Author
Listed:
- Nírvia Ravena
- Norbert Fenzl
- Rômulo Magalhães de Souza
- Voyner Ravena Cañete
- Roberto Célio Limão de Oliveira
- Cleyton Alves Candeira Pimentel
Abstract
The impacts of climate change are becoming more severe and can only be addressed through governance that spans from local to global levels. To enhance adaptation and response strategies, we need to integrate the knowledge of local communities and improve institutional and state capacity. In the Amazon Basin, current plans for adaptation and response only consider a global perspective, without any input from local communities. By including the region-specific knowledge of these communities, we can better identify the risks related to climate change. The research aimed to answer the question of how to integrate these specificities in an operational risk governance model. We developed an operational risk governance model for Amazon (R-GOMAM) that explores cross-scale interplay and risk identification related to climate change. It provides a comprehensive perspective of risk governance across different scales. A combination of methods was used to integrate the quantitative and qualitative dimensions of data collection and analysis. Additionally, we applied fuzzy logic, to synthesize the cross-scale interplay model. The model was able to account for all dimensions of the Amazon Basin countries, including dryland agriculture, floodplain agriculture, vegetable extraction, fishing, animal breeding, water quality, and household infrastructure. It considered the complexity and uncertainty of risk governance, identified hazard scenarios, and determined the level of risk in the region. Our evaluation of institutional and state capacity in the Purus River Basin revealed insufficient regulations and institutional mechanisms to address climate change risks. Our model identifies different scenarios of hazards and determines the degree of risk in the Amazon Basin countries. Prior models for Brazilian regions overlooked local differences in institutional and state capacities. Our study fills this gap, serving as a supplement for assessing climate change effects in not just Amazonia but other regions as well.
Suggested Citation
Nírvia Ravena & Norbert Fenzl & Rômulo Magalhães de Souza & Voyner Ravena Cañete & Roberto Célio Limão de Oliveira & Cleyton Alves Candeira Pimentel, 2024.
"Assessing climate change scenarios in the Amazon Basin: a risk governance model,"
Journal of Risk Research, Taylor & Francis Journals, vol. 27(2), pages 167-184, February.
Handle:
RePEc:taf:jriskr:v:27:y:2024:i:2:p:167-184
DOI: 10.1080/13669877.2024.2315989
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:jriskr:v:27:y:2024:i:2:p:167-184. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJRR20 .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.