A transfer function for estimating paleoceanographic conditions based on deep-sea surface sediment distribution of radiolarian assemblages in the South Atlantic

QUATERNARY

RESEARCH

12,

381-395 (1979)

A Transfer Function for Estimating Paleoceanographic Conditions Based on Deep-Sea Surface Sediment Distribution of Radiolarian Assemblages in the South Atlantic’ JOSEPHJ. Lamont-Doherty

Geological

MORLEY

Observatory of Columbia University, Palisades, New York 10964 Received May 2, 1978

A quantitative analysis of radiolarian species in 57 deep-sea surface sediment samples from the South Atlantic Ocean produced four geographically distinct assemblages (tropical, polar, gyre margin, and subtropical). The distributions of these assemblages or factors coincide with presentday patterns of sea-surface temperatures or water masses. These four assemblages were used to construct a transfer function relating radiolarian distribution in the surface sediments to present-day ‘nter and summer temperatures using standard regression techniques. As a test ofthiq I&? ’ y of this transfer function, temperatures were estimated on surface sediment samples from the eastern South Pacific. The temperatures produced by the transfer function compared favorably with the observed (present-day) winter and summer sea-surface temperatures at these sites.

INTRODUCTION

The purpose of this study was to determine if the radiolarian distribution expressed in surface sediments from the South Atlantic could be related to presentday sea-surface temperature and/or circulation patterns. If such a relationship did exist, then an attempt would be made to derive a transfer function based on radiolarian assemblages which would produce reliable paleotemperature estimates. Using planktonic foraminifera, Imbrie and Kipp (1971) showed that faunal abundances could be quantitatively related to oceanographic parameters. This method was later revised by Imbrie et al. (1973) and expanded by Kipp (1976). Sachs (1973a, 1973b, 1973~) demonstrated that Radiolaria could be successfully substituted for foraminifera in this technique. He developed a transfer function for the North Pacific Ocean based on the abundances of 57 species in 36 surface sediment samples. Lozano (1974) and Lozano and Hays (1976) discovered through application of the Imbrie-Kipp analysis that Radiolaria in sur1 Lamont -Doherty Geological Observatory Columbia University Contribution No. 2865.

of

face sediments in the Atlantic and western Indian Ocean sectors of the Antarctic Ocean could also be used to produce valid paleoecological equations. Using 18 taxonomic groups and 72 core-top samples, they derived a transfer function based on three radiolarian assemblages whose distribution patterns correlated with presentday sea-surface temperatures. PHYSICAL OCEANOGRAPHY

The Subtropical Convergence divides the South Atlantic into two distinct circulation patterns (Fig. 1). South of the convergence, the prevailing westerly winds drive the Antarctic Circumpolar Current in a clockwise direction. The Antarctic Convergence (Antarctic Polar Front) is positioned within this eastward-flowing current. Unlike the Subtropical Convergence whose position in the western South Atlantic may vary seasonally over several degrees of latitude, the Antarctic Polar Front remains within nearly the same latitudinal limits (Botnikov, 1964). The Polar Front marks the location of sinking Antarctic Surface Water which forms the major constituent of Antarctic Intermediate Water. 381 0033-5894179/060381-15$02.00/O Copyright @ 1979 by the Univenity of Washington. All rights of reproduction in any form reserved.

382

JOSEPH

J

The South Atlantic Central Water, which flows northward towards the equator, is formed by water sinking at the Subtropical convergence. The South Atlantic contains two other subsurface water masses, the North Atlantic Deep Water (NADW) and the Antarctic Bottom Water (AABW). The southward-flowing NADW occupies the water column between approximately 1500 and 4000 m. Originating close to the Antarctic Continent, the AABW sinks and flows northward underneath the NADW at depths usually greater than 4000 m. The surface area north of the Subtropical Convergence, the Subtropical Gyre, is characterized by counterclockwise-flowing currents which are driven by the southeast trade winds. The northward-flowing Ben-

MORLE\‘

guela Current draws surface water away from the African coast and creates a broad upwelling region along the eastern portion of this Gyre extending from southernmost South Africa to approximately 15”s latitude. The Benguela gradually departs from the coastline and flows westward becoming the South Equatorial Current north of 1S’S latitude. The South Equatorial Current forms the northern part of the Subtropical Gyre and generally encompasses the area between 10”s and 3”N latitude. The equatorial divergence is strongest in the eastern equatorial Atlantic where the eastwardflowing, very shallow Equatorial Counter and Guinea Currents interact with the westward-flowing South Equatorial Current. In

60

0

15

30

4

l eee*ooe

/ANTA

RCUC

POfA R FRONTS

l

. . . . . . .

55

,

FIG.

1. Generalized

convergences

surface

and divergences.

water

circulation

in the

South

Atlantic

with

locations

of major

TABLE LOCATION

1

OF CORES AND WATER

Core

Latitude

v27-206 v27-211 V27-231 V27-232 V27-238 V27-240 v30-33 V31-128 RC 8-18 RC 8-34 RCl l-26 RCll-36 RCll-65 RCll-69 RCll-78 RCll-80 RC12-241 RCl2-269 RCl2-274 RCl2-289 RCl2-294 RCl3-206 RCl3-218 RCl3-229 V 9-23 Vl2-78 v15-166 Vl6-34 Vl7-152 Vl8-166 Vl8182 Vl9-248 Vl9-267 V20-203 V22-140 V22-168 V22-170 V22-175 V22-178 V22-180 V22-182 V24-228 V24-230 V26-55 V26-63 V26-99 v27-181 v27-191 RCl3-239 RCl3-242 RCl3-252 RCl3-255 RCl3-256 RCl3-273 RCl3-275 RCl5-91 RCl5-166

31722’S 27’49’s 03”28’S oo”l4’S 06”28’S 02’03’s 02’58’s 02’53’s 24’04’s 32’37’s 28’35’s 33’52’s 47”02’S 48’54’s 50’52’s 46”45’S 43’28’s 36’58’s 32”34’S 47”54’S 37’16’s 04’28’s lO”38’S 25’30’s 05”53’S 04’23’s 02’46’s 17”02’S 03”09’S 34”59’S 32”3O’S 24’34’s 13’23’s 28’39’s 33”37’S 17”28’S 14’38’s 08”46’S 05”Ol’S 03’18’s 00’32’s 34”55’S 34”13’S 1 l”36’S 23”58’S 01’28’s Oo”O4’S 33”03’S 32’56’s 37”32’S 45”05’S 50”34’S 53”ll’S 55”04’S 50”43’S 49”53’S OO”43’S

DEPTH

Longitude Ol”4l’W Ol”32’E 07’26’E 07’32’E 03”43 ’ w o5”oo’w 31”14’W 26”23’W 15”17’W ll”4l’E 3Ow’W 35’16’W 43”4l’W 4l”OO’W OY52’W OO”O3’W 57”4O’W 32’12’W 46”52’W 23”42’W lO”O6’W 02”54’E 09’33’E 1 l”l8’E 21”02’W 00”11’w 34”17’W 16’13’W 19’23’W 27’07’W 15”Ol’E 04”5O’E 02’13’E 12’19’E 02”2l’E 05”ll’W 07”34’W 14”17’W 15”39’W 16”26’W 17’16’W 07”48’W 1l”59’W 15”34’W 37”57’W 32’43’W 25’3O’W 18”43’W Ol”26’W 03”35’W 09”OYE 02”54’E OO”2l’W 1 l”34’E 13’26’E lS”34’W 40”3O’W 383

Depth Cm) 4748 4609 4252 2615 4813 5115 4477 5372 3977 4521 2349 4222 5435 5492 3115 3656 3499 4360 3801 4484 3308 5194 4145 4191 5760 4232 3979 3530 5247 4527 2941 3321 5585 3860 4433 4625 4131 2950 4338 3614 4085 3543 3457 3619 4632 3601 3957 4177 4266 4523 3332 2525 4967 1984 3775 3768

384

JOSEPH

the western equatorial Atlantic, the South Equatorial Current divides into two parts. One part turns northward while the other division flows southward along the coast of South America as the Brazil Current. The Brazil Current extends from the equator to approximately 35”s latitude where it encounters the northward-flowing Falkland Current. The South Atlantic Current forms the southern portion of the Subtropical Gyre and spreads eastward paralleling the Subtropical Convergence. More detailed explanations of the circulation patterns in the South Atlantic are given by Sverdrup et ul. (1942), Defant (1961), and Gordon (1971). METHODS

Selection of Surface Sumples The preliminary core investigation

con-

J. MORLE,I

sisted of sampling and slide preparation (using the settling technique developed by Moore, 1973) of surface sediment samples. The Atlantic is a silica-deficient ocean (Broecker, 1974) and as a result, siliceous skeletons of Radiolaria are poorly preserved in deep-sea sediments in portions of both the North and South Atlantic (Go11 and Bjorklund, 1971, 1974). Many of the trigger cores sampled from the South Atlantic were either barren of Radiolaria or had too few Radiolaria to conduct a total fauna1 count. Several other surface sediment samples contained pre-Pleistocene species or anomalous fauna1 compositions compared to nearby samples. Since this group of cores did not represent presentday sedimentary environments, they were removed from all subsequent analyses. This preliminary investigation was success-

0

SURFACE SAMPLES 15

30

l RClZ-241 RCII-65 .

RCII-80 .

RCl2-289 . RC15-91 .

RCllf69 ?

RCl3-252 ’

45

RC13-255 . RCll

RCI;-275

‘78 R&256

\

RCE..273

45

FIG. 2. Location the Lamont -Doherty

and identification core collection.

. 30

. I5

of the 57 cores

. I5

0

used in the surface

study.

All cores

50

are from

PALEOCEANOGRAPHIC

TRANSFER

fully completed with the selection of 57 surface samples (Table 1, Fig. 2) which were used to develop the radiolarian transfer function for the South Atlantic. Data Analysis

This study followed procedures for Qmode factor analysis outlined by Imbrie and Kipp (1971) and updated by Imbrie et al. (1973). Of the 67 species counted in each of the 57 surface samples, only 35 reached or exceeded 2% in at least one sample. Imbrie and Kipp (1971) used only those species which achieved a minimum abundance of 2% in the surface samples for factor analysis to minimize

FUNCTION

385

counting errors and improve the signal-tonoise ratio. Therefore, the 32 radiolarian species with abundances lower than 2% in all surface samples were eliminated from the Q-mode analysis. Several species were also excluded which produced “no analog” conditions. This occurs when the abundance of a species in a sample in which oceanographic parameters are to be estimated by the transfer function exceeds the maximum (or minimum) abundance in the data set used to develop the function. Several circumstances could possibly create no analog conditions such as adaptation of a species to broader or narrower environmental con-

TABLE

2

SPECIES USED TO DEVELOP TRANSFER FUNCTION Species name Collosphaera Disolenia Polysolenia

Reference

Haeckel

tuberosa

spp.

Polysolenia Polysolenia

(Haeckell (Haeckell

murrayana spinosa

spp.

Siphonosphaera

polysiphonia

Nigrini, Nigrini, Nigrini, Nigrini, Nigrini, Nigrini,

1971, 1967, 1968, 1967, 1967, 1967.

PI. Pl. PI. PI. PI. PI.

34, Fig. I 1, Figs. 5, 6 1, Fig. la 1, Fig. 1 1, Figs. 2, 3b 1, Figs. 4a, 4b

(Haeckel) Actinomma Actinomma

medianum Nigrini haysi Bjorklund

Actinomma Actinomma

spp. 1

Axoprunum Cenosphaera Ommatartus Spongurus Stylatractus

spp. 2 spp. spp. tetrathalamus

(Haeckel)

spp. spp.

Heliodiscus Euchitonia

spp. spp.

Spongaster Spongopyle Larcopyle Antarctissa

tetras osculosa butschlii denticulata

Antarctissa

strelkovi

Ehrenberg Dreyer Dreyer (Ehrenberg) (Jorgensen)

Theocorythium Theocalyptra

trachelium bicornis

Triceraspyris

antarctica

(Ehrenbergl (Popofsky) (Haecker)

Nigrini, 1967, PI. 2, Fig. 2a Bjorklund, 1977, PI. 1, Figs. B, C, H Benson, 1966, PI. 5, Figs. 5, 6 Morley, 1977, PI. 3, Figs. 4, 5 Haeckel, 1887, Pl. 48, Fig. 4 Robertson, 1975, PI. 2, Figs. 5-8 Nigrini, 1967, PI. 2, Figs. 4a-4d Petrushevskaya, 1967, Figs. 16 I-II; Includes Spongurus pylomaticus Riedel, 1958, PI. 1, Figs. 10, 11 Robertson, 1975, PI. 5, Figs. l-3; Includes S. neptunus Haeckel, Riedel, 1958, PI. 1, Fig. 9; X. crones and X. Pluto (Haeckel), Benson, 1966, PI. 7, Figs. 12-17; and Stylatractus sp., Petrushevskaya, 1967, Fig. 15 Nigrini, 1967, PI. 3, Figs. la, 2a Nigrini, 1967, PI. 4, Fig. 2a; Ling and Anikouchine, 1967, PI. 189, Figs. 1, 2, PI. 190, Figs. 1, 2 Nigrini, 1967, PI. 5, Fig. la Reidel, 1958, Pl. 1, Fig. 12 Benson, 1966, Pl. 19, Figs. 3-5 Petrushevskaya, 1967, Figs. 49 I-VI, Figs. 50 I-IV Petrushevskaya, 1967, Figs. 51 III-VI: Reidel, 1958. Pl. 3, Fig. 8 Nigrini, 1967, PI. 8, Figs. la. lb, 2 Petrushevskaya, 1967, Figs. 71 III-IX, Figs. 72 I-IV Petrushevskaya, 1967, Figs. 37 I-III

TABLE VARIMAX Core RC13-273 RCl3-256 RCll-78 RCl3-275 RCl3-255 RCl?-289 RC15-91 RCll-80 RCll-69 RC13-252 RCl l-65 RC12-241 RC 13 -242 RC12-294 V24-228 RC12-269 V24-230 V18-182 V18-166 RC 8-34 V22-140 RCl3-239 V27-191 V20-203 RC13-229 V27-206 RCI I-36 V27-217 V19-248 RC12-274 RCl l-26 V19-267 RC13-218 V22-168 RC 8-18 V22-170 Vl6-34 V12-78 V26-63 V27-240 RC13-206 V27-238 V27-231 V26-55 V22-182 V22-175 v22-180 V22-178 v17-152 V 9-23 V27-181 V27-232 V31-128 v30-33 V26 -99 V15-166 RC15-166

3

FACT OR MA I RIY

Communality

Tropical

Polar

0.984 0.986 0.990 0.989 0.994 0.991 0.988 0.934 0.978 0.849 0.986 0.972 0.883 0.943 0.913 0.934 0.930 0.878 0.858 0.940 0.939 0.881 0.880 0.830 0.916 0.910 0.849 0.940 0.814 0.815 0.904 0.807 0.909 0.864 0.839 0.877 0.939 0.920 0.822 0.832 0.928 0.869 0.839 0.939 0.933 0.916 0.938 0.820 0.903 0.940 0.872 0.936 0.930 0.948 0.894 0.961 0.966 Variance

0.009 0.008 0.007 0.007 0.008 0.014 0.009 0.031 0.021 0.052 0.018 0.026 0.059 0.057 0.130 0.076 0.392 0.161 0.173 0.235 0.266 0.305 0.354 0.188 0.137 0.572 0.312 0.524 0.621 0.614 0.402 0.704 0.739 0.747 0.356 0.773 0.646 0.890 0.740 0.733 0.840 0.879 0.703 0.638 0.817 0.877 0.949 0.863 0.916 0.957 0.903 0.901 0.928 0.953 0.935 0.954 0.970 35.485

0.91’ 0.992 0.994 0.994 0.997 0.995 0.994 0.889 0.987 0.644 0.993 0.956 0.049 0.056 0.053 0.069 0.029 0.052 0.059 0.041 0.044 0.029 0.030 0.077 0.063 0.032 0.067 0.027 0.033 0.061 0.014 0.032 0.034 0.018 0.011 0.024 0.013 0.014 0.017 0.009 0.008 0.018 0.035 0.013 0.026 0.001 0.003 0.002 0.005 0.006 0.020 0.006 0.010 -0.000 0.011 0.016 0.000 19.379 386

Gyre

margin

PO.007 PO.034 -0.024 -0.019 0.015 0.045 0.023 0.377 0.061 0.656 0.029 0.239 0.937 0.966 0.929 0.956 0.355 0.91 I 0.907 0.937 0.923 0.554 0.385 0.886 0.944 0.436 0.778 0.204 0.537 0.571 0.064 0.506 0.580 0.266 0.036 0.155 0.149 0.275 0.105 0.505 0.417 0.107 0.582 0.049 0.460 -0.032 0.133 0.075 0.074 0.097 0.147 0.325 0.221 -0.024 0.130 0.042 -0.004 23.396

(I.015 0.0 I? 0.013 -0.01 I -0.013 -0.012 -0,014 -0.023 0.009 PO.039 0.020 PO.019 0.00 I 0.066 0.173 0.095 0.806 0.142 0.00 0.079 0. 129 0.693 0.778 0.052 0.050 0.626 0.?75 0.789 0.372 0.329 0.859 0.233 0. I 54 0.484 0.843 0.515 0.707 0.‘29 & 0.513 0.196 0.222 0.790 0.07 I 0.727 0.23 I 0.382 0.140 0.265 0.240 0. I17 0. I85 0.138 0. 140 0. I97 0.045 0.270 0. I55 12.863

PALEOCEANOGRAPHIC

TRANSFER

TABLE

387

FUNCTION

4

VARIMAX FACTOR SCORE MATRIX Species

Tropical

T. trachelium 0. tetrathalamus Heliodiscus spp. T. bicornis T. antarctica S. osculosa Spongurus spp. P. murrayana P. spinosa Polysolenia spp. S. polysiphonia C. tuberosa Disolenia spp. Cenosphaera spp. A. medianum A. haysi Actinomma spp. 1 spp. 2 Actinomma Stylatractus spp. Axoprunum spp. S. tetras spp. Euchitonia L. butschlii A. denticulata and A. strelkovi

-0.039 0.908 0.029 -0.045 -0.002 0.032

0.017 0.089 -0.046 -0.065 0.041 -0.013

0.142 0.074 -0.004 -0.026 0.055 0.008 0.057 0.030 0.270 0.198 0.084 0.004

straints or variations in silica dissolution patterns which might preferentially favor dissolution-resistant species. Lozano (1974) had discovered that Cycladophora davisiana and Pterocorys hirundo produced no analog results. Siphocampe spp. also produced a no analog problem since its abundance in the surface sediment samples from the South Atlantic never exceeded 3% whereas its abundance was in excess of 10% at several levels in a piston core (RC13-229) raised from the eastern subtropical South Atlantic which contains a nearly continuous sedimentary record of the last 700,000 yr. Examination of contoured maps of the percentage of each species in the 57 surface sediment samples disclosed that the distribution patterns of certain major species did not clearly correlate with present-day sea-surface temperatures. There could be several reasons for this phenomenon. Sea-

Polar

Gyre margin

Subtropical 0.121 0.106 0.148 -0.048 -0.004

0.007 0.004 0.003

0.303 -0.081 0.025 0.447 0.004 0.141 0.073 0.048 -0.036 -0.012 -0.002 -0.012

-0.001

-0.017

-0.013

0.027 0.054 -0.002 0.021 0.034 0.015 -0.002 -0.005 -0.004 -0.014 0.985

0.380 0.075 0.070 0.566 0.091 0.119 0.042 -0.018 -0.005 0.410 -0.062

0.117 -0.006 0.176 -0.027 -0.013 0.286 0.215 -0.180 -0.0% -0.167 -0.012

-0.026 -0.006

0.001 0.057 0.081 0.081 0.086 -0.006

0.011

-0.010 -0.017 0.027 0.547 0.478 0.397 0.140

surface temperature may not be an important dependent variable for these particular species. The assumption that there is a strong relationship between Radiolaria in the surface sediments and the overlying water masses may be erroneous in some areas of the oceans because of silica dissolution during passage through the water column, postdepositional solution, or transport and redeposition by bottom currents. Also certain Radiolaria may not live within the upper 300 m of the ocean and therefore may not reflect variations in seasurface temperatures. Since the major objective of this study was to develop a transfer function to predict paleotemperatures, these four species were withdrawn from further analysis (Ommatodiscus sp., Theoconus zancleus, Lithelius minor, and Lamprocyclas maritalis). Tetrapyle octacantha, Hymeniastrium spp., and Spongotrochus glacialis were all eliminated

388

JOSEPH

J

MORLEI

because of identification problems as ex- normalized data was resolved by this methpress,ed by their highly variable morphology. od into four varimax factors. The factor loadings shown in Table 3 represent the Antarctissa denticulato and Antclrctissrr proportion contributed by each factor to strelkovi appeared to intergrade (Lozano, 1974; Lozano and Hays, 1976), therefore, each sample. The surface samples in this table are arranged in increasing order of they were combined under one taxonomic present-day winter (August) sea-surface heading. As a result of these analyses, the radiolarian transfer function for the temperature at each core location so that South Atlantic Ocean was based on 24 the temperature dependence of any of the factors can be readily assessed. The comtaxonomic groups (Table 2). The raw counts of the 24 species were munality of each sample is printed in the normalized within each sample so that column to the right of the core-top listing. is obtained by summing each sample was given equal weight in The communality the squares of the individual varimax facsubsequent calculations. The normalized indicate that species’ counts were processed through a tors. Low communalities species’ abundances have been distorted Q-mode factor analysis. This operation expressed the species in each surface sam- by dissolution, mixing of distinctly differidentification of ple in terms of fractions of a number of ent faunas, inaccurate factors (assemblages or end members). The species, or other processes so that a poor

I

FIG.

loadings

SURFACE

FACTOR TDnDlrA,

3. Distribution x 100.

1

of factor

/

1, tropical

/

77

assemblage,

in surface

7.0

sediments

expressed

as factor

PALEOCEANOGRAPHIC

TRANSFER

389

FUNCTION

SURFACE

FACTOR

2

.

45

FIG. 4. Distribution loadings x 100.

.

30

.

15

.

0

.

I5

of factor 2, polar assemblage, in surface sediments expressed as factor

relationship exists between the assemblages’ model and the original sample’s information. If the communality is unity, then the model accounts for all the original information. The communalities of the 57 surface samples are all above 0.8. The four varimax factors account for over 91.1% of the distributional variance of the species included. The individual variances for each factor are as follows: factor 1 (tropical) 35.5%; factor 2 (polar) 19.4%; factor 3 (gyre margin) 23.4%; factor 4 (subtropical) 12.8%. The addition of a fifth factor explained less than 2% of the variance and showed no evident geographic distribution corresponding to a known oceanographic parameter. The varimax factor score matrix (F’) for the 57 core-top samples is shown in

Table 4. The absolute values in this matrix indicate the relative importance of each species for each factor. Factor Mapping Contoured maps of the factor loadings of each factor for each sample were constructed. This step was taken to see if the four assemblages had interpretable patterns which could be correlated with oceanographic parameters. The highest factor loadings for factor 1 (Fig. 3) occur in samples located near the equator with decreasing loadings toward higher latitudes. Examination of the varimax factor score matrix in Table 4 reveals that factor 1 (tropical factor) is dominated by two species, Ommatartus tetrathalamus and Spongaster tetras.

JOSEPH J. MORLEY

390

SURFACE

FACTOR

15

,YRE

3

MARGIN

'15

c45

45

.

60

.

45

FIG. 5. Distribution loadings x 100.

.

30

.

15

.

0

.

‘60

15

of factor 3, gyre margin assemblage, in surface sediments expressed as factor

Factor 2 (Fig. 4) is a polar factor with factor loadings of 0.99 or greater in all the surface samples located south of 46”s latitude. The lowest factor loadings for factor 2 occur in equatorial and subtropical cores. The variations in abundance of two species, Antarctissa denticulata and Antarctissa strelkovi, are responsible for most changes in the polar assemblage. Because of identification problems discussed earlier, these two species are combined into one taxonomic group. Samples with the highest values for factor 3 (Fig. 5) are located beneath the Subtropical Convergence and along the southwest coast of Africa. The dominant species (Table 4) in this factor are Actinomma spp. 1, Theocalyptra bicornis,

Larcopyle butschlii, and Cenosphaera spp.

Factor 4 (Fig. 6) accounts for the least amount of variance (12.8%). The highest factor loadings are from samples located within the Subtropical Gyre, therefore, this factor was referred to as a subtropical factor. Three species, Polysolenia spinosa, Polysolenia spp., and Siphonosphaera polysiphonia, dominate factor 4 (Table 4). Regression Analysis

The multivariate regression procedures detailed by Imbrie and Kipp (1971) were used to derive a transfer function for relating the four varimax factors (obtained from the Q-mode factor analysis) to both winter and summer sea-surface temperatures. This method is a least-squares best

PALEOCEANOGRAPHIC

TRANSFER

FUNCTION

C

SURFACE SUBTROPICAL

I5

30

45

. i2 60 60

FIG. 6. Distribution loadings x 100.

60 45

30

15

0

15

of factor 4, subtropical assemblage, in surface sediments expressedas factor

fit of the data. The present-day winter (August) and summer (February) temperatures for each of the surface sediment samples were determined using sea-surface temperature maps constructed by the Geophysical Fluid Dynamics Laboratory (GFDL) at Princeton (D. Hahn, personal communication, 1976). Linear and curvilinear equations were derived and examined. The statistical results are listed in Table 5. The curvilinear equation is statistically better than the linear. For both winter and summer, the curvilinear solution gives a lower standard error of estimate, and higher values for the multiple correlation coeffkient and cumulative proportion of variance reduced. Closer examination of the curvilinear equa-

tion reveals that the standard error of estimate for winter (August) of 1.36”C is approximately 5.2% of the range of the present-day winter temperature (0.6” to 26.7”C). The standard en-or of estimate for summer (February) of 1.37”C is less than 5.4% of the range of the present-day summer temperature (2.9” to 28.1”C). Over 98% of the original observational data is explained by the curvilinear solution. The coeffkients of the variables and the intercepts for the curvilinear equations for both the winter and summer are listed in Table 6. The F' matrix from the factor analysis on the surface samples (Table 4) and the regression coeffkients and intercepts (Table 6) define the transfer function (SAR 01) produced with the fauna1 and

392

JOSEPH

Multiple correlationn coefficients

J. MORLEI

Cumulative proportion reduced

Standard error of estimate

Linear T-Summer T-Winter

0.971 0.979

0.947 0.961

1.86”C 1.6X

4 -l

Curvilinear T-Summer T-Winter

0.988 0.988

0.982 0.982

I .37”C 1.36”C

14 14

sea-surface temperature sets described in this paper. To measure the ability of the transfer function to estimate temperatures, the estimated temperatures for both summer and winter were subtracted from the measured (observed) temperatures for each of the 57 surface samples. In no one sample was the difference between the two greater than 2.3”C for winter and 2.6”C for summer. Differences (residuals) of less than 1°C were recorded in 36 of the 57 samples. The plotted summer and winter temperature residuals in each sample showed no obvious geographical distribution pattern. TABLE PARAMETERS

Variable Tropical Polar Gyre margin x Subtropical Polar x Subtropical Polar x Gyre margin Polar x Polar Tropical x Subtropical Subtropical Gyre margin x Gyre margin Gyre margin Tropical x Tropical Tropical x Gyre margin Subtropical x Subtropical Tropical x Polar Intercepts

Figure 7 shows the temperature residuals plotted against the measured sea-surface temperatures for each of the 57 surface samples. The data indicate that the transfer function produces temperature estimates with similar reliability in all regions of the South Atlantic. APPLICATION OF TRANSFER FUNCTION IN OTHER REGIONS

To test the ability of the South Atlantic Radiolarian Transfer Function to produce reliable temperatures in other ocean areas, sea-surface temperatures were estimated for four surface sediment samples random6

OF TRANSFER

FUNCTIONS

Winter regression coefficient

Summer regression coefficient

52.89581 -9.61611 -36.71451 58.87440 -7.51203 x?.ll573 -36.59505 36.86906 -7.91525 30.11095 ~ 17.34039 -26.93280 - I 1.30349 ~ 19.23666 -9.05053

6.63597 71.67975 39.45581 -63.88632 -33.87775 23.58836 -47.00037 70.2974 1 -63.10623 77.55034 ~28.47157 -28.29770 -21.97058 -23.04901 - 24.07539

PALEOCEANOGRAPHIC

I -

TRANSFER

393

FUNCTION

. -3 -t..,.

I .,..

I

0

5

10

MEASURED

I .‘..+ 15

SEA

SURFACE

I ::.:

I :.

20

25

TEMP.

(“Cl

30

FIG. 7. Graphs of measured summer (February) and winter (August) sea-surface temperature minus estimated summer and winter temperatures (residuals) plotted against measured sea-surface temperatures for each of the 57 surface sediment samples.

ly selected from a group of core tops which had been used to derive a transfer function for the eastern South Pacific (Molina-Cruz, 1976). Table 7 shows the results of this experiment and the differences (residuals) between the present-day winter and summer sea-surface temperatures as calculated from the sea-surface temperature maps constructed by the Geophysical Fluid Dynamics Laboratory and the estimated winter and summer sea-surface temperatures. The low residuals, which are less than the standard error of estimate of the equation (a 1.4”C) attest to the ability of the South Atlantic Radiolarian Equation to predict rather accurately sea-surface temperatures in the eastern South Pacific TABLE

Ocean, thereby enhancing the possibility that this equation may produce accurate temperature estimates in cores not only in the South Atlantic but also in most ocean regions. SUMMARY

AND CONCLUSIONS

1. Comparison of the distribution patterns of 67 radiolarian species in the surface sediments throughout the South Atlantic with present-day sea-surface temperatures showed that the variations in abundance of several of the most prevalent species do not correlate with sea-surface temperatures. There are several possible reasons for this: (a) varying degrees of silica dissolution, (b) deep-living species 7

TESTRESULTS USINGSOUTH ATLANTIC EQUATION ON SAMPLES FROM PACIFIC Summer (February) temperatures

Winter (August) temperatures

South Pacific sample

Latitude

Longitude

Est.

Obs.

Res.

Est.

Obs.

Res.

V19-38 RC 9-86 RC13-105 RC13-117

12”3O’S 23”33’S 06”58’S OO”19’S

86”39’W 72”29’W 86”Ol’W 106”54’W

21.2 16.6 22.4 22.8

19.3 15.5 20.2 22.8

-1.9 -1.1 -2.2 0.0

24.5 22.3 24.8 26.9

26.0 21.0 25.9 26.1

1.5 -1.3 1.1 -0.8

394

JOSEPH

which do not reflect directly variations in sea-surface temperatures, (c) shallowwater species which are more dependent on ‘other physical and chemical oceanographic properties. or (d) species with highly variable morphologies which make it extremely difficult to relate their abundance patterns to tempertures. 2. The Q-mode factor analysis using the abundances of 24 taxonomic groups in 57 surface samples produced four fauna1 assemblages (tropical, polar, gyre margin, and subtropical) which show a close correlation to present-day sea surface temperatures and surface circulation patterns. These

four

factors

accounted

for

Over

91%

of the cumulative variance of the data. 3. The transfer function. derived from this data using standard regression techniques relating radiolarian assemblages to present-day sea-surface temperatures, has a standard error of estimate for winter of 1.36”C and for summer of 1.37”C. 4. Results from a test set of surface sediment samples from the eastern South Pacific indicate that the South Atlantic Radiolarian Transfer Function can predict accurate temperature estimates even in regions outside the South Atlantic. ACKNOWLEDGMENTS This work is part of a dissertation submitted to Columbia University in 1977. I thank my advisor, J. D. Hays, for his continued guidance and support. The thesis was read by A. McIntyre and N. Opdyke. Illustrations were drawn by M. Perry and B. Walter. N. Kipp, J. Lozano, B. Molfino, S. Streeter, and .I. Robertson frequently gave their time for fruitful discussions. L. Burckle, P. Lohmann. H. Sachs, and P. Thompson reviewed this manuscript and offered many helpful suggestions. The raw data presented in this study can be acquired from the CLIMAP archivist, W. H. Hutson, at Oregon State University, Corvallis, Oregon. This research was part of the CLIMAP project jointly funded by the National Science Foundation’s Office of Climate Dynamics and International Decade of Ocean Exploration Grants GX-28671 and OCE7519627 to Lamont-Doherty Geological Observatory. Coring operations supported by National Science Foundation Grant OCE76-18049 and Offtce of Naval Research Grant N00014-75-C-0210 (Scope E).

J.

MORLEY

REFERENCES Benson. R. M. (1966). “Recent Radiolaria from the Gulf of California.” Doctoral dissertation. University of Minnesota. Bjorklund, K. R. t 1977). Ac ti/)r~/rrr,)c/ Irri\ \i sp. n.. its Holocene distribution and size variation in Atlantic Ocean sediments. hlic.~opcl/rorrr(j/~~,~~ 23, I I4 - 126. Botnikov, V. N. (1964). Seasonal and long term fluctuations of the Antarctic Convergence Zone. Soi,irt Aurr/rctic~ E.rpedirio/i I+mtrrir~,r B/t//~~riu 45, 5, 92-95. Broecker, W. S. (1974). “Chemical Oceanography.” Harcourt Brace Jovanovich, New York. Defant. A. (1961). “Physical Oceanography.” Vol. 1. Pergamon Press. New York. GOB, R. M., and Bjorklund. K. R. (1971). Radiolaria in surface sediments of the North Atlantic Ocean. Mic~roprrIrorltoloX~ 17, 434-454. GOB, R. M.. and Bjorklund. K. R. (1974). Radiolaria in surface sediments of the South Atlantic. Microprr/eonrolog~ 20, 38-75. Gordon. A. L. (1971). Antarctic Polar Front Zone. frt “Antarctic Oceanology,” Vol. 15. pp. 205-221. Amrr-ic,trri

Grqd~.sicd

Unic~n

Antcfrc

I/C’ Rrseurc,h

Sarie.s. Haeckel, E. (1887). Report of the Radiolaria collected by H. M. S. Challenger during the years 1873-76. Rrprwr. Vowge “Chn/lengur” on Zoo/~~g~ 18, 1 1803. Imbrie, J.. and Kipp. N. G. (1971). A new micropaleontological method for quantitative paleoclimatology: Application to a late Pleistocene Caribbean core. In “The Late Cenozoic Glacial Ages” (K. K. Turekian, Ed.), pp. 71-181. Yale Univ. Press, New Haven. Imbrie. J.. van Donk, J., and Kipp. N. G. (1973). Paleoclimatic Investigation of a Late Pleistocene Caribbean deep-sea core: Comparison of isotopic and fauna1 methods. Qlccltrrncrrr Rcwwd~ 3. IO38. Kipp. N. G. (1976). New transfer function for estimating past sea-surface conditions from sea-bed distribution of planktonic foraminiferal assemblages in the North Atlantic. It) “Investigation of Late Quaternary Paleoceanography and Paleoclimatology” (R. M. Cline and J. D. Hays, Eds.), pp. 341. Geologiccll Socirt.v ofAme~ic~c/ ,Mc~rrloir 145. Ling. H. Y., and Anikouchine, W. A. (1967). Some Spumellarian Radiolaria from the Java. Philippine and Mariana Trenches. Jo//r-ntrl ~f’P~l/a~,r/to/~,~~ 41, 1481-1491. Lozano. I. A. (1974). “Antarctic Sedimentary, Fauna1 and Sea-Surface Temperature Responses during the Last 230.000 Years with Emphasis on Comparison between 18,000 Years Ago and Today.” Doctoral dissertation, Columbia University, New York. Lozano, J. A., and Hays, J. D. (1976). The relationship of radiolarian assemblages to sediment types

PALEOCEANOGRAPHIC and physical oceanography in the Atlantic and western Indian Ocean sectors of the Antarctic Ocean. 01 “Investigation of Late Quaternary PaIeoceanography and Paleoclimatology” (R. M. Cline and J. D. Hays, Eds.). pp. 303-336. Geologicc~l Societ.v of Amrriccr

Memoir

145.

Molina-Cruz, A. (1976). “Paleo-Oceanography of the Subtropical Southeastern Pacific during Late Quaternary: A Study of Radiolaria, Opal and Quartz Contents of Deep-Sea Sediments.” M.S. thesis, Oregon State University, Corvallis. Moore. T. C., Jr. (1973). Method of randomly distributing grains for microscopic examination. Jolrrntrl

oj.Sedirnenrrrry

Petrology

43, 904-906.

Morley, J. J. (1977). “Upper Pleistocene Climatic Variations in the South Atlantic Derived from a Quantitative Radiolarian Analysis: Accent on the Last 18,000 Years.” Doctoral dissertation, Columbia University, New York. Nigrini, C. (1967). Radiolaria in pelagic sediments from the Indian and Atlantic Oceans. Bulletin of Scripps Instituriorl of Ucrcinograph~ 11, I- 125. Nigrini, C. (1968). Radiolaria from eastern tropical Pacific sediments. Mic,r-opcrlrontolo~~ 14, 51-63. Nigrini, C. (1971). Radiolarian zones in the Quaternary of the equatorial Pacific Ocean. In “The Micropaleontology of Oceans” (W. R. Riedel and B. M. Funnel, Eds.), pp. 443-461. Cambridge Univ. Press, Cambridge, England.

TRANSFER

FUNCTION

395

Petrushevskaya, M. G. ( 1967). Radiolarians of orders Spumellaria and Nassellaria of the Antarctic region (from material of the Soviet Antarctic Expedition). In “Biological Reports of the Soviet Antarctic Expedition (1955-1958)” (A. P. Andriyashev and P. V. Ushakov, Eds.), pp. 2-186. Israel Program for Scientific Translations, Jerusalem. Riedel, W. R. (1958). Radiolaria in Antarctic sediments. B.A.N.Z. Antcrrcric Resecrrch E.ypedifion Reports. Series B 6 (lo), 217-255. Robertson, J. H. (1975). “Glacial to Interglacial Oceanographic Changes in the Northwest Pacific, Including a Continuous Record of the Last 400,000 Years.” Doctoral dissertation, Columbia University, New York. Sachs, H. M. (1973a). North Pacific radiolarian assemblages and their relationship to oceanographic parameters. Quaternar~ Research 3, 73 -88. Sachs, H. M. (1973b). Late Pleistocene history of the North Pacific: Evidence from a quantitative study of Radiolaria in Core V21- 173. Quafernaq Research 3, 89-98. Sachs, H. M. (1973~). “Quantitative RadiolarianBased Paleoceanography in Late Pleistocene Subarctic Pacific Sediments.” Doctoral dissertation, Brown University, Providence, R.I. Sverdrup, H. U.. Johnson, M. W., and Fleming, R. H. (1942). “The Oceans: Their Physics, Chemistry and Biology.” Prentice-Hall, Englewood Cliffs, N.J.