Measuring the effectiveness of protected area networks in reducing deforestation
Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional meth...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
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Proceedings of the National Academy of Sciences
2008
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/162342 |
| _version_ | 1855532789087076352 |
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| author | Andam, Kwaw S. Ferraro, Paul J. Pfaff, Alexander Sanchez-Azofeifa, G. Arturo Robalino, Juan A. |
| author_browse | Andam, Kwaw S. Ferraro, Paul J. Pfaff, Alexander Robalino, Juan A. Sanchez-Azofeifa, G. Arturo |
| author_facet | Andam, Kwaw S. Ferraro, Paul J. Pfaff, Alexander Sanchez-Azofeifa, G. Arturo Robalino, Juan A. |
| author_sort | Andam, Kwaw S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Rica's renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services. |
| format | Journal Article |
| id | CGSpace162342 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2008 |
| publishDateRange | 2008 |
| publishDateSort | 2008 |
| publisher | Proceedings of the National Academy of Sciences |
| publisherStr | Proceedings of the National Academy of Sciences |
| record_format | dspace |
| spelling | CGSpace1623422025-01-17T15:54:40Z Measuring the effectiveness of protected area networks in reducing deforestation Andam, Kwaw S. Ferraro, Paul J. Pfaff, Alexander Sanchez-Azofeifa, G. Arturo Robalino, Juan A. deforestation resource conservation quantitative analysis Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Rica's renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services. 2008-10-21 2024-11-21T10:02:28Z 2024-11-21T10:02:28Z Journal Article https://hdl.handle.net/10568/162342 en Limited Access Proceedings of the National Academy of Sciences Andam, Kwaw S.; Ferraro, Paul J.; Pfaff, Alexander; Sanchez-Azofeifa, G. Arturo; and Robalino, Juan A. 2008. Measuring the effectiveness of protected area networks in reducing deforestation. Proceedings of the National Academy of Sciences of the United States of America 105(42): 16089-16094. https://doi.org/10.1073/pnas.0800437105 |
| spellingShingle | deforestation resource conservation quantitative analysis Andam, Kwaw S. Ferraro, Paul J. Pfaff, Alexander Sanchez-Azofeifa, G. Arturo Robalino, Juan A. Measuring the effectiveness of protected area networks in reducing deforestation |
| title | Measuring the effectiveness of protected area networks in reducing deforestation |
| title_full | Measuring the effectiveness of protected area networks in reducing deforestation |
| title_fullStr | Measuring the effectiveness of protected area networks in reducing deforestation |
| title_full_unstemmed | Measuring the effectiveness of protected area networks in reducing deforestation |
| title_short | Measuring the effectiveness of protected area networks in reducing deforestation |
| title_sort | measuring the effectiveness of protected area networks in reducing deforestation |
| topic | deforestation resource conservation quantitative analysis |
| url | https://hdl.handle.net/10568/162342 |
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