Plant traits and associated data from a warming experiment, a seabird colony, and along elevation in Svalbard

Vigdis Vandvik, Aud H. Halbritter, Inge H.J. Althuizen, Casper T. Christiansen, Jonathan J. Henn, Ingibjörg Svala Jónsdóttir, Kari Klanderud, Marc Macias-Fauria, Yadvinder Malhi, Brian Salvin Maitner, Sean Michaletz, Ruben E. Roos, Richard J. Telford, Polly Bass, Katrín Björnsdóttir, Lucely Lucero Vilca Bustamante, Adam Chmurzynski, Shuli Chen, Siri Vatsø Haugum, Julia KemppinenKai Lepley, Yaoqi Li, Mary Linabury, Ilaíne Silveira Matos, Barbara M. Neto-Bradley, Molly Ng, Pekka Niittynen, Silje Östman, Karolína Pánková, Nina Roth, Matiss Castorena, Marcus Spiegel, Eleanor Thomson, Alexander Sæle Vågenes, Brian J. Enquist

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The 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.

Original languageEnglish (US)
Article number578
JournalScientific Data
Volume10
Issue number1
DOIs
StatePublished - Dec 2023

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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