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 <0.500. The most successful associations for predicting these variables are FA 3 for MORG, FA 6 for Fe and CaCO3, FA 7 for glauconite, FA 1 for sand, and FA 4 for mud. Discussion and conclusions

From our analysis of the distribution of the factor associations (Fig. 2A ) and the principal independent variables that control this distribution (Tables 4 and 5 ), we conclude that three fundamentally different hydrographic regimes limit the distribution of benthic ostracods on the continental margin of southwestern Africa: slope, shelf edge and shelf. Figures 2B and 3 conceptualise the relationship of these regimes with the FA's, water masses, and environmental controls. It is immediately clear that the controlling parameters are predominffntly of an oceanic nature (i.e. relating specifically to the water column) along the whole of the northern transect and along the outer shelf and slope portion of the southern transect, while the shelf area of the latter is controlled by parameters determined by the nature of the bottom sediments. The transition between the shelf oceanic-dominated and the shelf substrate-dominated regimes occurs between 25 ° and 27°S. The slope oceanic regime is characterised by FA 4 (Henryhowella melobesioides) and FA 8 (Krithe capensis), which comprise cosmopolitan faunal elements (Dingle and Lord, 1990). The boundary separating the two lies at the top of the salinity minimum zone in the upper part of the AAIW mass (approximately 600 m) (Shannon, 1985; Shannon and Hunter, 1988 ), where a salinity reversal, superimposed on a relatively steep temperature gradient forms an effective environmental barrier (Dingle et al., 1989). These associations persist along the length of the study area and reflect regionallydeveloped oceanic phenomena. The shelf edge oceanic regime is related pri-

83

marily to dissolved oxygen and temperature values of bottom waters. In the south, the barrier between the slope and shelf edge regimes is temperature-controlled, where cool, low salinity, oxygenated uppermost AAIW waters that are advected onto the outer shelf (particularly south of the Orange River) support FA 1 ( Ruggieria cytheropteroides). Between about 25 ° and 22°S this association is replaced northward and downslope by the FA 5 (Cytherella narnibensis), which favours the oxygen-depleted waters penetrating southward along the shelf edge from the Angolan Basin (e.g. Hart and Currie, 1960; Bubnov, 1972; Chapman and Shannon, 1985, fig. 6). The propensity of platycopid ostracods for such conditions has recently been discussed by Whatley ( 1991 ), who concluded that the filter feeding habit of this group allows it to survive at significantly lower levels of dissolved oxygen than most other ostracod taxa. The disposition of associations FA 1 and FA 5 indicates that the Angolan off-shelf water mass underrides the oxygen-rich uppermost layer of AAIW, which is cut off from its deeper source. A consequence of this is the isolation of the distal extension of the off-shelf oxygen depleted water mass from involvement in shelf upwelling south of Walvis Bay. This may account for the centre of shelf oxygen depletion lying north of Walvis Bay (see De Decker, 1970; Dingle and Nelson, in press), whereas the most intense upwelling lies south of Walvis Bay (see Lutjeharms and Meeuwis, 1987). The shelf regimes are characterised locally by relatively rapid across-shelf faunal changes, as well as extensive inner shelf areas barren ofostracods. The shelf regime north of 25°-27°S supports, almost exclusively, FA 3 (Palmoconcha walvisbaiensis), which is controlled by oceanic variables: warm, saline, oxygen-deficient bottom waters. It is maintained by the southward penetration of warm Angolan shelf water in the poleward undercurrent(Nelson, 1989; Dingle and Nelson, in press), and intense shelf upwelling of advected oxygen-de-

84

pleted water that is subsequently further depleted by sea-floor biochemical action. Small patches of FA 2 (Pseudokeijella lepralioides) and FA l0 (Ambostracon flabellicostata) reflect substrate changes and, in the case of the latter, slightly lower temperatures. Palmoconcha walvisbaiensis, like Cytherella namibensis, can tolerate low oxygen values (their respective ranges are 0.4-1.6 and 0.6-4.7 ml/l), and the boundary between the two associations on the outer shelf off Namibia is maintained by temperature/salinity and substrate variations (Fig. 3). In the vicinity of Luderitz, the primary environmental control in the shelf regime changes from oceanic to substrate. This is probably related to a variety of factors: lower intensity of upwelling to the south (see Lutjeharms and Meeuwis, 1987), southward limit of offshelf Angolan water penetration (Chapman and Shannon, 1985 ), the presence of major terrigenous sediment sources in the south, and the southward widening of the continental shelf. The latter phenomenon allows advection of upper AAIW, forcing the oxygen depleted water carried by the poleward undercurrent into a narrow inshore zone. As a consequence, the shelf substrate regime supports two along-shelf associations: FA 2 (Pseudokeijella lepralioides) and FA 9 (Bensonia knysnaensis knysnaensis). These favour different combinations of sand, mud and carbonate, but are primarily controlled by the terrigenous content of the bottom sediments (Fig. 2B). Less extensively developed associations favour various combinations of terrigenous (FA 6 Paracypris lacrimata), organic matter (FA 10 Ambostracon keeleri), and glauconite (FA 7 Bairdoppilata

simplex). In the case of FA 10, a positive correlation with water temperature is the dominant control. The fact that FA 2 and 3 also show such a relationship, appears to be a characteristic of the shelf regime. Much of the glauconite in sediments off the SW Cape is relict and derived from Tertiary

R.V. DINGLE AND J. (JlR ,~,t:DEAl

shelf sediments (Birch, 1975; Rogers and Bremner, 1991). The propensity of FA 7 (Bairdoppilata simplex) for glauconitic sediments must, therefore, reflect a property of the mineral grains as they influence food supply or habitat, rather than any chemical micro-environment connected to authigenic mineral formation. A further possibility is a link between the fauna and strong bottom currents which could erode the grains from sea-floor outcrops possibly under the influence of the outer shelf jet (Bang and Andrews, 1974; G. Nelson, pers. commun., 1992). Finally, it may be helpful to workers engaged in palaeobathymetric analyses for us to comment on correlations between the various factor associations and water depth. Although Williamson et al. (1983) and Mudie et al. ( 1984 ) included depth amongst their environmental variables in the factor analysis, we omitted it on the grounds that ostracod distributions are unlikely to be influenced by it per se. However, an assessment of water depth is often one of the variables that is attempted in, for example, basin analysis, and the establishment of any meaningful relationships will enhance the usefulness of our results. To this end we present some statistics using the factor scores ( > 0.5000) and water depths at sample sites in Appendix I. Table 6 shows the results arranged in descending order of average water depth for the factor associations. Four of these show relatively strong correlation coefficients with depth, suggesting that they may be of use in predicting the palaeobathymetry of various parts of the margin: inner-middle shelf, FA 9 ( Bensonia knysnaensis knysnaensis ) and FA 3 (Paimoconcha walvisbaiensis ); outer shelf, FA 6 (Paracypris lacrimata); upper slope, FA 4 (Henryhowella melobesioides). In contrast, FA l (Ruggieria cytheropteroides, FA 5 (Cytherella namibensis ) and FA 8 ( Krithe capensis) show very weak correlations, suggesting that they will be of little use in such predictions. The strong correlations can be explained in

BENTHIC OSTRACODA IN THE BENGUELA SYSTEM ( SE ATL~.NTIC )

85

"FABLE 6 Correlation o f factor associations with water d e p t h FA

9. Bensonia k. knysnaensis 10. Ambostraconflahellicostata/keeleri

3. Pahnoconcha walvtsbaiensis 2. Pseudokeuella lepralioides 6. Paracypris lacrtmata 7. Bamtoppilata simplex I. Ruggu,rta o'theropterotdes 5. ()'therella namthensis 8. Krtthe capensis 4. Iteno'howella melot~esioides

Average

Maximum

Minimum

SD

CC

137

283 188 280 278 450 545 560 590 725 945

18 18 15 88 100 18 140 139 140 305

95 52 63 40 108 174 94 111 202 209

-0.7453 0.2451 -0.5655 -0.2871 -0.5084 -0.3247 -0.1580 0.1450 0.1639 0.6814

139 140 177

216 244 293 368 502 682

FA = Factor associalion, SD = S t a n d a r d deviation, C C = Correlation coefficienl.

terms of the depth-dependent environmental parameters discussed above (Fig. 3). For example, on the inner-middle shelf, both FA 9 and FA 3 are restricted to depositional environments that occur only within well-defined depth ranges (terrigenous muds close to the coast, and warm, saline, oxygen-depleted shelf waters north of Luderitz, respectively), while FA 4 is controlled by the thermal/salinity gradient below the shelf break, which is strongly depth-related. Two of the weak correlations are with factor associations (FA l and FA 5 ) that are themselves strongly correlated with the advection of oxygen-rich and -poor waters, respectively, over the shelf edge. As Dingle and Nelson (in press) have shown, this phenomenon is progressively depth-transgressive along the margin, and may explain the poor correlation. Clearly, with the distribution of Ostracoda depending on a variety of factors, which themselves are more or less depth-dependent, direct predictions of palaeobathymetry from factor associations are likely to be tentative. Scrutiny of plots of depth against latitude for individual species along the margin off southwestern Africa suggests this will be the case ( Dingle, 1992, 1993). The pioneering work of Cronin and Dowsett (1990) demonstrated that factor analysis provided a solution for characterising continental

shelf ostracod faunas subject to strong latitudinal sea-bottom temperature gradients. Here, we have shown that a similar approach can be applied to the complex oceanographic regimes obtaining in an area of intense upwelling and water mass mixing. Sedimentary environments such as those found off southwestern Africa have numerous analogues in the geologic record, and our work suggests that quantitative analyses of ostracod faunas have great potential for interpreting similar palaeooceanographic settings.

Acknowledgments This work was funded by the Foundation for Research Development (FRD) and the South African Museum, to which we extend our thanks. RVD also gratefully acknowledges valuable discussions with Mr G. Nelson (Sea Fisheries Research Institute). Professor Hans Schrader (University of Bergen) and Thies Schrader provided the CLIMAP statistical program and technical instructions to load and run it on our PC. Mr Nelson and Drs J. Rogers and J.M. Bremner (University of Cape Town) read and suggested improvements to the manuscript. Two referees also gave us constructive criticism and valuable suggestions for improvement. Mrs J. Woodford is thanked for drafting the figures.

2361 2369 2440 2443 2446 2447 2448 2459 2460 2470 2472 2485 2488 2690 2691 2693

2344

104 270 271 300 311 346 1689 1690 1691 1692 1694 1697 1698 2222 2224 2257 2259 2260 2262 2335 2336 2337

no.

34.0667 34.5167 34.4500 34.9333 34.5500 34.9700 34.7000 34.5833 34.5667 34.6000 34.7500 34.7667 34.7833 33.1350 33.1567 32.7467 32.7333 32.7580 32.7917 31.9667 31.9583 31.9500 31.8333 31.3133 31.1533 33.2417 32.6500 31.9333 31.9250 31.9250 31.2333 31.2333 30.7550 30.7750 30.9167 30.8417 30.5167 30.5333 30.5167

17.7217 18.6833 18.5750 18.6000 18.4500 19.6000 18.6000 18.5867 18.4833 18.3667 18.3267 18.2500 18.2167 17.7767 17.9550 17.7617 17.4333 17.2200 16.8167 17.0417 17.2367 17.4333 17.8083 16.8583 17.2300 17.1500 17.0883 16.6583 16.4667 16.2550 16.3833 16.6250 15.5500 15.9250 16.0000 15.4667 15.8333 15.6167 15.2167

285 131 55 227 184 133 182 172 220 305 425 545 502 155 58 100 255 303 450 238 180 153 128 241 188 450 300 310 350 392 300 272 345 201 227 430 271 265 305

6 1440 5 74 397 15 39 911 513 9 30 78 8 3 140 8 3 12 3 9 7 4 3 54 II 17 2 38 44 38 290 38 59 303 ~08 14 138 42 41

0.963 0.995 0.768 0.994 0.993 0.835 0.983 0.995 0.996 0.973 0.990 0.650 0.975 0.997 0.978 0.602 0.887 0.931 0.308 0.964 0.966 0.965 0.997 0.735 0.886 0.984 0.994 0.949 0.986 0.972 0.995 0.984 0.992 0.992 0.987 0.981 0,986 0.995 0.996

0.365 - 0.013 0.018 0.589 0.711 -0.015 0.701 0.913 0.215 0.788 0.084 0.023 0.034 -0.033 -0.007 -0.005 0.588 0,614 0.018 0.365 -0.007 ---0.002 -0.033 0,841 0.167 0.134 0.996 0.823 0.949 0.903 0.996 0.939 0.994 0.993 0.989 0.127 0.958 0.961 i1.996 0.015 0.996 0.014 0.803 0.674 0.611 0.693 0.400 0.962 0.022 0,060 0.011 0.008 0.997 0.029 -0.012 0.012 0.028 -0.017 -0.006 0.148 -0.016 0.997 0.040 0.558 0.002 0.031 0.120 0.029 0.026 0.031 0.028 0.031 0.044 0.050 -0.015 0.257 {I.265 0.032 0.008 0.001 0.016 0.003 0.008 -0.002 0.003 0.005 0.001 0.003 0.002 0.012 0.000 -0.001 0.014 0.001 0.003 0.017 -0.002 0.003 -0.003 -0.003 -0.001 0.012 0.019 0.001 0.005 0.004 0.006 0.007 0.005 0.006 0.005 0.005 0.005 0.023 0.006 0.005 0.005

-0.006 -0.003 -0.014 -0.001 0.153 0.006 0.022 -- 0.028 0.156 0.558 0.984 0.419 0.976 -0.004 -0.012 0.015 -0.009 0.375 0.025 0.194 0.021 0.022 -0.004 0.070 -0.017 0.935 -0.031 0.503 0.280 0.378 -0.023 0.065 --0.030 -0.032 -- 0033 0.050 -0.031 0.031 .-~} 03~

0.008 -0.012 -0,015 -0.003 0.005 0.015 -- 0.001 0.009 -0.011 0.010 -0.010 0.073 -0.011 -0.012 0.029 0.028 0.019 0.197 0.017 0.032 0.033 0.035 -0.012 - 0.001 -0.006 0.004 0.010 0.005 0.009 0.004 0.022 0.022 0.031 0.022 0.008 -0.010 0.004 0.007 0.0t0

0.847 -0.005 0.855 .-0.015 0.020 0.260 0.090 - 0.023 -0.008 -0.015 0.104 0.650 0.129 -0.014 -0.022 0.012 0.458 0.580 -0.021 0.032 0.038 0.040 -0.014 0.049 0.037 0.011 -0.022 -0.006 - 0.006 0.011 --0.011 0.047 . (I.024 0.040 0.066 0.00": O008 -0.(124 •0 . 0 2 1

0.329 0.024 -0.012 0.014 0.005 0.626 0.058 0.009 0.015 0.200 --0.019 -0.056 -0.022 0.020 -0.002 0.774 0.570 0.161 0.548 0.881 0.970 0.980 0.020 0.022 -0.007 0.297 0.001 0,063 0.043 0.018 0.022 0.301 0.007 0.005 0.00t) 0.03~; (I.003 0.005 I}.O01

•0.01 ~

-0.017 -0.012 0.059 0.112 --0.018 ---0.031 --0.009 -0.019 0.019 0.979 --0.013 0.013

0.062

-0.024 0.018 --0.018 0.005 -0.011 -0.017 -0.007 --0.008 0.006 -0.031 0.014 0.094 -0.036 0.019 0.022 -0.034 -0.045 -0.048 0.076 0.125 -0.036 ..0.039 0.019 0.003 0.002

0.016 -0.025 0.027 -0.022 -0.008 -0.031 - 0.004 --0.007 -0.023 0.009 0.005 -0.012 0.026 -0.028 0.987 --0.001 0.050 0.050 0.003 -0.001 -0.006 -0.001 -0.028 0.012 0.004 0.010 0.002 0.004 0.002 0.009 0.001 0.009 0.001 0.007 0.003 -0.015 -0.005 0.005 f).OO2 - 0 . 0 0 ~}

-0.057 0.026 0.188 -0.022 0.092 0.016 -0.005 -0.006 -0.012 0.001 0.001 -0.183 0.026 -0.013 0.033 0.025 0.035 0.080 0.007 0.011 0.009 0.011 -0.013 0.138 0.738 0.017 -0.010 -0.015 -0.013 0,000 -0.01 f (I.044 -0.010 - 0.0O3 0.00-~ 0.020 0.008 -- 0.012

Sample Latitude Longitude Depth Valves Communality Factor I Factor2 Factor 3 Factor4 Factor 5 Factor6 Factor 7 Factor 8 Factor9 Factor 10

Varimax factor components matrix

Appendix 1

> 7_ ,7_,

7_ c.

<

oc

2697 2700 2703 2715 2717 2719 2736 2752 2754 2780 2785 2825 2840 2860 2861 2879 2884 2913 2924 2925 2926 2927 2928 2935 2970 3087 3089 3109 3112 3113 3304 ~341 3346 3414 3428 3458 3461 3462 3466 3467 3469 3500 3519 3520 3522 3523 3524 3525

311.2833 30.2167 30.1333 30.3500 30.4000 30.4500 29.9500 29.7833 29.7667 33.2417 33.2250 34.1000 30.9167 29.6333 29.6333 29.4833 29.3167 29.1667 28.9000 28.9000 28.8833 28.8833 28.8667 28.8000 28.4333 32.6200 32.6833 31.9000 31.4500 31.3667 31.0883 32.6833 31.1200 24.6000 24.4333 24.1000 23.9583 23.9583 23.9300 23.9300 23.9333 22.8950 22.9333 22.9267 22.9333 22.9283 22.9333 22.0333

14.3167 14.8500 15.4333 16.8167 16.4333 16.0667 15.4167 16.0167 15.6500 17.25~) 17.4500 17.6000 15.7000 16.2167 16.4167 14.5500 14.7167 14.9833 15.1667 15.3667 15.5667 15.7667 15.9667 16.1833 15.6000 18.0417 18.0833 15.9000 15.7667 15.5833 17.6467 16.5167 15.5750 14.1333 13.8700 13.2000 13.0167 13.1917 13.9067 14.1067 14.35511 14.4917 13.8883 13.7133 13.3450 13.1633 12.9667 12.8000

940 469 220 173 218 240 205 170 195 475 560 375 205 170 165 530 252 200 158 183 182 172 149 126 135 42 18 900 648 840 88 945 730 154 283 725 850 430 220 161 79 15 138 142 344 295 475 850

12 12 50 7 109 134 535 364 745 41 9 8 84 129 12 54 149 216 72 283 71 116 94 18 303 334 45 67 11 15 17 27 19 2 9 13 11 37 3 19 90 5 2 54 44 153 60 13 0.991

0.997 0.996 O.997 0.996 0.981 0.837 0.922 0.994 0.983 0.997 0.991 0.959 0.531 0.965 0.963 0.993 0.963 0.992 0.996 0.996 0.996 0.610 0.996 0.995 0.990 0.989

0.998

O.928 0.988 0.672 0.258 0.962 0.977 0.973 0.936 0.993 0.975 0.990 0.994 0.873 0.987 0.988 0.992 0.997 0.997 0.947 0.998

0.030 0.962 0.331 -0.001 0.824 0.945 0.971 0.380 0.860 0.901 0.717 0.725 0.874 0.135 0.068 0.112 0.997 0.374 0.491 0.115 0.082 -0.013 0.012 -0.033 I).118 - 0.007 0.027 0.032 0.030 11.11311 -0.033 0.030 0.031 - 0.005 0.883 0.037 0.032 0.730 -0.010 - 0.006 -0.005 -0.005 -0.008 - O.007 0.950 O.793 0.152 O.031 -0.001 0.010 0.000 0.009 0.007 0.007 0.005 0.009 0.004 0.012 0.007 0.003 0.009 0.139 0.984 0.003 0.990 -0.001 0.024 -0.015 0.048 0.005 0.925 0.002 0.006 0.838 0.991 0.003 0.987 0.003 0.000 0.998 0.997 0.000 0.997 -0.001 0.990 0.001 0.028 0.012 0.023 0.025 0.004 0.001 0.007 -0.001 0.006 -0.001 0.997 -0.001 0.005 -0.001 0.007 -0.001 0.014 0.728 0.392 0.006 0.015 -0.006 0.002 0.005 0.016 0.032 0.021 0.012 11.989 0.000 0.997 - 0.001 0.997 -0.001 0.011 0.013 0.991 O.002 0.011 0.033 0.016 0.032 0.021 0.018 0.001 0005

0.005 0.025 0.732 0.009 0.529 0.276 0.167 0.872 0.501 0.024 0.023 0.026

(k962 0.101 0.160 0.013 -0.029 0.045 -0.030 -0.018 -0.029 0.292 0.678 0.681 -0.031 -0.010 -0.007 0.197 - 0.024 -0.(116 -0.022 -11.0119 -0.009 0.005 -0.005 -0.004 -0.008 -0.011 -0.014 0.957 0.995 0.988 ..0.004 0.994 0.978 0.000 -0.031 0.719 0.993 -0.016 0.008 0.003 0.001 0.001 -0.006 0.001 -0.027 0.020 0.005 1/.994

-0.005 0.006 -0.003 0.008 -(I.002 0.003 0.022 -0.012 0.002 0.047 -0.001 0.001 0.044 -0.013 -0.007 0.018 0.009 -0.007 -0.008 -0.012 -0.007 -0.012 0.011 -0.012 0.028 0.030 -0.004 -0.006 -0.009 -0.005 -0.012 -0.006 -0.007 -0.017 0.010 -0.002 -0.010 0.653 0.994 0.104 -0.021 -0.021 -0.008 0.110 0.300 0.599 11.981 -0.009

-0.024 0.019 0.009 -0.060 0.007 -0.001 0.000 0.035 0.010 -0.001 -0.011 -0.016 -0.006 0.015 0.023 0.035 0.000 0.019 0.009 0.017 0.017 0.019 0.019 0.020 0.018 -0.001 -0.016 -0.022 -0.023 0.063 0.020 0.018 -0.023 0.001 0.007 0.003 -0.020 -0.020 -0.037 0.062 0.006 0.006 -0.014 0.000 -0.009 -0.012 -0.032 -0.021

-0.00l -0.022 -0.007 0.427 0.001 0.073 -11.007 0.010 -0.024 -0.015 -0.010 -0.013 0.286 0.007 -0.018 0.008 -0.021 -0.020 -0.002 -0.004 -0.011 0.002 -0.015 -0.014 -0.017 -0.025 0.699 0.001 0.003 0.006 -0.014 0.004 0.002 0.000 -0.028 0.011 0.005 -0.012 0.012 -0.011 -0.015 ..0.015 -0.037 -0.016 -0.018 -0.005 0.005 0.005

-0.030 0.224 0.032 0.028 -0.008 -0.019 -0.017 0.004 -0.007 0.275 0.122 -0.049 -0.027 0.013 0.016 0.968 -0.018 0.011 0.002 0.015 0.019 0.017 0.018 0.019 0.016 0.022 -0.017 0.071 -0.041 -0.029 0.019 -0.046 -0.016 -0.019 -0.005 0.666 0.068 -0.004 0.006 -0.024 -0.023 -0.023 0.004 -0.022 -0.013 0.015 0.010 0.029

0.012 0.000 -0.025 -0.058 -0.009 0.003 -0.002 -0.007 -0.012 0.000 0.008 0.011 0.029 -0.028 -0.029 -0.014 0.001 -0.025 -0.019 -11.025 0.124 -11.016 -0.017 -0.028 -0.028 0.988 0.443 0.010 0.013 0.012 -0.028 0.013 0.012 -0.016 0.171 -0.004 0.011 -0.019 -0.026 -0.013 -0.009 -0.009 0.005 -0.014 -0.006 -0.016 -0.027 0.012

0.011 -0.005 0.012 -0.261 0.040 0.017 -0.007 0.167 -0.013 0.001 0.003 0.001 0.046 0.003 -0.007 0.018 -0.008 -0.012 0.045 0.034 -0.001 -0.008 -0.014 -11.013 -0.015 -0.035 0.387 0.016 0.014 0.018 -0.013 0.011 0.018 -0.020 -0.019 0.020 0.016 0.007 0.005 -0.035 -0.037 -0.037 11.779 0.004 -0.008 0.004 11.008 0.011

E

),. 7"

>

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 ~ ....
Regression coefficient 49.73627 18.13933 29.50669 15.21230 22.06109 7.75913 20.30096 51.44729

l o r glaucomtc Multiple correlation coefficient (adjusted for D.F. ) . . . . ~.) 72 Standard error of estimate (adjusted for D.F. ) .......... 14.fl4~ Variable name Factor 7 Factor 1 Factor 4 Factor 6 Factor 3 Factor 2 Factor 5 Factor 9 Intercept

Regression coefficient 51.20992 22.99734 25.34144 23.67133 15.74051 11.87901 9.36073 10.75650 15.14375

l'or sand Multiple correlation coefficient (adjusted for D.F. i . . . . ~i.412 Standard error of estimate (adjusted for d.F. ) ............ I Z ~6 r Variable name Factor 1 Factor 4 Factor 8 Factor 9 Factor 2 Factor 3 Factor 7 Intercept

Regression coefficient 20.69594 6.20236 12.76822 21.86914 I 1.88257 9.08750 13.15442 55.75965

l'or m u d Multiple correlation coefficient (adjusted tor D.F. ) ...... (I.562 Standard error of estimate (adjusted for D.F. ) ............ 1¢).956 Variable name Factor 4 Factor 7 Factor 1 Factor 8 Factor 9 Factor 3 Factor 2 Factor I 0 Intercept

Regression coefficient 8.24655 35.10505 21.51159 12.37612 30.53593 18.60929 12.33196 18.87790 43.99345

BENTHIC OSTRACOI)A IN THE BENGUELA SYSTEM (SE Af[ .XN IICI

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