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As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiaġvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change. 

Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions. 

Peat mosses (Sphagnumspp.) are keystone species in boreal peatlands, where they dominate net primary productivity and facilitate the accumulation of carbon in thick peat deposits.Sphagnummosses harbor a diverse assemblage of microbial partners, including N₂‐fixing (diazotrophic) and CH₄‐oxidizing (methanotrophic) taxa that support ecosystem function by regulating transformations of carbon and nitrogen. Here, we investigate the response of theSphagnumphytobiome (plant + constituent microbiome + environment) to a gradient of experimental warming (+0°C to +9°C) and elevated CO₂(+500 ppm) in an ombrotrophic peatland in northern Minnesota (USA). By tracking changes in carbon (CH₄, CO₂) and nitrogen (NH₄‐N) cycling from the belowground environment up toSphagnumand its associated microbiome, we identified a series of cascading impacts to theSphagnumphytobiome triggered by warming and elevated CO₂. Under ambient CO₂, warming increased plant‐available NH₄‐N in surface peat, excess N accumulated inSphagnumtissue, and N₂fixation activity decreased. Elevated CO₂offset the effects of warming, disrupting the accumulation of N in peat andSphagnumtissue. Methane concentrations in porewater increased with warming irrespective of CO₂treatment, resulting in a ~10× rise in methanotrophic activity withinSphagnumfrom the +9°C enclosures. Warming's divergent impacts on diazotrophy and methanotrophy caused these processes to become decoupled at warmer temperatures, as evidenced by declining rates of methane‐induced N₂fixation and significant losses of keystone microbial taxa. In addition to changes in theSphagnummicrobiome, we observed ~94% mortality ofSphagnumbetween the +0°C and +9°C treatments, possibly due to the interactive effects of warming on N‐availability and competition from vascular plant species. Collectively, these results highlight the vulnerability of theSphagnumphytobiome to rising temperatures and atmospheric CO₂concentrations, with significant implications for carbon and nitrogen cycling in boreal peatlands.