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Article: Cryptic phenology in plants: case studies, implications, and recommendations

TitleCryptic phenology in plants: case studies, implications, and recommendations
Authors
Keywordsclimate change
dynamic global vegetation models
plant ecology
plant physiology
seasonality
Issue Date2019
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291365-2486
Citation
Global Change Biology, 2019, v. 25 n. 11, p. 3591-3608 How to Cite?
AbstractPlant phenology – the timing of cyclic or recurrent biological events in plants – offers insight into the ecology, evolution, and seasonality of plant‐mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season‐initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are “cryptic” – that is, hidden from view (e.g root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models.
Persistent Identifierhttp://hdl.handle.net/10722/274278
ISSN
2023 Impact Factor: 10.8
2023 SCImago Journal Rankings: 4.285
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorAlbert, LP-
dc.contributor.authorRestrepo-Coupe, N-
dc.contributor.authorSmith, MN-
dc.contributor.authorWu, J-
dc.contributor.authorChavana-Bryant, C-
dc.contributor.authorProhaska, N-
dc.contributor.authorTaylor, TC-
dc.contributor.authorMartins, GA-
dc.contributor.authorCiais, P-
dc.contributor.authorMao, J-
dc.contributor.authorArain, MA-
dc.contributor.authorLi, W-
dc.contributor.authorShi, X-
dc.contributor.authorRicciuto, DM-
dc.contributor.authorHuxman, TE-
dc.contributor.authorMcMahon, SM-
dc.contributor.authorSaleska, SR-
dc.date.accessioned2019-08-18T14:58:36Z-
dc.date.available2019-08-18T14:58:36Z-
dc.date.issued2019-
dc.identifier.citationGlobal Change Biology, 2019, v. 25 n. 11, p. 3591-3608-
dc.identifier.issn1354-1013-
dc.identifier.urihttp://hdl.handle.net/10722/274278-
dc.description.abstractPlant phenology – the timing of cyclic or recurrent biological events in plants – offers insight into the ecology, evolution, and seasonality of plant‐mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season‐initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are “cryptic” – that is, hidden from view (e.g root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291365-2486-
dc.relation.ispartofGlobal Change Biology-
dc.rightsThis is the peer reviewed version of the following article: Global Change Biology, 2019, v. 25 n. 11, p. 3591-3608, which has been published in final form at https://doi.org/10.1111/gcb.14759. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectclimate change-
dc.subjectdynamic global vegetation models-
dc.subjectplant ecology-
dc.subjectplant physiology-
dc.subjectseasonality-
dc.titleCryptic phenology in plants: case studies, implications, and recommendations-
dc.typeArticle-
dc.identifier.emailWu, J: jinwu@hku.hk-
dc.identifier.authorityWu, J=rp02509-
dc.description.naturepostprint-
dc.identifier.doi10.1111/gcb.14759-
dc.identifier.pmid31343099-
dc.identifier.scopuseid_2-s2.0-85071040663-
dc.identifier.hkuros301159-
dc.identifier.volume25-
dc.identifier.issue11-
dc.identifier.spage3591-
dc.identifier.epage3608-
dc.identifier.isiWOS:000482780400001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1354-1013-

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