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13th International Conference on Membrane Computing - MTA Sztaki

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Modelling ecological systems with the calculus of wrapped compartments<br />

Example 1. Immigrati<strong>on</strong> and extincti<strong>on</strong> are key comp<strong>on</strong>ents of island biogeography.<br />

We model a metapopulati<strong>on</strong> of species a in a c<strong>on</strong>text of 5 different patches:<br />

4 of which are relatively close, e.g. different ecological regi<strong>on</strong>s within a small<br />

c<strong>on</strong>tinent, the last <strong>on</strong>e is far away and difficult to reach, e.g. an island. The<br />

c<strong>on</strong>tinental patches are modelled as CWC compartments of type l c , the island<br />

is modelled as a compartment of type l i . Births, deaths and migrati<strong>on</strong>s in the<br />

c<strong>on</strong>tinental patches are modelled by the following CWC rules:<br />

l c : a 0.005<br />

↦−→ a a l c : a 0.005<br />

↦−→ •<br />

lc 0.01<br />

⊤ : (x ⌋ a X) ↦−→ a (x ⌋ X) lc ⊤ : a (x ⌋ X) lc 0.5<br />

↦−→ (x ⌋ a X) lc<br />

These rates are drawn c<strong>on</strong>sidering days as time unites and an average of life<br />

expectancy and reproducti<strong>on</strong> time for the individuals of the species a of 200 days<br />

1<br />

(<br />

0.005<br />

). For the modelling of real case studies, these rates could be estimated from<br />

data collected in situ by tagging individuals. 9 In this model, when an individual<br />

emigrates from its previous patch it moves to the top-level compartment from<br />

where it may reach <strong>on</strong>e of the close c<strong>on</strong>tinental patches (might also be the old<br />

<strong>on</strong>e) or start a journey through the sea (modelled as a rewrite rule putting the<br />

individual <strong>on</strong> the wrapping of the island compartment):<br />

⊤ : a (x ⌋ X) li 0.2<br />

↦−→ (x a ⌋ X) li<br />

Crossing the ocean is a l<strong>on</strong>g and difficult task and individuals trying it will<br />

probably die during the cruise; the luckiest <strong>on</strong>es, however, might actually reach<br />

the island, where they could eventually benefit of a better life expectancy for<br />

them and their descendants:<br />

li 0.333<br />

⊤ : (x a ⌋ X) ↦−→ (x ⌋ X) li li 0.0005<br />

⊤ : (x a ⌋ X) ↦−→ (x ⌋ a X) li<br />

l i : a 0.007<br />

↦−→ a a l i : a 0.003<br />

↦−→ •<br />

C<strong>on</strong>sidering the initial system modelled by the CWC term:<br />

t = (• ⌋ 30 ∗ a) lc (• ⌋ 30 ∗ a) lc (• ⌋ 30 ∗ a) lc (• ⌋ 30 ∗ a) lc (• ⌋ •) li<br />

we can simulate the possible evoluti<strong>on</strong>s of the overall diffusi<strong>on</strong> of individuals<br />

of species a in the different patches. Notice that, <strong>on</strong> average, <strong>on</strong>e over 0.333<br />

0.0005<br />

individuals that try the ocean journey, actually reach the island. In Figure 1 we<br />

show the result of a simulati<strong>on</strong> plotting the number of individuals in the different<br />

patches in a time range of approximatively 10 years. Note how, in the final part<br />

of the simulati<strong>on</strong>, empty patches get recol<strong>on</strong>ised. In this particular simulati<strong>on</strong>,<br />

also, an exp<strong>on</strong>ential growth begins after the col<strong>on</strong>isati<strong>on</strong> of the island. The full<br />

CWC model describing this example can be found at: http://www.di.unito.<br />

it/~troina/cmc13/metapopulati<strong>on</strong>.cwc.<br />

In ecology, using r to represent the pro-capita growth rate of a populati<strong>on</strong> and<br />

K the carrying capacity of the hosting envir<strong>on</strong>ment, 10 r/K selecti<strong>on</strong> theory [38]<br />

9 In the remaining examples we will omit a detailed time descripti<strong>on</strong>.<br />

10 I.e., the populati<strong>on</strong> size at equilibrium.<br />

391

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