Human Activities Caused Hypoxia Expansion in a Large Eutrophic Estuary: Non-negligible Role of Riverine Suspended Sediments
Bibliographic record
Abstract
Abstract. Increase in riverine nutrient loads was generally 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). By utilizing the physical-biogeochemical model, we reproduced the observed dissolved oxygen (DO) conditions off the PRE in the historical period (the 1990s with high-suspended sediments-DO and low-nutrient inputs) and the present period (the 2010s with low-suspended sediments-DO and high-nutrient inputs). Due to the decadal changes in riverine inputs, the PRE has witnessed more extensive and persistent low-oxygen events during summer in the 2020s, with larger spatial extents of ~2926 km2 for low oxygen (DO < 4 mg/L, increased by ~148 % relative to the 1990s) and 617 km2 for hypoxia (DO < 3 mg/L, by 192 %) and longer duration (by ~15–35 days), evolving into three distinct hypoxic centers controlled by different factors. Model experiments suggested that the decreased riverine DO content (46 %) has led to a low-oxygen expansion in the upper regions, accounting for 44 % to the total increment. Meanwhile, the increased nutrient levels (100 % in nitrogen and 225 % in phosphorus) and the declined suspended sediment concentration (60 %) have jointly promoted the primary production and bottom oxygen consumptions (dominated by sediment oxygen uptake), thus resulting in a substantial enlargement of low-oxygen area (104 %) and hypoxic area (192 %) in the lower reaches. Our results revealed a more critical role of the riverine suspended sediment decline in the exacerbation of eutrophication and deoxygenation off the PRE via improving light conditions to support higher local productivity, which could further amplify the effect combined with the growth in nutrients and confound the effectiveness of hypoxia mitigation under nutrient controls. Overall, in the context of global changes in riverine suspended sediments, it is imperative to reassess the contribution of riverine inputs to the coastal deoxygenation worldwide over the past decades, given that the impact of suspended sediments has been constantly overlooked in relevant investigations.
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 | 0.000 | 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 | 0.001 | 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".