Winner and losers: examining biotic interactions in forbs and grasses in response to changes in water and temperature in a semi-arid grassland
Bibliographic record
Abstract
Abstract Warming and changing water amount can alter the outcome of biotic interactions in native and exotic plants between facilitation and competition. Exotic plants may adapt better to changing environmental conditions, such that they may compete better than native plants. We conducted competition trials for four plant species, two exotic forbs (Centaurea stoebe and Linaria vulgaris) and two grasses (exotic Poa compressa and native Pseudoroegneria spicata), commonly found in Southern interior British Columbia. We compared the effects of warming and changing water on target plant shoot and root biomass, and on pair-wise competitive interactions among all four species. We quantified interactions using the Relative Interaction Intensity index, which has values from −1 (complete competition) to +1 (complete facilitation). C. stoebe biomass was highest under low water and no competition. Facilitation of C. stoebe was found under high water and low temperatures but shifted to competition under low water and/or warming. Competition in L. vulgaris decreased due to reduced water and increased due to warming. Grasses were less competitively suppressed by warming but more competitively suppressed by reduced water input. The response of exotic plants to climate change can differ by plant species, moving in opposite directions for both forbs, but grasses appear to respond similarly. This has consequences for grasses and exotic plants in semi-arid grasslands.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".