explore-trends

Last updated: 2021-05-03

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Rmd	ed171ab	Antonio J Perez-Luque	2021-05-03	explore abundance plots over time

Explore trends

knitr::opts_chunk$set(echo = TRUE, 
                      warning = FALSE, 
                      message = FALSE)

library("tidyverse")
library("here")
library("plotly")

Read data and compute average abundance by year

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) %>% 
  group_by(especie, 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))

bird_theme <- 
  ggplot2::theme_bw() + 
  ggplot2::theme(
    panel.grid.minor = element_blank(),
    strip.background = element_blank()
  )

We explore the abundance over time for each habitat, and then select those species with n years > 3.

Summit environment

cumbres.plotall <- passerine.ab %>% 
  filter(habitat == "cumbres") %>% 
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

Plot only the selected taxa (contacted in more than three years)

cumbres.plot <- passerine.ab %>% 
  filter(habitat == "cumbres") %>% 
  filter(stringr::str_detect(especie, "Card|Oena|Phoeni|collaris")) %>%
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme + 
  ggtitle("Summits")

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

Juniper scrublands

enebral.plotall <- passerine.ab %>% 
  filter(habitat == "enebral") %>% 
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme +
  theme(axis.text.x = element_text(angle=90))

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

Plot only the selected taxa (contacted in more than three years)

enebral.plot <- passerine.ab %>% 
  filter(habitat == "enebral") %>% 
  filter(stringr::str_detect(especie, 
                             "Alauda|Anthus|cannabina|Embe|Oena|Phoeni|collaris|rubicola|conspici|Troglo")) %>%
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie, nrow = 5) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme + 
  theme(axis.text.x = element_text(angle=90)) +  
  ggtitle("Juniper")

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

Oak populations

robledal.plotall <- passerine.ab %>% 
  filter(habitat == "robledal") %>% 
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme +
  theme(axis.text.x = element_text(angle=90))

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

Plot only the selected taxa (contacted in more than three years)

robledal.plot <- passerine.ab %>% 
  filter(habitat == "robledal") %>% 
  filter(stringr::str_detect(especie, 
                             "Aeg|cannabina|Certhia|Cyanis|Erith|Fringi|Garrulus|Lopho|Lullula|Parus|Peripares|Phoeni|bonelli|Regulus|rubicola|serinus|Sitta|atricapilla|cantillans|merula|visci|Troglo")) %>%
  ggplot(aes(x=as.factor(year), y=ab_avg)) + 
  geom_errorbar(aes(ymin = ab_avg - se, 
                    ymax = ab_avg + se),
                width = 0.2) +
  geom_point() +
  facet_wrap(~especie, nrow = 5) + 
  ylab("abundance (ind / 10ha)") + xlab("") + 
  bird_theme + 
  theme(axis.text.x = element_text(angle=90)) +  
  ggtitle("Oak woodlands")

Version	Author	Date
ebba38c	Antonio J Perez-Luque	2021-05-03

null device 
          1

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] plotly_4.9.3    here_1.0.1      forcats_0.5.1   stringr_1.4.0  
 [5] dplyr_1.0.4     purrr_0.3.4     readr_1.4.0     tidyr_1.1.2    
 [9] tibble_3.0.6    ggplot2_3.3.3   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      lazyeval_0.2.2    readxl_1.3.1     
[17] rstudioapi_0.13   data.table_1.13.6 whisker_0.4       jquerylib_0.1.3  
[21] rmarkdown_2.6.6   labeling_0.4.2    htmlwidgets_1.5.3 munsell_0.5.0    
[25] broom_0.7.4       compiler_4.0.2    httpuv_1.5.5      modelr_0.1.8     
[29] xfun_0.20         pkgconfig_2.0.3   htmltools_0.5.1.1 tidyselect_1.1.0 
[33] viridisLite_0.3.0 crayon_1.4.1      dbplyr_2.1.0      withr_2.4.1      
[37] later_1.1.0.1     grid_4.0.2        jsonlite_1.7.2    gtable_0.3.0     
[41] lifecycle_1.0.0   DBI_1.1.1         git2r_0.28.0      magrittr_2.0.1   
[45] scales_1.1.1      cli_2.3.0         stringi_1.5.3     farver_2.0.3     
[49] fs_1.5.0          promises_1.2.0.1  xml2_1.3.2        bslib_0.2.4      
[53] ellipsis_0.3.1    generics_0.1.0    vctrs_0.3.6       tools_4.0.2      
[57] glue_1.4.2        hms_1.0.0         yaml_2.2.1        colorspace_2.0-0 
[61] rvest_0.3.6       knitr_1.31        haven_2.3.1       sass_0.3.1

explore-trends

Antonio J Perez-Luque

2021-04-29

Explore trends

Summit environment

Juniper scrublands

Oak populations