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2,603 results for “Ecological data”
Data from Matrishin et al. "Phages are important unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis"
<p>Data files associated with Matrishin et al. "Phages are important unrecognized players in the ecology of the oral pathogen <em>Porphyromonas gingivalis</em>".</p> <p><strong>Please see the table in 00.README.xlsx for key information regarding nomenclature</strong>. We caution that the same locus tag identifiers refer to different genes in the Zenodo files than in NCBI. This difference resulted from use of the same Locus Tag Prefixes for in house gene calls using Bakta for the manuscript analyses as for the PGAP analyses ultimately performed upon submission of the assemblies to GenBank. Unlike the Supplementary Data Files submitted with the manuscript, see below, it was not possible to readily update all the Zenodo-deposited files to their updated final GCA and distinct locus tag identifiers because of the complexity of some of the included filetypes, therefore all files in the Zenodo set were left unchanged from the nomenclature used in the original in house analyses based on Bakta.</p> <table align="left"> <thead> <tr> <th scope="col">Directory</th> <th scope="col">Contents</th> </tr> </thead> <tbody> <tr> <td><strong>00.README</strong></td> <td>Important information regarding nomenclature differences across data types.</td> </tr> <tr> <td><strong>01.bax.bakta</strong></td> <td>Results of Bakta annotation of 88 <em>Pg</em> genomes.</td> </tr> <tr> <td><strong>02.bax.ppanggolin</strong></td> <td>Results of PPanGGOLiN pangenome analysis of 88 <em>Pg</em> genomes.</td> </tr> <tr> <td><strong>03.bax.combo</strong></td> <td>Results of multiple analyses used to inform identification and curation of prophages in <em>Pg</em> genomes, provided as bacterial genome fastas and gff files that can be uploaded together to genome viewer tools (e.g. Geneious) and visualized as tracks. Note, these do not include final prophage calls.</td> </tr> <tr> <td><strong>04.phage.genomes</strong></td> <td><em>Pg</em> phage genomes in fasta format.</td> </tr> <tr> <td><strong>05.phage.prots</strong></td> <td><em>Pg</em> phage proteins in fasta format, clipped proteins at the beginnings and ends of genomes are excluded.</td> </tr> <tr> <td><strong>06.phage.gbs</strong></td> <td><em>Pg</em> phage information in GenBank format, clipped proteins at the beginnings and ends of genomes are excluded.</td> </tr> <tr> <td><strong>07.phage.families.virclust</strong></td> <td>Results of VirClust analysis used to inform resolution family-level units.</td> </tr> <tr> <td><strong>08.phage.families.victor</strong></td> <td>Results of VICTOR analysis used to inform resolution of family-level units.</td> </tr> </tbody> </table> <p> </p>
Code and data supplement for "Unveiling the transition from niche to dispersal assembly in ecology"
<p>This repository contains the data and code needed to reproduce the results and figures in the article “Unveiling the transition from niche to dispersal assembly in ecology” published in Nature.</p>
Data from: Dynamic balancing of risks and rewards in a large herbivore: Further extending predator-prey concepts to road ecology
<p>Animal behavior is shaped by the ability to identify risks and profitably balance the levels of risks encountered with the payoffs experienced. Anthropogenic disturbances like roads generate novel risks and opportunities that wildlife must accurately perceive and respond to. Basic concepts in predator-prey ecology are often used to understand responses of animals to roads (e.g., increased vigilance, selection for cover in their vicinity). However, prey often display complex behaviors such as modulating space use given varying risks and rewards, and it is unclear if such dynamic balancing is used by animals in the context of road crossings.</p> <p>We tested whether animals dynamically balance risks and rewards relative to roads using extensive field -based and GPS collar data from elk in Yoho National Park (British Columbia, Canada) where a major highway completely bisects their range during most of the year.</p> <p>We analyzed elk behavior by combining hidden Markov movement models with a step-selection function framework. Rewards were indexed by a dynamic map of available forage biomass and risks were indexed by road crossings and traffic volumes.</p> <p>We found that elk generally selected intermediate and high forage biomass and avoided crossing the road. Most of the time, elk modulated their behavior given varying risks and rewards. When crossing the highway compared with not crossing, elk selected for greater forage biomass and this selection was stronger as the number of highway crossings increased. However, with traffic volume, elk only balanced foraging rewards when they crossed a single time during a travel sequence.</p> <p>Using a road ecology system, we empirically tested an important component of predator-prey ecology – the ability to dynamically modulate behavior in response to varying levels of risks and rewards. Such a test articulates how decision-making processes that consider the spatiotemporal variation in risks and rewards allow animals to successfully and profitably navigate busy roads. Applying well-developed concepts in predator-prey theory helps understand how animals respond to anthropogenic disturbances and anticipate the adaptive capacity for individuals and populations to adjust to rapidly changing environments.</p>
Data for: A model of ecological abundance: Terrestrial species inventories
<p>Counts of species in ecological samples are important for two reasons: they tell us about community assembly processes and they form the basis of species diversity estimates. Previous models of count distributions are either complex, widely rejected, not grounded in population dynamics, or not able to predict high unevenness. I present a new one-parameter model assuming that individual counts track the geometric series. The series' governing parameter <em>p</em> is set to vary randomly among species. Communities differ only in the centering of the distribution of <em>p</em>. To find the probability distribution, a vector of evenly-spaced initial values called q is drawn from the range 0 to 1. Values are then scaled by (1) transforming each q into the odds <em>o</em> = <em>q</em>/(<em>1 – q</em>), (2) multiplying each o by a fitted parameter <em>m</em>, and (3) back-computing each <em>p</em> as <em>m o</em>/(<em>m o </em>+ <em>1</em>). This skews the values to match the centering of the actual counts. The distribution is consistent with a population dynamics model in which the number of offspring produced in each interval by each species is distributed geometrically, rising with the number of adults. Large-scale surveys of corals, fishes, butterflies, and trees are consistent with the distribution, as are local-scale inventories of trees and assorted vertebrate and insect groups. Each local survey is used to predict counts within biogeographically and taxonomically matched surveys. When only decisive differences are considered, the model's predictions outperform those of each rival in at least 86% of all pairwise comparisons. The new distribution's estimates haves no substantial sample size bias. Thus, it is preferable to other species diversity estimation methods in the frequent cases where it is a good fit to count data.</p>
Data, tomatoes and ecological futures
<p>Exhibited complementary artefact for author's research presentation at the NORDES Doctoral Consortium </p>
Data from: An environmental habitat gradient and within-habitat segregation enable co-existence of ecologically similar bird species
<p>Niche theory predicts that ecologically similar species can co-exist through multidimensional niche partitioning. However, due to the challenges of accounting for both abiotic and biotic processes in ecological niche modelling, the underlying mechanisms that facilitate co-existence of competing species are poorly understood. In this study, we evaluated potential mechanisms underlying the co-existence of ecologically similar bird species in a biodiversity-rich transboundary montane forest in east-central Africa by computing niche overlap indices along an environmental elevation gradient, diet, forest strata, activity patterns, and within-habitat segregation across horizontal space. We found strong support for abiotic environmental habitat niche partitioning, with 55% of species pairs having separate elevation niches. For the remaining species pairs that exhibited similar elevation niches, we found that within-habitat segregation across horizontal space and to a lesser extent vertical forest strata provided the most likely mechanisms of species co-existence. Co-existence of ecologically similar species within a highly diverse montane forest was determined primarily by abiotic factors (e.g., environmental elevation gradient) that characterize the Grinnellian niche and secondarily by biotic factors (e.g., vertical and horizontal segregation within habitats) that describe the Eltonian niche. Thus, partitioning across multiple levels of spatial organization is a key mechanism of co-existence in diverse communities.</p>
Data from: A user-friendly guide to using distance measures to compare time series in ecology
<p>Time series are a critical component of ecological analysis, used to track changes in biotic and abiotic variables. Information can be extracted from the properties of time series for tasks such as classification (e.g. assigning species to individual bird calls); clustering (e.g. clustering similar responses in population dynamics to abrupt changes in the environment or management interventions); prediction (e.g. accuracy of model predictions to original time series data); and anomaly detection (e.g. detecting possible catastrophic events from population time series). These common tasks in ecological research rely on the notion of (dis-) similarity, which can be determined using distance measures. A plethora of distance measures have been described, predominantly in the computer and information sciences, but many have not been introduced to ecologists. Furthermore, little is known about how to select appropriate distance measures for time-series-related tasks. Therefore, many potential applications remain unexplored.</p> <p>Here we describe 16 properties of distance measures that are likely to be of importance to a variety of ecological questions involving time series. We then test 42 distance measures for each property and use the results to develop an objective method to select appropriate distance measures for any task and ecological dataset. We demonstrate our selection method by applying it to a set of real-world data on breeding bird populations in the UK and discuss other potential applications for distance measures, along with associated technical issues common in ecology.</p> <p>Our real-world population trends exhibit a common challenge for time series comparisons: a high level of stochasticity. We demonstrate two different ways of overcoming this challenge, first by selecting distance measures with properties that make them well-suited to comparing noisy time series, and second by applying a smoothing algorithm before selecting appropriate distance measures. In both cases, the distance measures chosen through our selection method are not only fit-for-purpose but are consistent in their rankings of the population trends.</p> <p>The results of our study should lead to an improved understanding of, and greater scope for, the use of distance measures for comparing ecological time series, and help us answer new ecological questions.</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: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>https://doi.org/10.5061/dryad.bnzs7h4h4</strong></a>.</p> <p>The files consist of the code of an agent-based model (ABM) in a NetLogo, detailed documentation of the ABM in a standard format, and a table of data exported from the simulation experiment reported on in the paper. By downloading the Netlogo file, one could not only rerun the experiment we report on and recreate the data table but toggle parameters or edit the model to explore other dynamics.</p>
Data, code, and supplementary materials for Pearman P. B., Broennimann, O., et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution
<p>The repository contains several archives of digital materials that were used and/or produced in the analyses presented in Pearman, P. B. and Broennimann et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. <strong>Nature Ecology & Evolution</strong>, likely 2023. These archives include (1) Supplementary Materials files ; (2) Data and code to generate country-level maps and plots; and (3) data and code to generate all maps of species and joint climate niche marginality, all in G-zipped tar archives. Readme files are available in each archive to guide running of the scripts and identification of objects in the Supplementary Materials. Please see the paper for all co-authors names, and the methods, the results obtained, and discussion of their implications.</p> <p>This work is dedicated to the memory of our friend and colleague Michael Bruford (1963-2023).</p>
Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Beaverdam Reservoir forecasting data assimilation experiments using the FLARE (Forecasting Lake And Reservoir Ecosystems) system: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations and meteorological data, forecasts.zip contains forecast parquet files generated from the BVR FLARE DA experiment workflow, and scores.zip contains forecast skill metrics required for analysis. Within the forecasts and scores folders, there are four runs that were conducted with different parameter tuning and uncertainty quantification. The "all_UC" folder includes forecasts run with process, driver, parameter, and initial condition uncertainty quantification. The "IC_off" folder includes forecasts run without initial conditions uncertainty included (i.e., only process, driver, and parameter uncertainty). The "constant_bad_pars" folder includes forecasts run with constant parameters (but daily updating of initial conditions) that were not tuned for Beaverdam Reservoir before forecasts were generated. Finally, the "tuned_bad_pars" folder includes forecasts that were run with daily updating of initial conditions and parameters, but the parameters started out at random values that were not tuned for Beaverdam Reservoir.</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: Soil microbes influence the ecology and evolution of plant plasticity
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Data from: Inferring ecological selection from multidimensional community trait distributions along environmental gradients
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Data from: Repeated evolution of reduced visual investment at the onset of ecological speciation in high-altitude <em>Heliconius</em> butterflies
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Data from: Linking land use and the nutritional ecology of herbivores: a case study with the Senegalese locust
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Data from: Global plant ecology of tropical ultramafic ecosystems
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Ecological data for: Subsidy accessibility drives asymmetric food web responses
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GPS collar data and social-ecological feature data for examining the movement of coyotes in Los Angeles, California (2019-2021)
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.