Predicting species’ potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, an...
© 2021 Roozbeh ValaviSpecies Distribution Modelling (SDM) is a widely used tool in ecological studie...
1Species distribution models could bring manifold benefits across ecology, but require careful testi...
Digitized species occurrence data provide an unprecedented source of information for ecologists and ...
Predicting species’ potential geographical range by species distribution models (SDMs) is central to...
Predicting species' potential geographical range by species distribution models (SDMs) is central to...
Aim: Forecasting changes in species distribution under future scenarios is one of the most prolific ...
<div><p>Species distribution modeling (SDM) is an increasingly important tool to predict the geograp...
A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others t...
A large array of species distribution model (SDM) approaches has been developed for explaining and p...
Aim Species Distribution Models (SDM) can be used to predict the location of unknown populations fro...
In past decades, a variety of statistical techniques have been used and developed to predict species...
Species distribution modeling (SDM) is an increasingly important tool to predict the geographic dist...
Species distribution modeling (SDM) is an increasingly important tool to predict the geographic dist...
Species distribution models (SDMs) are widely used predictive tools to forecast potential biological...
The evaluation of species distribution models (SDMs) is a crucial step; usually, a random subsample ...
© 2021 Roozbeh ValaviSpecies Distribution Modelling (SDM) is a widely used tool in ecological studie...
1Species distribution models could bring manifold benefits across ecology, but require careful testi...
Digitized species occurrence data provide an unprecedented source of information for ecologists and ...
Predicting species’ potential geographical range by species distribution models (SDMs) is central to...
Predicting species' potential geographical range by species distribution models (SDMs) is central to...
Aim: Forecasting changes in species distribution under future scenarios is one of the most prolific ...
<div><p>Species distribution modeling (SDM) is an increasingly important tool to predict the geograp...
A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others t...
A large array of species distribution model (SDM) approaches has been developed for explaining and p...
Aim Species Distribution Models (SDM) can be used to predict the location of unknown populations fro...
In past decades, a variety of statistical techniques have been used and developed to predict species...
Species distribution modeling (SDM) is an increasingly important tool to predict the geographic dist...
Species distribution modeling (SDM) is an increasingly important tool to predict the geographic dist...
Species distribution models (SDMs) are widely used predictive tools to forecast potential biological...
The evaluation of species distribution models (SDMs) is a crucial step; usually, a random subsample ...
© 2021 Roozbeh ValaviSpecies Distribution Modelling (SDM) is a widely used tool in ecological studie...
1Species distribution models could bring manifold benefits across ecology, but require careful testi...
Digitized species occurrence data provide an unprecedented source of information for ecologists and ...