Example multi-flight aerial count data for GLMM effort estimation

Simulated instantaneous angler counts from aerial overflights of a Nebraska reservoir, designed to demonstrate GLMM-based effort estimation following Askey (2018). Contains 48 rows: 12 survey days with 4 overflights per day at fixed hours (07:00, 10:00, 13:00, 16:00). Counts follow a diurnal curve (low at dawn, peak mid-morning, lower in afternoon) with day-level Poisson variability and a day random intercept.

Usage

example_aerial_glmm_counts

Format

A data frame with 48 rows and 4 columns:

date

Survey date (Date class), 12 days spaced 3 days apart starting 2024-06-03.

day_type

Day type stratum: "weekday" or "weekend", derived from the calendar date.

n_anglers

Instantaneous angler count from one aerial overflight (integer). Follows a diurnal curve with day-level random effects.

time_of_flight

Hour of the aerial overflight (numeric). One of 7.0, 10.0, 13.0, or 16.0.

Source

Simulated data following Askey (2018) NAJFM doi:10.1002/nafm.10010.

References

Askey, P.J., et al. (2018). Correcting for non-random flight timing in aerial creel surveys using a generalized linear mixed model. North American Journal of Fisheries Management, 38, 1204-1215. doi:10.1002/nafm.10010

See also

example_aerial_counts for the simple single-flight dataset, estimate_effort_aerial_glmm() for the GLMM-based estimator, creel_design(), add_counts()

Other "Example Datasets": creel_counts_toy, creel_interviews_toy, example_aerial_counts, example_aerial_interviews, example_calendar, example_camera_counts, example_camera_interviews, example_camera_timestamps, example_catch, example_counts, example_ice_interviews, example_ice_sampling_frame, example_interviews, example_lengths, example_sections_calendar, example_sections_counts, example_sections_interviews

Examples

data(example_aerial_glmm_counts)
head(example_aerial_glmm_counts)
#>         date day_type n_anglers time_of_flight
#> 1 2024-06-03  weekday         3              7
#> 2 2024-06-03  weekday        30             10
#> 3 2024-06-03  weekday        65             13
#> 4 2024-06-03  weekday        50             16
#> 5 2024-06-06  weekday         5              7
#> 6 2024-06-06  weekday        15             10

if (FALSE) { # \dontrun{
# Build an aerial design and estimate effort with GLMM correction
aerial_cal <- data.frame(
  date = unique(example_aerial_glmm_counts$date),
  day_type = unique(example_aerial_glmm_counts[, c("date", "day_type")])[["day_type"]],
  stringsAsFactors = FALSE
)
design <- creel_design(
  aerial_cal,
  date = date,
  strata = day_type,
  survey_type = "aerial",
  h_open = 14
)
design <- add_counts(design, example_aerial_glmm_counts)
result <- estimate_effort_aerial_glmm(design, time_col = time_of_flight)
print(result)
} # }