Experimental erosion of microbial diversity decreases soil <scp>CH<sub>4</sub></scp> consumption rates
Bibliographic record
Abstract
Abstract Biodiversity‐ecosystem functioning (BEF) experiments have predominantly focused on communities of higher organisms, in particular plants, with comparably little known to date about the relevance of biodiversity for microbially driven biogeochemical processes. Methanotrophic bacteria play a key role in Earth's methane (CH 4 ) cycle by removing atmospheric CH 4 and reducing emissions from methanogenesis in wetlands and landfills. Here, we used a dilution‐to‐extinction approach to simulate diversity loss in a methanotrophic landfill cover soil community. Replicate samples were diluted 10 1 –10 7 ‐fold, preincubated under a high CH 4 atmosphere for microbial communities to recover to comparable size, and then incubated for 86 days at constant or diurnally cycling temperature. We hypothesize that (1) CH 4 consumption decreases as methanotrophic diversity is lost, and (2) this effect is more pronounced under variable temperatures. Net CH 4 consumption was determined by gas chromatography. Microbial community composition was determined by DNA extraction and sequencing of amplicons specific to methanotrophs and bacteria ( pmoA and 16S gene fragments). The richness of operational taxonomic units (OTU) of methanotrophic and nonmethanotrophic bacteria decreased approximately linearly with log ‐dilution. CH 4 consumption decreased with the number of OTUs lost, independent of community size. These effects were independent of temperature cycling. The diversity effects we found occured in relatively diverse communities, challenging the notion of high functional redundancy mediating high resistance to diversity erosion in natural microbial systems. The effects also resemble the ones for higher organisms, suggesting that BEF relationships are universal across taxa and spatial scales.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".