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Field Testing Of An Expert Model: Can The Model Predict Habitat Potential For Saltmarsh Birds?
Berry, W., M. Nightingale, AND M. Mazzotta. Field Testing Of An Expert Model: Can The Model Predict Habitat Potential For Saltmarsh Birds? Presented at New England Estuarine Research Society (NEERS). Spring Meeting, Portland, ME, April 11 - 13, 2013.
The population status of salt marsh obligate breeding birds in Rhode Island is in doubt, because the breeding habitat of these birds is being eroded from both the seaward and landward sides. Our work will help to inform several conservation efforts underway in RI. The USFWS is currently carrying out studies of several salt marsh-obligate breeding birds on their refuges in RI. The information in this report will help them to formulate management plans for their marsh reserves. Save The Bay is doing assessments of a number of marshes in RI, to develop a baseline that can be used to measure the effects of global climate change. The data in this report will help them to develop a saltmarsh breeding bird baseline. Finally, the validation of the model itself will help determine if it is useful in predicting bird habitat potential on New England marshes. At least one organization in New Hampshire has expressed an interest in using the model in the future.
Salt marshes are valuable resources, which provide numerous ecosystem services, including flood protection, fish nursery habitat, and nesting habitat for a number of threatened and endangered species. At the present time, due primarily to coastal development and sea level rise, Rhode Island’s salt marshes are facing increasing pressure from both land and sea. There is not enough money to restore or save all of them, so we need to be able to select which marshes have the most potential for providing a given ecosystem service or group of services. Models are useful in this selection process. One class of model sometimes used is the expert model, where the opinions of experts are used to develop a predictive model, in the absence of extensive field data. Expert models are rarely field validated. We tested the predictions of bird habitat potential from one such model, which was developed using interviews with experts from three New England states. We used bird count data from 41 salt marshes in RI. The numbers of birds on the marshes from 3 classes of birds (salt marsh dependent songbirds, shorebirds, and wading birds), were positively correlated with model outputs (using rank order). Further work will be needed to determine if the predictions made by the model will be useful in decision making, and how the performance of the model compares to that of more geographically specific, data driven models.