The impact of induced drought on transpiration and growth in a temperate pine plantation forest
Bibliographic record
Abstract
Abstract The effects of early growing season droughts on water and carbon balances in conifer forests are poorly understood. In this study, the response of canopy transpiration (Ec) and growth rates to reduced precipitation input during the early growing season was evaluated in a 70‐year old temperate white pine (Pinus strobus L.) plantation forest, in Southern Ontario, Canada. In order to induce the drought, a 20 × 20 m throughfall exclusion setup was established. Throughfall was excluded from 1 April to 3 July 2009. During this period, 270 mm of rainfall occurred (27% of annual precipitation), of which more than 90% was excluded. Sapflow, stem growth, soil moisture and soil temperature were measured in both drought and reference plots. Prior to the induced drought, both plots showed similar soil water content, transpiration rates and tree diameters. The primary control on forest water loss was vapour pressure deficit, whereas soil moisture had an effect when it reached below 0.068 m3 m−3 during the growing season. The rainfall exclusion did not negatively affect Ec until early June, approximately 54 days after drought initiation. Ec was 27% less in the drought plot compared to the reference plot when evaluated at the end of the growing season in November. Tree growth estimates at the end of the growing season indicated a 17% decrease in growth in the drought plot as compared to the reference plot. Because climate predictions foresee changes in precipitation pattern, drought spells – similar to this artificial short‐term rainfall manipulation – may be more frequent in the future. Hence, although overall precipitation may remain the same, the short‐term deficit in water supply may have important implications for forest ecosystems. The findings of this rainfall manipulation will help quantify the impacts of spring and early summer water deficit on forest ecosystems and evaluate their potential responses to future climate regimes. Copyright © 2012 John Wiley & Sons, Ltd.
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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".