preparations for archiving

analysis/00-fit-LRR-models-maintext-code-for-eve/regional-ES-local.R

@@ -3,9 +3,11 @@ library(tidyverse)
 library(brms)
 
 
-# load('/data/idiv_chase/sablowes/homogenisation/data/allLRR_meta.Rdata')
-load('~/Dropbox/1current/spatial_composition_change/results/allLRR_meta-new.Rdata')
-load('~/Dropbox/1current/spatial_composition_change/results/ts-regions.Rdata')
+
+load('~/Dropbox/1current/spatial_composition_change/WhittakerBetaChange/analysis/data/all_meta-new.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/WhittakerBetaChange/analysis/data/allLRR_meta-new.Rdata')
+# id for regions in time series analyses
+load('~/Dropbox/1current/spatial_composition_change/WhittakerBetaChange/analysis/data/ts-regions.Rdata')
 
 regional_jk_summary <- regional_jknife_LRR %>% 
   group_by(regional_level) %>% 
@@ -61,7 +63,7 @@ regional_ES_jk_norm_sigma2_ts_anti <- brm(bf(ES_gamma ~ 1 + (1 | regional_level)
 			     mutate(logdt = log(dt),
 			            regional_level = ifelse(regional_level == 'i_Lee (Florida (United States))',
 			                                    'i_Lee', regional_level)) %>% 
-			     filter(regional_level %in% ts_regions$regional_level),
+			     filter(!regional_level %in% ts_regions$regional_level),
 			   prior = c(prior(normal(0,1), class = Intercept),
 			             prior(normal(0,1), class = sd),
 			             prior(normal(0,1), class = Intercept, dpar = sigma),

analysis/Fig2-1-wrangle.R

@@ -5,7 +5,7 @@ library(tidybayes)
 library(cowplot)
 
 
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-641269.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-3823365.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/data/all_meta-new.Rdata')
 
@@ -15,7 +15,7 @@ all_meta <- all_meta %>%
                                  'i_Lee', regional_level))
 
 set.seed(101)
-local_overall_post <- gather_draws(local_ES_norm_sigma2, b_Intercept) %>% 
+local_overall_post <- gather_draws(local_ES_norm_sigma, b_Intercept) %>% 
   # 90% credible interval of intercept
   median_qi(.width = 0.9)  
 
@@ -33,8 +33,8 @@ overall_intercept <- bind_cols(local_overall_post %>%
                                         regional_Q05 = .lower) %>% 
                                  select(regional_intercept, regional_Q95, regional_Q05))
 
-local_posterior_ES <- local_ES_norm_sigma2$data %>% 
-  add_predicted_draws(object = local_ES_norm_sigma2, ndraws = 1000)
+local_posterior_ES <- local_ES_norm_sigma$data %>% 
+  add_predicted_draws(object = local_ES_norm_sigma, ndraws = 1000)
 
 local_summary_ES <- local_posterior_ES %>% 
   group_by(regional_level) %>% 

analysis/Fig2-2-plot.R

@@ -120,7 +120,7 @@ alt_A <-
 
 # use full posterior of the overall intercept estimates to calculate average rate of 
 # change in beta-diversity (d)
-overall_d <- bind_cols(gather_draws(local_ES_norm_sigma2, b_Intercept, ndraws = 4000) %>%
+overall_d <- bind_cols(gather_draws(local_ES_norm_sigma, b_Intercept, ndraws = 4000) %>%
                          ungroup() %>%
                          select(x = .value),
                        gather_draws(regional_ES_jk_norm_sigma2, b_Intercept, ndraws = 4000) %>%
@@ -162,6 +162,6 @@ ggsave('~/Dropbox/1current/spatial_composition_change/figures/results/Fig2.pdf',
        width = 184, height = 100, units = 'mm')
 
 overall_d %>% 
-  summarise(median(dS),
-            quantile(dS, 0.05),
-            quantile(dS, 0.95))
+  summarise(median(d),
+            quantile(d, 0.05),
+            quantile(d, 0.95))

analysis/FigS2.R

@@ -71,5 +71,5 @@ ggplot() +
 
 
 # two column fig Sci Adv
-ggsave('~/Dropbox/1current/spatial_composition_change/figures/results/FigS1.pdf',
+ggsave('~/Dropbox/1current/spatial_composition_change/figures/results/FigS2.pdf',
        width = 184, height = 150, units = 'mm')

analysis/FigS3.R

@@ -86,7 +86,7 @@ gamma_forest <- ggplot() +
 
 # use full posterior of the overall average rates of changes at the alpha- 
 # and gamma-scales to estimate average beta-scale change
-overall_d <- bind_cols(gather_draws(local_ES_norm_sigma2, b_Intercept, ndraws = 4000) %>%
+overall_d <- bind_cols(gather_draws(local_ES_norm_sigma, b_Intercept, ndraws = 4000) %>%
                          ungroup() %>%
                          select(x = .value),
                        gather_draws(regional_ES_jk_norm_sigma2, b_Intercept, ndraws = 4000) %>%

analysis/FigS4-and-S6.R

@@ -12,10 +12,10 @@ library(tidybayes)
 library(cowplot)
 
 # anti-ts data (models fit to two time points only)
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-anti-730659.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-anti-3823550.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma-ts-anti.Rdata')
 # time series data (models fit to data > 2 time points)
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-730645.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-3802034.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma-ts.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/data/all_meta-new.Rdata')
 
@@ -25,7 +25,7 @@ all_meta <- all_meta %>%
                                  'i_Lee', regional_level))
 
 set.seed(101)
-anti_ts_local <- gather_draws(local_ES_norm_sigma2_ts_anti, b_Intercept) %>% 
+anti_ts_local <- gather_draws(local_ES_norm_sigma_ts_anti, b_Intercept) %>% 
   # 90% credible interval of intercept
   median_qi(.width = 0.9)  
 
@@ -122,7 +122,7 @@ anti_ts_two_scale <-
   labs(y = expression(paste(gamma-scale, ' effect size [log(S) / year]')),
        x = expression(paste(alpha-scale, ' effect size [log(S) / year]')),
        # tag = 'a',
-       title = expression(paste('Models fit to data with only\ntwo time points (n = 298)'))
+       title = expression(paste('Models fit to data with only\ntwo time points (n = 296)'))
        ) +
   scale_x_continuous(breaks = c(0, 3e-3, 6e-3)) +
   scale_y_continuous(breaks = c(0, 3e-4, 6e-4)) +
@@ -142,7 +142,7 @@ ts_d <- bind_cols(gather_draws(local_ES_norm_sigma2_ts, b_Intercept, ndraws = 40
                          select(y = .value)) %>%
   mutate(d = y - x)
 
-anti_ts_d <- bind_cols(gather_draws(local_ES_norm_sigma2_ts_anti, b_Intercept, ndraws = 4000) %>%
+anti_ts_d <- bind_cols(gather_draws(local_ES_norm_sigma_ts_anti, b_Intercept, ndraws = 4000) %>%
                     ungroup() %>%
                     select(x = .value),
                   gather_draws(regional_ES_jk_norm_sigma2_ts_anti, b_Intercept, ndraws = 4000) %>%
@@ -186,7 +186,7 @@ fig3_beta_anti_ts <-
                .width = c(0.50, 0.9)) +
   geom_vline(xintercept = 0, lty = 2, colour = '#bdbdbd') +
   scale_x_continuous(breaks = seq(from = -0.01, to = 0.01, by = 0.001),
-                     labels = c('-0.01', '', '-0.008', '', '', '', '-0.004', '', '', '', '0', '', '' , '', 
+                     labels = c('', '', '-0.008', '', '', '', '-0.004', '', '', '', '0', '', '' , '', 
                                 '0.004', '', '', '', '', '', '0.01')) +
   labs(x = expression(paste(Delta, beta, ' - diversity . ', year^-1)),
        y = '') +
@@ -218,8 +218,8 @@ ggsave('~/Dropbox/1current/spatial_composition_change/figures/results/FigS4.pdf'
 ts_local_posterior_ES <- local_ES_norm_sigma2_ts$data %>% 
   add_predicted_draws(object = local_ES_norm_sigma2_ts, ndraws = 1000)
 
-anti_ts_local_posterior_ES <- local_ES_norm_sigma2_ts_anti$data %>% 
-  add_predicted_draws(object = local_ES_norm_sigma2_ts_anti, ndraws = 1000)
+anti_ts_local_posterior_ES <- local_ES_norm_sigma_ts_anti$data %>% 
+  add_predicted_draws(object = local_ES_norm_sigma_ts_anti, ndraws = 1000)
 
 ts_regional_posterior_ES <- regional_ES_jk_norm_sigma2_ts$data %>% 
   add_predicted_draws(object = regional_ES_jk_norm_sigma2_ts, ndraws = 1000)
@@ -301,9 +301,9 @@ concept_colour = c('Gain low occupancy' = '#61CDE0',
                    'Gain high occupancy' = '#D9D956')
 
 # first, a plot to create the legend
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-641269.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-3823365.Rdata')
 col_shape_leg_plot <- left_join(anti_ts_regional_d_summary,
-                                local_ES_norm_sigma2$data %>% 
+                                local_ES_norm_sigma$data %>% 
                                   distinct(regional_level, sample_type, logdt)) %>% 
   mutate(dt = exp(logdt)) %>% 
   left_join(all_meta) %>% 
@@ -333,7 +333,7 @@ col_shape_leg <- gg_legend(col_shape_leg_plot)
 
 anti_ts_beta_dt <-
 left_join(anti_ts_regional_d_summary,
-          local_ES_norm_sigma2_ts_anti$data %>% 
+          local_ES_norm_sigma_ts_anti$data %>% 
             distinct(regional_level, logdt)) %>% 
   mutate(dt = exp(logdt)) %>% 
   left_join(all_meta) %>% 

analysis/FigS5.R

@@ -9,11 +9,11 @@ library(tidybayes)
 library(cowplot)
 
 
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-641269.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-3823365.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma.Rdata')
 
 
-dt <- local_ES_norm_sigma2$data %>% 
+dt <- local_ES_norm_sigma$data %>% 
   as_tibble() %>% 
   mutate(dt = exp(logdt)) %>% 
   group_by(sample_type) %>% 
@@ -25,7 +25,7 @@ dt <- local_ES_norm_sigma2$data %>%
               values_from = min_dt:max_logdt)
 
 
-sigma_model_summary <- gather_draws(local_ES_norm_sigma2, 
+sigma_model_summary <- gather_draws(local_ES_norm_sigma, 
              b_sigma_Intercept,
              b_sigma_sample_typeresurvey,
              b_sigma_logdt,
@@ -47,7 +47,7 @@ sigma_model_summary <- gather_draws(local_ES_norm_sigma2,
               values_from = c(.value, .lower, .upper)) %>% 
   bind_cols(dt) 
 
-sigma_local_CI <- local_ES_norm_sigma2$data %>% 
+sigma_local_CI <- local_ES_norm_sigma$data %>% 
   as_tibble() %>%
   group_by(sample_type) %>% 
   modelr::data_grid(logdt, n = 51) %>% 

analysis/FigS6-1-wrangle-anti-ts-data.R

@@ -6,12 +6,12 @@ library(tidybayes)
 library(cowplot)
 
 
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-anti-730659.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-anti-3823550.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma-ts-anti.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/data/all_meta-new.Rdata')
 
 set.seed(101)
-local_overall_post <- gather_draws(local_ES_norm_sigma2_ts_anti, b_Intercept) %>% 
+local_overall_post <- gather_draws(local_ES_norm_sigma_ts_anti, b_Intercept) %>% 
   # 90% credible interval of intercept
   median_qi(.width = 0.9)  
 
@@ -29,8 +29,8 @@ overall_intercept <- bind_cols(local_overall_post %>%
                                         regional_Q05 = .lower) %>% 
                                  select(regional_intercept, regional_Q95, regional_Q05))
 
-local_posterior_ES <- local_ES_norm_sigma2_ts_anti$data %>% 
-  add_predicted_draws(object = local_ES_norm_sigma2_ts_anti, ndraws = 1000)
+local_posterior_ES <- local_ES_norm_sigma_ts_anti$data %>% 
+  add_predicted_draws(object = local_ES_norm_sigma_ts_anti, ndraws = 1000)
 
 local_summary_ES <- local_posterior_ES %>% 
   group_by(regional_level) %>% 

analysis/FigS6-1-wrangle-ts-data.R

@@ -6,7 +6,7 @@ library(cowplot)
 
 
 # load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-es-norm-sigma2-25428714.Rdata')
-load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-730645.Rdata')
+load('~/Dropbox/1current/spatial_composition_change/results/model_fits/local-ES-norm-sigma-ts-3802034.Rdata')
 # load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-es-jk-norm-sigma2-25428781.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/results/model_fits/regional-ES-jk-norm-sigma-ts.Rdata')
 load('~/Dropbox/1current/spatial_composition_change/data/all_meta-new.Rdata')