Forty years ago, ecological restoration was conceptualized through a natural science lens. Today, ecological restoration has evolved into a social and scientific concept. The duality of ecological restoration is acknowledged in guidance documents on the subject but is not apparent in its definition. Current definitions reflect our views about what ecological restoration does but not why we do it. This viewpoint does not give appropriate credit to contributions from social sciences, nor does it provide compelling goals for people with different motivating rationales to engage in or support restoration. In this study, I give a concise history of the conceptualization and definition of ecological restoration, and I propose an alternative definition and corresponding viewpoint on restoration goal‐setting to meet twenty‐first century scientific and public inquiry.

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land use planning and environmental management priorities. Analysts and their stakeholder constituents should be cautioned that results may be sensitive to the methods that are chosen to perform the analysis. In this article, we investigate four common additive aggregation methods: global and local multi-attribute scaling, the analytic hierarchy process, and compromise programming. Using a hypothetical example, we explain scaling and compensation assumptions that distinguish the methods. We perform a case study application of the four methods to re-analyze a data set that was recently published in and demonstrate how results are sensitive to the methods.

Understanding the effects of environmental management strategies on society and the environment is critical for evaluating their effectiveness, but is often impeded by limited data availability. In this article, we present a method that can help scientists to support resource managers' thinking about social-ecological relationships in coupled human and natural systems. Our method aims to model qualitative cause-effect relationships between management strategies and ecosystem services, using information provided by knowledgeable participants, and the tradeoffs between strategies. Social, environmental, and cultural indicators are organized using the Driver-Pressure-State-Impact-Response, or DPSIR, framework. The relationships between indicators are evaluated using a decision tree and numerical representations of interaction strength. We use a matrix multiplication procedure to model direct and indirect interaction effects, and we provide guidelines for combining effects. Results include several data tables from which information can be visualized to understand the plausible interaction effects of implementing management strategies on ecosystem services. We illustrate our method with a water quality management case study on Cape Cod, Massachusetts.

Ecological restoration has traditionally been evaluated by monitoring the recovery of ecological conditions, such as species abundance and diversity, physical form, and water quality; monitoring the social benefits of restoration is uncommon. Current monitoring frameworks do not track who benefits from restoration or by how much. We investigate how ecological restoration could be monitored to provide indications of improvement in terms of social conditions. We provide suggestions for measuring several categories of social indicators, including access, beneficiaries, and quality of benefit, using information compiled from natural and social science literature. We demonstrate how to evaluate ecological and social indicators over time at a site or landscape scale using multicriteria analysis. We use flood protection and recreation as example benefits to monitor.

Accounting for ecosystem services in environmental decision making is an emerging research topic. Modern frameworks for ecosystem services assessment emphasize evaluating the social benefits of ecosystems, in terms of who benefits and by how much, to aid in comparing multiple courses of action. Structured methods that use decision analytic-approaches are emerging for the practice of ecological restoration. In this article, we combine ecosystem services assessment with structured decision making to estimate and evaluate measures of the potential benefits of ecological restoration with a case study in the Woonasquatucket River watershed, Rhode Island, USA. We partnered with a local watershed management organization to analyze dozens of candidate wetland restoration sites for their abilities to supply five ecosystem services-flood water retention, scenic landscapes, learning opportunities, recreational opportunities, and birds. We developed 22 benefit indicators related to the ecosystem services as well as indicators for social equity and reliability that benefits will sustain in the future. We applied conceptual modeling and spatial analysis to estimate indicator values for each candidate restoration site. Lastly, we developed a decision support tool to score and aggregate the values for the organization to screen the restoration sites. Results show that restoration sites in urban areas can provide greater social benefits than sites in less urban areas. Our research approach is general and can be used to investigate other restoration planning studies that perform ecosystem services assessment and fit into a decision-making process.