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An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns

We take a social-ecological systems perspective to investigate the linkages between ecosystem services and human well-being in South Africa. A recent paper identified different types of social-ecological systems in the country, based on distinct bundles of ecosystem service use. These system types w...

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Autores principales: Hamann, Maike, Biggs, Reinette, Reyers, Belinda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047452/
https://www.ncbi.nlm.nih.gov/pubmed/27695120
http://dx.doi.org/10.1371/journal.pone.0163476
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author Hamann, Maike
Biggs, Reinette
Reyers, Belinda
author_facet Hamann, Maike
Biggs, Reinette
Reyers, Belinda
author_sort Hamann, Maike
collection PubMed
description We take a social-ecological systems perspective to investigate the linkages between ecosystem services and human well-being in South Africa. A recent paper identified different types of social-ecological systems in the country, based on distinct bundles of ecosystem service use. These system types were found to represent increasingly weak direct feedbacks between nature and people, from rural “green-loop” communities to urban “red-loop” societies. Here we construct human well-being bundles and explore whether the well-being bundles can be used to identify the same social-ecological system types that were identified using bundles of ecosystem service use. Based on national census data, we found three distinct well-being bundle types that are mainly characterized by differences in income, unemployment and property ownership. The distribution of these well-being bundles approximates the distribution of ecosystem service use bundles to a substantial degree: High levels of income and education generally coincided with areas characterised by low levels of direct ecosystem service use (or red-loop systems), while the majority of low well-being areas coincided with medium and high levels of direct ecosystem service use (or transition and green-loop systems). However, our results indicate that transformations from green-loop to red-loop systems do not always entail an immediate improvement in well-being, which we suggest may be due to a time lag between changes in the different system components. Using human well-being bundles as an indicator of social-ecological dynamics may be useful in other contexts since it is based on socio-economic data commonly collected by governments, and provides important insights into the connections between ecosystem services and human well-being at policy-relevant sub-national scales.
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spelling pubmed-50474522016-10-27 An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns Hamann, Maike Biggs, Reinette Reyers, Belinda PLoS One Research Article We take a social-ecological systems perspective to investigate the linkages between ecosystem services and human well-being in South Africa. A recent paper identified different types of social-ecological systems in the country, based on distinct bundles of ecosystem service use. These system types were found to represent increasingly weak direct feedbacks between nature and people, from rural “green-loop” communities to urban “red-loop” societies. Here we construct human well-being bundles and explore whether the well-being bundles can be used to identify the same social-ecological system types that were identified using bundles of ecosystem service use. Based on national census data, we found three distinct well-being bundle types that are mainly characterized by differences in income, unemployment and property ownership. The distribution of these well-being bundles approximates the distribution of ecosystem service use bundles to a substantial degree: High levels of income and education generally coincided with areas characterised by low levels of direct ecosystem service use (or red-loop systems), while the majority of low well-being areas coincided with medium and high levels of direct ecosystem service use (or transition and green-loop systems). However, our results indicate that transformations from green-loop to red-loop systems do not always entail an immediate improvement in well-being, which we suggest may be due to a time lag between changes in the different system components. Using human well-being bundles as an indicator of social-ecological dynamics may be useful in other contexts since it is based on socio-economic data commonly collected by governments, and provides important insights into the connections between ecosystem services and human well-being at policy-relevant sub-national scales. Public Library of Science 2016-10-03 /pmc/articles/PMC5047452/ /pubmed/27695120 http://dx.doi.org/10.1371/journal.pone.0163476 Text en © 2016 Hamann et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hamann, Maike
Biggs, Reinette
Reyers, Belinda
An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title_full An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title_fullStr An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title_full_unstemmed An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title_short An Exploration of Human Well-Being Bundles as Identifiers of Ecosystem Service Use Patterns
title_sort exploration of human well-being bundles as identifiers of ecosystem service use patterns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5047452/
https://www.ncbi.nlm.nih.gov/pubmed/27695120
http://dx.doi.org/10.1371/journal.pone.0163476
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