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1,473 results for “Geographic distribution”
Fig. 1 in Predicting the geographic distribution of Lucilia sericata and Lucilia cuprina (Diptera: Calliphoridae) in South Africa
Fig. 1. Map of South Africa, showing the occurrence records and collection trip routes for (A) Lucilia sericata and (B) Lucilia cuprina.
Data and R code used in: Plant geographic distribution influences chemical defenses in native and introduced Plantago lanceolata populations
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Divergence, gene flow and the origin of leapfrog geographic distributions: the history of color pattern variation in Phyllobates poison-dart frogs
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Data from: Geographic distribution of terpenoid chemotypes in Tanacetum vulgare mediates tansy aphid occurrence but not abundance
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Geographic distribution change and climatic niche change of Odonates in Great Britain
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Data from: (Sub-)Antarctic endemic cyanobacteria from benthic mats are rare and have restricted geographic distributions
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Data from: Declining demographic performance and dispersal limitation influence the geographic distribution of the perennial forb, Astragalus utahensis (fabaceae)
1. A central goal of ecology is understanding the determinants of species' distributions. 'Metapopulation' models for the existence of distributional boundaries predict that species' geographic ranges arise from the landscape-scale deterioration of habitat suitability towards the range edge (i.e. niche mechanisms), which simultaneously hinders demographic performance and limits dispersal to suitable habitat beyond the edge (i.e. dispersal limitation). However, few studies have examined both of these mechanisms for the same species by examining abundance and comprehensive measures of demographic performance across the distribution and beyond its boundary. 2. We tested the predictions of metapopulation models for range limits by contrasting abundance, demographic performance, and population growth (λ) of the perennial forb Astragalus utahensis in central and northern range edge populations. We tested for dispersal limitation by transplanting individuals at and beyond the northern range boundary and monitoring their demographic performance. 3. Astragalus abundance and stochastic λ decreased from the range center to the northern range edge, with stochastic λ falling to or below replacement in range edge populations. However, transplants at some sites beyond the northern range edge survived and reproduced at levels similar to transplants within the range. Thus, in addition to deteriorating conditions at the range edge, dispersal limitation appears to contribute to limiting A. utahensis' northern distribution. 4. Synthesis: Our results support metapopulation models for range limits by suggesting that decreased demographic performance constrains the viability of range edge populations while contributing to dispersal limitation of A. utahensis' distribution. Thus, the tandem action of niche and dispersal processes appears to play an important role in constraining this species' northern latitudinal range.
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.
An update on Quararibea floribunda (Malvaceae: Malvoideae): untangling the taxonomy and geographic distribution
<p>Quararibea floribunda, a species endemic to Brazil, is poorly studied taxonomically, and little is known about its ecology and conservation status. Since its publication in 1842, only a few studies have reported on its morphological circumscription, thus remaining as a complex in the taxonomy of Quararibea. In addition, little is known about its geographic distribution, which, according to most authors, is restricted to the Cerrado Biome, a phytogeographic biome of dry forests. Therefore, we herein review and clarify the morphological circumscription and distribution of Q. floribunda in different vegetation types, designate a lectotype, and recognize its conservation status as Vulnerable (VU). The present study is based on analysis of protologues and further pertinent literature. Several herbaria were consulted, both in person and online. Fieldwork was done between 2017 and 2020 in different locations of midwestern and southeastern Brazil, mainly in dry forests of the Cerrado Biome. We confirm that Q. floribunda also occurs in the Atlantic Forest Biome and that it is not exclusive to the Cerrado Biome, as previously thought. All known populations in this biome inhabit humid habitats, and as such, they are closer to the vegetation of the Atlantic Forest Biome than the typical Cerrado dry forests. In addition to assessing the conservation status of Q. floribunda, we evaluate its nomenclatural history, leading to the designation of a lectotype, finally highlighting vegetative and floral diagnostic characters. A distribution map is provided, as well as a morphological comparative analysis between species with foliar domatia in extra-Amazonian Brazil.</p>
Fig. 1. A. caliginosa–A in The Alternative Distribution Of Related Earthworms Aporrectodea Caliginosa And A. Trapezoides (Oligochaeta, Lumbricidae) In Ukraine As A Case Of Geographical Parthenogenesis
Fig. 1. A. caliginosa–A. trapezoides sample locations from the territory of Ukraine.
Fig. 2 in Interspecific Interactions as a Factor of Limitation of Geographical Distribution: Evidence Obtained by Modeling Home Ranges of Vole Twin Species Microtus Arvalis – M. Levis (Rodentia, Microtidae)
Fig. 2. Potential distribution of the East European vole (Microtus levis). Captions as in fig.1.
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>
The geographic distribution of rodent granivory and cheek pouches across North America
<p>Seeds are an important food resource for many rodents. One of the specializations that many granivorous rodents exhibit to increase their efficiency in harvesting seeds is cheek pouches. However, many rodent species lack cheek pouches. We propose that the presence or absence of cheek pouches is related to seed size and the productivity of the habitat where those rodents reside. </p> <p><b>Location</b> North America – United States and Canada.</p> <p><b>Taxon</b> Granivorous rodents.</p> <p>We divided granivorous rodents into those species with and without cheek pouches. We then compiled a list of plant species (n = 389) that are known or suspected to be dispersed by these rodents via scatter hoarding the seeds in soil and compared the richness distributions of small (≤10 mm) and large seeds (>10 mm) to the distributions of rodents with and without cheek pouches. Large seeds are generally too large to fit into cheek pouches so they are usually carried one at a time with the incisors. Most rodents with cheek pouches live in the arid southwestern North America, whereas most rodents that lack cheek pouches live in the mesic southeastern North America. The richness distribution of rodents with cheek pouches was more similar to the richness distribution of small seeds, and the richness distribution of rodents that lack cheek pouches was more similar to the richness distribution of large seeds (nuts), although details of these distributions differed significantly. The body mass of rodents with cheek pouches (mean = 59.5 g) was significantly less than the body mass of rodents that lack cheek pouches (592.6 g). Large rodents that lack cheek pouches live mostly in the more productive southeastern portion of North America where there are many trees that produce large nuts. Small rodent with cheek pouches live mostly in the less productive southwestern portion of North America where there are many shrubs, forbs, and grasses that produce small seeds.</p>
Supplementary materials for "Modeling the geographical distributions of Chordodes formosanus and its mantis hosts in Taiwan, with considerations for their niche overlaps"
<p>Species distribution model (SDM) has conventionally been used for evaluating the<br> distribution of single species, but comparisons between different SDMs are possible for<br> evaluating the geographic similarity between taxa. Here we used a parasite and host system<br> to infer the geographic overlaps between species with tight biological interaction, e.g.<br> parasites and their obligate host; specifically, we used the horsehair worm <em>Chordodes<br> formosanus</em> and its three different mantis hosts to study the extent of niche overlap. We<br> retrieved presence points for the host species and the parasite and we built the SDMs with<br> MaxEnt implemented in ENMeval by using selected bioclim variables (based on VIF values)<br> at a 30 seconds scale. The models showed that the hosts and parasite do not occur in the high<br> elevation areas in Taiwan, which was expected based on their biology. Interestingly, the<br> predicted parasite distribution included areas without collection records, implying local<br> extinction or sampling bias. We subsequently evaluated niche overlap between hosts and the<br> parasite according to five similarity indices (Schoener’s D, I statistic, relative rank, Pearson<br> correlation coefficient and the rank correlation coefficient<em> rho</em>). Our models showed high<br> similarity of SDM predictions between hosts and the parasite. There were differences among<br> metrics about which host shared the highest similarity with the parasite, but the majority of<br> the results indicated that the Japanese boxing mantis has the highest niche similarity with the<br> horsehair worm. The choice of the niche overlap metric to use can be seen as a way to get<br> informations on the parasite’s ecology, which can be important for endangered species SDMs<br> are reliable tools for host and parasite conservation management and could help to improve<br> biological and ecological knowledge of parasites.</p>
Figure 4 in Geographic distribution patterns of galling insects in a protected area of Atlantic forest (southeast, Brazil)
Figure 4. The fit of the count part of the "hurdle" model to the relationship between galling species richness and plant genus species richness.
Figure 2 in Geographic distribution patterns of galling insects in a protected area of Atlantic forest (southeast, Brazil)
Figure 2. Boxplots with jittered illustrating the galling species richness between year season, with jitered raw values strung vertical corresponding to plots (a, b, c), numbers the plots (N) and sites (n), and mean ± SD bars.
Figure 3 in Geographic distribution patterns of galling insects in a protected area of Atlantic forest (southeast, Brazil)
Figure 3. The fit of the count part of the ZIP model to the relationship between galling species richness and plant family species richness.
Fig. 95 in Geographic Distribution Of Lispocephala Pokorny (Diptera: Muscidae), With Descriptions Of New Species From China
Fig. 95. Distribution map of endemic species of Lispocephala in China
Fig. 1 in Geographic Distribution Of Lispocephala Pokorny (Diptera: Muscidae), With Descriptions Of New Species From China
Fig. 1. Male genitalia figure of Lispocephala
Plant diversity darkspots for global collection priorities: time-to-event datasets per botanical country as defined by the World Geographical Scheme for Recording Plant Distributions (WGSRPD).
<p>Datasets used to predict the number of plant species remaining to be described and/or geolocated within a botanical country, which represents the third level of subdivision (generally equating to a political country) used by WGSRPD for recording plant distributions. The folder is composed of two subfolders <em>has_coords</em> and <em>has_no_coords</em> containing the time-to-event data for species with valid and no (invalidated) occurrence records within a given botanical country respectively<em>.</em></p> <ul> <li>Each folder contains a<strong> </strong>list of 361 botanical countries with the following 16 fields:</li> </ul> <pre><strong>species:</strong> species name<br><strong>time_ofdescription:</strong> year of the (first) description<br><strong>time_ofcollection:</strong> year of the collection of the earliest record<br><strong>family:</strong> species family name<br><strong>lifeform_description: </strong>the life form categorised into 4 classes <br><strong>CHELSA_bio_1: </strong>annual mean temperature (°C)<br><strong>CHELSA_bio_12:</strong> annual precipiation (mm)<br><strong>CHELSA_bio_15</strong>: temperature seasonality (-)<br><strong>CHELSA_bio_4</strong>: precipitation seasonality (-)<br><strong>elevation</strong>: elevation (m)<br><strong>range_size_area:</strong> total area of the botanical countries encompassing the species' native range <br>according to the World Checklist of Vascular Plants (WCVP) (km^2) <br><strong>taxo_activity</strong>: taxonomic activity calculated as the number of named authors in the World Checklist of Vascular Plants<br>describing species from the same family during the year of description of the species,<br>divided by the number of species described within the given family that year. <br><strong>num_records_per_year:</strong> geographic activity calculated as the number of occurrence records<br>collected within the native range of the species, divided by the number of years between <br>the earliest and the lastest (first) record collected within this range.<br><strong>num_uses</strong>: number of human uses<br><strong>time_todescription:</strong> number of years between the (first) description and 1753<br><strong>time_tocollection:</strong> number of years between the (first) description and the collection of the first record of the species<br><br></pre> <p> </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.