Recently, Wang Xingchang (Professor Wang Chuankuan’s research team), a teacher at National Field Observation Station for Forest Ecosystem in Mao’er Mountain, Heilongjiang Province, has been awarded a Ph.D. degree in Agroforestry and Forestry Meteorology (IF = 3.887 ). His dissertation and research papers are entitled “Improving the CO2 storage measurements with a single profile system in a tall-dense-canopy temperate forest”, “Quantifying and reducing the differences in forest CO2-fluxes estimated by eddy covariance, biometric and chamber methods: A global synthesis” and other papers promoting the determination of carbon fluxes in forest ecosystems. The improvement of terrestrial ecosystem carbon flux observation technology is of great significance.

The carbon cycle of the Earth system is closely linked to global climate change. However, the current quantitative measurement of CO2 revenues from terrestrial ecosystems (especially forest ecosystems) is still one of the major sources of uncertainty in the global carbon cycle estimation. Accurate determination of forest ecosystem carbon flux is a logical basis for assessing the role of forest ecosystems in biogeochemical cycles and their role in climate change regulation. According to the first author of the paper, Dr. Wang Xingchang and Professor Wang Chuankuan, there are three main methods for measuring CO2 flux on forest ecosystems (tree-finding method, box method and vortex covariance method) The vortex covariance method is widely used due to its advantages of high time resolution and in-situ jam-free continuous monitoring. However, due to the complex and diverse global forest ecosystems, tall canopies and fluctuating terrain, the effective application of the eddy covariance method poses a great challenge. After a 10-year continuous observation at Mao’ershan Forest Ecological Station, it was found that using common single-point observations or standard profiles to estimate canopy CO2 storage fluxes would significantly underestimate the net CO2 exchange between forests and the atmosphere, resulting in significant measurement errors. Further global data integration analysis found that the net carbon fixation of the forest obtained by the eddy covariance method was 25% higher than that of the tree-based method, but its ecosystem respiration was 10% lower than that of the box method, this error is more pronounced in forest ecosystems that have a complex topography and thick canopy. The reason is significantly related to the surface heating effect of the open coiled covariance system. These findings are helpful to improve the estimation accuracy of forest carbon budget, and provide an important methodological basis for the data fusion and assessment of global CO2 flux observation network.

This research is supported by the National Natural Science Foundation of China, the “12th Five-Year Plan” science and technology support project and the Changjiang Scholar Innovation Team project of the Ministry of Education.