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Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble predictionAuthor(s): D. Todd Jones-Farrand; Todd M. Fearer; Wayne E. Thogmartin; Frank R. Thompson; Mark D. Nelson; John M. Tirpak
Source: Ecological Applications
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionSelection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models.
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CitationJones-Farrand, D. Todd; Fearer, Todd M.; Thogmartin, Wayne E.; III, Frank R. Thompson; Nelson, Mark D.; Tirpak, John M. 2011.Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction. Ecological Applications. 21(6): 2269-2282. https://doi.org/10.1890/10-1047.1.
KeywordsBayesian hierarchical model, Breeding Bird Survey, classification and regression tree, forest inventory and analysis, habitat suitability index, model uncertainty, species distribution model
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