Improving ecosystem model PEPRMT and remote sensing photosynthesis (GPP) products in wetlands using stable carbon and oxygen isotopes

Background/Question/Methods

The partitioning of net ecosystem exchange of CO₂ (NEE) measured via the eddy covariance technique into gross photosynthesis (GPP) and ecosystem respiration (R_eco) is often associated with unknown amounts of uncertainty. Typically, NEE is partitioned by extrapolating nighttime measurements of NEE (R_eco) to the day using a temperature function. Then Reco is subtracted from NEE to obtain GPP (i.e., GPP = NEE - R_eco). However, recent studies employing stable carbon isotope partitioning have shown that this practice can strongly overestimate GPP and R_eco, from 10-100%. This is due to reduced leaf respiration during the day, aka the Kok effect. The Kok effect is most significant when R_eco is dominated by leaf respiration such as in wetlands with anaerobic soils. We are collecting ecosystem exchange measurements of stable carbon and oxygen isotopes of CO₂ in degraded and restored wetlands in the Sacramento-San Joaquin River Delta, California. These data are being used to improve stable isotope partitioning methods mainly by developing modeling approaches for constraining δ¹³C_r, the isotopic signature of ecosystem respiration, and developing theory to employ the stable isotopes of oxygen to partition NEE. Finally, we will use these partitioned fluxes to update an ecosystem model PEPRMT to account for the Kok effect and improve estimates of GPP in wetlands. GPP derived from standard and isotope partitioning approaches will be compared to satellite-derived GPP products, specifically MODIS and Landsat.

Results/Conclusions

Ecosystem exchange measurements of stable carbon and oxygen isotopes of CO₂ have been collected in a degraded peatland currently under alfalfa cultivation. Comparisons of standard and stable carbon isotope partitioning suggest that standard partitioning approaches overestimate GPP by 10-13%. Preliminary comparisons of standard and stable oxygen isotope partitioning are similar, where standard partitioning overestimates GPP by 15% relative to oxygen isotope partitioning. Isotope measurements in a restored wetland are planned for spring-summer 2017 during which comparison with remote sensing products will be conducted. The results of this study have implications for global measurements and modeling of GPP, a critical parameter in climate models.