Changes in trophic abundance of soil arthropods along a grass-shrub-forest gradient
Bibliographic record
Abstract
Ecological theory suggests that along productivity gradients, abundances of organisms within trophic levels will increase in a stepwise pattern from producers to consumers. To test this theory I investigated changes in abundance of soil arthropods at three trophic levels: microphytophages, represented by Collembola, predacious mites (Acari) that feed on Collembola, and three groups of macroarthropods (spiders, ants, and centipedes) that were observed to feed on mites. Changes in abundance were monitored along a gradient in vegetation structure from grass to shrub to forest in the Canadian prairies. I controlled for temporal variation in abundance among years and surveys within a year. As predicted, (i) numbers of Collembola did not change with increases in productivity; (ii) mite numbers were greatest in the shrublands; and (iii) numbers of macroarthropod predators increased from grassland to shrubland, and there was a nonsignificant increase in numbers of spiders and centipedes in forest habitat. Contrary to predictions, macroarthropod numbers were not significantly greater in forest habitat, and ant numbers actually declined. Possible explanations for the lack of increase in macroarthropod predator abundance in the forest habitat with the greatest productivity include decreased ground-level humidity and greater abundance of macroarthropod predators and parasites in forest environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".