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

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. As a result, 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:
 [1];  [2];  [3];  [4];  [5];  [3]; ORCiD logo [3];  [6]; ORCiD logo [7]; ORCiD logo [8]; ORCiD logo [9];  [10]; ORCiD logo [8]; ORCiD logo [8];  [11];  [12];  [3]
  1. Univ. of Arizona, Tucson, AZ (United States); Brown Univ., Providence, RI (United States)
  2. Univ. of Arizona, Tucson, AZ (United States); Univ. of Technology Sydney Ultimo, NSW (Australia)
  3. Univ. of Arizona, Tucson, AZ (United States)
  4. Brookhaven National Lab. (BNL), Upton, NY (United States); The Univ. of Hong Kong, Pokfulam (Hong Kong)
  5. Univ. of Oxford, Oxford (United Kingdom); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  6. Instituto Nacional de Pesquisas da Amazônia (INPA), Manaus, AM (Brazil)
  7. Lab des Sciences du Climat et de l'Environnement, Gif sur Yvette (France)
  8. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  9. McMaster Univ., Hamilton, ON (Canada)
  10. Lab des Sciences du Climat et de l'Environnement, Gif sur Yvette (France); Tsinghua Univ., Beijing (China)
  11. Univ. of California, Irvine, CA (United States)
  12. Smithsonian Institution's Forest Global Earth Observatory & Smithsonian Environmental Research Center, Edgewater, MD (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1545235
Alternate Identifier(s):
OSTI ID: 1565989
Grant/Contract Number:  
[AC05-00OR22725; SC0008383; SC0012704]
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. 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., and Saleska, Scott R. Thu . "Cryptic phenology in plants: case studies, implications and recommendations". United States. doi:10.1111/gcb.14759.
@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 = {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. As a result, 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 = {2019},
month = {7}
}

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Phenological variation of leaf functional traits within species
journal, January 2016


Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
journal, January 2017


Non-structural carbohydrate pools in a tropical forest
journal, December 2004

  • Würth, Mirjam K. R.; Peláez-Riedl, Susanna; Wright, S. Joseph.
  • Oecologia, Vol. 143, Issue 1
  • DOI: 10.1007/s00442-004-1773-2

Leaf flush drives dry season green-up of the Central Amazon
journal, September 2016


The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models
journal, April 2015

  • Keenan, Trevor F.; Richardson, Andrew D.
  • Global Change Biology, Vol. 21, Issue 7
  • DOI: 10.1111/gcb.12890

Evidence for a recent increase in forest growth
journal, February 2010

  • McMahon, Sean M.; Parker, Geoffrey G.; Miller, Dawn R.
  • Proceedings of the National Academy of Sciences, Vol. 107, Issue 8
  • DOI: 10.1073/pnas.0912376107

Responses of spring phenology to climate change
journal, May 2004


Onset of spring starting earlier across the Northern Hemisphere
journal, February 2006


Seasonal patterns of carbohydrate storage in four tropical tree species
journal, May 2002


Leaf flushing phenology and herbivory in a tropical dry deciduous forest, southern India
journal, January 1993


Fourier analysis to detect phenological cycles using long-term tropical field data and simulations
journal, December 2016

  • Bush, Emma R.; Abernethy, Katharine A.; Jeffery, Kathryn
  • Methods in Ecology and Evolution, Vol. 8, Issue 5
  • DOI: 10.1111/2041-210X.12704

Factors controlling CO 2 exchange on timescales from hourly to decadal at Harvard Forest
journal, January 2007

  • Urbanski, S.; Barford, C.; Wofsy, S.
  • Journal of Geophysical Research, Vol. 112, Issue G2
  • DOI: 10.1029/2006JG000293

Attribution of extreme weather and climate events overestimated by unreliable climate simulations: RELIABILITY AND EVENT ATTRIBUTION
journal, March 2016

  • Bellprat, Omar; Doblas-Reyes, Francisco
  • Geophysical Research Letters, Vol. 43, Issue 5
  • DOI: 10.1002/2015GL067189

Root phenology in a changing climate
journal, February 2016

  • Radville, Laura; McCormack, M. Luke; Post, Eric
  • Journal of Experimental Botany, Vol. 67, Issue 12
  • DOI: 10.1093/jxb/erw062

Towards a worldwide wood economics spectrum
journal, April 2009


Dry-Season Greening and Water Stress in Amazonia: The Role of Modeling Leaf Phenology
journal, June 2018

  • Manoli, Gabriele; Ivanov, Valeriy Y.; Fatichi, Simone
  • Journal of Geophysical Research: Biogeosciences, Vol. 123, Issue 6
  • DOI: 10.1029/2017JG004282

Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest
journal, November 2015

  • Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena
  • New Phytologist, Vol. 210, Issue 2
  • DOI: 10.1111/nph.13771

Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2
journal, January 2009

  • Medvigy, D.; Wofsy, S. C.; Munger, J. W.
  • Journal of Geophysical Research, Vol. 114, Issue G1
  • DOI: 10.1029/2008JG000812

Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees
journal, November 2012

  • Richardson, Andrew D.; Carbone, Mariah S.; Keenan, Trevor F.
  • New Phytologist, Vol. 197, Issue 3
  • DOI: 10.1111/nph.12042

Climate change, phenology, and phenological control of vegetation feedbacks to the climate system
journal, February 2013


Validating Herbarium-Based Phenology Models Using Citizen-Science Data
journal, October 2016


Quantifying ecological memory in plant and ecosystem processes
journal, December 2014

  • Ogle, Kiona; Barber, Jarrett J.; Barron-Gafford, Greg A.
  • Ecology Letters, Vol. 18, Issue 3
  • DOI: 10.1111/ele.12399

Heat freezes niche evolution
journal, July 2013

  • Araújo, Miguel B.; Ferri-Yáñez, Francisco; Bozinovic, Francisco
  • Ecology Letters, Vol. 16, Issue 9
  • DOI: 10.1111/ele.12155

Tropical forest biomass estimation and the fallacy of misplaced concreteness
journal, August 2012


Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery
journal, January 2014