Navigating snowscapes: scale-dependent responses of mountain sheep to snowpack properties

Diverse migration patterns and seasonal habitat use of Stone's sheep (Ovis dalli stonei)

We describe temporal and spatial patterns of seasonal space-use and migration by 16 GPS-collared Stone's sheep (Ovis dalli stonei) from nine bands in the Cassiar Mountains of northern British Columbia, Canada. Our objectives were to identify the timing of spring and fall migrations, characterize summer and winter ranges, map and describe migration routes and use of stopover sites, and document altitudinal change across seasons. Our last objective was to assess individual migration strategies based on patterns of geographic migration, altitudinal migration, or residency. Median start and end dates of the spring migration were 12 and 17 Jun (range: 20 May to 05 Aug), and of the fall migration were 30 Aug and 22 Sep (range: 21 Aug to 07 Jan). The median area of winter and summer ranges for geographic migrants were 630.8 ha and 2,829.0 ha, respectively, with a broad range from about 233.6 to 10,196.2 ha. Individuals showed high fidelity to winter ranges over the limited duration of the study. The winter and summer ranges of most individuals (n = 15) were at moderate to high elevations with a median summer elevation of 1,709 m (1,563-1,827 m) and 1,673 m (1,478-1,751 m) that varied <150 m between ranges. Almost all collared females (n = 14) exhibited changes in elevation use that coincide with abbreviated altitudinal migration. Specifically, these females descended to lower spring elevations from their winter range (Δ > 150 m), and then gradually moved up to higher-elevation summer ranges (Δ > 150 m). In the fall, they descended to lower elevations (Δ > 100 m) before returning to their higher winter ranges. The median distance travelled along geographic migration routes was 16.3 km (range: 7.6-47.4 km). During the spring migration, most geographic migrants (n = 8) used at least one stopover site (median = 1.5, range: 0-4), while almost all migrants (n = 11) used stopover sites more frequently in the fall (median = 2.5, range: 0-6). Of the 13 migratory individuals that had at least one other collared individual in their band, most migrated at about the same time, occupied the same summer and winter ranges, used similar migration routes and stopover sites, and exhibited the same migration strategy. We found collared females exhibited four different migration strategies which mostly varied across bands. Migration strategies included long-distance geographic migrants (n = 5), short-distance geographic migrants (n = 5), vacillating migrants (n = 2), and abbreviated altitudinal migrants (n = 4). Different migratory strategies occurred within one band where one collared individual migrated and two did not. We conclude that female Stone's sheep in the Cassiar Mountains displayed a diverse assemblage of seasonal habitat use and migratory behaviors. By delineating seasonal ranges, migration routes and stopover sites, we identify potential areas of priority that can help inform land-use planning and preserve the native migrations of Stone's sheep in the region.

The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets

Animal-borne tagging (bio-logging) generates large and complex datasets. In particular, accelerometer tags, which provide information on behaviour and energy expenditure of wild animals, produce high-resolution multi-dimensional data, and can be challenging to analyse. We tested the performance of commonly used artificial intelligence tools on datasets of increasing volume and dimensionality. By collecting bio-logging data across several sampling seasons, datasets are inherently characterized by inter-individual variability. Such information should be considered when predicting behaviour. We integrated both unsupervised and supervised machine learning approaches to predict behaviours in two penguin species. The classified behaviours obtained from the unsupervised approach Expectation Maximisation were used to train the supervised approach Random Forest. We assessed agreement between the approaches, the performance of Random Forest on unknown data and the implications for the calculation of energy expenditure. Consideration of behavioural variability resulted in high agreement (> 80%) in behavioural classifications and minimal differences in energy expenditure estimates. However, some outliers with < 70% of agreement, highlighted how behaviours characterized by signal similarity are confused. We advise the broad bio-logging community, approaching these large datasets, to be cautious when upscaling predictions, as this might lead to less accurate estimates of behaviour and energy expenditure.

Interactive effects of wildfires, season, and predator activity shape mule deer movements

Wildfires are increasing in size, frequency, and severity due to climate change and fire suppression, but the direct and indirect effects on wildlife remain largely unresolved. Fire removes forest canopy, which can improve forage for ungulates but also reduce snow interception, leading to a deeper snowpack and potentially increased vulnerability to predation in winter. If ungulates exhibit predator-mediated foraging, burns should generally be selected for in summer to access high-quality forage and avoided in winter to reduce predation risk in deep snow. Fires also typically increase the amount of deadfall and initiate growth of dense understory vegetation, creating obstacles that may confer a hunting advantage to stalking predators and a disadvantage to coursing predators. To minimize risk, ungulates may therefore avoid burns when and where stalking predators are most active, and use burns when and where coursing predators are most active. We used telemetry data from GPS-collared mule deer (Odocoileus hemionus), cougars (Puma concolor), and wolves (Canis lupus) to develop step selection functions to examine how mule deer navigated species-specific predation risk across a landscape in northern Washington, USA that has experienced substantial wildfire activity during the past several decades. We considered a diverse array of wildfire impacts, accounting for both the severity of the fire and time since the burn (1 to 35 years) in our analyses. We observed support for the predator mediating foraging hypothesis: mule deer generally selected for burned areas in summer and avoided burns in winter. In addition, deer increased use of burned areas when and where wolf activity was high and avoided burns when and where cougar use was high in winter, suggesting the hunting mode of resident predators mediated the seasonal response of deer to burns. Deer were not more likely to die by predation in burned than in unburned areas, indicating that they adequately manage fire-induced changes to predation risk. As fire activity increases with climate change, our findings indicate the impact on ungulates will depend on tradeoffs between enhanced summer forage and functionally reduced winter range, mediated by characteristics of the predator community.

Increasing fire frequency and severity will increase habitat loss for a boreal forest indicator species

Climate change will lead to more frequent and more severe fires in some areas of boreal forests, affecting the distribution and availability of late-successional forest communities. These forest communities help to protect globally significant carbon reserves beneath permafrost layers and provide habitat for many animal species, including forest-dwelling caribou. Many caribou populations are declining, yet the mechanisms by which changing fire regimes could affect caribou declines are poorly understood. We analyzed resource selection of 686 GPS-collared female caribou from three ecotypes and 15 populations in a ~600,000 km² region of northwest Canada and eastern Alaska. These populations span a wide gradient of fire frequency but experience low levels of human-caused habitat disturbance. We used a mixed-effects modeling framework to characterize caribou resource selection in response to burns at different seasons and spatiotemporal scales, and to test for functional responses in resource selection to burn availability. We also tested mechanisms driving observed selection patterns using burn severity and lichen cover data. Caribou avoided burns more strongly during winter relative to summer and at larger spatiotemporal scales relative to smaller scales. During the winter, caribou consistently avoided burns at both spatiotemporal scales as burn availability increased, indicating little evidence of a functional response. However, they decreased their avoidance of burns during summer as burn availability increased. Burn availability explained more variation in caribou selection for burns than ecotype. Within burns, caribou strongly avoided severely burned areas in winter, and this avoidance lasted nearly 30 years after a fire. Caribou within burns also selected higher cover of terrestrial lichen (an important caribou food source). We found a negative relationship between burn severity and lichen cover, confirming that caribou avoidance of burns was consistent with lower lichen abundance. Consistent winter avoidance of burns and severely burned areas suggests that caribou will experience increasing winter habitat loss as fire frequency and severity increase. Our results highlight the potential for climate-induced alteration of natural disturbance regimes to affect boreal biodiversity through habitat loss. We suggest that management strategies prioritizing protection of core winter range habitat with lower burn probabilities would provide important climate-change refugia for caribou.

Determining the influence of snow and temperature on the movement rates of wood bison (Bison bison athabascae)

Snow is understood to limit wildlife movements, often being the most important determinant of winter movement for animals in the boreal forest. However, the combined effect of snow and temperature on the movement ecology of animals at high latitudes is less understood. Here, we used GPS-collar data from a small population of wood bison (Bison bison athabascae Rhoads, 1898) in northeastern Alberta, Canada, to develop a series of generalized additive mixed models characterizing the effect of cumulative snow depth, daily change in snow depth, and temperature on movement rates. Our most supported model included cumulative snow depth, temperature, and day of winter. Bison movements decreased in the first 75 days of winter during snow accumulation and dramatically increased in the final 14 days of winter during snow melt. Cumulative snow depth, not daily change in snow depth, reduced wood bison movement rates, and movement rates increased more rapidly in warmer temperatures than in temperatures below −6.4 °C. By quantifying both the direction and the magnitude of snow and temperature’s effects on bison movement, our study fills critical knowledge gaps relating to the winter movement ecology of wood bison and contributes to a growing body of knowledge informing their conservation in the Anthropocene.

Habitat selection by Dall's sheep is influenced by multiple factors including direct and indirect climate effects

Arctic and boreal environments are changing rapidly, which could decouple behavioral and demographic traits of animals from the resource pulses that have shaped their evolution. Dall's sheep (Ovis dalli dalli) in northwestern regions of the USA and Canada, survive long, severe winters and reproduce during summers with short growing seasons. We sought to understand the vulnerability of Dall's sheep to a changing climate in Lake Clark National Park and Preserve, Alaska, USA. We developed ecological hypotheses about nutritional needs, security from predators, energetic costs of movement, and thermal shelter to describe habitat selection during winter, spring, and summer and evaluated habitat and climate variables that reflected these hypotheses. We used the synoptic model of animal space use to estimate parameters of habitat selection by individual females and calculated likelihoods for ecological hypotheses within seasonal models. Our results showed that seasonal habitat selection was influenced by multiple ecological requirements simultaneously. Across all seasons, sheep selected steep rugged areas near escape terrain for security from predators. During winter and spring, sheep selected habitats with increased forage and security, moderated thermal conditions, and lowered energetic costs of movement. During summer, nutritional needs and security influenced habitat selection. Climate directly influenced habitat selection during the spring lambing period when sheep selected areas with lower snow depths, less snow cover, and higher air temperatures. Indirectly, climate is linked to the expansion of shrub/scrub vegetation, which was significantly avoided in all seasons. Dall's sheep balance resource selection to meet multiple needs across seasons and such behaviors are finely tuned to patterns of phenology and climate. Direct and indirect effects of a changing climate may reduce their ability to balance their needs and lead to continued population declines. However, several management approaches could promote resiliency of alpine habitats that support Dall's sheep populations.

Spatiotemporally variable snow properties drive habitat use of an Arctic mesopredator

Climate change is rapidly altering the composition and availability of snow, with implications for snow-affected ecological processes, including reproduction, predation, habitat selection, and migration. How snowpack changes influence these ecological processes is mediated by physical snowpack properties, such as depth, density, hardness, and strength, each of which is in turn affected by climate change. Despite this, it remains difficult to obtain meaningful snow information relevant to the ecological processes of interest, precluding a mechanistic understanding of these effects. This problem is acute for species that rely on particular attributes of the subnivean space, for example depth, thermal resistance, and structural stability, for key life-history processes like reproduction, thermoregulation, and predation avoidance. We used a spatially explicit snow evolution model to investigate how habitat selection of a species that uses the subnivean space, the wolverine, is related to snow depth, snow density, and snow melt on Arctic tundra. We modeled these snow properties at a 10 m spatial and a daily temporal resolution for 3 years, and used integrated step selection analyses of GPS collar data from 21 wolverines to determine how these snow properties influenced habitat selection and movement. We found that wolverines selected deeper, denser snow, but only when it was not undergoing melt, bolstering the evidence that these snow properties are important to species that use the Arctic snowpack for subnivean resting sites and dens. We discuss the implications of these findings in the context of climate change impacts on subnivean species.

Seasonal influence of snow conditions on Dall's sheep productivity in Wrangell-St Elias National Park and Preserve

Dall's sheep (Ovis dalli dalli) are endemic to alpine areas of sub-Arctic and Arctic northwest America and are an ungulate species of high economic and cultural importance. Populations have historically experienced large fluctuations in size, and studies have linked population declines to decreased productivity as a consequence of late-spring snow cover. However, it is not known how the seasonality of snow accumulation and characteristics such as depth and density may affect Dall's sheep productivity. We examined relationships between snow and climate conditions and summer lamb production in Wrangell-St Elias National Park and Preserve, Alaska over a 37-year study period. To produce covariates pertaining to the quality of the snowpack, a spatially-explicit snow evolution model was forced with meteorological data from a gridded climate re-analysis from 1980 to 2017 and calibrated with ground-based snow surveys and validated by snow depth data from remote cameras. The best calibrated model produced an RMSE of 0.08 m (bias 0.06 m) for snow depth compared to the remote camera data. Observed lamb-to-ewe ratios from 19 summers of survey data were regressed against seasonally aggregated modelled snow and climate properties from the preceding snow season. We found that a multiple regression model of fall snow depth and fall air temperature explained 41% of the variance in lamb-to-ewe ratios (R2 = .41, F(2,38) = 14.89, p<0.001), with decreased lamb production following deep snow conditions and colder fall temperatures. Our results suggest the early establishment and persistence of challenging snow conditions is more important than snow conditions immediately prior to and during lambing. These findings may help wildlife managers to better anticipate Dall's sheep recruitment dynamics.

An application of upscaled optimal foraging theory using hidden Markov modelling: year-round behavioural variation in a large arctic herbivore

BACKGROUND

In highly seasonal environments, animals face critical decisions regarding time allocation, diet optimisation, and habitat use. In the Arctic, the short summers are crucial for replenishing body reserves, while low food availability and increased energetic demands characterise the long winters (9-10 months). Under such extreme seasonal variability, even small deviations from optimal time allocation can markedly impact individuals' condition, reproductive success and survival. We investigated which environmental conditions influenced daily, seasonal, and interannual variation in time allocation in high-arctic muskoxen (Ovibos moschatus) and evaluated whether results support qualitative predictions derived from upscaled optimal foraging theory.

METHODS

Using hidden Markov models (HMMs), we inferred behavioural states (foraging, resting, relocating) from hourly positions of GPS-collared females tracked in northeast Greenland (28 muskox-years). To relate behavioural variation to environmental conditions, we considered a wide range of spatially and/or temporally explicit covariates in the HMMs.

RESULTS

While we found little interannual variation, daily and seasonal time allocation varied markedly. Scheduling of daily activities was distinct throughout the year except for the period of continuous daylight. During summer, muskoxen spent about 69% of time foraging and 19% resting, without environmental constraints on foraging activity. During winter, time spent foraging decreased to 45%, whereas about 43% of time was spent resting, mediated by longer resting bouts than during summer.

CONCLUSIONS

Our results clearly indicate that female muskoxen follow an energy intake maximisation strategy during the arctic summer. During winter, our results were not easily reconcilable with just one dominant foraging strategy. The overall reduction in activity likely reflects higher time requirements for rumination in response to the reduction of forage quality (supporting an energy intake maximisation strategy). However, deep snow and low temperatures were apparent constraints to winter foraging, hence also suggesting attempts to conserve energy (net energy maximisation strategy). Our approach provides new insights into the year-round behavioural strategies of the largest Arctic herbivore and outlines a practical example of how to approximate qualitative predictions of upscaled optimal foraging theory using multi-year GPS tracking data.