Western redcedar dieback : possible links to climate change and implications for forest management on Vancouver Island, B.C.
Bibliographic record
Abstract
This thesis studied the distribution and potential causes of western redcedar (Thuja plicata Donn ex D. Don) dieback on the east coast of Vancouver Island, B.C. using dendrochronology and water balance modelling. Redcedar trees were cored in four of the driest and warmest biogeoclimatic (BEC) units on the island. Dieback was found in varying intensity in three of the four driest BEC units; however, it was primarily concentrated near the Qualicum Beach area (CDFmm). Ring-widths were found to be sensitive to climate on certain sites, but more complacent on other sites. Warm and dry summer climate was found to reduce radial growth of redcedar, and thus moisture stress may be the major determinant of redcedar dieback. Subsequent causes include well drained coarse textured soil conditions (predisposing), drought periods over the growing season (inciting), and contributing factors such as insects and pathogens. Water balance modelling found relationships between transpiration deficit index (TDI) and residual ring-width indices at three of the 16 study sites. The low number of significant relationships was likely caused by the low climate-sensitivity of breast-height tree ring data in redcedar growing on zonal sites. Low climate sensitivity may have been exacerbated by stand dynamics and competition, since study sites were often in mixed stands with multiple age cohorts. ForWaDy, when linked to FORECAST, could provide useful information on water stress and future growth of redcedar on the coast if linked with more climatically sensitive tree ring data. Over the next few hundred years, it is unlikely that redcedar will be lost completely from Vancouver Island due to the resilient and acclimative nature of this species; however, redcedar growing on low elevation sites vulnerable to moisture stress may experience increased dieback occurrences and eventual decline in these areas. Recommendations for future studies of redcedar dieback and considerations for forest management are provided.
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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".