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129 results for “ecological niche models”
Figure 2 in Climatic preferences and distribution of 6 evolutionary lineages of Typhlops vermicularis Merrem, 1820 in Turkey using ecological niche modeling
Figure 2. Predicted models of lineages B, C, and E according to Last Interglacial (LIG) and Last Glacial Maximum (LGM; CCSM and MIROC) (1, 1A, 1B, 1C for lineage B; 2, 2A, 2B, 2C for lineage C; 3, 3A, 3B, 3C for lineage E).
Figure 6 in A contribution to the biogeography and taxonomy of two Anatolian mountain brook newts, Neurergus barani and N. strauchii (Amphibia: Salamandridae) using ecological niche modeling
Figure 6. Results of the identity tests (D and I). The bars with different colors are calculated as the significance threshold of the replicates with identity test mode. Arrows refer to actual niche overlaps between Neurergus barani and N. strauchii.
Figure 4 in A contribution to the biogeography and taxonomy of two Anatolian mountain brook newts, Neurergus barani and N. strauchii (Amphibia: Salamandridae) using ecological niche modeling
Figure 4. The range of current climate suitability predicted by MaxEnt model for A) N. barani and B) N. strauchii in the Anatolian Peninsula and Near East Asia.
Figure 3 in A contribution to the biogeography and taxonomy of two Anatolian mountain brook newts, Neurergus barani and N. strauchii (Amphibia: Salamandridae) using ecological niche modeling
Figure 3. Relative predictive power of the six bioclimatic variables predicted by the jackknife of regularized training gain in MaxEnt model for both species (Neurergus barani and N. strauchii).
Figure S1 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure S1. Bayesian consensus tree of the Mesobuthus caucasicus complex reconstructed from mitochondrial DNA sequences.
Figure 9 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 9. Phylogeny the Mesobuthus caucasicus complex reconstructed using mitochondrial DNA sequences. The Przewalski's scorpion (M. przewalskii) is deeply diverged from other species and the Chinese scorpion (M. martensii) belongs to the species complex. Node supports are shown by bootstrapping probabilities from 1000 replicates and Bayesian posterior probabilities.
Figures 1–8 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figures 1–8. Mesobuthus przewalskii stat. nov., from Qiemo, Xinjiang. 1. Male, dorsal view. 2. Male, ventral view. 3. Female, dorsal view. 4. Female, ventral view. 5. Male, dentition of pedipalp chela movable finger. 6. Male, dentition of pedipalp chela fixed finger. 7. Male, ventral aspect of genital operculum and pectines. 8. Female, ventral aspect of genital operculum and pectines. Scale bars: 1–4 = 5.0 mm; 5–8 = 2.0 mm.
Figure 11 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 11. Ecological niche models of Mesobuthus scorpions. Potential distribution areas for the Przewalski's scorpion M. przewalsii (purple) is shown together with the Chinese scorpion M. martensii (green) and other species of the M. caucasicus complex (yellow). The entire Tarim Basin and adjacent Gobi region are suitable for survival of M. przewalskii. No area to the west of the Tianshan Mountains and the Pamir Plateau is suitable for M. przewalskii, and similarly no area to the east of the Tianshan Mountains and the Pamir Plateau is suitable for other species of the M. caucasicus complex. There are overlaps in predicted suitable distribution areas between M. przewalskii and M. martensii along the northeast edge of the Qinghai-Tibet Plateau. The suitable areas in the Junggar Basin and to the north of the Tianshan Mountains are likely due to over prediction of the model, because M. przewalskii does not occur in these regions. Ecological niche model for M. martensii was adopted from Shi et al. 2007.
Figure 10 in Genetic analysis and ecological niche modeling delimit species boundary of the Przewalski's scorpion (Scorpiones: Buthidae) in arid Asian inland
Figure 10. Phylogenetic network for the Mesobuthus caucasicus species complex. Although the interrelationships between species is poorly resolved, no reticulations have occurred in the most recent common ancestors for each species. The Przewalski's scorpion M. przewalskii is clearly diverged from other member of the species complex and warrants a species rank. The divergence of the Chinese scorpion M. martensii is comparable to the divergences among the members of the species complex.
Predicting daily activity time through ecological niche modeling and microclimatic data
<p><span>1. </span><span>Climate temporality is a phenomenon that affects species' activity and distribution patterns across spatial and temporal scales. Despite the global availability of microclimatic data, their use to predict activity patterns and distributions remains scarce, particularly at fine temporal scales (e.g., < month). Predicting activity patterns based on climatic data may allow us to foresee some of the consequences of climate change, particularly for ectothermic vertebrates. </span></p> <p><span>2. </span><span>The Gila monster exhibits marked daily and seasonal activity patterns linked to physiology and reproduction. Here we evaluate if ecological niche models fitted using microclimate data can predict temporal activity patterns using the Gila monster (<em>Heloderma suspectum</em>) as a study system. Further, we identified if the activity patterns are related to physiological constraints.</span></p> <p><span>3. </span><span>We used dated occurrences from museum specimens and human observations to generate and test ecological niche models using minimum-volume ellipsoids. We generated hourly microclimatic data for each occurrence site for ten years using the NicheMapR package. For ecological niche modeling, we compared the traditional seasonal approach versus a daily activity pattern strategy for model construction. We tested both using the omission rate of independent observations (citizen science data). Finally, we tested if unimodal and bimodal activity patterns for each season could be recreated through ecological niche modeling and if these patterns followed known physiological constraints.</span></p> <p><span>4. </span><span>The unimodal and bimodal activity patterns previously reported directly from tracking individuals across the year were recovered by using niche modeling and microclimate across the species' geographical range. We found that upper thermal tolerances can explain the daily activity patterns of this species. </span></p> <p><span>5. </span><span>We conclude that ecological niche models trained with microclimatic data can be used to predict activity patterns at fine temporal scales, particularly on ectotherm species of arid zones coping with rapid climate modifications. Further, the use of fine temporal scale variables can lead to a better niche delimitation, enhancing the results of any research objective that uses correlative models.</span></p>
The Prairie State: Using Ecological Niche Modeling to Predict Distributions of Early Land Plants
<p>This data includes raw data of over 12,000 occurrences were downloaded from the<strong> Consortium of Bryophyte Herbaria (<a href="http://www.bryophyteportal.org/portal">www.bryophyteportal.org/portal</a>), </strong>that were listed to be in Illinois and included longitude and latitude data. This data set was screened and cleaned to investigate species distribution models as well as generate models of selected bryophytes investigating future changes in distribution across climate change scenarios.</p>
Data from: Evaluating migration hypotheses for the extinct Glyptotherium using Ecological Niche Modeling
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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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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>
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>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.