Spatio-temporal modeling of an insect vector distribution

The pinewood nematode is a dangerous organism for the health of Pine forests and has already demonstrated its impact in Portugal and Spain. This organism was recently detected (november 2025) in France. It can spread over long distances (e.g., through wood transport) or short distances via its insect vector flights (about fifteen km), Monochamus galloprovincialis. The spatiotemporal distribution of the population of this insect vector is poorly understood in France. In this study, we propose to estimate the Monochamus population using official but heterogeneous in space and time trapping data. This spatiotemporal modeling is based on two Bayesian approaches (an INLA-based generalized additive model, and a mecanistic-statistical approach) and integrates environmental covariates as well as laboratory-derived experiments data about the insect vector. The results provide estimates and predictions of the spatiotemporal distribution of Monochamus galloprovincialis in France. This distribution varies according to environmental conditions and biological characteristics of the insect; the population dynamics thus can thus be estimated at all points in space and time. They will significantly improve the pinewood nematode surveillance plan to better monitor free zones and buffer zones around the outbreak.