library(dplyr)
library(ggplot2)
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))
esto se hizo con ctrl+alt+ i
library(readxl)
Abetos <- read_excel("Abetos.xlsx")
Abetos$DBH_SPEI <- as.numeric(Abetos$DBH_SPEI)
## Warning: NAs introducidos por coerción
Abetos$delta_time<- as.numeric(Abetos$delta_time)
## Warning: NAs introducidos por coerción
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 : num [1:4064] 41 26.3 35.8 38.8 35.5 ...
## $ delta_time : num [1:4064] 34 34 34 34 34 34 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" ...
modelo<-lm(DBH_SPEI~ delta_time, data= Abetos)
summary(modelo)
##
## Call:
## lm(formula = DBH_SPEI ~ delta_time, data = Abetos)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.895 -8.466 -3.074 4.515 146.426
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 28.8543 0.6737 42.83 <2e-16 ***
## delta_time -0.2320 0.0152 -15.27 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 13.94 on 3278 degrees of freedom
## (784 observations deleted due to missingness)
## Multiple R-squared: 0.06637, Adjusted R-squared: 0.06609
## F-statistic: 233 on 1 and 3278 DF, p-value: < 2.2e-16
ggplot(Abetos, aes(x= delta_time, y= DBH_SPEI, color = status))+
geom_point()+
theme_classic()
## Warning: Removed 784 rows containing missing values or values outside the scale range
## (`geom_point()`).