Plot varibles vs Elevation

Last updated: 2022-02-04

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Knit directory: ms_mariposas_biodiversity/

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File	Version	Author	Date	Message
html	c814af8	ajpelu	2022-01-18	fix error link ambientales
html	30a1406	ajpelu	2022-01-18	update
html	8d38806	ajpelu	2021-12-30	Build site.
Rmd	533f0a9	ajpelu	2021-12-30	add plot variables and outputs

Objetivo

Crear un plot de variación de los parámetros con la elevación

library(tidyverse)
library(here)
library(ggpubr)
library(ggrepel)

Read data

denraw <- read_csv(here::here("data/densidad_by_year.csv")) 
divraw <- read_csv(here::here("data/diversidad_by_year.csv")) 
riqraw <- read_csv(here::here("data/riqueza_by_year.csv"))

Plot Densidad

densidad_avg <- denraw %>%
  group_by(transecto, site, elev) %>%
  summarise(mean = mean(den, na.rm = TRUE),
            sd = sd(den, na.rm = TRUE),
            se = sd/sqrt(n()))

plot_density <- densidad_avg %>%
  ggplot(aes(x=elev, y = mean, label=site)) +
  geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs"), colour="gray", alpha=.3) +
  # geom_smooth(method="loess", span=.5) +
  geom_errorbar(aes(ymin = mean - se, ymax = mean + se)) +
  geom_point(size=2, shape=21, fill="white") +
  theme_bw() +
  theme(
    panel.grid = element_blank()
  ) +
  ylab("Abundance (n ind / 100 m)") +
  xlab("Elevation") +
  geom_text_repel()

plot_density

Version	Author	Date
30a1406	ajpelu	2022-01-18
8d38806	ajpelu	2021-12-30

Plot Diversidad

diversidad_avg <- divraw %>%
  group_by(transecto, site, elev) %>%
  summarise(mean = mean(diversidad, na.rm = TRUE),
            sd = sd(diversidad, na.rm = TRUE),
            se = sd/sqrt(n()))

plot_diversity <- diversidad_avg %>%
  ggplot(aes(x=elev, y = mean, label = site)) +
  geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs"), colour="gray", alpha=.3) +
  # geom_smooth() +
  geom_errorbar(aes(ymin = mean - se, ymax = mean + se)) +
  geom_point(size=2, shape=21, fill="white") +
  theme_bw() +
  theme(
    panel.grid = element_blank()
  ) +
  ylab("Diversity (Shannon index)") +
  xlab("Elevation") +
  geom_text_repel()

plot_diversity

Version	Author	Date
30a1406	ajpelu	2022-01-18
8d38806	ajpelu	2021-12-30

Plot Riqueza

richness_avg <- riqraw %>%
  group_by(transecto, site, elev) %>%
  summarise(mean = mean(riq, na.rm = TRUE),
            sd = sd(riq, na.rm = TRUE),
            se = sd/sqrt(n()))

plot_richness <- richness_avg %>%
  ggplot(aes(x=elev, y = mean, label = site)) +
  geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs"), colour="gray", alpha=.3) +
  # geom_smooth() +
  geom_errorbar(aes(ymin = mean - se, ymax = mean + se)) +
  geom_point(size=2, shape=21, fill="white") +
  theme_bw() +
  theme(
    panel.grid = element_blank()
  ) +
  ylab("Richness (species number") +
  xlab("Elevation") +
  geom_text_repel()

plot_richness

Version	Author	Date
30a1406	ajpelu	2022-01-18
8d38806	ajpelu	2021-12-30

Todas las variables juntas

p <- bind_rows(
  richness_avg %>% mutate(variable = "riq"),
  diversidad_avg %>% mutate(variable = "div"),
  densidad_avg %>% mutate(variable = "den"))
  
  
mylabel <- c(
  den = "Abundance (n ind / 100 m)",
  div = "Diversity (Shannon index)",
  riq = "Richness (species number)")


plot_variables <- p %>%
  ggplot(aes(x=elev, y = mean, label = site)) +
  geom_smooth(method = "gam", formula = y ~ s(x, bs = "cs"), colour="gray", alpha=.3) +
  # geom_smooth() +
  geom_errorbar(aes(ymin = mean - se, ymax = mean + se)) +
  geom_point(size=2, shape=21, fill="white") +
  theme_bw() +
  theme(
    panel.grid = element_blank(),
    strip.text = element_text(face = "bold"),
    strip.background = element_rect(fill="white")
  ) + geom_text_repel() + 
  facet_wrap(~variable, ncol=1, scales = "free_y",
             labeller = labeller(variable = mylabel),
             strip.position="top") + 
  xlab("Elevation") + ylab("")

ggsave(here::here("figs/plot_variables_elevation.pdf"),
       device = "pdf",
       width = 5, height = 7.5)
plot_variables

Version	Author	Date
30a1406	ajpelu	2022-01-18
8d38806	ajpelu	2021-12-30

dev.off()

null device 
          1

ggsave(plot= plot_variables,
       here::here("figs/plot_variables_elevation.png"),
       device = "png",
       dpi = 300,
       width = 5, height = 7.5)

sessionInfo()

R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.3

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

locale:
[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] ggrepel_0.9.1   ggpubr_0.4.0    here_1.0.1      forcats_0.5.1  
 [5] stringr_1.4.0   dplyr_1.0.6     purrr_0.3.4     readr_1.4.0    
 [9] tidyr_1.1.3     tibble_3.1.2    ggplot2_3.3.5   tidyverse_1.3.1
[13] workflowr_1.7.0

loaded via a namespace (and not attached):
 [1] nlme_3.1-152      fs_1.5.0          lubridate_1.7.10  httr_1.4.2       
 [5] rprojroot_2.0.2   tools_4.0.2       backports_1.2.1   bslib_0.2.4      
 [9] utf8_1.1.4        R6_2.5.1          DBI_1.1.1         mgcv_1.8-33      
[13] colorspace_2.0-2  withr_2.4.1       tidyselect_1.1.1  processx_3.5.1   
[17] curl_4.3          compiler_4.0.2    git2r_0.28.0      textshaping_0.3.2
[21] cli_2.5.0         rvest_1.0.0       xml2_1.3.2        labeling_0.4.2   
[25] sass_0.3.1        scales_1.1.1.9000 callr_3.7.0       systemfonts_1.0.0
[29] digest_0.6.27     foreign_0.8-81    rmarkdown_2.8     rio_0.5.16       
[33] pkgconfig_2.0.3   htmltools_0.5.2   highr_0.8         dbplyr_2.1.1     
[37] fastmap_1.1.0     rlang_0.4.12      readxl_1.3.1      rstudioapi_0.13  
[41] farver_2.1.0      jquerylib_0.1.3   generics_0.1.0    jsonlite_1.7.2   
[45] zip_2.1.1         car_3.0-10        magrittr_2.0.1    Matrix_1.3-2     
[49] Rcpp_1.0.7        munsell_0.5.0     fansi_0.4.2       abind_1.4-5      
[53] lifecycle_1.0.1   stringi_1.7.4     whisker_0.4       yaml_2.2.1       
[57] carData_3.0-4     grid_4.0.2        promises_1.2.0.1  crayon_1.4.1     
[61] lattice_0.20-41   haven_2.3.1       splines_4.0.2     hms_1.0.0        
[65] knitr_1.31        ps_1.5.0          pillar_1.6.1      ggsignif_0.6.0   
[69] reprex_2.0.0      glue_1.4.2        evaluate_0.14     getPass_0.2-2    
[73] data.table_1.14.0 modelr_0.1.8      vctrs_0.3.8       httpuv_1.5.5     
[77] cellranger_1.1.0  gtable_0.3.0      assertthat_0.2.1  xfun_0.23        
[81] openxlsx_4.2.3    broom_0.7.9       rstatix_0.6.0     later_1.1.0.1    
[85] ragg_1.1.1        ellipsis_0.3.2