Plant traits and associated ecological data from global change experiments and climate gradients in Norway

Plant functional trait-based approaches are powerful tools to assess the consequences of global environmental changes for plant ecophysiology, population and community ecology, ecosystem functioning, and landscape ecology. Here, we present data capturing these ecological dimensions from grazing, nitrogen addition, and warming experiments conducted along a 821 m a.s.l. elevation gradient and from a climate warming experiment conducted across a 3,200 mm precipitation gradient in boreal and alpine grasslands in Vestland County, western Norway. From these systems we collected 28,762 plant and leaf functional trait measurements from 76 vascular plant species, 88 leaf assimilation-temperature responses, 577 leaf handheld hyperspectral readings, 2.26 billion leaf temperature measurements, 3,696 ecosystem CO<sub>2</sub> flux measurements, and 10.69 ha of multispectral (10-band) and RGB cm-resolution imagery from 4,648 individual images obtained from airborne sensors. These data augment existing longer-term data on local climate, soils, plant populations, plant community composition, and ecosystem functioning from within the same experiments and study systems and from similar systems in other mountain regions globally.

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Publication Details

Journal
Scientific Data
Published
2025-08-25
DOI
https://doi.org/10.1038/s41597-025-05509-4
Citations
6
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
10.30

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article

Plant traits and associated ecological data from global change experiments and climate gradients in Norway

Sam J. Ahler, Courtenay A. Ray, Joseph Gaudard, Josef C. Garen et al.
6 citations
Scientific Data
Remote Sensing in Agriculture
10.30
article

Plant traits and associated ecological data from global change experiments and climate gradients in Norway

Sam J. Ahler, Courtenay A. Ray, Joseph Gaudard, Josef C. Garen, Aud H. Halbritter, Richard J. Telford, Dickson Gerald Mauki, Hilary Rose Dawson, Brian Joseph Enquist, Jonathan Wang, Jocelyn Navarro, Ragnhild Gya, Marta Correia, Kai Lepley, Vigdis Vandvik, Jonathan von Oppen, Tom Vorstenbosch, Dagmar Egelkraut, Celesté Maré, Joshua Erkelenz, Sonya R. Geange, Julia Chacón‐Labella, Emil Alexander Sherman Andersen, Brian Maitner, Alyssa Olson, Joe Atkinson, Sean T. Michaletz, Sehoya Cotner, Julia Eckberg, Marc Macias‐Fauria, Alexander Elsy, Meghan T. Hayden, Alyssa T. Kullberg, Bernard Olivier, Mukhlish Jamal Musa Holle, Pia M. Bradler, Coşkun Güçlü, Sorrel Hartford, Susan E. Eshelman, Nicole Bison, Barryette Oberholzer, Rebekka Gullvåg, Marta Baumane, Maria A. Rosati, Cora Ena Löwenstein
article en
6 citations

Abstract

Plant functional trait-based approaches are powerful tools to assess the consequences of global environmental changes for plant ecophysiology, population and community ecology, ecosystem functioning, and landscape ecology. Here, we present data capturing these ecological dimensions from grazing, nitrogen addition, and warming experiments conducted along a 821 m a.s.l. elevation gradient and from a climate warming experiment conducted across a 3,200 mm precipitation gradient in boreal and alpine grasslands in Vestland County, western Norway. From these systems we collected 28,762 plant and leaf functional trait measurements from 76 vascular plant species, 88 leaf assimilation-temperature responses, 577 leaf handheld hyperspectral readings, 2.26 billion leaf temperature measurements, 3,696 ecosystem CO<sub>2</sub> flux measurements, and 10.69 ha of multispectral (10-band) and RGB cm-resolution imagery from 4,648 individual images obtained from airborne sensors. These data augment existing longer-term data on local climate, soils, plant populations, plant community composition, and ecosystem functioning from within the same experiments and study systems and from similar systems in other mountain regions globally.

Scientific DataVol. 12(1)
Leuphana University of Lüneburg (DE), Australian National University (AU), University of Copenhagen (DK), University of Wyoming (US), University of Vienna (AT), University of Minnesota (US), Santa Fe Institute (US), University of Arizona (US), University of British Columbia (CA), University of Miami (US), Universitas Gadjah Mada (ID), University of Oregon (US), Institute of Arctic and Alpine Research (US), University of Basel (CH), University of Colorado Boulder (US), Aarhus University (DK), Masaryk University (CZ), University of Utah (US), University of Michigan (US), Bjerknes Centre for Climate Research (NO), UNSW Sydney (AU), ETH Zurich (CH), Institute of Forest Ecology of the Slovak Academy of Sciences (SK), Bridge University (SS), Senckenberg Biodiversity and Climate Research Centre (DE), Centre for Immunity, Infection and Evolution (GB), University of Bergen (NO), Universidad Autónoma de Madrid (ES), University of Coimbra (PT), Technische Universität Dresden (DE), University of Hong Kong (HK), Umeå University (SE), BOKU University (AT)
Universitetet i Bergen, Norges Forskningsråd, Senter for Internasjonalisering av Utdanning
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
10.30
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