Spatial Variability of the Dominant Climate Signal in <i>Cassiope tetragona</i> from Sites in Arctic Canada
Bibliographic record
Abstract
Our study investigates the nature of the climate signal in three populations of the Arctic dwarf-shrub Cassiope tetragona using dendrochronological and stable isotope analysis techniques. We present 15 new C. tetragona chronologies from three sites (Axel Heiberg, Bathurst, and Devon islands) in the eastern Canadian Arctic, of which three are the first continuous stable carbon isotope ratio (δ¹³C) time series developed for Arctic shrubs. Correlation and multivariate regression analyses revealed that multiple and different climate factors influenced the chronologies within and between the three sites. At the Axel Heiberg Island site, the dominant climatic influences over annual stem elongation were previous year (t-1) and current year (t) summer precipitation, while annual production of flower buds was influenced by (t) winter precipitation and spring temperature. At Bathurst Island, annual production of flower buds responded to (t-1) growing season sunshine hours and winter precipitation and to (t) late growing season temperature and moisture availability. Our analysis of the Axel Heiberg and Bathurst Island models revealed the positive influence on δ13C values of (t-1) winter temperature—and on Bathurst Island only, of (t-1) spring sunshine hours. The combined influence of these parameters on spring moisture availability suggests that the δ13C ratios varied in response to stomatal conductance. At Devon Island, the δ13C values varied in response to (t) and (t-1) spring and summer temperature and spring and fall solar radiation, which in turn influence the rate of photosynthesis. Our study supports the emerging hypothesis that Arctic shrubs are sensitive to climate. However, strong spatial variation in plant-climate response characterized our sampling sites. This variation may be linked to site sensitivity, or regional climate variability due to geographic and topographic differences, or both.
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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 | 0.001 | 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) | 0.001 | 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".