Florent Di Meglio

Pierre-Olivier Lamare

Jakob F Aarsnes

Robust output feedback stabilization of an ODE-PDE-ODE interconnection

Keywords: Hyperbolic Partial Differential Equations, stabilization, backstepping

We propose a controller that robustly stabilizes an interconnection of Ordinary Differential Equations with two hyperbolic linear Partial Differential Equations. The proposed design guarantees closed-loop asymptotic stability as well as robustness to small delays. The result is obtained through a backstepping approach. A boundary observer is also derived, yielding an output feedback controller with several calibration parameters.

Introduction

In this paper, we consider the problem of stabilizing the interconnection of a system of two first-order linear hyperbolic Partial Differential Equations (PDE) with Ordinary Differential Equations (ODE). More precisely, the interconnection features a controlled, scalar ODE coupled at one boundary of the spatial domain with the PDE, which we call the proximal boundary. At the distal boundary the other ODE is uncontrolled and may have a vector state. This situation is schematically depicted on Figure 1.

Such systems arise in many practical applications involving delay or transport phenomena, due to lumped physical elements or actuation and measurement dynamics. If the lumped dynamics are not taken explicitly into account in the controller design, e.g. by assuming they can be inverted or canceled, it could easily lead to robustness issues. This is illustrated in this paper by a discussion on delay robustness. Specific examples of this kind of systems include the: control of mining shaft elevators [START_REF] Wang | Control of a 2× 2 coupled linear hyperbolic system sandwiched between 2 odes[END_REF], hydraulic flowlines with lumped elements [START_REF] Goodson | Discussion: A Survey of Modeling Techniques for Fluid Line Transients[END_REF], control of loaded heavy chains with actuation dynamics [START_REF] Petit | Flatness of heavy chain systems[END_REF].

Of particular interest are the modeling and control of Email addresses: florent.di meglio@mines-paristech.fr (Florent Di Meglio), pierre-olivier.lamare@mines-paristech.fr (Pierre-Olivier Lamare), ulaa@norceresearch.no (Ulf Jakob F. Aarsnes).

Control input

ω 0 = a 0 ω 0 +b 0 v(0,t)+U(t) u(0,t)= c 0 ω 0 +d 0 v(0,t)

. torsional and axial vibrations in deep drilling systems. The hyperbolic PDE models the propagation of torsional and axial waves along the long (typically several thousand meters), slender drill string [START_REF] Aarsnes | Avoiding stick slip vibrations in drilling through startup trajectory design[END_REF][START_REF] Aarsnes | Torsional vibrations with bit off bottom: Modeling, characterization and field data validation[END_REF][START_REF] Jakob | Axial and torsional self-excited vibrations of a distributed drill-string[END_REF]. At the surface boundary, an electric motor applies a torque (the control input) to the so-called top drive, which has a large inertia and is responsible for the first-order dynamics at this boundary. At the bottom of the well, the drillstring is rigidly connected to the Bottom Hole Assembly (BHA), which consist of heavy collar sections that can be represented as a lumped element. Ignoring the lumped dynamics in this system leads to controllers which are not usable in practice. This is evident when considering the commercially available controllers [START_REF] Dwars | Recent advances in soft torque rotary systems[END_REF][START_REF] Kyllingstad | A Comparison of Stick-Slip Mitigation Tools[END_REF][START_REF] Kyllingstad | A new stick-slip prevention system[END_REF].

ω 1 = A 1 ω 1 +B 1 u(1,t) v(1,t)= C 1 ω 1 +d 1 u(1,

t)

Several contributions focus on ODE-PDE-ODE interconnections such as the one considered in this paper. In [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF], a backstepping approach is used to design a stabilizing full-state feedback controller for actuator dynamics of arbitrary order. Using the design of [START_REF] Di Meglio | Stabilization of coupled linear heterodirectional hyperbolic PDE-ODE systems[END_REF], the PDE in-domain coupling terms are canceled and the distal ODE is stabilized. Then, using an additional step of backstepping, the proximal wave reflection is entirely canceled and the influence of the PDE onto the state of the controlled ODE is entirely canceled. In an ideal setting, this control strategy efficiently stabilizes the plant regardless of the magnitude of coupling terms and of the natural time scales of the ODEs. However, as pointed out in [START_REF] Logemann | Conditions for robustness and nonrobustness of the stability of feedback systems with respect to small delays in the feedback loop[END_REF][START_REF] Hale | Stability and control of feedback systems with time delays[END_REF][START_REF] Auriol | Delay-robust control design for heterodirectional linear coupled hyperbolic PDEs[END_REF] it is likely to have zero delay robustness margin, i.e. to result in an unstable system in the presence of arbitrarily small delays. In [START_REF] Wang | Control of a 2× 2 coupled linear hyperbolic system sandwiched between 2 odes[END_REF], a similar strategy is employed in the particular case where actuator dynamics are of second-order. In [START_REF] Deutscher | Output feedback control of general linear heterodirectional hyperbolic ODE-PDE-ODE systems[END_REF], these results is improved, in particular by alleviating some restrictions on the controlled ODE, and an observer is designed, relying on a measurement of the boundary value of one of the PDEs. Again, the proximal reflection of the PDE is entirely canceled, leading to a stable cascade, but to a non-robust design.

The main contribution of this paper is an output feedback law that:

(1) stabilizes the plant depicted in Figure 1, (2) is robust to small actuator delays, (3) has tunable design parameters.

Our approach builds on the result from [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF]. We propose small modifications of the design that "robustify" the controller: rather than canceling the entire proximal wave reflection, we assign it the dynamics of a high-pass filter. The resulting target system dynamics take the form of a cascade of the distal ODE into a first-order neutral system, which, when stable, is shown to be wstable in the sense of [START_REF] Curtain | An introduction to Infinite-Dimensional Linear Systems Theory[END_REF][START_REF] Georgiou | Graphs, causality, and stabilizability: Linear, shift-invariant systems on L 2 [0, ∞)[END_REF]. Further, we propose an observer relying on collocated (proximal) measurements.

The paper is organized as follows: In Section 2 we define the problem and the notations used thoughout the paper. Then, in Section 3, we design the controller and prove its robustness properties. In Section 4 we design the observer and formulate the main result, i.e. the output feedback control law. Finally, we illustrate the design with numerical simulations on a toy problem in Section 5.

Problem setup and notations

In this paper, we consider the problem of stabilizing the following interconnection

ω0 =a 0 ω 0 + b 0 v(t, 0) + U (t) (1) u(t, 0) =c 0 ω 0 (t) + d 0 v(t, 0) (2) u t (t, x) = -λ(x)u x (t, x) + σ ++ (x)u(t, x) + σ +-(x)v(t, x) (3) v t (t, x) =µ(x)v x (t, x) + σ -+ (x)u(t, x) + σ --(x)v(t, x) (4) v(t, 1) =C 1 ω 1 (t) + d 1 u(t, 1) (5) ω1 =A 1 ω 1 + B 1 u(t, 1) (6) with λ, µ ∈ C 1 ([0, 1], R * + ), ω 0 ∈ R, (u, v) ∈ L 2 ((0, 1), R)
and ω 1 ∈ R n , using solely the measurement of the (scalar) ODE state at x = 0, i.e. y(t) = ω 0 (t) [START_REF] Curtain | An introduction to Infinite-Dimensional Linear Systems Theory[END_REF] under the following assumptions A1 The pair (A 1 , B 1 ) (resp. (A 1 , C 1 )) is stabilizable (resp.detectable). We denote κ1 (resp. Ľ1 ) a set of control (resp. observer) gains such that

A 1 + B 1 κ1 (resp. A 1 + Ľ1 C 1 i) is Hurwitz. A2 The reflection coefficients d 0 , d 1 satisfy R < 1 (8)
where

R = exp 1 0 σ ++ (x) λ(x) dx + 0 1 σ --(x) µ(x) dx |d 0 d 1 | (9)
A3 The proximal ODE has an effect on the rest of the system, i.e. c 0 = 0. Conversely, the PDE states have an effect on the proximal ODE, i.e. b 0 = 0.

Assumption A2 is a necessary and sufficient condition for the existence of a stabilizing controller robust to at least small delays [START_REF] Logemann | Conditions for robustness and nonrobustness of the stability of feedback systems with respect to small delays in the feedback loop[END_REF]. Indeed, when it is not satisfied, the open-loop system features an infinite number of poles in the Right-Half Plane. We first design a full-state feedback controller taking the form

U (t) = k 0 ω 0 (t) + k 1 ω 1 (t) + K 0 v(t, 0) + K 1 u(t, 1) + 1 0 [K(y)u(t, y) + L(y)v(t, y)]dy, (10)
before designing the observer.

3 Controller: design and robustness

Control design

The controller is based on a backstepping design similar to [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF]. More precisely, we map the system to the following target system

η0 (t) = pη 0 (t) + d 0 p - ž c 0 β(t, 0) (11) α(t, 0) = c 0 η 0 (t) + d 0 β(t, 0) (12) α t (t, x) + λ(x)α x (t, x) = σ ++ (x)α(t, x) (13) β t (t, x) -µ(x)β x (t, x) = σ --(x)β(t, x) (14) β(t, 1) = d 1 α(t, 1). (15) ω1 (t) = (A 1 -B 1 κ 1 )ω 1 (t) + B 1 α(t, 1) (16)
where p, ž and κ1 are control design parameters. The main difference with [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF] is that we cancel here the ODE term in [START_REF] Kyllingstad | A Comparison of Stick-Slip Mitigation Tools[END_REF] but not the PDE boundary reflection term in [START_REF] Georgiou | Graphs, causality, and stabilizability: Linear, shift-invariant systems on L 2 [0, ∞)[END_REF]. Besides, we introduce the degrees of liberty p and ž. To do so, we consider the following backstepping transformation.

α(t, x) = u(t, x) - 1 x K uu (x, y)u(t, y)dy - 1 x K uv (x, y)v(t, y)dy -G u (x) ω 1 (t) (17) β(t, x) = v(t, x) - 1 x K vu (x, y)u(t, y)dy - 1 x K vv (x, y)v(t, y)dy -G v (x) ω 1 (t), ( 18
)
where the transformation kernels are defined by the following set of well-posed [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF] equations

λ(x)K uu x (x, y) + λ(y)K uu y (x, y) = [σ ++ (x)-σ ++ (y)-λ (y)]K uu (x, y)-σ +-(y)K uv (x, y) (19)
λ(x)K uv x (x, y) -µ(y)K uv y (x, y) = [σ ++ (x)-σ --(y)+µ (y)]K uv (x, y)-σ -+ (y)K uu (x, y) (20)
K uv (x, x) = - σ +-(x) λ(x) + µ(x) (21)
λK uu (x, 1) =µ(1)d 1 K uv (x, 1) + G u (x) B 1 (22) λ(x)G u (x) =(σ ++ (x)I n -A 1 )G u (x) -µ(1)K uv (x, 1)C 1 (23) G u (1) = -κ1 ( 24
)
where I n is the identity matrix of size n, and

-µ(x)K vu x (x, y) + λ(y)K vu y (x, y) = [σ --(x)-σ ++ (y)-λ (y)]K vv (x, y)-σ -+ (y)K vv (x, y) (25) -µ(x)K vv x (x, y) -µ(y)K vv y (x, y) = [σ --(x)-σ --(y)+µ (y)]K vv (x, y)-σ +-(y)K vu (x, y) (26)
K vu (x, x) = σ -+ (x) λ(x) + µ(x) (27) µd 1 K vv (x, 1) = λK vu (x, 1) -G v (x) B 1 (28) µG v (x) = -(σ --(x)I n -A 1 )G v (x) + µ(1)K vv (x, 1)C 1 (29) G v (1) = -d 1 κ1 +C 1 . ( 30
)
With the following variable change for ω 0

η 0 (t) = ω 0 (t) -c -1 0 1 0 Kα (y)u(t, y) + Kβ (y)v(t, y) dyc -1 0 G ω 1 (t) (31)
where

Kα (y) = K uu (0, y) -d 0 K vu (0, y) (32) Kβ (y) = K uv (0, y) -d 0 K vv (0, y) (33) G = G u (0) -d 0 G v (0). ( 34
)
In [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF], the transformation ω 0 → η 0 contains an additional term -d 0 v(t, 0) that is used to cancel the reflecting wave from the PDE at x = 0. Rather, here, Equation ( 31) maps (2) to the following boundary condition

α(t, 0) = d 0 β(t, 0) + c 0 η 0 (t). ( 35
)
This choice is made to ensure delay robustness of the controller, as proved in Section 3.2.2. Indeed, canceling entirely the reflecting wave of the PDE at the left boundary will cause the delay robustness margin to be exactly zero when R ≥ 0.5, in [START_REF] Deutscher | Output feedback control of general linear heterodirectional hyperbolic ODE-PDE-ODE systems[END_REF], as detailed in [START_REF] Logemann | Conditions for robustness and nonrobustness of the stability of feedback systems with respect to small delays in the feedback loop[END_REF][START_REF] Auriol | Delay-robust control design for heterodirectional linear coupled hyperbolic PDEs[END_REF]. Moreover, the choices made in [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF][START_REF] Deutscher | Output feedback control of general linear heterodirectional hyperbolic ODE-PDE-ODE systems[END_REF] requires computing the time derivative of the PDE state at the boundary, or equivalently, its spatial derivative, resulting in both cases an acausal design necessitating approximations in the implementation. As will be made clear, this is not a requirement here. Plugging ( 17), ( 18), (31) into (1) yields

η0 (t) = U (t) + [a 0 -λ(0) Kα (0)]ω 0 (t) -c -1 0 G A 1 + C 1 µ(1) Kβ (1) ω 1 (t) + b 0 + c -1 0 µ(0) Kβ (0) -λ(0)d 0 Kα (0) v(t, 0) + c -1 0 -G b 1 + λ(1) Kα (1) -µ(1)d 1 Kβ (1) u(t, 1) -c -1 0 1 0 λ(y) K α (y) + λ (y) Kα (y) + σ ++ (y) Kα (y) +σ -+ (y) Kβ (y) u(t, y)dy -c -1 0 1 0 -µ(y) K β (y) + λ (y) Kβ (y) + σ --(y) Kβ (y) +σ +-(y) Kα (y) v(t, y)dy (36)
which, using the inverse backstepping transformations yields an expression of the form

η0 (t) = U (t) + A 0 η 0 (t) + B 0 β(t, 0) + D1 ω 1 (t) + B 1 α(t, 1) - 1 0 M (y)α(t, y)dy + 1 0 N (y)β(t, y)dy. ( 37
)
where A 0 , B 0 , B 1 , D1 , M and N are given in Appendix A. Equation (37), which is the open-loop dynamics of η 0 in the target system coordinates, will prove useful in the w-stability analysis in the next section while (36) is used to express the control law in the original coordinates.

More precisely, we propose a control law of the form [START_REF] Di Meglio | Stabilization of coupled linear heterodirectional hyperbolic PDE-ODE systems[END_REF] where the control gains are given by

k 0 = p -A 0 (38) k 1 = -D 1 - p c 0 G -d 0 p - ž c 0 G v (0) (39)
K 0 = d 0 p - ž c 0 -B 0 (40) K 1 = -B 1 (41) K(x) = c -1 0 K D u (x) -pc -1 0 Kα (x) -d 0 p - ž c 0 K vu (0, x) (42)
L(x) = c -1 0 K D v (x) -pc -1 0 Kβ (x) -d 0 p - ž c 0 K vv (0, x). ( 43
)
where p and ž are design parameters. This choice maps, in closed-loop, ( 1)-( 6) to ( 11)-( 16). In the next section, we investigate the stability properties of ( 11)-( 16).

Stability of the target system and controller robustness

In this Section, we give necessary and sufficient conditions on the control design parameters for the target system to be stable (Lemma 2). Then, we show that the closed-loop system is actually w-stable in the sense of [START_REF] Curtain | An introduction to Infinite-Dimensional Linear Systems Theory[END_REF].

Both results rely on the following Lemma.

Lemma 1 Consider Equations ( 12)-( 16). All the variables can be expressed, in the Laplace domain, as functions of α(s, 0) using proper transfer functions.

We recall the definition of a (strictly) proper transfer function from [START_REF] Curtain | Transfer functions of distributed parameter systems: A tutorial[END_REF] Definition

|G(s)| = 0. ( 45
)
We are now ready to prove Lemma 1.

Proof 1 Taking the Laplace transform of (12)-( 16)

yields α(s, x) = exp x 0 σ ++ (y) -s λ(y) dy α(s, 0) (46) ω 1 (s) = (sI -A 1 + B 1 κ1 ) -1 B 1 • exp 1 0 σ ++ (y) -s λ(y) dy α(s, 0) (47) β(s, x) = d 1 exp 1 0 σ ++ (y) -s λ(y) dy + 1 x σ --(y) -s µ(y) dy α(s, 0) (48)
And denoting

τ = 1 0 1 λ(y) + 1 µ(y) dy, (49)
k d = exp 1 0 σ ++ (y) λ(y) dx + 1 0 σ --(y) µ(y) dy , (50)
yields β(s, 0) = d 1 k d e -τ s α(s, 0) (51) c 0 η 0 (s) = 1 -d 0 d 1 k d e -τ s α(s, 0) (52)
One can readily check that all the transfer functions appearing in (46)-( 52) satisfy (44).

Stability

The stability of the target system is assessed in the following Lemma.

Lemma 2 Assume that p, ž satisfy either the following set of conditions

p -d 0 d 1 k d ž < 0, -p ≥ |d 0 d 1 k d ž| (53) or d 0 d 1 k d ž > |p| , (54) τ < (55) 1 -d 2 0 d 2 1 k 2 d d 2 0 d 2 1 k 2 d ž2 -p2 tan -1 d 2 0 d 2 1 k 2 d ž + p (d 2 0 d 2 1 k 2 d ž2 -p2 )(1 -d 2 0 d 2 1 k 2 d ) (56)
Then (11)-( 16) is asymptotically stable.

Proof 2 Note that α(s, 0) = d 0 s - ž s - p β(s, 0) (57)
Combining (51),( 52) and (57) we find that the states α(s, 0), β(s, 0) and η(s) all have the characteristic equation

s(1 -d 0 d 1 k d e -τ s ) -p + d 0 d 1 k d že -τ s = 0 (58)
A system with the characteristic equation (58) has the conditions (53)-( 56) for asymptotic stability as derived in [START_REF] Niculescu | Delay effects on stability: A robust control approach[END_REF]Proposition 3.16]. The distributed states α(s, x) and β(s, x) and the distal ODE state ω 1 (s) can be expressed as transfer functions with no poles in the RHP and α(s, 0) as input, and consequently these states are asymptotically stable as well.

Robustness

In this Section, we show that the closed-loop system is robust to approximate identities [START_REF] Curtain | An introduction to Infinite-Dimensional Linear Systems Theory[END_REF], that is, it is w-stable.

A family of operators I δ , δ > 0, is said to be an approximate identity if, for any δ, I δ has transfer function I δ (s) satisfying I δ (s) ∞ = 1 and (I δ (s) -I) ∞ → 0 as δ → 0, see [START_REF] Georgiou | Graphs, causality, and stabilizability: Linear, shift-invariant systems on L 2 [0, ∞)[END_REF]. This is important, as failure to be robust to approximate identities means that the system can be unstable for abritrarily small uncertainty or delays.

To show this, we write the open-loop and feedback law transfer functions in the target system coordinates. More precisely, we write the full-state feedback law as a causal dynamic output feedback law (for a conveniently chosen output) by using the structure of the target system. First, we recall the definition of w-stability.

Definition 2 (w-stability, [START_REF] Curtain | An introduction to Infinite-Dimensional Linear Systems Theory[END_REF] Definition 9.5.3) A stable feedback systen (G, K)is said to be w-stable if for any approximate identity I δ there exists a δ 0 such that (I δ G, K) is input-output stable for all δ ∈ [0, δ 0 ).

We are now ready to state an important result of the paper: when stable, the closed-loop system is w-stable.

Lemma 3 If system (37), ( 12)-( 16) with a control law of the form (10) is stable, then it is w-stable in the sense of [START_REF] Georgiou | Graphs, causality, and stabilizability: Linear, shift-invariant systems on L 2 [0, ∞)[END_REF]. In particular, it is robust to small delays in the actuation path.

Proof 3 The open-loop dynamics of η 0 given by (37) rewrite as follows

sη 0 = A 0 η 0 (s) + D 1 ω 1 (s) + B 0 β(s, 0) + B 1 α(s, 1) - 1 0 M (y)α(s, y)dy - 1 0 N (y)β(s, y)dy + U (s). (59)
Therefore, using Lemma 1 and its proof, the open-loop transfer function reads

α(s, 0) = c 0 s [1 -Re -τ s ] + H(s) U (s) (60)
:= G(s)U (s) ( 61
)
where R is defined by ( 9) and H can be computed from (46)-( 59) and is proper according to Definition 1. Besides, since R satisfies (9), one has

lim sup |s|→∞, s∈C 0 1 -Re -τ s > 0, (62)
where C 0 denotes the closed left half plane. This essentially means that there is no asymptotic chain of zeros converging towards the Right-Half-Plane, which, in turn, implies that G is strictly proper. Similarly, using the inverse backstepping transformation and relations (46)-( 52), the control law (10) rewrites as

U (s) = K(s)α(s, 0) (63)
where K(s) is proper. Therefore, for some sufficiently large M > 0, the loop transfer function satisfies

sup |s|>M G(s)K(s) < 1 (64)
which yields the result using [START_REF] Georgiou | Graphs, causality, and stabilizability: Linear, shift-invariant systems on L 2 [0, ∞)[END_REF]Proposition 16].

One should notice that a crucial element in the proof is that the feedback law is proper, which is not the case of, e.g., the feedback law in [START_REF] Bou Saba | Backstepping stabilization of 2 × 2 linear hyperbolic pdes coupled with potentially unstable actuator and load dynamics[END_REF]. In the case of [START_REF] Deutscher | Output feedback control of general linear heterodirectional hyperbolic ODE-PDE-ODE systems[END_REF], the nonproper nature of the control law is avoided by replacing the derivative feedback term v t (t, 0) with a term of the form v x (t, 0) using (4). We have not investigated the robustness properties of such a control law. Lemma 3 guarantees a certain robustness of the design when the closed-loop system is stable.

Output feedback controller

In this Section, we design an observer using a transformation with a structure dual that is dual to [START_REF] Logemann | Conditions for robustness and nonrobustness of the stability of feedback systems with respect to small delays in the feedback loop[END_REF], [START_REF] Niculescu | Delay effects on stability: A robust control approach[END_REF], before sketching the closed-loop stability proof for the corresponding output feedback controller.

Observer design

We consider the following Luenberger-like observer

ω0 (t) = a 0 ω0 (t) + b 0 v(t, 0) + U (t) -p 0 (ω 0 -ω 0 ) (65) û(t, 0) = c 0 ω0 (t) + d 0 v(t, 0) -P 0 (ω 0 -ω 0 ) (66) ût (t, x) = -λ(x)û x (t, x) + σ ++ (x)û(t, x) + σ +-(x)v(t, x) -p u (x)(ω 0 -ω 0 ) (67) vt (t, x) = µ(x)v x (t, x) + σ -+ (x)û(t, x) + σ --(x)v(t, x) -p v (x)(ω 0 -ω 0 ) (68) v(t, 1) = C 1 ω1 (t) + d 1 û(t, 1) -P 1 (ω 0 -ω 0 ) (69) ω1 (t) = A 1 ω1 (t) + B 1 û(t, 1) -p 1 (ω 0 -ω 0 ). ( 70
)
We define the error variables w = ŵ -w. M vu (x, y)α(t, y)dy

+ 1 0 M vv (x, y) β(t, y)dy -H v (x)η 0 (t) (73) ω1 (t) =η 1 (t) - 1 0 N u (x, y)α(t, y)dy (74) + 1 0 N v (x, y) β(t, y)dy -H 1 η0 (t) (75) is such that η0 (t) = pobs η0 (t) + b 0 β(t, 0) (76) α(t, 0) = d 0 β(t, 0) (77) αt (t, x) = -λ(x)α x (t, x) βt (t, x) = µ(x) βx (t, x) β(t, 1) = C 1 η1 (t) + d 1 α(t, 1) (78) η1 (t) = A 1 -Ľ1 C 1 η1 (t) (79) provided M uu , M uv , M vu , M vv , H u , H v ,
p 0 = a 0 -b 0 H v (0) -po bs (80) P 0 = c 0 + d 0 H v (0) -H u (0) (81) p u (x) = σ ++ H u (x) + σ +-H v (x) -λH u (x) -pH u (x) (82) p v (x) = σ -+ H u (x) + σ --H v (x) + µH v (x) -pH v (x) (83) p 1 = B 1 H u (1) + H 1 (p obs -a 1 ) (84) P 1 = d 1 H u (1) -H v (1) -C 1 H 1 (85)

Output feedback controller

The main result is stated in the following Theorem.

Theorem 1 Consider System (1)-( 6) with the following control law

U (t) = k 0 ω0 (t) + k 1 ω1 (t) + K 0 v(t, 0) + K 1 û(t, 1) + 1 0 [K(y)û(t, y) + L(y)v(t, y)]dy, (86)
where ω0 , ω1 , v, û are defined by (65)-(70). The zero equilibrium is asymptotically stable.

Proof 4 We only sketch here the proof for brevity's sake. Consider the observer error system in target system coordinates (76)-(79). It is a cascade of η1 into (α, β) into η0 , thus it is exponentially stable. Consider now (11)-( 16) with the control law (86) expressed in target system coordinates. It rewrites

η0 (t) = pη 0 (t) + d 0 p - ž c 0 β(t, 0) + Ũ (t) (87) α(t, 0) = c 0 η 0 (t) + d 0 β(t, 0) (88) α t (t, x) + λ(x)α x (t, x) = σ ++ (x)α(t, x) (89) β t (t, x) -µ(x)β x (t, x) = σ --(x)β(t, x) (90) β(t, 1) = d 1 α(t, 1). (91) ω1 (t) = (A 1 -B 1 κ 1 )ω 1 + B 1 α(t, 1) (92)
where Ũ (t) = k 0 ω0 (t) + k 1 ω1 (t) + K 0 ṽ(t, 0) + K 1 ũ(t, 1) (93)

+ 1 0
[K(y)ũ(t, y) + L(y)ṽ(t, y)]dy (94)

vanishes to zero since the observer error converges asymptotically to zero. Besides, the target system (87)-( 92) is linear, which implies by Lemma 1 and Proposition 3 in [START_REF] Dashkovskiy | Input-to-state stability of infinite-dimensional control systems[END_REF] that it is Input-to-State Stable (ISS) wrt to the input Ũ . Therefore, target system (87)-( 92) is asymptotically stable.

Numerical example

To illustrate the result we consider the following toy example ω0 (t) = 0.2ω 0 (t) + v(t, 0) + U (t) (95) u(t, 0) = ω 0 (t) + 0.9v(t, 0) (96) u t (t, x) + u x (t, x) = -0.01u(t, x) -0.05v(t, x) (97) v t (t, x) -v x (t, x) = 0.1u(t, x) -0.01(x)v(t, x) (98) v(t, 1) = 1 0 ω 1 (t) -0.9u(t, 1) (99)

ω1 (t) = 0.1 1 -1 0 ω 1 (t) + 1 0 v(t, 1). ( 100
)
This plant has unstable ODEs at both boundaries as well as an instability caused by the in-domain source terms.

For this plant we design a stabilizing collocated output injection controller using an observer with ω 0 as the measurement. For the observer we use the design parameters κ 1 = 3 1 , ž = 0, p = -1000. For the controller we use κ 1 = 1.5 0.6 , ž = 0, while for the proximal pole placement we consider two cases: p = -1000 and p = -5. The results are shown in Fig. 5. As is clearly illustrated in this Figure, increasing the magnitude of the p pole yields better performance, but at the cost of a more aggressive control effort and lower robustness to actuation delays. The limit where p → -∞ corresponds to the approach of using a full cancellation of the reflection at the proximal boundary, but this also yields zero delay robustness.

Fig. 1 .

 1 Fig. 1. Schematic description of the considered system. The black dotted arrows represent transport phenomena while the red arrows represent couplings.

Fig. 2 .

 2 Fig. 2. Toy example trends.

Acknowledgments

The work of the third author was supported by the Research Council of Norway, ConocoPhillips, AkerBP, Statoil and Wintershall through the research center DrillWell (203525/O30) at IRIS, and by the Marie Sk lodowska-Curie (MSCA) -Individual Fellowships through the Robust Estimation and Control of Infinite Dimensional Systems (RECIDS) Project.

A Open-loop dynamics of the target system

We detail here the open-loop dynamics of the target system. First, one has to compute the inverse backstepping transformation (η 0 , α, β, ω 1 ) → (ω 0 , u, v, ω 1 ). To do so, notice that [START_REF] Logemann | Conditions for robustness and nonrobustness of the stability of feedback systems with respect to small delays in the feedback loop[END_REF], [START_REF] Niculescu | Delay effects on stability: A robust control approach[END_REF] are Volterra equations in u and v.

Denoting L =

L uu L uv L vu L vv the inverse kernels and omiting the time argument, one has

that we rewrite

Plugging into (31) yields, simlilarly, an expression of the form

Lα (y)α(t, y) + Lβ (y)β(t, y)dy

Finally, plugging (A.3)-(A.5) into (36) yields (37) with 1)


C Munschy
email: cmunschy@ifremer.fr

E Vigneau

N Bely

K Héas-Moisan

N Olivier

C Pollono

S Hollanda

N Bodin

Legacy and emerging organic contaminants: Levels and profiles in top predator fish from the western Indian Ocean in relation to their trophic ecology

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Apical marine fish predators represent a major marine resource and play an essential role in marine ecosystems. In addition, they are of high economic value to industrial and artisanal fisheries and local populations due to their nutritional benefits (proteins, essential minerals, vitamins and polyunsaturated fatty acids) (Sioen et al., 2009). However, due to their position at the top of trophic webs, coupled with a long lifespan, they are prone to accumulating high levels of various contaminants, including toxic ones such as Persistent Organic Pollutants (POPs). POPs are defined by their persistent, bioaccumulative, toxic properties and propensity to travel far from their emission sources, hence leading to global distribution [START_REF] Wania | Tracking the distribution of persistent organic pollutants[END_REF][START_REF] Lohmann | Global fate of POPs: Current and future research directions[END_REF][START_REF] Rigét | Twenty years of monitoring of persistent organic pollutants in Greenland biota. A review[END_REF]. They are listed under the United Nations Stockholm Convention, which came into force in 2004 and aims to protect humans and the environment from chemicals. The POPs reported in this study include polychlorinated biphenyls (PCBs), organochlorinated pesticides (OCPs) (namely, dichlorodiphenyltrichloroethane -DDT and its isomers, hexachlorobenzene -HCB, hexachlorocyclohexanes -HCHs, mirex, dieldrin, aldrin and endosulfans) and perfluorooctane sulfonate (PFOS).

Although these POPs have been phased-out in many countries, especially in the Northern Hemisphere [START_REF] Kalantzi | The global distribution of organochlorine pesticides in butter[END_REF]Zitko, 2003;[START_REF] Barber | Hexachlorobenzene in the global environment: Emissions, levels, distribution, trends and processes[END_REF][START_REF] Breivik | Towards a global historical emission inventory for selected PCB congeners -A mass balance approach-3. An update[END_REF][START_REF] Vijgen | Hexachlorocyclohexane (HCH) as new Stockholm Convention POPs -a global perspective on the management of Lindane and its waste isomers[END_REF][START_REF] Land | What is the effect of phasing out long-chain per-and polyfluoroalkyl substances on the concentrations of perfluoroalkyl acids and their precursors in the environment? A systematic review[END_REF], their use is still reported in developing countries such as Asia, Africa and South America and secondary emissions persist [START_REF] Breivik | Are reductions in industrial organic contaminants Eemissions in rich countries achieved partly by export of toxic wastes?[END_REF][START_REF] Ali | Organochlorine pesticides (OCPs) in South Asian region: a review[END_REF][START_REF] Bouwman | Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment[END_REF], emphasizing the need to investigate further their occurrence in the marine environment. Besides, long-chain perfluorocarboxylic acids (PFCAs) have also been investigated as contaminants of emerging concern: they share similar properties to POPs and show an increasing production in Asia together with their precursors [START_REF] Wang | Global emission inventories for C4-C14 perfluoroalkyl carboxylic acid (PFCA) homologues from 1951 to 2030, Part I: production and emissions from quantifiable sources[END_REF] ; in addition, oceans are recognized as PFAS main reservoir [START_REF] Johansson | Global transport of perfluoroalkyl acids via sea spray aerosol[END_REF], which overall raise concern on their impact on marine ecosystems.

The tropical tuna species, namely, skipjack -SKJ-(Katsuwonus pelamis), yellowfin -YFT-(Thunnus albacares), bigeye -BET-(Thunnus obesus) tunas, and the billfish swordfish -SWO-(Xiphias gladius), were investigated for organic contamination. These four large pelagic top predator fish occur in all oceans but do not share similar trophic niches, as they feed at different depths of the water column [START_REF] Ménard | Isotopic evidence of distinct feeding ecologies and movement patterns in two migratory predators (yellowfin tuna and swordfish) of the western Indian Ocean[END_REF][START_REF] Sardenne | Trophic niches of sympatric tropical tuna in the Western Ehime University, Japan[END_REF]. They are known to be highly-migratory species that travel long distances. However, during the foraging and spawning season, they demonstrate seasonal resident behaviour at the temporal scale of their muscle turnover rate (i.e. months, [START_REF] Madenjian | Tissue turnover rates and isotopic trophic discrimination factors in the endothermic teleost, Pacific bluefin tuna (Thunnus orientalis)[END_REF][START_REF] Pethybridge | A global meta-analysis of marine predator nitrogen stable isotopes: relationships between trophic structure and environmental conditions[END_REF]. For several years, POPs in top predator fish have been used as time-integrated tracers of marine environmental contamination [START_REF] Ueno | Global pollution monitoring of polychlorinated dibenzo-p-dioxins (PCDDs), furans (PCDFs) and coplanar polychlorinated biphenyls (coplanar PCBs) using skipjack tuna as bioindicator[END_REF][START_REF] Hart | Skipjack tuna as a bioindicator of contamination by perfluorinated compounds in the oceans[END_REF]. Used in conjunction with trophic and ecological parameters such as stable isotopes of carbon (δ 13 C) and nitrogen (δ 15 N), POPs have proved to be suitable tracers of foraging habitats and trophic transfers in marine ecosystems [START_REF] Dickhut | Atlantic Bluefin Tuna (Thunnus thynnus) population dynamics delineated by organochlorine tracers[END_REF]Hisamishi et al., 2010;[START_REF] Deshpande | Polychlorinated biphenyls and organochlorine pesticides as intrinsic tracer tags of foraging grounds of blue fin tuna in the northwest Atlantic Ocean[END_REF][START_REF] Dirtu | Contrasted accumulation patterns of persistent organic pollutants and mercury in sympatric tropical dolphins from the south-western Indian Ocean[END_REF][START_REF] Chouvelon | Chemical contaminants (trace metals, persistent organic pollutants) in albacore tuna from western Indian and south-eastern Atlantic Oceans: trophic influence and potential as tracers of populations[END_REF].

The Indian Ocean is the world's third largest water body and a major production area for tuna and billfish fisheries, in particular in the Western part [START_REF] Pons | Effects of biological, economic and management factors on tuna and billfish stock status[END_REF][START_REF] Chassot | The key role of the Northern Mozambique Channel for Indian Ocean tropical tuna fisheries[END_REF].

However, to date, very few studies have focused on the contamination of its ecosystems by organic pollutants [START_REF] Bouwman | First report of chlorinated and brominated hydrocarbon pollutants in marine bird eggs from an oceanic Indian Ocean island[END_REF][START_REF] Munschy | Persistent organic pollutants in albacore tuna (Thunnus alalunga) from Reunion Island (Southwest Indian Ocean) and South Africa in relation to biological and trophic characteristics[END_REF]. The Western Indian Ocean (WIO) is characterized by asymmetric oceanic currents (North or South of 10°S latitude) and a seasonal effect strongly influenced by the monsoon regime. These specific water circulation regimes could, in turn, influence contaminant origins and transport in the WIO.

The main objectives of this study were to i) determine the contamination levels of selected legacy and emerging organic contaminants in four large pelagic top predator fish representing key species of the WIO ecosystem, ii) evaluate the influence of biological (size / age, sex) and trophic factors on organic contaminant bioaccumulation and iii) investigate differences in spatial contamination patterns (based on specific ratios of chemical tracers) at a regional scale that could be linked to different contamination sources. To the best of our knowledge, the data presented in this report are among the first obtained for various organic contaminant families in various large pelagic top predator fish species with such a large geographical distribution.

Materials and Methods

Sampling

Ethical approval was not required for this study, as all fish were collected as part of routine professional fishing practises.

The investigated areas (Fig. 1) in the WIO included the Seychelles exclusive economic zone (SEY), off the coasts of Somalia (SOM), the Mozambique Channel (MOZ) and an area located offshore between SEY and the Chagos archipelago (hereafter CHAG). SWO were only collected in SEY.

In total, 27 BET, 24 SKJ, 24 YFT and 18 SWO collected in 2013-2014 were analysed for organic contaminants. The white muscle of male individuals was analysed in all species from MOZ, SOM and CHAG, and the white muscle of both male and female individuals was analysed in all species collected from SEY. Although the fish were collected in different seasons and years, which could lead to variations in contaminant concentrations, the effect of collection time on results was not studied due to the limited number of samples available in each season.

Fish size (L in cm), corresponding to tuna fork length (from the tip of the snout to the fork of the tail) and swordfish lower jaw fork length (from the lower jaw to the fork of the tail), mass (W in kg) and sex (indeterminate, I; female, F; male, M) were recorded for each individual.

Individuals were selected to cover a large size range. Fulton's Condition Factor (K), as a proxy of relative fish fitness, was calculated as: K = W x 100,000) / L 3 , whereby L is fish size in cm and W is fish mass in kg.

Sub-samples of frozen fish of around 5 cm 3 were taken from the front dorsal white muscle (sampled under the dorsal spine on the left side) of each fish, and stored in amber glassware at -20°C prior to freeze-drying and further analysis of organic contaminants and total lipid content.

Sample treatment and analysis

Chemicals and sample analytical procedures for PCBs, OCPs and PFASs have been described previously [START_REF] Munschy | Persistent organic pollutants in albacore tuna (Thunnus alalunga) from Reunion Island (Southwest Indian Ocean) and South Africa in relation to biological and trophic characteristics[END_REF][START_REF] Munschy | Perfluoroalkyl substances (PFASs) in the marine environment: Spatial distribution and temporal profile shifts in shellfish from French coasts[END_REF]. Details on the chemicals used and additional information are provided in the Supplementary Material (SM).

Stable isotopes

Stable isotope analyses were performed according to [START_REF] Bodin | ASE extraction method for simultaneous carbon and nitrogen stable isotope analysis in soft tissues of aquatic organisms[END_REF]. Briefly, 1-2 mg of freeze-dried samples were ground and extracted with dichloromethane. Lipid-free samples were dried under a fume hood for 48h and packed in tin-capsules. Around 0.4 ± 0.08 mg of each lipid-free sample was then analyzed for stable isotopes using a Delta V Advantage isotope ratio mass spectrometer interfaced to a Flash EA 1112 elemental analyzer with a Conflo IV interface [START_REF] Sardenne | Methods of lipid-normalization for multi-tissue stable isotope analyses in tropical tuna[END_REF]. The results were reported in the δ unit notation and expressed per mil (‰) relative to international standards (Vienna-Pee Dee Belemnite for carbon and atmospheric N2 for nitrogen). Estimates using replicate measurements of internal laboratory standards (USGS-24, IAEA-CH6,-600 for carbon; IAEA-N2,-NO-3, -600 for nitrogen) gave an analytical variability of less than 0.15‰ for both δ 13 C and δ 15 N.

Total lipid content (TLC) analysis

An aliquot of each freeze-dried sample (0.5 g dw) used for organic contaminant analysis was extracted with a mixture of hexane / acetone (80:20) at 100 °C under 100 bars using accelerated solvent extraction (ASE) with Dionex ASE 200 (ASE, Dionex Corp., USA). The extracts were evaporated to dryness at 105°C for 12 hours to determine total lipid content (TLC) and expressed in % of wet weight (ww).

Organic contaminant analysis

Contaminant concentrations were calculated in pg g -1 or ng g -1 wet weight (ww), with a mean humidity percentage of 72% (calculated on all samples). Concentrations were converted into ng g -1 lipid weight (lw) using the TLC determined in each sample.

PCB and OCP analysis

Two to ten grams of the freeze-dried muscle samples were extracted with DCM using accelerated solvent extraction (ASE) with a Dionex ASE 300 (ASE, Dionex Corp., USA). Prior to extraction, 13 C12-labelled compounds (18 PCBs, including 12 dioxin-like (dl-), 6 indicator (i-) PCBs, 5 DDT isomers, aldrin, dieldrin, endrin, isodrin, α-, β-endosulfan and endosulfansulfate) were added to the sample for internal standard calibration and quantification using the isotopic dilution method. The extracts were successively purified using gel permeation chromatography, a silica and alumina column, and a two-dimensional HPLC system with two columns coupled in series. Four fractions were obtained (F1: non-coplanar PCBs and p,p'-DDE, F2: coplanar PCBs, F3: OCPs, F4: remaining OCPs, treated with concentrated sulphuric acid). The samples were analyzed for 34 PCBs, ranging from trichlorinated to decachlorinated congeners and including the 12 dl-PCBs and the 6 i-PCBs 5 DDTs (p,o,o,p,p, hereafter, the term "DDTs" refers to the sum of these 5 compounds), hexachlorobenzene (HCB) and hexachlorocyclohexanes (HCHs). In addition, aldrin, dieldrin, endrin, isodrin, mirex and endosulfans (α-, β-endosulfan isomers and endosulfan-sulfate) were analysed in tuna samples.

PCB and OCP analyses were performed by gas chromatography coupled to high resolution mass spectrometry (GC-HRMS) using a Hewlett-Packard 6890 gas chromatograph fitted with an SGE HT-8 capillary column (50 m × 0.22 mm × 0.2 μm) and coupled to a Micromass AutoSpec Ultima mass spectrometer. Compounds were quantified by isotopic dilution using the corresponding 13 C12-labelled isomers (except mirex, quantified using 13 C p,p'-DDE) and internal standard method was used to quantify samples. Prior to injection, a solution containing 13 C-labelled was added to the final purified extracts for signal correction.

PFAS analysis

PFAS analysis was conducted according to [START_REF] Munschy | Perfluoroalkyl substances (PFASs) in the marine environment: Spatial distribution and temporal profile shifts in shellfish from French coasts[END_REF]. One gram of a freeze-dried sample, to which an internal standard mixture of nine labelled compounds was added prior to agitation, was extracted using liquid-solid extraction with MeOH/KOH (0.01 M of KOH), purified onto two consecutive SPE cartridges (a WAX weak anion exchange stationary phase and an Envicarb charcoal stationary phase, [START_REF] Couderc | Occurrence of POPs and other persistent organic contaminants in the European eel (Anguilla anguilla) from the Loire estuary, France[END_REF], evaporated to dryness and reconstituted in 200 µL of a mixture of MeOH:H2O (50:50, v/v).

The following compounds were analysed, including five C4-to C10-perfluoroalkyl sulfonates (PFSAs) PFOS 13 C8 was added to the purified extracts before injection and used as an injection standard.

Analysis was performed using an Acquity ultra performance liquid chromatograph (UPLC®, Waters Corp.) coupled to a triple quadrupole mass spectrometer (Xevo® TQ-S micro, Waters

Corp.) interfaced with a Z-sprayTM (Waters Corp.) electrospray ionization source. UPLC separation was achieved using an Acquity UPLC BEH C18 reversed-phase column eluted with ammonium acetate in water (20 mM) (A) and methanol (B).

QA/QC

QA / QC procedures were followed during each sequence analysis, i.e. 10 samples for PCBs and OCPs and up to 20 samples for PFASs, to which one procedural blank and one quality control (as described in the SM QA/QC section) were added. In order to minimize external and cross-contaminations, all samples were processed in a clean laboratory (low dust and positive pressure) under a fume hood. QA / QC procedures included the analysis of certified material, in-house control samples, blanks and participation in interlaboratory comparison tests for the marine environment. LOQ values were determined for each target compound in each analyzed sample according to [START_REF] Wenzl | Guidance document on the estimation of LOD and LOQ for measurements in the field of contaminants in feed and food. UR 28099[END_REF], i.e., using a signal-to-noise ratio of 3 (peak-to-peak)

for the less intensive raw data signal (qualifier ion). Detailed information can be found in the SM (Table S1).

Statistical analysis

Statistical analyses were performed using StatSoft Statistica software v 7.1.

Correlations (e.g. between total lipid content and organic contaminant concentrations) were tested using simple linear regression coefficients. In view of the small sample size per group, data comparisons (biological and trophic parameters, organic contaminant concentrations and ratios) across fish groups were preferably performed using non-parametric tests (Mann-Whitney test for comparison of two independent samples, or one-way ANOVA Kruskal-Wallis's test), with a significance level (α) of 0.05. Results were considered to be significant only when both tests gave significant results. Statistical analyses were conducted on summed or individual compounds detected in at least 50% of the samples.

Results and discussion

Biometric parameters

Out of all the studied fish species (BET from MOZ excluded, see below), SKJ was the smallest in size, with a mean FL of 57.6 ± 7.6 cm. This species is classified as a small tuna (≤ 100 cm).

The largest fish was SWO (166.8 ± 28.6 cm), which is classified as one of the largest pelagic fish species [START_REF] Vanpouille | Atelier de travail sur les poissons à rostre. Commission thonière de l'Océan Indien. Etude de la croissance de l'espadon (Xiphias gladius)[END_REF]. BET (with the exception of those from MOZ) and YFT average FLs across all areas were > 100 cm (i.e. 131.0 ± 26.3 cm and 121.5 ± 28.8 cm, respectively); these species are considered as large tunas [START_REF] Sardenne | Trophic niches of sympatric tropical tuna in the Western Ehime University, Japan[END_REF]. All BET from MOZ were of indeterminate sex with lower fish size (52.9 ± 3.5 cm) and mass (3.4 ± 0.6 kg) versus other areas (Table 1). Age was estimated using growth curves from [START_REF] Dortel | An integrated Bayesian modeling approach for the growth of Indian Ocean yellowfin tuna[END_REF] for YFT, from [START_REF] Eveson | Estimating growth of tropical tunas in the Indian Ocean using tag-recapture data and otolith-based age estimates[END_REF] for BET and SKJ, and from [START_REF] Farley | Determination of swordfish growth and maturity relevant to the southwest Pacific stock[END_REF]Farley et al. ( , 2019) ) for SWO. Calculations gave estimated ages ranging from under 1 year to 10 years for tropical tuna species (mean values of 3.2 ± 2.5 years, 5.1 ± 3.2 years and 4.8 ± 3.1 years for SKJ, BET and YFT, respectively) and from 2 to 20 years (mean value of 6.5 ± 4.6 years) for SWO (Table 1). Although inter-species differences in fish sizes were significant (except between BET and YFT), only SKJ and SWO showed significant (p < 0.05) age differences (SKJ being younger than SWO). Regardless of species, no differences in fish size or age were found between male and female individuals sampled in SEY. Regarding tuna species, significant differences in fish size and age were observed across the sampling areas for BET and YFT, with smaller and younger individuals of both species in MOZ versus other areas.

TLC

TLCs were low and similar in the three tropical tuna species, ranging from 0.13 to 1.11 % ww (Table 1), with values similar to those reported in [START_REF] Sardenne | Trophic niches of sympatric tropical tuna in the Western Ehime University, Japan[END_REF], i.e. from 2.0 ± 1.0 % dw to 3.1 ± 3.5 % dw versus 1.3 ± 0.7 % dw to 1.8 ± 1.1 % dw in our study. SWO and SKJ showed the highest (9.4 ± 5.7% ww) and lowest (0.37 ± 0.19% ww) TLCs of all species, respectively. No TLC differences were identified between males and females of any species collected in SEY, or between tuna species across the study areas.

Stable isotopes

δ 15 N and δ 13 C values (means and standard deviations, Table 1) are shown in Figure 2 for the various fish species and sampling areas.

δ 13 C values were significantly higher in SWO than in tunas overall, although the difference between SWO and YFT was not significant (p = 0.09). SWO hence appears to rely on specific carbon sources, different to those of the three tropical tuna species. The only significant difference found across areas was between fish from MOZ (lower δ 13 C) and SEY. δ 15 N values were significantly higher in SWO and BET versus SKJ and YFT, in agreement with previouslyreported data [START_REF] Olson | Bioenergetics, trophic ecology, and niche separation of tunas[END_REF]. Globally, tunas from MOZ were characterized by lower δ 15 N, confirming the reports of [START_REF] Sardenne | Trophic niches of sympatric tropical tuna in the Western Ehime University, Japan[END_REF], while fish from the other studied areas had similar levels.

Organic contaminant levels and profiles

Organic contaminant levels in tropical tunas and swordfish

Concentrations of the various families of studied organic contaminants in tunas and swordfish are presented in Fig. 3 and detailed results are given in Table 2.

Globally, organic contaminant concentrations in tropical tuna species ranked in the order PFAS > OCP > PCB, while in SWO, they ranked in the order DDT > PCB = PFAS (Figure 3).

The variations in organic contaminant distribution across species could be explained by species biochemical composition and organic contaminant affinities. As a lipid-rich species, SWO accumulates lipophilic contaminants, such as PCBs and OCPs. Conversely, the studied tropical tunas are lean species with higher protein contents [START_REF] Sardenne | Trophic niches of sympatric tropical tuna in the Western Ehime University, Japan[END_REF] for which

PFASs have a greater affinity.

The effect of fish age on POP concentrations was investigated in each species and generally showed that contaminant concentrations were not significantly correlated to fish age. The only significant correlations (positive) were found for PFCAs in both SKJ and YFT and for PCBs in YFT. A lack of significantly higher contaminant levels with increasing size / age has already been reported previously and might reflect complex interactions between fish growth rate and contaminant accumulation rates [START_REF] Nakata | Growth-dependent and species-specific accumulation of polychlorinated biphenyls (PCBs) in tidal flat organisms collected from the Ariake Sea, Japan[END_REF][START_REF] Baptista | Organochlorine contaminants in different tissues from Platichthys flesus (Pisces, Pleuronectidea)[END_REF].

The effect of sex on contaminant concentrations was evaluated in each species collected in SEY and revealed no significant difference, except for PFCAs and mirex, which showed higher concentrations in YFT males. Previous studies have reported differences in contaminant levels between female and male mature fish related to a contaminant loss following female spawning [START_REF] Madenjian | Tissue turnover rates and isotopic trophic discrimination factors in the endothermic teleost, Pacific bluefin tuna (Thunnus orientalis)[END_REF]. The lack of gender influence on contaminant levels in tunas and swordfish in SEY is, however, expected owing to their reproductive strategy (i.e. multiple spawning, income breeders), which requires a high energy income from food intake and may, in turn, increase contaminant inputs [START_REF] Grande | Energy allocation strategy of skipjack tuna Katsuwonus pelamis during their reproductive cycle[END_REF][START_REF] Zudaire | Variations in the diet and stable isotope ratios during the ovarian development of female yellowfin tuna (Thunnus albacares) in the Western Indian Ocean[END_REF][START_REF] Poisson | Reproductive dynamics of swordfish (Xiphias gladius) in the southwestern Indian Ocean (Reunion Island). Part 1: oocyte development, sexual maturity and spawning[END_REF].

Most chlorinated contaminants were positively intercorrelated, with high correlation coefficients (0.56-0.91), whereas correlations between the various chlorinated and perfluorinated contaminants were weaker (0.24-0.46). These correlations indicate strong similarities in sources and bioaccumulation propensities of the various organochlorine families, in contrast to the perfluorinated ones. Indeed, the various studied organic contaminant families differ in terms of physico-chemical properties and behave differently in the environment and in fish.

PCBs and OCPs are lipophilic compounds, which bioaccumulate in the fat of living organisms, while PFASs have a stronger affinity with proteins, lipoproteins, and phospholipids [START_REF] Dassuncao | Phospholipid levels predict the tissue distribution of poly-and perfluoroalkyl substances in a marine mammal[END_REF][START_REF] Wen | Bioconcentration and tissue distribution of shorter and longer chain perfluoroalkyl acids (PFAAs) in zebrafish (Danio rerio): Effects of perfluorinated carbon chain length and zebrafish protein content[END_REF].

Out of all the studied species, SWO was the most-contaminated by chlorinated POPs, which is consistent with the higher trophic position and higher TLC of SWO. TLC showed high correlation with PCB and DDT concentrations (r =0.86 and 0.93, respectively) in SWO.

Conversely, and for similar reasons (low trophic position and low TLC), SKJ exhibited the lowest chlorinated POP concentrations. When normalized to TLC, PCBs in SWO were similar to those in tuna species, while DDTs remained significantly higher. These results suggest that the differences in DDT concentrations across species were due to parameters other than TLC and that PCB and DDT concentrations displayed varying bioaccumulation propensities and affinities with TLCs. Among tunas, BET was the most-contaminated species (significantly higher HCB and PFASs than in YFT and SKJ) but displayed similar PFAS levels to SWO.

When all species were considered, δ 15 N was significantly positively correlated with ∑ 18 PCB (r = 0.24, p < 0.05) and ∑ DDT (r = 0.52, p < 0.05) concentrations (in lw), but not with HCB or HCHs. However, the correlations were not significant when tunas alone were considered.

Similarly, PFAS concentrations (ww) showed a significant correlation with δ 15 N when all species were considered, and the correlation was significant in SKJ and YFT when tunas alone were considered.

PCB contamination levels and profiles

Among the 6 i-PCBs, congeners CB-180, CB-153 and CB-138 showed the highest detection frequencies (> 80%), with concentrations varying between 203.7-3117.3 (mean of 773.7) pg g - 1 ww in SWO and 2.6-153.5 (mean of 26.4) pg g -1 ww in tropical tunas. Among dl-PCBs, congeners CB-169, -167 and -189 were the most-frequently detected (> 80%). CB-28, CB-31, CB-81 and CB-114 were seldom detected (13%, 11%, 12% and 5% of samples, respectively).

On average, i-PCB concentrations were 8 times higher than DL-PCB concentrations (i-PCB / dl-PCB ratio of 8.4 ± 5.9), ranging from 34.7 to 599.1 (mean of 154.6) pg g -1 ww in SWO and from 0.2 to 29.8 (mean of 4.5) pg g -1 ww in tunas. No significant differences in PCB concentrations were detected in tunas across the studied areas (with the exception of BET from MOZ: these smaller / younger individuals showed significantly lower contamination levels).

i-PCB profiles showed a predominance of hexa-and hepta-chlorinated congeners CB-153 > CB-138 > CB-180. These highly-bioaccumulable congeners are recalcitrant to degradation due to their chlorine atoms in positions 2,4,5 in one or both rings and often prevail in fish, including tunas [START_REF] Gómara | Levels and trends of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (PCBs) in Spanish commercial fish and shellfish products, 1995-2003[END_REF][START_REF] Corsolini | HCB, p,p '-DDE and PCB ontogenetic transfer and magnification in bluefin tuna (Thunnus thynnus) from the Mediterranean Sea[END_REF][START_REF] Vizzini | Comparison of stable isotope composition and inorganic and organic contaminant levels in wild and farmed bluefin tuna, Thunnus thynnus, in the Mediterranean Sea[END_REF][START_REF] Munschy | Persistent organic pollutants in albacore tuna (Thunnus alalunga) from Reunion Island (Southwest Indian Ocean) and South Africa in relation to biological and trophic characteristics[END_REF]. dl-PCB profiles showed predominant CB-118, followed by CB-105, CB-156 and CB-167. Similar profiles have already been reported in marine, lake and river fish from various regions around the globe [START_REF] Ueno | Global pollution monitoring of polychlorinated dibenzo-p-dioxins (PCDDs), furans (PCDFs) and coplanar polychlorinated biphenyls (coplanar PCBs) using skipjack tuna as bioindicator[END_REF][START_REF] Bhavsar | Composition of dioxin-like PCBs in fish: an application for risk assessment[END_REF][START_REF] Munschy | Persistent organic pollutants in albacore tuna (Thunnus alalunga) from Reunion Island (Southwest Indian Ocean) and South Africa in relation to biological and trophic characteristics[END_REF].

Globally, all congeners showed significant correlations, suggesting similar sources and bioaccumulation in fish.

PCB profiles were examined in terms of number of chlorine atoms and structure activity groups (SAG I to V). SAG I, II and most SAG III congeners are non-metabolizable in fish, while SAG IV and V have been shown to metabolize [START_REF] Boon | Concentration-dependent changes of PCB patterns in fisheating mammals: Structural evidence for induction of cytochrome P450[END_REF]. Although PCB biotransformation in fish is expected to be low in comparison to mammals, several studies have shown that fish were able to metabolize PCBs (Buckman et al., 2006 and references therein). This process may be enhanced in warmer climates such as those encountered in tropical areas [START_REF] Buckman | Role of temperature and enzyme induction in the biotransformation of polychlorinated biphenyls and bioformation of hydroxylated polychlorinated biphenyls by rainbow trout (Oncorhynchus mykiss)[END_REF]. Among the various studied species, the SWO PCB profiles differed most, with significantly higher (17 ± 5%) and lower (29 ± 2%) contributions of 5 and 7 chlorine atom congeners respectively versus tunas (9 ± 8% and 39 ± 10%, respectively).

SWO profiles were also characterized by lower SAG I and higher SAG IV contributions (although SAG IV was not significantly different in SWO and BET).

OCP concentrations and profiles

DDTs were the most-detected OCPs (91-100% depending on the isomer), together with mirex (detected in 100% of tuna samples). DDT concentrations ranged from 244.4 to 16836.1 pg g -1 ww (mean of 7269.1 pg g -1 ww) in SWO and 13.9 to 777 pg g -1 ww (mean of 112.0 pg g -1 ww) in tunas. Mirex was in the 0.4-34.1 pg g -1 ww range (mean of 3.7 pg g -1 ww) in tunas (not analysed in SWO). Among HCHs, ß-HCH was the most-prevalent isomer (84% of samples)

and displayed the highest levels, at concentrations of 1.6-101.1 pg g -1 ww (mean of 58.0 pg g -1 ww) in SWO and 0.32-19.7 pg g -1 ww (mean of 2.5 pg g -1 ww) in tunas. α-HCH was quantified in 25% of samples. δ-and γ-HCH isomers were seldom detected in tunas (8% and 4% of samples, not analysed in SWO). HCB was detected in 65% of samples, at levels ranging from 37.3 to 533.2 pg g -1 ww in SWO (mean of 314.0 pg g -1 ww) and 4.1-37.2 pg g -1 ww in tunas (mean of 10.1 pg g -1 ww). Dieldrin (not analysed in SWO) was identified in 59% of tuna samples at concentrations ranging from 1.3 to 20.7 pg g -1 ww (4.3 pg g -1 ww mean value).

Aldrin and endrin were detected in 30% and 16% of tuna samples, at concentrations of 0.2-3.3 pg g -1 ww (mean 0.9 pg g -1 ww) and 0.3-2.1 pg g -1 ww (mean 0.8 pg g -1 ww), respectively.

Isodrin and endosulfans were below LOQs in all tuna samples.

Among DDT isomers, p,p'-DDE exhibited by far the highest contributions in all species (71 ± 9%), followed by p,p'-DDT (16 ± 7%), p,p'-DDD (7 ± 6%), o,p'-DDT (5 ± 3%) and o,p'-DDD (2 ± 2 %). In view of its longer half-life (7 years in fish, Binelli and Provini, 2003a) and higher accumulation propensity, p,p'-DDE is generally identified as a predominant DDT isomer in fish, while p,p'-DDD ranks second [START_REF] Covaci | Levels and distribution of organochlorine pesticides, polychlorinated biphenyls and polybrominated diphenyl ethers in sediments and biota from the Danube Delta, Romania[END_REF][START_REF] Jürgens | PCB and organochlorine pesticide burden in eels in the lower Thames River (UK)[END_REF]. In our samples, the high p,p'-DDT abundance (second-most abundant isomer) suggests potential inputs of technical DDT to this oceanic region from surrounding countries. Indeed, several publications have reported the continued use of DDT for various purposes in Southern Asia, Africa, India and China [START_REF] Chakraborty | Selected organochlorine pesticides in the atmosphere of major Indian cities: levels, regional versus local variations, and sources[END_REF][START_REF] Cheng | Characterization of HCHs and DDTs in urban dustfall and prediction of soil burden in a metropolis-Beijing, China[END_REF]Gioa et al., 2012;[START_REF] Bogdal | Worldwide distribution of persistent organic pollutants in air, including results of air monitoring by passive air sampling in five continents[END_REF][START_REF] Ali | Organochlorine pesticides (OCPs) in South Asian region: a review[END_REF][START_REF] Bouwman | Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment[END_REF]. In particular, various nations in South-Eastern Africa were still listed as using DDT against malaria in [START_REF] Focardi | Levels of mercury and polychlorobiphenyls in commercial food in Siena Province (Tuscany, Italy) in the period 2001-2010[END_REF]-2014[START_REF] Van Den Berg | Global trends in the production and use of DDT for control of malaria and other vector-borne diseases[END_REF] and DDT was reported being sprayed in the Northeast part of South Africa [START_REF] Bouwman | Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment[END_REF].

Similar contamination profiles as those found in our study have also been encountered in fish from coastal areas of Southern China and explained by DDT use in antifouling paints containing p,p'-DDT > o,p'-DDT > p,p'-DDE [START_REF] Guo | Levels and bioaccumulation of organochlorine pesticides (OCPs) and polybrominated diphenyl ethers (PBDEs) in fishes from the Pearl River estuary and Daya Bay, South China[END_REF].

Organochlorine contaminant specific ratios

Various ratios using DDT isomers and PCB concentrations can be used to distinguish contamination sources in fish. The o,p'-DDT / p,p'-DDT concentration ratio, which is used to track the origin of DDT, was lower in SWO and BET (0.23 ± 0.16 and 0.27 ± 0.11, respectively) versus YFT and SKJ (0.47 ± 0.18 and 0.56 ± 0.31, respectively) (Fig. 4). This ratio is reported to be in the 0.2-0.3 range in technical DDT [START_REF] Kalantzi | The global distribution of organochlorine pesticides in butter[END_REF], whereas a ratio above 0.34 is observed when DDT originates from dicofol acaricide impurities (Suarez et al., 2013), which is used mainly in Asia [START_REF] Li | Global inventory, long-range transport and environmental distribution of Dicofol[END_REF]. Our results suggest that SWO and BET sources of DDT contamination are both similar and closer to technical DDT than those of YFT and SKJ. In addition, SWO and BET exhibited significantly higher ∑ DDT / ∑ i-PCB concentration ratios (12.2 ± 3.3 and 9.1 ± 4.3, respectively) than SKJ and YFT (4.0 ± 2.1 and 4.6 ± 1.9, respectively) (Fig. 4), indicating SWO and BET exposure to different sources versus SKJ and YFT. This ratio is commonly used to distinguish agricultural (DDTs) from industrial and urban (PCBs) sources and indicates that tropical tunas and swordfish from the WIO were globally more exposed to DDTs over PCBs, reflecting the past or recent use of DDT by several countries in the Southern Hemisphere for vector-borne disease control purposes [START_REF] Kalantzi | The global distribution of organochlorine pesticides in butter[END_REF][START_REF] Chakraborty | Selected organochlorine pesticides in the atmosphere of major Indian cities: levels, regional versus local variations, and sources[END_REF][START_REF] Cheng | Characterization of HCHs and DDTs in urban dustfall and prediction of soil burden in a metropolis-Beijing, China[END_REF][START_REF] Bogdal | Worldwide distribution of persistent organic pollutants in air, including results of air monitoring by passive air sampling in five continents[END_REF][START_REF] Ali | Organochlorine pesticides (OCPs) in South Asian region: a review[END_REF][START_REF] Bouwman | Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment[END_REF]. Hence, although no significant differences were found in δ 13 C values across the three tuna species, both o,p'-DDT / p,p'-DDT and DDT / PCB concentration ratios suggested that BET was exposed to similar trophic sources as SWO. Indeed, BET and SWO both feed on deep water mesopelagic cephalopods and fish, while YFT feed on surface and subsurface (< 100 m) epipelagic species [START_REF] Ménard | Isotopic evidence of distinct feeding ecologies and movement patterns in two migratory predators (yellowfin tuna and swordfish) of the western Indian Ocean[END_REF][START_REF] Potier | Forage fauna in the diet of three large pelagic fishes (lancetfish, swordfish and yellowfin tuna) in the western equatorial Indian Ocean[END_REF][START_REF] Olson | Bioenergetics, trophic ecology, and niche separation of tunas[END_REF]. No statistically significant differences in o,p'-DDT / p,p'-DDT or ∑ DDT / ∑ i-PCB ratios were observed across tropical tuna sampling areas.

The (p,p'-DDE + p,p'-DDD) / ∑ DDTs ratio, which can be used to distinguish new and old DDT sources, was similar in all species (0.77 ± 0.08, on average), indicating that all fish were exposed to old DDT inputs (Suarez et al., 2013). This ratio was significantly lower in tunas from MOZ (0.70 ± 0.08) than in those from the other sampling areas (0.79 ± 0.07, on average) (Fig. 4). These results suggest that tunas from MOZ have been exposed to different DDT sources versus other areas, coinciding with the reported use of DDT in various Southern

African countries [START_REF] Bouwman | Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment[END_REF][START_REF] Van Den Berg | Global trends in the production and use of DDT for control of malaria and other vector-borne diseases[END_REF]. They are also consistent with the recent work of [START_REF] Chassot | The key role of the Northern Mozambique Channel for Indian Ocean tropical tuna fisheries[END_REF], showing an extended residency time of tropical tunas in the northern Mozambique Channel, which would be reflected in their contamination profiles.

Among the analysed PFASs, PFUnDA, PFTrDA, PFDoDA, PFOS, PFDA, PFTeDA and PFNA were detected in 100%, 93%, 90%, 88%, 85%, 74% and 54% of samples, respectively. Most of these PFASs were significantly inter-correlated, indicating similar sources and bioaccumulation (i.e. accumulation, elimination) across all species. PFNA showed the lowest correlations (no significant correlation with PFOS and PFDoDA and lower significant correlation coefficients with other PFASs), underlining a singular behaviour and/or source for this compound. In addition, PFOA and PFHxA were seldom detected (12% and 7% of samples, respectively) and PFHpA was below LOQ in all samples. Consequently, these 3

PFASs were not considered further in data evaluation. PFCA individual mean concentrations were between 12.4 ± 8.6 pg g -1 ww (PFTeDA) and 95.4 ± 61.9 pg g -1 ww (PFUnDA), while PFOS was in the 4.5-85.9 pg g -1 ww range (mean concentration of 37.9 ± 17.3 pg g -1 ww). ∑ PFCA concentrations were, on average, 6 times higher than PFOS concentrations in all samples. Interestingly, the ∑ PFCA / PFOS ratios were significantly higher in SEY and CHAG (6.9 ± 2.9 and 5.7 ± 1.3, respectively) than in MOZ and SOM (4.1 ± 1.2 and 4.5 ± 1.7, respectively) which are situated the closest to African continental coasts. Oceans are recognized as the main reservoirs of PFASs [START_REF] Johansson | Global transport of perfluoroalkyl acids via sea spray aerosol[END_REF] and PFCAs have been

shown to accumulate in central ocean gyres including the Indian Ocean [START_REF] Gonzalez-Gaya | Perfluoroalkylated substances in the global tropical and subtropical surface oceans[END_REF]. In addition, the particular regional monsoon-driven circulation pattern occurring in the WIO [START_REF] Olson | Bioenergetics, trophic ecology, and niche separation of tunas[END_REF] could have a major influence upon the spatial distribution of PFCAs, and, in turn, upon swordfish and tuna exposure in open waters. SWO and BET showed significantly higher PFOS and ∑ PFCA concentrations than SKJ and YFT, in line with their higher trophic position and with the higher biomagnification propensity of PFASs of higher carbon-chain length in trophic webs [START_REF] Conder | Are PFCAs bioaccumulative? A critical review and comparison with regulatory lipophilic compounds[END_REF][START_REF] Loi | Trophic magnification of poly-and perfluorinated compounds in a subtropical food web[END_REF]. Individually, higher correlations were found for PFDA (r = 0.67) and PFUnDA (r = 0.58). The ∑ PFCA / PFOS concentration ratios showed significant differences across species (all sampling areas considered), with SKJ exhibiting significantly lower values (3.8 ± 1.4) than the 3 other species (6.4 ± 2.5).

The majority of PFASs identified in samples were long-chain PFCAs (C ≥ 8), consistent with the higher bioaccumulative abilities of these compounds versus their short-chain counterparts [START_REF] Martin | Bioconcentration and tissue distribution of perfluorinated acids in rainbow trout (Oncorhynchus mykiss)[END_REF][START_REF] Kelly | Perfluoroalkyl contaminants in an Arctic marine food web: trophic magnification and wildlife exposure[END_REF][START_REF] Pan | Bioaccumulation and risk assessment of per-and polyfluoroalkyl substances in wild freshwater fish from rivers in the Pearl River Delta region, South China[END_REF]. In marine biota, the atmospheric degradation of neutral precursors is the main source of PFCAs [START_REF] Ellis | Degradation of fluorotelomer alcohols: A likely atmospheric source of perfluorinated carboxylic acids[END_REF][START_REF] Li | Length-specific occurrence and profile of perfluoroalkyl acids (PFAAs) in animal protein feeds[END_REF]. PFUnDA and other long-chain perfluorocarboxylates could also originate from the degradation of 10:2 FTOH [START_REF] Hart | Skipjack tuna as a bioindicator of contamination by perfluorinated compounds in the oceans[END_REF]. More specifically, PFCA profiles showed a predominance of odd-chain length compounds (PFUnDA and PFTrDA) versus even-chain (PFDA, PFDoA and PFTeDA), which has been previously observed in fish and partially explained by the degradation of fluorotelomer alcohols (FTOHs) [START_REF] Ellis | Degradation of fluorotelomer alcohols: A likely atmospheric source of perfluorinated carboxylic acids[END_REF]Martin et al., 2004). However, as FTOHs degrade in both odd and even numbered PFCAs, this alone does not explain the predominance of odd-numbered PFCAs. Interestingly, odd-numbered PFCAs, particularly PFUnDA, were also identified as the predominant components in human serum samples from various East Asian countries [START_REF] Harada | Odd-numbered perfluorocarboxylates predominate over perfluorooctanoic acid in serum samples from Japan, Korea and Vietnam[END_REF], thought to originate from the industrial production of fluoropolymers (Surflon S-111). Indeed, odd-chain PFCAs such as PFUnDA and PFTrDA have been reported as impurities in PFNA produced from the oxidation of fluorotelomer olefins [START_REF] Prevedouros | Sources, fate and transport of perfluorocarboxylates[END_REF][START_REF] Rotander | Increasing levels of long-chain perfluorocarboxylic acids (PFCAs) in Arctic and North Atlantic marine mammals, 1984-2009[END_REF]. PFUnDA has been identified as the predominant PFCA in various fish species from East Asia [START_REF] Hart | Skipjack tuna as a bioindicator of contamination by perfluorinated compounds in the oceans[END_REF][START_REF] Loi | Trophic magnification of poly-and perfluorinated compounds in a subtropical food web[END_REF]. Neutral precursors such as 10:2 perfluorodecanol (FTOH) could also be at the origin of PFUnDA in marine biota, together with PFDA [START_REF] Ellis | Degradation of fluorotelomer alcohols: A likely atmospheric source of perfluorinated carboxylic acids[END_REF][START_REF] Hart | Skipjack tuna as a bioindicator of contamination by perfluorinated compounds in the oceans[END_REF]. PFUnDA was found in higher concentrations than PFDA, due to its higher propensity to bioaccumulate and biomagnify in food chains [START_REF] Loi | Trophic magnification of poly-and perfluorinated compounds in a subtropical food web[END_REF][START_REF] Pan | Species-specific profiles and risk assessment of perfluoroalkyl substances in coral reef fishes from the South China Sea[END_REF].

One remarkable finding was the PFUnDA / PFDA ratio, which showed significantly lower values in SWO (3.2 ± 0.8) than in tunas (5.3 ± 1.1). This finding could be the result of complex interrelated effects between the biochemical composition of muscle in the various studied species and different PFCA binding affinities [START_REF] Verreault | Perfluorinated alkyl substances in plasma, liver, brain, and eggs of glaucous gulls (Larus hyperboreus) from the Norwegian Arctic[END_REF].

PCB, DDT and PFAS levels in tropical tunas and swordfish versus other areas worldwide

A comparison of the levels of PCBs and DDTs (the two most-reported POP families in tunas and swordfish) determined in this study versus those reported in the literature in various top predator species collected from around the world is presented in Table 3. By far the most widely-studied species is BFT, with the majority of studies pertaining to the Mediterranean Sea. Variations in sampling times, size/age and sex of fish studied in the literature make comparisons difficult. In addition, some of the available data are up to 20 years old and does not therefore take into account the global decrease in environmental PCB and OCP levels brought about by effective regulations. However, the concentrations determined in our study are globally low in comparison to those reported in other oceans, in particular in the Northern Hemisphere, which is subject to higher inputs from industrialized and urban areas [START_REF] Aguilar | Geographical and temporal variation in levels of organochlorine contaminant s in marine mammals[END_REF]Tanabe and Ramu, 2012). Indeed, distance from continental industrial and urban sources is the main factor influencing POP levels in oceans (Gioa et al., 2012) ng g -1 lw, Table 3). According to the authors, PCB, DDT, HCH and HCB concentrations in SKJ liver collected off the Seychelles were the lowest out of all the studied areas, including the North Pacific (mainly), Indian Ocean (off-Seychelles and the Bay of Bengal) and Atlantic

Ocean (off-Brazil) [START_REF] Ueno | Global pollution monitoring of PCBs and organochlorine pesticides using skipjack tuna as a bioindicator[END_REF]. ∑ 7 PCBs were in the 21.6-226.7 ng g -1 lw range in YFT collected in 2007 from Reunion island [START_REF] Torres | Organohalogen compounds in yellowfin tuna (Thunnus albacares) from the Western Indian Ocean[END_REF], i.e. higher than that determined in our samples (8.0 ± 8.3 ng g -1 lw). PCB levels determined in our study were comparable to those found in remote areas. For example, [START_REF] Lana | Fingerprint of persistent organic pollutants in tissues of Antarctic notothenioid fish[END_REF] reported PCB concentrations of 11.1-63.1 ng g -1 lw in demersal Nototheniidae fish from the South Shetland Islands (Antarctica), i.e. close to the mean concentrations determined in our samples (5.3 ± 6.5 ng g -1 lw in BET to 9.3 ± 12.8 ng g -1 lw in SWO). Dl-PCB concentrations in top predators from WIO are also comparable to those reported in various freshwater fish from Africa (for a review, see Ssebugere et al., 2019).

With regards to DDTs, the levels (in lw) determined in this study are comparable to those reported in YFT from WIO [START_REF] Torres | Organohalogen compounds in yellowfin tuna (Thunnus albacares) from the Western Indian Ocean[END_REF] and in albacore tuna (Thunnus alalunga) from Reunion island and South East Atlantic Ocean [START_REF] Munschy | Persistent organic pollutants in albacore tuna (Thunnus alalunga) from Reunion Island (Southwest Indian Ocean) and South Africa in relation to biological and trophic characteristics[END_REF] and in a similar range in SWO to those reported in YFT from Brazil (South West Atlantic Ocean) [START_REF] Pizzochero | Persistent organic pollutants in muscle of yellowfin tuna (Thunnnus albacares) from the Atlantic Ocean[END_REF]. Higher DDT levels were reported in YFT from Australia-New Zealand (South West Pacific Ocean) [START_REF] Endo | Relationship between mercury, organochlorine compounds and stable isotope ratios of carbon and nitrogen in yellowfin tuna (Thunnus albacares) taken from different regions of the Pacific and Indian Oceans[END_REF]. DDT levels reported in various species from the Northern Hemisphere (bearing in mind that some data were collected 20 years ago) were generally higher than those determined in our study, but the differences between hemispheres were lower than for PCBs.

Less data are available for PFASs and liver is the most widely-studied fish tissue. [START_REF] Hart | Skipjack tuna as a bioindicator of contamination by perfluorinated compounds in the oceans[END_REF] reported PFAS concentrations in the liver of SKJ collected from various locations in the Pacific and Indian Oceans. The lowest PFAS levels were determined in samples from openocean sites, with Mauritius in the Indian Ocean demonstrating the lowest concentrations (1.04 ng g -1 ww), while samples collected off Japan were 10 to 80 times higher. PFOS and PFUnDA were the most-detected compounds (100%) and exhibited the highest concentrations, while PFNA was the least-detected compound (57%), mostly below LOQs. PFOS, PFDA and PFNA below limits of detection were reported in the muscle of YFT from the Indian Ocean [START_REF] Zabaleta | Simultaneous determination of perfluorinated compounds and their potential precursors in mussel tissue and fish muscle tissue and liver samples by liquid chromatography-electrospray-tandem mass spectrometry[END_REF] and in the muscle and liver of SWO from the Mediterranean Sea [START_REF] Corsolini | Polybrominated diphenyl ethers, perfluorinated compounds and chlorinated pesticides in swordfish (Xiphias gladius) from the Mediterranean Sea[END_REF]. PFOS ranged from 21 to 87 (mean of 47) ng g -1 ww in the liver of Atlantic bluefin tuna (Thunnus thynnus) from the Italian coast, while PFOA and PFHxS were < LOQs (Kannan et al., 2002). PFOS concentrations were between < LOQ and 13 ng g -1 ww in SWO livers from the same area. In Atlantic bluefin tuna and SWO consumed in France (no reported geographical origin), ∑ PFASs were in the 0.86-1.38 ng g -1 ww and 0.28-1.11 ng g -1 ww ranges, respectively [START_REF] Yamada | Perfluoroalkyl acid contamination and polyunsaturated fatty acid composition of French freshwater and marine fishes[END_REF].

POP levels versus environmental and human health regulations

The ubiquity, persistence, accumulation in food chains and toxicity of POPs has raised concern as to their harmfulness to humans. Food and, in particular, seafood, is one of the major routes of human exposure to these pollutants [START_REF] Törnkvist | PCDD/F, PCB, PBDE, HBCD and chlorinated pesticides in a Swedish market basket from 2005 -Levels and dietary intake estimations[END_REF]Shin et al., 2015).

Maximum residue levels in foodstuffs have therefore been established for selected POPs. The European Commission has introduced maximum levels for PCBs (dl-PCBs and i-PCBs) in fishery products (EU, 2011). Other countries, such as the USA, Canada, Japan and Australia, have also defined maximum or guideline values. Environmental quality standards (EQSs) have been established within the EU Water Framework Directive (WFD) for certain priority substances, in the aim of protecting humans and wildlife. EQSs for HCB, PFOS and dl-PCBs are defined according to human health considerations (contaminated fish consumption).

Globally, the levels of all studied POPs were far below admissible levels (several orders of magnitude) in the white muscle of the studied fish species; their consumption is therefore of no risk to humans. i-PCBs were far below (24 to 29000 times, mean of 5200 times) the maximum levels set by the European Commission for non dl-PCBs in foodstuffs (EU, 2011), i.e. 75 ng g -1 ww in muscle, hence below the maximum values set by the governments of Japan (500 ng g -1 ww), Australia (500 ng g -1 ww) and the US (2000 ng g -1 ww) for total PCBs [START_REF] Vizzini | Comparison of stable isotope composition and inorganic and organic contaminant levels in wild and farmed bluefin tuna, Thunnus thynnus, in the Mediterranean Sea[END_REF]. dl-PCB concentrations calculated in toxic equivalents (TEQs) using the toxic equivalent factors (TEFs) set by the World Health Organization in 2005 (Van den [START_REF] Van Den Berg | The 2005 World Health Organization reevaluation of human and mammalian toxic equivalency factors for dioxins and dioxin-like compounds[END_REF] showed average levels of 0.016 ± 0.011 pg TEQ g -1 ww in tunas and 0.375 ± 0.314 pg TEQ g -1 ww in SWO, i.e. far below the maximum level of 3 pg TEQ g -1 ww set by the European Commission for dl-PCBs in foodstuffs (EU, 2011). They were also below the guideline value of 0.79 pg TEQ g -1 ww set by Canada to protect wildlife consumers of aquatic biota (CCME, 2001). Non-ortho PCBs and, in particular, CB-126 (78% of dl-PCB TEQs) contributed the most to TEQ values. Lindane and other HCH concentrations were below EU and China maximum limits. HCB concentrations were far below (20 to 7000 times) the environmental quality standards (EQS) of 10 µg kg -1 set to protect human health. Regarding DDTs, the maximum levels found in our study were below the value of 3000 ng g -1 ww and 1000 ng g -1 ww, respectively set by Japan and Australia for p,p'-DDE [START_REF] Vizzini | Comparison of stable isotope composition and inorganic and organic contaminant levels in wild and farmed bluefin tuna, Thunnus thynnus, in the Mediterranean Sea[END_REF]. DDT concentrations were below the maximum admissible concentrations set by the EU (50 ng g -1 ww, Binelli and Provini, 2003b) for human consumption. Three SWO samples (2 females and one male at 15.6, 16.8 and 16.6 ng g -1 ww) exceeded the maximum levels of 14 ng g -1 ww set by Canada (CCME, 1999). PFOS concentrations were below the EQS of 9.1 ng g -1 ww in biota in all samples.

In addition, PCB levels were compared to OSPAR assessment criteria, i.e., EACs (Environmental Assessment Criterias) and BACs (Background Assessment Criterias) defined for congeners CB-28, -52, -101, -118, -138, -153 and -180. All PCB concentrations were below BACs in tunas, but exceeded BACs for CB-101, -118, -138, 153 and -180 in 44%, 22%, 55%, 72% and 50% of SWO samples. EACs were never exceeded.

Conclusions

The results of this study emphasize the widespread contamination of various top predator fish species from the WIO by legacy POPs and organic contaminants of emerging concern, although at low levels in comparison to oceans worldwide, representing no risk to human health in reference to current regulations. DDTs and PFASs were identified as the predominant families of studied organic contaminants in SWO and tunas, respectively.

Organic contaminant accumulation profiles were influenced by multiple factors (both biological and ecological) and were shown to be useful tracers for differentiating fish populations exploiting different trophic habitats when used in combination with trophic ecology parameters (C and N stable isotopes). SWO showed the highest organic contamination levels, in relation to their higher lipid content and trophic position, while SKJ was the least-contaminated species. SWO and BET exhibited the most organic contaminant profile similarities, due to their common feeding habitat in deeper layers versus SKJ and YFT. More differences in contaminant profiles were found across species than areas. However, tunas from the Mozambique Channel showed unique DDT profiles, confirming that tunas tend to reside longer in this area and possibly reflecting the use of DDT by various SE African countries. The PFCA / PFOS concentration ratio also proved to be a useful chemical tracer of fish populations from more-oceanic regions. Our results show that organic contaminant signatures are discriminant in long-lived migratory species. Table 1 Biometric parameters (size in cm, mass in kg), condition index (K), TLC (% ww) and stable isotope signatures Major POP concentrations (pg g -1 ww) in the white muscle of tropical tunas and swordfish collected in the western Indian Ocean in 2013-2014. MOZ = Mozambique Channel, SOM = off the Somalian coast, SEY = Seychelles, CHAG = Chagos. YFT = yellowfin tuna (Thunnus albacares), SKJ = skipjack tuna (Katsuwonus pelamis), BET = bigeye tuna (Thunnus obesus), SWO = swordfish (Xiphias gladius). M = male, F = female, I = immature.

CRediT author statement

Species

Fig. 1 .

 1 Fig. 1. Map of tropical tuna and swordfish fishing positions in the western Indian Ocean in 2013-2014. Dot size is proportional to the number of individuals (for details, see Table 1). MOZ = Mozambique Channel, SOM = off the Somalian coast, SEY = Seychelles, CHAG = Chagos. YFT = yellowfin tuna (Thunnus albacares), SKJ = skipjack tuna (Katsuwonus pelamis), BET = bigeye tuna (Thunnus obesus), SWO = swordfish (Xiphias gladius).

Fig. 2 .

 2 Fig. 2. Stable isotope signatures (δ 13 C and δ 15 N in ‰) in SWO (swordfish), BET (bigeye tuna), SKJ (skipjack tuna) and YFT (yellowfin tuna) collected in the western Indian Ocean in 2013-2014 and analysed for organic contaminants according to species and sampling areas. CHAG, MOZ, SOM and SEY are for Chagos, Mozambique Channel, off the Somalian coast and Seychelles, respectively.

Fig. 3 .Fig. 4 .

 34 Fig. 3. PCB (∑ 18 PCBs), DDT (∑ 5 isomers) and PFAS (∑ PFSAs + PFCAs) concentrations

  (δ 13 C and δ 15 N in ‰) of fish analysed for POPs. MOZ = Mozambique Channel, SOM = off the Somalian coast, SEY = Seychelles, CHAG = Chagos. YFT = yellowfin tuna (Thunnus albacares), SKJ = skipjack tuna (Katsuwonus pelamis), BET = bigeye tuna (Thunnus obesus), SWO = swordfish (Xiphias gladius). M = male, F = female, I = immature.

  Ocean inferred by stable isotopes and neutral fatty acids. Progress inOceanography, 146, 75- 88. dx.doi.org/10.1016/j.pocean.2016.06.001. Shin, E.s., Nguyen, K.H., Kim, J., Kim, C.i., Chang, Y.S., 2015. Progressive risk assessment of polychlorinated biphenyls through a Total Diet Study in the Korean population. Environmental Pollution 207, 403-412. dx.doi.org/10.1016/j.envpol.2015.08.051. Sioen, I., De Henauw, S., Ven Camp, J., Volatier, J.L., Leblanc, J.C., 2009. Comparison of the nutritional-toxicological conflict related to seafood consumption in different regions worldwide. Regulatory Toxicology and Pharmacology 55, 219-228. https://doi.org/10.1016/j.yrtph.2009.07.003. Sprague, M., Dick, J.R., Medina, A., Tocher, D.R., Bell, J.G., Mourente, G., 2012. Lipid and fatty acid composition, and persistent organic pollutant levels in tissues of migrating Atlantic bluefin tuna

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Table 2

 2

	Species Location Sex n	Size (cm)	Age (year)	Mass (kg)	K	TLC %	δ 13 C ‰	δ 15 N ‰
	BET	All	All	27	116.5 ± 38.9 (47.1-166.5)	5.1 ± 3.2 (0.8-10.0)	48.5 ± 34.0 (2.6-108.7)	2.3 ± 0.2 (2.1-2.8)	0.45 ± 0.17 (0.14-0.88)	-17.2 ± 0.3 (-17.9 --16.7)	13.1 ± 0.8 (11.3-14.0)
	BET	CHAG	M	6	144.7 ± 15.6 (115.6-160.0)	7.8 ± 2.4 (3.7-10.0)	71.6 ± 20.5 35.5-94.7)	2.3 ± 0.1 (2.2-2.5)	0.37 ± 0.13 (0.25-0.56)	-17.2 ± 0.4 (-17.9 --16.8)	13.5 ± 0.3 (13.1-13.9)
		MOZ	I	5	52.9 ± 3.5 (47.1-55.5)	1.2 ± 0.2 (0.8-1.3)	3.4 ± 0.6 (2.6-3.9)	2.3 ± 0.1 (2.1-2.5)	0.42 ± 0.11 (0.32-0.59)	-17.5 ± 0.1 (-17.5 --17.4)	11.6 ± 0.3 (11.3-11.8)
		SEY	M	5	116.6 ± 34.3 (82.0-166.5)	4.7 ± 3.2 (2.2-10.0)	46.5 ± 39.4 (12.0-108.7)	2.4 ± 0.3 (2.2-2.8)	0.43 ± 0.16 (0.34-0.71)	-17.3 ± 0.3 (-17.6 --17.0)	13.0 ± 0.6 (12.5-13.5)
		SEY	F	5	114.5 ± 25.8 (85.5-137.5)	4.1 ± 1.6 (2.4-5.7)	40.9 ± 24.1 (14.3-61.4)	2.4 ± 0.1 (2.3-2.6)	0.55 ± 0.22 (0.34-0.88)	-17.1 ± 0.1 (-17.2 --17.0)	13.2 ± 0.3 (12.9-13.6)
		SOM	M	6	142.9 ± 17.5 (114.1-160.8)	7.1 ± 2.6 (3.6-10.0)	71.1 ± 22.7 (36.1-96.0)	2.4 ± 0.2 (2.2-2.7)	0.47 ± 0.23 (0.14-0.81)	-16.9 ± 0.2 (-17.1 --16.7)	13.4 ± 0.6 (12.5-14.0)
	SKJ	All	All	24	57.6 ± 7.6 (44.3-71.6)	3.2 ± 2.5 (0.7-10.0)	4.7 ± 2.0 (1.8-8.5)	2.3 ± 0.2 (1.9-2.7)	0.37 ± 0.19 (0.17-0.85)	-17.0 ± 0.3 (-17.5 --16.4)	11.3 ± 0.8 (9.8-12.6)
	SKJ	CHAG	M	4	64.6 ± 9.4 (51.0-71.6)	6.6 ± 4.2 (1.2-10.0)	6.7 ± 2.7 (2.7-8.5)	2.4 ± 0.3 (2.0-2.7)	0.37 ± 0.25 (0.20-0.73)	-17.0 ± 0.3 (-17.5 --16.8)	11.9 ± 0.5 (11.4-12.6)
		MOZ	M	5	53.1 ± 6.5 (47.0-62.2)	1.8 ± 1.2 (0.8-3.7)	3.3 ± 1.5 (2.1-5.5)	2.1 ± 0.1 (1.9-2.3)	0.33 ± 0.09 (0.24-0.47)	-17.2 ± 0.1 (-17.4 --17.1)	10.4 ± 0.6 (9.8-11.2)
		SEY	M	5	58.6 ± 8.1 (44.3-63.9)	3.1 ± 1.4 (0.7-4.3)	4.9 ± 1.8 (1.8-6.4)	2.3 ± 0.2 (2.1-2.5)	0.28 ± 0.10 (0.17-0.43)	-16.8 ± 0.2 (-17.0 --17.0)	11.9 ± 0.6 (11.1-12.3)

Table 3

 3 Concentrations of PCBs andDDTs in the muscle of tropical tunas, swordfish and other top predator fish species worldwide. Albacore tuna Thunnus alalunga = ALB; Bluefin tuna Thunnus thynnus = BFT; Yellowfin tuna Thunnus albacares = YFT; Skipjack tuna Katsuwonus pelamis = SKJ; Southern bluefin tuna Thunnus maccoyii = SBT; Swordfish Xiphias gladius = SWO). ATL = Atlantic Ocean, MED = Mediterranean Sea, IO = Indian Ocean, WIO = western Indian Ocean, PAC = Pacific Ocean. Data are presented as minimum-maximum (mean ± sd) when available. Data are sorted by ocean, species and sampling date.

	Species	Sampling date	Ocean / Location	PCB Congeners	PCBs ng/g ww	PCBs ng/g lw	Number of DDT isomers	DDTs ng/g ww	DDTs ng/g lw	Reference
					0.0003-0.120	0.123-46.086
	SKJ	2013-2014	WIO	i-PCBs dl-PCBs	(0.002 ± 0.004) (0.017 ± 0.025) 0.0002-0.021	(0.752 ± 1.631) (5.432 ± 9.366) 0.007-8.00	5	0.014-0.129 (0.

040 ± 0.025) 2.013-55.629 (13.206 ± 10.869) This study YFT 2013-2014 WIO i-PCBs dl-PCBs 0.0058-0.119 (0.035 ± 0.029) 0.0006-0.026 (0.007 ± 0.006) 0.300-27.984 (7.968 ± 8.304) 0.0437-7.796 (1.572 ± 1.902) 5 0.020-0.445 0.120 ± 0.099) 5.161-133.899 (30.873 ± 31.385) This study BET 2013-2014 WIO i-PCBs dl-PCBs 0.0036-0.153 (0.027 ± 0.034) 0.0002-0.030 (0.004 ± 0.007) 0.571-27.134 (5.300 ± 6.502

	BFT (a) BFT	--2003-2007	MED PAC / Japan (shops)	ndl 13 PCBs	3.4-219.3 (84.2 ± 64.3) 0.5-46.1 (13.6 ± 17.2)	209.8-6042.2 (982.1 ± 1041.0) 70-4370 (930 ± 600)	1 (b)	1.0-104 (14.6 ± 17.2)	140-2860 (1040 ± 570)	Barone et al., 2018 Hisamichi et al., 2010
	YFT			dl 13 PCBs	0.9-46.6 (17.4 ± 12.5) 0.03-7.29 (0.31 ± 0.43)	22.7-631.3 (149.9 ± 145.3) 60-660 (230 ± 120)	1 (b)	0.03-1.59 (0.24 ± 0.26)	50-480 (200 ± 100)
	Tunas ALB	2012	MED / Spain (markets)	18 13 PCBs	10.54 0.02-11.61 (1.32 ± 2.10)	30-1300 (400 ± 280)	1 (b)	0.08-6.52 (0.97 ± 1.53)	20-1390 (290 ± 270)	Perello et al., 2015
	BFT BFT	2005 2005-2007	MED / Sicily PAC / Korea (markets)	43 PCBs 22 PCBs	(14.0 ± 14.3)	(2751.7 ± 1276.8)	1 (b) 4	(12.5 ± 10.1)	(2923.0 ± 785.9)	Vizzini et al., 2010 Moon et al., 2009
	BFT SKJ	2004 1997-2001	MED/ Sicily PAC / Various locations	3 PCBs dl-PCBs	nd-188.5	nd-2324 6.3-62.0	1 (b)	3.5-515.0	nd-3480	Di Bella et al., 2006 Ueno et al., 2005
	BFT (a) SKJ	2003 1997-2001	MED / Italy IO / India	43 PCBs dl-PCBs	5-1327	17-16839 8.1	1 (b)	0.8-112	2.5-551	Corsolini et al., 2007 Ueno et al., 2005
	BFT	2001-2003	Spain (markets)	23 PCBs	10-176 (100.4) SOUTHERN HEMISPHERE				Gomara et al., 2005
	SWO BFT BFT BFT ALB BFT YFT SWO SBT (wild) SWO SBT (farmed) SWO SKJ SWO SWO ALB BFT YFT BFT SWO SWO YFT SKJ YFT	2013-2014 WIO / Seychelles 2001-2010 Italy (food shops) 1999 MED / Sicily 1999 MED / Italy 2013 IO / Réunion island 1999 MED/Sicily 2007 IO / Western 2012 MED / Spain 2004 IO / Australia 2005 MED / Spain (markets) 2005 IO / Australia 1999 MED / Sicily 1997-2001 IO / Indonesia, Seychelles, 1999 MED / Sicily 1999 MED / Italy 2013 ATL / South Africa 2006 ATL / Spain 2009 ATL / Brazil 2008 ATL (north) ATL (north) 2001 ATL / Brazil 2005-2007 PAC / Japan, Hawai, California 1997-2001 ATL / Brazil India IO / Maldives, 2005-2007 PAC / Australia, New Zealand	i-PCBs dl-PCBs Total PCBs 35 12 i-PCBs dl-PCBs 57 28 PCBs 7 PCBs 18 45 PCBs 11 12 PCBs 57 dl-PCBs 34 12 i-PCBs dl-PCBs dl-PCBs 27 dl-PCBs dl-PCBs 25 13 dl-PCBs 13 13	) 0.0708-4.697 (0.856 ± 1.251) 3.017-53.776 (9.274 ± 12.797) 0.478-10.336 (1.832 ± 2.469) NORTHERN HEMISPHERE 0.204-3.117 (0.774 ± 0.713) 0.035-0.599 (0.155 ± 0.092) 666 ± 475 21.39-324.54 (74.91) 197-363 0.02-0.52 (0.20 ± 0.14) 0.01-0.09 2.2-32.7 (10.2 ± 7.6) 0.52-5.84 (0.03 ± 0.02) (1.8 ± 1.3) 12-229 (80 ± 86) 43.8-381.7 21.6-226.7 36.56 0.4-0.55 24-200 (0.47) (100) 13.27 0.08-1.58 11-267 (89 ± 82) 4.2-6.5 7.5-333.2 (80.4) 258-399 0.21-1.27 2.7-21.8 (0.58 ± 0.22) 0.05-0.33 (8.6 ± 4.7) 0.7-5.5 (0.14 ± 0.06) (2.1 ± 1.2) 5.16 ± 0.88 116.2-2556 (518.2) 17.97 0.28 1.30-24.8 (6.5) 17.67-319.17 (127.2) 80 ± 70 550 ± 260 14.0 330 ± 420 2890 ±3620 5250 ± 3380	5 5 6 5 1 (b) 1 (b) 4 1 (b) 6 1 (b) 5 6 4 1 (b) 1 (b) 1 (b)	0.050-0.777 (0.171 ± 0.168) 0.244-16.84 (7.269 ± 5.221) 0.95-299.58 (52.04) 30-67 0.08-2.18 (0.59 ± 0.48) (49) 5-97 (31 ± 38) 4.7-93 (38 ± 29) 2.61-161.37 (52.11) 45-69 (57) 0.71-4.10 (2.09 ± 0.70) 0.15-10.53 (2.47)	12.866-119.283 (34.824 ± 28.492) 36.056-290.439 (81.355 ± 61.305) 8.9-83.8 (28.4 ±16.1) 4.4-43.2 8.9-62.8 (29.9 ±14.4) 15.8-178.7 (77.5) 30 ± 70 360 ± 190 60 ± 100 180 ± 210 540 ± 530	This study This study Focardi, 2012 Stefanelli et al., 2002 Kannan et al., Munschy et al., 2016 2002 Corsolini et Torres et al., 2009 al., 2005 Perello et al., Padula et al., 2008 2015 Bocio et al., Phua et al., 2008 2007 Corsolini et Ueno et al., 2005 al., 2005 Stefanelli et al., 2004 Kannan et al., Munschy et al., 2016 2002 Sprague et Pizzochero et al., 2011 al., 2012 Mezzetta et al., 2011 de Azevedo e Silva et al., 2007 Mezzetta et al., 2011 Ueno et al., 2005 Endo et al., 2016 Endo et al ;, 2016

(a)

Includes juveniles and adults

(b)

p,p'-DDE

Acknowledgements

The authors would like to thank the fishermen from tropical tuna purse seiners operating in the western Indian Ocean and landing in the Seychelles and from the semi-industrial longliner MV Albacore operating in Seychelles waters who assisted with fish sampling. Special thanks also to the SFA research technicians for their invaluable help in processing the samples. This work is part of the CONSWO research project led by the Seychelles Fishing Authority (SFA) in collaboration with the French Research Institute for Sustainable Development (IRD), with the financial support of the European Fisheries Partnership Agreement (EU-FPA). We acknowledge Laura Valentine from "English Assistance for Industry" for the English corrections made to the manuscript.

Funding

This work is part of the CONSWO research project led by the Seychelles Fishing Authority (SFA) in collaboration with the French Research Institute for Sustainable Development (IRD), with the financial support of the European Fisheries Partnership Agreement (EU-FPA).

Data acquisition: CM, NB, KHM, NO, CP Statistical analysis: EV, CM Writing -review & editing: CM -NB

2

Tropical Tunas; Swordfish; Seychelles; Persistent Organic Pollutants (POPs); Perfluoroalkyl Substances (PFASs)