This page summarizes my latest research.
Statistical population reconstruction for harvested wildlife
I developed a Bayesian hierarchical model allowing the reconstruction of a wildlife population from age-at-harvest data. From an extensive simulation study, I showed that this model enables the integration of life histories as prior information to improve its estimation. I applied this model to a population of harvested (2012-2021) white-tailed deer and a mammalian carnivore, the fisher, in an ecological critical zone. The model provided biologically realistic abundance and demographic rate estimates for the two species. This approach is helpful in monitoring harvested populations and helping species conservation. This study can be read here.
Wildlife populations in managed ecosystems
I developed a Bayesian multi-species model that estimates taxon-level parameters related to dynamics, abundance, detection probability, and environmental stochasticity. From this model, I analyzed the variability of populations of a community of raptors composed of accipiters, buteos, and owls in a southern terrestrial ecosystem. I showed that migration pulses of the accipiter, buteo, and fledging owl’s dispersal drive variation of raptor’s abundances. I also demonstrated that large-scale climatic processes, such as the North Atlantic Oscillation (NAO), influenced the variation in abundances of raptors. When the NAO was in a positive phase, the abundance of raptors decreased, and inversely. The approach developed in this study aimed to facilitate the modeling of species-specific effects of environmental variation and guild-level dynamics that could be used for ecosystem-based conservation measures. This study can be read here.
Community dynamics and variable environment
I applied a multivariate stochastic community dynamics model to describe the fluctuations in the abundances of a freshwater community over 28 years (1990-2017) in a boreal lake during the ice-free period. I showed that the community dynamics was driven by environmental variability in spring. In contrast, community-level ecological heterogeneity was highest in the autumn. The community returned faster toward equilibrium when the ecological heterogeneity was the highest over the autumn. Moreover, the community responded to the long-term warming of water temperature by decreasing species diversity and increasing abundances. This study can be read here.