A1644
Title: Bayesian modeling of long-term blue jay spring counts in Illinois: A county-level spatiotemporal analysis
Authors: Weijia Jia - University of Illinois Urbana-Champaign (United States) [presenting]
Weidai He - University of Illinois Urbana-Champaign (United States)
Abstract: Long-term (19752024) Spring Bird Count (SBC) data from Illinois were analyzed to assess population trends of Blue Jays (Cyanocitta cristata). The SBC is a yearly, volunteer-based census conducted on the Saturday between May 4 and May 10 across all 102 Illinois counties. To account for variation in survey effort across parties and years, a Bayesian hierarchical areal modeling framework was developed incorporating an effort-adjustment term of the form $\exp(B*(effort^p-1)/p)$ within a Markov Chain Monte Carlo (MCMC) setting. Counts were modeled across counties and years to estimate temporal trends while explicitly accounting for spatial dependence and heterogeneity in observation processes. The model incorporates relevant environmental and observational predictors to better explain variation in counts and improve inference on population dynamics. This approach provides robust estimation of Blue Jay population trends from volunteer-collected, county-level Count data and enables investigation of potential drivers underlying long-term changes.
