Biogeochemical cycles and biodiversity as key drivers of ecosystem services provided by soils
Bibliographic record
Abstract
Abstract. Soils play a pivotal role in major global biogeochemical cycles (carbon, nutrient, and water), while hosting the largest diversity of organisms on land. Because of this, soils deliver fundamental ecosystem services, and management to change a soil process in support of one ecosystem service can either provide co-benefits to other services or result in trade-offs. In this critical review, we report the state-of-the-art understanding concerning the biogeochemical cycles and biodiversity in soil, and relate these to the provisioning, regulating, supporting, and cultural ecosystem services which they underpin. We then outline key knowledge gaps and research challenges, before providing recommendations for management activities to support the continued delivery of ecosystem services from soils. We conclude that, although soils are complex, there are still knowledge gaps, and fundamental research is still needed to better understand the relationships between different facets of soils and the array of ecosystem services they underpin, enough is known to implement best practices now. There is a tendency among soil scientists to dwell on the complexity and knowledge gaps rather than to focus on what we do know and how this knowledge can be put to use to improve the delivery of ecosystem services. A significant challenge is to find effective ways to share knowledge with soil managers and policy makers so that best management can be implemented. A key element of this knowledge exchange must be to raise awareness of the ecosystems services underpinned by soils and thus the natural capital they provide. We know enough to start moving in the right direction while we conduct research to fill in our knowledge gaps. The lasting legacy of the International Year of Soils in 2015 should be for soil scientists to work together with policy makers and land managers to put soils at the centre of environmental policy making and land management decisions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| 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".