Improved modeling of gross primary productivity (GPP) by better representation of plant phenological indicators from remote sensing using a process model
Improved modeling of gross primary productivity (GPP) by better representation of plant phenological indicators from remote sensing using a process model
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DOI：
10.1016/j.ecolind.2018.01.042
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发表时间：
2018-05
影响因子：
6.9
通讯作者：
Jian Wang;Chaoyang Wu;Chunhua Zhang;W. Ju;Xiaoyue Wang;Zhi Chen;B. Fang
中科院分区：
文献类型：
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作者：
Jian Wang;Chaoyang Wu;Chunhua Zhang;W. Ju;Xiaoyue Wang;Zhi Chen;B. Fang
物候学是生态系统功能的重要指标，也是总初级生产力(GPP)最重要的控制因素之一。综合陆地生态系统碳收支模型(INTEC)通过模拟一系列生态系统过程，特别是根据度日指标得出的物候，来预测碳循环。然而，经验温度阈值可能不能很好地代表低纬地区的生态系统增长。本文利用30年超高分辨率辐射计第三代归一化植被指数(NDVI3g)数据(1983-2012年)，采用3种算法从中国森林生态系统NDVI时间序列中得到植被指数的起始(SOS)、结束(EOS)和生长季长度(LOS)。物候学模块随后被合并到INTEC模型中，然后使用涡旋协方差测量的地面观测进行验证。结果表明，与基于温度的物候学模型相比，基于NDVI的物候学模型改进了GPP的建模。利用修正的INTEC模型分析了1983-2012年中国森林生态系统GPP的时空格局。我们发现，在大规模分析中，基于遥感的物候比基于温度的物候更可靠。利用修正的INTEC模型，我们发现中国森林生态系统的全球生产总值在1983年至2012年期间呈上升趋势，空间异质性很强，平均值为1.31 PG Cyr−1。我们的结果表明，遥感物候对于提高生态系统模型模拟全球生产总值的精度具有重要意义，这对大规模的碳汇评估具有启发意义。
Phenology is a significant indicator of ecosystem functioning and is one of the most important controllers of gross primary productivity (GPP). The Integrated Terrestrial Ecosystem C-budget model (InTEC) predicts carbon cycling by modeling a number of ecosystem processes, and in particularly, phenology derived from a degree-day metric. However, empirical temperature thresholds may not well represent ecosystem growth at low latitudes. Here, using 30-year Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index 3rd generation (NDVI3g) data (1983–2012), we obtained the start (SOS), end (EOS) and length of growing season (LOS) with three algorithms from time series of NDVI for forests ecosystems of China. The phenology module was then incorporated into the InTEC model before validation using ground observations from eddy covariance measurements. Our results showed that compared with temperature-based phenology of the original model, using NDVI-based phenology improved modeling of GPP. The modified InTEC model was used to analyze the spatial and temporal patterns of GPP for forest ecosystems of China during 1983 to 2012. We found that remote sensing-based phenology was more reliable than temperature-based phenology for large-scale analysis. Using the modified InTEC model, we revealed that the GPP of China’s forests ecosystems increased over 1983–2012 with high spatial heterogeneity, with a mean of 1.31 Pg Cyr−1. Our results demonstrated the significance of remotely sensed phenology for improving the accuracy of GPP modeling with ecosystem models, which is enlightening for the large-scale evaluation of carbon sequestration.