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Define the movement model of a graph

Source: R/graph_set_movement.R
graph_set_movement.Rd

Configure the movement model of a graph by defining the value of the parameters needed to build the transition graph_transition() through speed2prob().

Three methods are currently implemented with two parametric function "gamma" and "logis" suitable when wind data is not available and are thus defining the probability of a groundspeed.

If wind data is available, it is recommended to use the "power" method which rely on the power curve equation (energy vs airspeed) to estimate the probability of a airspeed. Read more about this approach in section 2.2.5. of Nussbaumer et al. (2023b)

Usage

graph_set_movement(
  graph,
  type = ifelse("ws" %in% names(graph), "as", "gs"),
  method = ifelse("ws" %in% names(graph), "power", "gamma"),
  shape = 7,
  scale = 7,
  location = 40,
  bird = NULL,
  power2prob = function(power) (1/power)^3,
  low_speed_fix = 15
)

Arguments

graph

a GeoPressureR graph object.

type

Ground speed "gs" or airspeed "as"

method

method used to convert the speed to probability ("gamma", "logis" or "power")

shape

parameter of the gamma distribution

scale

parameter of the gamma and logistic distribution

location

parameter for the logistic distribution

bird

A GeoPressureR bird object containing the basic morphological traits necessary: mass, wing span, wing aspect ratio, and body frontal area. See bird_create().

power2prob

function taking power as a single argument and returning a probability

low_speed_fix

speed below which the probability remains the same. This parameter is used to allow short flights covering small distances.

Value

Graph list with a new list graph$movement storing all the parameters needed to compute the transition probability

References

Nussbaumer, Raphaël, Mathieu Gravey, Martins Briedis, Felix Liechti, and Daniel Sheldon. 2023. Reconstructing bird trajectories from pressure and wind data using a highly optimized hidden Markov model. Methods in Ecology and Evolution, 14, 1118–1129 https://doi.org/10.1111/2041-210X.14082.

See also

Other graph: graph_add_wind(), graph_create(), graph_marginal(), graph_most_likely(), graph_simulation(), print.graph()

Other movement: bird_create(), graph_add_wind(), graph_transition(), plot_graph_movement(), speed2prob(), tag_download_wind()

Examples

owd <- setwd(system.file("extdata", package = "GeoPressureR"))
tag <- tag_create("18LX", quiet = TRUE) |>
  tag_label(quiet = TRUE) |>
  twilight_create() |>
  twilight_label_read() |>
  tag_set_map(
    extent = c(-16, 23, 0, 50),
    known = data.frame(stap_id = 1, known_lon = 17.05, known_lat = 48.9)
  ) |>
  geopressure_map(quiet = TRUE) |>
  geolight_map(quiet = TRUE)
setwd(owd)

graph <- graph_create(tag, quiet = TRUE)

graph <- graph_set_movement(graph,
  method = "gamma",
  shape = 4,
  scale = 6,
  low_speed_fix = 10
)
plot_graph_movement(graph)


graph <- graph_set_movement(graph,
  method = "logis",
  shape = 4,
  location = 60,
  low_speed_fix = 10
)
plot_graph_movement(graph)