Modern and late Holocene climate-tree-ring growth relationships and growth patterns in Douglas-fir, coastal British Columbia, Canada
Bibliographic record
Abstract
This thesis investigates nonlinear climate-growth relationships and spatio-temporal variations in radial growth of Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco) in coastal British Columbia (BC), Canada. The technique of Artificial Neural Network (ANN) is used to model tree-ring growth response to climatic variables. Spatial variations in radial growth are examined by comparing ring-width chronologies from three sites on southeastern Vancouver Island and nine sites in Bella Coola area of central coast BC. Radial growth in late Holocene is analyzed by examining ring-width chronologies developed from subfossil Douglas-fir at the Heal Lake site on southern Vancouver Island. \n \nA two-level linear aggregate model is proposed as an improved conceptual framework for study of tree-rings and environment. This model is useful for better understanding the interactions and transformations between different environmental factors and for unambiguous interpretation of the impact of disturbance on tree growth. The ANN technique is demonstrated to be superior to the traditional linear regression approach because of its ability to capture nonlinear and complex relationships between climatic variables and tree-ring growth. The ANN model can be used to predict tree-ring growth under given climatic conditions, and to understand climate-growth relationships by scenario analysis. Comparisons of tree-ring chronologies from three sites on southeastern Vancouver Island suggest that the climate-growth responses are generally similar. In the Bella Coola area of central coast BC, principal component analysis shows that there is common growth response throughout the nine sites of different elevations. However, there is also contrasting growth responses between sites of high and low elevations. The growing season precipitation is likely a major factor controlling radial growth of Douglas-fir on macro-regional scale in coastal BC. Five floating ring-width chronologies in the past 3rd and 4th millennia are developed using 79 subfossil Douglas-fir from the Heal Lake site on southern Vancouver Island. These chronologies show slight fluctuations and strong variations at different intervals. Notable growth anomalies occurred at about 4000 years before present, suggesting intense environmental changes, e.g., frost and droughts, at a time of suspected climate transition. The results of this study will be of use to forest management and climate studies in coastal BC.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".