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  Upscaling in socio-environmental systems modelling: Current challenges, promising strategies and insights from ecology

Dressler, G., Groeneveld, J., Hetzer, J., Janischewski, A., Nolzen, H., Rödig, E., Schwarz, N., Taubert, F., Thober, J., Will, M., Williams, T., Wirth, S. B., Müller, B. (2022): Upscaling in socio-environmental systems modelling: Current challenges, promising strategies and insights from ecology. - Socio-Environmental Systems Modelling, 4, 18112.
https://doi.org/10.18174/sesmo.18112

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 Creators:
Dressler, Gunnar1, Author
Groeneveld, Jürgen1, Author
Hetzer, Jessica1, Author
Janischewski, Anja1, Author
Nolzen, Henning1, Author
Rödig, Edna1, Author
Schwarz, Nina1, Author
Taubert, Franziska1, Author
Thober, Jule1, Author
Will, Meike1, Author
Williams, Tim1, Author
Wirth, Stephen Björn2, Author              
Müller, Birgit1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Sustainability challenges in socio-environmental systems (SES) are inherently multiscale, with global-level changes emerging from socio-environmental processes that operate across different spatial, temporal, and organisational scales. Models of SES therefore need to incorporate multiple scales, which requires sound methodologies for transferring information between scales. Due to the increasing global connectivity of SES, upscaling – increasing the extent or decreasing the resolution of a modelling study – is becoming progressively more important. However, upscaling in SES models has received less attention than in other fields (e.g., ecology or hydrology) and therefore remains a pressing challenge. To advance the understanding of upscaling in SES, we take three steps. First, we review existing upscaling approaches in SES as well as other disciplines. Second, we identify four main challenges that are particularly relevant to upscaling in SES: 1) heterogeneity, 2) interactions, 3) learning and adaptation, and 4) emergent phenomena. Third, we present an approach that facilitates the transfer of existing upscaling methods to SES, using two good practice examples from ecology. To describe and compare these methods, we propose a scheme of five general upscaling strategies. This scheme builds upon and unifies existing schemes and provides a standardised way to classify and represent existing as well as new upscaling methods. We demonstrate how the scheme can help to transparently present upscaling methods and uncover scaling assumptions, as well as to identify limits for the transfer of upscaling methods. We finish by pointing out research avenues on upscaling in SES to address the identified upscaling challenges.

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Language(s): eng - English
 Dates: 2022-08-012022-08-01
 Publication Status: Finally published
 Pages: 25
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.18174/sesmo.18112
MDB-ID: No data to archive
PIKDOMAIN: RD2 - Climate Resilience
Organisational keyword: RD2 - Climate Resilience
Research topic keyword: Ecosystems
Model / method: Qualitative Methods
Working Group: Land Use and Resilience
OATYPE: Gold Open Access
 Degree: -

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Title: Socio-Environmental Systems Modelling
Source Genre: Journal, other, oa
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Pages: - Volume / Issue: 4 Sequence Number: 18112 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/2663-3027
Publisher: International Environmental Modelling and Software Society