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Glen E. Liston

Publications and source records attributed to Glen E. Liston.

4 recordsLinked to original sources

Heterogeneity of locked‐pasture snow conditions modulate habitat and movement choices of a facultative migrant

Habitat selection and movement are key mechanisms by which animals can respond to and potentially cope with highly variable environmental conditions. Optimal responses likely vary, however, depending on the severity and scope of conditions. We tested this hypothesis using a facultative migrant species, the Great Gray Owl ( Strix nebulosa ), which exhibits high inter- and intra-individual variation in the timing, direction, and distance of winter movements. Specifically, we evaluated whether episodic, spatiotemporally variable “locked-pasture” snow conditions, which restrict access to subnivean food, prompted shifts in habitat selection or long-distance movements by owls. We quantified the movement of 42 owls using global positioning system (GPS) data within the Greater Yellowstone Ecosystem, USA, during 2017–2022. We used a novel ecological application of SnowModel, a snow evolution modeling system, to estimate fine-scale, physical snow properties likely to influence access to prey. Variables included snow depth, snow crusts produced by wind, and ice crusts produced by melt-freeze and rain-on-snow events. Owls avoided heterogeneously distributed wind crusts via local shifts in habitat selection. More homogenous ice crusts elicited long-distance movements away from affected home ranges. Finally, owls employed both proximate shifts in habitat selection and long-distance movements to avoid deeper snow. Ultimately, owls exhibited behavioral flexibility in response to limiting snow conditions that can vary in terms of severity, spatial extent, and duration. Such behavioral responses determine species distribution, with implications for population and community dynamics in spatiotemporally variable systems. Understanding the effects of, and responses to, environmental controls is increasingly important given the scope of on-going global change.

Idaho, Wyoming

Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

Water Resources Research

Analysis of ERS 1 synthetic aperture radar data of frozen lakes in northern Montana and implications for climate studies

Lakes that freeze each winter are good indicators of regional climate change if key parameters, such as freeze-up and breakup date and maximum ice thickness, are measured over a decade-scale time frame. Synthetic aperture radar (SAR) satellite data have proven to be especially useful for measurement of climatologically significant parameters characteristic of frozen lakes. In this paper, five lakes in Glacier National Park, Montana, have been studied both in the field and using Earth Remote-Sensing Satellite (ERS) 1 SAR data during the 1992-1993 winter. The lakes are characterized by clear ice, sometimes with tubular or rounded bubbles, and often with a layer of snow ice on top of the clear ice. They are also often snow covered. Freeze-up is detected quite easily using ERS 1 SAR data as soon as a thin layer of ice forms. The effect of snow ice on the backscatter is thought to be significant but is, as yet, undetermined. On the five lakes studied, relative backscatter was found to increase with ice thickness until a maximum was reached in February. Breakup, an often ill-defined occurrence, is difficult to detect because surface water causes the SAR signal to be absorbed, thus masking the ice below. Comparison of the bubble structure of thaw lakes in northern Alaska with lakes in northern Montana has shown that the ice structure is quite different, and this difference may contribute to differential SAR signature evolution in the lakes of the two areas.

Journal of Geophysical Research