Quantifying the importance of day length in process-based models for the prediction of temperate spring flowering phenology-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Quantifying the importance of day length in process-based models for the prediction of temperate spring flowering phenology

Published:2022-10 Issue: Volume:843 Page:156780
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Kim Sukyung,Kim Tae Kyung,Yoon Sukhee,Jang Keunchang,Chun Jung-Hwa,Won Myoungsoo,Lim Jong-Hwan,Kim Hyun Seok

Funder

Korea Forest Service

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference80 articles.

1. Earlier plant flowering in spring as response to global warming in the Washington, DC, area;Abu-Asab;Biodivers. Conserv.,2001

2. Phenological models to predict the main flowering phases of olive (Olea europaea L.) along a latitudinal and longitudinal gradient across the Mediterranean region;Aguilera;Int. J. Biometeorol.,2015

3. Maximum likelihood identification of gaussian autoregressive moving average models;Akaike;Biometrika,1973

4. Understanding dormancy release in apricot flower buds (Prunus armeniaca L.) using several process-based phenological models;Andreini;Agric. For. Meteorol.,2014

5. Evaluating phenological models for the prediction of leaf-out dates in six temperate tree species across Central Europe;Basler;Agric. For. Meteorol.,2016

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Variable warming effects on flowering phenology of cherry trees across a latitudinal gradient in Japan;Agricultural and Forest Meteorology;2023-08

2. The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States;Remote Sensing of Environment;2023-08

3. Prediction of apple first flowering date using daily land surface temperature spatio-temporal reconstruction and machine learning;Computers and Electronics in Agriculture;2022-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3