Nonlinear responses of wolverine populations to declining winter snowpack

Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought

Recent snow droughts associated with unusually warm winters are predicted to increase in frequency and affect species dependent upon snowpack for winter survival. Changes in populations of some cold-adapted species have been attributed to heat stress or indirect effects on habitat from unusually warm summers, but little is known about the importance of winter weather to population dynamics and how responses to snow drought vary among sympatric species. We evaluated changes in abundance of hoary marmots (Marmota caligata) over a period that included a year of record-low snowpack to identify mechanisms associated with weather and snowpack. To consider interspecies comparisons, our analysis used the same a priori model set as a concurrent study that evaluated responses of American pikas (Ochotona princeps) to weather and snowpack in the same study area of North Cascades National Park, Washington, USA. We hypothesized that marmot abundance reflected mechanisms related to heat stress, cold stress, cold exposure without an insulating snowpack, snowpack duration, atmospheric moisture, growing-season precipitation, or select combinations of these mechanisms. Changes in marmot abundances included a 74% decline from 2007 to 2016 and were best explained by an interaction of chronic dryness with exposure to acute cold without snowpack in winter. Physiological stress during hibernation from exposure to cold, dry air appeared to be the most likely mechanism of change in marmot abundance. Alternative mechanisms associated with changes to winter weather, including early emergence from hibernation or altered vegetation dynamics, had less support. A post hoc assessment of vegetative phenology and productivity did not support vegetation dynamics as a primary driver of marmot abundance across years. Although marmot and pika abundances were explained by strikingly similar models over periods of many years, details of the mechanisms involved likely differ between species because pika abundances increased in areas where marmots declined. Such differences may lead to diverging geographic distributions of these species as global change continues.

Low wolverine (Gulo gulo) density in a national park complex of the Canadian Rocky Mountains

Large carnivores are sensitive to human-caused extirpation due to large home ranges, low population densities, and low reproductive rates. Protected areas help maintain populations by acting as sources, but human-caused mortality, habitat displacement, and edge effects occurring at protected area boundaries may reduce that function. The national parks Banff, Yoho, and Kootenay in the Canadian Rocky Mountains are refugia for large carnivores, including wolverines (Gulo gulo (Linnaeus, 1758)). Despite growing conservation concern, empirical baseline population data for wolverines remain scarce throughout their range, including most of Canada. We hypothesized (i) that in these national parks, wolverine density matched values expected for high-quality habitat, and (ii) that edge effects decreased density towards park boundaries. We conducted systematic non-invasive genetic sampling surveys covering >7000 km2 (2011 and 2013). Using spatial capture–recapture models, we estimated mean (±SE) female (1.5 ± 0.3 and 1.4 ± 0.3 wolverine/1000 km2), male (1.8 ± 0.4 and 1.5 ± 0.3 wolverine/1000 km2), and combined (3.3 ± 0.5 and 3.0 ± 0.4 wolverine/1000 km2) densities for 2011 and 2013, respectively. These estimates were lower than predictions based on density extrapolation from nearby high-quality habitat, and density decreased towards park boundaries. To benefit the population, we recommend creating buffer zones around parks that protect female habitat and prohibit harvest.

Assessing the risks to United States and Canadian mammals caused by climate change using a trait-mediated model

A set of 182 populations of 76 mammal species in the United States and Canada, examined in natural conditions with minimized disturbances or management effects, shows that responses to climate change include negative responses, such as elevational range contractions, upward shifts and decreases in abundance, positive responses, such as range expansions, and no detectable responses. Responses vary among and within mammal species but many are correlated with species traits, particularly the responses linked to high extinction risks (= climate change risk: decreases in population sizes, range contractions, local extirpations). The traits showing the strongest links to differential responses to climate change are 1) body size—large mammals respond more often and most negatively to climate change, 2) activity times—few mammals with flexible active times respond to climate change, and 3) spatial distribution—high-latitude and high-elevation mammals responded more often to climate change. Using these traits and two approaches to trait weighting, I modeled the relative climate change risk for all 328 terrestrial, nonvolant mammal species in the United States and Canada across 10 levels of risk (low = 1–2, moderate = 3–4, moderate-high = 5–6, high = 7–8, very high = 9–10). The models predicted that 15% of these mammalian species are in the high- and very high-risk categories, including species from most orders. Many mammal populations and species listed as of conservation concern due to other human impacts by national or international agencies are also predicted by my models to be in the higher categories of climate change risk. My intention for these models is to clarify for managers and researchers which, where, and how mammals are responding to climate change relatively independent of other anthropogenic stressors (e.g., large-scale habitat change, overhunting) and to provide a preliminary assessment of species most in need of careful monitoring for climate change impacts.

Compounding effects of climate change reduce population viability of a montane amphibian

Anthropogenic climate change presents challenges and opportunities to the growth, reproduction, and survival of individuals throughout their life cycles. Demographic compensation among life-history stages has the potential to buffer populations from decline, but alternatively, compounding negative effects can lead to accelerated population decline and extinction. In montane ecosystems of the U.S. Pacific Northwest, increasing temperatures are resulting in a transition from snow-dominated to rain-dominated precipitation events, reducing snowpack. For ectotherms such as amphibians, warmer winters can reduce the frequency of critical minimum temperatures and increase the length of summer growing seasons, benefiting post-metamorphic stages, but may also increase metabolic costs during winter months, which could decrease survival. Lower snowpack levels also result in wetlands that dry sooner or more frequently in the summer, increasing larval desiccation risk. To evaluate how these challenges and opportunities compound within a species' life history, we collected demographic data on Cascades frog (Rana cascadae) in Olympic National Park in Washington state to parameterize stage-based stochastic matrix population models under current and future (A1B, 2040s, and 2080s) environmental conditions. We estimated the proportion of reproductive effort lost each year due to drying using watershed-specific hydrologic models, and coupled this with an analysis that relates 15 yr of R. cascadae abundance data with a suite of climate variables. We estimated the current population growth (λ_s ) to be 0.97 (95% CI 0.84-1.13), but predict that λ_s will decline under continued climate warming, resulting in a 62% chance of extinction by the 2080s because of compounding negative effects on early and late life history stages. By the 2080s, our models predict that larval mortality will increase by 17% as a result of increased pond drying, and adult survival will decrease by 7% as winter length and summer precipitation continue to decrease. We find that reduced larval survival drives initial declines in the 2040s, but further declines in the 2080s are compounded by decreases in adult survival. Our results demonstrate the need to understand the potential for compounding or compensatory effects within different life history stages to exacerbate or buffer the effects of climate change on population growth rates through time.

Cumulative effects of climate and landscape change drive spatial distribution of Rocky Mountain wolverine (Gulo gulo L.)

Contemporary landscapes are subject to a multitude of human‐derived stressors. Effects of such stressors are increasingly realized by population declines and large‐scale extirpation of taxa worldwide. Most notably, cumulative effects of climate and landscape change can limit species’ local adaptation and dispersal capabilities, thereby reducing realized niche space and range extent. Resolving the cumulative effects of multiple stressors on species persistence is a pressing challenge in ecology, especially for declining species. For example, wolverines (Gulo gulo L.) persist on only 40% of their historic North American range. While climate change has been shown to be a mechanism of range retractions, anthropogenic landscape disturbance has been recently implicated. We hypothesized these two interact to effect declines. We surveyed wolverine occurrence using camera trapping and genetic tagging at 104 sites at the wolverine range edge, spanning a 15,000 km² gradient of climate, topographic, anthropogenic, and biotic variables. We used occupancy and generalized linear models to disentangle the factors explaining wolverine distribution. Persistent spring snow pack—expected to decrease with climate change—was a significant predictor, but so was anthropogenic landscape change. Canid mesocarnivores, which we hypothesize are competitors supported by anthropogenic landscape change, had comparatively weaker effect. Wolverine population declines and range shifts likely result from climate change and landscape change operating in tandem. We contend that similar results are likely for many species and that research that simultaneously examines climate change, landscape change, and the biotic landscape is warranted. Ecology research and species conservation plans that address these interactions are more likely to meet their objectives.

Wolverine behavior varies spatially with anthropogenic footprint: implications for conservation and inferences about declines

Understanding a species’ behavioral response to rapid environmental change is an ongoing challenge in modern conservation. Anthropogenic landscape modification, or “human footprint,” is well documented as a central cause of large mammal decline and range contractions where the proximal mechanisms of decline are often contentious. Direct mortality is an obvious cause; alternatively, human‐modified landscapes perceived as unsuitable by some species may contribute to shifts in space use through preferential habitat selection. A useful approach to tease these effects apart is to determine whether behaviors potentially associated with risk vary with human footprint. We hypothesized wolverine (Gulo gulo) behaviors vary with different degrees of human footprint. We quantified metrics of behavior, which we assumed to indicate risk perception, from photographic images from a large existing camera‐trapping dataset collected to understand wolverine distribution in the Rocky Mountains of Alberta, Canada. We systematically deployed 164 camera sites across three study areas covering approximately 24,000 km², sampled monthly between December and April (2007–2013). Wolverine behavior varied markedly across the study areas. Variation in behavior decreased with increasing human footprint. Increasing human footprint may constrain potential variation in behavior, through either restricting behavioral plasticity or individual variation in areas of high human impact. We hypothesize that behavioral constraints may indicate an increase in perceived risk in human‐modified landscapes. Although survival is obviously a key contributor to species population decline and range loss, behavior may also make a significant contribution.

Cold truths: how winter drives responses of terrestrial organisms to climate change

Winter is a key driver of individual performance, community composition, and ecological interactions in terrestrial habitats. Although climate change research tends to focus on performance in the growing season, climate change is also modifying winter conditions rapidly. Changes to winter temperatures, the variability of winter conditions, and winter snow cover can interact to induce cold injury, alter energy and water balance, advance or retard phenology, and modify community interactions. Species vary in their susceptibility to these winter drivers, hampering efforts to predict biological responses to climate change. Existing frameworks for predicting the impacts of climate change do not incorporate the complexity of organismal responses to winter. Here, we synthesise organismal responses to winter climate change, and use this synthesis to build a framework to predict exposure and sensitivity to negative impacts. This framework can be used to estimate the vulnerability of species to winter climate change. We describe the importance of relationships between winter conditions and performance during the growing season in determining fitness, and demonstrate how summer and winter processes are linked. Incorporating winter into current models will require concerted effort from theoreticians and empiricists, and the expansion of current growing-season studies to incorporate winter.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (< 1 km2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9-2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model's resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

Ice-cover effects on competitive interactions between two fish species

1. Variations in the strength of ecological interactions between seasons have received little attention, despite an increased focus on climate alterations on ecosystems. Particularly, the winter situation is often neglected when studying competitive interactions. In northern temperate freshwaters, winter implies low temperatures and reduced food availability, but also strong reduction in ambient light because of ice and snow cover. Here, we study how brown trout [Salmo trutta (L.)] respond to variations in ice-cover duration and competition with Arctic charr [Salvelinus alpinus (L.)], by linking laboratory-derived physiological performance and field data on variation in abundance among and within natural brown trout populations. 2. Both Arctic charr and brown trout reduced resting metabolic rate under simulated ice-cover (darkness) in the laboratory, compared to no ice (6-h daylight). However, in contrast to brown trout, Arctic charr was able to obtain positive growth rate in darkness and had higher food intake in tank experiments than brown trout. Arctic charr also performed better (lower energy loss) under simulated ice-cover in a semi-natural environment with natural food supply. 3. When comparing brown trout biomass across 190 Norwegian lakes along a climate gradient, longer ice-covered duration decreased the biomass only in lakes where brown trout lived together with Arctic charr. We were not able to detect any effect of ice-cover on brown trout biomass in lakes where brown trout was the only fish species. 4. Similarly, a 25-year time series from a lake with both brown trout and Arctic charr showed that brown trout population growth rate depended on the interaction between ice breakup date and Arctic charr abundance. High charr abundance was correlated with low trout population growth rate only in combination with long winters. 5. In conclusion, the two species differed in performance under ice, and the observed outcome of competition in natural populations was strongly dependent on duration of the ice-covered period. Our study shows that changes in ice phenology may alter species interactions in Northern aquatic systems. Increased knowledge of how adaptations to winter conditions differ among coexisting species is therefore vital for our understanding of ecological impacts of climate change.