<- function (parEst, parSE) {<- parEst %>% mutate (region = sapply (log, extract_region),genus = sapply (species, extract_genus),continent = ifelse (region == "europe" , "EU" , "NA" ),species_region = paste0 (species, "_" , region)<- if ("bfec.shade" %in% colnames (parSE)) {$ bfec.shadeelse {rep (NA_real_ , nrow (parEst))<- tibble (species = parEst$ species,species_region = parEst$ species_region,region = parEst$ region,continent = parEst$ continent,genus = parEst$ genus,shade_sensitivity = parEst$ bfec.shade,shade_se = shade_se,n_trees = parEst$ trees,n_treeYr = parEst$ treeYr%>% filter (! is.na (region))return (shade_data_raw)<- function (shade_data_raw,min_trees = 50 ,min_treeYr = 100 ) {<- shade_data_raw %>% filter (>= min_trees,>= min_treeYr<- shade_data_raw %>% count (genus, continent) %>% pivot_wider (names_from = continent,values_from = n,values_fill = 0 )<- shade_data_filtered %>% count (genus, continent) %>% pivot_wider (names_from = continent,values_from = n,values_fill = 0 )<- setdiff (%>% filter (EU > 0 & NA > 0 ) %>% pull (genus),%>% filter (EU > 0 & NA > 0 ) %>% pull (genus)return (list (shade_data_filtered = shade_data_filtered,lost_genera = lost_genera<- function (shade_data_filtered,exclude_genera = c ("castanea" ),min_trees_per_continent = NULL ) {<- shade_data_filtered %>% filter (! genus %in% exclude_genera)<- df %>% group_by (genus, continent) %>% summarise (shade_mean = mean (shade_sensitivity, na.rm = TRUE ),shade_se = ifelse (n () > 1 ,sd (shade_sensitivity, na.rm = TRUE ) / sqrt (n ()),mean (shade_se, na.rm = TRUE )),n_species = n (),total_trees = sum (n_trees),total_treeYr = sum (n_treeYr),.groups = "drop" if (! is.null (min_trees_per_continent)) {<- shade_by_genus_region %>% filter (total_trees >= min_trees_per_continent) %>% group_by (genus) %>% filter (n () == 2 ) %>% ungroup ()<- shade_by_genus_region %>% pivot_wider (names_from = continent,values_from = c (shade_mean, shade_se,names_sep = "_" %>% filter (! is.na (shade_mean_EU),! is.na (shade_mean_NA)) %>% mutate (diff = shade_mean_EU - shade_mean_NA,eu_more_sensitive = diff < 0 <- nrow (shade_wide)<- sum (shade_wide$ eu_more_sensitive)<- if (n_total >= 5 ) {binom.test (n_eu_more, n_total, p = 0.5 , alternative = "greater" )else NULL return (list (shade_wide = shade_wide,n_genera = n_total,n_eu_more_sensitive = n_eu_more,binom_test = binom_result<- function (shade_comparison) {<- shade_comparison$ shade_wideif (nrow (df) == 0 ) return (NULL )<- range (c (df$ shade_mean_EU,$ shade_mean_NA),na.rm = TRUE ) + c (- 0.3 , 0.3 )ggplot (df, aes (x = shade_mean_NA,y = shade_mean_EU)) + geom_abline (slope = 1 , intercept = 0 ,linetype = "dashed" ,color = "gray50" ) + geom_point (aes (color = eu_more_sensitive),size = 3.5 ) + coord_fixed (xlim = lims,ylim = lims) + scale_color_manual (values = c ("TRUE" = "#E69F00" ,"FALSE" = "#56B4E9" ),labels = c ("EU more sensitive" ,"NA more sensitive" ),name = "" + theme_bw (base_size = 12 )<- function (shade_data_filtered,<- shade_data_filtered %>% group_by (species) %>% summarise (shade_sensitivity = mean (shade_sensitivity, na.rm = TRUE ),.groups = "drop" <- shade_by_species %>% left_join (%>% select (code8, gmPerSeed, maxHt) %>% rename (species = code8),by = "species" %>% mutate (genus = sub ("^([a-z]+).*" , " \\ 1" , species),epithet = tolower (sub ("^[a-z]+" , "" , species)),tree_name = paste0 (toupper (substr (genus, 1 , 1 )),substr (genus, 2 , nchar (genus)),"_" ,return (phylo_data)<- function (shade_data_filtered) {<- shade_data_filtered %>% filter (genus == "quercus" )if (nrow (oak_data) == 0 ) return (NULL )<- oak_data %>% group_by (continent) %>% summarise (mean_shade = mean (shade_sensitivity, na.rm = TRUE ),se_shade = sd (shade_sensitivity, na.rm = TRUE ) / sqrt (n ()),n = n (),total_trees = sum (n_trees),.groups = "drop" <- oak_data$ shade_sensitivity[oak_data$ continent == "EU" ]<- oak_data$ shade_sensitivity[oak_data$ continent == "NA" ]<- if (length (oak_eu) >= 2 && length (oak_na) >= 2 )t.test (oak_eu, oak_na, alternative = "less" ) else NULL <- if (length (oak_eu) >= 2 && length (oak_na) >= 2 )wilcox.test (oak_eu, oak_na, alternative = "less" ) else NULL return (list (oak_data = oak_data,oak_summary = oak_summary,t_test = t_result,wilcox_test = wilcox_result<- function (shade_data_filtered, traits) {<- shade_data_filtered %>% filter (genus == "quercus" ) %>% left_join (%>% select (code8, gmPerSeed) %>% rename (species = code8),by = "species" %>% filter (! is.na (gmPerSeed))if (nrow (oak_data) < 6 ) return (NULL )<- median (oak_data$ gmPerSeed, na.rm = TRUE )<- oak_data %>% mutate (seed_category = ifelse (gmPerSeed > median_seed,"Large seed" , "Small seed" ))<- oak_data %>% group_by (seed_category, continent) %>% summarise (n = n (),mean_shade = mean (shade_sensitivity, na.rm = TRUE ),se_shade = sd (shade_sensitivity, na.rm = TRUE ) / sqrt (n ()),.groups = "drop" return (list (data = oak_data,summary = seed_summary,median_seed = median_seed