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5,828 results for “Traits”
Data on soil variables (with plot IDs) and grassland species traits used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. Journal of Vegetation Science, 35, e13259. Available from: https://doi.org/10.1111/jvs.13259
<p>File <a href="../api/records/10983049/draft/files/Plot_IDs_990ua.txt/content" target="_blank" rel="noopener noreferrer">Plot_IDs_990ua.txt</a> contains the IDs of the 1-m2 plots used for the analysis of grassland vegetation data by Pillar, V.D. (2024) Trait divergence in plant community assembly is generated by environmental factor interactions. The plot data are stored in the sPlot database (PPBio South Brazilian Grassland Database).</p> <p>File <a href="../api/records/10983049/draft/files/E_990ua_21SoilVar.txt/content" target="_blank" rel="noopener noreferrer">E_990ua_21SoilVar.txt</a> contains data on soil variables evaluated in the 250 m transects, but here expanded to the 990 1-m2 plots (each transect was sampled using 10 1-m2 pots).</p> <p>File <a href="../api/records/10983049/draft/files/B_769spp_4t.txt/content" target="_blank" rel="noopener noreferrer">B_769spp_4t.txt</a> is the species trait database collected in the framework of several research projects in the Quantitative Ecology Lab (EcoQua) and Grassland Vegetation Studies Lab (LevCamp) of Universidade Federal do Rio Grande do Sul (UFRGS). Data gaps were filled by compiled from the TRY database and data imputation.</p> <p> </p> <p> </p>
Does fortune follow function? Exploring how consumer preferences drive the functional trait composition of the global songbird trade
<p>Defaunation and extinction undermine the resilience and functioning of ecological communities and ecosystems. Relative to other disturbances, overexploitation for the global wildlife trade presents a unique case of trait-based selection, as demand for specific individuals is often tied to unique morphological or aesthetic traits desired by consumers ("market traits"). Because evolutionary history leads to species that share both market and functional traits, we posit that non-random patterns of exploitation will result in non-random loss of functional diversity. <br>We applied a trait-based framework to the global songbird trade for 4616 species, 148 of which are plausibly threatened by the trade. We quantified select market traits, such as unique coloration and song quality, and ecological traits related to body size, diet, and foraging strategy to assess whether the trade disproportionately threatens particular functional groups. We additionally looked for patterns of association between market traits and functional traits to assess whether selection on certain market traits could drive selection on associated functional traits.<br>We found that overexploited birds are a distinct functional subset of the global songbird pool, with the trade disproportionately threatening large bodied, frugivorous, and seed eating birds. Across all songbirds, there were multiple non-random associations between market traits and functional traits, with the strongest associations observed among trade-threatened birds; this was consistent with our theory that consumer-driven selection on market traits could theoretically result in selection on functional traits. However, there was mixed evidence for this hypothesis at a global scale, suggesting that disproportionate threat to functional diversity may be more likely in regions where there is heavy demand for associated market traits. <br><em>Policy Implications:</em> Our results highlight the need for increased focus on the mechanistic drivers of trait-based selection on the consumer side of wildlife trade, and how patterns of overexploitation can systematically affect ecological communities and ecosystem services.</p>
Data from the journal article "Individual versus combined effects of warming, elevated CO2 and drought on grassland water uptake and fine root traits"
<p>This data file contains all data used in the aforementioned article (DOI: 10.1111/pce.15274). The data was obtained in a long-term multifactor global-change experiment (‘ClimGrass’) in a managed (three cuts, fertilized) C3 grassland near the central European Alps in Styria, Austria (47°29′44.6″N, 14°5′54.6″E). Grassland plots were exposed to six treatments: (i) ambient conditions (control; n = 8); (ii) drought (n = 4); (iii) warming (n = 3); (iv) elevated CO2 (n = 3), (v) future conditions (warming and elevated CO2; n = 3); and (vi) drought in future conditions (warming, elevated CO2 and drought; n = 4). The experiment was conducted during the growing seasons of 2017, 2019, and 2020. The aim was to determine how warming, elevated CO2 and drought individually and interactively affected root water uptake (RWU, calculated from soil water dynamics) as well as the corresponding mass and key traits (specific root length (SRL); specific root area (SRA); mean diameter) of newly produced fine roots (extracted using ingrowth cores) and biomass allocation (fine-root-to-shoot production ratios; R/S ratios). Treatment effects on RWU were studied across varying conditions of soil water content (SWC) and vapour pressure deficit (VPD), referred to as dryness conditions. Fine root characteristics were compared to the maximum hourly in-situ RWU observed. </p> <p>The following data is contained in this file (processed as described in the journal article and, importantly, in the supplementary information):<br>- data_SWC: SWC and precipitation, used to calculate RWU (resolution: hourly; figures: 1)<br>- data_RWU_daily: RWU for the main rooting horizon, fractions of total RWU across depth (resolution: daily; figures: 1, 2, 3)<br>- data_RWU_hourly: RWU for the main rooting horizon, SWC, VPD (resolution: hourly; figures: 1, 4, 5)<br>- data_FineRoots: Mass, traits (SRL, SRA, diameter) and maximum hourly RWU of newly produced fine roots across depth, R/S ratios (resolution: three samplings per growing season; figures: 6, 7)</p> <p>The metadata.xlsx file summarizes the contents of these datasets, including units and descriptions of the variables.</p> <p>Note below: the name of the project funded by the Austrian Academy of Sciences is ClimGrassHydro.</p>
Supplementary data: Effect of genotype by environment interaction (GEI) analysis for potato tuber yield and their quality traits in organic multi-environment domains of Poland
<p>Climate and raw data supplementary to the related publication in the journal Agriculture (ISSN 2077-0472).</p>
Pleiotropic Expression Quantitative Trait Loci Are Enriched in Enhancers and Transcription Factor Binding Sites and Impact More Genes
<p>This dataset comprises two files that accompany the article (link to be added upon publication).</p> <h2>1. gwas2eqtl_colocalization_full.tar.gz</h2> <p>This file contains the complete colocalization dataset generated using the code from the following GitHub repository: gwas2eqtl. This dataset is used as input for the pleiotropic eQTL analysis available at gwas2eqtl_pleiotropy, which produces the figures in the article.</p> <p><strong>File structure:</strong></p> <blockquote> <p>.<br>└── gwas417<br> └── coloc<br> ├── ebi-a-GCST000998<br> │ └── pval_5e-08<br> │ └── r2_0.1<br> │ └── kb_1000<br> │ └── window_1000000<br> │ ├── Alasoo_2018_ge_macrophage_IFNg+Salmonella.tsv<br> │ ├── Alasoo_2018_ge_macrophage_IFNg.tsv<br>...</p> </blockquote> <p>Each TSV file contains the following columns:</p> <blockquote> <p>chrom pos rsid ref alt eqtl_gene_id gwas_beta gwas_pval gwas_id eqtl_beta eqtl_pval eqtl_id PP.H4.abf SNP.PP.H4 nsnps PP.H3.abf PP.H2.abf PP.H1.abf PP.H0.abf coloc_variant_id coloc_region<br>1 109272258 rs4970834 C T ENSG00000168765 -0.12874.25001047052626e-09 ebi-a-GCST000998 -0.250697 0.0893351 Alasoo_2018_ge_macrophage_IFNg+Salmonella 0.108283426725895 0.0520205502224409 6 0.000552728832012655 2.09397277427793e-07 0.890881419183881 0.000282215860934432 1_109279544_G_A 1:108779544-109779543<br>1 109274968 rs12740374 G T ENSG00000168765 -0.103341 1.63998546891446e-09 ebi-a-GCST000998 -0.197397 0.172673Alasoo_2018_ge_macrophage_IFNg+Salmonella 0.108283426725895 0.0857585178966856 6 0.000552728832012655 2.09397277427793e-07 0.890881419183881 0.000282215860934432 1_109279544_G_A 1:108779544-109779543<br>1 109275216 rs660240 T C ENSG00000168765 0.1044492.78997299740827e-09 ebi-a-GCST000998 0.214165 0.139318 Alasoo_2018_ge_macrophage_IFNg+Salmonella 0.108283426725895 0.0557749486050279 6 0.000552728832012655 2.09397277427793e-07 0.890881419183881 0.000282215860934432 1_109279544_G_A 1:108779544-109779543<br>1 109275684 rs629301 G T ENSG00000168765 0.1054716.129993302249e-10 ebi-a-GCST000998 0.197397 0.172673 Alasoo_2018_ge_macrophage_IFNg+Salmonella 0.108283426725895 0.22229240584331 6 0.000552728832012655 2.09397277427793e-07 0.890881419183881 0.000282215860934432 1_109279544_G_A 1:108779544-109779543<br>1 109278889 rs602633 T G ENSG00000168765 0.1034352.15998134341707e-09 ebi-a-GCST000998 0.226329 0.102673 Alasoo_2018_ge_macrophage_IFNg+Salmonella 0.108283426725895 0.0782482718431504 6 0.000552728832012655 2.09397277427793e-07 0.890881419183881 0.000282215860934432 1_109279544_G_A 1:108779544-109779543<br>...</p> </blockquote> <p> </p> <p>The dataset provides colocalization statistics for GWAS-eQTL pairs, including posterior probabilities and variant annotations.</p> <h2>2. gwas2eqtl0.1.3.tsv.gz</h2> <p>This file is a filtered version of the colocalization dataset, refined based on cutoffs of PP.H4.abf ≥ 0.75 and SNP.PP.H4 ≥ 0. This subset is utilized in the gwas2eqtl web application for data visualization.</p> <p>Sample Columns:</p> <blockquote> <p>chrom pos19 pos38 cytoband rsid ref alt gwas_trait gwas_class gwas_beta eqtl_gene_symbol eqtl_beta eqtl_id eqtl_gene_id gwas_id gwas_pval eqtl_pval pp_h4_abf snp_pp_h4 tophits_variant_id nsnps<br>1 1163804 1228424 1p36.33 rs7515488 C T Inflammatory bowel disease Autoimmune dis. 0.0874308 ANKRD65 -0.175816 BrainSeq_ge_brain ENSG00000235098 ebi-a-GCST003043 2.85292266979231e-10 0.000841046 0.978425254116226 6.18454060493069e-12 1_1312114_T_C 3<br>1 1163804 1228424 1p36.33 rs7515488 C T Inflammatory bowel disease Autoimmune dis. 0.0874308 ANKRD65 -0.175816 BrainSeq_ge_brain ENSG00000235098 ieu-a-294 2.85292266979231e-10 0.000841046 0.974019788384412 7.52286530905187e-12 1_1312114_T_C 4<br>1 1163804 1228424 1p36.33 rs7515488 C T Inflammatory bowel disease Autoimmune dis. 0.0874308 ANKRD65 -0.293529 CommonMind_ge_DLPFC_naive ENSG00000235098 ebi-a-GCST003043 2.85292266979231e-10 2.30452e-06 0.953333690803618 6.9758581004380506e-15 1_1312114_T_C 6<br>1 1163804 1228424 1p36.33 rs7515488 C T Inflammatory bowel disease Autoimmune dis. 0.0874308 ANKRD65 -0.293529 CommonMind_ge_DLPFC_naive ENSG00000235098 ieu-a-294 2.85292266979231e-10 2.30452e-06 0.951092499048109 7.0876793540547e-15 1_1312114_T_C 7<br>1 1163804 1228424 1p36.33 rs7515488 C T Inflammatory bowel disease Autoimmune dis. 0.0874308 ANKRD65 -0.510549 FUSION_ge_adipose_naive ENSG00000235098 ebi-a-GCST003043 2.85292266979231e-10 1.2212e-06 0.974412793352836 1.70246427912903e-11 1_1312114_T_C 6</p> </blockquote> <p> </p> <p>This filtered dataset focuses on high-confidence colocalization events for functional exploration of genetic associations and regulatory mechanisms.</p>
Love thy neighbour? Tropical tree growth and its response to climate anomalies is mediated by neighbourhood hierarchy and dissimilarity in carbon and water related traits
<div> <div>Data and R code to reproduce all analyses, figures and tables for Krebber et al. 2024, Ecology Letters:<br>Love thy neighbour? Tropical tree growth and its response to climate anomalies is mediated by neighbourhood hierarchy and dissimilarity in carbon and water related traits. </div> <div> </div> <div>All analyses have been conducted and produced in the R environment (R version 4.1.2; R Core Team, 2021; RStudio Team, 2020). Bayesian hierarchical models have been run using the R package brms (Version 2.19.0; Bürkner, 2017). The data and R files containing the code to reproduce the results, figures and tables are described in the README file and code in more detailed is described in <em>RCode_xxx</em> files. Please note that the analyses are highly computational intensive and the scripts should be run on a high performance cluster (models and scripts running models and handeling model outputs presented here have been run with 16 cpus and with 50 - 100 GB of RAM). Packages needed are loaded at the beginning of each script. Please ensure that these and all their dependencies have been previously installed. The R code in the files has been carefully commented.</div> </div>
OctocoralTraits: a global database of trait information for octocoral species
<p>The OctocoralTraits_v2_2 ZIP file contains structured data and code to create all figures from the manuscript: “The Octocoral Trait Database: a global database of trait information for octocoral species”. The folder also contains the code used to validate the data descriptor.</p> <p>Specifically, the folder contains the following files:</p> <p>· Code.R – This is the annotated code used to create all figures in R. (v R studio; 2023.06.0+421)</p> <p>· OctocoralTraits_v2_2.csv – This is the first data realase of the octocoral trait database, used to create all figures of the manuscript.</p> <p>· sp_id.csv – This is a file containing the list of accepted octocoral species contained in the database</p> <p>· iqtree.tre – This is a tree object used to create a family-resolved tree of octocorals. It has been downloaded from McFadden et al. 2022. Revisionary systematics of Octocorallia (Cnidaria: Anthozoa) guided by phylogenomics</p> <p>· MEOW folder – A folder containing regional information from Spalding et al. 2007. Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas</p> <p>· Provinces_coord.csv: A file containing the coordinates of marine provinces, also derived from Spalding et al. 2007</p> <p>· Table_ids folder - A folder containing tables with information of the corresponding ids that appear in the file database.</p> <p>· Validation folder: A folder containing a Technical_validation.R file that was used to flag outliers and extreme outliers, duplicated rows and potential structural errors in the data (e.g., a given observation_id linked to more than one resource, species or location). </p>
Data on Trait diversity and spider community composition are associated with lower herbivory in young forest plantations
Open the record for dataset details and reuse information.
Experimental data on trait-mediated interactions in temperate forests of northeastern China
<p>The study area was a 30-ha (500 600 m) permanent forest plot (43°57.928′–43°58.214′N; 127°45.287′–127°45.790′E) in Jilin Province, China. Two species, <em>Pinus koraiensis</em> and <em>Ulmus laciniata</em>, were selected as focal trees at the neighborhood scale. In 2010, all healthy adult individuals of <em>P. koraiensis </em>and<em> U. laciniata </em>were selected as focal trees, covering a wide range of DBH (diameter at breast height, 1.3m) classes (10 cm<DBH<80 cm). We obtained a dataset containing measurements for 74 trees of <em>P. koraiensis </em>and 70 trees of <em>U. laciniata</em>. There were 2,109 neighboring trees sampled for the focal trees of <em>P. koraiensis</em> and 1,400 neighboring trees were neighbors for the focal trees of <em>U. laciniata</em>. We determined soil properties and topographic features as abiotic variables influencing the interactions between trees. The 30-ha plot was divided into 20 ×20 m grid cells. Soils samples were collected from evenly distributed cells at a depth of 10 cm at the four corners of these cells. Four soil properties (soil pH, soil water content, soil organic matter content, and soil nutrients) were measured. The topographic variables, including elevation, convexity, slope steepness, and aspect were calculated for each sample cell</p>
Birth season associates with multiple anthropometric traits in Estonian children
<p>Seasonal variation in maternal exposure to sunlight during pregnancy, which leads to a variation in vitamin D availability for a fetus, is a prevalent explanation for the variation of offspring traits with birth season. However, little consensus exists about the pregnancy period during which the fetus is most sensitive to maternal UV exposure and which offspring traits are most sensitive. We examined the association between 11 anthropometric traits and birth season/month among 18,459–23,876 Estonian children born in 1937–62. Nine traits showed seasonal patterns, which were generally weak, compared to the effects of family socioeconomic position (SEP). Clear nonlinear associations between offspring traits and birth month emerged only among children of mothers in non-manual professions. A possible explanation is that the growth of children in high-SEP families is more strongly buffered against any external exposures than the growth of children in low-SEP settings. For most traits, children born in spring/summer were larger than those born in autumn/winter. Hip width, trunk length and weight showed the most distinct seasonal patterns.</p> <p><strong> </strong></p>
Data & codes for "Changes in abundance and distribution of European forest bird populations depend on biome, ecological specialisation and traits"
<h1>1. Selection of European forest bird species and classification of their biome preferences</h1> <p>We selected all species that are related to forest and woodland based on two data sources: Storchová & Hořák (2018) and Tobias et al. (2022), resulting in 107 bird species studied (Data S1). We defined forest bird species as those using environments ranging from closed-canopy forests to more open-canopy woodlands (A. Lehikoinen & Virkkala, 2018; Storchová & Hořák, 2018; Tobias et al., 2022). We determined their biome specialisation using breeding distribution centroids and the overall breeding distribution of each of the species, using the global map of terrestrial ecoregions from Olson et al. (2001) and range data from European Breeding Bird Atlas 1 and 2 (Hagemeijer & Blair, 1997; Keller et al., 2020). We categorised species as Mediterranean, temperate, or boreal based on their predominant biogeographic region. We considered species commonly occurring over several biomes as “generalists”. For instance, we reclassified the two typically boreal species Glaucidium passerinum Linnaeus and Strix uralensis Pallas as “generalists” due to significant range expansions into central and southern Europe in recent decades, therefore no longer restricted to the boreal region. For the complete list of species, biome specialisation, traits, and specialisation indices, refer to Data S1.</p> <h1>2. Changes in abundance and distribution of European forest bird species</h1> <p>We assessed long-term changes in European forest bird populations through two approaches: (i) changes in estimated total European-level species abundance over a 40-year timeframe; and (ii) changes in species spatial distribution over a 30-year timeframe (Fig. 1).</p> <p>We utilized the estimated trends in European-level population size (i.e., the total number of individuals) for each common native European bird species from 1980 to 2017, as reported by Burns et al. (2021). Three species out of the 107 studied forest species were missing in the original manuscript and we used data generated with the same method from 1980 to 2018 from the European assessment, Article 12 (https://nature-art12.eionet.europa.eu/article12/). These abundance trends were calculated by Burns et al. (2021) using multi-sourced annual times series. For each species, they gathered population estimates and trends from each European country as well as European Union (EU)-level population trends. They analysed these data with a Bayesian hierarchical model to reconstruct EU-level smoothed species population time series. The model outputs include an average annual rate of abundance change and an associated 95% credible interval (Burns et al., 2021). Therefore, we did not directly use the average annual rate of abundance change, as this would have led us to consider species with low uncertainty as similar to those with high uncertainty. To account for the uncertainty, we categorised species as (i) declining, i.e., annual rates below one, (ii) increasing, i.e., annual rates above one and (iii) stable, i.e., annual rate whose 95% CI overlap one, i.e., no significant change. To better acknowledge the magnitude of the abundance change, significant changes with rates below 0.98 were labelled as “strongly declining” (i.e., 6.5% of the 107 species), while those above 1.02 were labelled as “strongly increasing” (i.e., 11% of the 107 species). To evaluate the sensitivity of the decision to categorised abundance change data, we also analysed abundance trend as continuous variable (see Supporting Information Fig. S8).</p> <p>To determine changes in species distributions, we used a comparison of species distributions between two periods (i.e., 1985-1988 and 2013-2017) using the European Breeding Bird Atlas 1 and 2 (EBBA 1 & 2; Hagemeijer & Blair, 1997; Howard et al., 2023; Keller et al., 2020). Howard et al. (2023) provided calculations of observed colonisation and extinction areas at a 50 x 50 km resolution across Europe. We measured changes in range as the difference between colonisations and extinctions of each species, with negative values indicating contracting ranges and positive values indicating expanding ranges. Additionally, we calculated the shift in the centre of gravity of the distribution range between the two periods, as a distance (km) along the south-north gradient for each species (Howard et al., 2023).</p> <h1>3. Trait and specialisation data for European forest bird species</h1> <p>We extracted data for six functional traits from several sources (Table 1). (i) The species temperature index (STI)represents the long-term average temperature within the species’ breeding range (A. Lehikoinen et al., 2021). (ii) Diet data during the breeding season were obtained from Storchová & Hořák (2018), classifying species into binary variables as vertebrate carnivorous, invertebrate carnivorous, and herbivores (combining the leaf and seed eaters). Storchová & Hořák (2018) classified species into a diet category when the corresponding food resource represented at least 10% of the species diet throughout the breeding season. Therefore, one species can be in several categories (i.e., omnivores). (iii) We obtained nesting site data from Pearman et al. (2014), classifying species into binary variables as ground nesters, tree hole nesters, or elevated nesters (> 1 m in a tree or shrub). We also included data on (iv) species dependence on old-growth forests (Data S1; mostly from Fraixedas et al. (2015) and Mönkkönen et al. (2014), if present on both references, we classified them as “1” and if only in one reference as “0.5”), (v) migration distance (Howard et al., 2023), and (vi) body mass (Tobias et al., 2022).</p> <p>Finally, we extracted and developed seven species specialisation indices. (i) We used an overall specialisation index based on multiple traits (i.e., temperature, diet, foraging behaviour and substrate, habitat, and nesting site), and (ii) a nesting specialisation index, both obtained from Morelli et al. (2019). Both indices represent species specialization based on the dispersion of trait preferences for each species: e.g., nesting specialism equal 0 for species that nest in all habitat type and equal 1 for species that nest in only one habitat type). They are both calculated using the Gini index of inequality, which measures overall dispersion across, e.g., all traits for the overall specialization, based on data from Pearman et al. (2014) and Storchová & Hořák (2018). For additional information, see Morelli et al. (2019). We also used (iii) the diet specialisation index, (iv) the species distribution range during the breeding season (hereafter “breeding range area”) and (v) the climatic niche breadth from Reif et al. (2016). The diet specialisation index was calculated as the coefficient of variation for diet preferences for each species, where high values denotes specialized species (Reif et al., 2016). The breeding range area was evaluated as the number of 50-km squares in the distribution maps in Europe occupied by each species during the reproduction period, and is based on EBBA 1 (Hagemeijer & Blair, 1997). The climatic niche breadth was calculated as the difference between the 5% hottest and the 5% coldest mean temperature between April and June in which each species occurs, using EBBA 1 (Hagemeijer & Blair, 1997; Reif et al., 2016).</p> <p>Additionally, (vi) we calculated a broadleaf forest specialisation index based on binary forest habitat preferences (Storchová & Hořák, 2018), assigning values of one for species found only in broadleaf forests; zero for those in coniferous forests, and 0.5 for those found in both. Lastly, (vii) we created a forest specialisation index based on the species habitat preferences (Storchová & Hořák, 2018). The forest specialisation index was calculated as the mean of species affinity across habitats. We used increasing habitat weights along a gradient of tree dominance: open habitats as 1, shrubland as 1.5, woodland as 2 (i.e., species associated with habitats structured by trees in lower density than in forest), forest generalist (found in both coniferous and broadleaf dense forests) as 3, and forest specialist (found only either in coniferous or broadleaf dense forests) as 4. For instance, the index value for species occurring either in shrubland, woodland or both broadleaf and coniferous forests is 2.167.</p> <h1>4. Data analysis</h1> <p>Data analyses were conducted with R software version 4.4.1. (R Core Team, 2024). Given the non-independence of species due to their genetic relatedness, we accounted for interspecific phylogenetic distance in all models. We constructed the phylogenetic tree for the 107 European forest bird species using ‘rotl’ and ‘ape’ R-packages (Michonneau et al., 2022; Paradis et al., 2023). We used rotl as an interface with the "Open Tree of Life", employing tol_induced_subtree R-function to generate the phylogenetic tree and compute.brlen R-function to set branch lengths using Grafen’s computation. We generated separate phylogenetic trees for boreal (17), temperate (15), Mediterranean (16) and “generalist” (59) species to perform biome-specific analysis (see Supplementary Information, Figs. S1 & S2).</p> <p>To investigate the effects of functional traits and specialisation indices on abundance, range changes, and distribution shift, we used two regression methods. All methods were based on the relationships between a measure of change and a functional trait or specialisation index. Our sample unit is an individual forest bird species (i.e., one value for each species, either abundance or range change, or distribution shift). Abundance change was a categorical variable (i.e., strong decline – decline – stable – increase – strong increase), while range change (i.e., difference between colonisation and extinction) and distribution shift (i.e., south-north shift) were continuous variables. Therefore, to study abundance changes, we used proportional-odds linear mixed effects model using (Phylo)clmm R-function from the ‘ordinal’ R-package (Christensen, 2022). Interspecific phylogenetic relatedness was included as a random effect, reflecting the correlation between species based on phylogenetic distances (see also Hagge et al. (2021) and Seibold et al. (2015)). For distribution changes, we employed phylogenetic generalised least squares regression (PGLS) using the gls R-function from the ‘nlme’ R-package (Pinheiro et al., 2023). The phylogenetic correlation structure was integrated into PGLS using Pagel’s lambda parameter (λ; Pagel (1999)) a widely used measured of phylogenetic signal strength (see, e.g., Hagge et al., 2021; Triviño et al., 2013).</p> <p>Furthermore, we included latitude, a key driver of bird communities at broad scales (Luoto et al., 2007), as a fixed covariable (centroid latitude of the species’ breeding distribution) in all global models (i.e., species from all biomes together), except for the STI model due to strong correlation. For biome-specific analysis, we included latitude only in boreal species models for range change and distribution shift, as it significantly improved model fit (ΔAIC < -2). We did not add latitude for models specific to temperate, Mediterranean, and generalist species since it did not improve model fits (ΔAIC > -2). Additionally, we included breeding range area in range change and distribution shift models, assuming that species with larger ranges would exhibit larger shifts. We scaled predictors to a mean of 0 and standard deviation of 1 to facilitate effect size comparisons. We adjusted p-values using the Holm method (for n=3) to account for multiple testing of traits and specialisation indices on three response variables.</p>
Morphological trait matching in plant–Hymenoptera and plant–Diptera mutualisms across an elevational gradient
<p>Morphological trait-matching and species abundance are thought to be the main factors affecting the frequency and strength of mutualistic interactions. However, the relative importance of trait-matching and species abundance in shaping species interactions across environmental gradients remains poorly understood, especially for plant–insect mutualisms involving generalist species.</p> <p>Here, we characterised variation in species and trait composition and the relative importance of trait-matching and species abundance in shaping plant–Hymenoptera and plant–Diptera mutualisms in four meadows across an elevational gradient (2,725–3,910 m) in Yulong Snow Mountain, Southwest China. We also evaluated the effects of morphological traits of flower visitors and plant composition on their foraging specialisation (d' and normalised degree).</p> <p>There was a high degree of dissimilarity in the composition of Hymenoptera and Diptera visitors and their visited plants between communities. This variation was mainly driven by the spatial replacement of species. Both for plant–Hymenoptera and plant–Diptera networks, trait-matching between nectar tube depth and proboscis length was a stronger predictor of the interactions between temporally co-occurring plants and flower visitors than species abundance. Fourth-corner analyses revealed statistically significant trait-matching between nectar tube depth and proboscis length in plant–Hymenoptera networks at all sites, suggesting that Hymenoptera consistently foraged on plant species with nectar tube depths matching their proboscis lengths. By contrast, significant trait-matching in plant–Diptera networks was only observed at the two lower elevation sites. The species-level specialisation d' of flower visitors increased significantly as the proboscis length and the difference in nectar tube depth between the plant community and the plants visited by flower visitors increased.</p> <p>Our results highlight that the importance of trait-matching in shaping pairwise interactions and niche partitioning depends on the specific features (e.g. species composition and trait availability) of the plant-pollinator system. For specialised plant-Hymenoptera systems, trait-matching is an important determinant of species interactions, whereas for generalist plant-Diptera systems, trait-matching is relatively unimportant.</p>
Inter- and intraspecific selection in alien plants: how population growth, functional traits and climate responses change with residence time
<p><strong>Aim: </strong>When alien species are introduced to new ranges, climate or trait mismatches may initially constrain their population growth. However, inter- and intraspecific selection in the new environment should cause population growth rates to increase with residence time. Using a species-for-time approach, we test whether with increasing residence time (a) negative effects of climatic mismatches between the species' new and native range on population growth weaken, and (b) functional traits converge towards values that maximize population growth in the new range.</p> <p><strong>Location:</strong> Germany.</p> <p><strong>Time period: </strong>12,000 years BP to present.</p> <p><strong>Major taxa studied: </strong>46 plant species of the Asteraceae family.</p> <p><strong>Methods:</strong> We set up a common-garden mesocosm-experiment using annual plant species with a wide range of residence times (7-12,000 years) and followed their population dynamics over two years. We calculated climatic distance between the common garden and the species' native range. We also measured key functional traits of each species to analyse trait-demography relationships and test trait convergence with increasing residence time.</p> <p><strong>Results: </strong>We found no support for the hypothesis that negative effects of climatic mismatches on population growth weaken with residence time. However, seed mass had a clear negative effect on population growth. As expected under such strong directional selection between or within species, increasing residence time led seed mass to converge to low values that increase population growth. Accordingly, population growth tended to increase with residence time.</p> <p><strong>Main conclusions: </strong>We identify trait but not climatic mismatches as important constraints on population growth of invaders. Understanding how inter- and intraspecific selection shapes functional traits of alien species should improve the predictability of future invasions and help understanding limits to the population growth and spread of invaders already present. In a broader context, this study contributes to the conceptual integration of invasion biology with community, functional, and population ecology.</p>
Data and files for: Decoupling cooperation and punishment in humans shows that punishment is not an altruistic trait
<p>Economic experiments have suggested that cooperative humans will altruistically match local levels of cooperation ('conditional cooperation') and pay to punish non-cooperators ('altruistic punishment'). Evolutionary models have suggested that if altruists punish non-altruists this could favour the evolution of costly helping behaviours (cooperation) among strangers. An often-key requirement is that helping behaviours and punishing behaviours form one single, conjoined trait ('strong reciprocity'). Previous economics experiments have provided support for the hypothesis that punishment and cooperation form one conjoined, altruistically motivated, trait. However, such a conjoined trait may be evolutionarily unstable, and previous experiments have confounded a fear of being punished with being surrounded by cooperators, two factors that could favour cooperation. Here, we experimentally decouple the fear of punishment from a cooperative environment and allow cooperation and punishment behaviour to freely separate (420 participants). We show, that if a minority of individuals are made immune to punishment, they (1) learn to stop cooperating on average despite being surrounded by high levels of cooperation, contradicting the idea of conditional cooperation; and (2) often continue to punish, 'hypocritically', showing that cooperation and punishment do not form one, altruistically motivated, linked trait.</p>
Vertical profiles of leaf photosynthesis and leaf traits, and soil nutrients in two tropical rainforests in French Guiana before and after a three-year nitrogen and phosphorus addition experiment
<p>We provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two three-year, large-scale fertilisation experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients, in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C)-nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests.</p>
Probabilistic inference of the genetic architecture of functional enrichment of complex traits
<p>We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only $\leq$ 10\% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having >95% probability of contributing >0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.</p>
Data from: Functional identity regulates aboveground biomass better than trait diversity along abiotic conditions in global forest metacommunities
<p>Although several studies have identified the effects of functional trait diversity (FTD) and/ or identity, i.e., the community-weighted mean (CWM) of a trait, on aboveground biomass (AGB) along abiotic conditions, these effects on AGB in global forest metacommunities are still largely unexplored. Here, we modelled the effects of abiotic (i.e., climate, soil and plot physical conditions) and biotic [i.e., FTD, CWM of conservative traits (CWMCT), CWM of acquisitive traits (CWMAT), and functional dominance (FunDom; based on CWM of plant maximum height or diameter)] factors on AGB in 76 forest metacommunities (from 24 studies). Using multiple linear regression models and piecewise structural equation modeling (pSEM), we tested the hypothesis that both abiotic and biotic factors regulate AGB, but that the mass ratio mechanism underpins AGB of metacommunities in global forests better than the niche complementarity mechanism. We found that abiotic and biotic factors contributed 45.39% and 54.07%, respectively, to the explained variance in AGB (<i>R<sup>2</sup></i> = 0.59), and as such, abiotic factors shaped FTD (<i>R<sup>2</sup></i> = 0.42 to 0.48), CWMCT (<i>R<sup>2</sup></i> = 0.33 to 0.36), CWMAT (<i>R<sup>2</sup></i> = 0.27 to 0.33), and FunDom (<i>R<sup>2</sup></i> = 0.59 to 0.61) through divergent effect sizes and directions. The final best-fitted pSEM showed that FunDom increased (<i>β</i> = 0.49) but CWMCT (<i>β</i> = -0.35) and CWMAT (<i>β</i> = -0.11) decreased AGB (<i>R<sup>2</sup></i> = 0.52) as compared to the negligible effect of FTD (<i>β</i> = 0.04). This study supports the mass ratio effect, specifically the overruling role of tall-stature or dominant trees on AGB, at a macroecological scale, and hence, suggests that a suitable species' functional strategy is important to promote carbon sequestration in forest metacommunities that underpins human well-being. We expect that our study will advance the field of biodiversity – ecosystem functioning at a macroecological scale by using the metacommunity concept and approach.</p>
Specimens from Brand et al. 2021, "Large-scale phylogenomics of the genus Macrostomum (Platyhelminthes) reveals cryptic diversity and novel sexual traits"
<p>The deposited folders contain image and video material of free-living flatworm specimens that were documented in vivo. These data support the following publication:</p> <p>Jeremias N. Brand, Gudrun Viktorin, R. Axel W. Wiberg, Christian Beisel, Lukas Schärer.<br> Large-scale phylogenomics of the genus<em> Macrostomum</em> (Platyhelminthes) reveals cryptic diversity and novel sexual traits.<br> Molecular Phylogenetics and Evolution. Volume 166. 2022. <a href="https://doi.org/10.1016/j.ympev.2021.107296">https://doi.org/10.1016/j.ympev.2021.107296</a></p> <p>For more information about these specimens see also http://macrostomorpha.info.</p>
Identifying traits that enable lizard adaptation to different habitats
<p><b>Aim: </b>Species adapt differently to contrasting environments, such as open habitats with sparse vegetation and forested habitats with dense forest cover. We investigated colonization patterns in the open and forested environments in the Diagonal of Open Formations and surrounding rain forests (i.e., Amazon and Atlantic Forest) in Brazil, tested whether the diversification rates were affected by the environmental conditions, and identified traits that enabled species to persist in those environments.</p> <p><b>Location: </b>South America, Brazil.</p> <p><b>Taxon: </b>Squamata, Lizards</p> <p><b>Methods: </b>We estimated ancestral ranges to identify range shifts relative to traditional open and forested habitats for all species. We used phylogenetic information and the current distribution of species in open and forested environments. To evaluate whether these environments influenced species diversification, we tested 12 models using a Hidden Geographic State Speciation and Extinction analysis. Finally, we combined phylogenetic relatedness and species traits in a machine learning framework to identify the traits permitting adaptation in those contrasting environments.</p> <p><b>Results: </b>We identified 41 total transitions between open and forested habitats, of which 80% were from the forested habitats to the open habitats. Widely distributed species had lower speciation and extinction rates than species in forested or open habitats, with the latter having the higher overall rates. Mean body temperature, microhabitat, female SVL, and diet were identified as putative traits that enabled adaptation to different environments, and phylogenetic relatedness was an important predictor of species occurrence.</p> <p><b>Main conclusions:</b> Our results indicate that transitions from forested to open habitats are most common. The combination of phylogenetic reconstruction of ancestral distributions and the machine learning framework enables us to integrate organismal trait data, environmental data, and evolutionary history in a manner that could be applied on a global scale.</p>
Termite trait data from: Continental-scale shifts in termite diversity and nesting and feeding strategies
<p>Typically, termites are treated as a single guild, which ignores important internal diversity, including diverse feeding and nesting traits. These termite traits are crucial for both ecosystem-level fluxes and trophic webs, with implications for vertebrate species. Despite their ecological importance, the large-scale distribution of termite feeding and nesting traits and the relationship with termite diversity is largely unknown. We investigated whether functional diversity, species richness, and feeding (wood, litter, grass, dung) and nesting trait (aboveground mound, belowground nest, inside tree or outside tree nest) distributions of termites were climatically control. To address this gap, we assembled a continental-scale database of termite traits and occurrence in Australia and modelled termite nesting and feeding traits in response to macroclimate. Functional richness and evenness increased primarily with temperature. Australia showed multiple hotspots of termite diversity with each hotspot showing a distinct guild composition. The large-scale distribution of nesting traits showed that aboveground nesting species were the most common nesting guild in the dry and wet tropics while belowground nesting dominated in seasonally cold arid environments, demonstrating a strong climatic control on nesting strategy. Given their large biomass and many interactions with other species, the macro-ecology of termite traits may be especially important in predicting shifts in other species' distributions at continental and global scales.</p>
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.