Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model.
Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model.
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DOI：
10.1371/journal.pone.0154615
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Tagesson T
中科院分区：
文献类型：
--
作者：
Boke-Olén N;Lehsten V;Ardö J;Beringer J;Eklundh L;Holst T;Veenendaal E;Tagesson T
根据目前的气候变化预测，预计萨凡纳地区的降水模式将发生变化。这种变化将影响控制净初级生产力的叶物候。研究这一点很重要，因为稀树草原由于其面积覆盖而在全球碳循环中发挥重要作用，并可能对依赖自给农业的地区的粮食安全产生影响。在这项研究中，我们调查如何土壤水分，年平均降水量，和日长控制稀树萨凡纳物候发展滞后的时间序列模型。该模型使用四大洲15个通量塔站点的气候数据，以及来自卫星的归一化差异植被指数来优化统计物候模型。我们表明，所有这三个变量都可以用来估计全球范围内的萨凡纳物候。然而，如果不包括更多的场地特定参数，就不可能创建一个在全球范围内对所有场地都同样有效的简化萨凡纳模型。简化的模型没有显示出对树木覆盖或大陆之间的偏见，并导致交叉验证的r2为0.6，均方根误差为0.1。因此，我们期望类似的平均结果时，将该模型应用到其他萨凡纳地区，并进一步期望它可以用来估计萨凡纳地区的生产力。
Savannah regions are predicted to undergo changes in precipitation patterns according to current climate change projections. This change will affect leaf phenology, which controls net primary productivity. It is of importance to study this since savannahs play an important role in the global carbon cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore expect similar average results when applying the model to other savannah areas and further expect that it could be used to estimate the productivity of savannah regions.