Climate, topography and productivity data
We extracted different sets of current climate data for two purposes:
(i) to test the prediction that climate variability and drought would
influence the use of shelters by arthropods at the experiment scale, and
(ii) to predict the effects of future climate variability on refuge
usage (Fig. 1). Climate data and topographic data were extracted from
WorldClim (Fick and Hijmans, 2017) version 2 (http://www.worldclim.org/)
and ENVIREM (Title and Bemmels, 2017) (https://envirem.github.io/). For
each site we chose four variables for temperature (bio1, bio2, bio4,
bio7), four variables for precipitation (bio12, bio14, bio15, Aridity),
two variables related to topography (TRI and topoWET) and one variable
denoting site productivity (AnnualPET). A detailed description of the
variables is presented in the Table S2. WorldClim variables were
extracted at 30 arc-second, 2.5 arc-minute and 10 arc-minute
resolutions. Since the above variables were very strongly correlated
among these different resolutions (Pearson correlation, r ≥ 0.97), we
decided to use only data on a 10 arc-minute resolution. The variables
TRI and topoWET from ENVIREM were available only for 30 arc-second
resolutions. The variables Aridity and AnnualPET were extracted at 30
arc-second and 10 arc-minute resolutions; since these variables were
strongly correlated between the two resolutions (Pearson correlation, r
≥ 0.98), we used only data on 30 arc-second resolutions.
Future climate database at local scale was extracted from WorldClim
version 2 using MIROC5 (RCP8.5) and CCSM4 (RCP8.5) as representative
concentration pathways of CO2 emission projected for
2070 (Romero et al ., 2018). Future bioclimatic variables are not
available in ENVIREM databases. Since the bioclimatic variables were
very strongly correlated between these two predictive climatic models
(Pearson correlation, r ≥ 0.98), we focused our analyses only on MIROC5
(RCP8.5) database.
We measured average local temperature during the 10-day experiment. For
sites missing such data, we extracted the mean near-surface daily
temperature from the RNCEP database (Kemp et al., 2012). This was
done for all the 10 days of the experiment, from which data we then
calculated the average over the experiment. The RNCEP database has a
spatial resolution of 2.5 x 2.5o and a temporal
resolution of 6 h (Kemp et al., 2012).