TY - JOUR
T1 - Intercomparison of methods to estimate gross primary production based on CO2 and COS flux measurements
AU - Kohonen, Kukka Maaria
AU - Dewar, Roderick
AU - Tramontana, Gianluca
AU - Mauranen, Aleksanteri
AU - Kolari, Pasi
AU - Kooijmans, Linda M.J.
AU - Papale, Dario
AU - Vesala, Timo
AU - Mammarella, Ivan
N1 - Publisher Copyright:
© 2022 Kukka-Maaria Kohonen et al.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO2) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO2-based methods use traditional flux partitioning and artificial neural networks to separate the net CO2 flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO2 (LRU), of which one (LRUCAP) was developed in this study. LRUCAP was based on a previously tested stomatal optimization theory (CAP), while LRUPAR was based on an empirical relation to measured radiation. For the measurement period 2013-2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO2-based estimates on daily (23 % and 7 % higher, using LRUPAR and LRUCAP, respectively) and monthly scales (20 % and 3 % higher), as well as a higher cumulative sum over 3 months in all years (on average 25 % and 3 % higher). LRUCAP was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRUCAP gave closer agreement with CO2-based estimates of GPP than use of LRUPAR. When extended to other sites, LRUCAP may be more robust than LRUPAR because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRUPAR may be more site-specific. However, this requires further testing at other measurement sites.
AB - Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO2) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO2-based methods use traditional flux partitioning and artificial neural networks to separate the net CO2 flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO2 (LRU), of which one (LRUCAP) was developed in this study. LRUCAP was based on a previously tested stomatal optimization theory (CAP), while LRUPAR was based on an empirical relation to measured radiation. For the measurement period 2013-2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO2-based estimates on daily (23 % and 7 % higher, using LRUPAR and LRUCAP, respectively) and monthly scales (20 % and 3 % higher), as well as a higher cumulative sum over 3 months in all years (on average 25 % and 3 % higher). LRUCAP was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRUCAP gave closer agreement with CO2-based estimates of GPP than use of LRUPAR. When extended to other sites, LRUCAP may be more robust than LRUPAR because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRUPAR may be more site-specific. However, this requires further testing at other measurement sites.
UR - http://www.scopus.com/inward/record.url?scp=85140637401&partnerID=8YFLogxK
U2 - 10.5194/bg-19-4067-2022
DO - 10.5194/bg-19-4067-2022
M3 - Article
SN - 1726-4170
VL - 19
SP - 4067
EP - 4088
JO - Biogeosciences
JF - Biogeosciences
IS - 17
ER -