sample_fish: Sample numbers-at-age to create composition data

In r4atlantis/atlantisom: Generates Data Sets From Atlantis Scenarios

Sample numbers-at-age to create composition data

Description

Create sampled data from numbers-at-age data to create composition data from and Atlantis scenario by default. todo: add more information here later

Usage

sample_fish(dat, effN, sample = TRUE)

Arguments

dat	A data.frame of numbers at age containing the following columns: species agecl polygon layer time atoutput The data.frame is generated from either create_survey or create_fishery_subset.
effN	Efficiency for each species: a matrix with nrow=length(species). Columns: species: the species name. Matches names in species effN: the effective N for each species (effective sample size)
sample	Logical asking whether to apply multinomial sampling using effN. Setting to false results in simple aggregation of atoutput to annual age class values. The default value is TRUE.

Details

The function takes numbers-at-age data from an Atlantis scenario where the data was read in from Atlantis output using load_nc within run_truth. One does not need to use these functions to create dat, rather you must only ensure that the structure of dat is the same. Currently, the function creates sampled numbers-at-age data to create composition data (age, convert to length, age-at-weigth, etc.). sums across boxes to properly weight the numbers-at-age data. Subsequently, the data is sampled using a multinomial with the effective sample size based on the number of fish you pass in dat and prop. Density data are also needed for biological sampling. Therefore, when called with sample=FALSE for density data, applies median to aggregate and does not apply multinomial. The function starts with numbers-at-age data and therefore the function then must sum across boxes to properly weight them. Subsequently, the function then uses a multinomial with a specified effective sample size. The function could be improved by adding an argument to create spatial strata which are conglomerations of subsets of boxes.

Author(s)

Poseidon

Examples

	directory <- system.file("extdata", "SETAS_Example", package = "atlantisom")
	scenario <- "outputs"
	species <- c("Pisciv_T_Fish","Pisciv_S_Fish")
	results <- run_truth(scenario = scenario,
	dir = directory,
	file_fgs = "Functional_groups.csv",
	file_bgm = "Geography.bgm",
	select_groups = species,
	file_init = "Initial_condition.nc",
	file_biolprm = "Biology.prm",
	file_runprm = "Run_settings.xml",
   file_fish = "Fisheries.csv")

    boxes <- 1:3
	effic <- data.frame(species=c("Pisciv_T_Fish","Pisciv_S_Fish"), efficiency=c(0.3,0.1))
	selex <- data.frame(species=c(rep("Pisciv_T_Fish",10),rep("Pisciv_S_Fish",10)),
	                agecl=c(1:10,1:10),
	                selex=c(0,0,0.1,0.5,0.8,1,1,1,1,1,0,0,0.1,0.3,0.5,0.7,0.9,1,1,1))

	tmp <- create_survey(dat=results$nums, time=seq(10,55,3), species=species, boxes=boxes, effic=effic, selex=selex)
	effN <- data.frame(species=species, effN=c(200, 500))
	samp <- sample_fish(tmp, effN=effN)

r4atlantis/atlantisom documentation built on Nov. 12, 2023, 2:59 a.m.