From Ecosystem Services to Ecosystem Benefits: Unpacking the Links Between Ecosystems and Human Well-Being in Agricultural Communities in Costa Rica
Bibliographic record
Abstract
This dissertation presents an exploration of the links between ecosystem services and human well-being in resource-dependent communities in diverse agricultural regions in Costa Rica. As such, this dissertation considers the key roles played by environmental management and environmental governance. In broad terms, the question that this dissertation examines is: How does the management of ecosystem services derived from agriculture impact human well-being in resource-dependent communities in Costa Rica? This dissertation has taken as a point of departure the framework proposed by the Millennium Ecosystem Assessment and has applied it to the examination of communities that are particularly vulnerable to environmental change. The focus on well-being brings to the forefront questions about the distribution of the benefits derived from ecosystems and highlights the perceptions of ecosystem-users. Three manuscripts make up this dissertation: The first manuscript uses a participatory method (photovoice) to elicit narratives about the ecosystems that impact the well-being of residents in the pineapple community of Volcán in South-Pacific Costa Rica. The manuscript offers a community-level perspective on the ecosystem services that contribute to the well-being of agricultural communities. The second manuscript focuses on how access and power relations affect the benefits experienced by Indigenous farmers in the Bribri Territory who produce plantains for sale in the national and international markets. The manuscript identifies how access to the means of production is gained, controlled and maintained within the social-ecological system of plantain agriculture. It also identifies the mechanisms that gatekeepers employ to exercise their power. The manuscript concludes with possible leverage points that could be used to challenge existing power relations and improve human well-being in the Bribri Indigenous Territory. The third manuscript presents three community-level assessments of well-being from agricultural regions on the Caribbean side of Costa Rica that have different environmental management systems ranging from large-scale monocrop banana plantations in Matina to agroforestry in the Bribri Indigenous Territory. The analysis investigates the ways in which different systems of resource extraction shape well-being at the local level. In brief, the dissertation offers insights for improving the theoretical and empirical understandings of how changes in ecosystems affect human well-being in resource-dependent communities. It also offers suggestions to render the ecosystem services framework more relevant to guide environmental management at the micro-scale and in the context of poverty alleviation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".