Growth model of the reared sea urchin Paracentrotus ... - SciViews
Growth model of the reared sea urchin Paracentrotus ... - SciViews
Growth model of the reared sea urchin Paracentrotus ... - SciViews
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have <strong>the</strong> basic von Bertalanffy 1 <strong>model</strong> that was designed for linear<br />
measurements <strong>of</strong> size (1938, his eq. 26). With d = 3, we have <strong>the</strong> cube <strong>of</strong> a<br />
linear measurement, that is, a volume or a weight (not considering possible<br />
allometries) and Richards <strong>model</strong> reduces to von Bertalanffy <strong>model</strong> 2,<br />
designed for weight measurements. Weibull's <strong>model</strong> (Weibull, 1951)<br />
belongs probably to this category too, though <strong>the</strong> exponent c applies only<br />
to time t. When c = 1, it also reduces to <strong>the</strong> basic von Bertalanffy 1 <strong>model</strong>,<br />
with a slightly different parameterization. The effect <strong>of</strong> <strong>the</strong> exponent,<br />
being d in Richards or c in Weibull, is to transform <strong>the</strong> von Bertalanffy 1<br />
curve into a S-shaped one, or sigmoid, by means <strong>of</strong> a power<br />
transformation.<br />
'Transitional' <strong>model</strong>s fit <strong>the</strong> S-shape as a transition between two states.<br />
The logistic function describes a transition between two constant states<br />
corresponding to its two horizontal asymptotes: D = 0 and D = a. In regard<br />
to <strong>the</strong> results obtained in Table 12, this <strong>model</strong> is not adapted here and it<br />
has no affinity with <strong>the</strong> von Bertalanffy 1 <strong>model</strong>. This <strong>model</strong> was initially<br />
designed to <strong>model</strong> population growth, not individual growth (Verhulst,<br />
1838). The 4-parameter logistic is ano<strong>the</strong>r 'transitional' <strong>model</strong> and we will<br />
demonstrate later its relation with von Bertalanffy 1. With <strong>the</strong> current<br />
parameterization, it also represents a transition between two constant states<br />
materialized by two horizontal asymptotes at D = a and D = d. It fits P.<br />
lividus data very well.<br />
The original growth <strong>model</strong> <strong>of</strong> eq. 29 is a third 'transitional' <strong>model</strong> and<br />
is our missing link as a general equivalent for 'transitional' <strong>model</strong>s to <strong>the</strong><br />
Richards' curve for 'dimensional' <strong>model</strong> (if we except d = -1 and d → ∞<br />
that are physically and biologically meaningless, and thus probably<br />
ma<strong>the</strong>matic artifacts in this context). When l = 0, it reduces to <strong>the</strong> von<br />
Bertalanffy 1 <strong>model</strong>. We now have to demonstrate it is a generalization <strong>of</strong><br />
<strong>the</strong> 4-parameter logistic function. If, in D = d + (a - d)/(1+e -b(t-c) ) we<br />
perform <strong>the</strong> following replacements: t ⇒ t', a ⇒ D0 + ∆D∞, b ⇒ k,<br />
c ⇒ ln(l)/k and d ⇒ D0 – ∆D∞/l, we obtain:<br />
Part IV: A growth <strong>model</strong> with intraspecific competition<br />
173