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Managing coupled human and natural systems (CHANS) : the case of water
RISE Research Institutes of Sweden, Built Environment, Energy and Resources. SLU, Sweden.ORCID iD: 0000-0002-6323-1397
2022 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Many sustainability challenges of the 21st century are the result of poor management of coupled human and natural systems (CHANS). Limited understanding of the mechanisms that give rise to complex dynamics in CHANS has contributed to overexploitation and degradation of water and other natural resources around the globe, leading to unintended consequences of well-intentioned policies. This raises the question of whether the tools and methods currently used in environmental management and policy design meet the requirements of complex dynamic systems. In this thesis, qualitative and quantitative research approaches from the fields of systems thinking and simulation modelling were combined with the aim of improving understanding of the dynamics of CHANS, and human-water systems in particular, and developing better methods and tools to support more effective policy and management strategies in the future. The work included a systematic review, qualitative and quantitative system dynamics modelling case studies, method development, and agent-based modelling and simulation. The results showed that changes in CHANS are driven by observable and unobservable exchanges of energy, matter and information across space and time that give rise to constantly changing, nonlinear dynamics. Many contemporary tools and methods used in management and policy design are not suited to this dynamic complexity and, instead of embracing complexity, seek to reduce it by excluding structural drivers of endogenous behaviour. This can contribute to unsustainable water use and amplify impacts of climate change in coupled human and water systems. This thesis showed that system dynamics-based approaches can effectively complement conventional static management tools, to better account for dynamic complexity. By tapping into the collective intelligence of actors engaged in the system, the approaches can support more realistic models and more effective and sustainable management, leading to establishment of middle-range theories for management of CHANS.

Place, publisher, year, edition, pages
SLU , 2022. , p. 286
Series
SLU Doctoral Thesis No. 2022:70
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-62554ISBN: 978-91-8046-016-3 (print)OAI: oai:DiVA.org:ri-62554DiVA, id: diva2:1728358
Available from: 2023-01-19 Created: 2023-01-18 Last updated: 2023-05-09Bibliographically approved

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Nicolaidis Lindqvist, Andreas

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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