Maximum summer temperatures predict the temperature adaptation of Arctic soil bacterial communities
Maximum summer temperatures predict the temperature adaptation of Arctic soil bacterial communities
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DOI：
10.5194/bg-20-767-2023
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发表时间：
2023-02
期刊：
影响因子：
4.9
通讯作者：
Ruud Rijkers;M. Dekker;R. Aerts;J. Weedon
中科院分区：
文献类型：
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作者：
Ruud Rijkers;M. Dekker;R. Aerts;J. Weedon
摘要。北极陆地地区的快速变暖有可能加快土壤分解速度，并对未来的气候变化形成碳驱动的反馈。为了准确预测土壤微生物在这些过程中的作用，了解土壤细菌群落的温度响应并将其应用到生物地球化学模型中是非常重要的。北极地区大部分地区土壤细菌群落的温度适应性尚不清楚。我们评估了亚北极至高北极地区12个采样点土壤细菌群落的温度适应性。这些地点的土壤细菌群落对温度的适应有很大差异，估计最佳生长温度（Topt）在23.4±0.5到34.1±3.7°C之间。基于土壤温度记录或细菌群落组成数据得出的不同气候指数，我们评估了预测土壤细菌群落温度适应性的可能统计模型。我们发现最高日平均土壤温度是土壤细菌群落Topt的最佳预测因子，增加0.63°C°C−1。基于最常见细菌种类的相对丰度数据，我们发现回归树分析不支持温度适应的预测。夏季气温的升高可能会增加北极土壤细菌群落的Topt。将这一机制纳入土壤生物地球化学模型，并将其与土壤温度预测相结合，将有助于减少北极土壤碳储量脆弱性评估中的不确定性。
Abstract. Rapid warming of the Arctic terrestrial region has the potential to increase soil decomposition rates and form a carbon-driven feedback to future climate change. For an accurate prediction of the role of soil microbes in these processes, it will be important to understand the temperature responses of soil bacterial communities and implement them into biogeochemical models. The temperature adaptation of soil bacterial communities for a large part of the Arctic region is unknown. We evaluated the current temperature adaption of soil bacterial communities from 12 sampling sites in the sub- to High Arctic region. Temperature adaptation differed substantially between the soil bacterial communities of these sites, with estimates of optimal growth temperature (Topt) ranging between 23.4 ± 0.5 and 34.1 ± 3.7 ∘C. We evaluated possible statistical models for the prediction of the temperature adaption of soil bacterial communities based on different climate indices derived from soil temperature records or on bacterial community composition data. We found that highest daily average soil temperature was the best predictor for the Topt of the soil bacterial communities, increasing by 0.63 ∘C ∘C−1. We found no support for the prediction of temperature adaptation by regression tree analysis based on the relative abundance data of the most common bacterial species. Increasing summer temperatures will likely increase Topt of soil bacterial communities in the Arctic. Incorporating this mechanism into soil biogeochemical models and combining it with projections of soil temperature will help to reduce uncertainty in assessments of the vulnerability of soil carbon stocks in the Arctic.