Differences between flower and leaf phenological responses to environmental variation drive shifts in spring phenological sequences of temperate woody plants
Bibliographic record
Abstract
Abstract The relative timing of growth and reproduction is an important driver of plant fitness. For deciduous woody species in temperate regions, leaves and flowers both appear in the early spring, but the order and duration of these phenological events vary among species, populations and individuals. Researchers have long hypothesized that this variation in flower–leaf sequences (FLSs) may be important—affecting the reproduction, recruitment and survival of individuals. Furthermore, FLSs appear to be shifting with climate change; thus, anticipating the extent of these shifts may influence projections of how climate change impacts species' performance and reshapes forest communities. Predicting FLS shifts requires an improved understanding of how environmental variation dictates FLS patterns. To address this, we compared the phenological responses of flowers and developing leaves for 10 temperate woody species to varying levels of temperature and photoperiod in a lab experiment. Our experimental design allowed us to test competing hypotheses for how environmental cues determine FLS variation—specifically whether forcing (warm temperatures) alone drives variation or differential sensitivity to chilling (cool temperatures generally in the fall/winter) and/or photoperiod matter. Within species, we found that flower and leaf phenology responded with differential sensitivity to environmental cues, with differences in their response to chilling being the dominant driver of FLS variation. These differences between flowering and leaf responses were consistent across species, but because species differ in the order of phenological events in their FLSs (flowering‐first versus leafing‐first), differences between flower and leaf phenology will have contrasting impacts on FLS variation across species. Simple projections of FLS shifts with climate change showed large shifts in species that flower before leafing, with flower–leaf interphases substantially shortened. For wind‐pollinated species, this shorter interphase would reduce the time period for efficient pollen transfer, and thus raises the possibility that wind‐pollinated taxa may experience reproductive declines due to FLS shifts. Synthesis . Our study provides strong evidence that flower and leaf phenology responds with differential sensitivity to environmental variation. Because climate change will amplify variability in temperature across time and space, our findings suggest that FLS shifts may be large, but are likely to vary substantially among populations and species. Our analyses indicate that climate change will likely decrease flower–leaf interphases, especially in flowering‐first species. FLS shifts are likely to affect fitness for some species more strongly than others, thereby impacting community structure and function as climate continues to change.
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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) | 0.000 | 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".