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the seminal paper of Mason, 1974) improvements in
(semi-) automatic measurements methods have made
interpretation easier. Morales-Nin et al. (1998) used
Fourier analysis and subsequent wavelet analysis for
studying the periodic signals obtained from an otolith
radius (Figure 17.8). This method allowed the analysis of
signals having the potential to discriminate between the
different time-scales (daily, weekly, monthly) interacting
with the otolith growth rate.
Such methods were later complemented and somewhat
enhanced by new algorithms. For instance, Cao and Fablet
(2006) developed an automatic detection of the growth
centre (i.e. otolith nucleus) to limit experimenter effects.
In some crustaceans, there is a relationship between
age and lipofuscin concentrations in the brain (Sheehy,
1990a). Belchier et al. (1998) used confocal fluorescence
microscopy and IA of histological sections to quantify
lipofuscin in the crayfish Pacifastacus leniusculus . After the
excitation of olfactory lobe sections (to reveal autofluores-
cence) and the optimisation of image catch (see Sheehy,
1990b for details), brightly autofluorescing lipofuscin
granules were discriminated from the darker background
of neurone somata using greyscale thresholding. The
outline of the cell-mass background in the image was
traced manually and, finally, the total cross-sectional areas
of both lipofuscin and the background cells were calcu-
lated by the software. Following this procedure, Belchier
et al. (1998) showed that lipofuscin concentration was
linearly associated with age (r 2
0 . 92) and produced
much more accurate age estimates than conventional
body size-based procedures.
Individual growth, rather than population growth rate
(PGR), is central to the theory of population ecology. In
some cases, IA offers potential tools for estimating PGR.
In the Crustacean Daphnia magna , PGR was estimated as
the ratio of population sizes at two different times, where
size was measured by the sum of the individuals' surface
areas (Hooper et al., 2006). The IA system proved reliable
and reproducible in counting and estimating surface area
of up to 440 individuals in 5 L of water.
=
17.2.2.3 Description of ontogenetic stages
For many species, successive ontogenetic stages differ
in physiological, behavioural and morphological ways.
Therefore, IA tools can be used to differentiate life stages,
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Figure 17.8 Left: otolith of Atlantic salmon (Salmo salar) showing the reading radius with enhanced increments. Right: signal vector
corresponding to a grey level of enhanced increments, with noise (top), and the same signal once filtered by a Fast Fournier
Transform (bottom). Reproduced with permission from Morales-Nin, B., Lombarte, A. and Jap on, B. (1998) Approaches to otolith
age determination: image signal treatment and age attribution. Scientia Marina 62, 247-256.
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