Benthic algal biomass — measurement and errors1
Bibliographic record
Abstract
Abstract: While benthic algal biomass is one of the most commonly measured variables within littoral communities, it is also one of the most poorly characterized. The use of chlorophyll a as an estimate of biomass, while easy and inexpensive, can be affected by changes in environmental conditions and algal community composition. Biovolume-based measure-ments often have high variability and are affected by changes in cell volume due to preservation. Using 12 years of data from the Experimental Lakes Area (northwestern Ontario, Canada) as well as short-term surveys and experimental studies from the Experimental Lakes Area and the Canadian Rocky Mountains, we demonstrate that biovolume and chlorophyll a are often decoupled in the littoral zone of temperate oligotrophic lakes. We recommend that researchers revisit the limita-tions of both metrics and specifically caution against the use of chlorophyll a as a biomass indicator when light, tempera-ture, or species composition vary significantly. Résume ́ : Bien que la biomasse des algues benthiques soit l’une des variables les plus fréquemment mesurées dans les communautés littorales, c’est aussi l’une des moins bien caractérisées. L’utilisation de la chlorophylle a pour l’estimation de la biomasse, bien que facile et peu coûteuse, peut être affectée par des changements des conditions du milieu et par la composition de la communaute ́ algale. Les mesures basées sur le biovolume ont souvent une forte variabilite ́ et sont affect-ées par les changements des volumes cellulaires causés par les méthodes de conservation. Nous utilisons des données éta-lées sur 12 ans provenant de la Région des lacs expérimentaux (Ontario, Canada) ainsi que des inventaires a ̀ court terme
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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 | 0.019 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".