Hot-Moments of Soil CO2 Efflux in a Water-Limited Grassland

Hot-Moments of Soil CO2 Efflux in a Water-Limited Grassland
复制标题

DOI:
10.3390/soilsystems2030047
复制
发表时间:
2018-08
期刊:
影响因子:
3.5
通讯作者:
R. Vargas;Enrique Sánchez-Cañete P.;P. Serrano-Ortiz;J. Curiel Yuste;F. Domingo;A. López-Ballesteros;C. Oyonarte
R. Vargas;Enrique Sánchez-Cañete P.;P. Serrano-Ortiz;J. Curiel Yuste;F. Domingo;A. López-Ballesteros;C. Oyonarte
中科院分区:
--
文献类型:
--
作者:
R. Vargas;Enrique Sánchez-Cañete P.;P. Serrano-Ortiz;J. Curiel Yuste;F. Domingo;A. López-Ballesteros;C. Oyonarte

文献摘要

被引文献

相似文献

水有限生态系统的代谢活动与降水脉冲的时间和幅度密切相关,降水脉冲可以触发不成比例的高(即,热时)生态系统CO2通量。我们分析了超过2年的连续测量土壤CO2排放量(Fs)植被(Fsveg)和裸露土壤(Fsbare)在水有限的草地。连续小波变换用于:(a)描述FS的时间变异性;(B)测试复杂度不同的经验模型的性能;以及(c)识别FS的热点时刻。我们使用部分小波相干(PWC)分析,以测试Fs与温度和土壤水分之间的时间相关性。PWC分析提供的证据表明,土壤水分盖过土壤温度的影响Fs在这个水分有限的生态系统。降水脉冲触发热的时刻,增加Fsveg(高达9000%)和Fsbare(高达17,000%)相对于脉冲前率。高度参数化的经验模型(使用支持向量机(SVM)或8天移动窗口)是用于表示Fs的每日时间变化性的良好方法,但是SVM是表示Fs的高时间变化性(即,小时估算)。我们的研究结果具有代表性的热时刻的生态系统CO2通量在这些全球分布的生态系统。
The metabolic activity of water-limited ecosystems is strongly linked to the timing and magnitude of precipitation pulses that can trigger disproportionately high (i.e., hot-moments) ecosystem CO2 fluxes. We analyzed over 2-years of continuous measurements of soil CO2 efflux (Fs) under vegetation (Fsveg) and at bare soil (Fsbare) in a water-limited grassland. The continuous wavelet transform was used to: (a) describe the temporal variability of Fs; (b) test the performance of empirical models ranging in complexity; and (c) identify hot-moments of Fs. We used partial wavelet coherence (PWC) analysis to test the temporal correlation between Fs with temperature and soil moisture. The PWC analysis provided evidence that soil moisture overshadows the influence of soil temperature for Fs in this water limited ecosystem. Precipitation pulses triggered hot-moments that increased Fsveg (up to 9000%) and Fsbare (up to 17,000%) with respect to pre-pulse rates. Highly parameterized empirical models (using support vector machine (SVM) or an 8-day moving window) are good approaches for representing the daily temporal variability of Fs, but SVM is a promising approach to represent high temporal variability of Fs (i.e., hourly estimates). Our results have implications for the representation of hot-moments of ecosystem CO2 fluxes in these globally distributed ecosystems.