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

该项目将确定土壤和土壤生物如何应对未来将更加普遍的严重干旱，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，威胁着世界的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，本项目将使用由美国国家科学基金会支持的干旱网络研究协调网络的样本。干旱网由一系列简单、廉价的实验组成，这些实验使用相同的标准协议在全球150多块土地上控制降雨。来自39个干旱网络站点的土壤样本已经暴露在干旱中四年了，将在实验室中进行操作，以确定它们对不同湿度的反应。土壤微生物群落变化和二氧化碳排放将被测量，结果将被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引起碳循环的变化和反馈，进而预测生态系统的功能和稳定性。这些研究还将包括博士后研究人员、研究生和本科生的培训，以及其他教育和推广活动。该项目的目标和目的的成功完成将有助于社会了解它需要如何适应和应对全球环境变化。虽然最近将微生物机制纳入生态系统模型提高了我们预测土壤碳(C)循环的能力，但即使是这些模型中最先进的模型也只能解释当前碳库中50%的变化，因此对未来土壤碳储量的预测缺乏信心。过去的研究主要集中在微生物的温度响应上，但水分和干旱可能是对微生物活动更重要的限制。因此，需要了解微生物水分响应来改进生态系统C模型。本研究解决了四个关键问题：(1)是什么驱动了不同生态系统中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响应？(3)影响水分响应功能差异的微生物机制是什么？(4)不同湿度响应对碳储存的影响是什么？为了建立一个强大的土壤微生物水分功能预测框架，该项目将利用干旱网研究协调网络，该网络已经在世界各地实施了标准化、协调的降雨操纵实验。在39个地点进行环境和干旱处理后的完整土壤岩心将暴露在一系列土壤水势中，以量化异养呼吸的水分响应如何依赖于历史气候和土壤因子。潜在的微生物机制将通过表征生理特征和个体和社区水平的耐受性来检查。研究结果将扩展到生态系统水平，首先测试群落总体响应如何在基于性状的模型中影响功能，然后将响应函数纳入土壤C循环的传统和微生物显式生态系统模型。该奖项反映了美国国家科学基金会的法定使命，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。

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.