Climate warming-related hydrological transformations are changing material mobilization, composition, and transport pathways along the terrestrial-aquatic continuum. Here, we integrate decade-long hydrometeorological and biogeochemical data from the High Arctic to show that annual fluvial energy is shifting from a skewed (snowmelt-dominated) to a multi-modal (snowmelt- and rainfall-dominated) distribution. This shift enhanced terrestrial-aquatic connectivity for dissolved and particulate material fluxes, but to overcome the watersheds’ buffering capacity for particulate material rainfall events had to increase by an order of magnitude. Permafrost disturbances (< 3 % of the watersheds’ areal extent) reduced watershed-scale DOC export enough to offset concurrent increased DOC export in undisturbed watersheds but play a weaker role in altering C export than the increased magnitude and frequency of late summer rainfall events. However, the disturbances have primed the landscape for accelerated geomorphic change when future rainfall magnitudes and consequent pluvial responses exceed the current buffering capacity of the terrestrial-aquatic continuum.

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Abstract. Landscapes are often assumed to be homogeneous when interpreting eddy covariance fluxes, which can lead to biases when gap-filling and scaling-up observations to determine regional carbon budgets. Tundra ecosystems are heterogeneous at multiple scales, with variation in plant functional types, soil moisture, thaw depth, and microtopography, for example, influencing net ecosystem exchange (NEE) of carbon dioxide (CO2) and methane (CH4) fluxes. With warming temperatures, Arctic ecosystems could change from a net sink to a net source of carbon to the atmosphere in some locations, but the carbon balance remains highly uncertain. In this study we report results from growing season NEE and CH4 fluxes from an eddy covariance tower in the Yukon-Kuskokwim Delta in Alaska. We used footprint models and Bayesian Markov Chain Monte Carlo (MCMC) methods to un-mix tower observations into constituent landcover fluxes based on high resolution landcover maps of the tower region. We compared three types of footprint models and used two landcover maps with varying complexity to determine the effects of these choices on derived ecosystem fluxes. We used artificially created gaps of withheld observations to compare gap-filling performance using our derived landcover-specific fluxes and traditional gap-filling methods that assume homogeneous landscapes. We also compared resulting regional carbon budgets when scaling-up observations using heterogeneous and homogeneous approaches. Traditional gap-filling methods performed worse at predicting artificially withheld gaps in NEE than those that accounted for heterogeneous landscapes, while there were only slight differences between footprint models and landcover maps. We identified and quantified hot spots of carbon fluxes in the landscape (e.g., late growing season emissions from wetlands and small ponds). We resolved distinct seasonality in tundra growing season NEE fluxes. Scaling while assuming a homogeneous landscape overestimated the growing season CO2 sink by a factor of two and underestimated CH4 emissions by a factor of two when compared to scaling with any method that accounts for landscape heterogeneity. We show how Bayesian MCMC, analytical footprint models, and high resolution landcover maps can be leveraged to derive detailed landcover carbon fluxes from eddy covariance timeseries. These results demonstrate the importance of landscape heterogeneity when scaling carbon emissions across the Arctic.

Overall, this paper provides a clear method section and presents an extensive analysis of a dataset of available inorganic nitrogen in a high arctic wet sedge meadow. The spatial extent of data collection is welcome and given the importance of arctic wetlands, this study could provide a valuable addition from a different site. There is definitely value in improving understanding the controls on C and N cycling in arctic wetlands and there are potentially interesting data here. The manuscript, however, would benefit from an appropriate title, clearer aims and a greater effort to highlight what novel contribution the study makes. There is a substantial quan-C1

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