Landscape Ecology

, Volume 22, Issue 1, pp 61–75 | Cite as

Scaling Local Species-habitat Relations to the Larger Landscape with a Hierarchical Spatial Count Model

  • Wayne E. Thogmartin
  • Melinda G. Knutson
Research article


Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species.

Key words

Abundance map Black-billed cuckoo Hierarchical model Information-theoretic model selection Multi-level model Red-headed woodpecker Spatial count model Wood thrush 


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We thank the numerous individuals involved in the collection of Breeding Bird Survey data, which made this analysis possible. We thank L. Powell and K. Smith for providing important feedback regarding development of the a priori models, J. Sauer, J. Royle, and W. Link for valuable discussion of spatial and hierarchical models in a Bayesian framework, S. Weick and C. Beckman for their attention to the point count model evaluation data, T. Fox and J.Nelson for geographic information systems support, and E. Linder, L. Venier, and anonymous reviewers for their comments on an earlier version of this manuscript.


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Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  1. 1.U.S. Geological SurveyUpper Midwest Environmental Sciences CenterLa CrosseUSA

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