[Quantitative Analysis of the Spatial and Temporal Distribution Pattern of Net Primary Productivity of Vegetation in Hubei Province and Its Multiple Driving Forces].

The health and stability of vegetation ecosystems in Hubei Province are important to the ecological security of the entire Yangtze River Basin. The spatio-temporal succession pattern of vegetation net primary productivity (NPP) in Hubei Province was analyzed by using the Sen trend+MK test, based on the Google earth engine (GEE) platform to obtain the MOD17A3HGF.061 vegetation NPP dataset from 2002 to 2020. The coefficient of variation and the Hurst index were then employed to elucidate the multiple driving mechanisms of NPP spatio-temporal differentiation. This was achieved through the use of optimal parameters-based geographical detectors (OPGD), which were employed to clarify the multiple driving mechanisms of spatial and temporal variability of NPP. The results showed that: ① Between 2002 and 2020, vegetation NPP in Hubei Province showed an increasing trend with a rate of 2.423 8 g·m<sup>-2</sup>·a<sup>-1</sup>, spatially higher in the west and lower in the east; vegetation NPP was dominated by low volatility (about 79% of the total), the trend of change was dominated by increase (about 89% of the total), and future change was dominated by weak inverse persistence (about 62% of the total). ② The main factors affecting the change in vegetation NPP in Hubei Province were secondary GDP, tertiary GDP, the number of high-tech enterprises, and elevation (all <i>q</i>-values were greater than 0.5); the two-factor interactions all showed either a two-factor enhancement or a nonlinear enhancement, whereas evapotranspiration ∩ secondary GDP had the highest explanatory power of 0.74. ③ Except for the indicators of type variables, such as slope direction, vegetation type, rock type, soil type, and land use type, most of the other factors showed significant differences in their effects on vegetation NPP in Hubei Province. Economic factors, such as first production GDP in the interval of (1.03 million yuan, 1.16 million yuan), the mean value of NPP in Hubei Province was the largest at 733.886 7 g·m<sup>-2</sup>·a<sup>-1</sup>, and the NPP showed a decreasing trend with the increase in these factors. For natural factors, such as elevation in the largest interval measured, in the interval of (1.16e+03 m, 2.71e+03 m), the mean value of NPP in Hubei Province was the largest at 686.4599 g·m<sup>-2</sup>·a<sup>-1</sup>, and then the opposite trend was observed. ④ Most of the influencing factors were significantly different from each other on the NPP of vegetation in Hubei Province, indicating that these factors had different mechanisms of action in influencing the NPP of vegetation. The results of the study can provide a data basis for the formulation of policies on ecological protection and restoration of vegetation in Hubei Province and the Yangtze River Basin.

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Journal
PubMed
Published
2025-05-08
DOI
https://doi.org/10.13227/j.hjkx.202405158
Citations
1
Primary Topic
Remote Sensing and Land Use
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article
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article

[Quantitative Analysis of the Spatial and Temporal Distribution Pattern of Net Primary Productivity of Vegetation in Hubei Province and Its Multiple Driving Forces].

S. M. Tian, Min-Li Wang, Fan Huang, H. J. Zhang et al.
1 citations
PubMed
Remote Sensing and Land Use
article

[Quantitative Analysis of the Spatial and Temporal Distribution Pattern of Net Primary Productivity of Vegetation in Hubei Province and Its Multiple Driving Forces].

S. M. Tian, Min-Li Wang, Fan Huang, H. J. Zhang, Ye Ding, Feng Yan, Zhigang Zhou
article en
1 citations

Abstract

The health and stability of vegetation ecosystems in Hubei Province are important to the ecological security of the entire Yangtze River Basin. The spatio-temporal succession pattern of vegetation net primary productivity (NPP) in Hubei Province was analyzed by using the Sen trend+MK test, based on the Google earth engine (GEE) platform to obtain the MOD17A3HGF.061 vegetation NPP dataset from 2002 to 2020. The coefficient of variation and the Hurst index were then employed to elucidate the multiple driving mechanisms of NPP spatio-temporal differentiation. This was achieved through the use of optimal parameters-based geographical detectors (OPGD), which were employed to clarify the multiple driving mechanisms of spatial and temporal variability of NPP. The results showed that: ① Between 2002 and 2020, vegetation NPP in Hubei Province showed an increasing trend with a rate of 2.423 8 g·m<sup>-2</sup>·a<sup>-1</sup>, spatially higher in the west and lower in the east; vegetation NPP was dominated by low volatility (about 79% of the total), the trend of change was dominated by increase (about 89% of the total), and future change was dominated by weak inverse persistence (about 62% of the total). ② The main factors affecting the change in vegetation NPP in Hubei Province were secondary GDP, tertiary GDP, the number of high-tech enterprises, and elevation (all <i>q</i>-values were greater than 0.5); the two-factor interactions all showed either a two-factor enhancement or a nonlinear enhancement, whereas evapotranspiration ∩ secondary GDP had the highest explanatory power of 0.74. ③ Except for the indicators of type variables, such as slope direction, vegetation type, rock type, soil type, and land use type, most of the other factors showed significant differences in their effects on vegetation NPP in Hubei Province. Economic factors, such as first production GDP in the interval of (1.03 million yuan, 1.16 million yuan), the mean value of NPP in Hubei Province was the largest at 733.886 7 g·m<sup>-2</sup>·a<sup>-1</sup>, and the NPP showed a decreasing trend with the increase in these factors. For natural factors, such as elevation in the largest interval measured, in the interval of (1.16e+03 m, 2.71e+03 m), the mean value of NPP in Hubei Province was the largest at 686.4599 g·m<sup>-2</sup>·a<sup>-1</sup>, and then the opposite trend was observed. ④ Most of the influencing factors were significantly different from each other on the NPP of vegetation in Hubei Province, indicating that these factors had different mechanisms of action in influencing the NPP of vegetation. The results of the study can provide a data basis for the formulation of policies on ecological protection and restoration of vegetation in Hubei Province and the Yangtze River Basin.

PubMedVol. 46(5)
Hebei Agricultural University (CN), Hubei Water Resources Research Institute (CN)
Remote Sensing and Land Use
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