Climatic and land-use variables, present and future scenarios
To avoid possible mismatches between observations and climatic
variables, we excluded from the analysis the records before 1970 and
those without date (time range: 1970-2018, but for konradini1960-2020 due to the few data available). Three different categories of
possible environmental drivers were considered: climate, topography, and
land-use/land-cover (LULC). Climatic variables were derived from the
database CHELSA V2.1 (Karger et al. 2017, 2021), and were the following
ones: mean annual 2-m air temperature, annual range in 2-m air
temperature, sum of annual precipitation, precipitation seasonality
(Thuiller et al. 2019), all calculated for the period 1981–2010.
Topographic variables were computed starting from a fine-scale digital
elevation model (25 m-resolution; EU-DEM v1.0, publicly available from
the European Environment Agency). Finally, LULC variables were obtained
from the CORINE land cover map (Corine Land Cover — European
Environment Agency , 2018). All variables were then estimated for 1 × 1
km2 cells, as average values (climate and topograhy),
or as proportional cover (LULC). When needed (climatic variables),
raster resampling was carried out by bilinear interpolation. LULC
categories with negligible cover were excluded, while some other
categories poorly represented were merged (Supporting text A2). The
variables so worked out showed relatively modest correlations (r
< |.7|; Grimmett et al. 2020).
To describe possible alternative future climates on the medium-term, we
relied on the downscaled CMIP6 (Coupled Model Intercomparison Project
Phase 6) data, choosing the period 2041–2070, and two alternative
climate models (a ‘warmer’ one and a ‘colder’ alternative) as provided
by ISIMIP (Intersectoral Impact model Intercomparison Project;
Warszawski et al., 2014): GFDL-ESM4 and UKESM1-0-LL. Those data are
tailored for such a kind of application. For both climate models, we
picked the ‘worst case’ scenario SSP585 and the moderate change one
SSP370 (Eyring et al. 2016). Therefore, we based our assessment on four
alternative climatic conditions for the future, based on the combination
between two very different climate models and on two different
scenarios. Also those data were retrieved from the CHELSA V 2.1
database.