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Understanding the implications of a changing environment on harvested bivalve populations using habitat suitability models
Lewis, N., Ted DeWitt, AND EricW Fox. Understanding the implications of a changing environment on harvested bivalve populations using habitat suitability models. CERF, Providence, RI, November 05 - 09, 2017.
Scientists from WED’s Pacific Coastal Ecology Branch in Newport, OR have developed a bay clam habitat suitability model using existing habitat datasets and natural history information, that was successfully utilized for multiple bivalve species and transferred within estuaries of the Pacific Northwest. Predicted habitat suitability index (HSI) values (1-4, low-high) showed general correspondence with bivalve presence probabilities calculated from two separate validation methods; in other words, as the predicted HSI increased, so did the presence probability for each species. The potential applications of this habitat suitability model offer resource managers time- and cost-efficient means to identify where important clam stocks occur, forecast how environmental changes can alter stock distributions, and prioritize estuarine land use decisions. Spatial patterns in ecologically- and economically-important fisheries species can allow managers and stakeholders to make more informed decisions about underutilized fisheries, shellfish preserves, habitat restoration, and aquaculture designations. This research was conducted under RAP task SHC 2.61.3.
Habitat suitability models are useful to forecast how environmental change may affect the abundance or distribution of species of interest. In the case of harvested bivalves, those models may be used to estimate the vulnerability of this valued ecosystem good to stressors. Using literature-derived natural history information, rule-based habitat suitability models were constructed in a GIS for several bivalve species (Clinocardium nuttallii, Mya arenaria, and Tresus capax) that are recreationally and commercially harvested in NE Pacific estuaries. Spatially-explicit habitat maps were produced for Yaquina and Tillamook estuaries (Oregon) using environmental data (salinity, depth, sediment grain size, and burrowing shrimp density) from multiple studies (1960-2012). Habitat suitability values ranged from 1-4 (lowest to highest) depending on the number of environmental variables that fell within a bivalve’s tolerance limits. The models were tested by comparing the observed distribution of bivalves reported in benthic community studies (1996-2012) to the range of each suitability class. Results primarily showed that habitats of highest predicted suitability contained the greatest proportion of bivalve observations and highest population densities. Our model was further supported by logistic regression analyses that showed correspondence between predicted habitat suitability values and logistic model probabilities. We demonstrate how these models can be used as tools to forecast changes in the availability of suitable habitat for these species using projected changes in salinity and depth associated with environmental change scenarios. The advantage of this approach is that disparate, independent sets of existing data are sufficient to parameterize the models, and to produce and validate maps of habitat suitability. If the models are robust for multiple estuaries and bivalves, resource managers can transfer the approach to data-poor systems with only modest investment.