@ 1979, by the American Society of Limnology and Oceanography, Inc. Zooplankton grazing and phytoplankton species richness: Field tests of the predation hypothesis1
Bibliographic record
Abstract
The hypothesis that herbivory plays a major role in the maintenance of high algal diversity was tested over a e-year period in polyethylene enclosures at Heney Lake, Quebec. Reduction of grazing pressure resulted in a significant decrease in the number of inedible species, whereas the diversity of edible algae remained unaffected. Lowering the herbivore levels may cause an intensification of exploitative competition among phytoplankton, which favors edible species and a few inedible algae like Synedra at the expense of many inedible species that are eliminated. Predation has been implicated as a po-tential factor allowing the coexistence of competing species ever since Darwin (1859) recorded the effect of mowing on grassland plant communities. Indeed grazing was one of the factors initially proposed by Hutchinson (1961) to ex-plain the surprisingly high diversity ob-served in lake phytoplankton. Yet, while the high degree of temporal and spatial overlap found among phytoplankton species in nature (Wall and Briand in prep.) suggests low competition levels that are quite compatible with this hy-pothesis, very few workers (Porter 1973, 1977; O’Brien 1974) have investigated this possibility. The predation hypothesis was first clearly formulated as such by Paine (1966) to account for the diversity pat-terns of intertidal communities on rocky shores. He demonstrated that predation can promote prey diversity by allowing the local coexistence of prey species that would otherwise be eliminated by com-petitive exclusion. A large body of theo-retical evidence has since accumulated to isolate the parameters affecting the op-eration of such a mechanism (e.g. Spight
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.337 | 0.280 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".