中图分类号：S812 文献标识码：A 文章编号：1007-0435（2025）07-2320-13

doi：10.11733/j.issn.1007-0435.2025.07.026

引用格式：，等.新疆草地地上生物量时空变化及对气候因子的响应[J].草地学报，2025，33（7）：2320 -2332 WANG Sheng-ju，LIU Wen-hao，JINGui-li，et al. Temporal and Spatial Changes of Grassand Aboveground Bio mass and Its Response to Climate Factors in Xinjiang[J]. Acta Agrestia Sinica，2O25，33（7） ：2320-2332

Temporal and Spatial Changes of Grassland Aboveground Biomass and Its Response to Climate Factors in Xinjiang

WANG Sheng-ju ^1，2，3 ，LIU Wen-hao1，2.3， JIN Gui- ⋅li^1，2，3* ， CUI Guo-ying4， ZHANG Yong-juan ⁴ ， WEI Xiu-hong4，LI Chao1，2.3，CHEN Meng-tian1.2.3，LI Wen-xiong1.2.3， DU Wen-lin1.2.3

（1.CollgofrassadSieeijanggriculturalUniversitUrui，Xijag30，Chia;2.XijagKyLborato

resourcesandolUruiiinKebatoyfsandoudidest

China，MinistrucatiUigin;4UilsaeialtesiiU grass seedling station），Urumqi，Xinjiang 830o92，China）

Abstract：Timely and accurate estimation of aboveground biomass （AGB） is of great significance for grassland production and ecological evaluation.In this study，we used Landsat-NDVIdata from 199O to 2O22 and field measurements to construct an AGB inversion model to analyze the temporal and spatial variation characteristics of grassland yield over 33 years. The results showed that： （1） The inversion model， y=743.9000x²- 9 8.3630x+49.2360 ，constructed by normalized difference vegetation index and ground measured data had the best fitting effect，with an accuracy of 63.70% ；（2）From 1990 to 2022，the grassland AGB showed an increasing trend and a low value in the mountainous high plain area of the northwest mountainous area.Among the14 prefectures and cities，the Ili Kazak Autonomous Prefecture had the highest average AGB over the years，reaching 31.70g⋅m^-2 ；Among the 11 grassland types，the AGB of lowland meadow grassland was relatively stable compared to other types，and the average AGB of meadow grassland was higher than that of steppe and desert grassland;（3） Grassland AGB was highly corelated with temperature and precipitation，and the most obvious places were the Tianshan Mountains，the Altai Mountains，the marginal desert areas of the Tarim Basin，and the Kunlun Mountains. The results provided a reference for grasping the multi-year variation of grassland AGB and accurately estimating grassland amount and carbon storage in Xinjiang.

Key words：Grassand aboveground biomass;Normalized vegetation index;Inversion;Landsat

草地地上生物量（Aboveground biomass，AGB）是表征植被生长状况、衡量初级生产力的基础指标，对草地载畜能力起决定性作用1。反演天然草地的AGB，了解大面积草地植物生物量的空间动态分布及变化规律，对于评价草地初级生产力、确定草地合理载畜量、确保草地生态安全具有重要的实用价值。目前，草地AGB的估测方法有实地测量和遥感估测2种，传统的调查往往耗时且对草原具有破坏性，遥感技术具有宏观、连续、长期的对地观测能力，为大范围草地植被生物量的动态监测提供了可能2-4。随着遥感数据的不断完善，利用长期地面植被遥感数据动态监测草地植被变化是目前植被生态遥感领域的研究热点[5-6]。例如，张雅等利用Landsat8遥感数据提取6种常用植被指数，运用统计分析方法建立了天山北坡紫泥泉牧场阳坡与阴坡的草地生物量遥感预测模型，并进行了生物量空间反演与验证；赵慧芳等8基于中分辨率成像光谱仪（Moderate-resolution imagingspectroradiometer，MODIS）的归一化植被指数（Normalized difference vegetation index，NDVI）数据结合野外调查，构建了青海省草地地上生物量遥感估算模型，为青海省草地资源保护和草地资源利用提供了科学依据；Zhou等9利用MODIS-NDVI数据集结合机器学习算法构建了三江源地区2001—2019年草地生物量估测模型，认为高精度曲面模型能更准确反演草地地上生物量的空间分布特征。以上研究表明，牧草生长期的地……