Spatial, environmental and landscape variables
The 16 predictor variables included in the study were (see Appendix A1):
- Spatial : LAT: mid-gridcell latitude (°absolute); ALT: area of
high altitude land per gridcell as % gridcell area >1000
m above sea level, a.s.l.;
- Environmental : ET0 (mm): potential evapotranspiration; AI
(ratio between precipitation and ET0 × 10,000): aridity index; TYR
(°C): average annual temperature; TMX (°C): maximum temperature of
warmest month; TRG (°C): maximum temperature of warmest month –
minimum temperature of coldest month; TDRY (°C): average temperature
of driest quarter; PCP (mm): annual precipitation; PCPDR (mm):
precipitation of driest quarter; PCPS: precipitation seasonality
(coefficient of variation of monthly precipitation); CCV (m
year-1): historic (Late Quaternary) climate change
velocity;
- Landscape : grAH (km2): area of aquatic
habitat present per gridcell; CROP (% agricultural land cover per
gridcell);
- Biotic : Stot: total macrophyte species
richness; Send: species richness of ecozone-endemic
macrophytes, both as number of species per gridcell.
Climate variables were obtained from the Bioclim project source
(www.worldclim.org/data/bioclim.html) and downloaded at 30 arc-seconds
resolution, except for ET0 and AI, which were obtained from Trabucco and
Zomer (2019), who derived them (also 30 arc-seconds resolution) from the
Worldclim dataset; CCV spatial dataset was obtained from Sandel et al.
(2019); water (grAH) and agricultural (CROP) cover data from the USGS
Global Land Cover Characterization (GLCC,
https://doi.org/10.5066/F7GB230D), and altitude from the USGS Global
Multi-Resolution Terrain Elevation Data 2010
(https://topotools.cr.usgs.gov/GMTED_viewer/). Mean, median and
standard deviation for climate variables per gridcell were obtained
using a 10° gridcell shapefile and the Zonal statistics tool in QGIS
(version 3.4.9-Madeira). The area occupied by each agricultural land use
category (and subsequently total agricultural land cover) per gridcell
was obtained using the above-mentioned shapefile and the Zonal Histogram
tool in the ArcMap™ Spatial Analyst toolbox using ArcMap™ v. 9.3.1, see
Murphy et al. (2019, 2020) for further details. All-species richness and
ecozone-endemic species richness values were obtained from Murphy et al.
(2019).