Influence of cover crops at the four spheres: A review of ecosystem services, potential barriers, and future directions for North America
Bibliographic record
Abstract
Cover crops have been studied for over a century, but the recognition of a complex interaction of cover crop on the Earth's biosphere, lithosphere, hydrosphere, and atmosphere is relatively recent. Furthermore, previously published cover crop research has largely focused on evaluating cover crop impacts on subsequent crop yield. Understanding the cover crop-induced benefits on soil organic carbon (SOC) sequestration, nitrous oxide (N 2 O) emissions, wind and water erosion, weed control, and soil microbial communities has gained considerable attention in the last few decades, which is crucial to make progress towards developing sustainable agricultural production systems. New research is continuously published to gain a comprehensive understanding of the multiple ecosystem services provided by cover crops. Here, in this review, we aimed to (a) summarize current knowledge related to cover crop impacts on agroecosystem functioning and explore the potential mechanisms responsible for those effects, and (b) identify the key factors limiting the adoption of cover crops into agroecosystems and the conspicuous knowledge gaps in cover crop research. Overall, the review results suggest that cover crops increased subsequent crop yield, increased SOC storage, increased weed suppression, mitigated N 2 O emissions, reduced wind and water erosion, suppressed plant pathogens, and increased soil microbial activity and wildlife biodiversity. However, the magnitude of benefits observed with cover crops varied with cover crop type, location, and the duration of cover cropping. Notably, cover crop termination methods, designing crop rotations to fit cover crops, additional costs associated with cover crop integration, and uncertainty related to economic returns with cover crops are some of the major barriers limiting the adoption of cover crops into production systems, particularly in North America. In addition to long-term effects, future research on cover crop agronomy, breeding cover crop cultivars, and interactive effects of cover crops with other sustainable land management practices is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".