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84 results for “distribution shift”
Data and Analysis for Kaplanis, Denny, and Raimondi 2024, "Vertical distribution of rocky intertidal organisms shifts with sea-level variability on the Northeast Pacific Coast".
<p>This repository contains all the data and R scripts used to produce all analyses and figures for Kaplanis, Denny, and Raimondi 2024, as well as all intermediate outputs and final figures. To access this content, download and unzip the intertidalvertdist folder (for intertidal vertical distribution). The R Project is titled "intertidalvertdist". All pertinent information needed to access data, replicate the analyses, and produce figures is contained within the README file, but a brief desciption is below.</p> <p><br>Directory Architecture:</p> <p>Data:<br>Contains all data. Within this folder are two subdirectories - Raw Data, and Processed Data. Raw Data are unmanipulated, straight from the data source. Processed Data are outputs from scripted data wrangling and transformations. </p> <p>Within each of these folders are two more subdirectories: Tide Gauge Data, and MARINe Data. These are the two data sources used in this manuscript - monthly sea-level data from The National Oceanic and Atmospheric Administration Center for Operational Oceanographic Products and Services (NOAA CO-OPS) tide gauge stations, and long-term rocky intertidal biological monitoring data from Multi-Agency Rocky Intertidal Network (MARINe) survey sites.</p> <p>Scripts:<br>All R scripts are contained within the Scripts folder. The scripts have the prefix IVD (for intertidal vertical distribution), then a name that indicates the major function of the code. The scripts either downloads data, manipulates data, conducts analyses, and/or produces a figure.</p> <p>Outputs:<br>Any figures and tables from preliminary analyses, but that are not used in the final manuscript, are saved in Outputs.</p> <p>Figures:<br>All final figures and tables are contained in the Figures folder. All figures are produced by scripts, except Figs. 1 and 2, which are schematics produced manually in a graphics editor. This folder contains two other folders: Supplemenatary Figures, and Partial Regression Plots. Partial Regression plots are the same as the final Figures 8-12, except they are grouped by taxa rather than by explanatory variable.</p> <p>Data Processing Workflow - Overview: <br>Tide Gauge Data (Data/Raw Data/Tide Gauge Data/individual stations) were downloaded using the NOAA Co-Ops API URL Builder (https://tidesandcurrents.noaa.gov/api-helper/url-generator.html), merged, then analyzed. Three MARINe data sets from the Coastal Biodiversity Survey (CBS) were accessed via data requests (https://marine.ucsc.edu/explore-the-data/contact/data-request-form.html). The first MARINe dataset (Data/Raw Data/MARINe Data/CBS_Percent Cover Data, both First Sample and Full Sample) was used to determine the top ten most abundant taxa (hereafter termed “dominant taxa”) across CBS survey sites during the monitoring period of 2001-01-01 to 2021-09-30. The second MARINe dataset (Data/Raw Data/MARINe Data/CBS_Elevation Data) was used to describe the upper limits of vertical distribution of dominant taxa through time. The third MARINe dataset (Data/Raw Data/MARINe Data/CBS_Presence Data) was used to visualize latitudinal distribution of taxa.</p> <p>Location information for Tide Gauge Stations and CBS Survey Sites were assembled into a table (Data/Raw Data/CBS_Tide Gauge_Data.csv)</p> <p>Tide Gauge Data were processed first, then MARINe Data. To replicate this workflow follow the steps described in the README file, in order.</p>
Crop classification dataset for testing domain adaptation or distributional shift methods
<p>In this upload we share processed crop type datasets from both France and Kenya. These datasets can be helpful for testing and comparing various domain adaptation methods. The datasets are processed, used, and described in this paper: <a href="https://doi.org/10.1016/j.rse.2021.112488">https://doi.org/10.1016/j.rse.2021.112488</a> (arXiv version: <a href="https://arxiv.org/pdf/2109.01246.pdf">https://arxiv.org/pdf/2109.01246.pdf</a>). </p> <p>In summary, each point in the uploaded datasets corresponds to a particular location. The label is the crop type grown at that location in 2017. The 70 processed features are based on Sentinel-2 satellite measurements at that location in 2017. The points in the France dataset come from 11 different departments (regions) in Occitanie, France, and the points in the Kenya dataset come from 3 different regions in Western Province, Kenya. Within each dataset there are notable shifts in the distribution of the labels and in the distribution of the features between regions. Therefore, these datasets can be helpful for testing for testing and comparing methods that are designed to address such distributional shifts.</p> <p>More details on the dataset and processing steps can be found in <a href="https://doi.org/10.1016/j.rse.2021.112488">Kluger et. al. (2021)</a>. Much of the processing steps were taken to deal with Sentinel-2 measurements that were corrupted by cloud cover. For users interested in the raw multi-spectral time series data and dealing with cloud cover issues on their own (rather than using the 70 processed features provided here), the raw dataset from Kenya can be found in <a href="https://openreview.net/forum?id=5HR3vCylqD">Yeh et. al. (2021)</a>, and the raw dataset from France can be made available upon request from the authors of this Zenodo upload.</p> <p>All of the data uploaded here can be found in "CropTypeDatasetProcessed.RData". We also post the dataframes and tables within that .RData file as separate .csv files for users who do not have R. The contents of each R object (or .csv file) is described in the file "Metadata.rtf".</p> <p><strong>Preferred Citation:</strong></p> <p>-Kluger, D.M., Wang, S., Lobell, D.B., 2021. Two shifts for crop mapping: Leveraging aggregate crop statistics to improve satellite-based maps in new regions. Remote Sens. Environ. 262, 112488. https://doi.org/10.1016/j.rse.2021.112488.</p> <p>-URL to this Zenodo post https://zenodo.org/record/6376160</p>
Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation (original datasets)
<p>This repository provides the data for the manuscript "Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation"</p> <p>We investigated thermal tolerances and interspecific competition as causes of species turnover in the nine most abundant species of <em>Drosophila</em> along elevational gradients in the Australian Wet Tropics. Specifically, we 1) analyzed the distribution patterns of the studies <em>Drosophila</em> species; 2) fitted thermal performance curves; 3) tested the correlation between multiple thermal traits and distribution patterns; 4) fitted the Beverton-Holt model to describe the single-generation intra- and inter-specific competition effect; 5) examined the long-term effect of competition and temperature on the population size of a pair of Drosophila species.</p> <p>More details are provided in the README file.</p>
Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift
<p>The Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>) is native to Southeast Asia. Since its first detection in 2008 in Europe and North America, it has been a pest to the fruit production industry as it feeds and oviposits on ripening fruit. Here we aim to model the potential geographical distribution of <em>D. suzukii</em>. We performed an extensive literature review to map the current records. In total, 517 documented occurrences (96 native and 421 invasive) were identified spanning 52 countries. Next, we constructed three species distribution models (SDMs) based on occurrence records in: 1) the native range (SDMnative), 2) the invasive range in Europe (SDMEurope) and 3) a global model of all records (SDMglobal). The models aimed to investigate, whether this species will be able to occupy additional ecological niches beyond its native range and expand its current geographic distribution both globally and in Europe. The SDMs were generated using Maximum Entropy algorithms (Maxent) based on present occurrence records and bioclimatic variables (WorldClim). Predictions of habitat suitability vary greatly depending on the origins of occurrence records. According to all models, precipitation and low temperatures were key limiting factors for the distribution of <em>D. suzukii</em>, which suggests that this species requires a humid environment with mild winters in order to establish a permanent population in its invasive range. Several regions in the invasive range, not presently occupied by this species, were predicted highly suitable, especially in northern Europe, suggesting that <em>D. suzukii</em> is not occupying its full fundamental niche yet. Synthesis and applications. Based on these models of potential geographic distribution of the Spotted Wing Drosophila (<em>Drosophila</em> <em>suzukii</em>), we show a shift in the ecological niche in <em>D. suzukii</em> populations, emphasizing the importance of using presence and local environmental data. Further investigation regarding new occurrences is recommended to secure optimal pest management. Despite a continuing expansion, many countries still lack proper surveillance schemes, and we urge policymakers to initiate appropriate management programs.</p>
Livestock activity shifts large herbivore temporal distributions to their crepuscular edges
<p>Wildlife species are transitioning to greater crepuscular and nocturnal activity in response to high human densities. This plasticity in temporal niches may partially mitigate the impacts of human activity but may also result in underestimating human effects on species foraging, predator-prey relationships, and community level interactions. We deployed remote cameras to characterize shifts in herbivore diel activity in protected habitat vs pastoralist landscapes. We then compared species traits including body mass, dietary preferences, and behavioral characteristics as potential predictors of species sensitivity to livestock. Our data capture a significant temporal shift away from core cattle activity for nearly every herbivore species in our study, leading to more crepuscular activity patterns. As livestock were primarily diurnal and predators primarily nocturnal in pastoralist habitat, species that decreased their overlap with livestock were more likely to increase their overlap with potential predators. Other than species' typical daytime activity levels, we found no evidence that any particular trait significantly predicted temporal shifts in response to livestock. Instead, species generally trended toward greater activity levels at dawn, suggesting that cattle have a homogenizing effect on community-wide activity patterns. Our findings highlight how cohabitation with livestock can profoundly alter the temporal niches of wild herbivores. Shifts in diel activity patterns may reduce herbivore foraging time or efficiency and potentially have cascading shifts on predator-prey dynamics. Given that species traits could not predict responses to livestock, our analysis suggests that conservation strategies should consider each species separately when designing interventions for wildlife management.</p>
Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
<p><strong>Aim</strong>: Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors of range shifts, with the identification of general trends being of great interest for conservation efforts. However, studies reviewing relationships between traits and range shifts have questioned the existence of such generalized trends, due to mixed results and weak correlations, as well as analytical shortcomings. The aim of this study was to test this relationship empirically, using analytical approaches that account for common sources of bias when assessing range trends.<br><strong>Location</strong>: Tanzania, East Africa.<br><strong>Time period</strong>: 1980-1999 and 2000-2020.<br><strong>Major taxa studied</strong>: 57 savannah specialist birds found in Tanzania, belonging to 26 families and 11 orders.<br><strong>Methods</strong>: We applied recently developed integrated spatio-temporal species distribution models in R-INLA, combining citizen science and bird atlas data to estimate ranges of species, quantify range shifts, and test the predictive power of traditional trait groups, as well as exposure-related and sensitivity traits. We based our study on 40 years of bird observations in East African savannahs, a biome that has experienced increasing climatic and non-climatic pressures over recent decades. We correlated patterns of change with species traits.<br><strong>Results</strong>: We find indications of relationships identified by previous research, but low average explanatory power of traits from an ecological perspective, confirming the lack of meaningful general associations. However, our analysis finds compelling species-specific results.<br><strong>Main conclusions</strong>: We highlight the importance of individual assessments, while demonstrating the usefulness of our analytical approach for analyses of range shifts.</p>
Code and data for "Species traits associated with rapid shifts in elevational distributions of Swiss birds"
<p><strong>Abstract</strong><br> Global change in climate and land use have profound effects on species’ geographic and elevational distributions. In European birds, while species are predicted to track their climatic niches upslope, lowland agricultural intensification and high elevation land abandonment can drive elevational shifts. Species traits that can predict response to change in climate and land use can inform conservation, but thorough examination of their relationships with elevational shifts in European birds are lacking. We estimate change in the elevational distributions of 71 species from 1996 to 2016 in a region of the western Palearctic with wide elevational gradients (approximately 3,000 m) and large changes in temperature. We model the relationships between elevational shifts and species traits associated with resource preference and adaptive capacity at five reference points including the cool edge, warm edge, and the core of species’ elevational distributions. When intermediate reference points were removed changes to the results were negligible, indicating that three reference points are likely sufficient. We found significant upslope and downslope shifts in 56% and 23% of our study species, respectively. Asymmetric rates of shifts in the cool and warm edges caused significant contractions in elevational extent in 30% of our study species. The effect of elevational preference (i.e. midpoint elevation) was habitat dependent. Movement in alpine birds was unidirectionally upslope, with nearly half displaying significant or apparent elevational range contractions. In woodland birds, asymmetries of shifts in reference points led to expansions in extent in low elevation species and contractions in high elevation species. Generally, migrants, species with smaller mass, smaller relative brain size, smaller hand-wing index, and generalists in diet, habitat, and elevation had greater upslope shifts. While elevational shifts in European birds were heterogenous and species-specific, many were rapid, and species traits associated with resource preference and adaptive capacity were associated with common patterns of elevation.</p>
Northeast Atlantic species distribution shifts over the last two decades
<p>Marine species are widely shifting their distributions in response to global changes, and it is commonly expected they will move northward and to greater depths to reach cooler, less disturbed habitats. However, local manifestations of global changes, anthropogenic pressures, and species characteristics may lead to unanticipated and varied responses by individual species. In this regard, the Celtic-Biscay Shelf is a particularly interesting study system because it has historically been heavily fished and occurs at the interface between two distinct biogeographic provinces, its community is thus comprised of species with diverse thermal preferenda. In the context of rapidly warming temperatures and intense fishery exploitation, we investigated the distribution shifts of 93 taxa (65 Actinopteri, 10 Elasmobranchii, 11 Cephalopoda, 5 Malacostraca, and 2 Bivalvia), which were sampled annually from 1997 to 2020 during a scientific bottom trawl survey. We used a set of 11 complementary spatial indices to quantify taxon distribution shifts over time. Then, we explored the relative effect of taxon abundance, fishing pressure, and climatic conditions on taxon's distribution shift when a significant shift was detected. We observed that 56% of the taxa significantly shifted. Not all taxa will necessarily shift northward and to deeper areas, as is often expected. Two opposite patterns were identified: taxa either moving deeper and to the southeast, or moving closer to the surface and to the northwest. The main explanatory factors were climate change (short- and long-term temperatures) and taxon abundance. Fishing pressure was the third, but still significant, explanatory factor of taxa of greater commercial importance. Our research highlights that taxa are displaying complex distribution shifts in response to the combined anthropogenic disturbances and underscores the need to conduct regional studies to better understand these responses at the ecosystem scale to develop more suitable management plans and policies.</p>
Data from: Estimating a physiologically-based threshold to oxygen and temperature from marine monitoring data reveals challenges and opportunities for forecasting distribution shifts
Open the record for dataset details and reuse information.
Data from: To the top or into the dark? Relationships between elevational and canopy cover distribution shifts in mountain forests
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Livestock activity shifts large herbivore temporal distributions to their crepuscular edges
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Northeast Atlantic species distribution shifts over the last two decades
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Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
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Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift
Open the record for dataset details and reuse information.
Data from: Shifts in phenological distributions reshape interaction potential in natural communities
Climate change has changed the phenologies of species worldwide, but it remains unclear how these phenological changes will affect species interactions and the structure of natural communities. Using a novel approach to analyse long‐term data of 66 amphibian species pairs across eight communities, we demonstrate that phenological shifts can significantly alter the interaction potential of coexisting competitors. Importantly, these changes in interaction potential were mediated by non‐uniform, species‐specific shifts in entire phenological distributions and consequently could not be captured by metrics traditionally used to quantify phenological shifts. Ultimately, these non‐uniform shifts in phenological distributions increased the interaction potential for 25% of species pairs (and did not reduce interaction potential for any species pair), altering temporal community structure and potentially increasing interspecific competition. These results demonstrate the potential of phenological shifts to reshape temporal structure of natural communities, emphasising the importance of considering entire phenological distributions of natural populations.
DATA & CODE for "Substrate-dependent fish have shifted less in distribution under climate change"
<p>Authors: Sarah M. Roberts*<sup>1</sup>, Andre M. Boustany<sup>2</sup>, Patrick N. Halpin<sup>1</sup></p> <p><strong>Author affiliations: </strong></p> <p>*<sup>1</sup>Marine Geospatial Ecology Lab, Nicholas School of the Environment and Earth Sciences, Duke University, Durham, NC 27708, US</p> <p><sup>2 </sup>Monterey Bay Aquarium, 886 Cannery Row, Monterey, CA 93940, USA</p> <p>This dataset and code run the necessary methods for the manuscript titled: "<strong>Substrate-dependent fish have shifted less in distribution under climate change. </strong><strong>Substrate-dependent fish have shifted less in distribution under climate change" </strong>published in Nature Communications Biology. In order to run the code, you need to request data from <a href="https://oceanadapt.rutgers.edu/">https://oceanadapt.rutgers.edu/</a>. The download is free, I just don't have permission to publish their data. Software needed is Rstudio and R. This is the updated and current version. </p>
Data from: Distributional shifts – not geographic isolation – as a probable driver of montane species divergence
As biodiversity hotspots, montane regions have been a focus of research to understand the divergence process. Like their oceanic counterparts, the diversity of the "sky islands" might be ascribed to geographic isolation of mountaintops. However, because the sky islands, and especially those in northern latitudes, are subject to extreme climatic events such as the glacial cycles that drove both altitudinal and geographical shifts in species' distributions, the dynamic colonization process is also a possible factor driving divergence. Here we test these two hypotheses (i.e., isolation versus colonization) in a flightless montane grasshopper, Melanoplus oregonensis, which is a member of a diverse group that radiated across the Rocky Mountains of North America. Using approximate Bayesian computation (ABC) and spatially explicit simulations that account for spatial heterogeneity and temporal shifts in species distributions, we show that a colonization model of the sky islands from refugial populations provides a significantly better fit to the empirical genetic data than a model of the geographic isolation among sky islands. Moreover, support for the colonization model holds irrespective of whether the movement of individuals was modeled as a diffusion process or was informed by differences in habitat suitabilities across the landscape. With validation analyses to confirm the models provide a good fit to the data, as well as general power and quality analyses, the research not only adds to a growing body of work on the complex dynamics underlying montane biodiversity, but it also provides much needed evaluation of competing hypotheses based on explicit models of the divergence process, as opposed to inferences about diversification drivers from species diversity patterns.
Directional selection shifts trait distributions of planted species in dryland restoration
<p>1. The match between species trait values and local abiotic filters can restrict community membership. An often-implicit assumption of this relationship is that abiotic filters select for a single locally optimal strategy, though difficulty in isolating effects of the abiotic environment from those of dispersal limitation and biotic interactions has resulted in few empirical tests of this assumption. Similar constraints have made it difficult to assess whether the type and intensity of abiotic filters shift along gradients of environmental harshness, as predicted by the stress dominance hypothesis.</p> <p>2. We planted 9,216 plants of perennial grass and forb species that had a range of functional trait values and were assigned to a warm, intermediate, or cool temperature tolerance pools across eight sites on the Colorado Plateau. We compared the distributions of traits of surviving individuals to null distributions to evaluate whether there were shifts in trait means and variation. Borrowing from phenotypic selection concepts in evolutionary biology, we assessed support for stabilizing, directional, and disruptive abiotic filtering of trait distributions and whether these types of filtering varied with initial species pool.</p> <p>3. Functional composition was significantly different from null distributions for nearly all traits at all sites, with trait variation more restricted in harsher abiotic conditions, supporting the stress-dominance hypothesis. Contrary to expectations, we primarily found evidence for directional selection, which increased in frequency in warm species pools while disruptive selection was found more often in cool and intermediate species pools.</p> <p>4. Synthesis: This study provides a controlled experimental approach to test the effect of the abiotic environment on plant trait filtering. We found that opportunistic strategies allowing for rapid water acquisition during favorable periods improved survival at warmer sites. Species with these strategies may be expected to benefit from increasing aridity and may be selected for active management efforts. More generally, the prevalence of directional selection may have important implications for dynamic vegetation models that rely on trait distributions for translating environmental variation into ecosystem processes.</p>
Natural history and community science records confirm rapid geographic shifts in the distribution of Bachman's Sparrow (Peucaea aestivalis) since 1850
<p>North American grassland birds colonized emerging habitat created by expanding agriculture in a pattern of eastward expansions from the mid-1800s to mid-1900s. These birds have been declining, since at least the mid1900s, largely as result of anthropogenic landscape change. Only one bird that now breeds predominantly in southeastern pine savannas is thought to have experienced a concurrent range expansion into this region: <em>Peucaea aestivalis </em>(Bachman's Sparrow). However, our understanding of the <em>P. aestivalis</em> expansion, and subsequent retraction to the southeastern United States, is largely based on a contemporaneous review of only a subset of historical records from beyond its modern, northern limit. We suggest an alternative explanation for these historical records is that <em>P. aestivalis</em> historically occurred more broadly than was recognized in contemporaneous literature. To evaluate these hypotheses, we reviewed field observations from literature, natural history collections, and eBird to show how <em>P. aestivalis </em>presence throughout eastern North America has shifted since the mid-1800s. To confirm that these findings were not the result of detection bias, we repeated our analysis on a common sparrow species (<em>Spizella pusilla</em>) with a largely overlapping breeding range, but no history of expansion and retraction. We confirm that <em>P. aestivalis</em> expanded its range, but add that prior to that expansion, its historical distribution was broader than commonly acknowledged today. As a result, we identify the northwestern historical limit of <em>P. aestivalis</em>, the Ouachita and Ozark highlands, as a potential source region for an eastward expansion that is consistent with those of other North American grassland birds of the era. We discuss the potential evolutionary and conservation implications of this range expansion on <em>P. aestivalis</em> given our more nuanced understanding of it. Anthropogenic landscape change initially provided additional habitat for <em>P. aestivalis</em> but has ultimately resulted in a reduction of the <em>P. aestivalis</em> distribution.</p>
Distribution of blood flow oscillation across the Doppler shift evaluated by the proposed approach with local pressure test.
<p>A step-wise increase in local pressure is known to cause a gradual change in the parameters of capillary blood flow in the<br> upper layers of the skin, and can also affect the measurement results of various optical methods. The impact of the procedure has several subsequent effects, such as mechanical compression of vessels, and neurological and metabolic compensating mechanisms like pressure-induced vasodilation, which maintain the homeostasis of the skin during moderate levels of external pressure and tissue hypoxia. To examine how those effects are translated to the blood flow registering in different ranges of the Doppler spectra, we have developed a 3D-printed pressure distribution tool compatible with the developed sensor which was used, and equipped with a set of weights. </p> <p>During the main series of measurements, the weights were placed into the PDT in a step-wise manner to achieve the<br> following values of pressure applied: 10 mmHg, 30 mmHg, 90 mmHg, 150 mmHg, 210 mmHg. At the end of the procedure, the load was reduced back to 30 mmHg. Experiments were conducted with the participation of 7 healthy volunteers with 10 min LDF recording for each step. To estimate the prominence of the observed effects and substantiate the measuring routing, several preliminary experiments were also conducted where the set of values of pressure was applied with a step-wise increase and then decrease with about 2 min of LDF recordings for each step.</p> <p>Published in IEEE Transactions on Biomedical Engineering "Diagnosis of skin vascular complications revealed by time-frequency analysis and laser Doppler spectrum decomposition", Zherebtsov et al.</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.