Relocating croplands could drastically reduce the environmental impacts of global food production
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Agricultural production has replaced natural ecosystems across the planet, becoming a major driver of carbon emissions, biodiversity loss, and freshwater consumption. Here we combined global crop yield and environmental data in a ~1-million-dimensional mathematical optimisation framework to determine how optimising the spatial distribution of global croplands could reduce environmental impacts whilst maintaining current crop production levels. We estimate that relocating current croplands to optimal locations, whilst allowing ecosystems in then-abandoned areas to regenerate, could simultaneously decrease the current carbon, biodiversity, and irrigation water footprint of global crop production by 71%, 87%, and 100%, respectively, assuming high-input farming on newly established sites. The optimal global distribution of crops is largely similar for current and end-of-century climatic conditions across emission scenarios. Substantial impact reductions could already be achieved by relocating only a small proportion of worldwide crop production, relocating croplands only within national borders, and assuming less intensive farming systems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it