MCP calculation error when following a tutorial - r

Question

I am trying to follow this tutorial but I am encountering an error. I have my data formatted exactly like it is in the example, at least as far as I can tell. But when I try to run the calculation for the MCP below:
#Space use by week, month, or year - MCP
> mcps.year<-trk %>% nest(-id,-year) %>%
+ mutate(mcparea = map(data, ~hr_mcp(., levels = c(0.95)) %>% hr_area)) %>%
+ select(id, year, mcparea) %>% unnest()
I receive this error:
Error: Problem with `mutate()` column `mcparea`.
i `mcparea = map(data, ~hr_mcp(., levels = c(0.95)) %>% hr_area)`.
x is.numeric(crs) || is.character(crs) || inherits(crs, "crs") is not TRUE
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
All elements of `...` must be named.
Did you want `data = c(x_, y_, t_, tod_, week, month, hour, sl, nsd_)`?
How can I fix this? I tried setting x_ and y_ as coordinates and then setting the projection to make it a spatial points dataframe:
trk <- st_as_sf(trk, coords = c("x_", "y_"))
st_crs(trk) <- 32614
But then I got this error:
Error: Problem with `mutate()` column `mcparea`.
i `mcparea = map(data, ~hr_mcp(., levels = c(0.95)) %>% hr_area)`.
x Can't subset columns that don't exist.
x Columns `x_` and `y_` don't exist.
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
All elements of `...` must be named.
Did you want `data = c(t_, tod_, week, month, hour, sl, nsd_, geometry)`?
EDIT:
Ok here is the code Im running!
#Set seed for random number generator
set.seed(10299)
#Import data
setwd("C:/Users/saraa/OneDrive - UNT System/Masters Thesis/Data/Testing RSF")
turtle <- read_csv("West2021KDE.csv")
turtle.dat <- as(turtle, "data.frame")
#Data cleaning
#Remove incomplete observations
ind<-complete.cases(turtle.dat[,c("y", "x", "date", "CST")])
turtle.dat<-turtle.dat[ind==TRUE,]
#Check for and remove duplicates
ind2<-turtle.dat %>% select(y, x, CST, date, id) %>% duplicated
sum(ind2)
turtle.dat<-turtle.dat[ind2!=TRUE,]
#Make timestamp a date/time variable
turtle.dat$timestamp <- with(turtle.dat, mdy(date) + hms(CST))
turtle.dat$timestamp<-as.POSIXct(turtle.dat$timestamp, format="%Y-%m-%d %H:%M")
#Plot data
#Separately
ggplot(turtle.dat, aes(x=x, y=y))+geom_point()+
facet_wrap(~id, scales="free")
#Combined
ggplot(turtle.dat, aes(x=x, y=y, color=as.factor(id)))+
geom_point()
#Creating a track using amt
trk <- mk_track(turtle.dat, .x=x, .y=y, .t=timestamp, id=id,
crs = CRS("+init=epsg:4326"))
#Now it is easy to calculate day/night with either movement track
trk <- trk %>% time_of_day()
#Transform coordinates
trk <- transform_coords(trk,sp::CRS("+init=epsg:32614"))
trk.class<-class(trk)
#Nest tracks by individual
nesttrk<-trk%>%nest(-id)
nesttrk
#Make new columns of time of observation
trk <- trk %>%
mutate(week = week(t_),
month = month(t_, label=TRUE),
year=year(t_),
hour = hour(t_))
#Calculate movement distances
trk <- trk %>% nest(-id) %>%
mutate(sl = map(data, step_lengths),
nsd_=map(data, nsd)) %>% unnest(cols = c(data, sl, nsd_))
#Transform to track object
class(trk)
class(trk)<-trk.class
trk
#Net squared displacement over time
ggplot(trk, aes(x = t_, y=nsd_)) + geom_point()+
facet_wrap(~id, scales="free")
#Step length distribution
ggplot(trk, aes(x = month, y = log(sl))) +
geom_boxplot()+geom_smooth()+facet_wrap(~id)
#Space use by week, month, or year - MCP
mcps.year<-trk %>% nest(-id,-year) %>%
mutate(mcparea = map(data, ~hr_mcp(., levels = c(0.95)) %>% hr_area)) %>%
select(id, year, mcparea) %>% unnest()
ggplot(mcps.year, aes(x = year, y = area, colour=as.factor(year))) + geom_point()+
geom_smooth()+ facet_wrap(~id, scales="free")
and str(trk)
> str(trk)
track_xyt [1,058 x 13] (S3: track_xyt/track_xy/tbl_df/tbl/data.frame)
$ id : chr [1:1058] "M13" "M13" "M13" "M13" ...
$ x_ : Named num [1:1058] 687578 687491 687455 687566 687518 ...
..- attr(*, "names")= chr [1:1058] "1" "3" "122" "128" ...
$ y_ : Named num [1:1058] 3659888 3659889 3659893 3659891 3659959 ...
..- attr(*, "names")= chr [1:1058] "1" "3" "122" "128" ...
$ t_ : POSIXct[1:1058], format: "2021-04-03 15:19:00" "2021-04-18 11:19:00" "2021-05-02 12:43:00" "2021-06-03 11:23:00" ...
$ tod_ : Factor w/ 2 levels "day","night": 1 2 1 1 2 2 2 2 2 2 ...
$ dir_abs: num [1:1058] 1.558 1.485 4.699 0.616 5.525 ...
$ dir_rel: num [1:1058] NA -0.073 -3.07 2.2 -1.374 ...
$ sl : num [1:1058] 87.2 36.1 111.6 83.8 40.5 ...
$ nsd_ : Named num [1:1058] 0 7600 15171 140 8642 ...
..- attr(*, "names")= chr [1:1058] "1" "3" "122" "128" ...
$ week : num [1:1058] 14 16 18 22 23 25 26 27 30 30 ...
$ month : Ord.factor w/ 12 levels "Jan"<"Feb"<"Mar"<..: 4 4 5 6 6 6 7 7 7 7 ...
$ year : num [1:1058] 2021 2021 2021 2021 2021 ...
$ hour : int [1:1058] 15 11 12 11 10 9 9 9 10 0 ...