Soil nematodes show a mid-elevation diversity maximum and elevational zonation on Mt. Norikura, Japan
Bibliographic record
Abstract
Little is known about how nematode ecology differs across elevational gradients. We investigated the soil nematode community along a ~2,200 m elevational range on Mt. Norikura, Japan, by sequencing the 18S rRNA gene. As with many other groups of organisms, nematode diversity showed a high correlation with elevation, and a maximum in mid-elevations. While elevation itself, in the context of the mid domain effect, could predict the observed unimodal pattern of soil nematode communities along the elevational gradient, mean annual temperature and soil total nitrogen concentration were the best predictors of diversity. We also found nematode community composition showed strong elevational zonation, indicating that a high degree of ecological specialization that may exist in nematodes in relation to elevation-related environmental gradients and certain nematode OTUs had ranges extending across all elevations, and these generalized OTUs made up a greater proportion of the community at high elevations - such that high elevation nematode OTUs had broader elevational ranges on average, providing an example consistent to Rapoport's elevational hypothesis. This study reveals the potential for using sequencing methods to investigate elevational gradients of small soil organisms, providing a method for rapid investigation of patterns without specialized knowledge in taxonomic identification.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".