A systematic review of ecosystem services modeling for environmental health assessment

Increasingly, environmental modelers are called upon to evaluate the sustainability and ecosystem health (EH) impacts of new policies and land management practices. This demand requires modelers to convert the normative, value-laden concept of EH into a measurable quantity. To solve this problem, many have turned to the ecosystem services (ES) framework, an established system for quantifying the benefits humans derive from their natural environment. ES include a wide range of environmental variables, allowing modelers to select diverse indicators for EH. But leaving indicator selection up to modelers’ individual judgment gives researchers substantial control over the discourse of EH, raising ethical questions about inclusivity and objectivity. This study aims to examine the ES used in published EH modeling studies, with the goal of generating insight into the ways modelers define EH through ES indicator selection. Through a Web of Science database search, we identified 310 journal articles that lay at the intersection of EH and ES research. Further screening narrowed our focus to 49 papers that employed ES as the sole indicator variables in an EH assessment. In our systematic review of these 49 ES/EH modeling research papers, we classified indicators systematically and collected quantitative data on the ES that appear frequently in EH research. The three most frequently studied ES in the review, appearing in more than 20 papers each, were water quality, water provisioning, and global climate regulation. Results suggested physical ecosystem goods are preferred EH indicators, while environmental processes that do not have direct benefits for humans tend to be less frequently chosen as indicators in ES modeling research. Textual analysis and interviews with modelers are needed to fully understand the EH values and beliefs that influence indicator selection, but this study is an initial step towards a clearer understanding of the patterns of ES indicator selection in modeling research that involves normative assessment of EH.