Combination of nitrogen deposition and ultraviolet-B radiation decreased litter decomposition in subtropical China - Song, Xinzhang; Zhang, Huiling; Jiang, Hong; Peng, Changhui (Plant and Soil, 2014)

Observed high and persistent carbon uptake by Moso bamboo forests and its response to environmental drivers - Song, Xinzhang; Chen, Xiaofeng; Zhou, Guomo; Jiang, Hong; Peng, Changhui (Agricultural and Forest Meteorology, 2017)

Chinese Grain for Green Program led to highly increased soil organic carbon levels: A meta-analysis - Song, Xinzhang; Peng, Changhui; Zhou, Guomo; Jiang, Hong; Wang, Weifeng (Scientific Reports, 2014)

Biochar amendment decreases soil microbial biomass and increases bacterial diversity in Moso bamboo ( Phyllostachys edulis ) plantations under simulated nitrogen deposition - Li, Quan; Lei, Zhaofeng; Song, Xinzhang; Zhang, Zhiting; Ying, Yeqing; Peng, Changhui (Environmental Research Letters, 2018)

Effects of nitrogen deposition and management practices on leaf litterfall and N and P return in a Moso bamboo forest - Zhang, Junbo; Lv, Jianhua; Li, Quan; Ying, Yeqing; Peng, Changhui; Song, Xinzhang (Biogeochemistry, 2017)

Dynamic allocation and transfer of non-structural carbohydrates, a possible mechanism for the explosive growth of Moso bamboo (Phyllostachys heterocycla) - Song, Xinzhang; Peng, Changhui; Zhou, Guomo; Gu, Honghao; Li, Quan; Zhang, Chao (Scientific Reports, 2016)
Abstract Moso bamboo can rapidly complete its growth in both height and diameter within only 35–40 days after shoot emergence. However, the underlying mechanism for this “explosive growth” remains poorly understood. We investigated the dynamics of non-structural carbohydrates (NSCs) in shoots and attached mature bamboos over a 20-month period. The results showed that Moso bamboos rapidly completed their height and diameter growth within 38 days. At the same time, attached mature bamboos transferred almost all the NSCs of their leaves, branches and especially trunks and rhizomes to the “explosively growing” shoots via underground rhizomes for the structural growth and metabolism of shoots. Approximately 4 months after shoot emergence, this transfer stopped when the leaves of the young bamboos could independently provide enough photoassimilates to meet the carbon demands of the young bamboos. During this period, the NSC content of the leaves, branches, trunks and rhizomes of mature bamboos declined by 1.5, 23, 28 and 5 fold, respectively. The trunk contributed the most NSCs to the shoots. Our findings provide new insight and a possible rational mechanism explaining the “explosive growth” of Moso bamboo and shed new light on understanding the role of NSCs in the rapid growth of Moso bamboo.

Interactive effects of elevated UV-B radiation and N deposition on decomposition of Moso bamboo litter - Song, Xinzhang; Jiang, Hong; Zhang, Zhiting; Zhou, Guomo; Zhang, Shuikui; Peng, Changhui (Soil Biology and Biochemistry, 2014)

Direct and Indirect Effects of UV-B Exposure on Litter Decomposition: A Meta-Analysis - Song, Xinzhang; Peng, Changhui; Jiang, Hong; Zhu, Qiuan; Wang, Weifeng (PLoS ONE, 2013)

Quantifying the effects of climate change and harvesting on carbon dynamics of boreal aspen and jack pine forests using the TRIPLEX-Management model - Wang, Weifeng; Peng, Changhui; Kneeshaw, Daniel D.; Larocque, Guy R.; Song, Xinzhang; Zhou, Xiaolu (Forest Ecology and Management, 2012)

Biochar mitigates dissolved organic carbon loss but does not affect dissolved organic nitrogen leaching loss caused by nitrogen deposition in Moso bamboo plantations - Lei, Zhaofeng; Li, Quan; Song, Xinzhang; Wang, Weifeng; Zhang, Zhiting; Peng, Changhui; Tian, Linlin (Global Ecology and Conservation, 2018)

MODELING INDIVIDUAL TREE MORTALITY RATES USING MARGINAL AND RANDOM EFFECTS REGRESSION MODELS - Ma, Zhihai; Peng, Changhui; Li, Weizhong; Zhu, Qiuan; Wang, Weifeng; Song, Xinzhang; Liu, Jianwei (Natural Resource Modeling, 2013)
A bstract Developing models to predict tree mortality using data from long‐term repeated measurement data sets can be difficult and challenging due to the nature of mortality as well as the effects of dependence on observations. Marginal (population‐averaged) generalized estimating equations (GEE) and random effects (subject‐specific) models offer two possible ways to overcome these effects. For this study, standard logistic, marginal logistic based on the GEE approach, and random logistic regression models were fitted and compared. In addition, four model evaluation statistics were calculated by means of K ‐fold cross‐valuation. They include the mean prediction error, the mean absolute prediction error, the variance of prediction error, and the mean square error. Results from this study suggest that the random effects model produced the smallest evaluation statistics among the three models. Although marginal logistic regression accommodated for correlations between observations, it did not provide noticeable improvements of model performance compared to the standard logistic regression model that assumed impendence. This study indicates that the random effects model was able to increase the overall accuracy of mortality modeling. Moreover, it was able to ascertain correlation derived from the hierarchal data structure as well as serial correlation generated through repeated measurements.

Elevated UV-B radiation increased the decomposition of Cinnamomum camphora and Cyclobalanopsis glauca leaf litter in subtropical China - Song, Xinzhang Z.; Zhang, Huiling L.; Chang, Scott X.; Jiang, Hong; Peng, Changhui H.; Yu, Shuquan Q. (Journal of Soils and Sediments, 2012)

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009 - Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui (Journal of Applied Remote Sensing, 2014)

Quantification of soil respiration in forest ecosystems across China - Song, Xinzhang; Peng, Changhui; Zhao, Zhengyong; Zhang, Zhiting; Guo, Baohua; Wang, Weifeng; Jiang, Hong; Zhu, Qiuan (Atmospheric Environment, 2014)

Carbon sequestration by Chinese bamboo forests and their ecological benefits: assessment of potential, problems, and future challenges - Song, Xinzhang; Zhou, Guomo; Jiang, Hong; Yu, Shuquan; Fu, Jinhe; Li, Weizhong; Wang, Weifeng; Ma, Zhihai; Peng, Changhui (Environmental Reviews, 2011)

Model prediction of biome‐specific global soil respiration from 1960 to 2012 - Zhao, Zhengyong; Peng, Changhui; Yang, Qi; Meng, Fan‐Rui; Song, Xinzhang; Chen, Shutao; Epule, Terence Epule; Li, Peng; Zhu, Qiuan (Earth's Future, 2017)
Abstract Biome‐specific soil respiration (Rs) has important yet different roles in both the carbon cycle and climate change from regional to global scales. To date, no comparable studies related to global biome‐specific Rs have been conducted applying comprehensive global Rs databases. The goal of this study was to develop artificial neural network ( ANN ) models capable of spatially estimating global Rs and to evaluate the effects of interannual climate variations on 10 major biomes. We used 1976 annual Rs field records extracted from global Rs literature to train and test the ANN models. We determined that the best ANN model for predicting biome‐specific global annual Rs was the one that applied mean annual temperature ( MAT ), mean annual precipitation ( MAP ), and biome type as inputs ( r 2 = 0.60). The ANN models reported an average global Rs of 93.3 ± 6.1 Pg C yr −1 from 1960 to 2012 and an increasing trend in average global annual Rs of 0.04 Pg C yr −1 . Estimated annual Rs increased with increases in MAT and MAP in cropland, boreal forest, grassland, shrubland, and wetland biomes. Additionally, estimated annual Rs decreased with increases in MAT and increased with increases in MAP in desert and tundra biomes, and only significantly decreased with increases in MAT ( r 2 = 0.87) in the savannah biome. The developed biome‐specific global Rs database for global land and soil carbon models will aid in understanding the mechanisms underlying variations in soil carbon dynamics and in quantifying uncertainty in the global soil carbon cycle. , Key Points Predict biome‐specific global soil respiration from 1960 to 2012 using an artificial neural network model Prediction determined an average global soil respiration of 93.3 ± 6.1 Pg C yr −1 and an increasing trend of 0.04 Pg C yr −1 The 10 biome‐specific soil respiration estimates made it possible to trace different responses to global climate change in each biome

Nitrogen depositions increase soil respiration and decrease temperature sensitivity in a Moso bamboo forest - Li, Quan; Song, Xinzhang; Chang, Scott X.; Peng, Changhui; Xiao, Wenfa; Zhang, Junbo; Xiang, Wenhua; Li, Yan; Wang, Weifeng (Agricultural and Forest Meteorology, 2019)

Linkage between tree species richness and soil microbial diversity improves phosphorus bioavailability - Wu, Huili; Xiang, Wenhua; Ouyang, Shuai; Forrester, David I.; Zhou, Bo; Chen, Lingxiu; Ge, Tida; Lei, Pifeng; Chen, Liang; Zeng, Yelin; Song, Xinzhang; Peñuelas, Josep; et al. (Functional Ecology, 2019)
Abstract Increased availability of soil phosphorus (P) has recently been recognised as an underlying driving factor for the positive relationship between plant diversity and ecosystem function. The effects of plant diversity on the bioavailable forms of P involved in biologically mediated rhizospheric processes and how the link between plant and soil microbial diversity facilitates soil P bioavailability, however, remain poorly understood. This study quantified four forms of bioavailable P (CaCl 2 ‐P, citric‐P, enzyme‐P and HCl‐P) in mature subtropical forests using a novel biologically based approach, which emulates how rhizospheric processes influence the release and supply of available P. Soil microbial diversity was measured by Illumina high‐throughput sequencing. Our results suggest that tree species richness significantly affects soil microbial diversity ( p < 0.05), increases litter decomposition, fine‐root biomass and length and soil organic carbon and thus increases the four forms of bioavailable P. A structural equation model that links plants, soil microbes and P forms indicated that soil bacterial and fungal diversity play dominant roles in mediating the effects of tree species richness on soil P bioavailability. An increase in the biodiversity of plants, soil bacteria and fungi could maintain soil P bioavailability and alleviate soil P limitations. Our results imply that biodiversity strengthens plant and soil feedback and increases P recycling. A plain language summary is available for this article.