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Extensive regions in the permafrost zone are projected to become climatically unsuitable to sustain permafrost peatlands over the next century, suggesting transformations in these landscapes that can leave large amounts of permafrost carbon vulnerable to post‐thaw decomposition. We present 3 years of eddy covariance measurements of CH4 and CO2 fluxes from the degrading permafrost peatland Iškoras in Northern Norway, which we disaggregate into separate fluxes of palsa, pond, and fen areas using information provided by the dynamic flux footprint in a novel ensemble‐based Bayesian deep neural network framework. The 3‐year mean CO2‐equivalent flux is estimated to be 106 gCO2 m−2 yr−1 for palsas, 1,780 gCO2 m−2 yr−1 for ponds, and −31 gCO2 m−2 yr−1 for fens, indicating that possible palsa degradation to thermokarst ponds would strengthen the local greenhouse gas forcing by a factor of about 17, while transformation into fens would slightly reduce the current local greenhouse gas forcing. Plain Language Summary: Arctic and sub‐arctic regions on the southern border of the permafrost zone often feature peatlands with a patchy surface of peat mounds, thaw ponds, and surrounding fens. As the permafrost underneath peat mounds thaws, these areas transform and can change their emission or uptake of greenhouse gases like CO2 and methane. Assessing this gas exchange on the patchy surface is difficult because our measurement techniques cannot directly observe the variability in space and time. We collected 3 years of gas exchange measurements at a Norwegian permafrost peatland and developed a new method using a collection of uncertainty‐aware neural networks to predict the greenhouse gas exchange of different surface types. Our work suggests that large amounts of methane are emitted by ponds and fens, while the elevated peat mounds have almost no methane emissions. For CO2, we see that ponds are strong emitters, while fens take up substantial amounts as their vegetation absorbs this gas. We are still unsure when the peat mounds will collapse and if they turn into ponds or fens, but we can say that pond formation would give a 17 fold increase in greenhouse gas emissions, while fen formation would slightly reduce today's emissions of permafrost peatlands. Key Points: Eddy covariance fluxes are disaggregated for different surfaces using Bayesian neural networks to derive uncertainty‐aware carbon balancesWhile palsa areas have a near‐zero annual methane balance, the fens and ponds that form upon palsa degradation emit large amounts of methaneFens compensate for methane emissions with strong annual CO2 sinks, while ponds appear as strong, yet uncertain, CO2 emission hotspots [ABSTRACT FROM AUTHOR]

While climate models broadly agree on the changes expected to occur over the Arctic with global warming on a pan-Arctic scale (i.e., polar amplification, sea-ice loss, increased precipitation), the magnitude and patterns of those changes at regional and local scales remain uncertain. This limits the usability of climate model projections for risk assessments and their impact on human activities or ecosystems (e.g., fires, permafrost thawing). Whereas any single or ensemble-mean projection may be of limited use to stakeholders, recent studies have shown the value of the storyline approach in providing a comprehensive and tractable set of climate projections that can be used to evaluate changes in environmental or societal risks associated with global warming. Here, we apply the storyline approach to a large ensemble of CMIP6 models, with the aim of distilling the wide spread in model predictions into four physically plausible outcomes of Arctic summertime climate change. This is made possible by leveraging strong covariability in the climate system, associated with well-known but poorly constrained teleconnections and local processes: specifically, we find that differences in Barents-Kara Sea warming and lower tropospheric warming over polar land regions among CMIP6 models explain most of the inter-model variability in pan-Arctic surface summer climate response to global warming. Based on this novel finding, we compare regional disparities in climate change across the four storylines. Our storyline analysis highlights the fact that, for a given amount of global warming, certain climate risks can be intensified while others may be lessened, relative to a "middle-of-the-road" ensemble mean projection. We find this to be particularly relevant when comparing climate change over terrestrial and marine areas of the Arctic, which can show substantial differences in their sensitivity to global warming. We conclude by discussing potential implications of our findings for modelling climate change impacts on ecosystems and human activities. [ABSTRACT FROM AUTHOR]

In the high Arctic, plant community species composition generally responds slowly to climate warming, whereas less is known about the community functional trait responses and consequences for ecosystem functioning. The slow species turnover and large distribution ranges of many Arctic plant species suggest a significant role of intraspecific trait variability in functional responses to climate change. Here we compare taxonomic and functional community compositional responses to a long‐term (17‐year) warming experiment in Svalbard, Norway, replicated across three major high Arctic habitats shaped by topography and contrasting snow regimes. We observed taxonomic compositional changes in all plant communities over time. Still, responses to experimental warming were minor and most pronounced in the drier habitats with relatively early snowmelt timing and long growing seasons (Cassiope and Dryas heaths). The habitats were clearly separated in functional trait space, defined by 12 size‐ and leaf economics‐related traits, primarily due to interspecific trait variation. Functional traits also responded to experimental warming, most prominently in the Dryas heath and mostly due to intraspecific trait variation. Leaf area and mass increased and leaf δ15N decreased in response to the warming treatment. Intraspecific trait variability ranged between 30% and 71% of the total trait variation, reflecting the functional resilience of those communities, dominated by long‐lived plants, due to either phenotypic plasticity or genotypic variation, which most likely underlies the observed resistance of high Arctic vegetation to climate warming. We further explored the consequences of trait variability for ecosystem functioning by measuring peak season CO2 fluxes. Together, environmental, taxonomic, and functional trait variables explained a large proportion of the variation in net ecosystem exchange (NEE), which increased when intraspecific trait variation was accounted for. In contrast, even though ecosystem respiration and gross ecosystem production both increased in response to warming across habitats, they were mainly driven by the direct kinetic impacts of temperature on plant physiology and biochemical processes. Our study shows that long‐term experimental warming has a modest but significant effect on plant community functional trait composition and suggests that intraspecific trait variability is a key feature underlying high Arctic ecosystem resistance to climate warming. [ABSTRACT FROM AUTHOR]

Permafrost soils in boreal and Arctic ecosystems store almost twice as much carbon as is currently present in the atmosphere. Permafrost thaw and the microbial decomposition of previously frozen organic carbon is considered one of the most likely positive climate feedbacks from terrestrial ecosystems to the atmosphere in a warmer world. The rate of carbon release from permafrost soils is highly uncertain, but it is crucial for predicting the strength and timing of this carbon-cycle feedback effect, and thus how important permafrost thaw will be for climate change this century and beyond. Sustained transfers of carbon to the atmosphere that could cause a significant positive feedback to climate change must come from old carbon, which forms the bulk of the permafrost carbon pool that accumulated over thousands of years. Here we measure net ecosystem carbon exchange and the radiocarbon age of ecosystem respiration in a tundra landscape undergoing permafrost thaw to determine the influence of old carbon loss on ecosystem carbon balance. We find that areas that thawed over the past 15 years had 40 per cent more annual losses of old carbon than minimally thawed areas, but had overall net ecosystem carbon uptake as increased plant growth offset these losses. In contrast, areas that thawed decades earlier lost even more old carbon, a 78 per cent increase over minimally thawed areas; this old carbon loss contributed to overall net ecosystem carbon release despite increased plant growth. Our data document significant losses of soil carbon with permafrost thaw that, over decadal timescales, overwhelms increased plant carbon uptake at rates that could make permafrost a large biospheric carbon source in a warmer world. [ABSTRACT FROM AUTHOR]

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts.