Temporal variations in the understory photosynthetic photon flux density of deciduous stand: the effects of canopy development, solar elevation, and sky conditions
Bibliographic record
Abstract
The effects of canopy development, solar elevation, and sky conditions on temporal variation in photosynthetic photon flux density (PPFD) were examined within a 9-year-old bigleaf maple stand on Vancouver Island (Canada). PPFD was measured every second and stored as 10-min averages from 18 May to 14 October 1996, at 52 microsites characterised according to their growing season %PPFD (GSP). PPFD and %PPFD variability was examined at three different temporal levels. Specific days in May, July, and September with clear and overcast sky conditions were selected to separate the effects of canopy development and solar elevation on diurnal and seasonal light variability. \nDiurnal light variability expressed as the mean of the difference between two consecutive 10-min averages of PPFD and %PPFD decreased with increasing GSP on clear days in May. For clear days in July and September, variability was characterised by arc-shaped relationships with high variability for microsites receiving between 20 and 80% GSP and lower variability for microsites below 20 and above 80% GSP. On overcast days, diurnal variability in PPFD increased with increasing GSP while diurnal variability in %PPFD showed an arc-shape relationship. The coefficient of variation of PPFD and %PPFD decreased with increasing GSP on clear days and sunflecks decreased with decreasing GSP and from May to September. \nDay-to-day light variability expressed as the mean difference between consecutive daily PPFD increased with increasing GSP while the mean difference between consecutive daily %PPFD was higher for microsites receiving between 20 and 80% GSP. The coefficient of variation for the daily PPFD and %PPFD was higher for microsites receiving <20% GSP compared to other microsites. Seasonal light variability showed that microsites with <50% GSP received up to eight times more light in May than in July on both clear and overcast sky conditions because of canopy development. From July to September in clear sky conditions, decrease in light was variable for microsites receiving <40% GSP; probably because of the position of microsites in relation to the solar track. On overcast days, mean daily PPFD above canopy and in the understorey was 2 to 3 times higher in July than in September while mean daily %PPFD remained stable. The possible effects of the types of diurnal and day-to-day light variability on physiological and morphological responses of understorey plants are discussed.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".