Bioeconomic responses to provide pollination service in intensive agricultural ecosystems ; Leviers bioéconomiques pour assurer la fourniture du service écosystémique de pollinisation dans les territoires agricoles intensifs
While one of the major objectives put forward by the IPBES (2019) is to feed the planet while improving the overall health of ecosystems, intensive agriculture remains one of the main causes of biodiversity decline, of which the decline of pollinators on a global scale is emblematic. Pollinated crops represent nearly 80% of the species grown in Europe and play a crucial ecological and economic role in agro-ecosystems (Klein et al., 2007). Therefore, the decline of pollinators questions current agricultural practices. The objective of this thesis is to identify and evaluate effective and sustainable solutions to ensure the provision of the pollination service in intensive agroecosystems. To date, research conducted to tackle pollinator decline has focused on several technical responses, while ignoring the preferences of farmers or beekeepers. First, we identify the most effective technical levers to increase the magnitude of the pollination service, and then analyze agents' preferences about them. In a second step, we evaluate some bioeconomic responses (i.e. combining the adoption of a practice with a socio-economic motivation) from an economic but also an ecological point of view. To do so, we use concepts and theories from several academic fields, mainly from economics and psychology, as well as bioeconomic modeling and econometric approaches. We focus on the case study of the "Plaine & Val de Sèvre" area (Deux-Sèvres, France), a typical West European intensive agroecosystem, which we use for model calibration. For the identification of preferences, we use two datasets from farmer surveys: one conducted in the Deux-Sèvres area, and one conducted online at the national level. Our results show that the pro-pollinator practices have a high acceptability among farmers, but that they are not widely adopted. The most effective levers are often the least adopted. We show that adoption is influenced by costs, but also by risk preferences and other behavioral factors. We first simulate, using a bioeconomic model, a ...