Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    A historical, geographical and ecological perspective on the 2018 European summer drought
    Peters, Wouter ; Bastos, Ana ; Ciais, Philippe ; Vermeulen, Alex - \ 2020
    Philosophical Transactions of the Royal Society B. Biological sciences 375 (2020)1810. - ISSN 0962-8436 - 8 p.
    atmosphere - carbon dioxide - drought - Europe - photosynthesis - soil moisture
    An Assessment of Climate Induced Increase in Soil Water Availability for Soil Bacterial Communities Exposed to Long-Term Differential Phosphorus Fertilization
    Randall, Kate C. ; Brennan, Fiona ; Clipson, Nicholas ; Creamer, Rachel E. ; Griffiths, Bryan S. ; Storey, Sean ; Doyle, Evelyn - \ 2020
    Frontiers in Microbiology 11 (2020). - ISSN 1664-302X
    bacteria - climate change - phosphorus - rhizosphere - soil moisture

    The fate of future food productivity depends primarily upon the health of soil used for cultivation. For Atlantic Europe, increased precipitation is predicted during both winter and summer months. Interactions between climate change and the fertilization of land used for agriculture are therefore vital to understand. This is particularly relevant for inorganic phosphorus (P) fertilization, which already suffers from resource and sustainability issues. The soil microbiota are a key indicator of soil health and their functioning is critical to plant productivity, playing an important role in nutrient acquisition, particularly when plant available nutrients are limited. A multifactorial, mesocosm study was established to assess the effects of increased soil water availability and inorganic P fertilization, on spring wheat biomass, soil enzymatic activity (dehydrogenase and acid phosphomonoesterase) and soil bacterial community assemblages. Our results highlight the significance of the spring wheat rhizosphere in shaping soil bacterial community assemblages and specific taxa under a moderate soil water content (60%), which was diminished under a higher level of soil water availability (80%). In addition, an interaction between soil water availability and plant presence overrode a long-term bacterial sensitivity to inorganic P fertilization. Together this may have implications for developing sustainable P mobilization through the use of the soil microbiota in future. Spring wheat biomass grown under the higher soil water regime (80%) was reduced compared to the constant water regime (60%) and a reduction in yield could be exacerbated in the future when grown in cultivated soil that have been fertilized with inorganic P. The potential feedback mechanisms for this need now need exploration to understand how future management of crop productivity may be impacted.

    Critical Soil Moisture Derived From Satellite Observations Over Europe
    Denissen, Jasper M.C. ; Teuling, Adriaan J. ; Reichstein, Markus ; Orth, René - \ 2020
    Journal of Geophysical Research: Atmospheres 125 (2020)6. - ISSN 2169-897X
    evapotranspiration - land-atmosphere interactions - remote sensing - soil moisture

    Evapotranspiration (ET) is a crucial quantity through which land surface conditions can impact near-surface weather and vice versa. ET can be limited by energy or water availability. The transition between water- and energy-limited regimes is marked by the critical soil moisture (CSM), which is traditionally derived from small-sample laboratory analyses. Here, we aim to determine the CSM at a larger spatial scale relevant for climate modeling, using state-of-the-art gridded data sets. For this purpose, we introduce a new correlation-difference metric with which the CSM can be accurately inferred using multiple data streams. We perform such an analysis at the continental scale and determine a large-scale CSM as an emergent property. In addition, we determine small-scale CSMs at the grid cell scale and find substantial spatial variability. Consistently from both analyses we find that soil texture, climate conditions, and vegetation characteristics are influencing the CSM, with similar respective importance. In contrast, comparable CSMs are found when applying alternative large-scale energy and vegetation data sets, highlighting the robustness of our results. Based on our findings, the state of the vegetation and corresponding land-atmosphere coupling can be inferred, to first order, from easily accessible satellite observations of surface soil moisture.

    Plant communities on nitrogen-rich soil are less sensitive to soil moisture than plant communities on nitrogen-poor soil
    Shovon, Tanvir Ahmed ; Rozendaal, Danaë M.A. ; Gagnon, Daniel ; Gendron, Fidji ; Vetter, Mary ; Vanderwel, Mark C. - \ 2020
    Journal of Ecology 108 (2020)1. - ISSN 0022-0477 - p. 133 - 144.
    community assembly - environmental filtering - light - multiple resource limitation - nitrogen - plant strategies - soil moisture - trait-based ecology

    Plant species composition and diversity are known to change across local gradients of light, moisture and nutrients, but ecologists still have a relatively limited understanding of how communities respond to multiple limiting resources. We used a trait-based approach to investigate how the functional composition and diversity of forest understorey plant communities change along gradients in light, soil moisture and nitrogen availability. We used a total of seven leaf, root and whole-plant traits for 55–78 species, and estimated the effects of the three resources on the mean and dispersion of these traits in understorey plant communities across 50 forest sites. Soil moisture and nitrogen availability (C/N ratio) both influenced plant community traits, but light availability (canopy openness) did not. Generally, increases in moisture and nitrogen both resulted in shifts towards more acquisitive resource use strategies, including greater leaf area, specific leaf area and maximum plant height, and lower leaf dry matter content, root dry matter content and rooting depth. Functional diversity of most traits also increased with increasing soil moisture and nitrogen. Although most traits varied with soil moisture on nitrogen-poor sites, moisture did not influence of the distribution of any traits on nitrogen-rich sites. Synthesis. Independent co-limitation of soil moisture and nitrogen appeared to influence the functional composition and diversity of understorey vegetation in our study area. The co-occurrence of species with resource acquisitive and conservative strategies on nitrogen-rich sites may make plant communities relatively resistant to changes to soil moisture. These results suggest that altered precipitation regimes under climate change could lead to greater changes in the composition and diversity of plant communities on nutrient-poor soils than on nutrient-rich soils.

    Data from: Plant communities on nitrogen‐rich soil are less sensitive to soil moisture than plant communities on nitrogen‐poor soil
    Shovon, Tanvir Ahmed ; Rozendaal, Danaë ; Gagnon, Daniel ; Gendron, Fidji ; Vetter, Mary ; Vanderwel, Mark C. - \ 2019
    Dryad
    multiple resource limitation - soil moisture - Light - nitrogen - plant strategies - trait-based ecology - Environmental filtering - community assembly
    1.Plant species composition and diversity are known to change across local gradients of light, moisture, and nutrients, but ecologists still have a relatively limited understanding of how communities respond to multiple limiting resources. 2.We used a trait‐based approach to investigate how the functional composition and diversity of forest understory plant communities change along gradients in light, soil moisture and nitrogen availability. We used a total of seven leaf, root, and whole‐plant traits for 55‐78 species, and estimated the effects of the three resources on the mean and dispersion of these traits in understory plant communities across 50 forest sites. 3.Soil moisture and nitrogen availability (C/N ratio) both influenced plant community traits, but light availability (canopy openness) did not. Generally, increases in moisture and nitrogen both resulted in shifts towards more acquisitive resource use strategies, including greater leaf area, specific leaf area and maximum plant height, and lower leaf dry matter content, root dry matter content and rooting depth. Functional diversity of most traits also increased with increasing soil moisture and nitrogen. Although most traits varied with soil moisture on nitrogen‐poor sites, moisture did not influence of the distribution of any traits on nitrogen‐rich sites. 4.Synthesis: Independent co‐limitation of soil moisture and nitrogen appeared to influence the functional composition and diversity of understory vegetation in our study area. The co‐occurrence of species with resource acquisitive and conservative strategies on nitrogen‐rich sites may make plant communities relatively resistant to changes to soil moisture. These results suggest that altered precipitation regimes under climate change could lead to greater changes in the composition and diversity of plant communities on nutrient‐poor soils than on nutrient‐rich soils.
    Cone index and surface soil moisture measurements in selected agricultural fields within the Raam and Twente soil moisture monitoring networks
    Carranza, C.D. - \ 2019
    agriculture - cone index - soil moisture - trafficability
    This dataset covers cone index and surface soil moisture measurements over selected agricultural fields, which are also the sites of a few stations within the Raam and Twente soil moisture monitoring networks. A penetrologger (Eijkelkamp) with 1 cm diameter and 60 degree angle was used to collect cone index over the topsoil (upper 20 cm layer) and a TDR (TRIME-IMKO) was used to collect surface soil moisture (upper 5 cm layer). The data set covers 2016 and 2017 growing seasons.
    Changes in surface hydrology, soil moisture and gross primary production in the Amazon during the 2015/2016 El Niño
    Schaik, Erik van; Killaars, Lars ; Smith, Naomi E. ; Koren, Gerbrand ; Beek, L.P.H. van; Peters, Wouter ; Laan-Luijkx, Ingrid T. van der - \ 2018
    Philosophical Transactions of the Royal Society B. Biological sciences 373 (2018)1760. - ISSN 0962-8436 - 9 p.
    Amazon - El Niño - gross primary productivity - river discharge - soil moisture - tropical terrestrial carbon cycle

    The 2015/2016 El Niño event caused severe changes in precipitation across the tropics. This impacted surface hydrology, such as river run-off and soil moisture availability, thereby triggering reductions in gross primary production (GPP). Many biosphere models lack the detailed hydrological component required to accurately quantify anomalies in surface hydrology and GPP during droughts in tropical regions. Here, we take the novel approach of coupling the biosphere model SiBCASA with the advanced hydrological model PCR-GLOBWB to attempt such a quantification across the Amazon basin during the drought in 2015/2016. We calculate 30-40% reduced river discharge in the Amazon starting in October 2015, lagging behind the precipitation anomaly by approximately one month and in good agreement with river gauge observations. Soil moisture shows distinctly asymmetrical spatial anomalies with large reductions across the north-eastern part of the basin, which persisted into the following dry season. This added to drought stress in vegetation, already present owing to vapour pressure deficits at the leaf, resulting in a loss of GPP of 0.95 (0.69 to 1.20) PgC between October 2015 and March 2016 compared with the 2007-2014 average. Only 11% (10-12%) of the reduction in GPP was found in the (wetter) north-western part of the basin, whereas the north-eastern and southern regions were affected more strongly, with 56% (54-56%) and 33% (31-33%) of the total, respectively. Uncertainty on this anomaly mostly reflects the unknown rooting depths of vegetation.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

    Regional soil moisture monitoring network in the Raam catchment in the Netherlands - 2016-04 / 2017-04 (corrected)
    Benninga, H.F. ; Carranza, C.D. ; Pezij, M. ; Ploeg, M.J. van der; Augustijn, D.C.M. ; Velde, R. van der - \ 2018
    University of Twente
    agriculture - hydrology - soil moisture - soil temperature - unsaturated zone - water management
    Regional soil moisture monitoring network in the Raam catchment in the Netherlands - 2016-04 / 2017-04
    Benninga, H.F. ; Carranza, C.D. ; Pezij, M. ; Ploeg, M.J. van der; Augustijn, D.C.M. ; Velde, R. van der - \ 2017
    University of Twente
    agriculture - hydrology - soil moisture - soil temperature - unsaturated zone - water management
    The Raam soil moisture measurement network dataset contains soil moisture and soil temperature measurements for 15 locations in the Raam, which is a 223-km2 river catchment in the southeast of the Netherlands. The network monitors soil moisture in the unsaturated zone for different soil textures and land covers present in the area, and it covers the topographic gradient of the region. At each location we installed Decagon 5TM sensors at depths of 5 cm, 10 cm, 20 cm, 40 cm and 80 cm. The logging time interval is set on 15 minutes. The Raam network is operational since April 2016 and the measurements are on-going.
    Crop backscatter modeling and soil moisture estimation with support vector regression
    Stamenkovic, Jelena ; Ferrazzoli, Paolo ; Guerriero, Leila ; Tuia, Devis ; Thiran, Jean Philippe ; Borgeaud, Maurice - \ 2014
    In: International Geoscience and Remote Sensing Symposium (IGARSS). - Institute of Electrical and Electronics Engineers Inc. (International Geoscience and Remote Sensing Symposium (IGARSS) ) - ISBN 9781479957750 - p. 3228 - 3231.
    Crop backscatter - soil moisture - SVR

    In this paper, we used an improved version of the Tor Vergata radiative transfer model to simulate the backscattering coefficient for the L-band SAR signals over areas covered with vegetation. Fields of winter wheat, maize and sugar beet observed during the AgriSAR2006 campaign were investigated. For maize field, the presence of periodic soil surface profiles played an important role in determining the total backscattering. Soil moisture was also estimated using an inverse algorithm based on a supervised, non-parametric learning technique, v-SVR. v-SVR proved good generalization properties even with a limited number of training samples available. Dependence to the origin of training samples, as well as the influence of different features, was thoroughly considered.

    Retrieving high-resolution surface soil moisture by downscaling AMSR-E brightness temperature using MODIS LST and NDVI data
    Song, Chengyun ; Jia, Li ; Menenti, Massimo - \ 2014
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7 (2014)3. - ISSN 1939-1404 - p. 935 - 942.
    Downscaling - high resolution - microwave brightness temperature - soil moisture

    A method to retrieve soil moisture at high spatial resolution is presented in this paper. The method is based on soil moisture retrieval with passive brightness temperature. The method of retrieving land surface temperature with passive microwave is combined with the relationship between the microwave polarization difference index (MPDI) and normalized difference of vegetation index (NDVI) to obtain high-resolution microwave brightness temperature and soil moisture. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) 18.7-GHz brightness temperature at 25-km resolution is downscaled to 1-km using high-resolution MODIS visible/infrared (VIS/IR) data. High-resolution soil moisture is retrieved with the downscaled microwave brightness temperature using a single-channel algorithm (SCA) and the Qp model to deal with the influence of roughness. The method is applied to an area in northwest of China. The downscaled high-resolution soil moisture is tested with ground data collected at three sites within the Maqu monitoring network from July 1, 2008 to June 30, 2009. The trend of the time series of the downscaled soil moisture is similar to the ground measurements during this period with root mean-square error (RMSE) less than 0.12. The results show that the method is more suitable to moderate to drier soil conditions with bare surface or covered by sparse vegetation.

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