Bacterioplankton heterotrophic activity in relation to the phytoplankton compartment in a recently formed reservoir
Bibliographic record
Abstract
Abstract Seasonal and spatial variations in bacterial abundance, biomass and potential heterotrophic activity in a recently flooded reservoir were measured for two consecutive years, in conjunction with phytoplankton biomass (chlorophyll‐a concentration) and activity (primary production). The mean value of primary production remained constant between the two study years, while those of the chlorophyll‐a concentrations, bacterial abundance, bacterial biomass and bacterial heterotrophic activity decreased. The observed trends in the bacterial variables were linked to changes in the relative importance of allochthonous dissolved organic matter, in addition to selective grazing activity on bacterioplankton. Multivariate regression analyses identified bacterial abundance (29%) and temperature (17%) as dominant correlates of the bacterial potential heterotrophic activity. We concluded that, in a new reservoir, organic matter, other than that from phytoplankton, might be of great importance for bacterioplankton metabolism. Furthermore, grazing activity on bacteria by metazoa in a new reservoir represents, on occasion, an important trophic link between the top consumer and otherwise unavailable dissolved organic carbon sources. Finally, even if little energy is transferred to larger consumers, the microbial route is still important in re‐mineralizing organic matter in Sep Reservoir.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".