## ----set_options, include = FALSE--------------------------------------------- knitr::opts_chunk$set( eval = FALSE, # Chunks of codes will not be evaluated by default collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 5, # Set device size at rendering time (when plots are generated) fig.align = "center" ) ## ----setup, eval = TRUE, include = FALSE-------------------------------------- library(deepSTRAPP) is_dev_version <- function (pkg = "deepSTRAPP") { # # Check if ran on CRAN # not_cran <- identical(Sys.getenv("NOT_CRAN"), "true") # || interactive() # Version number check version <- tryCatch(as.character(utils::packageVersion(pkg)), error = function(e) "") dev_version <- grepl("\\.9000", version) # not_cran || dev_version return(dev_version) } ## ----adjust_dpi_CRAN, include = FALSE, eval = !is_dev_version()--------------- knitr::opts_chunk$set( dpi = 50 # Lower DPI to save space ) ## ----adjust_dpi_dev, include = FALSE, eval = is_dev_version()----------------- # knitr::opts_chunk$set( # dpi = 72 # Default DPI for the dev version # ) ## ----load_data_biogeo_2lvl---------------------------------------------------- # # ------ Step 0: Load data ------ # # # ## Load range data # data(Ponerinae_binary_range_table, package = "deepSTRAPP") # # dim(Ponerinae_binary_range_table) # View(Ponerinae_binary_range_table) # # ## Prepare range data for Old World vs. New World # # # No overlap in ranges in current taxa # table(Ponerinae_binary_range_table$Old_World, Ponerinae_binary_range_table$New_World) # # Ponerinae_NO_tip_data <- stats::setNames(object = Ponerinae_binary_range_table$Old_World, # nm = Ponerinae_binary_range_table$Taxa) # Ponerinae_NO_tip_data <- as.character(Ponerinae_NO_tip_data) # Ponerinae_NO_tip_data[Ponerinae_NO_tip_data == "TRUE"] <- "O" # O = Old World # Ponerinae_NO_tip_data[Ponerinae_NO_tip_data == "FALSE"] <- "N" # N = New World # names(Ponerinae_NO_tip_data) <- Ponerinae_binary_range_table$Taxa # table(Ponerinae_NO_tip_data) # # # Select color scheme for ranges # colors_per_ranges <- c("mediumpurple2", "peachpuff2") # names(colors_per_ranges) <- c("N", "O") # # ## Load phylogeny # data(Ponerinae_tree_old_calib, package = "deepSTRAPP") # # plot(Ponerinae_tree_old_calib) # ape::Ntip(Ponerinae_tree_old_calib) == length(Ponerinae_NO_tip_data) # # ## Check that trait data and phylogeny are named and ordered similarly # all(names(Ponerinae_NO_tip_data) == Ponerinae_tree_old_calib$tip.label) # # ## Reorder trait data as in phylogeny # Ponerinae_NO_tip_data <- Ponerinae_NO_tip_data[match(x = Ponerinae_tree_old_calib$tip.label, # table = names(Ponerinae_NO_tip_data))] # # ## Plot data on tips for visualization # pdf(file = "./Ponerinae_biogeo_data_old_calib_on_phylo.pdf", width = 20, height = 150) # # # Set plotting parameters # old_par <- par(no.readonly = TRUE) # par(mar = c(0.1,0.1,0.1,0.1), oma = c(0,0,0,0)) # bltr # # # Graph presence/absence using plotTree.datamatrix # range_map <- phytools::plotTree.datamatrix( # tree = Ponerinae_tree_old_calib, # X = as.data.frame(Ponerinae_NO_tip_data), # fsize = 0.7, yexp = 1.1, # header = TRUE, xexp = 1.25, # colors = colors_per_ranges) # # # Get plot info in "last_plot.phylo" # plot_info <- get("last_plot.phylo", envir=.PlotPhyloEnv) # # # Add time line # # # Extract root age # root_age <- max(phytools::nodeHeights(Ponerinae_tree_old_calib)) # # # Define ticks # # ticks_labels <- seq(from = 0, to = 100, by = 20) # ticks_labels <- seq(from = 0, to = 120, by = 20) # axis(side = 1, pos = 0, at = (-1 * ticks_labels) + root_age, labels = ticks_labels, cex.axis = 1.5) # legend(x = root_age/2, # y = 0 - 5, adj = 0, # bty = "n", legend = "", title = "Time [My]", title.cex = 1.5) # # # Add a legend # legend(x = plot_info$x.lim[2] - 10, # y = mean(plot_info$y.lim), # # adj = c(0,0), # # x = "topleft", # legend = c("Absence", "Presence"), # pch = 22, pt.bg = c("white","gray30"), pt.cex = 1.8, # cex = 1.5, bty = "n") # # dev.off() # # # Reset plotting parameters # par(old_par) # # ## Inputs needed for Step 1 are the tip_data (Ponerinae_NO_tip_data) and the phylogeny # ## (Ponerinae_tree_old_calib), and optionally, a color scheme (colors_per_ranges). # ## ----load_data_biogeo_2lvl_eval, eval = TRUE, echo = FALSE-------------------- ## Load phylogeny data(Ponerinae_tree_old_calib, package = "deepSTRAPP") ## Load and prepare range tip_data data(Ponerinae_binary_range_table, package = "deepSTRAPP") Ponerinae_NO_tip_data <- stats::setNames(object = Ponerinae_binary_range_table$Old_World, nm = Ponerinae_binary_range_table$Taxa) Ponerinae_NO_tip_data <- as.character(Ponerinae_NO_tip_data) Ponerinae_NO_tip_data[Ponerinae_NO_tip_data == "FALSE"] <- "N" # N = New World Ponerinae_NO_tip_data[Ponerinae_NO_tip_data == "TRUE"] <- "O" # O = Old World names(Ponerinae_NO_tip_data) <- Ponerinae_binary_range_table$Taxa Ponerinae_NO_tip_data <- Ponerinae_NO_tip_data[match(x = Ponerinae_tree_old_calib$tip.label, table = names(Ponerinae_NO_tip_data))] # Select color scheme for ranges colors_per_ranges <- c("mediumpurple2", "peachpuff2") names(colors_per_ranges) <- c("N", "O") ## ----prepare_trait_data_biogeo_2lvl------------------------------------------- # # ------ Step 1: Prepare trait data ------ # # # ## Goal: Map trait evolution on the time-calibrated phylogeny # # # 1.1/ Fit evolutionary models to trait data using Maximum Likelihood. # # 1.2/ Select the best fitting model comparing AICc. # # 1.3/ Infer ancestral characters estimates (ACE) at nodes. # # 1.4/ Run stochastic mapping simulations to generate evolutionary histories # # compatible with the best model and inferred ACE. (Only for categorical and biogeographic data) # # 1.5/ Infer ancestral states along branches. # # - For continuous traits: use interpolation to produce a `contMap`. # # - For categorical and biogeographic data: compute posterior frequencies of each state/range # # to produce a `densityMap` for each state/range. # # library(deepSTRAPP) # # # All these actions are performed by a single function: deepSTRAPP::prepare_trait_data() # ?deepSTRAPP::prepare_trait_data() # # ## The R package `BioGeoBEARS` is needed for this workflow to process biogeographic data. # ## Please install it manually from: https://github.com/nmatzke/BioGeoBEARS. # # # In this example, to simplify the analyses, we set 'split_multi_area_ranges' = TRUE such as # # multi-range areas ('NO' in this case) are split between unique areas ('N' and 'O') # # to keep only two areas for downstream analyses # # # Run prepare_trait_data with default options # # For biogeographic data, a DEC model is assumed by default. # Ponerinae_biogeo_data_old_calib <- prepare_trait_data( # tip_data = Ponerinae_NO_tip_data, # trait_data_type = "biogeographic", # phylo = Ponerinae_tree_old_calib, # evolutionary_models = "DEC+J", # Default = "DEC" for biogeographic # BioGeoBEARS_directory_path = "./BioGeoBEARS_directory/", # prefix_for_files = "Ponerinae_old_calib", # split_multi_area_ranges = TRUE, # Set to TRUE to split multi-range areas NO between N and O # nb_simulations = 100, # Reduce number of simulations to save time # colors_per_levels = colors_per_ranges, # seed = 1234) # Set seed for reproducibility # # ## Load Result to save time # data(Ponerinae_biogeo_data_old_calib, package = "deepSTRAPP") # # # Explore output # str(Ponerinae_biogeo_data_old_calib, 1) # # # $densityMaps hold maps for unique areas (Here, 'N' and 'O'), that will be used for downstream analyses. # # $densityMaps_all_ranges hold maps for unique areas AND multi-range areas (Here, also includes 'NO') # # ## Plot densityMaps for each range # # # densityMap for range n°1 (N = "New World") # plot(Ponerinae_biogeo_data_old_calib$densityMaps[[1]]) # # densityMap for range n°2 (N = "Old World") # plot(Ponerinae_biogeo_data_old_calib$densityMaps[[2]]) # # densityMap for range n°3 (NO = "New World" + "Old World") # plot(Ponerinae_biogeo_data_old_calib$densityMaps_all_ranges[[3]]) # # ## Plot densityMaps for all ranges together # # # densityMaps with all unique areas overlaid # plot_densityMaps_overlay(Ponerinae_biogeo_data_old_calib$densityMaps) # # densityMaps with all ranges (including multi-area ranges) overlaid # plot_densityMaps_overlay(Ponerinae_biogeo_data_old_calib$densityMaps_all_ranges) # # # As you can see, the probability of multi-range area 'NO' is significant only for deep nodes # # and is not likely to affect any of our downstream analyses if ignored. # # ## Inspect ancestral ranges at nodes # # # Posterior probabilities of each range (= ACE) at internal nodes # Ponerinae_biogeo_data_old_calib$ace # Only with unique areas (Here, N and O) # Ponerinae_biogeo_data_old_calib$ace_all_ranges # Including multi-area ranges too (Here, NO) # # # ## Inputs needed for Step 2 are the densityMaps (Ponerinae_densityMaps), and optionally, # ## the tip_data (Ponerinae_NO_tip_data), and the ACE (Ponerinae_ACE) # # ## ----prepare_diversification_data_biogeo_2lvl--------------------------------- # # ------ Step 2: Prepare diversification data ------ # # # ## Goal: Map evolution of diversification rates and regime shifts on the time-calibrated phylogeny # # # Run a BAMM (Bayesian Analysis of Macroevolutionary Mixtures) # # ## You need the BAMM C++ program installed in your machine to run this step. # ## See the BAMM website: http://bamm-project.org/ and the companion R package [BAMMtools]. # # # 2.1/ Set BAMM - Record BAMM settings and generate all input files needed for BAMM. # # 2.2/ Run BAMM - Run BAMM and move output files in dedicated directory. # # 2.3/ Evaluate BAMM - Produce evaluation plots and ESS data. # # 2.4/ Import BAMM outputs - Load `BAMM_object` in R and subset posterior samples. # # 2.5/ Clean BAMM files - Remove files generated during the BAMM run. # # # All these actions are performed by a single function: deepSTRAPP::prepare_diversification_data() # ?deepSTRAPP::prepare_diversification_data() # # # Run BAMM workflow with deepSTRAPP # ## This step is time-consuming. You can skip it and load directly the result if needed # Ponerinae_BAMM_object_old_calib <- prepare_diversification_data( # BAMM_install_directory_path = "./software/bamm-2.5.0/", # To adjust to your own path to BAMM # phylo = Ponerinae_tree_old_calib, # prefix_for_files = "Ponerinae_old_calib", # seed = 1234, # Set seed for reproducibility # numberOfGenerations = 10^7, # Set high for optimal run, but will take a long time # BAMM_output_directory_path = "./BAMM_outputs/") # # # Load directly the result # data(Ponerinae_BAMM_object_old_calib) # # This dataset is only available in development versions installed from GitHub. # # It is not available in CRAN versions. # # Use remotes::install_github(repo = "MaelDore/deepSTRAPP") to get the latest development version. # # # Explore output # str(Ponerinae_BAMM_object_old_calib, 1) # # Record the regime shift events and macroevolutionary regimes parameters across posterior samples # str(Ponerinae_BAMM_object_old_calib$eventData, 1) # # Mean speciation rates at tips aggregated across all posterior samples # head(Ponerinae_BAMM_object_old_calib$meanTipLambda) # # Mean extinction rates at tips aggregated across all posterior samples # head(Ponerinae_BAMM_object_old_calib$meanTipMu) # # # Plot mean net diversification rates and regime shifts on the phylogeny # plot_BAMM_rates(Ponerinae_BAMM_object_old_calib, # labels = FALSE, legend = TRUE) # # ## Input needed for Step 3 is the BAMM_object (Ponerinae_BAMM_object) # ## ----run_deepSTRAPP_biogeo_2lvl----------------------------------------------- # # ------ Step 3: Run a deepSTRAPP workflow ------ # # # ## Goal: Extract traits, diversification rates and regimes at a given time in the past # ## to test for differences with a STRAPP test # # # 3.1/ Extract trait data at a given time in the past ('focal_time') # # 3.2/ Extract diversification rates and regimes at a given time in the past ('focal_time') # # 3.3/ Compute STRAPP test # # 3.4/ Repeat previous actions for many timesteps along evolutionary time # # # All these actions are performed by a single function: # # For a single 'focal_time': deepSTRAPP::run_deepSTRAPP_for_focal_time() # # For multiple 'time_steps': deepSTRAPP::run_deepSTRAPP_over_time() # ?deepSTRAPP::run_deepSTRAPP_for_focal_time() # ?deepSTRAPP::run_deepSTRAPP_over_time() # # ## Set for five time steps of 5 My. Will generate deepSTRAPP workflows for 0 to 40 Mya. # time_step_duration <- 5 # time_range <- c(0, 40) # # # Run deepSTRAPP on net diversification rates # ## This step is time-consuming. You can skip it and load directly the result if needed # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40 <- run_deepSTRAPP_over_time( # densityMaps = Ponerinae_biogeo_data_old_calib$densityMaps, # ace = Ponerinae_biogeo_data_old_calib$ace, # tip_data = Ponerinae_NO_tip_data, # trait_data_type = "biogeographic", # BAMM_object = Ponerinae_BAMM_object_old_calib, # time_range = time_range, # time_step_duration = time_step_duration, # seed = 1234, # Set seed for reproducibility # alpha = 0.10, # Select a generous level of significance for the sake of the example # # Needed to obtain STRAPP stats and plot evaluation histograms (See 4.2) # return_perm_data = TRUE, # # Needed to get trait data and plot rates through time (See 4.3) # extract_trait_data_melted_df = TRUE, # # Needed to get diversification data and plot rates through time (See 4.3) # extract_diversification_data_melted_df = TRUE, # # Needed to obtain STRAPP stats and plot evaluation histograms (See 4.2) # return_STRAPP_results = TRUE, # # Needed to plot updated densityMaps (See 4.4) # return_updated_trait_data_with_Map = TRUE, # # Needed to map diversification rates on updated phylogenies (See 4.5) # return_updated_BAMM_object = TRUE, # verbose = TRUE, # verbose_extended = TRUE) # # # Load the deepSTRAPP output summarizing results for 0 to 40 My # data(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, package = "deepSTRAPP") # # This dataset is only available in development versions installed from GitHub. # # It is not available in CRAN versions. # # Use remotes::install_github(repo = "MaelDore/deepSTRAPP") to get the latest development version. # # ## Explore output # str(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, max.level = 1) # # # See next step for how to generate plots from those outputs # # # Display test summary # # Can be passed down to [deepSTRAPP::plot_STRAPP_pvalues_over_time()] to generate a plot # # showing the evolution of the test results across time # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$pvalues_summary_df # # # Access STRAPP test results # # Can be passed down to [deepSTRAPP::plot_histograms_STRAPP_tests_over_time()] to generate plot # # showing the null distribution of the test statistics # str(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$STRAPP_results, max.level = 2) # # # Access trait data in a melted data.frame # head(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$trait_data_df_over_time) # # Access the diversification data in a melted data.frame # head(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$diversification_data_df_over_time) # # Both can be passed down to [deepSTRAPP::plot_rates_through_time()] to generate a plot # # showing the evolution of diversification rates though time in relation to trait values # # # Access updated densityMaps for each focal time # # Can be used to plot densityMaps with branch cut-off at focal time # # with [deepSTRAPP::plot_densityMaps_overlay()] # str(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time, max.level = 2) # # # Access updated BAMM_object for each focal time # # Can be used to map rates and regime shifts on phylogeny with branch cut-off # # at focal time with [deepSTRAPP::plot_BAMM_rates()] # str(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time, max.level = 2) # # ## Input needed for Step 4 is the deepSTRAPP object (Ponerinae_deepSTRAPP_biogeo_old_calib_0_40) # ## ----plot_pvalues_biogeo_2lvl------------------------------------------------- # # ------ Step 4: Plot results ------ # # # ## Goal: Summarize the outputs in meaningful plots # # # 4.1/ Plot evolution of STRAPP tests p-values through time # # 4.2/ Plot histogram of STRAPP test stats # # 4.3/ Plot evolution of rates through time in relation to ranges # # 4.4/ Plot rates vs. ranges across branches for a given 'focal_time' # # 4.5/ Plot updated densityMaps mapping range evolution for a given 'focal_time' # # 4.6/ Plot updated diversification rates and regimes for a given 'focal_time' # # 4.7/ Combine 4.5 and 4.6 to plot both mapped phylogenies with range evolution (4.5) # # and diversification rates and regimes (4.6). # # # Each plot is achieved through a dedicated function # # # Load the deepSTRAPP output summarizing results for 0 to 40 My # data(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, package = "deepSTRAPP") # # This dataset is only available in development versions installed from GitHub. # # It is not available in CRAN versions. # # Use remotes::install_github(repo = "MaelDore/deepSTRAPP") to get the latest development version. # # ### 4.1/ Plot evolution of STRAPP tests p-values through time #### # # # ?deepSTRAPP::plot_STRAPP_pvalues_over_time() # # ## Plot results of Mann-Whitney-Wilcoxon tests across all time-steps # deepSTRAPP::plot_STRAPP_pvalues_over_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # alpha = 0.1) # # # This is the main output of deepSTRAPP. It shows the evolution of the significance # # of the STRAPP tests over time. # # This example highlights the importance of deepSTRAPP as the significance # # of STRAPP tests change over time. # # Differences in net diversification rates are not significant in the present # # (assuming a significant threshold of alpha = 0.10). # # Meanwhile, rates are significantly different in the past between 8 My to 30 My (the green area). # # This result supports the idea that differences in biodiversity across bioregions # # (i.e., "Old World" vs. "New World" ants) can be explained by differences of diversification rates # # that was detected in the past. # # Without use of deepSTRAPP, this conclusion would not have been supported by current diversification rates # # alone (although here, results should be discussed is regards to their weak degree of significance). # ## ----plot_pvalues_biogeo_2lvl_eval_dev, eval = is_dev_version(), echo = FALSE---- # # # Load the deepSTRAPP output summarizing results for 0 to 40 My # data(Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, package = "deepSTRAPP") # # # Produce plot for results of overall Kruskal-Wallis tests over time # ggplot_STRAPP_pvalues <- deepSTRAPP::plot_STRAPP_pvalues_over_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # alpha = 0.1, display_plot = FALSE) # # Adjust main title size # ggplot_STRAPP_pvalues <- ggplot_STRAPP_pvalues + # ggplot2::theme(plot.title = ggplot2::element_text(size = 18)) # # Print plot # print(ggplot_STRAPP_pvalues) # ## ----plot_pvalues_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.1_plot_pvalues.PNG") ## ----plot_histogram_STRAPP_tests_overall_biogeo_2lvl-------------------------- # ### 4.2/ Plot histogram of STRAPP test stats #### # # # Plot an histogram of the distribution of the test statistics used # # to assess the significance of STRAPP tests # # For a single 'focal_time': deepSTRAPP::plot_histogram_STRAPP_test_for_focal_time() # # For multiple 'time_steps': deepSTRAPP::plot_histograms_STRAPP_tests_over_time() # # # ?deepSTRAPP::plot_histogram_STRAPP_test_for_focal_time # # ?deepSTRAPP::plot_histograms_STRAPP_tests_over_time # # ## These functions are used to provide visual illustration of the results of each STRAPP test. # # They can be used to complement the provision of the statistical results summarized in Step 3. # # # Display the time-steps # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$time_steps # # ## Plot results from Mann-Whitney-Wilcoxon between the two unique areas #### # # # Plot the histogram of test stats for time-step n°3 = 10 My # plot_histogram_STRAPP_test_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 10) # # # The black line represents the expected value under the null hypothesis H0 # # => Δ Mann-Whitney-Wilcoxon U-stat = 0. # # The histogram shows the distribution of the test statistics as observed # # across the 1000 posterior samples from BAMM. # # The red line represents the significance threshold for which 90% of the observed data # # exhibited a higher value than expected. # # Since this red line is above the null expectation (quantile 10% = 380.4), # # the test is significant for a value of alpha = 0.10. # # # Plot the histograms of test stats for all time-steps # plot_histograms_STRAPP_tests_over_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40) # ## ----plot_histogram_STRAPP_tests_biogeo_2lvl_eval_dev, eval = is_dev_version(), echo = FALSE---- # # # Produce the histogram of test stats for time-step n°3 = 10 My # ggplot_histogram <- plot_histogram_STRAPP_test_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 10, display_plot = FALSE) # # Adjust title size # ggplot_histogram <- ggplot_histogram + # ggplot2::theme(plot.title = ggplot2::element_text(size = 18)) # # Print plot # print(ggplot_histogram) # ## ----plot_histogram_STRAPP_tests_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.2_plot_STRAPP_tests.PNG") ## ----plot_rates_through_time_biogeo_2lvl-------------------------------------- # ### 4.3/ Plot evolution of rates through time ~ trait data #### # # # ?deepSTRAPP::plot_rates_through_time() # # # Generate ggplot # plot_rates_through_time(deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # colors_per_levels = colors_per_ranges, # plot_CI = TRUE) # # # This plot helps to visualize how differences in rates evolved over time. # # You can see that both bioregions "New World" and "Old World" had fairly different rates over time, # # with differences detected as significant between 8 to 30 My. # # However, in the present, we recorded an increase in diversification rates that blurred # # these differences and led to a non-significant STRAPP test when comparing current rates. # # This plot, alongside results of deepSTRAPP, supports the Diversification Rate Hypothesis # # in showing how "Old World" ant lineages may have accumulated faster, especially between 8 to 30 My. # # # N.B.: The increase of diversification rates recorded in the present may largely be artifactual, # # due to the fact some lineages in the present will go extinct in the future, # # but have not been recorded as such. # # This bias is named the "pull of the present", and can impair evaluation of # # the Diversification Rate Hypothesis based only on current rates. # # deepSTRAPP offers a solution to this issue by investigating rate differences at any time in the past. # ## ----plot_rates_through_time_biogeo_2lvl_eval_dev, eval = is_dev_version(), echo = FALSE---- # plot_rates_through_time(deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # colors_per_levels = colors_per_ranges, # plot_CI = TRUE) ## ----plot_rates_through_time_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.3_plot_rates_through_time.PNG") ## ----plot_rates_vs_traits_biogeo_2lvl----------------------------------------- # ### 4.4/ Plot rates vs. ranges across branches for a given focal time #### # # # ?deepSTRAPP::plot_rates_vs_trait_data_for_focal_time() # # ?deepSTRAPP::plot_rates_vs_trait_data_over_time() # # # This plot help to visualize differences in rates vs. ranges across all branches # # found at specific time-steps (i.e., 'focal_time'). # # # Generate ggplot for time = 10 My # plot_rates_vs_trait_data_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 10, # colors_per_levels = colors_per_ranges) # # # Here we focus on T = 10 My to highlight the differences detected in the previous steps. # # You can see that "Old World" ants tend to have higher rates than "New World" ants, at this time-step. # # This plot, alongside other results of deepSTRAPP, supports the Diversification Rate Hypothesis in showing # # "Old World" ant lineages may have accumulated faster, especially between 8 to 30 My. # # Additionally, the plot displays summary statistics for the STRAPP test associated with the data shown: # # * An observed statistic computed across the mean rates and trait states (i.e., habitats) shown on the plot. # # Here, U-stat obs = -27346, indicating ants in the "New World" exhibited lower rates than "Old World" ants. # # This is not the statistic of the STRAPP test itself, which is conducted across all BAMM posterior samples. # # * The quantile of null statistic distribution at the significant threshold used to define test significance. # # The test will be considered significant (i.e., the null hypothesis is rejected) # # if this value is higher than zero, as shown on the histogram in Section 4.2. # # Here, Q10% = 380.4, so the test is significant (according to this significance threshold). # # * The p-value of the associated STRAPP test. Here, p = 0.088. # # # Plot rates vs. ranges for all time-steps # plot_rates_vs_trait_data_over_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # colors_per_levels = colors_per_ranges) # ## ----plot_rates_vs_traits_biogeo_2lvl_eval, fig.height = 7, fig.width = 8.5, out.width = "100%", eval = is_dev_version(), echo = FALSE---- # # Generate ggplot for time = 10 My # plot_rates_vs_trait_data_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 10, # colors_per_levels = colors_per_ranges) ## ----plot_rates_vs_traits_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.4_plot_rates_vs_traits.PNG") ## ----plot_updated_densityMaps_biogeo_2lvl------------------------------------- # ### 4.5/ Plot updated densityMaps mapping trait evolution for a given 'focal_time' #### # # # ?deepSTRAPP::plot_densityMaps_overlay() # # ## These plots help to visualize the evolution of trait data across the phylogeny, # ## and to focus on tip values at specific time-steps. # # # Display the time-steps # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$time_steps # # ## The next plot shows the evolution of trait data across the whole phylogeny (100-0 My). # # # Plot initial densityMaps (t = 0) # densityMaps_0My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time[[1]] # plot_densityMaps_overlay(densityMaps_0My$densityMaps, # colors_per_levels = colors_per_ranges, # cex_pies = 0.3, # Reduce pie size # fsize = 0.1) # Reduce tip label size # title(main = "Trait evolution for 100-0 My") # # ## The next plot shows the evolution of trait data from root to 10 Mya (100-10 My). # # # Plot updated densityMaps for time-step n°3 = 10 My # densityMaps_10My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time[[3]] # plot_densityMaps_overlay(densityMaps_10My$densityMaps, # colors_per_levels = colors_per_ranges, # cex_pies = 0.4, # Reduce pie size # fsize = 0.1) # Reduce tip label size # title(main = "Trait evolution for 100-10 My") # # ## The next plot shows the evolution of trait data from root to 40 Mya (100-40 My). # # # Plot updated densityMaps for time-step n°9 = 40 My # densityMaps_40My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time[[9]] # plot_densityMaps_overlay(densityMaps_40My$densityMaps, # colors_per_levels = colors_per_ranges, # fsize = 0.2) # Reduce tip label size # title(main = "Trait evolution for 100-40 My") # ## ----plot_updated_densityMaps_biogeo_2lvl_eval, eval = is_dev_version(), echo = FALSE---- # # Plot initial densityMaps (t = 0) # densityMaps_0My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time[[1]] # plot_densityMaps_overlay(densityMaps_0My$densityMaps, # colors_per_levels = colors_per_ranges, # cex_pies = 0.3, # Reduce pie size # fsize = 0.1) # title(main = "Trait evolution for 100-0 My") # # # Plot updated densityMaps for time-step n°9 = 40 My # densityMaps_40My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_trait_data_with_Map_over_time[[9]] # plot_densityMaps_overlay(densityMaps_40My$densityMaps, # colors_per_levels = colors_per_ranges, # fsize = 0.2) # title(main = "Trait evolution for 100-40 My") ## ----plot_updated_densityMaps_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.5_plot_updated_densityMaps_1.PNG") knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.5_plot_updated_densityMaps_2.PNG") ## ----plot_BAMM_rates_biogeo_2lvl---------------------------------------------- # ### 4.6/ Plot updated diversification rates and regimes for a given 'focal_time' #### # # # ?deepSTRAPP::plot_BAMM_rates() # # ## These plots help to visualize the evolution of diversification rates across the phylogeny, # ## and to focus on tip values at specific time-steps. # # # Display the time-steps # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$time_steps # # # Extract root age # root_age <- max(phytools::nodeHeights(Ponerinae_tree_old_calib)[,2]) # # ## The next plot shows the evolution of net diversification rates across the whole phylogeny (100-0 My). # # # Plot diversification rates on initial phylogeny (t = 0) # BAMM_map_0My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time[[1]] # plot_BAMM_rates(BAMM_map_0My, labels = FALSE, par.reset = FALSE) # abline(v = root_age - 10, col = "red", lty = 2) # Show where the phylogeny will be cut for t = 10My # abline(v = root_age - 40, col = "red", lty = 2) # Show where the phylogeny will be cut for t = 40My # title(main = "BAMM rates for 100-0 My") # # ## The next plot shows the evolution of net diversification rates from root to 10 Mya (100-10 My). # # # Plot diversification rates on updated phylogeny for time-step n°3 = 10 My # BAMM_map_10My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time[[3]] # plot_BAMM_rates(BAMM_map_10My, labels = FALSE, # colorbreaks = BAMM_map_10My$initial_colorbreaks$net_diversification) # title(main = "BAMM rates for 100-10 My") # # ## The next plot shows the evolution of net diversification rates from root to 40 Mya (100-40 My). # # # Plot diversification rates on updated phylogeny for time-step n°9 = 40 My # BAMM_map_40My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time[[9]] # plot_BAMM_rates(BAMM_map_40My, labels = FALSE, # colorbreaks = BAMM_map_40My$initial_colorbreaks$net_diversification) # title(main = "BAMM rates for 100-40 My") # ## ----plot_BAMM_rates_biogeo_2lvl_eval_dev, eval = is_dev_version(), echo = FALSE---- # old_par <- par(no.readonly = TRUE) # par(mfrow = c(1, 2)) # # # Plot diversification rates on initial phylogeny (t = 0) # BAMM_map_0My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time[[1]] # plot_BAMM_rates(BAMM_map_0My, labels = FALSE, legend = TRUE, par.reset = FALSE) # abline(v = max(phytools::nodeHeights(Ponerinae_tree_old_calib)[,2]) - 10, col = "red", lty = 2) # Show where the phylogeny will be cut # title(main = "BAMM rates for 100-0 My") # # # Plot diversification rates on updated phylogeny for time-step n°3 = 10 My # BAMM_map_10My <- Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$updated_BAMM_objects_over_time[[3]] # plot_BAMM_rates(BAMM_map_10My, labels = FALSE, legend = TRUE, # colorbreaks = BAMM_map_10My$initial_colorbreaks$net_diversification) # title(main = "BAMM rates for 100-10 My") # # par(old_par) ## ----plot_BAMM_rates_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.6_plot_BAMM_rates.PNG") ## ----plot_traits_vs_rates_on_phylogeny_biogeo_2lvl---------------------------- # ### 4.7/ Plot both trait evolution and diversification rates and regimes updated for a given 'focal_time' #### # # # ?deepSTRAPP::plot_traits_vs_rates_on_phylogeny_for_focal_time() # # ## These plots help to visualize simultaneously the evolution of trait and diversification rates # # across the phylogeny, and to focus on tip values at specific time-steps. # # # Display the time-steps # Ponerinae_deepSTRAPP_biogeo_old_calib_0_40$time_steps # # ## The next plot shows the evolution of ranges and rates across the whole phylogeny (100-0 My). # # # Plot both mapped phylogenies in the present (t = 0) # plot_traits_vs_rates_on_phylogeny_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 0, # ftype = "off", lwd = 0.7, # colors_per_levels = colors_per_ranges, # labels = FALSE, legend = FALSE, # par.reset = FALSE) # # ## The next plot shows the evolution of ranges and rates from root to 10 Mya (100-10 My). # # # Plot both mapped phylogenies for time-step n°3 = 10 My # plot_traits_vs_rates_on_phylogeny_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 10, # ftype = "off", lwd = 1.2, # colors_per_levels = colors_per_ranges, # labels = FALSE, legend = FALSE, # par.reset = FALSE) # # ## The next plot shows the evolution of ranges and rates from root to 40 Mya (100-40 My). # # # Plot both mapped phylogenies for time-step n°9 = 40 My # plot_traits_vs_rates_on_phylogeny_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 40, # ftype = "off", lwd = 1.2, # colors_per_levels = colors_per_ranges, # labels = FALSE, legend = FALSE, # par.reset = FALSE) # ## ----plot_traits_vs_rates_on_phylogeny_biogeo_2lvl_eval_dev, eval = is_dev_version(), echo = FALSE---- # # Plot both mapped phylogenies in the present (t = 0) # plot_traits_vs_rates_on_phylogeny_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 0, # ftype = "off", lwd = 0.7, # colors_per_levels = colors_per_ranges, # labels = FALSE, legend = FALSE, # par.reset = FALSE) # # # Plot both mapped phylogenies for time-step n°9 = 40 My # plot_traits_vs_rates_on_phylogeny_for_focal_time( # deepSTRAPP_outputs = Ponerinae_deepSTRAPP_biogeo_old_calib_0_40, # focal_time = 40, # ftype = "off", lwd = 1.2, # colors_per_levels = colors_per_ranges, # labels = FALSE, legend = FALSE, # par.reset = FALSE) ## ----plot_traits_vs_rates_on_phylogeny_biogeo_2lvl_eval_CRAN, eval = !is_dev_version(), echo = FALSE, out.width = "100%"---- # Plot pre-rendered graph knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.7_plot_traits_vs_rate_maps_1.PNG") knitr::include_graphics("figures/1.3_deepSTRAPP_biogeographic_data_4.7_plot_traits_vs_rate_maps_2.PNG")