Soil erosion and sediment dynamics in the Anthropocene: a review of human impacts during a period of rapid global environmental change
Bibliographic record
Abstract
Abstract Purpose Humanity has been modifying the planet in a measurable way for thousands of years. Recently, this influence has been such that some feel we are in a new geological epoch, the Anthropocene. This review will describe how soil erosion and sediment dynamics have (i) been used to assess the impact of humans on the planet and (ii) affected the global climate and influenced water security. Emphasis is placed on changes since the middle of the twentieth century, as this coincides with what many suggest is the start of the Anthropocene Epoch. Results and discussion The use of sediment archives has been instrumental in our understanding of how environmental systems have developed over time, both naturally and in response to anthropogenic activities. Additional information has come from measurement and monitoring programs, and tracing and fingerprinting studies. In turn, models have been developed that enable forecasting. Some of the main global impacts of enhanced soil erosion and changes in sediment dynamics and sediment composition include: changes in radiative energy balances and impacts on the cryosphere; the global carbon cycle; and greenhouse gas emissions. Impacts on water security include: effects on freshwater biota, including wild salmon populations; fluxes of contaminants, including microplastics; and reservoir and river channel sedimentation, including flooding. Sediment archives and monitoring programs have also been used to document the effect of mitigation measures and environmental policies. Conclusion Sediment archives enable us to assemble information over a variety of timescales (i.e., 10 0 to 10 5 years and longer) and a range of spatial scales (from sub-watershed to continental), in addition to environments ranging from arid to tropical to polar. Often the temporal resolution is better than other paleoenvironmental reconstruction approaches. As such, sedimentary records, when combined with measurement and monitoring approaches and other sources of information, have enabled us to determine changes in atmospheric, terrestrial, and aquatic systems, especially over the last 100 years. While soil erosion and sediment dynamics have provided a wealth of information and greatly enhanced our understanding of the role of humanity in modifying the planet, suggestions are given for further research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".