The Situation
Just like land-based resources, ocean ecosystems are available for multiple activities and, although no single use may be significant in and of itself, cumulative impacts can have substantial effects. To determine the nature of ecosystem vulnerability to specific uses and assess the effects of cumulative impacts, it is necessary to integrate ecosystem and habitat data with spatial and temporal human use data. Development of a standard, scalable and transferable methodology is an important component of coastal and marine spatial planning.
The Project
SeaPlan worked with NCEAS to assess the cumulative impacts of existing uses in MA and adjacent federal waters. The analysis is based on a methodology that was developed by NCEAS and implemented in other parts of the world. Generally, the methodology utilizes expert judgment to characterize the relative vulnerability of an ecosystem to each human use and then utilizes this understanding of ecosystem vulnerability with data on the spatial patterns and intensity of each use to develop a scoring of relative cumulative impact for each cell in the study area.
Role in Coastal and Marine Spatial Planning
The results of these analyses can be viewed at different scales, depending on the level of detail in the data. Cumulative impact and vulnerability analysis taps into data and data products from a data network and provides a foundation for other decision support tools such as ecosystem service tradeoff analysis.
Challenges & Applications
The detail of available data determines the scale at which the analysis can be reliable (high resolution data allows for more precise analysis at a finer scale). A standardized classification of ecosystems/habitats is required to make meaningful comparisons of an ecosystems’ vulnerability to various human uses. Cumulative human impacts and habitat vulnerability assessments currently rely largely on expert interpretation and opinion as there is inadequate data in the literature to support more empirical characterizations; the methodology is scientifically robust, yet it is seen by some as a shortcoming.



