Distributions for five key tidal marsh-dependent bird species were modeled using boosted regression trees (Elith et al. 2008). Both methods are able to fit non-linear functions between environmental variables and the presence/absence of a species. Map values represent the probability of occurrence of a species. Higher values in a map indicate a higher likelihood that a species will be present at a site. Bird species modeled: Common yellowthroat, black rail, clapper rail, marsh wren, song sparrow. Model outputs: Probably of occurrence, density (birds per hectare).
This dataset was produced by PRBO Conservation Science's project to assess the effects of sea-level rise (SLR) and salinity changes on San Francisco Bay tidal marsh ecosystems. Tidal marshes are naturally resilient to SLR, in that they can build up elevation through the capture of suspended sediment and deposition of organic material (vegetation). Thus, a "bathtub" model approach is not appropriate for assessing impacts to this dynamic habitat. Rather, dynamic accretion potential can be modeled annually based on tidal inundation, sediment availability, and the rate of organic accumulation (related to salinity). Working with researchers at Philip Williams and Associates (http://www.pwa-ltd.com) University of San Francisco, University of California Berkeley, and San Francisco State University, we have developed a set of geographically based climate change scenarios based on a dynamic marsh accretion model. We have developed preliminary projections for potential changes in tidal marsh elevation and extent over five time frames (20, 40, 60, 80 and 100 years from now) and under eight scenarios representing different assumptions about sea-level rise, salinity, and sediment supply. Our goal is to provide an overview of potential future tidal marsh extent and location in San Francisco Bay, as well as information on priorities for restoration and conservation efforts. Due to the additional complexity of open-bay hydrodynamics, our analysis does not include bay-edge mudflats.
See the following website for additional information http://data.prbo.org/apps/sfbslr/
