Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a Mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental-scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 d of flight with a mean seasonal survivorship of 90.5% (95% Cl = 89.2%, 91.9%), whereas spring migration took a mean of 23.5 d of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry, and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including the Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.

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Future climate and land-use changes and growing human populations may reduce the abundance of water resources relative to anthropogenic and ecological needs in the Northeast and Midwest (U.S.). We used output from WaSSI, a water accounting model, to assess potential changes between 2010 and 2060 in (1) anthropogenic water stress for watersheds throughout the Northeast and Midwest and (2) native fish species richness (i.e., number of species) for the Upper Mississippi water resource region (UMWRR). Six alternative scenarios of climate change, land-use change, and human population growth indicated future water supplies will, on average across the region, be adequate to meet anthropogenic demands. Nevertheless, the number of individual watersheds experiencing severe stress (demand > supplies) was projected to increase for most scenarios, and some watersheds were projected to experience severe stress under multiple scenarios. Similarly, we projected declines in fish species richness for UMWRR watersheds and found the number of watersheds with projected declines and the average magnitude of declines varied across scenarios. All watersheds in the UMWRR were projected to experience declines in richness for at least two future scenarios. Many watersheds projected to experience declines in fish species richness were not projected to experience severe anthropogenic water stress, emphasizing the need for multidimensional impact assessments of changing water resources.(KEY TERMS: fish; climate variability/change; surface water hydrology; land-use/land-cover change; planning; water supply; water use; water stress; GIS.)

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