Project Title: Mapping, Valuation, and Optimization of Ecosystem Service Flows
Mendenhall Fellow: Kenneth J. Bagstad, (303) 202-4136, email@example.com
Duty Station: Denver, Colorado
Start Date: March 28, 2011
Education: Ph.D., Natural Resources, University of Vermont (2009)
Research Advisors: Darius Semmens, (303) 202-4331, firstname.lastname@example.org; Jay Diffendorfer, (303) 202-4070, email@example.com; Todd Hawbaker, (303) 202-4303, firstname.lastname@example.org; Lynne Koontz, (970) 226-9384, email@example.com
Project Description: When economic decisions lack full information about stakeholders, costs, and benefits, they are more likely to produce socially inefficient outcomes (Ligmann-Zielinska and others, 2008; Polasky and others, 2008). Ecosystem service flow maps can enable analysts to better evaluate tradeoffs in land management by showing which regions are critical to maintaining the supply and flows of particular benefits for specific beneficiary groups. The recent state of the practice—static maps of ecosystem service provision—fails to account for spatial flows of ecosystem services from ecosystems to their human beneficiaries (Tallis, 2008). A more realistic and policy-relevant approach to ecosystem services assessment would start by mapping ecosystem services production and beneficiaries and then accounting for the spatial flow of benefits from ecosystems to people (Villa and others, 2009) (fig. 1). This approach requires new language and modeling approaches but promises to provide a much more realistic view of human dependence on ecosystem services.
When conservation and restoration activities are prioritized around areas that provide services and flows, these flows may be maintained or increased. Conversely, focusing development or extractive resource use outside these regions can minimize degradation of ecosystem service flows. By identifying parties that benefit from or degrade benefit flows, results can provide guidance to economic incentive programs including payments for ecosystem services (Engel and others, 2008). Flow maps can help identify potential demand for ecosystem services, increasing the potential to “stack” or “bundle” ecosystem services within incentive systems.
Two case study sites provide opportunities to model ecosystem service flows in the context of public land management: the San Pedro River in southeast Arizona and Puget Sound in Washington State. These sites have highly varied ecological and socioeconomic contexts, which influence ecosystem service flows and applications for resource management. This project applies and builds on the Artificial Intelligence for Ecosystem Services (ARIES) modeling framework (Villa and others, 2009), which is developing a web-based tool to probabilistically model and quantify services and their spatial flows. The ARIES modeling system links appropriate GIS data to probabilistic or deterministic models that quantify supply and demand for services, as well as the strength of landscape features that deplete the physical, energetic, or informational “carrier” of that specific service. Agent-based models are then used to determine the actual flow path and quantity of a service received by spatially explicit human beneficiary groups (Johnson and others, 2012).
To conduct spatial optimization for ecosystem service flows, stakeholders from each region will be asked to define regional goals, including desirable levels of provision of key ecosystem service flows to given beneficiary groups, as well as other constraints of interest (for example, land-use types or patterns, resource management strategies, or rates of urban development or population growth). This background information, combined with ecosystem service flow maps, will be used in appropriate optimization algorithms to identify production possibilities frontiers for ecosystem services tradeoffs in alternative scenarios.
Spatial dynamics of ecosystem services. Sink regions are areas that block or absorb a matter, energy, or informational carrier of an ecosystem service (for example, areas that absorb flood water, sediment, or nutrients; visual blight that degrades a high-quality viewsheds). Sinks or rival use of an ecosystem service carrier deplete the carrier quantity while non-rival use does not (Johnson and others, 2012).
Engel, S., Pagiola, S., and Wunder, S., 2008, Designing payments for environmental services in theory and practice: An overview of the issues: Ecological Economics, v. 65, p. 663–674.
Johnson, G.W., Bagstad, K.J., Snapp, R.R., and Villa, F., 2012, Service Path Attribution Networks (SPANs): A network flow approach to ecosystem service assessment: International Journal of Agricultural and Environmental Information Systems, v. 3, no. 2, p. 54–71.
Ligmann-Zielinska, A., Church, R.L., and Jankowski, P., 2008, Spatial optimization as a generative technique for sustainable multi-objective land-use allocation: International Journal of Geographical Information Science, v. 22, no. 6, p. 601–622.
Polasky, S., Nelson, E., Camm, J., Csuti, B., Fackler, P., Lonsdorf, E., Montgomery, C., White, D., Arthur, J., Garber-Yonts, B., Haight, R., Kagan., J., Starfield, A., and Tobalske, C., 2008, Where to put things? Spatial land management to sustain biodiversity and economic returns: Biological Conservation, v. 141, p. 15054–1524.
Tallis, H., Kareiva, P., Marvier, M., and Chang, A., 2008, An ecosystem services framework to support both practical conservation and economic development: Proceedings of the National Academy of Sciences, v. 105, no. 28, p. 945–-9464.
Villa, F., Ceroni, M., Bagstad, K., Johnson, G., and Krivov, S., 2009, ARIES (Artificial Intelligence for Ecosystem Services): A new tool for ecosystem services assessment, planning, and valuation: Proceedings of the 11th Annual BIOECON Conference on Economic Instruments to Enhance the Conservation and Sustainable Use of Biodiversity, Venice, Italy, September 2009.
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