Consequences of altered precipitation, warming, and clipping for plant productivity, biodiversity, and grazing resources at three northern temperate grassland sites
Bibliographic record
Abstract
There is limited understanding about how altered precipitation and warming associated with climate change affect grassland systems. Also, although grasslands commonly support herbivores, it is unclear how grazing influences responses to climate change. To address these knowledge gaps, I carried out a fully controlled and factorial three-year, multi-site experiment simulating climate change and grazing (via clipping). This experiment was conducted at three sites, chosen to broadly represent northern temperate grassland in the region, and each of Canada’s prairie provinces. I increased air temperature by 2-4°C, reduced precipitation by 60%, and clipped plants at low and high intensity. At one site, I also applied added (+60%) precipitation. I monitored an array of responses, including plant biomass and biodiversity, and grazing resources. Shoot biomass decreased strongly with reduced precipitation and clipping, and tended to decrease with warming. However, shifts in root: shoot ratio and associated root biomass responses enabled stability of total biomass. With respect to grazing resources, herbage availability and quality decreased with reduced precipitation and warming; decline in herbage availability was less pronounced with warming than reduced precipitation. To assess biodiversity responses, I evaluated indirect and direct treatment effects on species richness and evenness. Across sites, richness declined with environmental changes associated with all three treatments. However, evenness responses varied by site, and were overall more resistant. I also assessed changes in similarity between the seed bank and aboveground vegetation at one location. Precipitation and clipping affected similarity between the seed bank and vegetation, while warming did not. Across sites, responses were generally consistent, except for the driest site, which remained largely resistant to reduced precipitation. Generally, the grasslands were highly responsive to warming, altered precipitation, and clipping, with negative implications for ecosystem function and biodiversity. However, productivity and biodiversity responses were asynchronous; productivity was more responsive to precipitation and clipping, while richness was more sensitive to increased air temperature. As well, results suggest that management will not substantially influence responses to climate change. Overall, maintenance of total biomass suggests that ecosystem function is relatively resistant to climate change, but climate change has negative ramifications for biodiversity and grazing resources.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".