Increase in tundra productivity in Sweden is not related to thermophilization of vascular plant communities: Data, codes and supplementary material

The material stored on this repository refers to the publication “Increase in plant productivity in the tundra in Sweden is not related to increasing presence of warm-adapted vascular plant species”, currently accepted for publication in Ecography (May 2026). Here, we provide data and codes to reproduce the analysis, as well as additional supplementary material that is not included in the manuscript. Content: 1) Codes and data to reproduce the analyses on vegetation dynamics and environmental indicators (Vegetation analysis.zip) 2) Codes and data to reproduce the analyses on NDVI (NDVI analysis.zip) 3) Supplementary tables and figures (Supplemenatry material to Horstkotte T.docx) 4) Supplementary methods on NDVI analyses (NDVI.docx) Description of the data and file structure Data descriptionThe data included contain files to reproduce the analysis. Data are all publicly available from online data sources. These include: a) Vegetation survey data from the monitoring program NILS , funded by the Swedish Environmental Protection Agency and curated by the Swedish University of Agricultural Sciences. The Swedish mountain area can be accessed at (in Swedish): https://landskap.slu.se/nils/dv b) Environmental indicators for plant speciesIndicator values for Swedish plants and cryptogams are accessible from: Tyler, T., Herbertsson, L., Olofsson, J., & Olsson, P. A. (2021): Ecological indicator and traits values for Swedish vascular plants. Ecological Indicators, 120, 106923. https://doi.org/10.1016/j.ecolind.2020.106923 c) Climate data (monthly time series) used in the vegetation analysis are available at:https://chelsa-climate.org/timeseries/ d) NDVI data are retrieved as Landsat 5, 7 and 8 Collection 2 Surface Reflectance products (30 m resolution) Codes use the LandsatTS R package version 12.2 (Berner et al. 2023), for data retrieval from the Google Earth Engine. Codes are in R language, with the necessary files provided to run the code. These files are csv.-files, shp.-files.These are divided into two folders, that largely correspond to the analysis as described in the manuscript:1) NDVI analysisContains necessary codes and files to run the NDVI analysis. 2) Vegetation analysisContains necessary codes and files to run the vegetation analysis. Description of statistcal software All data analysis is run in R, version 4.4.1.The following packages (libraries) are used for the analysis: Data manipulation and organization dplyrdata.tabletidyrpurrr # functional programmingR.utils # Various Programming Utilities Spatial data and visualizationrastersfleafletcolorspacegtlsatTS # Analysis of LandSat datargee # Google Earth Engine for R Plotting ggplot2ggpubrviridisRColorBrewersjPlotcowplotpatchworkgrid Statistical modelingnlme # Generalized Least Squares regressionlme4 # Linear and GLMMsDHARMa # Residual diagnostics for GLMMscaret # model tuningforecast # Time series analysis