Species Richness Promotes Productivity through Tree Crown Spatial Complementarity in a Species-Rich Natural Forest
Bibliographic record
Abstract
Ecological theory suggests that species with complementary architectural and physiological traits can optimize crown packing to improve resource efficiency and promote ecosystem productivity in forest communities. However, empirical evidence of this prediction is rare in species-rich natural forests, as little is known about how crown spatial complementarity regulates community species richness-productivity relationship (SRPR). In this study, we measured tree architectural traits (stem diameter, height, crown depth and width) for 11,337 trees, and quantified species richness, functional diversity, crown spatial complementarity, soil fertility and forest productivity for 44 quadrats (20 m × 20 m per quadrat) in the Badagongshan 25 ha forest plot, central China. We tested bivariate correlations between species richness, crown complementarity, functional diversity and forest productivity. We employed linear mixed effects models to predict crown complementarity and examined its relationship with functional diversity. Finally, we applied structural equation modeling to quantify the mediation effects of crown complementarity on SRPRs. Species richness promoted crown complementarity and forest productivity. Crown complementarity varied across quadrats, with increases driven primarily by changes in tree height. Crown complementarity was positively related to functional diversity and forest productivity. Species richness increased with soil total phosphorus, while functional diversity decreased with soil bulk density. Forest productivity increased with soil organic carbon and total nitrogen, but decreased with bulk density. Crown complementarity partially mediated the positive effect of species richness on forest productivity, and the mediation effect was mainly through functional diversity. Our results suggest that the crown complementarity index accurately reflects the niche complementarity through light utilization and carbon reallocation. Our study emphasizes that species richness can promote crown complementarity, leading to greater forest productivity, which provides greater insight into the mechanical understanding of the SRPRs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".