An Integration of Habitat Evaluation, Individual Based Modeling, and Graph Theory for a Potential Black Bear Population Recovery in Southeastern Texas, USA

Author(s):

Anita Morzillo; Joseph R. Ferrari; Jianguo Liu

Journal or Book Title: Landscape Ecology

Keywords: black bear; connectivity; conservation; dispersal; graph theory; landscape ecology; network analysis; population recovery; ursus americanus

Volume/Issue: 26

Page Number(s): 69-81

Year Published: 2010

Abstract:

Population recovery is difficult for species that require large contiguous areas of habitat, particularly within areas of heterogeneous land ownerships. Ecologically, potential for recovery success requires assessment of quantity, quality, and distribution of available habitat. Our objective was to evaluate habitat for a possible Louisiana black bear recovery in southeastern Texas.

First, we categorized land cover and identified remote areas of highly suitable habitat. Next, we used the individual based simulation model J-walk to estimate ability of female black bears to move among remote habitat patches. Then, we applied graph theory to J-walk output to evaluate overall connectivity of remote habitat. An estimated 225,626 ha of remote habitat were identified in 901 patches, most of which was located within the eastern half of the study area. Network analysis showed specific areas where targeted conservation efforts may help black bear population expansion throughout the study region.

Ultimately, enough habitat area exists to sustain a black bear population and it is best connected among public and private lands largely within the eastern half of the study area. Habitat evaluation will need to be revisited if black bears establish themselves locally and actual habitat use data become available. Regardless, our analysis demonstrates an important first step that may be incorporated into a larger adaptive management framework, updated, and replicated as more-detailed habitat suitability and land use data are available.

DOI: 10.1007/s10980-010-9536-4

Type of Publication: Journal Article

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