Light interception in experimental forests affected by tree diversity and structural complexity of dominant canopy
Bibliographic record
Abstract
Biodiversity affects ecosystem functioning in forests by, for example, enhancing growth and altering the forest structure towards greater complexity with cascading effects on other processes and trophic levels. Complexity in forest canopy could enhance light interception and form a link between diversity and productivity in polyculture forests, but the effect of canopy structure on light interception is rarely directly measured. We modelled the canopy surface structure of a tree diversity experiment by photographing it using unmanned aerial vehicle (UAV) and combining the photos into a digital elevation model with photogrammetry tools. We analysed the effects of tree diversity and functional diversity on canopy structural complexity and light interception with a structural equation model. Our results show that: a) increased structural complexity of the canopy reduces light interception, whereas b) tree diversity increases the structural complexity of the canopy, and has a dual impact on light interception. Tree diversity decreased light interception through the structural complexity of the canopy but increased it probably through canopy packing and crown complementarity. However, the effects of both tree diversity and structural complexity of canopy were smaller than the effect of the functional identities of the tree species, especially the differences between deciduous and evergreen trees. We conclude that more complexity in canopy structure can be gained through increased tree diversity, but complex canopy structure does not increase light interception in young forests.
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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 | 0.000 | 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".