L'impact des déterminants globaux sur l'agriculture et les usages des sols.
Bibliographic record
Abstract
In a context of future tensions on the land resource, the objective of this thesis is to study the impact of global drivers, which are globalisation and climate change, on agriculture and land-use. To conduct this study, a new global land-use model, called ''Nexus Land-Use", is developed, to allow for a consistent vision of the socio-biospheric system. Existing land-use models are firstly reviewed, with the objective of assessing their capacity to estimate indirect land-use changes (ILUC). Because they result from international exchanges, ILUC can be viewed as characteristic symptoms of the influence of global drivers. Their estimation is a challenge for modellers as they require an integrated vision of the agricultural system, incorporating at the global scale a representation of both the supply- and demand-side. In spite of significant progress in the modelling of the land supply and the bioenergy sector, existing models do not manage yet to provide a robust assessment of ILUC, due especially to divergences on the price-elasticity of agricultural yields and food demand. To meet the challenge of modelling global drivers, this thesis presents the Nexus Land-Use model. Based on a representation of agricultural intensification mechanisms, its basic characteristics are to combine economics and biophysics into a single modelling framework and to represent multi-scale effects by incorporating local heterogeneity into a global architecture. The specificity of the model is also to endogenously calculate the land rent, which makes it possible, with exogenous scenarios of chemical inputs, to model the land-fertiliser substitution and its effect on land-use. With this modelling framework, the influence of globalisation on agriculture is studied through the lens of the food diets. Using three representative food scenarios, we show the critical role of diet convergence as driver of tensions on land-use. Our results reveal that a global convergence towards US diet to 2050 is not feasible with ongoing trends of agricultural expansion. Interactions between food scenarios and other land-use policies -- support to biofuel production and reduction of deforestation -- are enlightened, and some options for mitigating tensions on land-use are tested. Two prospects for the model development are finally presented to analyse the influence of climate change on land-use. The first one is the coupling to Imaclim-R with the aim of incorporating consistent values of the land rent into the agricultural price and the biomass supply curves. The second prospect is to include in the Nexus Land-Use crop yields variations simulated by the vegetation model ORCHIDEE under a climate change scenario. On this latter point, first results show that climate change induces a partial relocation of agricultural production from Southern regions -- Africa and Latin America -- to Northern ones, mainly Canada and Former Soviet Union.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".