Habitat risk assessment for regional ocean planning in the U.S. Northeast and Mid-Atlantic

Abstract

Coastal habitats provide important benefits to people, including habitat for species targeted by fisheries and opportunities for tourism and recreation. Yet, such human activities also can imperil these habitats and undermine the ecosystem services they provide to people. Cumulative risk assessment provides an analytical framework for synthesizing the influence of multiple stressors across habitats and decision-support for balancing human uses and ecosystem health. To explore cumulative risk to habitats in the U.S. Northeast and Mid-Atlantic Ocean Planning regions, we apply the open-source InVEST Habitat Risk Assessment model to 13 habitats and 31 stressors in an exposure-consequence framework. In doing so, we advance the science priorities of EBM and both regional planning bodies by synthesizing the wealth of available data to improve our understanding of human uses and how they affect marine resources. We find that risk to ecosystems is greatest first, along the coast, where a large number of stressors occur in close proximity and secondly, along the continental shelf, where fewer, higher consequence activities occur. Habitats at greatest risk include soft and hard-bottom nearshore areas, tidal flats, soft-bottom shelf habitat, and rocky intertidal zones—with the degree of risk varying spatially. Across all habitats, our results indicate that rising sea surface temperatures, commercial fishing, and shipping consistently and disproportionally contribute to risk. Further, our findings suggest that management in the nearshore will require simultaneously addressing the temporal and spatial overlap as well as intensity of multiple human activities and that management in the offshore requires more targeted efforts to reduce exposure from specific threats. We offer a transparent, generalizable approach to evaluating cumulative risk to multiple habitats and illustrate the spatially heterogeneous nature of impacts along the eastern Atlantic coast and the importance of spatial scale in estimating such impacts. These results offer a valuable decision-support tool by helping to constrain the decision space, focus attention on habitats and locations at the greatest risk, and highlight effect management strategies.

Using GIS and stakeholder involvement to innovate marine mammal bycatch risk assessment in data-limited fisheries

“…The core functionality of the ByRA tool–to draw on assembled scores of interaction rates and assess bycatch risk ( Fig 4B and 4C )–is executed through the user interface of InVEST, a freely downloadable software suite ( naturalcapitalproject.stanford.edu/software/invest ) [ 74 ]. Here, we adapted the exposure-consequence criteria for habitat risk assessment [ 47 , 75 ], where risk of fisheries bycatch is calculated as a function of the likelihood of exposure (interaction between the marine mammal and the fishery), and its consequence , which is the gear-specific impact to a species. For two additional exposure criteria unique to bycatch risk, we defined: (1) likelihood of interaction , as the probability that the animal will encounter a fishing gear if spatial overlap was detected, and (2) catchability , as the likelihood of animal capture by a gear type when this overlap occurs.…”

Identification and Prediction of Wetland Ecological Risk in Key Cities of the Yangtze River Economic Belt: From the Perspective of Land Development

“…The HRA model is well suited for screening the risks of current and future human activities to prioritize the best management strategies for risk mitigation. There are two dimensions of information used to calculate the risk or impact of the ecosystem in the HRA model, which is called "exposure" and "consequence" [37,39]. The HRA model makes full use of GIS spatial superposition analysis technology and assesses the risk of wetland degradation caused by different stressors according to several "exposure" and "consequence" indicators [34,38].…”

“…We can use this model to analyze the location and intensity of human impacts on nearshore ecosystems to identify areas of greatest risk of degradation and their primary causes. The model has been successfully applied around the world [34,[36][37][38][39][40]. The model can use land-use data to evaluate the impact of human activities on the environment from the land development perspective [34,40].…”

Integrating fisheries management into sustainable development planning

“…Spatial variation in nursery and adult habitat, and changes in habitats for the future scenarios, were modeled with the InVEST Habitat Risk Assessment (HRA) model (Dugan et al 2011, Arkema et al 2014, Wyatt et al 2017, Sharp et al 2018. Full details of the risk assessment and application of the HRA model in Belize can be found in Arkema et al (2014).…”