Linking population performance to nutritional condition in an alpine ungulate

Abstract

Bighorn sheep (Ovis canadensis) can live in extremely harsh environments and subsist on submaintenance diets for much of the year. Under these conditions, energy stored as body fat serves as an essential reserve for supplementing dietary intake to meet metabolic demands of survival and reproduction. We developed equations to predict ingesta-free body fat in bighorn sheep using ultrasonography and condition scores in vivo and carcass measurements postmortem. We then used in vivo equations to investigate the relationships between body fat, pregnancy, overwinter survival, and population growth in free-ranging bighorn sheep in California and Nevada. Among 11 subpopulations that included alpine winter residents and migrants, mean ingesta-free body fat of lactating adult females during autumn ranged between 8.8% and 15.0%; mean body fat for nonlactating females ranged from 16.4% to 20.9%. In adult females, ingesta-free body fat > 7.7% during January (early in the second trimester) corresponded with a > 90% probability of pregnancy and ingesta-free body fat > 13.5% during autumn yielded a probability of overwinter survival > 90%. Mean ingesta-free body fat of lactating females in autumn was positively associated with finite rate of population increase (λ) over the subsequent year in bighorn sheep subpopulations that wintered in alpine landscapes. Bighorn sheep with ingesta-free body fat of 26% in autumn and living in alpine environments possess energy reserves sufficient to meet resting metabolism for 83 days on fat reserves alone. We demonstrated that nutritional condition can be a pervasive mechanism underlying demography in bighorn sheep and characterizes the nutritional value of their occupied ranges. Mountain sheep are capital survivors in addition to being capital breeders, and because they inhabit landscapes with extreme seasonal forage scarcity, they also can be fat reserve obligates. Quantifying nutritional condition is essential for understanding the quality of habitats, how it underpins demography, and the proximity of a population to a nutritional threshold.