Earlier and increased growth of tundra willows after a decade of growth in a warmer common garden environment
Bibliographic record
Abstract
1. The expansion of woody shrubs, known as shrubification, is one of the most widely observed patterns of vegetation change in the tundra. Yet, we do not know the relative importance of plant plasticity and genetic change in determining shrub responses to warming. Plastic responses to the environment can be rapid, while genetic differentiation is much slower. 2. We established a common garden experiment, using three tundra willow species (two tall willow shrubs: Salix richardsonii, S. pulchra, and one prostrate willow: S. arctica). We transplanted cuttings from southern (alpine, high elevation) and northern (Arctic) source populations to a 5ºC warmer environment in southern boreal Yukon, simulating projected future Arctic conditions. We monitored growth, phenology and functional traits in the common garden over a ten-year period from 2013 to 2023 and measured the same variables in the source populations. 3. The three willow species responded differently to a warmer environment. Southern S. richardsonii shrubs in the common garden grew almost seven times faster than the northern willows of the same species. Neither common garden populations of S. pulchra increased in height, but southern individuals grew wider. S. arctica growth patterns were similar between southern and northern common garden populations. All shrubs in the garden advanced their date of leaf bud burst by approximately one month compared to source populations. All northern willows growing in the garden also advanced senescence timing, resulting in less change to overall growing season length for northern willows. We suggest local adaptation to source population conditions as a likely cause of early senescence and limiting growth of northern willows in the common garden. 4. Synthesis: Our findings suggest longer growing seasons due to the advancement of leaf bud burst but not delayed senescence, and potential for rapid shrub growth as tundra ecosystems continue to warm. However, responses to warming vary by species and population, as we observed varied levels of plasticity for traits, phenology and growth. Local adaptation to past climatic conditions and slow genetic change may limit future shrub growth and determine which shrub species proliferate with future warming.
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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 | 0.000 |
| 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 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".