run_LeMans | R Documentation |
Project the LeMans model forward in time.
run_LeMans(params, ...) ## S4 method for signature 'missing' run_LeMans( N0, Fs, tot_time, nsc, nfish, phi_min, mature, sc_Linf, wgt, phi, ration, other, M1, suit_M2, stored_rec_funs, recruit_params, eps = 1e-05 ) ## S4 method for signature 'LeMans_param' run_LeMans( params, years = 10, N0 = NULL, effort = matrix(0, years, dim(params@Qs)[3]), Fs, intercept = 1e+10, slope = -5, tot_time )
params |
A LeMans_param object containing the parameter values of the current LeMans model. |
... |
Additional arguments. |
N0 |
A matrix with dimensions |
Fs |
An array with dimensions |
tot_time |
A numeric value representing the number of time steps to run the model for. |
nsc |
A numeric value representing the number of length classes in the model. |
nfish |
A numeric value representing the number of fish species in the model. |
phi_min |
A numeric value representing the time step of the model. |
mature |
A matrix with dimensions |
sc_Linf |
A numeric vector of length |
wgt |
A matrix with dimensions |
phi |
A matrix with dimensions |
ration |
A matrix with dimensions |
other |
A numeric value representing the amount of other food (g) available from prey that is not explicitly represented in the model. |
M1 |
A matrix of dimensions |
suit_M2 |
A list object of length |
stored_rec_funs |
A list object of length |
recruit_params |
A list object of length |
eps |
A numeric value specifying a numerical offset. The default value is |
years |
A numeric value representing the number of years that the model is run for. The default is 10. |
effort |
A matrix with dimensions |
intercept |
A numeric value representing the number of individuals in the first length class. This parameter is only required if |
slope |
A numeric value representing the slope of the community size spectrum. This parameter is only required if |
An object of class LeMans_outputs
.
LeMans_outputs
, LeMans_param
, LeMansParam
# Run the model with all inputs specified explicitly: # Set up the inputs to the function - species-independent parameters nfish <- nrow(NS_par) nsc <- 32 maxsize <- max(NS_par$Linf)*1.01 # the biggest size is 1% bigger than the largest Linf l_bound <- seq(0, maxsize, maxsize/nsc); l_bound <- l_bound[-length(l_bound)] u_bound <- seq(maxsize/nsc, maxsize, maxsize/nsc) mid <- l_bound+(u_bound-l_bound)/2 # Set up the inputs to the function - species-specific parameters Linf <- NS_par$Linf # the von-Bertalanffy asymptotic length of each species (cm). W_a <- NS_par$W_a # length-weight conversion parameter. W_b <- NS_par$W_b # length-weight conversion parameter. k <- NS_par$k # the von-Bertalnaffy growth parameter. Lmat <- NS_par$Lmat # the length at which 50\% of individuals are mature (cm). # Get phi_min tmp <- calc_phi(k, Linf, nsc, nfish, u_bound, l_bound, calc_phi_min=FALSE, phi_min=0.1) # fixed phi_min phi <- tmp$phi phi_min <- tmp$phi_min # Calculate growth increments tmp <- calc_ration_growthfac(k, Linf, nsc, nfish, l_bound, u_bound, mid, W_a, W_b, phi_min) ration <- tmp$ration sc_Linf <- tmp$sc_Linf wgt <- tmp$wgt g_eff <- tmp$g_eff # Calculate maturity mature <- calc_mature(Lmat, nfish, mid, kappa=rep(10, nfish), sc_Linf) # Create recruitment functions stored_rec_funs <- get_rec_fun(rep("hockey-stick", nfish)) recruit_params <- do.call("Map", c(c, list(a=NS_par$a, b=NS_par$b))) # Calculate background mortality M1 <- calc_M1(nsc, sc_Linf, phi_min) # Calculate predator-prey size preferences prefs <- calc_prefs(pred_mu=-2.25, pred_sigma=0.5, wgt, sc_Linf) # Calculate prey preference and prey suitability suit_M2 <- calc_suit_vect(nsc, nfish, sc_Linf, prefs, NS_tau) # Calculate catchability Qs <- calc_Q(curve=rep("logistic", nfish), species=NS_par$species_names, max_catchability=rep(1, nfish), gear_name=NS_par$species_names, nsc=nsc, nfish=nfish, mid=mid, l_bound=l_bound, u_bound=u_bound, species_names=NS_par$species_names, eta=rep(0.25, nfish), L50=Lmat) # Get an initial population N0 <- get_N0(nsc, nfish, mid, wgt, sc_Linf, intercept=1e10, slope=-5) years <- 10 # run the model for 10 years tot_time <- years*phi_min # total number of time steps # Define fishing effort to be 0.5 for all species effort <- matrix(0.5, tot_time, dim(Qs)[3]) # Calculate F Fs <- array(0, dim=c(nsc, nfish, tot_time)) for (j in 1:ncol(effort)) { for (ts in 1:tot_time) { Fs[,,ts] <- Fs[,,ts]+effort[ts, j]*Qs[,,j] } } # Run the model model_run <- run_LeMans(N0=N0, tot_time=tot_time, Fs=Fs, nsc=nsc, nfish=nfish, phi_min=phi_min, mature=mature, sc_Linf=sc_Linf, wgt=wgt, phi=phi, ration=ration, other=NS_other, M1=M1, suit_M2=suit_M2, stored_rec_funs=stored_rec_funs, recruit_params=recruit_params, eps=1e-05) ############################################## # Alternatively: NS_params <- LeMansParam(NS_par,tau=NS_tau,eta=rep(0.25,21),L50=NS_par$Lmat,other=NS_other) # Define fishing effort effort <- matrix(0.5, 10, dim(NS_params@Qs)[3]) # Run the model model_run <- run_LeMans(NS_params, years=10, effort=effort)
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