Error in file(fn, "rb") : cannot open the connection In addition: Warning message: In file(fn, "rb") : cannot open file

Question

I'm trying to do a Species distribution model and every time I close Rstudio I receive this error when trying to plot my data and can't continue from where I stopped:

> Error in file(fn, "rb") : cannot open the connection In addition:
> Warning message: In file(fn, "rb") :   cannot open file
> '/tmp/RtmpqebvDu/raster/r_tmp_2022-10-19_154556_18241_29080.gri': No
> such file or directory

Also, even if a load the previously saved environment and script, it doesn't allow me to plot any bioclim variables. I even change my OP from Ubuntu 22.04 to Ubuntu 20.04 that is more stable and the error remains the same. Idk if they are saving the rasters in a temp file but I can't load all the script over and over again every time I close RStudio.

Below is my script.

#---------packages

library(sdm) 
library(dplyr) 
library(tidyr)

#-------import data

setwd('/home/laislacosta/srf/B_marajoensis')

marajoensis2 <- read.csv('/home/laislacosta/srf/B_marajoensis/occumrj.csv')

#------- selection sp

mrj2 <- marajoensis2 %>% 
  filter(Species %in% c("Bothrops marajoensis"))

#------- select long lat

mrj2 <- mrj2 %>%  
  select(Longitude, Latitude)

#------- remove NA values

mrj2 <- mrj2 %>%
  drop_na()

#-------- remove duplicate

mrj2 <- unique(mrj2)

#-------- bioclim variable

bio_raw <- raster::getData("worldclim", var = "bio", res = 2.5)
bio_raw <- raster::stack(list.files(path = "/home/laislacosta/srf/B_marajoensis/wc5", 
                                    pattern = "bil$",
                                    full.names = TRUE, recursive = TRUE))

#-------- prepare data for modelling

#passo 1: create column presence mrj2$spc_marajoensis <-1

#passo 2: transform object to SpatialPointsDataFrame

coordinates(mrj2) <- c("Longitude", "Latitude") 
proj4string(mrj2) <- raster::projection(raster::raster())

#passo 3: area cut

brasil <- raster::shapefile('/home/laislacosta/srf/B_marajoensis/shape/lm_bioma_250.shp') 
bio <- raster::mask(bio_raw, brasil) 
bio <- raster::crop(bio, brasil)

plot(bio[[1]])

save.image("all_data.RData")