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Gross primary productivity (GPP) is the most basic variable in a carbon cycle study that determines the carbon that enters the ecosystem. The remote sensing-based light use efficiency (LUE) model is one of the primary tools that is currently used to estimate the GPP at the regional scale. Many remote sensing-based GPP models have been developed in the last several decades, and these models have been well evaluated at some sites. However, an accurate estimation of the GPP remains challenging work using LUE models because of uncertainties in the model caused by model parameters, model forcing, and vegetation spatial heterogeneity. In this study, five widely used LUE models, Glo-PEM, VPM, EC-LUE, the MODIS GPP algorithm, and C-fix, were selected to simulate the GPP of the Heihe River Basin forced using in situ measurements. A multiple-model averaging method, Bayesian model averaging (BMA), was used to combine the five models to obtain a more reliable GPP estimation. The BMA was trained using carbon flux data from five eddy covariance towers located at dominant vegetation types in the study area. Generally, the BMA method performed better than any single LUE model. From the case study in the study area, it is indicated that the trained BMA is an efficient method to combine multiple LUE models and can improve the GPP simulation accuracy.
Jun Zhang; Xufeng Wang; Jun Ren. Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models. Land 2021, 10, 329 .
AMA StyleJun Zhang, Xufeng Wang, Jun Ren. Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models. Land. 2021; 10 (3):329.
Chicago/Turabian StyleJun Zhang; Xufeng Wang; Jun Ren. 2021. "Simulation of Gross Primary Productivity Using Multiple Light Use Efficiency Models." Land 10, no. 3: 329.
Gross primary production (GPP) is the overall photosynthetic fixation of carbon per unit space and time. Due to uncertainties resulting from clouds, snow, aerosol, and topography, it is a challenging task to accurately estimate daily GPP. Daily digital photos from a phenological camera record vegetation daily greenness dynamics with little cloud or aerosol disturbance. It can be fused with satellite remote sensing data to improve daily GPP prediction accuracy. In this study, we combine the two types of datasets to improve the estimation accuracy of GPP for alpine meadow on the Tibetan Plateau. To examine the performance of different methods and vegetation indices (VIs), three experiments were designed. First, GPP was estimated with the light use efficiency (LUE) model with the green chromatic coordinate (GCC) from the phenological camera and vegetation index from MODIS, respectively. Second, GPP was estimated with the Backpropagation neural network machine learning algorithm (BNNA) method with GCC from the phenological camera and vegetation index from MODIS, respectively. Finally, GPP was estimated with the BNNA method using GCC and vegetation index as inputs at the same time. Compared with eddy covariance GPP, GPP predicted by the BNNA method with GCC and vegetation indices as inputs at the same time showed the highest accuracy of all the experiments. The results indicated that GCC had a higher accuracy than NDVI and EVI when only one vegetation index data was used in the LUE model or the BNNA method. The R2 of GPP estimated by BNNA and GPP from eddy covariance increased by 0.12 on average, RMSE decreased by 1.13 g C·m−2·day−1 on average, and MAD decreased by 0.87 g C·m−2·day−1 on average compared with GPP estimated by the traditional LUE model and GPP from eddy covariance. This study puts forth a new way to improve the estimation accuracy of GPP on the Tibetan Plateau. With the emergence of a large number of phenological cameras, this method has great potential for use on the Tibetan Plateau, which is heavily affected by clouds and snow.
Xuqiang Zhou; Xufeng Wang; Songlin Zhang; Yang Zhang; Xuejie Bai. Combining Phenological Camera Photos and MODIS Reflectance Data to Predict GPP Daily Dynamics for Alpine Meadows on the Tibetan Plateau. Remote Sensing 2020, 12, 3735 .
AMA StyleXuqiang Zhou, Xufeng Wang, Songlin Zhang, Yang Zhang, Xuejie Bai. Combining Phenological Camera Photos and MODIS Reflectance Data to Predict GPP Daily Dynamics for Alpine Meadows on the Tibetan Plateau. Remote Sensing. 2020; 12 (22):3735.
Chicago/Turabian StyleXuqiang Zhou; Xufeng Wang; Songlin Zhang; Yang Zhang; Xuejie Bai. 2020. "Combining Phenological Camera Photos and MODIS Reflectance Data to Predict GPP Daily Dynamics for Alpine Meadows on the Tibetan Plateau." Remote Sensing 12, no. 22: 3735.
As an important component to quantify the carbon budget, accurate evaluation of terrestrial gross primary production (GPP) is crucial for large-scale applications, especially in dryland ecosystems. Based on the in situ data from six flux sites in northwestern China from 2014 to 2016, this study compares seasonal and interannual dynamics of carbon fluxes between these arid and semi-arid ecosystems and the atmosphere. Meanwhile, the reliability of multiple remotely-derived GPP products in representative drylands was examined, including the Breathing Earth System Simulator (BESS), the Moderate Resolution Imaging Spectroradiometer (MODIS) and data derived from the OCO-2 solar-induced chlorophyll fluorescence (GOSIF). The results indicated that the carbon fluxes had clear seasonal patterns, with all ecosystems functioning as carbon sinks. The maize cropland had the highest GPP with 1183 g C m−2 y−1. Although the net ecosystem carbon exchange (NEE) in the Tamarix spp. ecosystem was the smallest among these flux sites, it reached 208 g C m−2 y−1. Furthermore, distinct advantages of GOSIF GPP (with R2 = 0.85–0.98, and RMSE = 0.87–2.66 g C m−2 d−1) were found with good performance. However, large underestimations in three GPP products existed during the growing seasons, except in grassland ecosystems. The main reasons can be ascribed to the uncertainties in the key model parameters, including the underestimated light use efficiency of the MODIS GPP, the same coarse land cover product for the BESS and MODIS GPP, the coarse gridded meteorological data, and distribution of C3 and C4 plants. Therefore, it still requires more work to accurately quantify the GPP across these dryland ecosystems.
Qing Gu; Hui Zheng; Li Yao; Min Wang; Mingguo Ma; Xufeng Wang; Xuguang Tang. Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China. Land 2020, 9, 288 .
AMA StyleQing Gu, Hui Zheng, Li Yao, Min Wang, Mingguo Ma, Xufeng Wang, Xuguang Tang. Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China. Land. 2020; 9 (9):288.
Chicago/Turabian StyleQing Gu; Hui Zheng; Li Yao; Min Wang; Mingguo Ma; Xufeng Wang; Xuguang Tang. 2020. "Performance of the Remotely-Derived Products in Monitoring Gross Primary Production across Arid and Semi-Arid Ecosystems in Northwest China." Land 9, no. 9: 288.
Soil Moisture (SM) is a direct indicator of dryness of the land surface, and the amount of precipitation (P), vegetation status, and Land Surface Temperature (LST) are directly related to SM; thus, these factors indirectly characterize the dryness of the land surface. However, there are limitations and shortcomings of using a single factor to assess dryness because of the interactions among factors. A method that can combine the advantages of the three factors is needed to better monitor dryness. In this study, a new Remote Sensing (RS) dryness index, called the Temperature Vegetation Precipitation Dryness Index (TVPDI), was defined and developed using the Euclidean distance method and three-dimensional (3D) P-Normalized Difference Vegetation Index (NDVI)-LST.The reasonableness of this index was tested and verified using SM data, three variables (P, NDVI, and LST), other recognized dryness indices, crop yield per unit area and Net Primary Productivity (NPP). In addition, the reliability of the TVPDI results was analyzed at different spatial scales and using different data sources. The results demonstrated that the TVPDI was highly correlated with SM (R > 0.64, p < .01) and exhibited better performance than the P, NDVI, and LST results. The time series of the TVPDI and other dryness indices exhibited spatially good consistency. The TVPDI was temporally well-matched to the crop yield per unit area and NPP in most regions of China, and performed better than other dryness indices. Furthermore, in the four sample regions, the TVPDIMODIS results closely matched the TVPDILandsat and Landsat image results, indicating that the TVPDI is a reliable and robust index for dryness monitoring to some extent. Moreover, the application of the TVPDI for dryness-wetness monitoring in China indicated significant spatiotemporal differences in the dryness-wetness status at both monthly and annual scales. The distribution of dryness in China exhibited obvious differences in different agricultural regions. In conclusion, the TVPDI is an RS dryness index that can be applied to dryness assessments.
Wei Wei; Sufei Pang; Xufeng Wang; Liang Zhou; Binbin Xie; Junju Zhou; Chuanhua Li. Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China. Remote Sensing of Environment 2020, 248, 111957 .
AMA StyleWei Wei, Sufei Pang, Xufeng Wang, Liang Zhou, Binbin Xie, Junju Zhou, Chuanhua Li. Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China. Remote Sensing of Environment. 2020; 248 ():111957.
Chicago/Turabian StyleWei Wei; Sufei Pang; Xufeng Wang; Liang Zhou; Binbin Xie; Junju Zhou; Chuanhua Li. 2020. "Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China." Remote Sensing of Environment 248, no. : 111957.
Permafrost on the Tibetan Plateau (TP) is controlled by high-elevation and the complex hydrothermal processes and energy balance on the ground surface. To successfully model or map permafrost distribution, it is necessary to parameterize near-surface air or land-surface temperatures (Ta or LST) to ground surface temperature (GST) at local-, meso‑, or macro-scale. Here, a long-term experimental observation (November 2010 to December 2018) was conducted for understanding the differences between Ta and GST at a plot with 26 sites at Chalaping to the south of the Sisters Lakes in the Source Area of the Yellow River, northeastern TP. Results show that GST varies considerably within an area of about 3.5 km2 under the combined thermal influences of surface vegetation, soil moisture conditions, and microtopography. Mean annual GST (MAGST) ranged from –0.55 to –3.02°C, with an average of –1.35±0.63°C. The surface offset varied from 1.01 to 3.90°C, with an average of 2.72±0.70°C. The difference between monthly Ta and monthly GST decreased from 4.64±2.09°C in January to 1.09±1.34°C in July and then gradually increased to 5.61±2.53°C in November. The active layer thickness (ALT) calculated with the ground-surface thawing index ranged from 0.85 to 1.95 m, with an average of 1.51±0.33 m. Annual freezing N-factors and annual thawing N-factors were averaged at 0.58±0.12 and 1.31±0.28, respectively. Although weakly, hourly and daily GST values are positively correlated to NDVI, while ALT negatively correlated with NDVI. This study demonstrates the complex thermal regimes on the ground surface, even within a small area despite the relatively consistent topography. It will likely facilitate the parameterization of the upper thermal boundary of permafrost modeling or mapping on the TP where the landscapes are characterized by extensive presence of dwarf alpine meadow and alpine steppe, further contributing to the study in ecosystem feedbacks to the regional climate change.
Dongliang Luo; Lei Liu; Huijun Jin; Xufeng Wang; Fangfang Chen. Characteristics of ground surface temperature at Chalaping in the Source Area of the Yellow River, northeastern Tibetan Plateau. Agricultural and Forest Meteorology 2019, 281, 107819 .
AMA StyleDongliang Luo, Lei Liu, Huijun Jin, Xufeng Wang, Fangfang Chen. Characteristics of ground surface temperature at Chalaping in the Source Area of the Yellow River, northeastern Tibetan Plateau. Agricultural and Forest Meteorology. 2019; 281 ():107819.
Chicago/Turabian StyleDongliang Luo; Lei Liu; Huijun Jin; Xufeng Wang; Fangfang Chen. 2019. "Characteristics of ground surface temperature at Chalaping in the Source Area of the Yellow River, northeastern Tibetan Plateau." Agricultural and Forest Meteorology 281, no. : 107819.
Identifying the changes in precipitation and temperature at a regional scale is of great importance for the quantification of climate change. This research investigates the changes in precipitation and surface air temperature indices in the seven irrigation zones of Punjab Province during the last 50 years; this province is a very important region in Pakistan in terms of agriculture and irrigated farming. The reliability of the data was examined using double mass curve and autocorrelation analysis. The magnitude and significance of the precipitation and temperature were visualized by various statistical methods. The stations’ trends were spatially distributed to better understand climatic variability across the elevation gradient of the study region. The results showed a significant warming trend in annual Tmin (minimum temperature) and Tmean (mean temperature) in different irrigation zones. However, Tmax (maximum temperature) had insignificant variations except in the high elevation Thal zone. Moreover, the rate of Tmin increased faster than that of Tmax, resulting in a reduction in the diurnal temperature range (DTR). On a seasonal scale, warming was more pronounced during spring, followed by that in winter and autumn. However, the summer season exhibited insignificant negative trends in most of the zones and gauges, except in the higher-altitude Thal zone. Overall, Bahawalpur and Faisalabad are the zones most vulnerable to warming annually and in the spring, respectively. Furthermore, the elevation-dependent trend (EDT) indicated larger increments in Tmax for higher-elevation (above 500 m a.s.l.) stations, compared to the lower-elevation ones, on both annual and seasonal scales. In contrast, the Tmin showed opposite trends at higher- and lower-elevation stations, while a moderate increase was witnessed in Tmean trends from lower to higher altitude over the study region. An increasing trend in DTR was observed at higher elevation, while a decreasing trend was noticed at the lower-elevation stations. The analysis of precipitation data indicated wide variability over the entire region during the study period. Most previous studies reported no change or a decreasing trend in precipitation in this region. Conversely, our findings indicated the cumulative increase in annual and autumn precipitation amounts at zonal and regional level. However, EDT analysis identified the decrease in precipitation amounts at higher elevation (above 1000 m a.s.l.) and increase at the lower-elevation stations. Overall, our findings revealed unprecedented evidence of regional climate change from the perspectives of seasonal warming and variations in precipitation and temperature extremes (Tmax and Tmin) particularly at higher-elevation sites, resulting in a variability of the DTR, which could have a significant influence on water resources and on the phenology of vegetation and crops at zonal and station level in Punjab.
Naima Nawaz; Xin Li; Yingying Chen; Yanlong Guo; Xufeng Wang. Temporal and Spatial Characteristics of Precipitation and Temperature in Punjab, Pakistan. Water 2019, 11, 1916 .
AMA StyleNaima Nawaz, Xin Li, Yingying Chen, Yanlong Guo, Xufeng Wang. Temporal and Spatial Characteristics of Precipitation and Temperature in Punjab, Pakistan. Water. 2019; 11 (9):1916.
Chicago/Turabian StyleNaima Nawaz; Xin Li; Yingying Chen; Yanlong Guo; Xufeng Wang. 2019. "Temporal and Spatial Characteristics of Precipitation and Temperature in Punjab, Pakistan." Water 11, no. 9: 1916.
Dryland regions cover >40% of the Earth's land surface, making these ecosystems the largest biome in the world. Ecosystems in these areas play an important role in determining the interannual variability of the global terrestrial carbon sink. Examining carbon fluxes of various types of dryland ecosystems and their responses to climatic variability is essential for improving projections of the carbon cycle in these regions. In this study, we made use of observations from a regional flux tower observation network in a typical arid endorheic basin, the Heihe river basin (HRB). As a representative area of both the arid region of China and the entire region of central Asia, the HRB includes the main ecosystems in arid regions. We compared the spatial variations of carbon fluxes of five terrestrial ecosystems (i.e., grassland, cropland, desert, wetland, and forest ecosystems) and explored the responses of ecosystem carbon fluxes to climatic factors across different ecosystems. We found that our region exhibits a carbon sink ranging from 85.9 to 508.7 gC/m2/yr for different ecosystems, and the water availability is critical to the spatial variability of carbon fluxes in arid regions. Carbon fluxes across all sites exhibited weak correlations with temperature and precipitation. Marked differences in precipitation effects were observed between the sites within oases and those outside of oases. Irrigation and groundwater recharge were of great importance to the variations in carbon fluxes for the sites within oases. Evapotranspiration (ET) exhibited strong relationships with carbon fluxes, indicating that ET was a better metric of soil water availability than was precipitation in driving the spatial variability of carbon fluxes in arid regions. This study has implications for better understanding the carbon budget of terrestrial ecosystems and informing ecological management in dryland regions.
Haibo Wang; Xin Li; Jingfeng Xiao; Mingguo Ma; Junlei Tan; Xufeng Wang; Liying Geng. Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability. Science of The Total Environment 2019, 697, 133978 .
AMA StyleHaibo Wang, Xin Li, Jingfeng Xiao, Mingguo Ma, Junlei Tan, Xufeng Wang, Liying Geng. Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability. Science of The Total Environment. 2019; 697 ():133978.
Chicago/Turabian StyleHaibo Wang; Xin Li; Jingfeng Xiao; Mingguo Ma; Junlei Tan; Xufeng Wang; Liying Geng. 2019. "Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability." Science of The Total Environment 697, no. : 133978.
The allocation of net primary production (NPP) to different plant structures, such as leaves, wood and fine roots, plays an important role in the terrestrial carbon cycle. However, the biogeographical patterns of NPP allocation are not well understood. We constructed a global database of forest NPP to investigate the observed spatial patterns of forest NPP allocation, as influenced by environmental drivers and forest stand age. We then examined whether dynamic global vegetation models (DGVMs) could capture these allocation patterns. The NPP allocation response to variations in temperature or precipitation were often opposite in leaves and fine roots, a finding consistent with the functional balance theory for allocation. The observed allocation to fine roots decreased with increasing temperature and precipitation. The observed allocation to wood and leaves decreased with forest stand age. The simulated allocation with five DGVMs was compared with the observations. The five models captured the spatial gradient of lower allocation to fine roots with increasing temperature and precipitation, but did not capture coincident gradients in allocation to wood and leaves. None of the five models adequately represented the changes in allocation with forest stand age. Specifically, the models did not reproduce the decrease in allocation to wood and leaves and the increase in allocation to fine roots with increasing forest stand age. An accurate simulation of NPP allocation requires more realistic representation of multiple processes that are closely related to allocation. The NPP allocation database can be used to develop DGVMs.
Jiangzhou Xia; Wenping Yuan; Sebastian Lienert; Fortunat Joos; Philippe Ciais; Nicolas Viovy; Ying‐Ping Wang; Xufeng Wang; Haicheng Zhang; Yang Chen; Xiangjun Tian. Global Patterns in Net Primary Production Allocation Regulated by Environmental Conditions and Forest Stand Age: A Model‐Data Comparison. Journal of Geophysical Research: Biogeosciences 2019, 124, 2039 -2059.
AMA StyleJiangzhou Xia, Wenping Yuan, Sebastian Lienert, Fortunat Joos, Philippe Ciais, Nicolas Viovy, Ying‐Ping Wang, Xufeng Wang, Haicheng Zhang, Yang Chen, Xiangjun Tian. Global Patterns in Net Primary Production Allocation Regulated by Environmental Conditions and Forest Stand Age: A Model‐Data Comparison. Journal of Geophysical Research: Biogeosciences. 2019; 124 (7):2039-2059.
Chicago/Turabian StyleJiangzhou Xia; Wenping Yuan; Sebastian Lienert; Fortunat Joos; Philippe Ciais; Nicolas Viovy; Ying‐Ping Wang; Xufeng Wang; Haicheng Zhang; Yang Chen; Xiangjun Tian. 2019. "Global Patterns in Net Primary Production Allocation Regulated by Environmental Conditions and Forest Stand Age: A Model‐Data Comparison." Journal of Geophysical Research: Biogeosciences 124, no. 7: 2039-2059.
Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks. A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.
Xufeng Wang; Jingfeng Xiao; Xin Li; Guodong Cheng; Mingguo Ma; Gaofeng Zhu; M. Altaf Arain; T. Andrew Black; Rachhpal S. Jassal. No trends in spring and autumn phenology during the global warming hiatus. Nature Communications 2019, 10, 1 -10.
AMA StyleXufeng Wang, Jingfeng Xiao, Xin Li, Guodong Cheng, Mingguo Ma, Gaofeng Zhu, M. Altaf Arain, T. Andrew Black, Rachhpal S. Jassal. No trends in spring and autumn phenology during the global warming hiatus. Nature Communications. 2019; 10 (1):1-10.
Chicago/Turabian StyleXufeng Wang; Jingfeng Xiao; Xin Li; Guodong Cheng; Mingguo Ma; Gaofeng Zhu; M. Altaf Arain; T. Andrew Black; Rachhpal S. Jassal. 2019. "No trends in spring and autumn phenology during the global warming hiatus." Nature Communications 10, no. 1: 1-10.
Carbon exchange between terrestrial ecosystems and environment is paid great attention in recent decades, because it can regulate the atmospheric carbon dioxide concentration. Photosynthesis is the key process in the carbon cycle. GPP, NPP, and NEP are key variables in carbon cycle study. Thus, accurate estimation of these carbon fluxes is important for understanding the interactions between terrestrial ecosystems and atmosphere. In this chapter, we introduce measuring methods of these carbon fluxes at field scale and estimating models of these carbon fluxes based on remote sensing data at regional or global scale. The processes and key questions in these methods or models are specifically analyzed.
Xufeng Wang; Haibo Wang; Xin Li; Youhua Ran. Photosynthesis (NPP, NEP, Respiration). River Basin Management 2019, 329 -358.
AMA StyleXufeng Wang, Haibo Wang, Xin Li, Youhua Ran. Photosynthesis (NPP, NEP, Respiration). River Basin Management. 2019; ():329-358.
Chicago/Turabian StyleXufeng Wang; Haibo Wang; Xin Li; Youhua Ran. 2019. "Photosynthesis (NPP, NEP, Respiration)." River Basin Management , no. : 329-358.
A clear interannual variability in annual production of grasslands (termed AEVI) has been reported over the Tibetan Plateau (TP), but the underlying mechanism has not been fully understood. Here, we explained the interannual variability of AEVI during 2001–2015 by two phenological metrics (the start and end of the growing season, termed SOS and EOS, respectively) and one physiological metric (the maximum capacity of canopy light absorbance, termed MEVI) using MODIS Enhanced Vegetation Index (EVI) data over the TP. The results showed that the interannual variability of AEVI can be well attributed to not only the trends of, but also the sensitivities of AEVI to, the selected biological metrics. On the one hand, the advancing SOS and delaying EOS dominated the study area while both increased and decreased MEVI were observed. On the other hand, the AEVI responded negatively to the SOS and positively to the EOS and MEVI, exhibiting significant variations along the temperature and precipitation gradients. Hence, the current interannual variability of SOS and EOS mainly increased the AEVI; meanwhile, both enhancement and suppression of the interannual variability of MEVI to the AEVI were widespread over the TP. Overall, the interannual variability of MEVI mostly contributed to that of the AEVI, indicating a dominant role of the physiological metric rather than phenological metrics in carbon gain of TP grasslands. The achievements of this study are helpful to understand the underlying biological causes of the interannual variability of grassland production over the TP.
Jiaxin Jin; Xuanlong Ma; Huai Chen; Han Wang; XiaoMing Kang; Xufeng Wang; Ying Wang; Bin Yong; Fengsheng Guo. Grassland production in response to changes in biological metrics over the Tibetan Plateau. Science of The Total Environment 2019, 666, 641 -651.
AMA StyleJiaxin Jin, Xuanlong Ma, Huai Chen, Han Wang, XiaoMing Kang, Xufeng Wang, Ying Wang, Bin Yong, Fengsheng Guo. Grassland production in response to changes in biological metrics over the Tibetan Plateau. Science of The Total Environment. 2019; 666 ():641-651.
Chicago/Turabian StyleJiaxin Jin; Xuanlong Ma; Huai Chen; Han Wang; XiaoMing Kang; Xufeng Wang; Ying Wang; Bin Yong; Fengsheng Guo. 2019. "Grassland production in response to changes in biological metrics over the Tibetan Plateau." Science of The Total Environment 666, no. : 641-651.
The Qilian Mountain ecosystems play an irreplaceable role in maintaining ecological security in western China. Vegetation, as an important part of the ecosystem, has undergone considerable changes in recent decades in this area, but few studies have focused on the process of vegetation change. A long normalized difference vegetation index (NDVI) time series dataset based on remote sensing is an effective tool to investigate large-scale vegetation change dynamics. The MODerate resolution Imaging Spectroradiometer (MODIS) NDVI dataset has provided very detailed regional to global information on the state of vegetation since 2000. The aim of this study was to explore the spatial-temporal characteristics of abrupt vegetation changes and detect their potential drivers in the Qilian Mountain area using MODIS NDVI data with 1 km resolution from 2000 to 2017. The Breaks for Additive Season and Trend (BFAST) algorithm was adopted to detect vegetation breakpoint change times and magnitudes from satellite observations. Our results indicated that approximately 80.1% of vegetation areas experienced at least one abrupt change from 2000 to 2017, and most of these areas were distributed in the southern and northern parts of the study area, especially the area surrounding Qinghai Lake. The abrupt browning changes were much more widespread than the abrupt greening changes for most years of the study period. Environmental factors and anthropogenic activities mainly drove the abrupt vegetation changes. Long-term overgrazing is likely the main cause of the abrupt browning changes. In addition, our results indicate that national ecological protection policies have achieved positive effects in the study area.
Liying Geng; Tao Che; Xufeng Wang; Haibo Wang. Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017. Remote Sensing 2019, 11, 103 .
AMA StyleLiying Geng, Tao Che, Xufeng Wang, Haibo Wang. Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017. Remote Sensing. 2019; 11 (2):103.
Chicago/Turabian StyleLiying Geng; Tao Che; Xufeng Wang; Haibo Wang. 2019. "Detecting Spatiotemporal Changes in Vegetation with the BFAST Model in the Qilian Mountain Region during 2000–2017." Remote Sensing 11, no. 2: 103.
Sun-induced chlorophyll fluorescence (SIF) provides a new method for monitoring vegetation photosynthesis from space and has been widely used to estimate gross primary productivity (GPP). However, the ability of SIF obtained from the Orbital Carbon Observatory 2 (OCO-2 SIF) and Global Ozone Monitoring Experiment-2 (GOME-2) to estimate GPP in the cold and arid region of Heihe River Basin remains unclear because previous comparisons were insufficient. Here, we choose maize and alpine meadow to evaluate the performance of SIF obtained by OCO-2 and GOME-2 in GPP estimations. The results of this study show that daily SIF757 had stronger correlations with daily tower GPP than daily SIF771, and the correlation between daily SIF757 and daily tower GPP was stronger than the correlation between 16-d averaged SIF740 and 16-d averaged tower GPP. The 16-d averaged absorbed photosynthetically active radiation (APAR) and reconstructed sun-induced fluorescence (RSIF) had the strongest linear correlations with 16-d averaged tower GPP. GPP_VPM and GPP_RSIF exhibited the best performance in GPP estimation, closely followed by GPP_SIF757, then GPP_SIF771 and GPP_ SIF740. We also found that the robustness of the correlation coefficients of OCO-2 SIF with GOME-2 SIF was highly dependent on the size of their spatial footprint overlaps, indicating that the spatial differences between OCO-2 and GOME-2 footprints contribute to the differences in GPP estimates between OCO-2 and GOME-2. In addition, the differences of viewing zenith angle (VZA), cloud contamination, scale effects, and environmental scalars (Tscalar × Wscalar) can result in differences between OCO-2 SIF and GOME-2 SIF.
Xiaoxu Wei; Xufeng Wang; Wei Wei; Wei Wan. Use of Sun-Induced Chlorophyll Fluorescence Obtained by OCO-2 and GOME-2 for GPP Estimates of the Heihe River Basin, China. Remote Sensing 2018, 10, 2039 .
AMA StyleXiaoxu Wei, Xufeng Wang, Wei Wei, Wei Wan. Use of Sun-Induced Chlorophyll Fluorescence Obtained by OCO-2 and GOME-2 for GPP Estimates of the Heihe River Basin, China. Remote Sensing. 2018; 10 (12):2039.
Chicago/Turabian StyleXiaoxu Wei; Xufeng Wang; Wei Wei; Wei Wan. 2018. "Use of Sun-Induced Chlorophyll Fluorescence Obtained by OCO-2 and GOME-2 for GPP Estimates of the Heihe River Basin, China." Remote Sensing 10, no. 12: 2039.
Increase of surface temperatures has long been recognized as an unequivocal response to radiative forcing and one of the most important implications for global warming. However, it remains unclear whether the variation of ground surface temperature (GST) and soil temperatures is consistent with simultaneous changes of the near‐surface air and land (or skin) surface temperatures (Ta and LST). In this study, a seven‐year continuous observation of GST, Ta, and surface water and heat exchange was carried out at an elevational permafrost site at Chalaping, northeastern Qinghai‐Tibet Plateau. Results showed a distinct retarding of warming on the ground surface and subsurface under the presence of dense vegetation and moist peat substrates. Mean annual Ta and LST increased at noteworthy rates of 0.22 and 0.32 °C/a, respectively, while mean annual GST increased only at a rate of 0.057 °C/a. No obvious trends were detected for the four radiation budgets except the soil heat flux (G), which significantly increased at a rate of 0.29 W · m−2 · a−1, presumably inducing the melting of ground ice and resulted in much higher moisture content through the summers of 2015 and 2016 than preceding years and subsequent 2017 at the depths between 80 and 120 cm. However, no noticeable immediate variations of soil temperatures occurred owing to the large latent heat effect (thermal inertia) and the extending zero‐curtain period. We suggest that a better protected eco‐environment, particularly the surface vegetation, helps preserving the underlying permafrost, and thus to mitigates the potential degradation of elevational permafrost on the Qinghai‐Tibet Plateau.
D. L. Luo; H. J. Jin; R. X. He; X. F. Wang; R. R. Muskett; Sergey Marchenko; V. E. Romanovsky. Characteristics of Water‐Heat Exchanges and Inconsistent Surface Temperature Changes at an Elevational Permafrost Site on the Qinghai‐Tibet Plateau. Journal of Geophysical Research: Atmospheres 2018, 123, 1 .
AMA StyleD. L. Luo, H. J. Jin, R. X. He, X. F. Wang, R. R. Muskett, Sergey Marchenko, V. E. Romanovsky. Characteristics of Water‐Heat Exchanges and Inconsistent Surface Temperature Changes at an Elevational Permafrost Site on the Qinghai‐Tibet Plateau. Journal of Geophysical Research: Atmospheres. 2018; 123 (18):1.
Chicago/Turabian StyleD. L. Luo; H. J. Jin; R. X. He; X. F. Wang; R. R. Muskett; Sergey Marchenko; V. E. Romanovsky. 2018. "Characteristics of Water‐Heat Exchanges and Inconsistent Surface Temperature Changes at an Elevational Permafrost Site on the Qinghai‐Tibet Plateau." Journal of Geophysical Research: Atmospheres 123, no. 18: 1.
Gross primary productivity (GPP) is very important in the global carbon cycle. Currently, the newly released estimates of 8-day GPP at 500 m spatial resolution (Collection 6) are provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Science Team for the global land surface via the improved light use efficiency (LUE) model. However, few studies have evaluated its performance. In this study, the MODIS GPP products (GPPMOD) were compared with the observed GPP (GPPEC) values from site-level eddy covariance measurements over seven maize flux sites in different areas around the world. The results indicate that the annual GPPMOD was underestimated by 6%‒58% across sites. Nevertheless, after incorporating the parameters of the calibrated LUE, the measurements of meteorological variables and the reconstructed Fractional Photosynthetic Active Radiation (FPAR) into the GPPMOD algorithm in steps, the accuracies of GPPMOD estimates were improved greatly, albeit to varying degrees. The differences between the GPPMOD and the GPPEC were primarily due to the magnitude of LUE and FPAR. The underestimate of maize cropland LUE was a widespread problem which exerted the largest impact on the GPPMOD algorithm. In American and European sites, the performance of the FPAR exhibited distinct differences in capturing vegetation GPP during the growing season due to the canopy heterogeneity. In addition, at the DE-Kli site, the GPPMOD abruptly produced extreme low values during the growing season because of the contaminated FPAR from a continuous rainy season. After correcting the noise of the FPAR, the accuracy of the GPPMOD was improved by approximately 14%. Therefore, it is crucial to further improve the accuracy of global GPPMOD, especially for the maize crop ecosystem, to maintain food security and better understand global carbon cycle.
Xiaojuan Huang; Mingguo Ma; Xufeng Wang; Xuguang Tang; Hong Yang. The uncertainty analysis of the MODIS GPP product in global maize croplands. Frontiers of Earth Science 2018, 12, 739 -749.
AMA StyleXiaojuan Huang, Mingguo Ma, Xufeng Wang, Xuguang Tang, Hong Yang. The uncertainty analysis of the MODIS GPP product in global maize croplands. Frontiers of Earth Science. 2018; 12 (4):739-749.
Chicago/Turabian StyleXiaojuan Huang; Mingguo Ma; Xufeng Wang; Xuguang Tang; Hong Yang. 2018. "The uncertainty analysis of the MODIS GPP product in global maize croplands." Frontiers of Earth Science 12, no. 4: 739-749.
Vegetation phenology is a sensitive indicator of climate change, and has significant effects on the exchange of carbon, water and energy between the terrestrial biosphere and the atmosphere. The Tibetan Plateau, the Earth's “third pole”, is a unique region for studying the long-term trends in vegetation phenology in response to climate change because of the sensitivity of its alpine ecosystems to climate and its low-level human disturbance. There has been a debate whether the trends in spring phenology over the Tibetan Plateau have been continuously advancing over the last two to three decades. In this study, we examine the trends in the start of growing season (SOS) for alpine meadow and steppe using the GIMMS3g NDVI dataset (1982-2014), the GIMMS NDVI dataset (1982-2006), the MODIS NDVI dataset (2001-2014), the SPOT Vegetation NDVI dataset (1999-2013) and the SeaWiFS NDVI dataset (1998-2007). Both logistic and polynomial fitting methods are used to retrieve the SOS dates from the NDVI datasets. Our results show that the trends in spring phenology over the Tibetan Plateau depend on both the NDVI dataset used and the method for retrieving the SOS date. There are large discrepancies in the SOS trends among the different NDVI datasets and between the two different retrieval methods. There is no consistent evidence that spring phenology (“green-up” dates) has been advancing over the Tibetan Plateau during the last two to three decades. Ground-based budburst data also indicate no consistent trends in spring phenology. The responses of SOS to environmental factors (air temperature, precipitation, soil temperature and snow depth) also vary among NDVI datasets and phenology retrieval methods. The increases in winter and spring temperature had offsetting effects on spring phenology.
Xufeng Wang; Jingfeng Xiao; Xin Li; Guodong Cheng; Mingguo Ma; Tao Che; Liyun Dai; Shaoying Wang; Jinkui Wu. No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau. Journal of Geophysical Research: Biogeosciences 2017, 122, 3288 -3305.
AMA StyleXufeng Wang, Jingfeng Xiao, Xin Li, Guodong Cheng, Mingguo Ma, Tao Che, Liyun Dai, Shaoying Wang, Jinkui Wu. No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau. Journal of Geophysical Research: Biogeosciences. 2017; 122 (12):3288-3305.
Chicago/Turabian StyleXufeng Wang; Jingfeng Xiao; Xin Li; Guodong Cheng; Mingguo Ma; Tao Che; Liyun Dai; Shaoying Wang; Jinkui Wu. 2017. "No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau." Journal of Geophysical Research: Biogeosciences 122, no. 12: 3288-3305.
Open-path eddy covariance systems are widely used for measuring the CO2 flux between land and atmosphere. A common problem is that they often yield negative fluxes or physiologically unreasonable CO2 uptake fluxes in the nongrowing season under cold conditions. In this study, a meta-analysis was performed on the eddy flux data from 64 FLUXNET sites and the relationship between the observed CO2 flux and the sensible heat flux was analyzed. In theory, these two fluxes should be independent of each other in cold conditions (air temperature lower than 0°C) when photosynthesis is suppressed. However, the results show that a significant and negative linear relationship existed between these two fluxes at 37 of the sites. The mean linear slope value is −0.008 ± 0.001 µmol m−2 s−1 per W m−2 among the 64 sites analyzed. The slope value was not significantly different among the three gas analyzer models (LI-7500, LI-7500A, IRGASON/EC150) used at these sites, indicating that self-heating may not be the only reason for the apparent wintertime net CO2 uptake. These results suggest a systematic bias toward larger carbon uptakes in the FLUXNET sites that deploy open-path eddy covariance systems.
Liming Wang; Xuhui Lee; Wei Wang; Xufeng Wang; Zhongwang Wei; Congsheng Fu; Yunqiu Gao; Ling Lu; Weimin Song; Peixi Su; Guanghui Lin. A Meta-Analysis of Open-Path Eddy Covariance Observations of Apparent CO2 Flux in Cold Conditions in FLUXNET. Journal of Atmospheric and Oceanic Technology 2017, 34, 2475 -2487.
AMA StyleLiming Wang, Xuhui Lee, Wei Wang, Xufeng Wang, Zhongwang Wei, Congsheng Fu, Yunqiu Gao, Ling Lu, Weimin Song, Peixi Su, Guanghui Lin. A Meta-Analysis of Open-Path Eddy Covariance Observations of Apparent CO2 Flux in Cold Conditions in FLUXNET. Journal of Atmospheric and Oceanic Technology. 2017; 34 (11):2475-2487.
Chicago/Turabian StyleLiming Wang; Xuhui Lee; Wei Wang; Xufeng Wang; Zhongwang Wei; Congsheng Fu; Yunqiu Gao; Ling Lu; Weimin Song; Peixi Su; Guanghui Lin. 2017. "A Meta-Analysis of Open-Path Eddy Covariance Observations of Apparent CO2 Flux in Cold Conditions in FLUXNET." Journal of Atmospheric and Oceanic Technology 34, no. 11: 2475-2487.
Xin Tian; Min Yan; Christiaan van der Tol; Zengyuan Li; Zhongbo Su; Erxue Chen; Xin Li; Longhui Li; Xufeng Wang; Xiaoduo Pan; Lushuang Gao; Zongtao Han. Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains. Agricultural and Forest Meteorology 2017, 246, 1 -14.
AMA StyleXin Tian, Min Yan, Christiaan van der Tol, Zengyuan Li, Zhongbo Su, Erxue Chen, Xin Li, Longhui Li, Xufeng Wang, Xiaoduo Pan, Lushuang Gao, Zongtao Han. Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains. Agricultural and Forest Meteorology. 2017; 246 ():1-14.
Chicago/Turabian StyleXin Tian; Min Yan; Christiaan van der Tol; Zengyuan Li; Zhongbo Su; Erxue Chen; Xin Li; Longhui Li; Xufeng Wang; Xiaoduo Pan; Lushuang Gao; Zongtao Han. 2017. "Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains." Agricultural and Forest Meteorology 246, no. : 1-14.
Carbon exchange between terrestrial ecosystems and environment is paid great attention in recent decades, because it can regulate the atmospheric carbon dioxide concentration. Photosynthesis is the key process in the carbon cycle. GPP, NPP, and NEP are key variables in carbon cycle study. Thus, accurate estimation of these carbon fluxes is important for understanding the interactions between terrestrial ecosystems and atmosphere. In this chapter, we introduce measuring methods of these carbon fluxes at field scale and estimating models of these carbon fluxes based on remote sensing data at regional or global scale. The processes and key questions in these methods or models are specifically analyzed.
X. F. Wang; H. B. Wang; X. Li; Y.H. Ran. Photosynthesis (NPP, NEP, Respiration). River Basin Management 2017, 1 -30.
AMA StyleX. F. Wang, H. B. Wang, X. Li, Y.H. Ran. Photosynthesis (NPP, NEP, Respiration). River Basin Management. 2017; ():1-30.
Chicago/Turabian StyleX. F. Wang; H. B. Wang; X. Li; Y.H. Ran. 2017. "Photosynthesis (NPP, NEP, Respiration)." River Basin Management , no. : 1-30.
Youhua Ran; Xin Li; Rui Sun; Natascha Kljun; Lei Zhang; Xufeng Wang; Gaofeng Zhu. Spatial representativeness and uncertainty of eddy covariance carbon flux measurements for upscaling net ecosystem productivity to the grid scale. Agricultural and Forest Meteorology 2016, 230-231, 114 -127.
AMA StyleYouhua Ran, Xin Li, Rui Sun, Natascha Kljun, Lei Zhang, Xufeng Wang, Gaofeng Zhu. Spatial representativeness and uncertainty of eddy covariance carbon flux measurements for upscaling net ecosystem productivity to the grid scale. Agricultural and Forest Meteorology. 2016; 230-231 ():114-127.
Chicago/Turabian StyleYouhua Ran; Xin Li; Rui Sun; Natascha Kljun; Lei Zhang; Xufeng Wang; Gaofeng Zhu. 2016. "Spatial representativeness and uncertainty of eddy covariance carbon flux measurements for upscaling net ecosystem productivity to the grid scale." Agricultural and Forest Meteorology 230-231, no. : 114-127.