Cryptic phenology in plants: case studies, implications and recommendations
Abstract
Abstract Plant 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.
- Authors:
-
[3];
[7];
[8];
[9];
[8];
[8];
- Univ. of Arizona, Tucson, AZ (United States); Brown Univ., Providence, RI (United States)
- Univ. of Arizona, Tucson, AZ (United States); Univ. of Technology Sydney Ultimo, NSW (Australia)
- Univ. of Arizona, Tucson, AZ (United States)
- Brookhaven National Lab. (BNL), Upton, NY (United States); The Univ. of Hong Kong, Pokfulam (Hong Kong)
- Univ. of Oxford, Oxford (United Kingdom); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
- Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, AM (Brazil)
- Lab des Sciences du Climat et de l'Environnement, Gif sur Yvette (France)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- McMaster Univ., Hamilton, ON (Canada)
- Lab des Sciences du Climat et de l'Environnement, Gif sur Yvette (France); Tsinghua Univ., Beijing (China)
- Univ. of California, Irvine, CA (United States)
- Smithsonian Institution's Forest Global Earth Observatory & Smithsonian Environmental Research Center, Edgewater, MD (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1545235
- Alternate Identifier(s):
- OSTI ID: 1565989
- Grant/Contract Number:
- AC05-00OR22725; SC0008383
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Global Change Biology
- Additional Journal Information:
- Journal Volume: 25; Journal Issue: 11; Journal ID: ISSN 1354-1013
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; climate change; plant ecology; plant physiology; seasonality; terrestrial biosphere models; dynamic global vegetation models; whole plant biology
Citation Formats
Albert, Loren P., Restrepo‐Coupe, Natalia, Smith, Marielle N., Wu, Jin, Chavana‐Bryant, Cecilia, Prohaska, Neill, Taylor, Tyeen C., Martins, Giordane A., Ciais, Philippe, Mao, Jiafu, Arain, M. Altaf, Li, Wei, Shi, Xiaoying, Ricciuto, Daniel M., Huxman, Travis E., McMahon, Sean M., and Saleska, Scott R. Cryptic phenology in plants: case studies, implications and recommendations. United States: N. p., 2019.
Web. doi:10.1111/gcb.14759.
Albert, Loren P., Restrepo‐Coupe, Natalia, Smith, Marielle N., Wu, Jin, Chavana‐Bryant, Cecilia, Prohaska, Neill, Taylor, Tyeen C., Martins, Giordane A., Ciais, Philippe, Mao, Jiafu, Arain, M. Altaf, Li, Wei, Shi, Xiaoying, Ricciuto, Daniel M., Huxman, Travis E., McMahon, Sean M., & Saleska, Scott R. Cryptic phenology in plants: case studies, implications and recommendations. United States. https://doi.org/10.1111/gcb.14759
Albert, Loren P., Restrepo‐Coupe, Natalia, Smith, Marielle N., Wu, Jin, Chavana‐Bryant, Cecilia, Prohaska, Neill, Taylor, Tyeen C., Martins, Giordane A., Ciais, Philippe, Mao, Jiafu, Arain, M. Altaf, Li, Wei, Shi, Xiaoying, Ricciuto, Daniel M., Huxman, Travis E., McMahon, Sean M., and Saleska, Scott R. Thu .
"Cryptic phenology in plants: case studies, implications and recommendations". United States. https://doi.org/10.1111/gcb.14759. https://www.osti.gov/servlets/purl/1545235.
@article{osti_1545235,
title = {Cryptic phenology in plants: case studies, implications and recommendations},
author = {Albert, Loren P. and Restrepo‐Coupe, Natalia and Smith, Marielle N. and Wu, Jin and Chavana‐Bryant, Cecilia and Prohaska, Neill and Taylor, Tyeen C. and Martins, Giordane A. and Ciais, Philippe and Mao, Jiafu and Arain, M. Altaf and Li, Wei and Shi, Xiaoying and Ricciuto, Daniel M. and Huxman, Travis E. and McMahon, Sean M. and Saleska, Scott R.},
abstractNote = {Abstract Plant 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.},
doi = {10.1111/gcb.14759},
journal = {Global Change Biology},
number = 11,
volume = 25,
place = {United States},
year = {Thu Jul 25 00:00:00 EDT 2019},
month = {Thu Jul 25 00:00:00 EDT 2019}
}
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Figures / Tables:
Table 1: Categorization of plant phenologies based on our current capacity for successful measurement, observation, and/or interpretation.
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Works referencing / citing this record:
Monitoring Mega-Crown Leaf Turnover from Space
journal, January 2020
- Bush, Emma R.; Mitchard, Edward T. A.; Silva, Thiago S. F.
- Remote Sensing, Vol. 12, Issue 3
Figures / Tables found in this record:
Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.