set_trait_model: Sets up parameters for a trait-based model

In pwoodworth-jefcoats/Size-Based-Modeling: Mizer With The Effects Of Temperature Included

Sets up parameters for a trait-based model

Description

This functions creates a therMizerParams object so that trait-based-type models can be easily set up and run. The trait-based size spectrum model can be derived as a simplification of the general size-based model used in therMizer. All the species-specific parameters are the same, except for the asymptotic size, which is considered the most important trait characterizing a species. Other parameters are related to the asymptotic size. For example, the size at maturity is given by w_inf * eta, where eta is the same for all species. For the trait-based model the number of species is not important. For applications of the trait-based model see Andersen & Pedersen (2010). See the mizer vignette for more details and examples of the trait-based model.

Usage

set_trait_model(no_sp = 10, min_w_inf = 10, max_w_inf = 1e+05,
  no_w = 100, min_w = 0.001, max_w = max_w_inf * 1.1, min_w_pp = 1e-10,
  no_w_pp = round(no_w) * 0.3, w_pp_cutoff = 1, k0 = 50, n = 2/3,
  p = 0.75, q = 0.9, eta = 0.25, r_pp = 4, kappa = 0.005, lambda = 2
  + q - n, alpha = 0.6, ks = 4, z0pre = 0.6, h = 30, beta = 100,
  sigma = 1.3, f0 = 0.5, gamma = NA, knife_edge_size = 1000,
  gear_names = "knife_edge_gear", ...)

Arguments

no_sp	The number of species in the model. The default value is 10. The more species, the longer takes to run.
min_w_inf	The asymptotic size of the smallest species in the community.
max_w_inf	The asymptotic size of the largest species in the community.
no_w	The number of size bins in the community spectrum.
min_w	The smallest size of the community spectrum.
max_w	The largest size of the community spectrum. Default value is the largest w_inf in the community x 1.1.
min_w_pp	The smallest size of the background spectrum.
no_w_pp	The number of the extra size bins in the background spectrum (i.e. the difference between the number of sizes bins in the community spectrum and the full spectrum).
w_pp_cutoff	The cut off size of the background spectrum. Default value is 1.
k0	Multiplier for the maximum recruitment. Default value is 50.
n	Scaling of the intake. Default value is 2/3.
p	Scaling of the standard metabolism. Default value is 0.75.
q	Exponent of the search volume. Default value is 0.9.
eta	Factor to calculate w_mat from asymptotic size.
r_pp	Growth rate of the primary productivity. Default value is 4.
kappa	Carrying capacity of the resource spectrum. Default value is 0.005.
lambda	Exponent of the resource spectrum. Default value is (2+q-n).
alpha	The assimilation efficiency of the community. The default value is 0.6
ks	Standard metabolism coefficient. Default value is 4.
z0pre	The coefficient of the background mortality of the community. z0 = z0pre * w_inf ^ (n-1). The default value is 0.6.
h	Maximum food intake rate. Default value is 30.
beta	Preferred predator prey mass ratio. Default value is 100.
sigma	Width of prey size preference. Default value is 1.3.
f0	Expected average feeding level. Used to set gamma, the factor for the search volume. The default value is 0.5.
gamma	Volumetric search rate. Estimated using h, f0 and kappa if not supplied.
knife_edge_size	The minimum size at which the gear or gears select species. Must be of length 1 or no_sp.
gear_names	The names of the fishing gears. A character vector, the same length as the number of species. Default is 1 - no_sp.
...	Other arguments to pass to the therMizerParams constructor.

Details

The function has many arguments, all of which have default values. Of particular interest to the user are the number of species in the model and the minimum and maximum asymptotic sizes. The asymptotic sizes of the species are spread evenly on a logarithmic scale within this range.

The stock recruitment relationship is the default Beverton-Holt style. The maximum recruitment is calculated using equilibrium theory (see Andersen & Pederson, 2010) and a multiplier, k0. Users should adjust k0 to get the spectra they want.

The factor for the search volume, gamma, is calculated using the expected feeding level, f0.

Fishing selectivity is modelled as a knife-edge function with one parameter, knife_edge_size, which is the size at which species are selected. Each species can either be fished by the same gear (knife_edge_size has a length of 1) or by a different gear (the length of knife_edge_size has the same length as the number of species and the order of selectivity size is that of the asymptotic size).

The resulting therMizerParams object can be projected forward using project_therMizer() like any other therMizerParams object. When projecting the community model it may be necessary to reduce dt to 0.1 to avoid any instabilities with the solver. You can check this by plotting the biomass or abundance through time after the projection.

Value

An object of type therMizerParams

References

K. H. Andersen and M. Pedersen, 2010, Damped trophic cascades driven by fishing in model marine ecosystems. Proceedings of the Royal Society V, Biological Sciences, 1682, 795-802.

See Also

therMizerParams

Examples

## Not run: 
trait_params <- set_trait_model(no_sp = 15)
init_pop <- get_initial_n(trait_params, n0_mult = 0.001)
sim <- project_therMizer(trait_params, effort = 0, t_max = 50, dt=0.2,
    initial_n = init_pop, t_save = 1)
plot(sim)
## Set up industrial fishery that only fishes on species with w_inf <= 500 g
## And where the selectivity of the industrial fishery = w_inf * 0.05
no_sp <- 10
min_w_inf <- 10
max_w_inf <- 1e5
w_inf <- 10^seq(from=log10(min_w_inf), to = log10(max_w_inf), length=no_sp)
knife_edges <- w_inf * 0.05
industrial_gears <- w_inf <= 500
other_gears <- w_inf > 500
gear_names <- rep("Industrial", no_sp)
gear_names[other_gears] <- "Other"
params_gear <- set_trait_model(no_sp = no_sp, min_w_inf = min_w_inf,
    max_w_inf = max_w_inf, knife_edge_size = knife_edges, gear_names = gear_names)
## Only turn on Industrial fishery. Set effort of the Other gear to 0
sim <- project_therMizer(params_gear, t_max = 20, effort = c(Industrial = 1, Other = 0))

## End(Not run)

pwoodworth-jefcoats/Size-Based-Modeling documentation built on Sept. 15, 2023, 8:13 a.m.