SPATIAL AUTOCORRELATION AND AUTOREGRESSIVE MODELS IN ECOLOGY
2002; Wiley; Volume: 72; Issue: 3 Linguagem: Inglês
10.1890/0012-9615(2002)072[0445
ISSN1557-7015
AutoresJeremy W. Lichstein, Theodore R. Simons, Susan A. Shriner, Kathleen E. Franzreb,
Tópico(s)Wildlife Ecology and Conservation
ResumoEcological MonographsVolume 72, Issue 3 p. 445-463 Monograph SPATIAL AUTOCORRELATION AND AUTOREGRESSIVE MODELS IN ECOLOGY Jeremy W. Lichstein, Jeremy W. Lichstein Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USA Current address: Laboratorio de Investigaciones Ecológicas de las Yungas, Casilla de Correo 34, (4107) Yerba Buena, Tucumán, ArgentinaSearch for more papers by this authorTheodore R. Simons, Theodore R. Simons Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USA Author for reprints ( E-mail: [email protected]).Search for more papers by this authorSusan A. Shriner, Susan A. Shriner Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USASearch for more papers by this authorKathleen E. Franzreb, Kathleen E. Franzreb Southern Appalachian Cooperative Ecosystems Studies Unit, Department of Forestry, Wildlife, and Fisheries, University of Tennessee, Knoxville, Tennessee 37901 USASearch for more papers by this author Jeremy W. Lichstein, Jeremy W. Lichstein Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USA Current address: Laboratorio de Investigaciones Ecológicas de las Yungas, Casilla de Correo 34, (4107) Yerba Buena, Tucumán, ArgentinaSearch for more papers by this authorTheodore R. Simons, Theodore R. Simons Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USA Author for reprints ( E-mail: [email protected]).Search for more papers by this authorSusan A. Shriner, Susan A. Shriner Cooperative Fish and Wildlife Research Unit, Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695-7617 USASearch for more papers by this authorKathleen E. Franzreb, Kathleen E. Franzreb Southern Appalachian Cooperative Ecosystems Studies Unit, Department of Forestry, Wildlife, and Fisheries, University of Tennessee, Knoxville, Tennessee 37901 USASearch for more papers by this author First published: 01 August 2002 https://doi.org/10.1890/0012-9615(2002)072[0445:SAAAMI]2.0.CO;2Citations: 644 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available software, to examine breeding habitat relationships for three common Neotropical migrant songbirds in the southern Appalachian Mountains of North Carolina and Tennessee, USA. In preliminary models that ignored space, the abundance of all three species was correlated with both local- and landscape-scale habitat variables. These models were then modified to account for broadscale spatial trend (via trend surface analysis) and fine-scale autocorrelation (via an autoregressive spatial covariance matrix). Residuals from ordinary least squares regression models were autocorrelated, indicating that the assumption of independent errors was violated. In contrast, residuals from autoregressive models showed little spatial pattern, suggesting that these models were appropriate. The magnitude of habitat effects tended to decrease, and the relative importance of different habitat variables shifted when we incorporated broadscale and then fine-scale space into the analysis. The degree to which habitat effects changed when space was added to the models was roughly correlated with the amount of spatial structure in the habitat variables. Spatial pattern in the residuals from ordinary least squares models may result from failure to include or adequately measure autocorrelated habitat variables. In addition, contagious processes, such as conspecific attraction, may generate spatial patterns in species abundance that cannot be explained by habitat models. 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