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The structural and functional characteristics of soil prokaryotic community are important for maintaining ecosystem functions. In this study, we examined the diversity and compositions, the key drivers, as well as functional characteristics of prokaryotic communities in the rhizosphere and non-rhizosphere soils of Picea asperata with different stand ages using high-throughput sequencing technique and bioinformatics methods. The results showed that β -diversity of soil prokaryotic communities in both rhizosphere and non-rhizosphere showed significant differences among different stand ages, but no significant difference between rhizosphere and non-rhizosphere in the same stand age. In terms of community composition at the phylum level, the relative abundances of Proteobacteria and Rokubacteria showed an increasing trend with the increases of stand age, while the relative abundance of Actinobacteria showed a decreasing trend, but no significant difference was observed between 75 year-old planted forests (PF75) and natural forests (NF). The relative abundances of Firmicutes and Thaumarchaeota in the soil of the 25 year-old planted forests (PF25) were significantly higher than in other planted forests and NF. At the genus level, the relative abundances of RB 41, Terrimonas and Acidibacter showed an increasing trend with the increases of stand age, and RB 41 and Terrimonas in rhizosphere soil of PF75 were significantly higher than those in NF . Soil properties and vegetation characteristics jointly influenced the structure of soil prokaryotic communities, with herb layer coverage, soil pH, total phosphorus, and total nitrogen as major drivers. The functional characteristics of soil prokaryotic communities were significantly different among different stand ages. The relative abundances of functions involved in carbon and nitrogen cycle, e.g ., cellulolysis and nitrification, decreased with the increases of stand age, whereas that of sulfate respiration involved in the sulfur cycle increased. We proposed that the structure and functional characteristics of soil prokaryotic communities could serve as important indicators of the development stages of P. asperata forests. In the later stages of plantation forest development, soil nutrient availability could be improved by mediating phosphorus-dissolving and nitrogen-enhancing microorganisms to maintain the stability of the plantation ecosystem.

More attention has been paid to the monitoring, assessment, prediction, early warning and sustainable management of regional ecological environment and the changes of ecosystem state in recent years. It is an important scientific and technological task to develop quantitative methods and numerical simulation techniques for ecosystem modelling, and to construct the continental scale numerical simulator with the characteristics of multi-process coupling, multi-technology integration, and multi-objective application for stimulating research on ecosystem and global change and its resources, environment and disaster effects, based on the in-depth understanding of the components, processes, functions, patterns, and their interaction mechanism of terrestrial ecosystem. Here, we reviewed the current status and future direction of terrestrial ecosystem models, and discussed the conceptual framework of developing the simulation system of dynamic change and spatial variation in large-scale terrestrial ecosystems and its resource and environment effect, as well as basic issues on the function orientation and structure design of the simulation system, which would provide reference for constructing Chinese terrestrial ecosystem numerical simulator.

Evapotranspiration (ET) is a fundamental flux in land surface hydrothermal process. Because of the differences in basic concepts, assumptions, application scales, different models have induced varying uncertainties to the estimation and simulation of evapotranspiration. With the Three-River-Source National Park as an example, we used the Bayesian model averaging (BMA) method to integrate the ET estimations from five models of PT-JPL, ARTS-GIMMS3, ARTS-MODIS, MODIS global evapotranspiration product (MOD16), and SSEBop, and tried to improve the estimating accuracy of evapotranspiration. The results showed that the five models could well capture the seasonal variations in evapotranspiration at Haibei Flux Station, with an explanation range of 64%-86% variability in the observed ET, and a root means square deviation (RMSD) ranged from 0.47 mm·(8 d) -1 to 0.76 mm·(8 d) -1 . BMA-based ET greatly improved its explanation to 89% and decreased the RMSD to 0.43 mm·(8 d) -1 . The Three-River-Source National Park experienced an overall insignificant increasing trend in its inter-annual ET from 2003 to 2015. At the regional scale, the effects of temperature and precipitation on evapotranspiration were not significant, but were significant in the Yangtze River Source Park. Temperature and precipitation had positive impacts on evapotranspiration. The evapotranspiration showed different trends due to the geographi-cal differences between parks. This study provided a method reference for other multi-source data integration analysis. The integrated evapotranspiration data could effectively reduce the uncertainty of the original models and provide a more accurate data basis for the study of regional water heat change, which is of great significance to better understand water cycle under climate changes.

Cosmic-ray neutron sensing (CRNS) is a new method for measuring mean soil moisture at regional scale. On the basis of continuous observation data of CRNS and the measurements of soil moisture with the distributed sensor network in Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences, we examined the applicability of the CRNS method to the agroecosystem in North China Plain. The stability of the neutron number in dry conditions (N 0 ) and the effects of rainfall and irrigation on soil moisture estimation were investigated. The results showed that N 0 was significantly affected by the underlying surface. The changes of N 0 corresponded well to the planting and harvesting time of winter wheat and summer maize. Soil moisture estimated by the CRNS method had obvious response to rainfall and irrigation. When irrigation or rainfall occurred, soil moisture was overestimated. The CRNS method could effectively estimate regional soil moisture for the agroecosystem in North China Plain. The estimates of soil moisture were closest to the soil moisture in 10 cm depth.

Based on the eddy covariance observations at 4 sites (2 forested sites and 2 grassland sites) in Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX), this paper analyzed the effects of three data processing methods, i.e., spike detection, threshold (u*c) determination of nocturnal friction velocity (u*), and gap-filling model selection, on the estimation of CO2 flux components. All the three methods had significant impacts on the estimation of annual net ecosystem exchange (NEE), and the determination of (u*c) was an important factor affecting the annual NEE estimation. The estimation deviation of the annual NEE caused by spike detection, determination of (u*c), and gap-filling model selection was 0.62-21.31 g C x m(-2) x a(-1) (0.84%-65.31%), 4.06-30.28 g C x m(-2) x a(-1) (3.76%-21.58%), and 0.69-27.73 g C x m(-2) x a(-1) (0.23%-55.62%), respectively. Comparing with that of forested ecosystem, the NEE estimation of grassland ecosystem was more sensitive to the parameter setting of data processing method, and the relative estimation deviation of annual gross ecosystem exchange and ecosystem respiration induced by the uncertainty in data processing was 3.88%-11.41% and 6.45%-24.91%, respectively.