Geology topics

Julian B. Fischer

Publications and source records attributed to Julian B. Fischer.

4 recordsLinked to original sources

USGS2022

Optimizing surveys of fall-staging geese using aerial imagery and automated counting

Ocular aerial surveys allow efficient coverage of large areas and can be used to monitor abundance and distribution of wild populations. However, uncertainty around resulting population estimates can be large due to difficulty in visually identifying and counting animals from aircraft, as well as logistical challenges in estimating detection probabilities. Photographic aerial surveys can mitigate these challenges and can allow flight at higher altitudes to minimize disturbance of birds and improve safety for surveyors. We evaluated a photographic aerial survey that incorporated a systematic sampling design with automated photo capture and processing for fall-staging geese at Izembek Lagoon, Alaska, in 2017–2019. Ocular aerial surveys have been completed at Izembek Lagoon for >40 years. For the new photo survey, we used a commercial system to automatically trigger cameras at preset points. We then applied a machine-learning algorithm trained to automatically identify and count geese in our photos, manually corrected those counts, and quantified the algorithm's accuracy. We translated corrected counts into density and extrapolated mean density across the entire lagoon to estimate total population size for Pacific brant ( Branta bernicla ) and cackling geese ( B. hutchinsii ). The automated algorithm undercounted geese, but successfully identified the small subset of photos containing geese. Manual correction was therefore needed only for photos automatically identified as containing geese, allowing substantial reduction of workload. Manually-corrected, photo-based estimates of Pacific brant and cackling goose population sizes were larger and more precise than ocular estimates in all 3 years. To reduce costs with little penalty for variance around population estimates, the photographic survey design could be optimized by reducing the number of transects to ~67% of the current number while still manually correcting all photos in which the automated algorithm detected geese. Further years of both ocular and photo surveys would be needed to calibrate the photo estimates against the >40-year timeseries of the ocular survey, after which the photo series could successfully guide management of Pacific brant. As technologies continue to advance, we expect photographic surveys with automated counting to be easily implemented and advantageous to many monitoring programs.

Alaska↗

USGS2022

Effects of mass capture on survival of greater white-fronted geese in Alaska

Mass capture of flightless geese during the summer is a common trapping technique to obtain large numbers of individuals for research and marking, but few studies have assessed the impacts of this method on the survival of after-hatch-year geese. We evaluated the effects of holding time and captured flock size on the survival of >26,000 subadult (second yr) and adult (≥third yr) greater white-fronted geese ( Anser albifrons frontalis ) banded in Alaska, USA, 1999–2017. We constructed models with and without capture effects to analyze our band-recovery data and used Akaike's Information Criterion to rank our model set. Models that included both capture-related variables ranked highest. Longer individual holding times negatively affected survival during the first year after banding, and effects were greatest during the earliest years of our study when holding times were generally longer and protocols to minimize negative capture effects were less refined. There was a positive relationship between survival and captured flock size. We suggest practitioners reduce holding times of geese during mass captures to the extent practicable and continually evaluate and refine their methods to minimize negative capture effects.

Alaska↗

USGS2019

Spatio-temporal population change of Arctic-breeding waterbirds on the Arctic Coastal Plain of Alaska

Rapid physical changes that are occurring in the Arctic are primary drivers of landscape change and thus may drive population dynamics of Arctic-breeding birds. Despite the importance of this region to breeding and molting waterbirds, lack of a comprehensive analysis of historic data has hindered quantifying avian population change. We estimated distribution, abundance, and spatially explicit population trend of 20 breeding waterbird species using 25 years (1992–2016) of aerial survey data collected on the Arctic Coastal Plain (ACP), Alaska. The ACP is an extensive wetland complex on Alaska’s North Slope that supports millions of breeding waterbirds and includes portions of the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge. We summarized annual counts into approximately 6-km by 6-km grid cells and analyzed data with generalized linear mixed models that accounted for survey timing and spatio-temporal autocorrelation. Geese and swans were most abundant along the coast between Admiralty Bay and Prudhoe Bay. Sea ducks, generalist predators (i.e., jaeger, gulls, terns), and loons were most abundant between Utqiaġvik and Point Lay, Alaska. Important areas for most species included the coastal fringe near Teshekpuk Lake, the Colville River Delta, and Admiralty Bay. The National Petroleum Reserve—Alaska was an important area for all species examined. Conversely, density on the coastal plain of the Arctic National Wildlife Refuge was greater than average for 20% of species. Annual population growth rates over the 25-year survey period were variable: 13 increased (range: 1.4%–13.8%), one decreased (-3.4%), and six were stable. However, even species with no overall population trend had areas of changing population size, suggesting localized conditions affected waterbird distributions on the ACP. Our results can be used to better inform land use decisions, improve monitoring of waterbird populations, and increase understanding of avian response to ecological change in the Arctic.

Alaska↗

USGS2018

Variation in age ratio of midcontinent greater white-fronted geese during fall migration

Annual productivity is an important parameter for the management of waterfowl populations. Fall age ratio (juveniles:total birds) is an index of productivity of the preceding breeding season. However, differences in the timing of migration between family groups and nonbreeding birds may bias age-ratio estimates. We examined temporal variation in age ratios of midcontinent greater white-fronted geese Anser albifrons frontalis from interior and northwestern Alaska at a northern autumn staging area near Delta Junction, Alaska. Photographic sampling conducted near Delta Junction resulted in an annual age ratio of 0.388 ± 0.004 (mean ± SE) in 2010 and 0.390 ± 0.001 in 2011. Our study demonstrated temporal variation in age ratios over the duration of the migration period during August and September. We recommend that sampling be conducted for 3-d periods at the beginning, middle, and end of the migration period to account for temporal variation in migration of family groups.

Journal of Fish and Wildlife Management↗