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A Cross-National Analysis of How Economic Inequality Predicts Biodiversity Loss
Stockholm University, Stockholm Resilience Centre. Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
2009 (English)In: Conservation Biology, ISSN 0888-8892, E-ISSN 1523-1739, Vol. 23, no 5, 1304-1313 p.Article in journal (Refereed) Published
Abstract [en]

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.

Place, publisher, year, edition, pages
2009. Vol. 23, no 5, 1304-1313 p.
Identifiers
URN: urn:nbn:se:su:diva-31155DOI: 10.1111/j.1523-1739.2009.01207.xOAI: oai:DiVA.org:su-31155DiVA: diva2:275575
Available from: 2009-12-07 Created: 2009-11-05 Last updated: 2017-12-12Bibliographically approved

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Peterson, Garry
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Stockholm Resilience CentreDepartment of Physical Geography and Quaternary Geology
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CiteExportLink to record
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