Using nematode traits to evaluate the effects of topography and grazing on the function of wet grassland soils
Bibliographic record
Abstract
Understanding belowground impacts of livestock in rangelands is critical to developing sustainable grazing practices. This is particularly the case in wet grasslands, which face increased pressures in the timing and intensity of grazing in a changing climate. To understand the coupled effects of topography and grazing on wet grassland soils, I examined the generic diversity, feeding composition, and traits of soil nematode communities. I collected nematodes from grazed and ungrazed upland prairies and wet meadows in southern and central Manitoba. Nematodes were extracted from fresh soil cores, counted, identified to the genus level, and assigned to feeding groups. I measured morphological, metabolic, and reproductive traits for a subset of dominant nematode genera and calculated community-weighted means and variances of five nematode traits (length, greatest body diameter, mass, b-ratio, average number of gonads). Topography and grazing did not affect the alpha and beta diversity of nematode genera. However, wet meadows and grazed treatments were characterized by a higher proportion of bacteria-feeding nematodes. On average, larger nematodes with lower b-ratios (i.e., longer esophagus relative to body length) dominated wet meadow soils compared to upland prairie soils. Grazing significantly interacted with topography to result in community-weighted means and variances of nematode traits that were similar across topography. The observed changes in nematode feeding composition and traits suggest that topography and grazing may alter rates of carbon and nutrient cycling in wet grassland soils. This study reinforces the ability of nematode communities, particularly their traits, to serve as valuable bioindicators of soil function in changing environments.
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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) | 0.000 | 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".