Nitrogen (N) is a limiting nutrient for many herbivores, especially when plant availability and N content are low during the period of maternal investment, which is common for arctic ungulates. We used natural abundance of N isotopes to quantify allocation of maternal nitrogen to neonatal calves and milk in wild migratory caribou (Rangifer tarandus). We contrasted female-calf pairs from two herds in northern Quebec/Labrador, Canada: Rivière-George herd (RG; low population size with heavy calves) and the Rivière-aux-Feuilles herd (RAF; high population size and small calves). We assessed whether females of both herds relied on body protein or dietary N to produce the neonatal calf and milk at calving and weaning. Female caribou of both herds relied mostly on body N for fetal development. RAF females allocated less body N to calves than did RG females (92% vs. 95% of calf N), which was consistent with the production of calves that were 8% smaller in RAF than in RG. Allocation of body N to milk was also high for both herds, similar at calving for RAF and RG females (88% vs. 91% of milk N, respectively), but lower in RAF than RG females (95% vs. 99% of milk N) at weaning, which was consistent with a small but significantly greater reliance on dietary N supplies to support milk production at weaning. Female caribou used body protein stores to ensure a constant supply of N for fetal growth and milk production that minimized the effects of trophic mismatches on reproduction. The combination of migration and capital investment may therefore allow females to produce calves and attenuate the effects of both temporal and spatial mismatches between vegetation green-up and calf growth, which ultimately would reduce trophic feedbacks on population growth. Our data suggest that small changes in maternal allocation of proteins over the long period of gestation produce significant changes in calf mass as females respond to changes in resources that accompany changes in the size and distribution of the population.
Genetic diversity is a key parameter to delineate management units, but many organisms also display ecological characteristics that may reflect potential local adaptations. Here, we used ecological and genetic information to delineate management units for a complex system involving several ecotypes of caribou (Rangifer tarandus) from Québec and Labrador, eastern Canada. We genotyped 560 caribou at 16 microsatellite loci and used three Bayesian clustering methods to spatially delineate and characterize genetic structure across the landscape. The different approaches employed did not converge on the same solution, and differed in the number of inferred genetic clusters that best fit the dataset but also in the spatial distribution of genetic variation. We reconciled variability among the methods using a synthetic approach that considers the sum of the partitions obtained by each of them and retrieved six genetically distinct groups that differ in their spatial extent across the range of caribou in the study area. These genetic groups are not consistent with the presently defined ecological designations for this species. Combining both genetic and ecological criteria, we distinguished eight independent management units. Overall, the management units we propose should be the focus of conservation and management actions aimed to maximize genetic and ecological diversity and ensure the persistence of caribou populations inhabiting increasingly disturbed landscapes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.