Relationships between Plant Biodiversity and Soil Fertility in a Mature Tropical Forest, Costa Rica
Bibliographic record
Abstract
We aimed to study relationships between plant biodiversity and soil chemical fertility in a mature tropical forest of Costa Rica. Soil samples were collected in nine sampling plots (5 m by 25 m) in order to identify P, K, Ca, Mg, Fe, Zn, Mn, Cu, and Al and total N contents, soil fertility index, CEC, pH, and C/N ratio. Furthermore, species richness, Shannon-Wiener and Simpson’s species diversities, structural richness, and structural diversity were calculated for each plot. Simple linear regression analyses were conducted. Tree species richness was inversely related to concentration levels of K, Ca, and P, CEC, and soil fertility index. Therefore, higher tree species richness tended to be found on sites with lower soil fertility, which is the complete opposite of temperate forests. As a result, tropical and temperate forest ecology should be considered separately. Shannon-Wiener tree species diversity was positively correlated to C/N ratio. Herb structural richness was positively correlated with soil fertility index and P concentration. Therefore, herb structural richness may be a good indicator of soil fertility. This study gives important insights on ecological relationships between plant biodiversity and soil chemical fertility in a primary tropical forest.
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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 | 0.001 |
| 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".