Human activities caused hypoxia expansion in a large eutrophic estuary: non-negligible role of riverine suspended sediments
Bibliographic record
Abstract
An increase in riverine nutrient loads has generally been recognized as the primary cause of coastal deoxygenation, whereas the role of other riverine factors, especially suspended sediments, has received less attention. This study aims to discern the impacts of anthropogenic alterations in various riverine inputs on the subsurface deoxygenation over the past three decades in a large river-dominated estuary, the Pearl River estuary (PRE). Using a physical–biogeochemical model, we reproduced the observed dissolved oxygen (DO) conditions off the PRE in the historical period (the 1990s, with a high suspended sediment concentration (SSC), high DO, and low nutrients) and the present period (the 2010s, with low SSC, low DO, and high nutrients). In the 2010s, the PRE exhibited more extensive and persistent summer hypoxia, with the low-oxygen area (DO<4mgL-1) expanding by ∼148 % (to ∼2926 km 2 ) and the hypoxia area (DO<3mgL-1) increasing by 192 % (to ∼617 km 2 ). Low-oxygen durations extended to 15–35 d, and three distinct hypoxic centers formed under different controlling factors. Single-factor experiments suggested that the decreased riverine DO content (46 %) alone expanded low-oxygen areas in the upper estuarine regions by 44 %, the decreased SSC (by 60 %) alone caused a 47 % expansion in the lower reaches of the PRE, and the increased nutrients alone (100 % in dissolved inorganic nitrogen and 225 % in phosphate) drove a 31 % expansion. In comparison, the combined nutrient increases and the SSC declines synergistically enhanced primary production and bottom oxygen consumptions (dominated by sediment oxygen uptake), amplifying low-oxygen (104 %) and hypoxic (192 %) area growth in lower estuaries. Our results revealed that, by improving light availability for productivity, SSC declines play a larger role than nutrient increases in exacerbating deoxygenation off the PRE. This synergy complicates hypoxia mitigation efforts focused solely on nutrient controls. Given the widespread global declines in riverine suspended sediments, our findings underscore the importance of incorporating sediment-mediated processes, a relatively overlooked factor, in coastal deoxygenation studies.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".