Avian Spatial Responses to Forest Spatial Heterogeneity at the Landscape Level: Conceptual and Statistical Challenges


An explicit consideration of spatial structure in ecological studies plays an increasingly important role in attempts to better understand and manage ecological processes, such as deforestation, forest homogenization, and escalating landscape heterogeneity. The goal of this chapter is to quantify the relationship between forest cover data and ovenbird (Seiurus aurocapilla) abundance—a ground nesting passerine that breeds in contiguous forests—in southern Ontario (Canada). To quantify this relationship, we use the Ontario Breeding Bird Atlas 2001–2005 and compare two spatially explicit modeling methods: geographically weighted regression (GWR) and regression kriging (RK). We show how GWR and RK account for residual spatial autocorrelation in models of forest cover and ovenbird abundance, and we examine the insights they provide. Based on regression kriging, we found that 68 % (adjusted R 2 ) of ovenbird abundance was explained by forest cover, which was an improvement over ordinary least-square regression (adjusted R 2 = 43%), but was not uniformly better than variance explained by GWR in different subregions. These results emphasize the importance of both performing spatial data exploration prior to statistical analyses and accounting for spatial structure during the analysis.


Forest Cover Spatial Autocorrelation Geographically Weighted Regression Generalize Little Square Universal Transverse Mercator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Ontario Provincial Landcover Data has been supplied under license by Members of The Ontario Geospatial Data Exchange. Thanks to the official sponsors of the Ontario Breeding Bird Atlas (Bird Studies Canada, Canadian Wildlife Service, Federation of Ontario Naturalists, Ontario Field Ornithologists, and Ontario Ministry of Natural Resources) for supplying Atlas data, and to the thousands of volunteer participants who gathered data for the project. We gratefully acknowledge the assistance of Trevor Middel for reading and editing previous versions of this chapter. A very special thanks to Randy McVeigh for discussions, analytical support, and assistance with preparing figures. Thanks also to colleagues at Wageningen and Utrecht University for discussions that helped to shape some of the ideas presented herein. Finally we would like to acknowledge the help of the four anonymous reviewers whose comments greatly improved the quality of this chapter.


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoCanada
  2. 2.Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoCanada

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