Friday, August 8, 2008 - 10:30 AM

COS 112-8: Modeling multiple ecosystem services and tradeoffs at landscape scales

Erik J. Nelson1, Guillermo Mendoza1, Jim Regetz2, Steve Polasky3, Heather Tallis1, Dick Cameron4, Kai Ming A. Chan5, Gretchen Daily1, Joshua Goldstein1, Peter Kareiva6, Eric Lonsdorf7, Robin Naidoo8, Taylor Ricketts9, and M. Rebecca Shaw6. (1) Stanford University, (2) National Center for Ecological Analysis and Synthesis, University of California - Santa Barbara, (3) University of Minnesota, (4) The Nature Conservancy - California, (5) University of British Columbia, (6) The Nature Conservancy, (7) Lincoln Park Zoo, (8) WWF-US, (9) World Wildlife Fund


In this paper we describe InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs), a new spatially explicit modeling tool that predicts the consequences on land-use and land-cover (LULC) change on the production of multiple ecosystem services, biodiversity, and commodity production.  Unlike the benefits transfer approach, InVEST uses ecological production functions and economic valuation methods to make predictions.  We apply InVEST to three alternative scenarios of LULC change in the Willamette Basin, Oregon, USA.  We show how these different scenarios affect two hydrological service levels, soil conservation, the rates of terrestrial carbon sequestration, biodiversity, and market returns to landowners. 

We find no evidence of significant tradeoffs among ecosystem services and biodiversity across scenarios.  The one tradeoff in the Basin is between market value, which is higher under the two scenarios that do not change development policies in the Basin, and all other ecosystem services and biodiversity, which are higher under the scenario that implements policies to more closely regulate development (the Conservation scenario).  However, we find that the economic value of the Conservation scenario is higher than the economic value of the other two scenarios when reasonable values for ecosystem services produced by the landscape are added to market value estimates.