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Abstract Tall deciduous shrubs are critically important to carbon and nutrient cycling in high-latitude ecosystems. As Arctic regions warm, shrubs expand heterogeneously across their ranges, including within unburned terrain experiencing isometric gradients of warming. To constrain the effects of widespread shrub expansion in terrestrial and Earth System Models, improved knowledge of local-to-regional scale patterns, rates, and controls on decadal shrub expansion is required. Using fine-scale remote sensing, we modeled the drivers of patch-scale tall-shrub expansion over 68 years across the central Seward Peninsula of Alaska. Models show the heterogeneous patterns of tall-shrub expansion are not only predictable but have an upper limit defined by permafrost, climate, and edaphic gradients, two-thirds of which have yet to be colonized. These observations suggest that increased nitrogen inputs from nitrogen-fixing alders contributed to a positive feedback that advanced overall tall-shrub expansion. These findings will be useful for constraining and projecting vegetation-climate feedbacks in the Arctic. 

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m− 2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ~6000 g m− 2 (mean ≈350 g m− 2), while predicted values ranged from 0 to ~4000 g m− 2 (mean ≈275 g m− 2), resulting in model validation root-mean-squared-error (RMSE) ≈400 g m− 2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling 

The below-ground growing season often extends beyond the above-ground growing season in tundra ecosystems. However, we do not yet know where and when this occurs and whether these phenological asynchronies are driven by variation in local vegetation communities or by spatial variation in microclimate. Here, we combined above- and below-ground plant phenology metrics to compare the relative timings and magnitudes of leaf and root growth and senescence across microclimates and plant communities at five sites across the tundra biome. We observed asynchronous growth between above-ground and below-ground plant tissue, with the below-ground season extending up to 74% beyond the onset of above-ground leaf senescence. Plant community type, rather than microclimate, was a key factor controlling the timing, productivity and growth rates of roots, with graminoid roots exhibiting a distinct ‘pulse’ of growth later into the growing season than shrub roots. Our findings indicate the potential of vegetation change to influence below-ground carbon storage as roots remain active in unfrozen soils for longer as the climate warms. Taken together, increased root growth in soils that remain thawed later into the growing season, in combination with ongoing tundra vegetation change including increased shrubs and graminoids, can act together to alter below-ground productivity and carbon cycling in the tundra biome. 

Abstract Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we presentThe Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m⁻²) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic. 

Abstract. Soil pore water (SPW) chemistry can vary substantially acrossmultiple scales in Arctic permafrost landscapes. The magnitude of thesevariations and their relationship to scale are critical considerations forunderstanding current controls on geochemical cycling and for predictingfuture changes. These aspects are especially important for Arctic changemodeling where accurate representation of sub-grid variability may benecessary to predict watershed-scale behaviors. Our research goal is tocharacterize intra- and inter-watershed soil water geochemical variations attwo contrasting locations in the Seward Peninsula of Alaska, USA. We thenattempt to identify the key factors controlling concentrations of importantpore water solutes in these systems. The SPW geochemistry of 18 locationsspanning two small Arctic catchments was examined for spatial variabilityand its dominant environmental controls. The primary environmental controlsconsidered were vegetation, soil moisture and/or redox condition, water–soilinteractions and hydrologic transport, and mineral solubility. The samplinglocations varied in terms of vegetation type and canopy height, presence orabsence of near-surface permafrost, soil moisture, and hillslope position.Vegetation was found to have a significant impact on SPW NO3-concentrations, associated with the localized presence of nitrogen-fixingalders and mineralization and nitrification of leaf litter from tall willowshrubs. The elevated NO3- concentrations were, however, frequentlyequipoised by increased microbial denitrification in regions with sufficientmoisture to support it. Vegetation also had an observable impact on soil-moisture-sensitive constituents, but the effect was less significant. Theredox conditions in both catchments were generally limited by Fe reduction,seemingly well-buffered by a cache of amorphous Fe hydroxides, with the mostreducing conditions found at sampling locations with the highest soilmoisture content. Non-redox-sensitive cations were affected by a widevariety of water–soil interactions that affect mineral solubility andtransport. Identification of the dominant controls on current SPWhydrogeochemistry allows for qualitative prediction of future geochemicaltrends in small Arctic catchments that are likely to experience warming andpermafrost thaw. As source areas for geochemical fluxes to the broaderArctic hydrologic system, geochemical processes occurring in theseenvironments are particularly important to understand and predict withregards to such environmental changes. 

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. 

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate.