Personality differences in the selection of dynamic refugia have demographic consequences for a winter-adapted bird

Habitat and climatic associations of climate-sensitive species along a southern range boundary

Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate-sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen-science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate-sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus] and moose [Alces alces]). We used total basal area of at-risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce-fir and lowland riparian forest types, hares with lowland conifer and aspen-birch, grouse with lowland riparian hardwoods, and moose with upland spruce-fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce-fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate-sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy-relevant scales.

Review of range-wide vital rates quantifies eastern wild Turkey population trajectory

Recent declines in eastern wild turkeys (Meleagris gallopavo silvestris) have prompted increased interest in management and research of this important game species. However, the mechanisms underlying these declines are unclear, leaving uncertainty in how best to manage this species. Foundational to effective management of wildlife species is understanding the biotic and abiotic factors that influence demographic parameters and the contribution of vital rates to population growth. Our objectives for this study were to (1) conduct a literature review to collect all published vital rates for eastern wild turkey over the last 50 years, (2) perform a scoping review of the biotic and abiotic factors that have been studied relative to wild turkey vital rates and highlight areas that require additional research, and (3) use the published vital rates to populate a life-stage simulation analysis (LSA) and identify the vital rates that make the greatest contribution to population growth. Based on published vital rates for eastern wild turkey, we estimated a mean asymptotic population growth rate (λ) of 0.91 (95% CI = 0.71, 1.12). Vital rates associated with after-second-year (ASY) females were most influential in determining population growth. Survival of ASY females had the greatest elasticity (0.53), while reproduction of ASY females had lower elasticity (0.21), but high process variance, causing it to explain a greater proportion of variance in λ. Our scoping review found that most research has focused on the effects of habitat characteristics at nest sites and the direct effects of harvest on adult survival, while research on topics such as disease, weather, predators, or anthropogenic activity on vital rates has received less attention. We recommend that future research take a more mechanistic approach to understanding variation in wild turkey vital rates as this will assist managers in determining the most appropriate management approach.

Dynamic winter weather moderates movement and resource selection of wild turkeys at high-latitude range limits

For wide-ranging species in temperate environments, populations at high-latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high-latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state-specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries.

Anomalous snow events increase mortality for a winter-adapted species

Winter is a costly time for animals, requiring individuals to adapt to increased energetic costs, and reduced resources. Porcupines (Erethizon dorsatum Linnaeus, 1758) confront winter by storing and catabolizing somatic stores. Increasing temperatures and attenuated snow conditions due to climate change increase porcupine survival, but impacts of greater weather variability has not been explored. In April of 2018, an anomalously heavy and late snowstorm occurred at our long-term study site in central Wisconsin followed by multiple mortalities among adult porcupines. We assessed cause of mortality and determined nutritional condition by extracting bone marrow, and quantifying lipid content. Porcupines that died following the snow event had lower fat stores than the fall 2019 group, and likely died of starvation. We estimated survival of female porcupines during the winters 2012 & 2015-2018 to assess the effects of snow conditions and nutritional condition on survival. Survival declined with increased snow depth but increased with improved nutritional condition. The mass starvation event we observed in 2018 appeared to have resulted from deep snow increasing locomotive costs and reducing nutritional condition. As climate change increases the frequency of extreme weather events, including extreme snowfalls, we predict that the frequency of such clustered mortalities will increase.