2020
DOI: 10.1098/rsos.201511
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Uncertainty in and around biophysical modelling: insights from interdisciplinary research on agricultural digitalization

Abstract: Agricultural digitalization is providing growing amounts of real-time digital data. Biophysical simulation models can help interpret these data. However, these models are subject to complex uncertainties, which has prompted calls for interdisciplinary research to better understand and communicate modelling uncertainties and their impact on decision-making. This article develops two corresponding insights from an interdisciplinary project in a New Zealand agricultural research organization. First, we expand on … Show more

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Cited by 7 publications
(10 citation statements)
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“…These experiences show that reflexivity is needed throughout R&D programmes to achieve more RI outcomes. Both digital agtech programmes included projects where teams came to realise the value of interdisciplinary research and associated prompts for reflexive engagements with underlying assumptions and disciplinary limitations, despite initial time requirements (Espig et al., 2020; Fleming et al., 2021; Jakku et al., 2022). In addition to fostering an appreciation for reflexivity, relevant activities need to be adequately resourced and incentivised as core elements of R&D programmes.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…These experiences show that reflexivity is needed throughout R&D programmes to achieve more RI outcomes. Both digital agtech programmes included projects where teams came to realise the value of interdisciplinary research and associated prompts for reflexive engagements with underlying assumptions and disciplinary limitations, despite initial time requirements (Espig et al., 2020; Fleming et al., 2021; Jakku et al., 2022). In addition to fostering an appreciation for reflexivity, relevant activities need to be adequately resourced and incentivised as core elements of R&D programmes.…”
Section: Resultsmentioning
confidence: 99%
“…After two years of proof‐of‐concept research that started in early 2019, NZBIDA is now considered a flagship integrative programme for developing digital agtech and new research approaches. Project teams have, for instance, trialled agile work principles, co‐designed activities with end users, and implemented inter‐/transdisciplinary approaches (Espig et al., 2020). These activities are aimed at realising the programme's ten to twenty‐year vision, as introduced by the programme leader in a PowerPoint presentation during the fourth workshop: The power of digital technologies is harnessed to enable the transformation of New Zealand food systems to meet the challenges the world faces by diversifying land use, creating new ways of doing business and new ways of adding value to products we produce.…”
Section: Resultsmentioning
confidence: 99%
“…That can be attributed to what Wynne (1992) and Espig et al. (2020) call ignorance and indeterminacy. Simply put, the dimension of ignorance refers to the unknown unknowns: advisors’ inability to be aware of what they do not know and how these knowledge gaps can lead to unintended impacts.…”
Section: Discussionmentioning
confidence: 99%
“…Anticipation, in this vein, is narrowed to the impacts that Agriculture 4.0 technologies might have on farmers, whereas there is considerable difficulty in predicting what the societal impacts of Agriculture 4.0 will be ahead of time. That can be attributed to what Wynne (1992) and Espig et al (2020) call ignorance and indeterminacy. Simply put, the dimension of ignorance refers to the unknown unknowns: advisors' inability to be aware of what they do not know and how these knowledge gaps can lead to unintended impacts.…”
Section: Redefining Advisors' Responsible Professionalismmentioning
confidence: 99%
“…If decisions are made without adequate acknowledgment of uncertainty, the chances of unanticipated outcomes are either understated or overlooked. Quantitative and qualitative metrics of uncertainty also improve confidence in the validity of the information, and provide evidence for the underlying quality of the model (Espig, Finlay‐Smits, Meenken, Wheeler & Sharifi, 2020; Mastrandrea et al., 2010). Thus, the facility to report the degree of certainty in findings in way that exploits all available information is beneficial for informed decision making.…”
Section: Introductionmentioning
confidence: 99%