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Spatio-temporal heterogeneity of vegetation cover and its driving forces in the Taihangshan-Yanshan Region
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Min-li WANG1, 2, Hui-cong ZHANG1, Li-yao DONG1, Jia-rui LI1, Jiao PANG3, *, Feng YAN1, 4, Ling HE1
China Environmental Science | 2025, 45(5) : 2792 - 2805
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China Environmental Science | 2025, 45(5): 2792-2805
Environmental Ecology
Spatio-temporal heterogeneity of vegetation cover and its driving forces in the Taihangshan-Yanshan Region
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Min-li WANG1, 2, Hui-cong ZHANG1, Li-yao DONG1, Jia-rui LI1, Jiao PANG3, *, Feng YAN1, 4, Ling HE1
Affiliations
  • 1.College of Land and Resources, Hebei Agricultural University, Baoding 071001, China
  • 2.School of Land Science and Technology, China University of Geosciences(Beijing), Beijing 100083, China
  • 3.Bohai College, Hebei Agricultural University, Huanghua 061100, China
  • 4.College of Water Resources and Environment, China University of Geosciences(Beijing), Beijing 100083, China
Published: 2025-05-20
Outline
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The Taihangshan-Yanshan region serves as a crucial ecological barrier for the Beijing-Tianjin-Hebei area. Investigating the spatiotemporal patterns of vegetation growth and their influencing factors holds significant importance for implementing ecological conservation and restoration decisions. The MOD13A2.061NDVI dataset was obtained through the Google Earth Engine(GEE)platform, and the kernel Normalized Difference Vegetation Index(kNDVI)was further calculated. The spatiotemporal heterogeneity of vegetation cover was analyzed using the Theil-Sen Median method, coefficient of variation method, and Hurst index method. Subsequently, the optimal parameter geographical detector(OPGD)method was employed to identify the multivariate driving mechanisms behind its spatiotemporal differentiation. Results demonstrated that: From 2001 to 2020, the kNDVI in the study area showed a gradual increasing trend during spring, summer, and autumn, while exhibiting a decreasing trend in winter. The annual mean kNDVI displayed a spatial distribution pattern characterized by "higher values in northern and southern regions, lower in central areas", with significant spatial variability. The area with increased kNDVI(66.36%)was larger than that with decreased kNDVI(33.64%). Weak anti-persistence and weak positive persistence coexisted, collectively accounting for 99.26% of the total area. Approximately 80% of the region maintained kNDVI fluctuations at moderate or lower levels. OPGD analysis revealed that the primary drivers of kNDVI changes included evapotranspiration, land surface temperature, land use type, soil type, and vegetation type(all with q-values greater than 0.20). The interaction effects between land surface temperature and annual average temperature, and between land surface temperature and cumulative precipitation demonstrated particularly strong explanatory power, exceeding 0.50 and 0.47 respectively. Higher kNDVI values were observed when evapotranspiration ranged within(634mm, 814mm], land surface temperature fell within [5.2°C, 11.2°C], and urban population remained in(216000, 280000).

kernel-Normalized Vegetation Index(kNDVI)  /  spatial and temporal succession  /  driving forces  /  Optimal Parameters-based Geographical Detectors(OPGD)  /  Taihangshan-Yanshan region
Min-li WANG, Hui-cong ZHANG, Li-yao DONG, Jia-rui LI, Jiao PANG, Feng YAN, Ling HE. Spatio-temporal heterogeneity of vegetation cover and its driving forces in the Taihangshan-Yanshan Region[J]. China Environmental Science, 2025 , 45 (5) : 2792 -2805 .
Year 2025 volume 45 Issue 5
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Article Info
  • Receive Date:2024-10-12
  • Online Date:2026-03-18
  • Published:2025-05-20
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  • Received:2024-10-12
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Affiliations
    1.College of Land and Resources, Hebei Agricultural University, Baoding 071001, China
    2.School of Land Science and Technology, China University of Geosciences(Beijing), Beijing 100083, China
    3.Bohai College, Hebei Agricultural University, Huanghua 061100, China
    4.College of Water Resources and Environment, China University of Geosciences(Beijing), Beijing 100083, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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