Title: Models the Capture Processes in American Lobster Trap Fishery
Version: 0.1.0
Description: Simulate lobster catch process in a trap fishery. Factors such as lobster density on ocean floor, their movement, trap saturation and bait shrinkage rate can be modeled. Details of the methods for modeling those processes can be found in: Addison and Bell (1997) <doi:10.1071/MF97169>.
License: GPL (≥ 3)
Depends: R (≥ 2.10)
Imports: stats, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-06-18 22:24:42 UTC; payma
Author: Pourfaraj vahab [aut], Cook Adam [aut], Jamie Tam [ctb], Nickchi Payman [aut, cre]
Maintainer: Nickchi Payman <payman.nickchi@gmail.com>
Repository: CRAN
Date/Publication: 2023-06-19 15:40:05 UTC

This function extracts the results of simulation.

Description

This function extracts the results of simulation.

Usage

GetSimOutput(x, mls = 82.5)

Arguments

x

is an object generated by SimulateLobsterMovement function.

mls

is the minimum legal size(mls) in mm. The default is 82.5 mm.

Value

Returns the followings for each replicate: the number of lobsters caught, legal catch weight (bigger than mls), total catch weight and length of time to reach maximum catch.

Lobster size frequency data

Description

The dataset contains frequency of each size bin (from Carapace length of 50 mm to 200 mm)

Usage

data(LobsterSizeFreqs)

Format

A data frame with 31 rows and 2 variables

Details

Function to run the simulation based on defined parameters

Description

Function to run the simulation based on defined parameters

Usage

SimulateLobsterMovement(p)

Arguments

p

is a list of all input variables

Value

Returns a list

See Also

Examples of the input parameters and more details can be found here: https://github.com/pnickchi/lobstercatch/blob/main/Examplecode.R

Examples

p = list()
p$nrowgrids = 10
p$ncolgrids = 10
p$ngrids = p$nrowgrids * p$ncolgrids
p$unitarea = 1
p$initlambda = 0.5
p$dStep = 1
p$howClose = 1
p$initD = 1
p$shrinkage = 0.993
p$currentZoI = 15
p$radiusOfInfluence = 15
p$q0 = 0.5
p$qmin = 0
p$Trap = data.frame( x = c(5), y = c(5) )
p$ntraps = nrow(p$Trap)
p$saturationThreshold = 5
p$lengthBased = FALSE
p$lobsterSizeFile =
'https://raw.githubusercontent.com/vpourfaraj/lobsterCatch/main/inst/extdata/LobsterSizeFreqs.csv'
p$lobLengthThreshold = 115
p$trapSaturation = FALSE
p$sexBased = FALSE
p$lobsterSexDist = list(labels = c('M','F','MM','BF'),
                        prob1 = c(0.55,0.35,0.05,0.05),
                        prob2 = c(0.5,0.50,0,0),
                        lobsterMatThreshold = 100)
p$realizations = 2
p$tSteps = 2
Simrun = SimulateLobsterMovement(p)

This function calculates the probability of entry into a trap, also known as catchability. It includes the parameters described in Addison and Bell (1997), and can also incorporate the length of the catch while calculating the catchability.

Description

This function calculates the probability of entry into a trap, also known as catchability. It includes the parameters described in Addison and Bell (1997), and can also incorporate the length of the catch while calculating the catchability.

Usage

catchability(
  q0,
  qmin,
  saturationThreshold,
  Ct,
  lengthBased,
  lobLengthThreshold,
  lobSize = NA,
  sexBased,
  lobSex
)

Arguments

q0

is the initial probability of entry into an empty trap (range is from 0-1). Default value is 0.5.

qmin

is the asymptotic minimum probability of entry with default value being 0.

saturationThreshold

is the number of lobsters in a trap at which the probability of another lobster entering the trap is zero (i.e. no more entry due to agnostic behavior of trapped lobsters).

Ct

is the number of caught lobster

lengthBased

Logical. If TRUE the length of lobsters caught will be taken into account

lobLengthThreshold

Logical.If TRUE the carapace length (in milliliters) beyond which there is no chance of catching another lobster due to bold agnostic behavior of large lobsters.

lobSize

is a size frequency dataset that is representative of the population and can be incorporated to the model.

sexBased

Logical. If TRUE, lobster sex is taken into account and user must provide a list containing sex distribution for the simulated population

lobSex

is the sex of trapped lobster

Value

Returns the probability of entry to trap.

References

Julian T. Addison and Michael C. Bell (1997), Simulation modelling of capture processes in trap fisheries for clawed lobsters, Marine Freshwater Research, 48(8), 1035-1044, https://www.publish.csiro.au/MF/MF97169

This function models movement of lobsters toward the trap.The distance of lobsters to trap determines the magnitude of those moves. As lobster gets closer to the trap, the magnitude of its directional move becomes larger and the random move becomes smaller.

Description

This function models movement of lobsters toward the trap.The distance of lobsters to trap determines the magnitude of those moves. As lobster gets closer to the trap, the magnitude of its directional move becomes larger and the random move becomes smaller.

Usage

directionalMove(
  Lobster,
  dStep,
  minDistoTrap,
  Trap,
  radiusOfInfluence,
  currentZoI
)

Arguments

Lobster

location of lobster in the grid in x and y coordinates.

dStep

Distance that each lobster moves during one time step.

minDistoTrap

Distance from the trap.

Trap

location of trap in the arena.

radiusOfInfluence

Radius of influence for the baited trap.

currentZoI

Radius of influence in each time step given the bait shrinkage.

Value

Returns the new coordinates of each lobster in the arena after each directional move.

This function calculates the variance to mean ratio (also known as dispersion index).

Description

This function calculates the variance to mean ratio (also known as dispersion index).

Usage

dispersion(x)

Arguments

x

is a numeric vector.

Value

Returns the dispersion index.

The function finds the closest trap to a lobster and calculates the distance.

Description

The function finds the closest trap to a lobster and calculates the distance.

Usage

distanceToClosestTrap(Lobster, Trap)

Arguments

Lobster

location of lobster in the arena

Trap

location of trap in the arena

Value

Returns distance to closest trap and saves the trap number in case of multiple traps.

This function calculates the Euclidean distance between Trap(s) and each lobster. The function is internally called in distanceToClosestTrap function.

Description

This function calculates the Euclidean distance between Trap(s) and each lobster. The function is internally called in distanceToClosestTrap function.

Usage

distanceToTrapCalculator(Lobster, Trap)

Arguments

Lobster

location of lobster in the grid in x and y coordinates.

Trap

location of trap in the grid in x and y coordinates.

Value

Returns the distance to trap.

This function simulates an arena (or grid) with lobsters in it based on the provided density, size and sex distribution.

Description

This function simulates an arena (or grid) with lobsters in it based on the provided density, size and sex distribution.

Usage

initialLobsterGrid(
  nrowgrids,
  ncolgrids,
  unitarea,
  initlambda,
  initD,
  lobsterSizeFile,
  lobsterSexDist
)

Arguments

nrowgrids

is a numeric value which defines the number of rows of the arena.

ncolgrids

is a numeric value which defines the number of columns of the arena.

unitarea

is the unit area used for estimating density of lobsters.

initlambda

is the density of lobsters at the beginning of simulation.

initD

is the dispersion index of lobsters on seabed at the beginning of the simulation.

lobsterSizeFile

is a csv file that contains the frequency of lobsters size class.

lobsterSexDist

is a list that contains the sex ratio of lobsters. Possible values are M=male, F=female, MM=mature male, BF=berried female)

Value

Returns x and y coordinates of simulated lobsters at the beginning.

The function randomly selects an angle (0:360) and moves the lobster. This function is called when a lobster is outside the area of influence.

Description

The function randomly selects an angle (0:360) and moves the lobster. This function is called when a lobster is outside the area of influence.

Usage

randomMove(Lobster, dStep)

Arguments

Lobster

location of lobster in x and y coordinates

dStep

is how much a lobster moves in each time step

Value

Returns the new coordinates of each lobster

This function replicates the coordinates where there are multiple lobsters

Description

This function replicates the coordinates where there are multiple lobsters

Usage

replicateCoordinates(d)

Arguments

d

is a data frame containing x and y coordinates of lobsters and number of lobsters at each coordinate

Value

Returns a data frame

This function generates a Poisson or a negative binomial distribution for lobsters in the arena

Description

This function generates a Poisson or a negative binomial distribution for lobsters in the arena

Usage

rpoisD(n, lambda, D = 1)

Arguments

n

is the number of lobsters to be generated

lambda

is the mean density of lobsters

D

is the dispersion index to be used. Default value is 1

Value

A vector of integers that is used as initial distribution of lobsters

This function determines if lobster gets into a trap and is caught.

Description

This function determines if lobster gets into a trap and is caught.

Usage

trapInPath(loc1, loc2, Trap, howClose)

Arguments

loc1

is the location of lobster at the start of each time step

loc2

is the location of lobster at the end of each time step

Trap

is the location of trap

howClose

The area within which a lobster considered trapped

Value

Returns a vector that contain lobster path and whether its trapped

This function updates the coordinate of each lobster at each timestep,

Description

This function updates the coordinate of each lobster at each timestep,

Usage

updateGrid(
  Lobster,
  Trap,
  trapCatch,
  lobSize,
  lobSex,
  radiusOfInfluence,
  currentZoI,
  dStep,
  howClose,
  q0,
  qmin,
  saturationThreshold,
  trapSaturation,
  lengthBased,
  lobLengthThreshold,
  sexBased
)

Arguments

Lobster

is the x & y coordinates of each lobster

Trap

is the x & y coordinates of the trap

trapCatch

number of trapped lobster

lobSize

Size of trapped lobster

lobSex

Sex of trapped lobster

radiusOfInfluence

is the initial radius of influence

currentZoI

is the bait's area of influence at each timestep

dStep

is how much a lobster moves in each time step

howClose

The area within which a lobster considered trapped

q0

is the initial probability of entry into an empty trap

qmin

is the asymptotic minimum probability of entry

saturationThreshold

is the number of lobsters in a trap at which the probability of another lobster entering the trap is zero

trapSaturation

Logical. If TRUE, lobsters behavioral interaction is included during the simulation.

lengthBased

Logical. If TRUE, lobster size is taken into account

lobLengthThreshold

is a size threshold (Carapace Length in mm), if a lobster larger than this threshold caught there will be no more entry to the trap

sexBased

Logical. If TRUE, lobster sex is taken into account and user must provide a list containing sex distribution for the simulated population

Value

a list of new coordinates, number of catch and their sizes