Yoann Bourhis

NameYoann Bourhis
Job titleEco-Systems Modeller
Email addressyoann.bourhis@rothamsted.ac.uk
DepartmentNet Zero and Resilient Farming
ORCIDhttps://orcid.org/0000-0002-9365-9597
OfficeHarpenden

Research outputs

Explainable neural networks for trait-based multispecies distribution modelling—A case study with butterflies and moths

Bourhis, Y., Bell, J. R., Shortall, C. R., Kunin, W. and Milne, A. E. 2023. Explainable neural networks for trait-based multispecies distribution modelling—A case study with butterflies and moths. Methods in ecology and evolution. 14 (6), pp. 1531-1542. https://doi.org/10.1111/2041-210X.14097

The value of volunteer surveillance for the early detection of biological invaders

Van Den Bosch, F., McRoberts, N., Bourhis, Y., Parnell, S. and Hassall, K. L. 2023. The value of volunteer surveillance for the early detection of biological invaders. Journal of Theoretical Biology. 560, p. 111385. https://doi.org/10.1016/j.jtbi.2022.111385

Yearly occurrence of 544 species of moths (UK 1990-2019), with trait values and putative environmental drivers.

Bourhis, Y., Bell, J. R., Shortall, C. R. and Milne, A. E. 2022. Yearly occurrence of 544 species of moths (UK 1990-2019), with trait values and putative environmental drivers. Rothamsted Research. https://doi.org/10.23637/rothamsted.988z5

Dynamic role of grasslands as sources of soil-dwelling insect pests: new insights from in silico experiments for pest management strategies

Poggi, S., Sergent, M., Mammeri, Y., Plantegenest, M., Le Cointe, R. and Bourhis, Y. 2021. Dynamic role of grasslands as sources of soil-dwelling insect pests: new insights from in silico experiments for pest management strategies. Ecological Modelling. 440 (15 Jan), p. 109378. https://doi.org/10.1016/j.ecolmodel.2020.109378

The potential for soybean to diversify the production of plant-based protein in the UK

Coleman, K., Whitmore, A. P., Hassall, K. L., Shield, I. F., Semenov, M. A., Dobermann, A., Bourhis, Y., Eskandary, A. and Milne, A. E. 2021. The potential for soybean to diversify the production of plant-based protein in the UK. Science of the Total Environment. 767, p. 144903. https://doi.org/10.1016/j.scitotenv.2020.144903

Artificial neural networks for monitoring network optimisation—a practical example using a national insect survey

Bourhis, Y., Bell, J. R., Van Den Bosch, F. and Milne, A. E. 2021. Artificial neural networks for monitoring network optimisation—a practical example using a national insect survey. Environmental Modelling and Software. 135, p. 104925. https://doi.org/10.1016/j.envsoft.2020.104925

UK aphid migration percentiles, covariates and model outputs from the Rothamsted Insect Survey's 12.2 m suction-trap network: 1965 to 2018

Bourhis, Y., Bell, J. R., Van Den Bosch, F. and Milne, A. E. 2020. UK aphid migration percentiles, covariates and model outputs from the Rothamsted Insect Survey's 12.2 m suction-trap network: 1965 to 2018. Rothamsted Research. https://doi.org/10.23637/rothamsted.979yv

Translating surveillance data into incidence estimates

Bourhis, Y., Gotwald, T. R. and Van Den Bosch, F. 2019. Translating surveillance data into incidence estimates. Philosophical Transactions of the Royal Society B-Biological Sciences. 374 (1776). https://doi.org/10.1098/rstb.2018.0262

Sampling for disease absence-deriving informed monitoring from epidemic traits

Bourhis, Y., Gottwald, T.R., Lopez-Ruiz, F.J., Patarapuwadol, S. and Van Den Bosch, F. 2019. Sampling for disease absence-deriving informed monitoring from epidemic traits. Journal of Theoretical Biology. 461, pp. 8-16. https://doi.org/10.1016/j.jtbi.2018.10.038

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