Phenological plasticity: shifting growth and developmental phases of North American tree species in response to environmental stressors
Bibliographic record
Abstract
Trees inhabiting seasonal climates organize their life cycle activities following an internal program termed phenology. The rising temperature through global warming has substantially influenced the timing of these phenological events, most prominently studied through the advancement of leaf emergence. Moreover, changes in precipitation patterns have led to severe drought events that have increased in both intensity and frequency worldwide. Both trends necessitate trees to adjust and synchronize their annual cycle within the ‘window of opportunity’ presenting itself based on favourable temperature and available soil moisture. Depending on when critical water limitations occur, tree species are affected at different developmental stages throughout their seasonal cycle. Thus, the severity of impact at a given stage and/or the flexibility to shift developmental and growth activities determine whether the same stressor results in mortality or minor growth reductions.We used over 1000 saplings of six North American tree species (Sequoia sempervirens, Pinus contorta, Quercus garryana, Betula papyrifera, Prunus virginiata, and Acer macrophyllum) to investigate how flexibly (or conservatively) trees re-arrange (or stick to) their phenological sequence and growth activities when impacted by a) drought or b) defoliation events. Both treatments were applied separately at three different times (after leaf emergence, at the summer solstice, and in August) on different batches of saplings. The saplings were grown in a Polytunnel in Vancouver, BC, Canada without water limitations (except for the periodic drought treatments) and were equipped with magnetic dendrometers to monitor radial growth along with observations of bud development and shoot elongation. After harvest, we assessed total root and shoot biomass. In addition, through an image analysis of micro stem slices (utilizing a microtome), we were able to review the xylem properties (e.g., the number of cells produced, vessel size) of treated and control saplings.Our findings reveal how artificial downregulation of source and sink activities at different points in the growing season impacts the performance of radial and apical meristems. Furthermore, we identify the potential of temperate tree species to cope with environmental stressors by optimally utilizing the available ‘time window of opportunity’—for instance, by shifting or splitting their phenological development and growth activity around a drought period. Finally, we discuss how these characteristics correlate with a species’ strategy and the level of bud determinism, i.e., whether shoots continue to grow later in the season (neo-growth atop pre-formed tissue).
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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 | 0.001 |
| 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".