You are here:
Eco-decisional well-being networks as a tool for community decision support
Citation:
Fulford, R. AND E. Paulukonis. Eco-decisional well-being networks as a tool for community decision support. Frontiers in Ecology and Evolution. Frontiers, Lausanne, Switzerland, 12:1210154, (2024). https://doi.org/10.3389/fevo.2024.1210154
Impact/Purpose:
This peer-reviewed paper will be a part of a special issue of Frontiers in Ecology and Evolution focused on applications of human well-being in measuring resilience. We have developed a network-based approach to well-being assessment that allows for integrated planning on complex decision making based on the links between proposed actions, ecosystem services, and domains of human well-being. The tool allows for the application of network theory and network based metrics to the assessment of decisions.
Description:
Community decision making based on the sustainability of ecosystem services is an integrated process that involves multiple complex decisions and is greatly aided by an understanding of how those decisions are interrelated. The interrelatedness of decisions can be understood and even measured based on connections between actions and services and influence of services on domains of human well-being. These connections can be formed into a network structure so that quantifiable properties of networks can be applied to understanding decision impacts. We developed an eco-decisional network based on weighted social-ecological networks as a tool for integrated decision making based on ecosystem services and human well-being. Nodes are actions, services, or domains of human well-being and they are linked by weighted influence derived from community stakeholder input. Examination of the eco-decisional network based on network theory and random network analysis suggests there are important patterns of influence, which describe community priorities and define unique roles through which chosen actions can influence human well-being. The eco-decisional network is generalized across communities but can also be made community specific, which provides a tool for comparison between communities in decisional priorities (network properties), as well as comparisons between proposed actions within a community (network paths). The ordered nature of networks, well-established network theory, as well as established network metrics such as ascendancy and unique roles make this approach promising for application to integrated decision making and for communicating possible outcomes to stakeholders. The result is a guidance tool for connecting propose actions to ecosystem services and human well-being.
