Launch a survey on a population of moving individuals

This function identifies the individuals detected during a standardised survey by spatial and temporal matching between segments and movement bouts of individuals. The default behaviour emulates a strip-transect survey, by considering individuals falling within a strip around the surveyed segments to be detected, but line-transect methodology can also be emulated by setting line-transect to TRUE. In this case, the actual detection of individuals is conditioned by their distance to the track line (probability of detection is computed using either half-normal of hazard rate detection functions).

Usage

launch_survey_on_movement(
  survey_data_buffered,
  survey_data_linear,
  traj_data,
  track_id_col = "ind_id",
  seg_id_col = "seg_id",
  line_transect = FALSE,
  sigma = 0.2,
  b = 1,
  detection_function = "hn"
)

Arguments

survey_data_buffered: sf object, buffered segments as provided by generate_survey_plan and processed by assign_flight_plan. Matching sightings will be defined as individual movement bouts falling within the buffer around segments, so be careful about the buffer length.
survey_data_linear: sf object, non-buffered segments (LINESTRING type) as provided by generate_survey_plan, used to compute distance to the trac line
traj_data: data.frame of individual movements, as provided by simulate_trajectory_CPF and simulate_trajectory_FR
track_id_col: character, the column name storing the individual id in traj_data
seg_id_col: character, the column name storing the segment id in survey_data
line_transect: Boolean. Should the detection process follow line-transect methodology? Default to FALSE (strip-transect setting). If TRUE, sightings are spatially matched (falling inside segment buffers) then a detection probability is calculated based on the distance to the track line.
sigma: numeric, if line_transect is TRUE, defines the effective strip half-width used in detection functions (km)
b: numeric, if detection_function = "hr", b value to be passed on to the detection_hr function
detection_function: character, half-normal ("hn") or hasard rate ("hr") detection function, default to "hn"

Value

A list included an effort table (the survey_data with the number of individuals sighted per segment "N_ind_tot") and an obs_table (summarising the movement bouts detected by the survey, with their centroid coordinates). If line_transect is TRUE, obs_table includes two supplementary columns describing the probability an individual is detected based on its distance to the track line ("prob_dist") and whether it is detected or not ("detected"), while the effort table includes an additional column ("N_ind_detected") summarising the number of individuals detected based on distance to the track line.

Examples

# an example with a small number of individuals
survey <- launch_survey_on_movement(
  survey_data_buffered = example_data$flight_plan,
  survey_data_linear = example_data$survey$segments,
  traj_data = example_data$mvmt_data,
  line_transect = TRUE, detection_function = "hn",
  sigma = 0.2
)
#> Applying detection function

# look at the number of sightings
summary(survey$effort_table$N_ind_tot)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> 0.00000 0.00000 0.00000 0.03846 0.00000 6.00000 

plot(sf::st_drop_geometry(survey$obs_table[, c("dist_seg", "prob_dist")]), 
     xlab = "distance to the track line", ylab = "detection probability")


# all sightings are in a few segments
library(ggplot2)
ggplot(survey$effort_table) +
  geom_sf(data = survey$obs_table, 
          aes(shape = as.factor(detected)), size = 2) +
  geom_sf(aes(fill = N_ind_tot)) + 
  viridis::scale_fill_viridis(limits = c(1,10), 
                              na.value = NA, alpha = 0.5)

Usage

Arguments

Value

See also

Examples