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Environmental effects on Octopus vulgaris landings in northwest Spanish waters.
Gersom CostasIsabel BrunoGraham J. Pierce
2014I CES Annual Science Conference. A Coruña (Spain).Theme Session P:Operational solutions for cephalopod fisheries and culture. P06
Aim
Identifying the most important environmental variables influencing Octopus abundance in Northwestern Iberian Peninsula
• Short-lived species ( ~12 ~24 months) • Non-overlapping generations, 1or 2 cohorts in fishery• Very rapid growth • Semelparous species. High fecundity rates. • Shore zone. Variety of substrates
one single spawning peak in spring in the Galician waters~24 monthsParalarvae in the plankton for _40 days, after bottom 4 months
Life History
Material and Methods
Data of artisanal octopus fishery logbooks from the Spanish Administration.
Artisanal trap fleet in northwestern iberian peninsula from 2003 to 2012
Environmental data.
Abbreviation Name Periodicity Source
sst Sea Surface temperature
Montly http://rda.ucar.edu/datasets/
cloudneess cloudness Montly http://rda.ucar.edu/datasets/
wind_f wind strengh Montly http://rda.ucar.edu/datasets/
press sea level pressure Montly http://rda.ucar.edu/datasets/
NAO North atlatic Oscillation Annual http://www.cpc.ncep.noaa.gov/
mean_upwell Upwelling index Quarterly www.indicedeafloramiento.ieo.es
0
500
1000
1500
2000
2500
Penas
Altas
BaixasLand
ings
(t)
Reporting obligation of fishing operation in logbooks of fishing vessels >10 m in length.
Comparative : sales at fish markets- logbooks
Material and Methods
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
-12 -8 -5 -2 1 4
41
42
43
44
E0 E1 E2 E3 E4 E5
10 9 8 7 6 5 4
11
12
13
14
15
16
17
0
50
100
150
200
1 2 3 4
quarter
CP
UE
(kg/
day)
area
Altas
Baixas
Penas
0
1000
2000
3000
1 2 3 4
Quarter
Effo
rt (m
ean_
Nda
ys)
Rias Altas
Rias Baixas
Cabo Peñas
Material and Methods
Material and Methods
0
5
10
15
20
1 2 3 4
Quarter
win
d (
0.1
m/s
)
0
2
4
6
8
1 2 3 4
Quarter
Clo
ud
ne
ss
1000
1020
1040
1 2 3 4
Quarter
pres
siom
(mB
)
10
15
20
1 2 3 4
Quarter
Tem
p (º
C)
NAO
UPWELLING
Seasonal and Trend decomposition using Loess
The response: LPUEThe initial predictor variables with the input terms:
1. sea surface temperature (SST)2. wind strength (wind_f)3. sea level pressure (press) 4. cloudiness (cloud)5. Annual NAO index previous year (lag -1)6. Upwelling index Quarter 1 previous year (lag -1)7. Upwelling index Quarter 4 of 2 previous year (lag -2)8. Month9. ICES Statistical Rectangle
GAM for investigating the influence the influence of environmental variables over octopus abundance
Material and Methods
-1 0 1
-30
theoretical quantiles
devi
ance
res
idua
ls
2.0 3.0 4.0
-30
Resids vs. linear pred.
linear predictor
resi
dual
sHistogram of residuals
Residuals
Fre
quen
cy
-3 -2 -1 0 1
030
2.0 3.0 4.0
14
Response vs. Fitted Values
Fitted Values
Res
pons
e
-1.0 -0.5 0.0
-1.0
-0.5
0.0
0.5
nao
s(n
ao
,2.9
5)
-1200 -800 -400 0 200
-1.0
-0.5
0.0
0.5
mean_upw
s(m
ea
n_
up
w,2
.19
)
ResultsCabo Peñas
The final optimum model is:
log(lpue) ~ s(upwell_Q1(lag-1), 4) + s(nao(lag-1), 4) + month +sr
R-sq.(adj) = 0.356 Deviance explained = 44.6%GCV score = 0.53333 Scale est. = 0.45573 n = 159
-1.0 -0.5 0.0
-0.6
-0.2
0.2
nao
s(n
ao
,3)
-1000 -500 0
-0.6
-0.2
0.2
mean_upw
s(m
ea
n_
up
w,2
.52
)
-1500 -1000 -500 0
-0.6
-0.2
0.2
mean_upw2
s(m
ea
n_
up
w2
,2.9
6)
ResultsRias Altas
The final optimum model is:
log(lpue) ~ s(upwell_Q1(lag-1), 4) + s(upwell_Q4(lag-2), 4) + s(nao(lag-1), 4) + month +sr
R-sq.(adj) = 0.564 Deviance explained = 59.3%GCV score = 0.11235 Scale est. = 0.10472 n = 463
1 2 3 4 5 6 7
-0.4
0.0
0.4
cloud
s(cl
ou
d,2
.61
)
1010 1015 1020 1025
-0.4
0.0
0.4
pres
s(p
res,
2.6
7)
15 16 17 18
-0.4
0.0
0.4
sst
s(ss
t,2
.87
)
-1.0 0.0 1.0
-1.5
1.0
theoretical quantiles
devia
nce r
esid
uals
3.0 4.0 5.0
-1.5
1.0
Resids vs. linear pred.
linear predictor
resid
uals
Histogram of residuals
Residuals
Fre
quency
-1.5 0.0 1.0
0150
3.0 4.0 5.0
2.5
5.0
Response vs. Fitted Values
Fitted Values
Response
-1.0 -0.5 0.0
-0.4
0.0
0.4
nao
s(n
ao
,2.0
2)
ResultsRias Baixas
-800 -600 -400 -200 0
-0.4
0.0
0.4
mean_upw
s(m
ea
n_
up
w,2
.95
)
-2000 -1000 0 500
-0.4
0.0
0.4
mean_upw2
s(m
ea
n_
up
w2
,2.9
6)
R-sq.(adj) = 0.595 Deviance explained = 61.9%GCV score = 0.117 Scale est. = 0.11004 n = 573
The final optimum model is:
log(lpue) ~ s(upwell_Q1(lag-1), 4) + s(upwell_Q4(lag-2), 4) + s(nao(lag-1), 4) + s(sst, 4) + s(cloud, 4)+ s(press, 4)+ month +sr
Discussion
• Negative NAO index in previous year creating no favourable conditions for
octopus abundance
• Effects of upwelling pulses after paralarval stage can be associated to
variability of recruitment and posterior abundance in 3 areas.
• Oceanographic variables have significant effects over Octopus abundance
just in southern area (Rias Baixas).
• Importance of environmental factors in 3 geographic areas in relation on
octopus abundance.