%A Bao-Lin Xue, Qinghua Guo, Yongwei Gong, Tianyu Hu, Jin Liu, Takeshi Ohta %T The influence of meteorology and phenology on net ecosystem exchange in an eastern Siberian boreal larch forest %0 Journal Article %D 2016 %J J Plant Ecol %R 10.1093/jpe/rtv075 %P 520-530 %V 9 %N 5 %U {https://www.jpe.ac.cn/CN/abstract/article_28825.shtml} %8 2016-09-20 %X Aims Boreal forests play an important role in the global carbon cycle. Compared with the boreal forests in North America and Europe, relatively few research studies have been conducted in Siberian boreal forests. Knowledge related to the role of Siberian forests in the global carbon balance is thus essential for a full understanding of global carbon cycle.
Methods This study investigated the net ecosystem exchange (NEE) during growing season (May–September) in an eastern Siberian boreal larch forest for a 3-year period in 2004–2006 with contrasting meteorological conditions.
Important findings The study found that the forest served as a carbon sink during all of the 3 studied years; in addition, the meteorological conditions essentially influenced the specific annual value of the strength of the carbon sinks in each year. Although 2005 was the warmest year and much wetter than 2004, 2005 also featured the greatest amount of ecosystem respiration, which resulted in a minimum value of NEE. The study also found that the phenological changes observed during the three study years had a relatively small effect on annual NEE. Leaf expansion was 26 days earlier in 2005 than in the other 2 years, which resulted in a longer growing season in 2005. However, the NEE in 2005 was counterbalanced by the large rate of ecosystem respiration that was caused by the higher temperatures in the year. This study showed that meteorological variables had larger influences on the interannual variations in NEE for a Siberian boreal larch forest, as compared with phenological changes. The overall results of this study will improve our understanding of the carbon balance of Siberian boreal larch forests and thus can help to forecast the response of these forests to future climate change.