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Published: 2009

Total Pages: 195

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Ecoregional conservation planning for priority landbirds requires methods that explicitly link populations to habitat conditions at multiple scales. We developed Habitat Suitability Index (HSI) models to assess habitat quality for 40 priority bird species in the Central Hardwoods and West Gulf Coastal Plain/Ouachitas Bird Conservation Regions. The models incorporated both site and landscape environmental variables derived from one of six nationally consistent datasets: ecological subsections from the National Ecological Unit Hierarchy, National Land Cover Dataset, National Elevation Dataset, National Hydrography Dataset, State Soil Geographic Database, and Forest Inventory and Analysis data. We initially defi ned potential habitat for each species from unique landform, landcover, and successional age class combinations. Species-specific environmental variables identifi ed from the literature were used to refi ne initial habitat estimates. We verified models by comparing subsection-level HSI scores and Breeding Bird Survey (BBS) abundance via Spearman rank correlation. To validate models, we developed generalized linear models that predicted BBS abundance as a function of HSI score and Bird Conservation Region. We considered models that included a significant (P [less than or equal to] 0.100) positive coefficient on the BBS predictor to be valid and useful for conservation planning.

Download or read book Multiscale Habitat Suitability Index Models for Priority Landbirds in the Central Hardwoods and West Gulf Coastal Plain/Ouachitas Bird Conservation Regions written by and published by . This book was released on 2009 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecoregional conservation planning for priority landbirds requires methods that explicitly link populations to habitat conditions at multiple scales. We developed Habitat Suitability Index (HSI) models to assess habitat quality for 40 priority bird species in the Central Hardwoods and West Gulf Coastal Plain/Ouachitas Bird Conservation Regions. The models incorporated both site and landscape environmental variables derived from one of six nationally consistent datasets: ecological subsections from the National Ecological Unit Hierarchy, National Land Cover Dataset, National Elevation Dataset, National Hydrography Dataset, State Soil Geographic Database, and Forest Inventory and Analysis data. We initially defi ned potential habitat for each species from unique landform, landcover, and successional age class combinations. Species-specific environmental variables identifi ed from the literature were used to refi ne initial habitat estimates. We verified models by comparing subsection-level HSI scores and Breeding Bird Survey (BBS) abundance via Spearman rank correlation. To validate models, we developed generalized linear models that predicted BBS abundance as a function of HSI score and Bird Conservation Region. We considered models that included a significant (P [less than or equal to] 0.100) positive coefficient on the BBS predictor to be valid and useful for conservation planning.