A dataset of carbon fluxes of the deciduous broad-leaved forest at Maoershan Station from 2016 to 2018

Abstract

Forest ecosystem dominates the terrestrial ecosystem carbon (C) cycle, thus the accurate estimation of C flux in the forest ecosystem is essential to understanding the impact of global change on global C cycle. Based on the micrometeorology theory, the eddy covariance technique is one of the standard methods for C flux monitoring in terrestrial ecosystems, which has been widely used in the long-term monitoring of C flux in forests, grasslands, croplands and other ecosystems. Heilongjiang Maoershan Forest Ecosystem National Observation and Research Station has a continental monsoon climate, dominated by natural secondary forests (temperate deciduous broad-leaved forestd) which are typical in the montane forests of Northeast China. In this dataset, we compiled the measured C flux data and routine meteorological data of a deciduous broad-leaved forest at Maoershan Station from 2016 to 2018, including gross primary productivity, ecosystem respiration, net ecosystem exchange, incoming solar radiation, incoming photosynthetically active radiation, air temperature, soil temperature, soil moisture and precipitation. The dataset is divided into four time scales: half-hourly, daily, monthly and yearly. The establishment and sharing of this dataset will provide necessary, accurate and reliable data to support the evaluation of the role of natural secondary forests in the regional C cycle and the optimization of C cycle models.