Environmental variation is directly responsible for short‐ but not long‐term variation in forest‐atmosphere carbon exchange
Environmental variation is directly responsible for short‐ but not long‐term variation in forest‐atmosphere carbon exchange
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DOI：
10.1111/j.1365-2486.2007.01330.x
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发表时间：
2007-04
影响因子：
11.6
通讯作者：
A. Richardson;D. Hollinger;J. Aber;S. Ollinger;B. Braswell
中科院分区：
文献类型：
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作者：
A. Richardson;D. Hollinger;J. Aber;S. Ollinger;B. Braswell
基于塔涡度协方差测量的森林-大气二氧化碳（CO2）交换来自世界各地的许多站点表明，净生态系统交换（NEE）有相当大的年与年之间的变化。在这里，我们使用的统计建模方法来分区的年际变化NEE（及其组件通量，生态系统呼吸，Reco和总光合作用，Pgross）分为两个主要影响：环境驱动因素（空气和土壤温度，太阳辐射，蒸汽压赤字，土壤含水量）和变化的生物响应这种环境强迫（由模型参数的特点）。该模型应用于豪兰AmeriFlux网站，云杉为主的森林在缅因州，美国的9年数据集。在这个地点的间隙填充通量测量表明，森林已经螯合，平均为190 g C m−2 yr−1，范围从130到270 g C m−2 yr−1。我们的拟合模型预测的吸收量略高（平均270 g C m−2 yr−1），但年际变化相似，小波方差分析表明，在广泛的时间尺度（小时到年）内，塔测量值和模型预测值之间具有良好的一致性。与NEE的年际变化相关的是，Reco和Pgross的模型参数在不同年份之间存在明显差异。模型预测的分析表明，在每年的时间步长，约40%的模型NEE的方差可以归因于环境驱动程序的变化，和55%的变化，在生物响应这种强迫。由于模型预测是在较长的时间尺度上（从个别天到月再到日历年）进行汇总的，因此在确定建模通量时，环境驱动因素的变化变得越来越不重要，而生物反应的变化变得越来越重要。模拟的年度Pgross和Reco之间存在很强的负相关性（r=-0.93，P≤0.001）;讨论了这种相关性的两种可能解释。这种相关性促进了NEE的动态平衡：模型NEE的年际变化明显小于Pgross或Reco
Tower‐based eddy covariance measurements of forest‐atmosphere carbon dioxide (CO2) exchange from many sites around the world indicate that there is considerable year‐to‐year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration, Reco, and gross photosynthesis, Pgross) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9‐year data set from the Howland AmeriFlux site, a spruce‐dominated forest in Maine, USA. Gap‐filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m−2 yr−1, with a range from 130 to 270 g C m−2 yr−1. Our fitted model predicts somewhat more uptake (mean 270 g C m−2 yr−1), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both Reco and Pgross. Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual Pgross and Reco (r=−0.93, P≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either Pgross or Reco