We studied methanotrophic activity in the water column in relation to heterotrophic bacterial production and efflux of methane (CH 4 ) from the lake surface in a small, stratified, humic, boreal lake (Valkea-Kotinen, southern Finland). During summer and winter stratification, the highest methanotrophic activities were in the metalimnion, where oxygen concentration was Ͻ6 mmol m Ϫ3 . During an incomplete spring turnover and summer stratification period, 3-5 times more CH 4 was consumed by methanotrophs in the water column than was released to the atmosphere. The highest CH 4 effluxes (1.2-5.1 mmol m Ϫ2 d Ϫ1 ) to the atmosphere occurred during the autumnal turnover despite observed methanotrophic activity in the whole water column. In winter, the amount of CH 4 consumed by methanotrophs (0.20 mol CH 4 m Ϫ2 during 6.5 months) was of the same order of magnitude as that during the ice-free period (0.22 mol CH 4 m Ϫ2 during 5.5 months). Annually ϳ80% of CH 4 diffused from the sediment was consumed by methanotrophs in the water column, and only 20% (0.11 mol CH 4 m Ϫ2 yr Ϫ1) was released to the atmosphere. During the ice-free period, bacterial production measured as [14 C]leucine uptake showed a bell-shaped relation to CH 4 concentration. The highest production was found in the metalimnion at CH 4 concentrations ranging from 5 to 10 mmol m Ϫ3. During summer stratification, net production of methanotrophs corresponded to 23-47% of total bacterial production, but during the autumn turnover, this proportion was higher (27-81%), indicating that methanotrophs offer a potentially significant source of carbon to zooplankton in stratified humic lakes.

Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

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