Climate Change Perception and Adaptation in a Remote Costa Rican Agricultural Community
Bibliographic record
Abstract
Current agroecosystem management practices in tropical latitudes may not be an economically feasible and an effective long-term adaptation strategy to climate change. As such, implementing, improving and refining sustainable land management practices may be a more effective adaptation strategy. This study determined the perception and knowledge of climate change by landowners in a remote Costa Rican agricultural community, and evaluated the type of sustainable agricultural practices currently implemented and how such practices could also serve as a climate change adaptation strategy. Based on this information, recommendations for successful adaptation applicable to other communities were also discussed. This study showed that community members observed changes in local weather patterns over the past decade, which paralleled changes in the distribution patterns of vegetation and wildlife. Results also showed that community members had a good understanding of climate change and its potential impact(s) on agricultural production. Community members were continually striving to implement long-term sustainable agroecosystem management practices to maintain productivity, integrity and agroecosystem resilience while also meeting economic and socioecological needs. For example, implementing seedbanks helped to improve the quality of crops and provided a source of seeds adapted to current climate conditions. Other adaptation strategies included agroforestry for soil and water conservation and as a source of fruits, nuts and forage for people and livestock. The use of livestock nutritional supplements to offset low-quality forage during the now more intense dry season, compared to previous dry seasons, were also used as an adaptation strategy. An affiliation with social networks to help access resources and implement sustainable agriculture and climate change adaptation strategies were essential in this community. Based on surveys with community members, this study developed a 3- stage plan for developing successful adaptation programs for application in other small agricultural communities in tropical latitudes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".