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Human Ecology Review
Article . 2021 . Peer-reviewed
Data sources: Crossref
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Understanding Social–Ecological Systems using Loop Analysis

Authors: Marco Scotti; Daniel Filipe Da Silva Pereira; Antonio Bodini;

Understanding Social–Ecological Systems using Loop Analysis

Abstract

The sustainable management of social–ecological systems (SESs) requires that we understand the complex structure of relationships and feedbacks among ecosystem components and socioeconomic entities. Therefore, the construction and analysis of models integrating ecological and human actors is crucial for describing the functioning of SESs, and qualitative modeling represents an ideal tool since it allows studying dependencies among variables of diverse types. In particular, the qualitative technique of loop analysis yields predictions about how a system’s variables respond to stress factors. Different interaction types, scarce information about functional relationships among variables, and uncertainties in the values of the parameters are the rule rather than exceptions when studying SESs. Accordingly, loop analysis seems to be perfectly suitable to investigate them. Here, we introduce the key aspects of loop analysis, discuss its applications to SESs, and suggest it enables making the first steps toward the integration of the three dimensions of sustainability.

Countries
Germany, Italy
Keywords

social-ecological systems, networks, qualitative modeling, complex systems, sustainability, 004

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
gold