a1 School of International Development, University of East Anglia, Norwich NR4 7TJ, UK
a2 Stockholm Resilience Centre, Stockholm University, SE-106 91 Stockholm, Sweden
a3 e-GEO, Faculdade de Ciências Sociais e Humanas, FCSH, Universidade Nova de Lisboa, Avenida de Berna, 26-C, 1069-061 Lisbon, Portugal
a4 Department of Agricultural and Resource Economics/Connecticut Sea Grant, University of Connecticut, Groton, Connecticut, USA
The concept of ecosystem services (ES), the benefits humans derive from ecosystems, is increasingly applied to environmental conservation, human well-being and poverty alleviation, and to inform the development of interventions. Payments for ecosystem services (PES) implicitly recognize the unequal distribution of the costs and benefits of maintaining ES, through monetary compensation from ‘winners’ to ‘losers’. Some research into PES has examined how such schemes affect poverty, while other literature addresses trade-offs between different ES. However, much evolving ES literature adopts an aggregated perspective of humans and their well-being, which can disregard critical issues for poverty alleviation. This paper identifies four issues with examples from coastal ES in developing countries. First, different groups derive well-being benefits from different ES, creating winners and losers as ES, change. Second, dynamic mechanisms of access determine who can benefit. Third, individuals' contexts and needs determine how ES contribute to well-being. Fourth, aggregated analyses may neglect crucial poverty alleviation mechanisms such as cash-based livelihoods. To inform the development of ES interventions that contribute to poverty alleviation, disaggregated analysis is needed that focuses on who derives which benefits from ecosystems, and how such benefits contribute to the well-being of the poor. These issues present challenges in data availability and selection of how and at which scales to disaggregate. Disaggregation can be applied spatially, but should also include social groupings, such as gender, age and ethnicity, and is most important where inequality is greatest. Existing tools, such as stakeholder analysis and equity weights, can improve the relevance of ES research to poverty alleviation.
(Received December 08 2010)
(Accepted August 30 2011)
(Online publication November 03 2011)