Human Wellbeing and Ecosystem Services: A mixed-methods study of Shade-Grown Coffee in Veracruz, Mexico

The shade-grown coffee farms of Veracruz, Mexico have been studied for their environmental benefits, in particular their provision of ecosystem services (ES), but there is less research on how that relates to human wellbeing. A practical challenge is balancing these two simultaneous goals—improving farmers’ wellbeing whilst conserving the environment—through interventions like certification schemes. This study uses a case study of a new certification for quality coffee, drawing upon 40 interviews with shade-grown coffee farmers from 2013-2014, who had different levels of participation in the program. The objective of this study is to elicit a wide array of human wellbeing dimensions associated with ES. The mixed-methods research design draws upon social science fields (human geography, development economics, and sociology) with a survey and semi-structured interview, supported by exploratory methods like participatory mapping, ranking, and inventories. The sample is intentionally small to achieve breadth of these methodologies. The study highlights the intellectual challenge of fitting a practical issue to a theoretical framework, and of synthesizing mixed-methods data. However, it contributes to emerging research trends to step beyond disciplinary and methodological boundaries to address complex human-environmental relationships. In conclusion, this study suggests that systems approaches, with top-down and bottom-up methodologies, can increase knowledge of how to use scientific information to inform decision-making in real world contexts.

Name dc:type.qualificationname

Master of Philosophy (MPhil)

Level dc:type.qualificationlevel

Masters

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2015

Author dc:creator

• Weeks, Madeline Rose

• Coffee
• Latin America
• Ecosystem services
• Wellbeing
• Mixed-methods

Licence

• https://www.repository.cam.ac.uk/bitstreams/2adc5a0e-e917-49ca-b176-af35f05cd7f0/download
• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language

en

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.403

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/256675