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云师大地理学部秦军教授课题组op期刊《Science of The Total Environment》发表研究成果

已有 409 次阅读 2024-8-14 13:14 |个人分类:云师大研究|系统分类:论文交流

   2024年8月5日,Elsevier 旗下top期刊《Science of The Total Environment在线发表了云南师范大学地理学部秦军教授最新研究成果Enhanced autumn phenology model incorporating agricultural drought》。第一作者单位为中国科学院地理科学与资源研究所,通讯作者为中国科学院地理科学与资源研究所、云南师范大学地理学部秦军教授。

1-s2.0-S0048969724053312-ga1_lrg.jpgAbstract

The impacts of various drought types on autumn phenology have yet to be extensively explored. We address the influence of pre-season agricultural and meteorological droughts on autumn phenology in the Northern Hemisphere. To this end, enhanced autumn phenology models incorporating drought factors was developed, contributing to a deeper understanding of these complex interactions. The study reveals that there was no significant trend of advancement or delay in the End of Season (EOS) across the Northern Hemisphere based on SIF estimates from 2001 to 2020. The cumulative and delayed impacts of pre-season agricultural drought on EOS were found to be more pronounced than those associated with meteorological drought. The analysis of various evaluation indexes shows that the performance of the Cooling Degree Days (CDD) model incorporating the Standardized Soil Moisture Drought Index (CDDSSMI) in simulating EOS in the Northern Hemisphere is >14 % higher than that of the standard CDD model. Additionally, the performance of the CDD model with the Standardized Precipitation Index (CDDSPI) in simulating EOS in the Northern Hemisphere is improved by >5.6 % compared to the standard CDD model. A comparison of future EOS projections across various models reveals that the CDD model significantly overestimates EOS in different scenarios (SSP245 and SSP585). The CDDSSMI model projects EOS approximately 7 days earlier than the CDD model, and the CDDSPI model projects EOS approximately 5 days earlier than the CDD model. This study highlights the diverse impacts of drought types on plant autumn phenology and underscores the significance of parameterizing drought impacts in autumn phenology models.

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