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Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time.
Here, I provide a short, half-day introduction to species distribution modelling in R. The course gives a brief overview of the concept of species distribution modelling, and introduces the main modelling steps.
Species distribution modelling (SDM), also known as environmental (or ecological) niche modelling (ENM), habitat modelling, predictive habitat distribution modelling, and range mapping uses computer algorithms to predict the distribution of a species across geographic space and time using environmental data. The environmental data are most ...
17 de ene. de 2018 · Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given...
3 de may. de 2023 · Species distribution models (SDMs) have become the most widely used method for wildlife management and have been applied in the fields of ecology, biogeography, and conservation. Species distribution modelling commonly requires two categories of data: (1) species data and (2) environmental data.
Predicting suitable habitats of species from latitude and longitude coordinates has become increasingly easier with a suite of R packages. This introductory tutorial will show you how to turn your coordinate data into a range map.
Species distribution modelling (SDM), also called environmental or ecological niche modelling, combines species locality data, or other attributes of biological diversity, with environmental predictors using statistical and machine learning models to produce empirical descriptions and spatial predictions of species–environment relationships ...
