The fate of organic carbon (C) in permafrost soils is important to the climate system due to the large global stocks of permafrost C. Thawing permafrost can be subject to dynamic hydrology, making redox processes an important factor controlling soil organic matter (SOM) decomposition rates and greenhouse gas production. In iron (Fe)-rich permafrost soils, Fe(III) can serve as a terminal electron acceptor, suppressing methane (CH4) production and increasing carbon dioxide (CO2) production. Current large-scale models of Arctic C cycling do not include Fe cycling or pH interactions. Here, we coupled Fe redox reactions and C cycling in a geochemical reaction model to simulate the interactions of SOM decomposition, Fe(III) reduction, pH dynamics, and greenhouse gas production in permafrost soils subject to dynamic hydrology. We evaluated the model using measured CO2 and CH4 fluxes as well as changes in pH, Fe(II), and dissolved organic C concentrations from oxic and anoxic incubations of permafrost soils from polygonal permafrost sites in northern Alaska, United States. In simulations of higher frequency oxic-anoxic cycles, rapid oxidation of Fe(II) to Fe(III) during oxic periods and gradual Fe(III) reduction during anoxic periods reduced cumulative CH4 fluxes and increased cumulative CO2 fluxes. Lower pH suppressed CH4 fluxes through its direct impact on methanogenesis and by increasing Fe(III) bioavailability. Our results suggest that models that do not include Fe-redox reactions and its pH dependence could overestimate CH4 production and underestimate CO2 emissions and SOM decomposition rates in Fe-rich, frequently waterlogged Arctic soils.

Accurate simulations of high latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Such models often represent high-latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine arctic-specific PFTs. The PFTs that are new to the model include: 1) nonvascular mosses and lichens, 2) deciduous and evergreen shrubs of various height classes, including an alder PFT, 3) graminoids, and 4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario showed alder-dominated plant communities gaining more biomass and lichen-dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.