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299 results for “niche models”
Data from: Biophysical modeling of the temporal niche: from first principles to the evolution of activity patterns
Most mammals can be characterized as nocturnal or diurnal. However infrequently, species may overcome evolutionary constraints and alter their activity patterns. We modeled the fundamental temporal niche of a diurnal desert rodent, the golden spiny mouse, Acomys russatus. This species can shift into nocturnal activity in the absence of its congener, the common spiny mouse, A. cahirinus, suggesting that it was competitively driven into diurnality, and that this shift in a small desert rodent may involve physiological costs. Therefore, we compared metabolic costs of diurnal vs. nocturnal activity using a biophysical model to evaluate the preferred temporal niche of this species. The model predicted that energy expenditure during foraging is almost always lower during the day except during mid-day in summer at the less sheltered microhabitat. We also found that a shift in summer to foraging in less sheltered microhabitats in response to predation pressure and food availability involves a significant physiological cost moderated by midday reduction in activity. Thus adaptation to diurnality may reflect the 'ghost of competition past'; Climate-driven diurnality is an alternative but less likely hypothesis. While climate is considered to play a major role in the physiology and evolution of mammals, this is the first study to model its effect on the evolution of activity patterns of mammals.
Figure 3 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 3. Distributions of pronotal widths and resulting predicted instars in two species of coastal Atyphella.
Figure 2 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 2. (a) Collection site of coastal Atyphella. Yellow dots indicate locations specimens were collected in 2018. (b) Predictive model for possible localities of coastal Atyphella in Vanuatu. White squares indicate locations Atyphella was collected in 2018.
Figure 1 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 1. (a) Typical habitat of coastal Atyphella (Efate, Vanuatu). (b) Typical habitat of coastal Atyphella (Malekula, Vanuatu). (c) Experimental setup of submersion experiment. (d) Captive coastal Atyphella feeding on snail.
Reassessing the taxonomy of Libidibia ferrea complex, the iconic Brazilian tree "pau-ferro" using morphometrics and ecological niche modeling
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Ecological niche modelling to project past, current and future distributional shift of black ebony tree (Diospyros melanoxylon Roxb.) in India
<p>The present study utilized an ensemble modelling approach to predict the distribution of <em>D. melanoxylon</em> under present, past (Last Glacial Maximum, ~22,000 cal yr BP, Middle Holocene ~6000 cal yr BP) and future climate change scenarios (RCP 2.6 and 8.5 for 2050s and 2070s). The annual mean temperature, mean temperature of the wettest quarter and annual precipitations were the most critical parameters that chiefly influence the distribution of <em>D. melanoxylon</em>. The ensemble model rendered high accuracy with AUC=0.93, TSS=0.74, and Kappa=0.71. Past projections of <em>D. melanoxylon</em> indicated a widespread distribution during the Last Glacial Maximum and Middle Holocene suggesting its adaptability to semi-dry as well as warm and humid climates, respectively. The presence of fossil pollen evidence of <em>D. melanoxylon</em> in the suitable habitats derived through past projections in this study complements the model results and marks occurrences of the species during the Last Glacial Maximum and Middle Holocene. By 2050s and 2070s (RCP 8.5), there would be a decline in the distribution by only 0.4% (13622 km2) and 0.2% (6842 km2) of the extremely habitat suitable, respectively. The main factor leading to reduced habitat suitability is the anticipated rise in temperature and variations in seasonal precipitation patterns. Our findings, help in identifying the parts of the country which would be severely affected by future climate change scenarios and plan conservation strategies for this commercially important species to facilitate its growth in suitable habitats which are likely to sustain under future climatic conditions.</p>
Fig. 8 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 8. Myosotis antarctica subsp. traillii photographs and distribution map. (a) Habit. (b, d) Rosette leaf tips: (b) adaxial and (d) abaxial sides. (c) Flower. (e) Nutlets. (f) Map of georeferenced herbarium specimens observed by J. M. Prebble (35). Whie scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, e by J. M. Prebble (a: WELT SP100487, Tiwai Point, Southland, South Island; e: WELT SP104518, cultivated ex Mason Bay, Stewart Island). b, c © Te Papa by H. M. Meudt (b: WELT SP090544, Manihi Rd, Taranaki, North Island; c: WELT SP090629, Hukanui, Gisborne, North Island; d: WELT SP090631, Waipuna, Gisborne, North Island).
Fig. 2 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 2. Maps of MaxEnt niche models for pygmy Myosotis in New Zealand and southern South America. (a) Myosotis glauca (light blue circles). (b) M. pygmaea (green circles). (c, h) M. "Volcanic Plateau" (grey triangles). (d) M. brevis (yellow cir-cles). (e) M. drucei (dark blue circles; excluding individuals identified as M. "Volcanic Plateau"). (f) M. drucei (dark blue circles) + M. pygmaea (green circles) + M. "Volcanic Plateau" (grey triangles) (g) M. antarctica (pink circles; Chilean locations), note scale is the same as for maps of New Zealand. a–f use models based on the nine-layer model (see Table 1), whereas g and h are based on the sevenlayer model.
Fig. 5 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 5. Myosotis glauca photographs and distribution map. (a) Habit. (b) Rosette leaves, adaxial and abaxial sides. (c) Calyces, left to right most to least mature. (d) Nutlets. (e) Map of georeferenced herbarium specimens observed by J. M. Prebble (16). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: all by J. M. Prebble (WELT SP093285, Nevis Valley, Otago).
Fig. 4 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 4. Myosotis brevis photographs and distribution map. (a) Habit. (b) Inflorescence showing cauline leaf abaxial side. (c) Inflorescence showing cauline leaf adaxial side, calyces, and flower. (d) Rosette leaf adaxial side showing colour morphs. (e) Flower. (f) Nutlet. (g) Map of georeferenced herbarium specimens observed by J. M. Prebble (25). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: a–e © Te Papa by H. M. Meudt (a: WELT SP090549, Te Ikaamaru Bay, Wellington; b, c: WELT SP090545, Ngawi, Wairarapa; d: WELT SP090543, Stent Road, Taranaki; e: WELT SP090550, Ohau Bay, Wellington); f by J. M. Prebble (WELT SP090543, cultivated ex Stent Road, Taranaki).
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 7. Myosotis antarctica subsp. antarctica. Illustration reproduced from Bot. Antarct. Voy. I. (Fl. Antarct.) Part I, plate 38 (Hooker 1844). Illustration by W. H. Fitch. This image is in the public domain, downloaded from the Biodiversity Heritage Library (https:// www.biodiversitylibrary.org/page/13448452#page/81/ mode/1up, accessed 8 June 2021). Draft pencil drawings for this figure are attached to the type specimen of M. antarctica (K0007878799; visible online at http:// apps.kew.org/herbcat/getImage.do?imageBarcode= K000787899, accessed 8 June 2021), which was collected by J. D. Hooker from Campbell Island.
Fig. 6 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 6. Myosotis antarctica subsp. antarctica photographs and distribution maps. (a, b) Habit. (c) Rosette leaves abaxial and adaxial sides. (d) Flower. (e) Nutlets. (f) Map of mainland New Zealand distribution based on georeferenced herbarium specimens observed by J. M. Prebble (163). (g) Map of Campbell Island distribution based on georeferenced herbarium specimens observed by J. M. Prebble (14). (h) Map of Chilean distribution based on georeferenced herbarium specimens observed by J. M. Prebble (2). White scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, c, e by J. M. Prebble (a: WELT SP102777, Mt Azimuth, Campbell Island; c: WELT SP093293, Port Hills, Canterbury, South Island E: WELT SP100466, cultivated ex Mt Peel, Western Nelson. South Island). b, d © Te Papa by H. M. Meudt (b: WELT SP106592, Matiri Range, Western Nelson, South Island; d: WELT SP107322, Mt Starveall, Western Nelson, South Island).
Fig. 3 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 3. Plots displaying (a, c) omission and commission values and (b, d) area under the receiving operating characteristic curve (AUC) for two pygmy forget-me-not taxa: (a, b) M. "Volcanic Plateau" and (c, d) M. drucei, modelled using MaxEnt and all nine environmental layers for the New Zealand extent.
Fig. 1. Maps displaying all 290 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 1. Maps displaying all 290 occurrence points used for Myosotis pygmy species group niche modelling (Supplementary Table S1). Maps, clockwise from top: World, New Zealand, Campbell Island, and southern South America. Colour represents a priori species: M. antarctica (pink circles); M. drucei (dark blue circles); M. pygmaea (green circles); M. brevis (yellow circles); M. glauca (light blue circles); M. "Volcanic Plateau" (grey triangles).
Worldclim 2.1 versus Worldclim 1.4: climatic niche and grid resolution affect between-version mismatches in habitat suitability models predictions across Europe
<p>The influence of climate on the distribution of taxa has been extensively investigated in the last two decades through Habitat Suitability Models (HSMs). In this context, the Worldclim database represents an invaluable data source as it provides worldwide climate surfaces for both historical and future time horizons. Thousands of HSMs-based papers have been published taking advantage of Worldclim 1.4, the first online version of this repository. In 2017, Worldclim 2.1 was released. Here, we evaluated spatially explicit prediction mismatch at continental scale, focusing on Europe, between HSMs fitted using climate surfaces from the two Worldclim versions (between-version differences). To this aim, we simulated occurrence probability and presence-absence across Europe of four virtual species (VS) with differing climate-occurrence relationships. For each VS, we fitted HSMs upon uncorrelated bioclimatic variables derived from each Worldclim version at three grid resolutions. For each factor combination, HSMs attaining sufficient discrimination performance on spatially independent test data were projected across Europe under current conditions and various future scenarios, and importance scores of the single variables were computed. HSMs failed in accurately retrieving the simulated climate-occurrence relationships for the climate-tolerant VS and the one occurring under a narrow combination of climatic conditions. Under current climate, noticeable between-version prediction mismatch emerged across most of Europe for these two VSs, whose simulated suitability mainly depended upon diurnal or yearly variability in temperature; differently, between-version differences were more clustered toward areas showing extreme values, like mountainous massifs or southern regions, for VSs responding to average temperature and precipitation trends. Under future climate, the chosen emission scenarios and Global Climate Models did not evidently influence between-version prediction discrepancies, while grid resolution synergistically interacted with VSs' niche characteristics in determining extent of such differences. Our findings could help in re-evaluating previous biodiversity-related works relying on geographical predictions from Worldclim-based HSMs.</p>
FIGURE 6 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 6. MaxEnt model outputs for Ampedus samedovi. Minimum Training Presence threshold is applied to outputs.
FIGURE 5 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 5. MaxEnt model outputs for Ampedus platiai. Minimum Training Presence threshold is applied to outputs.
FIGURE 2 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 2. Distributions and collecting localities of Ampedus platiai and Ampedus samedovi. Red: Distribution of only A. platiai in the provinces, Blue: Distribution of only A. samedovi in the provinces, Yellow: Distribution of A. platiai and A. samedovi in the provinces (The map is designed in ArcGis 10.2).
FIGURE 1 in Comparisons of two cryptic Ampedus species (Coleoptera: Elateridae) by using classical systematics, ecological niche modeling, and DNA barcoding
FIGURE 1. Habitus and aedeagi photos of examined species. A–B. Ampedus platiai, C–D. A. samedovi, E–F. A. pomonae (Aedeagi of A. platiai and A. samedovi are redrawn from Kabalak 2010 and aedeagus of A. pomonae is redrawn from Platia 1994.). BML: Basal struts of median lobe, BP: Basal piece, ML: Median Lobe, PDT: Paramere distal tooth, PR: Paramere.
Spatiotemporal monitoring of the rare Northern dragonhead, Dracocephalum ruyschiana (Lamiaceae): SNP genotyping and environmental niche modelling herbarium specimens
<p><strong>Aim: </strong>We have studied spatiotemporal genetic change in the Northern dragonhead, a plant species that has experienced a drastic population decline and habitat loss in Europe. We add a temporal perspective to the monitoring of dragonhead in Norway by genotyping herbarium specimens up to 200 years old. We also assess whether dragonhead has achieved its potential distribution in Norway. Location: Europe (mainly Norway)</p> <p><strong>Methods:</strong> We have applied a microfluidic array consisting of 96 SNP markers on 130 herbarium specimens collected from 1820 to 2008, mainly from Norway (83) but also beyond (47). We have compared our new genotype data with existing data from modern samples. We have modelled the species' environmental niche and potential distribution in Norway using sample metadata and observational records.</p> <p><strong>Results: </strong>The SNP array successfully genotyped all included herbarium specimens. The captured genetic diversity was negatively correlated with distance from Norway. The historical-modern comparison revealed similar genetic structure and diversity across space and limited genetic change through time in Norway. The ENM suggests that dragonhead is anchored in warmer and drier habitats.</p> <p><strong>Main conclusions: </strong>With appropriate design procedures, the SNP array technology is promising for genotyping old herbarium specimens. We found no signs of any regional bottleneck. The regional areas in Norway have remained genetically divergent, however, both from each other and more so from populations outside of Norway, rendering continued protection of the species in Norway relevant. The ENM suggests that dragonhead has not fully achieved its potential distribution in Norway.</p>
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Allen Brain Atlas
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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.