INVEST Ecosystem Services Valuation With The Natural Capital Project

By April 22, 2013Library
Client Organization: The Natural Capital Project
SNRE Faculty Advisors: Michael Moore and Allen Burton
Master Students Involved in Project: 
  • Martha Campbell (Erb ’13), MBA/MS Sustainable Systems
  • Kirsten Howard, MS Environmental Policy and Planning
  • Kevin Le, MS Environmental Policy and Planning
  • John Shriver, MS Sustainable Systems
  • Lisa Wan, MS Environmental Policy and Planning
Summary of Project Idea: 

The Natural Capital Project (NatCap) is an innovative partnership among Stanford University, The Nature Conservancy (TNC), University of Minnesota (UMN), and World Wildlife Fund (WWF) aimed at aligning economic forces with conservation. Our vision is a world in which people and institutions recognize natural systems as capital assets, appreciate the vital roles they play in supporting human well-being, and incorporate the intrinsic and economic values of natural capital into decision making.

NatCap has 3 major foci to develop and promote this strategy: (1) develop general tools and approaches, such as InVEST for Integrated Valuation of Ecosystem Services and Tradeoffs; (2) apply these for refinement, feedback, and achievement of conservation results at focal demonstration sites around the world; and (3) magnify the impact. Our free suite of Ecosystem Services models (InVEST) allows ArcGIS users to quantify the biophysical and economic value of natural resources such as forests and riparian buffers. We adopted a tiered approach, with “Tier 1″ models being simple process-based or regression based models with minimal data requirements (and thus widely applicable), and “Tier 2″ models of higher complexity and larger data requirements.    Read more

SNRE Program Areas:

  • Conservation Ecology (Aquatic Sciences, Terrestrial Ecosystems, and Conservation Biology)
  • Environmental Policy and Planning
  • Behavior, Education, and Communication
  • Environmental Informatics
  • Environmental Justice
  • Sustainable Systems