Do Meio- and Macrobenthic Nematodes Differ in Community Composition and Body Weight Trends with Depth?
Bibliographic record
Abstract
Nematodes occur regularly in macrobenthic samples but are rarely identified from them and are thus considered exclusively a part of the meiobenthos. Our study compares the generic composition of nematode communities and their individual body weight trends with water depth in macrobenthic (>250/300 µm) samples from the deep Arctic (Canada Basin), Gulf of Mexico (GOM) and the Bermuda slope with meiobenthic samples (<45 µm) from GOM. The dry weight per individual (µg) of all macrobenthic nematodes combined showed an increasing trend with increasing water depth, while the dry weight per individual of the meiobenthic GOM nematodes showed a trend to decrease with increasing depth. Multivariate analyses showed that the macrobenthic nematode community in the GOM was more similar to the macrobenthic nematodes of the Canada Basin than to the GOM meiobenthic nematodes. In particular, the genera Enoploides, Crenopharynx, Micoletzkyia, Phanodermella were dominant in the macrobenthos and accounted for most of the difference. Relative abundance of non-selective deposit feeders (1B) significantly decreased with depth in macrobenthos but remained dominant in the meiobenthic community. The occurrence of a distinct assemblage of bigger nematodes of high dry weight per individual in the macrobenthos suggests the need to include nematodes in macrobenthic studies.
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) | 0.001 | 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 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".