Geology topics

Sophie L. Gilbert

Publications and source records attributed to Sophie L. Gilbert.

3 recordsLinked to original sources

USGS2025

Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter

Collared pikas ( Ochotona collaris ) are cold adapted alpine lagomorphs of western Canada and Alaska, USA, that are vulnerable to direct and indirect effects of climate change. However, how and to what extent such changes influence persistence for this species is not well understood, particularly at fine spatial scales. Our goal was to evaluate how microclimate and microhabitat characteristics influence occupancy of collared pikas. We quantified thermal conditions during both summer and winter to test hypotheses about potential drivers of pika persistence. We recorded den occupancy and territory characteristics, including in situ measurements of den microclimate, across three study areas with contrasting climate gradients in southcentral and interior Alaska during 2017–2022. We examined changes in pika den occurrence by estimating annual colonization and extinction rates with a Bayesian dynamic occurrence model with forage availability, rock size, and multiple den temperature metrics as the explanatory variables. Our top model indicated that daily maximum temperature during both summer and winter best predicted den persistence and larger rocks had a moderating effect on warm summer den temperatures. This information helps to advance understanding about the mechanistic links between climate and population persistence for small mammal species under a rapidly changing arctic climate.

Alaska↗

USGS2016

Unmanned aircraft systems in wildlife research: Current and future applications of a transformative technology

Unmanned aircraft systems (UAS) – also called unmanned aerial vehicles (UAVs) or drones – are an emerging tool that may provide a safer, more cost-effective, and quieter alternative to traditional research methods. We review examples where UAS have been used to document wildlife abundance, behavior, and habitat, and illustrate the strengths and weaknesses of this technology with two case studies. We summarize research on behavioral responses of wildlife to UAS, and discuss the need to understand how recreational and commercial applications of this technology could disturb certain species. Currently, the widespread implementation of UAS by scientists is limited by flight range, regulatory frameworks, and a lack of validation. UAS are most effective when used to examine smaller areas close to their launch sites, whereas manned aircraft are recommended for surveying greater distances. The growing demand for UAS in research and industry is driving rapid regulatory and technological progress, which in turn will make them more accessible and effective as analytical tools.

Frontiers in Ecology and the Environment↗

USGS2014

Re-evaluating neonatal-age models for ungulates: Does model choice affect survival estimates?

New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001–2009, we captured and radiocollared 174 newborn (≤24-hrs old) ungulates: 76 white-tailed deer ( Odocoileus virginianus ) in Minnesota and South Dakota, 61 mule deer ( O. hemionus ) in California, and 37 pronghorn ( Antilocapra americana ) in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age) in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days) for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days) for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatal-age models on short- and long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i.e., weekly versus daily) for estimating survival.

PLoS ONE↗