The spatial growth model in this section differs from the logistic growth model in only

one respect. When an individual is created, it must be placed in a patch that is neighboring the parent. This might model the spreading growth of plants or bacterial colonies, whereas the original model might apply to a species with rapid dispersal. For the new model, when an individual is born, select one of the eight neighbors of the parent site. If this site is vacant, the new individual is added; otherwise, the new individual cannot grow, as before.

Change the section of the code that selects the site for the new individual. You will need to read the netlogo manual here. Things that might be useful:

one-of neighbors this means choose one of the eight neighbors at random you might also need 'sprout' instead of 'hatch'. A patch can sprout a new turtle, whereas a

turtle can hatch a new turtle. These are different in the syntax of netlogo. Keep the setup and the exact solution part the same as in the logistic-growth case.

to go birth-death tick set time dt * ticks set nexact (K * exp((r - 1) * time) / (C + exp((r - 1) * time))) plot-conc end

to birth-death set npop count turtles ask turtles [ if random-float 1.0 < dt * r [ set i random-pxcor set j random-pycor ask patch i j [set lpop count turtles-here] if lpop = 0 [ hatch 1 [ set color green set xcor i set ycor j ] ] ] if random-float 1.0 < dt [ die ] ] end