Anticipating future risk in social-ecological systems using fuzzy cognitive mapping : The case of wildfire in the Chiquitania, Bolivia
(2016) In Ecology and Society 21(4).- Abstract
Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation... (More)
Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The “Hands-off” scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The “Fire management” scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the “Fire suppression” scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decisionsupport tool and serve as a “boundary object” to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.
(Less)
- author
- Devisscher, Tahia ; Boyd, Emily LU and Malhi, Yadvinder
- organization
- publishing date
- 2016-12-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adaptation, Climate change, Complexity, Scenario, Social-ecological system, Uncertainty, Wildfire risk
- in
- Ecology and Society
- volume
- 21
- issue
- 4
- article number
- 18
- publisher
- The Resilience Alliance
- external identifiers
-
- wos:000391199400005
- scopus:85008152074
- ISSN
- 1708-3087
- DOI
- 10.5751/ES-08599-210418
- language
- English
- LU publication?
- yes
- id
- 357d92ee-849a-4cb4-94d3-27349eb12bcb
- date added to LUP
- 2017-01-13 10:53:21
- date last changed
- 2024-06-28 23:23:00
@article{357d92ee-849a-4cb4-94d3-27349eb12bcb,
abstract = {{<p>Understanding complex social-ecological systems, and anticipating how they may respond to rapid change, requires an approach that incorporates environmental, social, economic, and policy factors, usually in a context of fragmented data availability. We employed fuzzy cognitive mapping (FCM) to integrate these factors in the assessment of future wildfire risk in the Chiquitania region, Bolivia. In this region, dealing with wildfires is becoming increasingly challenging because of reinforcing feedbacks between multiple drivers. We conducted semistructured interviews and constructed different FCMs in focus groups to understand the regional dynamics of wildfire from diverse perspectives. We used FCM modelling to evaluate possible adaptation scenarios in the context of future drier climatic conditions. Scenarios also considered possible failure to respond in time to the emergent risk. This approach proved of great potential to support decision making for risk management. It helped identify key forcing variables and generate insights into potential risks and trade-offs of different strategies. The “Hands-off” scenario resulted in amplified impacts driven by intensifying trends, affecting particularly the agricultural production under drought conditions. The “Fire management” scenario, which adopted a bottom-up approach to improve controlled burning, showed less trade-offs between wildfire risk reduction and production compared with the “Fire suppression” scenario. Findings highlighted the importance of considering strategies that involve all actors who use fire, and the need to nest these strategies for a more systemic approach to manage wildfire risk. The FCM model could be used as a decisionsupport tool and serve as a “boundary object” to facilitate collaboration and integration of different perceptions of fire in the region. This approach also has the potential to inform decisions in other dynamic frontier landscapes around the world that are facing increased risk of large wildfires.</p>}},
author = {{Devisscher, Tahia and Boyd, Emily and Malhi, Yadvinder}},
issn = {{1708-3087}},
keywords = {{Adaptation; Climate change; Complexity; Scenario; Social-ecological system; Uncertainty; Wildfire risk}},
language = {{eng}},
month = {{12}},
number = {{4}},
publisher = {{The Resilience Alliance}},
series = {{Ecology and Society}},
title = {{Anticipating future risk in social-ecological systems using fuzzy cognitive mapping : The case of wildfire in the Chiquitania, Bolivia}},
url = {{http://dx.doi.org/10.5751/ES-08599-210418}},
doi = {{10.5751/ES-08599-210418}},
volume = {{21}},
year = {{2016}},
}