DOI: 10.5061/dryad.dncjsxm8s
title: Data from: Climatic resilience after extreme drought in Mediterranean shrubland plant communities

description: Extreme climatic events are increasing with climate change, producing
 changes in communities climatic characterization. So, mismatches between
 climatic conditions inferred from species requirements (Community Inferred
 Climate, CIC) and macroclimate (climatic disequilibrium, CD) may change
 with extreme climatic events. Climatic resilience is defined as the
 ability to maintain or recover community climatic characteristics,
 regardless of species identity, after disturbance or stress. We evaluated
 the dynamics of plant community climatic characterization in Mediterranean
 shrublands that experienced a drought event, considering CIC and CD. CIC
 was calculated by averaging species’ climatic niche centroids, weighted by
 species' relative abundances, in the multivariate environmental space
 obtained from the climate of the species' geographical occurrence. CD
 was estimated as Euclidean distance in this space between the observed
 macroclimate and CIC. Climatic resistance was inferred by the distance
 between pre-drought and drought CIC, climatic resilience by the distance
 between pre-drought and post-drought CIC, and relative climatic resilience
 by the interaction between both distances. We found a significant
 reduction in community CD after drought, with CIC becoming more arid,
 likely due to environmental filtering of those species with wetter
 distributions. Communities with less pre-drought CD showed higher climatic
 resistance, but pre-drought CD did not explain climatic resilience.
 Communities with more arid CIC exhibited high climatic resilience
 regardless of drought impact (high relative climatic resilience), except
 for those with the most arid CIC, which suffered delayed die-off.
 Communities with less arid CIC showed low relative climatic resilience, as
 their resilience was associated with high resistance. The study highlights
 community impacts by extreme droughts through filtering of species
 distributed in more humid climates when their populations grow close to
 the arid edge. This produces changes in CD, whose resilience is determined
 by CIC, pre-drought CD, and drought impact in terms of CIC change.
description: # Climatic resilience after extreme drought in Mediterranean shrubland
 plant communities "**work_ext.zip**" contains the vector
 boundary (work_extension.shp and auxiliary files dbf, .shx, .prj) used to
 define the study region for climatic niche modeling. The spatial mask
 delimits the Mediterranean Basin and adjacent regions (Longitude: -18.64°W
 to 37.29°E; Latitude: 26.70°N to 56.34°N), optimizing computational
 efficiency by restricting analyses to the area where the study species
 were distributed. "**species_centroid.csv**" contains the
 centroids' coordinates in the common climatic space (PCA1 and PCA2)
 for all the studied species. * "species": valid scientific name
 of the studied species * "centroid_pca1": axis 1 coordinate in
 the common climatic space for each studied species *
 "centroid_pca2": axis 2 coordinate in the common climatic space
 for each studied species "**Interannual_observed_climate.csv**"
 contains the 12 biovariable values for the study plot positions for the
 reference period. * "plot": identifier of each plot *
 "lat": UTM latitude coordinate * "long": UTM longitude
 coordinate * "bio_1": Annual Mean Temperature (°C) *
 "bio_2": Mean Diurnal Range (°C) (Mean of monthly (max temp -
 min temp)) * "bio_3": Isothermality (%) (BIO2/BIO7)(×100) *
 "bio_4": Temperature Seasonality (°C) (standard deviation ×100)
 * "bio_5": Max Temperature of Warmest Month (°C) *
 "bio_6": Min Temperature of Coldest Month (°C) *
 "bio_7": Temperature Annual Range (BIO5-BIO6) *
 "bio_8": Mean Temperature of Wettest Quarter (°C) *
 "bio_9": Mean Temperature of Driest Quarter (°C) *
 "bio_10": Mean Temperature of Warmest Quarter (°C) *
 "bio_11": Mean Temperature of Coldest Quarter (°C) *
 "bio_12": Annual Precipitation (mm) * "bio_13":
 Precipitation of Wettest Month (mm) * "bio_14": Precipitation of
 Driest Month (mm) * "bio_15": Precipitation Seasonality
 (Coefficient of Variation) * "bio_16": Precipitation of Wettest
 Quarter (mm) * "bio_17": Precipitation of Driest Quarter (mm) *
 "bio_18": Precipitation of Warmest Quarter (mm) *
 "bio_19": Precipitation of Coldest Quarter (mm)
 "**Community_composition.csv**" list of individuals registered
 in the study communities during the three study periods (pre-drought,
 drought, post-drought) * "year": year of the field survey.
 "2013" corresponds to the pre-drought period, "2016"
 corresponds to the drought period, and "2022" corresponds to the
 post-drought period. * "plot": identifier of each plot *
 "cod": identifier of each plot during each period *
 "species": valid scientific name of the studied species *
 "n": number of recruits of each species belonging to each
 categorical group "**disequilibrium.csv**" contains the
 community inferred climate and climatic disequilibrium of communities
 during each period. * "cod": identifier of each plot during each
 period * "plot": identifier of each plot * "year":
 year of the field survey. "2013" corresponds to the pre-drought
 period, "2016" corresponds to the drought period, and
 "2022" corresponds to the post-drought period. *
 "oc_x": axis 1 coordinate in the common climatic space for each
 plot and period, therefore, experienced by communities (observed climate)
 * "oc_y": axis 2 coordinate in the common climatic space for
 each plot and period, therefore, experienced by communities (observed
 climate) * "cic_x": community inferred climate for axis x
 represented as the axis 1 coordinate in the common climatic space for each
 community and period * "cic_y": community inferred climate for
 axis y represented as the axis 2 coordinate in the common climatic space
 for each community and period * "cd": climatic disequilibrium of
 each community during each period, calculated as the difference between
 observed climate and community inferred climate.
 **"climatic_resilience_components.csv**" contains climatic
 resistance and climatic resilience of each plot. * "plot":
 identifier of each plot * "cic_x_pred": axis 1 coordinate in the
 common climatic space for each community during the pre-drought period,
 calculated through the species centroid axis 1 coordinate (community
 inferred climate) * "cd_pred": climatic disequilibrium of each
 community during the pre-drought period, calculated as the difference
 between observed climate and pre-drought community inferred climate. *
 "cd_postd": climatic disequilibrium of each community during the
 post-drought period, calculated as the difference between observed climate
 and post-drought community inferred climate. *
 "climatic_resistance": climatic resistance of each community,
 calculated as distance between pre-drought CIC(cic_x_pred, cic_y_pred) and
 drought CIC(cic_x_d, cic_y_d) * "climatic_resilience": climatic
 resilience of each community, calculated as distance between pre-drought
 CIC (cic_x_pred, cic_y_pred) and post-drought CIC (cic_x_postd,
 cic_y_postd) #### KEY INFORMATION SOURCES/ CODE **species niches and
 climatic disequilibrium**
 "**interannual_climatic_niche_modelling.R**" contains the code
 for modeling biovariables and obtaining each species' niche centroid
 in the multivariate climatic space. The analysis requires (1) downloading
 and filtering species occurrence records from GBIF (DOIs provided in the
 Supplementary Material) and (2) extracting climatic variables from
 WorldClim 2.0 ([Timeseries – Chelsa
 Climate](https://chelsa-climate.org/timeseries/)), using the spatial
 delineations provided in "*work_ext.zip*". Some required
 functions are contained in "niche_required_functions.R".
 "**community_CD_CIC_climatic_resilience_components.R**" allows
 to estimate each community inferred climate (CIC) and climatic
 disequilibrium (CD) basing on multivariates species niche centroids
 obtained from "*Interannual_climatic_niche_modelling.R*",
 species relative abundances in each community, contained in table
 "*Community_composition.csv*" and historic observed climate of
 each plot contained in "*Interannual_observed_climate.csv*. Some
 required functions are contained in
 "niche_required_functions.R". This R code consists of a
 collection of functions used in niche modeling, spatial data analysis, and
 data visualization, particularly for ecological and biogeographic studies.
 #### RESULTS To perform the statistical analyses specified in the
 manuscripts, use the "**linear_mixed_effect_models.R**" R
 script. The "**disequilibrium.csv**" and
 "**climatic_resilience_components.csv**" tables are required.