Abstract
Bioaggressors cause significant losses in crop production and the efficacy of control methods, primarily based on chemical compounds, comes with considerable environmental and health costs. Plant protection practices implemented locally overlook the mobility of bioaggressors, which can spread between fields, connecting different crop populations. As a consequence, the yield in a given field depends also on the management of connected fields. In this study, the efficiency of different fungicide deployment strategies across a national-scale agriculture landscape is assessed, balancing the conflicting objectives of maximizing crop production and reducing fungicide use. A climate-driven metapopulation model describing the dynamics of the peach (Prunus persica)-brown rot (caused by Monilinia spp.) pathosystem in continental France is used. Fungicide deployment strategies are based on indices or algorithms, considering network topology, epidemic risk, territory, and stochastic sampling, which prioritize sites to be treated first. Finally, the objective of maximizing crop revenue is investigated, assuming that untreated fruit can be marketed at higher prices. The optimal strategy depends on the treatment allocation threshold: if up 20 % of the area is treated, epidemic risk provides the most effective prioritization. If more than 40 % of the area can be treated, a combination of random sampling and risk-based prioritization proves optimal. When only considering monetary revenues, we find that the higher the consumer's willingness to pay for untreated fruit, the larger the proportion of untreated sites becomes. Fungicide use could be avoided if untreated fruit were sold at 2.9 times the price of treated fruit.