Links between resources, C metabolism and the major components of bacterioplankton community structure across a range of freshwater ecosystems
Bibliographic record
Abstract
We explored the patterns in bacterioplankton community metabolism (BCM) and four components of community structure [composition (BCC), metabolic capacities (MC), physiological structure (PS) and single-cell characteristics (SCC)], between lakes, rivers and marshes within a watershed in Québec, to assess the connections that exist between them and with the main resources (organic matter, nutrients). Habitat types were well segregated by both resources and BCM and their corresponding dissimilarity matrices were significantly correlated, suggesting that BCM tracks resource conditions in a consistent manner across ecosystem types. MC also segregated the various habitats and was correlated to BCM but less so to resources, whereas BCC at times resulted in a clear separation of habitats, but was rarely correlated to resources and never to BCM, suggesting a higher degree of ecosystem specificity at this particular level. Finally, there was no clear separation of habitats in terms of PS and SCC, and none covaried with resources or BCM. The habitat patterns based on these different components of structure were rarely correlated to each other, indicating weak deterministic connections between them. MC appears to mediate the link between resources and BCM more directly and consistently across systems; BCC appears to be more influenced by ecosystem-specific factors that weaken its overall connection to both resources and BCM, whereas PS and SCC show no discernible patterns. Our results thus suggest that the bottom-up regulation of BCM by resources is mediated by complex shifts within components of community structure that can be directional, ecosystem-specific or apparently random, which combined nevertheless result in a systematic overall response to resources in terms of C metabolism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".