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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Biogeogra...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Biogeography
Article . 2018 . Peer-reviewed
License: Wiley Online Library User Agreement
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Forecasted homogenization of high Arctic vegetation communities under climate change

Authors: Lærke Stewart; Caroline E. Simonsen; Jens‐Christian Svenning; Niels Martin Schmidt; Loïc Pellissier;

Forecasted homogenization of high Arctic vegetation communities under climate change

Abstract

AbstractAimClimate change results in increasing temperature and modified precipitation regimes in the High Arctic. Models can help anticipate the consequences on future biotic dynamics, e.g. vegetation. In rugged terrain, forecasts should consider fine‐scale spatial variability in environmental conditions that are proximally linked to plant performance. Here, we forecasted Arctic plant community response to future climate change using high‐resolution environmental variables.LocationZackenberg in the High Arctic of Greenland.MethodsUsing a combination of remote‐sensing data and field measurements, we interpolated soil moisture and temperature at 1 m resolution together with spatial data on snow cover and solar radiation. We calibrated stacked species distribution models (S‐SDMs) with data from 200 vegetation plots. To explore the sensitivity of Arctic communities to climate change, we forecasted these models under simulated increases in temperature and changes (positive or negative) in snow cover and soil moisture, corresponding to more winter and/or summer precipitation and higher frequencies of summer droughts.ResultsS‐SDMs associated with high‐resolution environmental variables were able to reproduce the spatial variation in species richness and plant community structure along a mountain slope in Zackenberg. Model forecasts under climate change revealed that most species reacted to a combination of changes in soil moisture and temperature, and changes in these two variables resulted in an extensive restructuring of the distributions of species assemblages. In most scenarios, a gradual homogenization of communities was forecasted due to shrub expansion.Main conclusionsIncreasing temperatures and altered soil moisture were predicted to turn the currently highly heterogeneous tundra landscape at Zackenberg into homogenous dwarf‐shrub tundra. Such homogenization of vegetation communities may have profound ramifications for species, interaction webs, and ecosystem processes via modifications to the surface albedo, energy and water balance, as well as snow accumulation and permafrost.

Keywords

climate change, model forecasts, vegetation, soil moisture, species distribution modelling, plant communities

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    27
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    Top 10%
    influence
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    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Average
Top 10%