Geng Yixin, Hisoriev Hikmat, Wang Guangyu, Ma Xuexi, Fan Lianlian, Mekhrovar Okhonniyozov, Abdullo Madaminov, Li Jiangyue, Li Yaoming
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.
Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China.
Plants (Basel). 2025 Apr 21;14(8):1266. doi: 10.3390/plants14081266.
Mountain grassland ecosystems around the globe are highly sensitive to seasonal extreme climate events, which thus highlights the critical importance of understanding how such events have affected vegetation dynamics over recent decades. However, research on the time-lag of the effects of seasonal extreme climate events on vegetation has been sparse. This study focuses on Tajikistan, which is characterized by a typical alpine meadow-steppe ecosystem, as the research area. The net primary productivity (NPP) values of Tajikistan's grasslands from 2001 to 2022 were estimated using the Carnegie-Ames-Stanford Approach (CASA) model. In addition, 20 extreme climate indices (including 11 extreme temperature indices and 9 extreme precipitation indices) were calculated. The spatiotemporal distribution characteristics of the grassland NPP and these extreme climate indices were further analyzed. Using geographic detector methods, the impact factors of extreme climate indices on grassland NPP were identified along a gradient of different altitudinal bands in Tajikistan. Additionally, a time-lag analysis was conducted to reveal the lag time of the effects of extreme climate indices on grassland NPP across different elevation levels. The results revealed that grassland NPP in Tajikistan exhibited a slight upward trend of 0.01 gC/(m·a) from 2001 to 2022. During this period, extreme temperature indices generally showed an increasing trend, while extreme precipitation indices displayed a declining trend. Notably, extreme precipitation indices had a significant impact on grassland NPP, with the interaction between Precipitation anomaly (PA) and Max Tmax (TXx) exerting the most pronounced influence on the spatial variation of grassland NPP (q = 0.53). Additionally, it was found that the effect of extreme climate events on grassland NPP had no time-lag at altitudes below 500 m. In contrast, in mid-altitude regions (1000-3000 m), the effect of PA on grassland NPP had a significant time-lag of two months ( < 0.05). Knowing the lag times until the effects of seasonal extreme climate events on grassland NPP will appear in Tajikistan provides valuable insight for those developing adaptive management and restoration strategies under current seasonal extreme climate conditions.
全球山地草原生态系统对季节性极端气候事件高度敏感，这凸显了了解近几十年来此类事件如何影响植被动态的至关重要性。然而，关于季节性极端气候事件对植被影响的时间滞后性研究一直较少。本研究聚焦于以典型高山草甸草原生态系统为特征的塔吉克斯坦作为研究区域。利用卡内基—埃姆斯—斯坦福方法（CASA）模型估算了2001年至2022年塔吉克斯坦草原的净初级生产力（NPP）值。此外，计算了20个极端气候指数（包括11个极端温度指数和9个极端降水指数）。进一步分析了草原NPP和这些极端气候指数的时空分布特征。运用地理探测器方法，沿塔吉克斯坦不同海拔带梯度确定了极端气候指数对草原NPP的影响因素。此外，进行了时间滞后分析，以揭示不同海拔水平下极端气候指数对草原NPP影响的滞后时间。结果表明，2001年至2022年塔吉克斯坦草原NPP呈现出每年每平方米0.01克碳的轻微上升趋势。在此期间，极端温度指数总体呈上升趋势，而极端降水指数呈下降趋势。值得注意的是，极端降水指数对草原NPP有显著影响，降水异常（PA）与最高温度最大值（TXx）之间的相互作用对草原NPP的空间变化影响最为显著（q = 0.53）。此外，发现海拔500米以下地区极端气候事件对草原NPP的影响没有时间滞后。相比之下，在中海拔地区（1000 - 3000米），PA对草原NPP的影响有两个月的显著时间滞后（< 0.05）。了解塔吉克斯坦季节性极端气候事件对草原NPP影响出现的滞后时间，为那些在当前季节性极端气候条件下制定适应性管理和恢复策略的人提供了有价值的见解。
