COS 137-10
Setting conservation banking endangered species credits using geospatioal analysis of widely available GIS data in conjunction with species-specific life history information: A new method

Friday, August 14, 2015: 11:10 AM
319, Baltimore Convention Center
Margaret Conroy, Department of Ecology, Evolution, and Natural Resources, Rutgers, the State University of New Jersey, New Brunswick, NJ
Richard G. Lathrop, Department of Ecology, Evolution, & Natural Resources, Rutgers University, New Brunswick, NJ
Larry Niles, LJ Niles Associates, LLC

Conservation Banking (or species banking) has the potential to be a useful tool in slowing, stopping, or reversing habitat destruction and degradation which are the most pervasive threat to biodiversity and to most threatened and endangered (T&E) species.  However, the implementation of conservation banking has been hindered by the difficulty of determining the tradable debits (quantitative measure of adverse impacts of intended use/development) and credits (quantitative measure of increased value due to permanent protection, perpetual management, and possible restoration). Current methods of setting debits/credits are often either ineffective such as acre for acre trades, or expensive and time-consuming such as one-off biological surveys of land parcels. We are testing the efficacy of alternative approaches that rely on widely available GIS land use/land cover data along with species-specific life history and habitat information. We have created geospatial models for each of 15 wide-ranging T&E species to map relative habitat value across the entire state of New Jersey.  We have validated these values against an independent sightings data set and have translated these habitat values into debits/credits for trading.  


We have found that one can indeed determine biologically reasonable relative habitat value using landscape scale habitat metrics customized with species specific life history and habitat needs information. This capability allows a proactive valuation which is consistent across large areas.  We are completing sensitivity analysis and running hypothetical scenarios in order to determine the probability that such a system, if implemented, could ensure no net loss of habitat value for these species.  This is complemented by an economic cost analysis to determine the average cost of credits including perpetual management. Our habitat valuation approach shows promise in providing debits/credits consistently over wide geographic areas, thereby removing one of the stumbling blocks to the wider adoption of conservation banking.