Optimal migration schedules depend on the landscape and the physical environment: a dynamic modeling view

We developed a dynamic state variable model of individual migrating shorebirds for use in testing hypotheses about spring migration strategies of the Pectoral Sandpiper Calidris melanotos. We conducted model sensitivity analyses to determine how predicted migration schedules might vary with respect to the landscape and the physical environment. In landscapes with closely spaced, high-quality stopovers, female Pectoral Sandpipers can vary widely in their migration schedules and still arrive on the breeding grounds early enough and with sufficient energy reserves to achieve maximum reproductive success. Such a population might appear quite variable, and show no stopover patterns, even if all individuals were making optimal decisions. Latitudinal gradients in temperature and photoperiod differentially affect a bird's energy budget as it moves northward in the spring. Stopovers at more northerly locations are associated with higher metabolic rates, lower food abundance in early spring, and longer days for feeding. The optimal migration schedule in these conditions can be quite different from that in a homogeneous environment, and patterns observed in the field can be misinterpreted if the environmental gradients are not considered. The landscape and the physical environment shape migration schedules and influence one's ability to interpret patterns observed at stopovers. Modeling these factors may lead to new insights about migration adaptations in heterogeneous environments.