How does gridmetrics handle IF condition in user defined functions?

I noticed a kind of "inconsistency" in the values returned from two user-defined functions. I tested on a tile of 200mx200m to return a raster of pixel size 50m (16 pixels)

In the following function, if the condition is satisfied, the function returns ONLY one value.

funcky <- function(x)
{
  if (max(x) < 22)
     return(max(x))
}
grd <- grid_metrics(lasca, funcky(Z), 50)

When the condition is not satisfied, NA values are returned.

> as.array(grd[[1]])
, , 1

      [,1]  [,2]  [,3] [,4]
[1,] 19.92 21.90    NA   NA
[2,]    NA 21.46 21.89   NA
[3,]    NA 21.73    NA   NA
[4,]    NA    NA    NA   NA

I expected the same logic to be applied when the function returns a list of values. For example,

funcky <- function(x)
{
  if (max(x) < 22)
    return(list(max(x), mean(x), min(x)))
}
grd <- grid_metrics(lasca, funcky(Z), 50)

But the values are not NA, they are 0s as shown below.

> as.array(grd[[1]])
, , 1

      [,1]  [,2]  [,3] [,4]
[1,] 19.92 21.90  0.00    0
[2,]  0.00 21.46 21.89    0
[3,]  0.00 21.73  0.00    0
[4,]  0.00  0.00  0.00    0

, , 2

         [,1]     [,2]     [,3] [,4]
[1,] 6.555234 7.434102 0.000000    0
[2,] 0.000000 5.038366 5.733465    0
[3,] 0.000000 8.699386 0.000000    0
[4,] 0.000000 0.000000 0.000000    0

, , 3

      [,1]  [,2]  [,3] [,4]
[1,] -0.83 -0.04  0.00    0
[2,]  0.00 -0.07 -0.09    0
[3,]  0.00 -0.07  0.00    0
[4,]  0.00  0.00  0.00    0

If the metrics can have negative values (skewness, for example), then these 0s could potentially be misleading, as is the case in the third layer. Is this behaviour alright?

Adding an else {return(NULL)} didn’t make any difference. And adding else {return(list(NA,NA,NA))} generated an error:

Error: Column 1 of result for group 2 is type 'logical' but expecting type 'double'. Column types must be consistent for each group.

funcky <- function(x)
{
  if (max(x) < 22)
    return(list(max(x), mean(x), min(x)))
  else
    return(list(NA_real_, NA_real_, NA_real_)
}