Mixedgrass vegetation is tolerant to a short‐term but not season‐long access mat use during mitigation of industrial traffic
Bibliographic record
Abstract
Abstract Grasslands are impacted by many disturbances, including energy development. While temporary working platforms using access mats to support large equipment can minimize soil disturbance, less is known about matting impacts on grassland vegetation. We assessed heavy traffic effects on sandy and loamy Mixedgrass Prairie in southeast Alberta, Canada, where traffic occurred in 2015 either directly on grassland or on temporary matting. Vegetation was assessed in 2016 and 2017. Treatments varied in type (with/without matting), timing (spring vs. fall vs. season‐long) and duration (6 vs. 12 weeks, and 24 weeks for season‐long) of occurrence. While grass biomass was unaffected by direct wheeled traffic, native forb biomass declined, particularly during the first growing season; 1 year later, plots with prior long‐term matting had more native forbs. Where traffic occurred on mats, grass biomass decreased when mats were placed for 6 or 12 weeks in spring, or for the entire growing season. Longer mat use also increased introduced forbs, which were positively associated with soil nitrogen supply rates. Plant biomass changes from matting (less grass, more introduced forbs) were more apparent in loamy‐sand than loam soils. Overall, while direct traffic had limited impacts on vegetation, matting was more likely to alter vegetation, particularly when placed in spring or for longer periods, and further varied with ecosite type and the timing of traffic disturbance. We recommend that access mats be limited to placement for short periods (≤12 weeks), preferably in falling, to conserve mixedgrass prairie, while longer placement intervals be avoided.
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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 | 0.000 | 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 | 0.000 | 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".