Peak radial growth of diffuse-porous species occurs during periods of lower water availability than for ring-porous and coniferous trees
Why this work is in the frame
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Bibliographic record
Abstract
Climate models project warmer summer temperatures will increase the frequency and heat severity of droughts in temperate forests of Eastern North America. Hotter droughts are increasingly documented to affect tree growth and forest dynamics, with critical impacts on tree mortality, carbon sequestration and timber provision. The growing acknowledgement of the dominant role of drought timing on tree vulnerability to water deficit raises the issue of our limited understanding of radial growth phenology for most temperate tree species. Here, we use well-replicated dendrometer band data sampled frequently during the growing season to assess the growth phenology of 610 trees from 15 temperate species over 6 years. Patterns of diameter growth follow a typical logistic shape, with growth rates reaching a maximum in June, and then decreasing until process termination. On average, we find that diffuse-porous species take 16-18 days less than other wood-structure types to put on 50% of their annual diameter growth. However, their peak growth rate occurs almost a full month later than ring-porous and conifer species (ca. 24 ± 4 days; mean ± 95% credible interval). Unlike other species, the growth phenology of diffuse-porous species in our dataset is highly correlated with their spring foliar phenology. We also find that the later window of growth in diffuse-porous species, coinciding with peak evapotranspiration and lower water availability, exposes them to a higher water deficit of 88 ± 19 mm (mean ± SE) during their peak growth than ring-porous and coniferous species (15 ± 35 mm and 30 ± 30 mm, respectively). Given the high climatic sensitivity of wood formation, our findings highlight the importance of wood porosity as one predictor of species climatic sensitivity to the projected intensification of the drought regime in the coming decades.
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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 it