Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts DOI Creative Commons
Ziyu Wang, Weiqing Zhao, Sen Cao

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(5)

Published: March 4, 2025

Abstract China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation and model‐based simulations. This fundamental mismatch remains largely unexplored. Here, we conducted comprehensive analysis using diverse observation data to identify determinant within Dynamic Global Vegetation Models (DGVMs) that underestimates growth in China. By developing high‐resolution forest cover change set, found LUH2‐GCB, common land use input for DGVMs, causes underestimate afforestation. With neighborhood comparison analysis, quantitively demonstrated predominant role of underestimated lowering leaf area index (LAI) trends. Overall, DGVMs China's by an average 26.88%, leading 29.46% underestimation LAI increase. Our findings confirm greening trend highlight need improved representation DGVMs.

Language: Английский

Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts DOI Creative Commons
Ziyu Wang, Weiqing Zhao, Sen Cao

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(5)

Published: March 4, 2025

Abstract China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation and model‐based simulations. This fundamental mismatch remains largely unexplored. Here, we conducted comprehensive analysis using diverse observation data to identify determinant within Dynamic Global Vegetation Models (DGVMs) that underestimates growth in China. By developing high‐resolution forest cover change set, found LUH2‐GCB, common land use input for DGVMs, causes underestimate afforestation. With neighborhood comparison analysis, quantitively demonstrated predominant role of underestimated lowering leaf area index (LAI) trends. Overall, DGVMs China's by an average 26.88%, leading 29.46% underestimation LAI increase. Our findings confirm greening trend highlight need improved representation DGVMs.

Language: Английский

Citations

0