UCSB Biogeography Lab Publications Abstracts

A proposed protocol for identifying potential Research Natural Areas with Gap Analysis data.

Max A. Moritz, David M. Stoms, Mark I. Borchert, and Frank W. Davis

In this paper we propose a protocol for identifying and evaluating candidate sites for the U. S. National Forest's Research Natural Area (RNA) program. The approach is explicit and repeatable and consists of the five following steps: 1) Vegetation Target Type Identification, 2) Quantification of Environmental Variation, 3) Calculation of Site Suitability, 4) Site Selection, and 5) Ground Truth. We also describe a prototype case study using this approach for Mixed Evergreen Forest in Los Padres National Forest in central coastal California. This case study demonstrates the usefulness of Gap Analysis data and GIS-based procedures in conjunction with applications outside GIS, such as vegetation classification and optimization programs. Results indicate that there are often complex trade-offs between efficiency (i.e, covering the most types with the least sites) and suitability (i.e., choosing the most ecologically appropriate sites) of solutions, even in a simple case such as the one described here.

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	UCSB Biogeography Lab Publications Abstracts A proposed protocol for identifying potential Research Natural Areas with Gap Analysis data. Max A. Moritz, David M. Stoms, Mark I. Borchert, and Frank W. Davis In this paper we propose a protocol for identifying and evaluating candidate sites for the U. S. National Forest's Research Natural Area (RNA) program. The approach is explicit and repeatable and consists of the five following steps: 1) Vegetation Target Type Identification, 2) Quantification of Environmental Variation, 3) Calculation of Site Suitability, 4) Site Selection, and 5) Ground Truth. We also describe a prototype case study using this approach for Mixed Evergreen Forest in Los Padres National Forest in central coastal California. This case study demonstrates the usefulness of Gap Analysis data and GIS-based procedures in conjunction with applications outside GIS, such as vegetation classification and optimization programs. Results indicate that there are often complex trade-offs between efficiency (i.e, covering the most types with the least sites) and suitability (i.e., choosing the most ecologically appropriate sites) of solutions, even in a simple case such as the one described here. Full paper
	Email stoms@bren.ucsb.edu