Location: University of Alberta
Research Team: Dr. Vic Adamowicz, Dr. Peter Boxall, and Alicia Entem
Duration: December 2009 – March 2011
Brief Project Description/Overview:
Species at risk in Canada are designated through a process defined by the Species at Risk Act (SARA). The act outlines the management implications of species listing. Species that are listed require recovery or action plans that include socioeconomic analysis. In addition, SARA typically examines species one at a time, rather than in complexes of multiple species on a variety of habitat types.
This project will examine the economic implications of single versus multiple species approaches to the Species at Risk Act in a case study in an agricultural region of southern Saskatchewan. The Milk River Watershed contains as many as 25 listed species. Research undertaken by the Canadian Wildlife Service is providing habitat information on these species as well as general information on the overall landbase. This information, along with land use data for the region, will be used to develop cost effective management plans or plans that maximize conservation objectives subject to the opportunity costs associated with land use (farming, oil and gas, etc.). A comparison of single versus multiple species objectives will provide insights into the potential for integrated habitat based approaches to SARA to generate superior solutions to the species at risk challenge. Capturing interactions between species and habitat types in conservation planning could yield significant advantages.
Data and Methods:
An integrated ecological-economic optimization model will be developed based on the wildlife habitat information available in the region and information on land uses and opportunity costs. The model will be developed using an optimization framework. One candidate software option is Marxan (Marine Spatially Explicit Annealing) although other programming options will be investigated in the literature review component of the project. Marxan is a popular program used to optimize selection of reserve sites based on biodiversity and economic information. However, it is limited in its flexibility for inclusion of economic dimensions of the problem. Alternatives, including development within GAMS or Risk Solver Platform will also be investigated. The latter has been employed by the investigators in other contexts. Data for the model include information on species abundance and relation to habitat as well as costs associated with agricultural practices in the region and the opportunity costs of energy sector activity. Wildlife data are being collected by Canadian Wildlife Service (one of the graduate students on the project was employed this past summer to help collect these data) while the economic information will be collected within the project.
The project will provide information on the impact of moving towards multiple-species or system based approaches for SARA relative to single species approaches. These impacts will be measured in terms of cost effectiveness as well as efficacy in meeting biodiversity criteria. The project will also provide information to support decision making regarding implementation of SARA in the region.