The importance of meiofauna to lotic ecosystem functioning
Bibliographic record
Abstract
1 Although meiofauna occur in large numbers in many streams, almost nothing is known about their functional role. 2 In other systems, meiofauna influence microbial and organic matter dynamics through consumption and bioturbation. Given that these are important processes in streams, meiofauna have the potential to influence lotic function by changing the quality and availability of organic matter as well as the number and biotic activity of benthic microbes. Selective feeding by meiofauna has the potential to alter the availability of nutrients and organic carbon. 3 Meiofauna generally contribute only a small amount to metazoan production and biomass in streams, although exceptions occur. Within a stream, the relative importance of meiofauna may reflect whether the temporary or permanent meiofauna dominate the meiobenthos as well as the season when samples are collected. 4 We suggest stream conditions (small sediment grain size, restricted interstitial flow) under which meiofauna have the greatest likelihood of influencing stream ecosystem function. 5 Important areas for future research include addressing whether meiofauna feed selectively, whether meiofauna are links or sinks for carbon in streams, and whether bioturbation by meiofauna influences stream ecosystem processes in a predictable manner.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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; both teacher heads agree on what is shown here.
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".