Predicting suitable locations for invasive alien terrestrial vertebrates (IATV) under different scenarios of global change is essential for local and transboundary management aimed to prevent the spread of invasions. Using a spatial modelling approach adapted to invasive species, we identify range-shifts in suitable areas for 15 of the most harmful IATV in Europe, considering future climate and land-use changes. We predict range contractions for seven of these IATV, expansion for four, and inconclusive outputs for the rest. For most Europe, future aggregated distributions show stable or decreasing trends in total IATV richness. Still, specific regions will increase their suitability for additional IATVs, including some protected and last-of-the-wild areas. Our results are informative for early decision-making and long-term strategies to prevent negative effects of IATV. Our approach is based on publicly available data, so predictions can be revised as new data becomes available.

This dataset includes an R-script that navigates through the data collection, filtering, organization and model fitting. All data required by this script are included in the dataset.

This dataset was used to produce the paper: "The future of invasive terrestrial vertebrates in Europe under climate and land-use change," published in Environmental Research Letters.

GENERAL INFORMATION

1. Title of Dataset: "Data from: The future of invasive terrestrial vertebrates in Europe under climate and land-use change"

2. Author Information

    A. Principal Investigator Contact Information
        Name: Mariano R. Recio    
        Institution: Rey Juan Carlos University, Biodiversity and Conservation Unit
        Address: C/ Tulipán s/n, 28933, Móstoles (Madrid), Spain
        Email: mariano.recio@gmail.com

    B. Author responsible for data manipulation:
        Name: Ester Polaina
        Institution: Swedish University of Agricultural Sciences, Department of Ecology
        Address: Ulls Väg 16, 75007, Uppsala, Sweden
        Email: e.polaina@gmail.com

3. Date of data collection & other useful information: Data were downloaded between September 2018 and January 2019. All data are available from the original source at the original resolution. Here we only include processed data according to the working resolution of the article. 

SHARING/ACCESS INFORMATION

1. Was data derived from another source? YES

2. Data sources & links:

- CHELSA. Climatologies at high resolution for the Earth's land surface areas (http://chelsaclimate.org/).

- Land use harmonization 2 (http://luh.umd.edu/data.shtml).

- Natural Earth (https://www.naturalearthdata.co m/downloads/10m-physicalvectors/10m-rivers-lakecenterlines/). 

- Corine Land Cover (https://land.copernicus.eu/paneuropean/corine-land-cover/lcc-2012-2018)

- GTOPO30. Digital elevation model (https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-global-30-arc-second-elevation-gtopo30?qt science_center_objects=0#qt-science_center_objects)

- Accesibility, travel time to major cities: A global map of accesibility. Joint Research Center. The European Comission's science and knowledge service (https://forobs.jrc.ec.europa.eu/products/gam/download.php)

- GBIF. www.gbif.org

Please check the R script included in this folder ("Polaina_et_al_2021_ERL.r") for additional information on data used and model fitting. 

DATA & FILE OVERVIEW

1. File List: 

- eu_ref_raster.tif. Reference raster with a grid resolution of 0.25×0.25º covering the following countries: Albania, Andorra, Austria, Belgium, Bosnia & Herzegovina, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxemburg, Malta, Moldova, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland and United Kingdom. 

- Ref_raster.7z. Reference raster with a grid resolution of 0.25×0.25º covering the whole world. 

- Accesibility.7z. Travel time to major cities using land or water based travel (>50,000 people). Raster format. Data averaged from the original data source resolution (30 arc-sec) to the 0.25×0.25º reference raster ("eu_ref_raster.tif").

- CHELSA_clim.7z. This folder includes 19 bioclimatic variables in raster format for 3 different time periods. Variables: annual mean temperature (bio1) , mean diurnal range (bio2), isothermality (bio3), temperature seasonality (bio4), maximum temperature of the warmest month (bio5), minimum temperature of the coldest month (bio6), temperature annual range (bio7), mean temperature of the wettest quarter (bio8), mean temperature of the driest quarter (bio9), mean temperature of the warmest quarter (bio10), meean temperature of the coldest quarter (bio11), annual precipitation (bio12), precipitation of the wettest month (bio13), precipitation of the driest month (bio14), precipitation seasonality (bio15), precipitation of the wettest quarter (bio16), precipitation of the driest quarter (bio17), precipitation of the warmest quarter (bio18), precipitation of the coldest quarter (bio19).

The "CHELSA_tech_specification.pdf" document includes details from the original source. The folder "resampled_30k" includes the mentioned variables (one raster per variable) corresponding to the Present time period (average 1979-2013), averaged from the original data source resolution (30 arc-sec) to the 0.25×0.25º reference raster ("eu_ref_raster.tif"). The folder "Future" includes two subfolders ("new_2050" and "new_2070") including the same variables and using the same spatial resolution, corresponding to the time periods Future 2050 (average of the period 2041-2060) and Future 2070 (average of the period 2061-2080). Suffixes correspond to different RCPs (2.6, 4.5, 6.0 and 8.5) and GCMs (MIROC5, IPSL.CM5A.MR, GISS.E2.H, FIO.ESM and CESM1.CAM5).

- Coastline.7z. This folder includes a single layer calculated as the distance from the centroid of each grid cell from the reference raster ("eu_ref_raster.tif").

- GTOPO30.7z. This folder includes the average and standard elevation of elevation per grid cell over the 0.25×0.25º reference raster ("eu_ref_raster.tif"), based on the digital elevation model GTOPO30 (30 arc-sec, original resolution). 

- Hydro.7z. This folder includes two raster layers "waterbodies_europe.tif" and "rivers_europe.tif". "waterbodies_europe.tif" was resampled to the 0.25×0.25º reference raster ("eu_ref_raster.tif") from the original Corine dataset (100x100m spatial resolution). "rivers_europe.tif" was averaged over the 0.25×0.25º reference raster ("eu_ref_raster.tif") based on the original shapefile from Natural Earth, and expressed in km/grid-cell. 

- Invasive_spp_to_use.csv. This file is the list of latin names of the species used in the original study to model range shifts. 

- LUH.7z. This folder includes 8 land-use variables (one raster per variable), expressed as the proportion of grid-cell covered by each category. The categories are forested primary land, non-forested primary land, potentially forested secondary land, potentially non-forested secondary land, urban, managed pasture, rangeland and cropland. Crop categories were added in a single category (see "Polaina_et_al_2021_ERL.r" for details). Future folder contains two sub-folders ("2050", average of the period 2041-2060; and "2070", average of the period 2061-2080) including 4 sub-folders each (named "rcp26", "rcp45", "rcp60" and "rcp85") with information on the mentioned land-use categories for each RCP scenario. All files outside the "Future" folder correspond to the Present dataset (2015). The original resolution matched the 0.25×0.25º working resolution. 

- Occ_vs_pres.7z. This folder contains the ocurrences of the species Oxyura jamaicensis and Branta canadensis, without filtering. From gbif.org (see "Polaina_et_al_2021_ERL.r" for further details).

- Polaina_et_al_2021_ERL.r. This is an r script that includes the workflow of the article "The future of invasive terrestrial vertebrates in Europe under climate and land-use change", published in Environmental Research Letters. It includes all steps of analises and additional information on data manipulation.

METHODOLOGICAL INFORMATION

Please check the R script included in this folder for additional information on data used and model fitting.