Operationalizing Network Theory for Ecosystem Service Assessments. (February 2017) - Dee, Laura E.; Allesina, Stefano; Bonn, Aletta; Eklöf, Anna; Gaines, Steven D.; Hines, Jes; Jacob, Ute; McDonald-Madden, Eve; Possingham, Hugh; Schröter, Matthias; Thompson, Ross M.
Abstract : Managing ecosystems to provide ecosystem services in the face of global change is a pressing challenge for policy and science. Predicting how alternative management actions and changing future conditions will alter services is complicated by interactions among components in ecological and socioeconomic systems. Failure to understand those interactions can lead to detrimental outcomes from management decisions. Network theory that integrates ecological and socioeconomic systems may provide a path to meeting this challenge. While network theory offers promising approaches to examine ecosystem services, few studies have identified how to operationalize networks for managing and assessing diverse ecosystem services. We propose a framework for how to use networks to assess how drivers and management actions will directly and indirectly alter ecosystem services. Trends: Managing ecosystems to provide ecosystem services (ESs) in the face of global change is a pressing challenge for both policy and science. Most ES studies do not consider interactions, limiting insight into how future conditions will change ES. Failure to consider interactions among components of socioeconomic, ecological, management systems can lead to detrimental outcomes from management decisions. Recent papers call to use network theory in ES research, yet adoption remains challenged by a gap between broad concepts and application. We suggest a starting point to operationalize networks for ES: build an integrated socioeconomic and ecological network around the management objective, the ES of interest. We outline steps to represent ES using networks and to analyze how drivers and management actions will impact ES directly and indirectly. Operationalizing network theory for ES is a promising step toward more predictive approaches to assess and manage ES – and for avoiding unintended outcomes from management decisions.