Rémy Cuisinier
email: remy.cuisinier@imag.fr

Isabelle Olivier

Jocelyne Troccaz

Nicolas Vuillerme

Vincent Nougier

Is there a differential effect as a function of transition trials?

Keywords: Auditory biofeedback, proprioception, isometric force, sense of effort, short term memory processes

Introduction

It is well established that force production can be controlled by two different mechanisms. The first one is provided by the feedforward command of the central nervous system generally called sense of effort [START_REF] Mccloskey | Estimation of weights and tensions and apparent involvement of sense of effort[END_REF][START_REF] Gandevia | Kinesthesia: Roles for afferent signals and motor commands[END_REF][START_REF] Proske | Force matching errors following eccentric exercise[END_REF]. The second one is provided by feedback signals from ascending sensory information and called sense of force [START_REF] Simon | Lower limb force production and bilateral force asymmetries are based on sense of effort[END_REF]. Golgi tendons organs and cutaneous receptors can provide such information to gauge sense of force.

In some cases, the use of tools does not allow to provide good proprioceptive and haptic feedbacks. For example, currently available laparoscopic tool in minimally invasive surgery is unable to provide such information to control force production in robot-assisted surgical systems. Indeed, direct contact is replaced by long instruments between the tissue and fingers, resulting in reduced and distorted haptic (kinaesthetic and tactile) feedback [START_REF] Den Boer | Sensitivity of laparoscopic dissectors: What can you feel ?[END_REF][START_REF] Zahariev | Auditory contact cues improve performance when grasping augmented and virtual objects with a tool[END_REF]. This can modify surgeon's behavior, especially in the application of forces while interacting with the tissue.

To supply the lack of sensory information in using tools, another type of feedback seemed to be necessary. In this way, sensory substitution has been used to replace direct tactile or force feedback with other sensory modalities such as visual or auditory feedback to provide a better representation of force production. In tasks requiring a steady force, it is possible to introduce an auditory biofeedback to control force production by providing information when the force is lower or higher than required. This auditory rather than visual biofeedback could be useful because in specific tasks like surgical ones when a computer aided surgery takes place, visual information is often used to control tools trajectories.

Several studies have shown that sensory substitution feedback enhances movement ability and control [START_REF] Massimino | Improved force perception through sensory substitution[END_REF][START_REF] Kitawaga | Effect of sensory substitution on suture-manipulation forces for robotic surgical systems[END_REF]Zahariev andMackenzie, 2007, 2008). For example, Zahariev andMackenzie (2007, 2008) showed that movement time shortened using an auditory cue to grasp an object with different sizes. Using a protocol with visual feedback withdrawal after several seconds (i.e., in vision-Novision transition trials), several studies found that variability of the isometric force production decreased with visual withdrawal when normalized by target force or maximal voluntary contraction [START_REF] Tracy | Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles[END_REF][START_REF] Welsh | Variability of quadriceps femoris motor neuron discharge and muscle force in human aging[END_REF] or increased without normalization [START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF]Baweja et al., 2009).

These studies suggested that visual feedback contributes to increase force correction and thus force variability during an isometric force task. Moreover, these authors highlighted the presence of a drift of the isometric force over time which was dependent on force level after withdrawal of visual information. They excluded the effect of fatigue to explain this drift because they found it also for lower forces (5% MVC). Among these authors, results have also shown that the initiation of force decay started 1.5 -2.5 s following the removal of visual information [START_REF] Vaillancourt | Visual control of isometric force in Parkinson's desease[END_REF][START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF][START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF]. This time was too long to explain this force decay over time by the sensory reflex pathways. Indeed, studies have shown that changes in force output due to altered feedback conditions occur after 20-150 ms for proprioceptive feedback [START_REF] Marsden | Long-latency automatic responses to muscle stretch in man: origin and function[END_REF]. The decay over time better fit with the impact of short term memory processes. It could explain why the force decay occurred only after 1.5 -2.5 s following the removal of visual inputs. [START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF] agreed with the impact of short memory processes on force output and extended this effect to a bimanual isometric finger force task. This author proposed a visuomotor force control model which includes a leaky memory buffer to explain the exponential drift of force output when no error feedback was available. In line with this finding, [START_REF] Vaillancourt | Visual control of isometric force in Parkinson's desease[END_REF] found that this decay of force over time was faster in parkinson's disease and concluded that this effect was related to deficits in higher sensorymotor processes.

The effect of the short term memory processes on motor control has been also described by [START_REF] Miall | Evidence of a limited visuo-motor memory used in programming wrist movements[END_REF] by analyzing the position and amplitude of several wrist flexion and extension movements with and without vision as a function of pause interval between each trial. By plotting parameters of the first movement made after each pause against the pause interval, they obsverd a degradation of the accuracy related to the interval duration. Following a pause shorter than six seconds, the first movement was quite accurate. After 12 seconds, even the first movement was inaccurate in amplitude and in absolute position. Miall et al.'s result (1995) suggested that there is some form of internal visuo-motor memory supporting motor control and that the memory fades only after few seconds. In other words, the accuracy of reproduction of a required level of force without any biofeedback would be dependent on this memory effect after a short pause.

Therefore, the purpose of the present study was to investigate force accuracy and variability during constant isometric force production at different force levels in two types of transition trials. Biofeedback-Nobiofeedback transition trials were used to evaluate subjects' ability to regulate the isometric force while being exposed to abrupt changes in the availability of auditory information. Nobiofeedback-Biofeedback transition trials were used to evaluate subjects' ability to 1) reproduce the force required after a short period of time and 2) integrate a new auditory biofeedback to regulate their isometric force.

Methods

Participants 16 right-handed adults (age: 27 ± 6.1 years; body weight: 72.3 ± >8.2 kg; height: 178.1 ± 7.4 cm; mean ± SD) with no history of previous motor problems or neurological disease voluntarily participated in the experiment. They gave their informed consent to the experimental procedure as required by the Helsinki declaration (1964).

Procedures

The feet in a semi tandem position, participants stood in front of a force platform (AMTI ® , model OR6-5-1) which was vertically positioned at the elbow level. The right arm flexed to 90 deg, the fist closed, they were asked to produce and maintain a horizontally isometric force on the force platform with or without an auditory feedback. This auditory feedback was provided by two continuous buzzers (low-and high-pitched sound, Velleman models, sound frequency of 2.8 kHz and 4.5 kHz, respectively).When participants produced a lower force than required, the low-pitched sound was delivered whereas a high-pitched sound occurred when participants produced a higher force than required. Participants were asked to produce two different forces: 30 N ± 5 % and 90 N ± 5 %. In these intervals (± 5 %), no auditory feedback was provided indicating that participants produced the required force.

Before the experiment, participants heard the auditory biofeedback to identify the low and high-pitched sounds. Ten 25 s trials for each level of force were then performed. Two types of trials which corresponded to two different feedback transitions were presented alternatively in each block of 10 trials per force level. In uneven trials, participants produced and maintained the force with the auditory feedback during the first 15 s. For the later 10 s, no auditory feedback was provided whatever the force produced (trials with a BioFB-NoBioFB transition) but participants were instructed to maintain the force required. In even trials, participants had to produce and maintain the required force during the first 15 s without auditory feedback. For the later 10 s, participants could gain efficiency by using the auditory feedback to reach the required force (trials with a NoBioFB-BioFB transition) (cf. figure 1).

The rest time between two transition trials was 20 s. Participants reported no muscle fatigue during the protocol.

Data analysis

Force production was analyzed during two temporal frames of 8 s each: from 7 to 15 s and from 17 to 25 s called first and second temporal frames, respectively, in order to eliminate 1) the time necessary to produce and increase the force to reach the force target and 2) the time necessary to adjust the force in the NoBioFB-BioFB transition (i.e., from 15 to 17 s as observed in figure 1). Data forces were sampled at 100 Hz (12-bit A/D conversion). Data were low pass filtered with a second-order Butterworth (6 Hz). The cut-off frequency was fixed following a spectral and residual analysis [START_REF] Winter | Biomechanics and motor control of human movement[END_REF].

Four dependent variables were used to describe participants' isometric force production behavior: (1) the percentage of success of the isometric force production (i.e., the percentage of time over the two temporal frames of 8 s spent in the required force target 30 N ± 5 % or 90 N ± 5 %), (2) the percentage of constant error (CE) expressed as the constant error (mean produced force minus force target) divided by force target, 3) the slope of the linear regression of the isometric force calculated for each individual trial and each temporal frame (7-15 s and 17-25 s) to quantify the drift of the isometric force production within a given time interval [START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF][START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF][START_REF] Tracy | Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles[END_REF]. This drift was expressed in N.s -1 and normalized with respect to the mean force produced. The fourth dependent variable was the coefficient of variation (SD/mean). For each force target and each temporal frame, this variable was quantified after removing the linear trend due to the drift of the isometric force control. The drift was removed because it did not represent the force fluctuations of interest and would increase SD values. This SD was then normalized as a percentage of the mean force produced during each force and each BioFB condition. Note that the normalization with respect to the force target was not applied due to the presence of the drift.

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Statistical analysis

A previous analysis was done to test the existence of a learning effect. Five trials x 2 force targets (30 N ± 5 % vs. 90 N ± 5 %)  2 temporal frames (7-15 s vs. 17-25 s) analyses of variance (ANOVAs) were applied to the two transition trials (NoBioFB-BioFB and BioFB-NoBioFB transitions). Results did not show any effect of trials on the variables used. As a result, the five trials were averaged for each experimental condition and used for further statistical analyses. Three ANOVAs with repeated measures were used to answer different questions.

In order to check that participants were as accurate in the first and second temporal frames when using the auditory Biofeedback (i.e., from 7 to 15 s in the BioFB-NoBioFB transition trials vs. 17 to 25 s in the NoBioFB-BioFB transition trials), 2 force targets (30 N ± 5 % vs. 90 N ± 5 %)  2 temporal frames (7-15 s vs. 17-25 s) ANOVAs with repeated measures on all factors were applied to the data. The same analysis was done when the auditory biofeedback was not available in order to test the effect of a short pause to reproduce the required force. So, 2 force targets (30 N ± 5 % vs. 90 N ± 5 %)  2 temporal frames (7-15 s in the NoBioFB-BioFB transition trials vs. 17-25 s in the BioFB-NoBioFB transition trials) ANOVAs with repeated measures on all factors were applied to the data.

In order to investigate the effects of adding the auditory Biofeedback, 2 force targets (30 N ± 5 % or 90 N ± 5 %)  2 auditory feedbacks (NoBioFB vs. BioFB) ANOVAs with repeated measures on all factors were applied to the NoBioFB-BioFB transition trials (i.e., from 7 to 15 s vs. 17 to 25 s in the NoBioFB-BioFB transition trials). Finally, in order to investigate the effects of interrupting the auditory biofeedback on force control, 2 force targets (30 N ± 5 % or 90 N ± 5 %)  2 auditory feedbacks (BioFB vs. NoBioFB) ANOVAs with repeated measures on all factors were applied to the BioFB-NoBioFB transition trials (i.e., from 7 to 15 s vs. 17 to 25 s in the BioFB-NoBioFB transition trials).

Post hoc analyses (Newman-Keuls) were performed whenever necessary. The level of significance was set at 0.05.

Results

Force control when using the auditory biofeedback

Analysis of the percentage of success did not show any main effect of force target or temporal frame (F (1,15) = 0.39, p > 0.5 and F (1,15) = 2.90, p > 0.1, respectively) and no interaction of the two factors (F (1,15) = 0.86, p > 0.3). The percentage of success was about 70.95 % ± 1.76 (mean ± standard error) and was similar whatever the force target and temporal frame when using the auditory biofeedback.

Analysis of the percentage of constant error did not show any main effect of force target or temporal frame (F (1,15) = 4.16, p > 0.05 and F (1,15) = 2.12, p > 0.1, respectively) and no interaction of the two factors (F (1,15) = 1.58, p > 0.2). The percentage of constant error did not exceed 2.62 % ± 0.24.

Analysis of the coefficient of variation only showed a main effect of force target (F (1,15) = 5.07, p < 0.05). The coefficient of variation decreased from 30 N to 90 N (2.34 % ± 0.27 vs. 1.88 % ± 0.25, respectively).

Finally, the slope of the isometric force did not differ as a function of force target and temporal frame (F (1,15) = 0.11, p > 0.7 and F (1,15) = 1.99, p > 0.15, respectively). No interaction between the two factors was observed (F (1,15) = 0.36, p > 0.5).

Force control in the absence of auditory biofeedback

Analysis of the percentage of success showed a trend for the main effects of force target and temporal frame (F (1,15) = 4.26, p = 0.057 and F (1,15) = 4.53, p = 0.05, respectively) and a significant interaction of force target x temporal frame (F (1,15) = 8.64, p < 0.05). The decomposition of the interaction into its simple main effects showed that the percentage of success in 30 N was higher in the second (in the BioFB-NoBioFB transition trials) than in the first temporal frame (in the NoBioFB-BioFB transition trials). In other words, the percentage of success was higher when interrupting the auditory biofeedback than when initially producing the isometric force without biofeedback (44.23 % ± 5.15 vs. 23.26 % ± 4.35). Note that this percentage of success was also higher in the 30 N than in the 90 N force target condition whatever the temporal frame (44.23 % ± 5.15 vs. 28.79 % ± 2.84 and 25.49 % ± 5.52, respectively).

Analysis of the percentage of constant error showed a main effect of temporal frame (F (1,15) = 10.50, p < 0.005) and a significant interaction of temporal frame x force production (F (1,15) = 6.03, p < 0.05). The decomposition of this interaction into its simple main effects showed that the percentage of constant error did not vary in the 90 N force target condition (8.48 % ± 0.82 vs. 8.04 % ± 0.95) whereas this percentage was smaller in the second (in the BioFB-NoBioFB transition trials) than in the first temporal frame (in the NoBioFB-BioFB transition trials) in the 30 N force target condition (14.46 % ± 2.91 vs. 5.93 % ± 1.20, respectively). In other word, the percentage of constant error was smaller when the 30 N isometric force was maintained after the interruption of the auditory biofeedback than when initially producing the 30 N force without biofeedback.

Analysis of the coefficient of variation only showed a main effect of temporal frame (F (1,15) = 6.60, p < 0.05). This coefficient of variation was smaller when maintaining the force after the interruption of the auditory biofeedback than when starting to produce the required isometric force without biofeedback (2.09 % ± 0.19 vs. 1.67 % ± 0.20, respectively).

Finally, analysis of the slope of the isometric force did not show any main effect of force target (F (1,15) = 1.42, p > 0.25), temporal frame (F (1,15) = 0.38, p > 0.5) or interaction of the two factors (F (1,15) = 0.00, p > 0.90).

Force control when introducing the auditory biofeedback (NoBioFB-BioFB transition trials)

Analysis of the percentage of success only showed a main effect of biofeedback (F (1,15) = 571.76, p < 0.001). As observed in figure 2, participants were more successful with than without the auditory biofeedback whatever the force required (70.05 % ± 1.97 vs. 26.02 % ± 3.68, respectively).

Analysis of the percentage of constant error showed a main effect of biofeedback (F (1,15) = 47.18, p < 0.001) and a significant interaction of force target x biofeedback (F (1,15) = 4.62, p < 0.05). The decomposition of the interaction into its simple main effects showed that with the auditory biofeedback the percentage of constant error was similar whatever the force target (2.34 ± 0.25 % vs. 3.09 ± 0.27 % for 30 N and 90 N, respectively). Conversely, without biofeedback the percentage of constant error was higher for the 30 N than for the 90 N force target suggesting that force control was more difficult for lower levels of force (14.46 ± 2.91 % vs. 8.48 ± 0.83 %, respectively -figure 2).

The same analysis applied to the coefficient of variation did not showed any effect of the force target (F (1,15) = 0.59, p > 0.45), biofeedback (F(1,15) = 0.30, p > 0.50), and interaction of the two factors (F(1,15) = 0.95, p > 0.30). Note that the coefficient of variation was about 2.16 ± 0.25 %.

Analysis of the slope of the linear regression of the isometric force only revealed a significant main effect of biofeedback (F (1,15) = 17.87, p < 0.001). The decay of force over time disappeared when the auditory biofeedback was available, i.e., normalized from -0.56 ± 0.17 to .11 ± 0.05, respectively (figure 3B).

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Force control when interrupting the auditory biofeedback (BioFB-NoBioFB transition trials)

Analysis of the percentage of success showed main effects of force target (F (1,15) = 14.80, p < 0.005) and biofeedback (F (1,15) = 79.87, p < 0.001) and an interaction of force target x biofeedback (F (1,15) = 12.21, p < 0.005). The decomposition of the interaction into its simple main effects showed a decrease of the percentage of success with the interruption of the auditory biofeedback. This decrease was larger for the 90 N than for the 30 N force target (from 71.40 ± 1.49 % to 25.49 ± 5.52 % vs. from 71.77 ± 1.58 % to 44.23 ± 5.14 %, respectively, p<.005) (figure 2).

Analysis of the percentage of constant error only showed a main effect of biofeedback (F (1,15) = 34.61, p < 0.001). As illustrated in figure 2, this percentage increased when interrupting the auditory biofeedback (2.51 ± 0.21 vs. 6.99 ± 1.09 %, respectively).

Analysis of the coefficient of variation showed main effects of force target (F (1,15) = 9.34, p < 0.01) and biofeedback (F (1,15) = 9.42, p = 0.01). A decreasing variability was observed from 30 N to 90 N (2.07 % ± 0.22 vs. 1.60 % ± 0.15, respectively) and when interrupting the auditory biofeedback (2.00 % ± 0.21 vs. 1.67 % ± 0.16, respectively).

Analysis of the slope of the linear regression of the isometric force only revealed a significant main effect of biofeedback (F (1,15) = 18.40, p < 0.001). The decay of force over time appeared after interrupting the auditory biofeedback (normalized slope from -0.47 ± 0.15 to0.02 ± 0.06, respectively) (figure 3B).

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Discussion

Force accuracy, force decay and biofeedback transitions

The purpose of the present study was to investigate the transitional effects when using or interrupting an auditory biofeedback to control an isometric force production. To achieve this goal, two alternative trials were presented: Trials with a biofeedback-no biofeedback transition (BioFB-NoBioFB) and trials with a no biofeedback-biofeedback transition (NoBioFB-BioFB). The underlying principle of this auditory feedback was to deliver lowand high-pitched sounds when force production was lower or higher than required, respectively. In addition, two low and high levels of force (30 N and 90 N) were manipulated in order to investigate to which extent the effects of the biofeedback were dependent on the level of force production. Reinserting auditory information could lead participants to integrate auditory input with proprioceptive inputs, whereas the withdrawal of auditory biofeedback forced participants to reorganize sensory information because proprioceptive information became the only remaining source of information for regulating the isometric force. We hypothesized differences in regulating isometric force as a function of the transition trial.

Results showed that participants spent more time in the force target, i.e., better maintained the required force over time and reduced the constant error when using the auditory biofeedback than when it was absent, whatever the force required (30N ± 5% or 90N ± 5%). This was not surprising and corroborated previous results on the effects of a visual biofeedback to improve force control [START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF][START_REF] Gerovich | The Effect of Visual and Haptic Feedback on Computer-Assisted Needle Insertion[END_REF][START_REF] Wagner | The benefit of force feedback in surgery: examination of blunt dissection[END_REF][START_REF] Reiley | Effects of visual force feedback on robot-assisted surgical task performance[END_REF]. The present result extended this improvement to the use of an auditory biofeedback. It suggested that participants were able to integrate artificial force production information delivered through a two tones auditory biofeedback to produce and maintain a required level of force whatever the transition used.

When comparing the no biofeedback condition in the NoBioFB-BioFB versus BioFB-NoBioFB transition trials for the 30 N force, a lower percentage of success was observed because of a larger percentage of constant error. It seems that participants were less accurate to reproduce a lower 30 N force without any biofeedback as compared to a higher 90 N force production. This effect was also reported by [START_REF] Gandevia | Accuracy of weight estimation for weights lifted by proximal and distal muscles of the human upper limb[END_REF] in a force matching task (3 vs. 15 % of maximal isometric force for each muscle group) using proximal and distal muscles of the upper limb (first dorsal interosseous, flexor longus pollicis, biceps brachii). They showed a better accuracy using proximal than distal muscles and heavy than light weights. They excluded the impact of reflex inputs from muscles, joint and cutaneous receptors because the distal extremities (i.e., fingers) having the highest tactile acuity were not the most accurate for the matching weight task.

In summary, our results confirmed those reported by [START_REF] Gandevia | Accuracy of weight estimation for weights lifted by proximal and distal muscles of the human upper limb[END_REF] suggesting that 1) the recruitment of many motor units is not necessarily associated to an increased accuracy of force estimation and 2) with a progressive motor units recruitment as for a low force, the ability to grade muscular force does not remain constant. This unexpected findings need to be clarified with further experimentations. Furthermore, in conditions in which auditory biofeedback was withdrawn, output force steadily declined. Our results did not differ from previous studies in which this decay over time was compensated for by the visual biofeedback whatever the transition used. However, we found that a linear fit better fit with this decay over time than an exponential fit. This effect was probably due to the methodology presently used. We recorded only ten seconds of force production without feedback while the temporal frame used in previous studies was larger [START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF][START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF]. It is clear however, that time force production cannot decline below a given level of force production. In other words, our temporal frame was not large enough to report the exponential decay of force production.

To explain this drift, [START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF] proposed that visuomotor force control includes a leaky memory buffer. Using another sensory input to provide the biofeedback, the present results extended the integration of this leaky memory buffer to another sensory motor control and confirmed that this buffer is a central resource [START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF]. Moreover, when normalizing the slope decay by the force output, we observed that this decay did not differ as a function of force output and temporal frame (8-15 s or 17-25 s). Put together, these results suggested that the degradation of information about force output provided by this leaky memory buffer was mainly dependent on the sense of effort. This finding was in line with previous results showing that the decay of force over time was more pronounced in deafferented patients [START_REF] Lafargue | Production and perception of grip force whitout proprioception: is there a sense of effort in deafferented subjects[END_REF]) and parkinson's disease [START_REF] Vaillancourt | Visual control of isometric force in Parkinson's desease[END_REF] than in control subjects. However, because this drift remained constant whatever the transition used, this memory buffer seemed to be rather independent of short term memory processes. More generally, the key questions probably regard (1) and ( 2) the delay of efficiency of the short-term memory processes.

Force variability and biofeedback transitions

We observed the same effect of force fluctuation with an audio-as with a visuo-motor correction of the isometric force task [START_REF] Vaillancourt | Visual control of isometric force in Parkinson's desease[END_REF][START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF][START_REF] Davis | Memory and coordination in bimanual isometric finger force production[END_REF]. This was true even though visual afferent information was available during the entire force production task in previous studies, allowing continuous adjustments, whereas in the present study, auditory afferent information was provided only when the produced force was out of the force target. This general result may be due to the target used (± 5%) which was not large enough to reduce the variability, i.e., the number of adjustments required to remain in the target.

For example, several authors have found a non linear relationship between the gain of the visual feedback and force variability. More precisely, it has been shown that an inverted U shaped curve took place between these two parameters. Increasing the gain up to a given threshold enhanced the motor performance but increasing the gain beyond this threshold could lead to performance deficits [START_REF] Sosnoff | Independence between the amount and structure of variability at low force levels[END_REF][START_REF] Hong | Visual information gain and the regulation of constant force levels[END_REF]. However, this hypothesis is contradictory with recent results suggesting the absence of a U-shape function between gain and force (Baweja et al., 2009;[START_REF] Prodoehl | Effects of visual gain on force control at the elbow and ankle[END_REF]. Four factors, at least, could explain the discrepancy observed in the literature: (1) The type of feedback used (visual or auditory), (2) the intensity of the required force output which varied across experiments, (3) the type of movement required for producing the force output, and (4) the presence or absence of a bandwidth target which may weaken the gain effects and the Ushaped finding.

Previous studies comparing force variability with and without visual feedback during constant isometric tasks exhibited some contradictory results. Studies which involved the use of fingers, and thus primarily small hand and forearm muscles, suggested that the removal of visual feedback does not influence force variability [START_REF] Vaillancourt | Temporal capacity of short term visuomotor memory in continuous force production[END_REF]. Other studies which involved primarily larger muscles (Dorsiflexion or plantarfexion of the foot, quadriceps femoris) suggested that the removal of visual feedback decreases force variability [START_REF] Tracy | Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles[END_REF][START_REF] Welsh | Variability of quadriceps femoris motor neuron discharge and muscle force in human aging[END_REF]. However, using index finger abduction, Baweja et al. (2009) found an increasing variability with the use of the visual biofeedback and so, rejected the effect of muscles size to explain this difference.

In the present study, the presence of the auditory biofeedback was manipulated in two types of transition trials. In the BioFB-NoBioFB transition trials, we observed a decreasing variability of force output with the removal of the auditory biofeedback (from 2.07 % to 1.60 %), whereas in the NoBioFB-BioFB transition trials, the variability did not differ with the appearance of the biofeedback (about 2.16 %). In other words, the variability of the motor command only decreased with the removal of the auditory biofeedback. Two hypotheses could explain this result.

Following the first hypothesis, the decreasing variability illustrated the removal effect of the auditory biofeedback. Removing this feedback forced the subjects to reorganize sensory information because proprioceptive information became the only remaining source of information for regulating the isometric force. The decreasing variability observed in the BioFB-NoBioFB transition trials could result from the decreasing number of sensory sources of information to control the isometric force, each sensory input producing some variability.

Comparison of this variability to the one observed in the NoBioFB-BioFB transition trials forced to reject this hypothesis. Indeed, if this hypothesis was true, the same variability would be observed when the task began by the no biofeedback condition contrary to what was observed.

The second hypothesis thus suggested that this effect was task-specific: Starting with the biofeedback immediately gave a target reference. To be successful, subjects could adjust their motor command only by decreasing the variability of force output. In other words, the withdrawal of the auditory biofeedback forced the subjects to adapt their motor planning with the only remaining source of information for regulating the isometric force. In the NoBioFB-BioFB transition trials, the task was first to reproduce the isometric force output based on the proprioceptive information, only. Inserting the auditory feedback could lead subjects to integrate auditory inputs with proprioceptive ones in order to adjust the gain necessary to reach the target force. Further experiment would be necessary to validate this explanation.

To conclude, isometric force control differed as a function of biofeedback transition.

Interrupting a biofeedback forced the subjects to adapt their motor control with the only remaining source of sensory inputs whereas reproducing the required force and integrating a biofeedback during the force production only modified the gain of force. It is interesting to note that the decay over time did not differ as a function of the temporal frame used suggesting that the effect of short term memory processes was independent of those implied to reproduce a required force.

Legends

Figure 1 .

 1 Figure 1. Illustration for one subject of the average of five NoBioFB-BioFB transition trials (i.e., NoBioFB with the first temporal frame from 7 to 15 s and BioFB with the second temporal frame from 17 to 25 s) for a 90 N force target. In the BioFB-NoBioFB transition trials, BioFB was presented during the first 15 s and NoBioFB from 15 to 25 s.

Figure 2 .

 2 Figure 2. Mean and standard error of A) the percentage of success and B) the constant error of the force production produced in the two temporal frames of analysis (7-15 s and 17-25 s) without and with auditory feedback (NoBioFB and BioFB, respectively), as a function of force target 30 N (white bars) and 90 N (black bars).

Figure 3 .

 3 Figure 3. A) Example for one subject of the average of five NoBioFB-BioFB transition trials for the 90 N force target in which a drift of force over time was present in the NoBioFB condition and B) Mean and standard deviation of the slope of the linear regression of the isometric force in the NoBioFB-BioFB transition trials and BioFB-NoBioFB transition trials. The 30 N force target is represented with white bars whereas the 90 N force target is in black bars.

  Figure1

Acknowledgements

This project was supported by a public grant from the French research agency, through the TELEOS program (ANR-06-BLAN-0243).


D Nicolas

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Functional diversity in European estuaries: relating the composition of fish assemblages to the abiotic environment

Keywords: Functional diversity, fish assemblage, Europe, tidal estuaries, habitat, glm

Based on a large standardised dataset, the present study proposed a meta-analysis to describe general patterns in the functional diversity of estuarine fish assemblage in terms of both number of species and density along the European Atlantic coast. Fish species collected from 31 European estuaries from Portugal to Scotland were allocated to functional groups according to their ecological utilization of estuaries. A clustering analysis was performed to compare the overall functional structure of estuaries based on fish composition. Generalised linear models were computed to identify relationships between large-scale abiotic and intraestuarine descriptors and functional attributes of estuarine fish assemblages. The total number of species, and more especially of marine species, was higher in larger estuaries with a wide entrance and, locally, in polyhaline waters. The total density was mainly related to the proportion of intertidal mudflats and, locally, was greater in mesohaline waters. In terms of relative density, northern systems were dominated by marine and catadromous species, while estuarine species were prevalent in the southern ones.

Introduction

Estuaries constitute essential habitats for many fish species to complete their life cycle. While it is recognised that both diadromous and estuarine resident fish species truly depend on estuaries [START_REF] Ray | Connectivities of estuarine fishes to the coastal realm[END_REF], most species originating from the marine environment [START_REF] Mclusky | The Estuarine Ecosystem -ecology, threats and management[END_REF] exploit these areas in a more opportunistic manner [START_REF] Lenanton | Contribution of estuaries to commercial fisheries in temperate Western Australia and the concept of estuarine dependence[END_REF].

Estuaries act temporarily as nursery and feeding areas, especially for marine juveniles, offering a highly nutrient rich environment and shallow turbid refuges suitable to their development [START_REF] Blaber | Factors affecting the distribution of juvenile estuarine and inshore fish[END_REF][START_REF] Potter | Comparisons between the roles played by estuaries in the life cycles of fishes in temperate Western Australia and Southern Africa[END_REF]. Man uses estuarine goods and services intensively, enhancing trophic resource depletion and habitat degradation, e.g. through fishing, embankments and organic and metal contaminations (Le [START_REF] Pape | Convergent signs of degradation in both the capacity and the quality of an essential fish habitat: State of the Seine estuary (France) flatfish nurseries[END_REF][START_REF] Dauvin | The main characteristics, problems, and prospects for Western European coastal seas[END_REF]. As estuarine environments are naturally characterised by enrichment in organic matter and high variability of abiotic conditions, anthropogenic stresses are difficult to distinguish from natural ones [START_REF] Elliott | The Estuarine Quality Paradox, Environmental Homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas[END_REF]. The sustainability of estuarine ecosystem functions relies on a good understanding of ecological processes and the choice of adequate and efficient management measures. Fish species present a wide diversity of biological cycles and ecological compartments, making them relevant integrated indicators to reflect estuarine conditions at multiple spatial and temporal scales [START_REF] Whitfield | Fishes as indicators of environmental and ecological changes within estuaries: a review of progress and some suggestions for the future[END_REF]. Their life strategies related to their ecological use of estuarine habitats supposedly reflect the functioning of estuaries (Elliott et al., 2007). Relating the functional diversity in fish assemblages to the natural abiotic variability would constitute a starting point for better identifying estuarine fish assemblage reference conditions, to analyse subsequently the human-induced impacts and to assess the ecological status of estuarine ecosystems [START_REF] Coates | Efficacy of a multi-metric fish index as an analysis tool for the transitional fish component of the Water Framework Directive[END_REF][START_REF] Courrat | Anthropogenic disturbance on nursery function of estuarine areas for marine species[END_REF]Delpech et al., in press).

Functional attributes have been widely used to describe estuarine fish assemblages (e.g. [START_REF] Claridge | Seasonal changes in movements, abundance, size composition and diversity of the fish fauna of the Severn estuary[END_REF][START_REF] Potter | Comparisons between the roles played by estuaries in the life cycles of fishes in temperate Western Australia and Southern Africa[END_REF][START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF]Elliott et al., 2007;[START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF]. In such a classification, fish species that have similar features in resource exploitation are assigned to the same functional group [START_REF] Blondel | Guilds or functional groups: Does it matter?[END_REF]. This functional approach allows to reduce the complexity of fish assemblages and to focus on the use made by fish of estuarine environments and, thus, on the ecological functions of estuaries [START_REF] Garrison | Dietary guild structure of the fish community in the Northeast United States continental shelf ecosystem[END_REF]. In addition, categorization based on functionality rather than taxonomic attributes, allows the comparison of fish assemblages belonging to different biogeographical areas (Elliott et al., 2007). In the present study, functional groups related to fish ecological use of estuaries and reflecting salinity preference and migration behaviour (Elliott et al., 2007;[START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF] were used to analyse the functional diversity of fish assemblages in 31 European tidal estuaries. From the ichtyofauna analysis of 17 European estuaries of the eastern Atlantic seaboard, [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF] concluded that estuarine fish assemblages typically consist of "a majority equally of estuarine resident, marine adventitious and marine juveniles (25% each), with a small number of marine seasonal migrant, diadromous and freshwater adventitious species". Based on readjusted estuarine use categories, [START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF] found a similar pattern for 38 estuaries from the Mediterranean to the Baltic regions. On the contrary, [START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF] used a homogenous fish data set that allowed a quantitative analysis of 15 Atlantic French estuaries and found that estuarine (54%) and marine migrant (33%) fish dominated assemblages in autumn in terms of relative number of individuals. Based on a larger standardised data set, the aim of the present paper was to check whether estuarine fish assemblages along the European Atlantic coast fit with a functional pattern both in terms of number of species and fish density per guild of estuarine use. The second objective was to identify the degree of variation in the functional composition of fish communities in relation to large-scale abiotic descriptors of the estuarine environment and to salinity gradients. In particular, the following questions are addressed: Do larger estuaries shelter a higher species diversity (number of species and/or fish densities per functional group) compared to smaller estuaries? Do species richness and density patterns according to salinity estuarine zones are similar for different systems?

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

Materials and Methods

Acquisition and analyses of abiotic data

A total number of 31 European tidal estuaries from Portugal to Scotland (Fig. 1) were described by large scale abiotic descriptors using an ecohydrology approach [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Estuaries were characterised by several types of descriptors (Table 1): latitude; five continuous geomorphological quantitative variables (watershed area, estuarine water area, estuary mouth width and depth and continental shelf width); three geomorphological class factors (intertidal area type, main nature of littoral substrate and wave exposure), and two hydrological continuous variables (tidal range and mean annual river discharge).

A normed principal component analysis (PCA) combined with a hierarchical clustering procedure was performed on all of these abiotic descriptors [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Annual river discharge, watershed area and estuary area were log-transformed to lessen the influence of the few higher values on the many lower ones. The aim of this analysis was to highlight groups of estuaries with similar physical characteristics and select synthetic and uncorrelated variable(s) to describe fish communities.

Fish data

Collection, classification and selection of fish data

As specified by [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF], a large fish data set based on sampling surveys in the scope of the European Water Framework Directive (WFD, European Council Directive, 2000) was stored in a database. The present study only focuses on beam trawl surveys (i.e. 1 estuary × 1 year × 1 season) carried out in spring and autumn between 2005 and 2007, during which salinity was measured and a total area of at least 2500m² [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF] was sampled. A total of 878 trawls from 48 surveys were selected. These samples were categorised into three salinity classes (SC): oligohaline (salinity <5), mesohaline (salinity Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 between 5 and 18) and polyhaline (salinity >18), as simplified from the Venice classification system [START_REF] Courrat | Anthropogenic disturbance on nursery function of estuarine areas for marine species[END_REF].

Each caught fish was identified at species level. In Spanish Basque systems, Gobiidae species from Pomatoschistus genera were not determined and could correspond to different species.

To counteract this bias, all Pomatoschistus were considered to represent one unique estuarine resident species. Each of the other species was assigned to a category related to their estuarine use. Elliott et al. (2007) emphasized the need for a standardisation of functional typologies and proposed an estuarine use functional group that may be applied to any parts of the world.

Our functional classification corresponded to the one adapted by [START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF] from Elliott et al. (2007) to the European estuarine waters. The different categories were: estuarine species (ES); marine migrants (MM); marine stragglers (MS); anadromous species (AN); catadromous species (CA) and freshwater species (FS). The allocation of a species to one specific category was based on both previously mentionned sources and local expert knowledge (Table 2). Some allocations were not straightforward, especially for the European flounder Platichthys flesus and the thinlip grey mullet Liza ramada. While P. flesus was classified either as catadromous [START_REF] Lobry | Structure of the Gironde estuarine fish assemblages: a European estuaries comparison perspective[END_REF][START_REF] Kottelat | Handbook of European freshwater fishes. Kottelat, Cornol, Switzerland and Freyhof[END_REF], marine migrant [START_REF] Thiel | Composition, temporal changes and ecological guild classification of the ichthyofaunas of large European estuaries -A comparison between the Tagus (Portugal) and the Elbe (Germany)[END_REF][START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF] or estuarine resident [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF][START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF], L. ramada was either catadromous [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF][START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF][START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF] or marine migrant [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF].

These species can spend a long lifetime within estuaries [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF]Elliott et al., 2007). However, since they were observed to spawn at sea and to be able to enter freshwater [START_REF] Kottelat | Handbook of European freshwater fishes. Kottelat, Cornol, Switzerland and Freyhof[END_REF], they were grouped in the catadromous category together with the European eel Anguilla anguilla [START_REF] Tsukamoto | Migration, speciation and the evolution of diadromy in anguillid eels[END_REF].

Calculation of fish assemblage descriptors

Abundances were divided by the corresponding trawl sampled surface. These resulting densities of individuals (ind. 1000 m -²) were summed per functional group and per trawl sample then, taking into account their underlying lognormal distribution, log-transformed to reduce the influence of exceptionally high densities. These log-transformed densities ln(Dens+1) per functional group were averaged per survey then per estuary (pool of seasons and years) to compare the overall functional structure among estuaries. In a second approach analysing intra-estuarine processes, these indices were averaged at the salinity class scale (three classes per survey quite systematically, per season and estuary). Similarly, the total number of species (SR for species richness) was calculated per functional group and per survey and the same operation was carried out at the scale of the salinity class. Next, the number of species was divided by the log-transformed total sampled surface (m²) carried out during a survey (S) or per salinity class (S sc ) to standardise species richness in relation to sampling effort [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Consequently, indices based on species richness were referred to as SR/ln(S) or SR/ln(S sc ). To compare standardised values of species richness between estuaries, the number of species is expressed for a theoretical 1000m² trawl haul.

Clustering analyses of estuaries based on fish assemblage descriptors

Analyses were carried out in terms of both number of species and density of individuals per functional group per estuary (pool of seasons and years). Groups of estuaries displaying similar functional composition were highlighted through a hierarchical clustering analysis using the Ward agglomerative method based on square-root-transformed Bray-Curtis similarity matrices [START_REF] Faith | Compositional dissimilarity as a robust measure of ecological distance[END_REF][START_REF] Legendre | Distance-based redundancy analysis: Testing multispecies responses in multifactorial ecological experiments[END_REF]. The groups and distances to centroids were plotted on the first axes of a principal coordinate analysis (PCoA), using the function betadisper [vegan] on the R software (R Development Core Team, 2005).

For each identified cluster of estuaries, the relative functional composition in density and species richness were analysed.

Statistical analyses of the link between abiotic descriptors and fish functional groups

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

Patterns in the standardized estimates of species richness and fish densities, globally and per functional group, averaged per season and estuary then per salinity class, were analysed to identify the degree of variation in the functional composition of a fish assemblage related to large-scale abiotic descriptors of the estuarine environment and to salinity gradients. The identification of best explanatory descriptors was based on generalised linear models.

Preliminary graphic tests on data distribution showed that the Gaussian law was the most suitable to model both SR/ln(S sc ) and ln(Dens+1) indices. To reduce the presence of zerovalues while still keeping an ecological relevance, marine migrant and marine straggler species were pooled together as marine species (M) and catadromous and anadromous species as diadromous species (DIA, Table 1). Freshwater species, rarely present and in low densities, were not modelled.

Within models, we introduced factors related to the sampling procedure, when significant, in order to account for possible bias; these factors correspond to between-seasons and betweensalinity-types variability. The between-years effect was not considered because most estuaries were sampled in one year only. This is the reason why, when an estuary was sampled over two years, data were averaged per season then per salinity class. Thereafter, abiotic descriptors (X i ) were added to the models, so that the GLM could be written as follows:

Indices = Season + SC + X 1 …+ X i … + X n
The method used to select the best combination of abiotic descriptors was similar to [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Each preselected descriptor was first tested separately in models. To select the best explicative variables from among the significant ones, a stepwise procedure was used.

The best final combination of descriptors was determined according to analyses of variance (Chi-square test at 5% level), Akaike Information Criterion [START_REF] Sakamoto | Akaike Information Criterion Statistics[END_REF], ecological relevance and graphical analysis of residuals. The nature of the effect of the continuous explicative variables (i.e. positive or negative) on fish indices was identified from the sign of the corresponding coefficient(s). For the class factors, modalities were ordered Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 according to their corresponding coefficient and the difference between two adjoining modalities was checked with a student test (at 5% level).

Results

Abiotic contrasts among estuaries and preselection of potentially explanatory descriptors

The PCA plot based on abiotic data (60.2% of total inertia for the first two main components, Fig. 2) discriminated five distinct clusters of estuaries (hereafter referred as 'clusters').

Cluster A consisted of the smallest estuaries with a very narrow continental shelf, including the seven Spanish estuaries, the Goyen and Seudre (France), and the Mira (Portugal).

Localised within the English Channel, estuaries from cluster B were characterized by low depth at the river mouth, high proportion of intertidal area and a very wide continental shelf.

Cluster C pooled estuaries of intermediate size: three French estuaries in the Bay of Biscay and the two Scottish systems (the Forth and Tay). Cluster D consisted of the largest southern systems, characterized by mesotidal estuaries of moderate size associated with a huge watershed and a warm, dry climate. Last, the three widest French systems (cluster E) presented the highest river discharge.

The correlation circle (Fig. 2) highlighted the strong positive correlations between mean annual river discharge, watershed area and estuary area (0.68 < r < 0.92, p-value < 0.0001) and between estuary area and entrance width (r = 0.69, p-value < 0.0001). Mean annual river discharge, which reflected the overall system size, was selected for further tests of the effect of system size on fish assemblage attributes. Entrance width, which informed on the connectivity of the estuary with the marine environment, was used as an indicator of marine influence. Latitude, continental shelf width and tidal range were also positively correlated (0.61 < r < 0.76, p-value < 0.0001): continental shelf width and tidal range increased from the southern Portuguese coast towards the northern English Channel (Fig. 1

). Continental shelf

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 width was selected for further analyses of fish assemblages. The semi-quantitative intertidal class factor, which was negatively related to the entrance depth variable, (r = -0.4, p-value < 0.05), was the last selected descriptor. As most estuaries (58%) were well protected against waves, the wave exposure factor did not discriminate estuaries. Finally, the littoral substrate class factor was redundant with the continental shelf width effect.

Relative functional composition of estuarine fish assemblages

Over the entire study area, a total of 109 species from 42 different families were identified: among them 35% were marine straggler, 30% marine migrant, 15% freshwater, 12% estuarine, 5.5% anadromous and 3% catadromous species (Table 2).

Regarding the functional composition in terms of number of species, estuaries were categorised into three clusters (hereafter referred as 'groups', Fig. 3). Group I, which comprised most of the largest systems classed in clusters D and E (except the Douro estuary, Fig. 2), had the greatest number of species (with an average ± confidence interval of 13 ± 1 for a 1000m² trawl haul), while the group III, comprising five small systems from clusters A and B, had the lowest species diversity (SR = 5 ± 2 species). On average, estuarine fish assemblages in both groups I and II included all functional modalities and were largely dominated by marine species (i.e. MM and MS, on average 60.4% in relative proportion), and more particularly by marine migrant species (38.6 ± 2.4% of the total number of species). On the contrary, group III was characterised by the absence of species with a freshwater origin, i.e. anadromous and freshwater species, and was rather mainly occupied by estuarine species (60.6 ± 20%).

In terms of density, two groups were distinguished among the estuaries (Fig. 4). All functional attributes were represented in the estuaries of the first group, while in the second, species with a freshwater origin (FS and AN) were lacking. In group I (Fig. 4), individuals from marine migrant species and catadromous species were the major contributors to total Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 density with a relative proportion of 31.7 ± 3.7% and 21.7 ± 4.1%, respectively. By contrast, estuaries categorised in group II were largely dominated by the density of estuarine species (45.8 ± 9.5%). Group II consisted of ten of the smallest systems (clusters A and B, Fig. 2) and the three largest southernmost systems (cluster D).

Anadromous species were present in half of the studied estuaries and were best represented in terms of density in the northernmost Tay (24%) and Forth (32.2%) estuaries. Freshwater species were found in eleven French systems, where they were low both in number (on average SR = 1.4 ± 0.7 freshwater species per 1000m²) and in density of individuals (14.6 ± 5.4% of total catch).

Links between the functional composition of fish assemblage and the abiotic estuarine environment

Salinity class significantly influenced total species richness in estuaries (Table 3a). The polyhaline area displayed on average the highest total number of species (SR = 80 ± 11 for a 1000 m ² trawl haul) compared to the oligo-and mesohaline areas (50 ± 8 species). Contrary to marine and estuarine species, the diadromous species were more numerous in oligo-and mesohaline areas (SR = 14 ± 3 species) than in the salty downstream (10 ± 3 species, Table 3a). Most of the freshwater individuals (84%) were caught in the oligohaline area. The annual mean river discharge further explained the total number of species and the number of marine species with a positive effect (Table 3a). The three largest systems categorised in cluster E of Fig. 2 had a much higher total number of species (SR = 15 ± 3 species) than the small estuaries grouped in cluster A (6 ± 2 species). In addition, entrance width was positively related to the total number of species and to the number of diadromous species (Table 3a).

Fish density in the mesohaline area (64 ± 42 ind.1000m -2 ) was significantly higher, particularly for marine species, than in the oligohaline (36 ± 22) and polyhaline areas (22 ± 7, Table 3b). Density of diadromous fish was higher both in oligo-and mesohaline areas (16.5 ± Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 9.5 ind.1000m -2 ) than in polyhaline areas (3.7 ± 1.3 ind.1000m -2 , Table 3b). The relative intertidal area also explained a statistically significant part of variability in the total fish density and more especially the density of marine and estuarine species (Table 3b). Estuaries with the greatest proportion of intertidal mudflats (80-100% of total estuary area) had the highest densities (61 ± 31 ind.1000m -2 ), in particular with comparison to estuaries with less than 20% of intertidal mudflats (20 ± 15 ind.1000m -2 ). Entrance width had a further positive effect on the total density, the density of marine species and the density of diadromous species (Table 3b). Finally, continental shelf width also had a positive effect on diadromous species density (Table 3b), which was four times higher in the eastern Channel estuaries (25.7 ± 23.8 ind.1000m -2 ) than elsewhere (6.2 ± 2.2 ind.1000m -2 ).

Discussion

Prerequisites for a large-scale comparison of estuarine fish assemblages

A relevant and consistent comparison of estuarine fish assemblages on a large scale requires standardised fish data in relation to the type of fishing gear used, the sampling effort and the sampling period. Compared to the previous large scale qualitative analyses of European estuarine fish assemblages [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF][START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF], the present data set, based solely on beam trawl samples, was more homogenous. However, differences in the dimensions of the net, mesh size and weight exist between the beam trawls used for different surveys, according to the country and the size of estuaries [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Trawl samples could also differ due to haul duration and speed. Thus, this absence of a standardised sampling protocol within the WFD framework still enhances heterogeneity problems for statistical analyses and dampens accuracy of the analysis. Nonetheless, by applying a transformation to both species richness [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF] and abundance data based on the sampled surface, these differences were partly taken into account and our data were estimated Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 sufficiently standardised to compare fish assemblages in both qualitative and quantitative terms.

Latitudinal variability in fish reproduction and recruitment peaks together with seasonal patterns in migratory activities was expected to influence results [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF][START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF]. Nevertheless, among the 31 studied estuaries, the between-season variability was never found significant in the models. Pooling spring and autumn in the present comparative analyses appeared relevant and enabled us to consider a large data set, since only 42% of the estuaries were sampled at both seasons.

Regarding the functional description of fish species, such large-scale comparison requires clear definitions of the chosen functional groups and standardised allocations for each species (Elliott et al., 2007). Nonetheless, as detailed for P. flesus and L. ramada species in the Materials and Methods section, the allocation of some species to a specific functional group can differ greatly from an author to another. Moreover, because of local fish behavioural adaptations, [START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF] recommended the use of flexible allocations for one species to account for its associated geographical variability. For most of the identified fish species, especially when they are of no fisheries interest, further research on their biology is required at local level to allocate species to guilds according to region. As a consequence, these inconsistencies in functional attributions may have a marked influence on the results. For instance, [START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF], found for the three French Eastern English Channel Canche, Authie and Somme estuaries, a mean relative proportion of estuarine individuals of 43%. But, when allocating P. flesus as catadromous and not as estuarine species as done [START_REF] Selleslagh | Fish composition and assemblage structure in three Eastern English Channel macrotidal estuaries: A comparison with other French estuaries[END_REF], this proportion was reduced by 10%. Nevertheless, even if these problems of allocation generate uncertainty, general patterns can be inferred from the present study.

The functional diversity of European estuarine ichtyofauna: general patterns

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

Like the composition of fish assemblages found by [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF], the present estuarine fish assemblages were composed of a small number of diadromous and freshwater species and a majority of marine migrant, marine straggler and estuarine species. The large proportion of marine, and more precisely marine migrant species, and especially their juvenile stage, emphasised the great importance of estuaries as fish nursery grounds (e.g. [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF][START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF][START_REF] Laffaille | Composition of fish communities in a European macrotidal salt marsh (the Mont Saint-Michel Bay, France)[END_REF][START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF][START_REF] Courrat | Anthropogenic disturbance on nursery function of estuarine areas for marine species[END_REF] and their role in maintaining coastal stocks (Rochette et al., in press).

Nonetheless, contrary to Elliott and Dewailly's study (1995), these marine and estuarine species were not present in equal proportions in all estuaries. Although [START_REF] Elliott | The structure and components of European estuarine fish assemblages[END_REF] advanced 'common patterns of estuarine usage irrespective of the differences between the estuaries', the present analyses highlighted different patterns among estuaries in terms of both number of species and density. Large-scale abiotic gradients were shown to significantly influence the functional diversity of fish assemblages:

The effect of system size and entrance width on species richness

In terms of number of species, the clustering analysis emphasised that larger systems presented a higher functional diversity and a higher total number of species. This relationship between species richness and system size was confirmed by the GLM analyses and has already been reported in other worldwide studies [START_REF] Monaco | Assemblages of U.S. west coast estuaries based on the distribution of fishes[END_REF][START_REF] Pease | A spatially oriented analysis of estuaries and their associated commercial fisheries in New South Wales, Australia[END_REF][START_REF] Harrison | Estuarine typology and the structuring of fish communities in South Africa[END_REF][START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Nevertheless, while system size slightly influenced the number of marine species, it did not explain the number of estuarine or diadromous species. The increase in the total number of species according to the size of the estuarine system is often related to a diversity of habitats [START_REF] Monaco | Assemblages of U.S. west coast estuaries based on the distribution of fishes[END_REF][START_REF] Wootton | Ecology of teleost fishes[END_REF][START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. However, this hypothesis requires further tests to determine whether the heterogeneity of estuarine habitats influences the total number of species [START_REF] Pihl | Habitat use by fishes in estuaries and other brackish areas[END_REF].

Here, the width at the mouth further promoted total species richness, which tends to confirm that the enhancement of high-salinity habitats favoured the exploitation of the estuary by Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 more different species [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF]. Furthermore, the positive influence of entrance width on the density of marine species suggests that further seawater penetration raises the migration and concentration of some marine individuals into estuaries. The entrance width also promoted diadromous migrant species both in terms of number of species and of density, probably due to the attraction of diadromous species for large fluvial plumes [START_REF] Boehlert | Roles of behavioural and physical factors in larval and juvenile fish recruitment to estuarine nursery areas[END_REF][START_REF] Tosi | Relation of water odour, salinity and temperature to ascent of glass-eels, Anguilla anguilla (L.) : a laboratory study[END_REF][START_REF] Tosi | Role of geosmin, a typical inland water odor, in guiding glass eel Anguilla anguilla (L) migration[END_REF]. Nonetheless, as confirmed from the present analysis, the distribution of diadromous species, and more especially of anadromous species, are also related to biogeographical aspects, including homing and population decline [START_REF] Mcdowall | Diadromy in fishes -Migrations between freshwater and marine environments[END_REF].

The contrast between northern and southern estuaries in terms of density

In terms of relative density, the clustering analysis revealed that northern systems sheltered fish of all estuarine use categories and were dominated by marine and catadromous species (group I, Fig. 4), while southern systems were dominated by estuarine species (group II, Fig. 4). The GLM analyses also revealed higher densities of diadromous species in northern estuaries and more particularly in the eastern English Channel compared to southern systems. However, these analyses did not demonstrate a latitudinal contrast in the density of estuarine species. Models showed that estuaries in the English Channel, which generally display a high percentage of intertidal area, exhibited among the highest densities in both marine and estuarine species. Thus, although southern estuaries were dominated by estuarine species, the density of these species appeared nonetheless higher in northern English Channel systems. [START_REF] Claridge | Seasonal changes in movements, abundance, size composition and diversity of the fish fauna of the Severn estuary[END_REF] found that estuarine species represented only 0.6% of the total catch in the inner Severn estuary. [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF] presumed the situation was similar in all macrotidal holarctic estuaries and explained this low representation of estuarine species as a result of their strong hydrodynamics that prevent the eggs and larvae being able to remain inside the estuary. However, the present dataset showed that even in the widest megatidal Loire and Seine estuaries, estuarine species were well represented, with 11 and 14.5%

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 respectively of the total catch, moreover for high total densities in these systems. Moreover, southern systems (group II, Fig. 4) were clearly dominated by estuarine species which represented on average 45% of total species richness (from 31% in the Mira estuary to 100% in the Urumea estuary). In contrast to the northern systems, these southern systems were characterised by a reduced freshwater influence due to a warmer and drier climate and by small tidal exchanges. This higher hydrological steadiness associated with high salinity values appears to provide a more favourable environment for the recruitment of resident species [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF]. This may explain the high representation of estuarine individuals in southern estuaries and the low number of species with freshwater affinities, i.e. anadromous and freshwater species. Accordingly, comparing sampling surveys carried out in the Tejo estuary between 1979 and 2002, [START_REF] Costa | River flow influence on the fish community of the Tagus estuary (Portugal)[END_REF] showed that the density of estuarine species and marine species was higher in dry years than in wet ones. [START_REF] Martinho | The influence of an extreme drought event in the fish community of a southern Europe temperate estuary[END_REF] reported that a severe drought occurred between summer 2003 and June 2006 in Portugal and observed subsequently an increase in marine stragglers in the Mondego estuary.

Consequently, higher temperatures appeared to promote species with marine affinities (i.e. marine and estuarine species, [START_REF] Potter | Characteristics of the ichthyofaunas of southwestern Australian estuaries, including comparisons with holarctic estuaries and estuaries elsewhere in temperate Australia: A review[END_REF][START_REF] Costa | River flow influence on the fish community of the Tagus estuary (Portugal)[END_REF]. In future analyses, it would be interesting to test the effect of both water temperature and river discharges on a more simultaneous temporal scale.

The effect of intertidal area on density

The intertidal area type was the factor that accounted for the greatest deviance in total density, and more especially in density of marine and estuarine species. Elliott and Taylor (1989a;1989b) found in the Forth estuary that the biomass and the production of macrofauna per unit area were higher in the intertidal mud-flats than in the subtidal area. Most fish in estuaries have been shown to feed on benthic invertebrates [START_REF] De Sylva | Nektonic food webs in estuaries[END_REF]Elliott and Taylor, 1989b;[START_REF] Costa | Fish usage and feeding in two industrialised estuaries -the Tagus, Portugal, and the Forth, Scotland[END_REF]; the intertidal areas constitute the dominant feeding area for the Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 estuarine fish populations [START_REF] Costa | Fish usage and feeding in two industrialised estuaries -the Tagus, Portugal, and the Forth, Scotland[END_REF] and promote fish density. Both estuarine and marine species, and more particularly juveniles, preferred shallow systems with extensive intertidal mudflats, generally turbid, where they can find great food availability and reduced predation pressure [START_REF] Blaber | Factors affecting the distribution of juvenile estuarine and inshore fish[END_REF]. This also underlined the fact that small estuaries with a high proportion of intertidal flats could be as important as larger systems for their nursery function, displaying on average higher fish density per unit area (e.g. 44.9 ± 15.1 ind.1000 m-² in the Authie estuary vs 4.5 ± 1.2 ind.1000 m-² in the Gironde estuary). The loss of intertidal area through channelization or land reclamation in these estuaries might thus have a heavy impact on fish production, as demonstrated in the Forth [START_REF] Mclusky | The impact of land-claim on the invertebrates, fish and birds of the Forth estuary[END_REF] and the Seine (Rochette et al., in press) estuaries.

Intra-estuarine organisation of fish assemblages: the effect of the salinity gradient

The present study highlighted the intra-estuarine structure of the fish assemblages in terms of both number of species and density. While the upper low-salinity estuary areas were dominated by freshwater and diadromous species, the lower high-salinity parts contained a majority of marine and estuarine species. As expected, and highlighted in other studies [START_REF] Potter | Comparisons between the roles played by estuaries in the life cycles of fishes in temperate Western Australia and Southern Africa[END_REF][START_REF] Thiel | Environmental factors as forces structuring the fish community of the Elbe Estuary[END_REF][START_REF] Pease | A spatially oriented analysis of estuaries and their associated commercial fisheries in New South Wales, Australia[END_REF], a high-salinity area promoted species richness. This result further emphasises that large estuaries, which often present the entire range of haline habitats, may exhibit greater total species richness [START_REF] Nicolas | Fish under influence: a macroecological analysis of relations between fish species richness and environmental gradients among European tidal estuaries[END_REF].

On the other hand, the total maximum fish density was observed in the middle mesohaline parts of estuaries, where intertidal mudflats that display a high carrying capacity (Elliott and Taylor, 1989b;[START_REF] Costa | Fish usage and feeding in two industrialised estuaries -the Tagus, Portugal, and the Forth, Scotland[END_REF] might predominate. Indeed, in estuarine mesohaline areas, where the environmental conditions are especially harsh (i.e. high variability in hydrodynamics, salinity, turbidity and sediment erosion/deposition), few species are physiologically able to colonize, inducing a low biological competition but high abundances [START_REF] Mclusky | The Estuarine Ecosystem -ecology, threats and management[END_REF]. Furthermore, this reduced salinity area is often associated with Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 the presence of fine sediment particles [START_REF] Harris | Environmental management of clastic coastal depositional environments: inferences from an Australian geomorphic database[END_REF][START_REF] Mclusky | The Estuarine Ecosystem -ecology, threats and management[END_REF] with a high content of organic matter, which are particularly suitable for the development of benthic invertebrates [START_REF] Moore | Seasonal changes in distribution of intertidal macrofauna in the lower Mersey Estuary[END_REF]Elliott and Taylor, 1989b;[START_REF] Eisma | Particulate matter processes in estuaries[END_REF].

These great abundances of benthic preys may be the origin of the observed location of the high fish density [START_REF] Nicolas | Relationships between benthic macrofauna and habitat suitability for juvenile common sole (Solea solea, L.) in the Vilaine estuary (Bay of Biscay, France) nursery ground[END_REF]. The high density of marine species in the same mesohaline parts may also be partly related to a reduction in osmoregulation energy cost for lower salinities [START_REF] Potter | Comparisons between the roles played by estuaries in the life cycles of fishes in temperate Western Australia and Southern Africa[END_REF]. In contrast, the density of estuarine species, which are by definition well-adapted to the high variability of the estuarine environment, appeared not to be influenced by salinity, as found in other single-site studies [START_REF] Henderson | On the population dynamics of dab, sole and flounder within bridgwater bay in the lower severn estuary, England[END_REF][START_REF] Power | Environmental factors and interactions affecting the temporal abundance of juvenile flatfish in the Thames Estuary[END_REF]. The density of diadromous species, able to osmoregulate, was higher in both meso-and oligohaline estuary areas, while, as expected [START_REF] Franco | Life strategies of fishes in European estuaries: the functional guild approach[END_REF], the freshwater species were restricted to the oligohaline areas.

Conclusions

The present study highlighted four main trends in the functional diversity of fish assemblages:

(1) system size and entrance width, which facilitate seawater penetration, promoted functional diversity and the total number of species by enhancing density and number of marine species;

(2) northern estuaries were dominated by marine and catadromous species, while estuarine resident species were prevalent in southern estuaries, potentially due to more stable hydrology and higher temperature; (3) estuaries consisting for the most part of intertidal mudflats were further highlighted as having a crucial role of nursery and trophic support for juvenile fish; (4) fish assemblages were structured by the salinity gradient: high-salinity habitats concentrated maximum species richness, consisting mainly of marine and estuarine species, mesohaline habitats exhibited the greatest total density and especially the greatest density of marine species; low-salinity habitats had the greatest density of diadromous species and could also present some freshwater species.

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

Finally, despite the highly variable and complex functioning of estuaries that tends to hide anthropogenic impacts (the estuarine quality paradox, [START_REF] Elliott | The Estuarine Quality Paradox, Environmental Homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas[END_REF], general patterns in fish assemblages reflecting natural variability can be distinguished. As a result, when developing fish indicators to assess the level of anthropogenic pressures in estuaries [START_REF] Courrat | Anthropogenic disturbance on nursery function of estuarine areas for marine species[END_REF]Delpech et al., in press), considering significant natural explanatory descriptors such as system size, entrance width and salinity would greatly improve pressureimpact models and the precision of fish-based indicators. Moreover, these descriptors are, for most of them, easily available. Nonetheless, to improve the understanding of the relationship between fish and their environment, more precise investigations at a smaller habitat scale should be carried out.

Table 1: List of the abiotic attributes used to describe the estuarine environment, with their abbreviation and their ranges (minimum -maximum) and their units for quantitative variables or their classes for class factors. When the difference between two adjoining modalities was significant (student test), the symbol ">" was applied. Abbreviations of descriptors are detailed in Table 1.

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 , 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010 Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

Table 2 :

 2 List of fish species caught during the 48 selected European surveys with the estuarine use functional group they were allocated in, their occurrence in percentage and their mean density value (± confidence interval) in number of individuals per 1000m².Table3: Analysis of deviances for the generalized linear models computed on both (a) number of species (SR) and (b) densities (Dens) of each functional group category used as response variables with regards to selected descriptors (Intro. Var.) of abiotic attributes of estuaries. Df: degrees of freedom; Expl. Dev.: explained deviance in percentage per introduced descriptor. Sig.: significance (Chi square test), *: when p-value <5%, **: <1%, ***: <0.1%. Slope: slope sign when the explicative descriptor was a quantitative variable; for the class factors, all modalities were presented in decreasing order according to their effect.

Figures Fig. 1 :

 1 Figures Fig. 1: Location of the 31 European tidal estuaries studied. The continuous line off the coast corresponds to the 150m deep limit of the continental shelf.

Fig. 2 :

 2 Fig.2: Projection of the 31 estuaries on the first two main components of the PCA performed on abiotic variables (see Table1 and Fig. 1 for abbreviations). The correlation circle of active abiotic variables was inserted in the bottom right part. The six clusters were obtained by clustering method using Ward criteria based on the matrix of Euclidean distance between pairs of sites.

Fig. 3 :

 3 Fig. 3: Relative presence of estuarine use categories among estuaries in terms of species richness. a/ Ordination diagram for the principal coordinates analysis (PCoA) based on Bray-Curtis similarity matrices performed on the number of species per estuarine use categories, averaged per estuary. b/ Barplot representing in the upper part the relative percentage of estuarine use categories in number of species and in the lower part the total number of species per cluster.

Fig. 4 :

 4 Fig. 4: Relative densities of estuarine use categories among estuaries. a/ Ordination diagram for the principal coordinates analysis (PCoA) based on Bray-Curtis similarity matrices performed on the log-transformed densities of individuals per estuarine use categories, averaged per estuary. b/ Barplot representing in the upper part the relative percentage of estuarine use categories in densities and in the lower part the total mean of log-transformed densities per cluster.

  of the article published in Estuarine Coastal and Shelf Science

  Fig. 3 1 2

Table 1

 1 Author produced version of the article published in EstuarineCoastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010Author produced version of the article published in EstuarineCoastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

	Author produced version of the article published in
	Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338
	The original publication is available at http://sciencedirect.com/
	doi : 10.1016/j.ecss.2010.04.010
	Abbreviations	Abiotic attributes	Ranges and units or classes
	Continuous explaining variables
	LAT	Latitude	37.2 -56.5 decimal degrees
	CSW	Continental shelf width	4 -284 kilometres
	LS	Main Littoral substrate	1: Mud; 2: Mud/Sand; 3: Sand; 4:
			Sand/Gravel; 5: Rock
	TR	Tidal range	2.9 -11.8 metres
	RD	Mean annual river	2 -960 metres cube per second
		discharge
	WA	Watershed area	105 -117 955 square kilometres
	EA	Estuary area	0.5 -533 square kilometres
	EW	Entrance width	0.2 -16 kilometres
	ED	Entrance depth	0.5 -29 metres
	Categorical explaining factors
	IA	Intertidal area type	1: 0-20%; 2: 20-40%; 3: 40-60%;
			4: 60-80%; 5: 80-100%
	WE	Wave exposure	1: extremely exposed; 2:
			moderately exposed; 3: sheltered
	SC	Salinity class	1: oligohaline; 2: mesohaline; 3:
			polyhaline
	S sc	Sampled surface per	1 000 -174 155 square kilometres
		salinity class

Table 3 1

 3

	Intro. Var.	Df	Expl. Dev.	Sign.	Slope
	(a)

Models of species richness indices Total SR/ln(S sc ) ~ SC + log(RD) + EW

  Author produced version of the article published in EstuarineCoastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect.com/ doi : 10.1016/j.ecss.2010.04.010

	SC	2	16.4	***	SC3 > SC2, SC1
	+ log(RD)	1	16.8	***	+
	+ EW	1	6.1	**	+
	Residuals	90	60.7
	SR_M/ln(S sc ) ~ SC + log(RD)
	SC	2	36.7	***	SC3 > SC2 > SC1
	+ log(RD)	1	9.7	***	+
	Residuals	91	53.6
	SR_ES/ln(S sc ) ~ SC
	SC	2	17.9	***	SC3 > SC2 > SC1
	Residuals	92	82.1
	SR_DIA/ln(S sc ) ~ SC + EW
	SC	2	9.1	**	SC1, SC2, SC3
	+ EW	1	26.8	***	+
	Residuals	91	64.1
	(b) Models of density indices
	Total ln(Dens+1) ~ SC + IA + EW
	SC	2	7.9	**	SC2 > SC1, SC3 > 0
	+ IA	4	23.3	***	IA5, IA4, IA2, IA3 > IA1
	+ EW	1	7.9	**	+
	Residuals	87	60.9
	ln(Dens_M+1) ~ SC + IA + EW
	SC	2	7.1	*	SC2 > SC3, SC1
	+ IA	4	17.4	***	IA5, IA4, IA3, IA2, IA1
	+ EW	1	8.3	**	+
	Residuals	87	67.2
	ln(Dens_ES+1) ~ IA
	IA	4	17.9	***	IA5, IA3, IA4, IA2, IA1
	Residuals	90	82.1
	ln(Dens_Dia+1) ~ SC + CSW + EW
	SC	2	14.4	***	SC1, SC2 > SC3
	+ CSW	1	17.3	***	+
	+ EW	1	4.7	*	+
	Residuals	90	63.6
	2
	3
	4
	5
	6
	7

very grateful to all our European partners for sharing their WFD fish data: Steve Coates, Adam Waugh from Environmental Agency (London, England and Wales data), Alexis Pearce from Scottish Environment Protection Agency (Edinburgh, Scotland data), Angel Borja from AZTI -Tecnalia/Marine Research Division (Pasaia, Spain Basque data), Maria José Costa from Institute of Oceanography (Lisbon, Portugal data), Rachid Amara and Jonathan Selleslagh from University of Opale littoral coast (Wimereux, French Authie and Canche estuaries data) and Mario Lepage, Michel Girardin and Jacques Massé from Cemagref institute (Cestas, French data). Special thanks to Hilaire Drouineau for sharing his statistical knowledge.

Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329 -338 The original publication is available at http://sciencedirect. com/ doi : 10.1016/j.ecss.2010.04.010 Author produced version of the article published in Estuarine Coastal and Shelf Science, 2010, vol. 88, p. 329

Bay of Biscay North Sea

Atlantic Ocean

Eng lish Cha nne l