Citation:

Yee, S., L. Sharpe, B. Branoff, L. Harwell, G. Cicchetti, K. Rocha, E. Shuchenia, S. Jackson, AND M. Pryor. Linking Coastal Habitat Restoration to Ecosystem Services: Pairing the Biological Condition Gradient (BCG) with an Ecosystem Services Gradient (ESG). Massachusetts Bays National Estuary Program: Science and Technical Advisory Subcommittee Meeting, Gulf Breeze, FL, April 12, 2022.

Impact/Purpose:

This research describes historic losses or gains of coastal habitats and their benefits using an Ecosystem Services Gradient, an analog to the Biological Condition Gradient, the describes current condition within the context of fully degraded to fully functioning. This research is helping to support restoration target setting for Mass Bays National Estuary Partnership to restore seagrass, prevent further losses of salt marsh and tidal flats, and maintain and restore valuable ecosystem services.

Description:

The Massachusetts Bays National Estuary Partnership (Mass Bays NEP) has recently worked to update their comprehensive management plan to include restoration targets for salt marsh, seagrass, and tidal flats. A key question in target setting is asking not only “what kind of ecological future do we want?”, but “what kind of socio-economic future do we want?”. An understanding of historical changes in biological condition, as well as associated loss or gain in ecosystem services, can help to identify targets that are reasonable within the context of what might actually be possible, and that achieve desired levels of benefit. The Biological Condition Gradient (BCG) was developed to address a need for science-based approaches to more precisely and effectively communicate the existing and potential condition of aquatic resources.  Assessing how ecosystem services change with corresponding levels of BCG can further help to communicate the likely social and economic benefits of protecting or restoring a site, or evaluate potential tradeoffs between different restoration scenarios. A BCG, and analogous Ecosystem Services Gradient (ESG), were developed for Mass Bays to help support setting restoration targets, and form a foundation for future local implementation of restoration projects toward achieving those targets. Historical trends in habitat acres and associated ecosystem services provisioning were used to understand the range of potential condition and benefits. Before potential ecosystem goods and services benefits of restoration are quantified, an important first step is to identify how people in local communities are using coastal ecosystems, and what ecosystem goods and services are priorities for consideration. We used an analysis of community planning documents to understand 1) who is using these coastal habitats, 2) what ecosystem services do they each care about, and 3) what are the top ecosystem services that resonate with people in each embayment community. Next, models can be used to translate more commonly measured data, such as acres of habitat, into measures of ecosystem services provisioning. A values matrix, derived from literature reviews and expert opinion, was used to assign relative values of ecosystem services to different habitat types, thus allowing a comparison across different types of habitats on a comparable scale across space and time when paired with maps of changing landcover. Discussions about historic losses of coastal habitats and their benefits, described by the BCG and ESG, are helping to support restoration target setting for Mass Bays to restore seagrass, prevent further losses of salt marsh and tidal flats, and maintain and restore valuable ecosystem services. Mass Bays is also working to identify metrics for monitoring restoration progress. To achieve targets, local-scale restoration projects are being and will be implemented. Scaling BCG and ESG assessments to local-scales will help support an understanding of local loss or gain in habitats, prioritize and compare alternative restoration projects, and to communicate and track the potential benefits of restoration.

Record Details: