https://doi.org/10.5061/dryad.h9w0vt4rj

Facilitation is an ecological interaction that has allowed plant lineages to survive past climate aridification. This same interaction can be expected to buffer the effects of current climate change, which is tending to become more arid in the Mediterranean basin. However, facilitation may wane when stress conditions are extreme. Here we argue that the erosion of the facilitation signal between Quercus ilex and its nurses detected by García-Fayos et al. (2020) along 50 years in the eastern Iberian Peninsula may have been due to the reversion of facilitation to competition imposed by an increasingly arid climate. To support this speculation, we reconstructed the climatic niche of Q. ilex and its nurses as well as the local climate change occurring in the populations studied. We found that the decreasing trend in precipitation is pushing Q. ilex out of its climatic optimum in the stressful (semi-arid) but not in the mild (sub- humid) habitats. These results suggest that facilitation will be unable to mitigate the effects of climate change, especially those related to aridification. However, other scenarios linking climatic change with herbivory and rural abandonment should be considered to fully understand the past, present and future of facilitation interactions. Reconstructing past interactions can serve as an early warning signal about the future of populations in the face of climate change.

Description of the data and file structure

We have submitted the occurences of each studied species. For each occurrences dataset we extracted mean annual precipitation variables based on CHELSA climate database.

Species occurrences attached files:

Juniperus communis_clean.csv : Climatic data of the Juniperus communis occurrences extracted from CHELSA database.

Juniperus sabina_clean.csv : Climatic data of the Juniperus sabina occurrences extracted from CHELSA database.

Juniperus thurifera_clean.csv : Climatic data of the Juniperus thurifera occurrences extracted from CHELSA database.

Juniperus phoenicea_clean.csv : Climatic data of the Juniperus phoenicea occurrences extracted from CHELSA database.

Pinus nigra_clean.csv : Climatic data of the Pinus nigra occurrences extracted from CHELSA database.

Quercus ballota_clean.csv : Climatic data of the Quercus ballota occurrences extracted from CHELSA database.

Quercus faginea_clean.csv : Climatic data of the Quercus faginea occurrences extracted from CHELSA database.

Each species' occurrences dataset has 4 fields:

• species (scientific name of the species)
• x : decimal Longitude in WGS84 reference system
• y : decimal Latitude in WGS84 reference system
• precipitation: Mean annual precipitation of the climatic reference period.

Second, we also attached here the meteorological observations of our study plots (Precipitation_all_plots.csv). The preciptation of our study plots are based on quality controlled and homogenized meteorological observations from high spatial resolution databases (González‐Hidalgo et al. 2011, 2022).

Precipitation_all_plots.csv has 6 fileds:

• Plot: Id of the studied plot
• year: year of the meteorological record
• precipitation: Annual precipitation of the year
• X : decimal Longitude in WGS84 reference system
• Y: decimal Latitude in WGS84 reference system

Finally, we attached the Rcode for the analysis of the study:

1D_Quercus_ballota_niche_prec_trends.R: Code to model Quercus ballota niche based on Quercus ballota_clean.csv data. This script also includes the code to compute the precipitation trend model (GLM).

1D_all_species_niche.R : Code to model the niches of all the studied species by using the aforementioned data.

plots_graphs.R : Code to plot all the figures attached in the manuscript.