Summary: | I developed a stochastic dynamic programming model of adult female Semipalmated Sandpiper (Calidris pusilla) spring migration for the purpose of adaptive management of wetlands along their migratory route. Semipalmated Sandpipers are small abundant shorebirds that migrate through Merritt Island National Wildlife Refuge, FL, Yawkey Reserve, SC, Pea Island National Wildlife Refuge, NC, and Delaware Bay on their way from the Caribbean and South America to arctic North American breeding grounds. The first three stopover sites mentioned include managed wetlands. To manage these wetlands for Semipalmated Sandpiper and other migratory shorebirds' fitness by changing water levels to alter food availability, it is important to understand how the birds are using these stopover sites. A stochastic dynamic programming model is a model of organism behavior which assumes that the organism is attempting to optimize its fitness. In this model, the fitness of the birds depends on surviving migration as well as arriving on the breeding grounds close to an optimal date and with sufficient energy reserves. The birds can decide each day whether to stay at the current stopover site and feed, or to fly to the next site. Model parameters include flight constants, ground speed probabilities, energy gain, and predation rates. The values of several parameters were tuned so that average peaks of migration at the stopover sites and average percent fat of the birds on different days and stopover sites correlated well with data taken from published and unpublished studies. The model outcomes include average fitness, seasonal mortality rate, reproductive output, average length of stay at each stopover site, and percentage skimming (not staying to feed) at each stopover site. The peaks of migration matched the targets set. The birds stayed longest at the first and last stopover sites; many birds did not stop to feed at the middle two stopover sites. The average mortality of the spring migration season was 0.099, and the average reproductive ...
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