Northeast Fisheries Science Center Reference Document 09-07

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service

Northeast Fisheries Science Center

Woods Hole, Massachusetts

April 2009

Determination of Conversion Factors 

for Vessel Comparison Studies

by Henry O. Milliken and Michael J. Fogarty

Northeast Fisheries Science Center, 166 Water Street, Woods Hole, MA 02543
Northeast Fisheries Science Center Reference Documents

This series is a secondary scientific series designed to assure the long-term documentation and 

to enable the timely transmission of research results by Center and/or non-Center researchers, 

where such results bear upon the research mission of the Center (see the outside back cover for 

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All documents issued in this series since April 2001, and several documents issued prior to 

that date, have been copublished in both paper and electronic versions. To access the electronic 

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This document’s publication history is as follows: manuscript submitted for review 

March 23, 2009; manuscript accepted through technical review April 27, 2009; manuscript 

accepted through policy review April 27, 2009; and final copy submitted for publication April 

27, 2009. Pursuant to section 515 of Public Law 106-554 (the Information Quality Act), this 

information product has undergone a pre-dissemination review by the Northeast Fisheries Science 

Center, completed on April 27, 2009. The signed pre-dissemination review and documentation 

is on file at the NEFSC Editorial Office. This document may be cited as:

Milliken HO, Fogarty MJ. 2009. Determination of Conversion Factors for Vessel 

Comparison Studies. US Dept Commer, Northeast Fish Sci Cent Ref Doc. 09-07; 18 

p. Available from: National Marine Fisheries Service, 166 Water Street, Woods Hole, 

MA 02543-1026, or online at http://www.nefsc.noaa.gov/nefsc/publications/
Table of Contents 

ABSTRACT................................................................................................................................... iv 

INTRODUCTION .......................................................................................................................... 1 

MATERIALS & METHODS ......................................................................................................... 1 

RESULTS ....................................................................................................................................... 2 

DISCUSSION................................................................................................................................. 3 

ACKNOWLEDGEMENTS............................................................................................................ 3 

LITERATURE CITED ................................................................................................................... 3 

APPENDIX A................................................................................................................................. 9 

List of Tables 

Table 1. Cruise information for paired fishing power cruises between the R/V’s Albatross IV 

and Delaware II since 1982 .......................................................................................... 4 

Table 2. A list of the species analyzed, the ratio estimates (conversion factors), the standard 

error of the estimates, and 90% confidence limits........................................................ 4 

List of Figures 

Figure 1. Station locations for paired comparisons...................................................................... 5 

Figure 2. Confidence intervals for “GLM” conversion factors versus the “ratio” conversion 

factors for the 1980s data only...................................................................................... 6 

Figure 3. A comparison of the ratio conversion factors derived from the 1980s data and the data 

following the refit of the R/V Delaware II................................................................... 7 

Figure 4. Plot of the ratio between the sum of the R/V Albatross IV divided by the sum of the 

R/V Delaware II and the 90% confidence intervals ..................................................... 8 

iii
iv

ABSTRACT 

NOAA’s Northeast Fisheries Science Center has conducted groundfish surveys on the 

Northeast Continental Shelf of the United States in autumn since 1963. These surveys are used

compute relative abundance indices of fish and selected invertebrates. Since the inception of

the survey program, the R/V Albatross IV has been the primary vessel conducting the work,

except periodically when the R/V Delaware II has been utilized because the R/V Albatross IV 

was not available. When the R/V Delaware II was used, differences in vessel characteristics 

necessitate the development of conversion coefficients to adjust catch rates using the R/V 

Albatross as the standard. 

A series of vessel calibration studies between the R/Vs Albatross IV and Delaware II

employing a paired tow design were initiated in 1981. In 1997, the R/V Delaware II underwent a 

major refit. Accordingly, for these two research vessels, there are two variations in the 

experimental time series that require consideration in development of calibration coefficients. 

We explored the use of a ratio estimator for the development of a vessel conversion coefficient 

and compared these with a general linear model (GLM) approach used by Byrne and Forrester 

(1991). 
INTRODUCTION 

For many decades the Federal Government has conducted groundfish surveys out of 

Woods Hole, MA. With the arrival of the newly built research vessel R/V Albatross IV in 1963, 

the Bureau of Commercial Fisheries (now National Marine Fisheries Service) began a time series 

that serves as the basis for some of the longest time series of standardized fishery-independent 

indices of relative abundance in the world. In addition to tracking abundance of mature animals, 

research surveys provide indices of juvenile abundance, which can indicate strong year classes 

before fish are vulnerable to commercial or recreational fisheries. Research surveys indicate the 

status of a stock over its entire range, not just in small areas of commercial or recreational 

concentration. Surveys also provide data on growth, maturity, predation, and mortality of a stock 

as well as trophic dynamics of fish communities (Azarovitz 1981). 

The R/V Albatross IV’s autumn bottom trawl survey was conducted using a #36 Yankee 

net with a sixty-foot (18.3 m) headrope and eighty-foot (24.4 m) footrope. The sweep was 

comprised of sixteen-inch (40.6 cm) rollers that allow the gear to be fished on most bottom 

types. The net and fishing operation remained almost the same since the start of the autumn 

survey in 1963 (Azarovitz 1981). When changes were made, comparative tows were performed 

to quantify the changes in the catchability of the gear. Once determined, a conversion coefficient 

was applied to the data so that any differences in the catchability of the gear could be compared 

to future catches (Fogarty 1997). 

Conversion coefficients between the R/V’s Albatross IV and Delaware II were developed 

by Byrne and Forrester (1991) using a general linear model (GLM) approach. When the R/V 

Delaware II was used for surveys, these estimates were used to transform catch data. In 1997 the 

R/V Delaware II underwent a major refit. This refit included changing the winches from slower 

direct drive to faster free spooling winches. After the refit, the previous conversion factors were 

still employed to transform the data. However, the GLM approach does not allow the 

consideration of tows with zero catch, thus those data were lost. An alternative approach using 

ratio estimators, which use a ratio of the sum of the paired data, allows the comparison of all 

catch data between the two vessels. 

Because the GLM method does not permit the inclusion of paired tows where one of the 

tows has zero catch, we compared the use of the GLM and ratio estimator methods for deriving 

the conversion factors. Additionally we examined the conversion factors before and after the refit 

of the R/V Delaware II in 1997. 

MATERIALS & METHODS 

 

The R/V’s Albatross IV and Delaware II fished alongside each other five times since the 

R/V Delaware II was refurbished in 1997 (Table 1, Figure 1). During these cruises, the R/V 

Delaware II accompanied the R/V Albatross IV while the R/V Albatross IV was engaged in its 

standard bottom trawl survey. Three paired comparison cruises from the 1980s were used to 

compare the GLM and ratio estimators for developing conversion factors. One 1998 cruise and 

four cruises from the 2000s were utilized to construct the ratio estimator model to estimate 

conversion coefficients. 

The conversion coefficient (α) was calculated as: 

1
∑

∑

=

= = n

i

i

n

i

ii

wV

VwV

1

2

1

1

12

α

ˆ

where w is a weighting coefficient that depends on the relationship between the variance of V2 

(Vessel 2) and V1(Vessel 1); the variance is defined as: 

∑

∑

=

=

⎟

⎠

⎞ ⎜

⎝

⎛ − − ⎟ =

⎠

⎞ ⎜

⎝

⎛ n

i

i

n

i

i i

wV

VVw

n

1

2

2

1

^

1

12

1

1

α

α

ˆ ra

ˆ v

If the variance of V2 and V1 is proportional, the weighting coefficient is V1-1 and the 

estimator for the conversion coefficient is: 

∑

∑

=

= = n

i

i

n

i

i

V

V

1

1

1

2 ˆ

α

We used the proportional variance estimator in our analyses where “V2” is the variance of the 

R/V Albatross IV and “V1” is the variance of the R/V Delaware II. 

Conversion coefficients were developed for winter skate (Leucoraja ocellata) , silver 

hake (Merluccius bilinearis), Atlantic cod (Gadus morhua), haddock (Melanogrammus 

aeglefinus), white hake (Urophycis tenuis), red hake (Urophycis chuss), American plaice 

(Hippoglossoides platessoides), fourspot flounder (Hippoglossina oblonga), yellowtail flounder 

(Limanda ferruginea), witch flounder (Glyptocephalus cynoglossus), windowpane flounder 

(Scophthalmus aquosus), redfish (Sebastes fasciatus), and ocean pout (Zoarces americanus). 

RESULTS 

When we examined the conversion factors derived from both the GLM and ratio 

estimator models using the 1980s data, with the exception of haddock, there appears to be good 

correlation between the two methods for determining vessel conversion coefficients (Figure 2). 

Ratio conversion coefficients calculated for catches before and after the R/V Delaware’s 

1997 refit suggest that the vessel effect was reduced after the vessel was modified. Twelve of the 

14 species’ coefficients calculated from the 1980s data showed a difference, while only 4 of the 

14 species show a difference after the refit (Figure 3).The species that showed a difference 

included cod, haddock, pollock and redfish (Figure 4). For these four species, the post-fit 

2
conversion factors should be applied to the R/V Delaware II data when the R/V Delaware II was 

used in place of the R/V Albatross IV for the standardized groundfish surveys (Table 2). 

DISCUSSION 

Differences in catch efficiencies between the R/V Albatross IV and R/V Delaware II

were reduced after the refit of the R/V Delaware II. It was unanticipated that the refit would 

reduce the difference in the catchability between the two vessels or, in other words, reduce the 

catchability of the R/V Delaware II. After the R/V Delaware II was modified, the winches were 

replaced with faster winches. We hypothesize that because the winches were faster, the amount 

of time the net spent on the bottom was reduced. The winch speed was designed to match the 

speed of the winches on the R/V Albatross IV which appears to have equalized the catchability 

between the two vessels. 

The ratio conversion coefficients were calculated for fourteen species. The next step will 

be to apply it to the other principal groundfish species to determine if conversion coefficients are 

required. 

ACKNOWLEDGEMENTS 

This work would not be possible without the efforts of numerous members of the 

Northeast Fisheries Science Center, particularly the Resource Survey Branch, who participated 

in these cruises and helped collect this data. A special thanks is due to Kathy Mays of the 

Northeast Fisheries Science Center who spent considerable time helping to develop the proper 

scripts to pull the data from the survey database. 

LITERATURE CITED 

Azarovitz TR. 1981. A brief historical review of the Woods Hole Laboratory trawl survey time 

series. Can Spec Pub Fish Aq Sci. 58:62-67. 

Byrne CJ, Forrester JRS. 1991. Relative Fishing Power of NOAA R/V’s Albatross IV and 

Delaware II. In: Report of the Twelfth Northeast Regional Stock Assessment Workshop. 

US. Dept. Commer., NOAA, Northeast Fisheries Science Center Ref. Doc. 91-03, 187 p. 

Fogarty M.J. 1997. Standardizing fishing power in research vessel surveys. In: Proceedings of 

the Workshop on Maintaining Current & Future Fisheries Resource Survey Capabilities. 

Special Report No. 63 of the Atlantic States Marine Fisheries Commission, p 54-63. 

3
Table 1. Cruise information for paired fishing power cruises between the R/V’s Albatross IV

and Delaware II since 1982. When the start date for the Albatross IV precedes the 

Delaware II it is because the comparative work did not occur during all four legs of a 

survey.

CRUISE 

NUMBER VESSEL NAME START DATE 

END 

PATE SURVEY NUMBER OF PAIRS 

GEAR 

TYPE 

198206 Albatross IV 9/13/1982 11/12/1982 

198207 Delaware II 10/4/1982 10/29/1982 FALL 144 Yankee 36 

198306 Albatross IV 9/12/1983 11/10/1983 

198307 Delaware II 10/4/1983 10/26/1983 FALL 113 Yankee 36 

198803 Albatross IV 9/12/1988 10/28/1988 

198804 Delaware II 9/19/1988 10/28/1988 FALL 227 Yankee 36 

199802 Albatross IV 3/2/1998 4/20/1998 

199807 Delaware II 3/30/1998 4/10/1998 SPRING 44 Yankee 36 

200002 Albatross IV 3/16/2000 5/3/2000 

200003 Delaware II 3/20/2000 4/14/2000 SPRING 125 Yankee 36 

200102 Albatross IV 2/26/2001 4/30/2001 

200104 Delaware II 3/26/2001 4/20/2001 SPRING 69 Yankee 36 

200202 Albatross IV 3/4/2002 4/26/2002 

200203 Delaware II 4/3/2002 4/26/2002 SPRING 131 Yankee 36 

200209 Albatross IV 9/3/2002 10/25/2002 

200211 Delaware II 10/16/2002 10/25/2002 FALL 51 Yankee 36 

Table 2. A list of the species analyzed, the ratio estimates (conversion factors), the standard 

error of the estimates, and 90% confidence limits. 

SPECIES 

RATIO 

ESTIMATE 

STANDARD 

ERROR 

90% CONFIDENCE 

INTERVALS 

Winter Skate 0.93 0.06 0.831 1.029 

Silver Hake 1.02 0.07 0.9045 1.1355 

Cod 0.82 0.06 0.721 0.919 

Haddock 0.83 0.06 0.731 0.929 

Pollock 0.69 0.05 0.6075 0.7725 

White Hake 1.04 0.07 0.9245 1.1555 

Red Hake 0.91 0.06 0.811 1.009 

American Plaice 1.01 0.07 0.8945 1.1255 

Fourspot Flounder 1.04 0.07 0.9245 1.1555 

Yellowtail Flounder 1.07 0.07 0.9545 1.1855 

Witch Flounder 1.00 0.07 0.8845 1.1155 

Windowpane Flounder 0.95 0.07 0.8345 1.0655 

Redfish 0.87 0.06 0.771 0.969 

Ocean Pout 0.98 0.07 0.8645 1.0955 

4
Figure 1. Station locations for paired comparisons (listed in Table 1). Different colors signify 

different cruises. 

5
Figure 2. Confidence intervals (95%) for “GLM” conversion factors versus the “ratio” conversion factors for the 

Species which did not have a conversion factor in one of the data sets were omitted. When the error ba“1”, the catch weights between the two vessels are significantly different. When the bars fall below “1”

R/V Delaware caught significantly more of that species. 

6
Figure 3. A comparison of the ratio conversion factors derived from the 1980's data (A) and the data following t

Delaware II (B). When the error bar falls above or below “1”, the catch weights between the two vessels 

different. When the bars fall below “1”, it indicates that the R/V Delaware caught significantly more of threpresent the 90% confidence intervals. 

7
Figure 4. Plot of the ratio between the sum of the R/V Albatross IV divided by the sum of the R/V Delaware II 

confidence intervals. When the error bar falls above or below “1”, the catch weights between the two 

significantly different. When the bars fall below “1”, it indicates that the R/V Delaware caught signifspecies.

8
APPENDIX A 

Winter skate [cruise = Pooled data]

Dep Var: WINTERSK_ALB N: 482 Multiple R: 0.728 Squared multiple R: 0.530 

 

Adjusted squared multiple R: 0.529 Standard error of estimate: 40.948 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 4.502 1.934 0.000 . 2.328 0.020 

WINTERSK_DEL 0.614 0.026 0.728 1.000 23.276 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 908363.493 1 908363.493 541.750 0.000 

Residual 804825.997 480 1676.721 

 

------------------------------------------------------------------------------- 

Case 83 is an outlier (Studentized Residual = 5.259) 

Case 198 has large leverage (Leverage = 0.318) 

Case 198 is an outlier (Studentized Residual = -15.989) 

Case 198 has large influence (Cook distance = 38.888) 

Case 207 is an outlier (Studentized Residual = 12.938) 

Case 212 has large leverage (Leverage = 0.295) 

Case 216 is an outlier (Studentized Residual = 8.753) 

Case 224 has large leverage (Leverage = 0.054) 

Case 224 is an outlier (Studentized Residual = 9.839) 

Case 257 has large leverage (Leverage = 0.068) 

 

Durbin-Watson D Statistic 1.866 

First Order Autocorrelation 0.067 

 

Plot of Residuals against Predicted Values Winter skate weights (kg)

0 200 400 600 800 1000

Albatross IV

0

200

400

600

800

1000

D

ela

w

are II

500

0 100 200 300 400 500 600

ESTIMATE

-500

-400

-300

-200

-100

0

100

200

300

400

R

E

S

DI U

A

L

9
Silver Hake [cruise = Pooled data]

Dep Var: SH_ALB N: 482 Multiple R: 0.343 Squared multiple R: 0.118 

 

Adjusted squared multiple R: 0.116 Standard error of estimate: 22.614 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 1.921 1.073 0.000 . 1.791 0.074 

SH_DEL 0.613 0.077 0.343 1.000 8.012 0.000 

 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 32832.852 1 32832.852 64.200 0.000 

Residual 245479.063 480 511.415 

 

------------------------------------------------------------------------------- 

Case 95 is an outlier (Studentized Residual = 103.250) 

Case 229 has large leverage (Leverage = 0.044) 

Case 232 has large leverage (Leverage = 0.303) 

Case 248 has large leverage (Leverage = 0.309) 

Case 344 has large leverage (Leverage = 0.078) 

 

Durbin-Watson D Statistic 2.011 

First Order Autocorrelation -0.006 

Plot of Residuals against Predicted Values

0 20 40 60 80 100 120

ESTIMATE

-100

0

100

200

300

400

500

R

E

S

DI U

A

L

Silver hake weights (kg)

0 100 200 300 400 500

Albatross IV

0

100

200

300

400

500

D

ela

w

are II

10
Atlantic Cod [cruise = Pooled data]

Dep Var: COD_ALB N: 482 Multiple R: 0.634 Squared multiple R: 0.401 

 

Adjusted squared multiple R: 0.400 Standard error of estimate: 9.876 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.969 0.470 0.000 . 2.063 0.040 

COD_DEL 0.513 0.029 0.634 1.000 17.943 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 31398.690 1 31398.690 321.946 0.000 

Residual 46813.349 480 97.528 

------------------------------------------------------------------------------- 

Case 98 is an outlier (Studentized Residual = 6.186) 

Case 186 has large leverage (Leverage = 0.053) 

Case 222 has large leverage (Leverage = 0.046) 

Case 223 has large leverage (Leverage = 0.040) 

Case 236 has large leverage (Leverage = 0.182) 

Case 236 is an outlier (Studentized Residual = -7.502) 

Case 318 has large leverage (Leverage = 0.040) 

Case 318 is an outlier (Studentized Residual = 5.292) 

Case 329 is an outlier (Studentized Residual = 4.880) 

Case 342 has large leverage (Leverage = 0.177) 

Case 359 has large leverage (Leverage = 0.063) 

Case 361 has large leverage (Leverage = 0.051) 

Case 362 is an outlier (Studentized Residual = 17.078) 

Case 383 is an outlier (Studentized Residual = 6.324) 

Case 393 has large leverage (Leverage = 0.105) 

 

Durbin-Watson D Statistic 1.923 

First Order Autocorrelation 0.037 

Plot of Residuals against Predicted Values

0 10 20 30 40 50 60 70 80

ESTIMATE

-100

0

100

200

R

E

S

DI U

A

L

Atlantic cod weights (kg)

0 50 100 150 200

Albatross IV

0

50

100

150

200

D

ela

w

are II

11
Haddock [cruise = Pooled data]

Dep Var: HADDOCK_ALB N: 482 Multiple R: 0.646 Squared multiple R: 0.417 

 

Adjusted squared multiple R: 0.416 Standard error of estimate: 11.751 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.619 0.550 0.000 . 1.126 0.261 

HADDOCK_DEL 0.869 0.047 0.646 1.000 18.545 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 47488.890 1 47488.890 343.901 0.000 

Residual 66282.680 480 138.089 

 ------------------------------------------------------------------------------- 

Case 236 has large leverage (Leverage = 0.189) 

Case 325 has large leverage (Leverage = 0.088) 

Case 325 is an outlier (Studentized Residual = -4.370) 

Case 329 is an outlier (Studentized Residual = 11.928) 

Case 340 is an outlier (Studentized Residual = 27.927) 

Case 342 has large leverage (Leverage = 0.056) 

Case 382 has large leverage (Leverage = 0.177) 

Case 383 has large leverage (Leverage = 0.069) 

Case 389 is an outlier (Studentized Residual = 4.106) 

Case 393 has large leverage (Leverage = 0.214) 

 

Durbin-Watson D Statistic 1.996 

First Order Autocorrelation 0.002 

Plot of Residuals against Predicted Values

0 20 40 60 80 100 120

ESTIMATE

-100

0

100

200

300

R

E

S

DI U

A

L

Haddock weights (kg)

0 100 200 300

Albatross IV

0

100

200

300

D

ela

w

are II

12
White Hake [cruise = Pooled data]

Dep Var: W_HAKE_ALB N: 482 Multiple R: 0.693 Squared multiple R: 0.480 

 

Adjusted squared multiple R: 0.479 Standard error of estimate: 4.411 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.621 0.209 0.000 . 2.970 0.003 

W_HAKE_DEL 0.518 0.025 0.693 1.000 21.036 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 8608.851 1 8608.851 442.493 0.000 

Residual 9338.566 480 19.455 

------------------------------------------------------------------------------- 

Case 232 has large leverage (Leverage = 0.064) 

Case 233 has large leverage (Leverage = 0.188) 

Case 235 has large leverage (Leverage = 0.059) 

Case 243 is an outlier (Studentized Residual = 4.096) 

Case 252 has large leverage (Leverage = 0.139) 

Case 252 is an outlier (Studentized Residual = 4.065) 

Case 368 is an outlier (Studentized Residual = 5.060) 

Case 371 is an outlier (Studentized Residual = 6.549) 

Case 372 has large leverage (Leverage = 0.081) 

Case 372 is an outlier (Studentized Residual = 5.901) 

Case 392 has large leverage (Leverage = 0.061) 

Case 397 is an outlier (Studentized Residual = 14.868) 

Case 398 has large leverage (Leverage = 0.094) 

Case 398 is an outlier (Studentized Residual = -6.746) 

Case 405 is an outlier (Studentized Residual = 4.078) 

 

Durbin-Watson D Statistic 1.994 

First Order Autocorrelation 0.003 

Plot of Residuals against Predicted Values

0 10 20 30 40 50

ESTIMATE

-30

-20

-10

0

10

20

30

40

50

60

R

E

SID

U

A

L

White hake weights (kg)

0 10 20 30 40 50 60 70 80

Albatross IV

0

10

20

30

40

50

60

70

80

D

ela

w

are II

13
Red Hake [cruise = Pooled data]

Dep Var: RED_HAKE_ALB N: 482 Multiple R: 0.743 Squared multiple R: 0.552 

 

Adjusted squared multiple R: 0.551 Standard error of estimate: 6.582 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.561 0.312 0.000 . 1.800 0.073 

RED_HAKE_DEL 0.705 0.029 0.743 1.000 24.322 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 25627.542 1 25627.542 591.546 0.000 

Residual 20795.050 480 43.323 

------------------------------------------------------------------------------- 

Case 26 has large leverage (Leverage = 0.060) 

Case 27 has large leverage (Leverage = 0.048) 

Case 45 has large leverage (Leverage = 0.146) 

Case 45 is an outlier (Studentized Residual = -10.750) 

Case 86 is an outlier (Studentized Residual = 5.572) 

Case 95 is an outlier (Studentized Residual = 7.378) 

Case 145 has large leverage (Leverage = 0.085) 

Case 145 is an outlier (Studentized Residual = 11.807) 

Case 155 has large leverage (Leverage = 0.166) 

Case 157 has large leverage (Leverage = 0.136) 

Case 157 is an outlier (Studentized Residual = 5.016) 

Case 258 is an outlier (Studentized Residual = 6.661) 

Case 259 is an outlier (Studentized Residual = 4.167) 

Case 287 is an outlier (Studentized Residual = 4.699) 

Case 341 has large leverage (Leverage = 0.072) 

Case 341 is an outlier (Studentized Residual = -6.482) 

Case 346 is an outlier (Studentized Residual = 4.290) 

Case 347 has large leverage (Leverage = 0.063) 

 

Durbin-Watson D Statistic 1.839 

First Order Autocorrelation 0.080 

Plot of Residuals against Predicted Values

0 10 20 30 40 50 60 70

ESTIMATE

-100

-50

0

50

100

R

E

S

DI U

A

L

Red hake weights (kg)

0 50 100 150

Albatross IV

0

50

100

150

D

ela

w

are II

14
American Plaice [cruise = Pooled data]

Dep Var: A_PLAICE_ALB N: 482 Multiple R: 0.914 Squared multiple R: 0.836 

 

Adjusted squared multiple R: 0.835 Standard error of estimate: 1.373 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.102 0.064 0.000 . 1.600 0.110 

A_PLAICE_DEL 0.677 0.014 0.914 1.000 49.408 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 4602.279 1 4602.279 2441.151 0.000 

Residual 904.940 480 1.885 

 

------------------------------------------------------------------------------- 

Case 86 is an outlier (Studentized Residual = 4.381) 

Case 88 has large leverage (Leverage = 0.391) 

Case 97 is an outlier (Studentized Residual = -8.786) 

Case 229 has large leverage (Leverage = 0.117) 

Case 229 is an outlier (Studentized Residual = -9.536) 

Case 233 has large leverage (Leverage = 0.072) 

Case 235 has large leverage (Leverage = 0.067) 

Case 248 is an outlier (Studentized Residual = 4.296) 

Case 360 is an outlier (Studentized Residual = -4.445) 

Case 361 has large leverage (Leverage = 0.111) 

Case 361 is an outlier (Studentized Residual = 12.285) 

Case 481 has large leverage (Leverage = 0.059) 

Case 481 is an outlier (Studentized Residual = 7.078) 

 

Durbin-Watson D Statistic 2.125 

First Order Autocorrelation -0.063 

Plot of Residuals against Predicted Values

0 10 20 30 40 50

ESTIMATE

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American plaice weights (kg)

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Albatross IV

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Fourspot Flounder [cruise = Pooled data]

Dep Var: FOURSPOT_ALB N: 482 Multiple R: 0.932 Squared multiple R: 0.868 

 

Adjusted squared multiple R: 0.868 Standard error of estimate: 0.861 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.120 0.041 0.000 . 2.893 0.004 

FOURSPOT_DEL 0.725 0.013 0.932 1.000 56.206 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 2343.690 1 2343.690 3159.156 0.000 

Residual 356.099 480 0.742 

------------------------------------------------------------------------------- 

Case 26 has large leverage (Leverage = 0.037) 

Case 53 has large leverage (Leverage = 0.096) 

Case 56 is an outlier (Studentized Residual = 6.039) 

Case 103 has large leverage (Leverage = 0.056) 

Case 103 is an outlier (Studentized Residual = 6.099) 

Case 145 has large leverage (Leverage = 0.040) 

Case 145 is an outlier (Studentized Residual = 7.555) 

Case 149 has large leverage (Leverage = 0.096) 

Case 155 has large leverage (Leverage = 0.210) 

Case 155 is an outlier (Studentized Residual = -6.757) 

Case 157 has large leverage (Leverage = 0.070) 

Case 167 is an outlier (Studentized Residual = 4.315) 

Case 287 is an outlier (Studentized Residual = 5.937) 

Case 301 has large leverage (Leverage = 0.047) 

Case 305 is an outlier (Studentized Residual = -5.994) 

Case 478 is an outlier (Studentized Residual = 6.031) 

 

Durbin-Watson D Statistic 2.127 

First Order Autocorrelation -0.064 

Plot of Residuals against Predicted Values Fourspot flounder weights (kg)

8

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Albatross IV

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16
Yellowtail Flounder [cruise = Pooled data]

Dep Var: YT_ALB N: 482 Multiple R: 0.941 Squared multiple R: 0.886 

 

Adjusted squared multiple R: 0.886 Standard error of estimate: 1.887 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.146 0.088 0.000 . 1.655 0.099 

YT_DEL 0.658 0.011 0.941 1.000 61.078 0.000 

 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 13279.336 1 13279.336 3730.523 0.000 

Residual 1708.629 480 3.560 

 

------------------------------------------------------------------------------- 

Case 21 has large leverage (Leverage = 0.114) 

Case 21 is an outlier (Studentized Residual = 22.472) 

Case 30 has large leverage (Leverage = 0.279) 

Case 31 has large leverage (Leverage = 0.177) 

Case 31 is an outlier (Studentized Residual = -8.421) 

Case 92 is an outlier (Studentized Residual = -6.950) 

Case 149 has large leverage (Leverage = 0.194) 

Case 151 is an outlier (Studentized Residual = 5.007) 

Case 174 is an outlier (Studentized Residual = 5.075) 

 

Durbin-Watson D Statistic 1.948 

First Order Autocorrelation 0.023 

Plot of Residuals against Predicted Values

0 10 20 30 40 50 60 70

ESTIMATE

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Yellowtail flounder weights (kg)

0 10 20 30 40 50 60 70 80 90 100

Albatross IV

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17
Winter Flounder [cruise = Pooled data]

Dep Var: WINTER_F_ALB N: 482 Multiple R: 0.816 Squared multiple R: 0.666 

 

Adjusted squared multiple R: 0.666 Standard error of estimate: 2.643 

 

Effect Coefficient Std Error Std Coef Tolerance t P(2 Tail) 

CONSTANT 0.284 0.126 0.000 . 2.257 0.024 

WINTER_F_DEL 0.777 0.025 0.816 1.000 30.956 0.000 

Analysis of Variance 

Source Sum-of-Squares df Mean-Square F-ratio P 

 

Regression 6691.408 1 6691.408 958.245 0.000 

Residual 3351.831 480 6.983 

------------------------------------------------------------------------------- 

Case 81 has large leverage (Leverage = 0.038) 

Case 81 is an outlier (Studentized Residual = 4.042) 

Case 91 is an outlier (Studentized Residual = 5.199) 

Case 143 is an outlier (Studentized Residual = 11.007) 

Case 210 has large leverage (Leverage = 0.068) 

Case 210 is an outlier (Studentized Residual = 5.565) 

Case 239 has large leverage (Leverage = 0.110) 

Case 332 has large leverage (Leverage = 0.147) 

Case 332 is an outlier (Studentized Residual = -6.830) 

Case 382 has large leverage (Leverage = 0.042) 

Case 382 is an outlier (Studentized Residual = 4.839) 

Case 383 has large leverage (Leverage = 0.169) 

Case 383 is an outlier (Studentized Residual = 7.031) 

Case 469 has large leverage (Leverage = 0.116) 

Case 469 is an outlier (Studentized Residual = -10.115) 

 

Durbin-Watson D Statistic 1.893 

First Order Autocorrelation 0.054 

18

Plot of Residuals against Predicted Values Winter flounder weights (kg)

30

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Research Communications Branch

Northeast Fisheries Science Center

National Marine Fisheries Service, NOAA

166 Water St.

Woods Hole, MA 02543-1026

Publications and Reports

of the

Northeast Fisheries Science Center

The mission of NOAA’s National Marine Fisheries Service (NMFS) is “stewardship of living marine resources 

for the benefit of the nation through their science-based conservation and management and promotion of the 

health of their environment.” As the research arm of the NMFS’s Northeast Region, the Northeast Fisheries 

Science Center (NEFSC) supports the NMFS mission by “conducting ecosystem-based research and assessments of living marine resources, with a focus on the Northeast Shelf, to promote the recovery and long-term 

sustainability of these resources and to generate social and economic opportunities and benefits from their use.” 

Results of NEFSC research are largely reported in primary scientific media (e.g., anonymously-peer-reviewed 

scientific journals). However, to assist itself in providing data, information, and advice to its constituents, the 

NEFSC occasionally releases its results in its own media. Currently, there are three such media:

NOAA Technical Memorandum NMFS-NE -- This series is issued irregularly. The series typically includes: data reports of 

long-term field or lab studies of important species or habitats; synthesis reports for important species or habitats; annual reports 

of overall assessment or monitoring programs; manuals describing program-wide surveying or experimental techniques; literature 

surveys of important species or habitat topics; proceedings and collected papers of scientific meetings; and indexed and/or annotated 

bibliographies. All issues receive internal scientific review and most issues receive technical and copy editing.

Northeast Fisheries Science Center Reference Document -- This series is issued irregularly. The series typically includes: data 

reports on field and lab studies; progress reports on experiments, monitoring, and assessments; background papers for, collected 

abstracts of, and/or summary reports of scientific meetings; and simple bibliographies. Issues receive internal scientific review and 

most issues receive copy editing.

Resource Survey Report (formerly Fishermen’s Report) -- This information report is a regularly-issued, quick-turnaround report on 

the distribution and relative abundance of selected living marine resources as derived from each of the NEFSC’s periodic research vessel surveys of the Northeast’s continental shelf. This report undergoes internal review, but receives no technical or copy editing.

TO OBTAIN A COPY of a NOAA Technical Memorandum NMFS-NE or a Northeast Fisheries Science Center Reference Document, 

either contact the NEFSC Editorial Office (166 Water St., Woods Hole, MA 02543-1026; 508-495-2350) or consult the NEFSC webpage 

on “Reports and Publications” (http://www.nefsc.noaa.gov/nefsc/publications/). To access Resource Survey Report, consult the Ecosystem 

Surveys Branch webpage (http://www.nefsc.noaa.gov/femad/ecosurvey/mainpage/).

Any use of trade OR BRAND names in any NEFSC publication or report does not imply endorsement.

MEDIA

 MAIL
Procedures for Issuing Manuscripts

in the

Northeast Fisheries Science Center Reference Document (CRD) Series

Clearance

All manuscripts submitted for issuance as CRDs 

must have cleared the NEFSC’s manuscript/abstract/

webpage review process. If any author is not a federal 

employee, he/she will be required to sign an “NEFSC 

Release-of-Copyright Form.” If your manuscript 

includes material from another work which has been 

copyrighted, then you will need to work with the 

NEFSC’s Editorial Office to arrange for permission 

to use that material by securing release signatures on 

the “NEFSC Use-of-Copyrighted-Work Permission 

Form.” 

For more information, NEFSC authors should see 

the NEFSC’s online publication policy manual, “Manuscript/abstract/webpage preparation, review, and dissemination: NEFSC author’s guide to policy, process, 

and procedure,” located in the Publications/Manuscript 

Review section of the NEFSC intranet page.

Organization

Manuscripts must have an abstract and table of 

contents, and (if applicable) lists of figures and tables. 

As much as possible, use traditional scientific manuscript organization for sections: “Introduction,” “Study 

Area” and/or ”Experimental Apparatus,” “Methods,” 

“Results,” “Discussion,” “Conclusions,” “Acknowledgments,” and “Literature/References Cited.” 

Style

The CRD series is obligated to conform with the 

style contained in the current edition of the United 

States Government Printing Office Style Manual. That 

style manual is silent on many aspects of scientific 

manuscripts. The CRD series relies more on the CSE 

Style Manual. Manuscripts should be prepared to 

conform with these style manuals. 

The CRD series uses the American Fisheries Society’s guides to names of fishes, mollusks, and decapod 

crustaceans, the Society for Marine Mammalogy’s 

guide to names of marine mammals, the Biosciences 

Information Service’s guide to serial title abbreviations, 

and the ISO’s (International Standardization Organization) guide to statistical terms. 

For in-text citation, use the name-date system. A 

special effort should be made to ensure that all necessary bibliographic information is included in the list 

of cited works. Personal communications must include 

date, full name, and full mailing address of the contact.

Preparation

Once your document has cleared the review process, the Editorial Office will contact you with publication needs – for example, revised text (if necessary) and 

separate digital figures and tables if they are embedded 

in the document. Materials may be submitted to the 

Editorial Office as files on zip disks or CDs, email 

attachments, or intranet downloads. Text files should 

be in Microsoft Word, tables may be in Word or Excel, 

and graphics files may be in a variety of formats (JPG, 

GIF, Excel, PowerPoint, etc.).

Production and Distribution

The Editorial Office will perform a copy-edit of 

the document and may request further revisions. The 

Editorial Office will develop the inside and outside 

front covers, the inside and outside back covers, and 

the title and bibliographic control pages of the document.

Once both the PDF (print) and Web versions of 

the CRD are ready, the Editorial Office will contact 

you to review both versions and submit corrections or 

changes before the document is posted online.

A number of organizations and individuals in the 

Northeast Region will be notified by e-mail of the 

availability of the document online.