Patterns of food quality and availability, when combined with energetic demands in seasonal environments, shape resource acquisition and allocation by animals and hold consequences for life-history strategies. In long-lived species with extensive maternal care, regulation of somatic reserves of energy and protein can occur in a risk-sensitive manner, wherein resources are preferentially allocated to support survival at the cost of investment in reproduction. We investigated how Rocky Mountain bighorn sheep (Ovis canadensis), an alpine mammal in a highly seasonal environment, allocate somatic reserves across seasons. In accordance with the hypothesis of risk-sensitive resource allocation, we expected accretion and catabolism of somatic reserves to be regulated relative to pre-season nutritional state, reproductive state, and vary among populations in accordance with local environmental conditions. To test that hypothesis, we monitored seasonal changes of percent ingesta-free body fat (IFBFat) and ingesta-free, fat-free body mass (IFFFBMass) in three populations of bighorn sheep in northwest Wyoming between 2015 and 2019 through repeated captures of female sheep in December and March of each year in a longitudinal study design. Regulation of somatic reserves was risk sensitive and varied relative to the amount of somatic reserves an animal had at the beginning of the season. Regulation of fat reserves was sensitive to reproductive state and differed by population, particularly over the summer. In one population with low rates of recruitment of young, sheep that recruited offspring lost fat over the summer in contrast to the other two populations where sheep that recruited gained fat. And yet, all populations exhibited similar changes in fat catabolism and risk sensitivity over winter. Magnitude of body fat and mass change across seasons may be indicative of sufficiency of seasonal ranges to meet energetic demands of survival and reproduction. Risk-sensitive allocation of resources was pervasive suggesting nutritional underpinnings are foundational to behavior, vital rates, and ultimately, population dynamics. For species living in alpine environments, risk-sensitive resource allocation may be essential to balance investment in reproduction with ensuring survival.

Beginning in December 2015, we captured adult females using helicopter net-gunning (Whiskey Mountain and Jackson populations; Krausman et al. 1985; Wagler et al. 2022) or ground-darting and chemical immobilization (Upper Shoshone population) and fitted each with an individually identifiable GPS collar (various models, Advanced Telemetry Systems, Isanti, MN, USA; Vectronics Aerospace, Berlin, Germany). Every animal collared was assigned a unique identifier (animal ID). Each subsequent March and December 2015–2019, we recaptured collared females whenever possible and captured uncollared females to maintain sufficient sample sizes (25 in Whiskey Mountain, 20 in Jackson, 15 in Upper Shoshone populations). We programmed GPS collars to record locations 2–24 times per day.

Upon first capture, we estimated age using a combination of horn annuli and tooth eruption and wear (Geist 1966; Rubin et al. 2000; Dekelaita et al. 2020). Each March we determined pregnancy status using ultrasonography (Stephenson et al. 1995). Each December we determined lactation status (a proxy for recruitment) by palpating the udder and attempting to express milk (Monteith et al. 2014). At each capture event, we measured nutritional condition using ultrasonography to measure subcutaneous rump fat (5‐MHz transducer; Ibex Pro, E.I. Medical Imaging, Loveland, CO, USA) according to methods described in Stephenson et al. (2020). If there was no measurable subcutaneous rump fat, we used manual palpation to assign a body condition score (BCS; Stephenson et al. 2020).We used the ultrasonography measurements and BCS to estimate percent ingesta-free body fat (% IFBFat) using equations developed and validated for bighorn sheep (Stephenson et al. 2020). To measure body mass, we weighed each sheep using a platform or hanging scale to the nearest 0.1 kg. We subtracted 2 kg from pregnant sheep in March to account for fetal mass and products of conceptus (Cook et al. 2010, Monteith et al. 2013). We calculated ingesta-free body mass using the following equation (Stephenson et al. 2020):

Ingesta-free body mass (kg) = 0.668(body mass; kg) + 6.418 (Eq. 1)

We calculated ingesta-free, fat free body mass (IFFFBMass, kg) using the following equation for animals with no measurable subcutaneous rump fat (MAXFAT; Stephenson et al. 2020):

IFFFBMass (kg) = IFBMass - 2.11(BCS) - 1.46 (Eq. 2A)

We calculated IFFFBMass using the following equation for animals with measurable subcutaneous rump fat (MAXFAT; Stephenson et al. 2020):

IFFFBMass (kg) = IFBMass - 6.85(MAXFAT) + 3.28 (Eq. 2B)

Spatial data and statistical analysis

We completed all data analyses in Program R (R Core Team 2020). We defined summer as June through August because it is the primary growing season in the alpine zone and thus the primary period for nutrient acquisition and potential accumulation of somatic reserves. We defined winter as December through March because most sheep were on their winter ranges and most snowpack accumulated during these months. We randomly selected  two locations per day for each sheep to create a balanced sample size across individuals. We excluded sheep with fewer than 30 GPS locations during a season (Street et al. 2021). We calculated seasonal home ranges as 75% kernel density utilization distributions using a 250 m resolution for each sheep using the adehabitatHR package (Calenge 2006). We chose a 75% utilization distribution to include the core home range and the primary area that sheep are using while excluding areas that sheep likely are not using (Downs & Horner 2008, Clapp & Beck 2015) that may bias spatial variable estimates (e.g., heavily forested areas on the edge of escape terrain that may inflate biomass estimates). We extracted spatially explicit data for mean snow depth (m) at a 1-km resolution (National Operational Hydrologic Remote Sensing Center 2021) of each winter home range and herbaceous biomass estimates (Rangeland Analysis Platform; kg/ha; annual temporal resolution) for summer and winter home ranges at a 30-m resolution as an index of forage availability on seasonal ranges (Robinson et al. 2019, Jones et al. 2020). We extracted the spatial data for December through March for winter home ranges and June through August for summer home ranges. We used these spatial data on snow depth and biomass to assess the effects of weather and forage conditions on seasonal changes in fat and lean body mass of sheep. Annual estimates of biomass on winter range was used as an estimate of relative forage availability that was available following the primary growing season.