NCEAS Project 2077

Investigating alternative land use/habitat conservation strategies using GIS and optimization modeling (Extended)

  • Michael Gilpin
  • Richard L. Church
  • Ross Gerrard
  • Peter A. Stine


ActivityDatesFurther Information
Working Group16th—16th February 1998Participant List  
Working Group21st—22nd September 1998Participant List  

Abstract
This proposal is for a continuation of an NCEAS working group for an additional twelve months beginning October 1, 1997, including postdoctoral support for the current postdoctoral researcher Ross Gerrard. The subject of our research is the development of an innovative optimization modeling approach to selecting lands to set aside for habitat conservation. Our data and pilot study come from the eastern parts of Contra Costa and Alameda Counties in Northern California, a region that encapsulates state-wide and nation-wide issues of finding alternatives for conserving habitats amid growth pressures, cost constraints, and a prevalence of private ownership.
Our approach differs from previous reserve siting models in that we invest in a substantial amount of biological input so that the spatial units selected by the optimization model have been pre-defined to be suitable for supporting species. This front-end investment in defining appropriate biological parameters is accomplished and coordinated using Geographic Information Systems (GIS). In addition, the cost of preserving habitats at various locations is defined and stored using GIS. This biological and cost information undergoes significant processing and is ultimately used to define a mathematical programming model that selects habitat patches or territories (as opposed to the arbitrary spatial units used in almost all other such models). The math programming model can select a desired number of habitat patches based on objectives of minimizing acquisition cost, maximizing patch connectivity, and other objectives. We believe that our framework of combining our team strengths in expert biological opinion, optimization modeling, and GIS has achieved a significant synthesis and that considerably more progress can be achieved with an additional year of support.