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    • Reply to Ruhl and Craig: Assessing and Governing Extreme Climate Risks Needs to Be Legitimate and Democratic

    Luke Kemp,Chi Xu,Joanna Depledge,Kristie L. Ebi,Goodwin Gibbins,Timothy A. Kohler,Johan Rockstroem,Marten Scheffer,Hans Joachim Schellnhuber,Will Steffen,Timothy M. Lenton

    Proceedings of the National Academy of Sciences of the United States of America（2022）

    Univ Cambridge | Nanjing Univ | Univ Washington | Univ Oxford | Washington State Univ | Telegraphenberg | Univ Wageningen | Australian Natl Univ | Univ Exeter

    Cited 0|Views4
    Abstract
    Microbial communities are found throughout the biosphere, from human guts to glaciers, from soil to activated sludge. Understanding the statistical properties of such diverse communities can pave the way to elucidate the common mechanisms ...Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches—which combine phylogenetic relationships between species with community ecology—have the potential to disentangle such forces but are often ...
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    Ecosystem Resilience,Climate Tipping Points
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
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    【要点】：论文探讨微生物群落在生物圈中的多样性和组成，提出利用系统发育生态学方法解析影响微生物群落组成的多种生态力量，并强调在评估和管理极端气候风险时需要合法性和民主性。
    

    【方法】：作者采用系统发育生态学方法，结合物种间的系统发育关系和群落生态学，以解析影响微生物群落组成的生态力量。
    

    【实验】：具体实验细节和数据集名称在摘要中未提及，但论文可能涉及对微生物群落组成的统计分析和模型构建，以及评估极端气候风险管理的合法性及民主性研究。