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HIERARCHAL INDUCTIVE PROCESS MODELING AND ANALYSIS ...

HIERARCHAL INDUCTIVE PROCESS MODELING AND ANALYSIS ...

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(<br />

∴ P 0 + a )<br />

13<br />

α − δ Z 0 e −αlt − a 13<br />

α − δ Z 0e −δt ≤ P (t) ≤ P 0 e αut (20)<br />

P (t) > 0 ∈ (0, +∞)<br />

From a biological standpoint α l is the maximum rate of decline and α u is the maximum<br />

rate of growth. Theses bounds give us little information about the model, as<br />

they simply state that Phytoplankton concentration is contained between zero and<br />

infinity.<br />

Next we look at Detritus:<br />

dD<br />

(<br />

) (<br />

{ }} { )<br />

dt = (1 − a 10 )a 11 P + a 11 + (1 − a 12 ) a 13 (1 − e (−a 14P ) ) (1 − a 10 )Z − D(a 15 + a 18 )<br />

(<br />

)<br />

)<br />

≤ (1 − a 10 )a 11 P +<br />

(a 11 + (1 − a 12 )a 13 (1 − a 10 )Z − D(a 15 + a 18 )<br />

(<br />

)<br />

)<br />

≤ (1 − a 10 )a 11 P 0 e<br />

} {{ αut +<br />

(a<br />

} 11 + (1 − a 12 )a 13 (1 − a 10 ) Z 0 e<br />

} {{ −δt<br />

}<br />

(20)<br />

(16)<br />

− D(a 15 + a 18 )<br />

≥a 13<br />

Using (16) and (20)and simplifying a bit we get a more manageable upper bound.<br />

Solving for upper bound D u (t)<br />

dD u<br />

dt<br />

+ (a 15 + a 18 )D u = (1 − a 10 )a 11 P 0 e αut +<br />

(a 11 + (1 − a 12 )a 13<br />

)<br />

(1 − a 10 )Z 0 e −δt<br />

46

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