Bibliographic record
Abstract
The recent economic recession combined with the mountain pine beetle epidemic had a negative impact on forestry sector in British Columbia. The damage they caused could be a sign to look for new markets for future. Although in recent years new markets have been opening up to the forestry industry no study has been done to look at the possibility of marketing a new tree species. Coastal redwood is one of the strongest and most insect resistant species in North America. This species lives in coastal California and a small part of Oregon and its timber is highly valuable and can be used for several purposes. Redwood can consume and store large amount of carbon, which makes it a profitable species in the carbon market. The purpose of this paper is to examine the possibility of growing redwood in BC while comparing BC’s future climate to the past climate of California coast. The data utilized in predicting BC’s future climate is extrapolated from ClimateBC Software from 2020 to 2080. California historical data is taken from the Western Regional Climate Center and a long-term research trial that investigated the ecological implications of summer fog decline in coastal California. The result of comparison shows that BC can compete with coastal California in terms of precipitation and warm temperature. However, the future predictions show that BC is much too cold to support redwood’s survival for the next 70 years. Nevertheless, this result is faulty since there is no available data related to BEC Units’ zonal site or fog in BC. Future studies that examine the role of fog in BC can increase the chance of redwood’s introduction in this province. Although ClimateBC is sophisticated it uses data collected only until 2002. Future software improvements that include more recent data may result in more accurate predictions. The software also doesn’t include the “microclimatic effects” such as the effects of nearby lakes or snow pack on temperature. In addition, redwood habitat requirement criteria are biased due to the lack of historical data. Additional information about the past could modify our perception of redwood’s tolerance of BC’s environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".