Net Resource Assessment (NetRA): A Collaborative Effort Between USGS Science and Decisions Center, the Science Impact Laboratory for Policy and Economics (University of New Mexico) and Sandia National Laboratory
Abstract:Department of Interior Secretarial Order No. 3330, “… establishes a Department-wide mitigation strategy that will ensure consistency and efficiency in the review and permitting of infrastructure development projects and in conserving our Nation’s valuable natural and cultural resources.” The USGS Organic Act authorizes resource assessments to estimate the in-place potential capacity of energy, mineral, hydrologic, and biologic resources (20 Stat. 394; 43 U.S.C. 31) and later amendments. These two statements form the basis for the development of the Net Resources Assessment (NetRA) framework.
NetRA is a policy-relevant, interdisciplinary approach to assessing natural resources availability in examining the regional-scale interrelationships between energy or mineral extraction and impact on ecosystem services. The systems dynamics approach (SD) emphasizes the interdependence of natural resource development and its effect on collocated ecosystem services over space and time.
The example of the NetRA that will be presented focuses on tradeoffs associated with land management decisions in the West. The Piceance Basin, CO example that will be discussed involves development of a continuous gas deposit and its impact on Mule Deer and water quality. The SD is the hub for generating a range of simulated landscape outcomes. The probabilistic model provides an economic indicator as to the expected net societal benefit of economic development and biophysical indicators for ecosystem services affected in the region. Both natural and economic indicators are associated with each outcome via a tradeoff analysis the can be used for risk analysis.
The NetRA also retains map attributes for before and after map comparisons to specific alternatives for an existing baseline. The model has three stages: map-based scenario development with slider bars (choice variables), side-by–side extraction and ecosystem services sub-models, and integrated multiple resource trade-off outcomes.