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基于土地利用及植被覆盖变化的黄河源区生境质量时空变化特征
引用本文:潘耀,尹云鹤,侯文娟,韩皓爽. 基于土地利用及植被覆盖变化的黄河源区生境质量时空变化特征[J]. 生态学报, 2022, 42(19): 7978-7988
作者姓名:潘耀  尹云鹤  侯文娟  韩皓爽
作者单位:中国科学院地理科学与资源研究所 中国科学院陆地表层格局与模拟重点实验室, 北京 100101;中国科学院大学, 北京 100049
基金项目:第二次青藏高原综合科学考察研究项目(2019QZKK0403);中国科学院战略性先导科技专项(A类)(XDA20020202,XDA19040304)
摘    要:位于青藏高原腹地的黄河源地区生态环境脆弱,面临生物多样性锐减、生态系统退化等问题,黄河源区生态系统保护及其高质量发展已成为国家的重点战略之一。土地利用与植被覆盖是影响生境质量的重要因素,定量化土地利用方式、强度及格局和植被覆盖格局对生态质量影响的研究越来越受到关注,但其对黄河源区生态质量的耦合效应尚不明确。基于2000年和2015年黄河源区土地利用类型及生长季归一化植被指数(NDVI),采用InVEST模型探究了不同时期黄河源区生境质量时空变化,并采用地理加权回归(GWR)模型揭示了生境质量对土地利用和植被覆盖变化的空间响应特征。结果表明,2000年与2015年土地利用类型变化主要为未利用土地向草地的转移。植被覆盖变化方面,源区生长季NDVI整体上升。从生境质量的空间分布来看,黄河源区生境质量总体呈现南高北低的空间格局,高值分布在南部及中部地区,低值分布在北部布青山、东北部高海拔区及黄河乡的黄河沿岸。相较于2000年,2015年黄河源区生境质量平均提高11.47%。草地面积和NDVI与生境质量均呈显著正相关关系,其中NDVI是提高黄河源区生境质量的重要驱动因子。研究结果突出了NDVI对提高黄河源区生境质量的主导作用,可为未来源区生态保护提供借鉴。

关 键 词:生境质量  威胁  归一化植被指数(NDVI)  InVEST模型  地理加权回归模型(GWR)  时空变化
收稿时间:2021-05-13
修稿时间:2022-03-29

Spatiotemporal variation of habitat quality in the Source Region of the Yellow River based on land use and vegetation cover changes
PAN Yao,YIN Yunhe,HOU Wenjuan,HAN Haoshuang. Spatiotemporal variation of habitat quality in the Source Region of the Yellow River based on land use and vegetation cover changes[J]. Acta Ecologica Sinica, 2022, 42(19): 7978-7988
Authors:PAN Yao  YIN Yunhe  HOU Wenjuan  HAN Haoshuang
Affiliation:Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:The Source Region of the Yellow River is situated in the hinterland of Qing-Tibetan Plateau, with very fragile ecosystem. The Source Region of the Yellow River is facing problems such as biodiversity and ecosystem degradation. Ecological protection and high-quality development of the Source Region of the Yellow River has been risen to be one of the key concerns of the national strategy. Land use and vegetation cover are important factors affecting habitat quality. More and more attention has been paid to quantitative evaluation of the impact of the change of land use types, intensity and patterns to habitat quality and the change of the spatiotemporal pattern of vegetation cover to habitat quality. However, the coupling effects of land use and vegetation cover on the habitat quality of the Source Region of the Yellow River are still unclear. Based on the data of land use and the normalized difference vegetation index (NDVI) of vegetation growing season in the Source Region of the Yellow River in 2000 and 2015, this study used the InVEST model to explore the temporal and spatial changes of the habitat quality in the source area of the Yellow River in different periods, and used the geographical weighted regression (GWR) model to quantitatively analyze the coupling effect of land use and NDVI on the evolution of habitat quality. The results showed that land-use types had mainly changed from unused land to grassland in 2000 and 2015 in the Source Region of the Yellow. Overall NDVI in the Source Region of the Yellow River increased during the growing season in 2000 and 2015. From the perspective of spatial distribution, the habitat quality generally presented a spatial pattern of low in the north and high in the south. The high values were distributed in the southern and central regions, and the low values were distributed in the Buqing Mountain in the north, the high-altitude areas in the northeast and along the Yellow River in Yellow River Township. Compared with 2000, the habitat quality in the Source Region of the Yellow River in 2015 increased by 11.47% on average. Both the grassland and NDVI had a significantly positive correlation with the habitat quality, and NDVI dominated the change of habitat quality. The results of this study highlight the leading role of NDVI in improving the habitat quality in the Source Region of the Yellow River and can provide a reference for future ecological protection of the source region.
Keywords:habitat quality  threats  NDVI  InVEST  geographically weighted regression  spatiotemporal change
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