Neural dynamic N-mixture model: a deep learning framework to infer demographic rates from count data

François Leroy 1, Marta A. Jarzyna. 2026. DOI: 10.32942/X23979

Abstract

Changes in population abundance arise from underlying demographic processes, namely survival and recruitment, and knowledge of these two vital rates is crucial for better understanding biodiversity changes. Although demographic data based on individual encounter histories are often sparse in space and time, the dynamic N-mixture model provides an alternative by inferring survival and recruitment from repeated count data while accounting for imperfect detection. Here, we build on recent advances in neural hierarchical modelling and develop a neural dynamic N-mixture model. Specifically, we implement and optimize the likelihood of this model, i...