# Project the LeMans model Project the LeMans model forward in time. ```r 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 ) ``` ## Arguments - `params`: A LeMans_param object containing the parameter values of the current LeMans model. - `...`: Additional arguments. - `N0`: A matrix with dimensions `nsc` and `nfish` representing the number of individuals in each length class when the model is initialised. - `Fs`: An array with dimensions `nsc`, `nfish` and `tot_time` representing the fishing mortality of each species in each length class at each time step. - `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 `nsc` and `nfish` and elements in the range 0-1 representing the proportion of individuals that are mature for each species and length class. - `sc_Linf`: A numeric vector of length `nsc` representing the length class at which each species reaches its asymptotic length. - `wgt`: A matrix with dimensions `nsc` and `nfish` representing the weight of each species in each length class. - `phi`: A matrix with dimensions `nsc` and `nfish` representing the proportion of individuals that leave each length class. - `ration`: A matrix with dimensions `nsc` and `nfish` representing the amount of food required for fish of a given species and length class to grow according to the von Bertalanffy growth curve in a time step. - `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 `nsc` and `nfish` representing the natural mortality of each species for each length class. - `suit_M2`: A list object of length `nfish`. Each element in the list is an array of dimensions `nsc`, `nsc` and `nfish` containing a value between zero and 1 representing prey preference and prey suitability for each species and length class. - `stored_rec_funs`: A list object of length `nfish` where each element includes the stock recruitment function for each species. If an invalid recruitment function is selected, `NULL` is returned and a warning message is shown. - `recruit_params`: A list object of length `nfish` specifying the parameters for the recruitment function. - `eps`: A numeric value specifying a numerical offset. The default value is `1e-5`. - `years`: A numeric value representing the number of years that the model is run for. The default is 10. - `effort`: A matrix with dimensions `years` and the number of fishing gears, representing fishing effort in each year for each gear. This parameter is required only if `Fs` is missing. - `intercept`: A numeric value representing the number of individuals in the first length class. This parameter is only required if `N0` is missing. The default is `1e10`. - `slope`: A numeric value representing the slope of the community size spectrum. This parameter is only required if `N0` is missing. The default is -5. ## Returns An object of class `LeMans_outputs`. ## Examples ```r # 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) ``` ## See Also `LeMans_outputs`, `LeMans_param`, `LeMansParam`

run_LeMans function