The Service Path Attribution Network (SPAN) framework provides a novel, user-centric, connectivity-based approach to ecosystem service assessment and valuation (ESAV). Ecosystem services are delivered to users through the simulated flow of some service medium (i.e., matter, energy, or information) from the ecosystems in which it originates (sources) to the people or assets which it affects (users). Along the way, the service medium may be absorbed by intervening landscape features (sinks) or captured by rival users.
Crucially, the service medium is not itself an ecosystem service or benefit but rather an agnostic transport mechanism which establishes connectivity between sources, sinks, rival users, and nonrival users within a delimited study region. Each user then receives benefits or harm from the encountered service medium depending on their specific relationship with it. For example, if surface water is the simulated service medium, it may increase productivity at a hydropower plant but damage farmers in floodplains by drowning their crops.
In the SPAN terminology, sources provide provisioning ecosystem services to users with a beneficial relationship with the service medium. Similarly, sinks provide preventive ecosystem services to users with a detrimental relationship with the service medium by reducing the amount flowing to their locations. Notably, within a single SPAN analysis, both sources and sinks may provide ecosystem services given a sufficiently heterogeneous pool of users.
The results of a SPAN ESAV analysis are myriad, totalling up to 30 output maps for some services. Taken together, these maps tell the story of which sources provide services to which users, which sinks protect users from harm, which users compete for the same resources (and who wins), and how all of the sources, sinks, rival users, and nonrival users affect one another. Additionally, a SPAN simulation produces maps of the flow paths taken by the service medium from sources to users as well as where and by how much the flow strength is reduced by sinks. Studying these flow paths can help decision makers identify those locations at which management actions would be maximized or minimized depending on their specific development goals.
A crowning achievement of this work is that for most ecosystem services the SPAN algorithm's complexity is guaranteed to be linear O(n) in both time and space with respect to the number of discrete locations analyzed. This makes it a viable option for high resolution landscape level ESAV studies using no more than commodity hardware.
This dissertation explores the SPAN framework in depth, from its novel conceptual terminology and computational algorithms through to the intended interpretation of its results. In addition to describing the conceptual and mathematical components of this system in detail, this work also provides a complete Literate Program demonstrating the application of the SPAN framework to an assessment of the scenic beauty ecosystem service in Chittenden County, Vermont.
Identifer | oai:union.ndltd.org:uvm.edu/oai:scholarworks.uvm.edu:graddis-1300 |
Date | 01 January 2014 |
Creators | Johnson, Gary Wayne |
Publisher | ScholarWorks @ UVM |
Source Sets | University of Vermont |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate College Dissertations and Theses |
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