Leaf-level physiology in four subalpine plants in tephra-impacted forests during drought
Bibliographic record
Abstract
Ecological impacts of climate change in the Pacific Northwest may hinge on acclimation to drier summers, highlighting the importance of plant physiological studies in forests. Evaluating dominant forest plant species under old-growth and managed forest conditions is similarly important as timber harvest might change microclimates and alter drought effects on plants. We examined water potential and gas exchange rates of four dominant plant species in understories of subalpine forests of the Pacific Northwest region of the United States during 2015 — a year with drought conditions representative of future climate projections. We examined two conifer species (Abies amabilis Douglas ex J. Forbes and Tsuga heterophylla (Raf.) Sarg.) and two huckleberry species (Vaccinium membranaceum Douglas ex Torr. and Vaccinium ovalifolium Sm.) in old-growth and formerly clear-cut forests at two elevations. Contrary to expectations, we found no evidence of hydraulic stress, and there were no significant differences between old-growth and clear-cut stands, consistent with an edaphic buffering effect in this volcanic landscape. Variation in stem elongation rates among years also indicated the lack of a strong drought response in 2015. Water potential, photosynthesis, and stomatal conductance varied among species and among elevations. In combination, our results help constrain expected physiological activity of understory species in subalpine forests and emphasize the importance of the edaphic context (e.g., tephra deposits) in framing expectations for the responses to drought.
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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".