Sterol diagenesis in a recent marine intertidal sediment

Org. Geochem. Vol. 5, No. 4, pp. 291-297, 1984 Printed in Great Britain

0146-6380/84 $3.00 + 0.00 Pergamon Press Ltd

Sterol diagenesis in a recent marine intertidal sediment F. T. GILLAN* and R. B. JorINs Department of Organic Chemistry, University of Melbourne, Grattan St, Parkville, Victoria 3052, Australia (Received 15 October 1983; accepted 11 June 1984)

Abstract--The abundance of sterols in sediment depth profiles is determined by variations in input source abundances and diagenesis. Deconvolution of these variables would permit accurate estimation of degradation rates and initial input source contributions of sterols to the sediments. In this study we have demonstrated the application of a simple mathematical approach to the estimation of the relative stabilities of a range of sterols in a microbially-poor temperate intertidal sediment. The results indicate that st-5-enols and possibly 4-methyl sterols are less stable than other sterols in this environment. Since dehydration reactions of sterols would be favoured by both a 4-methyl substituent and a C5,6 double bond, whilst other processes would not be as selective, it seems probable that this abiolog]cal process predominates in the Corner Inlet sediments.

INTRODUCTION The sterols found in marine sediments can originate from a diverse range of source organisms or by diagenesis of suitable steroid precursors. Many studies have investigated the potential of steroids as chemical markers for the contribution from terrestrial and marine organisms to sediments (Cardoso et al., 1976; Lee et al., 1979, 1980; Nishimura and Koyama, 1977; Volkman et al., 1981; Wardroper et al., 1978). In the report on sediments from Corner Inlet by Volkman et al. (1981) it was proposed that the sterols originated predominantly from in situ and detrital microalgae. Previous studies of this sediment employing other chemical markers had indicated that the major lipid sources were diatoms, with other algal classes of relatively minor importance (Gillan and Johns, 1980; Volkman et al., 1980). A minor higher plant input, from the seagrass Zostera rnuelleri was also indicated in these studies. On the basis of the extensive lipid studies already performed on sediments from this environment (Volkman, 1977; Gillan, 1981), and the apparently simple input source distribution consisting of microalgae, seagrasses and probably meiofauna, the study site, Corner Inlet, was considered to be near ideal for analysis of the causes of sterol abundance variations (input variation and/or diagenesis). Diagenesis of sterols can be either abiological and/or microbially-mediated. Several studies have directed their attention to the identification of the degradative pathways of sterols in sediments (Dastillung and Albrecht, 1977; Gagosian et al., 1980; Gaskell and Eglinton, 1974, 1975; Lee et al., 1977, 1979, 1980; Nishimura, 1978), algal mats (Edmunds et al., 1980) and in bacterial cultures or microbial

* Present address: Australian Institute of Marine Science, Townsville, Queensland 4810, Australia.

enrichments (Arima et al., 1969; Cargile and McChesney, 1974; Eyssen et al., 1973; Marsheck et al., 1972; Nagasawa et al., 1969; Taylor et al., 1981). The recent study by Taylor et al. (1981) demonstrated that the anaerobic microbial degradation of cholesterol requires nitrate as a terminal electron acceptor, thus it would be expected that sterol diagenesis would be by predominantly abiological processes in environments where nitrate was absent and the bacterial population was low. Both of these criteria are met by the Corner Inlet intertidal environment: nitrate is virtually absent from the anoxic sediments and, the bacterial population is very low (Volkman et al., 1980). Bacteria producing the C18 monoenoic acid, vaccenic acid, as their major lipid fatty acid have been shown to be the major bacterial chemotype in this sediment (Gillan et al. 1983). In addition, the abundance of C18 monoenoic acids has been shown to decline by a factor of 20 in the depth range 2 to 7 dm in this environment (Johns et al., 1978). It is thus likely that the bacterial biomass declines by a similar factor over this depth range, and that the microbiaUymediated degradation rate in the Corner Inlet sediments (dependent on both the bacterial population and the abundance of terminal electron acceptors) would change by at least this factor. However, since the bacterial populations are extremely low (three orders of magnitude lower abundance than in mangrove sediments we are examining (Perry et al., 1979; Volkman et al., 1980), it is probable that abiogenic processes will predominate in this environment. In the absence of microbial processes, the degradation of sterols in a sediment is expected to be controlled by physicochemical stresses such as temperature and acidity. If all such stresses are invariant the rate of degradation of a sterol could be approximated by the equation:

291

Rate = k S

292

F.T. GILLANand R. B. JOHNS

where k is a constant, and S is the concentration of the sterol, i.e. a simple first order relationship. Providing the sedimentation rate is constant, and the input rate does not vary, this situation would result in an exponentially decaying concentration of the sterol with depth in the sediment. In a real situation the inputs are not invariant and the sedimentation rate is not constant. The objective of this study is to attempt to isolate the abundance variations in a sterol depth profile caused by diagenesis, from variations caused by input changes. METHODS Sediment samples were collected from just above the low-tide mark at Old Yanakie Beach (Comer Inlet, Victoria) using a plastic core tube (5 cm i.d.). The environment is a shallow, almost land-locked inlet. The sediments were fine sands and were very well sorted. The mean grain size was consistent throughout the core (Gillan and Johns, 1980). The sediment accumulation rate has been estimated to be approximately 1.5 mm/yr based on the depth profile of fire-derived polycyclic aromatic hydrocarbons (Clementson, 1981). The deepest section of the core is thus estimated to be ca. 500 yr old. The core was extruded and sectioned (5 cm sections) and samples at 10 cm intervals were extracted with solvent (chloroform:methanol, 2:1 v/v) as previously described (Johns et aL, 1980). An aliquot of the total solvent extract was fractionated by thinlayer chromatography on Silica gel GF254 using n-heptane: chloroform: diethylamine (9: 4:1, v/v/v) as solvent, and the unesterified ("free") sterol fraction was isolated (Rf cholest-5-enol: 0.28). The sterol mixture was reacted with bistrimethylsilyltrifluoroacetamideto produce the trimethylsilyl ethers, which were analysed by capillary GC (SCOT SE30 column, 50m × 0.5 mm, S.G.E. Australia). Identifications were based on the reported GC/MS characterization of the sterols from this environment (Volkman et aL, 1981). Analytical reproducibility was estimated to be + 5~o + 2 ng/g (2a) in total sterol abundance, and relative abundance reproducibility was c. __+2~o, based on electronic integrator response. Retention times for the sterols were scaled from cholest-5-enol = 1.000 to 24-ethylcholest-5-enol= 1.630 as used previously (Volkman et al., 1981). Reproducibility averaged +0.003 (20) for interpolated components whilst for extrapolated components, reproducibility was +0.005 (2a). All mathematical analyses were performed on a PDP11/70 computer. Rr..SULTS AND mSCUSmON

Sterol analyses Table 1 lists the free sterol abundances in the depth profile taken at Corner Inlet. The distribution and

Table 1. Sterol abundancedata (ng/g dry wt) Depth Sterol No. RRT° 0b 20 30 40 40 60 70 1 0.898 85 39 15 26 13 9 12 2 0.929 13 17 12 12 10 10 15 3 1.000 304 227 159 280 148 131 152 4 1.031 68 62 47 56 51 45 49 5 1.121 448 125 55 77 47 35 32 6 1.158 77 47 44 48 41 32 39 7 1.280 47 18 15 20 13 10 9 8 1.315 97 83 103 214 73 68 57 9 1.354 23 28 43 57 42 39 39 10 1.389 61 71 68 59 54 42 77 11 1.424 128 70 121 277 90 78 92 12 1.466 18 34 56 61 51 41 53 13 1.509 14 16 25 21 23 18 22 14 1.555 9 25 83 49 53 47 84 15 1.630 173 64 208 741 154 147 198 )6 1.679 50 41 126 183 128 113 120 17 1.705 16 22 35 17 28 25 106 Total 1631 989 1215 2198 1019 890 1156 °RRT=relative retention time on SE30 (see the text). Sterol identifications are as follows: (I) cholesta-5,22-dienol; (2) cholest-22E-enol; (3) cholest-5-enol; (4) cholestanol; (5) 24-methylcholesta-5,22-dienol; (6) 24-methylcholest-22-enol (plus a m i n o r amount of cholest-7-enol); (7) 24-methyleholesta-5,24(28)-dienol;(8) 24-methylcholest-5-enol; (9) 24-methyleholestanol; (10) 23,24-dimethylcholesta-5.22dienol; (11) 24-etbylcholesta-5,22-dienol; (12) 24-etbylcholest-22-enol; (13) 24-methyleholest-7-enol;(14) 24-ethyleholesta-7,22-dienol(tentative identificationbased on MS: no standards available); (15) 24-ethylcholest-5-enol; (16) 24-ethylcholestanol (plus a trace of 28-isofueosterol); (17) 4,23,24-trimethyleholest-22-enol. hAs reported by Volkman et al. (1981).

total abundance of the sterols was very similar to that reported for a surface sediment from this locality (Volkman et al., 1981). Full mass spectral identifications were reported in this earlier paper. In this study it was assumed that the components eluting at the same relative retention time~ were as previously identified. In the case of the sterol with relative retention time ( R R T ) = 1.158, two components were known to co-elute. Since one component was much more abundant than the other in the earlier analysis, it was assumed that this component predominated in all the samples from the depth profile. The total free sterol abundance varies from 900 to 2200 ng/g (dry wt) in the samples with the maximum abundance occurring at 40 cm depth. The observed increased abundance at 40 cm is due largely to higher abundances of the sterols 24-ethylcholest-5-enol, 24-ethylcholesta-5,22-dienol, 24-methyl- cholest-5enol and cholest-5-enol. The predominance of C29 sterols in this sample indicates a probable major input from higher plant material (Huang and Meinschein, 1979). Figure la is a plot of the abundance:depth profiles of sterols exhibiting maxima at 40 cm depth. Baseline interpolation between the data at 30 and 50 cm indicates that the deviation at 40 cm derives from an input which contains approximately 70% 24-ethylcholest-5-enol. Clearly, since this depth is characterized by a specific enhanced input, data from this depth will perturb any attempt to estimate degradation rates using the complete data set.

Sterol diagenesis (a)

7o0

•

A

(b)

2oo

lj~.~ \.-m_.

8/'\/.-

/

eco

J

o

70 o 70 Depth Fig. 1. Abundance:depth profiles for selected sterols. (1) 24-ethylcholest-5-enol; (2) 24-ethylcholesta-5,22-dienol; (3) 24-methylcholest-5-enol; (4) 24-ethylcholestanol; (5) 24-methylcholesta-5,22--dienol; (6) 4,23,24-trimethylcholest22-enol; (7) 23,24-dimethylcholesta-5,22-dienol; (8) cholest22-enol; (9) cholestanol. Figure lb is a graph of the abundance profiles of several sterols which do not prominently exhibit the distinctive 40 cm input. Both 23,24-dimethylcholesta-5,22-dienol and 4,23,24-trimethylcholest22-enol have abundance maxima at 70 cm depth, suggestive of a further input abundance change. Excluding the 70 cm data point, the former sterol depth profile is a reasonably smooth decline, as would be expected if diagenesis was the only cause of abundance variation. S t e r o l degradation rates

In a situation of constant input rates and sedimentation rate, sterol abundance:depth profiles should follow a simple exponential decay, however, this situation is unlikely to occur in real samples. As we have indicated, there are at least two points in this depth profile that exhibit input source and/or abundance changes. Indeed, our earlier study of phytyi ester diagenesis in this environment (Johns et al., 1980), indicated a further input source change between 20 and 30cm depth. Although not all the sterols are affected by each input change, the profile examined in this study is far from "ideal". We have assumed a stable sediment accumulation rate in all our calculations. On this basis, the depth profile is assumed to be equivalent to a linear time profile, and the depth-based degradation rate can thus be estimated using the equations:

or

293

points are available, the regression parameters will accurately represent both the mean input abundance of the sterol and its degradation rate. In a typical geochemical study, samples are strictly limited both by availability of material and time involved in work-up and analysis. In this study we have limited ourselves to six samples. Figure 2 is a plot of In (abundance: 23,24-dimethylcholesta-5,22-dienol):depth. Two regression lines are drawn, viz., a regression line using the full data set, and the regression line derived using the truncated (minus 70 cm) data set. 2a error bars are plotted for all data points. Regression lines could have been drawn for other datum deletions, however these would not have intersected as many data error bars as the - 7 0 cm regression line. Table 2 lists the effects of each of the possible deletions on the regression coefficient, the regression line intercepts and gradient, and the variance of the truncated data set from the regression line. The regression coefficient maximises with the 70 cm deletion and the variance of the truncated data minimises with this deletion. Since the regression coefficient is gradient dependent (for example, if the gradient is zero, R = 0.000 irrespective of the data deviations), the deviation from the regression line was chosen as the criterion for the quality of fit. N - 2 weighting was used to minimise bias. Deletion of a second data point (see Table 2) does not markedly improve the quality of fit, or appreciably alter the gradient of the regression line (and thus our estimated degradation rate). Since we know the experimental error inherent in our analytical procedures (see methods section), we can calculate the minimum variance that is likely to occur in the data set for a situation of constant input rate. This experimental variance was estimated to be the mean (N - 1 weighting) of the logarithmic standard deviations in the data points squared, that is:

4.5 ~

5

\}\ \

S = Soe -k°

In S = In So - k D where S is the sterol abundance at depth D, So is the initial sterol abundance and k is the "degradation constant". Regression of In S against D will then result in an intercept at In So and a gradient of - k . Providing the average initial abundance does not vary systematically with time, and sufficient data

3.5

I 70

0 Depth

Fig. 2. Natural logarithm of abundance (23,24dimethylcholesta-5,22-dienol) plotted against depth. - regression line derived using complete data set; - - - regression line excluding the 70 cm datum.

294

F.T. GILLANand R. B. JOHNS Table 2. Regression lines and variance for subsets of the 23,24-dirnethylcholesta-5,22-dienol data Datum deletion

Intercept

Gradient

Regression coefficient

Variance

--

4.25 (0.42)

- 0 . 0 3 2 (0.087)

--0.274

0.0565

20 30 40 50 60 70

4.12 4.20 4.27 4.26 4.15 4.57

(0.72) (0.59) (0.54) (0.50) (0.32) (0.14)

- 0.009 - 0.024 -0.034 -0.029 0.007 - 0.128

(0.138) (0.115) (0.108) (0.105) (0.070) (0.032)

- 0.063 - 0.195 -0.285 -0.249 0.089 - 0.966

0.0712 0.0733 0.0745 0.0713 0.0272 0.0039

4.70 4.54 4.56 4.59 4.47

(0.20) (0.20) (0.19) (0.15) (0.09)

-- 0.153 - 0.123 - 0.128 -- 0.137 - 0.096

(0.044) (0.045) (0.045) (0.037) (0.024)

-- 0.978 -- 0.964 - 0.968 - 0.980 - 0.982

0.0027 0.0050 0.0056 0.0033 0.0008

70, 70, 70, 70, 70,

20 30 40 50 60

Notes: " E x p e c t e d " variance = 0.0015. Intercept = In So; g r a d i e n t - - - k . limits are given in parentheses.

Data: In S + tr Minimum variance = ( ~ ,

try)/(N-1)

A "good" regression line would result in the calculated variance being less than four times this minimum variance. In the case of 23,24dimethyl-cholesta-5,22-dienol, the observed variance can be reduced to less than four times the minimum variance by deletion of just one data point, that at 70 cm. No further deletions can then be justified. This is not the situation for many of the sterols. Table 3 and Fig. 3 present the analysis for the sterol, 24-methylcholest-5-enol. Deletion of the 40 cm data point reduces the calculated variance by a factor of 12, but this variance is still fifteen times greater than that expected on the basis of experimental inaccuracies alone. Deletion of a second data point reduces the variance to near that expected. Figure 3 graphically depicts the effects of these deletions on the regression line. Whilst it is clearly extremely difficult to justify the deletion of three data points out of a set of six (note, however, the known specific variations in inputs at 20, 40 and 70 cm depth (see above)), in those cases in which deletion of two data points did not reduce the variance to, at most, six times the expected variance, a further datum was deleted. In each case, the set of deletions (out of all possible N deletions) resulting in the lowest variance for that number of deletions, and having a regression line of negative gradient (hence:

80°./oo confidence

only sterol diagenesis considered) was chosen as the "correct" deletion set. Table 4 lists the optimised results for each sterol. Three deletions were found to be necessary in five of the seventeen cases. It is notable that deletions of the 20 and/or 40 and/or 70 cm data account for 88% of the total deletions, consistent with the proposed specific input variations at these depths. The degradation constants (k) (per dm depth) for the sterols listed in Table 4 seem to fall into two groups: one at approximately k = 0.14, the other at k = 0.04. These correspond to degradation rates of 7 x 10-~]/s and 2 x 10-]~/s, that is, approx 0.2 and 0.06% per annum respectively (based upon an estimated sedimentation rate of 1.5 mm/yr (Clementson, 1981)). The former cluster of sterols includes nearly all the sterols characterised by a C5,6 double bond or the presence of a 4-methyl substituent. The latter group contains exclusively stanols and st-22-enols. Figure 4 is a plot of sterol: k with error bars for k at the 80~o confidence interval. The x-axis is sterol number (RRT increases to the right). Weighted means (weighted relative to the inverse of the confidence interval) of the degradation constants of the clusters are plotted as horizontal lines. C22,23 and C24,28 double bonds do not seem to effect the degradation rates of the sterols to an appreciable extent, only the presence of a C5,6 double bond or a 4-methyl group seems to have a significant effect on sterol diagenesis in this environment. There are several possible abiological pathways of

Table 3. Regression lines and variance for subsets o f the 24-methylcholest-5-enol data Datum deletion

Intercept

Gradient

Rego'ession coefficient

Variance

--

5.04 (0.82)

-- 0.120 (0.169)

-- 0.478

0.2135

40

4.74 (0.26)

-- 0.092 (0.052)

-- 0.859

0.0173

40, 20 40, 30 40, 50 40, 60 40, 70

5.05 (0.13) 4.58 (0.18) 4.74 (0.36) 4.75 (0.37) 4.69 (0.38)

-- 0.114 (0.024) -- 0.068 (0.037) --0.092 (0.074) --0.095 (0.078) -- 0.074 (0.089)

-- 0.992 --0.936 --0.857 --0.851 -- 0.744

0.0015 0.0046 0.0259 0.0254 0.0223

Sterol diagenesis

295

03

02

01

O0

Sterol 0

\

\t "

~

--

""'~.

o

70

Fig. 4. Degradation constants of the sterols as determined by regression of the optimally truncated data sets. The horizontal axis is sterol No. scaled from cholesta-5,22dienol = 1 to 4,23,24-trimethylcholest-22-enol = 17, numbered sequentially with respect to RRT (see Table I). The two horizontal lines represent means of the clustered degradation constants (see the text).

I

Depth

Fig. 3. Natural logarithm of abundance (24-methylcholest-5-enol) plotted against depth. Regression lines: - complete data set; . . . . deletion of 40 cm datum; . . . . . . deletion of 20 and 40 cm data.

sterol diagenesis, however, only those involving the 3-hydroxyl substituent are consistent with the observed degradation rates. Dehydration reactions would be accelerated by the presence o f either a C5,6 double bond or a 4-methyl substituent in the sterol. Similarly, other reactions involving the intermediate formation o f a carbonium ion would be relatively accelerated in these sterols. Dehydration is the most probable process (of such reaction types) in the sedimentary environment. The products from dehydration of the st-5-enols would be stera-3,5-dienes, whilst the stanols would yield ster-2-enes and ster-3enes. C o m p o u n d s of this type have been reported in

Sterol RRT 0.898 0.929 1.000 1.031

1.121 1.158 1.280 1.315 1.354 1.389 1.424 1.466 1.509 1.555 1.630 1.679 1.705

N a m i b i a n shelf (Gagosian and Farrington, 1978; Quirk et al., 1979) and other sediments (Dastillung and Albrecht, 1977; Brassel, 1980), however, sterenes and steradienes have not yet been found in sediments from Corner Inlet. In this sediment the stanol/sterol ratio for C27 sterois increases with depth (from 0.274 to 0.323). Other authors (Nishimuza and K o y a m a , 1977; Gaskell and Eglinton, 1975) have found similar trends and have proposed sterol reduction to the corresponding stanol as a likely cause. The previously reported analysis of this sediment (Volkman et al., 1981) did not enable assessment of which process (reduction:direct input) was predominant. The degradation constants determined here indicate that both sterols and stanols are degraded in the anoxic region of the Corner Inlet sediment. The changing stanol/sterol ratio is the result of more rapid degradation o f the sterol. The next step in the analysis of the depth profile

Table 4. Optimised regression lines for the Expected Deleted Observed variance data variance 0.0064 20, 40 0.0383 0.0090 70 0.0110 0.0008 30, 40, 70 0.0001 0.0016 30 0.0037 0.0015 20, 40 0.0067 0.0019 60 0.0034 0.0069 40 0.0037 0.0011 20, 40 0.0015 0.0020 20, 40 0.0006 0.0015 70 0.0039 0.0010 20, 40, 70 0.0000 0.0018 20, 60 0.0065 0.0044 20 0.0143 0.0019 20, 40, 70 0.0031 0.0008 20, 40, 70 0.0031 0.0011 20, 40 0.0031 0.0036 20, 40, 70 0.0000

truncated sterol data Intercept 2.93 (0.68) 2.98 (0.23) 5.70 (0.06) 4.24 (0.13) 4.47 (0.29) 3.94 (0.11) 3.15 (0.12) 5.05 (0.13) 3.85 (0.08) 4.57(0.14) 5.24 (0.01) 4.12 (0.27) 3.28 (0.32) 4.99 (0.38) 5.69 (0.38) 4.90 (0.19) 3.89 (0.01)

Gradient - 0.084 (0.125) -0.124 (0.054) - 0.138 (0.013) - 0.058 (0.026) - 0.143 (0.052) - 0.038 (0.025) - O.135 (0.024) - O.144 (0.024) -0.027 (0.015) -0.128(0.032) - O.147 (0.004) - 0.024 (0.051) -0.041 (0.062) -0.195 (0.079) - O. 121 (0.079) - 0.020 (0.035) - O.I 12 (0.001)

296

F.T. GILLANand R. B. JOHNS

data is to correct the sterol abundances to zero depth (making the assumption that the pooled degradation rates accurately represent the mean sterol degradation rates since deposition). With the data thus corrected to compositions at the time of deposition, all the variance in the data should be due to input source abundance variations. Regression of the corrected sterol abundances against the abundance profiles of selected specific markers, would then yield the convariant source composition. Examination of Fig. la reveals that, even without correction for diagenesis, certain sterols co-vary (note: the major sterols in this set all have a C5,6 double bond and would be subject to the same correction factor). Since many potential input sources are present in this environment, it is unrealistic to attempt to further analyse the data for input source compositions without further sterol analyses. At best three input source compositions could be derived from the present data set.

thanked for GC/MS support data, and the Australian Institute of Marine Science is thanked for the use of their facilities for the processing of the data. REFERENCES

Arima K. M., Nagasawa M. B. and Tamura G. (1969) Microbial transformation of sterols. Part 1. Decomposition of cholesterol by micro-organisms. Agric. Biol. Chem. 33, 1636-1643. Brassel S. C. (1980) The lipids of deep sea sediments: their origin and fate in the Japan Trench. Ph.D. Thesis, University of Bristol. Cardoso J., Brooks P. W., Eglinton G., Goodfellow R., Maxwell J. R. and Philp R. P. (1976) Lipids in recently deposited algal mats at Laguna Mormona, Baja, California. In Environmental Biogeochemistry (Edited by Nriagu J. D.), pp. 149-174. Ann Arbor. Cargile N. L. and McChesney J. D. (1974) Microbial sterol conversions: utilization of selected mutants. AppL Microbiol. 27, 991-994. Clementson L. A. (1981) Polycyclic aromatic hydrocarbons in the marine environment. M.Sc. Thesis, University of Melbourne. Dastillung M. and Albrecht P. (1977) A2-Sterenes as diagenetic intermediates in sediments. Nature 269, 678-679. CONCLUSIONS Edmunds K. L. H., Brassell S. C. and Eglinton G. (1980) The short-term diagenetic fate of 5c~-cholestan-3fl-ol: in Regression analysis of depth profile data has been situ radiolabelled incubations in algal mats. Adv. Org. shown to be capable of providing a reasonable estiGeochem. 1979, Phys. Chem. Earth 12, 427-434. mate of sterol degradation rates in a microbially-poor Eyssen J. H., Parmentier G. G., Compernolle F. C., De Pauw G. and Piessens-Denef M. (1973) Biohydrogenation environment in the presence of marked input variof sterols by Eubacterium ATCC 21,408-Nova Species. ations. The technique was demonstrated under worstEur. J. Biochem. 36, 411-421. case conditions involving only six data points per Gagosian R. B. and Farrington J. W. (1978) Sterenes in sterol. Sterol degradation rates were found to fall into surface sediments from the southwest African shelf and two distinct groups, consisting of st-5-enols plus slope. Geochim. Cosmochim. Acta 42, 1091-1101. Gagosian R. B., Smith S. O., Lee C., Farrington J. W. and 4-methyl sterols, and 4-desmethyl sterols lacking C5,6 Frew N. M. (1980) Steroid transformations in recent double bonds respectively. This division is consistent marine sediments. Adv. Org. Geochem. 1979, Phys. Chem. with abiologically-mediated dehydration as the major Earth 12, 407--419. process of sterol diagenesis in this environment. Both Gaskell S. J. and Eglinton G. (1974) Short-term diagenesis degradation rates were very low (0.2 and 0.06~ per of sterols. Adv. Org. Geochem. 1973, 963-976. annum respectively). It is therefore expected that, in Gaskell S. J. and Eglinton G. (1975) Rapid hydrogenation of sterols in a contemporary lacustrine sediment. Nature microbially rich environments, bacterial processes 254, 209-211. could readily mask this abiological pathway of di- GiUan F. T. (1981) Lipids of aquatic ecosystems. Ph.D. agenesis. However, since dehydration is an acidThesis, University of Melbourne. catalysed process, in very acidic sediments (e.g. at Gillan F. T. and Johns R. B. (1980) Input and early diagenesis of chlorophylls in a temperate intertidal sedipH = 5.5) the rate could be expected to be as much ment. Mar. Chem. 9, 243-253. as 1000 times greater than that observed here (sediGillan F. T., Johns R. B., Verheyen T. V., Nichols P. D., ment pH = 8.4). In such circumstances, the disEsdaile R. J. and Bavor H. J. 0983) Monounsaturated tinction between biological and abiological processes fatty acids as specific bacterial markers in marine sediments. In Adv. Org. Geochem. 1981 (Edited by Bjoroy will be obscure: microbial processes will control the M.), pp. 198-206. sedimentary pH which in turn will influence the rate Huang W.-Y. and Meinschein W. G. (1979) Sterols as of diagenesis. ecological indicators. Geochim. Cosmochim. Acta 43, The major feature of the analysis developed in this 739-745. study is its ability to distinguish abundance variations Johns R. B., Volkman J. K. and Gillan F. T. 0978) Kerogen precursors: chemical and biological alteration of lipids in caused by diagenesis from those resulting from input the sedimentary surface layer. APEA J. 18, 157-160. changes, Once the effects of diagenesis are removed Johns R. B., Gillan F. T. and Volkman J. K. (1980) Early from the data set, it is in a form amenable to much diagenesis of phytyl esters in a contemporary temperate simpler mathematical treatment. The next step in this intertidal sediment. Geochim. Cosmochim. Acta 44, 183-188. study is to apply the diagenesis analysis to a larger data set, and having corrected the data for degra- Lee C., Gagosian R. B. and Farrington J. W. (1977) Sterol diagenesis in recent sediments from Buzzards Bay, Massadation, use statistical analysis to determine covariant chusetts. Geochim. Cosmochim. Acta 41, 985-992. input compositions and abundance variations. Lee C., Farrington J. W. and Gagosian R. B. (1979) Sterol geochemistry of sediments from the western North AtlanAcknowledgements--The authors thank Dr M. Sandstrom tic Ocean and adjacent coastal areas. Geochim. Cosmofor critical review of this manuscript. Dr J. K. ¥olkman is chim. Acta 43, 35-46.

Sterol diagenesis Lee C., Gagosian R. B. and Farrington J. W. (1980) Geochemistry of sterols in sediments from the Black Sea and the Southwest African shelf and slope. Org. Geochem. 2, 103-113. Marsheck W. J., Kraychy S. and Muir R. D. (1972) Microbial degradation of sterols. Appl. Microbiol. 23, 72-77. Nagasawa M., Bae M., Tomura G. and Arima K, (1969) Microbial transformation of sterols. Part II. Cleavage of sterol side chains by microorganisms. Agric. Biol, Chem. 33, 1644-1650. Nishimura M. (1978) Geochemical characteristics of the high reduction zone of sterols in Suwa sediments and the environmental factors controlling the conversion of sterols to stanols. Geochim. Cosmochim. Acta 42, 349-357. Nishimura M. and Koyama T. (1977) The geochemical significance in early sedimentation of geolipids obtained by saponification of lacustrine sediments. Geochim. Cosmochim. Acta 41, 1817-1823. Perry G. J., Volkman J. K., Johns R. B. and Bavor H. J. (1979) Fatty acids of bacterial origin in contemporary marine sediments. Geochim. Cosmochim. Acta 43, 1715-1725.

297

Quirk M. M., Wardroper A. M. K., Brooks P. W., Wheatley R. E. and Maxwell J. R. (1979) Transformation of acyclic and cyclic isoprenoids in recent sedimentary environments. Actes Colloq. C.N.R.S. 293, 225-232. Taylor C. D., Smith S. O. and Gagosian R. B. (1981) Use of microbial enrichments for the study of the anaerobic degradation of cholesterol. Geochim. Cosmochim. Acta 45, 2161-2168. Volkman J. K. (1977) Studies of biological diagenesis in recent marine sediments. Ph.D. Thesis, University of Melbourne. Volkman J. K., Johns R. B., Gillan F. T., Perry G. J. and Bavor H. J. (1980) Microbial lipids of an intertidal sediment. I. Fatty acids and hydrocarbons. Geochim. Cosmochim. Acta 44, 1133-1143. Volkman J. K., Gillan F. T., Johns R. B. and Eglinton G. (1981) Sources of neutral lipids in a temperate intertidal sediment. Geochim. Cosmochim. Acta 45, 1817-1828. Wardroper A. M. K., Maxwell J. R. and Morris R. J. (1978) Sterols of a diatomaceous ooze form Walvis Bay. Steroids 32, 203-221.