NOAA Technical Memorandum NMFS 

MAY 1986 

DETERMINING FISH MOVEMENTS FROM AN 

“ARCHIVAL” TAG: PRECISION OF GEOGRAPHICAL 

POSITIONS MADE FROM A TIME SERIES 

OF SWIMMING TEMPERATURE AND DEPTH 

Paul Smith 

Daniel Goodman 

MOAA-TM-NMFS-S WFC-60 

U.S. DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration 

Southwest Fisheries Center 

National Marine Fisheries Service 
NOAA Technical Memorandum NMFS 

The National Oceanic and Atmospheric Administration (NOAA), organized in 

1970, has evolved into an agency which establishes national policies and 

manages and conserves our oceanic, coastal, and atmospheric resources. An 

organizational element within NOAA, the Office of Fisheries is responsible for 

fisheries policy and the direction of the National Marine Fisheries Service 

(NMFS). 

In addition to its formal publications, the NMFS uses the NOAA Technical 

Memorandum series to issue informal scientific and technical publications when 

complete formal review and editorial processing are not appropriate or feasible. 

Documents within this series, however, reflect sound professional work and may 

be referenced in the formal scientific and technical literature. 
NOAA Technical Memorandum NMFS 

This TM series IS used for documentallon and 11mely communuaon ot preltminary results. lmterwn reports. OT 

Special purpose intorma110n. and have not recelved complete formal revlew. edtlorlal control. or demled edtting 

MAY 1986 

DETERMINING FISH MOVEMENTS FROM AN 

“ARCHIVAL” TAG: PRECISION OF GEOGRAPHICAL 

POSITIONS MADE FROM A TIME SERIES 

OF SWIMMING TEMPERATURE AND DEPTH 

Paul Smith 

Southwest Fisheries Center 

National Marine Fisheries Service, NOAA 

La Jolla, California 

Daniel Goodman 

Montana State University 

Department of Biology 

Bozeman, Montana 

NOAA-TM-NMFS-SWFC-60 

U.S. DEPARTMENT OF COMMERCE 

Malcolm Baldrige. Secretary 

National Oceanic and Atmospheric Administration 

Anthony J. Calio, Administrator 

National Marine Fisheries Service 

William G. Gordon, Assistant Administrator for Fisheries 
DETERMINING FISH MDVEMENTS FROM AN ltARCHIVAL'l TAG: 

PREClSlCFI OF GEOGRAPHICAL POSITIONS MADE FROM A TIME SERIES 

OF SW IMMING TEMPERATURE AND DEPTH 

Paul Smith1 and Daniel Goodman2 

Given advances in integrated circuit technology, it is possible to 

design, bui I d and depl oy on a fish a device that woul d col lect and store 

data on elapsed time, I ight intensity, pressure (depth) and temperature. 

From this information it is theoretical ly possible to reconstruct a series 

of geographical positions visited by a fish equipped with a device. The 

tag (proposed by Northwest Marl ne Technology; discussed by Hunter et al. 

1986) would record time of sunset and sunrise from which an estimate of 

longitude could be directly made. The tag would also record temperature 

and depth from which estimates of latitude could be deduced. How 

accurately these estimates can be made is dependent both on the amount and 

qual ity of the data col lected and how we1 I sea-surface isotherms predict 

I atitude. 

The longitude estimate could be made directly from the time of sunrise 

and sunset, and should readily achieve an accuracy of one degree (Table 1). 

This requires that the tag be capable of distinguishing differences in 

sunrise times of at least four minutes. The engineers suggest that this is 

reasonably easy to attain. 

Estimates of latitude would be made from temperature gradient 

i nformation--both horizontal and vertical. I deal ly, the temperature f iel d 

of the Ocean would have sufficient gradient, north to south, that latitude 

could be establ ished--especial ly if longitude were known. The objective of 

this paper is to determine the precision with which latitude could be 

estlmated from simulated temperature and depth recwds, such as those which 

coul d be stored in an archival tag. As an exampl e we use the movements of 

the Pacific northern bluefin tuna. The range of movements includes an 

east-west migration corridor w Ith spawning grounds near the western 

extreme. Bluefin are caught on both sides of the Pacific and In both 

hem i spheres, and thel r presumed natural hi story of movements (Bay I iff 1980; 

Yamanaka 1984) are indicated in Figure 1. Although Pacific northern 

Southwest Fi sheries Center 

NMFS, NOAA, U.S. Department of Commerce 

La Jol la, Cal ifornia 92038, USA 

2Department of B io1 ogy 

Montana State Un iversi ty 

Bozeman, Montana 59717, USA 

3The authors wrote this paper to evaluate an idea that developed during a 

workshop on existing and new technologies that could be employed to measure 

tuna movements. The workshop was one of a series of three on tuna movements 

he1 d in 1985. The three workshops were jointly sponsored by the InterAmerican Tropical Tuna Commission and the Southwest Fisheries Center of the 

U.S. National Fisheries Service. For further details regarding the 

workshops see Hunter et al. 1986. 

1 
Table 1. Estimated day length and times of sunr i se and sunset I n the 

northern bluefin habitat (from The Nautical Almanac for the 

Year 1974, US Naval Observatory, Washington, D.C, USA). \ 

Day Day Day 

I ength Sunri se Sunset I ength Sunri se Sunset I ength Sunrise Sunset 

(hr) (GMT1) (GMT) (hr) (GMT) (GMT) (hr) (GMT) (GMT) 

~ 

11 5"W Long. 20" La*. 

Mar 21 

Jun 20 

Sep 20 

Dec 20 

125'W 

Mar 21 

Jun 20 

Sep 20 

Dec 20 

165"W 

Mar 21 

Jun 20 

Sep 20 

Dec 20 

16 5" E 

Mar 21 

Jun 20 

Sep 20 

Dec 20 

125'E 

Mar 21 

Jun 20 

Sep 20 

Dec 20 

12.12 

13.36 

12.18 

10.86 

12.1 2 

13.72 

1 2.20 

10.50 

12.1 2 

13.36 

12.18 

10.86 

12.12 

13.03 

12.16 

11.19 

12.1 2 

13.36 

12.18 

10.86 

1344 

1301 

1328 

141 2 

25" 

1424 

1330 

1408 

1502 

20'N 

1704 

1621 

1648 

1732 

15" 

20 24 

1950 

2009 

20 42 

20" 

21 44 

21 01 

21 28 

221 2 

01 51 

0222 

0139 

01 03 

0231 

0313 

0220 

0132 

051 1 

0542 

0459 

0 423 

083 1 

0 852 

081 9 

07 53 

0951 

1022 

0939 

0 903 

12.12 

13.72 

12.20 

10.50 

12.12 

14.11 

12.22 

10.1 1 

12.12 

14.55 

12.24 

9.67 

12.12 

14.11 

12.22 

10.1 1 

12.12 

13.72 

12.20 

10.50 

25" La+. 35" Lat. 

1344 

1250 

1328 

1422 

30" 

1424 

131 8 

1407 

1514 

35"N 

1704 

1545 

1646 

1807 

30" 

20 24 

1 91 8 

2007 

2114 

25" 

21 44 

20 50 

21 28 

2222 

01 51 

0233 

01 40 

00 53 

0231 

032 5 

0220 

01 21 

051 1 

061 8 

0501 

0348 

083 1 

0925 

0820 

0721 

0951 

1033 

0 940 

0 852 

12.12 

14.55 

12.24 

9.67 

12.12 

14.55 

12.24 

9.67 

12.13 

15.66 

12.30 

8.56 

12.13 

16.42 

12.33 

7.81 

12.1 2 

14.11 

12.22 

10.1 1 

1344 

1225 

1326 

1447 

35"N 

1424 

1305 

1406 

1527 

45"N 

1704 

1512 

1645 

1840 

50"N 

20 23 

1809 

2004 

2223 

30" 

21 44 

203 8 

21 27 

2234 

01 51 

0258 

01 41 

0028 

0231 

033 8 

0221 

01 08 

051 1 

06 51 

0503 

0314 

083 1 

1034 

0824 

061 2 

0951 

1045 

0 940 

0841 

2 
NORTHERN BLUEFIN MIGRATION 

m 

Figure 1. A model for northern bluefin migration In the Pacific Ocean 

(Bay1 iff 1980). 

3 
bluef In have not been tracked using sonic tags, al I acoustic tracking 

studies on tunas, including Atlantic bluefin (Carey and Lawson 1973; Carey 

and Olson 19821, indicate that they make extensive vertical movements from 

the surface to the thermocline d u r i n g t h e course of a day (Hunter et al. 

1986) and are I lkely to sampl e most of the depth range on reasonably short 

intervals (hours). 

Initial ly, we subdivided the east-west migration corridor in the north 

Pacific into cells 2 degrees on a side; the longitudinal assignment (I.&, 

assignment to a particul ar col umn of cel Is) was based on the time of 

sunrise a- sunset. Given the identity of the column, the problem is then 

one of deciding among the approximately 10 cel Is in that column. 

The long-term mean temperatures at selected positions in this field at 

depths 0, 200 (61 m) and 400 (122 m) ft for February and August are shown 

in Table 2. In February the horizontal north-south temperature gradient is 

we1 I developed at the surface, while the vertical gradient Is SI ight (the 

mixed layer is deep, and the mixing Is thorough). Thus the temperature 

pattern at the surface in February lends itself to extraction of position 

i nformation. 

Table 2. Temperatures ('C) in the North Pacif ic (from Robinson 1976). 

Temperature ("C) 

Fe br uary August 

Depth (ft) 0 200 40 0 0 200 400 

Position Depth (m) 0 61 1 22 0 61 122 

20" 115'W 22.7 21 .3 13.7 26.3 20 .o 14.1 

25 

25 

30 

35 

25 

30 

35 

25 

30 

35 

20 

30 

40 

115 

125 

125 

125 

135 

135 

135 

145 

145 

145 

155 

155 

155 

18.3 

18.4 

16.2 

12.7 

19.8 

18.1 

16.2 

21 .7 

19.3 

15.6 

23.8 

19.3 

10.9 

17.3 

18.2 

16.1 

12.3 

19.8 

17.9 

15.9 

21 .7 

19.3 

15.3 

23.6 

18.9 

10.9 

12.1 

16.8 

14.0 

10.1 

19.2 

17.7 

13.7 

20.6 

18.7 

15.1 

22.2 

18.1 

10.3 

22 .o 

20.8 

19.1 

16.7 

21.8 

21 .7 

21.1 

24.3 

23.7 

22.2 

26.3 

25 .O 

21.5 

15.7 

18.6 

16.4 

12.6 

20.9 

18.8 

16.3 

22.5 

20.7 

16.7 

24.8 

20.9 

11 .6 

12.2 

16.3 

13.7 

9.4 

18.7 

16.7 

14.4 

20 .o 

17.3 

13.2 

22.2 

17 .O 

9.7 

4 
Table 2. (continued) 

20 165 24.8 

35 165 14.6 

45 165 7.4 

20 175 25.1 

30 175 '1 9.0 

40 175 11.3 

25" 175'E 23.1 

30 

40 

20 

35 

40 

20 

30 

45 

15 

30 

50 

20 

30 

20 

25 

30 

17 5 

17 5 

165 

165 

165 

155 

155 

155 

145 

145 

145 

135 

135 

125 

125 

125 

18.7 

10.3 

25.9 

16.2 

8.4 

25.8 

19.9 

1.6 

27.6 

19.0 

-1.7 

25.2 

19.1 

25.7 

22.7 

13.0 

24.6 

14.4 

7.3 

24.6 

18.2 

11.2 

22.3 

18.4 

10.3 

25.5 

16.2 

9.3 

25.7 

19.4 

1.4 

27.4 

18.7 

-1 .7 

24.8 

19.1 

24.7 

22.4 

13 .O 

23.5 

13.9 

7.2 

23.5 

17.3 

11.1 

20.3 

17.8 

10.2 

23.4 

15.7 

8 .O 

23.4 

18.6 

1.5 

25.6 

18.3 

-1.7 

23.5 

19.4 

23 .O 

21.7 

- 

27.2 

24.4 

14.8 

27.4 

26.4 

21 .6 

28.4 

27.2 

21.3 

28.4 

25.4 

20.7 

29.1 

26.9 . 

13.5 

29.6 

27.5 

12.3 

29.2 

28.8 

29.7 

29.2 

28.2 

26 .O 

15.6 

7.5 

26.6 

19.8 

12.3 

24.1 

20.2 

13.5 

27.1 

18.6 

12.7 

27 .O 

19.9 

2.3 

27.9 

22.4 

-0.5 

26.8 

23.8 

28.2 

27.1 

19.0 

22.8 

13.3 

6.7 

23.1 

17.2 

11.3 

20.3 

17.3 

11.7 

23.7 

15.5 

11 .o 

23.8 

17.5 

1.8 

26.5 

19.2 

-1 .o 

24.7 

20.6 

24.1 

23.4 

- 

In August, how ever, the hor lzontal north-south temperature gradient at 

the surface is less distinct. The depth of the thermocl ine ranges through 

the middle depths, 50-200 ft (15-61 m), at this time in a somewhat 

convoluted pattern. There is reason to suspect that the interannual 

variation In depth of the thermocl Ine may be appreciable. Thus, the 400 ft 

depth is probably more suitable for extracting latitudinal information in 

August. 

In general, it would be w ise to avoid drawing Inferences about 

latitude from temperature-depth structure at depths near the thermocl i ne, 

since the position of the thermucl ine may vary from year to year, and the 

measurement error in estimating depth creates I arger uncertal nly where the 

temperature changes rapidly with depth. The usual depth of the mixed 1 ayer 

at selected positions in the north Paclflc is shown in Table 3 at intervals 

of two months. 
Table 3. Mixed layer depth (m) as a function of month and position 

in the North Pacific Ocean (from Robinson 1976). 

Mi xed I ayer depth (m) 

Position Feb APr J un Au 9 OCt DeC 

20"N 155'W 104 99 70 69 73 94 

30 122 76 30 34 46 76 

40 >122 107 15 <15 46 84 

20'N 155'E 101 70 46 46 52 08 

30 116 91 18 (15 46 76 

45 >122 >122 24 (1 5 23 91 

In Tab1 e 4 we show, for each of the longitudes in Table 2, the mean 

surface temperature, the mean horizontal north-south gradient of surface 

temperature, and the mean vertical gradient, over the Interval 0 to 200 ft, 

for two or three latitudinal stations within the migration corridor at this 

longitude. AI I are based on the long-term February mean. For most of the 

corridor we can count on a latitudinal gradient of about 0.667'C per degree 

of latitude and about 0.0015'C per foot of depth. 

In Tab1 e 5 we show, for each of the long1 tudes In Tab1 e 2, the mean 

temperature at 400 ft, the mean gradient of this temperature with respect 

to I at1 tude, and the mean gradi ent over the 1 nterval 200 to 400 ft of the 

temperature with respect to depth, for the two or three latitudinal 

stations within the migration mrridor at this longitude. All the data are 

are based on the long-term August mean. For most of the corri dor we can 

expect a I atitudi nal gradient of about 0.5'C per degree of I atitUdet and 

about 0.015'C per foot (0.049'C per meter) of depth. 

These temperatures from the mean f le1 d, at the appropriate depth for 

each season, w I I I be used as reference temperatures to infer I atitudi nal 

position from observed temperature (as recorded in an archival tag). 

Because of interannual variation, the actual temperature at a given 

position may depart somewhat from the long-term mean we are using as a 

reference. Table 6 shows estimates of the extent of the interannual 

standard deviatlon in temperature at depth for various stations in the 

migration corridor. For example, the standard deviation of the February 

surface field is 1.5'CI and for August the 400-ft field has a standard 

deviation of 0.6'C. 

A second source of deviation of the observed temperature from the 

reference temperature is measurement error of the depth estimate. We 

assume a standard deviation of 30 ft (9 m). Multiplying this value by the 

appropriate depth-temperature gradient gives an estimate of the error in 

the temperature estimate, due to error of the depth estimate. It is 

0.045'C for February at the surface, and 0.45'C for August at 400 ft. 

6 
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CY 
Table 6. CI imatol ogy of sea surf ace temperature in the North Paci f ic 

Ocean (from Fleet Numerical Oceanographic Center cl lmatological 

data base 1. 

February August 

Position MSql SubSq;! N3 SSfl S.D.5 N SST S. D. 

20"N 115"W 084 05 

25 115 084 55 

35 115 120 49 

5 

18 

158 

22 .o 

18.2 

14 .O 

2.1 12 

1.4 30 

1 .o 143 

25.9 

22.7 

18.2 

1.1 

1.9 

3.1 

25 125 0 85 55 

30 125 121 05 

35 125 121 55 

16 

24 

70 

18.4 

16.6 

13.5 

0.9 15 

1 .6 32 

1.5 126 

21.3 

18.9 

17.6 

0.9 

1.3 

1.7 

25 135 086 55 

30 135 122 05 

35 135 122 55 

10 

147 

109 

20 .o 

18.0 

15.0 

0.8 12 

1.0 157 

1.2 71 

22.3 

21.4 

20.7 

1.1 

1.3 

1.9 

25 145 0 87 55 

30 145 123 05 

35 145 123 55 

60 

69 

65 

21 .6 

18.8 

15.6 

1.3 42 

1.1 32 

1.3 38 

24.1 

23.3 

22.8 

1.2 

1 .o 

1.5 

20 155 088 05 

30 155 124 05 

40 155 160 05 

21 

100 

35 

23.4 

19.0 

11.2 

0.9 21 

1.4 32 

1.9 53 

26.4 

24.4 

21.1 

1 .o 

1 .7 

2.1 

20 165 0 89 05 

35 165 125 55 

45 165 161 55 

41 

64 

44 

24.6 

14.3 

7.1 

0.8 44 

1.5 51 

1 .9 48 

27.2 

24.5 

15.0 

1.2 

1.5 

1.8 

20 17 5 090 05 

30 175 126 05 

40 175 162 05 

44 

131 

35 

25.1 

18.3 

11 .o 

1 .o 41 

1.2 43 

1.1 53 

28.2 

25.9 

20.6 

1.1 

1.2 

2.3 

25"N 175"E 091 55 

30 175 1 27 05 

40 17 5 163 05 

65 

144 

25 

2.25 

18.1 

10.4 

2 .o 42 

1.4 74 

1 .7 55 

27.5 

26.3 

20 .o 

0.9 

1.2 

2.1 

20 165 0 92 05 

35 165 128 55 

40 165 164 05 

17 

77 

46 

25.6 

15.4 

10.2 

1 .o 17 

2.4 65 

2.3 52 

29.1 

25.2 

20.5 

0.6 

1.4 

2.1 

20 155 0 93 05 

30 155 129 05 

45 155 165 55 

49 

81 

33 

26 .O 

18.4 

2.2 

1 .o 47 

1.4 58 

1.4 54 

29.6 

27.2 

12 .o 

0.8 

1.2 

1.8 

15 145 0 58 55 

30 145 130 05 

19 

31 

26.9 

18.3 

1 .o 40 

1.1 42 

29.6 

28 .O 

0.8 

1.2 

9 
Tab1 e 6. (continued) 

20 135 0 95 05 11 25.9 1.3 25 28.8 1.8 

30 135 131 05 163 18.8 2 .O 231 28.4 1 .o 

35 135 131 55 2 12.8 5.5 8 26.3 1.8 

20 125 0% 05 44 24.7 1 .6 95 29.1 1.3 

25 125 0% 55 84 22 .o 1.7 113 28.8 1.3 

30 125 132 05 53 12.8 3 .O 61 28.2 1 .o 

1MSq=Marsden square. 

'SubSq= subsq uare. 

3N= number of observations. 

4SST= sea-surf ace temperature. 

5s. D.= standard deviation. 

We w 11 I presume that the error in measurement of temperature is smal I 

in comparison to the two previous sources of error. 

Then, the total variance in observed temperature relative to the 

reference temperature for that position is the sum of the interannual 

temperature variance and the variance due to depth estimation error. 

Expressed as a standard deviation, this w II I be about 1.5"C for the surface 

in February, and about 0.75"C for the 400-ft depth in August. 

Imagine that we carried out the estimation of latitude by asking which 

cel I, of the col umn corresponding to the longitude already establ ished by 

time of sunrise, had a reference temperature closest in value to the 

observed temperature. Then the probabil ity of correct assignment to cel I 

by latitude woul d be the probabi I ity of correct assignment to cel I by 

l a t i t u d e w i t h i n D/2 degrees of the reference temperature in the correct 

cel I , where D represents the di f ference In temperature between rows 

(latitudes at the resolution of cells) In the grid. For a given cell size, 

we may compute D from the latitudinal gradient in temperature (e.g., for a 

5-degree area at the surface in February, D is 3.33OCJ and for the same 

resolutlon in August at 400 ftJ D is 2.5'C). 

Assuming that the disturbance In observed temperature re1 ative to the 

reference temperature is Gaussian, with zero mean and with a standard 

deviation as computed from the interannual variation and the error In depth 

estimation, we can r e a d i l y compute the probabi I i ty of correct I atitude 

assignment by integrating the appropriate normal density from -D/2 to +D/2. 

For example, with a grid of 5-degree areas, the probabil ity of correct 

assignment is 73% for February and 91% for August. 

A 73% probabi I ity of correct position with 5-degree resolution 

probably is not very useful, while a 91% probability of correct position is 

border1 ine. 

10 
Inspection of the magnitudes of component errors that go into the 

calculation of the total standard deviation of observed temperature 

re1 ative to the reference temperature for that depth and posl tion, 

according to the formula 

where Se Is the environmental component and sd Is the depth error 

component, shows that the total standard deviation is dominated by the 

env I ronmental var I ance ow i ng to i nterannual differences. Thus improvement 

in the accuracy of positioning must rest on reduction of the effect of this 

error. 

The interannual variation probably can be represented as an effect 

with a substantial temporal autocorrelation (at lags of at least a month) 

and w ith substantial spati al autocorrel ation (perhaps on a scat e of tens of 

degrees of latitude and longitude). Therefore, it should be feasible to 

cal ibrate the reference temperature field being used for a particular 

period (season, year) from a handful of actual measurements of temperature. 

For surface temperature the correction is readily obtained from satel I ite 

determl nations of sea-surface temperature. Far temperatures at depth, we 

would require temperature prof ile data, perhaps from ships of opportunity 

or from a network of buoys. Table 7 shows temperature readfngs from 

crulses at specif ic times in the area of interest (McGowan and W il I lams 

1973; Hayward and Mdowan 1985) indicating the potential for cal I bration on 

the basis of the smoothness of the latitudinal temperature gradient at any 

t ime. 

lmagi ne that the cal ibration of the temperature reference f iel d 

reduced the effective uncertainty in temperature at position to a standard 

deviation of 025°C (corresponding to a reduction to 1/6 of the standard 

deviation owing to interannual variation for surface temperature in 

February, or SI ightly less than 1/2 of the standard deviation owing to 

interannual variation for temperature at 400 ft in August). This value for 

St yields a prediction of 99% correct assignment at a resolution of 2- 

degree squares for February, and 95% correct assignment at a resol ution of 

5-degree squares f or the August situation. For August, further reduction 

of the error owing to interannual variation is not valuable, since at about 

this I eve1 the depth measurement error component beg1 ns to dominate. 

Conceivably, the effect of depth measurement error could be reduced through 

averagi ng over mu1 ti pl e observations. Regardl ess, the above accuraci es f OT 

positioning should be acceptable for research purposes. 

We concl ude that the archival tag appears to offer considerable 

potential for determining historical fish position, inferring longitude 

from time of sunrise and sunset, and inferring latitude from temperature at 

depth relative to a reference field. The resolution achievable using 

simp1 e long-term mean temperatures for the reference field does not appear 

very attractive. By contrast the resol ution achievable by correcting the 

reference field on the basis of some cal ibration measurements in real time 

appears to be extremely good. 

11 

. - _I_ 

-- 
Table 7. Temperature ('C) at 200 meters as a function of 

latitude at 155"W. 

Crul se 

Ursa 

Maiorl Zetes I1 Fiona2 

Lati tude 9/; 4 1/66 10/80 Mea n S. D. 

26"N 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

20 .o 

18.8 

16.2 

15.4 

14.3 

13.7 

13.3 

12.5 

11.9 

11.7 

11 .o 

10.8 

10.6 

10.5 

10.3 

10.2 

9.2 

9 .o 

8.3 

15.0 

14.7 

15.7 

13.9 

12.8 

12.7 

12.3 

12.6 

12.0 

11.9 

10.9 

11.2 

11.1 

11.2 

10.2 

10.2 

9.5 

8.7 

7.7 

15.0 

15.0 

13.8 

13.5 

12.3 

12.5 

12.1 

11.6 

11 .6 

11.3 

10.7 

9.9 

9.9 

9.5 

9.3 

9 .o 

8.3 

7.9 

7.2 

16.7 

16.2 

15.2 

1 fte3 

13.1 

13 .o 

12.6 

12.2 

11.8 

11 .6 

10.9 

10.6 

10.5 

10.4 

9.9 

9.8 

9 .o 

8.5 

7.7 

2.9 

2.3 

1.3 

1 .o 

1 .o 

0.6 

0.6 

0.6 

0.2 

0.3 

0.2 

0.7 

0.6 

0.9 

0.6 

0.7 

0.6 

0.6 

0.6 

'MCGwan and W I1 I ims 1973. 

2Hayward and McGcwan 1985. 

ACKN Cw L EDG EMENTS 

James D. Ryan and Lawrence E. Eber provided crucial technical 

ass1 stance In acqui rl ng the data and programming. We al so acknow ledge Andy 

Dizon and Carol Kimbrel 1's extensive editorial help in bringing this note 

to completion. The expense of programming and computation was borne by Jay 

Bar1 ow and John Hunter. We thank Celeste Santos-Methot for organ izatlorial 

assistance. 

12 
L I TERATURE C I TED 

BAYL I FF, W. H. 

1980. Synopsis of biological data on the northern bluefin tuna, 

Thunnus thynne (Linnaeus, 17581, in the Pacific Ocean. InterAmer. Trop. Tuna Comm., Spec. Rep. 2:261-293. 

CAREY, F.G., and K.D. LAWSON. 

1973. Temperature regul ation in free-swimming bluef in tuna. Cbmp. 

Biochem. Physiol. 44A: 375-392. 

CAREY, F.G., and R.J. OLSON. 

1982. Sonic d-racki ng experiments w ith tunas. Int. Comm. Conserv. 

Atl. Tunas Collect. Vol. Scl. Pap., 17:458-466. 

YAYWARD, T.L. and J .A. McGCWAN. 

1985. Spatial patterns of chlorophyl I, primary production, 

macrozoopl an kton biomass, and physical structure In the central 

North Paclf ic Ocean. J. PI ank. Res. 7:147-167. 

HUNTER, J.R., A.W. AFGUE, W.H. BAYLI FF, A.E. DlZON, A. FONTENEAU, 

D. GOODMAN, and G.R. SECKEL. 

future research. FA0 Fish. Tech Pap. (In press). 

1986. The dynamics of tuna movements: an evaluation of past and 

LaV IOLETTE, P. E. and S. E. SEIM. 

1969. Monthly charts of mean, minimum, and maximum sea surface 

t e m p e r a t u r e o f the North Paclf ic Ocean. Nav. Oceanog. Off., Spec. 

Pub. NO. 123, 62 p. 

McGOWAN, J.A. , and P.M. WILLIAMS. 

1973. Oceanic habitat differences in the North Pacific. J. Exp. Mar. 

Bi 01. Eco~. 12:187-217. 

RCB INSON, M. K. 

1976. At1 as of the North Pacific Ocean monthly mean temperatures and 

mean sal inities of the surface I ayer. Nav. Ocean. Off. Ref. Pub. 

2, 19 173 fig. 

U. S. NAVAL OBSERVATORY. 

1972. The Nautical AI manac for the Year 1974. U.S. Gov. Print. Off., 

Washington, D.C. 

YAMANAKAI H. 

1984. The relationship between El NiRo episodes and fish migration 

and yields in the western Pacific Trop. Ocean-Atmos. 

News1 etter 25: 2-4. 

13 

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(October 1984) 

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(October 1984) 

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(May 1 985) 

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Proceedings of the workshop on the fate and impact of marine 

debris, 27-29, November 1985, Honolulu, Hawaii. 

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R.J. MORROW and E.K. BUELNA 

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Hawaiian Monk Seal observations and captive maintenance project 

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W.G. GILMARTIN, R.J. MORROW, and A.M. HOUTMAN 

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