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12 de jun. de 2024 · Species distribution models (SDMs) are statistical and machine learning tools that correlate species’ locations with environmental predictors (that is, covariates, variables and parameters)...
21 de jun. de 2024 · Predicting and explaining species occurrence using environmental characteristics is essential for nature conservation and management. Species distribution models consider species occurrence as the dependent variable and environmental conditions as the independent variables.
22 de jun. de 2024 · Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization.
24 de jun. de 2024 · Species distribution models consider species occurrence as the dependent variable and environmental conditions as the independent variables. Suitable conditions are estimated based on a sample of species observations, where one assumes that the underlying environmental conditions are known.
Hace 6 días · Species distribution models (SDMs) are widely used to infer species–environment relationships, predict spatial distributions and characterise species' environmental niches. While the importance of space and spatial scales is widely acknowledged in SDM applications, temporal components of the niche are rarely addressed. ...
28 de jun. de 2024 · dynamicSDM: Species Distribution and Abundance Modelling at High Spatio-Temporal Resolution. A collection of novel tools for generating species distribution and abundance models (SDM) that are dynamic through both space and time.
16 de jun. de 2024 · We developed species distribution models (SDMs) using Maxent modeling soft- ware for each Psilochalcis species to identify areas of probable suitable habitat for targeted collecting to improve our knowledge of their distributions.
