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International audience; Many phytopathogenic fungi are disseminated as spores via the atmosphere from short to long distances. The distance of dissemination determines the extent to which plant diseases can spread and novel genotypes of pathogens can invade new territories. Predictive tools including models that forecast the arrival of spores in areas where susceptible crops are grown can help to manage sustainable crop health. However, such models are difficult to establish for fungi with broad host ranges because sources of inoculum cannot be readily identified. Sclerotinia sclerotiorum, the pandemic agent of white mould disease, can attack > 400 plant species including economically important crops. Monitoring airborne inoculum of S. sclerotiorum in several French cropping areas has shown that viable ascospores are present in the air almost all the time, even when no susceptible crops are nearby. This raises the hypothesis of a distant origin of airborne inoculum. The objective of the present study was to determine the interconnectivity of reservoirs of S. sclerotiorum from distant regions based on networks of air mass movement. Viable airborne inoculum of S. sclerotiorum was collected in 4 distinct regions of France and 498 strains were genotyped with 16 specific microsatellite markers and compared among the regions. Air mass movements were inferred using the HYSPLIT model and archived meteorological data from the global data assimilation system (GDAS). The results show that up to 700 km could separate collection sites that shared the same haplotypes. There was low or no genetic differentiation between strains collected from the four sites. The rate of aerial connectivity between two sites varied according to the direction considered. The results also show that the aerial connectivity between sites is a better indicator of the probability of the incoming component of inoculum at a given site from another one than is geographic distance. We identified the links between specific sites in the trajectories of air masses and we quantified the frequencies at which the directional links occurred as a proof-of-concept for an operational method to assess the arrival of airborne inoculum in a given area from distant origins.

Barley yellow dwarf virus (BYDV) damage to winter cereals and population dynamics of the aphid Rhopalosiphum padi during fall were monitored in fields during 10 years at various locations in the northern half of France. Logistic regression was used to examine whether a simple risk probability algorithm based only on the autumnal population dynamics of R. padi can accurately predict yield losses caused by BYDV and, therefore, the need for insecticide treatment. Results showed that the area under the curve of the percentage of plants infested by R. padi during autumn was highly significantly related to BYDV yield losses. Then, a cost/benefit analysis was performed to estimate the optimal decision threshold resulting in the lowest annual average costs of BYDV damage and control. A “model use” strategy allowed a reduction in the annual average costs of BYDV disease and control of up to 36% when compared with a “prophylactic spraying” strategy. The optimal decision threshold was highly sensitive to variation in disease prevalence. This property was used to propose an easy way to adapt the model to any production situation through the determination of the most accurate decision threshold.

Fabre, F., Plantegenest, M., and Yuen, J. 2007. Financial benefit of using crop protection decision rules over systematic spraying strategies. Phytopathology 97:1484-1490. Decision rule models are considered to be one of the main cornerstones of the implementation of integrated pest management (IPM) programs. Even if the need for such programs to offer cost advantages over conventional strategies is a major incentive for IPM adoption, few studies focus on this financial dimension. In this article, a modeling approach of the response of a pathosystem to a disease control method and of the predictive performance of decision rules is used to explore how some basic factors act on the likelihood of adoption of decision rule models strategies (such as using an IPM system) over systematic strategies (such as systematic-spraying and never-spraying strategies). Even if the average cost of using the decision rule strategies is always lower than the average cost of systematic strategies in several different scenarios, the models developed here showed strong effects of different pathosystems and decision rules on financial benefits. The number of production situations where decision rules are of interest is highly correlated with their accuracy. However, because of the inescapable trade-offs between decision rule accuracy and limiting factors such as its user-friendly characteristics, the use of decision rules is unlikely to reduce costs to