DispersalPerRecruitModel {ConnMatTools}  R Documentation 
This function implements the marine population dynamics model described in Kaplan et al. (2006). This model is most appropriate for examining equilibrium dynamics of agestructured populations or temporal dynamics of semelparous populations.
DispersalPerRecruitModel( LEP, conn.mat, recruits0, timesteps = 10, settler.recruit.func = hockeyStick, ... )
LEP 
a vector of lifetimeeggproduction (LEP; also known as eggsperrecruit (EPR)) for each site. 
conn.mat 
a square connectivity matrix. 
recruits0 
a vector of initial recruitment values for each site. 
timesteps 
a vector of timesteps at which to record egg production, settlement and recruitment. 
settler.recruit.func 
a function to calculate recruitment from the
number of settlers at each site. Defaults to 
... 
additional arguments to settler.recruit.func. Typically

A list with the following elements:
eggs 
egg production for
the timesteps in 
settlers 
Similar for settlement 
recruits 
Similar for recruitment 
David M. Kaplan dmkaplan2000@gmail.com
Kaplan, D. M., Botsford, L. W., and Jorgensen, S. 2006. Dispersal per recruit: An efficient method for assessing sustainability in marine reserve networks. Ecological Applications, 16: 22482263.
See also BevertonHolt
, hockeyStick
library(ConnMatTools) data(chile.loco) # Get appropriate collapse slope # critical.FLEP=0.2 is just an example slope < settlerRecruitSlopeCorrection(chile.loco,critical.FLEP=0.2) # Make the middle 20 sites a reserve # All other sites: scorched earth n < dim(chile.loco)[2] LEP < rep(0,n) nn < round(n/2)9 LEP[nn:(nn+19)] < 1 Rmax < 1 recruits0 < rep(Rmax,n) # Use DPR model ret < DispersalPerRecruitModel(LEP,chile.loco,recruits0,1:20,slope=slope,Rmax=Rmax, settler.recruit.func=BevertonHolt) image(1:n,1:20,ret$settlers,xlab="sites",ylab="timesteps", main=c("Settlement","click to proceed")) locator(1) plot(ret$settlers[,20],xlab="sites",ylab="equilibrium settlement", main="click to proceed") locator(1) # Same, but with a uniform Laplacian dispersal matrix and hockeyStick cm < laplacianConnMat(n,10,0,"circular") ret < DispersalPerRecruitModel(LEP,cm,recruits0,1:20,slope=1/0.35,Rmax=Rmax) image(1:n,1:20,ret$settlers,xlab="sites",ylab="timesteps", main=c("Settlement","click to proceed")) locator(1) plot(ret$settlers[,20],xlab="sites",ylab="equilibrium settlement")