Modeling autumn migration of a rare soaring raptor identifies new movement corridors in central Appalachia

摘要: Abstract Understanding animal movements is fundamental to ecology and conservation, yet direct measurement of birds both challenging costly. Raptor behavior demography are especially difficult monitor, but models movement can provide information toward this goal. The golden eagle (Aquila chrysaetos) in eastern North America an apex predator regional conservation concern, little known about its population ecology, movements, or behavior. We designed agent-based model simulate autumn migration eagles Pennsylvania, USA. Inputs the included on topography, flight behaviors (i.e. slope-soaring thermal-soaring gliding), estimated uplift, a principal axis migration. In total, we modeled 6094 routes, averaging 2191 (±1281; ±SD; range: 3–5373) moves. Simulations were spatially comparable historic route data collected via telemetry generally followed topography that provided uplift. our model, orographic uplift available migrant was stronger more frequent than thermal forms not correlated with one another (r = −0.145). Modeled follows narrow-front pattern as individuals concentrated areas produce Simulated flights days when counts high at monitoring sites. contrast, simulations dispersed fewer actual recorded. used output from select new sites could be for migratory raptors. Relatively large numbers observed these sites, thus validating performance model. This work identifies novel, cost-effective method modeling patterns furthering goals rare, low-density raptor species.