Survey-based inference of continental African elephant decline.

ABSTRACT: Long-term quantification of temporal species trends is fundamental to the assignment of conservation status, which in turn is critical for planning and targeting management interventions. However, monitoring effort and methodologies can change over the assessment period, resulting in heterogeneous data that are difficult to interpret. Here, we develop a hierarchical, random effects Bayesian model to estimate site-level trends in density of African elephants from geographically disparate survey data. The approach treats the density trend per site as a random effect and estimates a parametric distribution of these trends for each partitioning of the data. Data were available from 475 sites, in 37 countries, between 1964 and 2016 (a total of 1,325 surveys). We implemented the model separately

SUBMITTER: Edwards CTT 

PROVIDER: S-EPMC11621759 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature