Stock and risk assessments of swordfish (Xiphias gladius ......IOTC–2014–WPB12–24 Rev_1 Page 1...

IOTC–2014–WPB12–24 Rev_1

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Stock and risk assessments of swordfish (Xiphias gladius) in the Indian Ocean

by ASPIC incorporating uncertainties

(Revised 1)

Tom Nishida

National Research Institute of Far Seas Fisheries (NRIFSF)

Fisheries Research Agency (FRA), Shimizu, Shizuoka, Japan

Sheng-Ping Wang

Department of Environmental Biology and Fisheries Science,

National Taiwan Ocean University, Keelung, Taiwan

October, 2014

Abstract

Stock and risk assessments were conducted by ASPIC software using 64 years data (1950-2013) for swordfish in

the whole and the SW Indian Ocean. In the stock assessments, uncertainties caused by production models

(Schaefer vs. Fox) and targeting effect (SWO cluster vs. NHBF) were taken into account.

As for the Whole Indian Ocean, the stock is now at the well safe zone (green zone in the Kobe plot), i.e., Total

biomass (TB) ratio=1.64 and F ratio=0.52. Risk assessments suggests no risks violating MSY levels at all if the

current catch in 2013 (31,000 tons) or less level continues next 10 years, while the low risk with 20% increases

(37,000 tons) and high risks with 40% increase (44,000 tons) for both TB and F ratios.

As for the SW Indian Ocean, the stock is now at the recovering stage (yellow zone close to both MSY levels of TB

and F in the Kobe plot), i.e., Total biomass (TB) ratio=0.95 and F ratio=0.93. Risk assessment suggests that there

are high risks violating MSY levels of TB ratio levels next 10 years if the current catch in 2013 (7,300 tons) were

increased by 10% or more, while low or no risks if the current catch or less level were continued. As for F ratio,

even if the current catch level were reduced by 10% (6,600 tons), there are high risks violating MSY levels. If the

current catch levels were reduced more than by 20% (5,900 ton), there are less or no risks next 10 years.

Contents 1. Introduction------------------------------------------------------------------------------------------------------ 02 2. Stock assessments in the whole Indian Ocean

2.1 Data---------------------------------------------------------------------------------------------------02-05 2.2 ASPIC runs-------------------------------------------------------------------------------------------05-07 2.3 Discussion (ASPIC)---------------------------------------------------------------------------------08-10 2.4 Risk assessments (Kobe II)-----------------------------------------------------------------------11-12

3. Stock assessments in the SW Indian Ocean 3.1 Data----------------------------------------------------------------------------------------------------12-15 3.2 ASPIC runs--------------------------------------------------------------------------------------------15-16 3.3 Risk assessments (Kobe II)------------------------------------------------------------------------17-18

Acknowledgements----------------------------------------------------------------------------------------------------19

References---------------------------------------------------------------------------------------------------------------19

_______________________________________________________________________ Submitted to the IOTC 12 th WPB meeting, Oct. 21-25, 2014, Yokohama, Japan

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1. Introduction

We attempted the stock assessment of swordfish (Xiphias gladius) (SWO) in the Indian Ocean

by A Stock-Production Model Incorporating Covariates (ASPIC) using 64 years data (1950-

2013). As in the past, we conducted stock assessments for 2 areas (whole Indian Ocean and

the SW IO) because the local depletion in the SW Indian Ocean has been detected (Nishida

and Wang, 2011) and we need to know the current situation.

2. Stock assessments in the whole Indian Ocean

2.1 Data

(1) Catch

We used the nominal catch data from the IOTC dataset (as of Oct., 15, 2014) (Fig. 1).

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Fig. 1 Nominal catch of swordfish in the Indian Ocean (1950-2013) (IOTC dataset, Oct., 15, 2014 version)

(2) CPUE

We have 4 STD_CPUE (standardized CPUE) (Japan, Taiwan, Spain and Portugal) in the whole IO.

Fig. 2a and 2b shows 4 STD_CPUE in 1971-2013 and in 1999-2013 respectively. JPN STD_CPUE

shows the decreasing trend from 1971-2005 and afterward increasing trends and stabilized in


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higher level, while they have big bumps. TWN STD_CPUE shows the increasing trend from

1980-1997, afterward constant trend, while they also have large bumps throughout. SPN and

POR STD_CPUE trends show more or less flat trend

During 1991-1998, STD_CPUE trends between Japan and Taiwan show different trends, i.e.,

Japan shows the decreasing trend, while Taiwan, increasing trend. During 1999-2013, 4

STD_CPUE show more or less similar trend (flat trend).

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Taiwan

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Fig 2a Comparisons of STD_CPUE among 4 fleets (Japan, Taiwan, Spain and Portugal) (1971-2013)

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Taiwan

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Portugal

Fig 2b Comparisons of STD_CPUE among 4 fleets (Japan, Taiwan, Spain and Portugal) (1999-2013).


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(3) Relation between nominal catch vs. STD_CPUE (Fig. 3)

Japan

Taiwan

Spain

Portugal

Fig. 3 Comparisons between nominal catch vs. STD_CPUE by fleet (Whole Indian Ocean)

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Based on Fig. 3, only Japan has the negative correlation between nominal catch and STD_CPUE,

hence we use JPN_CPUE for ASPIC runs.

2.2. ASPIC runs

We used the ASPIC software (ver. 5.05) developed by Prager (2004). For details of this

software, refer to “User’s Manual for ASPIC: A Stock-Production Model Incorporating

Covariates (ver. 5) and auxiliary programs, Population Dynamics Team, Center for Coastal

Fisheries and Habitat Research, National Oceanic and Atmospheric Administration, Beaufort,

North Carolina, USA: National Marine Fisheries Service Beaufort Laboratory Document BL-

2004-01” by Prager (2004).

In ASPIC, we set up 4 scenarios (Table 1) to incorporate uncertainties between models (FOX vs.

Schaefer) and also between targeting effects (SWO cluster vs. NHBF) (Fig.4). We assume

B1950 =K. Table 1 and Figs. 5-6 show results. To represent these uncertainties, we used

weighted average of RMSE (Root Mean Square Errors) and Fig. 7 and Table 1 show the results.

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case 5

case 6

Fig 4 JPN STD_CPUE used for the ASPIC runs (case 5: SWO cluster and case 6: NHBF)

(Refer to Table 1)


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Table 1 ASPIC runs incorporating uncertainties (4 scenarios) and results (1950-2013)

Scenario

Elements of uncertainty R2

(CPUE)

RMSE

(over all)

MSY

(tons)

TB(2013)

/TB(MSY)

F(2013)

/F(MSY) Model Targeting

effect

(1) FOX SWO cluster 0.416 0.2017 44,480 1.93 0.37

(2) NHBF 0.420 0.2003 37,300 1.46 0.57

(3) SCHAEFER SWO cluster 0.455 0.2706 35,970 1.69 0.51

(4) NHBF 0.419 0.2808 34,260 1.38 0.66

Overall ASPIC results

incorporating uncertainties

(weighted average by 1/RMSE)

38,450

1.63

0.52

SWO cluster NHBF

F

O

X

Scenario (1) Scenario (2)

S C H A E F E R


Fig. 5 Kobe plots of ASPIC results (4 scenarios) showing uncertainties among and within and scenarios.


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Fig. 6 Kobe plot incorporating uncertainties in 4 scenarios (weighted average of 1/RMSE)

Table 2 Summary of ASPIC result

Management Quantity Whole Indian Ocean

Most recent catch estimate (t) (2013) 31,804

Mean catch over last 5 years (t) (2009-2013) 26,510

MSY (1000 t) (80%CI) 38.5 (26.3-56.2)

Data Period used in assessment 1950-2013 (64 years)

F(2013)/F(MSY)

(80% CI)

0.52

(0.48-0.55)

TB(2013)/TB(MSY)

(80% CI)

1.63

(1.60-1.69)

SB(2013)/SB(MSY) NA

TB(2013)/TB(1950) 0.76

SB(2013)/SB(1950) NA

TB(2013)/TB(2013, F=0) NA

SB(2013)/SB(2013, F=0) NA


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95%

75%50%25%

5%

80 81 82 83 8485868788899091

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9697

989900

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0506

07

08

09

TB/TBmsy

3210

F/F

msy

2

1

0

2.3 Discussion (ASPIC)

(1) Why we got much more optimistic stock status this time than in last time (2011)?

In the last stock assessment by ASPIC (2011) using 30 years data (1980-2009), the Kobe plot

shows more conservative phase (Fig. 7) than those in this time (Figs. 5-6). This gap is likely

caused likely by the following reason, i.e., the previous assessment in 2011 used CPUE for 30

years [B]-[C] (1980-2009), while for this time for 43 years [A]-[D] (1971-2013). This means that

the stock assessment for this time include the recent recovery phase [D], which likely made

much optimistic stock status (Fig. 8).

Fig. 7 Kobe plot of the 2011 stock assessment by ASPIC using 1980-2009 data

(Nishida and Wang, 2011)

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Fig. 8 Trend of JPN STD_CPUE (4 phases) [A]-[D] and the catch trend

[A]

[B]

[C]

[D]


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(2) Why STD_CPUE (SWO cluster) made ASPIC results much optimistic than the one (NHBF)?

The reason is considered as follows: Targeting effect by NHBF cluster makes CPUE trends

much steeper than the one by SWO cluster. This is easily understood from the comparison of

STD_CPUE between 2 targeting effect (Fig. 9). Average slope of STD_CPUE with NHBF is much

lower than the one by SWO cluster. This means that STD_CPUE with SWO cluster will produce

much less stock reduction over the period than the one by NHBF, i.e., it makes the stock more

optimistic.

Comparison of STD_CPUE within 2014 (slope: -0.0122 vs. -0.0223)

Comparison of STD_CPUE between 2014 vs. 2011 (slope : -0.0122 vs. -0.017)

Fig. 9 Comparison JPN STD_CPUE between 2 different target effects: SWO cluster vs. NHBF

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(3) Why JPN STD_CPUE produced more realistic trends?

Japanese tuna LL has been exploiting SWO as bycatch in the whole Indian Ocean. This means

that Japanese tuna LL likely performs “simple random sampling” for SWO, which make CPUE

more realistic (abundance) trends even they have a lot of noises (bumps).

As for TWN tuna LL, they targets SWO for sometimes and for other times, exploits as bycatch

when they target other species such as albacore, bigeye tuna, yellowfin tuna and southern

Bluefin tuna. Thus, their samplings strategies are not consistent, which make CPUE biased with

large fluctuations. It is likely that even SWO cluster as targeting correction factor are used,

large biases causes by such inconsistent samplings may be not able to be reduced. In fact,

STD_CPUE with SWO cluster (targeting correction factor) (case 4 in Fig. 8) (Wang and Nishida,

2014) are much smoother than the one with species compositions (case 2). But, the rough

trends between two are more or less same because of inconsistent samplings.

Fig. 10 Comparison of TWN STD_CPUE by different targeting correction factor

(Wang and Nishida, 2014)

(Case 2: species composition; and case 4: SWO cluster)

As Spain and Portugal LL, the time series of their CPUE are short and it is difficult to explain

reasons why their STD_CPUE and catch are not well corresponding as shown Fig. 2


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2.4 Risk assessments (Kobe II)

Based on 500 time bootstraps by ASPIC software, we conducted risk assessments for TB ratios

and F ratios. Box 1 shows results. Box 1 suggests no risks violating MSY levels at all if the

current catch (31,000 tons) or less level continues next 10 years, while the low risk with 20%

increases (37,000 tins) and high risks 40% (44,000 tons) for both TB and F ratios.

Box 1 Kobe II risk assessment for TB ratio and F ratios (Whole Indian Ocean)

Color legends (4 probabilities ranges of risks violating MSY levels)

(1) TB (Total biomass) ratio

years later 1 2 3 4 5 6 7 8 9 10

catch level catch (tons) 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023-40% 18,650 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00-20% 24,867 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

current

(2013)31,084 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

20% 37,301 0.05 0.12 0.15 0.18 0.22 0.24 0.27 0.28 0.30 0.34

40% 43,518 0.13 0.28 0.40 0.52 0.60 0.70 0.75 0.80 0.87 0.89

(2) F ratios

years later 1 2 3 4 5 6 7 8 9 10catch level catch (tons) 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

-40% 18,650 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00-20% 24,867 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

current

(2013)31,084 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

20% 37,301 0.02 0.11 0.13 0.18 0.22 0.24 0.26 0.28 0.30 0.33

40% 43,518 0.20 0.36 0.47 0.53 0.63 0.71 0.77 0.81 0.87 0.89

0-0.25 0.25-0.50 0.50-0.75 0.75-1


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3. Stock assessment in the SW Indian Ocean

3.1 Data

(1) Catch

We used the nominal catch data in the SW region available in the IOTC dataset for SWO stock

assessments published in October 15, 2014 (Fig. 11).

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Catch : SW Indian Ocean (tons) (1950-2013)

Fig 11 Nominal catch (ton) used for the ASPIC analyses for the SW Indian Ocean

(IOTC dataset for stock assessments, October 15, 2014)

(2) STD_CPUE

We have 4 STD_CPUE (standardized CPUE) (Japan, Taiwan, Spain and Portugal) in the whole IO.

Fig. 12a and 12b shows 4 STD_CPUE in 1971-2013 and in 1999-2013 respectively. JPN

STD_CPUE shows the decreasing trend in general with large bumps (ups and downs). TWN

STD_CPUE shows the increasing trend from 1980-1993, afterward the decreasing trend, while

they also have large bumps throughout. SPN and POR STD_CPUE trends show more or less flat

trend

During 1980-1993, STD_CPUE trends between Japan and Taiwan show different trends, i.e.,

Japan shows the decreasing trend, while Taiwan, increasing trend, while both shows the


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decreasing trend during 1993-2013. 4 STD_CPUEs show more or less similar trend (flat trend)

except a big jump in JPN STD_CPUE in 2008.

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Fig 12a STD_CPUE in the SW Indian Ocean (Japan, Taiwan, Spain and Portugal) (1971-2013)

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Fig 12b STD_CPUE in the SW Indian Ocean (Japan, Taiwan, Spain and Portugal) (1999-2013)


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(3) Relation between nominal catch vs. 4 STD_CPUE (Fig. 13)

Japan

Taiwan

Spain

Portugal

Fig. 13 Comparisons between nominal catch vs. STD_CPUE by fleet (SW Indian Ocean)

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y = -1E-04x + 1.4477R² = 0.3767

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0 5000 10000 15000 20000

scal

ed

CP

UE

(ave

=1)

Catch (tons)

Relation : STD_CPUE vs Catch (SW)

0

0.5

1

1.5

2

2.5

0

5000

10000

15000

20000

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54

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scal

ed

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UE

(ave

=1)

catc

h (

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s)

Catch and POT STD_CPUE (SW)

y = -1E-06x + 1.0352R² = 0.0002

0

0.5

1

1.5

0 5000 10000 15000 20000

Scal

ed

CP

UE

(ave

=1)

Catch (tons)

Relation: POT STD_CPUE vs Catch


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Based on Fig. 13, only Japan has the negative correlation between nominal catch and

STD_CPUE, hence we use JPN_CPUE for the ASPIC.

3.2. ASPIC runs

We run ASPIC in the same way as in the Whole Indian Ocean using 4 scenarios (Table 3). Table

3 and Fig. 14 show the results. Scenarios (1) and (2) could not get convergences and (3) had

poor fits to the model hence reasonable confidence surface could not be obtained. Hence, for

the SW IO ASPIC, scenario (4) is considered to be the best results (Fig. 15). Table 3 shows the

summary.

Table 3 ASPIC runs incorporating uncertainties (4 scenarios) and results (SW IO) (1950-2013)

Scenario

Elements of uncertainty R2

(CPUE)

RMSE

(over all)

MSY

(tons)

TB(2013)

/TB(MSY)

F(2013)

/F(MSY) Model Targeting

effect

(1) FOX SWO cluster Not converged

(2) NHBF Not converged

(3) SCHAEFER SWO cluster 0.112 0.7714 9,965 0.43 1.13

(4) NHBF 0.418 0.4041 8,507 0.95 0.93

Scenario

selected

As (1)+(2) were not converged and (3) has lower R2 and higher RMSE (much

less fit) than in (4) and could not provide confidence surface, Scenario (4) is

selected as the best representative result of the ASPIC assessment.


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SWO cluster NHBF

F

O

X

Not converged

Not converged


S C H A E F E R

Scenario (3)

Confidence surface could not be evaluated due to

constrains in F pre-set in the ASPIC software

Scenario (4)

Fig. 14 Kobe plots of ASPIC results (4 scenarios) showing uncertainties among and within and scenarios.

Fig. 15 Magnified Kobe plot of scenario (4) as the best representative of ASPIC runs


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Table 3 Summary of ASPIC result (SW IO)

Management Quantity SW Indian Ocean

Most recent catch estimate (t) (2013) 7,349

Mean catch over last 5 years (t) (2009-2013) 7,260

MSY (1000 t) (80%CI) 8.51(7.76-9.22)

Data Period used in assessment 1950-2013 (64 years)

F(2013)/F(MSY)

(80% CI)

0.93

(0.65-1.28)

TB(2013)/TB(MSY)

(80% CI)

0.95

(0.69-1.24)

SB(2013)/SB(MSY) NA

TB(2013)/TB(1950) 0.45

SB(2013)/SB(1950) NA

TB(2013)/TB(2013, F=0) NA

SB(2013)/SB(2013, F=0) NA

3.3 Risk assessments (Kobe II) (SW IO)

Based on 500 time bootstraps using ASPIC software, we conducted risk assessment for TB

ration and F ratios for next 10 years. Box 2 shows results. Box 2 suggests that there are high

risks violating MSY levels of TB ratio levels next 10 years if the current catch were increased by

10% or more, while low or no risks if the current catch or less level were continued.

As for F ratio, even if the current catch level were reduced by 10%, there are high risks

violating the MSY levels. If the current catch levels were reduced more than by 20%, there are

less or no risks next 10 years.


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Box 2 Kobe II risk assessment for TB ratios and F ratios (SW Indian Ocean)

Color legends (4 probabilities ranges of risks violating MSY levels)

(1) TB ratio

years later 1 2 3 4 5 6 7 8 9 10

catch levelcatch

(tons)2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

-40% 4,409 0.24 0.09 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00-30% 5,144 0.31 0.13 0.03 0.02 0.01 0.01 0.01 0.01 0.00 0.00-20% 5,879 0.37 0.19 0.10 0.04 0.02 0.02 0.01 0.01 0.01 0.01-10% 6,614 0.43 0.28 0.18 0.12 0.07 0.05 0.04 0.04 0.03 0.03

current

(2013)7,349 0.49 0.40 0.31 0.26 0.21 0.18 0.16 0.14 0.14 0.12

10% 8,084 0.52 0.53 0.52 0.50 0.47 0.45 0.43 0.43 0.41 0.4020% 8,819 0.62 0.65 0.71 0.76 0.80 0.83 0.84 0.85 0.87 0.9030% 9,554 0.69 0.82 0.92 0.96 0.98 0.99 0.99 1.00 1.00 1.00

40% 10,289 0.71 0.86 0.94 0.98 0.99 0.99 1.00 1.00 1.00 1.00

(2) F ratio

years later 1 2 3 4 5 6 7 8 9 10

catch levelcatch

(tons)2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

-40% 4,409 0.10 0.03 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00-30% 5,144 0.10 0.06 0.02 0.01 0.01 0.01 0.00 0.00 0.00 0.00-20% 5,879 0.33 0.30 0.24 0.19 0.17 0.13 0.11 0.09 0.05 0.05-10% 6,614 0.54 0.56 0.58 0.62 0.64 0.67 0.69 0.69 0.67 0.68

current

(2013)7,349 0.72 0.81 0.84 0.87 0.90 0.91 0.91 0.92 0.92 0.93

10% 8,084 0.85 0.91 0.94 0.97 0.97 0.98 0.98 0.98 0.98 0.9820% 8,819 0.92 0.98 0.98 0.99 0.99 0.99 0.99 0.99 0.99 0.9930% 9,554 0.97 0.99 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

40% 10,289 0.99 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

0-0.25 0.25-0.50 0.50-0.75 0.75-1


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Acknowledgments

Many thanks for Mr. Miguel Herrera (IOTC data manager) to provide necessary information to

conduct the stock assessments. Thanks also for Mr. Iwasaki (Environmental Simulation

Laboratory) to provide the Kobe plot software (new version).

References

Nishida, T. and Wang, S-P. (2010) Stock assessment of swordfish (Xiphias gladius) in the Indian

Ocean by ASPIC (1980-2008). IOTC-2010-WPB-12

Prager, M. (2004) User’s Manual for ASPIC: A Stock-Production Model Incorporating

Covariates (ver. 5) and auxiliary programs, Population Dynamics Team, Center for

Coastal Fisheries and Habitat Research, National Oceanic and Atmospheric

Administration, 101 Pivers Island Road, Beaufort, North Carolina 28516 USA:

National Marine Fisheries Service Beaufort Laboratory Document BL-2004-01

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