Assessing the impact of climate change on threatened endemic vascular plants of Argentina
Creators: name: Salariato, Diego
Publisher: name: figshare
Year: 2022
Subjects: subject: 50202 Conservation and Biodiversity
subject: FOS: Biological sciences
subject: 50101 Ecological Impacts of Climate Change
subject: FOS: Earth and related environmental sciences
subject: Botany

description: Data and suplementary material generated for the paper “Assessing the impact of climate change on threatened endemic vascular plants of Argentina” <br> Supplementary Material <br> <strong>Fig. S1</strong> Maps for Argentina showing: a the ecoregions present sensu Olson et al. (2001), b the elevation (meters above sea level), c the species occurrence dataset used for this work. <strong>Fig. S2</strong> Histogram showing frequency of specimen records per species for the threatened endemics of Argentina. <br> <strong>Fig. S3</strong> Preliminary assessments for cell size using two cell resolutions: 0.25 arc-degrees (approx. 27 x 27 km) and 0.5 arc-degrees (approx. 55 x 55 km). a number on threatened endemics (richness) at 0.25 arc-degrees. b number on threatened endemics (richness) at 0.5 arc-degrees. c Values of C-index estimated through 10 cross-validations with glmm, gam and brt model techniques and using the two cell resolutions (0.25 and 0,5 arc-degrees). The closer the value of the C-index is to 1, the greater the number of matches between the ranking of the predictions and the ranking of the observations used for the test (i.e., the higher the prediction accuracy). <br> <strong>Fig. S4</strong> Variables for species richness models. a Correlation plot showing Spearman's correlation between 19 bioclimatic variables. The size of the circle is proportional to correlation (absolute value). b Spearman's correlation and variance inflation factor (VIF) (on the diagonal) for selected variables (BIO5, BIO13, BIO15). c BIO5 values for Argentina at 0.5 arc-degree. d BIO13 values for Argentina at 0.5 arc-degree. e BIO15 values for Argentina at 0.5 arc-degree. F Diagram showing the method used for variable selection. <br> <strong>Fig. S5</strong> Scatterplot between observed SR and predicted SR values of threatened endemics in Argentina obtained using 10-fold cross validation and different modeling techniques: generalized linear mixed model (glmm), generalized additive model (gam), boosted regression trees (brt), and an ensemble model (ensemble) using weighted-average over the three above techniques. <br> <strong>Fig. S6</strong> Predicted current species richness (SR) for threatened endemic species in Argentina using three different modeling techniques: a generalized linear mixed model (glmm), b generalized additive model (gam), and c boosted regression trees (brt). <br> <strong>Fig. S7</strong> Multivariate environmental similarity surface (MESS) maps for current and future climate data (four GCMs: HadGEM2-AO, BCC-CSM1-1, IPSL-CM5A-LR, and MRI-CGCM3; two RCPs: 4.5 and 8.2; two time periods: 2041-2060, 2061-2080). Blue color (or positve values) represents interpolation (analogous) habitat (climatic conditions) (positive value), white color represents marginal habitat (near zero), and red color (or negative values) represents extrapolation habitat (negative value). <br> <strong>Fig. S8</strong> Change in species richness (∆ richness) for threatened endemic species of Argentina under different future scenarios (four GCMs: HadGEM2-AO, BCC-CSM1-1, IPSL-CM5A-LR, and MRI-CGCM3; two RCPs: 4.5 and 8.2; two time periods: 2041-2060, 2061-2080), and obtained using an ensemble model of weighted-average over the different modeling techniques (glmm, gam, brt). For each cell i, ∆ richness cell i= future richness of cell i - current richness of cell i. <br> <strong>Fig. S9</strong> Density plots of species richness within the PA network and hotspots of threatened endemic species for current and future scenarios. <br> <strong>Fig. S10</strong> Correlation between the indices. a Spearman correlation coefficients between the different indices calculated for the most affected cells in the future climate projections (Ia, Ib and Ic). b Correlation circle (PC1 vs PC2) from the principal component analysis (PCA) obtained using values of Ia, Ib and Ic as variables over the 32 most affected cells. <br> <strong>Fig. S11</strong> Relationship of the different indices calculated for the most affected cells in future climate projections and the mean elevation, max elevation and roughness of these cells. a-c index Ia. d-f index Ib. g-i index Ic. j-m index Id. In all cases regression line corresponds to smooth local regression (loess), shaded area shows 0.95 confidence interval. <br> <strong>Table S1</strong> Mean ± standard deviation for root mean square error (RMSE), slope, intercept and Pearson's correlation coefficient between fitted vs. observed values of threatened endemic species richness obtained using 10-fold cross validation and different modeling techniques: generalized linear mixed model (glmm), generalized additive model (gam), boosted regression trees (brt), and an ensemble model using weighted-average over the three above techniques. <br> <strong>Table S2</strong> Richness variation of threatened endemic species in Argentina, estimated from MEMs using four different general circulation model (GCMs) for two representative concentration pathways (RCP) and two time periods. For ∆ richness: min., percentiles 2.5%, 50%, 97.5%, and max. ∆ richness for cell i= future richness of cell i - current richness of cell i. <br> <strong>Table S3</strong> Values of indices a, b, c, d; number of threatened endemic species (TES); and percentage of coverage by protected areas (PA) for cells most affected by climate change in Argentina. Longitude and latitude correspond to the center of the cell. For the geographic location of the cells see figure 4. <br> <strong>ESM_1.txt</strong> Specimen occurrence data from threatened endemic species of Argentina used to estimate the number of threatened endemics (richness – response variable) registered within cells of 0.5 arc-degrees. <br> <strong>ESM_2.xlsx</strong> List of threatened endemic species for the vascular flora of Argentina and their preliminary categorization sensu Salariato et al. (2021). <br> <strong>ESM_3.xlsx</strong> Species composition based on occurrence data for the cells most affected by climate change. <br>