GIScience & Remote Sensing (Dec 2024)

Relationship between ecological spatial network and vegetation carbon use efficiency in the Yellow River Basin, China

  • Chenglong Xu,
  • Xiang Chen,
  • Qiang Yu,
  • Buyanbaatar Avirmed,
  • Jikai Zhao,
  • Wei Liu,
  • Weijie Sun

DOI
https://doi.org/10.1080/15481603.2024.2318070
Journal volume & issue
Vol. 61, no. 1

Abstract

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ABSTRACTVegetation, as a crucial carbon sink, is facing extensive degradation under the mounting pressures of urbanization and excessive resource exploitation, exacerbating the imbalance between carbon sources and sinks. In response, the ecological spatial network has emerged as a comprehensive conservation strategy to establish and maintain connectivity and interactions among diverse ecosystems, ensuring the continuous provision of ecological services and preservation of biodiversity. A pivotal indicator in this context is vegetation carbon use efficiency (CUE), which elucidates the relationship between CO2 assimilation through photosynthesis and biomass growth. In this study, utilizing remote sensing data, the Yellow River Basin (YRB) was selected as a case study to analyze vegetation CUE through the Carnegie Ames Stanford Approach (CASA) and Light Use Efficiency-Normalized Difference Water Index (LUE-NDWI) models. Furthermore, the Morphological Spatial Pattern Analysis (MSPA) method and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were employed to delineate ecological sources for woodlands, shrublands, and grasslands, while the Minimum Cumulative Resistance (MCR) model was used to identify ecological corridors, forming an ecological spatial network within the YRB. Subsequently, the interrelationship between topological metrics and vegetation CUE was analyzed, and optimization strategies were proposed based on the significance of the structure and function. The findings revealed that: (1) Vegetation CUE exhibited a spatially decreasing trend from the western to eastern regions, with spatial patterns correlated with vegetation types, temperature, and precipitation distribution; (2) The ecological spatial network demonstrated a denser configuration in the upper and middle reaches and a sparser and shorter pattern in the lower reaches, with seamless connectivity among all regions; (3) Significant correlations were observed between topological metrics and vegetation CUE, prompting the adoption of ecological construction and protection measures when functional importance is deficient, and enhancing the connectivity of ecological sources through the augmentation of ecological corridors when structural importance is lacking. The implementation of these strategies is expected to bolster the ecological functions of the network, facilitate carbon cycling, and exert a positive and far-reaching impact on the sustainable development of the ecological environment in the YRB.

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