Adaptive Analysis of Locally Complex Systems in a Globally Complex World

Zambezi Valley agro-ecosystems are environmentally, economically, and institutionally variable. This variability means that it is not possible to measure everything necessary to develop a predictive understanding of them. In particular, because people and their environments are constantly changing,...

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Main Author: Timothy Lynam
Format: Article
Language:English
Published: Resilience Alliance 1999-12-01
Series:Ecology and Society
Subjects:
Online Access:http://www.ecologyandsociety.org/vol3/iss2/art13/
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spelling doaj-4f4e58357a734c18acccb8cb3419959b2020-11-24T21:03:04ZengResilience AllianceEcology and Society1708-30871999-12-01321310.5751/ES-00152-030213152Adaptive Analysis of Locally Complex Systems in a Globally Complex WorldTimothy Lynam0Tropical Resource Ecology Program, University of ZimbabweZambezi Valley agro-ecosystems are environmentally, economically, and institutionally variable. This variability means that it is not possible to measure everything necessary to develop a predictive understanding of them. In particular, because people and their environments are constantly changing, what was measured yesterday may change by tomorrow. Here, I describe elements of the approach that I have developed to address this problem. Called DAAWN, for Detail as and When Needed, the approach advocates an iterative and multiscaled methodology in which we first capture as broad an understanding of the system as possible and then use awareness developed at this scale to identify where to focus subsequent, more detailed, investigations. Because we cannot hope to measure or monitor everything in these complex and adaptive agro-ecosystems, the approach requires us to make judicious use of all available knowledge about the agro-ecosystem. The DAAWN approach is rooted in systems theory, but is tempered by systems and problems where boundaries are not clearly defined, where nonlinearities are the norm, and where structural and functional change is the order of the day. I describe a few of the most important data collection tools and methods that were developed to record the knowledge of local people and to observe, monitor, and measure changes in their resources. Of particular importance is the tool that I call a "spidergram." This tool, which I used extensively with village informants, symbolizes the DAAWN approach and was a major stimulus for its development. Simulation models provide another very important tool; here, I offer some examples of spatially explicit, multi-agent models. Some key findings of the research on Zambezi Valley agro-ecosystems are also briefly presented.http://www.ecologyandsociety.org/vol3/iss2/art13/comples adaptive systemshousehold and resource economicslivelihood strategiesmodelingmulti-agent simulation modelsnatural resource useparticipatory systems analysissouthern Africaspidergrams
collection DOAJ
language English
format Article
sources DOAJ
author Timothy Lynam
spellingShingle Timothy Lynam
Adaptive Analysis of Locally Complex Systems in a Globally Complex World
Ecology and Society
comples adaptive systems
household and resource economics
livelihood strategies
modeling
multi-agent simulation models
natural resource use
participatory systems analysis
southern Africa
spidergrams
author_facet Timothy Lynam
author_sort Timothy Lynam
title Adaptive Analysis of Locally Complex Systems in a Globally Complex World
title_short Adaptive Analysis of Locally Complex Systems in a Globally Complex World
title_full Adaptive Analysis of Locally Complex Systems in a Globally Complex World
title_fullStr Adaptive Analysis of Locally Complex Systems in a Globally Complex World
title_full_unstemmed Adaptive Analysis of Locally Complex Systems in a Globally Complex World
title_sort adaptive analysis of locally complex systems in a globally complex world
publisher Resilience Alliance
series Ecology and Society
issn 1708-3087
publishDate 1999-12-01
description Zambezi Valley agro-ecosystems are environmentally, economically, and institutionally variable. This variability means that it is not possible to measure everything necessary to develop a predictive understanding of them. In particular, because people and their environments are constantly changing, what was measured yesterday may change by tomorrow. Here, I describe elements of the approach that I have developed to address this problem. Called DAAWN, for Detail as and When Needed, the approach advocates an iterative and multiscaled methodology in which we first capture as broad an understanding of the system as possible and then use awareness developed at this scale to identify where to focus subsequent, more detailed, investigations. Because we cannot hope to measure or monitor everything in these complex and adaptive agro-ecosystems, the approach requires us to make judicious use of all available knowledge about the agro-ecosystem. The DAAWN approach is rooted in systems theory, but is tempered by systems and problems where boundaries are not clearly defined, where nonlinearities are the norm, and where structural and functional change is the order of the day. I describe a few of the most important data collection tools and methods that were developed to record the knowledge of local people and to observe, monitor, and measure changes in their resources. Of particular importance is the tool that I call a "spidergram." This tool, which I used extensively with village informants, symbolizes the DAAWN approach and was a major stimulus for its development. Simulation models provide another very important tool; here, I offer some examples of spatially explicit, multi-agent models. Some key findings of the research on Zambezi Valley agro-ecosystems are also briefly presented.
topic comples adaptive systems
household and resource economics
livelihood strategies
modeling
multi-agent simulation models
natural resource use
participatory systems analysis
southern Africa
spidergrams
url http://www.ecologyandsociety.org/vol3/iss2/art13/
work_keys_str_mv AT timothylynam adaptiveanalysisoflocallycomplexsystemsinagloballycomplexworld
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