Two mesocosm experiments investigating the control of summer phytoplankton growth in a small shallow lake
Bibliographic record
Abstract
Summary 1. Mesocosm experiments were carried out to examine the relative importance of top down (fish predation) and bottom up (nutrient addition) controls on phytoplankton abundance in a small shallow lake, Little Mere, U.K., in 1998 and 1999. These experiments were part of a series at six sites across Europe. 2. In the 1998 experiment, top‐down processes (through grazing of large Cladocera) were important in determining phytoplankton biomass. The lack of plant refugia for zooplankton was probably important in causing an increasing chlorophyll a concentration even at intermediate fish density. Little Mere normally has abundant macrophytes but they failed to develop substantially during both years. Bottom‐up control was not important in 1998, most probably because of high background nutrient concentrations, as a result of nutrient release from the sediments. 3. In 1999 neither top‐down nor bottom‐up processes were significant in determining phytoplankton biomass. Large cladoceran grazers were absent even in the fish‐free enclosures, probably because dominance of cyanobacteria and high phytoplankton biomass made feeding conditions unsuitable. As in 1998, bottom‐up control of phytoplankton was not important, owing to background nutrient concentrations that were even higher in 1999 than in 1998, perhaps because of the warmer, sunnier weather. 4. The differing outcomes of the two experiments in the same lake with similar experimental designs highlight the importance of starting conditions. These conditions in turn depended on overall weather conditions prior to the experiments.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".