bioRxivJClub
Prediction in trait-based ecology: global simulations of specific leaf area using a trait-based dynamic vegetation model
bioRxiv · · Preprint · Open access
Langan, Kattenborn + 6 more
Abstract ↗AI summary
The abstract is read at the publisher; the summary is JClub's.
In aDGVM2 simulations of global specific leaf area (SLA), mean differences versus GBIF-derived data are -2.9 m2 kg-1 with RMSE 7.26 and nMAE 26.56%.
- Why it matters: Trait-based vegetation models could offer process-linked trait predictions, but their global utility for SLA has not been tested against large-scale trait observations.
- What they did: The eco-evolutionary, trait- and individual-based DGVM2 simulates community assembly under abiotic conditions and plant competition, then compares simulated SLA to GBIF-derived SLA and tests drivers of mismatches.
- The result: Where deciduous and evergreen abundance mismatches occur, errors are large, but correcting them with observed leaf phenology abundances reduces mean differences to -0.11 to 0.43, RMSE to 5.86–5.91, and nMAE to 15.10%–19.61%.
The findingWhy it mattersWhat they didThe result
AI summary of the abstract · may contain errors · not medical advice · read the paper.
- Open access
- 2 cites