{"title":"“净生态系统碳交换模型的变异性和不确定性:通过集成机器学习在全球通量站点的系统估计”[农林气象,374(2025),110784]的更正。","authors":"Nannan Wang, Zijian Yue, Yaolin Liu, Zhaomin Tong, Yanfang Liu, Yanchi Lu, Yongge Shi","doi":"10.1016/j.agrformet.2025.110879","DOIUrl":null,"url":null,"abstract":"The authors regret that the article was published with incorrect citation information in Section 2.1.1. The revised citation information is as follows:","PeriodicalId":50839,"journal":{"name":"Agricultural and Forest Meteorology","volume":"73 1","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Corrigendum to “Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning” [Agricultural and Forest Meteorology, 374 (2025), 110784]\",\"authors\":\"Nannan Wang, Zijian Yue, Yaolin Liu, Zhaomin Tong, Yanfang Liu, Yanchi Lu, Yongge Shi\",\"doi\":\"10.1016/j.agrformet.2025.110879\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors regret that the article was published with incorrect citation information in Section 2.1.1. The revised citation information is as follows:\",\"PeriodicalId\":50839,\"journal\":{\"name\":\"Agricultural and Forest Meteorology\",\"volume\":\"73 1\",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Agricultural and Forest Meteorology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1016/j.agrformet.2025.110879\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural and Forest Meteorology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1016/j.agrformet.2025.110879","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
Corrigendum to “Variability and uncertainty in net ecosystem carbon exchange modeling: Systematic estimates at global flux sites via ensemble machine learning” [Agricultural and Forest Meteorology, 374 (2025), 110784]
The authors regret that the article was published with incorrect citation information in Section 2.1.1. The revised citation information is as follows:
期刊介绍:
Agricultural and Forest Meteorology is an international journal for the publication of original articles and reviews on the inter-relationship between meteorology, agriculture, forestry, and natural ecosystems. Emphasis is on basic and applied scientific research relevant to practical problems in the field of plant and soil sciences, ecology and biogeochemistry as affected by weather as well as climate variability and change. Theoretical models should be tested against experimental data. Articles must appeal to an international audience. Special issues devoted to single topics are also published.
Typical topics include canopy micrometeorology (e.g. canopy radiation transfer, turbulence near the ground, evapotranspiration, energy balance, fluxes of trace gases), micrometeorological instrumentation (e.g., sensors for trace gases, flux measurement instruments, radiation measurement techniques), aerobiology (e.g. the dispersion of pollen, spores, insects and pesticides), biometeorology (e.g. the effect of weather and climate on plant distribution, crop yield, water-use efficiency, and plant phenology), forest-fire/weather interactions, and feedbacks from vegetation to weather and the climate system.