Hello everyone, I am trying to estimate a Log Gaussian Cox Process Model in which the effort function changes every year. 
The information on effort is contained in a list of dataframes defined as follows:
List of 24
 $ eff_2000:'data.frame':	11589919 obs. of  4 variables:
  ..$ x      : num [1:11589919] -1760 -1759 -1758 -1757 -1756 ...
  ..$ y      : num [1:11589919] 5473 5473 5473 5473 5473 ...
  ..$ eff2000: num [1:11589919] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ Year   : int [1:11589919] 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 ...
 $ eff_2001:'data.frame':	11589919 obs. of  4 variables:
  ..$ x      : num [1:11589919] -1760 -1759 -1758 -1757 -1756 ...
  ..$ y      : num [1:11589919] 5473 5473 5473 5473 5473 ...
  ..$ eff2001: num [1:11589919] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ Year   : int [1:11589919] 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 etc...Meanwhile, the effort function is defined like this:
log_detect_year = function(xy, t1, t2, Year1) {indx <- Year1 
 print(paste("Detection:", indx), sep = " ") 
 print(xy) 
 eff <- rast(df[,1:3], type = "xyz") 
 dens = eval_spatial(eff, xy) 
 pnorm(dens / qexppnorm(t1, rate = 0.5) +
        t2,
        log.p = TRUE) 
} 
My INLA model is defined as follows:
cmp = ~
  intercept1(1, mean.linear = 0, prec.linear = 2) +
  SPDE(geometry, model = barrier.model, 
       mapper = bru_mapper(mesh_medit),
       replicate = Year1, nrep = 4) +
  depth_s(depth.r$depth, mean.linear = 0.5, prec.linear = 2) +
  temp(temp.mean.r$temp_fa, mean.linear = 0, prec.linear = 1.5) +
  bpi(bpi.r$bpi, mean.linear = 0, prec.linear = 1.5) +
  Year_cov(Year1, model = "linear", prec.linear = 0.01) +
  effort_scale(1, prec.linear = 1) + 
  effort_shift(1, prec.linear = 10)
 
formula_t = geometry + Year1 ~
  intercept1 +
  SPDE +
  depth_s +
  temp +
  bpi +
  Year_cov +
  log_detect_year(geometry, effort_scale, effort_shift, Year1)
lik_t <- like("cp",
              formula = formula_t,
              samplers = boundary_domain,
              domain = list(geometry = mesh_medit,
                            Year1 = seq(21, 24,1)),
              data = mk.sf)
fit <- bru(components = cmp,
           lik_t, 
           options = list(
             verbose = FALSE,
             inla.mode = "experimental",
             bru_max_iter = 35,
             control.inla = list(int.strategy = "eb")
           ))
The model doesn’t run and returns this error:
Error in eff.r.ls[[indx]] : no such index at level 2
I’m definitely doing something wrong in the implementation. 
Can you help me figure it out?