Mind the mind: How to effectively communicate about cognition in social–ecological systems research

Bercht, Anna Lena; Wijermans, Nanda

doi:10.1007/s13280-018-1099-7

Cited by 4 publications

(3 citation statements)

References 58 publications

(67 reference statements)

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“…The frequency of different keywords in each cluster is presented using a word cloud (Fig. 2 ; Bercht and Wijermans 2019 ; Anand and Radhakrishna 2020 ).…”

Section: Methodsmentioning

confidence: 99%

What determines the success and failure of environmental crowdfunding?

Kubo

Veríssimo

Uryu

et al. 2021

Ambio

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Online crowdfunding can help address the perennial financial shortfalls in environmental conservation and management. Although many online crowdfunding campaigns fail to collect any funds due to not achieving their targets, little is known about what drives success. To address this knowledge gap, we applied a mixed-methods approach to data from 473 successful and failed campaigns hosted on the online crowdfunding platform Readyfor. We found that fundraising performance varied by topic, with campaigns on pet animal management outperforming those focussed on landscape management and sustainable use. We also found that marketing strategies associated with online findability and increased reach through social networks, increased fundraising success. However, the existence of other environmental campaigns running simultaneously, reduced the chance of success, which implies that the selecting popular topics does not always increase the likelihood of success due to increased competition. Wider applications of marketing could enhance the ability of environmental crowdfunding campaigns to raise funds.

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“…The frequency of different keywords in each cluster is presented using a word cloud (Fig. 2 ; Bercht and Wijermans 2019 ; Anand and Radhakrishna 2020 ).…”

Section: Methodsmentioning

confidence: 99%

What determines the success and failure of environmental crowdfunding?

Kubo

Veríssimo

Uryu

et al. 2021

Ambio

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“…There is an urgent need for research and development of tools for the step between a mental model or suite of mental models and a combined mathematical model [1]. Bercht and Wijermans [65] describe how unstated and unreconciled mental models among researchers may hamper successful collaboration. As with judgments, the development of ideas of cause and effect, assumptions and modelling structure/ tools should be done independently and iteratively, to pit diversity of thought against individual bias.…”

Section: Discussionmentioning

confidence: 99%

Eliciting Model Structures for Multivariate Probabilistic Risk Analysis

Burgman

Layman²,

French

2021

Front. Appl. Math. Stat.

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Notionally objective probabilistic risk models, built around ideas of cause and effect, are used to predict impacts and evaluate trade-offs. In this paper, we focus on the use of expert judgement to fill gaps left by insufficient data and understanding. Psychological and contextual phenomena such as anchoring, availability bias, confirmation bias and overconfidence are pervasive and have powerful effects on individual judgements. Research across a range of fields has found that groups have access to more diverse information and ways of thinking about problems, and routinely outperform credentialled individuals on judgement and prediction tasks. In structured group elicitation, individuals make initial independent judgements, opinions are respected, participants consider the judgements made by others, and they may have the opportunity to reconsider and revise their initial estimates. Estimates may be aggregated using behavioural, mathematical or combined approaches. In contrast, mathematical modelers have been slower to accept that the host of psychological frailties and contextual biases that afflict judgements about parameters and events may also influence model assumptions and structures. Few, if any, quantitative risk analyses embrace sources of uncertainty comprehensively. However, several recent innovations aim to anticipate behavioural and social biases in model construction and to mitigate their effects. In this paper, we outline approaches to eliciting and combining alternative ideas of cause and effect. We discuss the translation of ideas into equations and assumptions, assessing the potential for psychological and social factors to affect the construction of models. We outline the strengths and weaknesses of recent advances in structured, group-based model construction that may accommodate a variety of understandings about cause and effect.

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“…Change in urban form, through land-use change, also has transportation implications and can significantly influence travel demand (Hankey and Marshall 2010). Comprehensive social-ecological assessment of urban land uses and GHG emissions thus needs to incorporate and couple multiple economic, land use, transportation, climate, and other environmental factors (Bercht and Wijermans 2019;Carrière 2019;Ehrich et al 2019;Valencia et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

Pan

Page

et al. 2019

Ambio

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Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social-ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social-ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers. Keywords Climate change Á Greenhouse gas emissions Á Land-use change Á Planning support system Á Social-ecological system Á Stockholm Electronic supplementary material The online version of this article (

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Mind the mind: How to effectively communicate about cognition in social–ecological systems research

Cited by 4 publications

References 58 publications

What determines the success and failure of environmental crowdfunding?

What determines the success and failure of environmental crowdfunding?

Eliciting Model Structures for Multivariate Probabilistic Risk Analysis

Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

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