Functional structure of the bromeliad tank microbiome is strongly shaped by local geochemical conditions
Bibliographic record
Abstract
Phytotelmata in tank-forming Bromeliaceae plants are regarded as potential miniature models for aquatic ecology, but detailed investigations of their microbial communities are rare. Hence, the biogeochemistry in bromeliad tanks remains poorly understood. Here we investigate the structure of bacterial and archaeal communities inhabiting the detritus within the tanks of two bromeliad species, Aechmea nudicaulis and Neoregelia cruenta, from a Brazilian sand dune forest. We used metagenomic sequencing for functional community profiling and 16S sequencing for taxonomic profiling. We estimated the correlation between functional groups and various environmental variables, and compared communities between bromeliad species. In all bromeliads, microbial communities spanned a metabolic network adapted to oxygen-limited conditions, including all denitrification steps, ammonification, sulfate respiration, methanogenesis, reductive acetogenesis and anoxygenic phototrophy. Overall, CO2 reducers dominated in abundance over sulfate reducers, and anoxygenic phototrophs largely outnumbered oxygenic photoautotrophs. Functional community structure correlated strongly with environmental variables, between and within a single bromeliad species. Methanogens and reductive acetogens correlated with detrital volume and canopy coverage, and exhibited higher relative abundances in N. cruenta. A comparison of bromeliads to freshwater lake sediments and soil from around the world, revealed stark differences in terms of taxonomic as well as functional microbial community structure.
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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 | 0.000 | 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 | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.054 | 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 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".