Pulses of seed release in riparian <scp><i>Salicaceae</i></scp> coincide with high atmospheric temperature
Bibliographic record
Abstract
Abstract Riparian shrubs and trees in the Salicaceae family release their seeds when floods that create nursery sites for germination are more frequent, but little is known about the factors controlling temporal variations in seed release within the seed release period. The seed release of three riparian tree species dominating European floodplain forests ( Populus alba L., Populus nigra L., and Salix alba L.) was monitored in spring 2007 and 2008 using seed traps placed along the Middle Ebro River, NE Spain. Correlations relating biweekly seed rain intensity (seeds trapped per square meter) to meteorological (atmospheric temperature, cumulative precipitation, relative humidity, solar radiation, mean wind speed) and hydrological (river discharge) variables were investigated. The best combination of environmental variables explaining seed rain intensity was identified using an Akaike information selection criterion‐based backward selection, after accounting for temporal autocorrelation both in seed rain intensity and environmental variables. Seed rain correlated positively with temperature for P. alba , P. nigra , and S. alba , though its effect decreased with relative humidity for P. nigra . Our results can help fine‐tune the design of environmental flows to promote sexual recruitment of Salicaceae trees: Planning water releases during the hottest days of the seed dispersal period, when seed rain peaks, should maximize seed germination density and thus increase the potential for successful seedling establishment.
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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 | 0.001 |
| 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 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".