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Northern high-latitude lakes are critical sites for carbon processing and serve as potential conduits for the emission of permafrost-derived carbon and greenhouse gases. However, the fate and emission pathways of permafrost carbon in these systems remain uncertain. Here, we used the natural abundance of radiocarbon to identify and trace the predominant sources of methane, carbon dioxide, dissolved inorganic and organic carbon in nine lakes within the Yukon Flats National Wildlife Refuge in interior Alaska, a discontinuous permafrost region with high landscape heterogeneity and susceptibility to climate, permafrost, and hydrological changes. We find that although Yukon Flats lakes primarily process young carbon (modern to 1290 ± 60 years before present), permafrost-derived carbon is present in some of the sampled lakes and contributes, at most, 30 ± 10% of the dissolved carbon in lake surface waters. Apportionment of young carbon and legacy carbon (carbon with radiocarbon age ⩾5000 years before present) is decoupled among the dissolved inorganic and organic carbon species, with methane showing a stronger legacy signature. Our observations suggest that permafrost-thaw-related transport of carbon through Yukon Flats lacustrine ecosystems and into the atmosphere is small, and likely regulated by surficial sediments, permafrost distribution, wildfire occurrence, or masked by contemporary carbon processes. The heterogeneity of lakes across our study area and northern landscapes more broadly cautions against using any one region (e.g. Yedoma permafrost lakes) to upscale their contribution across the pan-Arctic.

Rapid warming in Arctic tundra may lead to drier soils in summer and greater lightning ignition rates, likely culminating in enhanced wildfire risk. Increased wildfire frequency and intensity leads to greater conversion of permafrost carbon to greenhouse gas emissions. Here, we quantify the effect of recent tundra fires on the creation of methane (CH _4 ) emission hotspots, a fingerprint of the permafrost carbon feedback. We utilized high-resolution (∼25 m ^2 pixels) and broad coverage (1780 km ^2 ) airborne imaging spectroscopy and maps of historical wildfire-burned areas to determine whether CH _4 hotspots were more likely in areas burned within the last 50 years in the Yukon–Kuskokwim Delta, Alaska, USA. Our observations provide a unique observational constraint on CH _4 dynamics, allowing us to map CH _4 hotspots in relation to individual burn events, burn scar perimeters, and proximity to water. We find that CH _4 hotspots are roughly 29% more likely on average in tundra that burned within the last 50 years compared to unburned areas and that this effect is nearly tripled along burn scar perimeters that are delineated by surface water features. Our results indicate that the changes following tundra fire favor the complex environmental conditions needed to generate CH _4 emission hotspots. We conclude that enhanced CH _4 emissions following tundra fire represent a positive feedback that will accelerate climate warming, tundra fire occurrence, and future permafrost carbon loss to the atmosphere.

Forest structure—the height, cover, vertical complexity, and spatial patterns of trees—is a key indicator of productivity variation across forested extents. During the 2017 and 2019 growing seasons, NASA’s Arctic-Boreal Vulnerability Experiment collected full-waveform airborne LiDAR using the land, vegetation and imaging sensor, sampling boreal and tundra landscapes across a variety of ecological regions from central Canada westward through Alaska. Here, we compile and archive a geo-referenced gridded suite of these data that include vertical structure estimates and novel horizontal cover estimates of vegetation canopy cover derived from vegetation’s vertical LiDAR profile. We validate these gridded estimates with small footprint airborne LiDAR, and link >36 million of them with stand age estimates from a Landsat time-series of tree-canopy cover that we confirm with plot-level disturbance year data. We quantify the regional magnitude and variability in site index, the age-dependent rates of forest growth, across 15 boreal ecoregions in North America. With this open archive suite of forest structure data linked to stand age, we bound current forest productivity estimates across a boreal structure gradient whose response to key bioclimatic drivers may change with stand age. These results, derived from a reduction of a large archive of airborne LiDAR and a Landsat time series, quantify forest productivity bounds for input into forest and ecosystem growth models, to update forecasts of changes in North America’s boreal forests by improving the regional parametrization of forest growth rates.

Remote sensing and site-level observations have shown unprecedented changes in Arctic ecosystems owing to climate warming. These observations include greening and browning trends in Arctic vegetation as well as changes in species composition both in the tundra and the boreal forests. Here, we leveraged solar induced chlorophyll fluorescence (SIF) to study changes in ecosystem phenology across the pan-Arctic domain from 2000 to 2020. Ecoregions, as a proxy for plants’ functional traits, were the single most important variable to explain the spatial and phenological heterogeneity in observed SIF trends. We observed unique regional trends in ecosystems responses to climate change affecting the timing of spring photosynthesis onset, magnitude of peak productivity during the growing season (GS) and fall senescence. While, Photosynthetic activity in the early GS showed increasing trends across the vast majority of the pan-Arctic, it tends to decline at the end of the season for nearly half of the land area, including parts of North America but more significantly in central Siberia. The observed changes in phenology highlight the role of biodiversity in regional climate sensitivity and emphasizes the need for better representations of sub-biomes to community level information in Arctic ecosystem process models and projections. These results also highlight the importance of phenology information in ecosystem models for better understanding of the timing and magnitude of carbon uptake in the Arctic domain with accelerated changes in climate.

Solid waste management represents one of the largest anthropogenic methane emission sources. However, precise quantification of landfill and composting emissions remains difficult due to variety of site-specific factors that contribute to landfill gas generation and effective capture. Remote sensing is an avenue to quantify process-level emissions from waste management facilities. The California Methane Survey flew the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) over 270 landfills and 166 organic waste facilities repeatedly during 2016–2018 to quantify their contribution to the statewide methane budget. We use representative methane retrievals from this campaign to present three specific findings where remote sensing enabled better landfill and composting methane monitoring: (1) Quantification of strong point source emissions from the active face landfills that are difficult to capture by in situ monitoring or landfill models, (2) emissions that result from changes in landfill infrastructure (design, construction, and operations), and (3) unexpected large emissions from two organic waste management methods (composting and digesting) that were originally intended to help mitigate solid waste emissions. Our results show that remotely-sensed emission estimates reveal processes that are difficult to capture in biogas generation models. Furthermore, we find that airborne remote sensing provides an effective avenue to study the temporally changing dynamics of landfills. This capability will be further improved with future spaceborne imaging spectrometers set to launch in the 2020s.