National phosphorus planning for food and environmental security
Bibliographic record
Abstract
The dependence of countries on phosphorus fertilisers derived from phosphate rock to maintain crop yields and ensure food security is well established. Yet, exposure of national food systems to constrained reserves of phosphate rock and supply chain complexities still pose risks to farmers’ access to this critical nutrient in many countries. Whilst phosphorus scarcity can threaten food security, suboptimal fertiliser use and poor wastewater treatment can lead to pollution of freshwaters and coasts, causing eutrophication. This impacts biodiversity, drinking water and aquatic food production. In some countries, national plans targeting the recycling of phosphorus losses back into food production are being considered, offering environmental and socio-economic benefits. Here, we review the literature on assessing risks to food security and water quality associated with national reliance on phosphate rock as the primary source of phosphorus for fertilisers. The scientific community has developed data and tools to enable countries to assess exposure in food systems from phosphorus supply and management and in the environment from pollution. However, current assessment approaches often overlook economic vulnerability, a key gap that hinders our understanding of the urgency and severity of impacts from inaction. Exposure assessments could be used to develop National Sustainable Phosphorus Plans embedding priority actions and financial instruments across existing policy frameworks. Actions include identifying local to national sources and sites for phosphorus recycling, identifying catchments and ecosystems where the benefits of reducing phosphorus pollution are greatest, and establishing an infrastructure development plan to enable greater recycling and reduced pollution. We discuss four integrated actions that will enable countries to take the first steps towards a circular phosphorus economy in the context of a challenging global situation. • Phosphorus fertilizer dependence poses risks to food security and freshwater quality. • Suboptimal use of fertilizers and poor wastewater treatment cause eutrophication. • National plans for phosphorus recycling offer environmental and socio-economic benefits. • Current assessments lack economic vulnerability, hindering urgency and impact understanding. • Integrated actions for circular phosphorus economy can mitigate global phosphorus challenges.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".