DOI: 10.6084/m9.figshare.20332179.v1
title: Closely related Amazonian whiptail lizards (Cnemidophorus lemniscatus species group) show contrasting responses to climate change.

description: This repository contains the data to perform the analyses by Martins et al. occurrence_points.csv – Occurrence points extracted from Ribeiro-Junior et al. 2016 e Martins et al. 2021 Ribeiro-Junior, M. A., & Amaral, S. (2016). Catalogue of distribution of lizards (Reptilia: Squamata) from the Brazilian Amazonia. III. Anguidae, Scincidae, Teiidae. Zootaxa, 4205(5), 401–430. Martins, L. F., Choueri, E. L., Oliveira, A. F. S., Domingos, F. M. C. B., Leite, R. N., Fouquet, A., … & Werneck, F. P. (2021). Whiptail lizard’s lineages delimitation and population expansion as windows into the history of Amazonian open ecosystems. Systematics and Biodiversity, 19(8), 957–975. cnemis.tre – Phylogenetic relationships of <em>Cnemidophorus lemniscatus</em> species group described in Martins et al. 2021. Martins, L. F., Choueri, E. L., Oliveira, A. F. S., Domingos, F. M. C. B., Leite, R. N., Fouquet, A., … & Werneck, F. P. (2021). Whiptail lizard’s lineages delimitation and population expansion as windows into the history of Amazonian open ecosystems. Systematics and Biodiversity, 19(8), 957–975. hobo_microhabitat_df.csv – Data frame of operative temperatures (microhabitat) collected by sites with HOBOTM Onset Pro V2 and PVC tube models. Temp1 e temp2 correspond to the probes of each data logger. hobo_rh_df.csv – Data frame of environmental temperatures (temp) and relative humidity (rh) collected by sites with HOBOTM Onset Pro V2. sites_df.csv – Data frame of the sampled locations representing species, number of individuals per location, latitude, and longitude. MEM_df.csv – Moran’s Eigenvector Maps data frame based on principal components of spatial autocorrelation. See Materials and Methods for more details. PEM_df.csv – Phylogenetic Eigenvector Maps data frame based on the lineage’s genealogical relationship recovered in cnemis.tre. See Materials and Methods for more details. tpref_df.csv – Data frame of the preferential temperature (°C) per individual (id). tavg_df.csv – Data frame of average environment temperatures (°C) per locality. tpc_df.csv – data frame of the thermal performance curve. Svl = snout-vent length; temp = body temperature (°C) during sprint; sprint = speed (cm/s) reached at the corresponding temperature; PEM’s = Phylogenetic Eigenvector Maps; MEM’s = Moran’s Eigenvector Maps; tavg = average environment temperatures (°C) per locality; group = classification according to the two MEM’s (MEM1 and MEM6) recovered as most important in thermal performance. physio_df.csv – Data frame of ecophysiological data. Svl = snout-vent length; cc = tail length; bc = base of tail; tpref = preferential temperature; hr_i = experiment start time; hr_f = experiment final time; chan = channel of the artificial thermal gradient in which the lizard was placed during the experiment; ctmin = minimum critical temperature; ctmax = maximum critical temperature; sprint_c_tb = body temperature in cold sprint (5°C below room temperature); speed_c = speed (cm/s) reached in cold sprint; sprint_e_tb = body temperature in sprint at room temperature; speed_e = speed (cm/s) reached in sprint at room temperature; sprint_h_tb = body temperature in hot sprint (5°C above room temperature); speed_h = speed (cm/s) reached in hot sprint; wc_year_present – Temperature and precipitation raster (data extracted from WorldClim) corresponding to the current distribution of <em>Cnemidophorus lemniscatus</em> species group. cnemis_ha_present – Hours of activity raster at present considering minimum and maximum operative and voluntary temperatures. cnemis_ha_2060_ssp245 – Hours of activity rasters predicted for 2060 in the mild greenhouse gas emission scenario (SSP2-4.5) cnemis_ha_2060_ssp585 – Hours of activity rasters predicted for 2060 in the severe greenhouse gas emission scenario (SSP5-8.5) cnemis_ha_2100_ssp245 – Hours of activity rasters predicted for 2100 in the mild greenhouse gas emission scenario (SSP2-4.5) cnemis_ha_2100_ssp585 – Hours of activity rasters predicted for 2100 in the severe greenhouse gas emission scenario (SSP5-8.5) cnemis_perf_2060_ssp245 – Performance rasters predicted for 2060 in the mild greenhouse gas emission scenario (SSP2-4.5) cnemis_perf_2060_ssp585 – Performance rasters predicted for 2060 in the severe greenhouse gas emission scenario (SSP5-8.5) cnemis_perf_2100_ssp245 – Performance rasters predicted for 2100 in the mild greenhouse gas emission scenario (SSP2-4.5) cnemis_perf_2100_ssp585 – Performance rasters predicted for 2100 in the severe greenhouse gas emission scenario (SSP5-8.5) cnemis_perf_present – Performance rasters at present considering the thermal performance curves for each group. pred_year_present – Rasters summarized by year incorporating climate data, hours of activity, and performance for the present. pred_year_2060_ssp245 – Prediction rasters for 2060 in the mild greenhouse gas emission scenario (SSP2-4.5) considering future climatic data, hours of activity, and performance. pred_year_2060_ssp585 – Prediction rasters for 2060 in the severe greenhouse gas emission scenario (SSP5-8.5) considering future climatic data, hours of activity, and performance. pred_year_2100_ssp245 – Prediction rasters for 2100 in the mild greenhouse gas emission scenario (SSP2-4.5) considering future climatic data, hours of activity, and performance. pred_year_2100_ssp585 – Prediction rasters for 2100 in the severe greenhouse gas emission scenario (SSP5-8.5) considering future climatic data, hours of activity, and performance. <br>