Improved Modeling of Vegetation Phenology Using Soil Enthalpy DOI Open Access
Xupeng Sun, Ning Lu, Miaogen Shen

et al.

Global Change Biology, Journal Year: 2025, Volume and Issue: 31(3)

Published: March 1, 2025

Many vegetation phenological models predominantly rely on temperature, overlooking the critical roles of water availability and soil characteristics. This limitation significantly impacts accuracy projections, particularly in water-limited ecosystems. We proposed a new approach incorporating enthalpy-a comprehensive metric integrating moisture, texture-to improve modeling. Using an extensive dataset combining FLUXNET observations, solar-induced fluorescence (SIF), meteorological data across Northern Hemisphere (NH), we analyzed relationship between enthalpy phenology from 2001 to 2020. Our analysis revealed significant temporal trends that corresponded with changes leaf onset date (LOD) senescence (LSD). developed validated enthalpy-based model optimized parameters. The showed strong performance autumn phenology, improving LSD simulation by at least 15% all types. For shrub grassland ecosystems, LOD projections improved more than 12% compared temperature-based model. Future scenario using CMIP6 (2020-2054) consistently projects earlier later model, suggesting potential overestimation growing season length previous studies. study establishes as valuable for modeling highlights importance both characteristics accurate predictions under changing climatic conditions.

Language: Английский

Land Surface Phenology Response to Climate in Semi-Arid Desertified Areas of Northern China DOI Creative Commons
Xiang Song, Jie Liao, Shengyin Zhang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 594 - 594

Published: March 12, 2025

In desertified regions, monitoring vegetation phenology and elucidating its relationship with climatic factors are of crucial significance for understanding how desertification responds to climate change. This study aimed extract the spatial-temporal evolution land surface metrics from 2001 2020 using MODIS NDVI products (NASA, Greenbelt, MD, USA) explore potential impacts change on through partial least squares regression analysis. The key results as follows: Firstly, regionally annual mean start growing season (SOS) ranged day year (DOY) 130 170, end (EOS) fell within DOY 270 310, length (LOS) was between 120 180 days. Most areas demonstrated a tendency towards an earlier SOS, delayed EOS, prolonged LOS, although small portion exhibited opposite trends. Secondly, precipitation prior SOS period significantly influenced advancement while during had marked impact EOS delay. Thirdly, high temperatures in both pre-SOS seasons led moisture deficits growth, which unfavorable influence temperature mainly manifested months when occurred, minimum having more prominent effect than average maximum temperatures. Additionally, wind found adversely advancement, potentially due severe erosion spring. findings this reveal that spring phenology, precipitated by occurrence warm dry semi-arid northern China, has heighten risk desertification.

Language: Английский

Citations

0
Response and recovery times of vegetation productivity under drought stress: Dominant factors and relationships DOI
Chengyun Wang, Jie Chen, Sung‐Ching Lee

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: 655, P. 132945 - 132945

Published: Feb. 22, 2025

Language: Английский

Citations

0
Improved Modeling of Vegetation Phenology Using Soil Enthalpy DOI Open Access
Xupeng Sun, Ning Lu, Miaogen Shen

et al.

Global Change Biology, Journal Year: 2025, Volume and Issue: 31(3)

Published: March 1, 2025

Many vegetation phenological models predominantly rely on temperature, overlooking the critical roles of water availability and soil characteristics. This limitation significantly impacts accuracy projections, particularly in water-limited ecosystems. We proposed a new approach incorporating enthalpy-a comprehensive metric integrating moisture, texture-to improve modeling. Using an extensive dataset combining FLUXNET observations, solar-induced fluorescence (SIF), meteorological data across Northern Hemisphere (NH), we analyzed relationship between enthalpy phenology from 2001 to 2020. Our analysis revealed significant temporal trends that corresponded with changes leaf onset date (LOD) senescence (LSD). developed validated enthalpy-based model optimized parameters. The showed strong performance autumn phenology, improving LSD simulation by at least 15% all types. For shrub grassland ecosystems, LOD projections improved more than 12% compared temperature-based model. Future scenario using CMIP6 (2020-2054) consistently projects earlier later model, suggesting potential overestimation growing season length previous studies. study establishes as valuable for modeling highlights importance both characteristics accurate predictions under changing climatic conditions.

Language: Английский

Citations

0