Contrasting grazing practices alter plant community trajectories across western Canada’s grasslands with implications for ecosystem function
Bibliographic record
Abstract
Livestock grazing influences grassland biodiversity and ecosystem function. We report on the effects of adaptive multi-paddock (AMP) grazing (characterized by extended recovery periods between pulsed high animal density grazing events) on plant community composition and diversity across western Canada, compared to neighboring properties managed with conventional grazing (n-AMP). We also evaluated the influence of grazing practices, specifically stocking rate, cattle density, and variations in rest-to-grazing ratio at the start of the grazing season on plant community composition and diversity. We further explored the relationship between soil organic carbon (SOC) and plant diversity. Overall, AMP grazing, and specifically the use of high rest-to-grazing ratios early in the growing season, increased the proportion of non-native species. Native grasslands without prior cultivation had greater plant species richness, with fewer non-native species and containing phylogenetically more divergent plant communities, independent of grazing practices. The n-AMP pastures had higher functional trait dispersion, a pattern especially pronounced for tame (previously cultivated and seeded) pastures, and those with lower cattle stock densities (animals per unit area). Greater SOC was associated with communities higher in non-native plants, of lower species richness, and greater phylogenetic divergence, while no trend was identified for functional dispersion. Overall, AMP grazing did not increase plant species richness, functional diversity, or phylogenetic diversity. Instead, pulsed rotational grazing, specifically using high stock densities and extended rest periods, facilitated non-native species prevalence and reduced functional diversity. However, non-native species and lower overall species richness may benefit SOC accumulation, illustrating the challenges associated with building biodiverse plant communities with a high capacity for climate change mitigation. • Plant diversity in grasslands is not altered by adaptive multi-paddock grazing. • Plant functional diversity decreased with longer rest following early season cattle grazing. • Plant functional diversity was lower with higher cattle stock densities. • Adaptive multi-paddock grazing favors non-native plant species. • Higher levels of non-native species are associated with increased soil organic carbon.
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 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 | 0.001 | 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 | 0.002 | 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".