie en behandeling van bladluis in het gewas". (url https://research.wur.nl/en/projects/lwv23041-detectie-en-behandeling-van-bladluis-in-het-gewas-ts-02-/). The purpose was to create a computer vision method for automated early detection and monitoring of aphids. Images are captured with a Pixelink PL-D7620CU-AFE camera with a 16mm liquid lens, with a resolution of 5472x3648. This includes raw and processed focus-stacked images, where multiple images are captured with a different focus distance with the purpose of combining them into an all in-focus image. This data was collected over different trials between 2023 and 2025 in greenhouses in Bleiswijk. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-project-lwv23041-detectie-en-behandeling-van- 10.17887/WUR01-FSSPSA https://edepot.wur.nl/708734 aphids bell pepper focus stacking images Wageningen University & Research

oai:library.wur.nl:wurpubs/062e252a-44b3-4fc9-98e3-79c886c1811f 2026-04-02 dataset edurep openaire public

Drukker, Eva Froukje Dataset Data underlying the master thesis: Factors influencing invertebrate diversity on green rooftops in the Netherlands 2026 This study investigates how green roof characteristics and surrounding landscapes influence pollinator diversity and abundance in urban areas. Researchers collected ecological data on arthropods, using pan traps, pitfalls and hand netting across 21 green roofs categorized as sedum roofs, nature roofs, and roof gardens. The dataset includes measures of species richness, abundance, and functional diversity, alongside roof-level variables (flower diversity, vegetation cover, microrelief, roof size, height, and age) and landscape factors (percentage and proximity of surrounding green space). The research aims to identify which factors most strongly shape pollinator communities, providing evidence-based guidance for designing biodiversity-friendly green roofs. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-master-thesis-factors-influencing-invertebrat 10.4121/61d3c5c7-4dba-485f-8c95-0f8bf72d5046 https://edepot.wur.nl/708605 Biological sciences Ecology Invertebrate arthropods green roofs roof garden sedum roof Wageningen University & Research

oai:library.wur.nl:wurpubs/a4361e90-aa91-4c55-9fcc-c76511bb7e21 2026-04-20 dataset edurep openaire public

Hadush, Haftu Y. Baartman, Jantiene Grum, Berhane Wolka, Kebede Abebe, Niguse Hoitink, Ton van der Ploeg, Martine Dataset Data on “Matured gullies act primarily as sediment pathways rather than sources in catchment-scale sediment budgets” 2026 This dataset contains rainfall, monitored flow and sediment rates, gully morphology, and erosion model simulation data collected between August 2023 and August 2024. The data were collected to support analyses of rainfall-runoff processes, sediment transport, gully erosion, and the calibration of the SIMWE erosion model. Rainfall data include daily rainfall intensity, duration, and total rainfall amount from August 2023 to August 2024. Rainfall was measured with a rain gauge or an automated weather station and aggregated to daily values, following standard quality control procedures. Hydrological and sediment data were collected using both manual field measurements and automated sensors. Manual measurements of water depth, flow, and sediment rate were taken twice daily in the morning and evening using standardised field methods. Automated measurements were collected using TD Diver sensors installed at fixed locations at the catchment outlet locations. These sensors recorded water depth and derived flow and sediment rates at ten-minute intervals. Sensor data were corrected and processed using site-specific calibration relationships. Gully morphology data were collected during a field-based gully inventory conducted in Summer 2024. Measurements include gully dimensions and geometric characteristics obtained through direct field observation using measuring tools and GPS. The inventory followed a consistent protocol to ensure repeatability.The dataset also includes model outputs from the SIMWE erosion model. Flow simulations were generated for spring, summer, and autumn seasons and calibrated using Manning roughness coefficients. Sediment simulations were generated for the same seasons using transport coefficient, detachment coefficient, and critical shear parameters. Model calibration and evaluation were performed by comparing simulated results with observed field and sensor data. All data collection was conducted in accordance with applicable legal and ethical requirements, with permission from relevant landowners and authorities. No personal or sensitive human data are included. The dataset is intended to support reproducible research in hydrology, erosion modelling, and sediment transport analysis. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-on-matured-gullies-act-primarily-as-sediment-pathways-rather 10.4121/bb78b529-73e0-4efe-a026-fd9ac71c6b48 https://edepot.wur.nl/708541 Ethiopia Gully erosion Hydrological monitoring Omo-Gibe Basin SIMWE model Time: August 2023 - August 2024 Wageningen University & Research

oai:library.wur.nl:wurpubs/272b5105-8aa3-4f91-a529-192ceb27ec79 2026-04-20 dataset edurep openaire public

de Boer, J. van der Goot, A.J. Kers, Jannigje G. Capuano, E. Dataset Data underlying the research on: Effects of high-moisture extrusion on nutritional quality of protein isolates and concentrated from different sources 2026 Concerns have been raised over the nutritional adequacy of plant-based meat analogues, driven by the nutrient profile of their plant ingredients and their overall processed nature. To provide insights on the impact of processing on nutritional quality, this study evaluated the impact of high-moisture extrusion (HME) on anti-nutritional factors (ANFs), in vitro protein digestibility, amino acid score, and mineral bioaccessibility in commercial plant protein ingredients: faba bean isolate (FBI), pea protein isolate (PPI), soy protein concentrate (SPC), and vital wheat gluten (VWG). HME reduced the total phenolic content (8-35%) and trypsin inhibitor unit values (44-67%), while phytic acid levels remained stable. HME increased in vitro protein digestibility in SPC by 15–16%, whereas FBI, PPI, and VWG were unaffected despite the ANF reductions. The amino acid scores declined slightly, with PPI showing the lowest reduction (0.9%) and mineral bioaccessibility remained stable across most ingredients and minerals upon HME. This study provides a detailed, ingredient-specific overview of the nutritional effects of HME, demonstrating that the nutritional quality of the tested plant protein ingredients is shaped more by their inherent properties than by HME processing. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-research-on-effects-of-high-moisture-extrusio 10.17887/WUR01-1F6K4S https://edepot.wur.nl/708402 Anti-nutritional factors Extrusion Plant-based meat analogue Processing Protein quality Wageningen University & Research

oai:library.wur.nl:wurpubs/8a0e3bdc-cc62-459d-affa-67801a8054b6 2026-04-20 dataset edurep openaire public

Zuidema, Laura A. Poelman, Erik H. Delamore, Zoë Longuemare, Maxence Joachim, Gabriel Hendriks, Kasper P. Dataset Dataset and R-code associated with "Phylogenetic pattern of a clade-specific trade-off between resistance and tolerance to insect herbivory in Brassicaceae plants" 2026 Dataset used to calculate tolarance and resistance values of 18 different plant species from the Brassicaceae family. This dataset contains caterpillar weight of Pieris brassicae caterpillars, feeding damage resulting from these caterpillars, leaf area of the plants, and the seed count of the plants. The experiment took place in a greenhouse at Wageningen University and Research in 2023. 18 plant species were challenged with caterpillars (P. brassicae L1s) for seven days, or with mechanical damage (either 30%, 50% or 70%). Every species-damage treatment combination was replicated 12 times (in a randomized complete block design). After completion of the damage treatments, the plants species were left in the greenhouse to flower and produce seeds. Bombus terrestris were released for pollination. Resistance was calculated as the negation of the average caterpillar weight per plant. For plant species on which all caterpillars died, a resistance value of -0.24 was assigned, based on the average weight of 10 L1 caterpillars. In addition, plant damage caused by the caterpillars was assessed using a categorial scale from 1-10, with 1 indicating zero to 10% damage and 10 indicating 90% to 100% damage. Plant damage was assessed separately for foliage and flowers and the average was used in further analyses. Tolerance was calculated as the Pearson’s correlation coefficient of the relationship between the mechanical damage and the resulting seed count of the plants . Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-and-r-code-associated-with-phylogenetic-pattern-of-a-clad 10.4121/72a140b0-a941-4c3a-a210-175d63933ae0 https://edepot.wur.nl/708385 Biological sciences insect herbivory macroevolutionary trends plant defence resistance tolerance trade-off Wageningen University & Research

oai:library.wur.nl:wurpubs/bd35bd6a-a2e5-4cbf-8d1f-03b083ac56c7 2026-04-02 dataset edurep openaire public

Seeger, Katharina Minderhoud, Philip S.J. Dataset GLL-DTM v2 referenced to mean sea level (MDT HYBRID-CNES-CLS2022) 2026 The impacts of sea-level rise and other hazards on the world's coasts are determined by coastal sea-level height and land elevation. Their correct alignment is crucial for reliable impact assessments. However, we found that over 99% of the evaluated assessments handled sea-level and land elevation data inadequately and substantially misjudged sea level relative to coastal elevation. To facilitate proper, future (re)assessments of coastal hazard impacts, we provide several state-of-the-art and ready-to-use global Digital Elevation Models (DEM) properly converted to latest coastal sea-level height for a 500km-wide coastal zone. This dataset is one of those. Wageningen University & Research text/html https://research.wur.nl/en/datasets/gll-dtm-v2-referenced-to-mean-sea-level-mdt-hybrid-cnes-cls2022 10.17887/wur01-xgn3pk https://edepot.wur.nl/708300 Digital Elevation Model Natural Sciences - Earth and related environmental sciences (1.5) Sea level Wageningen University & Research

oai:library.wur.nl:wurpubs/064bde55-41c3-4422-aacd-96f28d0ab829 2026-05-07 dataset edurep openaire public

van Etten, Kim Brouwer, Ruben van Dam, J.C. Helfenstein, J. Dataset Data and R-scripts belonging with research paper: Determining future-proof crops based on diets and climate change 2026 Balancing human nutrition with environmental sustainability is one of the greatest challenges today as climate change threatens food production. Food systems are expected to face significant challenges in the coming decades. A shift towards new, more plant-based diets, like the EAT-Lancet diet, is necessary as adapting only agricultural practices is not enough to overcome concerns of both health and environment. Crop suitability analysis can provide crucial insights by offering vital insights into which crops have the greatest potential for cultivation in both the present and the future, supporting the transition towards climate-adaptive and nutritious food systems. The main objective of this thesis is to find out what a self-sufficient crop system, that conforms to the EAT-Lancet diet, would look like in the Netherlands in both current and future climates. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-and-r-scripts-belonging-with-research-paper-determining-futu 10.17887/wur01-tjg3i8 https://edepot.wur.nl/708248 Climate change Crop suitability indicator EAT-Lancet diet EcoCrop Natural Sciences - Earth and related environmental sciences (1.5) Protein transition Wageningen University & Research

oai:library.wur.nl:wurpubs/6a81835f-dc91-4974-8cbb-69f3db779b32 2026-04-20 dataset edurep openaire public

Fischer, Fabian Jörg Chave, Jerome Zanne, Amy Jucker, Tommaso Fajardo, Alex Fayolle, Adeline Ferreira de Lima, Renato Augusto Vieilledent, Ghislain Beeckman, Hans Hubau, Wannes De Mil, Tom Wallenus, Daniel Aldana, Ana María Alvarez-Davila, Esteban Alves, Luciana Apgaua, Deborah Mattos Guimarães Arcanjo, Fátima Bastin, Jean-Francois Bilous, Andrii Birnbaum, Philippe Blyshchyk, Volodymyr Borah, Joli Boukili, Vanessa Camarero, Jesus Julio Casas Caro, Luisa Fernanda Cazzolla Gatti, Roberto Chambers, Jeffrey Q. Chimbioputo Fabiano, Ezequiel Choat, Brendan Conti, Georgina Cornwell, Will Dar, Javid Ahmad Das, Ashesh Kumar Dobler, Magnus Dougabka, Dao Edwards, David Evans, Robert Falster, Daniel Fearnside, Philip Flores, Olivier Fyllas, Nikolaos Gerard, Jean Goodman, Rosa Guibal, Daniel Henao-Diaz, Luis Francisco Hervé, Vincent Hietz, Peter Homeier, Jürgen Ibanez, Thomas Ilic, Hugo Jansen, Steven Kalita, Rinku Moni Kenzo, Tanaka Kindermann, Liana Kothandaraman, Subashree Kotowska, Martyna Kubota, Yasuhiro Langbour, Patrick Lawson, James de Lima, André Luiz Alves Link, Roman Mathias Linstädter, Anja López, Rosana Macinnis-Ng, Cate Magnago, Luiz Martin, Adam Robert Matheny, Ashley Michelle McCarthy, James Miller, Regis B. Nath, Arun Jyoti Nelson, Bruce Njana, Marco Nogueira, Euler Melo Oliveira, Alexandre Oliveira, Rafael Olson, Mark Onoda, Yusuke Paul, Keryn Piotto, Daniel Radtke, Phil Razafindratsima, Onja Ramananantoandro, Tahiana Read, Jennifer Richardson, Sarah de la Riva, Enrique G. Rodriguez Reyes, Oris Rolim, Samir Rolo, Victor Rosell, Julieta A. Salguero-Gomez, Roberto Santini, Nadia Schuldt, Bernhard Schwendenmann, Luitgard Sellin, Arne Staples, Timothy Stevenson, Pablo R. Sundarapandian, Somaiah van der Sande, Masha Thibaut, Bernard Tng, David Torezan, Jose Marcelo Villanueva, Boris Weiskittel, Aaron Wells, Jessie Wright, S.J. Zieminska, Kasia Dataset Global Wood Density Database v.2 (GWDD v.2) 2026 The Global Wood Density Database v.2 The Global Wood Density Database v.2 (GWDD v.2) is a collection of 109,626 taxonomically standardized wood density records and 15,093 additional bark density records. Data include measurements at different levels of aggregation (individual, species) and both georeferenced records and values from the literature. For a full description of the database, please see the corresponding manuscript. (Fischer et al. 2026. Beyond species means – the intraspecific contribution to global wood density variation. New Phytol. https://doi.org/10.1111/nph.70860). It includes and supersedes the GWDD v.1 (Zanne et al. 2009, https://doi.org/10.5061/dryad.234). When using the GWDD v.2 in your work, please cite Fischer et al. 2026 as well as this repository using the corresponding DOI (10.5281/zenodo.16919509). If you would like to report an issue or suggest improvements for future updates of the GWDD, please do so on github: https://github.com/fischer-fjd/GWDD/issues Aggregated wood density data We provide pre-aggregated wood density data, with wood density estimates at species, binomial species and genus level. Wood density estimates are derived from hierarchical (random effects) models and provided both as simple species mean values (wsg_est) and as species mean values for trunks (wsg_est_trunk) and branches (wsg_est_branch) separately. In addition, we provide raw wood density means (wsg_raw), but we do not recommend using them for practical purposes due to outliers for poorly sampled species. gwddagg_v2.x_species: pre-aggregated wood density values for 17,261 species, including infraspecific epithets; comprises 16,828 taxonomically resolved species well as 433 values with uncertain taxonomic status gwddagg_v2.x_binomial: pre-aggregated wood density values for 16,905 binomial species gwddagg_v2.x_genus: pre-aggregated wood density values for 3,198 genera Raw wood density data In addition, we also provide the underlying raw wood density database. This collection contains one metadata file and raw data files in .csv format. Since special characters (e.g., in the references) can be distorted by operating systems when reading in .csv files, we also provide all data in .RData format, which can be loaded into R with the load() function. columns_gwdd_v2.x: metadata for all the columns included in the GWDD v.2 gwdd_v2.x: the GWDD v.2, including all 109,626 wood density records gwdd_v2.x_withbark: the GWDD v.2, including all 109,626 wood density records and 15,093 additional bark density records University of Bristol text/html https://research.wur.nl/en/datasets/global-wood-density-database-v2-gwdd-v2 10.5281/zenodo.16919509 https://edepot.wur.nl/708236 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/5b6476d2-44f5-4467-b74f-b42200e508ee 2026-04-02 dataset edurep openaire public

Linssen, Rikke de Smit, Sanne Ter Heijne, Annemiek Dataset Dataset accompanying "Anaerobic sulphide removal involves an intricate interplay between biomass, biosulphur, and dissolved compounds" 2026 In anaerobic conditions, haloalkaline sulphide oxidising bacteria (SOB) are able to spatially separate sulphide removal and oxygen consumption, thereby shuttling sulphide from sulphidic to aerobic environments. Previous investigations on sulphide shuttling was performed on biomass isolated from reactor effluent. To see whether the other constituents of reactor effluent also play a role in sulphide shuttling the anaerobic sulphide removal behaviour of isolated effluent fractions (biomass, biosulphur, and the dissolved fraction) of different reactor types were investigated in batch. In anaerobic conditions, sulphide concentration as well as oxygen reduction potential (ORP) were measured during for minutes after sulphide addition. Using this dataset, the related publication shows biomass, biosulphur, and the dissolved fraction all interact and contribute to anaerobic sulphide removal observed in the biodesulphurisation process. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-accompanying-anaerobic-sulphide-removal-involves-an-intri 10.4121/b8f6c0bf-8a0d-4392-9081-8af2a18312f2 https://edepot.wur.nl/708201 Environmental engineering anaerobic sulfide removal biodesulfurisation electron shuttling oxygen reduction potential sulfide oxidising bacteria Wageningen University & Research

oai:library.wur.nl:wurpubs/3062fe90-ff19-46d8-a721-25122a66daa5 2026-04-02 dataset edurep openaire public

Meijninger, Wouter Dataset Data used in the publication "Assessing grassland herb-richness through remote sensing" 2026 This dataset contains training data for random forests and convolutional neural networks to create models for predicting grassland herb richness, as indicated by the Q value, on the basis of remote-sensing data. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-used-in-the-publication-assessing-grassland-herb-richness-th 10.5281/zenodo.18242746 https://edepot.wur.nl/708199 Q value convolutional neural networks grasslands herb richness random forests remote sensing Wageningen University & Research

oai:library.wur.nl:wurpubs/5c3726f9-e017-4d91-b7e4-224a5349b1d4 2026-04-20 dataset edurep openaire public

Bonifazi, Renzo Meuwissen, Theo Croiseau, Pascal Restoux, Gwendal Minéry, Stephanie Vandenplas, Jeremie Windig, Jack J. Dataset Supplementary material of: Impact of genomic selection on genetic diversity in five local European cattle breeds. 2026 This paper investigates the impact of genomic selection on genetic diveristy of five local cattle breeds from three European countries. The five breeds evaluated are Meuse Rhine Yssel (MRY; from the Netherlands), Norwegian Red (from Norway), Abondance, Tarentaise, and Vosgienne (from France). We investigated changes in population demographic structure, as well as trends and rates of kinship and inbreeding, using both pedigree- and genomic-based measures. The population size varied depending on the breed, with Vosgienne being the smallest and Norwegian Red being the largest. Single nucleotide polymorphisms (SNPs) genotypes were available for 4,645 MRY, 193,489 Norwegian Red, 16,387 Abondance, 8,578 Tarentaise, and 4,472 Vosgienne animals. Animals were genotyped with more than 40,000 SNPs. For a detail description please refer to the full paper. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-material-of-impact-of-genomic-selection-on-genetic- 10.4121/492436f4-dc41-42a1-9c79-ab886089b28e https://edepot.wur.nl/708076 Animal and dairy science Genetic diversity Genomic selection Inbreeding Local breeds Wageningen University & Research

oai:library.wur.nl:wurpubs/b6c6e36f-894b-4a42-a155-a37001da7c48 2026-04-02 dataset edurep openaire public

Yan, Xiaofang de Smit, Sanne Liu, Dandan Buisman, Cees ter Heijne, Annemiek Dataset Data underlying the publication: Toward Nitrous Oxide-Free Ammonium Treatment: Integrating Hydrogenotrophic Denitrification in Anoxic Bioanodes 2026 Microbial electrolysis cells (MECs) offer a novel alternative to conventional biological ammonium (NH4+) removal by using electrodes, rather than oxygen, as electron acceptors. However, NH4+ oxidation at bioanodes can result in substantial nitrous oxide (N2O) emissions—a potent greenhouse gas with significant climate impact. We investigated the potential of hydrogenotrophic denitrification within the anodic compartment to mitigate N2O emissions during NH4+ removal. In situ hydrogen (H2) addition effectively reduced N2O concentrations to below 0.01 mg-N/L, without nitrate or nitrite accumulation. Batch experiments demonstrated that the suspended biomass, exhibited a high capacity for N2O reduction, which was strongly dependent on H2 availability and linked to denitrification activities. Integrating hydrogenotrophic denitrification with NH4+ oxidation in MECs presents a promising approach for sustainable nitrogen management with near-zero N2O emission. Wageningen University & Research text/html https://research.wur.nl/en/datasets/b6c6e36f-894b-4a42-a155-a37001da7c48 10.4121/dbeeeccc-0285-496c-9c8a-591bef50de9a https://edepot.wur.nl/707987 Ammonium Denitrification Hydrogen Microbial electrolysis cells Nitrous oxide Wageningen University & Research

oai:library.wur.nl:wurpubs/6ed5a520-8801-4493-87e1-f643da275ec5 2026-04-20 dataset edurep openaire public

Venkatachalam, A. Wilms, Patrick Patón Baeza, Júlia Schutyser, M.A.I. Zhang, L. Dataset Data underlying the publication: Formulation of pea-based inks with different starches to produce customized 3D printed and baked snacks 2026 This dataset was collected as a part of the NWO PhD project: PRINTYOURFOOD with grant number 18763. The current dataset was used to investigate the effect of varying composition and starch type (native pea starch, pre-gelled pea starch, and potato flakes) on 3D printability of formulated inks and the textural properties of post-processed pea-based snacks. To test for 3D printability, formulations were prepared by adding water based on the water holding capacity (WHC) of the raw materials. Doing so, the printability landscape obtained using different starch types were compared. Furthermore, well-printable formulation varying in starch-to-protein ratio were short-listed per starch type and further subject to 3D printing and post-processing (baking). The fracture properties (Young's modulus and fracture stress) of these short-listed samples were measured using single compression. These results showed the effect of starch type and baking time on fracture properties. This dataset provides a systematic approach to effectively formulate and process 3D printed products containing starch without compromising product quality in terms of nutritional composition, printability, and texture. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-publication-formulation-of-pea-based-inks-wit 10.17887/WUR01-R9RB2G https://edepot.wur.nl/707848 Extrusion Force Starch Water Holding Capacity Young's Modulus Wageningen University & Research

oai:library.wur.nl:wurpubs/de0d37c7-fd48-47db-b0a3-2c063725681d 2026-04-02 dataset edurep openaire public

van der Wal, J.T. Brinkman, A.G. Jacobs, P. Dataset Data underlying the report: Primary Production - Ems-Dollard estuary 2026 The Water Framework Directive (WFD) requires EU member states to achieve good ecological and chemical status of all designated water bodies (rivers, lakes, transitional and coastal waters) by 2015. Therefore Rijkswaterstaat Waterdienst has initiated the project ‘Research mud dynamics Ems Estuary’ (Onderzoek slibhuishouding Eems‐Dollard). The aim of this project, carried out by Deltares and IMARES, is to (1) improve our knowledge on the mud dynamics in the Ems Estuary (Figure 1.1), (2) to identify the reasons for the increase in turbidity and (3) to quantify measures to improve the ecological status of the estuary. The whole research consists of an analysis of available data, the collection of new data as well as the improvement and application of numerical models. The IMARES task, reported in this document, is to provide the numerical models with ecological data, and to answer a number of primary production related questions which are important for reaching aim (3). The last detailed research on ecological characteristics of the Ems‐Dollard estuary has been performed between 1976 and 1980. IMARES performed new research on phytoplankton presence and primary production in 2012 and 2103, and on phytobenthos presence and primary production in 2013. Beside this, concentrations of nutrients, suspended matter and a number of associated variables were measured. Brinkman et al. (2014, C160/14) the full-data report has the following topics covered (from paragraph 1.6): Chapter 2: characteristics of the area. Chapter 3: description of the measurements: where, when and how. Chapter 4-6: the analytical and mathematical methods used to analyse the data. Chapter 4: analyse on pelagic and benthic data; Chapter 5 pocket box data; Chapter 6 regression analyses. Chapter 7-10: result. Chapter 7 results of the correlation analyses and how these were mutally used to correct other observations. Chapter 11: discussion plus conclusions All chapters include a 'what have we learnt'-section and include recommendations for future research. Main report reference with DOI or download link; Brinkman, A. G., R. Riegman, P. Jacobs, S. Kuhn, and A. Meijboom. 2015. Ems-Dollard Primary Production Research: Full Data Report. C160/14. Wageningen Marine Research. https://research.wur.nl/en/publications/ems-dollard-primary-production-research-full-data-report or https://edepot.wur.nl/350873 . Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-the-report-primary-production-ems-dollard-estuary 10.17887/WUR01-8EMXH7 https://edepot.wur.nl/707734 Algae Diatoms Microphytobenthos Phytoplankton Primary Production Water Framework Directive Wageningen University & Research

oai:library.wur.nl:wurpubs/37cf8c08-0445-4bb8-a473-08bce74c6f35 2026-04-29 dataset edurep openaire public

Bagchus, C.R.P. Ramakers, L.A.I. Verhoeven, D. van Amerongen, H. Wientjes, I.E. Dataset Data underlying: Photodamaged PSII does not accumulate in the non-appressed thylakoid membranes in the absence of PSII repair 2026 In our research, we applied Fluorescence Lifetime Image Analysis (FLIM) and biochemical fractionation of the thylakoid membrane to investigate the localization of damaged PSII following photoinhibition in the presence of lincomycin. This dataset contains the data underlying the publication entitled "Photodamaged PSII does not accumulate in the non-appressed thylakoid membranes in the absence of PSII repair". In the README file, an overview is given of the presented data and Python codes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-photodamaged-psii-does-not-accumulate-in-the-non- 10.4121/731a604c-72bc-4aea-9197-51c7a2bef42c https://edepot.wur.nl/707595 Fluorescent Lifetime Image Microscopy (FLIM) Photoinhibition Photosynthesis Thylakoid membrane Wageningen University & Research

oai:library.wur.nl:wurpubs/c8c61377-9a68-44d6-9072-4a439415cd6f 2026-04-20 dataset edurep openaire public

Dörper, A. Nicolai, K. Gort, G. de Jong, I.C. van Harn, J. Veldkamp, T. Dicke, M. Dataset Supplementary results and videos from: Feeding live or processed black soldier fly larvae to slow-growing broilers impacts their behaviour differently 2026 To address the growing public concerns regarding poultry rearing, the purpose of this study was to investigate if black soldier fly larvae (BSF) as part of slow-growing broiler (Hubbard JA757) diets or rations have the potential to improve broiler health and welfare. Four different BSF larvae products and product combinations were tested in this study: live larvae (L), a combination of BSF larvae meal and fat (MO) mimicking the nutritional composition of the live larvae, and BSF larvae meal (M) and fat (O) separately. All BSF larvae products and product combinations were tested at two inclusion levels (low and high). Per treatment group 8 replicate pens were used, with 24 broilers housed in each pen. The broilers arrived at as 1 day old chickens and the experiment lasted until they reached 51 days of age. Blood biochemical parameters were assessed to quantity the health of the broilers, while physical welfare scores, behavioural observations, and activity tracking were performed to quantify the broilers welfare. In this repository supplementary tables and videos supporting the article (to be added later) have been deposited. The supplementary tables present the composition of BSF larvae products and pellets used in the experiment, including the nutrients, amino acids, minerals, and fatty acids. They also include results from statistical analyses of broiler behaviour observations, growth performance, blood serum parameters, and measurements of immunological organs. The supplementary videos show different situations where male slow-growing broilers (Hubbard JA757) consume live BSF larvae. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supplementary-results-and-videos-from-feeding-live-or-processed-b 10.4121/d07f34c4-55d1-4c70-83d3-4c081ff5d6de https://edepot.wur.nl/707300 Hermetia illucens activity health and welfare insects as feed live larvae Wageningen University & Research

oai:library.wur.nl:wurpubs/5d2f19cb-e234-42cd-a1cc-808b2d8a0b7f 2026-04-17 dataset edurep openaire public

van de Ven, R. Bressilla, K. Nelissen, B.J.H. Nieuwenhuizen, A.T. van Henten, E.J. Kootstra, G.W. Dataset Data for "Enhancing annotations for 5D apple pose estimation through Gaussian Splatting" 2026 Data related to the paper "Enhancing annotations for 5D apple pose estimation through Gaussian Splatting". This dataset contains the raw images, processed images used for training the 3D Gaussian Splat, trained 3DGS, and annotations of the fruit poses. The raw images were collected in an orchard in Randwijk in 2024. This data combines with the pipeline available at: https://github.com/WUR-ABE/Gaussian-Splatting_pose-estimation Together, these can be used to simplify the pose annotations process required to train apple pose estimation algorithms. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-for-enhancing-annotations-for-5d-apple-pose-estimation-throu 10.4121/976c94f2-028f-4291-adfd-20eb82b0f647 https://edepot.wur.nl/706996 3D Gaussian Splatting 3D detection Apple pose estimation fruit pose Wageningen University & Research

oai:library.wur.nl:wurpubs/654447 2026-04-20 dataset edurep openaire public

Fendor, Z. Carnoli, A.J. Hobé, R.G. Hoenderdaal, W.F. de Jong, I.C. Louton, Helen Quirin, Lisa Marchewka, Joanna Sztandarski, Patryk Ludwiczak, Agnieszka Erasmus, Sara Wilhelmina Yigitturk, S. Schou Grønbeck, Marlene van Asselt, E.D. Dataset Data underlying "Assessing the impact of husbandry conditions on broiler meat quality using machine learning" 2026 This repository contains the data used in the publication "Assessing the impact of husbandry conditions on broiler meat quality using machine learning" by Fendor et al. The data was collected as part of the European project mEATquality. The aim of the project was to study the effects of extensive husbandry practices on the quality of meat. The trials conducted within the project covered space allowance, space quality, breed, and diet. The meat quality was measured through physiochemical analysis, a sensory panel, and consumer tasters. More information about the set up of the study in the project can be found in the accompanying publication and on the project website: meatquality.eu. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-underlying-assessing-the-impact-of-husbandry-conditions-on-b 10.5281/zenodo.17482438 https://edepot.wur.nl/705965 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/becb5c2e-c5b2-4cc2-ad37-1b91908847db 2026-05-12 dataset edurep openaire public

Proske, Ulrike Staab, Martin Dataset Teaching materials for "Hello world! Teaching an interdisciplinary understanding of climate modelling" 2025 This repository contains the teaching materials referenced in the paper: Authors: Ulrike Proske and Martin Staab Titel: Hello world! Teaching an interdisciplinary understanding of climate modelling Date: 2025 Wageningen University & Research text/html https://research.wur.nl/en/datasets/becb5c2e-c5b2-4cc2-ad37-1b91908847db 10.5281/zenodo.17791563 https://edepot.wur.nl/715981 Climate Models Science and technology studies Teaching Materials Wageningen University & Research

oai:library.wur.nl:wurpubs/1d6f3207-9923-43ea-9781-1aced7f4961d 2026-05-12 dataset edurep openaire public

Upton, Samuel Reichstein, Markus Peters, Wouter Botía, Santiago Nelson, Jacob A. Walther, Sophia Gans, Fabian Jung, Martin Haszpra, László Dataset Data from: Constraining a data-driven CO2 flux model by ecosystem and atmospheric observations using atmospheric transport 2025 This dataset is a sample of the data from the paper 'Constraining a data-driven CO2 flux model by ecosystem andatmospheric observations using atmospheric transport' The data is a subset of daily mean NEE in $\mu mol CO_{2} m^{-2} s^{-1}$ downsampled form 0.05 to 0.25 deg spatial resolution for the years 2016-2020. Acknowledgements. We would like to thank the FLUXCOM team for their structural support, feedback and discussion. The authors wouldlike to thank the eddy covariance community, particularly FLUXNET and the associated regional networks, the European Integrated CarbonObservation System (ICOS) and AmeriFlux. We would like to thank Dr. Jost Lavric for the use of ATTO observational data. We wouldlike to thank Dieu Anh Tran and Dr. Sönke Zaehle for providing and facilitating our use of the ZOTTO observational data. The Authorswould like to thank the producers of the inversion data included in this study. We would like to thank Dr. Saqr Munassar and Dr. ThomasKoch for providing STILT footprint runs for the European domain. This research was funded by the European Research Council (ERC)Synergy Grant ’Understanding and modeling the Earth System with Machine Learning (USMILE)’ under the Horizon 2020 research andinnovation programme (Grant Agreement No. 855187). SB and the ATTO project were funded by the German Federal Ministry of Educationand Research (BMBF, contracts 01LB1001A and 01LK1602A). The ATTO project is furthermore funded by the Brazilian Ministério daCiência, Tecnologia e Inovação (MCTI/FINEP contract 01.11.01248.00) and the Max Planck Society. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-constraining-a-data-driven-co2-flux-model-by-ecosystem- 10.5281/zenodo.17531188 https://edepot.wur.nl/715962 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/5a90105b-70d1-46cb-9c04-bcfd84125064 2026-05-12 dataset edurep openaire public

La Capra, Marco Wagner, Daniel Agarwal, Seema Fleckenstein, Jan H. Frei, Sven Dataset Dataset and code for the publication: "Mobility and Retention of Microplastic Fibers and Irregular Fragments in Fluvial Systems: An Experimental Flume Study" 2025 Background:This dataset contains data from microplastic transport experiments conducted in an experimental flume at the University of Bayreuth. This data was analyzed in the paper by Marco La Capra, Daniel Wagner, Seema Agarwal, Jan H. Fleckenstein, and Sven Frei with the title: “Mobility and Retention of Microplastic Fibers and Irregular Fragments in Fluvial Systems: An Experimental Flume Study”, currently under review in Microplastics and Nanoplastics. Description: This dataset contains all the processed data obtained during the experiment. This dataset does not contain the raw images from the FIS and the PIV systems. The datasets included are: Individual experimental data and results in the folders: 250423-fibers (Dataset for the MPFs experiment) 250506-fragments (Dataset for the IMPs experiment) 250825-fluorescein (Datasets for the fluorescein experiment) Scripts (Contains the individual scripts used for the experiments outside of the folders with the folder logic used for the other experiments) Comparison files (contain the results of the experiments in comparison to one another) Experiment_book_yymmdd(metadata repository of each experiment. The file contains data used by the Python scripts) Code description: The Python scripts included in the “Script” folder are example scripts of the actual scripts used for data processing. The scripts used for each experiment, along with their modified variables, are located in the corresponding folder for each experiment. The scripts are divided into the same folder structure used for the experiments. Scripts utilized for the data processing of the Fluorescence imaging system (1_Data-FIS): FCS calibration: Reads the images taken for the calibration of the liquid and sedimented sections of the flume and performs the calibration of the two sections. The data is then plotted and saved as a .json file, which is used by the experimental script Well illuminated area mask: Reads the images taken for the determination of the area of the experimental flume that is illuminated by the laser. This area is then saved in both .npy and .tif formats. FCS experiment: Reads the calibration .json file and the metadata file to average every second of images and calculate the actual concentration from the .tiff values separated for the sediment and liquid sections. These values are then plotted within the well-illuminated area and are used to calculate the infiltration depth of each compound. Scripts utilized for the data processing of the fluorometer data (2_Data-Fluos): fluos filler: finds missing data in the raw datasets of the fluorometers and fills the data by interpolation fluo data plot: Performs the calibration of the two fluorometers and plots the results from the experiments by reading the Experiment_book file Script utilized for the data processing of the laser profiler data (3_Data-Profiler): laserprofiler script: reads the two folders of .txt data from the laser profiler, cleans them of the 0,0,0,0 tuples and plots both the evolution of the first three dunes over time and plots the total sediment profile by reading the loc_reference .xlsx file. Script utilized for the data processing of the PIV data (4_Data-PIV): PIV script: reads and opens both the total average and the Reynold stresses .dat files obtained from the PIV measurements. They are then merged to generate an overview of the whole investigated area, and the data is plotted for the section above the sediment. Script utilized for the data processing of the HOBOs data (5_Data_HOBOs): HOBO plot: reads each of the .csv files obtained from each HOBO used during the experiment, applies calibration when needed and plots them over time or over the length of the flume University of Bayreuth text/html https://research.wur.nl/en/datasets/dataset-and-code-for-the-publication-mobility-and-retention-of-mi 10.5281/zenodo.17249161 https://edepot.wur.nl/715958 Microplastics River bed River pollution Wageningen University & Research

oai:library.wur.nl:wurpubs/bc0a835f-2db7-4492-b4b6-9bc6905c83d5 2026-05-12 dataset edurep openaire public

Grünig, Marc Rammer, Werner Senf, Cornelius Albrich, Katharina André, Frédéric Augustynczik, Andrey Lessa Derci Baumann, Martin Bohn, Friedrich Bouwman, Meike Bugmann, Harald Collalti, Alessio Cristal, Irina Dalmonech, Daniela De Coligny, Francois Dobor, Laura Dollinger, Christina Espelta, Josep Maria Forrester, David Garcia-Gonzalo, Jordi González-Olabarria, José Ramón Hiltner, Ulrike Hlásny, Tomáš Honkaniemi, Juha Huber, Nica Jonard, Mathieu Jönsson, Anna Maria Kunstler, Georges Lagergren, Fredrik Lindner, Marcus Mina, Marco Moos, Christine Morin, Xavier Muys, Bart Nabuurs, Gert-Jan Nieberg, Mats Patacca, Marco Peltoniemi, Mikko Reyer, Christopher Schelhaas, Mart-Jan Storms, Ilié Thom, Dominik Toïgo, Maude Seidl, Rupert Dataset Data from: Climate change will increase forest disturbances in Europe throughout the 21st century 2025 Wildfires, insect outbreaks, and storms cause large pulses of tree mortality. Climate change amplifies these forest disturbances, yet their future magnitude and extent remain uncertain. Here, we simulate future forest disturbance regimes at 100m resolution across Europe, using a deep learning-based simulation framework. Our results show that forest disturbances will continue to increase throughout the 21st century, withthe disturbed area more than doubling relative to the recent past under an unabated continuation of climate change. Wildfires are the main agent driving future disturbance change. Changing disturbances result in an increase in young forests, substantially altering Europe’s forest demography. Because of their profound implications for forest carbon storage and the habitat value of forest ecosystems, disturbances should be a priority of forest policy and management. # Data from: Climate change will increase forest disturbances in Europe throughout the 21^st^ century Dataset DOI: [10.5061/dryad.tb2rbp0dv](https://doi.org/10.5061/dryad.tb2rbp0dv) ### Corresponding author information Name: Marc Grünig Affiliation: Swiss TPH, Switzerland email: marc.gruenig@swisstph.ch ### Alternative contact information Name: Werner Rammer Affiliation: TUM, Germany email: werner.rammer@tum.de ## Description of the data and file structure ### Files and variables This folder contains data for the publication `Climate change will increase forest disturbances in Europe throughout the 21st century`. The data provided here allows to run code that is stored in the folder `00_code`. We provide several folders with data. Each folder contains its own README file with more details about the files within the folder. Additional details and description about the data can be found in the R and Python scripts. The data is organized in the following folder structure that roughly follows the order of the steps taken: ### Directory tree ``` ├── 00_code ├── 01_simulation_data_pipeline ├── 02_dnn ├── 03_initial_forest_states ├── 04_disturbance_modules ├── 05_clim_data ├── 06_gis ├── 07_reference_grids ├── 08_svd ├── 10_results └── 11_figures ``` Below, the detailed description of all folders is listed. *00_code.zip* ``` 00_code ├── .gitignore ├── .Rhistory ├── 00_functions │ ├── check_attribute_cols_function.R │ ├── check_height_cols_function.R │ ├── check_species_cols_function.R │ ├── check_species_condition.R │ ├── create_aug_examples_function.R │ ├── create_examples_function.R │ ├── get_point_id.R │ ├── height_max_mean_function.R │ ├── height_transformer.R │ ├── kahn_factors_function.R │ ├── reorder_strings.R │ ├── states_mapping_function.R │ └── yield_table.R ├── 01_data_pipeline │ ├── 00_examples.R │ ├── 01_collect_soildata.R │ ├── 02_climate_data_timeseries.R │ ├── 03_collect_climatedata.R │ └── 04_examples_complete.R ├── 02_fire_module │ ├── 01_wind_directions.R │ ├── 02_summer_vpd_calc.R │ ├── 03_fire_freq_size_models.R │ ├── 04_fire_occurrence_model.R │ ├── 05_create_fire_events.R │ └── 06_fire_states.R ├── 03_wind_module │ ├── 01_wind_simulations.R │ └── 02_wind_susceptibility.R ├── 04_bbtl_module │ ├── 01_background_proba.R │ ├── 02_bbtl_susceptibility.R │ ├── 03_bbtl_kernels.R │ └── phenips │ ├── bbgenerations.cpp │ ├── bbgenerations.h │ ├── bbgenerations.o │ ├── bb_kernels.csv │ └── phenips.cpp ├── 05_mgmt_module │ ├── 01_mgmt_proba.R │ └── 02_mgmt_spatial_cap.R ├── 06_climate_data │ ├── 01_cordex_biascorrection.R │ ├── 02_svd_climate_data.R │ └── 03_svd_climate_compr.py ├── 07_svd_initial_landscape │ ├── 01_prepare_canopyheight_layer.R │ ├── 02_vegetation_stacks.R │ ├── 03_initial_soilconditions.R │ ├── 04_initial_states_landscape.R │ ├── 05_initial_vegetation_evaluation.R │ └── 06_forest_state_lookups.R ├── 08_outputs_analysis │ ├── 01_svd_grid_processing.R │ ├── 02_extract_distrate_25km.R │ ├── 03_annual_outputs_processing.R │ ├── 04_extreme_events.R │ ├── 05_old_young_forests.R │ ├── 06_Fig1a_disturbance_rates.R │ ├── 06_Fig1b_heatmap.R │ ├── 07_Fig2a_biomes_dist_change.R │ ├── 07_Fig2b_disturbancemaps.R │ ├── 08_Fig3a_stacked_bars.R │ ├── 08_Fig3bcd_extreme_events.R │ ├── 09_Fig4_structure_trends.R │ ├── 21_module_evaluation.R │ ├── 22_uncertainties.R │ └── 23_feedbacks_interactions.R ├── disturbance_scenarios_europe.Rproj └── README.md ``` Contains the code and resources to create and analyze future disturbance scenarios for Europe. The code is also available at [https://github.com/magrueni/disturbance_scenarios_europe](https://github.com/magrueni/disturbance_scenarios_europe) *01_simulation_data_pipeline.zip* ``` 01_simulation_data_pipeline ├── climate_expl.csv ├── climate_slopes.csv ├── clim_bias_expl.csv ├── clim_slopes │ ├── prec_ICHEC_EC_EARTH_historical.csv │ ├── prec_ICHEC_EC_EARTH_rcp_2_6.csv │ ├── prec_ICHEC_EC_EARTH_rcp_4_5.csv │ ├── prec_ICHEC_EC_EARTH_rcp_8_5.csv │ ├── prec_MPI_M_MPI_ESM_LR_historical.csv │ ├── prec_MPI_M_MPI_ESM_LR_rcp_2_6.csv │ ├── prec_MPI_M_MPI_ESM_LR_rcp_4_5.csv │ ├── prec_MPI_M_MPI_ESM_LR_rcp_8_5.csv │ ├── prec_NCC_NorESM1_M_historical.csv │ ├── prec_NCC_NorESM1_M_rcp_2_6.csv │ ├── prec_NCC_NorESM1_M_rcp_4_5.csv │ ├── prec_NCC_NorESM1_M_rcp_8_5.csv │ ├── temp_ICHEC_EC_EARTH_historical.csv │ ├── temp_ICHEC_EC_EARTH_rcp_2_6.csv │ ├── temp_ICHEC_EC_EARTH_rcp_4_5.csv │ ├── temp_ICHEC_EC_EARTH_rcp_8_5.csv │ ├── temp_MPI_M_MPI_ESM_LR_historical.csv │ ├── temp_MPI_M_MPI_ESM_LR_rcp_2_6.csv │ ├── temp_MPI_M_MPI_ESM_LR_rcp_4_5.csv │ ├── temp_MPI_M_MPI_ESM_LR_rcp_8_5.csv │ ├── temp_NCC_NorESM1_M_historical.csv │ ├── temp_NCC_NorESM1_M_rcp_2_6.csv │ ├── temp_NCC_NorESM1_M_rcp_4_5.csv │ └── temp_NCC_NorESM1_M_rcp_8_5.csv ├── examples_expl.csv ├── metadata_expl.csv ├── metadata_processed_expl.csv ├── readme.txt ├── simdata_expl.csv ├── states_lookup_pruned.csv ├── states_lookup_pruned_init_ls.csv └── time_series.csv ``` This folder contains data which can be used to have a look at the data pipeline that converts local forest simulations from the harmonized simulation database ([https://zenodo.org/records/12750180](https://zenodo.org/records/12750180)) to deep neural network training data. Values in the example have been modified for demonstration purposes. While we cannot provide the full dataset here, the corresponding code allows to create the full training dataset from the underlying database. More information and code is currently under review (Grünig, M. et al. Loss of competitive strength in European conifer species under climate change. Under review) The four main variables that are contained in the .csv files with climate information are: temperature [°C], precipitation [mm], VPD [kPa] and radiation [W/m²]. The file names represent one of the four climate variables (tas, prec, vpd, rad). All files containing climate data, start with `clim_`. The folder `clim_slopes` contains .csv tables with annual mean temperatures which are used to translate climate data from the forest simulations to the climate change scenarios used in SVD. File naming follows the convection of `climatevariable_GCM_RCP.csv` where climate variable can be `prec` or `temp`, GCM is one of `ICHEC_EC_EARTH`, `MPI_M_MPI_ESM_LR`, `NCC_NorESM1_M`. RCP is `historical`, `rcp_2_6`, `rcp_4_5` or `rcp_8_5`. Further, the folder contains .csv files with examples of simulation data and related metadata. Those files contain predominantly the three dimensions of forest states: species proportions [%], LAI [m²/m²], Dominant height [m], as well as stand soil information on WHC [mm], texture (sand, silt, clay [%]), depth [mm], plant available nitrogen [kg/ha/year]. The file `examples_expl.csv` contains training data examples with forest state transitions and residence times. *02_dnn.zip* ``` 02_dnn ├── dnn_states_lookup.csv ├── models │ ├── climcompressor_v4.h5 │ └── simple_frozen_graph_new_dnn_v17_7.pb ├── readme.txt ├── states.csv └── states_europe_meta.csv ``` This folder contains information that is relevant for the DNN part of SVD. It includes .csv files with forest state information (e.g. PIAB_20_22_2) and corresponding state IDs which are needed as SVD inputs. The trained models for climate compression and the model driving SVD are stored in the `models` subfolder. *03_initial_forest_states.zip* ``` 03_initial_forest_states ├── evaluation ├── initial_soil.csv ├── init_restime.tif ├── init_soil_rast.tif ├── init_veg_v2.tif ├── readme.txt ├── sampler │ ├── vegetationSampler.html │ └── vegetation_sampler.cpp ├── states_lookup_pruned.csv └── vegetation ``` This folder contains underlying data and results for the initial forest landscape and soil condittions that are used as starting point in SVD. * .tif & .csv files are the final layers and data for vegetation and soil that are used in SVD. The values represent forest state ids, residence time (1-10) or soil conditions (soil depth [mm], sand content [%], water holding capacity [mm], plant available nitrogen [kg/ha/year]) for each grid cell. * `evaluation` contains the results from the corresponding script as figures (.png) and tables (.csv). These files are not relevant to recreate the pipeline. * `sampler` contains C++ code for the tree species sampling performed for the initial vegetation * `vegetation` is currently empty. We cannot share the data aggregate from different sources that do not underly CC0 licensing. The relevant links to the sources are provided in the methods, suppl. material and code. *04_disturbance_modules.zip* ``` 04_disturbance_modules ├── bbtl_module │ ├── age_estimator.rds │ ├── background_equalproba_100km.tif │ ├── bb_kernels.csv │ ├── bb_patches_vpd.csv │ ├── patches │ ├── phenips │ ├── readme.txt │ ├── spruce_share.tif │ ├── states_bb.csv │ └── transition_matrix_bb.csv ├── fire_module │ ├── climate │ ├── complexes │ ├── figures │ ├── firestates.csv │ ├── fire_event_series │ ├── fire_transitions.csv │ ├── gis │ ├── models │ ├── readme.txt │ └── wind_table.csv ├── mgmt_module │ ├── management.csv │ ├── mean_harvest_100km.tif │ ├── mgmt_transitions.csv │ ├── patches │ └── readme.txt └── wind_module ├── copernicus_storms ├── patches ├── readme.txt ├── results ├── wind_event_series └── wind_transitions.csv ``` This folders contain all relevant data to the SVD external part of the disturbance modules (i.e., creating disturbance events). Readme files are included in each subfolder. We provide predominantly the calculated disturbance events along their position for wind and fire modules. The wind event series files contain information on the location of the event (cell_position, x, y), the number of 10km grid cells affected (number), proportion of 100m grid cells affected (proportion) and timepoint in the simulation (year). The wind event series tables follow the naming convention `simulated_storms_drawX.csv`, where `X` corresponds to the draw 1 to 90. The fire event series contains .csv tables with a unique fire id (fire_id), the timepoint in the simulation (year), coordinates of ignition (x, y). The allowed maximum size (max_size), the wind direction and speed (winddirection, windspeed). The table follow the naming convention `future_fire_simulation_GCM_RCP_simulation_REP.csv`. GCM is one of `ncc`, `ichec`, `mpi`, RCP is one of `historical`, `rcp26`, `rcp45`, `rcp85` and REP is the replicate 1 to 10. For bark beetle and management modules no such event series exist, however all relevant input for SVD is provided in the folders. The underlying data of the disturbance patches can be downloaded from [https://zenodo.org/records/7080016](https://zenodo.org/records/7080016), [https://zenodo.org/records/8202241](https://zenodo.org/records/8202241) and [https://zenodo.org/records/11070255](https://zenodo.org/records/11070255). Additionally, we provide VPD data [kPa] for fire and bbtl, as well as .tif and .csv files with results. *05_clim_data.zip* ``` 05_clim_data ├── annual_climate │ ├── svd_clim_ICHEC-EC-EARTH_historical_v3_aux_biascorr.csv │ └── svd_clim_ICHEC-EC-EARTH_rcp_8_5_v3_aux_biascorr.csv ├── biascorr_ICHEC-EC-EARTH_v3.csv ├── daily_climate └── readme.txt ``` This folder contains the examples of the climate data pipeline and the resulting annual climate that drives SVD. the example annual climate is also used for the SVD example landscape and has been modified. Due to limited data storage capacities, we can only provide one example for historical and future climate dataset here. The full datasets will be shared upon request. The .csv files of annual climate contain data on temperature [°C], precipitation [mm], VPD [kPa] and radiation [W/m²]. *06_gis.zip* ``` 06_gis ├── countries │ └── readme.txt ├── dem5.tif ├── europe_shp │ ├── europe.dbf │ ├── europe.prj │ ├── europe.shp │ ├── europe.shx │ ├── europe_lowres.dbf │ ├── europe_lowres.prj │ ├── europe_lowres.shp │ └── europe_lowres.shx ├── forest_mask_new_laea_masked.tif ├── forest_mask_new_laea_masked_nas.tif ├── forest_mask_wgs.tif ├── LAI_annual_mean_2020_2021_projwgs.tif ├── predicted_N_available.tif ├── readme.txt └── texture_categories.tif ``` This folder contains various shapefiles (.shp) and raster layers (.tif) that are used for calculation steps, including masks of the study region. *07_reference_grids.zip* ``` 07_reference_grids ├── biomes_hex.gpkg ├── eu_mask.cpg ├── eu_mask.dbf ├── eu_mask.prj ├── eu_mask.shp ├── eu_mask.shx ├── eu_mask_hexagons_25km.cpg ├── eu_mask_hexagons_25km.dbf ├── eu_mask_hexagons_25km.prj ├── eu_mask_hexagons_25km.shp ├── eu_mask_hexagons_25km.shx ├── gridID_10k.tif ├── hex_forest_mask_25km.gpkg ├── readme.txt ├── reference_grid.tif ├── reference_grid_100km.tif ├── reference_grid_10km.tif ├── reference_grid_1km.tif └── reference_grid_tab.csv ``` This folder contains raster layers (.tif) and sf objects (.shp) that are needed as reference grids in the code. Additionally, we provide a .csv table with the reference grid showing grid Ids along latitude and longitude. *08_svd.zip* ``` 08_svd └── svd_example ├── climate ├── dnn ├── example_ls_small │ └── output_example_1 ├── fire ├── gis ├── log └── wind ``` This folder contains the data for a small landscape to explore SVD. All relevant files to run a simulation are stored in the `svd_example` subfolder. Visit [https://github.com/edfm-tum/SVD/tree/main/SVDModel](https://github.com/edfm-tum/SVD/tree/main/SVDModel) to download SVD and look at the documentation. Note that we provide data for the fire and wind module only here for the sake of simplicity. *09_svd_simulations.tar.gz* ``` 09_svd_simulations ├── annual_outputs ├── biodiv ├── processed_data ├── raw ├── readme.txt └── svd_simulations_ids.csv ``` This folder contains the output of 120 SVD simulations. The file `svd_simulation_ids.csv` shows the configuration of each simulation with columns for simulation ID, RCP, GCM, Fire scenario, wind scenario and Replication ID. The folder `raw` contains the raw spatial outputs at 100 x 100m resolution at 10 year timesteps. There are four subfolders for each module output containing .tif raster files. name coding for the 10 year outputs is `module_timestep_RCP_GCM_REP_10year.tif`. values in the files correspond to number of disturbances per grid cell within the focal 10 year timestep. Additionally, we provide summed layers at 40 and 80 years of simulation (i.e. 2060 and 2100). Subfolders exist for barkbeelte, fire, management and wind. All files in the subfolers follow the naming convention `AGENT_YEAR_RCP_GCM_REP_10year.tif` (e.g. *`fire_10_rcp26_ncc_1_10year.tif`)*, summed layers at 40 and 80 years simulation end with `_summed.tif`. AGENT is one of `bbtl`, `fire`, `wind`, `mgmt`; YEAR corresponds to simulation decade (10, 20, 30, 40, 50, 60, 70, 80); RCP is one of `historical`, `rcp26`, `rcp45`, `rcp85`; GCM is one of `ichec`, `ncc`, `mpi`; REP is the simulation replicate 1 to 90 (future) and 91 to 120 (historical). The folder `annual_outputs` contains the annual timeseries of disturbed area across Europe the folder is organised in subfolders for each simulation which contain .csv files for barkbeetle, fire and wind. Subfolders are named `output_sim_eu_X` where X corresponds to the simulation replicate. The file `svd_simulation_ids.csv` shows the configuration of each simulation with columns for simulation ID, RCP, GCM, Fire scenario, wind scenario and Replication ID. Within each output folder, three .csv tables are provided with information on barkbeetles, fire and wind: * The barkbeetle output files show yearly outputs with columns for simulation year (year), number of gridcells with background infestations (n_background_infestation), number of gridcells with wind infestation (n_wind_infestation), number of grid cells impacted (n_impact), number of active infestations at the end of the year (n_active_yearend). * The fire output files show records for each fire with columns for simulation year (year), fire id (id), coordinates of ignitions (x, y), planned size from external event series (planned_size), realized size in SVD (realized_size), severity (share_high_severity). * The wind output files show records of each storm event with columns for simulation year (year), wind event id (id), coordinates of ignitions (x, y), proportion of planned effect (proportion), planned affected regions (=10km grids) (regions_planned), affected regions (regions_affected), forested cells in region (cells_forested), average successibility of forest in regions (mean_susceptibility), 100m cells planned (cells_planned), 100m cells affected (cells_affected). The folder `biodiv` contains the biodiversity data aggregated to 25km hexagons stored as .gpkg files. The files are named `undist_vs_recently_dist_forest_X.gpkg` where is corresponds to the simulation ID 1 to 120. The folder `processed_data` contains the processed spatial data at 25km and 50km hexagons. 50km hexagons were only used for demstration purposes. In the subfolder `dist_rates_25km` all process simulations used for the analysis are stored. The .csv tables follow the naming `all_dist_rates_YEAR_RCP.csv`, where YEAR corresponds to the simulation decade (10, 20, 30, 40, 50, 60, 70, 80); RCP is one of `rcp26`, `rcp45`, `rcp85` *10_results.zip* ``` 10_results ├── all_agents_distarea_final.csv ├── all_agents_distarea_fut.csv ├── all_agents_distarea_hist.csv ├── bbtl_results_final.csv ├── bbtl_results_fut_final.csv ├── bbtl_results_hist_final.csv ├── disturbance_change_final.csv ├── fire_results_final.csv ├── fire_results_fut_final.csv ├── fire_results_hist_final.csv ├── fut_dist_annual_final.csv ├── hist_dist_annual_final.csv ├── wind_results_final.csv ├── wind_results_fut_final.csv └── wind_results_hist_final.csv ``` Contains the results of the statistical analysis of the simulation outputs. Files are provided for individual all agents combined (`all_agents_distarea_`), individual agents (`bbtl_`, `fire_`, `wind_`), and split by historical and future simulations (`_fut.csv`, `_hist.csv`). The .csv files show simulation number (sim), simulation year (year), climate change scenario (scen), disturbed area [ha] (dist_area), time period (period) and disturbance agent (agent) as columns. *11_figures.zip* ``` 11_figures ├── figure_data │ ├── Fig1a_FigS1_fut.csv │ ├── Fig1a_FigS1_hist.csv │ ├── Fig1b.csv │ ├── Fig2a_biomes.csv │ ├── Fig2b.csv │ ├── Fig3a.csv │ ├── Fig3b_fire_extremes.csv │ ├── Fig3c_bbtl_extremes.csv │ ├── Fig3d_wind_extremes.csv │ ├── Fig4a_FigS23a.csv │ ├── Fig4b_FigS23b.csv │ ├── FigS10_data_map.csv │ ├── FigS11_data_map.csv │ ├── FigS12_data_map.csv │ ├── FigS13_sd_map_fire.csv │ ├── FigS14_sd_map_bbtl.csv │ ├── FigS15_sd_map_wind.csv │ ├── FigS16_fut.csv │ ├── FigS16_hist.csv │ ├── FigS17_fut.csv │ ├── FigS17_hist.csv │ ├── FigS18_fut.csv │ ├── FigS18_hist.csv │ ├── FigS19.csv │ ├── FigS2.csv │ ├── FigS20.csv │ ├── FigS21.csv │ ├── FigS22.csv │ ├── FigS24a.csv │ ├── FigS24b.csv │ ├── FigS29.csv │ ├── FigS3.csv │ ├── FigS31.csv │ ├── FigS32.csv │ ├── FigS33.csv │ ├── FigS34.csv │ ├── FigS35.csv │ ├── FigS36.csv │ ├── FigS4.csv │ ├── FigS5_data_map.csv │ ├── FigS6_data_map.csv │ ├── FigS7_data_map.csv │ ├── FigS8_data_map.csv │ └── FigS9_data_map.csv └── figure_descriptions.txt ``` Contains the underlying data of all figures in the manuscript and supplementary material (.csv tables). Figure descriptions are provided in the figure_descriptions.txt file. ## Code/software - **Python**: Version 3.9 or higher - **R**: Version 4.4.1 or higher Technical University of Munich text/html https://research.wur.nl/en/datasets/data-from-climate-change-will-increase-forest-disturbances-in-eur 10.5061/dryad.tb2rbp0dv https://edepot.wur.nl/715923 Earth and related environmental sciences Forest ecology Global change ecology Simulation and modeling Wildfires Wageningen University & Research

oai:library.wur.nl:wurpubs/a04bc8dc-c404-4a37-94cd-870c78b22ebe 2026-04-22 dataset edurep openaire public

Wieczorek, Karina Bugaj-Nawrocka, Agnieszka Coulson, Stephen J. Endrestøl, Anders Suñol-Escribano, Carla Magnússon, Rúna Dataset Arctic aphids - Acyrthosiphon svalbardicum, Macrosiphum calvulum, and Pemphigus populiglobuli 2025 The dataset was created as part of research published in the article "Macro- and microecological responses of Arctic aphids to climate change: linking distributional shifts and microscale environmental drivers" by Karina Wieczorek, Agnieszka Bugaj-Nawrocka, Stephen J. Coulson, Anders Endrestøl, Carla Suñol-Escribano, and Rúna Magnússon. It contains information on the occurrence of three aphid species in the Svalbard archipelago – Acyrthosiphon svalbardicum, Macrosiphum calvulum, and Pemphigus populiglobuli. Genetic data are also available for some of them. University of Silesia in Katowice text/html https://research.wur.nl/en/datasets/arctic-aphids-acyrthosiphon-svalbardicum-macrosiphum-calvulum-and 10.15468/u5p5mk https://edepot.wur.nl/714650 Occurrence Specimen Wageningen University & Research

oai:library.wur.nl:wurpubs/ff5ebdc4-aeda-49eb-aa02-9112c270a855 2026-04-15 dataset edurep openaire public

Barendse, Patrick Dataset Interference and recombination by the Thermus thermophilus Argonaute protein 2025 Here we investigate the in vivo role of the Thermus thermophilus Argonaute protein (TtAgo) during cultivation with a plasmid and antibiotic selection pressure. In addition a plasmid with arms homologous to bglT on pTT27 is used. Wageningen University & Research text/html https://research.wur.nl/en/datasets/interference-and-recombination-by-the-thermus-thermophilus-argona https://edepot.wur.nl/714122 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/35e6e55d-5498-4b5f-b2dc-47f2ed6f335b 2026-04-15 dataset edurep openaire public

Doorenspleet, Karlijn Jansen, Lara Oosterbroek, Saskia Kamermans, Pauline Bos, Oscar Wurz, Erik Murk, Albertinka Nijland, Reindert Dataset eDNA metabarcoding based marine fish biodiversity using short and long amplicons 2025 To monitor the effect of nature restoration projects in North Sea ecosystems, accurate and intensive biodiversity assessments are vital. DNA based techniques and especially environmental DNA (eDNA) metabarcoding is becoming a powerful monitoring tool. However, current approaches are based on genetic target regions <500 nucleotides, which offer limited taxonomic resolution. We developed a method for eDNA metabarcoding, based on nanopore sequencing of a longer amplicon, enabling improved identification of fish species. We designed a universal primer pair targeting a 2kb region of fish mitochondria, and compared it to the commonly used MiFish primer pair that targets only ∼170bp. In sillico and mock community testing showed that the 2kb fragments improved the accurate identification of genetically closely related species. eDNA was amplified, and sequenced using the Oxford Nanopore MinION in combination with the sequence read processing pipeline Decona. Analyzing eDNA from a North Sea aquarium showed that sequences from both primer pairs could be assigned to most species, but both approaches also identified unique species in the aquarium eDNA. Next, both primer pairs were used on multiple eDNA samples from the North Sea. Here, similar location specific fish communities were obtained from both approaches. More species were identified through the MiFish approach in the field samples. Interestingly, this difference was not observed in the aquarium, suggesting that 2kb fragment based metabarcoding potentially detects more recent occurrences of animals. This new method has the potential to improve and expand the molecular toolbox for eDNA based monitoring approaches. Wageningen University & Research text/html https://research.wur.nl/en/datasets/35e6e55d-5498-4b5f-b2dc-47f2ed6f335b https://edepot.wur.nl/714120 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/75fea961-f4e8-4226-b9e1-0d815d77cde5 2026-04-20 dataset edurep openaire public

van Himbeeck, Robbert Geisen, Stefan van Schaik, Casper van den Elsen, Sven Berendsen, Roeland Bertran, André Schepel, Egbert Helder, Johannes Dataset Local PCN suppression 2025 Local microbiome-based suppression of below-ground plant pathogens is rarely included in agricultural management practices, despite its potential value for the transition towards sustainable food production. Exploitation of this disease suppressive potential of agricultural soils is hindered by the complexity of this phenomenon that is assumed to result from the actions of a local conglomerate of microbial antagonists. Studying non-homogeneously distributed disease suppressiveness within single fields could be instrumental in pinpointing this phenomenon. In this study, we selected four apparently homogeneous potato fields that showed a patchy PCN distribution. Under controlled greenhouse conditions, we discovered that soil from patches where PCN was absent was generally more suppressive to PCN than soils were PCN was present and its biotic origin of suppression was corroborated by gamma-sterilization. Subsequent analysis of the potato rhizosphere microbial community revealed contrasts in community composition between suppressive and conducive patches, and we identified various fungal (e.g. Arthrobotrys elegans and Metacordyceps chlamydosporia) and bacterial (e.g. Pseudomonas fluorescens) nematode antagonists that were positively correlated with PCN suppressive patches. Moreover, these sets of antagonists associated with PCN suppression were field-specific, thereby emphasizing the complex and multi-faced nature of this phenomenon. Together, our findings highlight that the local heterogeneity of the soil microbiome can influence the local establishment of a phytopathogen within a field. Wageningen University & Research text/html https://research.wur.nl/en/datasets/local-pcn-suppression https://edepot.wur.nl/714118 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/bd82b830-1445-477c-8630-2e6d1f986479 2026-04-20 dataset edurep openaire public

Kerstens, Merijn van der Klugt, Freek Hofhuis, Hugo Scheres, Ben Willemsen, Viola Dataset PLETHORAs shape Arabidopsis phyllotaxis through modulation of patterning robustness and accelerated inflorescence development [WGS] 2025 Phyllotaxis is the arrangement of lateral organs on a stem axis, which in Arabidopsis follows a spiral pattern. We previously described that loss of three PLETHORA (PLT) transcription factors shifts the phyllotactic spiral to novel metastable patterns, but the mechanism behind these shifts remained unclear. • In this study, we aimed to fill this knowledge gap by performing detailed analysis of phyllotaxis in plt rosettes, inflorescences and meristems. We supplement our quantitative measurements with transcriptomic profiling of plt3 plt7 meristems, genome-wide in vitro binding assays and an EMS enhancer screen in plt3 plt5 plt7. • Contrary to earlier beliefs, primordium positioning at the inflorescence meristem is only subtly noisier in plt3 plt5 plt7, which we attribute to loss of PLT-controlled regulation of auxin and cytokinin networks. However, the meristematic patterning defects alone cannot explain the large deviations from the spiral pattern in mature mutant inflorescences. Instead, accelerated inflorescence development of plt3 plt5 plt7 generates larger patterning deviations through joint action of meristem chirality and stem torsion. We demonstrate the importance of the relationship between chirality, torsion and internode length in tissue-twisting mutants. Overall design: Whole-genome sequencing (Arabidopsis) of the segregating backcross progeny of an EMS-induced phenotype in the plt3plt5plt7 background. Wageningen University & Research text/html https://research.wur.nl/en/datasets/plethoras-shape-arabidopsis-phyllotaxis-through-modulation-of-pat-3 https://edepot.wur.nl/714117 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/b474dd39-98e7-445c-8729-6f9bf9f02360 2026-04-20 dataset edurep openaire public

Kerstens, Merijn van der Klugt, Freek Hofhuis, Hugo Scheres, Ben Willemsen, Viola Dataset PLETHORAs shape Arabidopsis phyllotaxis through modulation of patterning robustness and accelerated inflorescence development [RNA-seq] 2025 • Phyllotaxis is the arrangement of lateral organs on a stem axis, which in Arabidopsis follows a spiral pattern. We previously described that loss of three PLETHORA (PLT) transcription factors shifts the phyllotactic spiral to novel metastable patterns, but the mechanism behind these shifts remained unclear. • In this study, we aimed to fill this knowledge gap by performing detailed analysis of phyllotaxis in plt rosettes, inflorescences and meristems. We supplement our quantitative measurements with transcriptomic profiling of plt3 plt7 meristems, genome-wide in vitro binding assays and an EMS enhancer screen in plt3 plt5 plt7. • Contrary to earlier beliefs, primordium positioning at the inflorescence meristem is only subtly noisier in plt3 plt5 plt7, which we attribute to loss of PLT-controlled regulation of auxin and cytokinin networks. However, the meristematic patterning defects alone cannot explain the large deviations from the spiral pattern in mature mutant inflorescences. Instead, accelerated inflorescence development of plt3 plt5 plt7 generates larger patterning deviations through joint action of meristem chirality and stem torsion. We demonstrate the importance of the relationship between chirality, torsion and internode length in tissue-twisting mutants. • We conclude that shoot meristematic PLTs provide robustness to primordium patterning and phyllotaxis through integration of developmental processes during bolting. Overall design: RNA-seq profiling of Arabidopsis Col-0 and plt3 plt7 inflorescence meristems (31-33 dpg) and shoot apical meristems (7 dpg). Wageningen University & Research text/html https://research.wur.nl/en/datasets/plethoras-shape-arabidopsis-phyllotaxis-through-modulation-of-pat-2 https://edepot.wur.nl/714116 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/e809c7e5-5704-4f9d-bd70-1026f9d0b15b 2026-04-20 dataset edurep openaire public

Kerstens, Merijn van der Klugt, Freek Hofhuis, Hugo Scheres, Ben Willemsen, Viola Dataset PLETHORAs shape Arabidopsis phyllotaxis through modulation of patterning robustness and accelerated inflorescence development [DAP-seq] 2025 Phyllotaxis is the arrangement of lateral organs on a stem axis, which in Arabidopsis follows a spiral pattern. We previously described that loss of three PLETHORA (PLT) transcription factors shifts the phyllotactic spiral to novel metastable patterns, but the mechanism behind these shifts remained unclear. • In this study, we aimed to fill this knowledge gap by performing detailed analysis of phyllotaxis in plt rosettes, inflorescences and meristems. We supplement our quantitative measurements with transcriptomic profiling of plt3 plt7 meristems, genome-wide in vitro binding assays and an EMS enhancer screen in plt3 plt5 plt7. • Contrary to earlier beliefs, primordium positioning at the inflorescence meristem is only subtly noisier in plt3 plt5 plt7, which we attribute to loss of PLT-controlled regulation of auxin and cytokinin networks. However, the meristematic patterning defects alone cannot explain the large deviations from the spiral pattern in mature mutant inflorescences. Instead, accelerated inflorescence development of plt3 plt5 plt7 generates larger patterning deviations through joint action of meristem chirality and stem torsion. We demonstrate the importance of the relationship between chirality, torsion and internode length in tissue-twisting mutants. • We conclude that shoot meristematic PLTs provide robustness to primordium patterning and phyllotaxis through integration of developmental processes during bolting. Overall design: PLT3, PLT5 and PLT7 DAP-seq on gDNA derived from Arabidopsis shoot apical meristems and inflorescence meristems. Wageningen University & Research text/html https://research.wur.nl/en/datasets/plethoras-shape-arabidopsis-phyllotaxis-through-modulation-of-pat https://edepot.wur.nl/714115 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/57fd37d6-1255-419a-a0f5-b51f5d9e6501 2026-04-15 dataset edurep openaire public

Nieuwenhuis, Ronald Voorrips, Roeland Esselink, Danny Hesselink, Thamara Schijlen, Elio Arens, Paul Cordewener, Jan van den Broeck, Hetty C. Scholten, Olga Peters, Sander Dataset Allium ampeloprasum cultivar:Leidse prei 2018-94 Genome sequencing 2025 Genome reconstruction and transcriptome analysis of autotetraploid A. porrum (leek) cv. "Leidse prei 2018-94" Wageningen University & Research text/html https://research.wur.nl/en/datasets/allium-ampeloprasum-cultivarleidse-prei-2018-94-genome-sequencing https://edepot.wur.nl/714112 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/f9b65f19-af9a-4576-b448-1a8306b0309c 2026-04-15 dataset edurep openaire public

Crucitti, Antonino Dataset RNA-seq of onion basal plate from harvest to sprouting 2025 The transcriptome-wide expression was performed by RNA-Seq using the basal plate tissue, including the SAM. We used nine time points and the selection was based on periodic sprouting observations in onion bulbs of cv. Hyfive. We investigated the expression analysis from harvest throughout the whole storage period to select new candidate genes involved in dormancy release and sprouting regulation in onion bulbs. Wageningen University & Research text/html https://research.wur.nl/en/datasets/rna-seq-of-onion-basal-plate-from-harvest-to-sprouting https://edepot.wur.nl/714097 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/a99bf4e9-1117-4ec2-adf5-ea49ad08b312 2026-04-15 dataset edurep openaire public

Teunissen, Joliese Kupczok, Anne van Apeldoorn, Dirk F. Geisen, Stefan Dataset 16S metabarcoding analysis of field soil in intercropping 2025 We performed 16S metabarcoding on the soil of eight intercropped crop species and their 16 crop combinations. We aimed to investigate the effect of plant identity on the bacterial community composition. Intercropping of eight crop species showed within-field variation of soil bacterial communities Wageningen University & Research text/html https://research.wur.nl/en/datasets/16s-metabarcoding-analysis-of-field-soil-in-intercropping https://edepot.wur.nl/714096 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/9b8afeff-a03d-4104-b8c8-06a266f9b856 2026-04-20 dataset edurep openaire public

Wang, Yuxin Lejoly, Justine D.M. Berlinches de Gea, Alejandro Van den Elsen, Sven Veen, G.F. Geisen, Stefan Dataset 16S rRNA Sequencing to Analyze Bacterial Communities Influenced by Protist Communities of Different Size during Litter decompositions 2025 16S rRNA sequencing data is used to investigate bacterial community composition, diversity, and functional potential in response to protist communities of varying sizes during litter decomposition. This study aims to explore how different protist sizes influence bacterial interactions, abundance, and ecosystem functions, providing insights into microbial trophic dynamics and their links to carbon cycling. Wageningen University & Research text/html https://research.wur.nl/en/datasets/16s-rrna-sequencing-to-analyze-bacterial-communities-influenced-b https://edepot.wur.nl/714093 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/c3c82137-018d-438c-aaca-f0ce66e41636 2026-04-15 dataset edurep openaire public

Attiani, Valentina Smidt, Hauke van der Wielen, Paul W.J.J. Dataset "Impact of environmental and process conditions on the microbial ecology and performance of full-scale slow sand filters in drinking water treatment" 2025 Slow sand filters (SSFs) are commonly used for treating drinking water, effectively removing contaminants such as particles, organic matter, and microorganisms. However, the prokaryotic community ecology within these filters and the factors influencing its composition remain largely unclear. In this study, we analyzed the top sand layer of SSFs, known as the Schmutzdecke (SCM), along with the influent and effluent water from full-scale SSFs at four drinking water treatment plants (DWTPs) in the Netherlands. These plants use SSFs as the final step in their treatment to produce unchlorinated drinking water. Two DWTPs treat surface water after dune infiltration, whereas the other two treat reservoir-stored surface water. The biomass in the SCM of all SSFs ranged from 1.0 × 108 to 7.7 × 108 16S rRNA gene copies per gram of wet sand. The effluent water biomass was consistently lower than the influent water across all SSFs, indicating the effectiveness of the SSF process in reducing biomass load in the effluent. Key biological and chemical parameters showed that pretreatment with dune infiltration produced more biologically stable drinking water compared to reservoir storage. Beta diversity analysis and differently abundant taxa revealed distinct prokaryotic communities in the SCM and water samples, suggesting adaptation of the prokaryotes to their specific matrix type and environment rather than merely the accumulation of microorganisms in the sand from the influent water. The genera SWB02, Gemmata, Pedomicrobium, Nitrospira, and mle1-7 were more enriched in the SCM than in the water, while the genus Candidatus Omnitrophus was enriched in the water samples. Moreover, our findings show that each DWTP hosts a unique prokaryotic community composition in both the SCM and water samples, and that upstream treatment directly or indirectly, by affecting the biological stability of the SSF influent water, were likely to be responsible for the development of these unique communities. The results also showed that SSFs act as polishing filters when treating dune-infiltrated surface water or as filters that significantly change the prokaryotic community and biological stability of the water when treating reservoir-stored surface water. Wageningen University & Research text/html https://research.wur.nl/en/datasets/impact-of-environmental-and-process-conditions-on-the-microbial-e https://edepot.wur.nl/714092 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/565a1113-29de-4731-b0fd-5340fa4e77f9 2026-04-20 dataset edurep openaire public

Omary, Lina Canfora, Emanuel E. Puhlmann, Marie-Luise Gavriilidou, Asimenia Rijnaarts, Iris Holst, Jens J. Op den Kamp-Bruls, Yvonne M.H. de Vos, Willem M. Blaak, Ellen E. Dataset Effect of intrinsic chicory root fiber on individuals at risk for type 2 diabetes and with overweight/obesity by affecting microbial butyrate-producing pathways 2025 In this 12-week randomized, placebo-controlled trial in individuals at risk for type 2 diabetes and with overweight/obesity (NCT04714944), we investigated the effect of 12-week daily 30g dried chicory root intake on the human gut microbiome. Fecal samples were collected at baseline, and after 2, 6, 9, and 12 weeks, DNA was extracted, and changes in community structure and function were analyzed by using V4-16S rRNA gene amplicon and shotgun metagenomic sequencing. Wageningen University & Research text/html https://research.wur.nl/en/datasets/effect-of-intrinsic-chicory-root-fiber-on-individuals-at-risk-for https://edepot.wur.nl/714075 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/b2ed4590-34c4-4bc5-b8b2-a245dfa6b5c4 2026-04-14 dataset edurep openaire public

Bello Gonzalez, T.D.J. Marcato, F. Veldman, K.T. Wolthuis-Fillerup, M. Harders, F.L. van Reenen, C.G. Brouwer, M.S.M. Dataset Longitudinal veal study 2025 The present study aimed to evaluate the genetic diversity of ESBL/AmpC-producing E. coli isolates obtained during a longitudinal study from Dutch calves, to establish the genetic background of E. coli colonization dynamics present in calves during the rearing process. Wageningen University & Research text/html https://research.wur.nl/en/datasets/longitudinal-veal-study https://edepot.wur.nl/714071 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/2972723a-375a-47dd-86c0-a5238ad339d9 2026-04-14 dataset edurep openaire public

Berkhout, Maryse D. de Ram, Carol Boeren, Sjef Plugge, Caroline M. Belzer, Clara Dataset Niche occupation by Akkermansia muciniphila in a synthetic mucin-degrading community 2025 Akkermansia muciniphila is a specialist mucin degrader. Therefore, we assessed its ability to occupy its niche in an already established in vitro synthetic mucin-degrading community and how this affected said community. Wageningen University & Research text/html https://research.wur.nl/en/datasets/niche-occupation-by-akkermansia-muciniphila-in-a-synthetic-mucin- https://edepot.wur.nl/714067 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/297e74cf-fe70-4bad-975b-36da33f5cc30 2026-04-20 dataset edurep openaire public

Sun, Peixin Shao, Shiying Creemers, Robin W. Bekebrede, Anna F. Tang, Jing Driever, Steven Keijer, Jaap van Schothorst, Evert M. Dataset Lactose-Derived Carbohydrates Induce Sexually Dimorphic Nutritional Programming Effects on Lifespan in Drosophila melanogaster 2025 Galactose, the monosaccharide that gives together with glucose the milksugar lactose, plays a critical role in early-life nutrition and may exert long-lasting effects on later-life health. We tested whether early-life consumption of glucose and galactose (GLUGAL; as in hydorlysed lactose) shapes later-life metabolic health in the Drosophila melanogaster model. In the early life, GLUGAL versus glucose consumption alone (GLU) significantly extended the developmental time of larvae, increased the pupal volume, decreased pupal oxygen consumption, and reduced the pupal mitochondrial mass. These early-life effects were translated into sextually dimorphic effects on adult lifespan: the survival of adult male flies was reduced but the adult females lifespan was particularly extended by early-life GLUGAL consumption. Transcriptomics and lipidomics analyses in adult females revealed that early-life GLUGAL consumption systematically reduced glycerophospholipids saturation under a later-life high-carbohydrate obesogenic diet, which is characterized by decreased abundance of monounsaturated fatty acid-containing glycerophospholipids and increased abundance of polyunsaturated fatty acid-containing glycerophospholipids. This was accompanied with higher transcription levels of genes involved in hydrocarbon biosynthesis, a pathway that preferentially consumes saturated and monounsaturated fatty acids. Conclusively, early-life galactose and glucose co-consumption shortened adult males lifespan, but extended the lifespan and remodelled lipid metabolism in adult females. Overall design: Drosophila were fed glucose (GLU) or glucose+galactose (GLUGAL) diets in early-life (the larval period) and a high-glucose diet (HGLU) in later life (the adult period after eclosion). Wageningen University & Research text/html https://research.wur.nl/en/datasets/lactose-derived-carbohydrates-induce-sexually-dimorphic-nutrition https://edepot.wur.nl/714065 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/c9113a57-c06a-428f-ad16-b543da326aac 2026-04-14 dataset edurep openaire public

Scholtmeijer, Karin Lavrijssen, Brian Sonnenberg, Anton van Peer, Arend Dataset Identification of genetic variation in Illumina paired-end sequencing data of 21 Ceriporiopsis subvermispora accessions. 2025 For 21 Ceriporiopsis subvermispora accessions, Illumina paired-end sequencing data is generated and for C. subvermispora MES 15020 additional PacBio sequencing data is generated. Based on the PacBio sequencing data of C. subvermispora MES 15020, a de novo assembly is made (Cersu_MES15020_3.0_ref.fasta) to be used as a reference genome for alignment of the Illumina sequencing reads of the 21 C. subvermispora accessions and subsequent variant calling. Wageningen University & Research text/html https://research.wur.nl/en/datasets/identification-of-genetic-variation-in-illumina-paired-end-sequen https://edepot.wur.nl/714063 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/1931fb2a-fd87-41b6-8669-707620044cae 2026-04-20 dataset edurep openaire public

Jansen, Lara Loos, Eline Murk, Albertinka J. Priesmann, Birthe Valk, Sophie Walles, Brenda Kamermans, Pauline Nijland, Reindert Dataset metabarcoding of eDNA from tidal pools on artificial and natural oyster reefs 2025 The amount of humanmade structures in the worlds’ oceans is tremendous and provides a settlement opportunity for a broad range of species. The ecological value of adding hard substrate from a restoration point of view is increasingly recognized and nature-based solutions are integrated in new marine construction works to reduce erosion, enhance biodiversity or providing other ecosystem services. Artificial reefs are widely studied, yet predicting their community composition compared to natural reefs remains challenging. This study compared the community composition of a 13-year-old, humanmade intertidal Pacific oyster reef to a 27-year-old intertidal Pacific oyster reef of natural origin in the Oosterschelde Estuary in the Netherlands. Using eDNA metabarcoding of water samples and morphological identifications of hand-collected animals from tidal pools, we analyzed the communities and their biological traits at three time points. Additionally, we compared the species and biological traits detected by the two methods. Both reefs showed similar community composition, ecological traits, and prevalence of non-indigenous species (NIS). The artificial reef did not appear to facilitate the spread of NIS more than the natural reef at this stage of development. Notably, eDNA detected a broader range of ecological traits, including highly mobile species, while hand-collection of animals better identified burrowing and tube-dwelling organisms. We conclude that after 13 years, the artificial reef closely resembled the natural one, demonstrating successful ecological integration. These findings can inform nature-based construction and emphasize the need for tailored long-term monitoring based on target taxa and associated traits. Wageningen University & Research text/html https://research.wur.nl/en/datasets/metabarcoding-of-edna-from-tidal-pools-on-artificial-and-natural- https://edepot.wur.nl/714061 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/cdfa9cdf-b87e-403b-95a7-d4a2031fecfb 2026-04-14 dataset edurep openaire public

Juanpere-Borras, Maria Zhao, Tiantong Boekhorst, Jos Fernandez-Ciruelos, Blanca Sanyal, Rajrita Arifa, Nissa Wagenaar, Troy van Baarlen, Peter Wells, Jerry M. Dataset Raw and Processed Data for Nanopore-Based Tn-seq Analysis 2025 This dataset contains raw and processed sequencing data used in the analysis of transposon insertion sites using Oxford Nanopore Technologies. The data support the results presented in Genome-Wide Identification of Conditionally Essential Genes Supporting Streptococcus suis Growth in Serum and Cerebrospinal Fluid. Wageningen University & Research text/html https://research.wur.nl/en/datasets/raw-and-processed-data-for-nanopore-based-tn-seq-analysis https://edepot.wur.nl/714060 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/15eb0b88-f2cd-496d-8425-9185fc90bf91 2026-04-20 dataset edurep openaire public

Vliex, Lars M.M. Barnett, David Monzel, Elena Nauta, Arjen Oudhuis, Guy J. Fassarella, Marina Holst, Jens J. Zoetendal, Erwin G. Penders, John Blaak, Ellen E. Dataset Intervention human study with antibiotics and 2-FL 2025 Study the effects of the antibiotic vancomycin on the gut microbiota of overweight participants and the result of giving them prebiotics Wageningen University & Research text/html https://research.wur.nl/en/datasets/intervention-human-study-with-antibiotics-and-2-fl https://edepot.wur.nl/714057 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/33df0805-ee61-4d50-af51-3fa0df2d71e0 2026-04-20 dataset edurep openaire public

van Bree, Joyce W.M. Visser, Imke Marshall, Eleanor M. Willemsen, Wessel W. van de Waterbeemd, Carmen Kenbeek, Dennis Abma-Henkens, Marleen H.C. Pijlman, Gorben P. van Oers, Monique M. Rockx, Barry Fros, Jelke J. Dataset The effect of increased CpG and UpA dinucleotides in the West Nile virus genome on virus transmission by Culex mosquitoes and pathogenesis in a vertebrate host 2025 Vertebrate animals and many small DNA and single-stranded RNA viruses that infect vertebrates have evolved to suppress genomic CpG dinucleotides. All organisms and most viruses additionally suppress UpA dinucleotides in protein coding RNA. Synonymously recoding viral genomes to introduce CpG or UpA dinucleotides has emerged as an approach for viral attenuation and vaccine development. However, studies that investigate the effects of this recoding strategy on viral replication and pathogenesis in vivo are still limited. Flaviviruses including West Nile virus (WNV) are transmitted between vertebrate hosts by invertebrate vectors. In humans, WNV infection can cause flu-like symptoms and neuroinvasive disease. We investigated how alterations in WNV dinucleotide frequencies impact virus replication, transmission by vector mosquitoes, as well as pathogenesis and neuroinvasiveness in vertebrates. In Culex pipiens vector mosquitoes and Culex cell lines only WNV with elevated UpA frequencies displayed attenuated replication. In vertebrate cell lines and primary human neuro-astrocyte co-cultures both UpA and CpG enrichment reduced viral replication. In mice, the CpG-high WNV mutant demonstrated partial attenuation with delayed weight loss compared to wild-type WNV, though infection still resulted in 100% mortality. In contrast, 75% of animals survived inoculation with the UpA-high WNV mutant and were protected against wild-type WNV challenge. Notably, all animals that succumbed to infection had similar levels of virus in the brain, irrespective of the WNV mutant. Our results underscore the complex interplay between viral genome composition and host immune responses, highlighting potential safety concerns for dinucleotide manipulation as a strategy for live-attenuated vaccine development in flaviviruses. Wageningen University & Research text/html https://research.wur.nl/en/datasets/the-effect-of-increased-cpg-and-upa-dinucleotides-in-the-west-nil https://edepot.wur.nl/714056 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/fd7a4099-5c09-41ce-8f11-efaa5cf855d0 2026-04-14 dataset edurep openaire public

Bombelli, Alberto Crespo Tapia, Natalia Tempelaars, Marcel H. Boeren, Sjef den Besten, Heidy M.W. Abee, Tjakko Liu, Yue Dataset Evolution of Listeria monocytogenes to a strong biofilm producer via the overexpression of Lmo1799 2025 This study was conducted to evaluate the difference at the genomic level between the ancestral strain and the evolved variant isolates of L. monocytogenes and investigate the mechanism behind differences in phenotype. Wageningen University & Research text/html https://research.wur.nl/en/datasets/evolution-of-listeria-monocytogenes-to-a-strong-biofilm-producer- https://edepot.wur.nl/714055 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/d7500a11-8f45-41ba-8588-c49f950d2647 2026-04-20 dataset edurep openaire public

Jansen, L. Loos, E. Ariyati, R.W. Widowati, Lestari Lakhsmi Debrot, A.O. Nijland, R. Dataset Metabarcoding of fish eDNA in the Java Sea 2025 Mangrove ecosystems support a diverse array of animal species and also deliver pivotal ecosystem services to humans, such as coastal protection. However, these vital habitats are in global decline, leading to coastal degradation. To address this, a mangrove restoration project in Demak, Java, Indonesia, introduces the use of semi-permeable coastal protective barriers made of bamboo pilings to safeguard the shore zone and hinterland. Introduction of such hard substrate in the marine environment can attract a range of species and it is important to monitor changes in biodiversity from a restoration point of view. Here, we used environmental DNA metabarcoding to assess changes in fish biodiversity following the introduction of bamboo pilings. Our results show slight but significant changes in species richness and fish community composition upon the introduction of said substrate, although seasonal variation could be a confounding factor. More importantly, this study demonstrates a useful level of temporal resolution of eDNA metabarcoding and establishes a baseline for fish species richness in an understudied tropical mangrove coastal zone in Demak, Java, Indonesia. Our results are valuable for informing future restoration efforts and other (metabarcoding) biodiversity studies in the region. Wageningen University & Research text/html https://research.wur.nl/en/datasets/metabarcoding-of-fish-edna-in-the-java-sea https://edepot.wur.nl/714054 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/3ad2a114-2781-46de-973c-50357d4a44f9 2026-04-14 dataset edurep openaire public

Ntouranidi, Sofia Fryganas, Christos Fogliano, Vincenzo Smidt, Hauke Zoetendal, Erwin G. Capuano, Edoardo Dataset In vitro utilization of barley husk by human gut microbiota depends on husk composition and particle size 2025 In this study, we aimed to to understand how manipulating the composition and the physical structure of barley husk would affect its utilization by human gut microbiota. Wageningen University & Research text/html https://research.wur.nl/en/datasets/in-vitro-utilization-of-barley-husk-by-human-gut-microbiota-depen https://edepot.wur.nl/714053 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/1c0f1b4c-05bb-4f6e-8840-d0a6d673cd08 2026-04-14 dataset edurep openaire public

Van der Voort, Menno Castelijn, Greetje A.A. Stassen, Joost H.M. Dataset Whole genome sequencing of Salmonella enterica serovar Infantis isolates from retail poultry in The Netherlands 2025 Whole genome sequencing data of Salmonella enterica serovar Infantis isolates obtained from retail poultry samples collected by The Netherlands Food and Consumer Product Safety Authority (NVWA). Wageningen University & Research text/html https://research.wur.nl/en/datasets/whole-genome-sequencing-of-salmonella-enterica-serovar-infantis-i https://edepot.wur.nl/714052 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/f6f2937a-1786-4900-89f3-fd1eecd0081c 2026-04-20 dataset edurep openaire public

Puhlmann, Marie Luise Wegh, Carrie A.M. van der Zalm, Sofie C.C. Dam, Veerle Doolan, Andrea Meyer, Diederick Belzer, Clara Vaughan, Elaine E. Benninga, Marc A. Smidt, Hauke Dataset Inulin-induced changes in gut microbiota composition in Functional Constipation 2025 This study was a randomized, double-blind, placebo-controlled, cross-over trial, assessing the effect of four-week daily 12 g chicory inulin intake in 39 individuals, with functional constipation according to Rome III Criteria. Fecal samples were collected at four timepoints, which were during run-in, after the first study period, during the washout and after the second study period. Gut microbiota compositional changes were assessed through 16S rRNA sequencing, to be related to other outcomes, which were stool consistency, frequency and constipation-related quality of life (PAC-QOL) and symptoms (PAC-SYM). Wageningen University & Research text/html https://research.wur.nl/en/datasets/inulin-induced-changes-in-gut-microbiota-composition-in-functiona https://edepot.wur.nl/714038 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/42936ee4-8a4e-4c5b-a762-59e05db4ff8e 2026-04-20 dataset edurep openaire public

Barratt, Christopher D. Bwong, Beryl A. Lawson, Lucinda P. Lyakurwa, John V. Steinfartz, Sebastian Müller, Hendrik Jehle, Robert Loader, Simon P. Dataset Different strokes for different croaks: using an African reed frog species complex as a model to understand idiosyncratic population requirements for conservation management 2025 Biodiversity is under increasing pressure from environmental change, although the scope and severity of these impacts remain incompletely understood. For many species, a lack of information about population-specific responses to future environmental change hinders the development of effective conservation strategies. Here we use an East African reed frog species complex as a model to explore spatial variation in vulnerability to future environmental changes. Our sampling across two threatened biodiversity hotspots spans the entire geographic range of H. mitchelli and H. rubrovermiculatus in Kenya, Tanzania and Malawi. Using genome-wide (ddRAD-seq) we evaluate levels of neutral genetic diversity and local adaptations across sampling localities. We then integrate spatial approaches (genomic offset, modelled dispersal barriers and Species Distribution Models) to predict how populations may respond differently to future environmental changes, such as climate warming and predicted land use changes. Based on our analyses, we characterize population structure and identify region-specific management needs that reflect genetic variation among populations and the uneven impacts of predicted change across the landscape. Peripheral populations are most vulnerable to future environmental changes due to i) low levels of neutral genetic diversity (Malawi and Pare mountains in Tanzania), ii) putative signals of local adaptation to wetter conditions with predicted disruptions to genotype-environment associations (i.e. high genomic offset, Kenya and Northern Tanzania), and iii) the projected contraction of suitable habitat, which is a pervasive threat to the species complex in general. Populations in Northern, Central and Southern Tanzania show the lowest vulnerability to environmental change and may serve as important reservoirs of genetic diversity for potential future genetic rescue initiatives. Our study highlights how populations across different parts of species ranges may be unevenly affected by future global changes, and provides a framework to predict which conservation actions may help mitigate these effects. Wageningen University & Research text/html https://research.wur.nl/en/datasets/different-strokes-for-different-croaks-using-an-african-reed-frog https://edepot.wur.nl/714024 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/89911046-76b0-447c-a5f9-1e308efc66c1 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489891: Experimental Crystal Structure Determination 2025 URAWAP : bis(acetato)-[([1,1'-binaphthalene]-2,2'-diyl)-bis(diphenylphosphine)]-ruthenium(ii) tetrahydrofuran solvate Space Group: C 2/c (15), Cell: a 16.38440(10)Å b 18.67530(10)Å c 16.00030(10)Å, α 90° β 110.3060(10)° γ 90° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489891-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky29 https://edepot.wur.nl/713330 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/cdaabb93-5c1c-46c2-896f-a83659dbd5cd 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489892: Experimental Crystal Structure Determination 2025 URAWET : (([1,1'-binaphthalene]-2,2'-diyl)bis(diphenylphosphine))-bis(methanesulfonato)-ruthenium(ii) tetrahydrofuran solvate Space Group: P 1 (2), Cell: a 11.41430(10)Å b 14.00360(10)Å c 14.24130(10)Å, α 81.3960(10)° β 85.5940(10)° γ 82.0330(10)° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489892-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky3b https://edepot.wur.nl/713329 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/47146e07-19d3-45d3-8614-446a69a9b10a 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489893: Experimental Crystal Structure Determination 2025 URAWIX : (([1,1'-binaphthalene]-2,2'-diyl)bis(diphenylphosphine))-bis(4-methylbenzene-1-sulfonato)-ruthenium(ii) dichloromethane solvate Space Group: P 21/c (14), Cell: a 10.63100(10)Å b 38.3402(2)Å c 13.26890(10)Å, α 90° β 111.0320(10)° γ 90° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489893-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky4c https://edepot.wur.nl/713328 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/b20307cc-8073-4113-83f5-9fe9489c2215 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489894: Experimental Crystal Structure Determination 2025 URAWOD : ((rac)-([1,1'-binaphthalene]-2,2'-diyl)bis(diphenylphosphine))-bis(trifluoromethanesulfonato)-ruthenium(ii) dichloromethane solvate Space Group: P 1 (2), Cell: a 10.47950(10)Å b 10.54340(10)Å c 20.4022(2)Å, α 93.0600(10)° β 103.0990(10)° γ 101.1390(10)° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489894-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky5d https://edepot.wur.nl/713327 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/97e2b78b-9ad4-4597-8923-46647a86a746 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489895: Experimental Crystal Structure Determination 2025 URAWUJ : (([1,1'-binaphthalene]-2,2'-diyl)bis(diphenylphosphine))-(cycloocta-2,4-dien-1-yl)-ruthenium(ii) methanesulfonate dichloromethane solvate Space Group: P 21 (4), Cell: a 12.01327(4)Å b 20.95928(4)Å c 18.46209(4)Å, α 90° β 101.3516(3)° γ 90° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489895-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky6f https://edepot.wur.nl/713326 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/8e2ab0e5-e917-4597-bd16-fef47a637d9e 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489896: Experimental Crystal Structure Determination 2025 URAXAQ : (1-(1-(dicyclohexylphosphanyl)ethan-1-yl)-2-(diphenylphosphanyl)ferrocene)-bis(methanesulfonato)-ruthenium(ii) dichloromethane solvate Space Group: P 21 (4), Cell: a 10.20950(10)Å b 10.10690(10)Å c 20.07800(10)Å, α 90° β 96.9690(10)° γ 90° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489896-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky7g https://edepot.wur.nl/713325 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/f6db9b9f-87fa-46bf-a081-7f22f6e5d170 2026-04-20 dataset edurep openaire public

Zhou, Yifei Vink, Pim Kılınç, Ibrahim Sokolova, Olga O. Miloserdov, Fedor M. Dataset CCDC 2489897: Experimental Crystal Structure Determination 2025 URAXEU : ((1,2-phenylene)bis[t-butyl(methyl)phosphine])-bis(methanesulfonato)-aqua-ruthenium(ii) ((1,2-phenylene)bis[t-butyl(methyl)phosphine])-bis(methanesulfonato)-ruthenium(ii) Space Group: P 43 (78), Cell: a 16.10106(4)Å b 16.10106(4)Å c 19.32258(7)Å, α 90° β 90° γ 90° Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2489897-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pky8h https://edepot.wur.nl/713324 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/2a56ecdb-b71f-4843-9bf8-e633b2fe67ca 2026-04-20 dataset edurep openaire public

Zdouc, Mitja M. van Wezel, Gilles P. Dataset OSMAC Study on Streptomyces sp MBT27 2025 Re-acquisition of samples created in the scope of this study https://doi.org/10.1038/s41598-022-06736-0. Briefly, Streptomyces sp. MBT27 was cultivated on different carbon sources, leading to differential antibiotic activity against Staphylococcus aureus. This dataset was used for benchmarking of the FERMO metabolomics tool (https://github.com/fermo-metabolomics) and described in this preprint: https://doi.org/10.1101/2022.12.21.521422 . Derived files can be found here: https://github.com/fermo-metabolomics/fermo_ms/tree/main/case_study_2. Wageningen University & Research text/html https://research.wur.nl/en/datasets/osmac-study-on-streptomyces-sp-mbt27 10.25345/c5js9hm3j https://edepot.wur.nl/713266 Antibiotic Metabolomics OSMAC actinomycin D Wageningen University & Research

oai:library.wur.nl:wurpubs/6ae5b398-33c5-4119-ad4e-4e0f86caaef2 2026-04-20 dataset edurep openaire public

Fox-Rosales, Lester A. Monteza-Moreno, Claudio M. Jansen, Patrick A. McLean, Kevin Castillo-Caballero, Pedro L. Crofoot, Margaret C. Dataset Data and Code for: Does predation risk constrain behavior in prey species? A test with five species of Neotropical forest mammals 2025 Predation is a major force structuring ecological communities, and it is well known that predation risk can exert strong effects on behavior and ecology of prey species. One of the potential effects of predation risk is the constraint on the activity patterns and activity budgets of prey. Island populations that evolve under reduced predation risk provide valuable opportunities to assess the effects of such risk on prey behavior. We tested whether diel activity patterns and anti-predator behavior differed between mammal populations living on 2 land-bridge islands of the Coiban Archipelago off the Pacific coast of Panama—where predators are nearly absent—and the adjacent mainland where a diverse community of predators persists. Using ground-based and arboreal camera trapping, we compared temporal activity kernel density curves, foraging and ranging behavior, and visit duration between 2 island and 4 mainland populations of 5 tropical forest mammal species. We also tested whether temporal overlap between prey competitor species differed between island and mainland populations. Overall, we found that activity levels during risky times were higher on islands than on the mainland for two species of agouti and the White-faced Capuchin monkey. Island prey populations showed far less anti-predator behavior and more foraging behavior than their mainland counterparts. They did not, however, show higher levels of nocturnal activity during darker nights nor longer visits, both considered as indicative of predation release. We also found lower spatiotemporal overlap between the white-faced capuchins and the mantled howler monkeys on islands than their counterparts on the mainland. This result suggests that when predation pressure is relaxed, there is a decrease in direct competitive interactions between these species, which may also be associated with changes in the use of forest strata. These findings provide partial support for the hypothesis that predation risk constrains activity patterns and influences spatiotemporal niche differentiation among competing mammalian prey species. Max Planck Institute of Animal Behavior text/html https://research.wur.nl/en/datasets/data-and-code-for-does-predation-risk-constrain-behavior-in-prey- 10.17617/3.pv2zdz https://edepot.wur.nl/713260 Aloutta palliata Cebus capucinus imitator Dasyprocta coibae Dasyprocta punctata Didelphis marsupialis Odocoileus virginianus activity budget animal behavior camera traps moon phase Wageningen University & Research

oai:library.wur.nl:wurpubs/0381c238-2ee0-4e0c-a142-262a6c50109c 2026-04-20 dataset edurep openaire public

Philips, Robin C.M. Calabrese, Matteo van Leeuwen, Bas Keenan, Robert Dataset Regional Occupational Structure of Interwar England and Wales 2025 The dataset contains regional data on the occupational structure in England and Wales during the interwar years. Please cite as: Robin C. M. Philips, Matteo Calabrese, Robert Keenan & Bas van Leeuwen (2022). The regional occupational structure in interwar England and Wales, Historical Methods: A Journal of Quantitative and Interdisciplinary History. Utrecht University text/html https://research.wur.nl/en/datasets/regional-occupational-structure-of-interwar-england-and-wales 10.34894/btvgsq https://edepot.wur.nl/713052 England Wales census interwar occupational structure Wageningen University & Research

oai:library.wur.nl:wurpubs/bb1a6c8d-79de-4221-9fcc-877d99a6d743 2026-04-20 dataset edurep openaire public

Spiliotopoulou, Eirini Hofstra, Nienke de Leeuw, Sander Dataset Replication Data for: Ordering decisions under supply uncertainty and inventory record inaccuracy: An experimental investigation 2025 Data on how people make inventory ordering decisions when they face supply uncertainty and inventory record inaccuracy. Tilburg University text/html https://research.wur.nl/en/datasets/replication-data-for-ordering-decisions-under-supply-uncertainty- 10.34894/hhxmbm https://edepot.wur.nl/713048 Behavioral Operations Economics Experiments Inaccuracy Inventory Record Supply Uncertainty Wageningen University & Research

oai:library.wur.nl:wurpubs/cb211bdb-686f-4016-91ad-ee22ca7ee94a 2026-04-20 dataset edurep openaire public

Key, Emily Oudes, Dirk Sherren, Kate Dataset Using Q-method to understand how to incorporate large-scale solar in rural Nova Scotia, Canada 2025 Q-methodology surveys were completed in three Nova Scotia municipalities to understand the discourses around large-scale solar installation in everyday rural landscapes. We are unable due to ethics clearances to share the raw data, but provide the raw analytical output. Borealis: The Canadian Dataverse Repository text/html https://research.wur.nl/en/datasets/using-q-method-to-understand-how-to-incorporate-large-scale-solar 10.5683/sp3/gzxmoj https://edepot.wur.nl/712944 Q methodology community solar environmental social science large-scale solar rural landscapes social license solar farm Wageningen University & Research

oai:library.wur.nl:wurpubs/b2af4ef7-3de1-4713-a9e1-a0b79d71b36b 2026-03-25 dataset edurep openaire public

Calderon Novoa, Santiago van der Goot, Atze Jan Schutyser, Maarten Dataset ProPulse - Dataset supporting the publication: "How low can we go? Effect of moisture content on lactic acid fermentation of air-classified faba bean protein concentrate." 2025 This dataset contains all the raw data, data analysis scripts, and output figures supporting the publication in the journal Future Foods with DOI 10.1016/j.fufo.2025.100870. Please refer to README.md for a file description of this dataset. Wageningen University & Research text/html https://research.wur.nl/en/datasets/b2af4ef7-3de1-4713-a9e1-a0b79d71b36b 10.5281/zenodo.17600832 https://edepot.wur.nl/712940 Anti-nutritional factors Fermentation HPAEC-PAD HS-SPME GC-MS Lactic acid bacteria Off-flavours Plant protein Wageningen University & Research

oai:library.wur.nl:wurpubs/a69c701c-a8a9-4197-a2f3-6cda74efebdc 2026-04-20 dataset edurep openaire public

Riess, Christoph Boersma, Folkert van Vliet, Jasper Dataset Processed PARANOX ship NOx plume library 2025 This dataset contains simulated NO2 plume characteristics resulting from ship emissions under various atmospheric and emission conditions intended for the interpretation of ship NO2 plumes in the Mediterranean Sea observed with TROPOMI (or a comparable satellite instrument). The input variables include meteorological parameters, ship NOx emission rates, and chemical parameters, while the diagnostic variables describe the resulting NO2 plume properties such as 3h NO2 enhancement, total plume NO2 columns, maximum column density and the length of the detectable plume evaluated at 5km resolution. The simulations were performed using the plume model PARANOX. Details of the simulation and postprocessing can be found in Riess et al. (2024) [https://doi.org/10.1016/j.rse.2025.114734]. Wageningen University & Research text/html https://research.wur.nl/en/datasets/processed-paranox-ship-nox-plume-library 10.5281/zenodo.17939884 https://edepot.wur.nl/712938 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/7e664d2f-c0bc-444c-a159-aaa85b2c8f28 2026-04-20 dataset edurep openaire public

Ore, Alessia Palm, Emma H. van Wezel, Annemarie P. Sutton, Nora B. Dataset Predicted and detected transformation products of 20 organic micropollutants during batch biodegradation with soil 2025 This dataset contains transformation products (TPs) predicted using patRoon 2.3.3 from 20 organic micropollutants. Predictions were performed with BioTransformer 3.0 using the environmental microbial degradation module. This data is part of the article: Ore A., et al. (2025), "Higher microbial diversity enhances the extent and rate of organic micropollutant biodegradation under aerobic and nitrate-reducing conditions", Water Research (https://doi.org/10.1016/j.watres.2025.124921). Files included: Detected_TPs_MicrobialDiversity.csv - list of transformation products detected in the study. Includes identifiers and associated transformation reactions. SuspectListOfTPs.csv - list of transformation products predicted (up to the 7th generation) using BioTransformer3.0 with the environmental microbial degradation module in patRoon. SpikedPCs.csv - list of the 20 spiked organic micropollutants (parent compounds) with identifiers. Wageningen University & Research text/html https://research.wur.nl/en/datasets/predicted-and-detected-transformation-products-of-20-organic-micr 10.5281/zenodo.17910420 https://edepot.wur.nl/712929 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/6a2438cd-9dd7-4542-98dd-00ce17e91495 2026-04-20 dataset edurep openaire public

Paque, Rose Moore, Angus Dixon, Jean L. Christl, Marcus Montes, Yessenia Vanacker, Veerle Dataset Orographic and convective precipitation control meteoric 10Be wet depositional fluxes at low latitude 2025 There are three sheets in the provided Excel document: the first contains daily precipitation data, the second includes measured meteoric 10-beryllium concentrations in precipitation, and the third presents calculated and normalized annual fluxes along with the coordinates of the study sites. Wageningen University & Research text/html https://research.wur.nl/en/datasets/orographic-and-convective-precipitation-control-meteoric-10be-wet 10.5281/zenodo.14228933 https://edepot.wur.nl/712927 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/ecb9ff9f-f63d-45a6-9a66-e70acc2e2f68 2026-04-30 dataset edurep openaire public

Deshpande, Siddharth Nandy, Manali Ghosh, Udit Ganar, Ketan A. Ippel, Hans Dijkgraaf, Ingrid Dataset Dataset_pH-Tunable Material Properties of Glycine-rich Condensates from Tick Bioadhesive 2025 Liquid-liquid phase separation (LLPS) of biomolecules is crucial for maintaining the functional organization in biological systems. Intrinsically disordered proteins are particularly prone to LLPS and form condensates in response to various physicochemical triggers. This work studies the influence of pH on the LLPS behaviour and material properties of condensates. A glycine-rich protein present in the saliva and the resulting bioadhesive of tick ectoparasites was selected for the study, given its ability to undergo LLPS. After confirming its disordered nature through spectroscopy, the effect on LLPS dynamics over a wide pH range of the full protein and its two halves was investigated. By combining fluorescence microscopy, droplet evaporation, and tensionmetry assays, the findings reveal that pH-dependent changes in the protein hydrophobicity drive striking variations in the coacervation behavior including the propensity to phase separate and the underlying microstructure dynamics. Importantly, pH dictates the viscosity of condensates and can confer amphiphilic character to the peptides, making them interfacially active. Lastly, pH-dependent curcumin encapsulation by condensates is demonstrated, exhibiting their potential as drug-delivery agents. Given the ubiquitous presence of disordered proteins in biology, this study provides valuable insights about the broad implications of the pH-dependent manifestation of the material properties of protein condensates. Wageningen University & Research text/html https://research.wur.nl/en/datasets/datasetph-tunable-material-properties-of-glycine-rich-condensates 10.5281/zenodo.15726574 https://edepot.wur.nl/712926 Biomolecular condensates Coacervation dynamics Glycine-rich proteins Intrinsically disordered proteins Liquid-liquid phase separation NMR spectroscopy pH Wageningen University & Research

oai:library.wur.nl:wurpubs/f18517b9-0d65-45ec-9269-2d5c6d6b5c78 2026-04-20 dataset edurep openaire public

Haller, Ayke Risse, Judith Sepers, Bernice van Oers, Kees Dataset Independent avian epigenetic clocks for aging and development 2025 Information on individual age is a fundamental aspect in many ecological and evolutionary studies. However, accurate and non-lethal methods that can be applied to estimate the age of wild animals are often absent. Furthermore, since the process of aging is accompanied by a physical decline and the deterioration of biological functions, the biological age often deviates from the chronological age. Epigenetic marks are widely suggested to be associated with this age-related physical decline, and especially changes in DNA methylation are suggested to be reliable age-predictive biomarkers. Here, we developed separate epigenetic clocks for aging and development in a small passerine bird, the great tit (Parus major). The aging clock was constructed and evaluated using erythrocyte DNA methylation data of 122 post-fledging individuals, and the developmental clock using 67 pre-fledging individuals from a wild population. Using a leave-one-out cross validation approach, we were able to accurately predict the ages of individuals with median absolute deviations of 0.40 years for the aging and 1.06 days for the development clock. Moreover, using existing data from a brood-size manipulation we show that nestlings from reduced broods are estimated to be biologically older compared to control nestlings, while they are expected to have higher fitness. These epigenetic clocks provide further evidence that, as observed in mammals, changes in DNA methylation of certain CpG sites are highly correlated with chronological age in birds and this opens up new avenues for broad applications in behavioural and evolutionary ecology. Netherlands Institute of Ecology (NIOO-KNAW) text/html https://research.wur.nl/en/datasets/independent-avian-epigenetic-clocks-for-aging-and-development 10.5061/dryad.wstqjq2wq https://edepot.wur.nl/712765 Biological sciences DNA methylation Epigenetic clock Parus major ageing development Wageningen University & Research

oai:library.wur.nl:wurpubs/0f961c79-7950-4fec-94fd-162ccab9b5c2 2026-03-17 dataset edurep openaire public

Warmer, Femke E.M. van Vliet, Wessel A. van Hooft, Pim Hof, Anouschka R. Dataset Code from: The role of intrinsic factors in explaining range shifts of European breeding birds: A meta-analysis 2025 Species are shifting their distribution ranges in response to climate and land-use change. However, the observed range shift patterns are idiosyncratic in rate and direction. Species traits, such as ecological, life-history and movement traits, may play an important role in determining range shifts by influencing a species’ capacity to shift successfully. Whilst several studies investigate the role of different species traits in driving range shifts, they generally consider few traits and range shift types. Range shift types such as abundance shift and centroid shift are generally not taken into account. Drivers of range shifts may however differ per range shift type. We conducted a meta-analysis to uncover the role of intrinsic factors (9 species functional traits and 5 spatial abundance characteristics), in explaining six contemporary range shift types ( range size changes: expansion/contraction, relative change and rate of change; latitudinal shifts: abundance shift, centroid shift and range margin shift) in European breeding birds (n=270). We found that the role of intrinsic factors in explaining contemporary range shifts in European breeding birds is indeed range shift type dependent. Natal dispersal distance and clutch size were for instance positively related with range size changes, while diet breadth and conservation status showed both negative and positive relationships depending on the range shift type. Acknowledging limitations regarding unevenness of data availability across the study region; the region of study was an important predictor for range size changes, suggesting a relative importance of local context and extrinsic drivers. Future trait-based analyses of range shifts would benefit from accounting for intraspecific variation in functional traits across time and space, the inclusion of additional traits like phenological traits, exposure to environmental pressures, and competitive ability, and should be investigated across multiple scales and for multiple types of range shifts. Wageningen University & Research text/html https://research.wur.nl/en/datasets/code-from-the-role-of-intrinsic-factors-in-explaining-range-shift 10.5061/dryad.wstqjq2z5 https://edepot.wur.nl/712340 Biological sciences Birds Climate change Europe Wageningen University & Research

oai:library.wur.nl:wurpubs/bc5ab787-eb0a-4a53-b46f-7bf66ff40f16 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484323: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov.2025. Inorg.Chem. DOI:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484323-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4gq https://edepot.wur.nl/712031 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/0cb76921-358f-4c61-8fba-5d83bc2ffbdc 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484321: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov.2025. Inorg.Chem. DOI:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484321-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4dn https://edepot.wur.nl/712030 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/f510b497-ce80-4c0e-bf7f-a2aaba3c0ed6 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484330: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov.2025. Inorg.Chem. DOI:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484330-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4py https://edepot.wur.nl/712029 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/55ea25ff-9961-4f1d-9a50-528f968ca8e3 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484222: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484222-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd16c https://edepot.wur.nl/712027 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/298729b5-7df5-466b-8c22-bda803291c7d 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484332: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484332-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4r0 https://edepot.wur.nl/712026 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/de67cd01-4c7f-4047-86b9-7099513ef13b 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484223: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484223-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd17d https://edepot.wur.nl/712025 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/c96da1a5-ec14-48d5-a93d-f4a392f3b352 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484331: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484331-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4qz https://edepot.wur.nl/712024 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/c1b6c367-82cd-4362-ac2a-c4c2c05a33e6 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484322: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484322-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd4fp https://edepot.wur.nl/712023 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/9eb9a7ba-e8d4-4d76-a046-549d67b02cd9 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484224: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484224-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd18f https://edepot.wur.nl/712022 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/40b84639-0e95-4d66-89f2-b2a66b56b46d 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484225: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484225-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd19g https://edepot.wur.nl/712021 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/d82d4000-021d-4c11-bf3d-d4a6803c48df 2026-04-20 dataset edurep openaire public

Zhou, Yifei Cheasty, Kathleen C. de Graaf, Kelsey R. Miloserdov, Fedor M. Dataset CCDC 2484221: Experimental Crystal Structure Determination 2025 Related Article: Yifei Zhou, Kathleen C. Cheasty, Kelsey R. de Graaf, Fedor M. Miloserdov|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c04086 Wageningen University & Research text/html https://research.wur.nl/en/datasets/ccdc-2484221-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2pd15b https://edepot.wur.nl/712020 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/03671ebb-5dbc-46a7-a9c8-5521bd160b0b 2026-04-20 dataset edurep openaire public

Zhu, Yumei Krishna, Akash Chao, Yang Li, Xixi Pujari, Sidharam P. Li, Guanna Huang, Hong Zhao, Hongxia Dong, Jiajia Zuilhof, Han Dataset CCDC 2421104: Experimental Crystal Structure Determination 2025 Related Article: Yumei Zhu, Akash Krishna, Yang Chao, Xixi Li, Sidharam P. Pujari, Guanna Li, Hong Huang, Hongxia Zhao, Jiajia Dong, Han Zuilhof|2025|J.Org.Chem.|90|10218|doi:10.1021/acs.joc.5c00615 Tianjin University text/html https://research.wur.nl/en/datasets/ccdc-2421104-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2m8c4f https://edepot.wur.nl/712019 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/99992408-9aeb-403b-8746-bc5fea06bd37 2026-04-20 dataset edurep openaire public

Zhu, Yumei Krishna, Akash Chao, Yang Li, Xixi Pujari, Sidharam P. Li, Guanna Huang, Hong Zhao, Hongxia Dong, Jiajia Zuilhof, Han Dataset CCDC 2418873: Experimental Crystal Structure Determination 2025 Related Article: Yumei Zhu, Akash Krishna, Yang Chao, Xixi Li, Sidharam P. Pujari, Guanna Li, Hong Huang, Hongxia Zhao, Jiajia Dong, Han Zuilhof|2025|J.Org.Chem.|90|10218|doi:10.1021/acs.joc.5c00615 Tianjin University text/html https://research.wur.nl/en/datasets/ccdc-2418873-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2m6152 https://edepot.wur.nl/712018 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/b55752cd-d3ed-4e78-b732-ba3751dcdec5 2026-04-20 dataset edurep openaire public

Zhu, Yumei Krishna, Akash Chao, Yang Li, Xixi Pujari, Sidharam P. Li, Guanna Huang, Hong Zhao, Hongxia Dong, Jiajia Zuilhof, Han Dataset CCDC 2425236: Experimental Crystal Structure Determination 2025 Related Article: Yumei Zhu, Akash Krishna, Yang Chao, Xixi Li, Sidharam P. Pujari, Guanna Li, Hong Huang, Hongxia Zhao, Jiajia Dong, Han Zuilhof|2025|J.Org.Chem.|90|10218|doi:10.1021/acs.joc.5c00615 Tianjin University text/html https://research.wur.nl/en/datasets/ccdc-2425236-experimental-crystal-structure-determination 10.5517/ccdc.csd.cc2mdnf4 https://edepot.wur.nl/712017 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/92ec85e0-9ec0-4d87-a3a4-abc143b1f43a 2026-04-20 dataset edurep openaire public

Tavernier, C. Tavernier, Dimitri Marmara, A.I. van Dongen, Joep Creus Fabregat, Oscar Dataset Bat Event in Solar field and Control grasslands sampled in 2024 2025 he bat data were collected as part of the Ecocertified project, run at Wageningen University and Research. The general goal of the Ecocertified project was to understand and evaluate the impact of solar parks on biodiversity. This specific sampling effort was the result of 8 months of bat sampling in solar parks as well as in two grassland controls to understand the impact of solar parks on bat activity and occurrence. Wageningen University & Research text/html https://research.wur.nl/en/datasets/bat-event-in-solar-field-and-control-grasslands-sampled-in-2024 10.5281/zenodo.17313698 https://edepot.wur.nl/711179 Bat event EcoCertified Renewable Energy Solar parks Wageningen University & Research

oai:library.wur.nl:wurpubs/0a834928-c38c-48d9-b26b-0f0c4ef2c83b 2026-04-02 dataset edurep openaire public

Adema, H. Bolhuis, D.P. Dataset The impact of the Eco-Score and the co-presence of Nutri-Score on sustainable food identification by consumers 2025 Wageningen University & Research text/html https://research.wur.nl/en/datasets/the-impact-of-the-eco-score-and-the-co-presence-of-nutri-score-on 10.5281/zenodo.15609490 https://edepot.wur.nl/711142 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/b2e8764d-3bb2-4e21-80f9-693ecac09902 2026-04-20 dataset edurep openaire public

Jacobson, Andrew R. Schuldt, Kenneth N. Andrews, Arlyn E. Miller, John B. Oda, Tomohiro Basu, Sourish Mund, John Weir, Brad Ott, Lesley Wanninkhof, Rik Triñanes, Joaquin van der Laan-Luijkx, I.T. Dataset CarbonTracker CT2025 2025 CarbonTracker is a CO2 measurement and modeling system developed by NOAA to keep track of sources (emissions to the atmosphere) and sinks (removal from the atmosphere) of carbon dioxide around the world. CarbonTracker uses atmospheric CO2 observations from a host of collaborators and simulated atmospheric transport to estimate these surface fluxes of CO2. The current release of CarbonTracker, CT2025, provides global estimates of surface-atmosphere fluxes of CO2 from January 2000 through December 2024. University of Colorado text/html https://research.wur.nl/en/datasets/carbontracker-ct2025 10.15138/V4W1-2085 https://edepot.wur.nl/711141 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/0d151975-b0a5-4e25-a12a-076fd2a96c5b 2026-04-02 dataset edurep openaire public

Melsen, K.A.C. Dataset Improving Genomic Prediction using High-dimensional Secondary Phenotypes: the Genetic Latent Factor Approach, Code and Data 2025 Wageningen University & Research text/html https://research.wur.nl/en/datasets/improving-genomic-prediction-using-high-dimensional-secondary-phe 10.5281/zenodo.17091954 https://edepot.wur.nl/711112 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/0ff52d29-34a5-4f4d-bbb2-7a286b5697e3 2026-04-20 dataset edurep openaire public

Hewson, Ian Brandt, Marilyn Budd, Kayla Breitbart, Mya DeRito, Christopher Gittens, Samuel Henson, Michael Hylkema, Alwin Sevier, Moriah Souza, Matthew Vilanova-Cuevas, Brayan Von Hoene, Sarah Gittens, Samuel Souza, Matthew Vilanova-Cuevas, Brayan Budd, Kayla DeRito, Christopher Sevier, Moriah Von Hoene, Sarah Dataset Transcriptome and viral metagenome data from Diadema antillarum collected at St. Thomas (USVI) and Saba (Caribbean Netherlands) in Apr 2022 2025 A mass mortality of the tropical echinoderm Diadema antillarum (urn:lsid:marinespecies.org:taxname:124332) occurred beginning in January 2022 and continuing to at least July 2022. We sought to identify flaviviruses associated with this condition by performing viral metagenomics and tissue transcriptomics. We prepared these libraries from grossly normal, abnormal and reference specimens collected from St Thomas, U.S. Virgin Islands (USVI), and Saba, Caribbean Netherlands. This dataset includes the accession information for the sequences performed and archived at the National Center for Biotechnology Information (NCBI) Sequence Read Archive. While we were unsuccessful in recovering flaviviruses from tissues of these organisms, we were able to detect additional pathogenic agents (Philaster apodigitiformis; Ciliophora) from transcriptomes. Cornell University text/html https://research.wur.nl/en/datasets/transcriptome-and-viral-metagenome-data-from-diadema-antillarum-c 10.26008/1912/bco-dmo.985619.1 https://edepot.wur.nl/710522 Transcriptomics echinoderm metagenomics Wageningen University & Research

oai:library.wur.nl:wurpubs/5faeecc5-d1fa-44cc-a58a-4022df1066ea 2026-04-02 dataset edurep openaire public

Ruiperez Gonzalez, M. Woude, T.I.S. van Genuchten, P.P.L. Genova, G. Colman, B.H. Dataset Effective soil NPK supply, Rwanda 2025 Soil nitrogen (N), phosphorus (P) and potassium (K) supply effectively available for uptake (kg/ha), calculated as a fraction of the measured and mapped contents of N, P and K, using the formulas proposed by Sattari (Sattari et al. 2014, DOI:10.1016/j.fcr.2013.12.005) and pedotransfer functions (PTFs) from the QUEFTS model (Janssen et al., 1990, https://doi.org/10.1016/0016-7061(90)90021-Z). The NPK input data is derived from Africa SoilGrids [Soil property maps of Africa at 250 m resolution] (https://doi.org/10.1007/s10705-017-9870-x) aggregated for the topsoil at 0-30 cm. This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. Grant number: 4000004100 Wageningen University & Research text/html https://research.wur.nl/en/datasets/effective-soil-npk-supply-rwanda 10.5281/zenodo.17067876 https://edepot.wur.nl/710520 Africa SoilGrids Agriculture Crops Land Nitrogen Phosphorus Potassium QUEFTS Rwanda Soil soil nutrient supply Wageningen University & Research

oai:library.wur.nl:wurpubs/392de52c-832f-4d70-ae04-58251ce76f0b 2026-04-02 dataset edurep openaire public

Ruiperez Gonzalez, M. Woude, T.I.S. van Genuchten, P.P.L. Genova, G. Colman, B.H. Dataset Effective soil NPK supply, Kenya 2025 Soil nitrogen (N), phosphorus (P) and potassium (K) supply effectively available for uptake (kg/ha), calculated as a fraction of the measured and mapped contents of N, P and K, using the formulas proposed by Sattari (Sattari et al. 2014, DOI:10.1016/j.fcr.2013.12.005) and pedotransfer functions (PTFs) from the QUEFTS model (Janssen et al., 1990, https://doi.org/10.1016/0016-7061(90)90021-Z). The NPK input data is derived from Africa SoilGrids [Soil property maps of Africa at 250 m resolution] (https://doi.org/10.1007/s10705-017-9870-x) aggregated for the topsoil at 0-30 cm. This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR Grant number: 4000004100. Wageningen University & Research text/html https://research.wur.nl/en/datasets/effective-soil-npk-supply-kenya 10.5281/zenodo.17067854 https://edepot.wur.nl/710516 Africa SoilGrids Agriculture Crop production Kenya Land Nitrogen Phosphorus Potassium QUEFTS Soil soil nutrient supply Wageningen University & Research

oai:library.wur.nl:wurpubs/b592c622-ee17-474d-beaa-bf927db7eecc 2026-04-02 dataset edurep openaire public

Ruiperez Gonzalez, M. Woude, T.I.S. van Genuchten, P.P.L. Genova, G. Colman, B.H. Dataset Effective soil NPK supply, Ethiopia 2025 Soil nitrogen (N), phosphorus (P) and potassium (K) supply effectively available for uptake (kg/ha), calculated as a fraction of the measured and mapped contents of N, P and K, using the formulas proposed by Sattari (Sattari et al. 2014, DOI:10.1016/j.fcr.2013.12.005) and pedotransfer functions (PTFs) from the QUEFTS model (Janssen et al., 1990, https://doi.org/10.1016/0016-7061(90)90021-Z). The NPK input data is derived from Africa SoilGrids [Soil property maps of Africa at 250 m resolution] (https://doi.org/10.1007/s10705-017-9870-x) aggregated for the topsoil at 0-30 cm. This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR Grant number: 4000004100. ISRIC text/html https://research.wur.nl/en/datasets/effective-soil-npk-supply-ethiopia 10.5281/zenodo.17067708 https://edepot.wur.nl/710515 Africa SoilGrids Agriculture Crop production Ethiopia Land Nitrogen Phosphorus Potassium QUEFTS Soil soil nutrient supply Wageningen University & Research

oai:library.wur.nl:wurpubs/325e55d9-938f-4483-8705-f50a96ce0470 2026-04-20 dataset edurep openaire public

Beukhof, Esther Uhlmann, Sebastian van der Reijden, Karin J. Anastasopoulou, Aikaterini Altuna-Etxabe, Miren Astarloa, Amaia Basurko, Oihane C. Binch, Logan Bluemel, Joanna K. Carbonara, Pierluigi Dinesen, Grete E. Eigaard, Ole R. Festjens, Felien Girardin, Raphael Halouani, Ghassen Kempf, Alexander MacMillan, Isla Papadopoulou, Nadia Potier, Mikaela Romagnoni, Giovanni Seghers, Stephie Smith, Christopher J. Spedicato, Maria Teresa Thorpe, Robert B. Tsagarakis, Konstantinos Van Hoey, Gert Piet, Gerjan Reid, Dave Rindorf, Anna Brown, Elliot John Dataset Dataset to 'From bycatch to litter: a systematic map of the ecological impacts of fishing in European seas' 2025 Data extracted from a systematic review on the ecological impacts of fisheries in European seas.The methodology of how the systematic map database was produced and two case studies demonstrating the use of the database are published in:https://doi.org/10.1007/s11160-025-10013-413-4 Technical University of Denmark text/html https://research.wur.nl/en/datasets/dataset-to-from-bycatch-to-litter-a-systematic-map-of-the-ecologi 10.11583/dtu.28443983 https://edepot.wur.nl/710511 Bottom trawling Bycatch Ecosystem-based management Fishing Food webs Human impacts Knowledge synthesis Litter Systematic review Wageningen University & Research

oai:library.wur.nl:wurpubs/2f3e977c-c664-4008-9c5b-bff0a7af1272 2026-04-20 dataset edurep openaire public

Boogaard, Hendrik Pratihast, Arun Laso Bayasv, Juan Carlos Karanam, Santosh Fritz, Steffen Van Tricht, Kristof Degerickx, Jeroen Van Haren, Charlotte Dataset WorldCereal harmonized reference datasets - extended and updated 2025 Within the ESA WorldCereal project we have built a global, community-based and open repository of harmonized reference data on land cover, crop type and irrigation information. These datasets are typically used to construct and validate global cropland and crop type maps. We define reference data as all data which can either be used for calibrating classification algorithms or validating the resulting products. As such, reference data should contain location- and time-specific information about land cover and/or crop type. Reference data can include: In-situ field data gathered through dedicated field surveys Farmers declarations through parcel registration systems Data derived from visual or automated interpretation of very high-resolution satellite imagery or in-situ photographs (e.g. streetview or mapillary) Existing high-quality classified maps based on analysis of satellite imagery Reference data is typically available in different formats depending on the source of the dataset. To ensure multiple reference datasets can be readily combined and can serve as input for a dedicated calibration/validation task, all datasets have been structured, harmonized, annotated and evaluated. The datasets adhere to the same (meta)data standards and formats. See for more information the PDF document 'WorldCereal_Reference_dataset_naming_convention_v2'. Each individual dataset has its own data license defined by the original data holder, which can be retrieved from the accompanying Excel metadata file. The license will be one of the different licenses listed in this publication. The user must check the data license of each of these datasets before starting to use or redistribute the data. Individual datasets have been grouped per year and continent into a separate .zip archive. The title of individual datasets matches the Collection ID as specified in the WorldCereal Reference Data Module, our dedicated user interface for serving reference data to the community. A complete overview on WorldCereal reference data documentation can be found here. Information on WorldCereal reference data harmonization procedures, data standards and legend can be found here: and in the accompanying PDF document 'WorldCereal_Reference_dataset_naming_convention_v2' hosted in this repository. Wageningen University & Research text/html https://research.wur.nl/en/datasets/worldcereal-harmonized-reference-datasets-extended-and-updated 10.5281/zenodo.17288872 https://edepot.wur.nl/710501 crop mapping crop type in-situ data land cover Wageningen University & Research

oai:library.wur.nl:wurpubs/38795a8c-13e6-47b7-a47e-b70d7087d3e2 2026-04-20 dataset edurep openaire public

Hermann, Markus Amekor, Mawuli Kodjo Contrucci, Enzo Evarita, Ann Marielle Peeters, Edwin T.H.M. Van den Brink, Paul J. Dataset Data supporting: Multiple stressor effects of a neonicotinoid, heatwaves, and elevated temperatures on aquatic insect emergence 2025 Data used to obtain the results of the research paper entitled: "Multiple stressor effects of a neonicotinoid, heatwaves, and elevated temperatures on aquatic insect emergence" published in Environmental Science & Technology. The data derives from an outdoor (meso-) cosm experiment in the Netherlands (Sinderhoeve experimental field station, Wageningen University) in which the transportable temperature and heatwave control device (TENTACLE) was used to investigate the multiple stressors effects of two different climate change scenarios related to temperature (i.e., elevated temperature and reoccurring heatwaves) in combination with the neonicotinoid insecticide imidacloprid on aquatic insect emergence. The upload contains the following parts: README-file which explains the statistical analysis and the content of the Dataset Dataset of the field mesocosm study Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-supporting-multiple-stressor-effects-of-a-neonicotinoid-heat 10.5281/zenodo.15119467 https://edepot.wur.nl/710494 Climate change Climatic changes Community Ecology Ecology Ecosystem Ecotoxicology Environmental sciences FOS: Biological sciences Freshwater Freshwater biology Freshwater conservation Freshwater degradation Freshwater ecosystem Freshwater ecosystems Freshwater organism Freshwater pollution Global warming Insect Insecta Mesocosm Neonicotinoids Neonicotinoids/adverse effects Wageningen University & Research

oai:library.wur.nl:wurpubs/82ee3366-98bf-4bd4-80cc-16176fb1996d 2026-04-20 dataset edurep openaire public

Bishop, Gabriella Kleijn, David Albrecht, Matthias Bartomeus, Ignasi Isaacs, Rufus Kremen, Claire Magrach, Ainhoa Ponisio, Lauren Potts, Simon Scheper, Jeroen Smith, Henrik Tscharntke, Teja Albrecht, Jörg Åström, Jens Badenhausser, Isabelle Báldi, András Basu, Parthiba Berggren, Åsa Beyer, Nicole Blüthgen, Nico Bommarco, Riccardo Brosi, Berry Cohen, Hamutahl Cole, Lorna Denning, Kathy Devoto, Mariano Ekroos, Johan Fornoff, Felix Foster, Bryan Gillespie, Mark Gonzalez-Andujar, Jose González-Varo, Juan P. Goulson, Dave Grass, Ingo Hass, Annika Herrera, José Holzschuh, Andrea Hopfenmüller, Sebastian Izquierdo, Jordi Jauker, Birgit Kallioniemi, Eveliina Kirsch, Felix Klein, Alexandra-Maria Kóvacs-Hostyánszki, Anikó Krauss, Jochen Krimmer, Elena Kunin, William Laha, Supratim Lindström, Sandra Mandelik, Yael Marcacci, Gabriel McCracken, David Monasterolo, Marcos Morandin, Lora Morrison, Jane Mudri Stojnic, Sonja Ollerton, Jeff Persson, Anna Phillips, Benjamin Piko, Julia Power, Eileen Quinlan, Gabriela Rundlöf, Maj Raderschall, Chloé Riggi, Laura Roberts, Stuart Roth, Tohar Senapathi, Deepa Stanley, Dara Steffan-Dewenter, Ingolf Stout, Jane Sutter, Louis Tanis, Marco Tarrant, Sam van Kolfschoten, Lisette Vanbergen, Adam Vilà, Montserrat von Königslöw, Vivien Vujic, Ante WallisDeVries, Michiel Wen, Ai Westphal, Catrin Wickens, Jennifer Wickens, Victoria Wilkinson, Nicholas Wood, Thomas Fijen, Thijs Dataset Data for: Critical habitat thresholds for effective pollinator conservation in agricultural landscapes 2025 Biodiversity in human-dominated landscapes is declining, but evidence-based conservation targets to guide international policies for such landscapes are lacking. We present a framework for informing habitat conservation policies based on the enhancement of habitat quantity and quality and define thresholds of habitat quantity at which it becomes effective to also prioritize habitat quality. We applied this framework to pollinators, an important part of agroecosystem biodiversity, by synthesizing 59 studies from 19 countries. Given low habitat quality, hoverflies had the lowest threshold at 6% semi-natural habitat cover, followed by solitary bees (16%), bumble bees (18%), and butterflies (37%). These figures represent minimum habitat thresholds in agricultural landscapes, but when habitat quantity is restricted, marked increases in quality are required to reach similar outcomes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-for-critical-habitat-thresholds-for-effective-pollinator-con 10.5061/dryad.nk98sf82b https://edepot.wur.nl/710486 Biodiversity Biological sciences Conservation biology Ecology Wageningen University & Research

oai:library.wur.nl:wurpubs/cdd904a9-41f0-4d32-8781-600c3f73e6ee 2026-04-20 dataset edurep openaire public

Zuidema, Pieter Groenendijk, Peter Rahman, Mizanur Trouet, Valerie Hubau, Wannes Finnegan, Patrick Fayolle, Adeline Koprowski, Marcin Eshetu, Zewdu Acuna-Soto, Rodolfo Villanueva Diaz, Jose Nabais, Cristina D'Arrigo, Rosanne Locosselli, Giuliano Touchan, Ramzi Helle, Gerhard Pumijumnong, Nathsuda Doucet, Jean-Louis Schoengart, Jochen Quadri, Paulo Sheppard, Paul Enquist, Brian Robertson, Iain Lopez, Lidio Villalba, Ricardo Fan, Ze Xin Sanchez-Salguero, Raul Kaib, J.M. Maxwell, Justin Zhang, Yong Jiang Camarero, Jesus Julio Barbosa, Ana Speer, James Braeuning, Achim Beeckman, Hans Wehenkel, Christian Battipaglia, Giovanna Gloor, Emanuel Zavaleta, Erika Ferrero, M.E. Silva, Lucas Manzanedo, Ruben Zhou, Zhe Kun Abiyu, Abrham Carpillo-Parra, Artemio Cortes-Cortes, Otoniel del Valle, Jorge Ignacio Esemann-Quadrops, Karin Galvao, Franklin Haneca, Kristof Fenilli, Tatiele Anete Bergamo Giraldo, Jorge A. Costa, Clayane Matos Fichtler, Esther Dobner, Mário Jr. Assis-Pereira, Gabriel Botosso, Paulo Cesar Cornejo-Oviedo, Eladio Heriberto Brookhouse, Matthew Dunisch, Oliver Godoy-Veiga, Milena Francisco, Kainana Esquivel-Arriaga, Gerardo Harley, Grant Cerano-Parades, Julián Cervantes-Martinez, Rosalinda Anholetto, Claudio de Ridder, Maaike Buckley, Brendan Alfaro-Sanchez, Raquel Fontana, Claudia Loader, Neil Ceccantini, Gregório Aragao, José Roberto Vieira Centeno-Erguera, Librado R. Bourland, Nils Gebrekirstos, Aster Guerra, Anthony Astudillo-Sanchez, Claudia C. Chen, Ya Jun Couralet, Camille Granata-Souza, Daniela Crispin De La Cruz, Doris Bianca Cintra, Bruno Barcante Ladvocat Fu, Pei Li Buajan, Supaporn Adenesky-Filho, Eduardo Chanthorn, Wirong David, Diego A. Brienen, Roel Islam, Mahmuda Jiang, Yu Mei Layme, Eva Lopez-Hernandez, María I. Nathalang, Anuttara Reyes-Flores, Judith Roig, Fidel Alejandro Tomazello-Filho, Mario Velazquez-Perez, Adín H. Van den Bulcke, Jan Moors, Eddy Moreno-Valoyes, Miyer Ngoma, Justine Lousada, José Luís Penetra Cerveira Roquette, José Guilherme Menezes, Ítallo Romany Pagotto, Mariana Lisi, Claudio Nogueira de Carvalho, Francisco Jr. Therrell, Matthew Vourlitis, George Parades-Villanueva, Kathelyn Portal-Cahuana, Leif Pucha-Cofrep, Darwin Heinrich, Ingo Tor-Ngern, Pantana Hornink, Bruna Lobo, Francisco de Almeida Ponce-Calderon, Laura Ortega-Rodriguez, Daigard Ricardo Sousa, Luciana K.V.S. Longhi-Santos, Tomaz Oliveira, Juliano Ramirez, Jorge Andrés Ortiz, Carmen Eugenia Rodríguez Montoia, Valdinez Ribeiro Wils, Tommy Ticse-Otarola, Ginette Inga Guillen, Janet Rubio-Camacho, Ernesto Alonso Olmedo, Gabriela Khamisi, Zakia Hassan Vazquez-Selem, Lorenzo Mokria, Mulugeta Marcon, Amanda Soria-Diaz, Leroy Muniz-Castro, Miguel Angel Sass-Klaassen, Ute Ligot, Gauthier Perez-de-Lis, Gonzalo Vlam, Mart Venegas-Gonzalez, Alejandro Mendoza-Villa, Omar N. Ribeiro, Adauto Slotta, Franziska Torbenson, Max Requena-Rojas, Edilson Scipioni, Marcelo Leffler, A.J. Panthi, Shankar Babst, Flurin Dataset Pantropical tree rings show small effects of drought on stem growth 2025 Increasing drought pressure under anthropogenic climate change may jeopardize the potential of tropical forests to capture carbon in woody biomass and act as a long- term carbon dioxide sink. To evaluate this risk, we assessed drought impacts in 483 tree- ring chronologies from across the tropics and found an overall modest stem growth decline (2.5% with a 95% confi dence interval of 2.2 to 2.7%) during the 10% driest years since 1930. Stem growth declines exceeded 10% in 25% of cases and were larger at hotter and drier sites and for gymnosperms compared with angiosperms. Growth declines generally did not outlast drought years and were partially mitigated by growth stimulation in wet years. Thus, pantropical forest carbon sequestration through stem growth has hitherto shown drought resilience that may, however, diminish under future climate change. Wageningen University & Research text/html https://research.wur.nl/en/datasets/pantropical-tree-rings-show-small-effects-of-drought-on-stem-grow 10.5061/dryad.hx3ffbgq4 https://edepot.wur.nl/710481 Dendrochronology Drought FOS: Earth and related environmental sciences Trees Tropical forests Wageningen University & Research

oai:library.wur.nl:wurpubs/5080cd04-653a-40d9-a306-acd9d435378a 2026-04-20 dataset edurep openaire public

Barratt, Chris Bwong, Beryl A. Lawson, Lucinda P. Lyakurwa, John V. Steinfartz, Sebastian Mueller, Hendrik Jehle, Robert Loader, Simon P. Dataset Data from: Different strokes for different croaks: Using an African reed frog species complex as a model to understand idiosyncratic population requirements for conservation management 2025 Biodiversity is under increasing pressure from environmental change, although the scope and severity of these impacts remain incompletely understood. For many species, a lack of information about population‐specific responses to future environmental change hinders the development of effective conservation strategies. Here, we use an East African reed frog species complex as a model to explore spatial variation in vulnerability to future environmental changes. Our sampling across two threatened biodiversity hotspots spans the entire geographic range of H. mitchelli and H. rubrovermiculatus in Kenya, Tanzania, and Malawi. Using genome‐wide (ddRAD‐seq) data, we evaluate levels of neutral genetic diversity and local adaptations across sampling localities. We then integrate spatial approaches (genomic offset, modeled dispersal barriers, and Species Distribution Models) to predict how populations may respond differently to future environmental changes, such as climate warming and predicted land use changes. Based on our analyses, we characterize population structure and identify region‐specific management needs that reflect genetic variation among populations and the uneven impacts of predicted change across the landscape. Peripheral populations are most vulnerable to future environmental changes due to (i) low levels of neutral genetic diversity (Malawi and Pare mountains in Tanzania), (ii) putative signals of local adaptation to wetter conditions with predicted disruptions to genotype–environment associations (i.e., high genomic offset, Kenya and Northern Tanzania), and (iii) the projected contraction of suitable habitat, which is a pervasive threat to the species complex in general. Populations in Northern, Central, and Southern Tanzania show the lowest vulnerability to environmental change and may serve as important reservoirs of genetic diversity for potential future genetic rescue initiatives. Our study highlights how populations across different parts of species ranges may be unevenly affected by future global changes and provides a framework to predict which conservation actions may help mitigate these effects. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-from-different-strokes-for-different-croaks-using-an-african 10.5061/dryad.h1893200t https://edepot.wur.nl/710479 Biodiversity hotspot Biological sciences Climate change Eastern Afromontane Global Change Predictive Models adaptation coastal forests of Eastern Africa Wageningen University & Research

oai:library.wur.nl:wurpubs/a8132abd-0de8-49fa-86a0-f1d0805b6166 2026-04-29 dataset edurep openaire public

Bergh, Stijn van den Chardon, Iris Meima-Franke, Marion Pérez, Germán Rocha, Gabriel Brenzinger, Kristof Korthals, Gerard Mayer, Jochen Cougnon, Mathias Reheul, Dirk Boer, Wietse de Bodelier, Paul Dataset Improved methane mitigation potential and modulated methane cycling microbial communities in arable soil by compost addition 2025 The global atmospheric concentration of the potent greenhouse gas methane (CH4) is rising rapidly, and agriculture is responsible for 30-50% of the yearly CH4 emissions. To limit its global warming effects, strong and sustained reductions are needed. Sustainable agricultural management strategies, as the use of organic amendments like compost, have previously proven to have a potent CH4 mitigation effect in laboratory experiments. Here we investigated, using an extensive field study, the effect of organic amendments on the CH4 mitigation potential of agricultural soils and the CH4 cycling microbial communities. Organic-amended soils had higher potential CH4 uptake rates and an improved potential to oxidize CH4 to sub-atmospheric concentrations. Also, we showed for the first time that the methanotrophic and methanogenic microbial communities of arable soils were unequivocally altered after organic amendment application by increasing in size while getting less diverse. Compost-amended soils became dominated by the compost-originating methanotroph Methylocaldum szegediense and methanogen Methanosarcina horonobensis, replacing the indigenous methane cycling community members. However, multivariate analyses did not point out type Ib methanotrophs like M. szegediense as significant driving factors for the observed improved soil CH4 uptake potential. Conventional type IIa methanotrophs like Methylocystis sp. also had higher differential abundances in organic-amended soils and are speculated to be contributing to the improved CH4 uptake potential. Altogether, the results showed that compost serves as a vector for the introduction of CH4 cycling microbes and improves the soil’s CH4 uptake potential, which emphasizes the potential of organic fertilization with compost to contribute to CH4 mitigation in agricultural soils. # Improved methane mitigation potential and modulated methane cycling microbial communities in arable soil by compost addition Dataset DOI: [10.5061/dryad.dz08kps8h](10.5061/dryad.dz08kps8h) ## Description of the data and file structure To assess the effect of organic fertilization on the methane uptake potential and methane cycling microbial communities of agricultural soils, an extensive field screening was performed. To this end, soil samples (0-15cm depth) were collected at 6 sites in the Netherlands, Belgium and Switzerland. The following physicochemical properties were determined: Moisture content, organic matter content, pH, NO3+NO2-N-, NH4-N, Al-, Co-, Cu-, Fe-, K-, Mg-, Mn-, Mo-, Na-, Ni-, P-, S-, and Zn-content. Also, the potential methane uptake rates and lag phases were determined in incubations with 10 or 10.000 ppmv CH4 in the headspace, and the capacity to oxidize to sub-atmospheric CH4 concentrations. Furthermore, the gene copy numbers of the bacterial 16S rRNA, *pmoA* (total, type Ib, and type II), and *mcrA* were determined. Also, amplicon sequencing was performed, targetting *pmoA*, using a nested multiplex-reverse approach, of which the ASV matrix is also provided. ### Files and variables #### File: Amplicon_sequencing_pmoA_and_environmental_data_0-15cm_(incl_metadata).xlsx Description: All environmental data and *pmoA* amplicon sequencing results for agricultural soils (0-15 cm depth). #### File: Amplicon_sequencing_pmoA_and_environmental_data_0-7_5cm_(incl_metadata).xlsx Description: All environmental data and *pmoA* amplicon sequencing results for upper-top layer of agricultural soils (0-7.5 cm depth). #### File: Amplicon_sequencing_pmoA_and_environmental_data_7_5-15cm_(incl_metadata).xlsx Description: All environmental data and *pmoA* amplicon sequencing results for subtop layer of agricultural soils (7.5-15 cm depth). #### File: Amplicon_sequencing_mcrA_(incl_metadata).xlsx Description: All *mcrA* amplicon sequencing results for agricultural soils (0-15 cm depth), upper-top layer of agricultural soils (0-7.5 cm depth), and subtop layer of agricultural soils (7.5-15 cm depth). #### File: Amplicon_sequencing_16S_(incl_metadata).xlsx Description: All 16S amplicon sequencing results for agricultural soils (0-15 cm depth), upper-top layer of agricultural soils (0-7.5 cm depth), and subtop layer of agricultural soils (7.5-15 cm depth). ##### Variables General overview of metadata. See for data-specific metadata the accompanying sheet "Metadata" in each data file. | Sheet | Column | Name | Unit | Description | | :----------------- | :----- | :------------- | :--------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | ASV matrix | A | ASV | n.a. | ASV id. Corresponding with "Taxonomy table" column A. | | ASV matrix | B-BK | plot81-plot510 | n.a. | ASV matrix, how many amplicons per ASV id (column A) are found in the corresponding sample (column B-BK). MiSeq sequencing performed on samples plot81-plot334, NextSeq sequencing performed on samples plot401-plot510. | | Taxonomy table | A | ASV | n.a. | ASV id. Corresponding with "ASV matrix" column A. | | Taxonomy table | B | Kingdom | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | C | Phylum | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | D | Class | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | E | Order | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | F | Family | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | G | Genus | n.a. | Corresponding taxonomic identity of said ASV. | | Taxonomy table | H | Species | n.a. | Corresponding taxonomic identity of said ASV. | | Environmental data | A | Sample | n.a. | Sample id. Corresponding with "ASV matrix" columns B-BK. | | Environmental data | B | Location | n.a. | Location of visited field site. | | Environmental data | C | Practice | n.a. | No-tillage (notil) or tillage (til) practice. | | Environmental data | D | Treatment | n.a. | Organic-amended (oa) or unamended (control). | | Environmental data | E | Oa | n.a. | Organic amendment used (compost/cover crops) or unamended. | | Environmental data | F | Moistgrav | % | Gravimetric moisture content. | | Environmental data | G | Moistwhc | % | Moisture content as % of water holding capacity. | | Environmental data | H | OM | % | Organic matter content. | | Environmental data | I | pH | n.a. | pH. | | Environmental data | J | Chemnox | mg/kg | (NO3- + NO2)-N content. | | Environmental data | K | Chemnh4 | mg/kg | NH4+ content. | | Environmental data | L | Chemal | mg/kg | Al content. | | Environmental data | M | Chemco | µg/kg | Co content. | | Environmental data | N | Chemcu | µg/kg | Cu content. | | Environmental data | O | Chemfe | µg/kg | Fe content. | | Environmental data | P | Chemk | mg/kg | K content. | | Environmental data | Q | Chemmg | mg/kg | Mg content. | | Environmental data | R | Chemmn | mg/kg | Mn content. | | Environmental data | S | Chemmo | µg/kg | Mo content. | | Environmental data | T | Chemna | mg/kg | Na content. | | Environmental data | U | Chemni | mg/kg | Ni content. | | Environmental data | V | Chemp | mg/kg | P content. | | Environmental data | W | Chems | mg/kg | S content. | | Environmental data | X | Chemzn | mg/kg | Zn content. | | Environmental data | Y | ratelow | pmol/d/g dw soil | Potential CH4 uptake rate of soil sample in incubation with \~10 ppmv CH4. | | Environmental data | Z | laglow | d | Lag phase of soil sample before active CH4 oxidation activity in incubation with \~10 ppmv CH4. | | Environmental data | AA | ratehigh | nmol/h/g dw soil | Potential CH4 uptake rate of soil sample in incubation with \~10.000 ppmv CH4. | | Environmental data | AB | laghigh | d | Lag phase of soil sample before active CH4 oxidation activity in incubation with \~10.000 ppmv CH4. | | Environmental data | AC | belowatmlow | n.a. | Did sample oxidize to <1.89 ppmv (=sub-atmospheric) during incubation with \~10 ppmv CH4. | | Environmental data | AD | below10high | n.a. | Did sample oxidize to <10 ppmv during incubation with \~10.000 ppmv CH4. | | Environmental data | AE | belowatmhigh | n.a. | Did sample oxidize to <1.89 ppmv (=sub-atmospheric) during incubation with \~10.000 ppmv CH4. | | Environmental data | AF | 16S | copies/g dw soil | total 16S copy number in sample as determined with qPCR. | | Environmental data | AG | pmoAtot | copies/g dw soil | total pmoA copy number in sample as determined with qPCR. | | Environmental data | AH | pmoA1b | copies/g dw soil | pmoA type 1b copy number in sample as determined with qPCR. | | Environmental data | AI | pmoA2 | copies/g dw soil | pmoA type 2 copy number in sample as determined with qPCR. | | Environmental data | AJ | mcrA | copies/g dw soil | total mcrA copy number in sample as determined with qPCR. | Missing values are left as blank cells. ## Access information Other publicly accessible locations of the data: * Sequencing data can be found at the European Nucleotide Archive (ENA) under the accession number PRJEB75729 ([http://www.ebi.ac.uk/ena/data/view/PRJEB75729](http://www.ebi.ac.uk/ena/data/view/PRJEB75729)). Data was derived from the following sources: * Agricultural soils, locations: WUR Open Teelten location Vredepeel, WUR Open Teelten location Valthermond, WUR Open Teelten location Lelystad, Proefhoeve Melle - UGent, Unifarm (Wageningen University), and Agroscope Reckenholz Zürich. Netherlands Institute of Ecology (NIOO-KNAW) text/html https://research.wur.nl/en/datasets/improved-methane-mitigation-potential-and-modulated-methane-cycli 10.5061/dryad.dz08kps8h https://edepot.wur.nl/710478 Agricultural sciences Methane Methanotrophic bacteria agricultural soil compost Wageningen University & Research

oai:library.wur.nl:wurpubs/79d3e199-054f-4283-acf5-f011dbda1226 2026-04-20 dataset edurep openaire public

Roch, Cassandra Klein, Shannon G. Angulo-Preckler, Carlos Hutahaean, Andreas A. Wambugu, Joshua Yranzo-Duque, Anaurora Alamoudi, Taiba Naseem, Aya Gonzalez-Diaz, Patricia Jiddawi, Narriman Pluma, Naira Algethami, Bashaer Duarte, Carlos M. Dataset Towards inclusive global collaborations in coral reef science 2025 Protecting and restoring coral reefs demands concerted global efforts that transcend national boundaries. However, equitable participation in coral reef science remains challenging, particularly for researchers from lower-income nations. Through quantitative scientometric analyses and qualitative surveys, we examined global collaboration dynamics in coral reef research. Our findings reveal that high-income countries dominate the research landscape, often sidelining contributions from lower-income regions. While international collaborations were valued for benefits like access to funding, opportunities for professional development, enhanced publication success and improved conservation outcomes, most partnerships were short-term, with limited opportunities for evolving roles. Researchers from developing nations face significant barriers, including undervaluation of contributions, differing expectations around authorship, and ethical concerns like parachute science and tokenism, raising concerns about inclusivity and respect for local expertise. To improve collaborative practices and increase participation in coral reef science we propose actionable recommendations directed towards publishers, funders and the greater coral reef research community. We recommend fostering mutual respect, building long-term relationships, and promoting fair funding and publishing practices. These steps are essential for equitable research collaborations that support coral reefs and the communities that depend on them. Survey design and implementation We conducted an international survey aimed at evaluating collaboration and authorship practices within the coral reef science/conservation community. This study was conducted in accordance with ethical guidelines and received approval from the Institutional Biosafety and Ethics Committee (IBEC) at King Abdullah University of Science and Technology (KAUST) under protocol 23IBEC062 and 24IBEC024. All participants were informed about the purpose of the research, and their participation was voluntary. Informed consent was obtained from all participants, and they were assured of the confidentiality and anonymity of their responses. Participants were given the right to withdraw from the study at any time without any consequences. The survey, comprising 58 questions, was open to anyone working with coral reefs and we received responses from people working in academia, NGOs, government, industry, and tourism. The survey addressed a variety of ethical consideration, encompassing critical elements such as authorship naming, the prevalence of "parachute science" and “tokenism” practices, and ethical misconduct. Explanations for concept such as parachute science and tokenism were provided in the survey. Parachute was described as the practice whereby international scientists from higher-income countries, conduct field studies in a lower income nation, without engaging or acknowledging any local researchers, and tokenisms was described as the practice of making only a perfunctory or symbolic effort to be inclusive to members of minority groups, especially by recruiting people from underrepresented groups in order to give the appearance of racial (or gender) equality within a workplace or educational context. The survey was designed to explore variables such as gender, career rank, nationality/geographic factors, and more, aiming to uncover their influence on collaborative dynamics and ethical practices. To ensure the survey’s relevance across diverse cultural and economic contexts, a dedicated webinar was organized in partnership with collaborators (authors), to draft relevant questions attuned to a variety of socio-economic situations. This collective effort significantly shaped the survey's inclusivity and cultural sensitivity. Additionally, the survey was translated into eight different languages, to enhance its accessibility to a broader audience. Translations were done using AI tools (ChatGPT and Google translate) and were later reviewed and corrected by native speakers to ensure comprehensibility. Prospective survey participants were identified using the WOS database that was used for the bibliometric analysis, from which email addresses of corresponding authors could be extracted. The sample was randomly selected but we tried to specifically select for a broad geographical representation. Using the Web of Science (WoS) as a database inherently introduces biases, as it tends to favor researchers working in the natural sciences and those with higher publication outputs. To mitigate this bias, enhance outreach, and encourage participation from a diverse range of backgrounds, the survey was also promoted on various social media platforms, including Twitter, LinkedIn, and Instagram. Moreover, it was directly shared within the professional networks of all co-authors and we encouraged people to share the survey in their institutions and networks. We also asked international coral reef organisations to share the survey on their platforms. The survey was launched in November 2023 and responses were collected over four months (until March 1st 2024). Overall, we received 138 responses, but our analysis was constrained to 105 respondents who provided complete and comprehensive responses on the selected analytical variables. # Towards inclusive global collaborations in coral reef science [https://doi.org/10.5061/dryad.d2547d89w](https://doi.org/10.5061/dryad.d2547d89w) ## **Overview** This dataset contains responses from an international survey on collaboration and authorship practices within the coral reef science and conservation community (published article: [https://doi.org/10.1038/s44183-025-00120-x](https://doi.org/10.1038/s44183-025-00120-x)). The study explores how researchers across academia, NGOs, government, industry, and tourism collaborate, the challenges they face, and ethical concerns related to authorship, inclusion, and research integrity. A key focus of the survey was to assess ethical challenges in international collaborations, including parachute science (where foreign researchers conduct studies in lower-income nations without engaging local scientists) and tokenism (where underrepresented groups are included for optics rather than meaningful participation). The dataset also captures experiences with data sharing, funding accessibility, research leadership opportunities, and authorship disputes, providing a broad perspective on power dynamics and barriers in international research. To make the survey widely accessible, it was translated into eight languages and promoted across professional networks and social media. The responses have been fully anonymized to ensure participant confidentiality. The study received ethical approval from KAUST’s Institutional Biosafety and Ethics Committee (IBEC) under Protocols 23IBEC062 and 24IBEC024. ## Description of the data and file structure #### File: Responses_anonymised.xlsx **Description:** This file contains the anonymized responses from survey participants. Personally identifiable information (PII) has been removed or de-identified to protect participant confidentiality. **Note:** *DNR* (Did Not Respond) indicates that respondents did not provide an answer to the question. **Data structure:** * Columns: Represent survey questions and metadata fields. * Rows: Each row represents an anonymized participant’s response. * Data Types: * Categorical responses (e.g., multiple-choice answers). * Free-text responses (open-ended questions) anonymised. * Numeric responses (e.g., number of collaborations). #### File: Survey on International Collaborations in Coral Reef Science.pdf **Description**: This document contains the full survey questionnaire, including all questions that participants responded to. It provides context on the structure and purpose of the survey. #### King Abdullah University of Science and Technology text/html https://research.wur.nl/en/datasets/towards-inclusive-global-collaborations-in-coral-reef-science 10.5061/dryad.d2547d89w https://edepot.wur.nl/710476 Biological sciences Coral reefs Survey research collaborative research international collaboration marine science equity Wageningen University & Research

oai:library.wur.nl:wurpubs/0b1e469d-75f0-4220-8b8c-2ab0ef3e7457 2026-04-20 dataset edurep openaire public

van Loon, S.G.T. Heitkönig, I.M.A. Goedmakers, Annemarie Mundry, Roger Naguib, M. Dataset Stone-assisted drumming in Western chimpanzees and its implications for communication and cultural transmission 2025 Chimpanzees (Pan troglodytes) communicate in complex ways, including sounds produced by hand and foot drumming on trees, often combined with loud vocalisations. Recently, a puzzling stone throwing behaviour at trees was observed, resulting in stone piles at tree buttresses. It is a rare case of tool use for communication in animals and suggested to function like buttress drumming in long-distance communication and male displays. We tested this hypothesis by determining the behavioural dynamics in comparison to hand and foot tree buttress drumming in Western chimpanzees in Boé, Guinea Bissau. Using camera traps, we show that in 78% of cases, stones were picked up at trees, not leading to further stone accumulation beyond the already existing stone piles. Stone assisted and hand and foot drumming occurred separately or were combined in similar behavioural contexts in apparent long-distance communication and highly aroused behavioural contexts. Yet, immediately before stone drumming, chimpanzees swayed less and pant hooted more while afterwards pant hooting less compared to the other contexts, suggesting a separate motivation and/or function for stone assisted drumming. It suggests this unique stone-based activity having its own signal value, separate from hand/foot buttress drumming and, considering the spatial variation, might be culturally transmitted. Wageningen University & Research text/html https://research.wur.nl/en/datasets/stone-assisted-drumming-in-western-chimpanzees-and-its-implicatio 10.5061/dryad.9cnp5hqtp https://edepot.wur.nl/710474 Animal culture Biological sciences Chimanzee accumulative stone throwing communication drumming tool-use Wageningen University & Research

oai:library.wur.nl:wurpubs/621682bc-f859-4e99-a382-19a9cc3f73eb 2026-04-20 dataset edurep openaire public

Ernst, Tiffany Hogers, Regina M.H.W. Kwant, Peter J.C. Korosi, Aniko van Leeuwen, Johan L. Kotrschal, Alexander Pollux, Bart J.A. Dataset Data: Long-term sperm storage in a superfetatious live-bearing fish (Poeciliopsis gracilis, Poeciliidae) 2025 We tracked the offspring per brood and time between broods for 55 female porthole livebearers (Poeciliopsis gracilis) over a 9 month period to determine sperm retention time in females isolated from males. From our 55 fish, 27 were left isolated from males while the other 28 were paired with a male for breeding after 2.5 months of sexual isolation. This data set contains the raw data for the offspring per brood and time between broods. The included .html file contains the metadata for all the data files. This dataset is linked to the paper of the same name published in Ecology & Evolution (https://doi.org/10.1002/ece3.72086). All associated code, analyses, and additional supplemental appendices can be found at 10.6084/m9.figshare.24032109. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-long-term-sperm-storage-in-a-superfetatious-live-bearing-fis 10.6084/m9.figshare.24032028 https://edepot.wur.nl/710451 Poeciliidae Poeciliopsis gracilis brood sizes fecundity sperm reserves Wageningen University & Research

oai:library.wur.nl:wurpubs/2939c100-730a-4397-93be-34d49fcf03c4 2026-04-20 dataset edurep openaire public

Teitelbaum, Claire S. Prosser, Diann J. Ackerman, Joshua T. Ahmed, Sakib Alam, A.B.M. Sarowar Azmiri, Kazi Zenifar Batbayar, Nyambaya Bêty, Joël Blake-Bradshaw, Abigail Boiko, Dmitrijs Buitendijk, Nelleke H. Buler, Jeffrey J. Cabot, David Casazza, Michael Cohen, Bradley Davaasuren, Batmunkh Farau, Sébastien Feddersen, Jamie Fieberg, John Fiedler, Wolfgang Glazov, Peter Griffin, Larry Guillemain, M. Hagy, Heath Hardy, Matthew J. Highway, Cory Hoffman, David Kang, Tehan Keever, Allison Kilburn, Jennifer Kölzsch, Andrea Kruckenberg, Helmut Laaksonen, Toni Ladman, Brian S. Lee, Hansoo Lee, Siwan Lefebvre, Josée Legagneux, Pierre Linssen, Hans Madsen, Jesper Masto, Nicholas M. McWilliams, Scott Mezebish Quinn, Tori Mitchell, Carl Moreau, Axelle Müskens, Gerhard Newman, Scott H. Nolet, Bart A. Nuijten, R.J.M. Osenkowski, Jay Overton, Cory Piironen, Antti Plaquin, Betty Ramey, Andrew M. Rodrigue, Jean Rodrigues, David Schreven, Kees H.T. Si, Y. Sullivan, Jeffery D. Takekawa, John Y. Thomas, Philippe J. van Toor, Mariëlle Waldenström, Jonas Williams, Christopher K. Wolfson, David W. Xu, Fei Brosnan, Ian G. De La Cruz, Susan E.W. Dataset Code and data for analyzing relationships among environmental conditions, waterfowl movement, and influenza spread 2025 This data and code accompanies the manuscript "Waterfowl move less in heterogeneous and human-populated landscapes, with implications for spread of avian influenza viruses" by C.S. Teitelbaum et al. Please see the included Readme for descriptions of all data and files. United States Geological Survey (USGS) text/html https://research.wur.nl/en/datasets/code-and-data-for-analyzing-relationships-among-environmental-con 10.5281/zenodo.14781373 https://edepot.wur.nl/710235 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/fa3346dd-447a-4955-b291-b8f9df1a664b 2026-04-20 dataset edurep openaire public

Joonbakhsh, Alireza Farshidi, Siamak Dataset ModelSelect Data and Results 2025 Artificial intelligence (AI) and machine learning (ML) have revolutionized various domains, enabling faster, more accurate task execution in areas like healthcare, agriculture, and supply chain management. Despite the rapid growth of AI, selecting suitable models poses a challenge, especially for Research Software Engineers (RSEs) who often lack deep expertise in the field. This study addresses this challenge by proposing a structured decision model to guide RSEs in choosing AI models tailored to their needs. The proposed framework integrates multi-criteria decision-making (MCDM) principles and combines objective performance metrics with subjective user sentiment analysis. By collecting data from public sources like documentation, repositories, and community feedback, the model facilitates trade-off analysis, optimizing for constraints such as computational efficiency and long-term maintainability. Using Design Science Research (DSR) methodology, the model was developed and validated through real-world case studies, demonstrating its effectiveness in enhancing decision-making accuracy. Wageningen University & Research text/html https://research.wur.nl/en/datasets/modelselect-data-and-results 10.17632/j5hjz7srr8 https://edepot.wur.nl/710081 Artificial Intelligence Machine Learning Software Engineering Wageningen University & Research

oai:library.wur.nl:wurpubs/f06a4c8e-86b9-485c-ad4d-be5264abc48b 2026-04-02 dataset edurep openaire public

Farshidi, Siamak Dataset Supporting Evidence-Based Software Package Selection in Python: Data, Scripts, and Evaluation 2025 This dataset accompanies the study on data-driven software package selection in the Python ecosystem and supports the design, development, and evaluation of the PySelect system. It includes all relevant materials generated and used throughout the research process. The repository provides the full results of our large-scale analysis of nearly 800K Python scripts, including frequency distributions, package availability metrics, and domain keyword summaries. It also contains the complete set of data collection and analysis scripts used to extract, normalize, and structure the raw repository data. These scripts were used to process metadata, parse import statements, and generate the knowledge base used in the PySelect system. In addition to the empirical data, we include the outputs from the experimental evaluation of the pipelines, which assess the correctness and performance of the extraction procedures. The repository also contains the indexed knowledge base files generated from normalized usage and domain features, which form the foundation of the recommendation functionality. To support transparency in the conceptual foundations of the system, we provide the literature study compiled during the research, which outlines key themes and related work in software reuse, package recommendation, and empirical software engineering. Finally, all materials from the user study are included, such as survey instruments, anonymized participant responses, and analysis results based on the Technology Acceptance Model (TAM). This archive is intended to support replication, critical review, and further research on empirical approaches to developer tooling and software dependency management. All content is provided for reuse under the accompanying license. Wageningen University & Research text/html https://research.wur.nl/en/datasets/supporting-evidence-based-software-package-selection-in-python-da 10.17632/n99pxfpf4x https://edepot.wur.nl/709989 Artificial Intelligence Generative Artificial Intelligence Repository Studies Software Development Software Engineering Wageningen University & Research

oai:library.wur.nl:wurpubs/3784f1f9-bd00-43a3-9ceb-1cf95af81e2d 2026-04-02 dataset edurep openaire public

Farshidi, Siamak Dataset AI4RSE 2025 This dataset supports the study titled “Advancing Research Software Engineering with AI: A Research Framework”, which explores the emerging domain of Artificial Intelligence for Research Software Engineering (AI4RSE). It contains all materials used in the large-scale empirical analysis of over 1,500 open-source research software repositories. The repository includes: 1) Repository Metadata and Scores: A curated list of 1,512 research software repositories hosted on Zenodo, along with associated metadata extracted from GitHub. Each entry includes annotations for AI usage, engineering maturity, and compliance with the FAIR Principles for Research Software (FAIR4RS). 2) IEEE Taxonomy Mapping: A filtered subset of IEEE Taxonomy 2025 terms used to categorize the repositories and structure the domain-specific analysis. 3) Related Literature: A collection of key papers and survey articles that informed the theoretical framing of AI4RSE, quadrant modeling, and reproducibility metrics. 4) Analysis Scripts: Python and Jupyter-based scripts used to collect, process, score, and classify the repository data. These include tools for static and semantic code inspection, GenAI usage detection, FAIR4RS checks, and quadrant classification. All materials are made available to promote transparency, reproducibility, and further research at the intersection of AI, software engineering, and open science. Wageningen University & Research text/html https://research.wur.nl/en/datasets/ai4rse 10.17632/t2dygzcsyt https://edepot.wur.nl/709982 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/8143ffa5-5100-4a91-bc1c-34f9242022e4 2026-04-20 dataset edurep openaire public

Shao, Ran Xi, Cankun Zhou, Dong Guan, Junyong Huang, Yingran Qi, Yinglin Liu, Xing van Oers, Monique Fros, Jelke Yin, Xin Dataset ZAP Inhibits Double-Stranded RNA Virus Infection by Degrading Negative-Strand RNA and Blocking Elongation Phase of Viral Protein Synthesis 2025 Zinc-finger antiviral protein (ZAP) is a crucial host restriction factor that recognizes CpG dinucleotides in single-strand RNAs, yet its role in double-stranded RNA (dsRNA) virus replication remains uncharacterized. Here we demonstrate that ZAP broadly inhibits dsRNA viruses, including bluetongue virus (BTV) serotypes and epizootic hemorrhagic disease virus (EHDV), but not rotavirus (RV). Using BTV as a model, we reveal that ZAP inhibits replication via two mechanisms: 1) ZAP interacts with eukaryotic translation elongation factor 1A to block elongation during viral protein synthesis and 2) it binds preferentially to negative-sense RNA strands to stimulate their degradation. Additionally, BTV-NS1, encoded by segment 5, antagonizes ZAP by impairing its RNA-binding ability. Notably, synonymously CpG enrichment in BTV segment 5 significantly attenuated viral replication both in vitro and in vivo. Together, these findings uncover a dynamic interplay between ZAP and dsRNA viruses and suggest CpG-elevated BTV as a potential live attenuated vaccine candidate. Wageningen University & Research text/html https://research.wur.nl/en/datasets/zap-inhibits-double-stranded-rna-virus-infection-by-degrading-neg 10.17632/x448sh5bh2 https://edepot.wur.nl/709976 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/14f0f9e2-0e5c-4077-bd5a-17055a7cbd84 2026-04-02 dataset edurep openaire public

Jansman, Alfons Kar, Soumya Dataset GD 15_16_18 AVANT WP4 2025 Wageningen University & Research text/html https://research.wur.nl/en/datasets/gd-151618-avant-wp4 10.5281/zenodo.15783109 https://edepot.wur.nl/709970 Animal Feed Animal nutrition Chemokines Cytokines Fatty Acids, Volatile Immunity Insect Metabolomics Zinc Oxide alfa alfa black soldier fly (BSF) microbiome pig shot chain fatty acids Wageningen University & Research

oai:library.wur.nl:wurpubs/40a2195b-a150-4c06-9dcb-4eb462b45b8e 2026-04-02 dataset edurep openaire public

Jansman, Alfons Kar, Soumya Dataset GD 17 AVANT WP4 2025 Impact of feeding strategies on metabolomics profile in weaned piglet. Metabolome analysis was performed by two complementary untargeted metabolomics approaches: GCMS of derivatized polar compounds and LCMS of semi-polar compounds. Data contains measured level at day 6 and day 13 along with metadata. Wageningen University & Research text/html https://research.wur.nl/en/datasets/gd-17-avant-wp4 10.5281/zenodo.15783193 https://edepot.wur.nl/709967 Animal nutrition Metabolomics Pig gut health Wageningen University & Research

oai:library.wur.nl:wurpubs/720ba04f-e9ed-4b8c-9108-308d125c6511 2026-04-20 dataset edurep openaire public

Kar, Soumya Middelkoop, Anouschka Dataset GD 22 AVANT WP4 2025 Impact of feeding strategies on metabolomics profile in weaned piglet. Metabolome analysis was performed by two complementary untargeted metabolomics approaches: GCMS of derivatized polar compounds and LCMS of semi-polar compounds. Data contains measured level at day 22 with metadata. Wageningen University & Research text/html https://research.wur.nl/en/datasets/gd-22-avant-wp4 10.5281/zenodo.15783712 https://edepot.wur.nl/709966 Animal nutrition Dietary Fiber metabolomics pigs Wageningen University & Research

oai:library.wur.nl:wurpubs/0371b271-65d6-4335-ac62-ba1cbb1936c0 2026-04-02 dataset edurep openaire public

Vittek, Marian Krijgsveld, Karen Dataset Solar parks in the Netherlands 2025 The Solar Parks of the Netherlands is a geospatial vector dataset that provides information on the location and extent of all existing land-based solar parks in the Netherlands. The dataset is further enriched with information on underlying landscape factors, including soil type, distance to built-up areas, and the openness of the surrounding land. The dataset was first created in 2020 and has been updated annually at the end of June. It exclusively includes solar parks constructed on land, excluding those installed on rooftops or water bodies. Additionally, it only covers areas primarily dedicated to solar energy production (i.e., the paneled area), excluding associated buildings and boundary lands. For each solar park, the dataset provides the following attributes: Location – specified in latitude and longitude coordinates. Area (hectares) – total surface area covered by the solar park (ha). Soil type – dominant soil type within the solar park. Municipality – name of the municipality where the solar park is situated. Landscape openness – a measure of the visible surface area (ha). Distance to built-up areas – measured in kilometers. The dataset was generated using an automated detection approach based on Sentinel-2 satellite imagery. A machine-learning model employing the random forest algorithm was trained and validated using auxiliary land use datasets, including LGN, BRT TOP10NL, and OpenStreetMap. The detected solar park areas were initially represented as a raster layer and subsequently converted into a vector format. The precision of boundary delineation varies across the dataset. Approximately half of the solar parks, particularly those constructed in earlier years, have a higher level of precision as a result of additional manual boundary refinement. The additional attributes for each solar park were derived either directly from its geometry or through spatial overlays with ancillary datasets. The production of this dataset is part of the EcoCertified Solar Parks project. Wageningen University & Research text/html https://research.wur.nl/en/datasets/solar-parks-in-the-netherlands 10.5281/zenodo.17349175 https://edepot.wur.nl/709962 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/5afeab7c-f30c-4322-8cd0-386103f0d590 2026-04-02 dataset edurep openaire public

Dietrich, J.A. Dataset Blank Tomato Sample spiked with Pesticide Mixture at different spike levels without inclusion list 2025 This dataset was used as a case study nontarget screening with spectral alerts. Spectral alerts were mined with MS2LDA 2.0. It includes six samples: blank tomato sample, a tomato sample spiked at 200 ppb and 10 ppb, a blank orange sample, an orange sample spiked at 200 ppb and 10 ppb. The spiking was conducted with a pesticide mixture containing 211 compounds. No inclusion list was used for DDA acquisition in positive mode. Wageningen University & Research text/html https://research.wur.nl/en/datasets/blank-tomato-sample-spiked-with-pesticide-mixture-at-different-sp 10.25345/C5G737H3G https://edepot.wur.nl/709914 DDA Food Safety HRMS NTS Pesticides Xenobiotics Wageningen University & Research

oai:library.wur.nl:wurpubs/c69736a0-be79-4781-829f-3b3a1917c78f 2026-04-02 dataset edurep openaire public

Chisanga, Brian Dataset Fall Armyworm infestation, maize production and nutrition security: evidence from Uganda 2025 The dataset is for then study entiled "Fall Armyworm infestation, maize production and nutrition security: evidence from Uganda". It contains a dataset and codes. Wageningen University & Research text/html https://research.wur.nl/en/datasets/fall-armyworm-infestation-maize-production-and-nutrition-security 10.5281/zenodo.17229628 https://edepot.wur.nl/709912 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/ae180738-870d-4124-ab87-febdbabbc914 2026-04-02 dataset edurep openaire public

Matsuo, T. Dataset Replication Data for: Trait-based community assembly in early tropical forest succession 2025 Data belonging to the manuscript "Trait-based community assembly in early tropical forest succession" authored by Tomonari Matsuo, Masha T. van der Sande, Lucy Amissah, Jonathan Dabo, Salim Mohammed Abdul, and Lourens Poorter. Published in the Journal of Vegetation Science in 2025. Wageningen University & Research text/html https://research.wur.nl/en/datasets/replication-data-for-trait-based-community-assembly-in-early-trop 10.17026/LS/UUPATA https://edepot.wur.nl/709910 Earth and Environmental Sciences Wageningen University & Research

oai:library.wur.nl:wurpubs/a8f487d0-05fd-46f9-83b6-980653e4a00a 2026-04-20 dataset edurep openaire public

Segura, Hans Pedruzo-Bagazgoitia, Xabier Weiss, Philipp Müller, Sebastian K. Rackow, Thomas Lee, Junhong Dolores Tesillos, Edgar Benedict, Imme Dataset nextGEMS overview paper: scripts 2025 These are the scripts and data for creating figures in the nextGEMS overview paper Max-Planck Institute text/html https://research.wur.nl/en/datasets/nextgems-overview-paper-scripts 10.17617/3.qzhxmc https://edepot.wur.nl/709906 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/73e6edd9-4904-4858-817f-d28c14196f9a 2026-04-20 dataset edurep openaire public

Abou-Samra, Murielle Venema, Koen Blaak, Ellen Ayoub Moubareck, Carole Karavetian, Mirey Dataset Gut Microbiota and Peptides: Key Players in Obesity 2025 Obesity is a growing global epidemic associated with various metabolic disorders, including insulin resistance and cardiovascular diseases. The gut microbiota has emerged as a key player in obesity, influencing metabolic homeostasis through its interaction with gut peptides that regulate appetite and energy balance. This cross-sectional study investigated the relationship between gut microbiota composition and fasting gut peptides in people with obesity (POB) and normal weight (NW) Lebanese individuals. The study recruited 53 participants (30 POB, 23 NW) and assessed anthropometric, biochemical, and gut microbiota profiles. Results indicated significant differences in gut microbiota composition between the groups, with Lachnoclostridium being abundant in individuals with obesity and Peptococcus, Ruminococcus, and others more prevalent in NW individuals. Gut peptides such as ghrelin, GLP-1, and PYY showed significant associations with specific bacterial genera, suggesting a potential role of gut microbiota in metabolic regulation. Notably, GLP-1 levels were higher in POB and negatively associated with Butyricimonas and Ruminococcaceae species, while PYY levels were also higher in POB and negatively correlated with Alistipes and Parasutterella. These findings highlight the intricate interplay between gut microbiota and metabolic hormones, providing insights into potential microbiota-based strategies for obesity management. Further research is needed to understand casual links, the underlying mechanisms and their implications for therapeutic interventions. Maastricht University text/html https://research.wur.nl/en/datasets/gut-microbiota-and-peptides-key-players-in-obesity 10.17632/nkbgydybr4 https://edepot.wur.nl/709767 Glucagon-Like Peptide-1 Gut Microbiota Obesity Peptide YY Wageningen University & Research

oai:library.wur.nl:wurpubs/4b70f3b7-20b0-4d14-866d-9245f31cb705 2026-04-02 dataset edurep openaire public

Petie, R. Dataset Data used for identifying avian influenza hotspots in wild birds in the Netherlands 2025 This repository contains the minimal data set required to replicate the findings presented in the manuscript titled: "Identifying avian influenza hotspots in wild birds in the Netherlands" in PLOS ONE. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-used-for-identifying-avian-influenza-hotspots-in-wild-birds- 10.17026/LS/EEXJ0X https://edepot.wur.nl/709766 Health and Life Sciences Medicine Wageningen University & Research

oai:library.wur.nl:wurpubs/4cba1a39-d20f-4a31-bed9-8e934c45443a 2026-04-02 dataset edurep openaire public

Valk, Sophie Megens, Hendrik-Jan Kamermans, Pauline Tonk, Linda Dataset SNP Genotyping data from European flat oysters (Ostrea edulis) distributed in the Netherlands 2025 This data repository contains 5 Variant Call Format (.vcf) files that contain variants genotyped using a combined-species medium-density Affymetrux Axion array covering 14.950 SNPs for Ostrea edulis. The 5 .vcf files represent different combinations of 9 sampling sites and a total of 390 individuals. Files and variables: SNPChip_TotalPanel_10407variants_AxiomAssay_Oedulis.vcf.gz: .vcf file including the total number of successfully called 10407 variants, of 390 individuals for all nine study sites (GR, OS, VD, MA, WS< H1, H2, IR, and NW). SNPChip_PrunedPanel_8403variants_AxiomAssay_Oedulis.vcf.gz: .vcf file including the total number of pruned variants (8403 SNPs), of 390 individuals for all nine study sites (GR, OS, VD, MA, WS, H1, H2, IR, and NW). SNPChip_PrunedWildPanel_9293variants_AxiomAssay_Oedulis.vcf.gz: .vcf file including the number of pruned variants (9293 SNPs), of 277 individuals from wild native (GR, OS, VD, and MA) and wild foreign (IR and NW) study sites. SNPChip_PrunedWildNativePanel_8403variants_AxiomAssay_Oedulis.vcf.gz: .vcf file including the number of pruned variants (8403 SNPs), of 194 individuals from wild native study sites (GR, OS, VD, and MA). SNPChip_PrunedSubsampledNativePanel_8403variants_AxiomAssay_Oedulis.vcf.gz: .vcf file including the number of pruned variants (8403 SNPs), of 60 individuals (12 individuals subsampled for each study site), from wild native (GR, OS, VD, and MA) and cultured native (WS) study sites. Wageningen University & Research text/html https://research.wur.nl/en/datasets/snp-genotyping-data-from-european-flat-oysters-ostrea-edulis-dist 10.17882/108288 https://edepot.wur.nl/709765 Genetic diversity Ostrea edulis Population structure Restoration SNPs Wageningen University & Research

oai:library.wur.nl:wurpubs/745c74a3-dbf5-4f49-95bc-210a426e7f6c 2026-04-20 dataset edurep openaire public

Fiege, Kerstin Abdala Asbun, Alejandro Boeren, Sjef Engelmann, Julia Catherine Villanueva, Laura Dataset Membrane changes during syntrophic interactions of an archaeal-bacterial coculture 2025 Abstract Syntrophic interactions between bacteria and archaea are vital for anaerobic processes, relying on close cell-to-cell contact for efficient metabolite and electron transfer. Membrane-associated proteins and lipids likely play key roles in stabilizing these contacts, though little is known about membrane changes during syntrophy. These interactions are also central to theories of eukaryogenesis, where a symbiosis between an archaeal host—likely an Asgard archaeon—and a bacterial partner may have arisen from prior syntrophic interactions. Model systems of syntrophic microbes provide valuable insights into how such intimate associations could have led to the emergence of eukaryotic life. Here, we used syntrophic cocultures of the sulfate-reducing bacterium Desulfovibrio vulgaris and the methanogenic archaeon Methanococcus maripaludis to investigate membrane changes during a syntrophic interaction involving cell-to-cell contact. Evolved cocultures after several generations under syntrophic conditions were analyzed by proteomics and transcriptomics to identify differentially expressed proteins connected to cell-to-cell interactions, as well as by lipid analyses to determine changes in the cell membrane of both syntrophic partners. These data suggest a higher impact on the archaeon M. maripaludis, affecting transmembrane, signaling, and lipid biosynthesis proteins. To investigate the impact of evolutionary adaptation, both partners were re-isolated from a non-evolved ancestral coculture (coculture after mixing species), as well as from evolved (several generations) cocultures. While lipid profiles had changed in the coculture due to evolutionary adaptation, isolates were found to revert their lipid composition to the wildtype profile when growing independent again. This in-depth analysis of a model syntrophic coculture provides clues on how interdomain cell-to-cell interactions might have led to membrane changes during early eukaryogenesis. Description of .tar files containing data of intact polar lipid analysis: 1) Lipid_data_coculture_vs_monocultures.tar: Folders for each type of analysed culture (wildtype monocultures of D. vulgaris and M. maripaludis and cocultures Co-Anc, Co-300 and Co-1000) Raw data files of mass spectrometry runs of 5 biological replicates Folder with raw data files of mass spectrometry runs of growth medium blanks for all three different used growth media 2) Lipid_data_isolates_vs_cocultures.tar: Folders for each type of analysed culture (isolated monocultures of D. vulgaris and M. maripaludis and cocultures mixed with these isolates) Raw data files of mass spectrometry runs of 3 biological replicates Folder with raw data files of mass spectrometry runs of growth medium blanks for all three different used growth media NIOZ text/html https://research.wur.nl/en/datasets/membrane-changes-during-syntrophic-interactions-of-an-archaeal-ba 10.5281/zenodo.15633215 https://edepot.wur.nl/709719 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/1cafeef7-52bf-4d0a-9ee2-18a1e80bb970 2026-04-20 dataset edurep openaire public

Moatsos, Michalis de Zwart, P. Dataset Replication Data for: Real wages around the world: Insights from linear programming and accounting for climate differences 2025 The data include the estimates of historical real wages following the methodology described in the related publication. (2025-11-20) Maastricht University text/html https://research.wur.nl/en/datasets/replication-data-for-real-wages-around-the-world-insights-from-li 10.34894/RQTQVH https://edepot.wur.nl/709716 Heating needs Linear programming Little divergence Price index Real Wages Temperature differences Welfare ratio Wageningen University & Research

oai:library.wur.nl:wurpubs/df4d40d2-c18a-47c0-a976-c34fd95e409e 2026-04-02 dataset edurep openaire public

Limpens, J. Dataset Replication Data for: Quantifying plasticity of children’s visions of nature 2025 Purpose: data underlying article: Holmgren et al. 2025 Earth Stewardship: Quantifying plasticity of children’s visions of nature. Nature: quantitative results of surveys containing three exercises assessing the normative, expressive and cognitive dimensions of nature perception of children before and directly after nature education activities (excursion and nature-themed games) in the Venice lagoon Scope: anonymized quantitative data from surveys taken from 120 children aged 11-12 from six classes and three schools in Venice (2025-10-03) Wageningen University & Research text/html https://research.wur.nl/en/datasets/replication-data-for-quantifying-plasticity-of-childrens-visions- 10.17026/SS/RXSHVG https://edepot.wur.nl/709714 nature perception Wageningen University & Research

oai:library.wur.nl:wurpubs/732e9fed-2787-4b90-9596-f04b91f7c1b4 2026-04-02 dataset edurep openaire public

Maranganti Bhatter, Sushma Dataset New_Normal_Casestudy 2025 This open-access GIS dataset supports spatial planning for emission-free, energy-independent, and space-efficient urban mobility systems in Dutch cities. The dataset comprises 34 harmonized geospatial layers describing environmental, land use, infrastructural, demographic, hazard, risk, and socioeconomic conditions at fine spatial resolution. Thematic categories include: 1.Zoning Constraints Map: landing sites, drone no-fly zones, restricted areas 2.Topographic: elevation, recreation corridors, terrain 3.Transportation: road and rail networks, transit stations, bus stops 4.Landuse: land cover, buildings, water bodies 5.Mobility Indicator: car ownership and mobility proxies 6.Environmental / Air Quality Indicator: NO₂, O₃, PM2.5, PM10, tree/vegetation cover 7.Hazard & Risk Map: flood, drought, groundwater vulnerability, flammable zones 8.Energy: power lines, wind/solar infrastructure, substations, heating networks 9.Amenities / POIs: fuel and charging stations, public facilities, parking 10.Demographic: high-resolution population, age, gender, household size 11.Urban Governance / Planning Region: urban/recreational areas, business centers 12.Socioeconomic Data: income, employment rates, business activity. Format: Provided as geo-referenced rasters (.tif), ESRI shapefiles (.shp with associated files), and tabular (.csv, .xlsx) data with extensive metadata documentation. Sources: Data are derived from authoritative sources, including PDOK, CBS (Statistics Netherlands), BAG, Copernicus Land Monitoring, Eurostat, Risicokaart, h2inframap.eu, and relevant national/environmental platforms. Wageningen University & Research text/html https://research.wur.nl/en/datasets/newnormalcasestudy 10.17632/hf6sxy3wy5 https://edepot.wur.nl/709713 Assessment of Interests Bus Transportation Demographics Electroencephalogram Topographical Analysis Hazard Landuse Modeling for Bioenergy Road Transportation Social Mobility Socioeconomic Status Wageningen University & Research

oai:library.wur.nl:wurpubs/e1f2fb7a-2302-4342-8ea3-234c326af49c 2026-04-02 dataset edurep openaire public

Farshidi, Siamak Dataset Automated Ontology Construction for AI4RSE 2025 This dataset contains the input data, intermediate results, and generated outputs produced during the automated ontology construction process for the domain of Artificial Intelligence for Research Software Engineering (AI4RSE). It represents a structured example of how domain knowledge can be automatically extracted, organized, and visualized as an ontology. The dataset includes the following components: WorkflowInputs/ - Input files and configuration data used for the ontology construction workflow. WorkflowOutputs/ - Generated ontology files and related artifacts resulting from the automated processing steps. json_results/ - Machine-readable JSON files containing extracted terms, definitions, and relationships between concepts. Ontology_viewer.html - An interactive web-based viewer that allows users to explore the ontology structure and navigate semantic relationships among concepts. The dataset demonstrates an end-to-end ontology generation pipeline, from validated text inputs to structured, SKOS-compliant knowledge representations and visualization. It can be reused for studying automated ontology engineering, semantic data modeling, and AI-assisted knowledge organization. Wageningen University & Research text/html https://research.wur.nl/en/datasets/automated-ontology-construction-for-ai4rse 10.17632/3nwxxsdpr6 https://edepot.wur.nl/709707 Design Ontology Knowledge Representation and Reasoning Semantic Web Software Engineering Taxonomy Wageningen University & Research

oai:library.wur.nl:wurpubs/681c3f37-88e7-41b4-b9bd-b975c467ec89 2026-04-02 dataset edurep openaire public

Polling, M. Warmer, F.E.M. Buij, R. Laros, I. Visser, T. de Groot, G.A. Dataset Validating Airborne eDNA Using Manual Surveys, Acoustic Monitoring and Camera Traps to Detect Birds and Mammals in an Agroforestry Setting 2025 Global loss of biodiversity prioritizes the need for comprehensive and effective biomonitoring methods. Airborne environmental DNA (eDNA) has shown promise for monitoring terrestrial vertebrates but has not yet been rigorously compared to established biomonitoring methods. In a field-study in the Netherlands, this study aims to compare species detection from airborne eDNA with manual surveys, camera trapping and acoustic monitoring, focusing on birds and mammals. Monitoring was performed over the course of 4 weeks within an agroforestry ecosystem. Birds were monitored using eDNA, manual surveys and acoustic monitoring, while eDNA and camera trapping were used for mammals. This resulted in four mammal species, detected by both camera traps and eDNA, while eDNA identified an additional 16 species, primarily small-bodied, including two invasive species. A total of 74 bird species was detected, with varying degrees of overlap between methods and all three methods detected unique species. All but three bird and four mammal species detected were consistent with known occurrences near the study site. Rarefaction curves show that eDNA has the highest potential species diversity, but manual surveys are most efficient when limited time is available. Unique species can largely be explained by method characteristics or limitations; acoustic monitoring detections are limited to species that make sound, while eDNA requires further research on detection range and sensitivity. Our results indicate that for the studied agroforestry system, acoustic monitoring and airborne eDNA can detect a large proportion of birds and mammals detected by manual surveys, in addition to a range of species undetected by the latter, attesting to their effectiveness as biodiversity monitoring methods. This is the first study to compare airborne eDNA with manual surveys and acoustic data, further confirming the high potential of airborne eDNA for biodiversity monitoring. Wageningen University & Research text/html https://research.wur.nl/en/datasets/validating-airborne-edna-using-manual-surveys-acoustic-monitoring 10.5281/zenodo.16411331 https://edepot.wur.nl/709684 Airborne eDNA Biodiversity monitoring Metabarcoding Wageningen University & Research

oai:library.wur.nl:wurpubs/818cae32-091d-40a0-b642-1c946ba105bf 2026-04-02 dataset edurep openaire public

Huyan, Zongyao Scott, William Rubert, Josep Dataset Gut-specialized Clostridia and Gammaproteobacteria convert linoleic acid into polyunsaturated fatty acids that are building blocks for lipid synthesisGenome scale metabolic modeling 2025 Genome scale metabolic modeling scripts for manuscript NMICROBIOL-25114223 "Gut-specialized Clostridia and Gammaproteobacteria convert linoleic acid into polyunsaturated fatty acids that are building blocks for lipid synthesis" Wageningen University & Research text/html https://research.wur.nl/en/datasets/gut-specialized-clostridia-and-gammaproteobacteria-convert-linole 10.5281/zenodo.17739863 https://edepot.wur.nl/709682 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/1b3a6425-8940-4dd9-a120-8b8d5266b79b 2026-04-02 dataset edurep openaire public

Boogaard, Hendrik de Wit, Allard Berghuijs, Herman Hoek, Steven ter Horst, Mechteld Adriaanse, Pauline Hekkert, Gijs Dataset Simulated BBCH crop growh stages as function of calendar dates across the EU including underlying observations 2025 EU Regulation requires environmental risk assessments (ERA) for non-target organisms exposed to active substances in plant protection products. To advance the ERA of pesticides effectively, it is important to have accurate prediction of crop phenology spatially across the EU. Therefore, a study was conducted to enhance pesticide risk assessment for non-target organisms by precisely mapping crop development stages (BBCH ) across the EU by developing predictive models of crop sowing dates as well as calibrated models of crop phenology. We did an extensive data collection and curation from public sources like C2D2 (Hughes et al., 2023), PEP725 (Templ et al., 2018), and TEMPO (Maury et al., 2023), alongside literature, creating a harmonized database phenological observations. Comparisons revealed C2D2's broad spatial coverage across Europe, while PEP725 concentrated in Central Europe and TEMPO in France. C2D2 and TEMPO offered observations across various growth stages, unlike PEP725 which focused on sowing, emergence, and harvest. A model for spatially predicting sowing dates was developed using a temperature-driven rule, supplemented by a median rule for regions where management practices (like irrigation) heavily influence planting, as seen with maize in Southern Europe. The WOFOST cropping system model's phenological sub-model was used to simulate phenology. It predicts crop development through a dimensionless development stage (DVS) variable which is 0 at crop emergence and reaches 1.0 at anthesis and 2.0 at maturity. The model accounts for temperature as well as photoperiod and vernalization for winter crops. The temperature sum requirements to anthesis (TSUM1) and maturity (TSUM2) were calibrated using observed sowing, flowering and maturity dates from the datasets mentioned above. Observations were pooled by defining agroecological zones with similar agroclimatic conditions and all observations in an agroecological zones where used jointly to estimate the TSUM1 and TSUM2 parameters. Next, the intermediate BBCH stages were connected to the DVS scale as defined by WOFOST. Finally, the calibrated model was used to predict development stages based on the predicted sowing dates over the entire European 10x10 km grid in order to have wall-to-wall predictions of all BBCH development stages. The simulated BBCH crop growth stages and their corresponding observations are provided. The publication contains two SQLite databases: Simulated BBCH crop growth stages (simoutput_final_v20250630.db) Observed phenology data (EFSA_CURATED_DATA_v20250616-without-PEP725.db) For the observed phenology data, we include only those datasets that can be redistributed under the original data policies. Consequently, data from PEP725 is not included. For the other data sets the original data policy, defined in table DATASETS (EFSA_CURATED_DATA_v20250616-without-PEP725.d), must be followed. Thus the user must check the data license of each of these datasets before starting to use or redistribute the data. The simulated BBCH crop growth stages are available under Creative Commons Attribution 4.0 International. The structure of these databases is described in the document 'Readme simulated BBCH stages and observations.pdf'. To fully understand the background of the data, the reader is referred to the scientific report. Finally, an animation video, SBAR_BBCH_full.avi, is available presenting a time-lapse of simulated development stage for spring barley. This work was carried out under the Framework Partnership Agreement (GP/EFSA/PREV/2020/02) between the European Food Safety Authority (EFSA) and Wageningen Environmental Research (WENR), which aims to advance concepts and methodologies for assessing the exposure of terrestrial non-target organisms to plant protection products. Wageningen University & Research text/html https://research.wur.nl/en/datasets/simulated-bbch-crop-growh-stages-as-function-of-calendar-dates-ac 10.5281/zenodo.17658923 https://edepot.wur.nl/709678 BBCH agriculture crop growth model environmental exposure assessment pesticides phenology terrestrial non-target organisms Wageningen University & Research

oai:library.wur.nl:wurpubs/1e183700-0ad7-455b-a904-5940ba1a02d2 2026-04-20 dataset edurep openaire public

Lehtonen, Aleksi Mäkipää, Raisa Menichetti, Lorenzo Anttila, Jani Kupila, Taavi Tupek, Boris Salovaara, Petri Oskar Peltoniemi, Mikko Bosela, Michal Filipek, S.P. Santonja, Mathieu Sterck, F.J. Weikl, Fabian Christopher Wilms, Florian Pritsch, Karin Casals, Pere Curiel-Yuste, Jorge Garcia-Pausas, Jordi Petritan, Ion Catalin Aleinikovienė, Jūratė Van den Abbeele, Martin Dataset Soil respiration dataset for European forest sites evaluating holistic management practices 2025 Data file "holisoils_soil respiration dataset.csv" of forest soil respiration, soil and undestory respiration, soil temperature and volumetric water content from European forest sites collected during 2021-2025. Readme file and the short description of sites treatments and ids of the plot are below. File outline of sites/subsite/treatments/point types/point codes is in file "holisoils_data_structure.csv". Natural Resources Institute Finland (LUKE) text/html https://research.wur.nl/en/datasets/soil-respiration-dataset-for-european-forest-sites-evaluating-hol 10.5281/zenodo.17519670 https://edepot.wur.nl/709674 European forests managements soil respiration temperature volumetric soil water content Wageningen University & Research

oai:library.wur.nl:wurpubs/f0bfd7a7-c8fb-470e-939d-b2371e489bd1 2026-04-20 dataset edurep openaire public

Wakjira, Mosisa Tujuba Molnar, Peter Bartholomeus, Ruud Descheemaeker, Katrien Dataset Datasets of monthly reference agrohydrological variables for the rainfed agricultural region of Ethiopia (Ethio-AgHy) 2025 Summary The Ethio-AgHy reference agrohydrological dataset was developed using a modeling framework that integrates climate, soil, land use, and topographic data to simulate water balance components within the upper 60 cm soil layer of agricultural lands across Ethiopia. The database includes climatologies of the following variables: Monthly mean and standard deviation (std) of actual evapotranspiration, ETa [mm/month] Monthly mean and standard deviation (std) of reference evapotranspiration, ETo [mm/month] Monthly mean and standard deviation (std) of surface runoff, RO [mm/month] Monthly mean and standard deviation (std) of volumetric soil moisture, SMv [m^3/m^3] Monthly mean and standard deviation (std) of soil moisture deficit, SMD [%] Monthly mean and standard deviation (std) of soil aeration deficit, SAD [%] Annual mean and standard deviation (std) of waterlogging intensity, WLI [days/year]. For each variable with a monthly climatology, data are stored in a single GeoTIFF file containing 12 bands, each representing one calendar month (January to December). In the metadata, months are abbreviated as: Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec. The waterlogging intensity (WLI) dataset, being annual, is provided as a single-band GeoTIFF. The datasets cover the rainfed agricultural regions of Ethiopia, bounded by latitudes 4.445° N - 15.046° N and longitudes 32.852° E - 44.085° E. Data are provided on a 500 m × 500 m spatial grid (2120 rows × 2250 columns). Grid indexing starts from the north, and cells with no data are assigned NaN values. All datasets are provided in the WGS 84 geographic coordinate system (EPSG:4326). References Funk, C. et al. The climate hazards infrared precipitation with stations - A new environmental record for monitoring extremes. Nat. Sci. Data 2, (2015). Wakjira, M. T., Peleg, N., Burlando, P. & Molnar, P. Gridded daily 2-m air temperature dataset for Ethiopia derived by debiasing and downscaling ERA5-Land for the period 1981–2010. Data Br. 46, 108844 (2023). Wakjira, M. T., Peleg, N., Molnar, P. & Burlando, P. Bias-Corrected and Downscaled ERA5-Land 2-m Air Temperature Dataset for Ethiopia for the Period 1981-2010. (2022) doi:10.3929/ethz-b-000546574. Muñoz-Sabater, J. et al. ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth Syst. Sci. Data 13, 4349–4383 (2021). Poggio, L. et al. SoilGrids 2.0: Producing soil information for the globe with quantified spatial uncertainty. Soil 7, 217–240 (2021). Ross, C. W. et al. HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling. Sci. data 5, 180091 (2018). Wakjira, M. T., Peleg, N., Six, J. & Molnar, P. Green water availability and water-limited crop yields under a changing climate in Ethiopia. Hydrol. Earth Syst. Sci. 29, 863–886 (2025). USDA. Urban Hydrology for Small Watersheds. (1985). SRTM. Shuttle Radar Topography Mission (SRTM) Global. Distributed by OpenTopography. (2013) doi:10.5069/G9445JDF. Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. Crop Evapotranspiration. Irrigation and Drainage Paper No. 56 (1998). Saxton, K. E. & Rawls, W. J. Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions. Soil Sci. Soc. Am. J. 70, 1569–1578 (2006). Wageningen University & Research text/html https://research.wur.nl/en/datasets/datasets-of-monthly-reference-agrohydrological-variables-for-the- 10.5281/zenodo.17514459 https://edepot.wur.nl/709664 Agrohydrological fluxes Evapotranspiration Moisture stress Rainfed agriculture Soil mosture Surface runoff Waterlogging Wageningen University & Research

oai:library.wur.nl:wurpubs/e8e2bca0-0530-46bf-b594-baa1f30376c2 2026-04-20 dataset edurep openaire public

El Arnouki Belhaji, Fatima Alanjary, Mohammad Zdouc, Mitja Maximilian Medema, Marnix H. Masschelein, Joleen Dataset AntiSMASH genome mining for novel hybrid polyketide-nonribosomal peptide-specialized lipids output 2025 This repository contains results from an antiSMASH (version 7.1.0) genome mining approach on a dataset comprising 62,706 NRPS-containing bacterial genomic regions in Genbank format, obtained from the antiSMASH database (version 4). The dataset was analyzed via a custom-designed search rule, that we termed ‘zeamine-like’, with the goal of finding novel trihybrid polyketide synthase (PKS)-nonribosomal peptide synthetase (NRPS)-polyunsaturated fatty acid (PUFA) synthase-like clusters. This rule integrated pre-existing profile Hidden Markov Models (pHMMs) targeting PKS, NRPS and PUFA synthase-like biosynthetic machinery (cds(Condensation and (AMP-binding or A-OX)) and cds(PKS_AT and (PKS_KS or ene_KS or mod_KS or hyb_KS or itr_KS or tra_KS)) and (hglE or hglD or PUFA_KS)). A ‘relaxed’ level of strictness was applied, allowing for the detection of incomplete clusters lacking one or more functional components. The maximum allowed distance between core genes was set at 20 kbp, and an additional 20 kbp was included beyond the core genes to define the protocluster boundaries. This repository contains the combined results output from antiSMASH. KU Leuven text/html https://research.wur.nl/en/datasets/antismash-genome-mining-for-novel-hybrid-polyketide-nonribosomal- 10.5281/zenodo.17465186 https://edepot.wur.nl/709662 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/5fdaa32c-9210-4785-8aa5-814a7dda9a2d 2026-04-20 dataset edurep openaire public

Läpple, Doris de Mey, Y. Thoyer, Sophie Van den Broeck, Goedele Lécole, Pauline Sok, J. Dataset Farmers' Voices in European Protests: Diverse Complaints, Emotional Tones, and Policy Responses 2025 This dataset accompanies a study on the 2024 farmers’ protests in Germany, France, Belgium, and the Netherlands. It includes coded data derived from 2,232 farmers’ open-ended survey responses on farmers' reasons for protesting. Using a combination of manual and AI-assisted coding, the study categorizes protest reasons and emotional tone and links them to national and EU policy responses. The dataset captures cross-country differences in protest motivations and emotional expressions, reflecting diverse forms of agricultural discontent. Original text responses are not included due to confidentiality. University of Göttingen text/html https://research.wur.nl/en/datasets/farmers-voices-in-european-protests-diverse-complaints-emotional- 10.5281/zenodo.17435985 https://edepot.wur.nl/709659 Farmers’ protests agricultural policy open-ended survey question text-analysis Wageningen University & Research

oai:library.wur.nl:wurpubs/e378f3ec-663a-425e-83ad-2e2f77aabc5b 2026-04-20 dataset edurep openaire public

Frostenberg, Hannah Ickes, Luisa Costa-Surós, Montserrat Proske, J.U. Sotiropoulou, Georgia Dataset Model and satellite observational data to analyze microphysical processes in mixed-phase clouds 2025 These data were used for the analysis in the publication cited as Reference below. See Methods in the main article and Supplementary Sect. A.1. The model data were created using EC-Earth3-AerChem, NorESM2-MM, and ECHAM6.3-HAM2.3. For each of the models, 16 experiments were run (see Supplementary Table C2), and the additional experiment 'Meyers' for EC-Earth. All_models_Ref_iwc_lwc.zip contains zonal annual means of Ice Water Content (IWC) and Liquid Water Content (LWC) for the Ref experiment. The naming convention of the SLF (Supercooled Liquid Fraction), IWC and LWC model data is: {model}_{experiment}_{variable}_2018_monthly-annual_[zonal,box]_mean.nc. The geographical boxes are used in Fig. 3 in the main article and refer to: Northern polar (90-60° N), Northern mid-latitudes (60-30° N), Tropics (30° N-30° S), Southern mid-latitudes (30-60° S), Southern polar (60-90° S). All variables have the dimension T (temperature), since the data were binned every 5 K (see Results in the main manuscript). All averaging was done using CDO. Note that latitudes in ECHAM are reversed compared to the other models and GOCCP. The original source of the data in GOCCP_Observations.zip is https://climserv.ipsl.polytechnique.fr/cfmip-obs/Calipso_goccp.html. The data were zonally and annually averaged using CDO. Please refer to the article for more details. Chalmers University of Technology text/html https://research.wur.nl/en/datasets/model-and-satellite-observational-data-to-analyze-microphysical-p 10.5281/zenodo.17266270 https://edepot.wur.nl/709643 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/0cf1877b-4482-4c73-a6f9-34c8cbddef71 2026-04-02 dataset edurep openaire public

Grondard, Nicolas Bangalore Suresh, Nikshep Dataset Maps of flood damage costs 2025 Maps of flood damage costs used to assess flood risk mitigation benefits of freshwater ecosystem restoration in Cost Benefit Analysis of MERLIN case studies restoration scalability plans. Wageningen University & Research text/html https://research.wur.nl/en/datasets/maps-of-flood-damage-costs 10.5281/zenodo.17251001 https://edepot.wur.nl/709636 Cost-Benefit Analysis Ecosystem services Floods/economics Wageningen University & Research

oai:library.wur.nl:wurpubs/e1491d91-26f3-4245-8638-1cf934f1863f 2026-04-20 dataset edurep openaire public

Rieder, Lukas Hagens, M. Poetra, Reinaldy P. Vidal, A.M.C. Calogiuri, T. Neubeck, Anna Singh, Abhijeet Corbett, Thomas D.W. Niron, Harun Vicca, Sara Vlaeminck, Siegfried E. Janssens, Iris Verdonck, Tim Janssens, Ivan A. Hartmann, Jens Dataset Weathering indicators from biotic and organic amendments in rock powder column experiments 2025 The dataset comprises measurements of weathering indicators in relation to the addition of microorganisms, enzymes, earthworms, and organic matter to different rock powders. Data was collected within the BAM! project (Bio-Accelerated Mineral Weathering), which investigates the potential of soil biota and organic inputs to accelerate mineral weathering processes for carbon sequestration. Experimental data were obtained from 4 rounds of column experiments conducted between March 2022 and March 2023 at Wageningen University & Research. Treatments included combinations with and without biotic and organic amendments, allowing for comparative assessment of their influence on mineral weathering. The dataset contains measurements of key weathering indicators, including dissolved organic carbon, dissolved inorganic carbon, total alkalinity, pH, electrical conductivity, major cations and anions, as well as selected trace elements. University of Hamburg text/html https://research.wur.nl/en/datasets/weathering-indicators-from-biotic-and-organic-amendments-in-rock- 10.1594/PANGAEA.984825 https://edepot.wur.nl/709452 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/f200e9f5-e85a-491a-b937-1dbe9db6f9d7 2026-04-20 dataset edurep openaire public

Vilas Franquesa, A. Bensi, Sibilla Yang, S. Fogliano, V. Dataset Dataset: Yield vs. Functionality: Enzyme-Assisted Extraction of Mango Peel Reduces Antioxidant Dietary Fiber Quality 2025 The raw data is provided for the interested parties related to the manuscript in the title Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-yield-vs-functionality-enzyme-assisted-extraction-of-mang 10.17632/z2vs6gwbmk https://edepot.wur.nl/709448 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/0d4e31e3-01f9-4188-a7d7-824f0080b227 2026-04-20 dataset edurep openaire public

Frehner, A.M. Rojas Conzuelo, Z. Richter, Sebastian Lock, Roxanne Schader, Christian Dataset Harmonised dataset for decomposing and matching food items in dietary data for high-resolution modelling 2025 The dataset includes a decomposition table as well as matching tables linking FoodEx2 level 7 items to three commonly used environmental impact databases (Poore and Nemecek dataset, Agribalyse v3.2, Ecoinvent v3.10). Yield conversion factors and consumer food waste coefficients are incorporated to support full food supply chain impact modelling. The dataset is complemented by an R script that supports semi-automatic matching, which can easily be applied to other datasets. Research Institute of Organic Agriculture (FiBL) text/html https://research.wur.nl/en/datasets/harmonised-dataset-for-decomposing-and-matching-food-items-in-die 10.5281/zenodo.17311731 https://edepot.wur.nl/709446 Composite food decomposition Environmental impact modelling Food classification systems Matching Wageningen University & Research

oai:library.wur.nl:wurpubs/5fa3b66e-2bd5-43ae-8260-2c7868602d7c 2026-04-20 dataset edurep openaire public

Batool, Masooma Goyal, Shekhar Sharan Sarrazin, Fanny J. de Vries, Wim Ros, Gerard Kumar, Rohini Dataset ENMI Europe Dataset 2025 Data Description (v1) This datasets consist of ENMI (Environmental Nitrogen Management Index (ENMI)) estimaets for Europen countries, EU‑27 member states and NUTS‑1 regions. It pairs with R scripts so external users can reproduce the country/EU‑27/regional ENMI metrics, tables, and figures referenced in the study. Excel sheets enmi_country_yearly/decade.xlsx: yearly and decadal ENMI values at country-level with metadata README tabs. enmi_eu27_yearly/decade.xlsx: yearly and decadal ENMI values at EU27-level with metadata README tabs. enmi_nuts1_yearly/decade.xlsx: yearly and decadal ENMI values at NUTS1-levelwith metadata README tabs. Rscripts 01_compute_n_surplus_ratios.R: critical N surplus aggregation and country ratios. 02_compute_n_output_ratios.R: reference nitrogen output levels and actual/output ratios. 03_compute_enmi.R: ENMI calculation 04_export_enmi_tables.R: Excel workbooks (country, EU‑27, NUTS‑1) with README sheets. 05_plot_enmi_timeseries.R: Rscript for ENMI timeseries plot provided as an example (Figure 1b) Unit & Resolution ENMI is a unitless index bounded in [0, 1]; Time period: 1961-2019 Acknowledgments and underlying datasets The authors gratefully acknowledge the Global Water Quality Analysis and Service Platform (GlobeWQ) project to support a partial funding of this work, which was financed by the German Ministry for Education and Research (Grant No.:02WGR1527A). We are also thankful to UFZ for providing computing power and technical support related to the High-Performance Computing (HPC) Cluster EVE, a joint effort of both the Helmholtz Centre for Environmental Research - UFZ and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. Contact Further queries regarding these datasets can be directed to Masooma Batool (masooma.batool@ufz.de) and Rohini Kumar (rohini.kumar@ufz.de). Helmholtz Centre for Environmental Research text/html https://research.wur.nl/en/datasets/enmi-europe-dataset 10.5281/zenodo.17226010 https://edepot.wur.nl/709386 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/34eb8d0b-10ab-4bb0-8fd5-c456d85311b9 2026-04-02 dataset edurep openaire public

Roelofs, Tristan Castellnou Ribau, Marc Vila, Jordi Janssens, Martin van Heerwaarden, Chiel Dataset Dataset for paper: The impact of the Santa Coloma de Queralt fire on the atmospheric boundary layer: the development of a fire-induced circulation 2025 This dataset contains the data used for the paper: The impact of the Santa Coloma de Queralt fire on the atmospheric boundary layer: the development of a fire-induced circulation. The data presented here includes: The scq_setup folder contains the settings for MicroHH (scq.ini) and the 2D surface input fields for the virtual potential temperature (thl), specific humidity (qt) and a tracer released by the fire (s). We provided the 2D surface input files for both the environmental run (Environmental_2D_surface_input_fields) and for the fire run (Fire_2D_surface_input_fields). Note the fire-run only contains files between 7200 and 14400, since this simulation with the fire uses a restart from the environmental run at 7200 seconds. The fire perimeter data of the SCQ fire on the 24th of July is provided in the 'scq_fire_perimeter' folder. Acknowledgements This project during which this data was created received funding from the Union Civil Protection Mechanism of the European Union under grant agreement No 101140363 (EWED). Hence, this project is funded by the European Union. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Commission-EU. Neither the European Union nor the granting authority can be held responsible for them. Wageningen University & Research text/html https://research.wur.nl/en/datasets/dataset-for-paper-the-impact-of-the-santa-coloma-de-queralt-fire- 10.5281/zenodo.17159895 https://edepot.wur.nl/709385 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/5c1f9b19-f122-43d9-b429-50037941c1ed 2026-04-02 dataset edurep openaire public

Gobes, Martijn Dataset Data and scripts for Impact of pH, temperature, and moisture on the rheological behaviour of soy protein concentrate doughs 2025 This dataset contains all data associated with the manuscript titled 'Impact of pH, temperature, and moisture on the rheological behaviour of soy protein concentrate doughs'. The folders with raw data contain the amplitude sweeps in excel format, alongside metadata, and the .asc are raw text files containing the stress/strain curves. Wageningen University & Research text/html https://research.wur.nl/en/datasets/data-and-scripts-for-impact-of-ph-temperature-and-moisture-on-the 10.5281/zenodo.17142515 https://edepot.wur.nl/709383 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/c5e1a231-5845-4327-ad25-1c0ba61524ae 2026-04-20 dataset edurep openaire public

Teickner, Henning Agethen, Svenja Berger, Sina Boelsen, Rieke Inga Borken, Werner Bragazza, Luca Broder, Tanja De la Cruz, Florentino Diaconu, Andrei-Cosmin Dise, Nancy Drollinger, Simon Estop-Aragonés, Cristian Galka, Mariusz Martí Generó, Magalí Glatzel, Stephan Groß, Jessica Harris, Lorna Heffernan, Liam Hodgkins, Suzanne Hömberg-Grandjean, Annkathrin Hoppe, Helga Kleinebecker, Till Knierzinger, Wolfgang Liu, Haojie Mathijssen, Paul Mollmann, Christopher Schuster, Wiebke Närtker, Lisa Olefeldt, David Pancotto, Veronica A. Pelletier, Nicolas Reuter, Hendrik Robroek, Bjorn Svensson, Bosse Talbot, Julie Thompson, Lauren M. Worrall, Fred Yu, Zhi-Guo Knorr, Klaus-Holger Dataset Peatland Mid-Infrared Database (1.0.0) 2025 The peatland mid-infrared database (pmird) stores data from peat, vegetation, litter, and dissolved organic matter samples, in particular mid-infrared spectra and other variables, from previously published and unpublished data sources. The majority of samples in the database are peat samples from northern bogs. Currently, the database contains entries from 26 studies, 11216 samples, and 3877 mid infrared spectra. The aim is to provide a harmonized data source that can be useful to re-analyse existing data, analyze peat chemistry, develop and test spectral prediction models, and provide data on various peat properties. University of Münster text/html https://research.wur.nl/en/datasets/peatland-mid-infrared-database-100 10.5281/zenodo.17092586 https://edepot.wur.nl/709381 ATR-FTIR FTIR Sphagnum database mid infrared spectra peat peatland pmird Wageningen University & Research

oai:library.wur.nl:wurpubs/75158318-5550-45a5-972a-e8faff279d5b 2026-04-02 dataset edurep openaire public

Colman, B.H. Woude, T.I.S. Genova, G. Poggio, L. van Genuchten, P.P.L. Dataset Potential annual soil loss by erosion (RUSLE), Rwanda 2025 Average annual soil loss (t ha-1 yr-1) calculated using the Revised Universal Soil Loss Equation (RUSLE): A = R × K × LS × C × P. This model estimates sheet and rill erosion risk based on five factors: rainfall erosivity (R), soil erodibility (K), topography (LS), cover-management (C), and support practices (P). The resulting map supports erosion risk assessment and soil conservation planning in Rwanda. Each input layer (R, K, LS, C, P) was derived as a separate spatial dataset as follows: R factor: Rainfall erosivity factor (MJ mm ha⁻¹ h⁻¹ yr⁻¹). Derived by clipping the global rainfall erosivity dataset of Panagos et al. (2017, https://doi.org/10.1038/s41598-017-04282-8), as published in Panagos et al. (2023, https://doi.org/10.1016/j.dib.2023.1094820), to the administrative country boundary of Rwanda. K factor: Soil erodibility factor ((Mg/ha)[(MJ/ha)(mm/h)]⁻¹), calculated following the method of Torri et al. (1997, https://doi.org/10.1016/S0341-8162(97)00036-2). The input sand, silt, clay and soil organic carbon maps were generated using digital soil mapping as implemented in the seedling workflow (https://doi.org/10.17027/ISRIC-FSX2-2691). The input soil profile data for these were: Sand, Silt & Clay: AfSIS (URI:b88870b4-6af8-4e78-a3ac-38871d757525), Marshland & MINAGRI (provided by Rwanda Agricultural and Animal Resources Development Board (RAB)) Soil Organic Carbon: CATALIST (provided by the IFDC CATALIST project) & Marshland (shared by RAB) LS factor: Topographic factor computed using slope and flow accumulation following the method of Luvai et al. (2021, https://doi.org/10.7176/JEES/11-16-06), and applied to areas with slope <50% in accordance with Panagos, Borrelli, and Meusburger (2015, https://doi.org/10.1016/j.scitotenv.2015.01.008). The LS factor was derived from the MERIT Digital Elevation Model (https://doi.org/10.1002/2017GL072874). C factor: Cover-management factor, calculated following the method of Negese (2024: https://doi.org/10.1016/j.rsase.2023.101089), using NDVI data derived from Landsat 8 Surface Reflectance Tier 1 Collection 2 imagery (2018–2023) (https://www.usgs.gov/landsat-missions/landsat-8). P factor: Support practices factor. P = 1 due to data gaps. This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR Grant number: 4000004100. Wageningen University & Research text/html https://research.wur.nl/en/datasets/potential-annual-soil-loss-by-erosion-rusle-rwanda 10.5281/zenodo.17036320 https://edepot.wur.nl/708787 Agriculture Crop production Land Mapping Modelling RUSLE Rwanda Soil Soil erosion Wageningen University & Research

oai:library.wur.nl:wurpubs/d214b2b6-7a67-415d-b495-d21c5fa2a5b1 2026-04-20 dataset edurep openaire public

Fernandez, Sebastian Mabry, Makenzie Soltis, Pamela Douglas, Soltis Schranz, Eric Dataset Uncovering Climate Resilient Traits Through Ecological Niche Modeling of Cocoyam and Taro Wild Relatives Across Africa 2025 The present dataset consists of training data, output files, and a project summary poster generated from environmental niche modelling (ENM) analyses of 68 crop wild relatives of taro (Colocasia esculenta) and cocoyam (Xanthosoma sagittifolium). Each component is seperated by crop and are provided to ensure reproducibility and further research on ecological modelling and biogeographic analyses. Xanthosoma & Colocasia Raw and Cleaned Data Format: CSV Contents: Raw data consists of original species occurrence records obtained from GBIF and iDigBio. These records include coordinates, taxonomic information, and associated metadata. No filtering or cleaning was applied beyond the initial data download. Cleaned data consists of records retained after data cleaning and spatial filtering. Records were examined for coordinate validity, spatial precision, and duplication, and further filtered to reduce sampling bias where applicable (e.g. spatial thinning). These data represent the final presence points used in model calibration and evaluatio Xanthosoma & Colocasia Pearson Correlation Matrices for Environmental Layers Format: CSV Contents: Pairwise Pearson correlation coefficients calculated among environmental predictor variables for each species. Xanthosoma & Colocasia Current Crop and Crop Wild Relative Projections Format: GeoTIFF (.tif) Contents: Raster projections representing current habitat suitability for the species, as estimated by ENMs calibrated using present-day environmental variables within Africa. The GeoTIFF files contain continuous values indicating relative suitability across the modelled region. Botany 2025 Poster Format: PDF (.pdf) Contents: Overview of ENM project including background, workflow, results, and future directions. University of Florida text/html https://research.wur.nl/en/datasets/uncovering-climate-resilient-traits-through-ecological-niche-mode 10.5281/zenodo.16987738 https://edepot.wur.nl/708776 Life Science Wageningen University & Research

oai:library.wur.nl:wurpubs/deb52091-836f-4ea3-b93f-6ea3661381cf 2026-04-20 dataset edurep openaire public

X. Pinho, Bruno Poorter, Lourens Justeau-Allaire, Dimitri Fischer, Fabian Chave, Jerome Maréchaux, Isabelle Dataset Code and Data from Pinho et al. - "Fragmented tropical forests can maintain tree diversity and function, but not under high deforestation" 2025 This repository contains code and data used in the analyses for the manuscript entitled: "Fragmented tropical forests can maintain tree diversity and function, but not under high deforestation" - Pinho et al. 2025 (under review). See README.txt for details on the available materials. Wageningen University & Research text/html https://research.wur.nl/en/datasets/code-and-data-from-pinho-et-al-fragmented-tropical-forests-can-ma 10.5281/zenodo.16950704 https://edepot.wur.nl/708766 Forest loss and fragmentation Individual-based model TROLL spatially explicit model taxonomic and functional diversity trait-based model tropical forests Wageningen University & Research 200:::oai_dc:dataset: