Information on the size, distribution and trend of wildlife populations are key parameters when assessing the status of wildlife species. Quantifying the impacts of natural and anthropogenic activities on these dynamics is also essential in the development of recovery and restoration efforts. New methods using genetic data and advanced computing are becoming more accessible and very effective for studying sensitive species. Genetic data, most often obtained non-invasively by collecting fecal or hair samples, is then used to determine the population genetic structure, the extent of inbreeding and genetic differentiation within and among populations. The data is also used to generate a range of population demographic parameters including population size and trends, survival and recruitment rates, spatially-explicit densities, fitness levels and dispersal rates. New metagenomics methods are also being used to determine a range of health parameters (diet, microbiome diversity, parasites and viruses). In this presentation, I will show examples from projects completed on boreal and central mountain caribou and discuss the value of these methods for producing critical baseline data and ecological inferences that are directly linked to our conservation efforts. I will then discuss the evolution of wildlife monitoring in Canada, the importance of long-term datasets and reflect on future opportunities.
Related Resources
Applying Remote Sensing for Large-landscape Problems: Inventorying and Tracking Habitat Recovery for a Broadly Distributed Species At Risk
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Novel Multilayer Network Analysis to Assess Variation in the Spatial Co-occurrences of Close Kin in Wild Caribou Populations
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Movement Ecology of Endangered Caribou During a COVID-19 Mediated Pause in Winter Recreation
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