Collaborative Research: Microbes, memory, and moisture: leveraging DroughtNet to predict how microbial moisture responses will impact carbon cycling

合作研究：微生物、记忆和水分：利用 DroughtNet 预测微生物水分反应将如何影响碳循环

• 批准号: 2016482
• 负责人: Steven Allison
• 金额: $ 41.2万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016482&HistoricalAwards=false
• 关键词: Collaborative; Research; Microbes; memory; moisture

This project will determine how soils and soil organisms respond to severe drought, a condition that will be more common in the future, and how this response will impact the global carbon cycle. The increasing frequency of drought due to changing rainfall patterns is threatening the world's ecosystems and food security. Rainfall frequency also can affect whether the immense amount of carbon present in soil stays there, or is emitted by soil microbes into the atmosphere as carbon dioxide (CO2). In order to accurately predict the impact of drought on soils, soil microbes and the carbon cycle, this project will use samples from the Drought-Net Research Coordination Network supported by NSF. Drought-Net consists of a series of simple, inexpensive experiments that control rainfall at over 150 plots of land worldwide using the same standard protocols. Soil samples from 39 Drought-Net sites that have been exposed to drought for four years will be manipulated in the laboratory to determine how they respond to different amounts of moisture. Soil microbial community changes and CO2 emission will be measured, and the results will be incorporated into computer models of global carbon cycling. These models can then predict how drought will cause changes and feedbacks in carbon cycling and, in turn, ecosystem function and stability. The studies will also involve training at of postdoctoral researchers, graduate and undergraduate students, and other educational and outreach activities. Successful completion of the goals and objectives of this project will help society understand how it needs to adapt and respond to global environmental change. While the recent inclusion of microbial mechanisms in ecosystem models has improved our ability to predict soil carbon (C) cycling, even the most advanced of these models explains only 50% of the variation in current C pools, leaving little confidence in projections of future soil C stocks. Past efforts have mainly focused on microbial temperature responses, but moisture and drought may be an even more important constraint on microbial activity. Thus, an understanding of microbial moisture responses is required to improve ecosystem C models. This research addresses four key questions: (1) what drives differences in moisture response functions across ecosystems? (2) how does severe drought alter moisture response across ecosystems? (3) what microbial mechanisms influence differences in moisture response functions? (4) what are the implications of different moisture responses for C storage? In order to build a robust predictive framework for soil microbial moisture functions, this project will leverage the Drought-Net Research Coordination Network, which has implemented standardized, coordinated rainfall manipulation experiments across the world. Intact soil cores from ambient and drought treatments at 39 sites will be exposed to a range of soil water potentials to quantify how the moisture response of heterotrophic respiration depends on historical climate and soil factors. Underlying microbial mechanisms will be examined by characterizing physiological traits and tolerances at individual and community levels. Results will be scaled to the ecosystem level by first testing how aggregated community responses influence function in a trait-based model, and then by incorporating response functions into conventional and microbially-explicit ecosystem models of soil C cycling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将确定土壤和土壤生物如何应对严重干旱，这种情况在未来将更加普遍，以及这种反应将如何影响全球碳循环。由于降雨模式的变化，干旱日益频繁，威胁着世界生态系统和粮食安全。降雨频率也会影响土壤中存在的大量碳是留在那里，还是由土壤微生物以二氧化碳（CO2）的形式排放到大气中。为了准确预测干旱对土壤、土壤微生物和碳循环的影响，该项目将使用由NSF支持的干旱网络研究协调网络的样本。 Drought-Net由一系列简单、廉价的实验组成，这些实验使用相同的标准协议控制全球150多块土地的降雨量。来自39个干旱网络站点的土壤样本已经遭受了四年的干旱，将在实验室中进行处理，以确定它们对不同湿度的反应。将测量土壤微生物群落变化和CO2排放，并将结果纳入全球碳循环的计算机模型。然后，这些模型可以预测干旱将如何导致碳循环的变化和反馈，进而影响生态系统的功能和稳定性。这些研究还将涉及博士后研究人员、研究生和本科生的培训以及其他教育和推广活动。成功完成该项目的目标和目的将有助于社会了解如何适应和应对全球环境变化。虽然最近在生态系统模型中纳入微生物机制提高了我们预测土壤碳（C）循环的能力，但即使是最先进的模型也只能解释当前C库变化的50%，对未来土壤C库的预测信心不足。过去的努力主要集中在微生物的温度反应，但水分和干旱可能是一个更重要的限制微生物活性。因此，微生物水分响应的理解是必要的，以改善生态系统C模型。这项研究解决了四个关键问题：（1）是什么驱动不同生态系统的水分响应功能的差异？(2)严重干旱如何改变生态系统的水分反应？(3)什么微生物机制影响水分响应功能的差异？(4)不同的湿度对碳储存的影响是什么？为了建立一个强有力的土壤微生物水分功能预测框架，该项目将利用干旱网络研究协调网络，该网络在世界各地开展了标准化、协调一致的降雨量控制实验。在39个站点的环境和干旱处理的完整土芯将暴露于一系列土壤水势，以量化异养呼吸的水分响应如何取决于历史气候和土壤因素。潜在的微生物机制将通过表征个体和群落水平的生理特性和耐受性来研究。结果将扩展到生态系统水平，首先测试聚集的社区响应如何影响基于特征的模型中的功能，然后将响应函数纳入土壤碳循环的传统和微生物明确的生态系统模型中。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。