Project matrix with Density Dependence

Project the matrix model forward in time with density dependence.

Usage

Projection_DD(
  M.mx = NA,
  D.mx = NULL,
  H.mx = NULL,
  dat = NA,
  Nyears = 100,
  K = NA,
  p.cat = NA,
  CE_df = NULL,
  K_adj = FALSE,
  stage_k_override = NULL,
  bh_dd_stages = NULL
)

Arguments

M.mx

A projection matrix expression

D.mx

A matrix of density-dependence effect

H.mx

A harm projection matrix

dat

Life history data

Nyears

Years to run simulation

K

The population carrying Capacity of adults (mature individuals)

p.cat

Probability of catastrophic event.

CE_df

Cumulative effect data frame. Data frame identifying cumulative effects stressors targets system capacity or population parameter, or both, and target life stages.

K_adj

Boolean. Should K_adj be run. Defaults to false.

stage_k_override

Vector of K values for fry (0), stage_1, stage_2 values etc. defaults to NULL. If set values will override adult K value for alternative DD mechanism.

bh_dd_stages

Optional Character vector of life stages c("dd_hs_0", "bh_stage_1", "bh_stage_2", "bh_stage_3", ...) to apply classical Beverton-Holt density-dependence. To be used in place of compensation ratios if set. Use "dd_hs_0" for egg-to-fry k, "bh_stage_1" for fry to stage_1 k and "bh_stage_2" for stage_1 to stage_2 k etc. Densities are the capped value for the transition stage.

Value

A list object with projected years, population size, lambda, fecundity, survival, catastrophic events.

Details

The function runs the population projections forward through time. Life-cycle specific stressors (if set) will be applied based on values in the CE_df table. There are several ways to implement density dependence. deterministic projection matrix using popbio::stable.stage with initial parameters based on arguments provided. Applies CE stressors to appropriate targets based on CE_df. All population modeling components are contained within this function. Users define a projection matrix, density-dependence matrix, harm projection matrix, life history parameters, years to simulate, carrying capacity, catastrophic event probabilities and a cumulative effects data frame (CE_df). When run this function will project the population forward in time. See the vignette tutorial Population Model Overview for details and instructions.