Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S10 2TN, UK.
School of Mathematics and Statistics, University of Sheffield, Sheffield, UK.
Sci Rep. 2021 Sep 27;11(1):19157. doi: 10.1038/s41598-021-98290-4.
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.
环境和生态系统模型可以通过在一组共同的情景下预测替代的未来状态，帮助指导不断变化的自然系统的管理。将对比鲜明的模型组合成多模型集合（MME）可以提高预测的技能和可靠性，但相关的不确定性使输出的沟通变得复杂，影响管理决策的效果，有时还会影响公众对科学证据本身的信任。有效的数据可视化可以在准确传达此类复杂结果方面发挥关键作用，但我们缺乏一个证据基础，无法在设计时使它们在视觉上吸引人，同时又能有效地传达准确的信息。为了解决这个问题，我们进行了一项调查，以确定最有效的方法来可视化地传达一组全球气候模型的输出。我们衡量了调查参与者以不同方式解释相同模型输出的 10 种可视化方式的准确性、信心和易用性，以及他们的偏好。点和箱线图的表现优于所有其他可视化，热图和雷达图的效果相对较差，而我们的信息图在视觉吸引力方面得分很高，但缺乏准确解释所需的信息。我们提供了一套跨广泛研究领域可视化传达 MME 输出的指南，旨在最大限度地提高可视化的效果，同时最小化误解的可能性，增加模型的社会影响，并确保它们在未来能够很好地支持管理。
