Strong scale‐dependent relationships between fine‐root function and soil properties uncovered with spatially coupled sampling
Bibliographic record
Abstract
Substantial fine-root trait variation is found at fine spatial scales but rarely linked to edaphic variation. We assessed the spatial scales of variation in fine-root traits and adjacent soils using a spatially coupled, nested sampling scheme along a fertility gradient in a seasonally dry tropical forest tree, Handroanthus ochraceus. We examined relationships among fine-root traits and identified edaphic drivers of fine-root function. We collected fine-root samples at three scales: multiple samples within individual trees (separated by > 1 m), among trees in a site (3-60 m) and across three sites (15-60 km). We quantified physiological, symbiotic, morphological, chemical and architectural traits, and paired soil physical and chemical properties. Fine-root traits and soils often varied most at fine spatial scales. Root arbuscular mycorrhizal colonization and phosphomonoesterase activity were coordinated and driven by coarse-scale heterogeneity in bulk density, magnesium and phosphate. The trade-off between large diameter and high specific root length, respiration rate and nitrogen concentration was driven by fine-scale heterogeneity in ammonium. The role of base cations was notable, with nitrogen and phosphorus being less influential than expected. Intraspecific fine-root responses to edaphic properties can occur at multiple spatial scales simultaneously and be detected when variation in both is properly captured and spatially matched.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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 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".