Population dynamics

 Variable: n_total = sum({n}) 

Where: {n} = Cohort/n

Variable: population_total_size = sum({cohort_total_size})
Where: {cohort_total_size} = Cohort/cohort_total_size

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Submodel Bigger

Submodel "Bigger" is an association submodel between "Cohort" and itself with roles "other" and "me".

Condition: condition = other_size>me_size
Where:
me_size = Value(s) of ../Cohort/size from submodel "Cohort" in role "me"
other_size = Value(s) of ../Cohort/size from submodel "Cohort" in role "other"

Variable: total_size_of_bigger_cohort = other_cohort_total_size
Where:
me_cohort_total_size = Value(s) of ../Cohort/cohort_total_size from submodel "Cohort" in role "me"
other_cohort_total_size = Value(s) of ../Cohort/cohort_total_size from submodel "Cohort" in role "other"

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Submodel Cohort

Submodel "Cohort" is a population submodel.

Compartment: n
Initial value = 100
Rate of change = - loss

Compartment: size
Initial value = 0
Rate of change = + growth

Flow: growth = gr*(1-size/max_size)

Flow: loss = 5

Immigration: create_new_cohort = 1

Loss: remove_cohort = n<=0

Variable: cohort_total_size = n*size

Variable: gr = 1.5

Variable: max_size = 10

Variable: total_size_of_all_bigger_cohorts = sum({cohort_total_size_of_bigger_me})
Where:
{cohort_total_size_of_bigger_me} = ../Bigger/total_size_of_bigger_cohort for submodel "Cohort" in role "me"

 Compartment level

Initial value = rand_const(50,50.000001)
Rate of change = + change

Flow change
change = gain*level*(1-level/100)



 Compartments:

forest: initial value = 1
budworm: initial value = 10

Flows:
ageing = (if forest<4 then 0.02 else 0)
regression = (if budworm>300 then forest-1 else 0)
recruitment = forest*graph(0,400,400,5,0,400,1,21,points(292,315,346,346,328,311,302,301,301,308,318,327,332,339,345,346,348,352,352,352,353),budworm)*budworm where[budworm=budworm,forest=forest] 

 Equations in Desktop

N = sum({one})

Equations in ANIMAL
X: initial value = rand(30,70)
Y: initial value = rand(30,70)
Dir: initial value = rand(0,6.28)

create = 100
r = rand(0,2*0.7)
m = 0.6

xchange = (if outside == 1 then speed*cos(dir+3.14) else speed*cos(dir))
dirchange = (if outside == 1 then 3.14/dt(1) else rand(-0.4,0.4)/dt(1))
ychange = (if outside == 1 then speed*sin(dir+3.14) else speed*sin(dir))

speed = 5
size = 3
outside = (if (x<0;x>100;y<0;y>100)then 1 else 0)
one = 1

Equations in Desktop

births = sum([these_births])
pop size = sum([pop_size])

Equations in Age class

pop size: initial value = element([2,0,0,0],index(1))

ageing in = sum({ageing_next})
Where: {ageing_next}=../Next class/ageing (to Age class in next)

ageing out = element([1,0.2,0.1,0],index(1))*pop_size

births = if index(1)==1 then births else 0

deaths = m*pop_size

class = index(1)

m = element([0.05,0.01,0.01,0.05],index(1))

r = element([0,0.05,0.2,0.1],index(1))*(1-total_pop_size/100)

these births = r*pop_size

Equations in Next class

condition = class_next==class_this+1
Where: class_this=../Age class/class (from Age class in this) class_next=../Age class/class (from Age class in next)

ageing = ageing_out_this
Where: ageing_out_this=../Age class/ageing out (from Age class in this)

here: ageing_out_this=../Age class/ageing out (from Age class in this)/    

 Equations in Desktop

births = sum([these_births])
pop size = sum([pop_size])
ageing = [ageing_out]

Equations in Age class
pop size: initial value = element([2,0,0,0],index(1))
births = if index(1) == 1 then births else 0
ageing out = element([1,0.2,0.1,0],index(1))*pop_size
deaths = m*pop_size
ageing in = if index(1)>1 then element([ageing],index(1)-1)else 0
m = element([0.05,0.01,0.01,0.05],index(1))
r = element([0,0.05,0.2,0.1],index(1))*(1-pop_size/100)
these births= r*pop_size

 Compartments

pop_size_1: initial value = 2
pop size_2: initial value = 0
pop size_3: initial value = 0
pop size_4: initial value = 0

Flows
ageing_1 = pop_size_1
ageing_2 = 0.2*pop_size_2
ageing_3 = 0.1*pop_size_3
births = births_2+births_3+births_4
deaths_1 = m1*pop_size_1
deaths_2 = m2*pop_size_2
deaths_3 = m3*pop_size_3
deaths_4 = m4*pop_size_4

Parameters
m1 = 0.05
m2 = 0.01
m3 = 0.01
m4 = 0.05

Intermediate variables
births_2 = r2*pop_size_2
births_3 = r3*pop_size_3
births_4 = r4*pop_size_4
pop size = pop_size_1+pop_size_2+pop_size_3+pop_size_4
r2 = 0.05*(1-pop_size/100)
r3 = 0.2*(1-pop_size/100)