Metabolic changes and the resistance and resilience of a subtropical heterotrophic lake to typhoon disturbance
Bibliographic record
Abstract
We studied how typhoon strength affects the daily dynamics of ecosystem metabolism of a subtropical alpine lake in Taiwan. We identified proximal agents of typhoon disturbance and assessed the resistance (the extent of change induced by a disturbance) and resilience (the rate of recovery after a disturbance) of lake metabolism to them. Gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production were estimated from high-frequency dissolved oxygen data provided by an instrumented buoy. Typhoons resulted in significantly lower GPP (3%–81% decrease), and higher ER (7%–828% increase) compared with immediately before the events, and thus the lake became more heterotrophic (28%–852% increase in heterotrophy). The resistance and resilience of lake metabolism depended on the intensity of the typhoon. Smaller typhoons (with average daily accumulated precipitation (ADAP) < 200 mm·day–1) had greater effects on lake metabolism than medium (ADAP = 200–350 mm·day–1) and large (ADAP > 350 mm·day–1) typhoons. However, metabolism also recovered more quickly after smaller typhoons than after medium or larger typhoons. Typhoon effects on ecosystem metabolism is likely mediated by the magnitude and duration of typhoon-induced changes in lake mixing, the quantity and quality of dissolved organic carbon, and the biomass of primary producers.
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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 | 0.000 | 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".