The Barberton Greenstone Belt (BGB) of South Africa contains some of the world s

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Louisa Manning
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1 GSA Data Repository Items Geological Setting The Barberton Greenstone Belt (BGB) of South Africa contains some of the world s oldest and best-preserved pillow lavas. This study investigates the upper Hooggenoeg Formation a ~2700 m thick unit of predominantly basaltic lavas that on the eastern limb of the Onverwacht anticline is unconformably overlain by the ~200 m thick Noisy formation of clastic sedimentary rocks (see Grosch et al., 2011 and Fig. DR1). A maximum age of eruption for the Hoogenoegg eruptive interval is given by detrital zircons from the Middle Marker Chert at the base of the Formation dated at ± Ga (Armstrong et al., 1990). A minimum age of eruption is ± 10 Ga provided by detrital zircon grains recording the maximum depositional age of the overlying Noisy formation (Grosch et al., 2011). The Hooggenoeg surface sample investigated here was collected from a non-vesicular and variolitic pillow lava outcrop on the banks of the Komati River (Fig. DR1). This is the original outcrop that yielded the biotextures of Furnes et al. (2004) and sample 29-BGB-03 re-investigated here was cut from the same hand sample. The pillow lavas are little deformed with well-developed chilled margins of formerly glassy material that grade inwards into a variolitic zone. This horizon was also the target of a scientific drill hole KD2b of the Barberton Scientific Drilling Project (BSDP) described in Grosch et al. (2009) and Fig. DR1. This site is c metres into the pillow lava pile beneath the paleo-seafloor as recorded here by a thin chert horizon at the top of the Hooggenoeg Formation at the unconformity (Fig. 3, Grosch et al. 2009) the exact depth beneath the paleoseafloor cannot be precisely determined due to a diabase intrusion that likely expanded the sequence (Fig. 1, Grosch et al., 2009).

These drill core samples enable us to test the geochemical signatures associated with the candidate biotextures in samples unaffected by surface weathering. Fig. DR1.

studied here come from drill hole KD2b in the upper Hooggenoeg Formation; (d) simplified drill core log, total length 180 m, showing lithologies and depth of the three samples analyzed.

25 m depth, comprises two pillow rims with interpillow breccia, with large euhedral sulfide grains that cross-cut the putative biotextures near a quartz-carbonate vein (Fig. DR2).

2 These drill core samples enable us to test the geochemical signatures associated with the candidate biotextures in samples unaffected by surface weathering. Fig. DR1. (A) Map of South-Africa showing location of the Barberton Greenstone Belt (BGB); (B) sketch map of the BGB; (c) geological map of the BGB indicating the location of the BSDP drill sites, samples studied here come from drill hole KD2b in the upper Hooggenoeg Formation; (d) simplified drill core log, total length 180 m, showing lithologies and depth of the three samples analyzed. Sample descriptions and petrography Three samples from the BSDP drill core were investigated: B137, B175 and B177 (Fig. DR1). Sample B137 from m depth, comprises two pillow rims with interpillow breccia, with large euhedral sulfide grains that cross-cut the putative biotextures near a quartz-carbonate vein (Fig. DR2). Sample B175 from m depth is an inter-pillow hyaloclastite with small sulfide grains occurring in the putative biotextures (Fig. DR2). Sample B177 from m depth is a pillow rim with small sulfides associated with the candidate biotextures (Fig. DR2). All samples contain clusters of segmented titanite microtextures in a chlorite ± quartz ± epidote ±

calcite matrix that are morphologically comparable to the type microtextures of Furnes et al. (2004).

Fig. DR2); and 2), relatively large euhedral pyrites c.10 60 µm across that cross-cut the microtextures near a quartzcarbonate vein (B137; Fig. DR2). In sample B175 pyrite predominates with subordinate chalcopyrite, in B177 chalcopyrite dominates with fewer pyrite grains.

Petrographic images showing titanite microtextures and relationship to sulfides in the BSDP samples: (A) cluster of titanite microtextures that are segmented (arrowed); (B) two microtexture clusters

3 calcite matrix that are morphologically comparable to the type microtextures of Furnes et al. (2004). Two types of sulfide were identified: 1), small euhedral sulphides 1 15 µm across, intimately associated with the microtextures occurring in the root zones and individual microtubes (B175 and B177; Fig. DR2); and 2), relatively large euhedral pyrites c µm across that cross-cut the microtextures near a quartzcarbonate vein (B137; Fig. DR2). In sample B175 pyrite predominates with subordinate chalcopyrite, in B177 chalcopyrite dominates with fewer pyrite grains. No distinctively hydrothermal sulphide phases such as pentlandite (Fe,Ni) 9 S 8 or millerite (NiS) were identified in these samples. Fig. DR2. Petrographic images showing titanite microtextures and relationship to sulfides in the BSDP samples: (A) cluster of titanite microtextures that are segmented (arrowed); (B) two microtexture clusters that contain sulfide grains (yellow), size and location traced from reflected light images; (C) small sulfide inclusions encapsulated in titanite root zone of microtexture; (D) large euhedral sulfides cross-cutting microtextures near a quartz-carbonate vein; (E) coarse sulfides that cross cut titanite microtextures in a chlorite, epidote matrix.

4 NanoSIMS isotope analysis Sulfur isotope ratios ( 34 S/ 32 S) were determined using a CAMECA NanoSIMS 50 at The University of Western Australia. The samples were 40 m thin-sections, cut into c. 8x8 mm squares mounted in epoxy alongside the CMCA-S1 sulfur isotope standard, repolished to remove any surface topography, and mounted in a 25 mm diameter NanoSIMS sample holder. This was mapped in reflected light for navigation in the NanoSIMS and a 5 nm gold coat applied for conductivity at high voltage. NanoSIMS set up and data acquisition Measurements were obtained with a 100 nm Cs + primary ion beam, with net impact energy of ~16 kev, pre-sputtered with the primary ion beam at >2 x ions/cm 2 to reach a steady-state of ion emission, and therefore a steady sulfur isotope ratio. Isotope analyses were conducted using a c. 12 pa beam current with the NanoSIMS in isotope analysis mode. The more abundant 32 S isotope was detected using a Faraday Cup and the less abundant 34 S isotope using an electron multiplier on trolley 1. NanoSIMS parameters were configured to give a workable amount of signal for the 34 S isotope. (For example, ES=2, AS=0, Ens=10%, D1=2 gave c. 75,000 counts per second for 34 S.) Charge compensation was not necessary. Isotope data were acquired by rastering the primary beam across areas measuring 5x5 m with 25% blanking, and 3x3 m for smaller grains, collecting 100 measurement cycles (10 blocks, 10 measurements per block). Secondary ion beam and EOS centering were automatically conducted at the beginning and end of each analysis. Delta value calculation Yield, dead-time and background corrected 34 S/ 32 S raw ratios (R raw ) were drift corrected using a linear regression:

5 R drift R raw mx (1) where m is the slope of the regression and x is the analysis number for the session, scaled to ensure that the intercept (c) crosses the x-axis at x = 0. The drift corrected ratios were expressed as raw delta values (V-CDT) using: R 34 S drift 1000 drift (2) Instrumental mass fractionation ( was then calculated as the -2 drift (see below) weighted average of all estimates i of the 34 S drift values for the bracketing standards: i 1 34 S drift S std 1000 (3) where 34 S std is the 34 S V-CDT of the CMCA-S1 pyrite standard (+1.43 ± 0.06 ). Finally, single sample analyses were corrected to V-CDT using: 34 S sample 1 34 S drift *1000 (4) Error propagation The propagated error includes the uncertainty associated with drift correction: R drift 2 2 i reg (5) where i is the internal precision (standard error of the mean of the 10 analysis blocks of a single analysis i) and reg is the standard error of the estimate of the regression: reg x 2 m 2 c 2 2x m c (6) where m and c are the standard errors associated with the estimation of m and c respectively, and is the correlation coefficient between analysis number and R raw. The uncertainty of 34 S drift is then given by: 1000 drift ( (7) Rdrift )2 The uncertainty of individual i estimates is given by:

6 ai S drift S std drift 1000 std S std 2 2 (8) where std is the uncertainty of the reference value for the CMCA-S1 standard (0.06 ). The uncertainty associated with ( ) is the weighted mean standard error of the individual estimates i obtained from the drift corrected CMCA-S1 standards. Finally, the propagated uncertainty for the 34 S value of each sample spot is given by: sam drift 2 34 S sam 2 2 (9) Individual uncertainty measurements were multiplied by the ratio of the external SD of the drift corrected standards divided by the average internal precision of the standards. Correction for quasi simultaneous arrivals is not required when a Faraday Cup rather than an electron multiplier is used to detect the more abundant 32 S isotope. The instrumental mass fractionation was calculated separately for each of the seven individual analytical sessions. The uncertainty on bracketing 34 S standard analyses was: 2.1 (1) for session 1 (n = 9); 1.3 for session 2 (n = 7); 2.3 for session 3 (n = 10); 3.5 for session 4 (n = 7); 3.0 for session 5 (n = 5); 1.2 for session 6 (n = 6); and 1.0 for session 7 (n = 7). When processing the data, samples with low counts (set at ) were excluded, because these likely included analyses that ablated either inclusions in the sulfides or surrounding matrix. The pyrite standard was also used as the standard for the chalcopyrite grains as the bias imparted due to the difference in matrices has been shown to be small (~1 ) in comparison to the

$differences in the isotopic fractionation between the different sample grains (cf. Wacey et al., 2010; Riciputi et al.$ NanoSIMS Element Mapping Each region of interest was pre-sputtered using a 150 pa beam current to an ion dose of >2 x 10 17

NanoSIMS Element Mapping Each region of interest was pre-sputtered using a 150 pa beam current to an ion dose of >2 x 10 17

Negative secondary ions ( 12 C -, 16 O -, 12 C 14 N -, 28 Si -, 32 S - ) were then sputtered from the sample surface using

Positive secondary ions ( 27 Al +, 48 Ti +, and 56 Fe + ) were sputtered from the same areas using the O - primary beam

7 differences in the isotopic fractionation between the different sample grains (cf. Wacey et al., 2010; Riciputi et al., 1998). NanoSIMS Element Mapping Each region of interest was pre-sputtered using a 150 pa beam current to an ion dose of >2 x ions/cm 2. Negative secondary ions ( 12 C -, 16 O -, 12 C 14 N -, 28 Si -, 32 S - ) were then sputtered from the sample surface using a beam current of c. 2.5 pa. The Electron gun was used for charge compensation. Positive secondary ions ( 27 Al +, 48 Ti +, and 56 Fe + ) were sputtered from the same areas using the O - primary beam with a beam current of c. 1 pa. Information regarding the image size, dwell times and image resolution are the same as those reported in McLoughlin et al. (2011). Ion Images were processed using ImageJ, and each ion species was assigned a colour. Fig. DR3. NanoSIMS elemental maps through longitudinal (A-H) and transverse (I- L) sections of candidate biotextures (A-H) element maps of sample 29-BGB-03 note

segmentation of the microtextures, chlorite inclusions in the titanite; and absence of 12 C - and 26 CN - linings; (I-L) transverse section through a

Variations in ion intensity are shown by the calibration bars, where brighter colours indicate higher intensity. Fig. DR4.

Carbon ( 12 C - ) and Nitrogen ( 26 CN - ) are not enriched along the margins of the microtexture, rather they occur in small pores (arrowed) seen in

8 segmentation of the microtextures, chlorite inclusions in the titanite; and absence of 12 C - and 26 CN - linings; (I-L) transverse section through a titanite microtexture (starred) no 12 C - or 26 CN - linings were found, sample B175. Variations in ion intensity are shown by the calibration bars, where brighter colours indicate higher intensity. Fig. DR4. Cluster of titanite microtextures. Boxed area was mapped by NanoSIMS and contains a sulfide grain (ringed). Carbon ( 12 C - ) and Nitrogen ( 26 CN - ) are not enriched along the margins of the microtexture, rather they occur in small pores (arrowed) seen in the 16 O - and 28 Si - maps. SEM-EDS Investigations A JEOL 6400 at the University of Bergen, was used to check the composition of the sulfides (pyrite versus chalcopyrite), and the location of NanoSIMS pits to identify grain boundaries and inclusions that may have affected the isotopic results.

9 Additional references for repository items Armstrong, R.A., Compston, W., de Wit, M.J., Williams, I.S., 1990, The stratigraphy of the Ga Barberton Greenstone Belt revisited: a single zircon ion microprobe study: Earth Planetary Science Letters, 101, McLoughlin, N., Wacey, D., Kruber, C., Kilburn, M.R., Thorseth, I.H., Pedersen, R.B., 2011, A combined TEM and NanoSIMS study of Endolithic microfossils in altered seafloor basalt: Chemical Geology, Riciputi, L.R., Paterson, B.A., Ripperdan, R.L., 1998, Measurement of light stable isotope ratios by SIMS: Matrix effects for oxygen, carbon, and sulfur isotopes in minerals: International Journal of Mass Spectrometry, 178, Table DR1. Drift corrected NanoSIMS data table. Day 1 (cps) x10 6 δ 34 S V-CDT ( ) 2 sigma Mineral phase CMCA_S1_1.1 10,8-0,7 1,17 B137#5 9,5 10,9 1,43 pyrite CMCA_S1_1.2 10,9 2,2 1,22 B137#6 10,0 15,6 1,62 pyrite CMCA_S1_1.3 10,8 1,5 1,06 B137#7 9,9 8,0 1,84 pyrite CMCA_S1_1.4 10,7 4,7 1,08 B137#9 9,6 8,3 2,06 pyrite CMCA_S1_1.5 10,7-0,7 1,14 B137#10 10,0 17,9 2,29 pyrite CMCA_S1_1.6 9,0-2,3 2,78 CMCA_S1_1.7 9,0 1,8 3,02 CMCA_S1_1.8 9,2 2,7 3,27 CMCA_S1_1.9 9,1 1,9 3,54 Day 2 CMCA_S1_2.1 9,0-0,3 1,46 B137#12 9,4 13,7 1,29 pyrite CMCA_S1_2.2 9,0 2,8 1,40 B137#13 9,4 8,9 1,28 pyrite CMCA_S1_2.3 9,2 2,6 1,35 B137#14 9,3 13,5 1,30 pyrite CMCA_S1_2.4 9,1 0,7 1,38 B137#15 9,3 7,2 1,33 pyrite CMCA_S1_2.5 7,8-0,1 1,97 B137#16 9,2 6,7 1,37 pyrite CMCA_S1_2.6 8,3 1,8 2,07 B137#17 8,6 8,3 1,44 pyrite CMCA_S1_2.7 8,3 2,1 2,19 B137#18 8,7 7,3 1,50 pyrite B137#19 9,0 7,7 1,57 pyrite B137#21 8,5 13,2 1,76 pyrite

10 Day 3 CMCA_S1_3.1 7,7 2,1 2,78 B175#2 4,0-14,3 2,33 pyrite CMCA_S1_3.2 7,7 2,6 2,65 B175#3 3,7-16,8 2,27 pyrite CMCA_S1_3.3 7,6 0,4 2,53 B175#4 4,0-7,2 2,20 chalcopyrite CMCA_S1_3.4 7,6 2,9 2,42 B175#20 2,9-22,4 2,23 pyrite CMCA_S1_3.5 7,4 4,1 2,32 B175#7 3,4-18,4 2,24 pyrite CMCA_S1_3.6 4,6-1,2 2,07 B175#8 3,5-22,0 2,29 pyrite CMCA_S1_3.7 5,3 3,0 2,04 B175#9 3,9-19,8 2,34 pyrite CMCA_S1_3.8 5,6-1,7 2,04 B175#10 3,6-21,5 2,44 pyrite CMCA_S1_3.9 7,0 0,0 3,06 B175#12 3,6-27,3 2,65 pyrite CMCA_S1_3.10 6,9 5,4 3,20 B175#18 4,4-21,3 2,72 chalcopyrite B175#13a 3,1-18,7 2,92 pyrite B175#19 4,1-10,8 2,99 chalcopyrite Day 4 CMCA_S1_4.1 10,9 2,2 4,61 B177#1 5,9-25,1 3,70 chalcopyrite CMCA_S1_4.2 11,1 2,7 4,31 B177#3 6,5-39,8 3,57 pyrite CMCA_S1_4.3 11,1 3,7 4,05 B177#4 5,2-39,3 3,52 pyrite CMCA_S1_4.4 10,9-1,1 3,83 B177#15 4,0-34,9 3,69 chalcopyrite CMCA_S1_4.5 8,0-4,1 4,50 B177#12a 3,1-26,4 4,07 chalcopyrite CMCA_S1_4.6 8,8 2,1 4,80 B177#13 4,0-32,6 4,28 chalcopyrite Day 5 CMCA_S1_5.1 11,1-2,8 4,55 B137#26 10,1 11,0 3,93 pyrite CMCA_S1_5.2 11,2 2,9 4,31 B137#23 9,7 17,6 4,08 pyrite CMCA_S1_5.3 11,1 4,1 4,11 B137#24 9,6 11,9 4,28 pyrite CMCA_S1_5.4 9,9-1,1 5,34 B137#25 8,6 15,9 4,51 pyrite CMCA_S1_5.5 9,6 2,9 5,65 B137#27 9,4 15,2 4,76 pyrite B137#28 9,9 9,9 5,03 pyrite

11 Day 6 CMCA_S1_6.1 10,3 0,6 0,85 B175#21 5,3-5,8 1,08 pyrite CMCA_S1_6.2 10,3 2,9 0,84 B175#22 5,9-11,6 1,09 pyrite CMCA_S1_6.3 10,2 0,8 0,85 B175#23 5,6-5,1 1,18 pyrite CMCA_S1_6.4 9,2 0,5 2,09 B175#14 5,0-11,2 1,31 chalcopyrite CMCA_S1_6.5 8,7 0,6 2,24 B175#15 4,5-14,1 1,44 pyrite CMCA_S1_6.6 8,8 2,8 2,39 B175#16 6,2-10,6 1,47 pyrite B175#17 5,3-12,0 1,62 pyrite B175#24 3,8-12,2 1,84 chalcopyrite B175#25 4,8-3,2 1,91 chalcopyrite Day 7 (cps) x10 6 δ 34 S V-CDT ( ) 2 sigma Sample CMCA_S1_7.1 8,9-0,5 0,88 B177#18 6,1-12,8 1,01 chalcopyrite CMCA_S1_7.2 8,7 1,7 0,86 B177#05 3,8-26,9 1,22 chalcopyrite CMCA_S1_7.3 8,9 2,4 0,85 B177#07 5,4-23,5 1,22 pyrite CMCA_S1_7.4 9,1 2,2 0,87 B177#14 3,8-21,8 1,58 chalcopyrite CMCA_S1_7.5 9,3 0,8 1,69 B177#19 7,6-8,3 1,50 chalcopyrite CMCA_S1_7.6 9,1 1,7 1,81 CMCA_S1_7.7 9,0 1,2 1,92

GSA Data Repository Item Wacey et al.

GSA Data Repository Item Wacey et al. GSA Data Repository Item 2015025 Wacey et al. Figure DR1. Occurrence of putative framboidal pyrite from the late Ediacaran of the Catalina Dome, Bonavista Peninsula, Newfoundland (sample WM1, c. 560 Ma