TY - JOUR
T1 - Early spring onset increases carbon uptake more than late fall senescence
T2 - modeling future phenological change in a US northern deciduous forest
AU - Teets, Aaron
AU - Bailey, Amey S.
AU - Hufkens, Koen
AU - Ollinger, Scott
AU - Schädel, Christina
AU - Seyednasrollah, Bijan
AU - Richardson, Andrew D.
N1 - Funding Information:
The development of the PhenoCam network has been funded by the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (awards EF-1065029 and EF-1702697), and DOE’s Regional and Global Climate Modeling program (award DE-SC0016011). Research at the Bartlett Experimental Forest is supported by the USDA Forest Service’s Northern Research Station. We acknowledge funding support from the National Science Foundation for the Hubbard Brook Long Term Ecological Research (LTER) program, awards #DEB-1114804 and #DEB-1637685 and the Harvard Forest LTER award #DEB 1832210; and support from the Northeastern States Research Cooperative #12DG11242307065.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2023/1
Y1 - 2023/1
N2 - In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1–3.2 days decade−1) compared to the spring (0.9–1.5 days decade−1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.
AB - In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1–3.2 days decade−1) compared to the spring (0.9–1.5 days decade−1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.
KW - AmeriFlux
KW - Biogeochemical modeling
KW - Deciduous forests
KW - Forest carbon cycling
KW - Hubbard Brook
KW - PhenoCam
KW - Phenology
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U2 - 10.1007/s00442-022-05296-4
DO - 10.1007/s00442-022-05296-4
M3 - Article
C2 - 36525137
AN - SCOPUS:85144156738
SN - 0029-8549
VL - 201
SP - 241
EP - 257
JO - Oecologia
JF - Oecologia
IS - 1
ER -