compiled_climate_response_data_CCME
收藏figshare.com2023-05-31 更新2025-03-25 收录
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This project contains a dataset compiled based on previous-published data from controlled experiments on responses of 14 species to marine climate change variables. We searched the published literature for controlled experiments in which (i) temperature, oxygen, pCO2, and/or salinity were varied within the range of mean values expected between the present and year 2100 in the California Current Marine Ecosystem and (ii) the individual-level response of these species was measured in one or more of the following categories: survival, metabolic rate, locomotion, somatic growth rate, and resource consumption rate. We extracted either (i) all individual-level observations of the response variable (including control treatments), or (ii) the mean, error estimate, and sample size of aggregated response data. When values were not reported as numbers, we estimated values from figures using WebPlotDigitizer (Rohatgi, 2018). In addition to the category of response, we noted the location of organism collection, experimental treatments, duration of exposure, life phase, and other environmental variables for each experiment. We included published studies through December of 2020.
These data are further described and used in Sunday et al. Biological sensitivities to high-resolution climate change projections in the California Current Marine Ecosystem. Global Change Biology. 2022. 10.1111/gcb.16317
link to live GitHub page: https://github.com/jennsunday/downscaled_sensitivities_CCME
link to archived scripts: 10.6084/m9.figshare.16636087
本项研究包含一个基于先前公开发表的数据集,该数据集由对14种物种对海洋气候变化变量响应的受控实验组成。本研究在已发表的文献中搜索了受控实验,其中(i)温度、氧气、二氧化碳分压(pCO2)和/或盐度在加利福尼亚海流海洋生态系统当前与2100年之间预期平均值范围内变化;(ii)这些物种的个体水平响应在以下一个或多个类别中被测量:生存率、新陈代谢率、运动能力、躯体生长率和资源消耗率。我们提取了(i)响应变量的所有个体水平观察结果(包括对照处理),或(ii)汇总响应数据的平均值、误差估计和样本量。当数值未报告为数字时,我们使用WebPlotDigitizer(Rohatgi,2018)从图中估计数值。除了响应类别外,我们还记录了每个实验中生物体的采集地点、实验处理、暴露持续时间、生命阶段和其他环境变量。我们包括截至2020年12月的已发表研究。这些数据在Sunday等人撰写的《加利福尼亚海流海洋生态系统中对高分辨率气候变化预测的生物敏感性》一文中进一步描述和利用。全球变化生物学。2022年。10.1111/gcb.16317
GitHub页面链接:https://github.com/jennsunday/downscaled_sensitivities_CCME
存档脚本链接:10.6084/m9.figshare.16636087
提供机构:
figshare



