Physiological and morphological responses of pine and willow saplings to post-fire salvage logging
Bibliographic record
Abstract
With global warming, forest fires may be increasing in frequency, and subsequently post-fire salvage logging may become more common. The ecophysiological impacts of this practice on tree saplings remain poorly understood. In this study, I examined the physiological and morphological impacts of increased light intensity, due to post-fire salvage logging, on the conifer Pinus contorta (pine) and deciduous broadleaf Salix lucida (willow) tree and shrub species in the Crowsnest Pass region of southern Alberta. Photosynthetic gas-exchange and plant morphological measurements were taken throughout the summer of 2013 on approximately ten year-old saplings of both species. Neither species exhibited photoinhibition, but different strategies were observed to acclimate to increased light availability. Willow saplings were able to slightly elevate their light-saturated rate of net photosynthesis (Amax) when exposed to higher \nphotosynthetic photon flux density (PPFD), thus increasing their growth rate. Willow \nalso exhibited increased leaf inclination angles and leaf mass per unit area (LMA), to \ndecrease light interception in the salvage-logged plot. By contrast, pine, which exhibited \nlower Amax and transpiration (E), but higher water-use efficiency (WUE = Amax/E) than \nwillow, increased the rate at which electrons were moved through and away from the \nphotosynthetic apparatus in order to avoid photoinhibition. Acclimation indices were \nhigher in willow saplings, consistent with the hypothesis that species with short-lived \nfoliage exhibit greater acclimation. LMA was higher in pine saplings growing in the \nlogged plot, but whole-plant and branch-level morphological acclimation was limited and \nmore consistent with a response to decreased competition in the logged plot, which had \nmuch lower stand density.
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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 | 0.000 | 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 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".