Population viability analysis using Bayesian networks

Traditional population viability analysis (PVA) does not address the degree of measurement error or spatial and temporal variability of vital rate parameters, potentially leading to inappropriate conservation decision-making. We provide a methodology of applying Bayesian network (BN) modeling to PVA addressing these considerations, particularly for species with complex stage-class structures. We provide examples of three species from eastern Australia - hip pocket frog (Assa darilingtoni), squirrel glider (Petaurus norfolcensis) and giant burrowing frog (Heleioporus australiacus), comparing traditional matrix-based PVA with BN model analyses of mean stage abundance, quasi-extinction probability, and interval threshold extinction risk. Both approaches project similar population sizes, but BN PVA gave more clearly identifiable thresholds of population changes and extinction levels. The PVA BN uniquely represents complex stage-class structures and in a single network, including variation and uncertainty propagation of vital rates, to better inform conservation management decisions.

Automated summary

This study introduces a methodology of applying Bayesian network modeling to population viability analysis, which can better address the spatial and temporal variability of vital rate parameters, especially for species with complex stage-class structures. By comparing traditional matrix-based PVA with BN model analyses on three species from eastern Australia, it was found that BN PVA provides more clearly identifiable thresholds of population changes and extinction levels.