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Improving the visual communication of environmental model projections

Environmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated unc...

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Autores principales: Bannister, Hayley J., Blackwell, Paul G., Hyder, Kieran, Webb, Thomas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476535/
https://www.ncbi.nlm.nih.gov/pubmed/34580337
http://dx.doi.org/10.1038/s41598-021-98290-4
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author Bannister, Hayley J.
Blackwell, Paul G.
Hyder, Kieran
Webb, Thomas J.
author_facet Bannister, Hayley J.
Blackwell, Paul G.
Hyder, Kieran
Webb, Thomas J.
author_sort Bannister, Hayley J.
collection PubMed
description Environmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated uncertainty complicates communication of outputs, affecting both the effectiveness of management decisions and, sometimes, public trust in scientific evidence itself. Effective data visualisation can play a key role in accurately communicating such complex outcomes, but we lack an evidence base to enable us to design them to be visually appealing whilst also effectively communicating accurate information. To address this, we conducted a survey to identify the most effective methods for visually communicating the outputs of an ensemble of global climate models. We measured the accuracy, confidence, and ease with which the survey participants were able to interpret 10 visualisations depicting the same set of model outputs in different ways, as well as their preferences. Dot and box plots outperformed all other visualisations, heat maps and radar plots were comparatively ineffective, while our infographic scored highly for visual appeal but lacked information necessary for accurate interpretation. We provide a set of guidelines for visually communicating the outputs of MMEs across a wide range of research areas, aimed at maximising the impact of the visualisations, whilst minimizing the potential for misinterpretations, increasing the societal impact of the models and ensuring they are well-placed to support management in the future.
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spelling pubmed-84765352021-09-29 Improving the visual communication of environmental model projections Bannister, Hayley J. Blackwell, Paul G. Hyder, Kieran Webb, Thomas J. Sci Rep Article Environmental and ecosystem models can help to guide management of changing natural systems by projecting alternative future states under a common set of scenarios. Combining contrasting models into multi-model ensembles (MMEs) can improve the skill and reliability of projections, but associated uncertainty complicates communication of outputs, affecting both the effectiveness of management decisions and, sometimes, public trust in scientific evidence itself. Effective data visualisation can play a key role in accurately communicating such complex outcomes, but we lack an evidence base to enable us to design them to be visually appealing whilst also effectively communicating accurate information. To address this, we conducted a survey to identify the most effective methods for visually communicating the outputs of an ensemble of global climate models. We measured the accuracy, confidence, and ease with which the survey participants were able to interpret 10 visualisations depicting the same set of model outputs in different ways, as well as their preferences. Dot and box plots outperformed all other visualisations, heat maps and radar plots were comparatively ineffective, while our infographic scored highly for visual appeal but lacked information necessary for accurate interpretation. We provide a set of guidelines for visually communicating the outputs of MMEs across a wide range of research areas, aimed at maximising the impact of the visualisations, whilst minimizing the potential for misinterpretations, increasing the societal impact of the models and ensuring they are well-placed to support management in the future. Nature Publishing Group UK 2021-09-27 /pmc/articles/PMC8476535/ /pubmed/34580337 http://dx.doi.org/10.1038/s41598-021-98290-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Bannister, Hayley J.
Blackwell, Paul G.
Hyder, Kieran
Webb, Thomas J.
Improving the visual communication of environmental model projections
title Improving the visual communication of environmental model projections
title_full Improving the visual communication of environmental model projections
title_fullStr Improving the visual communication of environmental model projections
title_full_unstemmed Improving the visual communication of environmental model projections
title_short Improving the visual communication of environmental model projections
title_sort improving the visual communication of environmental model projections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476535/
https://www.ncbi.nlm.nih.gov/pubmed/34580337
http://dx.doi.org/10.1038/s41598-021-98290-4
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