Skip to contents

Example surfacing and diving intervals, by month

Source: R/data.R
example_dive_intervals.Rd

A worked example for availability(): mean surfacing and diving intervals over a six-month season, with standard errors.

Usage

example_dive_intervals

Format

A tibble with 6 rows and 5 columns:

month

Month, as an ordered factor from December to May.

surface

Mean surfacing interval, seconds.

dive

Mean diving interval, seconds.

se_surface

Standard error of surface, seconds.

se_dive

Standard error of dive, seconds.

These numbers are invented

They are not measurements. In particular they are not Ganley et al. (2019)'s Cape Cod Bay values, which are not open access. Do not use them to correct anything.

What is real is the pattern they were built to show. Ganley et al. (2019) found right whale availability in Cape Cod Bay varying by month between 0.27 and 0.85, tracking the depth of the copepod layer the whales were feeding on: feeding deep means long dives and little time at the surface, feeding shallow means available most of the time. These intervals reproduce that shape, and running availability() over them spans roughly 0.25 to 0.85 — which is the point of shipping them. A single representative availability is a real number for one month and wrong by a factor of two for others.

Real dive parameters come from focal follows, tagging, or drone work, and are specific to a place, a season and a behaviour. Substitute your own.

References

Ganley, L.C., Brault, S. and Mayo, C.A. (2019) What we see is not what there is: estimating North Atlantic right whale Eubalaena glacialis local abundance. Endangered Species Research 38:101-113. doi:10.3354/esr00938 The monthly pattern these values imitate, and the real measurements they are not.

See also

availability(), view_window()

Examples

example_dive_intervals
#> # A tibble: 6 × 5
#>   month surface  dive se_surface se_dive
#>   <fct>   <dbl> <dbl>      <dbl>   <dbl>
#> 1 Dec        35   155          6      24
#> 2 Jan        40   140          7      21
#> 3 Feb        50   120          8      18
#> 4 Mar        65    95         10      14
#> 5 Apr        95    60         14       9
#> 6 May       130    35         19       6

# The season's availability, from these intervals and a platform's geometry
availability(
  surface    = example_dive_intervals$surface,
  dive       = example_dive_intervals$dive,
  window     = view_window(radius = 300, speed = 50),
  se_surface = example_dive_intervals$se_surface,
  se_dive    = example_dive_intervals$se_dive,
  key        = as.character(example_dive_intervals$month)
)
#> # A tibble: 6 × 4
#>   key   component    value     se
#>   <chr> <chr>        <dbl>  <dbl>
#> 1 Dec   availability 0.245 0.0388
#> 2 Jan   availability 0.286 0.0431
#> 3 Feb   availability 0.361 0.0483
#> 4 Mar   availability 0.477 0.0525
#> 5 Apr   availability 0.683 0.0481
#> 6 May   availability 0.849 0.0339