Navigating causal reasoning in sustainability science DOI Open Access
Maja Schlüter‬, Tilman Hertz, María Mancilla García

et al.

Published: Nov. 16, 2023

Sustainability researchers aim to generate knowledge about causes of societal problems and possiblesolutions. Given the multidisciplinary nature field complexity problems, thecausal reasoning that underlies these activities may vary significantly across studies researchapproaches. Causal involves many assumptions, e.g. what aspects a systemmatter, counts as evidence for causal claim or biases data. These assumptionsinfluence emerging understandings, yet they are rarely made explicit. We clarify when andhow manifests during research process how it is shaped by goals astudy underlying idea causation. Drawing on philosophy science recent discussionsin social natural sciences, we identify four fundamental ideas illustrate comparethem through examples. Awareness differences’ influence helps betterevaluate solutions synergies strengthen claims complexsustainability problems.

Language: Английский

Uncovering the Dynamics of Multi‐Sector Impacts of Hydrological Extremes: A Methods Overview DOI Creative Commons
Mariana Madruga de Brito, Jan Sodoge, Alexander Fekete

et al.

Earth s Future, Journal Year: 2024, Volume and Issue: 12(1)

Published: Jan. 1, 2024

Abstract Hydrological extremes, such as droughts and floods, can trigger a complex web of compound cascading impacts (CCI) due to interdependencies between coupled natural social systems. However, current decision‐making processes typically only consider one impact disaster event at time, ignoring causal chains, feedback loops, conditional dependencies impacts. Analyses capturing these patterns across space time are thus needed inform effective adaptation planning. This perspective paper aims bridge this critical gap by presenting methods for assessing the dynamics multi‐sector CCI hydrological extremes. We discuss existing challenges, good practices, potential ways forward. Rather than pursuing single methodological approach, we advocate pluralism. see complementary or even convergent roles analyses based on quantitative (e.g., data‐mining, systems modeling) qualitative mental models, storylines). The data‐driven knowledge‐driven provided here serve useful starting point understanding both high‐frequency low‐likelihood but high‐impact CCI. With perspective, hope foster research improve development strategies reducing risk

Language: Английский

Citations

14
Navigating causal reasoning in sustainability science DOI Creative Commons
Maja Schlüter‬, Tilman Hertz, María Mancilla García

et al.

AMBIO, Journal Year: 2024, Volume and Issue: 53(11), P. 1618 - 1631

Published: July 17, 2024

Abstract When reasoning about causes of sustainability problems and possible solutions, scientists rely on disciplinary-based understanding cause–effect relations. These disciplinary assumptions enable constrain how causal knowledge is generated, yet they are rarely made explicit. In a multidisciplinary field like science, lack differences in impedes our ability to address complex problems. To support navigating the diversity reasoning, we articulate when during research process researchers engage discuss four common ideas causation that direct it. This articulation provides guidance for make their own choices transparent interpret other researchers’ approaches. Understanding claims justified enables evaluate claims, build collaborations across disciplines, assess whether proposed solutions suitable given problem.

Language: Английский

Citations

7
Policy and market forces delay real estate price declines on the US coast DOI Creative Commons
D. E. McNamara, Martin D. Smith,

Zachary Williams

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: March 12, 2024

Despite increasing risks from sea-level rise (SLR) and storms, US coastal communities continue to attract relatively high-income residents, property values rise. To understand this seeming paradox explore policy responses, we develop the Coastal Home Ownership Model (C-HOM) analyze long-term evolution of real estate markets. C-HOM incorporates changing physical attributes coast, economic these attributes, dynamic associated with storms flooding. Resident owners, renters, non-resident investors jointly determine choices that influence coast. In coupled system, find subsidies for management, such as beach nourishment, tax advantages stable or outside zone all dampen effects SLR on values. The effects, however, are temporary only delay precipitous declines total inundation approaches. By removing subsidies, prices would more accurately reflect but also trigger gentrification, owners enter market self-finance nourishment. Our results suggest a tradeoff between slowing demographic transitions in allowing markets adjust smoothly climate change.

Language: Английский

Citations

6
Theory for and from agent-based modelling: Insights from a virtual special issue and a vision DOI Creative Commons
Volker Grimm, Uta Berger, Matthias Meyer

et al.

Environmental Modelling & Software, Journal Year: 2024, Volume and Issue: 178, P. 106088 - 106088

Published: May 21, 2024

The Virtual Special Issue "Agents for Theory" discusses theory development using agent-based models (ABMs). six contributions focus on how the word "theory" is used in ABM literature, reviews of ABMs should be conducted to gain general insights, even conceptualisation can help transform heuristic theories into scientific ones, context-dependent choice decision better justified, reusable building blocks (RBBs) could support development, and a modular framework RBBs identify solutions. Overall, making that go system dynamics come out are interrelated, so micro-macro perspective attempt reproduce patterns at both levels simultaneously way forward. Theory requires clearer communication common language, reference patterns, more detailed model analysis testing.

Language: Английский

Citations

5
Quantifying the importance of farmers' behavioral factors in ex-ante assessments of policies supporting sustainable farming practices DOI Creative Commons
Robert Huber, Cordelia Kreft,

Karin Späti

et al.

Ecological Economics, Journal Year: 2024, Volume and Issue: 224, P. 108303 - 108303

Published: July 31, 2024

Behavioral factors have been identified to determine farmers' uptake of the adoption sustainable farming practices. However, coherent consideration empirically behavioral in ex-ante model-based policy assessments is still rare. This study presents an agent-based modelling framework that integrates empirical data on cognitive, social, and dispositional characteristics. Using this framework, we test quantify impact including agricultural policies aimed at promoting Thereby, apply same compare effectiveness results-based payments for climate change mitigation measures precision technologies two Swiss case studies. Our results indicate cognitive (e.g., reluctance change) reduce practices by 20–70% compared simulations using income maximization as underlying decision-making concept. In contrast, social can increase up 40%. We conclude allows improve context addition, these approaches highlight importance instruments complement traditional economic measures, such public support creation networks.

Language: Английский

Citations

5
Designing causal mediation analyses to quantify intermediary processes in ecology DOI Open Access
Hannah Correia, Laura E. Dee, Paul J. Ferraro

et al.

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2025, Volume and Issue: unknown

Published: March 9, 2025

Ecologists seek to understand the intermediary ecological processes through which changes in one attribute a system affect other attributes. A causal understanding of mediating is important for testing theory and developing resource management conservation strategies. Yet, quantifying effects these systems challenging, because it requires defining what we mean by "mediated effect", determining assumptions are required estimate mediation without bias, assessing whether credible study. To address challenges, scholars have made significant advances research designs analysis. Here, review ecologists. illustrate both challenges effects, use hypothetical study drought impacts on grassland productivity. With this study, show how common used ecology detect quantify may biases can be addressed alternative designs. Throughout review, highlight claims rely assumptions, different or definitions relax some assumptions. In contrast statistical not verifiable from data, so also describe procedures that assess sensitivity study's results potential violations its The analyses reviewed herein equip ecologists communicate clearly necessary valid inferences, examine using suitable experimental observational designs, will enable rigorous reproducible explanations ecology.

Language: Английский

Citations

0
Intensifying neotropical beef cattle grazing systems: Navigating complexity through modelling DOI
Raúl R. Vera, Carlos A. Ramírez-Restrepo, Idupulapati M. Rao

et al.

Agricultural Systems, Journal Year: 2025, Volume and Issue: 226, P. 104301 - 104301

Published: March 14, 2025

Language: Английский

Citations

0
Navigating the space between empirics and theory – Empirically stylized modelling for theorising social-ecological phenomena DOI Creative Commons
Maja Schlüter‬, Nanda Wijermans, Blanca González‐Mon

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106444 - 106444

Published: March 1, 2025

Language: Английский

Citations

0
Effects of systemic challenges on agricultural development systems: a systematic review of perspectives DOI Creative Commons
Enock Siankwilimba, Jacqueline Hiddlestone‐Mumford, Md Enamul Hoque

et al.

Cogent Food & Agriculture, Journal Year: 2025, Volume and Issue: 11(1)

Published: March 27, 2025

Language: Английский

Citations

0
Transdisciplinary coordination is essential for advancing agricultural modeling with machine learning DOI Creative Commons
Lily‐belle Sweet, Ioannis N. Athanasiadis,

Ron van Bree

et al.

One Earth, Journal Year: 2025, Volume and Issue: 8(4), P. 101233 - 101233

Published: April 1, 2025

Language: Английский

Citations

0