Integrated modelling of social-ecological systems for climate change adaptation

Giupponi, Carlo; Ausseil, Anne-Gäelle; Balbi, Stefano; Cian, Fabio; Fekete, Alexander; Gain, Animesh K.; Essenfelder, Arthur H.; Martínez‐López, Javier; Mojtahed, Vahid; Relvas, Hélder; Villa, Ferdinando

doi:10.18174/sesmo.18161

Cited by 4 publications

(6 citation statements)

References 127 publications

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“…However, ABMs are also viewed with scepticism by many researchers. Giupponi et al (2022) describe four main common concerns about land system ABMs: 1) they are excessively complicated for anything except specific, small-scale studies; 2) they have not generated transferrable modelling frameworks that can be applied by different researchers to different cases; 3) they are often complex and poorly-described 'black box' models, which are therefore hard to interpret or re-use; and 4) they are difficult to empirically validate. These concerns are widely held, and often expressed in reductionist form with reference to the 'YAAWN syndrome' (Yet Another Agent-based model … Whatever … Nevermind …) (O'Sullivan et al, 2016); originally a call for more coherent development across applications, including through contributions to general theoretical insights, that has in some cases devolved towards an arbitrary dismissal of ABM research.…”

Section: The Special Case Of Agent-based Models?mentioning

confidence: 99%

Assessing the quality of land system models: moving from valibration to evaludation

Brown

Millington

Rounsevell

2023

SESMO

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Reviews suggest that evaluation of land system models is largely inadequate, with undue reliance on a vague concept of validation. Efforts to improve and standardise evaluation practices have so far had limited effect. In this article we examine the issues surrounding land system model evaluation and consider the relevance of the TRACE framework for environmental model documentation. In doing so, we discuss the application of a comprehensive range of evaluation procedures to existing models, and the value of each specific procedure. We develop a tiered checklist for going beyond what seems to be a common practice of ‘valibration’ (the repeated variation of model parameter values to achieve agreement with data) to achieving ‘evaludation’ (the rigorous, broad-based assessment of model quality and validity). We propose the Land Use Change – TRACE (LUC-TRACE) model evaludation protocol and argue that engagement with a comprehensive protocol of this kind (even if not this particular one) is valuable in ensuring that land system model results are interpreted appropriately. We also suggest that the main benefit of such formalised structures is to assist the process of critical thinking about model utility, and that the variety of legitimate modelling approaches precludes universal tests of whether a model is ‘valid’. Evaludation is therefore a detailed and subjective process requiring the sustained intellectual engagement of model developers and users.

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Section: The Special Case Of Agent-based Models?mentioning

confidence: 99%

Assessing the quality of land system models: moving from valibration to evaludation

Brown

Millington

Rounsevell

2023

SESMO

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“…Agent-based modeling effectively present clear opportunities for SES modeling and help to address some of the main weaknesses of the various categories of models described in Schulze et al [13] and Giupponi et al [2], particularly with respect to the simulation of individual and social behavior and their ability to provide a descriptive and generative representation of the simulated system along the four dimensions briefly described below (loosely based on Giupponi et al [2]).…”

Section: Abm and Ses Modelingmentioning

confidence: 99%

“…The potential of ABM is thus clear for representing the social, heterogeneity, and interaction dimensions of SES, and indeed is the approach of choice for the majority of researchers faced with this need [2], but considerable methodological challenges remain, in particular, as will be seen in this review, those related to the explicit representation of scales and levels of abstraction, absent from the classical meta-model of agent-based modeling [20].…”

Section: The Fourth Dimension Deals With the Representation Of Organi...mentioning

confidence: 99%

“…In other words, while zooming in, the model will (1) call a transition function (defined by modelers) over the current level, (2) give this result to initialize the new level, then (3) destroy the previous level now unused. The system coherence over levels is insured by modelers with the transition function chosen.…”

Section: Zoom Problematic Faced In Sesmentioning

confidence: 99%

“…This is where the concept of a social-environmental system (or socio-ecological system), SES, comes in. It is defined as a complex dynamic system that includes people and nature and is continually changing in response to internal or external pressures [2]. Pressures can result from the behavior of their social (e.g., demographic changes) and ecological (e.g., climate fluctuations) components, or, more usually, from a combination of both (e.g., human-induced climate change).…”

Section: Introduction Socio-environmental Systemsmentioning

confidence: 99%

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Handling multiple levels in agent-based models of complex socio-environmental systems: A comprehensive review

Brugière

Nguyen-Ngoc

Drogoul

2022

Front. Appl. Math. Stat.

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Agent-based modeling (ABM) has been successfully used, since its emergence in the 1990s, to model and simulate the dynamics at work in complex socio-environmental systems, in many domains and applications where interactions between people and their environments give rise to emergent phenomena that are difficult to study otherwise (urban planning, land-use change, adaptation to environmental changes, biodiversity protection in socio-ecosystems, environmental pollution control, etc.). The inclusion of multiple levels of analysis, abstraction, and representation in these models, however, is much more recent and is still the subject of many proposals and discussions within a relatively informal field, Multilevel Agent-Based Modeling (ML-ABM), which is most often presented as an approach that extends the classical ABM paradigm to include multilevel concepts. Over the past decade, ML-ABM has been increasingly adopted and explored by researchers as an effective paradigm for framing and defining the mechanisms underlying multilevel dynamics. However, due to the youth of the field, no single definition, methodology, or tool unifies studies in this rapidly expanding area. This review will begin with an introduction to socio-environmental systems (SES) and the challenges that modeling approaches face in representing them properly, especially regarding the complexity of human behaviors and organizations. ABM presents opportunities for modeling SESs with respect to these challenges, including the simulation of individual and social behavior and their ability to provide a descriptive and generative representation of the simulated system. However, ABM is limited in its ability to represent levels and scales, as these concepts are absent from the classical ABM metamodel. A complete review of the ML-ABM literature will be carried out, structured around a continuum that emerged during the review: that of the distribution of behaviors (and thus, from a software engineering perspective, of control) across the levels, from approaches that allow only one level to be active at a time, to approaches that rely on simultaneous activity and feedback loops between several levels. Different design choices will, thus, be presented to meet the different needs of multi-level representation, focusing on the interest on modelers and the strengths and limitations of each. In particular, we will highlight a limitation shared by all the reviewed approaches, namely their inability to represent several parallel hierarchies of levels and their interactions, a capability that appears more and more crucial to finely represent social behaviors in SES. A new perspective on the interest that the AGR approach could represent to allow this representation of hierarchies allows us to conclude on the research perspectives are still open.

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