Substantial variation in leaf senescence times among 1360 temperate woody plant species: implications for phenology and ecosystem processes
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
BACKGROUND AND AIMS: Autumn leaf senescence marks the end of the growing season in temperate ecosystems. Its timing influences a number of ecosystem processes, including carbon, water and nutrient cycling. Climate change is altering leaf senescence phenology and, as those changes continue, it will affect individual woody plants, species and ecosystems. In contrast to spring leaf out times, however, leaf senescence times remain relatively understudied. Variation in the phenology of leaf senescence among species and locations is still poorly understood. METHODS: Leaf senescence phenology of 1360 deciduous plant species at six temperate botanical gardens in Asia, North America and Europe was recorded in 2012 and 2013. This large data set was used to explore ecological and phylogenetic factors associated with variation in leaf senescence. KEY RESULTS: Leaf senescence dates among species varied by 3 months on average across the six locations. Plant species tended to undergo leaf senescence in the same order in the autumns of both years at each location, but the order of senescence was only weakly correlated across sites. Leaf senescence times were not related to spring leaf out times, were not evolutionarily conserved and were only minimally influenced by growth habit, wood anatomy and percentage colour change or leaf drop. These weak patterns of leaf senescence timing contrast with much stronger leaf out patterns from a previous study. CONCLUSIONS: The results suggest that, in contrast to the broader temperature effects that determine leaf out times, leaf senescence times are probably determined by a larger or different suite of local environmental effects, including temperature, soil moisture, frost and wind. Determining the importance of these factors for a wide range of species represents the next challenge for understanding how climate change is affecting the end of the growing season and associated ecosystem processes.
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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) | 0.000 | 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 it