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.

Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction - Li, Weizhong; Peng, Changhui; Zhou, Xiaolu; Sun, Jianfeng; Zhu, Qiuan; Wu, Haibin; St-Onge, Benoit (Ecosphere, 2015)
It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process‐based ecological models and data in cohesive, systematic ways. In process‐based model applications, inherent spatial and temporal heterogeneities found within terrestrial ecosystems may lead to the uncertainties of model predictions. To reduce simulation uncertainties due to inaccurate model parameters, the Markov Chain Monte Carlo (MCMC) method was applied in this study to improve the estimations of four key parameters used in the process‐based ecosystem model of TRIPLEX‐FLUX. These four key parameters include a maximum photosynthetic carboxylation rate of 25°C (Vmax), an electron transport (Jmax) light‐saturated rate within the photosynthetic carbon reduction cycle of leaves, a coefficient of stomatal conductance (m), and a reference respiration rate of 10°C (R10). Seven forest flux tower sites located across North America were used to investigate and facilitate understanding of the daily variation in model parameters for three deciduous forests, three evergreen temperate forests, and one evergreen boreal forest. Eddy covariance CO 2 exchange measurements were assimilated to optimize the parameters in the year 2006. After parameter optimization and adjustment took place, net ecosystem production prediction significantly improved (by approximately 25%) compared to the CO 2 flux measurements taken at the seven forest ecosystem sites. Results suggest that greater seasonal variability occurs in broadleaf forests in respect to the selected parameters than in needleleaf forests. This study also demonstrated that the model‐data fusion approach by incorporating MCMC method is able to better estimate parameters and improve simulation accuracy for different ecosystems located across North America.

Monitoring the impact of aerosol contamination on the drought-induced decline of gross primary productivity - Zhang, Yao; Li, Weizhong; Zhu, Qiuan; Chen, Huai; Fang, Xiuqin; Zhang, Tinglong; Zhao, Pengxiang; Peng, Changhui (International Journal of Applied Earth Observation and Geoinformation, 2015)

Monitoring and estimating drought-induced impacts on forest structure, growth, function, and ecosystem services using remote-sensing data: recent progress and future challenges - Zhang, Yao; Peng, Changhui; Li, Weizhong; Fang, Xiuqin; Zhang, Tinglong; Zhu, Qiuan; Chen, Huai; Zhao, Pengxiang (Environmental Reviews, 2013)
Alongside global warming, droughts are expected to increase in frequency, severity, and extent in the near future, which will likely result in significant impacts on forest growth, production, structure, composition, and ecosystem services. However, due to spatial and temporal characteristics, it is difficult to monitor and assess the potential effects of droughts. Remote sensing can provide an effective way to obtain real-time conditions of forests affected by drought and offer a range of spatial and temporal insights into drought-induced changes to forest ecosystem structure, function, and services. Remote sensing is rapidly developing as more satellites are launched. In situ and remotely sensed data fusion techniques have achieved notable success in assessing drought-induced damage to forests and carbon cycles. Even so, constraints still exist when using satellite data. The objectives of this review are to (1) briefly review existing data sources and methods of remote sensing; (2) synthesize current applications and contributions of remote sensing in monitoring and estimating impacts of droughts on forest ecosystems; and (3) highlight research gaps and future challenges.

Climate change mitigation potential of kitchen waste utilization in China for combined heat and power production - Liu, Weiguo; Zhang, Dan; Tian, Jiajing; Yu, Feiyan; Xie, Yuanming; Cheng, Shengkui; Li, Qiang; Li, Weizhong; Peng, Changhui; Yan, Yan (Science of The Total Environment, 2023)

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests - Ma, Zhihai; Peng, Changhui; Zhu, Qiuan; Chen, Huai; Yu, Guirui; Li, Weizhong; Zhou, Xiaolu; Wang, Weifeng; Zhang, Wenhua (Proceedings of the National Academy of Sciences, 2012)
The boreal forests, identified as a critical “tipping element” of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change–induced droughts continue to intensify.

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)

A drought-induced pervasive increase in tree mortality across Canada's boreal forests - Peng, Changhui; Ma, Zhihai; Lei, Xiangdong; Zhu, Qiuan; Chen, Huai; Wang, Weifeng; Liu, Shirong; Li, Weizhong; Fang, Xiuqin; Zhou, Xiaolu (Nature Climate Change, 2011)

Methane emissions from the surface of the Three Gorges Reservoir: CH4 EMISSIONS FROM TGR - Chen, Huai; Yuan, Xingzhong; Chen, Zhongli; Wu, Yuyuan; Liu, Xianshu; Zhu, Dan; Wu, Ning; Zhu, Qiu'an; Peng, Changhui; Li, Weizhong (Journal of Geophysical Research: Atmospheres, 2011)

Detecting One-Hundred-Year Environmental Changes in Western China Using Seven-Year Repeat Photography - Chen, Huai; Yin, Kaipu; Wang, Haiyan; Zhong, Shenxian; Wu, Ning; Shi, Fusun; Zhu, Dan; Zhu, Qiuan; Wang, Weifeng; Ma, Zhihai; Fang, Xiuqin; Li, Weizhong; et al. (PLoS ONE, 2011)