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332 results for “Ecological niches”
Fig. 1 in Ecological niche difference associated with varied ethanol tolerance between Drosophila suzukii and Drosophila melanogaster (Diptera: Drosophilidae)
Fig. 1. Ethanol (A) and acetaldehyde (B) contents of grapes infested by Drosophila melanogaster and Drosophila suzukii.
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.
Not the same: phylogenetic relationships and ecological niche comparisons between two different forms of Aglaoctenus lagotis from Argentina and Uruguay
<p>We extracted genomic DNA from three species of <em>Aglaoctenus:</em> <em>A. lagotis, </em>and<em> A. castaneus </em>from Uruguay and Argentina. From those we obtained three mitochondrial markers including the 5’ half of cytochrome c oxidase subunit I (<em>cox1</em>), the 3’ half of the 16S rRNA ribosomal subunit plus the complete tRNA-Leu plus 5’ half of the NADH dehydrogenase subunit I (16S+L1+nad1), and a partial fragment of the small ribosomal unit (<em>12S</em>). Additionally, we sequenced the nuclear intron of the gene encoding translation initiation factor 5A (<em>tif5A</em>). The sequences of the <em>12S</em>, <em>16S</em>+<em>L1+nad1 </em>and <em>tif5A </em>gene fragments were aligned using the online version of MAFFT v7 using the Q-ins-i algorithm. The alignment of the partial fragment of <em>cox1 </em>sequences was trivial since no insertions/deletions (indels) were observed. The alleles in heterozygous individuals for the <em>tif5A</em> intron were separated using the PHASE algorithm, as implemented in DnaSP v6. 12.03. With this data we inferred gene trees with Maximum Likelihood, Bayesian and statistical parsimony analyses. We perform molecular species delimitation analyses conducted with STACEY, and the species tree and divergence times were co-estimated with *BEAST. Additionally, we build a haplotype network of the nuclear intron <em>tif5A</em>, the concatenated mitochondrial genes <em>cox1</em>+<em>12S</em>+<em>16S</em>+<em>L1</em>+<em>nad1</em>, and a partial fragment of <em>cox1 </em>gene were estimated using statistical parsimony in TCS and implemented in PopART v1.7.</p>
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>
Code and data supplement for "Unveiling the transition from niche to dispersal assembly in ecology"
<p>This repository contains the data and code needed to reproduce the results and figures in the article “Unveiling the transition from niche to dispersal assembly in ecology” published in Nature.</p>
Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)
<p>Data from: Alternative measures of trait-niche relationships: a test on dispersal traits in saproxylic beetles (Ecology and Evolution)</p> <p>DATA DOI: https://doi.org/10.5281/zenodo.8322080</p> <p>Associated article DOI: https://doi.org/10.1002/ece3.10588</p> <p>Ryan C. Burner, Jorg Stephan, Juha Siitonen, Tord Snall, et al. 2023</p> <p>ryan.c.burner@gmail.com</p> <p>This data release contains data files needed to run the Hmsc models described in the associated publication. It is a subset of the complete beetle capture and environmental covariate dataset maintained by Juha Siitonen (see associated manuscript for references to prior publications). It contains the following four files:</p> <p>1) Species_detections.csv</p> <p>This site_year x species table has detection/non-detection (1/0) values for each species at each site_year. Beetles were trapped at about 142 sites in Finland forests. Includes only beetle species (n = 212) which are considered saproxylic and which were detected at >=5 sites in the dataset, and for which trait information was available. Species names are as originally identified in the source dataset (see early publications by Juha Siitonen). Row names ('Row_ID'), which consist of [site]_[year], correspond to 'Row_ID' in the 'Site_covariates.csv' file. Species (column) names correspond to species row naes in 'Species_traits.csv'</p> <p>2) Site_covariates.csv</p> <p>This table has one row for each 'Row_ID' (n = 142) corresponding to rows in 'Species_data.csv'. Covariate columns have been scaled and centered for modeling. Columns are as follows:</p> <p>rowID - [site]_[year] of sampling<br> Year - year of sampling<br> Site - site name/number<br> climID - unique ID for each grid cell from which climate data were extracted<br> lat_WGS84 - latitude (WGS84)<br> lon_WGS84 - longitude (WGS84)<br> VD10 - scaled and centered total pooled volume of local standing and fallen dead trees (originally in m3/ha, before scaling) with a minimum diameter of 10 cm, estimated using transects<br> agedomin - scaled and centered mean age of the five oldest trees in the stand<br> OldFor_1km - scaled and centered volume of living wood in those forests older than 100 years within a one km radius around each site<br> MeanTemp - scaled and centered mean temperature during the trapping period, from mean of all ERA5 hourly estimates of 2m temperature (see manuscript for details)<br> TotalPrecip - scaled and centered total precipitation during the trapping period, from ERA5 summed across all hourly estimates of total precipitation (see manuscript for details)<br> globRad_WHm2 - scaled and centered total solar radiation during the trapping period, summed across all daily values, based on site slope and aspect, calculated using GIS (see manuscript for details). Units were Wh/m2 prior to scaling and centering.<br> log_Nr_traps - scaled and centered log-transformed number of traps used at each capture site </p> <p><br> 3) Species_traits.csv</p> <p>Trait data, based on trait values in Hagge et al. (2021 - see manuscript for full reference), for beetle species included in model (see species data information, above). In some cases traits are from synonyms used in Hagge that differ from taxonomy of this dataset. Traits have been scaled and centered. Row names are species names that match columns in 'Species_detections.csv'. Columns as follows:</p> <p>wing_length - scaled and centered (log(wing length divided by body length))<br> wing_load - scaled and centered (log(mass / wing area / body length))<br> wing_aspect - scaled and centered (log(wing aspect ratio)</p> <p><br> 4) Phylotree.csv</p> <p>A phylogenetic tree for the species in this dataset, written in the Newick (also known as New Hampshire) format. The tree is based on the species-level insect tree in Chesters et al. (2017) (see manuscript for full citation) but has missing species added randomly to the correct genus (when present) or family or (occassionally) order.</p>
Data from: Differential use of nest materials and niche space among avian species within a single ecological community
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Data from: Ecological responses of <em>Orientallactaga sibirica</em>: Variations in body size and trophic niche across changing habitats
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Data from: Fluctuation of ecological niches and geographic range shifts along chile pepper's domestication gradient
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Data from: Evaluating migration hypotheses for the extinct Glyptotherium using Ecological Niche Modeling
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Data from: Persistence of the ecological niche in pond damselflies underlies a stable adaptive zone despite varying selection
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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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Niche overlap in rodents increases with competition but not ecological opportunity: A role of inter-individual difference
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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.