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Item Shifts in the wintering distribution and abundance of emperor geese in Alaska(Elsevier BV, 2021-01) Uher-Koch, Brian D.; Buchheit, Raymond M.; Eldermire, Charles R.; Wilson, Heather M.; Schmutz, Joel A.For wildlife species that winter at northern latitudes, harsh overwinter conditions can play an important role in population dynamics. Recent changes in global temperatures have resulted in distributional shifts of wildlife species, as well as amelioration of winter climates in northern landscapes. The emperor goose (Anser canagicus), an endemic migratory bird of the Bering Sea region, winters across a large area of the subarctic, with potential differences in migration strategies and costs among individuals. As a long-standing species of conservation concern due to decreased population size, understanding the response of emperor geese to changing conditions has become critical to on-going management. We sought to evaluate changes in wintering distribution and arrival/departure dates over time, by comparing spatial and temporal patterns of wintering emperor geese from 2015 to 2017 (using geolocator data) to satellite telemetry data collected from 1999 to 2004. Further, we quantified changes in spatial patterns of winter abundance by comparing historical and contemporary aerial and ground surveys at three island complexes encompassing most of their winter distribution. Our results indicate that emperor geese are arriving at wintering areas earlier and spending more time at these areas than in the past. Our comparisons among historical aerial and ground surveys suggests that increasing numbers of emperor geese are wintering closer to breeding areas in western Alaska; a change likely related to increasing habitat availability due to shifting environmental conditions. Our results also showed that fewer emperor geese are using an area in the core of their wintering range, suggesting either decreased habitat quality or a reduction in migration distance via alternative wintering locations. Overall, our study highlights a rapid response to apparent habitat change likely due to warming temperatures and a reduction in ice cover and emphasizes the importance of understanding complex interactions among migration distance, the environment, and habitat in interpreting site selection.Item Using Remote Sensing and Machine Learning to Locate Groundwater Discharge to Salmon-Bearing Streams(MDPI AG, 2021-12) Gerlach, Mary E.; Rains, Kai C.; Guerrón-Orejuela, Edgar J.; Kleindl, William J.; Downs, Joni; Landry, Shawn M.; Rains, Mark C.We hypothesized topographic features alone could be used to locate groundwater discharge, but only where diagnostic topographic signatures could first be identified through the use of limited field observations and geologic data. We built a geodatabase from geologic and topographic data, with the geologic data only covering ~40% of the study area and topographic data derived from airborne LiDAR covering the entire study area. We identified two types of groundwater discharge: shallow hillslope groundwater discharge, commonly manifested as diffuse seeps, and aquifer-outcrop groundwater discharge, commonly manifested as springs. We developed multistep manual procedures that allowed us to accurately predict the locations of both types of groundwater discharge in 93% of cases, though only where geologic data were available. However, field verification suggested that both types of groundwater discharge could be identified by specific combinations of topographic variables alone. We then applied maximum entropy modeling, a machine learning technique, to predict the prevalence of both types of groundwater discharge using six topographic variables: profile curvature range, with a permutation importance of 43.2%, followed by distance to flowlines, elevation, topographic roughness index, flow-weighted slope, and planform curvature, with permutation importance of 20.8%, 18.5%, 15.2%, 1.8%, and 0.5%, respectively. The AUC values for the model were 0.95 for training data and 0.91 for testing data, indicating outstanding model performance.