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312 results for “ecological model”
Modeling data and R code for Chrysodeixis chalcites ecological niche
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Input files for ecological modeling in interior Alaska using LANDIS-II
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Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains - Ecological Niche Modeling and Corridors files
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Complex ecological phenotypes on phylogenetic trees: a Markov process model for comparative analysis of multivariate count data
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Paleobiogeographic insights gained from ecological niche models: progress and continued challenges
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Preservation biases in the fossil record distort species ecological niche and distribution models
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High-resolution species distribution modelling of two coastal biogenic habitat-forming species in an Ecologically and Biologically Significant Area of the Bay of Fundy, Canada
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Derived variables and coordinates to assess the ecological relevance of multiscale bathymetry for coral species distribution modelling across the Great Barrier Reef
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[Model outputs] Identifying major hydrologic change drivers in a highly managed transboundary endorheic basin: integrating hydro‐ecological models and time‐series data mining techniques
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The Effects of Climate Downscaling Technique and Observational Dataset on Modeled Ecological Responses: Supporting Data Tables
These data have been prepared as a supplement to Pourmokhtarian et al. (2016; full citation below), where complete details on methods can be found. We evaluated three downscaling methods: the delta method (or the change factor method); monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD); and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8th degree resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (8 ensembles of 6 runs). This dataset consists of three files - 1) a zip archive file of all raw daily downscaled AOGCMs (csv format; years 1960-2099; delta method 2012-2099 only) which were used as input for PnET-BGC model, 2) a zip archive file of all PnET-BGC output files for each model run (csv format; years 1000-2100), and 3) a pdf document file that describes the content of the input and output files. Data were also used from the following Hubbard Brook longterm datasests: Daily Streamflow Watershed 6: http://dx.doi.org/10.6073/pasta/727ee240e0b1e10c92fa28641bedb0a3 Chemistry of Streamwater at the Hubbard Brook Experimental Forest, Watershed 6: http://dx.doi.org/10.6073/pasta/2ec152b0ab1d4e64aa40f4aa9bc492ac Daily Precipitation Watershed 6: http://dx.doi.org/10.6073/pasta/17c8ff8b160bf7893ef39f75a02652e5 Daily Maximum/Minimum Temperature Data: http://dx.doi.org/10.6073/pasta/2a4ab5522ce15f28196a6035802b09e8 Daily Solar Radiation Data: http://dx.doi.org/10.6073/pasta/2fa098a5aa191c64e622b253c0fee5af These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest
Data from: Evolutionary constraint on low elevation range expansion: defense-abiotic stress tolerance tradeoff in crosses of the ecological model Boechera stricta
Most transplant experiments across species geographic range boundaries indicate that adaptation to stressful environments outside the range is often constrained. However, the mechanisms of these constraints remain poorly understood. We used extended generation crosses from diverged high and low elevation populations. In experiments across low elevation range boundaries, there was selection on the parental lines for abiotic stress tolerance and resistance to herbivores. However, in support of a defense-tolerance tradeoff, extended generation crosses showed non-independent segregation of these traits in the lab across a drought-stress gradient and in the field across the low elevation range boundary. Genotypic variation in a marker from a region of the genome containing a candidate gene (MYC2) was associated with change in the genetic tradeoff. Thus, using crosses and forward genetics, we found experimental genetic and molecular evidence for a pleiotropic tradeoff that could constrain the evolution of range expansion.
Evaluating multiple historical climate products in ecological models under current and projected temperatures
<p>Gridded historical climate products (GHCPs) are employed with increasing frequency when modeling ecological phenomena across large scales and predicting ecological responses to projected climate changes. Concurrently, there is an increasing acknowledgement of the need to account for uncertainty when employing climate projections from ensembles of global circulation models (GCMs) and emissions scenarios. Despite the growing usage and documented differences among GHCPs, uncertainty characterization has primarily focused on the roles of GCM and emissions scenario choice, while the consequences of using a single GHCP to make predictions over space and time has received relatively less attention. Here we employ average July temperature data from observations and seven GHCPs to model plant canopy cover and tree basal area across central Alaska, U.S.A. We first compare fit and support of models employing raw observed or GHCP temperature values versus those with an elevation adjustment, finding (1) greater support for, and better fit using elevation-adjusted versus raw temperature models and (2) overall similar fits of elevation-adjusted models employing temperature from observations or GHCPs. Focusing on basal area, we next compare predictions generated by elevation-adjusted models employing GHCP data under current conditions and a warming scenario of current temperatures plus 2 °C, finding good agreement among GHCPs though with between-GHCP differences and variation primarily at middle elevations (~ 1,000 m). These differences were amplified under the warming scenario. Finally, using pooled indices of prediction variation and difference across GHCP models, we identify characteristics of areas most likely to exhibit prediction uncertainty under current and warming conditions. Despite (1) overall good performance of GHCP data relative to observations in models and (2) positive correlation among model predictions, variation in predictions across models—particularly in mid-elevation areas where the position of treeline may be changing—suggests researchers should exercise caution if selecting a single GHCP for use in models. We recommend the use of multiple GHCPs to provide additional uncertainty information beyond standard estimated prediction intervals, particularly when model predictions are employed in conservation planning.</p>
Data from: Lessons from movement ecology for the return to work: modeling contacts and the spread of COVID-19
<p>Human behavior (movement, social contacts) plays a central role in the spread of pathogens like SARS-CoV-2. The rapid spread of SARS-CoV-2 was driven by global human movement, and initial lockdown measures aimed to localize movement and contact in order to slow spread. Thus, movement and contact patterns need to be explicitly considered when making reopening decisions, especially regarding return to work. Here, as a case study, we consider the initial stages of resuming research at a large research university, using approaches from movement ecology and contact network epidemiology. First, we develop a dynamical pathogen model describing movement between home and work; we show that limiting social contact, via reduced people or reduced time in the workplace are fairly equivalent strategies to slow pathogen spread. Second, we develop a model based on spatial contact patterns within a specific office and lab building on campus; we show that restricting on-campus activities to labs (rather than labs and offices) could dramatically alter (modularize) contact network structure and thus, potentially reduce pathogen spread by providing a workplace mechanism to reduce contact. Here we argue that explicitly accounting for human movement and contact behavior in the workplace can provide additional strategies to slow pathogen spread that can be used in conjunction with ongoing public health efforts.</p>
Data from: The plover neurotranscriptome assembly: transcriptomic analysis in an ecological model species without a reference genome
We assembled a de novo transcriptome of short-read Illumina RNA-Seq data generated from telencephalon and diencephalon tissue samples from the Kentish plover, Charadrius alexandrinus. This is a species of considerable interest in behavioural ecology for its highly variable mating system and parental behaviour, but it lacks genomic resources and is evolutionarily distant from the few available avian draft genome sequences. We assembled and identified over 21 000 transcript contigs with significant expression in our samples, showing high homology to exonic sequences in avian draft genomes. From these, we identified >31 000 high-quality SNPs and > 2500 simple sequence repeats (SSRs). We also analysed expression patterns in our data to identify potential candidate genes related to differences in male and female behaviour, identifying over 200 nonoverlapping putative autosomal transcripts that show significant expression differences between males and females. Gene ontology analysis revealed that female-biased transcripts were significantly enriched for cerebral functions related to learning, cognition and memory, and male-biased transcripts were mostly enriched for terms related to neural function such as neuron projection and synapses. This data set provides one of the first de novo transcriptome assemblies from non-normalized short-read next-generation data and outlines an effective strategy for measuring sequence and expression variability simultaneously without the aid of a reference genome.
Data from: Is there a correlation between abundance and environmental suitability derived from ecological niche modelling? A meta-analysis
It is thought that species abundance is correlated with environmental suitability and that environmental variables, scale, and type of model fitting can confound this relationship. We performed a meta-analysis to (i) test whether species abundance is positively correlated with environmental suitability derived from correlative ecological niche models (ENM), (ii) test whether studies encompassing large areas within a species range (>50%) exhibited higher AS correlations than studies encompassing small areas within a species range (<50%), (iii) assess which modelling method provided higher AS correlation, and (iv) compare strength of the AS relationship between studies using only climatic variables and those that used both climatic and other environmental variables to derive suitability. We used correlation coefficients to measure the relationship between abundance and environmental suitability derived from ENM. Each correlation coefficient was considered an effect size in a random-effects multivariate meta-analysis. In all cases we found a significantly positive relationship between abundance and suitability. This relationship was consistent regardless of scale of study, ENM method, or set of variables used to derive suitability. There was no difference in strength of correlation between studies focusing on large or small areas within a species' range or among ENM methods. Studies using other variables in combination with climate exhibited higher AS correlations than studies using only climatic variables. We conclude that occurrence data can be a reasonable proxy for abundance, especially for vertebrates, and the use of local variables increases the strength of the AS relationship. Use of ENMs can significantly decrease survey costs and allow the study of large-scale abundance patterns using less information. Including only climatic variables in ENM may confound the relationship between abundance and suitability when compared to studies including variables taken locally. However, modelers and conservationists must be aware that high environmental suitability does not always indicate high abundance.
Data from: Scale-dependent foraging ecology of a marine top predator modelled using passive acoustic data
1. Understanding which environmental factors drive foraging preferences is critical for the development of effective management measures, but resource use patterns may emerge from processes that occur at different spatial and temporal scales. Direct observations of foraging are also especially challenging in marine predators, but passive acoustic techniques provide opportunities to study the behavior of echolocating species over a range of scales. 2. We used an extensive passive acoustic dataset to investigate the distribution and temporal dynamics of foraging in bottlenose dolphins using the Moray Firth (Scotland, UK). Echolocation buzzes were identified with a mixture model of detected echolocation inter-click intervals, and used as a proxy of foraging activity. A robust modelling approach accounting for autocorrelation in the data was then used to evaluate which environmental factors were associated with the observed dynamics at two different spatial and temporal scales. 3. At a broad scale, foraging varied seasonally, and was also affected by sea-bed slope and shelf-sea fronts. At a finer scale, we identified variation in seasonal use and local interactions with tidal processes. Foraging was best predicted at a daily scale, accounting for site-specificity in the shape of the estimated relationships. 4. This study demonstrates how passive acoustic data can be used to understand foraging ecology in echolocating species, and provides a robust analytical procedure for describing spatio-temporal patterns. Associations between foraging and environmental characteristics varied according to spatial and temporal scale, highlighting the need for a multi-scale approach. Our results indicate that dolphins respond to coarser-scale temporal dynamics, but have a detailed understanding of finer-scale spatial distribution of resources.
Community science validates climate suitability projections from ecological niche modeling
<p><span>Climate change poses an intensifying threat to many bird species, and projections of future climate suitability provide insight into how species may shift their distributions in response. Climate suitability is characterized using ecological niche models (ENMs), which correlate species occurrence data with current environmental covariates and project future distributions using the modeled relationships together with climate predictions. Despite their widespread adoption, ENMs rely on several assumptions that are rarely validated <i>in situ </i>and can be highly sensitive to modeling decisions, precluding their reliability in conservation decision-making. Using data from a novel, large-scale community science program, we developed dynamic occupancy models to validate near-term climate suitability projections for bluebirds and nuthatches in summer and winter. We estimated occupancy, colonization, and extinction dynamics across species' ranges in the United States in relation to projected climate suitability in the 2020s, and used a Gibbs variable selection approach to quantify evidence of species-climate relationships. We also included a Bird Conservation Region strata-level random effect to examine among-strata variation in occupancy that may be attributable to land-use and ecoregional differences. Across species and seasons, we found strong evidence that initial occupancy and colonization were positively related to 2020 climate suitability, illustrating an independent validation of projections from ENMs across a large geographic area. </span><span>Random strata effects revealed that occupancy probabilities were generally higher than average in core areas and lower than average in peripheral areas of species' ranges, and served as a first step in identifying spatial patterns of occupancy from these community science data. </span><span>Our findings lend much-needed support to the use of ENM projections for addressing questions about potential climate-induced changes in species' occupancy dynamics. More broadly, </span>our work highlights the value of community scientist observations for ground-truthing projections from statistical models and for refining our understanding of the processes shaping species' distributions under a changing climate.</p>
Data from: Morphological, phylogenetic, and ecological diversity of the new model species Setaria viridis (Poaceae: Paniceae) and its close relatives
Premise of the study: Species limits of the emerging model organism Setaria viridis (tribe Paniceae, subtribe Cenchrinae) are not well defined. It is thought to be related to S. adhaerens, S. faberi, S. verticillata, and S. verticilliformis and in North America occurs with the morphologically similar S. pumila. An integrated approach was taken to evaluate its variation and relationships with the other taxa. Methods: Statistical morphology, flow cytometry, molecular phylogenetics, and growth experiments were employed to examine the group's physical variation, polyploidy, evolutionary relationships, and drought ecology, respectively. Key results: Setaria viridis contributed one genome to the tetraploids S. faberi, S. verticillata, and S. verticilliformis; the other genome of the latter two was contributed by S. adhaerens. Setaria pumila is unrelated. Morphologically, S. viridis is most similar to S. faberi, but all tested accessions of S. viridis were diploid, whereas those of S. faberi were all tetraploid. Principal component analysis of 70 morphological characters consistently separated S. viridis from S. faberi, largely by spikelet characters. The diagnostic morphological characters are not affected by watering. Setaria faberi is far more sensitive to drought, in terms of mortality and morphological stunting, than S. viridis or S. pumila. Conclusions: Setaria viridis is a diploid species and has contributed to several polyploid derivatives. The most morphologically similar of the polyploids is S. faberi, which differs in spikelet features, phylogenetics, genome size, and ecological response to drought. Researchers using field-collected S. viridis as a model organism will benefit from the clear delimitation provided in this study.
Data from: Ecological niche modeling as a tool for prediction of the potential geographic distribution of Bacillus anthracis spores in Tanzania
Introduction: Anthrax is caused by the spore-forming, Gram-positive bacterium Bacillus anthracis. The aim of this study was to predict the potential distribution of B. anthracis in Tanzania and produce epidemiological evidence for the management of anthrax outbreaks in the country. Methods: The Maxent algorithm was used to predict areas at risk of anthrax outbreaks based on the occurrence and environmental data in Arusha and Kilimanjaro regions; the model was later transferred to predict the entire country. Seventy percent of the occurrence data were used to train the model, while 30% were used for model evaluation. Results: Four regions of northern Tanzania are predicted to have a high risk for anthrax outbreaks, while the southern and western regions had low-risk areas. Soil type (56.5%), soil pH (23.7%), and isothermally (10.4%) were the most important variables for the model prediction, and the most significant soil types were solonetz, fluvisols, and lithosols. Conclusions: A strong risk level across districts of the Tanzania mainland was identified in this study. A total of 18 districts in Tanzania Mainland are predicted to be at very high risk of an anthrax outbreak occurrence. These findings are important for policymakers to effectively mount targeted control measures for anthrax outbreaks in Tanzania.
Data from: An Appalachian population of neochoristoderes (Diapsida: Choristodera) elucidated through fossil evidence and ecological niche modeling
<p>Four neochoristoderan vertebral centra are described from the latest Cretaceous of New Jersey. One specimen was recovered from the basal transgressive lag of the Navesink Formation in the area of Holmdel Park, New Jersey, and two others were recovered nearby and likely were derived from the same horizon. The fourth was recovered from the Marshalltown sequence in the vicinity of the Ellisdale Dinosaur Site. These vertebrae expand the geographic range of Late Cretaceous neochoristoderes in North America by over 2000 km further east, and represent the first neochoristoderan remains from the Atlantic coastal plain. To discern whether neochoristodere remains are to be expected in New Jersey, and elucidate why neochoristoderes are apparently so rare in Appalachia, we implemented ecological niche modeling to predict the range of suitable habitat for <i>Champsosaurus</i>, the only known genus of Late Cretaceous neochoristoderes. We found that in Appalachia, the ideal habitat of <i>Champsosaurus</i> likely existed slightly further north and west than the Atlantic coastal plain, and New Jersey is likely on or near the margin of this suitable habitat space. These results suggest that the occurrence of neochoristoderes in New Jersey is consistent with the habitat requirements of known Late Cretaceous neochoristoderes. These vertebrae therefore may represent the southern margin of a population of neochoristoderes that lived further inland, where latest Cretaceous sediments are not preserved. The continued recovery of material from Late Cretaceous deposits along the Atlantic coast, and review of existing collections, is encouraged to clarify the true distribution of neochoristoderes in Appalachia.</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.