Increased variance in temperature and lag effects alter phenological responses to rapid warming in a subarctic plant community
Bibliographic record
Abstract
Summer temperature on the Cape Churchill Peninsula (Manitoba, Canada) has increased rapidly over the past 75 years, and flowering phenology of the plant community is advanced in years with warmer temperatures (higher cumulative growing degree days). Despite this, there has been no overall shift in flowering phenology over this period. However, climate change has also resulted in increased interannual variation in temperature; if relationships between phenology and temperature are not linear, an increase in temperature variance may interact with an increase in the mean to alter how community phenology changes over time. In our system, the relationship between phenology and temperature was log-linear, resulting in a steeper slope at the cold end of the temperature spectrum than at the warm end. Because below-average temperatures had a greater impact on phenology than above-average temperatures, the long-term advance in phenology was reduced. In addition, flowering phenology in a given year was delayed if summer temperatures were high the previous year or 2 years earlier (lag effects), further reducing the expected advance over time. Phenology of early-flowering plants was negatively affected only by temperatures in the previous year, and that of late-flowering plants primarily by temperatures 2 years earlier. Subarctic plants develop leaf primordia one or more years prior to flowering (preformation); these results suggest that temperature affects the development of flower primordia during this preformation period. Together, increased variance in temperature and lag effects interacted with a changing mean to reduce the expected phenological advance by 94%, a magnitude large enough to account for our inability to detect a significant advance over time. We conclude that changes in temperature variability and lag effects can alter trends in plant responses to a warming climate and that predictions for changes in plant phenology under future warming scenarios should incorporate such effects.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".