Plant community composition, tree physiology, and bark-beetle mortality in relation to open and enclosed irrigation channels: a case study within a wildland-urban interface forest in western Montana
Bibliographic record
Abstract
Dry coniferous forests within the wildland–urban interface (WUI) in the northwestern US have experienced long-term drought and increasing bark-beetle infestations. An unexamined factor potentially affecting WUI forests are irrigation channels used to convey water to nearby farms. I studied the effects of two irrigation channels (a downslope, open channel and an upslope, recently enclosed channel) on plant community composition, tree water status and growth, and patterns of bark-beetle mortality in a WUI ponderosa pine/Douglas fir forest experiencing drought. Low-lying swale areas below the recently enclosed, upper channel had extensive down dead wood and showed shifts from mesic understory plant species to more xeric species. Tree density and basal area declined in swale areas below both channels. Ponderosa pine below the enclosed channel showed evidence of water stress (low water potentials) and negative growth responses to the channel enclosure. In contrast, hillslope trees below the open channel had higher growth rates and water potentials compared to trees above that channel. Beetle-kill was highest between the two channels, the area most likely affected by upper channel enclosure. The study provides evidence that plant community composition, tree physiology, and patterns of tree mortality in forests may be affected by irrigation channels interacting with small-scale topography.
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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 | 0.001 | 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) | 0.000 | 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 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".