Title: Incorporating remotely sensed tree canopy cover data into broad scale assessments of wildlife habitat distribution and conservation
Author: Martinuzzi, Sebastian; Vierling, Lee A.; Gould, William A.; Vierling, Kerri T.; Hudak, Andrew T.
Source: Journal of Applied Remote Sensing. 3: 033568.
Publication Series: Journal/Magazine Article (JRNL)
Description: Remote sensing provides critical information for broad scale assessments of wildlife habitat distribution and conservation. However, such efforts have been typically unable to incorporate information about vegetation structure, a variable important for explaining the distribution of many wildlife species. We evaluated the consequences of incorporating remotely sensed information about horizontal vegetation structure into current assessments of wildlife habitat distribution and conservation. For this, we integrated the new NLCD tree canopy cover product into the US GAP Analysis database, using avian species and the finished Idaho GAP Analysis as a case study. We found: (1) a 15-68% decrease in the extent of the predicted habitat for avian species associated with specific tree canopy conditions, (2) a marked decrease in the species richness values predicted at the Landsat pixel scale, but not at coarser scales, (3) a modified distribution of biodiversity hotspots, and (4) surprising results in conservation assessment: despite the strong changes in the species predicted habitats, their distribution in relation to the reserves network remained the same. This study highlights the value of area wide vegetation structure data for refined biodiversity and conservation analyses. We discuss further opportunities and limitations for the use of the NLCD data in wildlife habitat studies.
Keywords: species distribution model, National Land Cover Database, avian habitat, GAP, horizontal vegetation structure, wildlife conservation
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Martinuzzi, Sebastian; Vierling, Lee A.; Gould, William A.; Vierling, Kerri T.; Hudak, Andrew T. 2009. Incorporating remotely sensed tree canopy cover data into broad scale assessments of wildlife habitat distribution and conservation. Journal of Applied Remote Sensing. 3: 033568.
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