Paquetes

library(dplyr)
library(ggplot2)

Base de datos

Base de datos de prueba

Esta es mi base de datos para los análisis

vector <- cbind(fecha=c(2020,2021,2022,2023,2024),
                cobertura= c(50,60,68,70,85))

Base de datos 2

library(readxl)
Abetos <- read_excel("Abetos (1).xlsx")
str(Abetos)
## tibble [4,064 × 12] (S3: tbl_df/tbl/data.frame)
##  $ genus          : chr [1:4064] "Abies" "Abies" "Abies" "Abies" ...
##  $ species        : chr [1:4064] "Abies_alba" "Abies_alba" "Abies_alba" "Abies_alba" ...
##  $ site_plot      : chr [1:4064] "Bistra" "Bistra" "Bistra" "Bistra" ...
##  $ status         : chr [1:4064] "LIVING" "LIVING" "LIVING" "LIVING" ...
##  $ taxonomic_group: chr [1:4064] "gymnosperms" "gymnosperms" "gymnosperms" "gymnosperms" ...
##  $ DBH_SPEI       : chr [1:4064] "40.950000000000003" "26.268000000000001" "35.808" "38.776000000000003" ...
##  $ delta_time     : chr [1:4064] "34" "34" "34" "34" ...
##  $ aridity_index  : num [1:4064] 1.92 1.92 1.92 1.92 1.92 ...
##  $ soil_ferility  : num [1:4064] -1.94 -1.94 -1.94 -1.94 -1.94 ...
##  $ LOGresilience  : chr [1:4064] "7.4476384856171696E-2" "0.19737050040725601" "-6.3468620838860901E-2" "0.31750521015016497" ...
##  $ LOGresistance  : chr [1:4064] "-5.2648543499225701E-2" "7.0684097529436302E-2" "-0.140977639639357" "9.9800755912784506E-2" ...
##  $ LOGrecovery    : chr [1:4064] "0.12712492835539699" "0.12668640287781999" "7.7509018800495905E-2" "0.217704454237381" ...