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251 results for “ecological traits”
Fig. 3 in Adaptations, life-history traits and ecological mechanisms of parasites to survive extremes and environmental unpredictability in the face of climate change
Fig. 3. Flow chart outlining factors that can influence the response of parasites to climate change.
Table 1 in Review Of Bryophyte Functional Traits In Ecological Studies
<p><b>Table 1.</b> Overview of main bryophyte functional traits according to van Zuijlen et al. (2023).</p><table><tbody><tr><th>Biological traits</th><th><b>Ecological traits</b></th></tr></tbody><tbody><tr><th>generation length</th><td>aquatic species</td></tr><tr><th>growth form</th><td>epiphytic species or not</td></tr><tr><th>life form</th><td>how strong species are bound to forest habitats</td></tr><tr><th>life strategy</th><td>major habitat class “Artificial/Terrestrial”</td></tr><tr><th>peristome</th><td>major habitat class “Forest”</td></tr><tr><th>permanent protonema</th><td>major habitat class “Grassland”</td></tr><tr><th>rhizoids</th><td>major habitat class “Rocky areas”</td></tr><tr><th>r or K strategy</th><td>major habitat class “Shrubland”</td></tr><tr><th>length of the seta</th><td>major habitat class “Wetlands”</td></tr><tr><th>sexual condition</th><td>indicator value – moisture</td></tr><tr><th>sporophyte frequency</th><td>indicator value – heavy metal tolerance</td></tr><tr><th>shoot size</th><td>indicator value – continentality</td></tr><tr><th>spore size</th><td>indicator value – light</td></tr><tr><th>deciduous branches or stem tips</th><td>indicator value – nutrients</td></tr><tr><th>bulbils</th><td>indicator value – salt tolerance</td></tr><tr><th>gemmae</th><td>indicator value – temperature</td></tr><tr><th>deciduous leaves or leave fragments</th><td>substrate class: dead animal carcass or dung</td></tr><tr><th>tubers</th><td>substrate class: bark of living phanerophyte</td></tr><tr><th>size of vegetative propagule</th><td>substrate class: epiphytic on non­woody living substrate</td></tr><tr><th></th><td>substrate class: rock</td></tr><tr><th></th><td>substrate class: soil</td></tr><tr><th></th><td>substrate class: deadwood</td></tr></tbody></table>
Data from: N-dimensional hypervolumes in trait-based ecology: does occupancy rate matter?
<p>Many methods for estimating functional diversity of biological communities rely on measuring geometrical properties of n-dimensional hypervolumes in a trait space. To date, these properties are calculated from individual hypervolumes or from their pairwise combinations. Our capacity to detect functional diversity patterns due to the overlap of multiple hypervolumes is thus limited.</p> <p>Here, we propose a new approach for estimating functional diversity from a set of hypervolumes. We rely on the concept of occupancy rate, defined as the mean or absolute number of hypervolumes enclosing a given point in the trait space. Furthermore, we describe a permutation test to identify regions of the trait space in which the occupancy rate of two sets of hypervolumes differs.</p> <p>We illustrate the utility of our approach over existing methods with two examples on aquatic macroinvertebrates. The first example shows how occupancy rate relates to the stability of trait space utilisation due to increased flow intermittency and allows the identification of taxa in regions of the trait space with low occupancy rates. The second example shows how the permutation test based on occupancy rates can detect differences in trait space utilisation due to river morphology variation even with a high degree of overlap among input hypervolumes.</p> <p>Our newly developed approach is particularly suitable in functional diversity analysis when investigating patterns of overlap among multiple hypervolumes. We thus emphasise the need to consider analyses based on occupancy rate into functional diversity estimation.</p>
Data from: A framework to apply trait-based ecological restoration at large scales
<p>R scripts and data to run the proposed framework at</p> <p>Coutinho, A. G., Carlucci, M. B., Cianciaruso, M. V. (2023) A framework to apply trait-based ecological restoration at large scales. Journal of Applied Ecology.</p>
Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits
<p>Dataset and R scripts used in the publication "Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits", PeerJ</p>
Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
<p>Species declines and extinctions characterize the Anthropocene. Determining species vulnerability to decline, and where and how to mitigate threats, are paramount for effective conservation. We hypothesized that species with shared ecological traits also share threats, and therefore may experience similar population trends. Here, we used a Bayesian modeling framework to test whether phylogeny, geography, and 22 ecological traits predict regional population trends for 380 North American bird species. Groups like blackbirds, warblers, and shorebirds, as well as species occupying Bird Conservation Regions at more extreme latitudes in North America, exhibited negative population trends, while groups such as ducks, raptors, and waders, as well as species occupying more inland Bird Conservation Regions, exhibited positive trends. Specifically, we found that in addition to phylogeny and breeding geography, multiple ecological traits contributed to explaining variation in regional population trends for North American birds. Furthermore, we found that regional trends and the relative effects of migration distance, phylogeny, and geography differ between shorebirds, songbirds, and waterbirds. Our work provides evidence that multiple ecological traits correlate with North American bird population trends, but that the individual effects of these ecological traits in predicting population trends often vary between different groups of birds. Moreover, our results reinforce the notion that variation in avian population trends is controlled by more than phylogeny and geography, where closely-related species within one region can show unique population trends due to differences in their ecological traits. We recommend that regional conservation plans, i.e. one-size-fits-all plans, be implemented only for bird groups with population trends under strong phylogenetic or geographic controls. We underscore the need to develop species-specific research and management strategies for other groups, like songbirds, that exhibit high variation in their population trends and are influenced by multiple ecological traits.</p>
Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)
<p>Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)</p> <p>DATA DOI: https://doi.org/10.5281/zenodo.8322080</p> <p>Associated article DOI: https://doi.org/10.1002/ece3.10588</p> <p>Ryan C. Burner, Jorg Stephan, Juha Siitonen, Tord Snall, et al. 2023</p> <p>ryan.c.burner@gmail.com</p> <p>This data release contains data files needed to run the Hmsc models described in the associated publication. It is a subset of the complete beetle capture and environmental covariate dataset maintained by Juha Siitonen (see associated manuscript for references to prior publications). It contains the following four files:</p> <p>1) Species_detections.csv</p> <p>This site_year x species table has detection/non-detection (1/0) values for each species at each site_year. Beetles were trapped at about 142 sites in Finland forests. Includes only beetle species (n = 212) which are considered saproxylic and which were detected at >=5 sites in the dataset, and for which trait information was available. Species names are as originally identified in the source dataset (see early publications by Juha Siitonen). Row names ('Row_ID'), which consist of [site]_[year], correspond to 'Row_ID' in the 'Site_covariates.csv' file. Species (column) names correspond to species row naes in 'Species_traits.csv'</p> <p>2) Site_covariates.csv</p> <p>This table has one row for each 'Row_ID' (n = 142) corresponding to rows in 'Species_data.csv'. Covariate columns have been scaled and centered for modeling. Columns are as follows:</p> <p>rowID - [site]_[year] of sampling<br> Year - year of sampling<br> Site - site name/number<br> climID - unique ID for each grid cell from which climate data were extracted<br> lat_WGS84 - latitude (WGS84)<br> lon_WGS84 - longitude (WGS84)<br> VD10 - scaled and centered total pooled volume of local standing and fallen dead trees (originally in m3/ha, before scaling) with a minimum diameter of 10 cm, estimated using transects<br> agedomin - scaled and centered mean age of the five oldest trees in the stand<br> OldFor_1km - scaled and centered volume of living wood in those forests older than 100 years within a one km radius around each site<br> MeanTemp - scaled and centered mean temperature during the trapping period, from mean of all ERA5 hourly estimates of 2m temperature (see manuscript for details)<br> TotalPrecip - scaled and centered total precipitation during the trapping period, from ERA5 summed across all hourly estimates of total precipitation (see manuscript for details)<br> globRad_WHm2 - scaled and centered total solar radiation during the trapping period, summed across all daily values, based on site slope and aspect, calculated using GIS (see manuscript for details). Units were Wh/m2 prior to scaling and centering.<br> log_Nr_traps - scaled and centered log-transformed number of traps used at each capture site </p> <p><br> 3) Species_traits.csv</p> <p>Trait data, based on trait values in Hagge et al. (2021 - see manuscript for full reference), for beetle species included in model (see species data information, above). In some cases traits are from synonyms used in Hagge that differ from taxonomy of this dataset. Traits have been scaled and centered. Row names are species names that match columns in 'Species_detections.csv'. Columns as follows:</p> <p>wing_length - scaled and centered (log(wing length divided by body length))<br> wing_load - scaled and centered (log(mass / wing area / body length))<br> wing_aspect - scaled and centered (log(wing aspect ratio)</p> <p><br> 4) Phylotree.csv</p> <p>A phylogenetic tree for the species in this dataset, written in the Newick (also known as New Hampshire) format. The tree is based on the species-level insect tree in Chesters et al. (2017) (see manuscript for full citation) but has missing species added randomly to the correct genus (when present) or family or (occassionally) order.</p>
Data from: Inferring ecological selection from multidimensional community trait distributions along environmental gradients
<p>Understanding the drivers of community assembly is critical for predicting the future of biodiversity and ecosystem services. Ecological selection ubiquitously shapes communities by selecting for individuals with most suitable trait combinations. Detecting selection types on key traits across environmental gradients and over time has the potential to reveal underlying abiotic and biotic drivers of community dynamics. Here we present a model-based predictive framework to quantify multidimensional trait distributions of communities (community trait niches), which we use to identify ecological selection types shaping communities along environmental gradients. We apply the framework to over 3600 boreal forest understory plant communities with results indicating that directional, stabilizing, and divergent selection all modify community trait niches and that the selection type acting on individual traits may change over time. Our results provide novel and rare empirical evidence for divergent selection within a natural system. Our approach provides a framework for identifying key traits under selection and facilitates the detection of processes underlying community dynamics.</p>
Data from: Inferring ecological selection from multidimensional community trait distributions along environmental gradients
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Pitfalls of ignoring trait resolution when drawing conclusions about ecological processes
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Code for: A century of wild bee sampling: historical data and neural network analysis reveal ecological traits associated with species loss
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Data from: Ecological trait divergence over evolutionary time underlies the origin and maintenance of tropical spider diversity
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Data from: N-dimensional hypervolumes in trait-based ecology: does occupancy rate matter?
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Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
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Species traits modulate ecological release in island red devil spiders (Araneae: Dysderidae)
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Data from: Change in sexual signalling traits outruns morphological divergence across an ecological gradient in the post‐glacial radiation of the songbird genus Junco
<p>The relative roles of natural and sexual selection in promoting evolutionary lineage divergence remains controversial and difficult to assess in natural systems. Local adaptation through natural selection is known to play a central role in promoting evolutionary divergence, yet secondary sexual traits can vary widely among species in recent radiations, suggesting that sexual selection may also be important in the early stages of speciation. Here we compare rates of divergence in ecologically relevant traits (morphology) and sexually selected signaling traits (coloration) relative to neutral structure in genome-wide molecular markers, and examine patterns of variation in sexual dichromatism to explore the roles of natural and sexual selection in the diversification of the songbird genus <i>Junco </i>(Aves: Passerellidae). Juncos include divergent lineages in Central America and several dark-eyed junco (<i>J. hyemalis</i>) lineages that diversified recently as the group recolonized North America following the last glacial maximum (c.a. 18,000 years ago). We found an accelerated rate of divergence in sexually selected characters relative to ecologically relevant traits. Moreover, sexual dichromatism measurements suggested a positive relationship between the degree of color divergence and the strength of sexual selection when controlling for neutral genetic distance. We also found a positive correlation between dichromatism and latitude, which coincides with the geographic axis of decreasing lineage age in juncos but also with a steep ecological gradient. Finally, we found significant associations between genome-wide variants linked to functional genes and proxies of both sexual and natural selection. These results suggest that the joint effects of sexual and ecological selection have played a prominent role in the junco radiation.</p>
How butterflies keep their cool: physical and ecological traits influence thermoregulatory ability and population trends.
<p>Understanding which factors influence the ability of individuals to respond to changing temperatures is fundamental to species conservation under climate change.</p> <p>We investigated how a community of butterflies responded to fine-scale changes in air temperature, and whether species-specific responses were predicted by ecological or morphological traits.</p> <p>Using data collected across a UK reserve network, we investigated the ability of 29 butterfly species to buffer thoracic temperature against changes in air temperature. First, we tested whether differences were attributable to taxonomic family, morphology or habitat association. We then investigated the relative importance of two buffering mechanisms: behavioural thermoregulation versus fine-scale microclimate selection. Finally, we tested whether species' responses to changing temperatures predicted their population trends from a UK-wide dataset.</p> <p>We found significant interspecific variation in buffering ability, which varied between families and increased with wing length. We also found interspecific differences in the relative importance of the two buffering mechanisms, with species relying on microclimate selection suffering larger population declines over the last 40 years than those that could alter their temperature behaviourally.</p> <p>Our results highlight the importance of understanding how different species respond to fine-scale temperature variation, and the value of taking microclimate into account in conservation management to ensure favourable conditions are maintained for temperature-sensitive species.</p>
Including intraspecific trait variability to avoid distortion of functional diversity and ecological inference: lessons from natural assemblages
<p>1. Functional diversity assessments are crucial and increasingly used for understanding ecological processes and managing ecosystems. The functional diversity of a community is assessed by sampling traits at one or more scales (individuals, populations, species) and calculating a summary index of the variation in trait values. However, it remains unclear how the scale at which traits are sampled and the indices used to estimate functional diversity may alter the patterns observed and inferences about ecological processes.</p> <p>2. For 40 plant and 61 ant communities, we assess functional diversity using six methods – encompassing various mean-based and probabilistic methods – chosen to reflect common scenarios where different levels of detail are available in trait data. We test whether including trait variability at different scales (from individuals to species) alter functional diversity values calculated using volume-based and dissimilarity-based indices, Functional Richness (FRic) and Rao, respectively. We further test whether such effects alter the functional diversity patterns observed across communities and their relationships with environmental drivers such as abiotic gradients and occurrences of invasive species.</p> <p>3. Intraspecific trait variability strongly determined FRic and Rao. Methods using only species' mean trait values to calculate FRic (convex hulls) and Rao (Gower-based dissimilarity) distorted the patterns observed when intraspecific trait variability was considered. These distortions generated Type I and Type II errors for the effects of environmental factors structuring the plant and ant communities.</p> <p>4. The high sensitivity of FRic to individuals with extreme trait values was revealed in comparisons of different probabilistic methods including among-individual and among-population trait variability in functional diversity. By contrast, values and ecological patterns in Rao were consistent among methods including different scales of intraspecific trait variability.</p> <p>5. Decisions about where traits are sampled and how trait variability is included in functional diversity can drastically change the patterns observed and conclusions about ecological processes. We recommend sampling the traits of multiple individuals per species and capturing their intraspecific trait variability using probabilistic methods. We discuss how intraspecific trait variability can be reasonably estimated and included in functional diversity in the common circumstance where only limited trait data are available.</p>
Diversity of response and effect traits provides complementary information about avian community dynamics linked to ecological function
<p>Functional diversity metrics based on species traits are widely used to investigate ecosystem functioning. In theory, such metrics have different implications depending on whether they are calculated from traits mediating responses to environmental change (response traits) or those regulating function (effect traits), yet trait choice in diversity metrics is rarely scrutinized. Here, we compile effect and response traits for British bird species supplying two key ecological services – seed dispersal and insect predation – to assess the relationship between functional diversity and both mean and stability of community abundance over time. As predicted, functional diversity correlates with stability in community abundance of seed dispersers when calculated using response traits. However, we found a negative relationship between functional diversity and mean community abundance of seed dispersers when calculated using effect traits. Subsequently, when combining all traits together, we found inconsistent results with functional diversity correlating with reduced stability in insectivores, but greater stability in seed dispersers. Our findings suggest that trait choice should be considered more carefully when applying such metrics in ecosystem management.</p>
Dataset supplementing Lichtenberg et al. (2017) Foraging traits modulate stingless bee community disassembly under forest loss. Journal of Animal Ecology
<p>This dataset contains data and scripts that supplement the publication</p> <p>Lichtenberg et al. (2017) Foraging traits modulate stingless bee community disassembly under forest loss. Journal of Animal Ecology. DOI 10.1111/1365-2656.12747.</p> <p> </p> <p>Please cite the above article if you use any of the included data or code.</p> <p> </p> <p>Files are described in README.md.</p>
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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.