1. In many social species, reproductive success varies between individuals within a population, resulting in socially structured populations. Social network analyses of familial relationships may provide insights on how fitness influences population-level demographic patterns. These methods have however rarely been applied to genetically-derived pedigree data from wild populations. 2. Here we use social networks to reconstruct parent-offspring relationships and create a familial network from polygamous boreal woodland caribou (Rangifer tarandus caribou) in Saskatchewan, Canada, to inform recovery efforts. We collected samples from 933 individuals at 15 variable microsatellite loci along with caribou-specific primers for sex identification. Using social network metrics, we assess the contribution of individual caribou to the population with several centrality metrics and then determine which metrics are best suited to inform on the population demographic structure. We look at the centrality of individuals from eighteen different local areas, along with the entire population. 3. We found substantial differences in centrality of individuals in different local areas, that in turn contributed differently to the full network, highlighting the importance of analyzing social networks at different scales. The full network revealed that boreal caribou in Saskatchewan form a complex, interconnected social network with strong familial ties, as the removal of edges with high betweenness did not result in distinct subgroups. Alpha, betweenness, and eccentricity centrality were the most informative metrics to characterize the population demographic structure and for spatially identifying areas of highest fitness levels and social cohesion across the range. 4. Synthesis and applications: Our results demonstrate the value of different network metrics in assessing genetically-derived familial networks. The spatial application of the familial networks identified areas of higher fitness levels and social cohesion across the range in support of population monitoring and recovery efforts.