The impact of climate change and harvest of mountain pine beetle stands on streamflow in northern British Columbia.
Bibliographic record
Abstract
This research examines the impact of climate change and MPB harvest on streamflow in northern British Columbia using the Hydrologiska Byr~\u2022ns Vattenbalansmodell-Environment Canada model (HBV-EC) a semi-distributed conceptual hydrologic model. Streamflow for the Goathorn Creek watershed in Telkwa is modeled under the IPCC A1B, A2 and B1 emissions scenarios. The TreeGen downscaling method and four global climate models were used to generate future climate. Global climate models used were the Canadian developed CGCM3, ECHAM5 from Germany, GFDL-CM2.1 from the United States and CSIRO-Mk from Australia. Under all climate scenarios HBV-EC modeled a 16 percent reduction in mean annual flows the timing of spring peak flows was also forecast to occur up to 30 days earlier in the year. A change in the timing of peak flows and an overall reduction in mean flows will have important implications for water managers, domestic users and industrial development within the Bulkley Valley. The HBV-EC model was also used to model Moffat Creek streamflow under various harvest scenarios for mountain pine beetle stands. The model predicted an increase in streamflow with an increase in harvest area. When compared to measured streamflow it was however found that average spring discharge during the MPB epidemic was 14 percent lower than it had been during the previous 30 years. The low spring discharge during the MPB epidemic appeared to be related to the 9 percent decrease in SWE for the same years however further investigation is required.
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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 | 0.001 | 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) | 0.002 | 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".