From the Ground Up: Herbaceous Community Diversity and Management in Coffee Agroforestry Systems
Bibliographic record
Abstract
The herbaceous community (HC) is an understudied yet critical aspect of tropical agroecosystems. I measured the diversity and perceptions of the HC within organic coffee systems in the Central Valley of Costa Rica. The HC was taxonomically and functionally diverse; comprised of 39 species from 20 taxonomic groups. Farms below the regional mean size and those with canopy openness of 20-30% had higher HC functional diversity. Farmers perceived tall species with low SLA and LNC, but high height and LDMC to be undesirable, due to slow decomposition rates and management limitations. Farmers’ cognitive map complexity was positively related to HC functional richness, and negatively related to functional evenness and functional dissimilarity. All farmers placed higher emphasis on soil health and organic matter than coffee yield, which may be indicative of their role as land stewards. Workshops are needed to disseminate HC management information to optimize labour and ecosystem functioning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".