Spatial Pattern and Influence Mechanisms of Forest Land Quality under the Background of Carbon Peaking and Carbon Neutrality: A Case Study in Kaizhou District, Chongqing, China

Shasha Lu, Pan Zhang (), Jiayi Zhang, Rongfang Wang, Suxin Hu and Changjiang Ma
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Shasha Lu: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Pan Zhang: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Jiayi Zhang: School of Public Management, Tianjin University of Commerce, Tianjin 300134, China
Rongfang Wang: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Suxin Hu: School of Economics and Management, Beijing Forestry University, Beijing 100083, China
Changjiang Ma: School of Economics and Management, Beijing Forestry University, Beijing 100083, China

Land, 2024, vol. 13, issue 10, 1-25

Abstract: Since the goals of carbon peaking and carbon neutrality have been established, forest carbon sinks have garnered significant attention. As a fundamental component of forest carbon sinks, the quality of forest land significantly influences the carbon sink capacity of forests. This study utilized Kaizhou District, Chongqing City, a typical forest area as a case study, and used the correction method, factor method, CASA model, landscape ecology indexes, and canonical correlation analysis to evaluate the level of forest land quality and reveal the spatial distribution pattern and influencing mechanisms of forest land quality. The results showed that: (i) The quality index of public welfare forest land was distributed in [37.89, 148.15], and each quality level was diversified in space. The quality index of commodity forest land was distributed in [40.00, 92.67], and some high-quality forest land appeared in the transition zone of each region; (ii) The forest land quality index and the amount of net primary productivity passed the correlation test. Primary net productivity was higher on forest land with a high-quality index and lower on forest area with a low-quality index; (iii) public welfare forest land was mainly positively affected by community structure, average annual precipitation, average annual temperature, and soil moisture. Commodity forest land was mainly positively affected by average annual temperature, soil moisture, and slope aspect. However, landform had a significant negative impact on the two types of forest land. Given these findings, we also proposed a series of measures aimed at promoting the sustainable development of research on regional forest land.

Keywords: forest land quality; spatial pattern; influence mechanisms; canonical correlation analysis; Kaizhou District (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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