AI Article Synopsis

  • A study was conducted in northwestern Liaoning Province to identify factors affecting vegetation productivity in sandy lands, analyzing data at regional, pixel, and plot scales.
  • A random forest model was used to assess the impact of soil properties, topography, climate, and vegetation characteristics on productivity.
  • The results indicated that the most significant influences on vegetation productivity were fractional vegetation coverage and leaf area index, with topographical factors being second and climate factors having a minor role.

Article Abstract

To reveal the key factors influencing vegetation productivity in sandy lands, we conducted a comprehensive analysis of vegetation productivity on regional scale, pixel scale, and plot scale of the sandy lands in northwes-tern Liaoning Province, based on soil physicochemical data, topographical data, climate data, and the intrinsic characteristics of vegetation. On the regional scale, we established a random forest model to explore the impact of topographical factors, climate factors, and vegetation characteristics on vegetation productivity. On the pixel scale, we performed a correlation analysis between vegetation cover and climate factors. On the plot scale, we combined the physicochemical properties of 234 soil samples with topographical factors and vegetation characteristics, and utilized the random forest model to calculate the importance values of each factor. The results showed that soil nutrients could explain 24.8% of the spatial variation in net primary productivity when other factors were excluded. When introducing topographical factors into the model, the model could explain 40% variation of net primary productivity. When further incorporating fractional vegetation coverage and leaf area index into the model, the model could explain 72.8% variation of net primary productivity. Our findings suggested that fractional vegetation coverage and leaf area index were the most influential factors affecting vegetation productivity in this area. Topographical factors ranked second, followed by climate factors, which had a relatively small impact.

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Source
http://dx.doi.org/10.13287/j.1001-9332.202401.009DOI Listing

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