利用Biome-BGC模型模拟了1960—2013年太白山太白红杉林生态系统的净初级生产力(NPP),对其与太白红杉的径向生长关系进行了探讨,并分析了NPP值对气候变化的响应关系。结果表明:1960—2013年太白山太白红杉林北坡NPP年均值为305.33g C m^...利用Biome-BGC模型模拟了1960—2013年太白山太白红杉林生态系统的净初级生产力(NPP),对其与太白红杉的径向生长关系进行了探讨,并分析了NPP值对气候变化的响应关系。结果表明:1960—2013年太白山太白红杉林北坡NPP年均值为305.33g C m^(-2)a^(-1),南坡为320.71g C m^(-2)a^(-1),南北坡的NPP值均呈现出一定的上升趋势,北坡的上升速率(0.47g C m^(-2)a^(-1))要小于南坡(1.29g C m^(-2)a^(-1)),但是北坡太白红杉分布下限区NPP值波动浮动较大。且北坡太白红杉NPP值随着海拔高度的上升而逐渐下降,低海拔的变化振幅要大于高海拔地区,南坡无明显变化。多数采样点的模拟NPP值与树轮宽度指数年际变化趋势趋于一致,相关关系呈显著相关。太白红杉标准年表、模型模拟NPP值与气象因子的相关分析均表明太白红杉的生长与生长季气温的相关性显著高于降水,即生长季的气温是太白红杉生长的限制因子。气候的变化作为制约太白红杉生境的重要因素,影响了太白红杉树木的生长,进而对NPP的变化产生了影响。树木年轮很好的检验了Biome-BGC模型模拟结果。展开更多
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...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%。展开更多
以西双版纳橡胶适宜种植区(海拔550—600m)的橡胶林(Hevea brasiliensis)为研究对象,应用参数同化后的Biome-BGC模型模拟了1959—2012年橡胶林的碳循环。结果表明,(1)与涡度相关监测结果相比,橡胶林年总初级生产力(Gross Primary Produc...以西双版纳橡胶适宜种植区(海拔550—600m)的橡胶林(Hevea brasiliensis)为研究对象,应用参数同化后的Biome-BGC模型模拟了1959—2012年橡胶林的碳循环。结果表明,(1)与涡度相关监测结果相比,橡胶林年总初级生产力(Gross Primary Productivity,GPP)、年总呼吸(Total Respiration,Rt)的模拟精度分别为98.37%和90%。由于对年GPP的过低估计和对年Rt的过高估计,年净生态系统交换量(Net Ecosystem Exchange,NEE)的模拟值比实测值低157.35 g C m^(-2)a^(-1)。但若考虑干胶碳(139g C m^(-2)a^(-1)),模拟值与实测值十分接近;(2)橡胶林在模拟进行的前8年里因异养呼吸较高,以碳排放为主,NEE平均约357 g C m^(-2)a^(-1);之后转为以碳固定为主,NEE平均约^(-1)46 g C m^(-2)a^(-1);(3)橡胶林在40年的更新周期中可固定碳1835 g C m^(-2),是一个弱的碳汇。但与热带雨林相同周期固碳6720 g C m^(-2)相比,仍为碳源。以上结果为深入了解橡胶种植对区域碳循环的影响提供了科学依据,建议当地政府一方面要有计划的对老胶林进行更新,以维持当前橡胶林生态系统中的碳平衡;另一方面要注重对热带雨林的保护,从而实现区域经济和生态环境保护的协调发展。展开更多
三峡库区草地群落净生态系统生产力(NEP)的核算对于碳源/汇功能评价和生态屏障功能诊断具有重要理论意义。本文选取三峡库区的三种典型草地群落(雀梅藤群落、芒草群落、扭黄茅群落)为研究对象。基于气象数据和基础数据(高程、植被类型...三峡库区草地群落净生态系统生产力(NEP)的核算对于碳源/汇功能评价和生态屏障功能诊断具有重要理论意义。本文选取三峡库区的三种典型草地群落(雀梅藤群落、芒草群落、扭黄茅群落)为研究对象。基于气象数据和基础数据(高程、植被类型、土壤质地等),利用BIOME-BGC模型模拟并分析了1999—2013年库区草地群落植被NPP、NEP的变化特征及其与水热因子的相关性,分析了碳储量的变化特征及储存分布差异。结果表明:三种草地群落的植被NPP、NEP的年内变化规律均呈现倒U型,其中7—8月数值最大,呈现出明显碳源—碳汇—碳源的变化特征;三种草地群落多年NEP的平均值分别为6.63、4.85、4.17 g C·m^(-2)·a^(-1),碳汇功能明显。不同草地群落NPP、NEP对水热因子响应差异明显,其中雀梅藤群落NPP与温度呈显著正相关,与降水量呈负相关;芒草群落、扭黄茅群落NPP与温度均呈负相关,与降水量呈正相关;三个草地群落的NEP与温度均呈正相关,与降水量均呈负相关。三种草地群落碳储量丰富,多年累计值分别为33 979、50 750、29 236 kg C·m^(-2),且85%~90%储存在土壤中,植被碳储量最少约为3%~4%。展开更多
In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types inclu...In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types include: deciduous broadleaf forest,evergreen needle leaf forest, dwarf shrub and grass.Biome-BGC--a biogeochemical process model wasused to calculate annual ET and NPP for eachvegetation type in the study area from 1954 to 2000.Daily microclimate data of 47 years monitored byLushi meteorological station was extrapolated tocover the basin using MT-CLIM, a mountainmicroclimate simulator. The output files of MT-CLIM were used to feed Biome-BGC. We usedaverage ecophysiological values of each type ofvegetation supplied by Numerical TerradynamicSimulation Group (NTSG) in the University ofMontana as input ecophysiological constants file.The estimates of daily NPP in early July and annualET on these four biome groups were comparedrespectively with field measurements and other studies.Daily gross primary production (GPP) of evergreenneedle leaf forest measurements were very close tothe output of Biome-BGC, but measurements ofbroadleaf forest and dwarf shrub were much smallerthan the simulation result. Simulated annual ET andNPP had a significant correlation with precipitation,indicating precipitation is the major environmentalfactor affecting ET and NPP in the study area.Precipitation also is the key climatic factor for theinterannual ET and NPP variations.展开更多
草甸生态系统具有强大的碳汇功能,在全球碳循环过程中发挥着重要作用。区域尺度草甸生态系统碳通量的精准模拟,可以为揭示草地碳循环对全球变化的反馈机制提供理论依据。生态过程模型则是分析和预测区域碳平衡的重要途径。以甘南州高寒...草甸生态系统具有强大的碳汇功能,在全球碳循环过程中发挥着重要作用。区域尺度草甸生态系统碳通量的精准模拟,可以为揭示草地碳循环对全球变化的反馈机制提供理论依据。生态过程模型则是分析和预测区域碳平衡的重要途径。以甘南州高寒草甸生态系统为研究对象,利用参数优化后的Biome-BGC模型,模拟1979—2018年高寒草甸总初级生产力(Gross Primary Productivity,GPP)和净生态系统生产力(Net Ecosystem Productivity,NEP),以表征该区域碳收支的时空分布特征。以上述40年实测气象数据为基准,并结合第六次国际耦合模式比较计划(Coupled Model Intercomparison Project phase 6,CMIP6)中的3种共享社会经济路径(Shared Socio-economic Pathways,SSPs)情景,对甘南州2019—2100年高寒草甸碳收支进行情景模拟。结果表明:(1)参数优化后的Biome-BGC模型能较好的模拟甘南州高寒草甸GPP和NEP,且GPP模拟对比NEP的模拟效果更好;(2)甘南州高寒草甸在整个研究阶段表现为碳汇,过去40年GPP、NEP波动范围为600—1100 g C m^(-2) a^(-1)、150—300 g C m^(-2) a^(-1),GPP显著上升,NEP呈波动性上升趋势。未来暖湿化情景下,高寒草甸碳收支年际波动较大,NEP呈先上升再下降趋势,2060年前后出现极小值,年均增幅约为2.02 g C m^(-2) a^(-1),气温、降水和大气CO_(2)浓度升高共同影响该地碳收支格局;(3)季节尺度上表现为冬春季节为碳源、夏秋季节为碳汇,植被生长季固碳作用增强。年内GPP、NEP呈倒“U”型变化趋势,峰值均出现在7、8月,低温以及持续增温对碳汇具有抑制作用,生长季降水量与植被生产力呈正相关;(4)碳汇/碳源的空间分布随时间而变化,具有明显的地域差异性,总体上碳汇增长率由西南向东北递减。展开更多
Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations...Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.展开更多
The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of th...The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.展开更多
文摘利用Biome-BGC模型模拟了1960—2013年太白山太白红杉林生态系统的净初级生产力(NPP),对其与太白红杉的径向生长关系进行了探讨,并分析了NPP值对气候变化的响应关系。结果表明:1960—2013年太白山太白红杉林北坡NPP年均值为305.33g C m^(-2)a^(-1),南坡为320.71g C m^(-2)a^(-1),南北坡的NPP值均呈现出一定的上升趋势,北坡的上升速率(0.47g C m^(-2)a^(-1))要小于南坡(1.29g C m^(-2)a^(-1)),但是北坡太白红杉分布下限区NPP值波动浮动较大。且北坡太白红杉NPP值随着海拔高度的上升而逐渐下降,低海拔的变化振幅要大于高海拔地区,南坡无明显变化。多数采样点的模拟NPP值与树轮宽度指数年际变化趋势趋于一致,相关关系呈显著相关。太白红杉标准年表、模型模拟NPP值与气象因子的相关分析均表明太白红杉的生长与生长季气温的相关性显著高于降水,即生长季的气温是太白红杉生长的限制因子。气候的变化作为制约太白红杉生境的重要因素,影响了太白红杉树木的生长,进而对NPP的变化产生了影响。树木年轮很好的检验了Biome-BGC模型模拟结果。
文摘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%。
文摘以西双版纳橡胶适宜种植区(海拔550—600m)的橡胶林(Hevea brasiliensis)为研究对象,应用参数同化后的Biome-BGC模型模拟了1959—2012年橡胶林的碳循环。结果表明,(1)与涡度相关监测结果相比,橡胶林年总初级生产力(Gross Primary Productivity,GPP)、年总呼吸(Total Respiration,Rt)的模拟精度分别为98.37%和90%。由于对年GPP的过低估计和对年Rt的过高估计,年净生态系统交换量(Net Ecosystem Exchange,NEE)的模拟值比实测值低157.35 g C m^(-2)a^(-1)。但若考虑干胶碳(139g C m^(-2)a^(-1)),模拟值与实测值十分接近;(2)橡胶林在模拟进行的前8年里因异养呼吸较高,以碳排放为主,NEE平均约357 g C m^(-2)a^(-1);之后转为以碳固定为主,NEE平均约^(-1)46 g C m^(-2)a^(-1);(3)橡胶林在40年的更新周期中可固定碳1835 g C m^(-2),是一个弱的碳汇。但与热带雨林相同周期固碳6720 g C m^(-2)相比,仍为碳源。以上结果为深入了解橡胶种植对区域碳循环的影响提供了科学依据,建议当地政府一方面要有计划的对老胶林进行更新,以维持当前橡胶林生态系统中的碳平衡;另一方面要注重对热带雨林的保护,从而实现区域经济和生态环境保护的协调发展。
文摘三峡库区草地群落净生态系统生产力(NEP)的核算对于碳源/汇功能评价和生态屏障功能诊断具有重要理论意义。本文选取三峡库区的三种典型草地群落(雀梅藤群落、芒草群落、扭黄茅群落)为研究对象。基于气象数据和基础数据(高程、植被类型、土壤质地等),利用BIOME-BGC模型模拟并分析了1999—2013年库区草地群落植被NPP、NEP的变化特征及其与水热因子的相关性,分析了碳储量的变化特征及储存分布差异。结果表明:三种草地群落的植被NPP、NEP的年内变化规律均呈现倒U型,其中7—8月数值最大,呈现出明显碳源—碳汇—碳源的变化特征;三种草地群落多年NEP的平均值分别为6.63、4.85、4.17 g C·m^(-2)·a^(-1),碳汇功能明显。不同草地群落NPP、NEP对水热因子响应差异明显,其中雀梅藤群落NPP与温度呈显著正相关,与降水量呈负相关;芒草群落、扭黄茅群落NPP与温度均呈负相关,与降水量呈正相关;三个草地群落的NEP与温度均呈正相关,与降水量均呈负相关。三种草地群落碳储量丰富,多年累计值分别为33 979、50 750、29 236 kg C·m^(-2),且85%~90%储存在土壤中,植被碳储量最少约为3%~4%。
文摘In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types include: deciduous broadleaf forest,evergreen needle leaf forest, dwarf shrub and grass.Biome-BGC--a biogeochemical process model wasused to calculate annual ET and NPP for eachvegetation type in the study area from 1954 to 2000.Daily microclimate data of 47 years monitored byLushi meteorological station was extrapolated tocover the basin using MT-CLIM, a mountainmicroclimate simulator. The output files of MT-CLIM were used to feed Biome-BGC. We usedaverage ecophysiological values of each type ofvegetation supplied by Numerical TerradynamicSimulation Group (NTSG) in the University ofMontana as input ecophysiological constants file.The estimates of daily NPP in early July and annualET on these four biome groups were comparedrespectively with field measurements and other studies.Daily gross primary production (GPP) of evergreenneedle leaf forest measurements were very close tothe output of Biome-BGC, but measurements ofbroadleaf forest and dwarf shrub were much smallerthan the simulation result. Simulated annual ET andNPP had a significant correlation with precipitation,indicating precipitation is the major environmentalfactor affecting ET and NPP in the study area.Precipitation also is the key climatic factor for theinterannual ET and NPP variations.
文摘草甸生态系统具有强大的碳汇功能,在全球碳循环过程中发挥着重要作用。区域尺度草甸生态系统碳通量的精准模拟,可以为揭示草地碳循环对全球变化的反馈机制提供理论依据。生态过程模型则是分析和预测区域碳平衡的重要途径。以甘南州高寒草甸生态系统为研究对象,利用参数优化后的Biome-BGC模型,模拟1979—2018年高寒草甸总初级生产力(Gross Primary Productivity,GPP)和净生态系统生产力(Net Ecosystem Productivity,NEP),以表征该区域碳收支的时空分布特征。以上述40年实测气象数据为基准,并结合第六次国际耦合模式比较计划(Coupled Model Intercomparison Project phase 6,CMIP6)中的3种共享社会经济路径(Shared Socio-economic Pathways,SSPs)情景,对甘南州2019—2100年高寒草甸碳收支进行情景模拟。结果表明:(1)参数优化后的Biome-BGC模型能较好的模拟甘南州高寒草甸GPP和NEP,且GPP模拟对比NEP的模拟效果更好;(2)甘南州高寒草甸在整个研究阶段表现为碳汇,过去40年GPP、NEP波动范围为600—1100 g C m^(-2) a^(-1)、150—300 g C m^(-2) a^(-1),GPP显著上升,NEP呈波动性上升趋势。未来暖湿化情景下,高寒草甸碳收支年际波动较大,NEP呈先上升再下降趋势,2060年前后出现极小值,年均增幅约为2.02 g C m^(-2) a^(-1),气温、降水和大气CO_(2)浓度升高共同影响该地碳收支格局;(3)季节尺度上表现为冬春季节为碳源、夏秋季节为碳汇,植被生长季固碳作用增强。年内GPP、NEP呈倒“U”型变化趋势,峰值均出现在7、8月,低温以及持续增温对碳汇具有抑制作用,生长季降水量与植被生产力呈正相关;(4)碳汇/碳源的空间分布随时间而变化,具有明显的地域差异性,总体上碳汇增长率由西南向东北递减。
基金This research was funded by the National Natural Science Foundation of China(Grant Nos.31870426).
文摘Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.
基金supported by the Second Comprehensive Scientific Research Survey on the Tibetan Plateau[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant numbers 42375071 and 42230610].
文摘The alpine meadow ecosystem accounts for 27%of the total area of the Tibetan Plateau and is also one of the most important vegetation types.The Dangxiong alpine meadow ecosystem,located in the south-central part of the Tibetan Plateau,is a typical example.To understand the carbon and water fluxes,water use efficiency(WUE),and their responses to future climate change for the alpine meadow ecosystem in the Dangxiong area,two parameter estimation methods,the Model-independent Parameter Estimation(PEST)and the Dynamic Dimensions Search(DDS),were used to optimize the Biome-BGC model.Then,the gross primary productivity(GPP)and evapotranspiration(ET)were simulated.The results show that the DDS parameter calibration method has a better performance.The annual GPP and ET show an increasing trend,while the WUE shows a decreasing trend.Meanwhile,ET and GPP reach their peaks in July and August,respectively,and WUE shows a“dual-peak”pattern,reaching peaks in May and November.Furthermore,according to the simulation results for the next nearly 100 years,the ensemble average GPP and ET exhibit a significant increasing trend,and the growth rate under the SSP5–8.5 scenario is greater than that under the SSP2–4.5 scenario.WUE shows an increasing trend under the SSP2–4.5 scenario and a significant increasing trend under the SSP5–8.5 scenario.This study has important scientific significance for carbon and water cycle prediction and vegetation ecological protection on the Tibetan Plateau.
文摘准确估算生态系统碳、水通量及水分利用效率对于流域碳水循环研究具有重要意义。文章采用PEST模型参数优化后的Biome-BGC模型,模拟了2003—2019年及未来气候变化情景下总初级生产力(gross primary productivity,GPP)和蒸散发(evapotranspiration,ET),研究了GPP、ET和水分利用效率(water use efficiency,WUE)在不同时间尺度上的变化规律,并探讨了降水和温度的影响。结果表明:GPP、ET和WUE在年尺度上呈现不显著增加趋势;温度和降水联合增加情景对GPP、ET/WUE的影响大于温度或降水单独增加情景。该结果可为流域碳水循环研究提供重要参考。
