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312 results for “ecological model”
Data from: Evaluating migration hypotheses for the extinct Glyptotherium using Ecological Niche Modeling
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Data from: A hierarchical model for jointly assessing ecological and anthropogenic impacts on animal demography
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Ecological signal in the size and shape of marine amniote teeth – 3D models and landmarks
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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
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Predicting daily activity time through ecological niche modeling and microclimatic data
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Ecological niche models for American black bear, Rafinesque's big-eared bat, and timber rattlesnake
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Data from: Accounting for missing ticks: Use (or lack thereof) of hierarchical models in tick ecology studies
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Reliably predicting pollinator abundance: challenges of calibrating process-based ecological models
<p>1. Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate.</p> <p>2. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process.</p> <p>3. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores.</p> <p>4. Our results highlight a key universal challenge of calibrating spatially-explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that is often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data.</p>
Ecological niche modeling and first records from Namibia and Zimbabwe validate the amphi-equatorial distribution of Byrsinus pseudosyriacus (Hemiptera: Cydnidae) - Supplementary data
<p><em>Byrsinus pseudosyriacus (</em>Linnavuori, 1977), the most widely distributed Afrotropical species of the genus <em>Byrsinus</em> Fieber, 1860 known hitherto only from the Sudano-Eremian area is for the first time reported in two countries south of the Equator. The species potential distribution map was generated using the ecological niche modelling (ENM) methods that allowed this species to be regarded as amphi-equatorial in distribution<strong>.</strong></p>
Data from: A new null model approach to quantify performance and significance for ecological niche models of species distributions
Aim: Ecological niche modelling requires robust estimation of model performance and significance, but common evaluation approaches often yield biased estimates. Null models provide a solution but are rarely used in this field. We implemented an important modification to existing null-model tests, evaluating null models with the same withheld records that were used to evaluate the real model. We built and evaluated models across a range of modelling scenarios and for various performance measures using the algorithm Maxent and the monk parakeet (Myiopsitta monachus). Location: Native range in Southern America and global invasions predominantly in North/Central America and Europe Methods: We tested the ability of models built under 15 scenarios (five sets of calibration records and three settings that varied the level of model complexity) to predict spatially independent evaluation data in the invaded range (in effect, testing the models under spatial transfer). We quantified performance with measures of discriminatory ability and overfitting based on AUC and the omission error rate. We estimated null distributions of these measures and calculated effect size and significance. We determined how these estimates varied across modelling scenarios, comparing with two tests existing in the literature. Results: Performance varied starkly across modelling scenarios. As expected, the measures of overfitting agreed with each other and provided different information than that of discriminatory ability. However, high performance per se did not show strong association with high effect size and significance. Main Conclusions: Ecological niche models should be assessed with measures of effect size and significance based on appropriate null distributions, in contrast to several approaches existing in the literature. The proposed approach using independent evaluation data, implemented with our accompanying code, allows such estimates for either the same or a different region/time period, and it merits use and continued development.
Paleobiogeographic insights gained from ecological niche models: progress and continued challenges
<p>The spatial distribution of individuals within ecological assemblages, and their associated traits and behaviors, are key determinants of ecosystem structure and function. Consequently, determining the spatial distribution of species, and how distributions influence patterns of species richness across ecosystems today and in the past, helps us understand what factors act as fundamental controls on biodiversity. Here, we explore how ecological niche modeling has contributed to understanding the spatiotemporal distribution of past biodiversity, and past ecological and evolutionary processes. We first perform a semi-quantitative literature review to capture studies that applied ecological niche models (ENMs) in the past, identifying 668 studies. We coded each study according to focal taxonomic groups and whether and how the study used fossil evidence, whether it relied on evidence or methods in addition to ENMs, and spatial scale and temporal intervals. We used trends in publication patterns across categories to anchor discussion of recent technical advances in niche modeling, focusing on paleobiogeographic ENM applications. We then explored the contributions of ENMs to paleobiogeography, with a particular focus on examining patterns and associated drivers of range dynamics; phylogeography and within-lineage dynamics; macroevolutionary patterns and processes, including niche change, speciation, and extinction; drivers of community assembly; and conservation paleobiogeography. Overall, ENMs are powerful tools for elucidating paleobiogeographic patterns. ENMs are most commonly used to understand Quaternary dynamics, but an increasing number of studies use ENMs to gain important insight into both ecological and evolutionary processes in pre-Quaternary times. Deeper integration with traits and phylogenies may further extend those insights.</p>
SCAR DistAnt Ecological Model Output Repository
<p>This repository provides access to a collection of ecological model outputs (species distribution and similar models) from Antarctica and the Southern Ocean. It is a project of the SCAR <a href="https://scar.org/science/egabi/home/" rel="nofollow">Expert Group on Biodiversity Informatics</a> in conjunction with <a href="https://www.belspo.be/belspo/impuls/project_en.stm#ADVANCE" rel="nofollow">ADVANCE</a> (Royal Belgian Institute of Natural Sciences) and the Integrated Digital East Antarctica program at the <a href="https://www.antarctica.gov.au/science/" rel="nofollow">Australian Antarctic Division</a>.</p> <p><strong>Please note:</strong> the inclusion of a layer in this collection is not an endorsement of its quality or suitability for your intended purpose. Users should consult the associated publication for details on the source data and modelling processes. We encourage users to contact the original publication authors to discuss their intended use of these layers.</p> <p>Model outputs are provided as cloud-optimized geotiffs (COGs), with generally one file per species. The COG will have multiple bands if the original model predictions include uncertainty estimates or multiple model output variables. Each output has been kept on its original coordinate reference system (map projection) and spatial resolution.</p> <p>There is a <a href="https://github.com/SCAR/distant/blob/master/metadata.csv">table of minimal metadata</a> that describes the layers in the collection. This metadata is intended to be sufficient for users to find potential layers of interest, and make an initial evaluation of their high-level characteristics such as taxonomic details, spatial coverage and resolution, and model output types. Our metadata is NOT intended to provide a comprehensive description of each layer: users are referred to the original publication for that level of detail (see the layer’s <code>reference</code> entry).</p> <div> <h3>Citing</h3> The layers in this collection have been re-released under their original license where applicable, or a CC-BY licence otherwise. Please cite when using, and also cite the original data sources used. For example:</div> <div> <p>Kovacs J (2020) A model of my favourite Southern Ocean species. <em>Journal of Southern Ocean Stuff</em> <strong>123</strong>:1–10. Data obtained from the SCAR DistAnt Ecological Model Output Repository, doi:10.5281/zenodo.10910076</p> </div> <p>Individual data sources might have varying licence conditions: consult the <code>licence</code> field for details.</p>
A dataset of modeled hydrologic alteration and ecological consequences in stream reaches of the conterminous United States
<p>A dataset of modeled anthropogenically induced hydrologic alteration values for 43 hydrologic indices and modeled losses in native fish biodiversity as a result of streamflow modification, both mapped at the NHDPlus V1 and V2 stream-reach resolution.</p>
Modelling the origin, fate, and ecological and health impacts of heavy metals from an abandoned mercury mine in a paradise island in the Philippines
<p>This document contains supplementary tables for the article entitled "Modelling the origin, fate, and ecological and health impacts of heavy metals from an abandoned mercury mine in a paradise island in the Philippines"</p>
Fig. 5 in Using Ecological Niche Modeling For Biodiversity Conservation Guidance In The Western Podillya (Ukraine): Amphibians
Fig. 5. Summarized species richness map (see text for explanation).
Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains - Ecological Niche Modeling and Corridors files
<p><b>Aim</b></p> <p>Ancient climatic fluctuations are invoked as the main driving force that generates the astonishing biodiversity in ancient mountains. As a result, endemism and spatial turnover are usually high and few species are widespread among entire mountain ranges, precluding the understanding of origins of macroevolutionary patterns. Here, we used a species endemic to, but widespread in, one of the most species-rich ancient mountains on the globe to test how environmental changes acted on them and how their macroevolutionary patterns were shaped.</p> <p><b>Location</b></p> <p>Espinhaço Range, Eastern Brazil.</p> <p><b>Taxon</b></p> <p><i>Vriesea oligantha </i>species complex (Bromeliaceae).</p> <p><b>Methods</b></p> <p>We compiled data for plastidial regions and nuclear microsatellites to assess genetic diversity, population structure, migration rates and phylogenetic relationships. Using temperature and precipitation variables we modeled suitable areas for the present and the past, estimating corridors between isolated populations. We also implemented Bayesian demographic analyses to estimate ancient populations dynamics. Finally, we tested if population structure is driven by isolation by environment or by distance using a Bayesian modeling approach.</p> <p><b>Results</b></p> <p>Our results showed that the intraspecific divergence events of <i>V. oligantha</i> are older than those associated with the latest Pleistocene climatic oscillations, supporting the view that Quaternary climatic fluctuations are key components for understanding its population differentiation processes. Species distribution modeling estimated corridors between populations in the past, as also shown in the demographic analyses, depicting a major spatial reorganization during colder climates. Besides, the high genetic structure estimated results from both models of isolation by distance and by environment.</p> <p><b>Main conclusions</b></p> <p><i>V. oligantha</i> is a remarkable model to test the effects of climatic oscillations over the biological community, since this species originated in the early-Pleistocene, prevailing over several cycles of climatic fluctuations until today. The estimated demographic dynamics of <i>V. oligantha</i> agrees with the species-pump mechanism, suggesting it as the main cause of speciation within the Espinhaço Range. Moreover, the phylogeographic patterns of <i>V. oligantha</i> reflect previously recognized spatial and temporal macroevolutionary patterns in the Espinhaço Range, providing insights into how microevolutionary processes may have given rise to this astonishing mountain biodiversity.</p> <p> </p>
In the right place, at the right time: the integration of bacteria into the Plankton Ecology Group model
<p><strong><span>Background</span></strong></p> <p><span>Planktonic microbial communities have critical impacts on the pelagic food web and water quality status in freshwater ecosystems, yet no general model of bacterial community assembly linked to higher trophic levels and hydrodynamics has been assessed. In this study, we utilized a two-year survey of planktonic communities from bacteria to zooplankton on three freshwater reservoirs to investigate their spatiotemporal dynamics.</span></p> <p><strong><span>Result</span></strong></p> <p><span>We observed the site-specific presence and microdiversification of bacteria in lacustrine and riverine environments, as well as in deep hypolimnia. Moreover, we determined recurrent bacterial seasonal patterns driven by both biotic and abiotic conditions, which could be integrated into the well-known Phytoplankton Ecology Group (PEG) model describing primarily the seasonalities of larger plankton groups. Importantly, bacteria with different ecological potentials showed finely coordinated successions affiliated with four seasonal phases, including the spring bloom dominated by fast-growing opportunists, the clear-water phase associated with oligotrophic ultramicrobacteria, the summer phase characterized by phytoplankton bloom-associated bacteria, and the fall/winter phase driven by decay-specialists. </span><span> </span></p> <p><strong><span>Conclusion</span></strong></p> <p><span>Our findings elucidate the principles driving the spatiotemporal microbial community distribution in freshwater ecosystems. We suggest an extension to the original PEG model by integrating recurrent bacterial seasonal trends.</span></p>
Data from: Socio-ecological drivers of long-term ecosystem carbon stock trend: An assessment with the LUCCA model of the French case
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Data from: Too much of a good thing? Supplementing current species observations with fossil data to assess climate change vulnerability via ecological niche models
<p>Ecological niche models (ENMs) are a powerful tool in ecological research and conservation planning. Since ENMs provide probability maps of suitable areas under environmental change, they may assist in designing conservation actions and addressing conservation priorities. However, ENMs are usually implemented by learning the species climatic preferences from their current geographic distribution, which leaves them vulnerable to the issue of niche truncation issues, as if comes with non-climatic limits to the current species distribution posed by e.g. anthropic activities and settlements, and is bound to assume that species are at equilibrium with their environments. These problems might be alleviated by the inclusion of fossil occurrences, which refer to moments during species evolution when such limits were absent, and a larger fraction of the species fundamental niche was probably explored. Here, we combined current and fossil occurrence data for 38 medium-large mammal species of conservation concern to assess the influence of the fossil record on ENM predictions under future climate change scenarios. We found that ignoring or including fossil data yields consistent trends in terms of predicted range increase/decrease. Yet, although adding fossil data invariably results in increased niche width, estimates of range change magnitude improved for just one half only of the species. These results suggest that most species might be in non-equilibrium with their environment, and that the inclusion of fossil data may be crucial to the better understanding of species climatic requirements, hence for designing effective conservation strategies. </p>
Figure 3 in Establishment of an expansion-predicting model for invasive alien cerambycid beetle Aromia bungii based on a virtual ecology approach
Figure 3. Flow chart of simulation procedure the study.
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.