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166 Oceanography vs. behaviour<br />

the ocean at random) and such behaviour would be advantageous<br />

selectively. As a consequence self-recruitment and reduced dispersal<br />

should be high; and they are. Thus, long distance dispersal may only<br />

be regarded as a side effect of having a larval phase, rather than as a<br />

cause for it. Regarding our models, this means that swimming decisions<br />

maximising self-recruitment also make sense in a connectivity context.<br />

6.5.3 Model validation<br />

Distribution patterns<br />

agree with observations<br />

Vertical swimming<br />

found in real-world data<br />

Model predictions<br />

After justifying the hypotheses of optimal behaviour and focus on selfrecruitment<br />

a priori, we evaluate their performance when implemented<br />

in a model. As already noted, in the model, Pomacentridae are distributed<br />

closer to shore than the other species, which have pelagic eggs.<br />

This qualitatively agrees with observations near coral-reefs 168,259,293 . Similarly,<br />

fish larvae are observed to accumulate in the lee of emerged<br />

land 74,130,215,259 or at the edge of eddies 164 and these are also features of<br />

the model.<br />

Besides larval trajectories, that are the focus of all early life history<br />

models, our model also predicts behavioural strategies. One feature<br />

highlighted by the second model is that swimming downward, particularly<br />

in areas or intense surface flow, is an effective means of retention, or<br />

at least places larvae in environments where other behaviours make retention<br />

possible. This also agrees with the observations that ontogenetic<br />

downward migration increase retention 71,84 (see also chapter 5).<br />

Nevertheless, data allowing validation of such models is still very<br />

scarce and we have to resort to predictions about what should be<br />

observed. Because not all larvae behave optimally, young larvae are<br />

expected to be distributed differently from what the model predicts (all<br />

strategies would still be present at this stage, including non-optimal<br />

ones). The agreement between model and observations should progressively<br />

increase for older larvae, as mortality filters out the bad strategies.<br />

Yet, these models are more about processes than about the resulting<br />

patterns, so it would be more interesting to focus on decisions than on<br />

trajectories. Currently information regarding swimming decisions is virtually<br />

absent, except for the latest larval stages 25 . Hence the occurrence<br />

of early swimming, or its shoreward orientation in the island case for<br />

example (Figure 6.17), cannot be checked. New observational devices<br />

should prove useful in that respect (chapter 2).<br />

6.5.4 Consequences of larval behaviour on connectivity<br />

Events early in larval life<br />

determine retention<br />

Models help to get a mechanical understanding of processes. Here, the<br />

processes that increase self-recruitment can be identified and their consequences<br />

in terms of population connectivity, inferred. First, mortality<br />

by predation early in larval life seems key in determining the magnitude<br />

of self-recruitment, in particular in environments where resources are<br />

very concentrated near shore. In addition, early swimming is the most

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