Skip to content
DraconiticResearch
Search Sources API
186,086 studies31 sourcesUpdated 33 min ago
PreprintCC BYbioRxiv

Spatio-temporal modeling of an insect vector distribution

  1. 1INRAE

Abstract

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 spatio-temporal 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.

Related

  1. STEM-LM: Spatio-Temporal Ecological Modeling via Masked Language Model for Multi-Species Distribution
    J. K. Li, W. Lim, R. Rheem +4
    bioRxivPreprintCC BY-NCFull textEcologybioRxiv
  2. Spatio-temporal patterns of diversity and distribution of common Megachile bees across agroclimatic gradients in Eastern India
    Kaushik Pramanik, Ipsita Ghosh, Debashis Mandal +2
    Scientific ReportsPeer-reviewedCC BY 4.0Full textEcologyCrossref
  3. Graph attention spatio-temporal graph neural network based human–light interaction modeling for indoor lighting environments
    Ting Gao, Lingling Sun
    PLOS OnePeer-reviewedCC BY 4.0Full textNeurosciencePLOS
  4. Short-term metro passenger flow forecasting via decoupled spatio-temporal modeling with a diffusion-convergence graph and Swin-Enhanced LSTM
    Yixin Feng, Shangbing Gao, Hao Wang +5
    PLOS OnePeer-reviewedCC BY 4.0Full textCell biologyNeurosciencePLOS
  5. Diffusion-enhanced spatio-temporal models for estimating spatial expansion
    H.-H. Wu, J. T. Thorson, Y. Chang
    bioRxivPreprintAll rights reservedFull textEcologybioRxiv
BibTeX
@misc{grosdidier2026spatiotemporal,
  title = {{Spatio-temporal modeling of an insect vector distribution}},
  author = {M. Grosdidier and E. Walker},
  howpublished = {bioRxiv},
  year = {2026},
  month = may,
  doi = {10.64898/2026.05.22.727173},
  url = {https://www.biorxiv.org/content/10.64898/2026.05.22.727173v2},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Spatio-temporal modeling of an insect vector distribution
AU  - M. Grosdidier
AU  - E. Walker
PY  - 2026
DA  - 2026/05/22
PB  - bioRxiv
DO  - 10.64898/2026.05.22.727173
UR  - https://www.biorxiv.org/content/10.64898/2026.05.22.727173v2
AB  - 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 spatio-temporal 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.
ER  -