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.

曾经覆盖整个美国数百万英亩土地的本地草原已减少到其以前分布的一小部分。这些剩下的草原在碳和养分，生物多样性以及作为恢复的来源中起着重要作用。美国中部剩下的土壤草原的健康和季节性动态受降雨量和时机的控制。预计整个美国中部降雨量的可变性将会增加，预计极端潮湿的年度频率更高。草原可能对这种变化特别敏感，并有证据表明这些系统可能对潮湿的年度和干燥年份更敏感。但是，研究很少包括对极端年份的评估。该博士学位论文改善授予（DDIG）奖将在完整的半干旱草地系统中实验评估草原成分，碳循环和营养循环对极端降雨的敏感性。该研究结果将对自然资源和土地管理者在管理或恢复本地草原方面有价值。研究生和本科生将接受培训并参加研究。该研究项目旨在促进对生态系统将如何应对环境变异性和肢体增加的基本理解。假设草原生态系统对极端降雨的反应是非线性和双模式的。提出了一种新型的实验治疗方法，可以使半干旱草原暴露于大量生长季节降水梯度，该降水将能够检测到响应变量中的非线性，而这些变量否则在少数因素实验设计中无法检测到的响应变量。这项研究将允许评估关键碳循环成分对干燥年与湿年的比较敏感性，以及当降水从中等到极端偏离平均水平的降水转变时，这种敏感性如何变化。