Spatiotemporal variability of photosynthetic and non-photosynthetic vegetation under climate change in arid and semiarid regions in China

被引:0
|
作者
Guo, Liyang [1 ]
Zhang, Fei [2 ,5 ]
Chan, Ngai Weng [3 ]
Tan, Mou Leong [3 ]
Kung, Hsiang-Te [4 ]
Zhang, Mengru [1 ]
机构
[1] Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi, Peoples R China
[2] Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi, Peoples R China
[3] Univ Sains Malaysia, Sch Humanities, GeoInformat Unit, Geog Sect, Gelugor, Penang, Malaysia
[4] Univ Memphis, Dept Earth Sci, Memphis, TN USA
[5] Zhejiang Normal Univ, Coll Geog & Environm Sci, Jinhua 321004, Peoples R China
关键词
Photosynthetic vegetation; non-photosynthetic vegetation; arid and semiarid regions; spatiotemporal variation; climatic factors; partial correlation; NET PRIMARY PRODUCTIVITY; LEAF-AREA INDEX; FRACTIONAL COVER; BARE SOIL; XINJIANG; PRECIPITATION; RESPONSES; DROUGHT; TRENDS; GROWTH;
D O I
10.1080/01431161.2023.2229496
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Understanding the spatiotemporal characteristics of photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) is critical for the study of vegetation in arid and semiarid regions. However, the evaluation of the fractional cover of PV (f (PV)) and NPV (f (NPV)) in Xinjiang has received very little attention. Thus, this study aims to evaluate the spatiotemporal variation characteristics of PV and NPV and their responses to precipitation and temperature in Xinjiang from 2001 to 2020. The results showed that the overall stability of f (PV) and f (NPV) were of the low fluctuation and high fluctuation types, respectively. A significant increase trend of f (PV) was found in most regions (P < 0.01), while f (NPV) showed an insignificant increase trend in general, except for eastern Xinjiang (P > 0.05). The comparison of f (PV) and f (NPV) shows that the vegetation of Xinjiang has improved over time, except for the Yili region, showing the need to strengthen the environmental protection of this region. Through the spatial analysis, some agricultural oasis areas experienced an expansion in the distribution of vegetation, while some sparse vegetation distribution area has not improved. From the climate perspective, the response degree of f (PV) and f (NPV) with precipitation is higher than that of temperature. The responses of f (PV) and f (NPV) to precipitation are greater in the summer and spring phases, respectively. Whereas, the responses of both f (PV) and f (NPV) to temperature are greater in the autumn phase. In the time phase, precipitation mainly promotes the distribution of PV and NPV, while temperature mainly inhibits their distribution. This study provides a theoretical basis for ecological restoration and conservation in Xinjiang and other arid and semiarid regions worldwide.
引用
收藏
页码:3837 / 3860
页数:24
相关论文
共 50 条
  • [1] Effect of climate change on the seasonal variation in photosynthetic and non-photosynthetic vegetation coverage in desert areas, Northwest China
    Bai, Xuelian
    Zhao, Wenzhi
    Luo, Weicheng
    An, Ning
    CATENA, 2024, 239
  • [2] Degradation of Non-Photosynthetic Vegetation in a Semi-Arid Rangeland
    Jackson, Hasan
    Prince, Stephen D.
    REMOTE SENSING, 2016, 8 (08)
  • [3] Nonlinear spectral mixture effects for photosynthetic/non-photosynthetic vegetation cover estimates of typical desert vegetation in western China
    Ji, Cuicui
    Jia, Yonghong
    Gao, Zhihai
    Wei, Huaidong
    Li, Xiaosong
    PLOS ONE, 2017, 12 (12):
  • [4] Effects of Non-Photosynthetic Vegetation on Dust Emissions
    Huang, Xinyue
    Foroutan, Hosein
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2022, 127 (20)
  • [5] Reassessing Soil Wind Erosion in Arid Regions of Central Asia: Fully Considering the Contribution of Non-Photosynthetic Vegetation (NPV)
    Ma, Xiaofei
    He, Huili
    Huo, Tianci
    Su, Yuan
    Yan, Wei
    LAND DEGRADATION & DEVELOPMENT, 2025,
  • [6] Global trends in vegetation fractional cover: Hotspots for change in bare soil and non-photosynthetic vegetation
    Hill, Michael J.
    Guerschman, Juan P.
    AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 2022, 324
  • [7] Novel vegetation indices for estimating photosynthetic and non-photosynthetic fractional vegetation cover from Sentinel data
    Liu, Jiali
    Fan, Jianrong
    Yang, Chao
    Xu, Fubao
    Zhang, Xiyu
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2022, 109
  • [8] Vegetation cover dependence on accumulated antecedent precipitation in Australia: Relationships with photosynthetic and non-photosynthetic vegetation fractions
    Guerschman, Juan P.
    Hill, Michael J.
    Leys, John
    Heidenreich, Stephan
    REMOTE SENSING OF ENVIRONMENT, 2020, 240
  • [9] Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval
    Ji, Cuicui
    Li, Xiaosong
    Wei, Huaidong
    Li, Sike
    REMOTE SENSING, 2020, 12 (01)
  • [10] The Potential of Multispectral Vegetation Indices Feature Space for Quantitatively Estimating the Photosynthetic, Non-Photosynthetic Vegetation and Bare Soil Fractions in Northern China
    Zheng, Guoxiong
    Bao, Anming
    Li, Xiaosong
    Jiang, Liangliang
    Chang, Cun
    Chen, Tao
    Gao, Zhihai
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2019, 85 (01): : 65 - 76