Rainfall redistribution by the canopy of a juvenile lodgepole pine stand
Bibliographic record
Abstract
From May to October 2010, throughfall associated with 38 rainfall events in three below-canopy zones (inner-canopy, mid-canopy, and canopy-periphery) of nine juvenile lodgepole pine trees and in open areas between canopies was measured along north, south, east and west transects radiating from each tree bole. Median cumulative throughfall (%) significantly differed among the canopy zones under differing rain depth classes and was negatively correlated with tree size metrics, but only for certain combinations of canopy zones and rain depth classes. Although median cumulative throughfall (%) was negatively correlated with canopy cover fraction when all below-canopy gauges were considered, this relationship only held true for the inner- and mid-canopy zones under relatively small rain depth classes. Additionally, cumulative throughfall (%) was often dependent on transect direction, with event throughfall showing a dependence on the direction of storm origin. Temporal persistence of throughfall was assessed using time stability plots and Spearman rank coefficients of rain event and depth class pairings for all gauges and by canopy zone. The influence of temporal lag and meteorological variables on persistence was also assessed. The implications of our findings on throughfall sampling and for future ecohydrological studies in juvenile lodgepole pine and similar stands are discussed. Additionally, stemflow was measured so that a full canopy water balance could be derived for each event and over the study period. Canopy interception loss, throughfall and stemflow accounted for 87.7, 10.5, and 1.8% of the study-period rainfall, respectfully. Both the reformulated Gash and reformulated Liu models were found to have satisfactory simulated study-period interception loss; however, estimates at the rain-event scale were often poor. Interception loss from the juvenile stand is largely a factor of canopy cover fraction and relatively high during-rainfall evaporation rates.
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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 | 0.000 | 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 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".