DISSERTATION RESEARCH: Mechanisms of asymmetrical ecosystem responses to precipitation extremes in xeric vs. mesic grasslands

论文研究：旱地与中湿草原生态系统对极端降水的不对称响应机制

• 批准号: 1701966
• 负责人: Melinda Smith
• 金额: $ 1.93万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701966&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Mechanisms; asymmetrical; ecosystem

Native grasslands once covering millions of acres across the US have been reduced to a tiny fraction of their former distribution. These remaining grasslands play important roles in the cycling of carbon and nutrients, biodiversity, and as sources for restoration. The health and seasonal dynamics of the remaining native grasslands in the central US are controlled by the amount and timing of rainfall. Across the central US rainfall variability is predicted to increase, with greater frequencies of extreme wet and dry years expected. Grasslands are likely to be particularly sensitive to such changes, with evidence that these systems may be more sensitive to wet versus dry years. However, studies rarely include assessment of extreme years. This Doctoral Dissertation Improvement Grant (DDIG) award, will experimentally assess the sensitivity of the grassland composition, carbon cycle, and nutrient cycling to rainfall extremes within an intact semi-arid grassland system. The research results will be valuable to natural resource and land managers in managing or restoring native grasslands. Graduate and undergraduate students will be trained and participate in the research. This research project aims to advance a fundamental understanding of how ecosystems will respond to predicted increases in environmental variability and extremity. The grassland ecosystem's response to rainfall extremes is hypothesized to be non-linear and bi-modal. A novel experimental treatment is proposed to expose semi-arid grassland to a large gradient of growing season precipitation that will be able to detect nonlinearities in response variables that are otherwise not detectable in few-factor experimental design. The research will allow assessment of the comparative sensitivities of key carbon cycle components to dry versus wet years, and how this sensitivity may change when precipitation transitions from moderate to extreme deviations from mean levels.

美国本土草原曾经覆盖数百万英亩，现在已经减少到原来分布面积的一小部分。这些剩余的草原在碳和养分的循环、生物多样性以及作为恢复来源方面发挥着重要作用。美国中部剩余的本土草原的健康和季节动态受降雨量和时间的控制。预计整个美国中部的降雨量变化将会增加，极端潮湿和干旱年份的频率预计会更高。草原可能对这种变化特别敏感，有证据表明，这些系统可能对多雨的年份比干旱的年份更敏感。然而，研究很少包括对极端年份的评估。这项博士论文改良助学金(Ddig)奖，将在一个完整的半干旱草原系统内，通过实验评估草原组成、碳循环和养分循环对极端降雨的敏感性。研究成果将对自然资源和土地管理者管理或恢复天然草原具有一定的参考价值。研究生和本科生将接受培训并参与研究。这一研究项目旨在促进对生态系统将如何应对预计的环境变异性和极端情况增加的基本理解。假设草地生态系统对极端降雨的响应是非线性的和双峰的。提出了一种新的试验性处理方法，将半干旱草原暴露在生长季降雨量的大梯度中，这将能够检测到响应变量中的非线性，否则在少因素实验设计中无法检测到。这项研究将能够评估关键的碳循环组成部分对干旱年份和多雨年份的相对敏感性，以及当降水量从平均水平的中等偏差过渡到极端偏差时，这种敏感性可能会如何变化。