Another drought or more pesky humans? Anthropogenic impacts leave drought-like sedimentological signatures in offshore sediments
Bibliographic record
Abstract
Worldwide, rivers deliver sediments and nutrients into the marine system, and this discharge is naturally variable due to fluctuations in precipitation, climate, and the shifting morphology of river channels. The sedimentological fingerprint of these variations from cores has been used to reconstruct past trends and conditions. Today, many coastal rivers have been heavily altered by dam construction, flood control, harbors, irrigation canals, and other human activities; thus also changing the volume, location, and arrival intervals of sediment discharge into the shallow marine shelf. Therefore, differentiating between changes linked to natural versus anthropogenic causes is key to interpreting and understanding the long-term effects of human activity and better defining the Anthropocene in the sedimentological record. In this study, offshore sediment profiles from the shallow shelf northern Red Sea were used to investigate how their recent sedimentological signatures compare to those of the past few thousand years, during which larger climatic shifts influenced sedimentation. The results found that the sedimentological trends were more homogenous laterally prior to the most recent half century, after which channelization of the alluvial plain directed the majority of flashflood runoff to a single outlet. This led to an artificial ‘drought-like’ signature in areas recently cut-off from incoming sediments. Data from sediment cores collected from offshore the Mediterranean coast of Israel inside the Nile littoral cell, an area that may have been impacted by the immense decrease in sediment discharge from the Nile river following the building of the High Aswan Dam showed similar trends. The impact that anthropogenic manipulation has on river sedimentary discharge, and its sedimentary signature will be discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".