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metaRange

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More realistic and complicated simulations may require a more advanced setup. This vignette will cover some of the more advanced / hidden features of the metaRange package.

Time layer mapping

Section titled “Time layer mapping”

The setup and processing of the environmental SDS can take quite some time, especially when the environmental data is large. In order to save the user time, the method set_time_layer_mapping() allows the user to define a custom mapping between the time steps and the layers of the environmental raster. Use cases may be:

  1. In case of static environment -> use the same environmental raster layer for all time steps.
  2. Shortening or lengthening the number of time steps of the simulation.
  3. Using a “burn-in” period to let the simulation state reach a semi-equilibrium, before the main simulation begins.

Default mapping

Section titled “Default mapping”

The default configuration is that each layer in the environment represents one time step of the simulation. I.e:

library(metaRange)
library(terra)
raster_file <- system.file("ex/elev.tif", package = "terra")
r <- rast(raster_file)
temperature <- scale(r, center = FALSE, scale = TRUE) * 10 + 273.15
precipitation <- r * 2
temperature <- rep(temperature, 10)
precipitation <- rep(precipitation, 10)
landscape <- sds(temperature, precipitation)
names(landscape) <- c("temperature", "precipitation")
sim <- create_simulation(landscape)
sim$get_number_of_time_steps()
#> [1] 10
sim$get_time_layer_mapping()
#>  [1]  1  2  3  4  5  6  7  8  9 10

Static environment

Section titled “Static environment”

To use the same environmental raster (i.e. the first one) for all time steps, one can use:

sim$set_time_layer_mapping(rep_len(1, 10))
sim$get_number_of_time_steps()
#> [1] 10
sim$get_time_layer_mapping()
#>  [1] 1 1 1 1 1 1 1 1 1 1

Changing the number of time steps

Section titled “Changing the number of time steps”

In the same way described above, one can also pick the specific layer that are used and shorten the simulation length.

sim$set_time_layer_mapping(c(2, 4, 6))
sim$get_number_of_time_steps()
#> [1] 3
sim$get_time_layer_mapping()
#> [1] 2 4 6

Burn-in period

Section titled “Burn-in period”

To add a burn-in period of 10 time steps, where the environmental data is not updated, one could use the function as follows:

sim$set_time_layer_mapping(c(rep_len(1, 10), 2:10))
sim$get_number_of_time_steps()
#> [1] 19
sim$get_time_layer_mapping()
#>  [1]  1  1  1  1  1  1  1  1  1  1  2  3  4  5  6  7  8  9 10

Global variables and processes

Section titled “Global variables and processes”

In metaRange each species is described by its own biologically relevant processes and traits. However, there may be cases where the user wants to define a global variable or process that is shared between all species, either to store intermediate results that don’t belong to one species or processes to visualize or store output. This can be done by using the add_globals() function for adding global variables and the add_process() function with no species argument specified, for adding global processes. The global variables and processes are accessible through the globalsand processes fields of the simulation object itself, respectively. The benefit of using a global process is that the self keyword refers to the simulation object itself, which allows for easier indexing across multiple species.

sim$add_species("species_one")
sim$add_species("species_two")
sim$add_globals(
    mean_abundance_over_time = list(
        "species_one" = c(),
        "species_two" = c()
    )
    # ... more global variables
)
sim$globals$global_var
#> NULL
sim$add_process(
    # Note the missing species argument
    process_name = "global_process",
    process_fun = function() {
        # self = simulation object
        # easy access to simulation functions
        for (sp in self$species_names()) {
            self$globals$mean_abundance_over_time[[sp]] <-
                c(
                    self$globals$mean_abundance_over_time[[sp]],
                    mean(self[[sp]]$traits$abundance)
                )
        }
    },
    execution_priority = 1
)
sim$processes$global_process
#> Process name:  global_process
#> PID:  PID-11951bb8c1-global_process-simulation_448f0fd5
#> execution_priority:  1
#> execution_environment_label:  simulation_448f0fd5
#> $fun: function ()
#> {
#>     for (sp in self$species_names()) {
#>         self$globals$mean_abundance_over_time[[sp]] <- c(self$globals$mean_abundance_over_time[[sp]],
#>             mean(self[[sp]]$traits$abundance))
#>     }
#> }
#> <environment: 0x000002078f328c80>

Interaction with the priority queue

Section titled “Interaction with the priority queue”

With some study questions, it may not be desired to simulate all species from the first time step. For example, when simulating invasion dynamics, one may want to have a burn-in period without the invasive species present and then introduce it after this point. Aditionally, there may be the need to simulate a species for a period of time and then remove it from the simulation (e.g. there is no point in calculating the reproduction of a species that has gone extinct). To accommodate this, metaRange allows the user to manually add and remove processes from the priority queue during the simulation.

Queuing a process

Section titled “Queuing a process”

The default behavior of add_process() is to directly add the process to the priority queue (so that is is executed in the first time step). Setting the argument queue = FALSE will add the process to the simulation, but not to the priority queue. In that case, the user has at any point during the simulation the option to add the process to the priority queue using the enqueue() method of the priority queue.

sim <- create_simulation(landscape)
sim$set_time_layer_mapping(c(1:6))
sim$add_species(name = "species_1")
sim$add_process(
    species = "species_1",
    process_name = "invasion",
    process_fun = function() {
        message("Species invades!")
    },
    execution_priority = 1,
    # Note the queue = FALSE argument
    queue = FALSE
)
sim$add_process(
    process_name = "activate_species_1",
    process_fun = function() {
        message(paste0("time step: ", self$get_current_time_step()))
        # Note that when manually changing the queue,
        # the changes will take place in the
        # _next_ time step
        # e.g. the following will lead to the process
        # being first executed in time step 4)
        if (self$get_current_time_step() == 3) {
            message("Activating species 1")
            for (pr in self$species_1$processes) {
                self$queue$enqueue(pr)
            }
        }
    },
    execution_priority = 1
)
sim$begin()
#> time step: 1
#> time step: 2
#> time step: 3
#> Activating species 1
#> time step: 4
#> Species invades!
#> time step: 5
#> Species invades!
#> time step: 6
#> Species invades!

Dequeue a process

Section titled “Dequeue a process”

The dequeue() function of the priority queue allows the user to remove a process from the priority queue.

sim <- create_simulation(landscape)
sim$set_time_layer_mapping(c(1:6))
sim$add_species(name = "species_1")
sim$add_process(
    species = "species_1",
    process_name = "invasion",
    process_fun = function() {
        message("Species invades!")
    },
    execution_priority = 1,
)
sim$add_process(
    process_name = "stop_invasion",
    process_fun = function() {
        message(paste0("time step: ", self$get_current_time_step()))
        if (self$get_current_time_step() == 3) {
            message("Extiction species 1")
            for (pr in self$species_1$processes) {
                # Here we are querying the process ID,
                # which is a unique identifier for each process
                # so that the priority queue knows what to remove
                self$queue$dequeue(pr$get_PID())
            }
        }
    },
    execution_priority = 1
)
sim$begin()
#> Species invades!
#> time step: 1
#> Species invades!
#> time step: 2
#> Species invades!
#> time step: 3
#> Extiction species 1
#> time step: 4
#> time step: 5
#> time step: 6

Ending the simulation early

Section titled “Ending the simulation early”

To end the simulation safely, before the last time step, the user can use the exit() method of the simulation. This will end the simulation at the end of the process it is called inside of. A possible use case would be to conditionally end the simulation if all species are extinct.

sim <- create_simulation(landscape)
sim$set_time_layer_mapping(c(1:6))
sim$add_species(name = "species_1")
sim$add_process(
    species = "species_1",
    process_name = "invasion",
    process_fun = function() {
        message("Species invades!")
    },
    execution_priority = 1,
)
sim$add_process(
    process_name = "end_simualtion",
    process_fun = function() {
        message(paste0("time step: ", self$get_current_time_step()))
        if (self$get_current_time_step() == 4) {
            message("Ending simulation early")
            self$exit()
        }
    },
    execution_priority = 1
)
sim$begin()
#> Species invades!
#> time step: 1
#> Species invades!
#> time step: 2
#> Species invades!
#> time step: 3
#> Species invades!
#> time step: 4
#> Ending simulation early
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