Seasonal shifts in depth-to-water uptake by young thinned and overstocked lodgepole pine ( <i>Pinus contorta</i> ) forests under drought conditions in the Okanagan Valley, British Columbia, Canada
Bibliographic record
Abstract
As drought and prolonged water stress become more prevalent in dry regions under climate change, preserving water resources becomes a focal point for maintaining forest health. Forest regeneration after forest loss or disturbance can lead to overstocked juvenile stands with high water demands and low water-use efficiency. Forest thinning is a common practice with the goal of improving tree health, carbon storage, and water use while decreasing stand demands in arid and semi-arid regions. However, little is known about the impacts of stand density on seasonal variation in depth-to-water uptake or the magnitude of the effect of growing season drought conditions on water availability. Existing reports are highly variable by climatic region, species, and thinning intensity. In this study, stable isotope ratios of deuterium ( δ 2 H) and oxygen ( δ 18 O) in water collected from various soil depths and from branches of lodgepole pine ( Pinus contorta ) under different degrees of thinning (control: 27 000 stems per hectare; moderately thinned: 4500 stems per hectare; heavily thinned: 1100 stems per hectare) over the growing season were analyzed using the MixSIAR Bayesian mixing model to calculate the relative contributions of different water sources in the Okanagan Valley in the interior of British Columbia, Canada. We found that under drought conditions the lodgepole pine trees shifted their depth-to-water uptake through the growing season (June to October) to rely more heavily on older precipitation events that percolated through the soil profile when shallow soil water became less accessible. Decreased forest density subsequent to forest thinning did not cause a significant difference in the isotopic composition of branch water but did cause changes in the timing and relative proportion of water utilized from different depths. Thinned lodgepole pine stands were able to maintain water uptake from 35 cm below the soil profile, whereas the overstocked stands relied on a larger proportion of deep soil water and groundwater towards the end of the growing season. Our results support other findings by indicating that, although lodgepole pines are drought-tolerant and have dimorphic root systems, they do not shift back from deep water sources to shallow soil water when soil water availability increases following precipitation events at the end of the growing season.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".