disturbance_regime_trial=list() for (l in 1:num_trials){ disturbance_regime=matrix(1,nrow=max_time,ncol = total_patches) for (q in 1:max_time){ disturbance_regime_temp = rbinom(n = (total_patches),size=1,prob = 1-disturbance_prob_param) # This causes a disturbance in patches nearby the original disturbance location for (index in which(disturbance_regime_temp==0)){ patches_that_are_hit = (index-disturbance_size_param):(index+disturbance_size_param) patches_that_are_hit=patches_that_are_hit[patches_that_are_hit>0] patches_that_are_hit=patches_that_are_hit[patches_that_are_hit<=length(disturbance_regime_temp)] disturbance_regime_temp[patches_that_are_hit]=0 } disturbance_regime_temp[disturbance_regime_temp==0]=1-disturbance_magnitude disturbance_regime[q,]=disturbance_regime_temp } # Insert optional code here to modify where disturbances can occur if (biased_disturbance_side == TRUE){disturbance_regime[,32:39]=1} if (biased_disturbance_rotating == TRUE){disturbance_regime[,seq(32,47,2)]=1} #disturbance_regime[,32:41]=1 #disturbance_regime[,seq(30,48,2)]=1 #colSums(disturbance_regime==0) #disturbance_regime[,1:10]=1 #disturbance_regime[,30:42]=1 disturbance_regime_trial[[l]]=disturbance_regime } #probability_of_disturbance = 100*median(colSums(disturbance_regime==1-disturbance_magnitude)/(200))