Response of Mangrove Development to Air Temperature Variation Over the Past 3000 Years in Qinzhou Bay, Tropical China
Bibliographic record
Abstract
Mangroves, a blue carbon ecosystem between land and ocean in the (sub)tropics, are sensitive to changes in climate and the sea level. It is imperative to reconstruct the historical dynamics of their development to predict the fate of mangrove ecosystems in the backdrop of rapid global changes. This study analyzes records of the sources of organic matter from sediment core Q43 of Qinzhou Bay in tropical China by using the endmember mixing model based on stable organic carbon isotopes and C/N ratio. Mangrove-derived organic matter (MOM) is regarded as a reliable indicator for reconstructing the historical development of mangroves. The variations in MOM in Qinzhou Bay over the past ∼3,000 cal yr BP indicate that mangrove forests underwent two periods of flourishment: ∼2,200–1,750 cal yr BP and ∼1,370–600 cal yr BP, as well as three periods of deterioration: ∼3,000–2,200 cal yr BP, ∼1,750–1,370 cal yr BP, and ∼600–0 cal yr BP. Of factors that might have been influential, changes in the relative sea level and the regional hydrological environment (e.g., seawater temperature, salinity, and hydrodynamic conditions) did not appear to have notable effects on mangrove flourishing/degradation. However, climate change, especially the variation in air temperature, formed the primary factor controlling mangrove development. The stages of mangrove flourishing/deterioration corresponded to the warm/cold periods of the climate, respectively. Noteworthy is that the rapid rise in air temperature during the Anthropocene warm period should have promoted mangrove development, but the increasing intensity of human activity has reversed this tendency leading to the degradation of mangroves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".