IPSIM-Cirsium, a Qualitative Expert-Based Model to Predict Infestations of Cirsium arvense

Abstract

Throughout Europe, Cirsium arvense is the most problematic perennial weed in arable crops, whether managed under organic or conventional agriculture. Non-chemical control methods are limited with partial efficacy. Knowledge is missing on their effect across a wide gradient of cropping systems and pedoclimates. To achieve effective Cirsium arvense management ensuring crop productivity while limiting the reliance of cropping systems on herbicide, expert-based models are needed to gather knowledge on the effect of individual levers and their interactions in order to (i) design and assess finely tuned combinations of farming practices in different pedoclimates and (ii) support decisions for Cirsium arvense control. Based on expert-knowledge and literature, we developed IPSIM-Cirsium, a hierarchical qualitative model which evaluates the infestation of Cirsium arvense as a function of farming practices, climate conditions, soil descriptors and their interactions. IPSIM-Cirsium is a multi-attribute model considering all possibilities of interactions between factors, it estimates the infestation rate of the field graded according to a four-level scale. The model outputs were confronted to independent field observations collected across 6 fields, over a 16-year period in 3 sites. IPSIM-Cirsium showed a satisfactory predictive quality (accuracy of 78.2%). IPSIM-Cirsium can be used as a tool for crop advisors and researchers to assist the design of systems less reliant on herbicides, for farmers and advisers to assess ex-ante prototypes of cropping systems, and for teachers as an educational tool to share agroecological weed management knowledge.