Complexity and composition of pasture swards affect plant productivity and soil organisms
Bibliographic record
Abstract
McElroy, M. S., Papadopoulos, Y. A. and Adl, M. S. 2012. Complexity and composition of pasture swards affect plant productivity and soil organisms. Can. J. Plant Sci. 92: 687–697. The relationships between ecosystem diversity, productivity, and stability is a central theme in current ecological research; the links between above-ground and below-ground ecosystems, as well as their effects on ecosystem services, are becoming more understood. While plant communities differ in primary productivity, and in the communities of soil organisms they support, it is unclear whether these differences are attributable mainly to plant community diversity or to the dominant plant species. This study evaluated the effect of these two factors on plant productivity, and abundance of soil microorganisms and functional diversity, in an establishing pasture using sward complexity (plant species present) and sward composition (identity of species) as treatments in a design using the step-wise addition of grass species. While sward complexity affected plant productivity, showing higher productivity in plots of higher diversity, abundance and functional diversity of soil organism groups were generally not consistently affected by sward complexity or composition. Sward composition did influence soil community composition; there was a close correlation between microbial catabolic activity and sward composition. This study shows that grassland plants have a limited effect on the size and diversity of soil communities while they are being established. This result may have consequences for soil ecosystem services.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".