Global root traits (GRooT) database
Guerrero-Ramírez, Nathaly R. ; Mommer, Liesje ; Freschet, Grégoire T. ; Iversen, Colleen M. ; McCormack, M.L. ; Kattge, Jens ; Poorter, Hendrik ; Plas, Fons van der; Bergmann, Joana ; Kuyper, Thom W. ; York, Larry M. ; Bruelheide, Helge ; Laughlin, Daniel C. ; Meier, Ina C. ; Roumet, Catherine ; Semchenko, Marina ; Sweeney, Christopher J. ; Ruijven, Jasper van; Valverde-Barrantes, Oscar J. ; Aubin, Isabelle ; Catford, Jane A. ; Manning, Peter ; Martin, Adam ; Milla, Rubén ; Minden, Vanessa ; Pausas, Juli G. ; Smith, Stuart W. ; Soudzilovskaia, Nadejda A. ; Ammer, Christian ; Butterfield, Bradley ; Craine, Joseph ; Cornelissen, Johannes H.C. ; Vries, Franciska T. de; Isaac, Marney E. ; Kramer, Koen ; König, Christian ; Lamb, Eric G. ; Onipchenko, Vladimir G. ; Peñuelas, Josep ; Reich, Peter B. ; Rillig, Matthias C. ; Sack, Lawren ; Shipley, Bill ; Tedersoo, Leho ; Valladares, Fernando ; Bodegom, Peter van; Weigelt, Patrick ; Wright, Justin P. ; Weigelt, Alexandra - \ 2020
Global Ecology and Biogeography (2020). - ISSN 1466-822X
Belowground ecology - functional biogeography - macroecological studies - plant form and function - publicly-available database - root traits
Motivation: Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides ready-to-use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained: GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain: Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain: Data were recorded between 1911 and 2019. Major taxa and level of measurement: GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format: GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.
Erratum to: The sponge microbiome project
Moitinho-Silva, Lucas ; Nielsen, Shaun ; Amir, Amnon ; Gonzalez, Antonio ; Ackermann, Gail L. ; Cerrano, Carlo ; Astudillo-Garcia, Carmen ; Easson, Cole ; Sipkema, Detmer ; Liu, Fang ; Steinert, Georg ; Kotoulas, Giorgos ; McCormack, Grace P. ; Feng, Guofang ; Bell, James J. ; Vicente, Jan ; Björk, Johannes R. ; Montoya, Jose M. ; Olson, Julie B. ; Reveillaud, Julie ; Steindler, Laura ; Pineda, Mari Carmen ; Marra, Maria V. ; Ilan, Micha ; Taylor, Michael W. ; Polymenakou, Paraskevi ; Erwin, Patrick M. ; Schupp, Peter J. ; Simister, Rachel L. ; Knight, Rob ; Thacker, Robert W. ; Costa, Rodrigo ; Hill, Russell T. ; Lopez-Legentil, Susanna ; Dailianis, Thanos ; Ravasi, Timothy ; Hentschel, Ute ; Li, Zhiyong ; Webster, Nicole S. ; Thomas, Torsten - \ 2018
GigaScience 7 (2018)12. - ISSN 2047-217X
Genome-wide association study for bone strength in laying hens
Raymond, Biaty ; Johansson, Anna M. ; McCormack, Heather A. ; Fleming, Robert H. ; Schmutz, Matthias ; Dunn, Ian C. ; Koning, Dirk Jan De - \ 2018
Journal of Animal Science 96 (2018)7. - ISSN 0021-8812 - p. 2525 - 2535.
Bone strength - Genetic selection - Genome-wide association - Laying hens - Welfare
Bone fracture in egg laying hens is a growing welfare and economic concern in the industry. Although environmental conditions and management (especially nutrition) can exacerbate it, the primary cause of bone weakness and the resulting fractures is believed to have a genetic basis. To test this hypothesis, we performed a genome-wide association study to identify the loci associated with bone strength in laying hens. Genotype and phenotype data were obtained from 752 laying hens belonging to the same pure line population. These hens were genotyped for 580,961 SNPs, with 232,021 SNPs remaining after quality control. Each of the SNPs were tested for association with tibial breaking strength using the family-based score test for association. A total of 52 SNPs across chromosomes 1, 3, 8, and 16 were significantly associated with tibial breaking strength with the genome-wide significance threshold set as a corrected P value of 10e−5. Based on the local linkage disequilibrium around the significant SNPs, 5 distinct and novel QTLs were identified on chromosomes 1 (2 QTLs), 3 (1 QTL), 8 (1 QTL) and 16 (1 QTL). The strongest association was detected within the QTL region on chromosome 8, with the most significant SNP having a corrected P value of 4e−7. A number of candidate genes were identified within the QTL regions, including the BRD2 gene that is required for normal bone physiology. Bone-related pathways involving some of the genes were also identified including chloride channel activity, which regulates bone reabsorption, and intermediate filament organization, which plays a role in the regulation of bone mass. Our result supports previous studies that suggest that bone strength is highly regulated by genetics. It is therefore possible to reduce bone fractures in laying hens through genetic selection and ultimately improve hen welfare.
The sponge microbiome project
Moitinho-Silva, Lucas ; Nielsen, Shaun ; Amir, Amnon ; Gonzalez, Antonio ; Ackermann, Gail L. ; Cerrano, Carlo ; Astudillo-Garcia, Carmen ; Easson, Cole ; Sipkema, Detmer ; Liu, Fang ; Steinert, Georg ; Kotoulas, Giorgos ; McCormack, Grace P. ; Feng, Guofang ; Bell, James J. ; Vicente, Jan ; Björk, Johannes R. ; Montoya, Jose M. ; Olson, Julie B. ; Reveillaud, Julie ; Steindler, Laura ; Pineda, Mari Carmen ; Marra, Maria V. ; Ilan, Micha ; Taylor, Michael W. ; Polymenakou, Paraskevi ; Erwin, Patrick M. ; Schupp, Peter J. ; Simister, Rachel L. ; Knight, Rob ; Thacker, Robert W. ; Costa, Rodrigo ; Hill, Russell T. ; Lopez-Legentil, Susanna ; Dailianis, Thanos ; Ravasi, Timothy ; Hentschel, Ute ; Li, Zhiyong ; Webster, Nicole S. ; Thomas, Torsten - \ 2017
GigaScience 6 (2017)10. - ISSN 2047-217X
16S rRNA gene - Archaea - Bacteria - Marine sponges - Microbial diversity - Microbiome - Symbiosis
Marine sponges (phylum Porifera) are a diverse, phylogenetically deep-branching clade known for forming intimate partnerships with complex communities of microorganisms. To date, 16S rRNA gene sequencing studies have largely utilised different extraction and amplification methodologies to target the microbial communities of a limited number of sponge species, severely limiting comparative analyses of sponge microbial diversity and structure. Here, we provide an extensive and standardised dataset that will facilitate sponge microbiome comparisons across large spatial, temporal, and environmental scales. Samples from marine sponges (n = 3569 specimens), seawater (n = 370), marine sediments (n = 65) and other environments (n = 29) were collected from different locations across the globe. This dataset incorporates at least 268 different sponge species, including several yet unidentified taxa. The V4 region of the 16S rRNA gene was amplified and sequenced from extracted DNA using standardised procedures. Raw sequences (total of 1.1 billion sequences) were processed and clustered with (i) a standard protocol using QIIME closed-reference picking resulting in 39 543 operational taxonomic units (OTU) at 97% sequence identity, (ii) a de novo clustering using Mothur resulting in 518 246 OTUs, and (iii) a new high-resolution Deblur protocol resulting in 83 908 unique bacterial sequences. Abundance tables, representative sequences, taxonomic classifications, and metadata are provided. This dataset represents a comprehensive resource of sponge-associated microbial communities based on 16S rRNA gene sequences that can be used to address overarching hypotheses regarding host-associated prokaryotes, including host specificity, convergent evolution, environmental drivers of microbiome structure, and the sponge-associated rare biosphere.
Predicting the HMA-LMA status in marine sponges by machine learning
Moitinho-Silva, Lucas ; Steinert, Georg ; Nielsen, Shaun ; Hardoim, Cristiane C.P. ; Wu, Yu Chen ; McCormack, Grace P. ; López-Legentil, Susanna ; Marchant, Roman ; Webster, Nicole ; Thomas, Torsten ; Hentschel, Ute - \ 2017
Frontiers in Microbiology 8 (2017). - ISSN 1664-302X - 14 p.
16S rRNA gene - Marine sponges - Microbial diversity - Microbiome - Random forest - Symbiosis
The dichotomy between high microbial abundance (HMA) and low microbial abundance (LMA) sponges has been observed in sponge-microbe symbiosis, although the extent of this pattern remains poorly unknown. We characterized the differences between the microbiomes of HMA (n = 19) and LMA (n = 17) sponges (575 specimens) present in the Sponge Microbiome Project. HMA sponges were associated with richer and more diverse microbiomes than LMA sponges, as indicated by the comparison of alpha diversity metrics. Microbial community structures differed between HMA and LMA sponges considering Operational Taxonomic Units (OTU) abundances and across microbial taxonomic levels, from phylum to species. The largest proportion of microbiome variation was explained by the host identity. Several phyla, classes, and OTUs were found differentially abundant in either group, which were considered "HMA indicators" and "LMA indicators." Machine learning algorithms (classifiers) were trained to predict the HMA-LMA status of sponges. Among nine different classifiers, higher performances were achieved by Random Forest trained with phylum and class abundances. Random Forest with optimized parameters predicted the HMA-LMA status of additional 135 sponge species (1,232 specimens) without a priori knowledge. These sponges were grouped in four clusters, from which the largest two were composed of species consistently predicted as HMA (n = 44) and LMA (n = 74). In summary, our analyses shown distinct features of the microbial communities associated with HMA and LMA sponges. The prediction of the HMA-LMA status based on the microbiome profiles of sponges demonstrates the application of machine learning to explore patterns of host-associated microbial communities.
Species–area relationships are modulated by trophic rank, habitat affinity, and dispersal ability
Noordwijk, C.G.E. ; Verberk, W.C.E.P. ; Turin, H. ; Heijerman, Th. ; Alders, K. ; Deconinck, W. ; Hannig, K. ; Regan, E. ; McCormack, S. ; Brown, M.J. ; Remke, E. ; Siepel, H. ; Berg, M.P. ; Bonte, D. - \ 2015
Ecology 96 (2015)2. - ISSN 0012-9658 - p. 518 - 531.
abundance-occupancy relationships - ground beetles coleoptera - insect communities - calcareous grasslands - population-density - forest fragments - tropical forest - body-size - traits - conservation
In the face of ongoing habitat fragmentation, species–area relationships (SARs) have gained renewed interest and are increasingly used to set conservation priorities. An important question is how large habitat areas need to be to optimize biodiversity conservation. The relationship between area and species richness is explained by colonization–extinction dynamics, whereby smaller sites harbor smaller populations, which are more prone to extinction than the larger populations sustained by larger sites. These colonization– extinction dynamics are predicted to vary with trophic rank, habitat affinity, and dispersal ability of the species. However, empirical evidence for the effect of these species characteristics on SARs remains inconclusive. In this study we used carabid beetle data from 58 calcareous grassland sites to investigate how calcareous grassland area affects species richness and activity density for species differing in trophic rank, habitat affinity, and dispersal ability. In addition, we investigated how SARs are affected by the availability of additional calcareous grassland in the surrounding landscape. Beetle species richness and activity density increased with calcareous grassland area for zoophagous species that are specialists for dry grasslands and, to a lesser extent, for zoophagous habitat generalists. Phytophagous species and zoophagous forest andwet-grassland specialistswere not affected by calcareous grassland area. The dependence of species on large single sites increased with decreasing dispersal ability for species already vulnerable to calcareous grassland area. Additional calcareous grassland in the landscape had a positive effect on local species richness of both dry-grassland specialists and generalists, but this effect was restricted to a few hundred meters. Our results demonstrate that SARs are affected by trophic rank, habitat affinity, and dispersal ability. These species characteristics do not operate independently, but should be viewed in concert. In addition, species’ responses depend on the landscape context. Our study suggests that the impact of habitat area on trophic interactions may be larger than previously anticipated. In small habitat fragments surrounded by a hostile matrix, food chains may be strongly disrupted. This highlights the need to conserve continuous calcareous grassland patches of at least several hectares in size.
Good Practice in European Recreation Planning and Management
Kaae, B.C. ; Pröbstl, U. ; Wirth, V. ; Bell, S. ; McCormack, A. ; Elands, B.H.M. - \ 2010
In: Management of Recreation and Nature Based Tourism in European Forests / Pröbstl, U., Wirth, V., Elands, B.H.M., Bell, S., Berlin Heidelberg : Springer Verlag - ISBN 9783642031441 - p. 175 - 285.
This chapter describes a number of good practice examples in outdoor recreation and nature-based tourism collected from different European countries. The examples provide trans-national inspiration on how to solve some of the problems and challenges identified in the previous chapters. Furthermore, it includes a range of good examples of initiatives that enhance forest recreation experiences. The examples represent a selection from over 100 good practices examples submitted by participants of the COST action E33 “Forest Recreation and Nature based tourism”, working group “recreation planning and management”. Examples have been submitted by more than 20 countries across Europe.
|Glycerol generates turgor in rice blast
Jong, J.C. de; McCormack, B.J. ; Smirnoff, N. ; Talbot, N.J. - \ 1997
Nature 389 (1997). - ISSN 0028-0836 - p. 244 - 245.