Summarise effort by continuous track

Totals the point-to-point effort on each continuous track and drops tracks too short to be worth segmenting.

Usage

track_effort(dat, min_track_km = 1)

Arguments

dat

A data frame with DATE, new_trackno, pt2pt.effort, and TIME.

min_track_km

Tracks with less than this much effort are dropped. Default 1.

Value

A tibble with one row per track: DATE, new_trackno, track_effort (km), and start_time (the earliest TIME on the track, used to keep tracks in survey order).

References

Becker, E.A., Forney, K.A., Ferguson, M.C., Foley, D.G., Smith, R.C., Barlow, J. and Redfern, J.V. (2010) Comparing California Current cetacean-habitat models developed using in situ and remotely sensed sea surface temperature data. Marine Ecology Progress Series 413:163-183. doi:10.3354/meps08696

Examples

path <- system.file("extdata", "narwc-example.csv", package = "distsamp")
dat <- point_to_point_effort(
  split_tracks(flag_effort(make_leg_id(read_narwc(path))))
)
#> `read_narwc()` renamed 2 columns:
#>   LAT_DD  -> LATITUDE
#>   LONG_DD -> LONGITUDE
#> All matched an exact entry in the alias table; `narwc_column_mapping()` returns this, and `quiet = TRUE` silences it.
track_effort(dat)
#> # A tibble: 7 × 4
#>   DATE       new_trackno track_effort start_time
#>   <date>     <chr>              <dbl>      <dbl>
#> 1 2024-04-01 2                  22.2      120400
#> 2 2024-04-01 4                   7.78     123000
#> 3 2024-04-01 6                   8.89     123920
#> 4 2024-04-02 1                  33.3      133000
#> 5 2024-04-02 2                   3.33     134320
#> 6 2024-04-02 4                   7.78     134640
#> 7 2024-04-02 5                   8.89     135050