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Northern lakes are important sources of the climate forcing trace gases methane (CH4) and carbon dioxide (CO2). A substantial portion of lakes' annual emissions can take place immediately after ice melt in spring. The drivers of these fluxes are neither well constrained nor fully understood. We present a detailed carbon gas budget for three subarctic lakes, using 6 years of eddy covariance and 9 years of manual flux measurements. We combine measurements of temperature, dissolved oxygen, and CH4 stable isotopologues to quantify functional relationships between carbon gas production and conversion, energy inputs, and the redox regime. Spring emissions were regulated by the availability of oxygen in winter, rather than temperature as during ice‐free conditions. Under‐ice storage increased predictably with ice‐cover duration, and CH4 accumulation rates (25 ± 2 mg CH4‐C·m−2·day−1) exceeded summer emissions (19 ± 1 mg CH4‐C·m−2·day−1). The seasonally ice‐covered lakes emitted 26–59% of the annual CH4 flux and 15–30% of the annual CO2 flux at ice‐off. Reduced spring emissions were associated with winter snowmelt events, which can transport water downstream and oxygenate the water column. Stable isotopes indicate that 64–96% of accumulated CH4 escaped oxidation, implying that a considerable portion of the dissolved gases produced over winter may evade to the atmosphere. Plain Language Summary: Northern lakes are globally significant sources of greenhouse gases methane and carbon dioxide, but the seasonal pattern of emissions from lakes that are ice covered in winter remains poorly resolved. Our multiyear, multilake study reveals the importance of emissions during the ice‐off period, when carbon gas that had accumulated under ice is released. We show that more than half of the annual methane emissions and a third of the yearly carbon dioxide flux can be released at spring ice‐out. Unlike emissions during summer, which tend to be closely correlated with temperature, spring emissions of both gases are in part regulated by the availability of oxygen under ice. The quantity of carbon gas accumulating under ice, and therefore the amount that can be emitted in spring, scales predictably with ice‐cover duration. Parameterizations of winter and spring carbon cycling processes, such as those described in this study, may contribute to more accurate models of annual, ecosystem‐level carbon fluxes and are essential tools to improve freshwater emission inventories and quantify critical Arctic warming feedbacks. Key Points: Multiyear flux measurements show that annual CH4 emissions from northern lakes can be dominated by emissions during ice‐off in springCH4 accumulates under ice at rates exceeding summer emissions, in part because prolonged anoxia limits methanotrophyUnder‐ice carbon gas storage scales predictably with ice‐cover season length, but meltwater advection or dilution can limit fluxes in spring [ABSTRACT FROM AUTHOR]

Since the advancement in CH4 gas analyser technology and its applicability to eddy covariance flux measurements, monitoring of CH4 emissions is becoming more widespread. In order to accurately determine the greenhouse gas balance, high quality gap-free data is required. Currently there is still no consensus on CH4 gap-filling methods, and methods applied are still study-dependent and often carried out on low resolution, daily data. In the current study, we applied artificial neural networks to six distinctively different CH4 time series from high latitudes, explain the method and test its functionality. We discuss the applicability of neural networks in CH4 flux studies, the advantages and disadvantages of this method, and what information we were able to extract from such models. Three different approaches were tested by including drivers such as air and soil temperature, barometric air pressure, solar radiation, wind direction (indicator of source location) and in addition the lagged effect of water table depth and precipitation. In keeping with the principle of parsimony, we included up to five of these variables traditionally measured at CH4 flux measurement sites. Fuzzy sets were included representing the seasonal change and time of day. High Pearson correlation coefficients (r) of up to 0.97 achieved in the final analysis are indicative for the high performance of neural networks and their applicability as a gap-filling method for CH4 flux data time series. This novel approach which we show to be appropriate for CH4 fluxes is a step towards standardising CH4 gap-filling protocols. [ABSTRACT FROM AUTHOR]

The Lena, a large river that drains the northern coldest region of the Northern Hemisphere, is deeply influenced by the continuous permafrost and degradation of the frozen ground has been shown to be the main cause of the marked increase in water discharge. The first objective of this study conducted on the middle Lena was to analyze the island dynamics for the last 50 years (1967 to 2017). Several morphological parameters were surveyed using a GIS on seven series of aerial photographs and satellite images of a 100 km-long reach: island size, eroded and deposited areas, position and morphology of the islands. This approach enabled the identification of evolutionary models. Our second objective was to evaluate the potential impact of ongoing climate change. We analyzed morphological parameters with respect to two main factors: efficient discharge (bar-full, bankfull and flood discharges) and water temperature. A potential erosion index (PEI) was calculated by coupling the duration of discharge exceeding the bar-full level and water temperature. The results identified several morphological changes that occurred at the end of the 20th century: an increase in the number of islands, greater eroded surfaces and accelerated migration of islands. Comparing the dynamics of islands with and without permafrost is a good indicator of their sensitivity to climate change. A major change was observed concerning the erosion and migration of islands with and without permafrost. This evolution seems to be linked both with the duration of the discharge that exceeds the bar-full level and with the number of flood peaks. The water temperature in May and August have a major influence on permafrost islands that become increasingly destabilized. Thus, as large rivers are assumed to slowly react to climate change, the recent changes in the Lena River prove that the global change deeply impacts periglacial rivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)