Chemical and microbial diversity covary in fresh water to influence ecosystem functioning
Bibliographic record
Abstract
Invisible to the naked eye lies a tremendous diversity of organic molecules and organisms that make major contributions to important biogeochemical cycles. However, how the diversity and composition of these two communities are interlinked remains poorly characterized in fresh waters, despite the potential for chemical and microbial diversity to promote one another. Here we exploited gradients in chemodiversity within a common microbial pool to test how chemical and biological diversity covary and characterized the implications for ecosystem functioning. We found that both chemodiversity and genes associated with organic matter decomposition increased as more plant litterfall accumulated in experimental lake sediments, consistent with scenarios of future environmental change. Chemical and microbial diversity were also positively correlated, with dissolved organic matter having stronger effects on microbes than vice versa. Under our experimental scenarios that increased sediment organic matter from 5 to 25% or darkened overlying waters by 2.5 times, the resulting increases in chemodiversity could increase greenhouse gas concentrations in lake sediments by an average of 1.5 to 2.7 times, when all of the other effects of litterfall and water color were considered. Our results open a major new avenue for research in aquatic ecosystems by exposing connections between chemical and microbial diversity and their implications for the global carbon cycle in greater detail than ever before.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".