A cytometric framework to assess trends in the morphological structure of bacterioplankton communities along freshwater environmental gradients
Bibliographic record
Abstract
Bacterioplankton communities are characterized by varying distributions of cell size, shape and internal complexity, and macromolecular composition, yet there have been few attempts to quantitatively describe this complex community structure and to assess how it varies among communities and habitats. Here we present a framework to assess this morphological structure, based on the analysis of dot clouds resulting from flow cytometric measurements of side and forward scatter and cell fluorescence of individual bacterioplankton cells. Each community has a characteristic cytometric dot cloud, which forms an ellipsoid that can be described by a combination of metrics that quantify its shape, elongation, volume, orientation, and internal complexity. We apply this framework to assess how the bacterioplankton morphological structure (BMS) varies in 637 lakes distributed across Canada, covering a wide range of limnological, watershed, and climatic features. We show that there is a BMS core, which is characterized by small, simple and oblate shapes, and low overall fluorescence i.e. present in all lakes but is prevalent in oligotrophic lakes with hydrologically less evaporated water and low retention time, likely reflecting mass effects and allochthonous bacterial inputs. We further show that along gradients of increasing network water residence time, system productivity and dissolved organic carbon enrichment, there is a clear succession wherein BMS becomes increasingly dispersed, complex, and prolate shapes, likely reflecting environmental selection of aquatic taxa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".