Biogeochemistry of manganese in Lake Matano, Indonesia

C. Jones, S. A. Crowe, A. Sturm, K. L. Leslie, L. C. W. MacLean, S. Katsev, C. Henny, D. A. Fowle, and D. E. Canfield Nordic Center for Earth Evolution, Institute of Biology, 55 Campusvej, Univ. of Southern Denmark, 5230 Odense, Denmark Dept. of Geology, Univ. of Kansas, Lawrence, KS 66047, USA Canadian Light Source Inc., Univ. of Saskatchewan, Saskatoon, SK, S7N 0X4 Canada Large Lakes Observatory and Dept. of Physics, Univ. of Minnesota, Duluth, MN 55812, USA Research Center for Limnology, Indonesian Institute of Sciences (LIPI), Cibinong Bogor, Indonesia

concentration develops from reduction of these particles as they settle. Contrary to the generally accepted cascade of terminal electron acceptors used in stratified environments (Froelich et al., 1979), Mn reduction can occur in oxic environments (Bratina et al., 1998;Canfield et al., 2005), so oxidation and reduction can occur simultaneously in the same water mass. Dissolved Mn concentrations typically decrease with depth 10 in anoxic water (Davison, 1993), potentially through precipitation of a Mn(II)-bearing mineral phase.
Perhaps the best-studied, stratified water column with respect to Mn geochemistry is the Black Sea, where N and S may play key roles in Mn cycling. For example, hydrogen sulfide, the dominant reducing species in the euxinic water column, is possibly oxidized 15 by complexed Mn(III) (Yakushev et al., 2009), first identified in the environment in the Black Sea and Chesapeake Bay (Trouwborst et al., 2006). This Mn(III) may be what is sustaining the zone where oxygen and sulfide are both undetectable, which extends for 5-10 m below the depth of oxygen penetration (Yakushev et al., 2009). One dimensional modeling implicated nitrate, as opposed to O 2 , as an alternative oxidant for Mn 20 in this zone (Murray et al., 1995), but this has yet to be corroborated with field studies (Clement et al., 2009;Schippers et al., 2005).
In Lake Matano, a 590 m deep meromictic lake located on Sulawesi Island, Indonesia, Mn(II) is mixed into the oxic zone where it is oxidized. The oxides sink below the redox boundary where there is very little sulfide to act as reductant, but there is Introduction particles, and reaction transport modeling to quantify the oxidation and reduction kinetics of Mn. We then place the results of this work into geobiological context and offer an alternative interpretation for Precambrian sedimentary Mn deposits.

Location
The Malili Lake system is situated on the southeastern peninsula of Sulawesi Island, 5 Indonesia (Crowe et al., 2008b). The Lake Matano basin (164 km 2 ) is formed by a horst and graben depression, and at nearly 600 m deep, it is the eighth deepest lake in the world. Between one and four million years in age, it is also one of only a handful of ancient lakes on the planet. It has a catchment made predominantly of ophiolitic rock and weathered lateritic soils (Golightly, 1981), which contribute to the high (40-60%, Crowe et al., 2004) iron (hydr)oxide concentrations in the lake sediments. The lake is persistently stratified by weak thermal and salinity gradients (Crowe et al., 2008b) that have likely been maintained for centuries (Katsev et al., 2010). Lake Matano has been suggested as the best modern analogue for the Precambrian, ferruginous oceans (Crowe et al., 2008a).

Sampling
Sampling was conducted at a central, deep-water station (2 • 28 00 S and 121 • 17 00 E) in January-March 2009. Water samples were collected by one of two methods. In the first, we used 5 L Go-Flow (Niskin) bottles attached in series to a stain-20 less steel cable placed at depth with a precision and accuracy of ±1 m using a commercial sonar device (Furuno FCV585) to monitor the position of the bottles within the water column. In the second method, we collected water with a Johnson WPS 2.9 diaphragm pump through 150 m of 1 cm internal diameter plastic tubing. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | pump inlet was set using a conductivity, temperature, depth probe (CTD, Sea and Sun Technology) mounted just above the pump inlet and interfaced to a computer at the surface using a hydrowire. This set-up allowed real-time positioning of the pump inlet with a vertical accuracy of 0.1 m and a between-cast precision of 0.25 m. Prior to sampling, the tubing was flushed with at least three times its internal volume (12 L) using 5 the diaphragm pump. Following the flushing period, water was pumped for sampling using a peristaltic pump (Masterflex L/S computerized drive, model number 7523-60) through a combination of Tygon ® and Marprene ® tubing.
Samples for dissolved manganese and major ion concentrations were taken directly from the Niskin bottle spout or pump stream with a syringe and filtered through a 0.2 µm 10 pore, 25 mm diameter cellulose acetate filter into acid washed HDPE 125 mL bottles that were rinsed three times with sample water. Samples were acidified to 2% with trace-metal grade HNO 3 . Samples for Fe(II) were taken directly from the Niskin bottle spout or from the pump stream with a pipette and placed immediately in ferrozine reagent to avoid oxidation. These samples were unfiltered as Fe particles could con-15 tribute at most 200 nM to the Fe(II) determination, and filtration would likely have oxidized some of the Fe(II) (Troup et al., 1974). All Fe and Mn samples were refrigerated and maintained at 4 • C until analysis within 8 h. Surface water particles (collected from 20 and 90 m depth) were sampled by pumping water and filtering 10-20 L through a 0.2 µm pore, 142 mm diameter, polycarbonate filter housed on an in-line (allowing no 20 contact with atmosphere) filtration device. Filters for bulk X-ray absorption near edge structure (XANES) analysis were sealed in Kapton ® tape prior to storage. Kapton ® is a strong, low molecular weight polyimide that is nearly transparent to hard X-rays (> 4000 eV) and resists damage from radiation (Alkire and Rotella, 1997), so it makes an excellent protective sheath for samples to be analyzed by hard X-ray techniques. 25 The filters were stored frozen at −20 • C in 50 mL plastic tubes until analysis. Chemocline particle samples were taken in a similar fashion, except they were filtered and handled in a glove bag on board a local fishing boat under an atmosphere of high purity nitrogen. Like surface water particle filters, chemocline particle filters for bulk XANES were sealed in Kapton ® tape, which also served as an additional oxygen barrier before storage. All chemocline particle filters were stored in nitrogen-filled glass vials at −20 • C until analysis.

Sample analyses
Dissolved oxygen, temperature, conductivity, and turbidity were measured in situ using 5 a multiparameter probe (Sea and Sun Technology). Mn, Fe, and major ion concentrations were determined on a Perkin Elmer Optima 5300DV ICP-OES. Fe(II) was analyzed by the ferrozine method (Viollier et al., 2000;Stookey, 1970). Chemocline carbon fixation rates were measured in situ at 122,124,126,128,130, and 135 m using the H 13 CO − 3 technique (Slawyk et al., 1977) and integrated to attain an area specific rate.

10
Methane and ammonium data are reproduced from Crowe et al. (2011).

Mn oxidation rate incubations
Samples for determining manganese oxidation rates were acquired by pumping water from four depths (118, 119, 120, and 121 m) into triplicate, acid cleaned, 60 mL glass vials, first rinsed 3 times with sample water, then crimp sealed with rubber septa. Within 15 4 h, these samples were amended with a MnCl 2 solution to a total Mn concentration of approximately 40 µmol L −1 . Controls from each depth were additionally amended with 100 µL of 37% formaldehyde. Incubations were kept at 28 • C in the dark and subsampled by injecting an equal volume of sterile-filtered air as the sample was removed (4 cm 3 ). A time-zero sample was taken immediately from each vial. Mn(II) concentra-20 tions were analyzed in duplicate spectrophotometrically by the formaldoxime method (Brewer and Spencer, 1971).

Water column particle extractions
Particulate manganese concentrations were determined from particles collected on 0.2 µm pore, 142 mm diameter, polycarbonate filters. A known fraction of each filter Introduction  et al. (2004). This involved extracting with 0.1 mol L −1 hydroxylamine HCl for 2 h to obtain Mn oxides, although this extraction also incompletely dissolves the Al-Li-Mn oxide, lithiophorite and could also attack Fe oxides (Neaman et al., 2004). A parallel extraction used 30% H 2 O 2 with 0.5 N HNO 3 for 0.5 h. As the peroxide first oxidizes 5 the Mn(IV) to Mn(VII) in the Mn oxides, this extraction should not attack Fe oxides or Mn contained within Fe oxide structure. It will attack organic matter, however (Neaman et al., 2004). In addition to these two parallel extractions, a sequential extraction of 0.5 N HCl for 1 h was followed by digestion in 6 N HCl for 24 h at 100 • C to obtain reactive Fe and total extractible Fe and Mn, respectively (Lovley and Phillips, 1986;10 Poulton and Canfield, 2005). Filter extracts were analyzed on a Perkin Elmer Optima 5300DV ICP-OES for Fe, Mn, and other major ions.

Transmission electron microscopy (TEM)
Particles for TEM analyses were collected on 142 mm diameter polycarbonate filters as described above. Particles were washed from the filter surface with anaerobic deion-15 ized water, pipetted onto TEM grids, and dried. All manipulations were done in an anaerobic chamber. TEM micrographs were collected on a Tecnai 20 D491 X-Twin transmission electron microscope. The TEM operates at 200 kV using a field emission gun in STEM nP LM zoom diffraction mode as an electron source and is equipped with an energy dispersive X-ray spectrometer (EDS) operated at 4.2 kV extraction voltage.

Synchrotron-based X-ray fluorescence and spectroscopy
Particles for synchrotron X-ray spectroscopic analyses were collected and preserved on 142 mm diameter polycarbonate filters as described above. Micro X-ray Fluorescence (µXRF) maps and (micro) X-ray absorption near edge structure (XANES and µXANES) spectra were collected on beamline 20-BM-B (PNC-CAT) at the Advanced Introduction plane. The incident X-ray beam was focused using a pair of Kirkpatrick-Baez mirrors, and a monochromatic incident beam was achieved using a Si(111) double crystal monochromator. Filters used for µXANES and µXRF analyses were subsampled, and a single piece was placed particle-side down on kapton film then sealed in kapton tape under a nitrogen atmosphere prior to spectra collection. 5 µXRF elemental maps were collected with monochromatic incident X-rays (Si(111)) tuned to 14 000 eV (λ = 0.5580Å) and focused to a spot size of 5 µm by 5 µm using a pair of Kirkpatrick-Baez mirrors. The sample was rastered through the X-ray beam in 5 µm steps with a count time of 1 s per step. The emitted fluorescence X-rays of 9 elements (Ti K α, V K α, Cr K α, Mn K α, Fe K α, Co K α, Ni K α, Cu K α, and Zn K α) 10 were collected simultaneously with a 13-element Germanium detector (Canberra). In µXRF mapping, Fe and Mn raw intensity counts were calibrated to moles by integrating the raw intensity counts, less the average blank, in a given area and dividing by the concentration of Fe or Mn per given filter area as determined by total extractions. µXANES spectra were collected in fluorescence mode on selected areas of the µXRF 15 map where Mn counts were high. The Si(111) monochromator was calibrated to the Mn K α edge at 6539 eV using the first peak of the first derivative XANES spectrum for the Mn metallic foil. The energy scale for each sample was referenced to the edge in the Mn foil spectrum collected in transmission mode simultaneously with sample data. The X-ray absorption structure (XAS) data were normalized and processed using Introduction  Figure 2 shows temperature and density profiles from 2004 to 2010. These profiles depict seasonal, surface water differences but highlight the stability of the ∼ 100 m deep, persistent pycnocline. In 2009, however, the depth of the oxic mixed layer was ∼ 10 m deeper than previous years for reasons that remain unknown. In 2010, the depth of the oxic mixed layer shallowed to near its pre-2009 position. When discussing concentra-5 tion profiles, we will refer to the depths and concentrations measured in 2009, unless otherwise stated, as incubations were done this year. The chemical structure of the Lake Matano water column has been previously described (Crowe et al., 2008b), and in general, our observations are consistent with this earlier work (Fig. 3). The dissolved Mn(II) concentration profile develops as a balance 10 between sources and sinks, where Mn(II) oxidation is a sink, Mn(III/IV) reduction is a source, and precipitation of a Mn-bearing mineral is a sink. As it is currently understood, Mn oxidation requires molecular oxygen despite previous suggestions that NO − 3 could act as an oxidant (Luther et al., 1997;Murray et al., 1995;Schippers et al., 2005;Clement et al., 2009). In Lake Matano, oxygen concentration gradients reflect 15 the physical structure of the water column and oxygen demands. In the surface water, oxygen concentrations are near atmospheric saturation and decline due to respiration with increasing depth as the persistent pycnocline is approached (Fig. 3). Oxygen becomes undetectable with our methods at 120 m (±3 m between casts, conservatively, due to seiching/internal waves, Katsev et al., 2010). The steep oxygen, Mn, and Fe 20 gradients define a chemocline, and the point of undetectable oxygen defines a redox boundary that separates aerobic from anaerobic processes. We will reference other chemical species and processes to these features. As conceptualized in Fig. 1 and depicted for the specific case of Lake Matano in Fig. 3, dissolved manganese concentrations are sub-micromolar in the surface waters and high (∼ 6 µmol L −1 ) in the bottom

Mn oxidation and reduction: evidence from water column particles
Particles collected from the upper 130 m of the water column were analyzed by selective and total extractions (Table 2), XAS, and µXRF (Figs. 4,5,and 6). A TEM micrograph of particles from 118.6 m is presented in Fig. 7. The TEM image shows aggregates of dark, fibrous minerals, similar in morphology to Mn oxides studied pre-5 viously (Cheney et al., 2008). Also in the figure, EDS elemental spectra confirms that these dark fibrous particles are predominately Mn and O. In general, particulate Mn concentrations as determined by our extraction methods reached a maximum at 118.6 m. Extraction of particles in 6 N HCl (Table 2) demonstrates a sharp particulate Mn concentration peak with very little Mn in particles below 10 118.6 m or in the surface water. Fe particles show a peak above background levels at 118.6 m as well, but higher concentrations are sustained to deeper depths suggesting the persistence of authigenic Fe phases to depth in the lake. To summarize, while both Mn and Fe particles peak at 118.6 m, authigenic Fe particles persist deeper than Mn particles. There could be several reasons for this observation: sinking Mn oxides produced during Mn oxidation may be generating the Fe oxides by oxidizing Fe(II) diffusing up from below. This would produce a profile with a Mn oxide peak just above an Fe oxide peak, which may not be discernable at the resolution of our sampling. In addition, Mn oxides are more easily reduced than Fe oxides (Krauskopf, 1957;Crowe et al., 2007), so Fe particles may be sustained deeper than Mn particles due to their 20 relatively lower reactivity.
Water column particles were extracted with two different methods; one uses acidified H 2 O 2 and one uses hydroxylamine HCl (Neaman, 2004). These extractions allowed the discrimination of pure Mn oxides (e.g. birnessite, pyrolusite, ∂MnO 2 ) from Mn contained in Fe oxides, as well as Al-containing Mn minerals like lithiophorite, which, together with Mn oxides, are common in the lateritic catchment soils of Lake Matano (Golightly, 1981). For our samples, both of the extractions dissolved approximately the same amount of Mn ( Table 2), suggesting that lithiophorite, despite being a component of the catchment soils, is not common in the water column, and at the depths we BGD 8,2011 Biogeochemistry of manganese in Lake Matano, Indonesia C. Jones et al. sampled, most of the Mn was not incorporated into Fe oxides. These results verify that Mn oxides are the dominant Mn-bearing phase in the chemocline. At 118.6 m, a large fraction of the total extractable Mn is only extracted by subboiling 6 N HCl. This suggests the presence of an authigenic form of Mn that is not reactive to the selective extractions described above. These Mn phases, however, 5 are subsequently dissolved by reduction as they sink through the water column (see below). Additionally, the 0.5 M HCl extraction failed to extract most of the particulate Fe in the surface and deep waters. This suggests that a large fraction of the Fe particles raining through the water column is relatively unreactive.
The average oxidation state of the particles at four depths (20, 118.6, 123.5, and 10 129 m) was determined by bulk Mn XANES spectra, and the results are shown in Fig. 4.
In the surface water sample where particulate Mn is present at concentrations much less than at 118.6 m, the oxidation state is predominantly Mn(II). Surface waters are extremely clear, with secchi depths greater than 23 m, and particles at these depths are predominantly cellular material. The observed Mn(II) may, therefore, be incorpo-15 rated into bacterial enzymes and oxygen-evolving complexes of oxygenic phototrophs, although Mn(II) incorporated into silicates cannot be ruled out, as the 6 N HCl extraction would not attack silicate minerals. In contrast, the oxidation state of Mn in particles at 118.6 m is predominantly Mn(IV).
To identify the mineralogy of these Mn(IV) particles, the bulk XAS spectrum from 20 118.6 m has been plotted along with the spectrum of a birnessite standard (Fig. 5), and these two spectra are nearly identical. The dominant Mn mineralogy at 118.6 m appears, therefore, to be birnessite, consistent with previous studies of biological Mn oxidation products in lake environments (Friedl et al., 1997 Fig. 6, µXRF maps of particles from the same four depths are shown. These maps illustrate the spatial distribution of Fe and Mn on the filters at the micrometer scale. As noted above, concentrations of both Mn and Fe in particles increase at 118.6 m. µXRF maps show considerable spatial association between Mn and Fe at this depth. Molar ratio calculations for these particles, however, show two distinct populations: 5 a high Mn, low Fe population with a Mn:Fe molar ratio averaging approximately 3, and a high Fe, low Mn population with a molar ratio averaging approximately 0.3. Individual molar ratios span from 31.14 to 0.07 Mn:Fe. The high Mn:Fe particles likely represent the authigenic Mn oxides formed by Mn oxidation with oxygen. The high Fe particles with low Mn content are likely the product of Fe oxidation, as Fe(II) is oxidized by Mn oxides. The small amounts of associated Mn may be adsorbed on the surface, a minor coprecipitate, or incorporated into the Fe oxide structure. At all other depths analyzed, there is a small, background population of Fe particles with no discernable Mn. Chemical extractions, µXRF maps, and molar ratio plots all indicate this is a poorly reactive "background" of Fe particles supplied from the catchment.  Table 3. An initial decrease in Mn(II) in the 118 m incubations may be Mn sorption onto Fe and Mn oxides present at this depth in the water column, as no further change is observed. The oxidation rates are highest in the 120 and 121 m depth incubations, which we conclude reflects the relative abundance of Mn oxidizing microbes at this depth. No Mn oxidation occurs in controls amended 25 with formaldehyde or at 118 m, where Mn is normally absent from the water column (Fig. 3). These observations support our conclusion that Mn oxidation is biologically catalyzed. Averaging the experimental rates from 119, 120, and 121 m gives a mean rate of 0.15 ± 0.03 µmol L −1 d −1 .

Mn(II) mineral precipitation
In the bottom waters of Lake Matano, the Mn(II) concentration decreases to 6 µmol L −1 (Fig. 3). Removal of dissolved Mn(II) at depth is expected, since the waters reach saturation with respect to a variety of Mn(II) containing minerals, consistent with thermodynamic saturation calculations (Table 4). Indeed, the bottom waters (at 200 m) of 5 Lake Matano are oversaturated with respect to rhodochrosite, pseudo kutnahorite, and the hypothetical mineral, MnHPO 4 , with pseudo kutnahorite having the saturation index closest to zero and, therefore, being the most likely mineral buffering bottom water dissolved Mn(II) concentrations. As our deepest water column particle samples were from 129 m where we found no Mn particles, further work is needed to verify these 10 predictions.

Modeling
We used flux calculations and a one dimensional (1-D) reaction transport model to explore Mn dynamics in Lake Matano. The 1-D reaction transport model allows us to estimate rates of biogeochemical processes and sinking rates of particles in the water 15 column. It also allows us to test our experimental rate measurements by using the constants derived from the incubations to simulate the in situ profiles. The 1-D model uses AQUASIM software (Reichert, 1994), and assumes steady-state conditions and no lateral input. The model considers transport of Mn solutes and solids by turbulent eddy diffusion, sinking of Mn particles through the water column, reduction of particu-20 late Mn oxides to Mn(II) in the anoxic water column by Fe(II) and other mechanisms, oxidation of Mn(II) by O 2 above the redoxcline, and precipitation of a Mn(II) mineral in the deep water. The eddy diffusion rates were specified explicitly based on their depth distribution in Lake Matano reported in an earlier study (Katsev et al., 2010). These diffusion rates carry an uncertainty factor of ∼ 5. Rate expressions used in the model are 25 presented in Table 5. The concentrations of Fe(II) in the model rate expressions were specified as functions of depth from their measured distributions (Fig. 3) Model parameters were adjusted to fit the measured profiles (Fig. 3). Sensitivity of the model to the reaction rate constants is illustrated in Fig. 9. The corresponding parameters for each run are presented in Table 6. The Mn(II) oxidation rate constant, 5 k MnO x , was specified based on the results of our incubations and fluctuated to demonstrate the best fit and the sensitivity of the model to the constant. The rate constant for Mn oxide reduction by Fe(II), k MnRedFe , was chosen from values reported in sediment modeling studies (Hunter et al., 1998;Van Cappellen andWang, 1995, 1996) for lack of experimental values in comparable environments. The other Mn oxide reduction rate 10 constant, k MnRed , represents Mn oxide reduction by all other pathways. The rate constant for precipitation of the Mn(II) mineral phase was obtained by fitting the measured Mn(II) profile.
The model best fits the field measurements in runs 4 and 5. These fits resulted from the following parameter values: an input of Mn to the lake surface of 120 µmol m −2 d −1 ;

25
Trying to fit the profiles using only one of these pathways resulted in unrealistic values of rate constants. All simulated profiles in Fig. 9 exhibited epilimnetic Mn oxide concentrations higher than the observed values, which suggests that the Mn oxides are supplied into the lake predominantly as slumps along the steep bottom slopes, rather Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | than through the lake surface. This is consistent with previous conclusions about the supply of Fe to the lake's deep waters and sediments (Crowe et al., 2008). Flux calculations allow estimation of Mn recycling rates, which in turn allow us to constrain the potential contributions of various reductants in the reduction of authigenic Mn oxides, within a factor of 5. Fluxes of solutes, J, were calculated based on concentra-5 tion gradients measured in 2009 and eddy diffusivity coefficients, K z (Table 7), as Using a steady state assumption, the volume specific rate calculated from the upward flux of Mn(II) is Assuming a 3 m zone of oxidation (118.5 to 121.5 m), the measured gradients yield an average rate of R MnO x = 0.27 µmol L −1 d −1 . Using this rate, a range of Mn(II) concentrations from 1-15 µmol L −1 , and assuming a pseudo first order rate law: we calculate a range of Mn oxidation rate constants (k ox ) from 0.27 d −1 to 0.01 d −1 . As 15 discussed above, incubations of lake water augmented with Mn(II) suggested Mn oxidation rate constants around 0.015 d −1 , near the lower estimate of the range calculated here. Using a k ox value of 0.1 d −1 (chosen from within these derived values) in our 1-D model, we are able to reproduce the Mn(II) and particulate Mn oxide profiles (Fig. 9). The Mn oxidation rate constant used in the best-fit model (0. of populations to, for example, produce and excrete superoxide or maintain enzymatic heme peroxidase activity. Therefore, while the incubations allowed us to ensure that Mn(II) oxidation was biologically catalyzed, they likely underestimate in situ rates and rate constants. The Mn oxidation rates in our incubations displayed first order reaction kinetics 5 (Fig. 8b), which allows us to compare our results with first order rate constants reported from other environments (Table 8). In this comparison, we note a marked similarity between rate constants from diverse water column settings. These rate constants vary from 0.04 to 0.74 d −1 , with a mean of 0.26 d −1 . This may imply that the mechanism of Mn oxidation is similar in diverse situations and relatively insensitive to environmen-10 tal parameters other than [Mn(II)] and the presence of O 2 . Multiple enzymes have been suggested to play a role in the oxidation of manganese (e.g., Anderson et al., 2009;Brouwers et al., 2000). In Lake Matano, the water column concentrations of Cu are below 180 pmol L −1 (S. A. Crowe, unpublished data), whereas Fe is abundant, which suggests that heme peroxidase enzymes would be used in favor of multicopper 15 oxidase enzymes. Thus, the ubiquitous finding of similar rate constants might suggest that these enzymes function in a related manner, and Mn oxidation rate depends mainly on O 2 concentrations in a variety of different environments.

Recycling rates and potential reductants
Comparing calculated fluxes of Mn(II) allows us to quantify water column Mn recy-20 cling and constrain the potential reductants of Mn oxides (Fig. 10). Assuming pseudosteady state, the rate of Mn leaving the water column must equal the rate of Mn input. Thus, we can equate the downward flux of Mn(II) (driven by Mn(II) mineral precipitation/sedimentation), 61 µmol m −2 d −1 (Table 7), with the total flux of Mn into the system. Since Mn leaves the water column as a Mn(II) mineral, Mn reduction can be calcu- 25 lated as the sum of the upward (oxidative) and downward (precipitation driven) fluxes (821 + 61 = 882 µmol m −2 d −1 ). This rate of Mn reduction is a factor of 4 higher than estimated rates of Fe reduction in Lake Matano (Crowe et al., 2011 roughly 15 times the Mn input, suggesting that Mn is recycled at least 15 times within the water column before removal by sedimentation. As noted by reactions in Table 1, Mn oxides can be reduced using a number of electron donors. Figure 3 shows the concentration profiles of some of these reductants in Lake Matano, where Fe(II), NH  In Lake Matano's chemocline, area-specific sulfate reduction rates are 19 µmol m −2 d −1 (Crowe et al., 2008b). If all sulfide produced by sulfate reduc-20 tion is in turn oxidized back to sulfate by Mn oxides, sulfide could account for 9% of total Mn reduction. Since some sulfide precipitates as solid Fe sulfides (Crowe et al., 2008a), however, this is an overestimate. Organic carbon is also a known reductant for Mn oxides. In the epilimnion, primary production rates were measured at 3.8 × 10 −3 mol m 2 d −1 in 2007 (Crowe et al., 2011). This should generate enough 25 organic carbon to account for all Mn reduction, provided the organic carbon is not respired in the epilimnion. In the chemocline in 2009, however, area specific carbon fixation rates are 9.9 × 10 −3 mol m −2 d −1 . Therefore, there is ample organic carbon fixed in the vicinity of the chemocline to reduce the Mn oxides generated just above flux to account for all Mn reduction. To date, however, there is little experimental and environmental evidence for this process, and a detailed study found it absent from Mn-rich, marine sediments (Thamdrup et al., 2000). As previously proposed (Crowe et al., 2011), we suggest that CH 4 is an additional, potential reductant. While we have shown that Mn oxides are supplied with ample reductants, CH 4 is lacking oxidants (Crowe et al., 2011). At a rate of 882 µmol m −2 d −1 , Mn reduction could account for 5.3% of CH 4 oxidation in Lake Matano. If the maximum Mn reduction from the Fe(II) flux is first subtracted, Mn oxide reduction by CH 4 could be estimated to oxidize ∼ 2.3% 10 of the total CH 4 flux.

Conclusions and geobiological implications
Mn oxidation occurs in a ferruginous chemocline at rates similar to other diverse environments. This suggests that Mn oxidation is insensitive to environmental conditions and may be controlled by a single, common mechanism. Birnessite produced from 15 Mn oxidation settles less than 2 m in the water column before it is completely reduced, likely by a combination of Fe(II), H 2 S, organic matter, and CH 4 . Pseudo kutnahorite precipitation is predicted to buffer the bottom water dissolved Mn(II) concentrations. Due to Mn recycling, Mn reduction rates exceed those of Fe despite the much lower concentrations of Mn in the water column. According to our findings, the kinetics of au-20 thigenic Mn oxide reduction in a ferruginous environment are so rapid that they prevent Mn oxide sedimentation through the underlying anoxic water column. These conclusions could weigh heavily on our interpretation of Paleoproterozoic ocean water column chemistry from which large Mn formations were deposited. As far as current evidence suggests, Mn oxidizes only in the presence of O 2 , and most Mn in marine sedimentary Mn formations must have originally deposited as Mn oxides (Calvert and Pedersen, 1996). Based on C isotope studies, it has been suggested that the carbonate in Mn carbonate minerals from these formations was produced during the diagenetic oxidation of organic matter during respiratory Mn reduction (Tsikos et al., 2003). As Mn oxides would be reduced in a ferruginous water column, we can conclude that the accumulation of Mn oxides in sediments, necessary for subsequent diagenetic Mn reduction, requires that overlying waters contained less Fe(II) than Mn, 5 and the surface waters contained molecular oxygen. Additionally, H 2 S reacts abiotically with Mn in much the same way as Fe(II) (Yao and Millero, 1993). Formation of Mn oxide deposits, therefore, would be most favorable in settings with bottom waters that have low concentrations of both Fe(II) and H 2 S, and perhaps even CH 4 . This scenario could be envisioned as the stratified ocean transitioned from a ferruginous to a euxinic one. 10 The solubility of Fe sulfides is much lower than the solubility of Mn sulfides (Stumm and Morgan, 1996), so as Fe(II) is titrated from the oceans by increasing H 2 S, Mn(II) is left to accumulate. This stratified, manganous ocean would be poised to deposit large quantities of Mn oxides until the source of H 2 S overwhelmed the source of iron and the oceans became euxinic. Furthermore, we can assume that the concentration of Fe(II) 15 in these anoxic bottom waters was < 2 times the concentration of Mn(II) and sulfide concentrations were < 4 times the concentration of Mn(II) based on the stoichiometries of the reducing reactions seen in Table 1. The sources of Fe (weathering and hydrothermal) would still be active during the transitional, manganous ocean, explaining the presence of considerable Fe in most Mn deposits, whereas the concentration 20 of Mn in Fe deposits is low because the ferruginous conditions preclude Mn oxide sedimentation. An alternative explanation would be that Mn-oxide sedimentation occurred in sediments overlain by waters containing low oxygen concentrations and substantial dissolved Mn(II) (Calvert and Pedersen, 1996). These potential scenarios are being further investigated.

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Acknowledgement. The authors wish to thank Alfonso Mucci, Bjørn Sundby, and Raymond P. Cox for inspiring discussions. S. Nomosatryo, D. Rahim, and S. Rio are acknowledged for sampling and logistical support in Indonesia. PNC-CAT beamline scientists provided invaluable instruction and copious coffee. PNC/XSD facilities at the Advanced Photon Source, and research at these facilities, are supported by the US Department of Energy -Basic Energy Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | field, South Africa, Econ. Geol. Bull. Soc., 98, 1449-1462, 2003 Metal cycling in surface sediments: modeling the interplay of transport and reaction, in: Metal Contaminated Sediments, edited by: Allen, H. E., Ann Arbor Press, Chelsea, MI, 21-64, 1995. Van Cappellen, P. and Wang, Y.: Cycling of iron and manganese in surface sediments: a gen-5 eral theory for the coupled transport and reaction of carbon, oxygen, nitrogen, sulfur, iron, and manganese, Am. J. Sci., 296, 197-243, 1996. Viollier, E., Inglett, P. W., Hunter, K., Roychoudhury, A. N., and Van Cappellen, P Reactions marked with letter "a" have been suggested based on indirect evidence while that marked with letter "b" is only hypothesized.