A study on the simulation of carbon and water fluxes of Dangxiong alpine meadow and its response to climate change

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.

全球气候变化对青藏高原生态系统产生了深远影响,暖湿化背景下青藏高原植被碳,水通量变化趋势值得关注.高寒草甸是青藏高原最主要的植被类型之一,为理解青藏高原当雄地区高寒草甸生态系统碳,水通量,水分利用效率及其对未来气候变化的响应,本研究利用PEST和DDS两种参数率定方法优化Biome BGC模型,进而模拟2000-2019年当雄站的总初级生产力(GPP)和蒸散量(ET).研究结果表明:DDS参数率定方法具有更优的性能.GPP和ET在研究时段内呈上升趋势,而水分利用效率(WUE)则呈下降趋势.同时,ET和GPP分别在7月和8月达到峰值,而WUE则呈“双峰”变化,分别于5月和11月达到峰值.此外,未来近百年的模拟表明GPP和ET的集合平均结果呈显著增加趋势,其中在SSP5-8.5情景下的增速大于SSP2-4.5情景.WUE在SSP2-4.5情景下呈增加趋势,而在SSP5-8.5情景下呈显著增加趋势.本研究结果可为青藏高原碳,水循环预测研究和植被生态保护的应用研究提供参考和借鉴.