Plant traits and associated data from a warming experiment, a seabird colony, and along elevation in Svalbard
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Published:2023-09-04
Issue:1
Volume:10
Page:
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ISSN:2052-4463
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Container-title:Scientific Data
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language:en
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Short-container-title:Sci Data
Author:
Vandvik VigdisORCID, Halbritter Aud H.ORCID, Althuizen Inge H. J.ORCID, Christiansen Casper T., Henn Jonathan J.ORCID, Jónsdóttir Ingibjörg SvalaORCID, Klanderud KariORCID, Macias-Fauria Marc, Malhi YadvinderORCID, Maitner Brian SalvinORCID, Michaletz SeanORCID, Roos Ruben E., Telford Richard J.ORCID, Bass Polly, Björnsdóttir Katrín, Bustamante Lucely Lucero Vilca, Chmurzynski Adam, Chen Shuli, Haugum Siri Vatsø, Kemppinen JuliaORCID, Lepley KaiORCID, Li Yaoqi, Linabury Mary, Matos Ilaíne SilveiraORCID, Neto-Bradley Barbara M.ORCID, Ng MollyORCID, Niittynen Pekka, Östman Silje, Pánková Karolína, Roth NinaORCID, Castorena Matiss, Spiegel MarcusORCID, Thomson Eleanor, Vågenes Alexander Sæle, Enquist Brian J.ORCID
Abstract
AbstractThe Arctic is warming at a rate four times the global average, while also being exposed to other global environmental changes, resulting in widespread vegetation and ecosystem change. Integrating functional trait-based approaches with multi-level vegetation, ecosystem, and landscape data enables a holistic understanding of the drivers and consequences of these changes. In two High Arctic study systems near Longyearbyen, Svalbard, a 20-year ITEX warming experiment and elevational gradients with and without nutrient input from nesting seabirds, we collected data on vegetation composition and structure, plant functional traits, ecosystem fluxes, multispectral remote sensing, and microclimate. The dataset contains 1,962 plant records and 16,160 trait measurements from 34 vascular plant taxa, for 9 of which these are the first published trait data. By integrating these comprehensive data, we bridge knowledge gaps and expand trait data coverage, including on intraspecific trait variation. These data can offer insights into ecosystem functioning and provide baselines to assess climate and environmental change impacts. Such knowledge is crucial for effective conservation and management in these vulnerable regions.
Funder
Senter for Internasjonalisering av Utdanning
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Reference68 articles.
1. Rantanen, M. et al. The Arctic has warmed nearly four times faster than the globe since 1979. Communications Earth & Environment 3, 1–10 (2022). 2. IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (ed. Masson-Delmotte, V., et al (Cambridge University Press, 2021). 3. Paleczny, M., Hammill, E., Karpouzi, V. & Pauly, D. Population Trend of the World’s Monitored Seabirds, 1950–2010. PLoS One 10, e0129342 (2015). 4. Dias, M. P. et al. Threats to seabirds: A global assessment. Biol. Conserv. 237, 525–537 (2019). 5. Jónsdóttir, I. S. et al. Intraspecific trait variability is a key feature underlying high Arctic plant community resistance to climate warming. Ecol. Monogr. e1555, 1–21 (2022).
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