| Abstract: | Spatial autocorrelation in species‘ distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike‘s information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species‘ distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography. |
| Genre: | Article |
| ProdID: | 70028635 |
| Citation Author: | Bahn, V.; J. , O'Connor, R.; B. , Krohn, W. |
| Citation Contributing Office: | |
| Citation Datum: | |
| Citation Day: | |
| Citation Edition: | |
| Citation Editor: | |
| Citation End Page: | 844 |
| Citation Issue: | 6 |
| Citation Keywords: | |
| Citation Language: | English |
| Citation Larger Work Title: | Ecography |
| Citation LatN: | |
| Citation LatS: | |
| Citation LonE: | |
| Citation LonW: | |
| Citation Month: | |
| Citation No Pagination: | |
| Citation Number Of Pages: | 10 |
| Citation Online Only Flag: | |
| Citation Phsyical Description: | |
| Citation Projection: | |
| Citation Public Comments: | |
| Citation Publisher: | |
| Citation Series: | |
| Citation Series Code: | |
| Citation Series Number: | |
| Citation Search Results Text: | Importance of spatial autocorrelation in modeling bird distributions at a continental scale; 2006; Article; Journal; Ecography; Bahn, V.; J. , O‘Connor, R.; B. , Krohn, W. |
| Citation Start Page: | 835 |
| Citation Volume: | 29 |
| Citation Year: | 2006 |
| Type: | citation/reference |
| Text: | Importance of spatial autocorrelation in modeling bird distributions at a continental scale; 2006; Article; Journal; Ecography; Bahn, V.; J. , O‘Connor, R.; B. , Krohn, W. |
| URL (THUMBNAIL): | http://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg |
| URL (DIGITAL OBJECT IDENTIFIER): | http://dx.doi.org/10.1111/j.2006.0906-7590.04621.x |
| Date Other: | Sun, 1 Jan 2006 00:00 -0600 |
| Publisher: | |
