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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Assessing and prioritizing ecological communities for monitoring in a regional habitat conservation plan
Lauren A Hierl1, Janet Franklin, Douglas H Deutschman
1Department of Biology, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4614, USA.
Abstract:
In nature reserves and habitat conservation areas, monitoring is required to determine if reserves are meeting their goals for preserving species, ecological communities, and ecosystems. Increasingly, reserves are established to protect multiple species and communities, each with their own conservation goals and objectives. As resources are always inadequate to monitor all components, criteria must be applied to prioritize both species and communities for monitoring and management. While methods for prioritizing species based on endangerment or risk have been established, approaches to prioritizing ecological communities for monitoring are not well developed, despite a long-standing emphasis on communities as target elements in reserve design. We established guidelines based on four criteria derived from basic principles of conservation and landscape ecology--extent, representativeness, fragmentation, and endangerment--to prioritize communities in the San Diego Multiple Species Conservation Plan (MSCP). The MSCP was one of the first multiple-species habitat conservation areas established in California, USA, and it has a complex spatial configuration because of the patterns of surrounding land use, which are largely urbanized. In this case study, high priority communities for monitoring include coastal sage scrub (high endangerment, underrepresented within the reserve relative to the region, and moderately fragmented), freshwater wetlands, and coastal habitats (both have high fragmentation, moderate endangerment and representativeness, and low areal extent). This framework may be useful to other conservation planners and land managers for prioritizing the most significant and at-risk communities for monitoring.
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