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capsule in fourth instar
Chironomus riparius
larvae (e.g.
mentum width and antennal segment lengths), which
were collected from various sampling sites subjected to
different types and degrees of stress. The analysis grouped
the sampling sites in a similar way to other measures of
stress (e.g. head capsule deformities). However, FA as
a stress indicator should be used carefully. Servia et al.
(2004) suggested that several characters, not one, should
be considered in such analyses. Davis and Grosse (2008)
indicated that the magnitude of FA variation could differ
between genders (e.g. higher among male compared to
female turtles) and that asymmetry may vary naturally
with increasing age.
2010), which is currently another major environmental
problem. Obviously, the currently already amazing IA
techniques will continue to grow in power and utility
in applied and fundamental freshwater studies, towards
actually unexpected applications.
References
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17.5 Conclusion
With the emergence of new IA techniques, it is now
possible to push the boundaries by examining objects
either smaller or presenting more complex shapes. The
development of these techniques has greatly improved
accuracy and precision of various measurements and
subsequent objectivity and coherence in decision mak-
ing. The techniques for catching, correcting, sorting and
segmenting images still increase in quality; new and pow-
erful algorithms for extracting information from pictures
and for analysing data (e.g. 3D and even 4D data, see
Zhang et al., 2010) are still developed. Artificial intelli-
gence, through artificial neural networks or fuzzy logic
theory, is now being applied to image understanding
(e.g. Hemanth et al., 2010). Although these recent devel-
opments often emerge from medical research, nothing
prevents their use for ecological purposes. For instance,
in aquatic environments, some current IA developments
are oriented towards 1) a better detection of potential
risks for human and animal health (e.g. through early
detection of cyanobacteria or algae: Vardon et al., 2011);
2) a better detection of alien species, such as undesired
macrophytes in riparian zones (Jones et al., 2011), that
maybe conducted from satellite imagery (Dlamini, 2011);
3) a better automatic detection and classification of species
(or stocks) from underwater videos (Spampinato et al.,
2010), that can be of importance, for example, for the
management of patrimonial species or the detection of
invasive ones; 4) the use of non-invasive sex determi-
nation procedures (Ferreira et al., 2010), that can be of
interest for the detection of environmental exposure to
endocrine disruptive chemicals; 5) the documentation
about altered morphological and anatomical features of
organisms after an exposure to nanoparticles (Laban et al.,
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