Restoration, conservation and phytoplankton hysteresis
Bibliographic record
Abstract
Phytoplankton growth depends not only upon external factors that are not strongly altered by the presence of phytoplankton, such as temperature, but also upon factors that are strongly influenced by activity of phytoplankton, including photosynthetically active radiation, and the availability of the macronutrients carbon, nitrogen, phosphorus and, for some, silicate. Since phytoplankton therefore modify, and to an extent create, their own habitats, established phytoplankton communities can show resistance and resilience to change, including managed changes in nutrient regimes. Phytoplankton blooms and community structures can be predicted from the overall biogeochemical setting and inputs, but restorations may be influenced by the physiological responses of established phytoplankton taxa to nutrient inputs, temperature, second-order changes in illumination and nutrient recycling. In this review we discuss the contributions of phytoplankton ecophysiology to biogeochemical hysteresis and possible effects on community composition in the face of management, conservation or remediation plans.
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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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".