Intraspecific Fine-Root Trait-Environment Relationships across Interior Douglas-Fir Forests of Western Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Variation in resource acquisition strategies enables plants to adapt to different environments and may partly determine their responses to climate change. However, little is known about how belowground plant traits vary across climate and soil gradients. Focusing on interior Douglas-fir (Pseudotsuga menziesii var. glauca) in western Canada, we tested whether fine-root traits relate to the environment at the intraspecific level. We quantified the variation in commonly measured functional root traits (morphological, chemical, and architectural traits) among the first three fine-root orders (i.e., absorptive fine roots) and across biogeographic gradients in climate and soil factors. Moderate but consistent trait-environment linkages occurred across populations of Douglas-fir, despite high levels of within-site variation. Shifts in morphological traits across regions were decoupled from those in chemical traits. Fine roots in colder/drier climates were characterized by a lower tissue density, higher specific area, larger diameter, and lower carbon-to-nitrogen ratio than those in warmer/wetter climates. Our results showed that Douglas-fir fine roots do not rely on adjustments in architectural traits to adapt rooting strategies in different environments. Intraspecific fine-root adjustments at the regional scale do not fit along a single axis of root economic strategy and are concordant with an increase in root acquisitive potential in colder/drier environments.
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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) | 0.001 | 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 it