Taxonomic differences shape the responses of freshwater aerobic anoxygenic phototrophic bacterial communities to light and predation
Bibliographic record
Abstract
Aerobic anoxygenic phototrophic (AAP) bacteria are a phylogenetically diverse and ubiquitous group of prokaryotes that use organic matter but can harvest light using bacteriochlorophyll a. Although the factors regulating AAP ecology have long been investigated through field surveys, the few available experimental studies have considered AAPs as a group, thus disregarding the potential differential responses between taxonomically distinct AAP assemblages. Here, we used sequencing of the pufM gene to describe the diversity of AAPs in 10 environmentally distinct temperate lakes, and to investigate the taxonomic responses of AAP communities in these lakes when subjected to similar experimental manipulations of light and predator removal. The studied communities were clearly dominated by Limnohabitans AAP but presented a clear taxonomic segregation between lakes presumably driven by local conditions, which was maintained after experimental manipulations. Predation reduction (but not light exposure) caused significant compositional shifts across most assemblages, but the magnitude of these changes could not be clearly related to changes in bulk AAP abundances or taxonomic richness of AAP assemblages during experiments. Only a few operational taxonomic units, which differed taxonomically between lakes, were found to respond positively during experimental treatments. Our results highlight that different freshwater AAP communities respond differently to similar control mechanisms, highlighting that in-depth knowledge on AAP diversity is essential to understand the ecology and potential role of these photoheterotrophs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".