Last updated: 2022-01-18
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Knit directory: ms_mariposas_biodiversity/
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library(tidyverse)
library(here)
library(kableExtra)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"))
richness <- read_csv(here::here("data/riqueza_by_site.csv"))
transectos <- read_csv(here::here("data/transectos_tabla.csv"))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()))
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()))
abundancia <- denraw %>%
group_by(transecto, site) %>%
summarise(mean = round(mean(abundancia),2),
sd = sd(abundancia),
se = round(sd/sqrt(n()),2),
n_ind_total = sum(abundancia))descriptivos <-
transectos %>% inner_join(densidad_avg) %>%
dplyr::select(-sd) %>%
mutate(mean = round(mean, 2),
se = round(se,2)) %>%
unite("density", mean,se, sep = " ± ") %>%
inner_join(diversidad_avg) %>%
dplyr::select(-sd) %>%
mutate(mean = round(mean, 2),
se = round(se,2)) %>%
unite("diversity", mean,se, sep = " ± ") %>%
inner_join(richness) %>%
rename(richness = riq) %>%
inner_join(abundancia) %>%
dplyr::select(-sd) %>%
unite("abundancia_media", mean,se, sep = " ± ") %>%
unite("elev_rango", min_altitu, max_altitu, sep = "-") %>%
rowwise() %>%
mutate(elev_rango = paste0("(", elev_rango, ")")) %>%
unite("Elevation", elev, elev_rango, sep=" ") %>%
dplyr::select(
"Transect" = transecto,
"Code" = site,
Elevation,
"Length" = longitud,
"Abundance" = density,
"Diversity (H’)" = diversity,
"Richness" = richness,
"Mean number of individuals" = abundancia_media,
"Total number of individuals" = n_ind_total)
write_csv(descriptivos, here::here("data/tabla_descriptivos.csv"))descriptivos %>%
kbl() %>%
kable_styling()| Transect | Code | Elevation | Length | Abundance | Diversity (H’) | Richness | Mean number of individuals | Total number of individuals |
|---|---|---|---|---|---|---|---|---|
| Altas cumbres | AC | 3126 (3081-3170) | 3209 | 0.47 ± 0.03 | 1.02 ± 0.17 | 16 | 82.12 ± 10.04 | 657 |
| Barranco de San Juan | BSJ | 1362 (1347-1377) | 453 | 5.52 ± 0.63 | 2.92 ± 0.05 | 73 | 236.5 ± 38.17 | 1892 |
| Borreguiles San Juan | BOSJ | 2545 (2527-2563) | 2533 | 2.38 ± 0.27 | 2.49 ± 0.04 | 45 | 378.38 ± 45.91 | 3027 |
| Campos de Otero | CO | 2248 (2178-2317) | 2992 | 4.06 ± 0.48 | 2.67 ± 0.04 | 70 | 986.12 ± 157.42 | 7889 |
| Carihuela | CAR | 2808 (2792-2824) | 387 | 0.56 ± 0.1 | 1.02 ± 0.14 | 9 | 9 ± 1.35 | 72 |
| Catifas | CAT | 1666 (1658-1673) | 483 | 4.18 ± 0.27 | 2.75 ± 0.07 | 63 | 190.62 ± 22.05 | 1525 |
| Cauchiles | CAU | 3203 (3196-3210) | 624 | 1.08 ± 0.37 | 1.41 ± 0.19 | 18 | 28.12 ± 5.59 | 225 |
| Dúrcal | DU | 1950 (1913-1987) | 3563 | 9.41 ± 0.99 | 3.05 ± 0.04 | 64 | 3038.86 ± 331.97 | 21272 |
| Fabriquilla | FA | 992 (971-1013) | 415 | 2.47 ± 0.25 | 2.43 ± 0.06 | 56 | 88.5 ± 18.88 | 708 |
| Laguna Seca | LS | 2282 (2257-2306) | 3044 | 3.15 ± 0.46 | 1.85 ± 0.1 | 38 | 754.5 ± 119 | 6036 |
| Laguna | LP | 732 (726-739) | 500 | 3.95 ± 0.35 | 0.96 ± 0.13 | 24 | 193.14 ± 22.83 | 1352 |
| Matas Verdes | MV | 1919 (1851-1987) | 2672 | 5.23 ± 0.61 | 2.87 ± 0.12 | 78 | 1277.25 ± 168.91 | 10218 |
| Loma de Papeles Alto | PA | 2400 (2338-2463) | 3068 | 2.49 ± 0.34 | 2.23 ± 0.07 | 46 | 592.75 ± 103.02 | 4742 |
| Loma de Papeles Bajo | PB | 2121 (2052-2190) | 2743 | 1.95 ± 0.15 | 2.58 ± 0.05 | 56 | 448 ± 49.25 | 3584 |
| Pitres | PI | 1379 (1283-1475) | 2671 | 4.51 ± 0.35 | 2.85 ± 0.04 | 64 | 979.14 ± 84.37 | 6854 |
| Praillos | PRA | 1894 (1887-1900) | 366 | 4.61 ± 0.45 | 2.94 ± 0.09 | 73 | 156 ± 23.14 | 1248 |
| Purche | PU | 1442 (1387-1496) | 2758 | 5.67 ± 0.77 | 2.83 ± 0.06 | 78 | 1303.88 ± 235.67 | 10431 |
| Robledal de Dilar | DI | 1720 (1673-1767) | 2725 | 5.78 ± 0.52 | 2.93 ± 0.13 | 82 | 1402.38 ± 150.25 | 11219 |
| Sabinas | SA | 2180 (2177-2184) | 289 | 3.28 ± 0.51 | 2.42 ± 0.06 | 50 | 76 ± 11.82 | 608 |
| Turbera | TU | 745 (723-767) | 2754 | 1.4 ± 0.31 | 1.7 ± 0.09 | 45 | 364.14 ± 67.13 | 2549 |
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] kableExtra_1.3.1 here_1.0.1 forcats_0.5.1 stringr_1.4.0
[5] dplyr_1.0.6 purrr_0.3.4 readr_1.4.0 tidyr_1.1.3
[9] tibble_3.1.2 ggplot2_3.3.5 tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.7 lubridate_1.7.10 getPass_0.2-2 ps_1.5.0
[5] assertthat_0.2.1 rprojroot_2.0.2 digest_0.6.27 utf8_1.1.4
[9] R6_2.5.1 cellranger_1.1.0 backports_1.2.1 reprex_2.0.0
[13] evaluate_0.14 highr_0.8 httr_1.4.2 pillar_1.6.1
[17] rlang_0.4.12 readxl_1.3.1 rstudioapi_0.13 whisker_0.4
[21] callr_3.7.0 jquerylib_0.1.3 rmarkdown_2.8 webshot_0.5.2
[25] munsell_0.5.0 broom_0.7.9 compiler_4.0.2 httpuv_1.5.5
[29] modelr_0.1.8 xfun_0.23 pkgconfig_2.0.3 htmltools_0.5.2
[33] tidyselect_1.1.1 viridisLite_0.4.0 fansi_0.4.2 crayon_1.4.1
[37] dbplyr_2.1.1 withr_2.4.1 later_1.1.0.1 grid_4.0.2
[41] jsonlite_1.7.2 gtable_0.3.0 lifecycle_1.0.1 DBI_1.1.1
[45] git2r_0.28.0 magrittr_2.0.1 scales_1.1.1.9000 cli_2.5.0
[49] stringi_1.7.4 fs_1.5.0 promises_1.2.0.1 xml2_1.3.2
[53] bslib_0.2.4 ellipsis_0.3.2 generics_0.1.0 vctrs_0.3.8
[57] tools_4.0.2 glue_1.4.2 hms_1.0.0 processx_3.5.1
[61] fastmap_1.1.0 yaml_2.2.1 colorspace_2.0-2 rvest_1.0.0
[65] knitr_1.31 haven_2.3.1 sass_0.3.1