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208 results for “geographic patterns”
Supplementary material 2 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
: Data type: image
Figures 8-10 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
Figures 8-10 Chrysoteuchiacurvicavus Song & Chen 8 head in lateral view, male 9 adult, male 10 male genitalia.
Figures 3-7 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
Figures 3-7 Chrysoteuchialandryi sp. nov. 3–6 holotype, male 7 paratype, female 3 head in lateral view 4 head in dorsal view 5 adult 6 male genitalia 7 female genitalia.
Figure 1 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
Figure 1 Potential distribution of Chrysoteuchia in China. Histograms show the contribution in percentage of the important variables affecting the distribution patterns. The rainbow bar indicates logistic values of potential habitats.
Supplementary material 1 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
: Data type: species data
Figure 2 from: Jie L-L, Yang J-B, Li W-C (2019) The geographical distribution patterns of Chrysoteuchia Hübner in China and description of a new species (Lepidoptera, Crambidae). ZooKeys 853: 109-118. https://doi.org/10.3897/zookeys.853.34149
Figure 2 Geographical distribution of Chrysoteuchia in China and precipitation of the warmest quarter (Bio18). White circles indicate surveyed sites and number of species per site. Green bars show the known numbers of species at every 5° between 20°N and 55°N.
Fig. 1 in A volunteer-populated online database provides evidence for a geographic pattern in symptoms of black spot infections
Fig. 1. Example photos of a blacknose dace, a stoneroller (Campostoma sp.), a creek chub, and a chub (Nocomis sp.) exhibiting evidence of a black grub infection.
Fig. 3 in A volunteer-populated online database provides evidence for a geographic pattern in symptoms of black spot infections
Fig. 3. If an observation of blacknose dace, creek chub, chubs (Nocomis spp.), or stonerollers (Campostoma spp.) is reported on iNaturalist from the watersheds of Northern Lake Erie or Lake Ontario – Niagara Peninsula it is more likely to exhibit macroscopic signs of infection by metacercariae. Also a high percentage of the observations by user bkorol exhibited symptoms, all from Eastern Georgian Bay which is adjacent to the two other watersheds mentioned. Data were analyzed using conditional information trees in r using package caret to train and tune the model. Percentage of actual observations summarized in bar charts below each split that significantly described the data.
Fig. 2 in A volunteer-populated online database provides evidence for a geographic pattern in symptoms of black spot infections
Fig. 2. Watersheds shaded by the percentage of observations with signs of black spot infection for four groups of fishes, each of which show higher prevalence in the watersheds near Toronto and the northern shoreline of Lake Erie. Watersheds are transparent if only 1 or 2 fish were observed in them, otherwise they increase in opaqueness as sample number increase, those with>15 observations are solid. Refer to Table 1 for numbers.
Data from: Geographical patterns in phylogenetic diversity of Chinese woody plants and its application for conservation planning
<p><b>Aim:</b> Biodiversity hotspots are widely used as conservation priorities to preserve the tree of life. However, many conservation practices identify biodiversity hotspots without considering phylogenetic diversity (PD), which reflects total evolutionary history and feature diversity of a region. Moreover, conservation planning rarely distinguishes between neo- and paleo-biodiversity hotspots despite their differences. Here, we 1) estimated large-scale patterns in PD of woody plants, 2) identified neo- and paleo-biodiversity hotspots, and 3) demonstrated their implication in conservation planning, with special focus on Hengduan Mountains and southern China.</p> <p><b>Location: </b>China.</p> <p><b>Methods: </b>Distributions of 11,405 woody species from the <i>Atlas of Woody Plants in China</i> were updated, and were transformed into a grid of 50 × 50 km<sup>2</sup>. By integrating distribution maps with a genus-level phylogeny of angiosperms, <span>we estimated Faith's PD of each grid cell and evaluated </span>the contribution of species relatedness to PD at given levels of species diversity (i.e. standardized PD, sPD) using <span>regressions </span>and three null models. Then we identified areas with significantly lower or higher sPD than expected as neo- and paleo-hotspots and estimated the coverage of protected areas in these regions.</p> <p><b>Results:</b> Species diversity and PD decreased towards the north. Southern China had high species diversity, PD and sPD, while Hengduan Mountains had high species diversity and PD but low sPD. The coverage of protected areas in southern China was less than half of that in Hengduan Mountains and entire China.</p> <p><b>Main conclusions:</b> Our results identified Hengduan Mountains as a neo-hotspot and southern China as a paleo-hotspot, highlighting their importance for biodiversity conservation. Compared to Hengduan Mountains, southern China has low coverage of protected areas, which calls for more conservation attention. Our study demonstrates a way of incorporating the phylogenetic component in the identification of neo- and paleo-hotspots, and hence of achieving a more complete perception of biodiversity patterns for conserving the tree of life.</p>
Geographic patterns of Lucanus (Coleoptera: Lucanidae) species diversity and its environmental determinants in China
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Extraordinary variation in a simple song: No geographical patterns in initial phrase variation of the Yellowhammer, a passerine with pronounced dialects
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Demographic history shaped geographical patterns of deleterious mutation load in a broadly distributed Pacific Salmon
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Primary data on skull and brain morphology for: Geographical patterns in seasonal changes of body mass, skull, and brain size of common shrews
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Data from: Geographically distinct patterns of reproductive isolation and hybridisation in two sympatric species of the Jaera albifrons complex (marine isopods)
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Data from: Geographical patterns in phylogenetic diversity of Chinese woody plants and its application for conservation planning
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Stable Patterns of Gene Expression Regulating Carbohydrate Metabolism Determined by Geographic Ancestry
GEO Series GSE12959. Homo sapiens. 161 samples. Type: Expression profiling by array.
Data from: Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system
To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.
Figure 7 from: Ythier E, Lourenço WR (2017) The geographical patterns of distribution of the genus Teuthraustes Simon, 1878 in Ecuador and description of three new species (Scorpiones, Chactidae). ZooKeys 721: 45-63. https://doi.org/10.3897/zookeys.721.21529
Figure 7 - Teuthraustes kuryi sp. n. Female holotype. A–B Habitus, dorsal A and ventral B aspects.
Figure 2 from: Ythier E, Lourenço WR (2017) The geographical patterns of distribution of the genus Teuthraustes Simon, 1878 in Ecuador and description of three new species (Scorpiones, Chactidae). ZooKeys 721: 45-63. https://doi.org/10.3897/zookeys.721.21529
Figure 2 - Vegetation map of Ecuador showing the distribution of the known species of Teuthraustes.
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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.