Details zur Publikation
Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1111/j.1466-8238.2006.00279.x
Titel (primär) Effects of incorporating spatial autocorrelation into the analysis of species distribution data
Autor Dormann, C.F.
Quelle Global Ecology and Biogeography
Erscheinungsjahr 2007
Department CLE
Band/Volume 16
Heft 2
Seite von 129
Seite bis 138
Sprache englisch
Keywords Autologistic regression; autoregressive model; spatial statistics; spatial autocorrelation; species distribution analysis; statistical biogeography
Abstract Aim Spatial autocorrelation (SAC) in data, i.e. the higher similarity of closer samples, is a common phenomenon in ecology. SAC is starting to be considered in the analysis of species distribution data, and over the last 10 years several studies have incorporated SAC into statistical models (here termed 'spatial models'). Here, I address the question of whether incorporating SAC affects estimates of model coefficients and inference from statistical models.Methods I review ecological studies that compare spatial and non-spatial models.Results In all cases coefficient estimates for environmental correlates of species distributions were affected by SAC, leading to a mis-estimation of on average c. 25%. Model fit was also improved by incorporating SAC.Main conclusions These biased estimates and incorrect model specifications have implications for predicting species occurrences under changing environmental conditions. Spatial models are therefore required to estimate correctly the effects of environmental drivers on species present distributions, for a statistically unbiased identification of the drivers of distribution, and hence for more accurate forecasts of future distributions.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=1722
Dormann, C.F. (2007):
Effects of incorporating spatial autocorrelation into the analysis of species distribution data
Glob. Ecol. Biogeogr. 16 (2), 129 - 138 10.1111/j.1466-8238.2006.00279.x