Benthic Ostracoda in the Benguela System (SE Atlantic)\" A multivariate analysis

.~larine Micropaleontology, 22 ( 1993 ) 7 1 - 9 2

71

Elsevier Science Publishers B.V., A m s t e r d a m

Benthic Ostracoda in the Benguela System (SE Atlantic)" A multivariate analysis R.V. Dingle and J. Giraudeau Micropalaeontology Research Unit, South .-lfrican Museum, P.O. Box 61. ( "ape l-~wn ,~¢000.S~mth ..l/rwa ( Received August 24, 1992: revision accepted March 22. 1993 )

ABSTRACT Q-mode factor analysis of ostracod faunas from 127 modern sediment samples associated with the Bcnguela System over the continental margin off Namibia and South Africa identifies ten Factor Associations of species ( FA ). These FA account for 93% of the variance, and can be related to nine sea-bottom variables: temperature, salinity, dissolved oxygen, total organic matter, elemental iron ( = terrigenous component ), calcium carbonate, glauconitc, sand and mud. Transfer functions for these variables are calculated for future palaeo-environmcntal analyses. On the modern continental slope FA Henryhowella melobesiotdes and Krithe capensis are controlled primarily by crossshelf temperature gradients, while on the uppermost slope and outer shelf dissolved oxygen values restrict the distribution of FA ()'therella namibensis (oxygen depleted ) and Ruggieria o'theropteroides ("normal'" oxygen levels ) in the north and south, respectively. Inner and middle shelf faunal associations are controlled by high salinities north of 26~S ( FA Pahnoconcha walvisbaiensis), while substrate variables (terrigenous, glauconite, mud and organic matter) are the main determinants farther south (FA Bensonia knysnaensis knysnaensis, Pseudokeijella lepralioides, Bairdoppilata simple.~:. ..lmhostracon keeleri/flabellicostata and Paracyprts lacrirnata). These faunal/hydrographic relationships are linked to various dynamic oceanographic features such as upwelling, cross-shelf advection and shelf-parallel bottom currems.

Introduction

The nearshore ( 15 m ) to mid-slope (950 m) benthic ostracod fauna from the continental margin off southwestern Africa (Fig. 1 ) comprises 123 species in at least 54 genera (Dingle, 1992, 1993). An analysis of the environmental preferences of the most abundant species suggests that the relationships between the fauna and oceanography are influenced mainly by shelfupwelling and the nature of seafloor sediments (Dingle, in press). In the present paper, we apply a multivariate statistical analysis to the data to establish quantitative links between ostracod assemblages and environmental parameters (Figs. 2 and 3), and to develop transfer functions for use in palaeo-oceanographic studies. lmbrie and Kipp ( 1971 ) first used the technique of Q-mode factor analysis and multiple regression to extrapolate into Quaternary sed-

iments the modern sea-surface temperature and salinity signals of planktic foraminifera. Numerous workers have since used this method, and it has recently been modified by Dowsett and Poore (1990) for application to Pliocene sediments. In addition, it has been applied to other planktic groups such as radiolaria (Hays et al., 1989), coccolithophores (Giraudeau and Pujos, 1990) and diatoms (Schrader and Sorknes, 1991 ). For benthic taxa, the range of variables affecting their distribution relates to both the water column and substrate and is consequently so much larger. Regional studies involving the technique have been made on benthic foraminifera (Mudie et al., 1984; Williamson et al., 1984) and Ostracoda (Cronin and Dowsett, 1990) from the continental shelves of North America. In the latter study, seven factors were related to one independent variable (bottom-water temperature), which was assumed to account for all the variance,

0 3 7 7 - 8 3 9 8 / 9 3 / $ 0 6 . 0 0 © 1993 Elsevier Science Publishers B.V. All rights reserved.

72

R.V. DINGLE AND J. G I R A U I ) E A t

?Jl k ~'

.

\ - .~...

AB

/

)

WR

~,

CB

Fig. 1. Sea-floor sediment samples from which ostracods were recovered. Data from the additional sites (squares) were used to complete the maps in Fig. 2 where we had insufficient environmental data to include the samples in the full factor analysis. Insert map shows location of area in the Southeast Atlantic. Depths in kilometres. For site coordinates and depths see Appendix 1. Abbreviations: OS=Orange shelf, WR=Walvis Ridge, AB=Angola Basin. CB=Cape Basin.

while Williamson et al. ( 1984 ) correlated eight factor assemblages with water depth and five environmental parameters (temperature, sal-

inity, gravel, sand and mud). Mudie et al. (1984) correlated seven factor assemblages with depth, temperature and salinity. The regional oceanography off southwestern Africa consists essentially of three deep-water masses abutting the continental margin (Antarctic Bottom Water, North Atlantic Deep Water and Antarctic Intermediate Water), and a mixed layer on the continental shelf (e.g. Hart and Currie, 1960; Stander, 1964; Shannon. 1985; Chapman and Shannon, 1985: Lutjeharms and Meeuwis, 1987: Shannon et al.. 1990) (Figs. 2B and 3 ). The mixed layer has several complexly related components, and is subject to considerable variability. Surface waters for the most part emanate from the South Atlantic gyre and move in a northerly direction more or less parallel to the coast. This is the main component of the Benguela Current, and strong wind stress over it results in quasi-permanent regions of subsurface upwelling of varying intensity. Other major features are, in the north, intrusions of sub-tropical water adjacent to the coast ( surface Angola Current ) and west of the shelf edge (subsurface), and in the south, periodic intrusions of vortices and filaments of warm Agulhas Current water around the southern tip of the continent (Fig. 2B). Southward subsurface movement of shelf water has been documented by De Decker (1970) and Nelson (1989) along most of the west coast (poleward undercurrent; Fig. 3 ). It is the relatively complex structure of the water masses of the Benguela System that gives rise to the great variability in continental shelf sedimentary environments off southwestern Africa (Rogers and Bremner, 1991 ). Here we will demonstrate that a quantitative approach to the benthic micropalaeontology can help our understanding of the relationships between faunal distribution and hydrography, and ultimately to provide a palaeoenvironmental tool in the form of transfer functions for various independent variables.

73

BENTtlI(" O S T R A C O D A IN T H E B E N G U E L A SYS'FEM ( SE A I L.,~NTI("

I

I~OE

~

i o 15

4 ILLI

!!!!!!N!!!!I!

T or r,genou'..,

J

,

I emperalure

t

Sahmly ~

.'..:~ : . .

Oxygen Temp//sahnll,t

-10 C) AAIW AAIW a d v e c h o n (~) Angola current (~ Angola off shelf w a l e r (~) AOW a d v e c l l o r ' (~) P o l e w a r d u n d e r c u r r e p ! (~ Shelf e d g e let ~) Agulhas w a l e r (~) Fluvial mpu!

WALVIS BAY

25 °

~J

i3

,,

,LUDERITZ

',', 1 4 ~\x< \\ IJ Iii

rl I,

30 °

barren

:APE TO

35°s I

A [

1

I

1

, ~ \ 2 /6, I

I

1

1

I

I

Fig. 2. Factor associations and hydrographic regimes. (A) Distribution of Factor Associations l - l O . as designated in "Fable 2. Areas were delimited by plotting factor scores > 0.7. Tentative boundaries in the area offshore l,udcritz are based on an enlarged data set using the additional sites shown in Fig. 1. Note Factor Association 7 is outlined by a long-dashed line. Inshore areas with numerous barren sites arc enclosed by dotted lines. It "R= axis of Walvis Ridge. ( B ) Hydrographic rcgimcs (slope, shelf edge and shelf) and the main dynamic components ( 1 - 9 ) . Plus and minus signs dcnote positive and negative correlations of the factor associations with the controlling parameters ( temperature etc. )..4,411~'= Antarctic Intermediate Water.

74

R.V. DINGLE ,ANt).I GIRa.t I)EAI~

Slope

Shelf edge

Shelf

J

Ihydrographic regimes

,=

22oS

-BC PUC

PW

Oxygen-depleled ! ngola Basin waler (~

S alin,ly M i n , m u m / f Zone AAIW .~" I

(~

~

J

+S +1 ........

O _CaCO3 i \ -GI

-O~

\

X,

qHM

o-,-*x ,30°S

®Puc I -PL RC

+02 +SO -MORG

I'+Fe ~.! ~-GI -- CaCO3 - MORG ÷ 02 -Md -Md ÷ MORG

+l-O

+T +SO

~)

+~.t. ~

• ..1d --,,a(,O:~

Oxygen deficient water

Sahnily Minimum Zone: AAIW

KC -T HM -S -T +Md -S +Md

BKK

[ ~

Substrate control

Fig. 3. Schematic cross-shelf relationships of sea-floor hydrographic regimes and oceanic feature with factor associations. based on profiles at 22°S and 30~S (thickened lines are the sea-floor). Double lines separate the hydrographic regimes, single lines the factor associations. The latter are designated by their dominant taxon (e.g. tl.~,I= Henryhowella mel,#,~'. sioides). Plus and minus signs indicate direction of movement ofwater masses (negative moves into plane of section i.e. northward). Beneath each taxon are listed the three ranking independent variables based on correlation coefficients ( + = positive,- = negative). Abbreviations. Oceanography: AAI I*'= Antarctic Intermediate Water. B('= Bengucla Current, PUC=poleward undercurrent. Factor Associations: HM=lteno,howella me/obesioides, KC=Krithe ,upen.~t,. PI4"= Palmoconcha walvisbaiensis, R ( ' = Ruggieria ~3'theropteroules, PAL = Para~37~ris lacrimata, AK= 4mhostrac,m kecleri, BS= Bairdoppilata simplex, PL = Pseudokeijella lepralioides, BKK= Ben3onia knysnaensis knrsnaen.sts. Independent variables: 02 = dissolved oxygen, ('a('03 = carbonate content, Gl= glauconite, S = salinity, T= temperature, .~ld---m ud. Sd= sand, MORG= total organic matter, /-'e= terrigenous component. Data analysis O u r a n a l y s i s i n v o l v e d the thirty-six M o s t Abundant Species (MAS) of Ostracoda (which

a c c o u n t for 9 5 . 4 7 % o f total s p e c i m e n s available for study: T a b l e 1 ) in 127 surface sedim e n t s a m p l e s f r o m the c o n t i n e n t a l m a r g i n bet w e e n n o r t h e r n N a m i b i a ( 19 ° S ) a n d C a p e

BENTHI( OSTRACODAIN THE BENGUELASYSTEM (SE ATLa.NTI(') TABI.E 1 Statistics of d o m i n a n t species. Values are percentages of the total n u m b e r of valves of the 36 MAS in each sample. N = 127 Mean

Max

Min

SI)

Ruggierm cTtheropteroides Pseudokeijella lepralioides Ilenryhowella melohesioides

21.26 14.72 13.09

100.0 100.0 100.0

0 0 0

27.7 28.3 27.5

Palmoconcha walvishaiensts

12.49

100.0

0

31).2

9.20 4.47 2.68 2.29 2.24 1.67 1.64 1.48

100.0 100.0 64.6 44.4 100.0 27.5 100.0 100.0

0 0 0 0 0 0 0 0

22.1 14.4 9.6 7.5 12.2 4.9 9.6 9.7

1.31 1.25 1.07 0.95 0.93 0.92 0.81 0.74 0.74 0.71 0.67 0.66 0.54 0.25 0.24 0.21 0.20 0.16 0.14 0.10 0.10 0.05 0.04 0.01

85.7 66.4 15.9 25.0 50.0 13.9 43.6 14.7 17.2 16.8 14.5 50.0 50.0 11. I 14.7 6.0 9. I 14.3 13.8 2.8 6.3 3.2 3.8 0.6

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

8.5 6.2 3.2 3.5 4.8 2.6 5.2 2.4 2.3 2.4 2.1 4.7 4.5 I. 1 1.5 0.9 1.1 1.3 1.2 0.5 0.6 0.3 0.3 O. I

('vtherella namibensis l'arac3,prts lacrimata Krithe capensis Bairdoppilata stmph;~ Bensonia k. knysnaensts Arnbostracon keeleri AmbostraconJTabelltcostata .~,lacro(3"pris cf. M. matuenda .,lustraloectahdleri Buntonia namaquaensis Buntoma bremnert Buntonta roser~feldi Buntonta rogerst l)oratocvthere exdts Bensonia k. robusta Incongruelltna venusta ( ),theropteron whatleyi l'osetdonamicus panopsus ( "ho'socvthere craticula I "rocvtherets arcana Neocaudttes lordi Xestoh'beris ctfricana ( "ytheropteron trmodosum Krithespatularis Buntoma gibhera ( "vtherella dromedaria ( oqutmha hircht Neoc3'thertdets t,oomeri Neocaudttes osseus ,lustroaurtla rugosa Xestoleberis hartmanni Buntoma dewett SI) = standard deviation.

Agulhas in South Africa (35°S; Fig. 1; see Appendix 1 for coordinates and depth of each site). Sediment samples were collected from the sea floor using a Van Veen grab and processed by washing through a 63/~m sieve. Ostracoda were picked from > 125 #m sieve fractions. The data set used was that by Dingle ( 1992,

75

1993, in press), which contained 270 samples. This number was reduced to 127 by omitting 62 samples from sites lacking values for the full range of sea-floor environmental variables, and 81 barren sites. Table 1 shows the mean, maximum, m i n i m u m and standard deviation of the relative abundances of the MAS in the sediment samples. The highest ranking six species combined account for > 75% ofthe total of the 36 MAS, and attention is drawn to the relatively wide diversity at the generic level of this assemblage ( 2 4 = 67%). The following environmental variables were considered: temperature, salinity, dissolved oxygen, total organic matter ( M O R G ) , elemental Fe, calcium carbonate, glauconite, sand and mud. These values were extracted for each site from the data sets of Birch ( 1975 ), Rogers ( 1977 ), Bremner ( 1981 ) and Dingle and Nelson (in press) (see Dingle, in press, Dingle and Nelson, in press, and Bremner and Willis, 1993, for details of analytical techniques and data processing). The elemental Fe determinations were done on the clay fraction of the sediments and are reckoned to be reliable indicators of the terrigenous component (Bremner and Willis, 1993). Depth was not considered separately within the factor analysis because its relationship to species distribution is clearly coincidental with any dependence of other variables with depth. However, in the discussion some remarks are directed towards this aspect in order to assist in palaeobathymetric reconstructions. Computation was carried out on a PC running a Q-mode factor analysis program [Oregon State University's ('I.IMAI'/(',kBFAC program of Imbrie and Kipp (1971)]. The varimax solution involved one rotation of the matrix, resulting in two matrices, the one giving the composition of each sample in terms of the resultant factors (varimax factor matrix), and the other the species composition of the factors (varimax factor score matrix). Multiple stepwise regression analysis was then run on the varimax factor and environmental vari-

76

able matrices to calculate transfer functions for each variable [Oregon State University's CLIMAP-REGRESS program of Imbrie and Kipp ( 1971 ) ]. A variance cutoff value of 0.005 was used.

R.V. DINGLE AND J. GIR.AUDEAU "FABLE 2

Summary of factor scores and ostracod associations based on 127 samples. See Appendices I and 2 for complete factor matrix Factor

% var.

Species

Results I

Ten factors generated by the analysis accounted for 93% of the total variance, with 86% of the sample sites having a communality > 0.90. As Cronin and Dowsett (1990) point out, selecting the number of factors is partly arbitrary, but in the previous study ( Dingle, in press) ten faunal associations were distinguished, and in the present analysis nine factors were necessary to account for more than 90% of the total variance. The factor score matrix shows that each factor is characterized by a high loading with one particular species (after which it is named), and a lower correlation with minor species. These Factor Associations of species ( FA ) are summarized in Table 2 (full matrix in Appendices 1 and 2 ), and their distribution on the continental shelf is shown in Fig. 2A. Further, a stepwise multiple linear regression analysis was made using the ten FA and the independent environmental variables to develop transfer function equations for each sea-floor parameter. The results of this analysis are summarized in Table 3, which shows the multiple correlation coeffÉcients and standard errors of estimate for each independent variable (the full transfer equations are given in Appendix 3 ). Finally, in order to assess which independent variable is most strongly correlated with particular FA, we produce the matrix of correlation coefficients between all the dependent and independent variables (Table 4). Using the two (or three) highest coefficients, we have computed various statistics for those environmental parameters that most strongly influence the distribution of each FA on the modem continental shelf (Table 5 ).

I.acto~ Sc()r("

25.3

Ruggieria cytheropterotde.s tSzseidonamtclt5 panopst~ Doral oc)'t here e vt l l.~

O.t}3 7 ,1.[137

[1.996

2

17.2

Pseudokeuella h'praltoMcs ( "hrysocj'therc cratwula Neocytheridet~ t,oomert

o.997 0.037 11.004

3

13.4

Pahnoconcha walvtshawnsts ( rocj'thcret.~ ar~a na

(I.097

lh,nrvhowella melobestotde~

I).9q4

14.3

( 1.()33

5

9.9

( ~vtherella namdJenst.s ( )'theropteron trtnodosum

0.995 ) 02 ~

6

4.0

Parao'prts lacrtmala Buntonta ttamaquaenst.~ Neocaudite~ lordt ( oquimtJa bircht

O. 123 O. 114 0.035

Batrdoppilata st mplex A ustrah)ecia Juller~ Macroo'prts cf. :~,1. metuenda C)'therella dromedarta Xestoleberts hartmannt

IL 774 O.428

Krtthe capensc~ Buntonia bremm'rl lncongruelhna vcnusta Buntonia rosenteldt f'.vtheropteron whatleyt Krithe spat ulart.s

I L97 tk o. I 12

1.9

Bensonta k. kn.l'.snaensts Xestoleberts a[rtcana .4 ustroaurila rugosa

0.988 0.012 0.003

1.7

Arnbostracon flabellicostata Ambostracon keeleri Bensonia k. robusta Buntonia rogerst Neocaudites osseu.~ Buntonia gibbera Buntonia deweti

0.779 0.484 i). 27 I 0.072 0.017 0.015 0.002

2.8

2.5

10

0.980

0.400 0.026

0.016

(I.067 ~/.062 0.035 I).014

BENTItlC OSI RACODAIN THE BENGUELASYSTEM (SE AI L.¢NTIC)

TABI_E 3 Summa%' of mutiple regressionanalyses(See Appendix 3 for equations of transfer functions)

Temperature Salinit.~ Dissol~ cd ()2 Organic matter Fe Ca('()s ( ilauconite Sand Mud

MCC

SEE

range

0.863 0.856 0.820 0.510 0.605 0.448 0.572 0.452 0.562

1.358 0.126 0.782 2.665 1.361 25.995 14.049 17.767 16.956

11.00 C 0.93%o 4.40 ml/l 17.20% 8.60% 91.50% 86.00% 92.70% 94.50%

Factor associations Factor I This association is dominated by Ruggieria cytheropteroides, with minor contributions by Poseidonamicus panopsus and Doratocythere exilis. It occurs as a continuous zone on the outer shelf and upper slope from the southern part of the area to 22 °S, with a small outlier at 20°S on the southern flank of the Walvis Ridge abutment plateau. The main controlling parameters are the dissolved oxygen value of the bottom water (positive correlation) and the sand content of the sediment (positive correlation ). Mean values for these parameters ( 3.4 ml/I and 74.5%, respectively), together with the relatively strong positive correlation with CaCO3 and negative correlations with temperature and salinity, show that the distribution of this association is related to the penetration of well-oxygenated, cool, low salinity water from about 400 m onto the outer shelf (Dingle and Nelson, in press), where the bottom sediments are carbonate-rich sands.

77

to 26°S, with a further narrow occurrence between 22 ° and 24°S. The main controlling parameters are the terrigenous (=elemental iron) content of the bottom sediments and bottom water temperature (both positive correlations). Mean values for these parameters (4.2% and 9.7~C, respectively), together with the relatively high positive correlation with sand content, show that this association favours hydrographic conditions intermediate between the cool, advected upper slope water, and warm, oxygen-deficient water emanating from areas north of 25 ° S. The relatively strong correlation with terrigenous, sandy sediments reflects FA 2's wide distribution on the shelf between the Orange and Olifants rivers.

Factor 3 This association is dominated by Palmoconcha walvisbaiensis, with a minor contribution by Urocythereis arcana. It is confined to areas north of 26~S, where it occupies almost the whole inner to outer shelf area (except two large inshore zones to the north and south of Walvis Bay which are barren of ostracods). Three parameters have a strong correlation with this association: temperature and salinity (both positive), and dissolved oxygen (negative), indicating that the primary control on distribution is the warm, saline, oxygen-deficient water produced by the upwelling regime of the northern Benguela system (Dingle and Nelson, in press). The bottom sediments are high in MORG and opal (average 28%; Dingle, in press), and low in terrigenous detritus (Table 5; Dingle, in press), and constitute the diatomaceous muds described by Bremner (1981).

Factor 4 Factor 2 This association is dominated by Pseudoke(jella lepralioides, with minor contributions by Chrysocythere craticula and Neocytherideis boomeri. It occurs as a continuous zone on the middle shelf from the southern part of the area

This association consists solely of the species llenryhowella melobesioides. It is confined to the upper continental slope, where temperature and salinity are the dominant controls (both negative correlations). Their low mean values (5.6-~C and 34.75%0, respec-

78

R.V. f)INGI.E A N D .I. ( ; [ R M IDEAI"

TABLE 4 Correlation matrix for factors and independent variables

Temperature Salinity Oxygen MORG Fe CaCO3 Glauconite Sand Mud Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor7 Factor 8 Factor 9 Factor 10

Temperature

Salinity

Oxygen

MORG

Fc

('a(.'O.~

Glauconitc

,%and

Mud

1 0.908 -0.620 0.295 -0.087 -0.240 -0.210 0.185 -0.373 -0.198 0.175 0.643 -0.634 0.015 -0.063 -0.079 -0.228 0.131 0.151

0.908 1 -0.721 0.380 -0.235 -0.200 -0.247 0.055 -0.274 -0.270 0.067 0.756 -0.493 0.017 -0.173 -0.096 -0.223 0.033 0.108

-0.620 -0.721 I -0.582 0.2111 0.095 0.410 0.255 -0.090 (/.468 0.1)56 - 0 . 6 3 .7 I).323 - 0.347 0.203 0.203 0.155 -0.061 -0.113

0.295 0.380 -0.582 I -0.151 -0.120 -0.338 -0.479 0.512 --0.330 --0.041 11.369 -0.106 0.081 -0.049 .... 0.267 -0.016 -0.077 0.131

-0.087 -0.235 0.210 -0.151 1 -0.408 0.209 0.042 --0.022 -0.060 0.216 -0.318 -0.074 -- 0.093 0.405 0.150 -0.034 0.290 0.012

--0.240 --0.200 1/.1195 -11.120 -0.408 I --0.376 -0.156 0.1170 0.190 0.004 -0.222 0.058 (I. 179 -.C).323 -0.093 0.143 -0.137 0.085

-0.210 -11.247 0.410 -0.338 0.209 -0.376 I I).3711 -11.295 I).244 -I).143 0.174 0.199 -- 0.12~ 1/.178 0.389 -0.065 -0.016 -11.076

(I. 1~;5 0.055 ~1.255 -- i).47t~ IL042 .il.I St, (I.371! I - I I 87¢~ ().343 ILI5~ .... 1/.034 --I1.2~7 ().064 II.tll" I!.(153 -0.176 1/.097 ().(JSt~

II.373 -!).274 -- 0.09(} 0.512 0.022 0.i}70 11.295 0876 I ;) 2-I tLl~'~ . ci i),~¢, cL'~83 !l.t)47 ql.t~2 ~, . ~L22i,~ qL211i -0.165 ILl ~I

RC = Ruggieria cytheropteroides, PL = Pseudokeijella lepralimdes, PW = Pahnoconcha walvisbaiensis, H M = tteno'howel/a mch,besioides, CN = Cytherella nambibensis. PAL = Paraoppris lacrimata, BS = Bairdoppilata simpler. Kf" = Krithe , ape~t.gl BKK = Bensonia knysnaensis kn.vsnaensis, A F / K = A mbostracon flabellicostata/keelerl.

tively ), together with relatively strong positive correlation with dissolved oxygen, confirm that this association is confined by the upper limits of the salinity m i n i m u m zone of the Antarctic Intermediate Water (AAIW), which lies below the oxygen-deficient upper water masses (Dingle et al., 1989). These regions are characterized by fine-grained sea-floor sediments (relatively high positive correlation with m u d content: Table 4).

Factor 5 This association is dominated by Cytherella namibensis, with a minor contribution by Cytheropteron trinodosum. It is confined to outer shelf and upper slope areas north of 25°S, where the main controlling parameter is the dissolved oxygen content of the bottom water (negative correlation). The high mean carbonate value of the sediments in this area (compare with values for whole data set, Table

5 ) reflects the paucity of terrigenous influx off" northern Namibia.

Factor 6 This association is dominated by Paracvpris lacrimata, with minor contributions by Buntonia namaquaensis, Neocaudites k~rdi and Coquimba birchi. It is confined to small sectors of the mid- to outer shelf off Luderitz and the Olifants River, and the middle shelf in the extreme south. The main controlling parameters are the terrigenous (positive correlation) and carbonate (negative correlation ) values of the sea-floor sediments. The latter in particular is low compared to the mean for the whole data set (16.00 compared to 50.72%), while the average elemental Fe content is almost double the regional mean (6.00 versus 3.60% ). These relationships show that FA 6 favours carbonate-poor, terrigenous-rich sediments with an affinity for increasing M O R G values.

79

B E N T I I I ( ()$1 R A C O D A IN I H E B E N G I I E L A SYSTEM ( SE A T L A N T I C )

IZactor I R("

Facto r 2 PL

Factor 3 PW

Factor 4 HM

Faclor 5 CN

F a c l or 6 PAL

I-aclor 7 BS

Facto) 8 KC

Faclor 9 BKK

Factor 10 AF/K

-0.198 -0.270 0.468 -0.330

0.175 0.067 0.056 -0.041

0.643 0.756 -0.637 0.369

-0.634 -0.493 0.323 -0.106

0.015 0.017 -0.347 0.081

--0.060

0.216

-0.318

-0.074

-0.093

0.190 0.244

0.004 -0.143

-0.222 -0.174

0.153

-0.034

-0.063 -0.173 0.203 -0.049 0.405 -0.323 0.178 0.017 0.025

-0.079 -0.096 0.203 -0.267 0.150 -0.093 0.389 0.053

-0.228 -0.223 0.155 -0.016 -0.034 0.143 -(}.065 -0.176 0.210

0.131 0.033 -0.061 -0.077 0.290 -0.137 -0.016 0.097 -0.165

0.151 0.108 -0.113 0.131 0.012 0.085 -0.076 0.056 -0.131

0.343

0.058 0.199 -0.297

-0.064

-0.097

-0.096

I

-0.085

-0.362

-0.187

-(}.062

-0.038

-0.068

-0.034

--(}.101

-0.073

-0.085 -0.362

I -0.244

-0.244

-0.267 -0.219

-0.243 -0.046

-0.187

-0.267

-(}.219

- 0.062 -0.038 --0.068 -0.034

-0.243 -0.087 -0.126 - 0.099

-0.046 -0.140 -(').141 - 0.095

-0.087 -0.140 - 0.096 -0.077 1

-0.126 -0.141 - 0.036 -0.089 0. 120

-0.099 -0.095 0.069 -0.073 - 0.046

-0.114 --0.030 - 0.040 -0.053 - 0.051

0.002 -0.028 - 0.077 -0.035 - 0.038

-.0.101

- 0 . I 14

-. 0.073

0.002

I

0.047

-0.220

-0.271

I

0.383

0.179 -0.129

-0.215

-0.215 -0.096 -0.036 0.069

1 -0.077 -0.089 - 0.073

-0.030

-0.040

-0.053

- 0.028

- 0.077

- 0.035

O. 120

I

- 0.046

- 0.075

- 0.051 - 0.038

0.064 0.080

- 0.(}75 I

- 0.040 - 0.051

0.064

0.080

- 0.040

- 0.05 l

I 0.045

0.045 I

spatularis. It occurs in a very. narrow zone on Factor 7 This association is d o m i n a t e d by Bairdoppilata simpk, x, with important contributions by A ustraloeciafulleri and Macrocypris cf. M. matuenda, and minor contributions by Cytherella dromedaria and Xestoleberis hartmanni. It occurs in a narrow zone that crosses the mid to outer shelf off the coast of N a m a q u a l a n d and the SW Cape, where the main controlling parameters are the glauconite (positive correlation) and M O R G (negative correlation) contents of the bottom sediments. Clearly, the highly glauconitic sands in this area are low in organic matter due to local oceanic phenomena such as high currents or dissolved oxygen values.

Factor 8 This association is d o m i n a t e d by Krithe capensis, with minor contributions by Buntonia bremneri, Incongruellina venusta, Buntonia rosenfeldi, Cytheropteron whatleyi, and Krithe

the upper continental slope, and stretches almost the length of the study area. The main controlling parameters are the water temperature (negative correlation) and mud content of bottom sediments (positive correlation). The stronger correlation with CaCO3 than Fe (Table 4) suggests that this association favours carbonate-rich mud. These data confirm Dingle et al.'s (1989) recognition that Krithedominated slope faunas lie at the upper boundary of the salinity m i n i m u m zone of the AAIW, below which lower temperatures and salinities favour the FA 4 (Henryhowella meIobesioides). A short distance farther up slope, warmer water, and either oxygen-poor or sandy bottom sediments are favoured by other associations ( C)'therella namibensis and Ruggieria cytheropteroides north and south o f ~24~S, respectively: see Figs. 2 and 3 ).

Factor 9 This association is dominated by Bensonia

80

R.V. DINGLE AND J (ilRAIIt)EAt

TABLE 5 Statistics for independent variables A. Values for whole data set

Average Maximum Minimum SD n

temp

sal

ox~g

MORG

Fc

(.a(().,

glau

8.9 14.0 3.0 2.6 127

34.8 35.3 34.4 0.2 127

2.7 4.8 0.4 1.3 127

4.5 17.5 (I.3 3.0 1_, ~~

3.0 9.5 03) 1.7 127

50.7 q2.q 1.4 28.3 127

6.7 86.0 0.0 16.5 I"':

sand

in ud

b 5.':J

~(I.{~

q6. I L4 I~L3 i2-

=~6.6 2~

19.,',; .2-

B. Values for sample sites used to construct Fig. 2. Highest two or three correlatives for each factor

Average Maximum Minimum SI)

n

Average Maximum Minimum SD n

.Average Maximum Minimum SD n

Factor I

Factor 2

Faclor 3

R. o,theropterotdes

I'. 1~Tn'aliotde.~

P ~ alvtshaten~t.~

oxyg

sand

Fe

temp

temp

sal

ox) g

3.4 4.5 0.7 1.1 4q.

74.5 93.2 38.9 12.4 43

4.2 q.5 2.0 I.g _-,7

0.7 12.2 8.5 0.9 ,-~

12.6 14.0 8.5 1.2 i t)

35.2 35.3 343) 0. I i t)

0.8 1.4 0.4 0.3 i t)

Factor 4

Factor 5

Factor 6

]"actor :

H. melobesiotdes

( namibensLs

P. lacrtmata

11..~nnph'.\

temp

sal

ox~g

CaC(_)3

Fe

5.6 10.3 3.0 1.7 21

34.5 34.8 34.4 0. I 21

1.6 2.5 0.9 0.4 16

61.7 79. t 7.1 18.8 16

6.0 7.0 5.0 (I.q 7

Ca('Ox

glau

16.0 57.0 4.9 17.4 7

37.6 83.0 0.0 35. I 7

Factor 8

Factor 9

Factor 10

K. capensis

B.k. knysnaensis

.1..llabelltcostata/keelert

I-c

mud

temp

mud

MORG

17.2 32.8 2. I 10.1 7

I 1.2 13.4 g. 5 1.6 7

17.2 38.6 ,',;.2 1().5 7

6.3 16.2 l.S 4.5 7

mud

temp

50.9 75.8 27.4 15.3 7

5.9 7.2 4.0 1.0 7

4.9 7.0 2.0 2.0 7

MOR(I I.t~ 23) ~1.5 (i.7 7

temp = temperature ( ° C ), sal = salinity (%o), oxyg = dissolved oxygen ( m l / I ), M O R G = total organic matter ( % ), Fe = elemental iron (%), C a C O 3 = c a r b o n a t e (%), glau =glauconite (%). n = n u m b e r of samples. S D = s t a n d a r d deviation.

BENTHIC OSTRACODA IN THE BENGUELA SYSTEM (SE ATLANTIC)

knysnaensis knysnaensis, with minor contributions by Xestoleberis africana and Austroaurila rugosa. It is confined to a narrow inner-shelf zone between the southern end of the area and the vicinity of Luderitz, and in which the main controlling parameters are the terrigenous (positive correlation) and m u d (negative correlation) values of the bottom sediments. These preferences are reinforced by less strong, but relatively high positive correlations with temperature and sand, and negative correlations with CaCO3. In addition, this is one of only four factors that correlates negatively (albeit weakly) with dissolved oxygen. The sedimentary environments favoured by this association are mud- and carbonate-free, terrigenous and sandy, with warm bottom water, which explains why Bensonia knysnaensis knysnaensis is the only species occurring abundantly on the inner shelf that is also found in lagoons and estuaries on the west and south coasts (Benson and Maddocks, 1964; Hartmann, 1974; Dingle, 1992). Factor I0 This association is dominated by Ambostracon flabellicosta and A. keeleri, with minor contributions by Bensonia k. robusta, Buntonia rogersi, B. gibbera, B. deweti, and Neocaudites osseus. It is confined to three small areas on the middle to outer shelf off the SW Cape, Namaqualand, and Walvis Bay, where the main controlling parameters are water temperature (positive correlation) and m u d content of bottom sediments (negative correlation). Other correlations suggest that the association is further favoured by increasing values for water salinity and bottom sediment MORG, and lower than average dissolved oxygen. Off Walvis Bay, A mbostraconflabellicostata and Bensonia knysnaensis robusta are the main faunal elements, whereas south of 30°S, A. keeleri is generally more abundant than A. flabellicostata, and the various species of Bunionia replace Bensonia.

8I

Independent variables The strongest correlations amongst the independent variables (Table 4) are between temperature and salinity (0.908) and sand and m u d ( - 0 . 8 7 6 ) . Other correlations although less strong are, nevertheless likely to have an important influence on our results. Dissolved oxygen in the bottom waters is negatively correlated with temperature and salinity: i.e. as the latter two rise, the oxygen content of the water falls, and vice versa. This reflects the two major oceanographic features off the west coast, i.e., the upwelling of relatively warm, saline Angolan water and concomitant sea-floor biochemical activity off Namibia, and the invasion of the shelf south of the Orange River by cool, lower salinity, oxygen-rich AAIW water (Dingle and Nelson, in press). Organic matter in bottom sediments ( M O R G ) correlates most strongly with dissolved oxygen (negatively) and m u d (positively ), showing that in oxygen poor, mud-rich environments the MORG content tends to be higher (and vice versa). It follows from the above observations on oxygen, that MORG will be higher in areas with warm, saline bottom waters, especially in the regions of intense upwelling. Elemental iron ( =terrigenous component) correlates most strongly with CaCO3 (negatively), this mutually exclusive relationship probably reflects the preponderance of planktic carbonate debris away from terrigenous sources, and areas where high bottom currents inhibit the deposition of fine terrigenous material. A weaker correlation with salinity (negative) is probably related to lower salinity values off the major terrigenous source (Orange and Olifants rivers). Glauconite occurs abundantly on the continental shelf off southern Africa, particularly in the southern part of our study area (e.g. Birch, 1975), and correlates most strongly with dissolved oxygen (positive) and CaCO3 and

82

MORG (negative). The sympathetic increase in abundance of glauconite with bottom oxygen values over sediments low in carbonate a n d / o r organic matter reflects the situation in the southern parts of the area, where well-oxygenated AAIW invades the outer shelf. A complicating factor, however, is the relict nature of much of the glauconite. In addition to moderate negative correlations with Fe and glauconite, calcium carbonate is also weakly correlated (negatively) with temperature and salinity. These correlations seem logical, with carbonate values tending to decrease as terrigenous a n d / o r allochthonous mineral input increases, while in the warmer, more saline environments which, north of 28 ° S, tend to underlie areas of upwelling, opal and organic matter values are typically high (see Bremner, 1980; Rogers and Bremner, 1991; Dingle, in press). The purely textural parameters of the sediments [sand and m u d content (gravels are rare and were not included in the analysis)] are naturally mutually exclusive, but both correlate relatively strongly with M O R G (sandnegative, mud-positive). In other words, the m u d d i e r the sediments, the higher its M O R G value. In terms of water mass properties, correlations are weaker, but the m u d content correlates most strongly with water temperature (negative), while sand correlates most strongly with dissolved oxygen (positive). The explanation for the former relationship probably lies in the progressively finer-grained texture of the deeper water sediments (e.g. Rogers and Bremner, 1991; Dingle, in press), which are associated with a negative sea-floor temperature gradient (Dingle and Nelson, in press). The relative weakness of this correlation regionally, is probably attributable to the high m u d values that underlie the upwelling areas north of Luderitz, where sea-floor temperatures are relatively high. In the case of sand, the relationship is more obscure. A broad swathe of > 75% sand values crosses the shelf diagonally from < 100 m in the north ( 17 ° S )

R.V. DINGLE ANI)J, (ilR-~.IJI)EAI

to 200-450 m in the south (35°S), and this approximately corresponds to the m a x i m u m gradient of the dissolved oxygen content, which increases from north to south (see Dingle, in press, figs. 30 and 32 ).

Transfer Ji~nctions Most previous workers, mainly concerned with planktic taxa, developed transfer function equations for a single independent variable (usually surface water temperature), in studies of benthic organisms, the possibility of interactions between water masses and sediment parameters suggests that more than one environmental variable is likely to have a strong influence on distribution. Williamson et al. (1984) undertook multiple regression analyses on textural and water mass variables for their benthic foraminiferal assemblages, but our only direct comparison is with the work of Cronin and Dowsett (1990) who developed a transfer function for continental margin bottom temperatures for ostracods off eastern USA. In Table 3 we summarise our multiple regression analyses, where the multiple correlation coefficients (MCC) for temperature, salinity and dissolved oxygen are all > 0.800. ( Running the analyses again, but omitting the samples in Appendix 1 with communalities < 0.7 produced only marginally better MCCs. ) The standard error of the estimates (SEE) for these parameters suggest that our equations will predict temperatures to ___1.4°C, salinities +0.13%0, and dissolved oxygen ___0.80 ml/l. This compares with _+1.5°-2.0°C (range - 1.7°-27.8°C) for the results of Cronin and Dowsett (1990) who had, however, a MCC of > 0.95. These results (Appendix 3) indicate that FA 3 is the most successful for predicting temperature, salinity and dissolved oxygen, with the second ranking FA being 4 for temperature and salinity, and 5 for oxygen. Predictions for other variables are likely to be less accurate, with MCC for Fe, mud and

BEN IHIC.'OSTRA('()DA IN THE BENGUELA SYSTEM (SE AI LANTIC)

glauconite around 0.600, organic matter at 0.500, and sand and carbonate

Z c~

,-,I "r

>. r)

Z -4 -'r

23.4433 23.4333 23.4333 23.4317 23.4300 24.5800 24.6067 31.3667 33.1917 33.9950 19.3667 22.2500 22.2500 22.2500 21.9167 21.9000 21.9000 20.9333 20.9167 20.5917 20.5833 19.9167 19.9167 19.9500 19.9167 19.9167 19.1367 19.1567 19.1917 19.2100 19.7267 19.7333 19.9167 19.9167 19.9167 20.4500 20.4500 20.4333 20.4500 22.0833

13.0300 13.2167 13.3967 13.5733 13.7567 13.4167 13.5833 16.0833 17.7033 18.1483 11.0600 13.0500 13.2333 13.4500 13.3583 12.8167 12.6167 12.4667 13.0367 12.0833 11.8667 12.6417 12.4333 12.3233 11.9133 11.3667 11.1667 11.5000 11.9833 12.1767 12.3417 11.8167 12.8233 12.8600 12.8933 13.1467 13.0367 12.6833 12.34~) 12.9333

590 379 278 197 162 655 391 453 174 140 941 280 223 169 160 325 550 382 140 566 810 122 150 196 348 825 738 368 236 139 184 373 92 82 67 76 112 200 303 325

('ummulatlve

16 32 8 46 80 9 68 85 3 160 16 8 37 37 23 6 2 23 21 1 1 8 188 4 7 I 3 7 65 5 29 12 2 27 3 3 4 128 2 10 Variance variance

0.923 0.985 0.968 0.994 0.939 0.993 0.997 0.965 0.987 0.715 0.993 0.994 0.918 0.706 0.470 0.940 0.166 0.993 0.995 0.992 0.993 0.996 0.991 0.996 0.992 0.993 0.978 0.949 0.997 0.994 0.997 0.963 0.996 0.996 0.996 0.996 0.996 0.967 0.523 0.992 25.342 25.342

0.267 0.521 0.337 -0.035 -0.007 0.030 0.618 0.771 0.890 0.735 0.030 -0.011 ---0.023 -0.007 - 0.009 0.798 -- 0.009 -0.010 0.000 -0.010 0.030 -0.005 0.951 -0.005 0.153 0.030 0.035 -0.007 -0.011 -0.013 --0.006 -0.008 --0.005 -0.005 --0.005 -0.005 -0.005 - 0.004 0.719 0.544

0.015 0.020 0.001 0.142 0.759 -0.001 0.018 0.017 0.003 0.024 -0.001 0.720 0.010 0.799 0.315 0.015 0.004 0.021 0.945 0.021 -0.001 0.997 0.017 0.997 0.022 - 0.001 0.010 0.019 0.903 0.323 0.991 0.018 0.997 0.997 0.997 0.997 0.997 0.932 0.000 0.020 13.355 55.899

0.012 0.025 0.923 0.984 0.274 0.006 0.030 0.013 0.020 0.064 0.006 0.008 0.939 -0.003 0.005 0.035 0.009 0.013 -0.007 0.012 0.006 -0.001 0.049 - 0.001 0.017 0.006 -0.003 0.012 0.034 0.020 0.003 0.008 --0.001 -- 0.001 -O.O01 --0.001 --0.001 0.006 0.025 0.027 17.202 42.544

%ample number i~ lhe Umversn~ of ~.iape "l'o'~'n research, essel site number.

3555 3556 3557 3558 3559 3561 3562 3577 3585 3587 3704 3768 3769 3770 3786 3789 3790 3826 3829 3845 3846 3862 3863 3864 3866 3869 3921 3923 3926 3927 3940 3943 3951 3952 3953 3966 3969 3972 3974 4015

no.

14.278 70.177

0.009 -0.002 -0.014 -0.004 -0.007 0.994 -0.013 0.027 -0.018 0.063 0.994 0.006 -- 0.006 -0.001 0.000 -0.020 -0.010 0.008 0.015 0.008 0.994 0.0131 -0.027 0.001 0.003 0.994 0.908 0.008 0.001 0.004 --0.001 0.013 0.001 0.001 0.001 0.001 0.001 0.000 --0.026 -O.I)l 1 9.856 80.032

0.834 0.836 -0.002 0.043 0.133 -0.008 0.783 0.016 0.025 0.004 -0.008 0.688 -0.017 -0.004 0.426 0.548 -0.005 0.995 0.026 0.994 -0.008 -0.021 0.288 -0.021 0.983 -0.008 -0.012 0.973 0.363 0.902 --0.018 0.960 -0.021 -0.021 --0.021 -0.021 -0.021 0.280 0.035 0.833 4.02 ,',;4.052

0.393 0.098 0.016 0.025 -0.021 -0.023 -0.002 0.030 0.439 0.078 -0.023 --0.022 0.016 0.005 -0.029 -0.022 -0.004 -0.037 0.012 -0.037 -0.023 0.006 -0.007 0.006 -0.036 -0.023 -0.009 -0.033 -0.009 -0.032 0.006 0.200 0.006 0.006 0.006 0.006 0.006 -0.012 0.024 .-0.030 2.803 86.855

0.009 -0.002 -0.022 -0.018 0.074 0.003 -0.006 -0.013 -0.001 0.216 0.003 -0.003 0.181 -0.006 0.022 -0.013 0.400 0.011 -0.009 0.012 0.003 -0.015 -0.020 -0.015 0.008 0.003 0.010 0.010 -0.015 -0.002 -0.018 0.019 -0.015 -0.015 --0.015 -0.015 -0.015 0.034 -0.027 -0.002 2.536 89.391

0.007 0.060 0.017 0.016 -0.018 -0.053 0.000 0.607 -0.033 -0.025 -0.053 -0.012 0.011 -0.020 -0.007 -0.001 0.004 0.007 0.316 0.006 -0.053 -0.023 -0.007 -0.023 0.003 -0.053 0.391 0.019 -0.013 0.005 -0.020 0.012 -0.023 --0.023 -0.023 -0.023 -0.023 -0.024 -0.018 ...0.005 1.866 01.257

-0.027 -0.025 -0.026 0.026 0.001 0.013 -0.021 -0.011 0.001 0.040 0.013 -0.025 -0.013 -0.035 -0.048 -0.014 -0.070 -0.026 -0.018 -0.026 0.013 -0.009 -0.007 -0.009 -0.025 0.013 0.005 -0.028 0.214 0.271 0.104 -0.028 -0.009 -0.009 -.0.009 -0.009 -0.009 -0.014 -0.011 .0.021 1.728 t12.985

0.025 0.011 -0.017 -0.019 0.513 0.010 0.001 0.001 -0.003 0.333 0.010 -0.022 0.039 0.257 0.431 -0.006 -0.019 0.005 -0.016 0.005 0.010 -0.037 -0.008 -0.037 0.003 0.010 0.015 0.006 -0.040 -0.0"17 -0.041 0.007 -0.037 -0.037 -0.037 --0.037 -0.037 0.132 0.044 .-0.001

Sample Latitude Longitude Depth Valves Communality Factor l Factor 2 Factor 3 Factor4 Factor 5 Factor6 Factor 7 Faclor8 Factor9 Factor 10

Al~petadix I (continued) OC

Pseudokeijella h'praltoides Ruggleria~3'theropteroides Ambostraconllabellicostata Amhostraconkeeleri Bensonia k. knysnaensts tlenryhowellamelobesioide.~ Dorato(ythere exilis Neocytherideis hoomeri Palmoconcha walvtshaiensts Cvtherella namtbensis (),therelladromedaria Paracypris lacrimata Bensonia k. rohusta Xestoleberis africana Xestoleheris hartmanni Australoeciafulleri .4ustroaurila rugosa Bairdoppilata simplex Buntonia bremnert Buntonia deweti Buntonta gibbera Buntonia namaquaen.~ts Buntonia rogersi Buntoniarosetl/Ndt ('hvsoc),there craticula ('oquimba hirchi ('.vtheropteron trinodosum Cvtheropteron whatleyi Im'ongruelltna venusta Krithecapensis Krithespatularis .tlacroc),prts cf. M. matuenda Neocaudites Iordt Neocaudites osseus Poseidonamtcus panop.sus Urocvtherets arcana

Species

Varimax factor score matrix

Appendix 2

0.033 0.996 0.008 0.023 0.007 0.030 0.037 0.004 0.005 0.010 0.001 0.002 0.007 0.009 0.000 0.001 0.001 0.025 0.004 0.000 0.009 0.021 0.020 0.005 0.018 0.004 0.004 0.019 0.010 0.018 0.000 0.009 0.005 0.003 0.037 0.002

0.997 0.031 0.013 0.015 0.028 0.006 0.032 0.004 0.001 0.012 0.003 0.016 0.008 0.008 0.000 0.008 0.002 0.(105 (I.(106 0.000 0.007 0.011 0.005 0.002 0.037 0.009 0.001 0.012 0.002 0.019 0.001 0.009 0.001 0.000 0.009 0.020

0.001 0.005 0.011 0.032 0.012 0.001 0.001 0.000 0.997 0.021 0.001 0.003 0.055 0.000 0.000 0.009 0.000 0.004 0.000 0.000 0.000 0.000 0.006 0.001 0.000 0.000 0.002 0.003 0.005 0.024 0.001 0.004 0.005 0.00(I 0.001 0.033

0.004 0.031 0.006 0.011 0.011 0.994 0.009 0.001 0.001 0.008 0.001 0.022 0.000 0.002 0.001 0.014 0.000 0.006 0.059 0.(100 0.001 0.017 0.006 0.059 0.002 0.001 0.001 0.001 0.001 0.041 0.012 0.010 0.000 0.000 0.000 0.000

0.012 0.010 0.008 0.009 0.030 0.008 0.012 0.001 0.021 0.994 0.000 0.035 0.022 0.003 0.000 (I.008 0.000 0.012 0.004 0.000 0.004 0.001 0.040 0.008 0.007 0.000 0.023 0.031 0.059 0.011 0.009 0.005 0.005 0.001 0.013 0.003

(I.020 0.001 0.014 (I.039 0.001 0.023 0.016 0.002 0.006 0.037 0.006 0.980 0.007 0.004 (I.003 0.059 0.001 0.006 0.001 0.000 0.001 0.123 0.033 0.007 0.007 0.035 0.005 0.01 I 0.017 0.027 0.013 0.004 0.114 0.001 0.015 (I.004

0.014 0.022 0.037 0.216 0.025 0.003 0.017 0.004 0.015 0.012 0.026 0.040 0.013 0.006 0.016 0.428 0.001 O.774 0.000 0.001 0.003 0.044 0.016 0.012 0.006 0.018 0.002 0.007 0.(1(18 (I.016 0.005 (I.400 0.024 0.010 0.027 0.015

0.019 0.017 0.004 0.018 0.022 0.053 0.014 0.002 0.023 0.006 0.001 0.039 0.001 0.002 0.002 0.028 0.001 0.021 0.112 0.00(I 0.002 0.104 0.009 0.062 0.007 0.(102 0.003 0.035 0.067 0.979 0.014 (I.004 (].009 0.001 0.008 0.004

0.028 0.002 0.005 0.048 0.988 0.013 0.002 0.001 0.009 0.026 0.006 0.001 0.051 0.012 0.002 0.058 0.003 0.086 0.002 0.000 0.002 0.004 0.017 0.001 0.007 0.005 0.004 0.007 0.012 0.015 0.002 0.070 0.001 (I.006 0.005 0.013

0.013 0.010 0.779 0.484 0.035 0.010 0.015 0.002 0.037 0.005 0.024 0.011 0.271 0.003 0.007 0.261 0.000 0.059 0.037 0.002 0.015 0.002 0.072 0.004 0.006 0.005 0.007 0.005 0.002 0.013 0.004 0.019 0.024 0.017 0.030 0.008

Factor I Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8 Factor 9 Factor 10

Oc ,,D

7.

-'4

.,<

r-

7.

..v rr/

-7.

..4 7e

m 7. '-4 -'r

90

R.V. [)INGLE AND J. (ilRM !I)F.AI+

Appendix 3

Variable name

Transfer equations l'or temperature Multiple correlation coefficient (adjusted for D.F. ) ...... 0.863 Standard error of estimate (adjusted for D.F. ) ............... 1.358 Variable name Factor 3 Factor 4 Factor 2 Factor 9 Factor I 0 Factor 8 Intercept

Regression coefficient 4.71480 - 3.24738 1.57602 2.82990 2.49202 1.81834 8.29615

kor salinity Multiple correlation coefficient (adjusted for D.F. ) ....... 0.856 Standard error of estimate (adjusted for D.F. ) ............... 0.126 Variable name Factor 3 Factor 4 Factor 2 Factor 8 Factor 10 Factor 6 Factor 1 Intercept

Regression coefficient 0,46142 - 0.23448 0.06968 - 0.20048 0.15215 - O. 13902 0.05573 34.73574

l'~)r o+,,ygen Multiple correlation coefficient (adjusted for D.F. ) ....... 0.820 Standal"d error of estimate (adjusted for D.F. ) ............... 0,782 Variable name Factor 3 Factor 5 Factor 1 Factor 4 Factor 6 Factor 7 Factor 8 Factor 10 Intercept

Regression coefficient 1.63893 1.19305 1.22628 0.97096 1.01010 1.2543 I 0.89722 0.91780 2.38322

For M O R G Multiple correlation coefficient (adjusted for D.F. ) ....... 0.510 Standard error of estimate (adjusted for D.F. ) ............... 2.665 Variable name Factor 3 Factor 7 Factor 1 Factor 10 Factor 4 Factor 2 Factor 9 Intercept

Regression coefficient 1.06715 5.65197 2.77124 2.88912 1.70107 1.23452 2.67101 6.00505

For b~" Multiple correlation coefficient (adjusted for D.F. ) ....... 0.605 Standard error of estimate (adjusted for D.F. ) ............... 1.361

Factor 6 Factor 9 Factor 2 Factor 3 Factor 7 Intercept

Regression coefficient 3.58169 4.(1553 I 1.20709 0.88378 (I.90719 3. I 1760

I'~)r ('a('O ~ Multiple correlation coefficient (adjusted for I ) . F ~ ....