Dissertation - HQ
Dissertation - HQ
Dissertation - HQ
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38 Behaviour in models<br />
In situ studies<br />
are required to test<br />
whether larvae orient<br />
Information about<br />
cues and detection<br />
thresholds is scarce<br />
The first step is to detect whether fishes orient or not. Such information<br />
can be provided by field studies involving the release of larvae<br />
followed by divers 90,109–111 , or in situ orientation chambers 112 .<br />
The second step involves testing experimentaly the ability of larvae<br />
to detect environemental cues 100,102,103,113–116 . The potential for detecting<br />
a cue can be demonstrated in the laboratory by testing the preference<br />
of larvae toward a given environmental signal for example (e.g. coastal<br />
vs. oceanic water, reef sounds vs. random sound). Which cue is actually<br />
used in situ is currently unknown, due to the lack of experimental<br />
means of testing cues separately in the pelagic environment.<br />
The last step would be to describe thresholds for detection. This<br />
directly relates to the spatial scale over which cues can be detected<br />
and used for orientation. Knowledge in this regard is currently mostly<br />
lacking and is difficult to obtain, yet this is essential information for<br />
incorporation into models.<br />
1.5.4 Suggested implementation<br />
Orientation as a<br />
parameter or an<br />
emergent property<br />
The implementation of orientation is closely associated with that of<br />
swimming (both horizontal and vertical): orientation is simply a choice<br />
among the set of possible swimming vectors. Once again, two approaches<br />
can be taken: (1) behavioural rules in response to the environment<br />
can be defined a priori, based on observations and experimental<br />
work; (2) these behavioural rules can emerge from the model by defining<br />
the set of possible swimming vectors, a biologically sensible “goal” for<br />
larvae (e.g. settlement), and letting an algorithm choose the suite of<br />
decisions to achieve this goal (see Irisson et al. 117 for an example of the<br />
use of stochastic dynamic programming to solve such an optimisation<br />
problem).<br />
In both cases, orientation is a function which associates a swimming<br />
decision to the current state of a particle, such as<br />
f : state × time × environment → swimming(speed,direction)<br />
The amount of detail in the orientation behaviour is determined by<br />
what is incorporated in each of the left hand side variables. In the most<br />
simple model, when orientation is observed but the clues are unknown,<br />
orientation depends only on the position of larvae and on time. When<br />
responses to sensory clues are involved, the environment can include<br />
temperature, food, predators, current fields, land associated chemical<br />
concentrations, sun orientation, etc. If some kind of energy budget is<br />
present, the state of larvae can also encompass energetic reserves. This<br />
formalisation is therefore very scalable.