ACCOUNTING FOR SPATIAL FLOWS TO MAP ECOSYSTEM SERVICES SUPPLY AND DEMAND

Ecosystem services mapping to date has largely focused on the “supply side” – the provision of benefits by ecosystems to humans. This has largely taken place through static mapping of levels of potential service provision that incorporates ecological process models with spatial data. By comparison, the “demand side,” or human demand for and use of ecosystem services, has received less attention. In addition, the spatial flow of these services from ecosystems to people has been qualitatively conceptualized but not quantitatively modeled. We describe a process used by the Artificial Intelligence for Ecosystem Services (ARIES) project (Villa and others 2009) that links spatial data and ecological knowledge to map the spatial dynamics of ecosystem services – their provision, use, and spatial benefit flows.

We first describe the concrete benefits and human beneficiaries (or “endpoints,” Boyd 2007) provided by ecosystems, as opposed to the popular but abstract list of ecosystem services used in the Millennium Ecosystem Assessment. For each specific benefit, we describe a matter, energy, or information carrier, along with a benefit-specific flow pattern (for example, movement through hydrologic or transportation networks, spatial proximity, line of sight, or uniform mixing). Then, for each ecosystem service, we model the potential provision, users, and “sinks” that can deplete the carrier quantity as it moves across space. Provision, use, and sinks can be modeled using established ecological process models or ad hoc probabilistic models as appropriate. Finally, a set of agent-based “Service Path Attribution Network” (SPAN) models (Johnson and others in press) quantify the carrier flow based on benefit-specific movement rules, quantifying actual levels of ecosystem service provision and use.

The resulting provision, use, and flow maps provide a more realistic view of the spatial dependencies between regions that provide ecosystem services and their human beneficiaries. Such mapping operationalizes the ecosystem service flow concepts developed elsewhere (Fisher and others 2008, Tallis and Polasky 2009) while providing support for conservation and economic development planning, economic valuation of ecosystem services, and cross-boundary analysis for public land management or other transboundary decision making.

List of acronyms

ARIES – Artificial Intelligence for Ecosystem Services

SPAN – Service Path Attribution Network

References

Boyd, J., 2007, The endpoint problem: Resources, v. 165, p. 25-28.

Fisher, B., et al., 2008, Ecosystem services and economic theory: Integration for policy-relevant research: Ecological Applications, v. 18, p. 2050-2067.

Johnson, G.W., et al., in press, Service Path Attribution Networks (SPANs): Spatially quantifying the flow of ecosystem services from landscapes to people: Forthcoming in: Lecture Notes in Computer Science.

Tallis, H. and Polasky, S., 2009, Mapping and Valuing Ecosystem Services as an Approach for Conservation and Natural-Resource Management: Annals of the New York Academy of Sciences, v. 1162, p. 265-283.

Villa, F., et al., 2009, ARIES (Artificial Intelligence for Ecosystem Services): A new tool for ecosystem services assessment, planning, and valuation: Proceedings of the 11^th Annual BIOECON Conference, Venice, Italy, September 2009.