Think Globally, Act Locally: The Small Scale Effects of Climate Change on Spruce Growth in SW Yukon
Bibliographic record
Abstract
In this research we investigate spatial complexity in growth patterns of Picea glauca (white spruce) around Kluane in SW Yukon. Assumptions of regional homogeneity are often made with research and legislation surrounding protected areas, where smaller scale sensitivities are often not considered. To test if such sensitivities were important, we studied differences in tree growth across three sites, and determined which climatic variables most strongly influenced growth at each site. The three sites chosen were Burwash Quill (BQ), a cold subalpine site, Cultus Grasslands (CG), a dry forest-grassland ecotone, and Alsek Valley (AV), a wind- scoured slope. Our analysis was conducted using ring-width dendroclimatology, and backed up by δ13C isotope analysis. Our results show that indeed, small scale sensitivities are important. In ring-width analysis, we found significant differences in tree growth between BQ and the other two sites, although AV and CG display similar growth patterns. We also found that correlations between BQ and the other two sites declined over time, which could indicate a threshold being breeched, or be evidence of the divergence problem at BQ. Isotope results show poor correlations between all three sites, and further confirm spatial heterogeneity. To determine which climate variables were important at each site, we correlated ring-widths and isotope values to climate records in the area. We found that the dominant climatic controls were winter and spring temperature at BQ, and previous year growing season precipitation at both CG and AV. Winter and spring temperatures correlated negatively to BQ ring-widths, which suggests that trees grow more when winters are colder. Previous year growing season precipitation correlated positively to ring-widths at both CG and AV, which suggests moisture stress at these sites. From our results, it is clear that decision makers and researchers should consider smaller scale differences in landscapes when discussing how change, particularly climate change, will impact an area.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".