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| 1 | Spatial patterns of ecosystem vulnerability changes during 2001–2011 in the three-river source region of the Qinghai-Tibetan Plateau, China显示文摘The three-river source region(TRSR, including Yangtze, Yellow and Lancang rivers), located in the Qinghai-Tibetan Plateau, China, is a typical alpine zone with apparent ecosystem vulnerability and sensitivity. In this paper, we introduced many interdisciplinary factors, such as landscape pattern indices(Shannon diversity index and Shannon evenness index) and extreme climate factors(number of extreme high temperature days, number of extreme low temperature days, and number of extreme precipitation days), to establish a new model for evaluating the spatial patterns of ecosystem vulnerability changes in the TRSR. The change intensity(CI) of ecosystem vulnerability was also analyzed. The results showed that the established evaluation model was effective and the ecosystem vulnerability in the whole study area was intensive. During the study period of 2001–2011, there was a slight degradation in the eco-environmental quality. The Yellow River source region had the best eco-environmental quality, while the Yangtze River source region had the worst one. In addition, the zones dominated by deserts were the most severely deteriorated areas and the eco-environmental quality of the zones occupied by evergreen coniferous forests showed a better change. Furthermore, the larger the change rates of the climate factors(accumulative temperature of ≥10°C and annual average precipitation) are, the more intensive the CI of ecosystem vulnerability is. This study would provide a scientific basis for the eco-environmental protection and restoration in the TRSR. | GUO Bing ZHOU Yi ZHU Jinfeng LIU Wenliang WANG Futao WANG Litao YAN Fuli WANG Feng YANG Guang LUO Wei JIANG Lin | 2016 | Journal of Arid Land2016，8，1： | 16 |
| 2 | Historic distribution and driving factors of human-caused fires in the Chinese boreal forest between 1972 and 2005显示文摘Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management.The aims of the study were:(i)to describe the history of human-caused fires by season and size of burned area over time;(ii)to identify the spatial patterns of human-caused fires and test for the existence of‘hotspots’to determine their exact locations in the Daxing’an mountains;(iii)to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire occurrence.Methods In this study,K-function and Kernel density estimation were used to analyze the spatial pattern of human-caused fires.The analysis was conducted in s-plus and arcgIs environments,respectively.The analysis of driving factors was performed in SPSS 19.0 based on a logistic regression model.The variables used to identify factors that influence fire occurrence included vegetation types,meteorological conditions,socioeconomic factors,topography and infrastructure factors,which were extracted and collected through the spatial analysis mode of arcgIs and from official statistics,respectively.Important Findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection act.There were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing’an mountains.The heterogeneity was caused by elevation,distance to the nearest railway,forest type and temperature.a logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing’an mountains;its global accuracy attained 64.8%.The model was thus comparable to other relevant studies. | Futao Guo John L.Innes Guangyu Wang Xiangqing Ma Long Sun Haiqing Hu Zhangwen Su | 2015 | Journal of Plant Ecology2015，8，5： | 10 |
| 3 | Dynamics of major air pollutants from crop residue burning in China's Mainland,2000–2014显示文摘Based on satellite image data and China's Statistical Yearbooks(2000 to 2014), we estimated the total mass of crop residue burned, and the proportion of residue burned in the field vs.indoors as domestic fuel. The total emissions of various pollutants from the burning of crop residue were estimated for 2000-2014 using the emission factor method. The results indicate that the total amount of crop residue and average burned mass were 8690.9 Tg and4914.6 Tg, respectively. The total amount of emitted pollutants including CO_2, CO, NOx,VOCs, PM_(2.5), OC(organic carbon), EC(element carbon) and TC(total carbon) were 4212.4–8440.9 Tg, 192.8–579.4 Tg, 4.8–19.4 Tg, 18.6–61.3 Tg, 18.8–49.7 Tg, 6.7–31.3 Tg, 2.3–4.7 Tg, and8.5–34.1 Tg, respectively. The emissions of pollutants released from crop residue burning were found to be spatially variable, with the burning of crop residue mainly occurring in Northeast, North and South China. In addition, pollutant emissions per unit area(10 km ×10 km) were mostly concentrated in the central and eastern regions of China. Emissions of CO_2, NOx, VOCs, OC and TC were mainly from rice straw burning, while burning of corn and wheat residues contributed most to emissions of CO, PM_(2.5) and EC. The increased ratio of PM_(2.5) emissions from crop residue burning to the total emitted from industry during the study period is attributed to the implementation of strict emissions management policies in Chinese industry. This study also provides baseline data for assessment of the regional atmospheric environment. | Quanfeng Jin Xiangqing Ma Guangyu Wang Xiajie Yang Futao Guo | 2018 | Journal of Environmental Sciences2018，30，8： | 9 |
| 4 | Coupled model constructed to simulate the landslide dam flood discharge:a case study of Baige landslide dam,Jinsha River显示文摘Landslide dam,always triggered by the strong earthquake and heavy rain,is a common natural disaster around the world.In this study,a coupled model was built by combining DB-IWHR model and the two-dimensional hydrodynamic model to simulate the landslide dam flood discharge.We mapped the maximum Baige landslide dam flood inundated area based on Gaofen-1 imagery,and then simulated the process of Baige landslide dam flood discharge using this coupled model.It was proved that,with 80.05%F values,the coupled model was suitable to simulate the process of landslide dam flood discharge.Lastly,multiple scenarios were simulated respectively by setting varying width and depth of spillway.The results of scenarios 1-4 indicated that spillway width presented low sensibility to the peak flow in spillway and the time of its arrival,and similarly to the water depth at river cross-section and the inundated area.Water depth at river cross-section and the inundated area decreased as spillway width increased.Even if spillway width varied at 10 m interval,the average variation of water depth was less than 1.82 m and the variation of inundated area was less than 2.85%.However,the results of scenarios 5-8 indicated that spillway depth was sensitive to the peak flow in spillway and its arrival time,and also to water depth at river cross-section and the inundated area.Water depth at river cross-section and the inundated area increased first and then started to drop with spillway depth kept decreasing.When spillway depth varied at only 2 m interval,the average variation of water depth at river cross-section basically exceeded 2 m and the variation of inundated area was more than 2.85%. | Hongjie WANG Yi ZHOU Shixin WANG Futao WANG | 2020 | Frontiers of Earth Science2020，14，1： | 3 |
| 5 | Adaptation of Asia-Pacific forests to climate change显示文摘Climate change is a threat to the stability and productivity of forest ecosystems throughout the AsiaPacific region. The loss of forests due to climate-induced stress will have extensive adverse impacts on biodiversity and an array of ecosystem services that are essential for the maintenance of local economies and public health. Despite their importance, there is a lack of decision-support tools required to evaluate the potential effects of climate change on Asia-Pacific ecosystems and economies and to aid in the development of regionally appropriate adaptation and mitigation strategies. The project Adaptation of AsiaPacific Forests to Climate Change, summarized herein,aims to address this lack of knowledge and tools and to provide support for regional managers to develop effective policy to increase the adaptive capacity of Asia-Pacific forest ecosystems. This objective has been achieved through the following activities:(1) development of a highresolution climate downscaling model, Climate AP, applicable to any location in the region;(2) development of climate niche models to evaluate how climate change might affect the distribution of suitable climatic conditions for regionally important tree species;(3) development and application of forest models to assess alternative management strategies in the context of management objectives and the projected impacts of climate change;(4) evaluation of models to assess forest fire risk and the relationship between forest fire and climate change;(5) development of a technique to assess ecosystem carbon storage using Li DAR; and(6) evaluation of how vegetation dynamics respond to climate change using remote sensing technology. All project outputs were developed with a focus on communication and extension to facilitate the dissemination of results to regional forest resource managers to support the development of effective mitigation and adaptation policy. | Guangyu Wang Tongli Wang Haijun Kang Shari Mang Brianne Riehl Brad Seely Shirong Liu Futao Guo Qinglin Li John L.Innes | 2016 | Journal of Forestry Research2016，27，3： | 2 |
| 6 | Overexpression of EphA2 correlates with epithelial–mesenchymal transition-related proteins in gastric cancer and their prognostic importance for postoperative patients显示文摘 | Futao Hou Weijie Yuan Jin Huang Liyuan Qian Zhikang Chen Jie Ge Shaobin Wu Jinxiang Chen Jixu Wang Zihua Chen | 2012 | Medical Oncology2012，，4： | 2 |
| 7 | Comparison of six generalized linear models for occurrence of lightning-induced fires in northern Daxing'an Mountains,China显示文摘The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion(i.e., variance is larger than mean) and a high frequency of zero counts. In this study, we used six generalized linear models to examine the relationship between the occurrence of lightning-induced forest fires and meteorological factors in the Northern Daxing'an Mountains of China. The six models included Poisson, negative binomial(NB), zeroinflated Poisson(ZIP), zero-inflated negative binomial(ZINB), Poisson hurdle(PH), and negative binomial hurdle(NBH) models. Goodness-of-fit was compared and tested among the six models using Akaike information criterion(AIC), sum of squared errors, likelihood ratio test, and Vuong test. The predictive performance of the models wasassessed and compared using independent validation data by the data-splitting method. Based on the model AIC, the ZINB model best fitted the fire occurrence data, followed by(in order of smaller AIC) NBH, ZIP, NB, PH, and Poisson models. The ZINB model was also best for predicting either zero counts or positive counts(C1). The two Hurdle models(PH and NBH) were better than ZIP,Poisson, and NB models for predicting positive counts, but worse than these three models for predicting zero counts.Thus, the ZINB model was the first choice for modeling the occurrence of lightning-induced forest fires in this study,which implied that the excessive zero counts of lightninginduced fires came from both structure and sampling zeros. | Futao Guo Guangyu Wang John L. Innes Zhihai Ma Aiqin Liu Yurui Lin | 2016 | Journal of Forestry Research2016，27，2： | 2 |
| 8 | Gamma generalized linear model to investigate the effects of climate variables on the area burned by forest fire in northeast China显示文摘The purpose of this study was to determine a suitable model for investigating the effects of climate factors on the area burned by forest fire in the Tahe forest region, Daxing'an Mountains, in northeast China. The response variables were the area burned by lightningcaused fire, human-caused fire, and total burned area. The predictor variables were nine climate variables collected from the local weather station. Three regression models were utilized, including multiple linear regression, loglinear model(log-transformation on both response and predictor variables), and gamma-generalized linear model.The goodness-of-fit of the models were compared based on model fitting statistics such as R^2, AIC, and RMSE. The results revealed that the gamma-generalized linear model was generally superior to both multiple linear regression model and log-linear model for fitting the fire data. Further,the best models were selected based on the criteria that the climate variables were statistically significant at a = 0.05.The gamma best models indicated that maximum wind speed, precipitation, and days that rainfall greater than0.1 mm had significant impacts on the area burned by the lightning-caused fire, while the mean temperature and minimum relative humidity were the main drivers of the burned area caused by human activities. Overall, the total burned area by forest fire was significantly influenced by days that rainfall greater than 0.1 mm and minimum relative humidity, indicating that the moisture condition of forest stands determine the burned area by forest fire. | Futao Guo Guangyu Wang John L. Innes Xiangqing Ma Long Sun Haiqing Hu | 2015 | Journal of Forestry Research2015，26，3： | 2 |
| 9 | FWENet:a deep convolutional neural network for flood water body extraction based on SAR images显示文摘As one of the most severe natural disasters in the world,floods caused substantial economic losses and casualties every year.Timely and accurate acquisition of flood inundation extent could provide technical support for relevant departments in the field of flood emergency response and disaster relief.Given the accuracy of existing research works extracting flood inundation extent based on Synthetic Aperture Radar(SAR)images and deep learning methods is relatively low,this study utilized Sentinel-1 SAR images as the data source and proposed a novel model named flood water body extraction convolutional neural network(FWENet)for flood information extraction.Then three classical semantic segmentation models(UNet,Deeplab v3 and UNet++)and two traditional water body extraction methods(Otsu global thresholding method and Object-Oriented method)were compared with the FWENet model.Furthermore,this paper analyzed the water body area change situations of Poyang Lake.The main results of this paper were as follows:Compared with other five water body extraction methods,the FWENet model achieved the highest water body extraction accuracy,its F1 score and mean intersection over union(mIoU)were 0.9871 and 0.9808,respectively.This study could guarantee the subsequent research on flood extraction based on SAR images. | Jingming Wang Shixin Wang Futao Wang Yi Zhou Zhenqing Wang Jianwan Ji Yibing Xiong Qing Zhao | 2022 | International Journal of Digital Earth2022，15，1： | 1 |
| 10 | Estimation of gases emitted by forest fires based on remote sensing data显示文摘Forest fire, an important agent for change in many forest ecosystems, plays an important role in atmospheric chemical cycles and the carbon cycle. The primary emissions from forest fire, CO_2, CO, CH_4, long-chained hydrocarbons and volatile organic oxides, however, have not been well quantified. Quantifying the carbonaceous gas emissions of forest fires is a critical part to better understand the significance of forest fire in calculating carbon balance and forecasting climate change. This study uses images from Enhanced Thematic Mapper Plus(ETM+) on the Earth-observing satellite LANDSAT-7 for the year 2005 to estimate the total gases emitted by the 2006 Kanduhe forest fire in the Daxing'an Mountains. Our results suggest that the fire emitted approximately149,187.66 tCO_2, 21,187.70 tCO, 1925.41 tC_xH_y, 470.76 t NO and 658.77 tSO_2. In addition, the gases emitted from larch forests were significantly higher than from both broadleaf-needle leaf mixed forests and broadleaf mixed forests. | Qiang Wang Futao Guo Haiqing Hu Sen Jin Zhangwen Su | 2016 | Journal of Forestry Research2016，27，2： | 0 |
| 11 | Erratum to: Adaptation of Asia-Pacific forests to climate change显示文摘During the final preparation of this manuscript, Craig R.Nitschke's name was inadvertently omitted from the list of authors. The corresponding author and all co-authors acknowledge that this was an error and that his name should be included amongst the authors of the manuscript. | Guangyu Wang Tongli Wang Haijun Kang Shari Mang Brianne Riehl Brad Seely Shirong Liu Futao Guo Qinglin Li Craig R. Nitschke John L. Innes | 2017 | Journal of Forestry Research2017，28，5： | 0 |
| 12 | Preparation of waterborne polyurethane/β-cyclodextrin composite nanosponge by ion condensation method and its application in removing of dyes from wastewater显示文摘Currently,polymer nanosponges have received extensive attention.However,developing new synthetic techniques for novel nanosponges remains a challenge.Furthermore,to date,composite nanosponge adsorbents based on waterborne polyurethane(WPU)andβ-cyclodextrin(β-CD)have not been reported.Herein,a novel green method,ion condensation method,was developed in this study for the preparation of polymer nanosponge adsorbents for efficient removal of dyes from wastewater.Based on the principle of charge repulsion between nanoparticles to maintain emulsion stability,waterborne polyurethane/β-cyclodextrin composite nanosponges(WPU-x,y)were prepared by coagulating the emulsions synthesized from 2,2-dimethylolpropionic acid,polypropylene glycol and hexamethylene diisocyanate as raw materials in a mixture of hydrochloric acid and anhydrous ethanol.The structure and appearance of WPU-x,y were characterized by attenuated total reflectance Fourier transform infrared spectroscopy,thermal gravimetric analyzer,scanning electron microscope and mercury intrusion porosimetry.The adsorption capacity of WPU-x,y was tested by parameters such as cross-linking degree,β-CD dosage,contact time,initial dye concentration and p H value.The study found that WPU-4,4.62 had the best adsorption effect on methylene blue(MB),the maximum removal rate was 93.42%,and the maximum adsorption capacity was 136.03 mg·g^(-1).Moreover,the Sips isotherm and pseudo-second-order-model were suitable for MB adsorption.Therefore,this study provides some perspectives for the fabrication of nanosponge adsorbents. | Shanghong Ma Haitao Zhang Jianbo Qu Xiuzhong Zhu Qingfei Hu Jianyong Wang Peng Ye Futao Sai Shiwei Chen | 2023 | Chinese Journal of Chemical Engineering2023，58，6： | 0 |
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