Project ID: WA2012_22
Lead Investigator: Sarah Saalfeld, Manomet Center for Conservation Sciences
Collaborators: Julian Fischer, USFWS; Thomas Ravens, University of Alaska Anchorage; Stephen Brown, Manomet Center for Conservation Sciences
Project Duration: 2012 - 2015
This project evaluated the potential impacts of storm surges and relative sea level rise on nesting geese and eider species that commonly breed on the Yukon-Kuskokwim Delta (Y-K Delta). Habitat suitability maps for breeding waterbirds were developed to identify current waterbird breeding habitat and distributions. Short-term climate change impacts were assessed by comparing nest densities in relation to magnitude of storms that occurred in the prior fall from 2000-2013. Additionally, nest densities were modeled using random forests in relation to the time-integrated flood index (e.g., a storm specific measure accounting for both water depth and duration of flooding) for four modeled storms (2005, 2006, 2009, and 2011), as well as other environmental covariates. Long-term impacts were assessed using a derived annual inundation index (from the storm modeling) and other environmental covariates over the time frame 1985-2013.
No association was found between the short-term or long-term impacts of storms; storm magnitude, time-integrated flood index, and the annual inundation index explained little of the observed variation in geese and eider nest densities. Other environmental variables such as distance to coast appeared more influential to both annual and long-term nest densities. The sampling design and limited availability of inundation projections may have precluded finding a storm effect if one existed. For example, the monitoring design in which plots were surveyed once for waterbird nests then specifically not revisited the next five years precluded a more focused assessment comparing spatial distribution of next densities immediately before and after specific storms. Additionally, the temporal and spatial scale of the nest density and storm surge data may be have been inadequate to detect trends if they existed.
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