Analysis of determinants of mammalian species richness in South America using spatial autoregressive models

摘要: Classically, hypotheses concerning the distribution of species have been explored by evaluating relationship between richness and environmental variables using ordinary least squares (OLS) regression. However, ecological data generally show spatial autocorrelation, thus violating assumption independently distributed errors. When autocorrelation exists, an alternative is to use autoregressive models that assume spatially autocorrelated We examined mammalian in South America variables, thereby relative importance four competing explain richness. Additionally, we compared results regression Conditional Simultaneous Autoregressive (CAR SAR, respectively) models. Variables associated with productivity were most important at determining scale analyzed. Whereas OLS residuals strongly autocorrelated, those from showed less particularly SAR model, indicating its suitability for these data. also fit better than model (increasing R2 5-14%), explanatory shifted under CAR These analyses underscore controlling biogeographical studies.