Mixing tree species and density management to reduce drought susceptibility in coastal plantation forests of British Columbia
Bibliographic record
Abstract
The coastal forests of British Columbia have been experiencing longer and more intense droughts in recent years. To evaluate the effects of species composition and density on drought sensitivity, a study was conducted in a Douglas-fir:western redcedar plantation established in 1992, in the eastern variant of the Coastal Western Hemlock very dry maritime (CWHxm1) bio- geoclimatic subzone along the east side of Vancouver Island. This plantation consists of a 4x3 factorial design with four different species mixtures (Douglas-fir:western redcedar mixtures of 1:0, 1:1, 1:3, and 0:1) at three different planting densities (500, 1000, and 1500 stems/ha). In summer 2022, measurements were taken to evaluate soil moisture, drought tolerance and water use efficiency of these stands. Soil moisture decreased with increasing stand density except for pure Douglas-fir stands which had consistently low soil moisture at all densities. Drought indices calculated from tree core data showed that drought resistance, resilience and recovery increased with decreasing stand basal area. Wood carbon isotopic data indicated that western redcedar trees in their pure stands had higher water use efficiency at lower basal area and these trees were sensitive to drought compared to Douglas-fir trees. Douglas-fir benefitted when mixed with Western redcedar and showed higher water use efficiency in mixed stands compared to pure stands both during wet and dry years. In conclusion, reducing stand basal area, which can be achieved by mixing the two species and controlling stand density, can help reduce the drought susceptibility of these forests to long-term drought
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".