Exploring Synergies: Greenhouse Gas Dynamics, Soil Mechanisms, and Forest Ecosystems for Climate Resilience and Sustainable Environmental Stewardship

Abstract

ABSTRACT Rising global temperatures underscore the urgent need to understand the complex interplay between greenhouse gas (GHG) emissions and climate change. This study investigates the relationships between GHG emissions and key environmental factors in China from 1990 to 2019, focusing on the role of forest ecosystems and soil management practices. Utilizing FAOSTAT and World Development Indicators data, we analyze the connections between total GHG emissions and factors such as biomass burning (BM), net stock change (NSC), fertilizer application (FERT), and manure application (MA) in soils. Employing impulse response analysis and Robust Least Squares Estimation with transformed logarithmic independent parameters, we find strong positive correlations between GHG emissions and both BM (coefficient 0.82) and FERT (coefficient 0.95). Robust Least Squares Estimation further confirms the significant influence of BM (coefficient 0.85) and FERT (coefficient 1.01) on GHG emissions. Notably, the interaction between precipitation (PPT) and NSC significantly impacts GHG emissions, with a negative coefficient (−0.58) for “PPT * NSC”. In contrast, the interaction between PPT and FERT significantly impacts GHG emissions, with a positive coefficient (0.29) for “PPT * FERT.” Furthermore, a unidirectional causality is observed from GHGs to BM (coefficient 6.31). These findings highlight the critical roles of BM, fertilizer use, and PPT patterns in driving GHG dynamics and underscore the potential of forest management strategies, particularly those focused on NSC, to mitigate climate change. This research provides valuable insights for promoting a sustainable balance between human activities and the vital role of forests in maintaining a healthy environment.

Keywords

• climate change
• forest ecosystem
• greenhouse gas emission
• manure
• net stock change
• precipitation