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Existing research on autumn vegetation phenology is limited to phenological responses to gradual climate change. Considerably less attention has been paid to extreme climate events, resulting in a substantial gap in our understanding of the climatic response mechanism of vegetation autumn phenology. Therefore, in the present study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) observations to explore the responses of autumn phenology to extreme climate events (e.g., frost, heat, wetness, and drought) across the Tibetan Plateau (TP) from 2000 to 2018. We found that preseason drought and high heat stress generally induced early vegetation dormancy onset date (DOD) in most regions of the TP, whereas moderate heat and rainfall delayed the DOD in the agriculture and steppe ecoregions. Overall, cold and heat stress markedly affected the DOD in most ecoregions, whereas water stress (wetness and drought) mainly influenced the DOD in the meadow and steppe ecoregions. Modeling based on partial least squares regression (PLS), which considered these extreme climate events, predicted an earlier DOD (1.9–3.1 days earlier for RCP4.5 and 12.2–14.3 days earlier for RCP8.5) at the end of this century than traditional projections. Our findings demonstrate the combined influence of multiple extreme climate stress events on autumn vegetation phenology on the TP and highlight the need to integrate extreme climate events into future vegetation phenology models.
Peng Li; Zelin Liu; Xiaolu Zhou; Binggeng Xie; Zhongwu Li; Yunpeng Luo; Qiuan Zhu; Changhui Peng. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change. Agricultural and Forest Meteorology 2021, 308-309, 108571 .
AMA StylePeng Li, Zelin Liu, Xiaolu Zhou, Binggeng Xie, Zhongwu Li, Yunpeng Luo, Qiuan Zhu, Changhui Peng. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change. Agricultural and Forest Meteorology. 2021; 308-309 ():108571.
Chicago/Turabian StylePeng Li; Zelin Liu; Xiaolu Zhou; Binggeng Xie; Zhongwu Li; Yunpeng Luo; Qiuan Zhu; Changhui Peng. 2021. "Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change." Agricultural and Forest Meteorology 308-309, no. : 108571.
Elevation gradients are frequently treated as useful space-for-time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls along elevation gradients. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass (Nmass), leaf nitrogen per unit area (Narea), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal-to-ambient CO2 ratio (Ci:Ca, termed χ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analysed using multivariate analysis and variance partitioning procedures. We found that (1) LMA, Narea and LT captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (2) Nmass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapour pressure deficit (VPD), while χ showed negative relationships with elevation; and (3) 78% of the variation in the studied plant functional traits could be explained by climate, soil and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning.
Yanzheng Yang; Ruikun Gou; Wei Li; Jalal Kassout; Jun Wu; Liming Wang; Changhui Peng; Guanghui Lin. Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient. Journal of Geophysical Research: Biogeosciences 2021, 126, 1 .
AMA StyleYanzheng Yang, Ruikun Gou, Wei Li, Jalal Kassout, Jun Wu, Liming Wang, Changhui Peng, Guanghui Lin. Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient. Journal of Geophysical Research: Biogeosciences. 2021; 126 (7):1.
Chicago/Turabian StyleYanzheng Yang; Ruikun Gou; Wei Li; Jalal Kassout; Jun Wu; Liming Wang; Changhui Peng; Guanghui Lin. 2021. "Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient." Journal of Geophysical Research: Biogeosciences 126, no. 7: 1.
Understanding the impacts of nitrogen (N) addition on soil respiration (RS) and its temperature sensitivity (Q10) in tropical forests is very important for the global carbon cycle in a changing environment. Here, we investigated how RS respond to N addition in a tropical montane rainforest in Southern China. Four levels of N treatments (0, 25, 50, and 100 kg N ha−1 a−1 as control (CK), low N (N25), moderate N (N50), and high N (N100), respectively) were established in September 2010. Based on a static chamber-gas chromatography method, RS was measured from January 2015 to December 2018. RS exhibited significant seasonal variability, with low RS rates appeared in the dry season and high rates appeared in the wet season regardless of treatment. RS was significantly related to the measured soil temperature and moisture. Our results showed that soil RS increased after N additions, the mean annual RS was 7% higher in N25 plots, 8% higher in N50 plots, and 11% higher in N100 plots than that in the CK plots. However, the overall impacts of N additions on RS were statistically insignificant. For the entire study period, the CK, N25, N50, and N100 treatments yielded Q10 values of 2.27, 3.45, 4.11, and 2.94, respectively. N addition increased the temperature sensitivity (Q10) of RS. Our results suggest that increasing atmospheric N deposition may have a large impact on the stimulation of soil CO2 emissions from tropical rainforests in China.
Fangtao Wu; Changhui Peng; Weiguo Liu; Zhihao Liu; Hui Wang; Dexiang Chen; Yide Li. Effects of Nitrogen Additions on Soil Respiration in an Asian Tropical Montane Rainforest. Forests 2021, 12, 802 .
AMA StyleFangtao Wu, Changhui Peng, Weiguo Liu, Zhihao Liu, Hui Wang, Dexiang Chen, Yide Li. Effects of Nitrogen Additions on Soil Respiration in an Asian Tropical Montane Rainforest. Forests. 2021; 12 (6):802.
Chicago/Turabian StyleFangtao Wu; Changhui Peng; Weiguo Liu; Zhihao Liu; Hui Wang; Dexiang Chen; Yide Li. 2021. "Effects of Nitrogen Additions on Soil Respiration in an Asian Tropical Montane Rainforest." Forests 12, no. 6: 802.
Globally, increasing drought-induced tree mortality rates under climate change are projected to have far-reaching effects on forest ecosystems. Among these forest systems, the boreal forest is considered a ‘tipping element’ of the Earth's climate system. This forest biome plays a critical role in ecosystem services, structures and functions while being highly sensitive to drought stress. Although process-based models are important tools in ecological research, very few have yet been developed that integrate advanced physiological mechanisms to simulate drought-induced mortality in boreal forests. Accordingly, based on the process-based TRIPLEX model, this study introduces the new TRIPLEX-Mortality submodule for the Canadian boreal forests at the stand level, that for the first time successfully incorporates two advanced drought-induced physiological mortality mechanisms (i.e., hydraulic failure and carbon starvation). To calibrate and validate the model, 73 permanent sample plots (PSPs) were selected across Canada's boreal forests. Results confirm a good agreement between simulated mortality and mortality observations (R2=0.79; P<0.01; IA=0.94), demonstrating good model performance in simulating drought-induced mortality in boreal forests. Sensitivity analysis indicated that parameter sensitivity increased as drought intensified, and the shape parameter (c) for calculating percentage loss of conductivity (PLC) was the most sensitive parameter (average SI = -3.51) to simulate tree mortality. Furthermore, the results of model input sensitivity analysis also showed that the model can capture changes in mortality under different drought scenarios. Consequently, our model is suitable for simulating drought-induced mortality in boreal forests while also providing new insight into improving model simulations for tree mortality and associated carbon dynamics in a progressively warmer and drier world.
Qiuyu Liu; Changhui Peng; Robert Schneider; Dominic Cyr; Zelin Liu; Xiaolu Zhou; Daniel Kneeshaw. TRIPLEX-Mortality model for simulating drought-induced tree mortality in boreal forests: Model development and evaluation. Ecological Modelling 2021, 455, 109652 .
AMA StyleQiuyu Liu, Changhui Peng, Robert Schneider, Dominic Cyr, Zelin Liu, Xiaolu Zhou, Daniel Kneeshaw. TRIPLEX-Mortality model for simulating drought-induced tree mortality in boreal forests: Model development and evaluation. Ecological Modelling. 2021; 455 ():109652.
Chicago/Turabian StyleQiuyu Liu; Changhui Peng; Robert Schneider; Dominic Cyr; Zelin Liu; Xiaolu Zhou; Daniel Kneeshaw. 2021. "TRIPLEX-Mortality model for simulating drought-induced tree mortality in boreal forests: Model development and evaluation." Ecological Modelling 455, no. : 109652.
Terrestrial ecosystems provide multiple services interacting in complex ways. However, most ecosystem services (ESs) models (e.g., InVEST and ARIES) ignored the relationships among ESs. Process-based models can overcome this limitation, and the integration of ecological models with remote sensing data could greatly facilitate the investigation of the complex ecological processes. Therefore, based on the Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA) models, we developed a process-based ES model (CEVSA-ES) integrating remotely sensed leaf area index to evaluate four important ESs (i.e., productivity provision, carbon sequestration, water retention, and soil retention) at annual timescale in China. Compared to the traditional terrestrial biosphere models, the main innovation of CEVSA-ES model was the consideration of soil erosion processes and its impact on carbon cycling. The new version also improved the carbon-water cycle algorithms. Then, the Sobol and DEMC methods that integrated the CEVSA-ES model with nine flux sites comprising 39 site-years were used to identify and optimize parameters. Finally, the model using the optimized parameters was validated at 26 field sites comprising 135 site-years. Simulation results showed good fits with ecosystem processes, explaining 95%, 92%, 76%, and 65% interannual variabilities of gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration, respectively. The CEVSA-ES model performed well for productivity provision and carbon sequestration, which explained 96% and 81% of the spatial-temporal variations of the observed annual productivity provision and carbon sequestration, respectively. The model also captured the interannual trends of water retention and soil erosion for most sites or basins.
Zhongen Niu; Honglin He; Shushi Peng; Xiaoli Ren; Li Zhang; Fengxue Gu; Gaofeng Zhu; Changhui Peng; Pan Li; Junbang Wang; Rong Ge; Na Zeng; Xiaobo Zhu; Yan Lv; Qingqing Chang; Qian Xu; Mengyu Zhang; Weihua Liu. A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services. Journal of Advances in Modeling Earth Systems 2021, 13, 1 .
AMA StyleZhongen Niu, Honglin He, Shushi Peng, Xiaoli Ren, Li Zhang, Fengxue Gu, Gaofeng Zhu, Changhui Peng, Pan Li, Junbang Wang, Rong Ge, Na Zeng, Xiaobo Zhu, Yan Lv, Qingqing Chang, Qian Xu, Mengyu Zhang, Weihua Liu. A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services. Journal of Advances in Modeling Earth Systems. 2021; 13 (6):1.
Chicago/Turabian StyleZhongen Niu; Honglin He; Shushi Peng; Xiaoli Ren; Li Zhang; Fengxue Gu; Gaofeng Zhu; Changhui Peng; Pan Li; Junbang Wang; Rong Ge; Na Zeng; Xiaobo Zhu; Yan Lv; Qingqing Chang; Qian Xu; Mengyu Zhang; Weihua Liu. 2021. "A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services." Journal of Advances in Modeling Earth Systems 13, no. 6: 1.
Establishing forest plantations is an important solution to the growing conflict between an increasing human population and mounting pressure to protect the natural forests, as plantations also harbor great potential for providing multiple ecosystem services (ESs). However, because of the trade-offs between multiple ESs and the conflicts between different stakeholders, the sustainable management of plantations has been exceedingly challenging. Especially in recent years, with China's emphasis on ecological civilization construction and sustainable development, forestry departments have begun to focus on long-term ecological benefits, which conflict with farmers' attention to short-term economic gains. In this study, we quantified 15 field-based ES indicators from the data measured in Chinese fir (Cunninghamia lanceolata) plantations aged 4 to 32 years. Corresponding to the concerns of two different stakeholders (forestry departments and farmers), we calculated ES-multifunctionality with different thresholds under four management scenarios: equal weight, production only, production multifunctionality, and supporting multifunctionality. Our results suggested pronounced stand age effects on both individual ESs and ES-multifunctionality of plantations. For individual ESs, stand age had a greater impact on provisioning services than on supporting services. High degree of trade-offs existed between plantation provisioning ESs and soil nutrient supporting ESs, and between water relevant ESs and the other ESs. With respect to ES-multifunctionality, the values under different scenarios were all augmented with stand age, but to differing degrees. The values for supporting multifunctionality were higher than those of production multifunctionality and production only before 21 years of stand development, but completely reversed once the fir plantations reached an age of 25 years. Finally, several stage-based plantation management recommendations are proposed to minimize conflicts between different stakeholders. Our results combined measures of temporal stability and multifunctionality, thereby providing valuable and timely insight into the multifunctional stability of plantations represented by Chinese fir.
Yelin Zeng; Huili Wu; Shuai Ouyang; Liang Chen; Xi Fang; Changhui Peng; Shirong Liu; Wenfa Xiao; Wenhua Xiang. Ecosystem service multifunctionality of Chinese fir plantations differing in stand age and implications for sustainable management. Science of The Total Environment 2021, 788, 147791 .
AMA StyleYelin Zeng, Huili Wu, Shuai Ouyang, Liang Chen, Xi Fang, Changhui Peng, Shirong Liu, Wenfa Xiao, Wenhua Xiang. Ecosystem service multifunctionality of Chinese fir plantations differing in stand age and implications for sustainable management. Science of The Total Environment. 2021; 788 ():147791.
Chicago/Turabian StyleYelin Zeng; Huili Wu; Shuai Ouyang; Liang Chen; Xi Fang; Changhui Peng; Shirong Liu; Wenfa Xiao; Wenhua Xiang. 2021. "Ecosystem service multifunctionality of Chinese fir plantations differing in stand age and implications for sustainable management." Science of The Total Environment 788, no. : 147791.
Alpine wetlands are an important natural source of methane (CH4) to the atmosphere. However, the temporal variations and main driving factors of CH4 fluxes in alpine wetlands are not yet well understood. In this study, CH4 fluxes were measured from an alpine wetland in the Qinghai Lake using eddy covariance (EC) technique. Strong seasonal variability in the daily CH4 fluxes was observed, ranging from − 18.24 mg CH4 m− 2 d− 1 during the non-growing season to 117.44 mg CH4 m− 2 d− 1 during the growing season in 2017. The annual CH4 budget was 9.41 g CH4 m− 2. The growing season CH4 flux accounted for 91.5 % of the annual budget. At the daily scale, the CH4 fluxes increased significantly as the net radiation, air temperature, vapor pressure deficit, soil temperature, and soil volumetric water content at 5 cm depth increased. Additionally, correlation analysis also revealed that daily CH4 flux was significantly related to CO2 flux when daily CO2 flux was negative, but there was no correlation when daily CO2 flux was positive. Path analysis showed that seasonal variations of soil temperature at 5 cm depth and CO2 flux had strong direct effects on daily CH4 fluxes.
Fangtao Wu; Shengkui Cao; Guangchao Cao; Kelong Chen; Changhui Peng. The Characteristics and Seasonal Variation of Methane Fluxes From an Alpine Wetland in the Qinghai Lake watershed, China. Wetlands 2021, 41, 1 -11.
AMA StyleFangtao Wu, Shengkui Cao, Guangchao Cao, Kelong Chen, Changhui Peng. The Characteristics and Seasonal Variation of Methane Fluxes From an Alpine Wetland in the Qinghai Lake watershed, China. Wetlands. 2021; 41 (5):1-11.
Chicago/Turabian StyleFangtao Wu; Shengkui Cao; Guangchao Cao; Kelong Chen; Changhui Peng. 2021. "The Characteristics and Seasonal Variation of Methane Fluxes From an Alpine Wetland in the Qinghai Lake watershed, China." Wetlands 41, no. 5: 1-11.
Few studies have focused on the combined impact of climate change, CO2, and land-use cover change (LUCC), especially the evaluation of the impact of LUCC on net primary productivity (NPP) in the future. In this study, we simulated the overall NPP change trend from 2010 to 2100 and its response to climatic factors, CO2 concentration, and LUCC conditions under three typical emission scenarios (Representative Concentration Pathway RCP2.6, RCP4.5, and RCP8.5). (1) Under the predicted global pattern, NPP showed an increasing trend, with the most prominent variation at the end of the century. The increasing trend is mainly caused by the positive effect of CO2 on NPP. However, the increasing trend of LUCC has only a small positive effect. (2) Under the RCP 8.5 scenario, from 2090 to 2100, CO2 has the most significant positive impact on tropical areas, reaching 8.328 Pg C Yr−1. Under the same conditions, climate change has the greatest positive impact on the northern high latitudes (1.175 Pg C Yr−1), but it has the greatest negative impact on tropical areas, reaching −4.842 Pg C Yr−1. (3) The average contribution rate of LUCC to NPP was 6.14%. Under the RCP8.5 scenario, LUCC made the largest positive contribution on NPP (0.542 Pg C Yr−1) globally from 2010 to 2020.
Xiao Hu; Yujie He; Ze Kong; Jiang Zhang; Minshu Yuan; Le Yu; Changhui Peng; Qiuan Zhu. Evaluation of Future Impacts of Climate Change, CO2, and Land Use Cover Change on Global Net Primary Productivity Using a Processed Model. Land 2021, 10, 365 .
AMA StyleXiao Hu, Yujie He, Ze Kong, Jiang Zhang, Minshu Yuan, Le Yu, Changhui Peng, Qiuan Zhu. Evaluation of Future Impacts of Climate Change, CO2, and Land Use Cover Change on Global Net Primary Productivity Using a Processed Model. Land. 2021; 10 (4):365.
Chicago/Turabian StyleXiao Hu; Yujie He; Ze Kong; Jiang Zhang; Minshu Yuan; Le Yu; Changhui Peng; Qiuan Zhu. 2021. "Evaluation of Future Impacts of Climate Change, CO2, and Land Use Cover Change on Global Net Primary Productivity Using a Processed Model." Land 10, no. 4: 365.
Intense and frequent drought events strongly affect plant survival. Non-structural carbohydrates (NSCs) are important “buffers” to maintain plant functions under drought conditions. We conducted a drought manipulation experiment using three-year-old Pinus tabulaeformis Carr. seedlings. The seedlings were first treated under different drought intensities (i.e., no irrigation, severe, and moderate) for 50 days, and then they were re-watered for 25 days to explore the dynamics of NSCs in the leaves, twigs, stems, and roots. The results showed that the no irrigation and severe drought treatments significantly reduced photosynthetic rate by 93.9% and 32.6% for 30 days, respectively, leading to the depletion of the starch storage for hydraulic repair, osmotic adjustment, and plant metabolism. The seedlings under moderate drought condition also exhibited starch storage consumption in leaves and twigs. After re-watering, the reduced photosynthetic rate recovered to the control level within five days in the severe drought group but showed no sign of recovery in the no irrigation group. The seedlings under the severe and moderate drought conditions tended to invest newly fixed C to starch storage and hydraulic repair instead of growth due to the “drought legacy effect”. Our findings suggest the depletion and recovery of starch storage are important strategies for P. tabulaeformis seedlings, and they may play key roles in plant resistance and resilience under environmental stress.
Xinyi Guo; Changhui Peng; Tong Li; Jingjing Huang; Hanxiong Song; Qiuan Zhu; Meng Wang. The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings. Biology 2021, 10, 281 .
AMA StyleXinyi Guo, Changhui Peng, Tong Li, Jingjing Huang, Hanxiong Song, Qiuan Zhu, Meng Wang. The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings. Biology. 2021; 10 (4):281.
Chicago/Turabian StyleXinyi Guo; Changhui Peng; Tong Li; Jingjing Huang; Hanxiong Song; Qiuan Zhu; Meng Wang. 2021. "The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings." Biology 10, no. 4: 281.
Forest soils play an important role in controlling global warming by reducing atmospheric methane (CH4) concentrations. However, little attention has been paid to how nitrogen (N) deposition may alter microorganism communities that are related to the CH4 cycle or CH4 oxidation in subtropical forest soils. We investigated the effects of N addition (0, 30, 60, or 90 kg N ha−1 yr−1) on soil CH4 flux and methanotroph and methanogen abundance, diversity, and community structure in a Moso bamboo (Phyllostachys edulis) forest in subtropical China. N addition significantly increased methanogen abundance but reduced both methanotroph and methanogen diversity. Methanotroph and methanogen community structures under the N deposition treatments were significantly different from those of the control. In N deposition treatments, the relative abundance of Methanoculleus was significantly lower than that in the control. Soil pH was the key factor regulating the changes in methanotroph and methanogen diversity and community structure. The CH4 emission rate increased with N addition and was negatively correlated with both methanotroph and methanogen diversity but positively correlated with methanogen abundance. Overall, our results suggested that N deposition can suppress CH4 uptake by altering methanotroph and methanogen abundance, diversity, and community structure in subtropical Moso bamboo forest soils.
Quan Li; Changhui Peng; Junbo Zhang; Yongfu Li; Xinzhang Song. Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest. Scientific Reports 2021, 11, 1 -14.
AMA StyleQuan Li, Changhui Peng, Junbo Zhang, Yongfu Li, Xinzhang Song. Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest. Scientific Reports. 2021; 11 (1):1-14.
Chicago/Turabian StyleQuan Li; Changhui Peng; Junbo Zhang; Yongfu Li; Xinzhang Song. 2021. "Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest." Scientific Reports 11, no. 1: 1-14.
A challenge in urbanization is how to improve the usage of temporary fragmented land, alleviate land degradation and ensure food self-sufficiency. The greenhouses for cultivation have the potential to utilize the fragmented lands, yet there are little known of their spatial information. This study developed a framework to visually identify greenhouses and mapped the spatial pattern through the Google Earth Engine. Based on the investigation of 28,700 plots in three cities in China, it has found that: (1) the greenhouses distribution peaked at 1−2 km outside the built-up area; (2) more than 60 % of the greenhouses are less than 0.5 ha and the area increase with the distance from city center, which enabled the greenhouses to adapt to the fragmented lands; (3) the economic returns (average 2,400 yuan ha−1 yr−1) were much higher than the environmental impacts related to land degradation (500 yuan ha−1 yr−1); and (4) the economic returns provided by the greenhouses near urban fringes were higher than those in the rural, indicating the economic incentives and feasibility of greenhouse cultivation in urban fringes. This study will help decision-makers to form more effective strategies for utilizing temporary fragmented and degraded land to contribute to sustainable development of cities.
Guofu Yang; Ronghua Xu; Yi Chen; Zhaoping Wu; Yuanyuan Du; Shun Liu; Zelong Qu; Kejian Guo; Changhui Peng; Jie Chang; Ying Ge. Identifying the greenhouses by Google Earth Engine to promote the reuse of fragmented land in urban fringe. Sustainable Cities and Society 2021, 67, 102743 .
AMA StyleGuofu Yang, Ronghua Xu, Yi Chen, Zhaoping Wu, Yuanyuan Du, Shun Liu, Zelong Qu, Kejian Guo, Changhui Peng, Jie Chang, Ying Ge. Identifying the greenhouses by Google Earth Engine to promote the reuse of fragmented land in urban fringe. Sustainable Cities and Society. 2021; 67 ():102743.
Chicago/Turabian StyleGuofu Yang; Ronghua Xu; Yi Chen; Zhaoping Wu; Yuanyuan Du; Shun Liu; Zelong Qu; Kejian Guo; Changhui Peng; Jie Chang; Ying Ge. 2021. "Identifying the greenhouses by Google Earth Engine to promote the reuse of fragmented land in urban fringe." Sustainable Cities and Society 67, no. : 102743.
Allometric scaling laws critically examine structure-function relationships. In estimating the forest biomass carbon and its response under climate change, the issue of scaling has resulted in difficulties when modelling the biomass for different-sized trees, especially large ones, and has not yet been solved in either theory or practice. Here, we propose the concept of a dynamic allometric scaling relationship between stem biomass and above-ground biomass The allometric curve approaches an asymptote with an increase in tree size. An asymptotic allometric equation is presented that has a better fit to the data than the simple power-law allometric equation. The non-constant exponent is determined by the change in the biomass ratio for different organs and is governed by the dynamic allometric coefficient. This study presents a methodological framework to theoretically characterize allometric relationships and provides new insights in understanding the general scaling pattern and carbon sequestration capacity of large trees across global forests.
Xiaolu Zhou; Mingxia Yang; Zelin Liu; Peng Li; Binggeng Xie; Changhui Peng. Dynamic allometric scaling of tree biomass and size. Nature Plants 2021, 7, 42 -49.
AMA StyleXiaolu Zhou, Mingxia Yang, Zelin Liu, Peng Li, Binggeng Xie, Changhui Peng. Dynamic allometric scaling of tree biomass and size. Nature Plants. 2021; 7 (1):42-49.
Chicago/Turabian StyleXiaolu Zhou; Mingxia Yang; Zelin Liu; Peng Li; Binggeng Xie; Changhui Peng. 2021. "Dynamic allometric scaling of tree biomass and size." Nature Plants 7, no. 1: 42-49.
The carbon use efficiency (CUE) of ecosystems, expressed as the ratio of net primary production (NPP) and gross primary production (GPP), is extremely sensitive to climate change and has a great effect on the carbon cycles of terrestrial ecosystems. Climate change leads to changes in vegetation, resulting in different CUE values, especially on the Qinghai-Tibet Plateau, one of the most climate-sensitive regions in the world. However, the change trend and the intrinsic mechanism of climate effects on CUE in the future climate change scenario are not clear in this region. Based on the scheme of the coupled model intercomparison project (CMIP6), we analyze the simulation results of the five models of the scenario model intercomparison project (ScenarioMIP) under three different typical future climate scenarios, including SSP1-2.6, SSP3-7.0 and SSP5-8.5, on the Qinghai-Tibet Plateau in 2015–2100 with methods of model-averaging to average the long-term forecast of the five several well-known forecast models for three alternative climate scenarios with three radiative forcing levels to discuss the CUE changes and a structural equations modeling (SEM) approach to examine how the trends in GPP, NPP, and CUE related to different climate factors. The results show that (1) GPP and NPP demonstrated an upward trend in a long time series of 86 years, and the upward trend became increasingly substantial with the increase in radiation forcing; (2) the ecosystem CUE of the Qinghai-Tibet Plateau will decrease in the long time series in the future, and it shows a substantial decreasing trend with the increase in radiation forcing; and (3) the dominant climate factor affecting CUE is temperature of the factors included in these models, which affects CUE mainly through GPP and NPP to produce indirect effects. Temperature has a higher comprehensive effect on CUE than precipitation and CO2, which are negative effects on CUE on an annual scale. Our finding that the CUE decreases in the future suggests that we must pay more attention to the vegetation and CUE changes, which will produce great effects on the regional carbon dynamics and balance.
Yue Wang; Jinming Hu; Yanzheng Yang; Ruonan Li; Changhui Peng; Hua Zheng. Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models. Forests 2020, 12, 12 .
AMA StyleYue Wang, Jinming Hu, Yanzheng Yang, Ruonan Li, Changhui Peng, Hua Zheng. Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models. Forests. 2020; 12 (1):12.
Chicago/Turabian StyleYue Wang; Jinming Hu; Yanzheng Yang; Ruonan Li; Changhui Peng; Hua Zheng. 2020. "Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models." Forests 12, no. 1: 12.
Although an increasing number of reports have revealed that rivers are important sources of greenhouse gases (GHGs), the magnitude and underlying mechanism of riverine GHG emissions are still poorly understood. The global extent of the headwater stream ecosystem may represent one of the important GHG emitters. A global database of GHG measurements from 595 rivers, indicated that the concentrations of riverine GHGs continually decrease as the stream order increases. Further analysis suggested that high GHG emissions from headwater streams (Strahler stream orders of 1 to 3) could be related to the low levels of dissolved oxygen, massive terrestrially derived carbon/nitrogen inputs and large gas exchange velocity. Through a combination of the predicted river surface areas and gas transfer velocities, we estimated that globally, the rivers emit approximately 6.6 (5.5–7.8) Pg CO2, 29.5 (19.6–37.3) Tg CH4, and 0.6 (0.2–0.9) Tg N2O per year, and totally emit 7.6 (6.1–9.1) CO2 equivalent into atmosphere per year. The headwater streams contribute 72.3%, 75.5%, and 77.2% of the global riverine CO2, CH4, and N2O emissions, respectively. This study presents a systematic estimation of GHG emissions from river ecosystems worldwide and highlights the dominant role played by headwater streams in GHG evasions from global rivers.
Mingxu Li; Changhui Peng; Kerou Zhang; Li Xu; Jianming Wang; Yan Yang; Peng Li; Zelin Liu; Nianpeng He. Headwater stream ecosystem: an important source of greenhouse gases to the atmosphere. Water Research 2020, 190, 116738 .
AMA StyleMingxu Li, Changhui Peng, Kerou Zhang, Li Xu, Jianming Wang, Yan Yang, Peng Li, Zelin Liu, Nianpeng He. Headwater stream ecosystem: an important source of greenhouse gases to the atmosphere. Water Research. 2020; 190 ():116738.
Chicago/Turabian StyleMingxu Li; Changhui Peng; Kerou Zhang; Li Xu; Jianming Wang; Yan Yang; Peng Li; Zelin Liu; Nianpeng He. 2020. "Headwater stream ecosystem: an important source of greenhouse gases to the atmosphere." Water Research 190, no. : 116738.
Rapid urbanization has led to the continuous deterioration of the surrounding natural ecosystem. It is important to identify the key urbanization factors that affect ecosystem services and analyze the potential effects of these factors on the ecosystem. We selected the Beijing, Tianjin, and Hebei (BTH) urban agglomeration to investigate these effects, and designed three indicators to map the urbanization level: Population density, gross domestic product (GDP) density, and the construction land proportion. Four indicators were chosen to quantify ecosystem services: Food production, carbon sequestration and oxygen production, water conservation, and soil conservation. To handle the nonlinear interactions, we used a random forest (RF) method to assess the effect of urbanization on ecosystem services in the BTH area from 2000 to 2014. Our study demonstrated that population density and economic growth were the internal driving forces affecting ecosystem services. We observed changing trends in the effect of urbanization: The effect of population density on ecosystem services increased, the effect of the proportion of construction land was consistent with population density, and the effect of GDP density on ecosystem services decreased. Our results suggest that controlling the population and GDP would significantly influence the sustainable development in large urban areas.
Shan Liu; Mingxia Yang; Yuling Mou; Yanrong Meng; Xiaolu Zhou; Changhui Peng. Effect of Urbanization on Ecosystem Service Values in the Beijing-Tianjin-Hebei Urban Agglomeration of China from 2000 to 2014. Sustainability 2020, 12, 10233 .
AMA StyleShan Liu, Mingxia Yang, Yuling Mou, Yanrong Meng, Xiaolu Zhou, Changhui Peng. Effect of Urbanization on Ecosystem Service Values in the Beijing-Tianjin-Hebei Urban Agglomeration of China from 2000 to 2014. Sustainability. 2020; 12 (24):10233.
Chicago/Turabian StyleShan Liu; Mingxia Yang; Yuling Mou; Yanrong Meng; Xiaolu Zhou; Changhui Peng. 2020. "Effect of Urbanization on Ecosystem Service Values in the Beijing-Tianjin-Hebei Urban Agglomeration of China from 2000 to 2014." Sustainability 12, no. 24: 10233.
The 2001–2012 MODIS MCD12Q1 land cover data and MOD17A3 NPP data were used to calculate changes in land cover in China and annual changes in net primary productivity (NPP) during a 12-year period and to quantitatively analyze the effects of land cover change on the NPP of China’s terrestrial ecosystems. The results revealed that during the study period, no changes in land cover type occurred in 7447.31 thousand km2 of China, while the area of vegetation cover increased by 160.97 thousand km2 in the rest of the country. Forest cover increased to 20.91%, which was mainly due to the conversion of large areas of savanna (345.19 thousand km2) and cropland (178.96 thousand km2) to forest. During the 12-year study period, the annual mean NPP of China was 2.70 PgC and increased by 0.25 PgC, from 2.50 to 2.75 PgC. Of this change, 0.21 PgC occurred in areas where there was no land cover change, while 0.04 PgC occurred in areas where there was land cover change. The contributions of forest and cropland to NPP exhibited increasing trends, while the contributions of shrubland and grassland to NPP decreased. Among these land cover types, the contributions of forest and cropland to the national NPP were the greatest, accounting for 40.97% and 27.95%, respectively, of the annual total NPP. There was no significant correlation between changes in forest area and changes in total annual NPP (R2 < 0.1), while the correlation coefficient for changes in cropland area and total annual NPP was 0.48. Additionally, the area of cropland converted to other land cover types was negatively correlated with the changes in NPP, and the loss of cropland caused a reduction in the national NPP.
Hanwei Li; Juhua Ding; Jiang Zhang; Zhenan Yang; Bin Yang; Qiuan Zhu; Changhui Peng. Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012. Land 2020, 9, 480 .
AMA StyleHanwei Li, Juhua Ding, Jiang Zhang, Zhenan Yang, Bin Yang, Qiuan Zhu, Changhui Peng. Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012. Land. 2020; 9 (12):480.
Chicago/Turabian StyleHanwei Li; Juhua Ding; Jiang Zhang; Zhenan Yang; Bin Yang; Qiuan Zhu; Changhui Peng. 2020. "Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012." Land 9, no. 12: 480.
The spatial distribution patterns of land cover greatly influence the ecological balance of the Loess Plateau. Understanding the bio-physical drivers of land cover change is important for ecological restoration in the context of climate change. However, in the analysis of the drivers of land cover change in the Loess Plateau, the role of bio-physical drivers has not been quantitatively evaluated. Using remote sensing data, machine learning, and statistical methods, this study analyzed the spatial and temporal patterns of land cover from 2001 to 2018 in the Loess Plateau of China. We used a random forest (RF) model to quantify the importance of bio-physical drivers of land cover. Our results demonstrated that the RF model has good performance and high reliability (model accuracy score > 0.8). Our simulation experiment revealed that evapotranspiration was the most important driver (importance score, IS >0.2), temperature and precipitation had regional heterogeneity, and slope was the least important (IS <0.05). We suggest that evapotranspiration can be regulated by properly allocating the type of land cover, so as to rationally allocate water resources on the Loess Plateau. This study provides a new foundation for quantitatively evaluating the drivers of land cover change and regulating the distribution of water resources on the Loess Plateau, China.
Yanrong Meng; Mingxia Yang; Shan Liu; Yuling Mou; Changhui Peng; Xiaolu Zhou. Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method. Ecological Informatics 2020, 61, 101204 .
AMA StyleYanrong Meng, Mingxia Yang, Shan Liu, Yuling Mou, Changhui Peng, Xiaolu Zhou. Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method. Ecological Informatics. 2020; 61 ():101204.
Chicago/Turabian StyleYanrong Meng; Mingxia Yang; Shan Liu; Yuling Mou; Changhui Peng; Xiaolu Zhou. 2020. "Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method." Ecological Informatics 61, no. : 101204.
Digital leaf physiognomy (DLP) is considered as one of the most promising methods for estimating past climate. However, current models built using the DLP dataset still lack precision, especially for mean annual precipitation (MAP). To improve predictive power, we developed five machine learning (ML) models for mean annual temperature (MAT) and MAP respectively, and then tested the precision of these models and some of their averaging compared with that obtained from other models. The precision of all models was assessed using a repeated stratified 10‐fold cross‐validation. For MAT, three combinations of models (R2 = 0.77) presented moderate improvements in precision over the multiple linear regression (MLR) model (R2 = 0.68). For loge(MAP), the averaging of the support vector machine (SVM) and boosting models improved the R2 from 0.19 to 0.63 compared with that of the MLR model. For MAP, the R2 of this model combination was 0.49, which was much better than that of the artificial neural network (ANN) model (R2 = 0.21). Even the bagging model, which had the lowest R2 (0.37) for loge(MAP), demonstrated better precision (R2 = 0.27) for MAP. Our palaeoclimate estimates for nine fossil floras were also more accurate, because they were in better agreement with independent paleoclimate evidence. Our study confirms that our ML models and their averaging can improve paleoclimatic reconstructions, providing a better understanding of the relationship between climate and leaf physiognomy. This article is protected by copyright. All rights reserved.
Gang Wei; Changhui Peng; Qiuan Zhu; Xiaolu Zhou; Bin Yang. Application of machine learning methods for paleoclimatic reconstructions from leaf traits. International Journal of Climatology 2020, 41, 1 .
AMA StyleGang Wei, Changhui Peng, Qiuan Zhu, Xiaolu Zhou, Bin Yang. Application of machine learning methods for paleoclimatic reconstructions from leaf traits. International Journal of Climatology. 2020; 41 (S1):1.
Chicago/Turabian StyleGang Wei; Changhui Peng; Qiuan Zhu; Xiaolu Zhou; Bin Yang. 2020. "Application of machine learning methods for paleoclimatic reconstructions from leaf traits." International Journal of Climatology 41, no. S1: 1.
The study of carbon sequestration capacity under intensive management (IM)1 measures (such as cutting, thinning, plowing, and fertilization) has become a major issue of carbon budgets in the context of global climate change. Bamboo forest, also known as “the second largest forest in the world,” plays an important role in the carbon cycle. Due to its high economic value, IM practices have been widely used to manage bamboo forests, which in turn may affect the global carbon cycle and carbon budget balance of the ecosystem. However, due to a lack of long-term field experiments and suitable representative models for carbon cycle research in bamboo forests, there is little understanding of the effects of IM measures on carbon sources/sinks in bamboo forest ecosystems at large temporal scales. In this study, we used a representative Lei bamboo (Phyllostachys praecox C.D. Chu & C.S. Chao) forest occurring in Taihuyuan town, Zhejiang Province, China as the study object and a new generation Triplex-Flux model to simulate the net ecosystem productivity (NEP) and net primary productivity (NPP) of the Lei bamboo forest under IM and nonintensive management (NIM) in 2011–2013 and 2015. The aim was to reveal the impact of IM on the carbon cycle of a bamboo forest ecosystem. The results showed that the Triplex-Flux model was suitable for studying the carbon cycle in the Lei bamboo forest. On a 30 min time scale, R2 values ranged between 0.78–0.91 (p0.42, p<0.001). However, the Triplex-Flux model failed to reveal the NEP patterns, as there were certain deviations between some of the simulated NEP peak and valley values, which were underestimated at noon and overestimated at night. IM played a key role in controlling carbon budget of the Lei bamboo forest. On a seasonal scale, the effect of IM measures was the most significant in spring; harvesting old bamboo wood and removing new shoots caused a 27.71% and 58.52% decrease in NEP and NPP, respectively. Hooking tips and trimming diseased branches had little impact on NEP and NPP (0.02% and 7.27%, respectively) in autumn. On an annual scale, IM measures resulted in average annual decrease in NEP and NPP by 27.20% and 13.72%, respectively. Our findings can provide a reference base that may be applicable to studying the carbon cycle in bamboo forests across the country and even at larger scales.
Minxia Zhang; Shulin Chen; Hong Jiang; Changhui Peng; Jinmeng Zhang; Guomo Zhou. The impact of intensive management on net ecosystem productivity and net primary productivity of a Lei bamboo forest. Ecological Modelling 2020, 435, 109248 .
AMA StyleMinxia Zhang, Shulin Chen, Hong Jiang, Changhui Peng, Jinmeng Zhang, Guomo Zhou. The impact of intensive management on net ecosystem productivity and net primary productivity of a Lei bamboo forest. Ecological Modelling. 2020; 435 ():109248.
Chicago/Turabian StyleMinxia Zhang; Shulin Chen; Hong Jiang; Changhui Peng; Jinmeng Zhang; Guomo Zhou. 2020. "The impact of intensive management on net ecosystem productivity and net primary productivity of a Lei bamboo forest." Ecological Modelling 435, no. : 109248.
The study was to investigate the change patterns of soil organic carbon (SOC), total nitrogen (TN), and soil C/N (C/N) in each soil sublayer along vegetation restoration in subtropical China. We collected soil samples in four typical plant communities along a restoration chronosequence. The soil physicochemical properties, fine root, and litter biomass were measured. Our results showed the proportion of SOC stocks (Cs) and TN stocks (Ns) in 20–30 and 30–40 cm soil layers increased, whereas that in 0–10 and 10–20 cm soil layers decreased. Different but well-constrained C/N was found among four restoration stages in each soil sublayer. The effect of soil factors was greater on the deep soil than the surface soil, while the effect of vegetation factors was just the opposite. Our study indicated that vegetation restoration promoted the uniform distribution of SOC and TN on the soil profile. The C/N was relatively stable along vegetation restoration in each soil layer. The accumulation of SOC and TN in the surface soil layer was controlled more by vegetation factors, while that in the lower layer was controlled by both vegetation factors and soil factors.
Zhiwei Cao; Xi Fang; Wenhua Xiang; Pifeng Lei; Changhui Peng. The Vertical Differences in the Change Rates and Controlling Factors of Soil Organic Carbon and Total Nitrogen along Vegetation Restoration in a Subtropical Area of China. Sustainability 2020, 12, 6443 .
AMA StyleZhiwei Cao, Xi Fang, Wenhua Xiang, Pifeng Lei, Changhui Peng. The Vertical Differences in the Change Rates and Controlling Factors of Soil Organic Carbon and Total Nitrogen along Vegetation Restoration in a Subtropical Area of China. Sustainability. 2020; 12 (16):6443.
Chicago/Turabian StyleZhiwei Cao; Xi Fang; Wenhua Xiang; Pifeng Lei; Changhui Peng. 2020. "The Vertical Differences in the Change Rates and Controlling Factors of Soil Organic Carbon and Total Nitrogen along Vegetation Restoration in a Subtropical Area of China." Sustainability 12, no. 16: 6443.