Last updated: 2021-05-07

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Knit directory: booksn_dispersantes/

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File Version Author Date Message
Rmd 73addc3 Antonio J Perez-Luque 2021-05-07 add richness analysis
html dad5db5 Antonio J Perez-Luque 2021-05-06 Build site.
Rmd 4ef40a7 Antonio J Perez-Luque 2021-05-06 compare diversity by temporal steps
html 12af27d Antonio J Perez-Luque 2021-05-03 Build site.
Rmd 5306189 Antonio J Perez-Luque 2021-05-03 compute diversity (alpha) analysis

Diversity analysis

  • Compute Simpson and Shannon diversity index. See diversity functions in vegan pkg.
knitr::opts_chunk$set(echo = TRUE, 
                      warning = FALSE, 
                      message = FALSE)
library("tidyverse")
library("here")
library("vegan")
passerine <- read_csv(here::here("data/passerine.csv")) 
passerine_abbreviations <- read_csv(here::here("data/passerine_abbrev.csv")) 

passerine.ab <- passerine %>% 
  rename(sp = sp.abb) %>% 
  dplyr::select(-especie) %>% 
  group_by(sp, year, habitat) %>% 
  summarise(ab_avg = round(mean(den, na.rm=TRUE),2), 
            sd = sd(den, na.rm = TRUE), 
            se = sd/sqrt(length(den)), 
            n = length(den))

df <- passerine.ab %>% 
  unite("site", habitat:year, sep="_", remove = FALSE) %>% 
  dplyr::select(-sd, -se, -n) %>% 
  pivot_wider(names_from = sp, 
              values_from = ab_avg, 
              values_fill = 0)

Create a function to compute Simpson and Shannon diversity indices

computeDiversity <- function(d, hab, ...){
  
  df.habitat <- d %>% 
    filter(habitat == hab) %>% 
  dplyr::select(-habitat, -site) %>% 
  dplyr::select_if(
    negate(function(x) is.numeric(x) && sum(x) == 0)) %>%
    column_to_rownames("year")
  

  shannon <- diversity(df.habitat, "shannon") %>%
    as.data.frame() %>% rownames_to_column("year") %>%
    rename(shannon = starts_with("."))

  simpson <- diversity(df.habitat, "simpson") %>%
    as.data.frame() %>%
    rownames_to_column("year") %>%
    rename(simpson = starts_with("."))

  diver <- shannon %>%
  inner_join(simpson) %>%
  mutate(habitat = hab)
  
  return(diver)
}
  • Compute diversity index for each site
diver.summits <- computeDiversity(df, "cumbres")
diver.juniper <- computeDiversity(df, "enebral")
diver.robledal <- computeDiversity(df, "robledal")

diversity_index <- bind_rows(diver.summits, diver.juniper, diver.robledal)
write_csv(diversity_index, here::here("output/diversity/alfa_diversity.csv"))
diversity_plot <- diversity_index %>% 
  filter(!(habitat == "cumbres" & year == 2013)) %>% 
  ggplot(
  aes(x=year, y=shannon, colour=habitat, group=habitat)) +
    geom_point() + geom_line() +
  geom_smooth(method = "lm", 
              se=FALSE, size = .5, linetype="dashed") + 
  ylab("Shannon Index (H')") + 
  theme_bw() + 
  theme(
    panel.grid = element_blank(),
    #panel.grid.major.x = element_blank(),
    strip.background = element_blank()
  )


ggsave(here::here("output/diversity/diversity_habitat.pdf"),
       width = 18, height = 12, units = "cm")
diversity_plot

Version Author Date
12af27d Antonio J Perez-Luque 2021-05-03
dev.off()
null device 
          1 

Compare three temporal times

  • Generate three temporal times: 1983; 2009: mean for 2008 - 2009; and 2018: mean for 2017 - 2018.
shannon <- diversity_index %>% 
  filter(year %in% c(1981:1985, 2008:2009, 2017:2018)) %>% 
  mutate(yearF = case_when(
    year %in% c(1981:1985) ~ as.character(1983), 
    year %in% c(2008:2009) ~ as.character(2009),
    year %in% c(2017:2018) ~ as.character(2018)
  )) %>% 
  group_by(yearF, habitat) %>% 
  summarise(mean = mean(shannon, na.rm=TRUE), 
            sd = sd(shannon, na.rm=TRUE),
            se = sd/sqrt(length(shannon)))

shannon %>% 
  ggplot(aes(x=yearF, y=mean, group=1)) + 
  geom_point() +
  geom_line() + 
  # geom_bar(stat="identity", fill="black") + 
  geom_errorbar(aes(ymax = mean + se, ymin= mean - se), 
                width = .2, size = .3) + 
  facet_wrap(~habitat, ncol = 1) + 
  theme_bw() +
  theme(
    panel.grid.minor = element_blank(),
    strip.background = element_blank()
  ) + 
  ylab("Shannon Index (H')") + xlab("")

Version Author Date
dad5db5 Antonio J Perez-Luque 2021-05-06

Richness

richness <- passerine.ab %>% 
  group_by(habitat, year) %>% 
  summarise(richness = length(sp))
write_csv(richness, here::here("output/diversity/richness.csv"))
richness %>% 
  ggplot(aes(as.factor(year), richness)) +
  geom_point() + 
  geom_path(aes(group=habitat)) + 
  facet_wrap(~habitat, nrow = 3) + 
  ylab("Richness (n sps)") + xlab("") + 
  theme_bw() + 
  theme(
    panel.grid.minor = element_blank(),
    strip.background = element_blank()
  )


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] vegan_2.5-7     lattice_0.20-41 permute_0.9-5   here_1.0.1     
 [5] forcats_0.5.1   stringr_1.4.0   dplyr_1.0.4     purrr_0.3.4    
 [9] readr_1.4.0     tidyr_1.1.2     tibble_3.0.6    ggplot2_3.3.3  
[13] tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.6        lubridate_1.7.10  assertthat_0.2.1  rprojroot_2.0.2  
 [5] digest_0.6.27     R6_2.5.0          cellranger_1.1.0  backports_1.2.1  
 [9] reprex_1.0.0      evaluate_0.14     highr_0.8         httr_1.4.2       
[13] pillar_1.4.7      rlang_0.4.10      readxl_1.3.1      rstudioapi_0.13  
[17] whisker_0.4       jquerylib_0.1.3   Matrix_1.3-2      rmarkdown_2.6.6  
[21] labeling_0.4.2    splines_4.0.2     munsell_0.5.0     broom_0.7.4      
[25] compiler_4.0.2    httpuv_1.5.5      modelr_0.1.8      xfun_0.20        
[29] pkgconfig_2.0.3   mgcv_1.8-33       htmltools_0.5.1.1 tidyselect_1.1.0 
[33] crayon_1.4.1      dbplyr_2.1.0      withr_2.4.1       later_1.1.0.1    
[37] MASS_7.3-53       grid_4.0.2        nlme_3.1-152      jsonlite_1.7.2   
[41] gtable_0.3.0      lifecycle_1.0.0   DBI_1.1.1         git2r_0.28.0     
[45] magrittr_2.0.1    scales_1.1.1      cli_2.3.0         stringi_1.5.3    
[49] farver_2.0.3      fs_1.5.0          promises_1.2.0.1  xml2_1.3.2       
[53] bslib_0.2.4       ellipsis_0.3.1    generics_0.1.0    vctrs_0.3.6      
[57] tools_4.0.2       glue_1.4.2        hms_1.0.0         parallel_4.0.2   
[61] yaml_2.2.1        colorspace_2.0-0  cluster_2.1.0     rvest_0.3.6      
[65] knitr_1.31        haven_2.3.1       sass_0.3.1