Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

Meng, Lin; Mao, Jiafu; Ricciuto, Daniel M.; Shi, Xiaoying; Richardson, Andrew D.; Hanson, Paul J.; Warren, Jeffrey M.; Zhou, Yuyu; Li, Xuecao; Zhang, Li; Schädel, Christina

doi:10.1016/j.agrformet.2021.108556

Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

Journal Article · Tue Aug 03 00:00:00 EDT 2021 · Agricultural and Forest Meteorology

DOI:https://doi.org/10.1016/j.agrformet.2021.108556· OSTI ID:1817548

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Iowa State Univ., Ames, IA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Northern Arizona Univ., Flagstaff, AZ (United States)
China Agricultural Univ., Beijing (China)
Chinese Academy of Sciences (CAS), Beijing (China)

Phenological transitions determine the timing of changes in land surface properties and the seasonality of exchanges of biosphere-atmosphere energy, water, and carbon. Accurate mechanistic modeling of phenological processes is therefore critical to understand and correctly predict terrestrial ecosystem feedbacks with changing atmospheric and climate conditions. However, the phenological components in the land model of the US Department of Energy's (DOE) Energy Exascale Earth System Model (ELM of E3SM) were previously unable to accurately capture the observed phenological responses to environmental conditions in a well-studied boreal peatland forest. In this research, we introduced new seasonal-deciduous phenology schemes into version 1.0 of ELM and evaluated their performance against the PhenoCam observations at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in northern Minnesota from 2015 to 2018. We found that phenology simulated by the revised ELM (i.e., earlier spring onsets and stronger warming responses of spring onsets and autumn senescence) was closer to observations than simulations from the original algorithms for both the deciduous conifer (Larix laricina) and mixed shrub layers. Moreover, the revised ELM generally produced higher carbon and water fluxes (e.g., photosynthesis and evapotranspiration) during the growing season and stronger flux responses to warming than the default ELM. A parameter sensitivity analysis further indicated the significant contribution of phenology parameters to uncertainty in key carbon and water cycle variables, underscoring the importance of precise phenology parameterization. Furthermore, this phenological modeling effort demonstrates the potential to enhance the E3SM representation of land-climate interactions at broader spatiotemporal scales, especially under anticipated elevated CO₂ and warming conditions.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: U.S. Department of Energy; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1817548

Alternate ID(s):: OSTI ID: 1811732

Journal Information:: Agricultural and Forest Meteorology, Journal Name: Agricultural and Forest Meteorology Journal Issue: 1 Vol. 308-309; ISSN 0168-1923

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (65)

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2017 Richardson, Andrew; Hufkens, Koen; Milliman, Thomas SPRUCE (Spruce and Peatland Responses Under Changing Environments) https://doi.org/10.3334/cdiac/spruce.045	dataset	January 2018
The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 2 https://doi.org/10.1002/2017MS000962	journal	February 2018
Use of digital webcam images to track spring green-up in a deciduous broadleaf forest Richardson, Andrew D.; Jenkins, Julian P.; Braswell, Bobby H. Oecologia, Vol. 152, Issue 2 https://doi.org/10.1007/s00442-006-0657-z	journal	March 2007
European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling? Migliavacca, M.; Cremonese, E.; Colombo, R. International Journal of Biometeorology, Vol. 52, Issue 7 https://doi.org/10.1007/s00484-008-0152-9	journal	April 2008
Bringing Color into the Picture: Using Digital Repeat Photography to Investigate Phenology Controls of the Carbon Dioxide Exchange in a Boreal Mire Peichl, Matthias; Sonnentag, Oliver; Nilsson, Mats B. Ecosystems, Vol. 18, Issue 1 https://doi.org/10.1007/s10021-014-9815-z	journal	November 2014
Evapotranspiration dynamics over a temperate meadow ecosystem in eastern Inner Mongolia, China Li, Huidong; Wang, Anzhi; Yuan, Fenghui Environmental Earth Sciences, Vol. 75, Issue 11 https://doi.org/10.1007/s12665-016-5786-z	journal	June 2016
A model comparison for daylength as a function of latitude and day of year Forsythe, William C.; Rykiel, Edward J.; Stahl, Randal S. Ecological Modelling, Vol. 80, Issue 1 https://doi.org/10.1016/0304-3800(94)00034-F	journal	June 1995
Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests Thornton, P. E.; Law, B. E.; Gholz, Henry L. Agricultural and Forest Meteorology, Vol. 113, Issue 1-4 https://doi.org/10.1016/S0168-1923(02)00108-9	journal	December 2002
Chilling and forcing model to predict bud-burst of crop and forest species Cesaraccio, Carla; Spano, Donatella; Snyder, Richard L. Agricultural and Forest Meteorology, Vol. 126, Issue 1-2 https://doi.org/10.1016/j.agrformet.2004.03.002	journal	November 2004
Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France Delpierre, N.; Dufrêne, E.; Soudani, K. Agricultural and Forest Meteorology, Vol. 149, Issue 6-7 https://doi.org/10.1016/j.agrformet.2008.11.014	journal	June 2009
Digital repeat photography for phenological research in forest ecosystems Sonnentag, Oliver; Hufkens, Koen; Teshera-Sterne, Cory Agricultural and Forest Meteorology, Vol. 152 https://doi.org/10.1016/j.agrformet.2011.09.009	journal	January 2012
Climate change, phenology, and phenological control of vegetation feedbacks to the climate system Richardson, Andrew D.; Keenan, Trevor F.; Migliavacca, Mirco Agricultural and Forest Meteorology, Vol. 169 https://doi.org/10.1016/j.agrformet.2012.09.012	journal	February 2013
Heat wave hinders green wave: The impact of climate extreme on the phenology of a mountain grassland Cremonese, Edoardo; Filippa, Gianluca; Galvagno, Marta Agricultural and Forest Meteorology, Vol. 247 https://doi.org/10.1016/j.agrformet.2017.08.016	journal	December 2017
A spatially explicit modeling analysis of adaptive variation in temperate tree phenology Liang, Liang Agricultural and Forest Meteorology, Vol. 266-267 https://doi.org/10.1016/j.agrformet.2018.12.004	journal	March 2019
Divergent responses of spring phenology to daytime and nighttime warming Meng, Lin; Zhou, Yuyu; Li, Xuecao Agricultural and Forest Meteorology, Vol. 281 https://doi.org/10.1016/j.agrformet.2019.107832	journal	February 2020
Modelling carbon and water cycles in a beech forest Dufrêne, E.; Davi, H.; François, C. Ecological Modelling, Vol. 185, Issue 2-4 https://doi.org/10.1016/j.ecolmodel.2005.01.004	journal	July 2005
A finite element strategy to investigate the free expansion behaviour of a biodegradable polymeric stent Debusschere, Nic; Segers, Patrick; Dubruel, Peter Journal of Biomechanics, Vol. 48, Issue 10 https://doi.org/10.1016/j.jbiomech.2015.03.024	journal	July 2015
Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery Bolton, Douglas K.; Gray, Josh M.; Melaas, Eli K. Remote Sensing of Environment, Vol. 240 https://doi.org/10.1016/j.rse.2020.111685	journal	April 2020
Experiments Are Necessary in Process-Based Tree Phenology Modelling Hänninen, Heikki; Kramer, Koen; Tanino, Karen Trends in Plant Science, Vol. 24, Issue 3 https://doi.org/10.1016/j.tplants.2018.11.006	journal	March 2019
Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades: PHENOLOGY AND CARBON CYCLE IN NH Piao, Shilong; Friedlingstein, Pierre; Ciais, Philippe Global Biogeochemical Cycles, Vol. 21, Issue 3 https://doi.org/10.1029/2006GB002888	journal	September 2007
Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model: PARAMETERIZATION IMPROVEMENTS AND FUNCTIONAL AND STRUCTURAL ADVANCES Lawrence, David M.; Oleson, Keith W.; Flanner, Mark G. Journal of Advances in Modeling Earth Systems, Vol. 3, Issue 1 https://doi.org/10.1029/2011MS00045	journal	January 2011
Warming‐Induced Earlier Greenup Leads to Reduced Stream Discharge in a Temperate Mixed Forest Catchment Kim, Ji Hyun; Hwang, Taehee; Yang, Yun Journal of Geophysical Research: Biogeosciences, Vol. 123, Issue 6 https://doi.org/10.1029/2018JG004438	journal	June 2018
Rapid Net Carbon Loss From a Whole‐Ecosystem Warmed Peatland Hanson, Paul J.; Griffiths, Natalie A.; Iversen, Colleen M. AGU Advances, Vol. 1, Issue 3 https://doi.org/10.1029/2020AV000163	journal	July 2020
A continental phenology model for monitoring vegetation responses to interannual climatic variability White, Michael A.; Thornton, Peter E.; Running, Steven W. Global Biogeochemical Cycles, Vol. 11, Issue 2 https://doi.org/10.1029/97GB00330	journal	June 1997
Growing season extended in Europe Menzel, Annette; Fabian, Peter Nature, Vol. 397, Issue 6721 https://doi.org/10.1038/17709	journal	February 1999
Climate mitigation from vegetation biophysical feedbacks during the past three decades Zeng, Zhenzhong; Piao, Shilong; Li, Laurent Z. X. Nature Climate Change, Vol. 7, Issue 6 https://doi.org/10.1038/nclimate3299	journal	May 2017
Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures Richardson, Andrew D.; Hufkens, Koen; Milliman, Thomas Nature, Vol. 560, Issue 7718, p. 368-371 https://doi.org/10.1038/s41586-018-0399-1	journal	August 2018
Tracking vegetation phenology across diverse biomes using Version 2.0 of the PhenoCam Dataset Seyednasrollah, Bijan; Young, Adam M.; Hufkens, Koen Scientific Data, Vol. 6, Issue 1 https://doi.org/10.1038/s41597-019-0229-9	journal	October 2019
Characteristics, drivers and feedbacks of global greening Piao, Shilong; Wang, Xuhui; Park, Taejin Nature Reviews Earth & Environment, Vol. 1, Issue 1 https://doi.org/10.1038/s43017-019-0001-x	journal	December 2019
Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom Scientific Data, Vol. 5, Issue 1 https://doi.org/10.1038/sdata.2018.28	journal	March 2018
Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States Meng, Lin; Mao, Jiafu; Zhou, Yuyu Proceedings of the National Academy of Sciences, Vol. 117, Issue 8 https://doi.org/10.1073/pnas.1911117117	journal	February 2020
Temperature rather than photoperiod controls growth cessation and dormancy in Sorbus species Heide, O. M. Journal of Experimental Botany, Vol. 62, Issue 15 https://doi.org/10.1093/jxb/err213	journal	August 2011
Apple Fruit Bud Development and Growth; Analysis and an Empirical Model Landsberg, J. J. Annals of Botany, Vol. 38, Issue 5 https://doi.org/10.1093/oxfordjournals.aob.a084891	journal	November 1974
Leaf water relations reflect canopy phenology rather than leaf life span in Sonoran Desert trees González-Rebeles, Georgina; Terrazas, Teresa; Méndez-Alonzo, Rodrigo Tree Physiology https://doi.org/10.1093/treephys/tpab032	journal	February 2021
A Cellular Timetable of Autumn Senescence Keskitalo, Johanna; Bergquist, Gustaf; Gardeström, Per Plant Physiology, Vol. 139, Issue 4 https://doi.org/10.1104/pp.105.066845	journal	November 2005
The Control of Autumn Senescence in European Aspen Fracheboud, Yvan; Luquez, Virginia; Björkén, Lars Plant Physiology, Vol. 149, Issue 4 https://doi.org/10.1104/pp.108.133249	journal	February 2009
Detecting nonlinear response of spring phenology to climate change by Bayesian analysis Pope, Katherine S.; Dose, Volker; Da Silva, David Global Change Biology, Vol. 19, Issue 5 https://doi.org/10.1111/gcb.12130	journal	February 2013
The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models Keenan, Trevor F.; Richardson, Andrew D. Global Change Biology, Vol. 21, Issue 7 https://doi.org/10.1111/gcb.12890	journal	April 2015
A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios Chen, Min; Melaas, Eli K.; Gray, Josh M. Global Change Biology, Vol. 22, Issue 11 https://doi.org/10.1111/gcb.13326	journal	May 2016
Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel Global Change Biology, Vol. 22, Issue 10 https://doi.org/10.1111/gcb.13383	journal	July 2016
Plant phenology and global climate change: Current progresses and challenges Piao, Shilong; Liu, Qiang; Chen, Anping Global Change Biology, Vol. 25, Issue 6 https://doi.org/10.1111/gcb.14619	journal	April 2019
Modeling leaf senescence of deciduous tree species in Europe Liu, Qiang; Piao, Shilong; Campioli, Matteo Global Change Biology, Vol. 26, Issue 7 https://doi.org/10.1111/gcb.15132	journal	May 2020
Photoperiod decelerates the advance of spring phenology of six deciduous tree species under climate warming Meng, Lin; Zhou, Yuyu; Gu, Lianhong Global Change Biology, Vol. 27, Issue 12 https://doi.org/10.1111/gcb.15575	journal	March 2021
Macroscale prediction of autumn leaf coloration throughout the continental United States: Scaling and predicting autumn phenology Jeong, Su-Jong; Medvigy, David Global Ecology and Biogeography, Vol. 23, Issue 11 https://doi.org/10.1111/geb.12206	journal	July 2014
Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006 White, Michael A.; de BEURS, Kirsten M.; Didan, Kamel Global Change Biology, Vol. 15, Issue 10 https://doi.org/10.1111/j.1365-2486.2009.01910.x	journal	October 2009
Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis Richardson, Andrew D.; Anderson, Ryan S.; Arain, M. Altaf Global Change Biology, Vol. 18, Issue 2 https://doi.org/10.1111/j.1365-2486.2011.02562.x	journal	November 2011
Seasonal variation in the canopy color of temperate evergreen conifer forests Seyednasrollah, Bijan; Bowling, David R.; Cheng, Rui New Phytologist, Vol. 229, Issue 5 https://doi.org/10.1111/nph.17046	journal	December 2020
Photoperiod constraints on tree phenology, performance and migration in a warming world: Photoperiod limits on tree climate responses Way, Danielle A.; Montgomery, Rebecca A. Plant, Cell & Environment, Vol. 38, Issue 9 https://doi.org/10.1111/pce.12431	journal	October 2014
Summer soil drying exacerbated by earlier spring greening of northern vegetation Lian, Xu; Piao, Shilong; Li, Laurent Z. X. Science Advances, Vol. 6, Issue 1 https://doi.org/10.1126/sciadv.aax0255	journal	January 2020
Phenology Under Global Warming Korner, C.; Basler, D. Science, Vol. 327, Issue 5972 https://doi.org/10.1126/science.1186473	journal	March 2010
Response--Warming, Photoperiods, and Tree Phenology Korner, C.; Basler, D. Science, Vol. 329, Issue 5989 https://doi.org/10.1126/science.329.5989.278	journal	July 2010
Process-Based Models of Phenology for Plants and Animals Chuine, Isabelle; Régnière, Jacques Annual Review of Ecology, Evolution, and Systematics, Vol. 48, Issue 1 https://doi.org/10.1146/annurev-ecolsys-110316-022706	journal	November 2017
Phenology and Springtime Surface-Layer Change Schwartz, Mark D. Monthly Weather Review, Vol. 120, Issue 11 https://doi.org/10.1175/1520-0493(1992)120<2570:PASSLC>2.0.CO;2	journal	November 1992
Impact of Earth Greening on the Terrestrial Water Cycle Zeng, Zhenzhong; Piao, Shilong; Li, Laurent Z. X. Journal of Climate, Vol. 31, Issue 7 https://doi.org/10.1175/JCLI-D-17-0236.1	journal	April 2018
Dimensionality Reduction for Complex Models via Bayesian Compressive Sensing Sargsyan, Khachik; Safta, Cosmin; Najm, Habib N. International Journal for Uncertainty Quantification, Vol. 4, Issue 1 https://doi.org/10.1615/Int.J.UncertaintyQuantification.2013006821	journal	January 2014
Relationship between leaf physiologic traits and canopy color indices during the leaf expansion period in an oak forest Liu, Zhunqiao; Hu, Haibo; Yu, Hua Ecosphere, Vol. 6, Issue 12 https://doi.org/10.1890/ES14-00452.1	journal	December 2015
Thermal Time, Chill Days and Prediction of Budburst in Picea sitchensis Cannell, M. G. R.; Smith, R. I. The Journal of Applied Ecology, Vol. 20, Issue 3 https://doi.org/10.2307/2403139	journal	December 1983
Date of Budburst of Fifteen Tree Species in Britain Following Climatic Warming Murray, M. B.; Cannell, M. G. R.; Smith, R. I. The Journal of Applied Ecology, Vol. 26, Issue 2 https://doi.org/10.2307/2404093	journal	August 1989
Modelling the timing of Betula pubescens budburst. II. Integrating complex effects of photoperiod into process-based models Caffarra, A.; Donnelly, A.; Chuine, I. Climate Research, Vol. 46, Issue 2 https://doi.org/10.3354/cr00983	journal	March 2011
Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets Wang, Kai; Mao, Jiafu; Dickinson, Robert Remote Sensing, Vol. 5, Issue 6 https://doi.org/10.3390/rs5062857	journal	June 2013
Climate-driven local adaptation of ecophysiology and phenology in balsam poplar, Populus balsamifera L. (Salicaceae) Keller, Stephen R.; Soolanayakanahally, Raju Y.; Guy, Robert D. American Journal of Botany, Vol. 98, Issue 1 https://doi.org/10.3732/ajb.1000317	journal	January 2011
Environmental drivers of drought deciduous phenology in the Community Land Model Dahlin, K. M.; Fisher, R. A.; Lawrence, P. J. Biogeosciences, Vol. 12, Issue 16 https://doi.org/10.5194/bg-12-5061-2015	journal	January 2015
Representing northern peatland microtopography and hydrology within the Community Land Model Shi, X.; Thornton, P. E.; Ricciuto, D. M. Biogeosciences, Vol. 12, Issue 21 https://doi.org/10.5194/bg-12-6463-2015	journal	January 2015
Attaining whole-ecosystem warming using air and deep-soil heating methods with an elevated CO ₂ atmosphere Hanson, Paul J.; Riggs, Jeffery S.; Nettles, W. Robert Biogeosciences, Vol. 14, Issue 4 https://doi.org/10.5194/bg-14-861-2017	journal	January 2017
Plant phenology evaluation of CRESCENDO land surface models – Part 1: Start and end of the growing season Peano, Daniele; Hemming, Deborah; Materia, Stefano Biogeosciences, Vol. 18, Issue 7 https://doi.org/10.5194/bg-18-2405-2021	journal	January 2021

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54 ENVIRONMENTAL SCIENCES
Climate change
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Evaluation and modification of ELM seasonal deciduous phenology against observations in a southern boreal peatland forest

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