Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica. Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

预测物种如何响应气候变化是海洋生态学中日益发展的研究领域，但如何将未来气候数据的不确定性纳入此类预测的相关认知，仍是一项重大挑战。为助力攻克这一难题，本综述将气候不确定性划分为三大组成部分：情景不确定性、模型不确定性以及模式内部变率，并确立了四项准则，用以全面解读生态响应与气候变化相关不确定性的关联，即认知、获取、纳入与传播。通过文献综述，本研究评估了海洋生态学界在预测研究中落实上述准则的程度。尽管学界对气候不确定性已有较高认知，但相关研究仍倾向于选取最极端的排放情景，且仅将少数气候模型作为生态分析的输入数据。以海表温度为例，此类模型的预测结果可能无法代表更大集合平均的结果。此外，91%的研究未将气候模型的内部变率纳入研究结果。本研究探讨了在预测远洋鱼类南极电灯鱼（Electrona antarctica）未来分布时，排放情景选择、气候模型选取以及模式实现方式所产生的影响。其未来分布受气候模型选取的影响极大，且在部分场景中，内部变率对分布变化的方向与强度具有决定性作用。提升经处理气候数据的清晰度与可获取性，将有助于更全面地探索气候不确定性，同时提高海洋预测研究的质量与标准化水平。