Rooting for the little guy: Below‐ground traits predict juvenile grass demography in microsites
Bibliographic record
Abstract
Abstract Plant functional traits can be a powerful tool for predicting species demography in response to variable environmental conditions. However, accurate predictions of juvenile plant response require ontogenetically relevant traits that capture the response to microsite variability. This is particularly important when considering drivers of seedling emergence, survival, growth and recruitment of species in the context of population persistence or community assembly. We tested the effect of two different microsites on juvenile demography for eight perennial grass species in a semi‐arid system in Colorado along the western edge of the Great Plains. We used seed and root functional traits across multiple life stages to predict these responses and identify mechanisms driving species' emergence, survival, growth and recruitment. Contrary to our expectations, we found that microsites with increased soil moisture (i.e. furrows) had a negative effect on grass emergence early in the season but no effect on recruitment at the end of the season. This was likely driven by the increased growth and survival of grass juveniles in furrows compared to grass juveniles on the surface (reduced soil moisture). We also found that species with more acquisitive roots—from more rapid root elongation—benefited from the increased soil moisture early in the season, but this benefit disappeared later in the season, speaking to the value of using life‐stage specific traits to predict early life‐stage transitions. Variation in microsites will impact juvenile perennial grass demography differently depending on species' traits across life stages. While species in this system typically experience wet to dry transitions across the growing season, furrows with increased soil moisture reduce the intensity of this dry down and may alter demographic responses depending on grass functional traits across ontogeny. We found grass species that are adapted to take advantage of resource pulses did best in furrows where moisture was greater, but that species adapted to conserve resources under stress had limited capacity to respond to these resource pulses. Read the free Plain Language Summary for this article on the Journal blog.
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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) | 0.002 | 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".