Last updated: 2022-09-16

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Rmd a449c23 ajpelu 2022-09-16 add correlations

Prepare data

Warning: package 'ggstatsplot' was built under R version 4.0.5
Warning: replacing previous import 'dplyr::collapse' by 'glue::collapse' when
loading 'statsExpressions'
Warning: package 'statsExpressions' was built under R version 4.0.5
den <- raster::raster(here::here("data/density.ovr"))
riq <- raster::raster(here::here("data/richness.ovr"))
div <- raster::raster(here::here("data/diversity_v2.ovr"))

s <- stack(den, riq, div)

df <-, xy=TRUE) %>% 


cor_den_rich_np <- ggscatterstats(df, 
               x = density, y = richness, 
               marginal = FALSE, 
               type = "parametric", 
               point.args = list(fill="gray", alpha = 0.8),
               smooth.line.args = 
                 list(method = "gam", formula = y ~ s(x, bs = "cs"),
                      color = "blue"))

cor_den_div_np <- ggscatterstats(df, 
               x = density, y = diversity_v2, 
               marginal = FALSE, 
               type = "nonparametric",
               point.args = list(fill="gray", alpha = 0.2),
               smooth.line.args = 
                 list(method = "gam", formula = y ~ s(x, bs = "cs"),
                      color = "blue"))

cor_div_ric_np <-  ggscatterstats(df, 
                               y = richness, x = diversity_v2, 
                               marginal = FALSE, 
                               type = "nonparametric",
                               point.args = list(fill="gray", alpha = 0.2),
                               smooth.line.args = 
                                 list(method = "gam", formula = y ~ s(x, bs = "cs"),
                                      color = "blue"))

  filename = "figs/cor_den_rich_np.png",
  plot = cor_den_rich_np,
  width = 8,
  height = 8,
  device = "png"

  filename = "figs/cor_den_div_np.png",
  plot = cor_den_div_np,
  width = 8,
  height = 8,
  device = "png"

  filename = "figs/cor_div_ric_np.png",
  plot = cor_div_ric_np,
  width = 8,
  height = 8,
  device = "png"


mylabel <- c(
  den = "Abundance (n ind / 100 m)",
  div = "Diversity (Shannon index)",
  riq = "Richness (species number)")
ct <- corr_test(df, x = density, y = richness, type = "parametric")

cor_den_rich_p <- ggplot(df, aes(x=density, y=richness)) + 
  geom_point(col="gray", size=.3, alpha=.2) + 
  theme_minimal() + 
  geom_smooth(method = "gam", 
              formula = y ~ s(x, bs = "cs"),
              color = "blue", 
              size =.5) + 
  labs(subtitle = ggplot2::expr(paste(
    widehat(italic("r"))["Pearson"], "=0.727, ", italic("p"), "<", "0.001")),
    x = mylabel["den"], 
    y = mylabel["riq"])


ct <- corr_test(df, x = density, y = diversity_v2, type = "parametric")

cor_den_div_p <- ggplot(df, aes(x = density, y = diversity_v2)) + 
  geom_point(col="gray", size=.3, alpha=0.2) + 
  theme_minimal() + 
  geom_smooth(method = "gam", 
              formula = y ~ s(x, bs = "cs"),
              color = "blue", 
              size =.5) + 
  labs(subtitle = ggplot2::expr(paste(
    widehat(italic("r"))["Pearson"], "=0.773, ", italic("p"), "<", "0.001")),
    x = mylabel["den"], 
    y = mylabel["div"])

ct <- corr_test(df, x = diversity_v2, y = richness, type = "parametric")

cor_div_ric_p <- ggplot(df, aes(x = diversity_v2, y = richness)) + 
  geom_point(col="gray", size=.3, alpha=0.2) + 
  theme_minimal() + 
  geom_smooth(method = "gam", 
              formula = y ~ s(x, bs = "cs"),
              color = "blue", 
              size =.5) + 
  labs(subtitle = ggplot2::expr(paste(
    widehat(italic("r"))["Pearson"], "=0.673, ", italic("p"), "<", "0.001")),
    x = mylabel["div"],
    y = mylabel["riq"])


  filename = "figs/cor_den_rich_p.png",
  plot = cor_den_rich_p,
  width = 8,
  height = 8,
  device = "png"

  filename = "figs/cor_den_div_p.png",
  plot = cor_den_div_p,
  width = 8,
  height = 8,
  device = "png"

  filename = "figs/cor_div_ric_p.png",
  plot = cor_div_ric_p,
  width = 8,
  height = 8,
  device = "png"

R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS  10.16

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] statsExpressions_1.3.1 here_1.0.1             ggstatsplot_0.9.1     
 [4] ggpubr_0.4.0           rgdal_1.5-23           fasterize_1.0.3       
 [7] raster_3.4-5           sp_1.4-5               forcats_0.5.1         
[10] stringr_1.4.0          dplyr_1.0.6            purrr_0.3.4           
[13] readr_1.4.0            tidyr_1.1.3            tibble_3.1.2          
[16] ggplot2_3.3.5          tidyverse_1.3.1        workflowr_1.7.0       

loaded via a namespace (and not attached):
  [1] TH.data_1.0-10         colorspace_2.0-2       ggsignif_0.6.3        
  [4] ellipsis_0.3.2         rio_0.5.16             rprojroot_2.0.2       
  [7] estimability_1.3       parameters_0.17.0      fs_1.5.0              
 [10] mc2d_0.1-18            rstudioapi_0.13        farver_2.1.0          
 [13] MatrixModels_0.4-1     fansi_0.4.2            mvtnorm_1.1-1         
 [16] lubridate_1.7.10       xml2_1.3.2             codetools_0.2-18      
 [19] splines_4.0.2          knitr_1.31             zeallot_0.1.0         
 [22] jsonlite_1.7.2         broom_0.7.9            dbplyr_2.1.1          
 [25] effectsize_0.6.0.1     compiler_4.0.2         httr_1.4.2            
 [28] emmeans_1.5.4          backports_1.2.1        assertthat_0.2.1      
 [31] Matrix_1.3-2           fastmap_1.1.0          cli_2.5.0             
 [34] later_1.1.0.1          htmltools_0.5.2        tools_4.0.2           
 [37] coda_0.19-4            gtable_0.3.0           glue_1.4.2            
 [40] Rcpp_1.0.7             carData_3.0-4          cellranger_1.1.0      
 [43] jquerylib_0.1.3        vctrs_0.3.8            nlme_3.1-152          
 [46] insight_0.17.0         xfun_0.30              ps_1.5.0              
 [49] openxlsx_4.2.3         rvest_1.0.0            lifecycle_1.0.1       
 [52] gtools_3.8.2           rstatix_0.6.0          getPass_0.2-2         
 [55] MASS_7.3-53            zoo_1.8-8              scales_1.1.1.9000     
 [58] BayesFactor_0.9.12-4.3 ragg_1.1.1             hms_1.0.0             
 [61] promises_1.2.0.1       parallel_4.0.2         sandwich_3.0-0        
 [64] rematch2_2.1.2         yaml_2.2.1             curl_4.3.2            
 [67] pbapply_1.4-3          sass_0.4.1             reshape_0.8.8         
 [70] stringi_1.7.4          highr_0.8              paletteer_1.3.0       
 [73] bayestestR_0.11.5      zip_2.1.1              systemfonts_1.0.0     
 [76] rlang_0.4.12           pkgconfig_2.0.3        evaluate_0.14         
 [79] lattice_0.20-41        labeling_0.4.2         patchwork_1.1.1       
 [82] processx_3.5.1         tidyselect_1.1.1       plyr_1.8.6            
 [85] magrittr_2.0.1         R6_2.5.1               generics_0.1.0        
 [88] multcomp_1.4-16        DBI_1.1.1              mgcv_1.8-33           
 [91] pillar_1.6.1           haven_2.3.1            whisker_0.4           
 [94] foreign_0.8-81         withr_2.5.0            survival_3.2-7        
 [97] datawizard_0.4.0       abind_1.4-5            performance_0.8.0     
[100] WRS2_1.1-3             modelr_0.1.8           crayon_1.4.1          
[103] car_3.0-10             utf8_1.1.4             correlation_0.8.0     
[106] rmarkdown_2.14         grid_4.0.2             readxl_1.3.1          
[109] data.table_1.14.0      callr_3.7.0            git2r_0.28.0          
[112] reprex_2.0.0           digest_0.6.27          xtable_1.8-4          
[115] httpuv_1.5.5           textshaping_0.3.2      munsell_0.5.0         
[118] bslib_0.3.1