Habitat Modeling

Goals Predict the locations of as-yet undiscovered refuges in the Great Lakes Develop management protocols to create new unionid habitat

Goals Predict the locations of as-yet undiscovered refuges in the Great Lakes  what habitat parameters are necessary to sustain unionid populations  develop a GIS-based model that will summarize all the important features of the refuges. ◦ Test models predictions ◦ Use an iterative process to refine the model.

Habitat parameters important for unionid protection from zebra mussels may include: ◦ presence of substrates soft enough for unionids to burrow into ◦ large areas of shallow waters (protected bayous) with low flow and warmer temperatures that encourage unionid burrowing ◦ hydrological connection of the bayous to the lake ◦ fish predation of Dreissena attached to unionids ◦ Interactions of all these factors.

Factors that inhibit the establishment of stable dreissenid populations are: ◦ wave action in shallow areas, water level fluctuations, ice scouring ◦ dense reed-beds ◦ remoteness from the source of dreissenid veligers ◦ In addition, there may be other, yet unidentified, mechanisms that promote the long-term coexistence of dreissenids and native mussels.

At the local scale Focus on areas inhabited by mussels: ◦ substrate type, ◦ depths, ◦ water temperature, ◦ water velocity ◦ location ◦ species richness and abundance. Use multivariate methods such as multiscaled ordination with CCA (MSO-CCA) to define local scale habitat.

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At a regional scale Use ecological niche modeling to predict the potential presence or absence of mussel beds. Lots of options for model types, GARP, SVM, CART, etc. Use available environmental data ◦ water depth, wind-driven currents, mean, maximum and minimum annual temperature. Developed GIS data layers ◦ Turbidity, distance to deep-water, bay area and shape, bottom oxygen, distance to rivers, and human-related factors, such as distance to nearest dredging operation and distance to dams in upstream rivers.

Predicted the potential distribution of zebra mussels.  Based on current distribution of zebra mussels in U.S.  11 geologic and environmental variables. Biological model - 6 factors that have plausible explanations for limiting the distribution of zebra mussels.  frost frequency, maximum annual temperature, elevation, slope, bedrock geology, and surface geology. No Elevation model Drake & Bossenbroek, 2004, Bioscience Ecological Niche Model

Biological Model

Biological Model minus Elevation

Support Vector Data Description The support vector data description (SVDD) is an SVM for finding the boundary around a set of observations. This boundary is the simplest boundary in the sense that it represents the smallest possible hyper- volume (a hypersphere) containing a specified fraction of the observations in the projected feature space

Support Vector Data Description Drake & Bossenbroek, 2009, Theor. Ecol.

Questions?