Tree species richness affects litter production and decomposition rates in a tropical biodiversity experiment
Bibliographic record
Abstract
We report data on leaf litter production and decomposition from a manipulative biodiversity experiment with trees in tropical Panama, which has been designed to explore the relationship between tree diversity and ecosystem functioning. A total of 24 plots (2025 m 2 ) were established in 2001 using six native tree species, with 1‐, 3‐, and 6‐species mixtures. We estimated litter production during the dry season 2005 with litter traps; decomposition was assessed with a litter bag approach during the following wet season. Litter production during the course of the dry season was highly variable among the tree species. Tree diversity significantly affected litter production, and the majority of the intermediate diverse mixtures had higher litter yields than expected based on yields in monoculture. In contrast, high diverse mixtures did not show such overyielding in litter production. Litter decomposition rates were also highly species‐specific, and were related to various measures of litter quality (C/N, lignin/N, fibre content). We found no overall effect of litter diversity if the entire litter mixtures were analyzed, i.e. mixing species resulted in pure additive effects and observed decomposition rates were not different from expected rates. However, the individual species changed their decomposition pattern depending on the diversity of the litter mixture, i.e. there were species‐specific responses to mixing litter. The analysis of temporal C and N dynamics within litter mixtures gave only limited evidence for nutrient transfer among litters of different quality. At this early stage of our tree diversity experiment, there are no coherent and general effects of tree species richness on both litter production and decomposition. Within the scope of the biodiversity‐ecosystem functioning relationship, our results therefore highlight the process‐specific effects diversity may have. Additionally, species‐specific effects on ecosystem processes and their temporal dynamics are important, but such effects may change along the gradient of tree diversity.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".