Return
Dynamic Interactions Among Climate, Land, Energy, and Water Systems: Insights From a Panel Vector Autoregression Approach
DOI:10.1002/sd.71449.png)
Abstract
En 中文
This study examines the dynamic interactions among climate conditions, land use, energy consumption, water resources, population dynamics, and economic growth within the Climate–Land–Energy–Water (CLEW) nexus across 137 countries from 2000 to 2023. Recognising that food system stability emerges from complex interdependencies among environmental and economic systems, the study employs a panel vector autoregression framework to capture feedback mechanisms and causal relationships among the key nexus components. The empirical results reveal that food system outcomes are strongly influenced by climate variability, population growth, land dynamics, and water availability, indicating that ecological constraints and demographic pressures constitute the primary drivers of food supply variability. In contrast, economic growth and energy consumption do not exert direct short-run effects on food outcomes but operate indirectly through their interactions with land and water systems. Variance decomposition results identify land as the dominant transmission channel within the nexus, accounting for the largest share of fluctuations in food, water, energy, and economic growth over time. The findings further indicate that water availability plays a critical role in stabilising agricultural systems, although rising demographic pressures and land expansion increase demand for water resources. The study contributes to the growing nexus literature by providing global empirical evidence on the interconnected nature of resource systems and by highlighting the need for coordinated policy approaches that integrate land governance, water management, energy transitions, and climate adaptation strategies to achieve sustainable development.
Keywords:
climate variability
climate–land–energy–water nexus
food system stability
global panel analysis
resource interdependence
sustainable development
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.2
Papers:
3.9K
Citations:
1.2W

