Modeling the spatial–temporal dynamics of water use efficiency in Yangtze River Basin using IBIS model

Climate change alters regional water and carbon cycling, which has been a hot study point in the filed of climatology and ecology. As a traditionally “water-rich” region of China, Yangtze River Basin plays an important role in regional economic development and ecosystem productivity. However, the mechanism of the influence of climate change on water and carbon cycling has been received little attention. As a coupling indicator for carbon and water, the water use efficiency (WUE) is widely used, which indicates the water consumption for carbon sequestration in watershed and regional scale. A lot of studies showed that climate change has significantly affected the water resource and production of the ecosystems in Yangtze River Basin during the period of 1956–2006, when great climate variations were occurred. To better understand the alternation pattern for the relationship between water and carbon cycling under climate change at regional scale, the WUE and the spatiotemporal variations patterns were simulated in the study area from 1956 to 2006 by using the Integrated Biosphere Simulator (IBIS). The results showed that the WUE spatial pattern had the annual and seasonal variations. In general, the average annual WUE value per square meter was about 0.58 g C/kg H₂O in Yangtze River Basin. The high WUE levels were mainly distributed in the eastern area of Sichuan, western area of Jiangxi and Hunan, and the highest value reached 0.88 g C/kg H₂O. The lowest WUE’s were mainly located in the western area of Sichuan and Qinghai with the lowest values reaching to 0.36 g C/kg H₂O. The WUE in other regions mostly ranged from 0.5 to 0.6 g C/kg H₂O. For the whole study area, the annual WUE slowly increased from 1956 to 2006. The WUE in the upper reaches of Yangtze River increased based on the simulated temporal trends, which mainly located in the western area of the Sichuan Basin; the WUE of the middle reaches of Yangtze River had increased slightly from 1987 to 1996, and then decreased from 1996 to 2006; the lower reaches of Yangtze River always had smaller WUE’s than the average from 1956 to 2006. The spatiotemporal variability of the WUE in the vegetation types was obvious in the Yangtze River Basin, and it was depended on the climate and soil conditions, and as well the disturbance in its distribution areas. The temporal variations of WUE among different vegetation types had similar trends but different in values. The forest type had higher WUE than any other vegetation types ranging from 0.65 to 0.8 g C/kg H₂O. The WUE of shrubland ranged from 0.45 to 0.6 g C/kg H₂O. The WUE of tundra was the lowest, indicating the differences in plant physiology. The consistence of the spatial pattern of WUE with the NPP indicated that the regional production of Yangtze River Basin increased based on the water resources prompted and vegetation restoration. We found the drought climate was one of critical factor that impacts the alteration of WUE in Yangtze River Basin in the simulation.     

Simulating the rice yield change in the middle and lower reaches of the Yangtze River under SRES B2 scenario

As one of the most important crops in China, rice accounts for 18% of the country’s total cultivated area. Increasing atmospheric CO₂ concentration and associated climate change may greatly affect the rice productivity. Therefore, understanding the impacts of climate change on rice production is of great significance. This paper aims to examine the potential impacts of future climate change on the rice yield in the middle and lower reaches of the Yangtze River, which is one of the most important food production regions in China. Climate data generated by the regional climate Model PRECIS for the baseline (1961–1990) and future (2021–2050) period under IPCC SRES B2 scenario were employed as the input of the rice crop model ORYZA2000. Four experimental schemes were carried out to evaluate the effects of future climate warming, CO₂ fertilization and water managements (i.e., irrigation and rain-fed) on rice production. The results indicated that the average rice growth duration would be shortened by 4 days and the average rice yield would be declined by more than 14% as mean temperature raised by 1.5 °C during the rice growing season in 2021–2050 period under B2 scenario. This negative effect of climate warming was more obvious on the middle and late rice than early rice, since both of them experience higher mean temperature and more extreme high temperature events in the growth period from July to September. The significance effect of the enhanced CO₂ fertilization to rice yield was found under elevated CO₂ concentrations in 2021–2050 period under B2 scenario, which would increase rice yield by more than 10%, but it was still not enough to offset the negative effect of increasing temperature. As an important limiting factor to rice yield, precipitation contributed less to the variation of rice yield than either increased temperature or CO₂ fertilization, while the spatial distribution of rice yield depended on the temporal and spatial patterns of precipitation and temperature. Compared to the rain-fed rice, the irrigated rice generally had higher rice yield over the study area, since the irrigated rice was less affected by climate change. Irrigation could increase the rice yield by more than 50% over the region north of the Yangtze River, with less contribution to the south, since irrigation can relieve the water stress for rice growing in the north region of the study area. The results above indicated that future climate change would significantly affect the rice production in the middle and lower reaches of the Yangtze River. Therefore, the adverse effect of future climate change on rice production will be reduced by taking adaptation measures to avoid disadvantages. However, there is uncertainty in the rice production response prediction due to the rice acclimation to climate change and bias in the simulation of rice yield with uncertainty of parameters accompanied with the uncertainty of future climate change scenario.     

Simulating the rice yield change in the middle and lower reaches of the Yangtze River under SRES B2 scenario

As one of the most important crops in China, rice accounts for 18% of the country’s total cultivated area. Increasing atmospheric CO₂ concentration and associated climate change may greatly affect the rice productivity. Therefore, understanding the impacts of climate change on rice production is of great significance. This paper aims to examine the potential impacts of future climate change on the rice yield in the middle and lower reaches of the Yangtze River, which is one of the most important food production regions in China. Climate data generated by the regional climate Model PRECIS for the baseline (1961–1990) and future (2021–2050) period under IPCC SRES B2 scenario were employed as the input of the rice crop model ORYZA2000. Four experimental schemes were carried out to evaluate the effects of future climate warming, CO₂ fertilization and water managements (i.e., irrigation and rain-fed) on rice production. The results indicated that the average rice growth duration would be shortened by 4 days and the average rice yield would be declined by more than 14% as mean temperature raised by 1.5 °C during the rice growing season in 2021–2050 period under B2 scenario. This negative effect of climate warming was more obvious on the middle and late rice than early rice, since both of them experience higher mean temperature and more extreme high temperature events in the growth period from July to September. The significance effect of the enhanced CO₂ fertilization to rice yield was found under elevated CO₂ concentrations in 2021–2050 period under B2 scenario, which would increase rice yield by more than 10%, but it was still not enough to offset the negative effect of increasing temperature. As an important limiting factor to rice yield, precipitation contributed less to the variation of rice yield than either increased temperature or CO₂ fertilization, while the spatial distribution of rice yield depended on the temporal and spatial patterns of precipitation and temperature. Compared to the rain-fed rice, the irrigated rice generally had higher rice yield over the study area, since the irrigated rice was less affected by climate change. Irrigation could increase the rice yield by more than 50% over the region north of the Yangtze River, with less contribution to the south, since irrigation can relieve the water stress for rice growing in the north region of the study area. The results above indicated that future climate change would significantly affect the rice production in the middle and lower reaches of the Yangtze River. Therefore, the adverse effect of future climate change on rice production will be reduced by taking adaptation measures to avoid disadvantages. However, there is uncertainty in the rice production response prediction due to the rice acclimation to climate change and bias in the simulation of rice yield with uncertainty of parameters accompanied with the uncertainty of future climate change scenario.     

Response of vegetation and soil carbon accumulation rate for China's mature forest on climate change北大核心CSCD

Aims This study aims to evaluate the impacts of future climate change on vegetation and soil carbon accumulation rate in China's forests. Methods The vegetation and soil carbon storage were predicted by the atmosphere-vegetation interaction model (AVIM2) based on B2 climate change scenario during the period of 1981 2040. This study focused on mature forests in China and the forested area maintained constant over the study period. The carbon accumulation rate in year t is defined as the carbon storage of year t minus that of year t 1. Important findings Under B2 climate change scenario, mean air temperature in China's forested area was projected to rise from 7.8 °C in 1981 to 9.0 °C in 2040. The total vegetation carbon storage was then estimated to increase from 8.56 Pg C in 1981 to 9.79 Pg C in 2040, meanwhile total vegetation carbon accumulation rate was estimated to fluctuate between 0.054 0.076 Pg C•a1, with the average of 0.022 Pg C•a1. The total soil carbon storage was estimated to increase from 30.2 Pg C in 1981 to 30.72 Pg C in 2040, and total soil carbon accumulation rate was estimated to vary in the range of 0.035 0.072 Pg C•a1, with the mean of 0.010 Pg C•a1. The response of vegetation and soil carbon accumulation rate to climate change had significant spatial difference in China although the two time series did not show significant trend over the study period. Our results also showed warming was not in favor of forest carbon accumulation, so in the northeastern and southeastern forested area, especially in the Changbai Mountain, with highest temperature increase in the future, the vegetation and soil carbon accumulation rate were estimated to decrease greatly. However, in the southern of southwestern forested area and other forested area, with relatively less temperature increase, the vegetation and soil carbon accumulation rate was estimated to increase in the future.     

Advance in a terrestrial biogeochemical model—DNDC model

Global climate change is one of the most important issues of contemporary environmental safety. Quantifying regional or global greenhouse gas (GHG) emissions and searching for appropriate mitigation measures have become a relatively hot issue in international global climate change studies. The high temporal and spatial variability of GHG emissions from soils makes their field measurement at regional or national scales impractical. To develop emission factors for a wide range of management practices such as those given in the Intergovernmental Panel on Climate Change Tier I methodology are often considered as a convenient technique to estimate emissions, but these can result in substantial errors when applied to specific geographical regions. Accordingly, considering the complexity of greenhouse gas production in soils, process-based models are required to quantify and predict the GHG emissions, and also interpret the intricate relationships among the gas emissions, the environmental factors and the ecological drivers. Several detailed biogeochemical process-based models of GHG emissions have been developed and accepted in recent years to provide regional scale estimate of GHG emissions and assess the mitigation measures. Among these the DNDC (Denitrification–Decomposition) model, as a process-based biogeochemical model, is capable of predicting the soil fluxes of all three terrestrial greenhouse gases: nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄), as well as other important environmental and economic indicators such as crop production, ammonia (NH₃) volatilisation and nitrate NO₃^- leaching. Originally developed as a tool to simulate GHG emissions generated from agro-ecosystem, DNDC has since been expanded to include ecosystems such as rice paddies, grazed pastures, forests, and wetlands, and the model has attracted worldwide attention to simulate carbon and nitrogen biogeochemical cycles occurring in global ecosystems. This paper introduces the scientific basis underlying the modeling of greenhouse gas emissions from terrestrial soils, brings together the worldwide research undertaken on a wide range of ecosystems to test and verify, improve and modify, and apply the DNDC model to estimate GHG emissions from these systems, and furtherly sums up the advantages and disadvantages of the model for providing a reference for the application and development of the model. Most studies showed that there was a good agreement between the simulated and observed values of CO₂, CH₄ and N₂O emissions from arable, forest and grassland fields at different geographical locations over the world. However, some discrepancies still existed between observed and simulated seasonal patterns of CH₄ and N₂O emissions. Moreover, the DNDC model was mainly tested against experimental data on GHG emissions, but there were a few validations on NO₃^- leaching, soil water dynamics, NH₃ volatilisation which could greatly impact the GHG emissions. With the high development of society and economy, China had been facing a huge challenge between food production and environmental protection. Therefore, it was an urgent task to search optimal measures for optimizing land resource use, increasing crop productivity and reducing adverse environmental impacts. Process-based biogeochemical modeling, as with DNDC, can help in identifying optimal strategies to meet the needs. In future, the DNDC model need to not only improve the capability of predicting the GHG emissions, but also the accuracy of simulating the NO₃^- leaching and soil water dynamics for quantifying the non-point source pollution through modifying the parameters of the model or combining with other models, as SWAT model. The DNDC model will play more and more important role in future studies on global change.     

Advance in a terrestrial biogeochemical model—DNDC model

Global climate change is one of the most important issues of contemporary environmental safety. Quantifying regional or global greenhouse gas (GHG) emissions and searching for appropriate mitigation measures have become a relatively hot issue in international global climate change studies. The high temporal and spatial variability of GHG emissions from soils makes their field measurement at regional or national scales impractical. To develop emission factors for a wide range of management practices such as those given in the Intergovernmental Panel on Climate Change Tier I methodology are often considered as a convenient technique to estimate emissions, but these can result in substantial errors when applied to specific geographical regions. Accordingly, considering the complexity of greenhouse gas production in soils, process-based models are required to quantify and predict the GHG emissions, and also interpret the intricate relationships among the gas emissions, the environmental factors and the ecological drivers. Several detailed biogeochemical process-based models of GHG emissions have been developed and accepted in recent years to provide regional scale estimate of GHG emissions and assess the mitigation measures. Among these the DNDC (Denitrification–Decomposition) model, as a process-based biogeochemical model, is capable of predicting the soil fluxes of all three terrestrial greenhouse gases: nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄), as well as other important environmental and economic indicators such as crop production, ammonia (NH₃) volatilisation and nitrate NO₃^- leaching. Originally developed as a tool to simulate GHG emissions generated from agro-ecosystem, DNDC has since been expanded to include ecosystems such as rice paddies, grazed pastures, forests, and wetlands, and the model has attracted worldwide attention to simulate carbon and nitrogen biogeochemical cycles occurring in global ecosystems. This paper introduces the scientific basis underlying the modeling of greenhouse gas emissions from terrestrial soils, brings together the worldwide research undertaken on a wide range of ecosystems to test and verify, improve and modify, and apply the DNDC model to estimate GHG emissions from these systems, and furtherly sums up the advantages and disadvantages of the model for providing a reference for the application and development of the model. Most studies showed that there was a good agreement between the simulated and observed values of CO₂, CH₄ and N₂O emissions from arable, forest and grassland fields at different geographical locations over the world. However, some discrepancies still existed between observed and simulated seasonal patterns of CH₄ and N₂O emissions. Moreover, the DNDC model was mainly tested against experimental data on GHG emissions, but there were a few validations on NO₃^- leaching, soil water dynamics, NH₃ volatilisation which could greatly impact the GHG emissions. With the high development of society and economy, China had been facing a huge challenge between food production and environmental protection. Therefore, it was an urgent task to search optimal measures for optimizing land resource use, increasing crop productivity and reducing adverse environmental impacts. Process-based biogeochemical modeling, as with DNDC, can help in identifying optimal strategies to meet the needs. In future, the DNDC model need to not only improve the capability of predicting the GHG emissions, but also the accuracy of simulating the NO₃^- leaching and soil water dynamics for quantifying the non-point source pollution through modifying the parameters of the model or combining with other models, as SWAT model. The DNDC model will play more and more important role in future studies on global change.     

Present status and rate of carbon sequestration of forest vegetation in Jilin Province,Northeast China北大核心CSCD

Aims Forests represent the most important component of the terrestrial biological carbon pool and play an important role in the global carbon cycle. The regional scale estimation of carbon budgets of forest ecosystems, however, have high uncertainties because of the different data sources, estimation methods and so on. Our objective was to accurately estimate the carbon storage, density and sequestration rate in forest vegetation in Jilin Province of China, in order to understand the role of the carbon sink and to better manage forest ecosystems. Methods Vegetation survey data were used to determine forest distribution, size of area and vegetation types regionally. In our study, 561 plots were investigated to build volume-biomass models; 288 plots of shrubs and herbs were harvested to calculate the biomass of understory vegetation, and samples of trees, shrubs and herbs were collected to analyze carbon content. Carbon storage, density and sequestration rate were estimated by two forest inventory data (2009 and 2014), combined with volume-biomass models, the average biomass of understory vegetation and carbon content of vegetation. Finally, the distribution patterns of carbon pools were presented using ArcGIS soft ware. Important findings Understory vegetation biomass overall was less than 3% of the tree layer biomass, varying greatly among different forest types and even among the similar types. The carbon content of trees was between 45.80% 52.97%, and that of the coniferous forests was higher than that of the broadleaf forests. The carbon content of shrub and herb layers was about 39.79% 47.25% and 40%, respectively. Therefore, the vegetation carbon conversion coefficient was 0.47 or 0.48 in Jilin Province, and the conventional use of 0.50 or 0.45 would cause deviation of ±5.26%. The vegetation carbon pool of Jilin Province was at the upper range of regional carbon pool and had higher capacity of carbon sequestration. The value in 2009 and 2014 was 471.29 Tg C and 505.76 Tg C, respectively, and the total increase was 34.47 Tg C with average annual growth of 6.89 Tg C•a1. The corresponding carbon sequestration rate was 0.92 t•hm 2•a1. The carbon density rose from 64.58 t•hm 2 in 2009 to 66.68 t•hm2 in 2014, with an average increase of 2.10 t•hm2. In addition, the carbon storage of the Quercus mongolica forests and broadleaved mixed forests, accounted for 90.34% of that of all forests. The carbon increment followed the order of young > over-mature > near mature > middle-aged > mature forests. The carbon sequestration rate of followed the order of over-mature > young > near mature > middle-aged > mature forests. Both the carbon increment and the carbon sequestration rate of mature forests were negative. Furthermore, spatially the carbon storage and density were higher in the east than in the west of Jilin province, while the carbon increment was higher in northeast and middle east than in the west. The carbon sequestration rate was higher in Tonghua and Baishan in the south, followed by Jinlin in the middle and Yanbian in the east, while Baicheng and Songyuan, etc. in west showed negative values.     

The effect of ecological management in the upper reaches of Heihe River

Heihe River is the second largest inland river in northwest China which flows through Qinghai Province, Gansu Province and Inner Mongolia Autonomous Region. Because of the rapid development of social economy, the sharp increase of water utilization in the middle reaches and the aggravation of contradiction of supply and demand on water resources, the water to the lower reaches decreases and the ecological environment deteriorates constantly. According to the severe situation of ecology system depravation in Heihe River basin, Chinese government decided to invest 2.35 billion RMB to carry out 3 years ecological management in Heihe River basin from August in 2001. After 3 years ecological management, the depravation of ecological environment is controlled effectively. This paper researches the ecological management engineering in the upper reaches of Heihe River and evaluates the effect of the ecological management engineering. The methods of field sampling and measuring are used to obtain the index indicating the ecology change in the upper reaches of Heihe River in 2006. The effects of fencing grassland, fencing natural forest, and artificial afforestation to the ecology are evaluated. The result suggests that: Firstly, in fencing grassland area, the yield of grass had increased by 42–113%, average height of the grass had increased by 60–100%, and the degree of coverage had increased by 67–100%. Secondly, in fencing natural forests area, the degree of coverage had increased by 15–33%, the shade density had increased by 50–100%, average height had increased by 80–125%, and the crown size had increased by 63–186%. Thirdly, the growth increment of the trees in artificial afforestation area is bigger than that outside artificial afforestation area. In conclusion, ecological management leads to obvious ecological effect in the upper reaches of Heihe River.     

The effect of ecological management in the upper reaches of Heihe River

Heihe River is the second largest inland river in northwest China which flows through Qinghai Province, Gansu Province and Inner Mongolia Autonomous Region. Because of the rapid development of social economy, the sharp increase of water utilization in the middle reaches and the aggravation of contradiction of supply and demand on water resources, the water to the lower reaches decreases and the ecological environment deteriorates constantly. According to the severe situation of ecology system depravation in Heihe River basin, Chinese government decided to invest 2.35 billion RMB to carry out 3 years ecological management in Heihe River basin from August in 2001. After 3 years ecological management, the depravation of ecological environment is controlled effectively. This paper researches the ecological management engineering in the upper reaches of Heihe River and evaluates the effect of the ecological management engineering. The methods of field sampling and measuring are used to obtain the index indicating the ecology change in the upper reaches of Heihe River in 2006. The effects of fencing grassland, fencing natural forest, and artificial afforestation to the ecology are evaluated. The result suggests that: Firstly, in fencing grassland area, the yield of grass had increased by 42–113%, average height of the grass had increased by 60–100%, and the degree of coverage had increased by 67–100%. Secondly, in fencing natural forests area, the degree of coverage had increased by 15–33%, the shade density had increased by 50–100%, average height had increased by 80–125%, and the crown size had increased by 63–186%. Thirdly, the growth increment of the trees in artificial afforestation area is bigger than that outside artificial afforestation area. In conclusion, ecological management leads to obvious ecological effect in the upper reaches of Heihe River.     

Effects of simulated elevated concentration of atmospheric CO2 and temperature on soil enzyme activity in the subalpine fir forest

Little is known about the responses of the activities of soil enzymes that are related to mass cycle to simulated climate change. Therefore, 72 intact soil columns from the primary fir (Abies faxoniana Rehder & E. H. Wilson) forest were parked in environment-controlled chambers with the CK (outside ambient CO₂ concentration and temperature), EC (elevated concentration CO₂ with (347.1 ± 22.1) μmol·mol^?1), ET (elevated temperature with (2.4 ± 0.4)°C), and ECT (elevated CO₂ concentration with (352.8 ± 27.6) μmol·mol^?1 and temperature with (2.2 ± 0.5)°C) treatments, and the activities of invertase, urease, nitrate reductase and acid phosphatase, which are related to the cycles of carbon, nitrogen and phosphorus in mineral soil (MS) and organic layer (OL) were measured simultaneously to understand the responses of these enzymes to climate change. Significant monthly variations on the activities of the studied enzymes were found in both OL and MS with the highest enzyme activities in summer, which were of ecological significance for soil nutrient availability and tree nutrition in the subalpine forest ecosystem. Different monthly patterns of enzyme activities were attributed to enzyme sources and soil layer. EC treatment had influenced slightly on the activities of the studied enzymes resulting from the higher CO₂ concentration in soil atmosphere and no indirect effect from the EC owing to a lack of trees planted on soils. ET treatment increased enzyme activities in comparison with the CK treatment because ET was beneficial to microbial growth and propagation. The increments of the enzyme activities in OL were higher than those in MS, implying that OL is more sensitive to climate change. ECT treatment sharply increased enzyme activities in comparison with the EC and CK, but there was no significant difference between ET and ECT, which was also attributed to no indirect effect by EC treatment owing to trees not planted on soils, implying that the increment of enzyme activities resulted from the temperature effect. However, further studies on indirect effect and complex effect on soil enzyme activity caused by EC, ET and ECT are needed to understand the soil enzyme responses to the climate change.     

黄河流域植被格局变化对水分利用效率的影响

黄河流域横跨3个气候带,是全球人类活动最为强烈的地区之一,特殊的地理位置和复杂的下垫面导致其碳-水循环过程较为复杂。研究黄河流域碳水循环不仅是区域水资源利用的基础,也是实现气候变化条件下双碳目标的关键。水分利用效率(WUE)作为表征碳水过程的重要指标,可用于反映生态系统碳水耦合规律及其相互作用关系。基于此,利用全球陆表特征参量数据(GLASS)的净初级生产力(NPP)和蒸散(ET)产品以及中国逐年土地利用与覆盖数据集(CLUD-A),分析了黄河流域植被格局变化背景下WUE在1990—2018年的时空变化特征及其驱动力。结果表明：(1)黄河流域全域WUE在29 a的均值处在0.18—1.53 g C/kg H₂O之间,存在明显的空间异质性,上游地区WUE明显高于中下游地区,分别在0.66—0.92 g C/kg H₂O和0.43—0.62 g C/kg H₂O之间波动,二者均存在波动上升态势。(2)黄河流域全域WUE在以2000年为中间点的10 a的增速达到近29 a的峰值,流域植被格局变化所带来的流域内NPP与ET变化速...     

长江经济带水分利用效率变化及与温度和降水的关系

通过水分利用效率(Water Use Efficiency, WUE)深入理解生态系统水碳循环的相互关系,可以较好地评估生态系统对气候变化的响应。长江经济带自然资源丰富、生态系统格局复杂,是中国重要的经济发展区,同时也是响应气候变化的重要区域。基于生态系统过程模型CEVSA2(Carbon Exchange between Vegetation, Soil and Atmosphere),估算了1981—2010年长江经济带WUE的时空动态变化,并分析其与温度和降水之间的关系。结果表明:(1)长江经济带1981—2010年WUE均值为1.14 g C mm~(-1 )m~(-2),WUE的空间分布与降水量呈显著正相关关系(r=0.571,P0.01),而与温度呈显著负相关(r=-0.740,P0.01);(2)长江经济带1981—2010年WUE变动区间为1.04—1.19 g C mm~(-1) m~(-2),WUE总体呈减少趋势,平均每年降低0.0030 g C mm~(-1) m~(-2);(3)研究区域内四种主要植被类型常绿针叶林、常绿阔叶林、草地和常绿灌丛的水分利用效率均呈下降趋势,下降速率分别为-3.29×10~(-3)、-2.99×10~(-3)、-3.30×10~(-3)、-2.65×10~(-3) g C mm~(-1) m~(-2) a~(-1)。研究区域内各植被类型的WUE与降水量的相关性不如温度显著,温度对WUE的影响要大于降水对WUE的影响。今后在提高时空分辨率的基础上,更精确地模拟和预测未来温度、降水等气候因子变化下长江经济带WUE变化趋势及分析该地区水碳耦合关系。     

2000—2019年长江流域植被覆盖时空演化及其驱动因素

长江流域作为中国重要的生态屏障，科学认识长江流域植被覆盖时空变化及其驱动因素，对有效开展长江流域生态工程建设具有重要的指导意义与应用价值。基于2000—2019年间MODIS-NDVI与相关气象等数据，采用Theil-Sen median趋势分析、Mann-Kendall检验、变异系数、偏相关分析、残差分析等方法，研究了近20年来长江流域植被覆盖的时空分布与变化特征，并探究了研究区植被覆盖的驱动因素。结果表明：(1)时间变化上，长江流域生长季NDVI呈现波动增长趋势，显著改善面积大于退化面积；(2)空间分布上，流域植被覆盖空间分布格局大致呈现为“中部高，东西低”,生长季NDVI多年均值为0.6164,呈较高植被覆盖状态；(3)变化趋势上，植被增长区域大于减少区域，具体表现为“中部强于东部、东部强于西部”;(4)变化稳定性上，流域植被变异系数介于0.0104—1.3199之间，呈现出“中间低，东西高，东西部局部区域高低波动并存，地域性差异明显”的空间变化稳定性特征；(5)影响因素上，流域植被覆盖变化受气温和降水的共同影响，大部分区域生长季NDVI变化以气候驱动为主，局部区域表现自然因素叠...     

黑河流域植被水分利用效率时空分异及其对降水和气温的响应

植被水分利用效率(WUE)是衡量植被生态系统碳水耦合关系的重要指标,研究其时空分异特征对区域水资源合理利用及配置有重要意义。基于改进的光能利用率模型CASA,模拟估算了黑河流域2000—2013年植被净初级生产力(NPP),结合ETWatch模型估算的黑河流域2000—2013年蒸散数据ET,进一步估算了黑河流域植被水分利用效率WUE。分析了黑河流域NPP、ET和WUE空间格局和时间变化特征,探讨了WUE变化对降水和气温的相关性。结果表明:1)黑河流域空间上植被NPP在2000—2013年多年平均值为81.05 gC m~(-2) a~(-1),ET平均值为133.38 mm,植被WUE平均值为0.448 gC mm~(-1) m~(-2)。植被NPP、ET与WUE的空间格局基本上类似,均呈现出自上游至下游逐渐减少的分布格局。2)黑河流域2000—2013年间植被平均NPP与平均WUE均呈现显著上升趋势(P0.05),而ET平均值变化不显著。WUE年际变化斜率与其平均值在空间分布上存在一定的对应关系,空间上植被WUE的高值区同时是其呈增长趋势的主要区域,植被WUE平均值较低的区域其年际变化也趋于稳定。3)不同植被类型的WUE差异较为显著,植被自身受环境影响形成的生理生态参数是其WUE差异的主要原因,不同植被类型WUE平均值关系为:灌丛草地森林农田沼泽荒漠。中游绿洲区栽培植被平均WUE仅为0.90 gC mm~(-1) m~(-2),因此应当重视提高其对水资源的利用效率。4)整体上黑河流域植被WUE年际变化主要受降水的影响,植被WUE与降水呈负相关的区域主要分布在中游绿洲灌溉区,表明人为活动干扰会削弱气候因素对植被WUE的影响。     

宁夏陆地生态系统水分利用效率特征及其影响因子

生态系统水分利用效率(Water Use Efficiency, WUE)是表征生态系统碳水耦合程度的重要指标,能反映生态系统碳水循环规律及其相互作用关系。基于MODIS数据以及宁夏生态系统类型数据,分析2000—2017年宁夏不同生态系统WUE的变化特征,探讨了NPP和ET两种因子对WUE年际与年内变化的影响。结果表明:(1)全区陆地生态系统的年均WUE为1.03 g·C/kg·H_2O,值域在0.55—2.98 g·C/kg·H_2O之间,总体上呈现南北高、中部低的特征。(2)不同生态系统的WUE差异较大,由高到低为水体及湿地、森林、农田、草地、聚落、荒漠和其他生态系统,在同类生态系统中,植被生物量和盖度越高的亚类生态系统,其WUE也越高。(3)宁夏陆地生态系统WUE存在着每年0.0141 g·C/kg·H_2O的下降趋势,年内WUE呈典型的单峰形态,变化范围在0.02—2.16 g·C/kg·H_2O之间。(4)年际尺度上,宁夏陆地生态系统WUE与年蒸散(Evapotranspiration,ET)有极显著负相关性(P0.01),而与净初级生产力(Net Primary Production,NPP)没有相关性;年内尺度上,WUE变化与ET呈显著正相关(P0.05),与NPP呈极显著正相关(P0.01),这与植被的年内季节性生长过程有关。(5)根据ET强弱和WUE高低,可将宁夏陆地生态系统水分利用效率特征划分为4类,即低ET低WUE区、低ET高WUE区、高ET低WUE区和高ET高WUE区。宁夏的生态恢复工程在增强植被生产力的同时,也增强了区域水分消耗,致使陆地生态系统整体水分利用效率下降,这为宁夏未来水资源调控和生态重建提供了科学依据。     

鄱阳湖流域不同土地覆被碳水利用效率时空变化及其与气候因子的相关性

鄱阳湖流域作为较突出的碳汇功能区,深入掌握不同土地覆被碳素利用率（CUE）和水分利用效率（WUE）的时空分异规律及其对气候因子的响应,对明确气候变化背景下该流域生态功能和碳水循环有重要意义。利用MODIS数据产品,结合流域土地利用和气象监测数据,辅以趋势分析和相关分析等方法研究了2000-2014年鄱阳湖流域不同土地利用类型CUE和WUE的时空变化特征,并探讨了其与降水、气温和日照时数的相关性。结果表明：1）鄱阳湖流域CUE和WUE多年平均值分别为0.458和0.682 gC/kgH₂O,不同土地利用类型的CUE大小依次为草地 > 水田 > 其他林地 > 旱地 > 疏林地 > 灌木林 > 有林地,WUE大小依次为有林地 > 灌木林 > 旱地 > 疏林地 > 水田 > 其他林地 > 草地;2）鄱阳湖流域CUE、WUE在研究时段内均呈微弱下降趋势,各土地利用类型CUE和WUE则表现出较大的年际波动,且年际变化趋势率具有高度的相似性,其中林地各类型下降趋势最大,其次是旱地和水田,草地最小;3）降水是影响鄱阳湖流域土地覆被碳水利用效率变化的关键因素,其他因子与CUE和WUE的相关性均不显著,不同覆被CUE和WUE对气温、降水和日照时数的响应程度存在较大差异。     

Strong links between teleconnections and ecosystem exchange found at a Pacific Northwest old-growth forest from flux tower and MODIS EVI data

Variability in three Pacific teleconnection patterns are examined to see if net carbon exchange at a low‐elevation, old‐growth forest is affected by climatic changes associated with these periodicities. Examined are the Pacific Decadal Oscillation (PDO), Pacific/North American Oscillation (PNA) and El Niño‐Southern Oscillation (ENSO). We use 9 years of eddy covariance CO₂, H₂O and energy fluxes measured at the Wind River AmeriFlux site, Washington, USA and 8 years of tower‐pixel remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to address this question. We compute a new Composite Climate Index (CCI) based on the three Pacific Oscillations to divide the measurement period into positive‐ (2003 and 2005), negative‐ (1999 and 2000) and neutral‐phase climate years (2001, 2002, 2004, 2006 and 2007). The forest transitioned from an annual net carbon sink (NEP=+217 g C m^?2 yr^?1, 1999) to a source (NEP=?100 g C m^?2 yr^?1, 2003) during two dominant teleconnection patterns. Net ecosystem productivity (NEP), water use efficiency (WUE) and light use efficiency (LUE) were significantly different (P<0.01) during positive (NEP=?0.27 g C m^?2 day^?1, WUE=4.1 mg C g^?1 H₂O, LUE=0.94 g C MJ^?1) and negative (NEP=+0.37 g C m^?2 day^?1, WUE=3.4 mg C g^?1 H₂O, LUE=0.83 g C MJ^?1) climate phases. The CCI was linked to variability in the MODIS Enhanced Vegetation Index (EVI) but not to MODIS Fraction of absorbed Photosynthetically Active Radiation (FPAR). EVI was highest during negative climate phases (1999 and 2000) and was positively correlated with NEP and showed potential for using MODIS to estimate teleconnection‐driven anomalies in ecosystem CO₂ exchange in old‐growth forests. This work suggests that any increase in the strength or frequency of ENSO coinciding with in‐phase, low frequency Pacific oscillations (PDO and PNA) will likely increase CO₂ uptake variability in Pacific Northwest conifer forests.     

基于Biome-BGC模型的北方杨树人工林碳水通量对气候变化的响应研究

研究中国北方杨树人工林碳水通量对气候变化的响应,对于制定合理的经营管理措施以应对区域的气候变化具有重要意义。基于对杨树人工林碳水通量的连续监测数据和对Biome-BGC模型参数的校准,模拟分析杨树人工林碳水通量及水分利用效率(WUE)对气候变化(气温上升、降水变化和大气CO_2浓度上升)的响应规律。结果表明,Biome-BGC模型校准后显著提升了其对杨树人工林碳水通量的模拟精度,对GPP、ET模拟结果的Nash-Sutcliffe效率系数(NS)分别为0.69和0.63,各自提高了64.3%和80%,均方根误差(RMSE)则分别降低至1.94 g C m~(-2) d~(-1)和0.88 mm/d,分别下降了26.5%和25.4%。在未来气候变化情景中,单独的气温上升、降水增加和大气CO_2浓度上升分别造成GPP的降低、升高和升高,其中GPP对大气CO_2浓度上升的响应程度(28%—44%)远高于对气温上升(1%—5%)和降水变化(3%—10%)的,ET则主要受降水的影响,响应程度在5%—14%之间。GPP和ET对气候变化的响应则受不同水平的气温上升、降水变化和大气CO_2浓度上升三者综合作用的影响。基于GPP和ET对气候变化的响应,WUE随气温上升、降水增加表现为降低趋势,随降水减少和大气CO_2浓度升高则呈升高趋势;其对未来气候中大气CO_2浓度升高的响应程度为27.7%—43.6%,远高于对气温上升(1.2%—5.8%)和降水变化(1.2%—3.5%)的,说明未来气候变化中大气CO_2浓度上升是促进杨树生长的主要因素;其中相对于当前WUE(2.8 g C/kg H_2O),C2T2P1和C0T3P0情景下WUE的升高和降低幅度最大,分别为45.4%和5.8%。     

亚洲半干旱区碳水通量时空格局及驱动因素

亚洲半干旱区生态系统敏感，环境问题突出，作为全球近30年来碳水通量变化最大的区域，明确其碳水通量的时空分布格局和驱动因素对区域资源管理与可持续发展、全球气候变化等领域具有重要意义。基于植被与土壤湿度的联合同化产品(LPJ-Vegetation and soil moisture Joint Assimilation, LPJ-VSJA),结合研究区植被及气象数据，分析了亚洲半干旱区2010—2018年碳水通量植被总初级生产力(GPP)、蒸散发(ET)和水分利用效率(WUE)的时空变化、年际变化贡献率以及驱动因素。结果表明：(1)2010—2018年亚洲半干旱区年均GPP、ET、WUE空间格局总体呈“双夹型”,中高纬度与低纬度地区的碳水通量值大于中纬度区域。(2)2010—2018年GPP、ET和WUE的年际变化总体都呈现增长趋势，但只有GPP呈现显著增长趋势(P<0.05),增速为7.82 g C m^-2 a^-1。(3)WUE的年际变化表现为总体先增加后减少，正值中农田对WUE年际变化贡献率最大(54.6%),森林生态系统在面积占比仅有...     

三江平原植被水分利用效率时空变化及其对气象因子变化的响应

水分利用效率(water use efficiency,WUE)是陆地生态系统响应全球变化的重要参数,分析区域生态系统WUE的变化特征及其与气象因子之间的响应关系,对于区域生态系统碳水循环研究以及水资源的科学管理具有重要意义。本文以三江平原为研究区,基于MODIS GPP和ET遥感数据、气象数据以及2000年、2014年土地覆盖数据,分析2000-2014年间植被WUE的时空变化特征以及植被WUE与关键气象因子之间的响应关系,并分析了土地覆盖变化下各植被类型WUE的变化特征。结果表明:三江平原WUE年均值变化呈波动式减少趋势,多年平均植被WUE为1.44 g C·kg^-1H2O;WUE年内变化均近似呈"单峰型"曲线,1-3月及11、12月,WUE均处于最低值,在植被生长季(5-9月)期间,WUE均较高;季节WUE均值由高到低依次为夏季>秋季>春季>冬季;各植被类型WUE年内变化呈"双峰型"曲线,峰值主要分布在4-6月和9月;不同植被类型的年均WUE值从大到小依次为:混交林>针叶林>阔叶林>草地>耕地>永久湿地;三江平原植被WUE与降水、相对湿度、水气压呈正相关,与气温、日照时数呈负相关;随着耕地面积的减少,耕地WUE增加了11.1%,随着落叶阔叶林、草地面积的增加,其植被WUE分别增加了12.8%、15.9%。