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  • Energy Research

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mariana García Criado; Isla H. Myers-Smith; Anne D. Bjorkman; Signe Normand; +37 Authors

    Climate change is leading to a species redistributions. In the tundra biome, many shrub species are expanding into new areas, a process known as shrubification. However, not all tundra shrub species will benefit from warming. Winner and loser species (those projected to expand and contract their ranges, and/or those that have increased or decreased in cover over time), and the characteristics that may determine success or failure, have not been fully identified. Here, we investigate whether current range sizes are related to plant trait values and intraspecific trait variation by combining 17,921 trait records and distribution data from 62 shrub species across three continents (>30 degrees north). In addition, we determine which traits are associated with species projected by species distribution models to expand or contract their ranges under climate change, and species that have undergone past cover changes over time. Winner and loser shrub species identified from projected range shifts generally differed from those identified from observed past cover change. We found that greater variation in seed mass and specific leaf area were related to larger projected range shifts. Projected winner species generally had greater seed mass values than ‘no change’ and loser species. However, contrary to our expectations, traits’ values and variation were not consistently related to current and projected ranges, and depended upon the future climate scenarios considered in range projections. There were no clear relationships either between cover change over time and trait values or variation. Overall, our findings indicate that abundance changes and projected range shifts will not lead to directional modifications in shrub trait composition or variation with future warming, since winner and loser species share relatively similar trait spaces based on commonly measured traits. Future research could investigate other morpho-physiological traits underpinning climatic preferences, which might better predict future range and abundance changes.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Nature Communication...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Communications
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Communications
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Communications
    Article . 2023
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Communications
    Article . 2022 . Peer-reviewed
    https://doi.org/10.32942/x23s3...
    Article . 2022 . Peer-reviewed
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Climate change in arctic tundra is projected to affect air temperature, snow depth, soil fertility, and caribou herbivory, which may alter plant community composition by shifting niche space to favor particular species’ life history strategies. We report responses of a Canadian mesic birch hummock tundra plant community to a range of manipulative experiments (greenhouse warming, fertilization, snow fence, and caribou exclosure treatments). Aboveground biomass of each plant species was measured in the same permanent 1 m2 areas using the point frame method in 2005, 2011, and 2017. Although the greenhouse treatment had few effects on individual species, total vascular plant community biomass was enhanced between 2011 and 2017. Furthermore, species’ biomass across all control plots was stable from 2005 to 2011 but increased significantly from 2011 to 2017, with air temperatures also warmer over that same period. Species responded to high-level nitrogen and high-level nitrogen and phosphorus combined additions, with deciduous shrubs and graminoids increasing and evergreen shrubs decreasing. The snow fences and caribou exclosures had little effect on species biomass. Although vegetation greening trends have been reported in arctic environments that are primarily influenced by maritime climate, our study is one of the first to provide plot-based evidence of recent plant biomass increases in the low Arctic’s continental interior.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Arctic, Antarctic, a...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Arctic, Antarctic, and Alpine Research
    Article . 2020 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Arctic, Antarctic, and Alpine Research
    Article
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Other literature type . 2020
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Other literature type . 2020
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Arctic, Antarctic, a...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Arctic, Antarctic, and Alpine Research
      Article . 2020 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Arctic, Antarctic, and Alpine Research
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Other literature type . 2020
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Other literature type . 2020
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • Authors: Berner, Logan T.; Orndahl, Kathleen M.; Rose, Melissa; Tamstorf, Mikkel; +53 Authors

    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 present The Arctic Plant Aboveground Biomass Synthesis Dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass grams per meter squared (g/m^2) on 2327 sample plots 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.

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  • Authors: Berner, Logan T.; Orndahl, Kathleen M.; Rose, Melissa; Tamstorf, Mikkel; +49 Authors

    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 present The Arctic Plant Aboveground Biomass Synthesis Dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass grams per meter squared (g/m^2) on 2327 sample plots 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.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    Recent climate warming in the Arctic is enhancing microbial decomposition of soil organic matter, which may result in globally significant greenhouse gas releases to the atmosphere. To better predict future impacts, bacterial and fungal community structures in both the bulk soil and the rhizosphere of Arctic birch, Betula glandulosa, were determined in control, greenhouse summer warming, and annual factorial nitrogen (N) and phosphate (P) addition treatments twelve years after their establishment. DNA sequence analyses at multiple taxonomic levels consistently indicated substantial bulk soil and rhizosphere microbial community differences among the fertilization treatments but no significant greenhouse effects. These results suggest that climate warming will likely increase the activity rates of soil microbial decomposers but without substantially altering the structure of either the bacterial or fungal communities. Differential abundance testing revealed changes in ectomycorrhizal fungal species of the genus Thelephora in both bulk soil and rhizosphere, with increases in their relative abundance in P and N + P amended plots compared with warming and controls. Because birch is the principal low Arctic ectomycorrhizal host, our results suggest that these fungi may promote this shrub’s competitiveness where tundra soil nutrient availability is enhanced by warming or other means, ultimately contributing to arctic vegetation “greening.”

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Smithsonian figsharearrow_drop_down
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    Arctic, Antarctic, and Alpine Research
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Arctic, Antarctic, and Alpine Research
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Smithsonian figsharearrow_drop_down
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      Arctic, Antarctic, and Alpine Research
      Article . 2021 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Arctic, Antarctic, and Alpine Research
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Other literature type . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Katariina Vuorinen; Gunnar Austrheim; Jean-Pierre Tremblay; Isla H. Myers-Smith; +37 Authors

    Abstract Global warming has pronounced effects on tundra vegetation, and rising mean temperatures increase plant growth potential across the Arctic biome. Herbivores may counteract the warming impacts by reducing plant growth, but the strength of this effect may depend on prevailing regional climatic conditions. To study how ungulates interact with temperature to influence growth of tundra shrubs across the Arctic tundra biome, we assembled dendroecological data from 20 sites, comprising 1,153 individual shrubs and 22,363 annual growth rings. Evidence for ungulates suppressing shrub radial growth was only observed at intermediate summer temperatures (6.5-9°C), and even at these temperatures the effect was not strong. Multiple factors, including forage preferences and landscape use by the ungulates, and favourable climatic conditions enabling effective compensatory growth of shrubs, may weaken the effects of ungulates on shrubs, possibly explaining the weakness of observed ungulate effects. Earlier local studies have shown that ungulates may counteract the impacts of warming on tundra shrub growth, but we demonstrate that ungulates’ potential to suppress shrub radial growth is not always evident, and may be limited to certain climatic conditions. 

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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
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    Environmental Research Letters
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    Environmental Research Letters
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    Research@WUR
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    Wageningen Staff Publications
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    Munin - Open Research Archive
    Article . 2022 . Peer-reviewed
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    Environmental Research Letters
    Article . 2022 . Peer-reviewed
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      Wageningen Staff Publications
      Article . 2022
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      Munin - Open Research Archive
      Article . 2022 . Peer-reviewed
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  • Authors: Orndahl, Kathleen M.; Berner, Logan T.; Macander, Matthew J.; Arndal, Marie F.; +45 Authors

    This dataset provides estimates of live, oven-dried aboveground biomass of all plants (tree, shrub, graminoid, forb, bryophyte) and all woody plants (tree, shrub) at 30-meter resolution across the Arctic tundra biome. Estimates of woody plant dominance are also provided as: (woody plant biomass / plant biomass) * 100. Plant biomass and woody plant biomass were estimated for each pixel (grams per square meter [g / m2]) using field harvest data for calibration/validation along with modeled seasonal surface reflectance data derived using Landsat satellite imagery and the Continuous Change Detection and Classification algorithm, and other supplementary predictors related to topography, region (e.g. bioclimate zone, ecosystem type), land cover, and derivative spectral products. Modeling was performed in a two-stage process using random forest models. First, biomass presence/absence was predicted using probability forests. Then, biomass quantity was predicted using regression forests. The model outputs were combined to produce final biomass estimates. Pixel uncertainty was assessed using Monte Carlo iterations. Field and remote sensing data were permuted during each iteration and the median (50th percentile, p500) predictions for each pixel were considered best estimates. In addition, this dataset provides the lower (2.5th percentile, p025) and upper (97.5th percentile, p975) bounds of a 95% uncertainty interval. Estimates of woody plant dominance are not modeled directly, but rather derived from plant biomass and woody plant biomass best estimates. The Pan Arctic domain includes both the Polar Arctic, defined using bioclimate zone data from the Circumpolar Arctic Vegetation Mapping Project (CAVM; Walker et al., 2005), and the Oro Arctic (treeless alpine tundra at high latitudes outside the Polar Arctic), defined using tundra ecoregions from the RESOLVE ecoregions dataset (Dinerstein et al., 2017) and treeline data from CAVM (CAVM Team, 2003). The mapped products focus on Arctic tundra vegetation biomass, but the coarse delineation of this biome meant some forested areas were included within the study domain. Therefore, this dataset also provides a tree mask product that can be used to mask out areas with canopy height ≥ 5 meters. This mask helps reduce, but does not eliminate entirely, areas of dense tree cover within the domain. Users should be cautious of predictions in forested areas as the models used to predict biomass were not well constrained in these areas. This dataset includes 132 files: 128 cloud-optimized GeoTIFFs, 2 tables in comma-separated values (CSV) format, 1 vector polygon in Shapefile format, and one figure in JPEG format. Raster data is provided in the WGS 84 / North Pole LAEA Bering Sea projection (EPSG:3571) at 30 meter (m) resolution. Raster data are tiled with letters representing rows and numbers representing columns, but note that some tiles do not contain unmasked pixels. We included all tiles nonetheless to maintain consistency. Tiling information can be found in the ‘metadata’ directory as a figure (JPEG) or shapefile.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mariana García Criado; Isla H. Myers-Smith; Anne D. Bjorkman; Signe Normand; +37 Authors

    Climate change is leading to a species redistributions. In the tundra biome, many shrub species are expanding into new areas, a process known as shrubification. However, not all tundra shrub species will benefit from warming. Winner and loser species (those projected to expand and contract their ranges, and/or those that have increased or decreased in cover over time), and the characteristics that may determine success or failure, have not been fully identified. Here, we investigate whether current range sizes are related to plant trait values and intraspecific trait variation by combining 17,921 trait records and distribution data from 62 shrub species across three continents (>30 degrees north). In addition, we determine which traits are associated with species projected by species distribution models to expand or contract their ranges under climate change, and species that have undergone past cover changes over time. Winner and loser shrub species identified from projected range shifts generally differed from those identified from observed past cover change. We found that greater variation in seed mass and specific leaf area were related to larger projected range shifts. Projected winner species generally had greater seed mass values than ‘no change’ and loser species. However, contrary to our expectations, traits’ values and variation were not consistently related to current and projected ranges, and depended upon the future climate scenarios considered in range projections. There were no clear relationships either between cover change over time and trait values or variation. Overall, our findings indicate that abundance changes and projected range shifts will not lead to directional modifications in shrub trait composition or variation with future warming, since winner and loser species share relatively similar trait spaces based on commonly measured traits. Future research could investigate other morpho-physiological traits underpinning climatic preferences, which might better predict future range and abundance changes.

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    Nature Communications
    Article . 2023 . Peer-reviewed
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    Nature Communications
    Article . 2023
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    Nature Communications
    Article . 2023
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Nature Communications
    Article . 2022 . Peer-reviewed
    https://doi.org/10.32942/x23s3...
    Article . 2022 . Peer-reviewed
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    Climate change in arctic tundra is projected to affect air temperature, snow depth, soil fertility, and caribou herbivory, which may alter plant community composition by shifting niche space to favor particular species’ life history strategies. We report responses of a Canadian mesic birch hummock tundra plant community to a range of manipulative experiments (greenhouse warming, fertilization, snow fence, and caribou exclosure treatments). Aboveground biomass of each plant species was measured in the same permanent 1 m2 areas using the point frame method in 2005, 2011, and 2017. Although the greenhouse treatment had few effects on individual species, total vascular plant community biomass was enhanced between 2011 and 2017. Furthermore, species’ biomass across all control plots was stable from 2005 to 2011 but increased significantly from 2011 to 2017, with air temperatures also warmer over that same period. Species responded to high-level nitrogen and high-level nitrogen and phosphorus combined additions, with deciduous shrubs and graminoids increasing and evergreen shrubs decreasing. The snow fences and caribou exclosures had little effect on species biomass. Although vegetation greening trends have been reported in arctic environments that are primarily influenced by maritime climate, our study is one of the first to provide plot-based evidence of recent plant biomass increases in the low Arctic’s continental interior.

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    Arctic, Antarctic, and Alpine Research
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    Arctic, Antarctic, and Alpine Research
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  • Authors: Berner, Logan T.; Orndahl, Kathleen M.; Rose, Melissa; Tamstorf, Mikkel; +53 Authors

    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 present The Arctic Plant Aboveground Biomass Synthesis Dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass grams per meter squared (g/m^2) on 2327 sample plots 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.

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  • Authors: Berner, Logan T.; Orndahl, Kathleen M.; Rose, Melissa; Tamstorf, Mikkel; +49 Authors

    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 present The Arctic Plant Aboveground Biomass Synthesis Dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass grams per meter squared (g/m^2) on 2327 sample plots 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.

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    Recent climate warming in the Arctic is enhancing microbial decomposition of soil organic matter, which may result in globally significant greenhouse gas releases to the atmosphere. To better predict future impacts, bacterial and fungal community structures in both the bulk soil and the rhizosphere of Arctic birch, Betula glandulosa, were determined in control, greenhouse summer warming, and annual factorial nitrogen (N) and phosphate (P) addition treatments twelve years after their establishment. DNA sequence analyses at multiple taxonomic levels consistently indicated substantial bulk soil and rhizosphere microbial community differences among the fertilization treatments but no significant greenhouse effects. These results suggest that climate warming will likely increase the activity rates of soil microbial decomposers but without substantially altering the structure of either the bacterial or fungal communities. Differential abundance testing revealed changes in ectomycorrhizal fungal species of the genus Thelephora in both bulk soil and rhizosphere, with increases in their relative abundance in P and N + P amended plots compared with warming and controls. Because birch is the principal low Arctic ectomycorrhizal host, our results suggest that these fungi may promote this shrub’s competitiveness where tundra soil nutrient availability is enhanced by warming or other means, ultimately contributing to arctic vegetation “greening.”

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    Arctic, Antarctic, and Alpine Research
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    Authors: Katariina Vuorinen; Gunnar Austrheim; Jean-Pierre Tremblay; Isla H. Myers-Smith; +37 Authors

    Abstract Global warming has pronounced effects on tundra vegetation, and rising mean temperatures increase plant growth potential across the Arctic biome. Herbivores may counteract the warming impacts by reducing plant growth, but the strength of this effect may depend on prevailing regional climatic conditions. To study how ungulates interact with temperature to influence growth of tundra shrubs across the Arctic tundra biome, we assembled dendroecological data from 20 sites, comprising 1,153 individual shrubs and 22,363 annual growth rings. Evidence for ungulates suppressing shrub radial growth was only observed at intermediate summer temperatures (6.5-9°C), and even at these temperatures the effect was not strong. Multiple factors, including forage preferences and landscape use by the ungulates, and favourable climatic conditions enabling effective compensatory growth of shrubs, may weaken the effects of ungulates on shrubs, possibly explaining the weakness of observed ungulate effects. Earlier local studies have shown that ungulates may counteract the impacts of warming on tundra shrub growth, but we demonstrate that ungulates’ potential to suppress shrub radial growth is not always evident, and may be limited to certain climatic conditions. 

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    Environmental Research Letters
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    Wageningen Staff Publications
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    Munin - Open Research Archive
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    Environmental Research Letters
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  • Authors: Orndahl, Kathleen M.; Berner, Logan T.; Macander, Matthew J.; Arndal, Marie F.; +45 Authors

    This dataset provides estimates of live, oven-dried aboveground biomass of all plants (tree, shrub, graminoid, forb, bryophyte) and all woody plants (tree, shrub) at 30-meter resolution across the Arctic tundra biome. Estimates of woody plant dominance are also provided as: (woody plant biomass / plant biomass) * 100. Plant biomass and woody plant biomass were estimated for each pixel (grams per square meter [g / m2]) using field harvest data for calibration/validation along with modeled seasonal surface reflectance data derived using Landsat satellite imagery and the Continuous Change Detection and Classification algorithm, and other supplementary predictors related to topography, region (e.g. bioclimate zone, ecosystem type), land cover, and derivative spectral products. Modeling was performed in a two-stage process using random forest models. First, biomass presence/absence was predicted using probability forests. Then, biomass quantity was predicted using regression forests. The model outputs were combined to produce final biomass estimates. Pixel uncertainty was assessed using Monte Carlo iterations. Field and remote sensing data were permuted during each iteration and the median (50th percentile, p500) predictions for each pixel were considered best estimates. In addition, this dataset provides the lower (2.5th percentile, p025) and upper (97.5th percentile, p975) bounds of a 95% uncertainty interval. Estimates of woody plant dominance are not modeled directly, but rather derived from plant biomass and woody plant biomass best estimates. The Pan Arctic domain includes both the Polar Arctic, defined using bioclimate zone data from the Circumpolar Arctic Vegetation Mapping Project (CAVM; Walker et al., 2005), and the Oro Arctic (treeless alpine tundra at high latitudes outside the Polar Arctic), defined using tundra ecoregions from the RESOLVE ecoregions dataset (Dinerstein et al., 2017) and treeline data from CAVM (CAVM Team, 2003). The mapped products focus on Arctic tundra vegetation biomass, but the coarse delineation of this biome meant some forested areas were included within the study domain. Therefore, this dataset also provides a tree mask product that can be used to mask out areas with canopy height ≥ 5 meters. This mask helps reduce, but does not eliminate entirely, areas of dense tree cover within the domain. Users should be cautious of predictions in forested areas as the models used to predict biomass were not well constrained in these areas. This dataset includes 132 files: 128 cloud-optimized GeoTIFFs, 2 tables in comma-separated values (CSV) format, 1 vector polygon in Shapefile format, and one figure in JPEG format. Raster data is provided in the WGS 84 / North Pole LAEA Bering Sea projection (EPSG:3571) at 30 meter (m) resolution. Raster data are tiled with letters representing rows and numbers representing columns, but note that some tiles do not contain unmasked pixels. We included all tiles nonetheless to maintain consistency. Tiling information can be found in the ‘metadata’ directory as a figure (JPEG) or shapefile.

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