Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services

Ecosystem Services
By: , and 



Recent ecosystem services research has highlighted the importance of spatial connectivity between ecosystems and their beneficiaries. Despite this need, a systematic approach to ecosystem service flow quantification has not yet emerged. In this article, we present such an approach, which we formalize as a class of agent-based models termed “Service Path Attribution Networks” (SPANs). These models, developed as part of the Artificial Intelligence for Ecosystem Services (ARIES) project, expand on ecosystem services classification terminology introduced by other authors. Conceptual elements needed to support flow modeling include a service's rivalness, its flow routing type (e.g., through hydrologic or transportation networks, lines of sight, or other approaches), and whether the benefit is supplied by an ecosystem's provision of a beneficial flow to people or by absorption of a detrimental flow before it reaches them. We describe our implementation of the SPAN framework for five ecosystem services and discuss how to generalize the approach to additional services. SPAN model outputs include maps of ecosystem service provision, use, depletion, and flows under theoretical, possible, actual, inaccessible, and blocked conditions. We highlight how these different ecosystem service flow maps could be used to support various types of decision making for conservation and resource management planning.
Publication type Article
Publication Subtype Journal Article
Title Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services
Series title Ecosystem Services
DOI 10.1016/j.ecoser.2012.07.012
Volume 4
Year Published 2013
Language English
Publisher Elsevier
Contributing office(s) Rocky Mountain Geographic Science Center
Description 9 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecosystem Services
First page 117
Last page 125
Google Analytic Metrics Metrics page
Additional publication details