openpop_ratio: An open population function to calculate population changes...

In katherinekaplan/MPApopulationmodels: Population responses to marine protected areas (MPAs)

Description

This function calculates the ratio change abundance and biomass of a fished poulation, after a marine protected area is implemented assuming a population with external recruitment. The output is a data frame with population ratio changes from a fished population to unfished in the MPA It includes deterministic population model output and output using stochastic recruitment

Usage

openpop_ratio(tf, maxage, M, Fi, Lfish, Linf, k, a0, pW, qW, R, sig_r, MPAtime,
  simulations)

Arguments

tf:	the time steps to run the population
maxage:	max age of the species ie. number of age classes
Lmat:	length at maturity
M:	the natural mortality rate
Fi:	the fishing mortality rate, F, find in stock assessment if don't have more localized estimate
Linf:	asymptotic growth rate used in von-Bertallanfy growth equation, can find on fishbase
k:	von-bertallanfy growth parameter estimate
a0:	the age at length 0 used in the von-Bertallanfy growth equation
pW:	weight length relationship parameter, same as a on fishbase.org but need to divide by 1000 to get in kg not grams
qW:	weight length relationship parameter, same as b on fishbase.org
R:	number of recruits entering the population
sig_r:	stochastic parameter, log-normal distribution, around recruitment
MPAtime:	the time step to implement the MPA
simulations:	the number of simulations to run

Value

Nratio: the abundance ratio change over time

Bratio: the biomass ratio change over time

Nrat.sim.mean: the mean of abundance for simulation runs with stochastic recruitment in the MPA

Nrat.lowerCI.MPA: the lower quartile of abundance runs with stochastic recruitment in the MPA

Nrat.upperCI.MPA: the upper quartile of abundance runs with stochastic recruitment in the MPA

Nrat.mean.noMPA: the mean of changes in simulated abundance with stochastic recruitment in the fished state

Nrat.lowerCI.noMPA: the lower quartile of simulated runs for abundance with stochastic recruitment in the fished state

Nrat.upperCI.noMPA: the lower quartile of simulated runs with stochastic recruitment in the fished state

Bratio.sim.mean: the mean of changes in biomass for simulation runs with stochastic recruitment in the MPA

Brat.lowerCI.MPA: the lower quartile of biomass runs with stochastic recruitment in the MPA

Brat.upperCI.MPA: the upper quartile of biomass runs with stochastic recruitment in the MPA

Brat.mean.noMPA: the mean of changes in biomass for simulation runs with stochastic recruitment in the fished state

Brat.lowerCI.noMPA: the lower quartile of biomass runs with stochastic recruitment in the fished state

Brat.upperCI.noMPA: the upper quartile of biomass runs with stochastic recruitment in the fished state

Examples

openpop_ratio(tf=50, M=0.2,Fi=0.14,Lfish=25,Linf=37.8,k=0.13,a0=-0.7,maxage=25,pW=9.37e-06,qW=3.172,R=500,
 sig_r=0.5, MPAtime=1,simulations=100)

katherinekaplan/MPApopulationmodels documentation built on May 22, 2019, 8:51 p.m.