Global patterns in community‐scale leaf mass per area distributions of extant woody non‐monocot angiosperms and their utility in the fossil record
Bibliographic record
Abstract
PREMISE: /leaf area). Reliable interpretation of LMA reconstructed from the fossil record is limited by an incomplete understanding of how PM and LMA are correlated at the community scale and what climatic parameters drive variation of both measured and reconstructed LMA of WNMAs globally. METHODS: A modern, global, community-scale data set of in situ WNMA LMA and PM was compiled to test leading hypotheses for environmental drivers of LMA and quantify LMA-PM relationships. Correlations among PM, LMA, climate (Köppen types and continuous data), and leaf habit were assessed and quantified using several uni- and multivariate methods. RESULTS: Community mean LMA increased under warmer and less seasonal temperatures. Drought-prone communities had the highest LMA variance, likely due to disparity between riparian and non-riparian microhabitats. PM and LMA were correlated for community mean and variance, and their correlations with climate were similar. These patterns indicate that climatic correlatives of modern LMA can inform relative trends in reconstructed fossil LMA. In contrast, matching "absolute" LMA distributions between fossil and modern sites does not allow reliable inference of analogous climate types. CONCLUSIONS: This study furthers our understanding of processes influencing the assembly of WNMA leaf economic strategies in plant communities, highlighting the importance of temperature seasonality and habitat heterogeneity. We also provide a method to reconstruct, and refine the framework to interpret, community-scale LMA in the fossil record.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".