Guiding phosphorus stewardship for multiple ecosystem services
Bibliographic record
Abstract
Abstract The essential role of phosphorus (P) for agriculture and its impact on water quality has received decades of research attention. However, the benefits of sustainable P use and management for society due to its downstream impacts on multiple ecosystem services are rarely acknowledged. We propose a conceptual framework—the “phosphorus‐ecosystem services cascade” ()—to integrate the key ecosystem processes and functions that moderate the relationship between P released to the environment from human actions and ecosystem services at distinct spatial and temporal scales. Indirect pathways in the cascade via soil and aquatic processes link anthropogenic P to biodiversity and multiple services, including recreation, drinking water provision, and fisheries. As anthropogenic P cascades through catchments, it often shifts from a subsidy to a stressor of ecosystem services. Phosphorus stewardship can have emergent ecosystem service co‐benefits due to synergies with other societal or management goals (e.g., recycling of livestock manures and organic wastes could impact soil carbon storage). Applying the framework, we identify key research priorities to align P stewardship with the management of multiple ecosystem services, such as incorporating additional services into agri‐environmental P indices, assessing how widespread recycling of organic P sources could differentially impact agricultural yields and water quality, and accounting for shifting baselines in P stewardship due to climate change. Ultimately, P impacts depend on site‐specific agricultural and biogeophysical contexts, so greater precision in targeting stewardship strategies to specific locations would help to optimize for ecosystem services and to more effectively internalize the downstream costs of farm nutrient management.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".