Spatiotemporal characteristics and influencing factors of net primary production from 2000 to 2021 in China

Yang, Chen; Zhai, Guohui; Fu, Meichen; Sun, Cheng

doi:10.1007/s11356-023-28666-8

Cited by 5 publications

(2 citation statements)

References 36 publications

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“…The results show that the ReliefF algorithm indicates that NPP is related to r ainfall, surface temperature, sunshine,and evaporation, while the RF algorithm indicates t hat NPP is related to temperature, precipitation, and air pressure. It confirms that temper ature and precipitation have the most significant impact on the variation of vegetation net primary productivity.This is consistent with the conclusion of Yang(2023) that NPP has th e most significant influencing factors.…”

Section: The Relationship Between Climate Impact Factors and Changes ...supporting

confidence: 92%

Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses

Li,

Wu,

et al. 2024

Preprint

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In order to determine the evolution characteristics of net primary productivity of vegetation in Nanchang City and the main driving factors influencing its spatiotemporal evolution, based on the ArcGIS and Matlab platforms, ReliefF, Random Forest (RF),BP neural network, GRNN machine learning algorithm and geographic detector were used to quantitatively evaluate the evolution characteristics and spatiotemporal driving factors of Nanchang City from 1998 to 2015.The results show: 1) From a temporal perspective, NPP overall shows a fluctuating upward trend with distinct seasonal variations; spatially, it follows a distribution pattern of higher values in the middle and lower values around the edges; 2) The ReliefF algorithm has the highest fitting accuracy and is more suitable for regression analysis of NPP, with both algorithms indicating that air temperature and precipitation have the most significant impact on NPP evolution; 3) According to the results of the geographic detector, the NPP in Nanchang City is most significantly influenced by precipitation factors spatially, while the temporal dimension is dominated by human factors. In-depth study of the evolution characteristics of NPP can provide a scientific basis for quantifying the health of regional ecosystems and the balance of the ecological environment under the background of climate change.

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Section: The Relationship Between Climate Impact Factors and Changes ...supporting

confidence: 92%

Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses

Li,

Wu,

et al. 2024

Preprint

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“…Urban expansion (Liu et al, 2019), regional development (Xu et al, 2011), and overgrazing (Jiang et al, 2020) are human activities leading to land use change and vegetation loss and degradation (Liu et al, 2015), with disturbing impacts on the NPP (Huang et al, 2016). Some scholars have investigated the impact of driving factors on NPP through residual analysis (Liu et al, 2019), correlation analysis (Ge et al, 2021), and geographically weighted modeling (Yang et al, 2023).…”

mentioning

confidence: 99%

Evaluation of spatiotemporal variation and impact factors for vegetation net primary productivity in a typical open‐pit mining ecosystem in northwestern China

Wang,

Cui,

Yang

et al. 2024

Land Degrad Dev

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The vegetation net primary productivity (NPP) is a key indicator for evaluating vegetation carbon sequestration. Exploring its spatiotemporal changes and impact factors is essential for coal mining and ecological restoration in open‐pit mining areas. This study utilized the Carnegie‐Ames‐Stanford‐Approach (CASA) model to calculate monthly vegetation NPP in the Xiwan mine area, a typical open‐pit mine in northwestern China. The trend, stability, and persistence analysis were conducted, along with the development of a grading method to examine the vegetation NPP spatiotemporal variation across different land cover types. Statistical grading and correlation analysis were used to explore the relationships between the topographical factors, meteorological factors, human activities, and vegetation NPP. The following results were obtained: (1) The vegetation NPP in the study area exhibited a high stability and anti‐persistent decrease in trend. NPP reached a peak of 143.49 g C/(m2 year) in 2017, but declined to a low of 118.38 g C/(m2 year) in 2021. (2) The vegetation NPP decreases with increasing elevation and slope, and a relatively strong correlation with temperature and precipitation was also observed. (3) The impact intensity of human activities on vegetation NPP exhibited a rising and fluctuating volatile trend. In 2021, the inhibition of vegetation NPP by human activities reached its peak at 166.42 g C/(m2 year), with an impact effect share of 36.9%. This research provides a comprehensive framework for vegetation NPP analysis in open‐pit mining, offering valuable insights for ecological conservation in mining ecosystems.

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Spatiotemporal patterns of net regional productivity and its causes throughout Ordos, China

Zheng,

Du,

Sun

et al. 2024

Environ Sci Pollut Res

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Spatiotemporal characteristics and influencing factors of net primary production from 2000 to 2021 in China

Cited by 5 publications

References 36 publications

Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses

Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses

Evaluation of spatiotemporal variation and impact factors for vegetation net primary productivity in a typical open‐pit mining ecosystem in northwestern China

Spatiotemporal patterns of net regional productivity and its causes throughout Ordos, China

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