Long-term spatiotemporal variations and expansion of low-oxygen conditions in the Pearl River estuary: A study synthesizing observations during 1976–2017
Bibliographic record
Abstract
Abstract. The Pearl River estuary (PRE) frequently experiences low-oxygen conditions in summer, with large extents of low-oxygen events and a long-term deoxygenation trend being reported recently. In this study, we provide a synthesis of the spatiotemporal patterns and incidence of different low-oxygen levels in the PRE based on the in-situ observations collected from 1976 to 2017, and aim to elucidate the underlying mechanisms of low-oxygen conditions and their changes over the past 4 decades. The long-term observations show that the oxygen content in the PRE had significant temporal variability and spatial heterogeneity. Low-oxygen conditions occurred mostly in the bottom waters of 5–30 meters during summer and early autumn, with locations and severity varying substantially among years. Coastal waters from the southwest of Lantau Island to the northeast of Wanshan Islands were identified as the hotspot area prone to subsurface low-oxygen conditions due to the combined effects of comparatively deep topography, proper residence time and stability of the water column, and enhanced oxygen depletion related to high phytoplankton biomass. In addition, the low-oxygen waters, either directly imported from the upstream reaches or generated locally and further transported with the estuarine circulation, also had considerable impacts on the oxygen levels in the estuary. As for early autumn, marked low-oxygen conditions were present both in the surface and bottom waters. A large area affected by low oxygen (~ 4,450 km2) was found in September 2006, where the low-oxygen conditions were comparable to the most severe ones observed in summer and formed by distinct mechanisms. Our analysis also reveals an apparent expansion of the summertime low-oxygen conditions at the bottom of the PRE since the years around 2000, coincident with the major environment changes in the Pearl River region. Overall, the PRE seems to be undergoing a transition from a system characterized by episodic, small-scale hypoxic events to a system with seasonal, estuary-wide hypoxic conditions. Although exacerbated eutrophication associated with anthropogenic nutrient inputs was generally considered the primary cause for the deterioration of low-oxygen conditions in the PRE, the sharp decline in sediment load may play an important role as well via increasing water transparency and thereby supporting higher and broader phytoplankton biomass in the estuary.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".