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      Overestimation of the effect of climatic warming on spring phenology due to misrepresentation of chilling

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          Abstract

          Spring warming substantially advances leaf unfolding and flowering time for perennials. Winter warming, however, decreases chilling accumulation (CA), which increases the heat requirement (HR) and acts to delay spring phenology. Whether or not this negative CA-HR relationship is correctly interpreted in ecosystem models remains unknown. Using leaf unfolding and flowering data for 30 perennials in Europe, here we show that more than half (7 of 12) of current chilling models are invalid since they show a positive CA-HR relationship. The possible reason is that they overlook the effect of freezing temperature on dormancy release. Overestimation of the advance in spring phenology by the end of this century by these invalid chilling models could be as large as 7.6 and 20.0 days under RCPs 4.5 and 8.5, respectively. Our results highlight the need for a better representation of chilling for the correct understanding of spring phenological responses to future climate change.

          Abstract

          Climate warming is advancing spring leaf unfolding, but it is also reducing the cold periods that many trees require to break winter dormancy. Here, the authors show that 7 of 12 current chilling models fail to account for the correct relationship between chilling accumulation and heat requirement, leading to substantial overestimates of the advance of spring phenology under climate change.

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          Plant phenology and global climate change: Current progresses and challenges

          Plant phenology, the annually recurring sequence of plant developmental stages, is important for plant functioning and ecosystem services and their biophysical and biogeochemical feedbacks to the climate system. Plant phenology depends on temperature, and the current rapid climate change has revived interest in understanding and modeling the responses of plant phenology to the warming trend and the consequences thereof for ecosystems. Here, we review recent progresses in plant phenology and its interactions with climate change. Focusing on the start (leaf unfolding) and end (leaf coloring) of plant growing seasons, we show that the recent rapid expansion in ground- and remote sensing- based phenology data acquisition has been highly beneficial and has supported major advances in plant phenology research. Studies using multiple data sources and methods generally agree on the trends of advanced leaf unfolding and delayed leaf coloring due to climate change, yet these trends appear to have decelerated or even reversed in recent years. Our understanding of the mechanisms underlying the plant phenology responses to climate warming is still limited. The interactions between multiple drivers complicate the modeling and prediction of plant phenology changes. Furthermore, changes in plant phenology have important implications for ecosystem carbon cycles and ecosystem feedbacks to climate, yet the quantification of such impacts remains challenging. We suggest that future studies should primarily focus on using new observation tools to improve the understanding of tropical plant phenology, on improving process-based phenology modeling, and on the scaling of phenology from species to landscape-level.
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            An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets

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              An Overview of the Global Historical Climatology Network-Daily Database

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                Author and article information

                Contributors
                wanghj@igsnrr.ac.cn
                wucy@igsnrr.ac.cn
                geqs@igsnrr.ac.cn
                Journal
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                2 October 2020
                2 October 2020
                2020
                : 11
                : 4945
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, , Chinese Academy of Sciences, ; Beijing, 100101 China
                [2 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, University of Chinese Academy of Sciences, ; Beijing, 100049 China
                [3 ]GRID grid.457340.1, ISNI 0000 0001 0584 9722, Laboratoire des Sciences du Climat et de l’Environnement, IPSL-LSCE CEA CNRS UVSQ, ; 91191 Gif sur Yvette, France
                [4 ]GRID grid.4711.3, ISNI 0000 0001 2183 4846, CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, ; Barcelona, 08193 Catalonia Spain
                [5 ]GRID grid.452388.0, ISNI 0000 0001 0722 403X, CREAF, Cerdanyola del Valles, ; Barcelona, 08193 Catalonia Spain
                [6 ]GRID grid.20513.35, ISNI 0000 0004 1789 9964, College of Water Sciences, , Beijing Normal University, ; Beijing, 100875 China
                Author information
                http://orcid.org/0000-0002-2325-0120
                http://orcid.org/0000-0001-6163-8209
                http://orcid.org/0000-0001-8560-4943
                http://orcid.org/0000-0002-7215-0150
                http://orcid.org/0000-0001-8712-8565
                Article
                18743
                10.1038/s41467-020-18743-8
                7532433
                33009378
                d21577a9-9a98-44e3-ab47-149e270f7041
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 March 2020
                : 26 August 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 41871032
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                phenology,climate sciences,ecology,environmental sciences
                Uncategorized
                phenology, climate sciences, ecology, environmental sciences

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