RAPID: Breaking drought as an opportunity to examine regional vs. local constraints on microbial community responses to environmental change

土壤中储存的碳量是大气中二氧化碳的两倍多。微生物消耗土壤有机物质来获取碳和养分，因此它们的活动决定了土壤中保留了多少碳，以及释放了多少碳。目前用于预测微生物如何影响土壤碳的模型假设，无论它们位于何处，它们对湿度和温度的反应都完全相同。相比之下，PI最近的研究发现，干燥地区的土壤对水分的反应能力不如潮湿地区的土壤。这些当地的“历史突发事件”使得准确预测未来土壤碳储量和损失变得更加困难。使情况更加复杂的是，PI先前的研究是在一个长期的区域干旱期间进行的，因此可能反映了干旱胁迫造成的暂时状况。今年，她在得克萨斯州的采样点正在经历过多的降雨，甚至洪水，这可能会影响区域移民和休眠/复苏动态，这可能会克服当地的历史限制，并允许土壤微生物更好地适应湿度的变化。这个快速奖将使她能够测试这些想法。 她的团队将利用2015年这一罕见的潮湿年份，这是德克萨斯州自2007年以来的第一次。这些研究将使我们更好地了解土壤微生物群落如何发挥作用并对降水变化作出反应，这对农业、牧场和林业管理至关重要。一名技术人员、一名研究生和几名本科生将通过该项目接受培训。这些本科生将从PI为大一新生开设的课程中招募，作为德克萨斯大学奥斯汀分校新生研究计划的一部分，该计划实施创新的研究型教育，并针对STEM领域代表性不足的群体。研究生和本科生也将被鼓励开发一个相关的独立研究项目。这个快速项目的目标是确定当地与区域过程的平衡如何影响微生物对环境变化的反应的历史偶然性。目前的丰水年提供了一个机会，以区分当地与区域的驱动程序。这将通过以下方式解决：（1）测试土壤呼吸对水分反应的历史突发事件的释放，（2）记录群落组成的变化是否在田间平行发生，（3）检查可能是先前突发事件观察的基础的两种机制：休眠/复苏和移民动态。这项研究将使用PI和她的实验室工作了9年的陡峭降雨梯度，以及实验室微观实验来生成水分响应曲线和操纵扩散的组合来完成。研究结果有可能改善在气候变化情景下如何预测土壤生态地球化学过程。如果历史突发事件持续存在，尽管这个多雨的一年，那么当地的空间变化过程中的响应可能是必要的准确预测。或者，如果区域过程拯救以前的历史突发事件，并允许土壤适应一个新的降雨制度，那么模型可能会得到改善，将滞后过程的反应。

More than twice the amount of carbon is stored in soils than is found as carbon dioxide in the atmosphere. Microbes consume soil organic material for both carbon and nutrients, and so their activities dictate how much carbon is retained by soils, and how much is released. Current models used to forecast how microbes will affect soil carbon assume that they all behave exactly the same in response to moisture and temperature no matter where they are located. By contrast, recent research by the PI has found that soils from drier regions did not have the same capacity to respond to moisture as soils from wetter sites. These local 'historical contingencies' make it more difficult to accurately predict future soil carbon storage and loss. Also complicating the picture is that the PI's prior studies have taken place during an extended regional drought period, and therefore could reflect a temporary condition created by drought stress. This year, her sample sites in Texas are experiencing excessive rainfall, and even flooding, which could affect both regional immigration and dormancy/resuscitation dynamics that might overcome local historical constraints and allow for soil microbes to better acclimate to a change in moisture. This RAPID award will enable her to test these ideas. Her team will take advantage of this rare wet year in 2015, the first in Texas since 2007. These studies will result in improvements in our understanding of how soil microbial communities function and respond to changes in precipitation, knowledge that is important to agriculture, range land and forestry management. One technician, one graduate student, and several undergraduates will receive training through this project. The undergraduates will be recruited from a class taught by the PI for freshman as part of the Freshman Research Initiative at the University of Texas, Austin, which implements innovative research-based education and targets underrepresented groups in STEM fields. The graduate and undergraduate students also will be encouraged to develop a related independent research projects.The goal of this RAPID project is to determine how the balance of local vs. regional processes affect historical contingencies in microbial responses to environmental change. The current wet year provides an opportunity to separate local vs. regional drivers. This will be addressed by (1) testing for release of historical contingencies on soil respiration responses to moisture, (2) documenting whether community composition shifts occur in parallel in the field, and (3) examining two mechanisms that likely underlie the previous observations of contingencies: dormancy/resuscitation and immigration dynamics. This research will be accomplished using a combination of a steep rainfall gradient where the PI and her lab have worked for 9 years, as well as lab microcosm experiments to generate moisture response curves and manipulate dispersal. Results have the potential to improve how soil biogeochemical processes are forecast in climate change scenarios. If historical contingencies persist despite this wet year, then local spatial variation in process responses may be necessary for accurate forecasting. Alternatively, if regional processes rescue prior historical contingencies and allow soils to acclimate to a new rainfall regime, then models might be improved by incorporating lags in process responses.