|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|108128||161854||2013||9 صفحه PDF||سفارش دهید||دانلود رایگان|
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.
► Past classification of ecosystem services (ES) has lacked consensus.
► Newer classification systems identify concrete benefits and beneficiaries of ES.
► Spatially explicit ES flows are poorly represented in ES modeling approaches.
► We describe an algorithm, the Service Path Attribution Network (SPAN), for quantifying ES flows.
► ES flow model outputs can provide policy-relevant information.
Journal: Ecosystem Services - Volume 4, June 2013, Pages 117–125