Contrasting elevational diversity patterns between eukaryotic soil microbes and plants
Bibliographic record
Abstract
The diversity of eukaryotic macroorganisms such as animals and plants usually declines with increasing elevation and latitude. By contrast, the community structure of prokaryotes such as soil bacteria does not generally correlate with elevation or latitude, suggesting that differences in fundamental cell biology and/or body size strongly influence diversity patterns. To distinguish the influences of these two factors, soil eukaryotic microorganism community structure was investigated in six representative vegetation sites along an elevational gradient from forest to alpine tundra on Changbai Mountain in Northeast China, and compared with our previous determination of soil bacterial community structure along the same gradient. Using bar‐coded pyrosequencing, we found strong site differences in eukaryotic microbial community composition. However, diversity of the total eukaryotic microorganism community (or just the fungi or protists alone) did not correlate with elevation. Instead, the patterns of diversity and composition in the total eukaryotic microbial community (and in the protist community alone) were closely correlated with soil pH, suggesting that just as for bacteria, acidity is a particularly important determinant of eukaryotic microbial distributions. By contrast, as expected, plant diversity at the same sites declined along our elevational gradient. These results together suggest that elevational diversity patterns exhibited by eukaryotic microorganisms are fundamentally different from those of plants.
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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 | 0.001 | 0.001 |
| 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 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".