Lifetime, known‐age moose reproduction in a nutritionally stressed population

Tracking reproductive events: Hoof growth and steroid hormone concentrations in hair and hoof tissues in moose (Alces alces)

Measurements of reproductive and stress-related hormones in keratinous tissues (e.g. hair, claws, hooves, baleen) can provide a record of stress and reproductive response in wildlife. We evaluated a method to collect keratin tissue from hooves of immobilized moose (Alces alces) and validated enzyme immunoassays for measuring cortisol and progesterone in hooves and hair. We also measured the annual growth and wear rates of moose hooves. Progesterone (range: 1.0-43.7 pg/mg) and cortisol (range: 0.05-2.9 pg/mg) were measurable and showed variation among hoof samples and moose. Pregnant females had twice as high progesterone concentrations (18.00 ± 3.73 pg/mg) from hoof sample locations post breeding compared to non-pregnant moose (9.40 ± 0.25 pg/mg). Annual hoof growth differed between the front (5.58 ± 0.12 cm) and rear (4.73 ± 0.13 cm) hooves and varied by season with higher growth rates during summer which decreased into autumn and winter. Adult female hooves represented between 1.6 and 2.1 years of growth and included up to two reproductive cycles. We established a method to estimate hoof growth rate and applied this to postmortem samples and were able to detect previous pregnancies. Shoulder guard hairs grew between August and March including during late gestation; however, hair progesterone concentrations (range: 2-107.1 pg/mg) were not related to reproductive state. Hair cortisol concentrations in our study (range: 0.2-15.9 pg/mg) were within the range of values previously reported for cervids. Our study supports the use of hooves for longitudinal sampling and measuring reproductive and stress-related hormones, providing a new tool for tracking reproductive events and understanding what variables may contribute to population level changes in reproduction.

Efficacy of Killing Large Carnivores to Enhance Moose Harvests: New Insights from a Long-Term View

We analyzed harvest data to test hypotheses that nearly 4 decades of effort to reduce abundance of brown bears (Ursus arctos), black bears (U. americanus) and gray wolves (Canis lupis) in an 60,542 km2 area in south-central Alaska (Game Management Unit [GMU] 13) was positively correlated with moose (Alces alces) harvests in some time-lagged fashion. Predator-reduction efforts were progressively more aggressive over decades (both de facto and officially designated predator control) and did not have clear starting points which complicated our post hoc analyses. We documented no positive correlations (p > 0.05) between harvests of brown and black bears and subsequent moose harvests for any time lag. Moose harvest was negatively correlated with the previous years’ wolf harvest, but the relationship was weak (correlation = −0.33, p < 0.05). Consequently, we reject our hypotheses that harvest of predators was positively correlated with moose harvests. We also observed no differences in mean moose harvests during periods of officially designated wolf control (2005–2020) and a previous period (p > 0.50). We recommend that predator reductions designed to improve hunter harvests of moose be conducted within a research framework that will permit improved interpretations of results and the implementation of an adaptive-management approach to achieve management objectives.

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.

High-Arctic family planning: earlier spring onset advances age at first reproduction in barnacle geese

Quantifying how key life-history traits respond to climatic change is fundamental in understanding and predicting long-term population prospects. Age at first reproduction (AFR), which affects fitness and population dynamics, may be influenced by environmental stochasticity but has rarely been directly linked to climate change. Here, we use a case study from the highly seasonal and stochastic environment in High-Arctic Svalbard, with strong temporal trends in breeding conditions, to test whether rapid climate warming may induce changes in AFR in barnacle geese, Branta leucopsis. Using long-term mark–recapture and reproductive data (1991–2017), we developed a multi-event model to estimate individual AFR (i.e. when goslings are produced). The annual probability of reproducing for the first time was negatively affected by population density but only for 2 year olds, the earliest age of maturity. Furthermore, advanced spring onset (SO) positively influenced the probability of reproducing and even more strongly the probability of reproducing for the first time. Thus, because climate warming has advanced SO by two weeks, this likely led to an earlier AFR by more than doubling the probability of reproducing at 2 years of age. This may, in turn, impact important life-history trade-offs and long-term population trajectories.

Cohort antler size signals environmental stress in a moderate climate

Research in northern latitudes confirms that climate teleconnections exert important influences on ungulate fitness, but studies from regions with milder climates are lacking. We explored the influence of the Pacific Decadal Oscillation (PDO), Northern Atlantic Oscillation (NAO), and El Niño-Southern Oscillation (ENSO) on male, 2.5-year-old white-tailed deer (Odocoileus virginianus) antler and body mass in Mississippi, USA, a region with mild winters and warm, humid summers. Explanatory variables were seasonal averages of each climate index extending back to 3 years prior to account for possible maternal and lag effects. Seasonal climate indices from the period of gestation and the first year of life were correlated with deer morphometrics. Reduced antler mass was largely correlated (R² = 0.52) with PDO values indicating dry conditions during parturition and neonatal development and NAO values indicating warmer than normal winters during gestation and the first year of life. Body mass was less correlated (R² = 0.16) to climate indices, responding negatively to warmer winter weather during the first winter of life. Climate may promote variable fitness among cohorts through long-term effects on male competition for dominance and breeding access. Because broad-scale climate indices simplify complex weather systems, they may benefit management at larger scales. Although this study compared climate with morphological variables, it is likely that demographic characteristics can likewise be modeled using climate indices. As climate change in this region is projected to include greater variability in summer precipitation, we may see concomitantly greater variability in fitness among cohorts of white-tailed deer.