Tree Species Composition, Breeding Systems, and Pollination and Dispersal Syndromes in Three Forest Successional Stages in a Tropical Dry Forest in Mesoamerica
Bibliographic record
Abstract
Tropical dry forests (TDF) in Mesoamerica are highly endangered by the expansion of human activities (e.g., agriculture and cattle ranching). In contrast, TDF in Costa Rica have experienced outstanding restoration due to changes in economic and conservation policies. Currently TDF landscapes in Costa Rica are a mosaic of different successional stages. Tree breeding systems and pollination and dispersal syndromes are key elements for understanding restoration processes in TDFs. In this study we describe and compare tree species composition and diversity in three TDF successional stages (early, intermediate and late) in Guanacaste, Costa Rica. We describe for the first time tree species breeding systems and pollination and dispersal syndromes for the largest and most significant TDF remnant in Mesoamerica. We set up nine plots, three per successional stage, and we measured and identified 1,072 trees from 96 species. Species richness and diversity indices were higher for the intermediate stage. Monoecy was the most common breeding system, as in other tropical life zones. Insects were the dominant pollinators, facilitated by the trees' small inflorescences. Wind was found to be not only the next most influential pollinator, mainly in open and disturbed early forests, but also it was also a good seed dispersal agent. As TDF age increases so does the relevancy of birds and mammals as dispersers; the late stage therefore has more tree species with adaptations to these dispersers.
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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 | 0.001 | 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".