Guidebook for building expert-based predictive habitat models for threatened and endangered species
Focus Area
Environmental Management Systems
Subcommittee
Environmental Process
Status
Archived
Cost
Under $99k
Timeframe
Under 1 year
Research Idea Scope
State transportation agencies face an increasing number of federally listed species that need to be incorporated into planning processes, while needing to do so within a constrained budget. Each transportation agency has in-house experienced biologists who make judgments about Threatened and Endangered species habitat likelihood based on their considerable experience on a case-by-case basis. This knowledge can be more systematically incorporated into a basic and functional predictive model that a) does not require statistical sampling to build; b) uses simple likelihood rules for predictive purposes, and; c) can help minimize the demands placed on GIS systems, when appropriate. Such models have already been built and deployed in some states (Blandford et al 2013). They are built around a conceptually elegant design that does not require sophisticated mathematical modeling or unrealistic observation data sets. Rather, they capitalize on the already-existing knowledge and experience of biologists by developing simple methods for incorporating that knowledge into a GIS-based model: a true expert system. These systems, then, are designed by and for biologists at state transportation agencies to enhance their analytic capacity. This research project would create a guidebook for use by state transportation agencies and their biologists to bootstrap their own predictive systems for listed species of a particular type. The guidebook would contain these topics: a) Identifying the most critical species challenges b) Identifying the habitat characteristics most relevant to these species c) Identifying the GIS system data and capabilities vis-à-vis these habitat characteristics d) Building the necessary GIS layers e) Soliciting and incorporating expert biological knowledge into the system f) Developing a weighted model g) Testing the system against available data Works cited: Blandford, B., J. Ripy, and T. Grossardt. 2013 “GIS-Based Expert Systems Model for Predicting Habitat Suitability of Blackside Dace in Southeastern Kentucky.” TRB Annual Meeting Compendium of Papers, paper #13-5059.
Urgency and Payoff
The trend toward increasing numbers of listed species is not abating. Each new species poses an additional obligation on the part of state transportation agencies, one they would happily avoid given a reasonably reliable system of anticipating where these habitats are in advance. With a Guidebook to aid them in building their own simplified predictive models, time and money can be saved and environmental management systems can be improved.
Submitted
06/04/2015