Explaining inter-annual variability of gross primary productivity from plant phenology and physiology
Explaining inter-annual variability of gross primary productivity from plant phenology and physiology
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DOI：
10.1016/j.agrformet.2016.06.010
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发表时间：
2016-10
影响因子：
6.2
通讯作者：
Sha Zhou;Yao Zhang;Kelly K. Caylor;Yiqi Luo;X. Xiao;P. Ciais;Yuefei Huang;Guangqian Wang
中科院分区：
文献类型：
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作者：
Sha Zhou;Yao Zhang;Kelly K. Caylor;Yiqi Luo;X. Xiao;P. Ciais;Yuefei Huang;Guangqian Wang
气候变率影响植物物候和生理，导致陆地总初级生产力（GPP）的年际变化。然而，GPP的年际变化仍然难以解释。在这项研究中，我们提出了一个综合物候和生理统计模型（SMIPP）来解释最大日GPP （GPPmax）、生长季节开始和结束（gsstart和GSend）对北美和欧洲27个站点观测到的GPP年际变率的贡献。gppstart和春季GPP （r = 0.82±0.10）、gppmax和夏季GPP （r = 0.90±0.14）、gsendr和秋季GPP （r = 0.75±0.18）在各站点的异常之间存在较强的相关性。偏相关分析进一步支持GPP与GSstart（偏r值为0.72±0.20）、GPPmax（偏r值为0.87±0.15）、GSend（0.59±0.26）具有较强的相关性。此外，在27个站点中，这三个指标对年度GPP的影响相互独立。总体而言，站点校准的SMIPP解释了27个站点年度GPP变化的90±11%。总体而言，gppmax对GPP年变化的贡献大于这两个物候指标。这些结果表明，利用这三个指标可以有效地估算出GPP的年际变化。研究植物生理、春季和秋季物候对环境变化的影响，可以提高对未来气候变化下全年GPP变化轨迹的预测。
Climate variability influences both plant phenology and physiology, resulting in inter-annual variation in terrestrial gross primary productivity (GPP). However, it is still difficult to explain the inter-annual variability of GPP. In this study, we propose a Statistical Model of Integrated Phenology and Physiology (SMIPP) to explain the contributions of maximum daily GPP (GPPmax), and start and end of the growing season (GSstartand GSend) to the inter-annual variability of GPP observed at 27 sites across North America and Europe. Strong relationships are found between the anomalies of GSstartand spring GPP (r = 0.82 ± 0.10), GPPmaxand summer GPP (r = 0.90 ± 0.14), and GSendand autumn GPP (r = 0.75 ± 0.18) within each site. Partial correlation analysis further supports strong correlations of annual GPP with GSstart(partial r value being 0.72 ± 0.20), GPPmax(0.87 ± 0.15), and GSend(0.59 ± 0.26), respectively. In addition, the three indicators are found independent from each other to influence annual GPP at most of the 27 sites. Overall, the site-calibrated SMIPP explains 90 ± 11% of the annual GPP variability among the 27 sites. In general, GPPmaxcontributes to annual GPP variation more than the two phenological indicators. These results indicate that the inter-annual variability of GPP can be effectively estimated using the three indicators. Investigating plant physiology, and spring and autumn phenology to environmental changes can improve the prediction of the annual GPP trajectory under future climate change.