H. de Pontual, A. Jolivet, F. Garren, M. Bertignac & R. Fablet
Ifremer Brest, dpt Sciences et Technologies Halieutiques
First archival tagging on European hake:First archival tagging on European hake:what have we learnt?what have we learnt?
Key featuresKey features
� Widely distributed over the north east Atlantic shelf(Norway to Mauritania)
� Total landings declined 120,000 tons in 1960's to ~ 50,000 tons
� Recent concerns about the stock status: Low SSB,
low recruitment,
Recovery Plans in 2004 (NS) and 2006 (SS)
� Uncertainties on biological parameters Slow growing vs fast growing hypotheses
(Hickling, 1935; Belloc, 1935)
� Uncertainties about the population structure:2 stocks ?
carte
Recent advances from mark-recapture experiments
� Conventional tagging (pilot study 2002)
Growth underestimation …
Age (years)
0 2 4 6 8 10
Tota
l len
gth
(cm
)
0
20
40
60
80
100
120 Lucio et al. (2000a)ICES (1993)de Pontual et al. (2006)
♂ ♀ 301 days at liberty, TL 30 cm −−−−>>>> 49 cm
●●●● Winter ring (blind interpretation)●●●● OTC mark
… due to age overestimation
(de Pontual et al. 2003, 2006)
Fast growth confirmed:- experiments: BoB + off the Iberian Peninsula + Mediterranean Sea (Pineiro et al. 2007; Mellon et al. in prep; de Pontual et al. in prep)
- controlled conditions: growth rate ~ of cod (Jolivet et al. submitted)
� Archival tagging (pilot study in 2006)- Relate opacity complex pattern to temperature history
- Analyze migrations
DST methodologyDST methodology
� Can hake survive to archival tagging ?Controlled conditions: similar survival rate for conventional and DST tagging
(Jolivet et al. in press)
� Methodology:• Star-Oddi « DST micro » surgically implanted in the peritoneal cavity
• Temperature and pressure at 30’ intervals
• 115 tagged fish released (31- 40 cm)
• 4 recoveries / 3 fish returned with DST
• 18 – 80 days at liberty
Effects of conventional and DST tagging on survival and growth of European hake (Merluccius merluccius)
Aurélie Jolivet1, Hélène de Pontual1, François Garren1 and Marie-Laure Bégout2
1Ifremer LASAA, Brest, France 2Ifremer CRELA, L’Houmeau, France e-mail : [email protected]
Methods
Results
Conclusion
Fish were all caught in the wild in September 2005 and acclimated during 7 months. The tagging experiment started on February 7, 2006 and ended 128 days later. Two size groups were considered : small fish (average length ±SD, 29.9 cm ±2.17; SF) and larger fish (36.4 cm ± 2.5; LF). All fish were anaesthetized in a solution of benzocaïne (ethyl p-aminobenzoate), measured and weighted prior to subsequent treatment. For each size group, fish were randomly partitioned in 3 treatment groups : control (C), conventional tagging (CT : T-bar tag + oxytetracycline (OTC) injection), DST tagging (dummy tag + T-bar tag + OTC injection).
Anesthesia and sedation experiment
7:19 (±0:21)3b : Anesthesia
13:11(±3:58)3:54 (±0:39)3a : Total loss of equilibrium
11:27 (±8:31)1:48 (±0:44)2 : Deep sedation
Low dose (20 mg l-
1)High dose (100 mg l-
1)Stage
These data give anesthesia and sedation induction time at 9°C for hake (TL: 31.2cm ± 2.3). Benzocaïne was applied at a high concentration of 100 mg l-1 for surgery, and a low concentration of 20 mg l-1 for transport.
Important results are: 1) Conventional tagging impacts the survival probability which questions the use of mark-recapture data for estimations of natural mortality. 2) DST tagging should be feasible in the wild on “small fish” with survival rate and probabilities of recapture similar to that of conventional tagging. European hake is not a farmed species and husbandry conditions need to be improved. This was a limiting factor for this study.
Initial condition factor (CF) w.r.t size group and treatment
Distribution of Specific Growth Rate
- Out of the 60 fish, 21 survived (35%). - Survival probability for tagged fish decreased (CT or DST) particularly during the first 50 days-No significant difference between survival of SF tagged with CT and DST(P = 0.77). - Younger fish better supported stress induced by handling, anesthesia and tagging- Higher survival time for fish with a ratio: Weight DST/Weight Fish < 2% (Mantel-Cox : P = 0.04).
- High individual variability- No significant difference between control and tagged fish SGR (t-test: P>0.05). - Negative SGR for fish with a poor initial CF- 2 periods : recovery step during the first 30 days and a growth step with food intake.-Low survival limited further growth analysis
- Initial CF varying from 71% to 127%. - Homogeneity between treatment and group (KW test : P = 0.906).- Low survival (10%) for fish with initial CF <80%.
Initial condition GrowthSurvival
Introduction
(Mean response time in min:s ± SD)
CF >1
00%
CF 80-10
0%
CF < 8
0%
CF >1
00%
CF 80-
100%
CF < 8
0%
CT
DST
Control0
1
2
3
4
5
6
7
8
9
SF
LF
ControlDSTCT
European hake, Merluccius merluccius, is a major demersal resource in the North East Atlantic which has been heavily exploited. Recent mark-recapture experiments provided evidence of growth underestimation of the species due to bias in the agreed method of age estimation. To fully exploit mark-recapture data, estimations of the effects of tagging on both survival and growth are required. Hake is a little-known species and enriching information can be expected from DSTtagging at sea which requires a feasibility study on this reputed fragile species. The goal of this study were the following: 1) Establishing the conditions of application for surgery (anesthesia protocol);2) Estimation of the effects of conventional tagging on survival and growth; 3) Feasibility of DST tagging in the wild and estimation of effects on survival and growth.
120100806040200
Survival time
1,0
0,8
0,6
0,4
0,2
0,0
Cum
surv
ival
LF_DSTLF_CTLF_CSF_DSTSF_CTSF_C
Group_treatment
Survival function to the average of covariates
Survival time (days)
120100806040200
survival time
2,00
0,00
-2,00
-4,00
-6,00
-8,00
-10,00
spec
ific g
rowt
h ra
te
73,85
75,96
72,25
86,33
77,76
LF_DSTLF_CTSF_DSTSF_CT
Group_treatment
Survival time (days)
Kaplan –Meier survival function
F1 (U90)
Date30/ 06 07/ 07 14/ 07
Dep
th (
m) 0
10
20
30
40
50
60
Tem
pera
ture
(°C)
10
12
14
16
18
20
DST profile (1)DST profile (1)
18 days at liberty
♀♀ , TL 34 cm
LT
HT
Out of Range
62 days at liberty♂, TL 31 cm -> 32.5 cm
F2 (U72)
Date30/06 07/07 14/07 21/07 28/07 04/08 11/08 18/08 25/08
Dep
th (
m) 0
10
20
30
40
50
Tem
pera
ture
(°C
)
10
12
14
16
18
20
22
DST profile (2)DST profile (2)
OOR
80 days at liberty
♀♀, TL 34.5 cm -> 35.1 cm
F3 (U87)
Date 01/07 08/07 15/07 22/07 29/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09
Dep
th (
m) 0
20
40
60
80
100
120
Tem
pera
ture
°C
10
12
14
16
18
20
DST profile (3)DST profile (3)
OOR
� Questions to be addressed:
• Main characteristics of the VM behavior ?
(rhytmicity, amplitude, temperature variation,
tidal effects)
• What about horizontal movements ?
� Proposed method
• Automated analysis of DST signals
• Statistical analysis of extracted features
Quantitative analysis of DST signals: Quantitative analysis of DST signals: separation of vertical movement, seabed and tidal signalsseparation of vertical movement, seabed and tidal signals
Change detection
DST bathymetricsignal
VM signal
VM-removed signal
Low-pass filter
Seabed signal
VM- and seabed-removed signal
0 10 20 30 40 50 60 70 80
0
50
100
Dep
th(m
)
DST signal processingDST signalSeabed
0 10 20 30 40 50 60 70 800
50
100Estimated VM relative to seabed
Am
plitu
de (
m)
0 10 20 30 40 50 60 70 80
-5
0
5
Time (days)
Am
plitu
de (
m) Estimated seabed- & VM- removed signal
TF analysis of the ~ tidal signal
Time (days)
Num
ber
of p
erio
ds p
er d
ay
10 20 30 40 50 600
1
2
3
4
5
Time (days)
Num
ber
of p
erio
ds p
er d
ay
10 20 30 40 50 60 70 800
1
2
3
4
5
6Time (days)
Num
ber
of p
erio
ds p
er d
ay
5 10 150
1
2
3
4
5
Common features:• 1.93 period/day: M2 tidal constituent (period 12.4 hours)
Spring tide
• Higher intensities during spring tides : higher tidal signal and/or change of behavior
F3 (U87)
Date 01/07 08/07 15/07 22/07 29/07 05/08 12/08 19/08 26/08 02/09 09/09 16/09
Dep
th (
m) 0
20
40
60
80
100
120
No correlation between activity duration and night duration (p=0.13)
Rhythm persists even at high depth (>100 m)
20.5 21 21.5 22 22.5
20
21
22
23
Sunset time
VM
sta
rtin
g ho
urVertical movement: rhythmicity
VM activity begins at ~ sunset
Vertical movements: amplitude
45.5 46 46.5 47 47.5
30
40
50
60
70
80
90
100
Time (day)
Dep
th (
m)
0 20 40 60 800
20
40
60
80
Time (days)
Am
plitu
de (
m)
MaxMean
0 10 20 30 40 50 60 70 800
100
200
300
400
500
Date (days)
Cum
ulat
ive
dist
ance
(m
)
Vertical movements: temperature
High temperature High temperature
gradient for gradient for
several hoursseveral hours
Date (days)
Time (hours) at seabed T + DT (°C)
DT=0
0 2 4 6 80
5
10
15
Temperature gradient
Act
ivity
dur
atio
n
R = 0.0551p = 0.6732
No correlation btw activity duration and experienced temperature gradient
VMsVMs: tidal amplitude effect: tidal amplitude effect
20 40 60 80 100 1200
0.2
0.4
0.6
0.8
Tidal coefficient
Nor
mal
ized
div
e am
plitu
deR = - 0.4922p = 0.0001
VM amplitude decreases at spring tides
Horizontal movements
releaserecapture
SummaryFirst behavioral information
� Nocturnal activity characterized by :• high amplitude (cumulative distances)
• persisting at high depth
• depending on tidal amplitude
• high temperature variations
� Horizontal movements:• Homing behavior?
Prospect� More data needed: longer sequences , different areas, different seasons (large scale experiment at the EU level)
� Joint analyses of individual markers (natural & artificial)
Thanks:scientific team (Ifremer STH/Brest and EMH/Nantes)crew of the RV “Gwen Drez”participating fishermen Demostem and Sidepêche programs for funding
Thank youfor
listening
Pho
to F
. Gar
ren
ThankThank youyou for for listeninglistening
Date (days)
Time (hours) atseabedT + DT
‘‘Environmental’ factors: temperatureEnvironmental’ factors: temperature
Date (days)
Time (hours) atseabedT + DT
Date (days)
Time (hours) atseabedT + DT
Vertical behavior: Vertical behavior: rhythmicityrhythmicity (1)(1)
Activityduration(hours)
0 6 12 18 244
6
8
10
0 6 12 18 240
5
10
15
0 6 12 18 240
10
20
Timing of activity start (hour)
Vertical behavior: temperature (2)Vertical behavior: temperature (2)
0 2 4 6 80
10
20
30
40
Temperature gradient
VM
spe
ed
0 2 4 6 80
5
10
15
Temperature gradientA
ctiv
ity d
urat
ion
R = 0.326p = 0.0103
R = 0.0551p = 0.6732
Vertical behavior: temperature (2)Vertical behavior: temperature (2)
0 2 4 6 80
5
10
15
Temperature gradientA
ctiv
ity d
urat
ion
R = 0.326p = 0.0103
R = 0.0551p = 0.6732
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