This task aims at analyzing the effects of various determinants on land use as well as their consequences on production (crops, livestock, and forestry) and on the environment (in particular GHG emissions and carbon sequestration). The bio-technical indicators defined in Task 2 and produced for the various climate scenarios in Task 3 will be integrated in an economic framework in order to assess the potential impacts on food, feed, wood, energy and the environment. The modelling framework explicitly accounts for a) the scarcity of resources such as land, b) the economic behaviour of agents (farmers, forest owners) in allocating these resources, as well as c) the technical constraints faced by agents. We intend, here, to assess the potential implications of climate change on land uses, and discuss potential adaptation strategies both within and across agriculture and forest areas.
Task 4 addresses the following questions :
Without accounting for the socio-economic drivers, how can we make use of the climatically-induced variations in the various bio-technical indicators produced (Task 4.1.) to propose adaptation strategies for agro-ecosystems ?
How will changes in socio-economic drivers modify the anthropogenic land-uses ? How will climatic policies impact those land-uses (Task 4.3.)?
Can we try to assess the hierarchy of impacts related to economical and climatic drivers ? Can we identify areas where the impacts of climate change on land-uses over-rule those resulting from socio-economic changes ? Can we estimate the changes in the sharing of land between agriculture and forestry when climate and economy drivers change (Task 4.4) ?
The three previous questions will be viewed when outputs of the agro-systems are private goods (grains and marketed by-products) and public goods (greenhouse gas emissions and other pollutants). The question is now how sensitive are the outputs to the major drivers retained in the analysis. At last, two-way effects link land use and climate (briefly the ORCHIDEE model stresses the impact of land use on climate and bio-economic models stress the impact of climate and policies on land use). And following the majority of the research community, the climate is viewed as dependent of anthropogenic GHG emissions. The design of future climate policies should depend on GHG emissions evolution along time in average and variance. Can we contribute to estimate this evolution, focusing on the land use drivers analysed in this project?
The goal of the proposed approach is therefore to disentangle the impacts of these various drivers, to quantify their relative importance, and to assess the possible synergisms and trade-offs. We thus propose to simulate and analyse a nested set of combinations of these various drivers.