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487 results for “species distribution modeling”
Figure 3 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
Figure 3 Most likely migration model and altitudinal habitat maps reporting suitable area for the presence of the species during cold periods. A Most likely migration model. Arrows indicate unidirectional flows (in black) and bidirectional flows (in gray) between populations. B–F Suitable altitudinal habitat maps. In light grey are reported the areas suitable for the presence of the species above a certain altitudinal threshold; the yellow ellipses are schematic drawing of Cryptocephalusbarii populations; dendrograms showing the divergence events among populations, according to the tree in Fig. 1, are superimposed on the maps. At the bottom left of each map are reported: the minimum elevation at which climatic conditions are suitable for the presence of Cryptocephalusbarii (inferred from present knowledge) corresponding to the altitudinal threshold used to draw the suitable areas, and the corresponding estimates of temperature variation in respect to the present. Abbreviations: A.T. = altitudinal threshold; CON = Concarena; PRE = Presolana; ARE = Arera; ALB = Alben; GRI = Grigna; NGR = northern Grigna; SGR = southern Grigna; CG = Corna Grande; PEG = Pegherolo.
Figure 2 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
Figure 2 Maximum clade credibility tree and Minimum-spanning haplotype network. A Minimum-spanning haplotype network. Each colour represents a Cryptocephalusbarii population. Circles represent the different haplotypes; their diameter is proportional to the haplotypes abundance. B Maximum clade credibility tree. Horizontal blue bars represent 95% HPD age confidence intervals for the nodes. Under the main lineage nodes is reported the divergence time in thousands of years before present. Above the nodes Bayesian posterior probabilities > 0.8 are reported, black asterisks indicate Bayesian posterior probabilities values < 0.80. Vertical coloured bars on the right of the tree indicate monophyletic clades, the colours identify the C.barii populations. Under the tree, in blue, the estimated surface temperature for the last 800,000 years (Hansen et al. 2013).
Supplementary material 2 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
: Data type: statistical data
Figure 1 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
Figure 1 Cryptocephalusbarii Burlini, 1948 distribution. A) Geographic location of the Orobie Alps and Cryptocephalusbarii distribution. Yellow dots indicate localities where the species was observed, red dots indicate localities investigated with extensive sampling campaigns in which the species was absent (the source map was downloaded from http://www.geoportale.regione.lombardia.it/ and elaborated with QGIS 3.4.1). B) Cryptocephalusbarii picture acquired using a Canon 450D camera; the multilayered micrographs were processed with Zerene Stacker (Richland, WA, USA).
Figure 5 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
Figure 5 Changes in habitat suitability for Cryptocephalusbarii. Histogram reporting classes of habitat suitability calculated within the Minimum Convex Polygon built on Cryptocephalusbarii presence sites through Ensemble Modelling process. Areas calculated for current and future climatic conditions (2070, 4.5 and 8.5 scenarios) are reported, respectively, in green, orange and red.
Figure 4 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
Figure 4 Predicted suitability for Cryptocephalusbarii for current and future climatic conditions. Predicted suitability resulting from the Ensemble Modelling process performed over bioclimatic variables for Cryptocephalusbarii, with the Minimum Convex Polygon built on the species' presence sites for A current B 2070 – 4.5 scenario of radiative forcing, and C 2070 – 8.5 scenario of radiative forcing.
Supplementary material 1 from: Brunetti M, Magoga G, Iannella M, Biondi M, Montagna M (2019) Phylogeography and species distribution modelling of Cryptocephalus barii (Coleoptera: Chrysomelidae): is this alpine endemic species close to extinction? In: Schmitt M, Chaboo CS, Biondi M (Eds) Research on Chrysomelidae 8. ZooKeys 856: 3-25. https://doi.org/10.3897/zookeys.856.32462
: Data type: statistical model
РИС. 6. Пригодность местообитанийдля Brephulopsis cylindrica согласно протестированным моделям четырех типов. Имя колонки обоЗначает номер выборки. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 6. Пригодность местообитанийдля Brephulopsis cylindrica согласно протестированным моделям четырех типов. Имя колонки обоЗначает номер выборки.
РИС. 5. Пригодность местообитаний для Xeropicta derbentina согласно протестированным моделям четырех типов. Имя колонки обоЗначает номер выборки. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 5. Пригодность местообитаний для Xeropicta derbentina согласно протестированным моделям четырех типов. Имя колонки обоЗначает номер выборки.
РИС. 2. РеЗультаты кластерного аналиЗа по методу Уорда: дендрограмма и кластеры на карте. Цветами выделены кластеры с 1 по 6. in Land snails Brephulopsis cylindrica and Xeropicta derbentina (Gastropoda: Stylommatophora): case study of invasive species distribution modelling
РИС. 2. РеЗультаты кластерного аналиЗа по методу Уорда: дендрограмма и кластеры на карте. Цветами выделены кластеры с 1 по 6.
Fig. 1 in Parasite species co-occurrence patterns on Peromyscus: Joint species distribution modelling
Fig. 1. Summary of positive (green, +) and negative (red, -) associations between ectoparasite species (flea (Orchopeas leucopus), mite (Neotrombicula microti), botfly (Cuterebra sp.)) on deer mice with statistical support of at least 95% posterior probability (n = 229 individuals). Results presented are from the constrained model (species interactions) or unconstrained model (species associations). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Data for Spangenberg, Simpkins and Wiegand "Species distribution modeling using commonness optimization leads to poor predictions for rare species"
Open the record for dataset details and reuse information.
Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
<p>Climate change and habitat loss are main threats to forest biodiversity. We fitted ensembles of single species distribution models for 23 deadwood-living bryophyte species in Sweden, based on species records from the Swedish Lifewatch website. This data set comprises the species and environmental data used for species distribution modelling, and coefficients of the fitted single species distribution models (GLM, Poisson point-process, MaxEnt).</p> <p>Based on the fitted species distribution models, we conducted simulations of future species distributions given realistic climate and forest projection scenarios at the national scale of Sweden. The data used for the scenario analysis are stored here.</p>
Figure 4 from: Sarkinen T, Gonzáles P, Knapp S (2013) Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes. PhytoKeys 31: 1-20. https://doi.org/10.3897/phytokeys.31.6312
Figure 4 - Photos of Solanum pseudoamericanum. A Habit B Ridged stem C Flowers with small anthers c. 1.5 mm long, strongly exserted styles and with capitate stigmas D Developing fruits which turn purple-black when fully ripe with calyx appressed to the fruit. (A Särkinen et al. 4640; B Knapp et al. 10357; C, D Knapp et al. 10300) Scale bars = 1 mm.
Figure 1 from: Sarkinen T, Gonzáles P, Knapp S (2013) Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes. PhytoKeys 31: 1-20. https://doi.org/10.3897/phytokeys.31.6312
Figure 1 - Potential habitat distribution map of Solanum pseudoamericanum. The potential habitat areas reflect the cumulative output of the MAXENT model produced using 11 climatic variables with the original four collection localities from 2012 from southern Peru shown as grey squares on the map (see Methods for details). Areas identified as highly suitable (above 40% cumulative probability) in central and northern Peru were visited in 2013 during the second field season, and 17 new collection localities were found as a result (black squares). Five additional collections were identified amongst herbarium loans (purple triangles).
Figure 3 from: Sarkinen T, Gonzáles P, Knapp S (2013) Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes. PhytoKeys 31: 1-20. https://doi.org/10.3897/phytokeys.31.6312
Figure 3 - Illustration of Solanum pseudoamericanum. A Habit B Adaxial leaf surface C Abaxial leaf surface D Bud E Half flower F Fruit (A–F Knapp 10351). Illustration by Rosemary Wise.
Figure 2 from: Sarkinen T, Gonzáles P, Knapp S (2013) Distribution models and species discovery: the story of a new Solanum species from the Peruvian Andes. PhytoKeys 31: 1-20. https://doi.org/10.3897/phytokeys.31.6312
Figure 2 - Distribution map of Solanum pseudoamericanum. The potential habitat areas reflect the logistic output of the MAXENT model produced using 11 climatic variables with all current known occurrence records (N=26; Model 2).
FIGURE 1 in Distribution, Regionalization, and Diversity of the dung beetle genus Phanaeus MacLeay (Coleoptera: Scarabaeidae) using Species Distribution Models
FIGURE 1. Edmonds' (1994) distribution patterns of Phanaeus.
Figure 91 in Predicted and recorded distribution maps of the genus Phanaeus (Coleoptera: Scarabaeidae). Supplementary material of Distribution, Regionalization, and Diversity of the dung beetle genus Phanaeus MacLeay (Coleoptera: Scarabaeidae) using Species Distribution Models
Figure 91: Predicted and recorded distribution of Phanaeus vindex.
Figure 90 in Predicted and recorded distribution maps of the genus Phanaeus (Coleoptera: Scarabaeidae). Supplementary material of Distribution, Regionalization, and Diversity of the dung beetle genus Phanaeus MacLeay (Coleoptera: Scarabaeidae) using Species Distribution Models
Figure 90: Predicted and recorded distribution of Phanaeus igneus.
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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)
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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.