Ecosystem services on restored marginal farmland
Bibliographic record
Abstract
Industrialized agriculture often uses marginal‐land restoration to reduce environmental impacts, seeking to generate ecosystem services while maintaining food production on better soils. Here, we describe benefit trajectories for biodiversity, nutrient retention, and soil organic carbon (SOC) accumulation up to a decade after conversion of marginal farmlands to grasslands or wetlands. Even in small areas that were restored, biodiversity increased across most trophic levels, driven by colonization of non‐agronomic taxa. Nutrient retention by grassland buffers was substantive but seasonal, with losses common outside of the growing season. Although initial SOC gains were modest, a 20‐fold increase in recalcitrant root biomass to a depth of 60 cm suggests that SOC storage will accelerate. Overall, even if it were unable to unilaterally and immediately offset nutrient pollution or SOC loss, restoration created multiple benefits. Marginal‐land restoration can serve as a necessary and critical component to improved sustainable intensification, especially if partnered with on‐field crop management targeting nutrient retention and SOC accumulation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".