Primate life history, social dynamics, ecology, and conservation: Contributions from long‐term research in Área de Conservación Guanacaste, Costa Rica
Bibliographic record
Abstract
Abstract Research on non‐human primates in the endangered tropical dry forest of Sector Santa Rosa (SSR), Área de Conservación Guanacaste (ACG), was launched in 1983 and is now one of the longest running studies of primates globally. Such continuous study provides a rare opportunity to ask questions that are only answerable through decades‐long monitoring of these long‐lived monkeys. In turn, the mounting data generated by long‐term study, including knowledge of lifetime reproductive success, familial relatedness, comprehensive behavioral and dietary repertoires, and patterns of inter‐ and intra‐annual variation in forest productivity, provide diverse opportunities to researchers, and facilitate studies that are of shorter duration. Here, we review some of the contributions of our longitudinal research on white‐faced capuchins and Geoffroy's spider monkeys, together with newer studies on mantled howler monkeys. We begin by synthesizing findings from our research on demography, dispersal, social relationships, and reproduction. These life history and social traits interact with their foraging and sensory ecology, which we review next. We end by highlighting how the longitudinal study of primates in Sector Santa Rosa has made direct and indirect contributions to the conservation of the critically endangered dry forest biome and its inhabitants, as well as to education, community, and forest restoration initiatives. In particular, we focus our review on how long‐term research is uniquely positioned to make key contributions spanning different topical areas. Abstract in Spanish is available with online material.
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".