Comparing geographic boundaries in songbird demography data with vegetation boundaries: a new approach to evaluating habitat quality |
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Authors: | Kimberly R Hall |
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Institution: | (1) Department of Forestry and Department of Fisheries and Wildlife, Michigan State University, 126 Natural Resources Building, East Lansing, MI 48824, USA |
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Abstract: | To plan for the habitat needs of forest songbirds of conservation concern, managers need to understand how spatial heterogeneity
in forest conditions influences habitat quality. I used difference boundary detection (wombling) and spatially constrained
clustering to delineate boundaries in various combinations of four forest vegetation variables (understory height, understory
density, percent deciduous vs. conifer understory, and percent canopy closure) in two Michigan northern hardwood forests.
My goal was to identify vegetation boundaries that corresponded with boundaries in an understory-dependent songbird’s distribution,
and with boundaries in demographic measures for this songbird that indicate habitat quality (e.g., occupancy by older vs.
yearling males, reproductive success). Both forests were actively-managed, mature stands: The first site (78 ha) was heavily
deer-browsed (HB), with many browse-resistant conifers in the understory, and the second (62 ha) was less-browsed (LB), with
deciduous-dominated understory. I compared the vegetation difference and cluster boundaries to difference boundaries based
on 6 years of distribution and demographic data for black-throated blue warblers (Dendroica caerulescens). At the HB site, warbler boundaries overlapped strongly with vegetation boundaries that included all four variables, and
clustering effectively divided the habitat into areas with different warbler occupancy and demographic characteristics. At
the LB site, warbler distribution showed high overlap with difference and cluster boundaries based on just the height and
density of understory vegetation, and cluster boundaries again effectively partitioned the study area into sites that varied
in habitat quality. Thus, geographic boundary analysis is likely to be a useful tool for identifying key vegetation variables
for management, and for delineating clusters (habitat patches) within sites that capture differences in habitat quality.
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Keywords: | Boundary detection Dendroica caerulescens Deer impacts Forest heterogeneity Habitat quality Spatially-constrained clustering |
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