Advancing consistent socio-economic monitoring of coastal ecosystem restoration through collaborative metric development

Globally, ecological restoration programs are increasingly designed to achieve both environmental and socio-economic goals, aligning with the United Nations Sustainable Development Goals. While the inclusion of socio-economic objectives in restoration is gaining traction, the development and implementation of effective monitoring methods for these outcomes remain underdeveloped. This is particularly true in the context of large-scale restoration efforts, such as the RESTORE Act in the Gulf of Mexico, which aims to restore coastal habitats and economies following the Deepwater Horizon oil spill. The RESTORE Act's goals encompass both ecological and socio-economic aspects, yet initial monitoring efforts primarily focused on ecological indicators. This research addresses the need for improved socio-economic monitoring by developing a robust and replicable methodology.

The existing literature highlights a significant gap in the monitoring of socio-economic outcomes in ecological restoration projects. While some international standards and programs, such as the Gold Standard and the Global Environment Facility Forest and Landscape Restoration program, have begun to incorporate socio-economic indicators, widespread adoption of consistent and effective methods remains limited. Studies emphasizing the importance of adaptive management in restoration highlight the need for comprehensive monitoring to evaluate project effectiveness and inform future interventions. The literature also indicates the challenges in attributing specific changes to restoration projects due to the influence of various factors and the need for rigorous causal inference methods. Existing data gaps and the need to improve data accessibility and sharing also hinder consistent monitoring of socio-economic outcomes.

The Gulf of Mexico Ecosystem Service Logic Models & Socio-Economic Indicators Project (GEMS) employed a collaborative, stakeholder-engaged approach. The project involved seven in-person and four virtual workshops, one-on-one calls, and focus groups with over 80 scientists and practitioners from 62 organizations across the Gulf Coast. The core methodology involved developing ecosystem service logic models (ESLMs) for 23 distinct coastal restoration project types, categorized into habitat restoration, oyster reef restoration, recreation enhancement, and water quality improvement. These ESLMs visually depicted the causal pathways from restoration actions to socio-economic outcomes, allowing for the identification of relevant metrics. The identified metrics were then screened for feasibility based on data availability, measurement constraints, and expertise required. A tiered system (Tier 1: easily measurable; Tier 2: requiring more expertise; R&D: requiring further method development) was used to categorize metrics. The project also considered the scale of measurement (project-scale vs. regional-scale) and the relevance of metrics for evaluating community resilience and equity. Measurement protocols were developed for each core metric to guide consistent data collection and interpretation, including considerations for assessing equity effects. The project also leveraged the existing Deepwater Horizon Project Tracker to assess the alignment of GEMS project types with funded projects.

The GEMS project identified 44 potential metrics across the 23 restoration approaches. Eight were classified as Tier 1 (easily measurable), 24 as Tier 2 (requiring more expertise), and 12 as R&D (requiring further method development). Eighteen core metrics were identified as relevant to at least half of the restoration approaches within each category. Five project-scale core metrics were relevant across all categories: number of restoration jobs, restoration expenditures, change in recreational activity expenditures, change in cognitive function, and change in subjective well-being. Six additional project-scale core metrics were prevalent in habitat, oyster, and recreation categories, but not water quality improvement projects. These primarily focused on habitat-related outcomes and access to project sites. Four of these project-scale core metrics had regional-scale counterparts. One regional-scale core metric focused on commercial fishing economic activity. The study also highlighted the challenges in attributing changes in outcomes solely to restoration projects due to the influence of other factors and called for using methods like control sites or hedonic regression to address this. The project's findings showed that while many metrics are readily measurable, some require further development and that regional-scale impact assessment would require broader investments.

The GEMS project's findings directly address the research question by providing a consistent and community-vetted set of socio-economic metrics for monitoring coastal restoration in the Gulf of Mexico. The identification of core metrics provides a standardized approach, improving uniformity and efficiency in monitoring and evaluation across various restoration types and facilitating comparisons of project effectiveness. The comprehensive set of metrics, encompassing project-scale and regional-scale measurements, allows for a more nuanced understanding of restoration impacts, including contributions to community resilience and equity. The collaborative process enhanced the relevance and feasibility of the metrics, while the development of measurement protocols facilitates wider adoption and implementation. Addressing the challenges associated with attributing changes to restoration projects and the development of methods for regional-scale evaluation remain crucial for advancing the field.

The GEMS project offers a valuable contribution by providing a replicable framework for developing and implementing consistent socio-economic monitoring of coastal restoration. The identified core metrics provide a practical starting point for expanding project monitoring and improving the overall evaluation of restoration efforts. Future research should focus on testing the measurement protocols, developing methods for R&D metrics, investing in regional-scale evaluations, and exploring the use of causal inference methods to more accurately attribute socio-economic changes to restoration projects. Wider adoption of these metrics by funders and regulators is crucial for maximizing the benefits of restoration investments.

The study primarily focused on the Gulf of Mexico, limiting the generalizability of findings to other ecosystems. While the collaborative approach ensured stakeholder relevance, the specific socio-economic contexts in other regions might necessitate modifications to the metrics. The challenge of attributing specific changes solely to restoration projects, rather than other co-occurring factors, needs further methodological development. The study also notes that the regional-scale impact evaluation requires significant investment and resources, highlighting a constraint for smaller projects.