We compare two different elicitation methods for measuring risk attitudes on a sample of French farmers. We consider the lottery tasks initially proposed by Holt and Laury (Econ Rev 92:1644–1655, 2002) and by Eckel and Grossman (Evol Hum Behav 23:281–295, 2002; J Econ Behav Org 68:1–7, 2008). The main empirical result from this within-subject study is that risk preference measures are affected by the type of mechanism used. We first show that this risk preference instability can be related to non-expected utility preferences of farmers. Using a risk-taking psychometric questionnaire, we then demonstrate that risk preferences of farmers are context-dependent. This may be another explanation of the observed risk preference instability.

Climate change threatens the sustainability of agriculture and natural resources. Adaptive solutions must be designed locally with stakeholders. We developed the Approach for Building Adaptation Scenarios with Stakeholders (ABASS), which aims to identify adaptation policies and corresponding scenarios of natural resource management in the context of climate change. Its originality is the combination of different existing participatory methods, organized in three phases. In step 1, experts identify local environmental problems on a map and build the assumption tree of local climate change effects. In step 2, experts identify stakeholders. Step 3 leads to the construction of adaptation scenarios with stakeholders in two phases. First, in a participatory workshop gathering numerous stakeholders, the assumption tree is presented to help stakeholders identify potential policies that address the effects of climate change. Then, using the map produced in step 1, each group of stakeholders separately translates each potential policy into a detailed scenario. We applied ABASS to the context of groundwater overexploitation in South India. Two policies at the farm level emerged as consensual: (i) ponds to harvest runoff water and (ii) drip irrigation to conserve water; but their implementation highlights the differences of opinion among stakeholders.

Windstorms generate windfalls that may lead to price decreases. Studies often focus on stochastic growth and price, but consider that there is no link between these two risks. In our model, we assume that storms generate windfalls and that these windfalls have an impact on timber price through volume and quality. The objective of this paper is to analyse the impact of these two effects on harvesting behaviour. We consider that the dynamic of the timber stock follows a Markov decision process and that the harvesting decision is a control variable. We solve the optimal harvesting problem under storm risk with a risk-averse forest owner and when the storm has an impact on production and price. We study the impact of a change in the storm risk distribution, the percentage of quality loss and risk aversion on the optimal harvesting decision. We show that the greater the storm risk is, the greater the harvesting will be. In addition, we observe no noticeable effect of an increase in the percentage of quality loss on harvesting. Moreover, when the forest owner’s risk aversion increases, the harvesting is reduced. Finally, we discuss our results, in particular, in relation to climate change.