## InVEST Habitat Risk Assessment Model

The InVEST Habitat Risk Assessment model evaluates risks posed to coastal and marine habitats in terms of exposure to human activities and the habitat-specific consequence of that exposure for delivery of ecosystem services.

Habitat Riskecosystem
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Quoted from: https://naturalcapitalproject.stanford.edu/software/invest

The InVEST Habitat Risk Assessment model evaluates risks posed to coastal and marine habitats in terms of exposure to human activities and the habitat-specific consequence of that exposure for delivery of ecosystem services. The model can be employed to screen habitat risks under current and future scenarios of use, helping inform management strategies to minimize the impairment of habitat quality and function. More broadly, the model enables users to visualize areas on the seascape where the impacts of climate change and anthropogenic pressures may create tradeoffs among multiple ecosystem services.

Habitats and species provide essential benefits for people, including regulating, material, and non-material services (Pascual et al. 2017, Díaz et al. 2018). For example, nearshore habitats such as kelp forests and eelgrass meadows protect shorelines from storms, provide nursery habitat for fisheries, and store and sequester carbon. Terrestrial habitats like riparian forests absorb excess nutrients and sediment, provide habitat for riverine fish species, and mitigate inland flooding after rain events. As these habitats (or species) become degraded by human activities, the ecosystem services they provide are threatened. Recent global analyses have revealed that almost no area of the world’s oceans is untouched by human impacts (Halpern et al. 2008). Thus, an understanding of the location and intensity of human impacts on nearshore ecosystems is an essential component of informed and successful terrestrial, coastal, and ocean management. The InVEST HRA model allows users to assess the threat of human activities to the health of these ecosystems and species. The model has been successfully applied in numerous locations across the world (e.g. Arkema et al. 2014, Cabral et al. 2015, Chung et al. 2015, Duggan et al. 2015, Ma et al. 2016, Elliff et al. 2017, Wyatt et al. 2017).

The HRA model is a quantitative approach to evaluating the cumulative influence of stressors associated with human activities on habitats and species (Arkema et al. 2014, Arkema et al. 2015). HRA uses a well-established approach from the risk literature that originates from fisheries vulnerability assessments (Astles et al. 2006, Patrick et al. 2010, Hobday et al. 2011, Samhouri and Levin 2012).

The model incorporates two dimensions of information to calculate risk or impact to ecosystem components (figure 1; Halpern et al. 2008, Patrick et al. 2010, Samhouri and Levin 2012, Arkema et al. 2014). These dimensions are exposure and consequence.

Exposure is the degree to which a habitat or species experiences a stressor, given the effectiveness of management practices.

Consequence is the habitat (or species)-specific response to that exposure. Consequence incorporates the sensitivity of each habitat or species to the effects of a stressor, and the habitat’s resilience, or the ability of the habitat or species to resist or recover from a stressor to which it is exposed.

Figure 1: Habitats with high exposure to human activities and high consequence of that exposure are at high risk. Plotting exposure and consequence like this allows assessments of which components of risk are most significant and reveals risk-reduction strategies. Risks driven by exogenous human factors (top right region of the risk space) might be mitigated by management interventions, while risk driven by endogenous habitat-specific factors (top-left region of risk space) may be better addressed through monitoring and preparedness. (Adapted from Dawson et al. 2011).

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#### How to Cite

Natural Capital Project (2019). InVEST Habitat Risk Assessment Model, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/a9ccdf23-43ee-49a1-a047-5fd0f70e4b6b

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