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30 Behaviour in models 1.3 Vertical position 1.3.1 Potential influences Vertical heterogeneity in physical variables The unknown effect of boundary layers Any vertical heterogeneity in the current field will interact with the vertical distribution of larvae to indirectly influence their dispersal, as demonstrated by modelling 69,70 and empirical 71 studies. And of course, many things in addition to current velocity vary vertically in the ocean (temperature, light, food concentrations, etc.). Temperature influences pelagic phase duration 72 , development rates 73 , and swimming speed 25 . Food resources are often greater near the thermocline and fish larvae may accumulate at these depths 74–76 . Conversely, they might use diel vertical migration to avoid predation near the surface 77 . Larvae may use sun angle or sound for orientation, so the vertical position of a larva relative to the surface (sun angle detection) or the thermocline (hearing) may influence its ability to detect these cues and orient. Overall, the vertical position of larvae can therefore influence their feeding success, predation risk, growth, swimming ability, and ability to detect sensory cues, all of which can influence their trajectories 78 . Of all behaviours, vertical positionning is the most widely recognised as being influential and the one most often incorporated into biophysical models. Furthermore, in coastal waters, larvae may occupy the epibenthic boundary layer, where current velocity can differ substantially from that in the water column. Unfortunately, information on the occurrence of fish larvae in such epibenthic locations is limited because it is very hard to sample, especially in deep water or where the bottom is very irregular or hard. Occupancy of the boundary layer not only places the larvae in a different current regime, but it may also shift their food regime and expose them to increased risk of predation from benthic predators. Given the important effect boundary layers potentially have, further investigation is suited. 1.3.2 When to include this behaviour? Vertical behaviour should always be included Current velocity, hydrography (e.g. salinity, temperature), and fluorometry profiles (or their modelled equivalents) over the spatial scale and depth range where larval fishes occur are required in order to evaluate the degree of vertical shear in the current, the temperature gradient, and the depth of chlorophyll maximum. Clearly, if substantial heterogeneity in the velocity field is detected, vertical distribution of larvae must be included in a model. Some models integrate water movement over the surface Ekman Layer, while, in this layer, water velocity often differs with depth. This means that larvae at different depths within the Ekman Layer will be subject to different current speeds and directions, and the model should reflect this and avoid averaging over depth. If some modelled features (such as survival or growth) explicitly depend on food availability or temperature and these are not homogeneous on the
Vertical position 31 depth range of interest, vertical position must be included. Finally, if sensory cues are known to be used by larvae for orientation and are also affected by the vertical structure of the water column, this structure must be included. 1.3.3 Simple modelling tests When a 3D oceanographic model is available, the influence of vertical migration can be assessed by comparing the fate of particles constrained to the top and bottom layers within the species’ depth range. When 3D oceanographic models are computationally unfeasible, then 2D models are often employed. If the model simulates horizontal (e.g. cross shelf) and vertical (e.g. depth) dimensions, then the influence of vertical position could be tested in a manner similar to that used for 3D models. If the model dimensions do not include the vertical, then there is no simple test for the potential influence of vertical migration in the model. If a strong vertical current shear is observed in the field and larvae are observed to migrate through it, then the use of a 3D model is recommended. 1.3.4 How to get the relevant data? Vertical distribution is probably the behaviour about which we have the most information. It has been explored primarily with towed nets, performing stratified sampling of the water column. This requires multisample nets, preferably the Multi Opening and Closing Net and Environmental Sampling System (MOCNESS), or repeated single-net (e.g. Bongo net) sampling of the same area at different depths. To resolve diel vertical migration, a few stations should be sampled over several 24-h cycles. Similar information can be obtained from pump samples, but pumps suffer from significant avoidance, particularly when sampling larger larval stages. Acoustic methods can also provide useful information on vertical distribution, but suffer from difficulties in actually identifying the species whose vertical distribution they portray. Finally, in situ observations of larvae by divers 67 can provide detailed information on vertical distribution and changes therein by individual larvae that are caught, typically with light traps, and subsequently released. This approach can only be used in the day time, for larvae > 5 mm, and is limited by diver safety considerations to relatively shallow depths. Stratified sampling provides the concentrations of larvae caught within specific depth intervals. This information can be summarised using statistical descriptors such as the depth centre of mass of the larval patch, its variance, the total depth range in which larvae are caught. An alternative to a depth centre of mass portrayal of vertical distribution is the computation of a depth-frequency distribution. Depth bins, usually determined by the vertical resolution of the sampling design, are established and the mean percentage (and associated variance) Stratified sampling and direct observation . . .
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Page 6 and 7: vi Résumé La plupart des organism
Page 8 and 9: viii Abstract Most demersal marine
Page 10 and 11: x Table des matières 1.3.3 Simple
Page 12 and 13: xii Table des matières 6.2.3 Examp
Page 14 and 15: xiv Liste des figures 4.6 Distribut
Page 17: Liste des tableaux 1.1 Potential or
Page 20 and 21: 2 Introduction La survie des larves
Page 22 and 23: 4 Introduction Limitation par le re
Page 24 and 25: 6 Introduction Les courants déterm
Page 26 and 27: 8 Introduction où m est le taux de
Page 28 and 29: 10 Introduction biologique simple.
Page 30 and 31: 12 Introduction Le milieu lui-même
Page 32 and 33: 14 Introduction Figure I.6 Schémat
Page 34 and 35: 16 Introduction obstacles technique
Page 36 and 37: 18 Introduction Figure I.8 Prédict
Page 38 and 39: 20 Introduction I.5 La biologie des
Page 40 and 41: 22 Introduction du fonctionnement d
Page 42 and 43: 24 Introduction L’objectif de cet
Page 44 and 45: 26 Behaviour in models 1.1 Introduc
Page 46 and 47: 28 Behaviour in models Using mean p
Page 50 and 51: 32 Behaviour in models . . . bring
Page 52 and 53: 34 Behaviour in models of measured
Page 54 and 55: 36 Behaviour in models Additive dis
Page 56 and 57: 38 Behaviour in models In situ stud
Page 58 and 59: 40 Behaviour in models Operational
Page 60 and 61: 42 Behaviour in models Effects on p
Page 62 and 63: 44 Behaviour in models begins is no
Page 64 and 65: 46 Behaviour in models 1.10 Conclus
Page 66 and 67: 48 Larvae orientation in situ Diver
Page 68 and 69: 50 Larvae orientation in situ . . .
Page 70 and 71: 52 Larvae orientation in situ optio
Page 72 and 73: 54 Larvae orientation in situ if >
Page 74 and 75: 56 Larvae orientation in situ Table
Page 76 and 77: 58 Larvae orientation in situ that
Page 78 and 79: 60 Larvae orientation in situ 2.A A
Page 80 and 81: 62 Behaviour of settling fishes at
Page 87 and 88: Chapter 4 Biophysical correlates in
Page 89 and 90: Methods 71 4.2 Methods 4.2.1 Sampli
Page 91 and 92: Methods 73 Three rotations were com
Page 93 and 94: Methods 75 test really focuses on w
Page 95 and 96: Results 77 Figure 4.3 Mean of insta
Page 97 and 98: Results 79 Figure 4.5 Perspective v
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Results 81 Table 4.1 Abundances of
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Results 83 Figure 4.8 Distribution
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Results 85 Figure 4.10 Concentratio
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Discussion 87 Figure 4.11 Compariso
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Discussion 89 But the most likely e
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Acknowledgements 91 This evidence a
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Chapter 5 Ontogenetic vertical “m
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The statistical analysis of vertica
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Methods 101 80, 55, 30 m (Figure 4.
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Methods 103 same station were likel
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Results 105 Figure 5.2 Univariate r
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Results 107 5.4.3 Ontogenetic shift
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Results 109 Figure 5.5 Violin plot
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Discussion 111 5.5 Discussion 5.5.1
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Discussion 113 expression of differ
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Chapter 6 Oceanography vs. behaviou
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Introduction 117 a good description
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A general modelling framework for l
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The balance between feeding and pre
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Oriented swimming and passive advec
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General discussion 161 such integra
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General discussion 163 6.5.2 Why se
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General discussion 165 such as the
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General discussion 167 energeticall
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Acknowledgements 169 Therefore: •
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172 Conclusion Un environnement pé
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174 Conclusion global sur la connec
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176 Conclusion l’intérêt est po
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178 Conclusion La différence entre
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180 Conclusion Mieux décrire la di
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182 Conclusion Comme tout comportem
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184 Undescribed Chaetodonthidae Fig
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186 Undescribed Chaetodonthidae Fig
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188 Bibliographie [12] Cushing DH.
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190 Bibliographie [39] Johnson MW.
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192 Bibliographie [71] Paris CB, Co
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194 Bibliographie [99] Lara MR. Mor
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196 Bibliographie [127] Masuda R, S
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198 Bibliographie [157] Holbrook SJ
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200 Bibliographie [187] Bowen B, Ba
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202 Bibliographie [218] Oxenford HA
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204 Bibliographie [246] Wellington
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206 Bibliographie [276] Sargent RC,
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208 Bibliographie [308] Greenberg D
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210 Remerciements solides pour ces
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212 Remerciements tri des larves de
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214 Remerciements Évidemment, tout
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