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1,276 results for “distribution map”
FIGURE 2 in Description and bioecology of two new species of the genus Cryncus (Orthoptera Gryllidae, Gryllinae) from Cameroon with a key and distribution map of all African species
FIGURE 2. Morphology of Cryncus camerounensis sp. nov.: (A) male head and pronotum, (B) male lateral view of head and pronotum, (C) male forewing, (D) female head and pronotum, (E) female lateral view of head and pronotum, (F) female fore wing, (G) male forewing drawing, (H) male genitalia drawing in dorsal view, (I) male genitalia drawing in ventral view. Scale bars: A: 7 mm; B, C, E: 5 mm;D, 8 mm;F, 11 mm;G, 5 mm; H, I, 500 µm.
FIGURE 3 in Description and bioecology of two new species of the genus Cryncus (Orthoptera Gryllidae, Gryllinae) from Cameroon with a key and distribution map of all African species
FIGURE 3. Morphology of Cryncus desutterae sp. nov.: (A) male head and pronotum, (B) male lateral view of head and pronotum, (C) male fore wing, (D) female head and pronotum, (E) female lateral view of head and pronotum, (F) female forewing, (G) male forewing drawing, (H) male genitalia drawing in dorsal view, (I) male genitalia drawing in ventral view. Scale bars: A, 9 mm; B, 8 mm; C, 5 mm; D, F: 7 mm; E, 6 mm; H, I, 500 µm.
Mapping the Redshift Evolution of Hα Equivalent Width Distributions & RST Grism Surveys
<p>The Hα Equivalent Width (EW) is an observational proxy for the specific star formation rate (sSFR) and can give us valuable insight in regards to bursty star formation histories. Studies find Hα EW anti-correlates with stellar mass and increases in redshift similar to the `main sequence’ and sSFR redshift evolution. However, selection effects may bias the underlying results, such that measurements of the intrinsic correlations are needed. In this talk, I will be presenting a new methodology of constraining EW distributions by simulating emission line galaxies assuming an intrinsic EW distribution and applying selection criteria to match observations drawn from Hα narrowband surveys between z ~ 0.4 and 2. This nicely overlaps with the expected redshift coverage of RST planned surveys. We find EW intrinsically correlates with Hα luminosity and stellar mass, while ignoring selection effect corrections causes a steeper correlation. We also observe an increasing redshift evolution between EW and stellar mass. The correlation between EW and stellar mass is found to reproduce the EW distribution, LF, and SMF at all redshifts probed, which suggests it is shaped by physical processes associated with star formation. I will finish by discussing the implication of our results for RST survey planning by taking into account the effective EW threshold in slitless grism surveys set by the limiting resolving power using the redshift evolution of the EW — stellar mass correlation.</p>
Data from: Input matters matter: bioclimatic consistency to map more reliable species distribution models
1. Accuracy of global bioclimatic databases is essential to understand biodiversity-environment relationships. Many studies have explored biases and uncertainties related to species distribution models (SDMs) but the effect of choosing a specific database among the different alternatives has not been previously assessed. 2. The lack of bioclimatic congruence (degree of agreement) between different databases is a main concern in distribution modelling and it is critical in single-source models, for which the database choice is decisive. In order to prevent unreliable predictions derived from distorted input data, SDMs accuracy can be assessed by mapping model predictions according to a bioclimatic congruence measure derived from the comparison of multiple databases, which can be achieved with the bioclimatic consistency maps that we propose in this study. Here, i) we present the first global-scale bioclimatic congruence map to analyse environmental mismatches between recently updated bioclimatic databases. We also test the importance of input matters on the reliability of distribution models of sixteen mammals, by addressing ii) inconsistencies among species response curves (temperature and precipitation), and iii) discrepancies among SDMs predictions depending on the chosen bioclimatic database. Finally, iv) we propose a strategy to assess bioclimatic consistency of model predictions, showing its application to the specific case of Litocranius walleri. 3. Our results confirm that the single-source modelling approach greatly influences the estimation of species-environment relationship and consequently, bias spatial predictions derived from SDMs. This is especially true for studies conducted in polar and mountainous regions which showed the smallest bioclimatic congruence. We show that by adding bioclimatic congruence to SDMs projections, we can build a bioclimatic consistency map that enables the detection of both risky and consistent areas, as revealed for the case of L. walleri. 4. Assessing uncertainty in bioclimatic input data is key to avoid erroneous conclusions in macroecological and biogeographical studies. The spatial characterisation of bioclimatic consistency provides an adequate empirical framework which effectively illustrates bioclimatic data limitations. We strongly recommend that this new strategy should be formally and systematically incorporated into distribution modelling to build more reliable SDMs, which are essential to develop successful biodiversity conservation programmes.
Data from: Incorporating interspecific competition into species-distribution mapping by upward scaling of small-scale model projections to the landscape
There are a number of overarching questions and debate in the scientific community concerning the importance of biotic interactions in species distribution models at large spatial scales. In this paper, we present a framework for revising the potential distribution of tree species native to the Western Ecoregion of Nova Scotia, Canada, by integrating the long-term effects of interspecific competition into an existing abiotic-factor-based definition of potential species distribution (PSD). The PSD model is developed by combining spatially explicit data of individualistic species' response to normalized incident photosynthetically active radiation, soil water content, and growing degree days. A revised PSD model adds biomass output simulated over a 100-year timeframe with a robust forest gap model and scaled up to the landscape using a forestland classification technique. To demonstrate the method, we applied the calculation to the natural range of 16 target tree species as found in 1,240 provincial forest-inventory plots. The revised PSD model, with the long-term effects of interspecific competition accounted for, predicted that eastern hemlock (Tsuga canadensis), American beech (Fagus grandifolia), white birch (Betula papyrifera), red oak (Quercus rubra), sugar maple (Acer saccharum), and trembling aspen (Populus tremuloides) would experience a significant decline in their original distribution compared with balsam fir (Abies balsamea), black spruce (Picea mariana), red spruce (Picea rubens), red maple (Acer rubrum L.), and yellow birch (Betula alleghaniensis). True model accuracy improved from 64.2% with original PSD evaluations to 81.7% with revised PSD. Kappa statistics slightly increased from 0.26 (fair) to 0.41 (moderate) for original and revised PSDs, respectively.
FIGURES 32–34. Discozantaena distribution maps. —32. D. tibiovela. —33. D. leleupi. —34. D in A revision of the South African endemic humicolous beetle genus Discozantaena Perkins and BalfourBrowne (Coleoptera: Hydraenidae)
FIGURES 32–34. Discozantaena distribution maps. —32. D. tibiovela. —33. D. leleupi. —34. D. sepiola.
FIGURES 23–25. Discozantaena distribution maps. —23. All Discozantaena collecting sites. — 24. D. sequentia. —25. D in A revision of the South African endemic humicolous beetle genus Discozantaena Perkins and BalfourBrowne (Coleoptera: Hydraenidae)
FIGURES 23–25. Discozantaena distribution maps. —23. All Discozantaena collecting sites. — 24. D. sequentia. —25. D. endroedyi.
FIGURES 26–28. Discozantaena distribution maps. —26. D. drakensbergensis. —27. D. genuvela. —28. D in A revision of the South African endemic humicolous beetle genus Discozantaena Perkins and BalfourBrowne (Coleoptera: Hydraenidae)
FIGURES 26–28. Discozantaena distribution maps. —26. D. drakensbergensis. —27. D. genuvela. —28. D. brevicollis.
FIGURES 26–28. Pneuminion distribution maps. —26. P. balfourbrownei. —27. P. impressum. —28. P in A revision of the South African endemic water beetle genus Pneuminion Perkins (Coleoptera: Hydraenidae)
FIGURES 26–28. Pneuminion distribution maps. —26. P. balfourbrownei. —27. P. impressum. —28. P. nanum.
FIGURES 23–25. Pneuminion distribution maps. —23. P. velamen. —24. P. semisulcatum. —25. P. t u b u m in A revision of the South African endemic water beetle genus Pneuminion Perkins (Coleoptera: Hydraenidae)
FIGURES 23–25. Pneuminion distribution maps. —23. P. velamen. —24. P. semisulcatum. —25. P. t u b u m.
FIGURES 21–22. Pneuminion distribution maps. —21. All Pneuminion collecting sites. —22. P in A revision of the South African endemic water beetle genus Pneuminion Perkins (Coleoptera: Hydraenidae)
FIGURES 21–22. Pneuminion distribution maps. —21. All Pneuminion collecting sites. —22. P. endroedyi.
FIGURES 30–32. Distribution maps. 30 in The neotropical genera Microthereva Malloch and Peralia Malloch (Diptera: Therevidae: Therevinae)
FIGURES 30–32. Distribution maps. 30. Microthereva argentiventris (closed circles), M. variventris (arrow). 31. Peralia hermanni. 32. Peralia vittata.
FIGURES 18–19. Distribution maps. 18 in Notes on the Neotropical bee genera Agapostemonoides Roberts & Brooks and Rhinetula Friese, with description of a new species of Agapostemonoides (Hymenoptera, Apidae, Halictinae)
FIGURES 18–19. Distribution maps. 18, Agapostemonoides hurdi and A. weyrauchi sp. nov. 19, Rhinetula denticrus and R. rufiventris.
FIGURES 9–14. Distribution maps. 9 in A synopsis of the Endomychidae (Coleoptera: Cucujoidea) of México
FIGURES 9–14. Distribution maps. 9, Anidrytus mexicanus Strohecker (circles), Anidrytus nitidularius Gerstaecker (triangle), Ephebus sulcatus Strohecker (stars), Epopterus partitus maculosus Gorham (square). 10, Epipocus brunneus Gorham (triangles), Epipocus cinctus LeConte (circles). 11, Epipocus gorhami Strohecker (circles), Epipocus subcostatus Gorham (triangles). 12, Epipocus longicornis Gerstaecker. 13, Epipocus punctatus LeConte (triangles, darker gray, including dubious record from DGO), Epipocus unicolor Horn (circles, lighter gray). 14, Epipocus tibialis (Chevrolat). Shading indicates state record(s) only.
FIGURES 3–8. Distribution maps. 3 in A synopsis of the Endomychidae (Coleoptera: Cucujoidea) of México
FIGURES 3–8. Distribution maps. 3, Bystus limbatus (Gorham). 4, Archipines intricata (Gorham). 5, Corynomalus perforatus Gerstaecker. 6, Stenotarsus latipes Arrow. 7, Stenotarsus marginalis Arrow. 8, Stenotarsus rubrocinctus Gerstaecker. Shading indicates state record(s) only.
FIGURE 23. Distribution map. Chewobrachys limbourgi, C in Revision of the Eurybrachidae (XIII). The new Australian genus Chewobrachys (Hemiptera: Fulgoromorpha)
FIGURE 23. Distribution map. Chewobrachys limbourgi, C. sanguiflua and unidentified females of Chewobrachys in Australia.
FIGURES 23–24. Distribution maps. 23, N in Revision of the Eurybrachidae (XII). The Oriental genus Nicidus Stål, 1858 (Hemiptera: Fulgoromorpha)
FIGURES 23–24. Distribution maps. 23, N. fusconebulosus in Sri Lanka. 24, N. stali in peninsular Malaysia and Borneo.
FIGURES 115–116. Distribution maps for North American Leptonetidae. 115 in A study of the subfamily Archoleptonetinae (Araneae, Leptonetidae) with a review of the morphology and relationships for the Leptonetidae
FIGURES 115–116. Distribution maps for North American Leptonetidae. 115. Distribution of Archoleptoneta in California. A. schusteri localities outlined in orange, A. gertschi sp. nov. localities highlighted in red. Localities for which there are no known males and are in need of additional sampling are outlined in black. 116. Distribution of Darkoneta.
FIGURE 12. Distribution map for Leucaspis albotecta, L in Scale insect fauna (Hemiptera: Sternorrhyncha: Coccoidea) of New Zealand's pygmy mistletoes (Korthalsella: Viscaceae) with description of three new species: Leucaspis albotecta, L. trilobata (Diaspididae) and Eriococcus korthalsellae (Eriococcidae)
FIGURE 12. Distribution map for Leucaspis albotecta, L. trilobata and Eriococcus korthalsellae in New Zealand.
FIGURE 4. Distribution map for P in On the validity of Pelvicachromis sacrimontis Paulo, 1977 (Perciformes, Cichlidae), with designation of a neotype, and redescription of the species
FIGURE 4. Distribution map for P. sacrimontis, based on collection data of neotype and paraneotypes; unfilled dot = type locality for neotype.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.