Rapid Iron Reduction Rates Are Stimulated by High ... - Yuanzhi Tang

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Rapid iron reduction rates are stimulated by highamplitude redox fluctuations in a tropical forest soil Brian R. Ginn, Christof Meile, Jared Wilmoth, Yuanzhi Tang, and Aaron Thompson Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05709 • Publication Date (Web): 13 Feb 2017 Downloaded from http://pubs.acs.org on February 19, 2017

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Environmental Science & Technology

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Rapid iron reduction rates are stimulated by high-amplitude redox fluctuations in a tropical

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forest soil

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Brian Ginn1, Christof Meile2, Jared Wilmoth1, Yuanzhi Tang3 and Aaron Thompson1,*

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University of Georgia (Crop and Soil Sci.)

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University of Georgia (Marine Sci.)

Georgia Institute of Technology (Earth and Atmospheric Sci)

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For submission to Environmental Science and Technology

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*Corresponding author E-mail: [email protected], (01) 706-410-1293

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1

ACS Paragon Plus Environment


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Abstract:

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altered by redox-driven processes. This study examined the influence of temporal oxygen variations on

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Fe speciation in soils from the Luquillo Critical Zone Observatory (Puerto Rico). We incubated soils

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under cycles of oxic-anoxic conditions (τoxic:τanoxic = 1:6) at three frequencies with and without

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phosphate addition. Fe(II) production, P availability, and Fe mineral composition were monitored using

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batch analytical and spectroscopic techniques. The rate of FeII reduction increased from ~ 3 to > 45

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mmol Fe(II) kg-1 soil d-1 over the experiment with a concomitant increase of an Fe(II) concentration

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plateau within each anoxic period. The apparent maximum in reducible Fe is similar in all treatments,

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but was hastened by P-amendment. Numerical modelling suggests the Fe(II) dynamics can be

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explained by the formation of rapidly reducible Fe(III) phases derived from the progressive dissolution

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of native Fe(III) oxides accompanied by minor increases in Fe reducer populations. The shift in Fe(III)

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reactivity is evident from Fe-reducibility assays using Shewanella sp., however was undetectable by

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chemical extractions, Mössbauer or X-ray Absorption spectroscopies. More broadly, our findings

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suggest Fe reduction rates are strongly coupled to redox dynamics of the recent past, and that frequent

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shifts in redox conditions can prime a soil for rapid Fe-reduction.

Iron oxides are important structural and biogeochemical components of soils that can be strongly

Rapidly&Reducible&Fe(III)& Reducible&Fe(III)&

Oxida1on&

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Fe(II)&

Reduc1on&

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TOC ART

2


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Introduction

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Although iron comprises only 1-3% of the total mass in soils1, it has a profound influence on

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the properties of soils. The high reactivity and large surface area of Fe-(oxyhydr)oxide minerals

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influence many biogeochemical processes through the sorption of key nutrients or contaminants2-10.

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When exposed to low oxygen conditions, Fe minerals serve as important electron acceptors for

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microbial respiration11, leading to the dissolution of solid phases and release of sorbed and

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incorporated constituents12, 13. This reductive dissolution of Fe has significant implications for the

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global C cycle in soils where a substantial fraction of the total soil organic C oxidation is coupled to the

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microbial reduction of Fe-(oxyhydr)oxides (e.g., 44% in humid tropical forest soils14), which can occur

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in upland soils with Fe(II) production rates ranging from 0.5 to 50 mmol kg-1 d-1 15, 16. The availability

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of Fe minerals toward reduction is strongly correlated with their surface area and particle size17, 18. The

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crystallinity of Fe-(oxyhydr)oxides also strongly influences the kinetics of microbial Fe(III)

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reduction19. Microbes can rapidly reduce ferrihydrite and other short-range ordered (SRO) Fe minerals

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(typically within hours), but reduce well-ordered hematite (α-Fe2O3), goethite (α-FeOOH), and

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lepidocrocite (γ-FeOOH) at slower rates (e.g., several months)18, 20.

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In upland soils, Fe reduction takes place within microsites where high-levels of organic matter

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combine with ephemeral water saturation and low O2 diffusion rates to yield anoxic conditions21, 22.

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Since O2 often re-infuses such microsites as the soils dry, Fe(II) produced during the anoxic period via

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microbial Fe reduction is often re-oxidized to Fe(III) solid phases. This Fe redox cycling can influence

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the rapid cycling of other elements (e.g., C, N, and metals23). Redox fluctuations can drive repeated

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dissolution and precipitation of Fe (oxyhydr)oxide minerals with potential influence on the crystallinity

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of those phases21, 24-27. During anoxic periods, the sorption of the Fe2+(aq) ions to Fe mineral surfaces

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can accelerate the process of Ostwald ripening from SRO to secondary crystalline mineral phases (e.g.,

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goethite, magnetite) that are less chemically reactive and bioavailable than ferrihydrite26, 28, 29.

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However, there are also studies illustrating SRO phases form or persist in fluctuating redox

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environments30-34, indicating that the dynamics of the fluctuations are likely important in determining

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the trajectory of mineral transformations.

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Changes in the crystallinity of Fe (oxyhydr)oxides may also impact the fate of phosphorous (P)

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in natural systems because Fe (oxyhydr)oxide surfaces have a great capacity for adsorbing P4, 5.

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Ferrihydrite has a significantly higher sorption capacity than the crystalline (oxyhydr)oxides because of

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its large surface area, but can form weaker surface complexes with aqueous species than the more

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crystalline iron phases35-37. As a consequence, microbial Fe(III) reduction may simultaneously reduce

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the overall capacity of soils to adsorb metal/metalloids while strengthening the remaining sorbate-

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sorbent interactions.

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Given the potential importance of Fe redox cycling for soil systems, the influence of redox

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oscillations on Fe reduction rates needs to be quantified. A redox fluctuation can be characterized by

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(a) the frequency of the redox oscillation; (b) the oscillation amplitude; and (c) the time spent under

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oxic (τoxic) or anoxic (τanoxic) conditions. Here we hypothesize that shorter frequency oscillations will

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lead to faster Fe reduction rates with associated changes in Fe-(oxyhydr)oxide mineral composition and

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the distribution of phosphate. We test this by exposing a tropical soil to different redox oscillation

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frequencies while holding the oscillation amplitude and ratio of τoxic: τanoxic constant. In order to

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minimize spatial heterogeneity, soils were continuously mixed in slurries—separating the effects of

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redox fluctuations from transport to the extent possible. We then measure changes in HCl-extractable

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Fe(II), Fe mineral composition and P distribution, and simulate the experimental data in a numerical

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model to calculate Fe reduction rates.

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Methods

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Field site and soil preparation Intact soil blocks were collected from the upper 10 cm of soil at a site similar to that described

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by Peretyazhko and Sposito 38 in the Bisley watershed of the Luquillo Experimental Forest (LEF)

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Puerto Rico (approximate GPS location 18.31553N,-65.74574W), which is part of the Luquillo Long-

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term Ecological Research site and the Critical Zone Observatory. Samples were placed in 4-mil

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polyethylene ziplock bags and transported without cooling inside an insulated container to the

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University of Georgia. Within 24 h of sampling, all moist soils were processed by air-drying at 30°C

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for 24 h followed by 2-mm sieving/homogenization (to remove large roots and gravel) under field soil

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moisture conditions within a 95%:5% N2:H2 glovebox (Coy). All soils were stored at 22°C under oxic

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conditions in the dark. Ginn et al. 39 showed these soils maintained the highest levels of microbial Fe-

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reduction when air-dried prior to long-term storage. Soils in the LEF are classified predominately as

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Ultisols formed from volcanic parent material with quartz diorite intrusions40, 41. The major primary

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minerals consist of quartz and plagioclase feldspars with lesser amounts of biotite, hornblende, K-

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feldspar, and accessory magnetite, sphene, apatite, and zircon42. Prior work by Silver et al.21 has

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identified periodic fluctuations in soil O2 concentrations sufficient to generate anoxic conditions within

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the soil. Further information on this soil collection and characterization are described elsewhere39, 43.

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Redox oscillation experiments

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Three oscillation treatments were performed simultaneously. In each experiment, 4.5 g (dry-

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weight) of live soil (not sterilized) was suspended in a buffer solution containing 2 mM KCl and 10

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mM solution of 2-(N-morpholino)ethanesulfonic acid (MES) buffer with a 45 g final suspension mass. 5



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The suspension was supplemented with 200 mg kg-1 of P (i.e. 6.46 mmol kg-1 soil and 0.58 mmol L-1

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suspension). The slurries were incubated for 56 d in a glovebox (95% N2, 5% H2) on an end-over-end

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shaker at 250 rpm. Although these experiments likely had sufficient labile organic carbon to support Fe

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reduction rates (see below), the presence of H2 in the glovebox may have served as an additional

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electron donor for Fe reduction44. In each of the experiments, the soil slurries were exposed to

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alternating oxic-anoxic conditions at frequencies of 3.5, 7, and 14 d with the ratio of time under

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oxic/anoxic conditions (τoxic:τanoxic) maintained at 1:6 for all treatments (i.e., the 3.5 d oscillation had 3

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d of anoxic time and 0.5 d of oxic time; the 7 d period had 6 d anoxic and 1 d of oxic; and the 14 d

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period had 12 d anoxic and 2 d oxic time). Samples were transferred between shaker tables inside and

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outside of the glovebox to create anoxic and oxic conditions, respectively. Control soil slurries were

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maintained at constant anoxic or oxic conditions for 56 d.

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Samples were extracted at the beginning and end of each oscillation cycle using wide-orifice

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pipette tips that allowed complete collection of soil particles in the slurry. Aqueous Fe(II) was

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extracted from the soil slurries by centrifuging the samples at 11,000 rcf for 30 min, which will remove

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particles > 40 nm based on Stokes’ law with an assumed mean particle density of 2.72 g cm-3 for

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basalt-influenced soils45. Acid-extractable Fe(II) was solubilized by suspending the remaining pellet in

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1.0 mL of 0.5 M HCl and shaking it for 2 h on a horizontal shaker at 150 rpm. The extracts were then

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centrifuged at 11,000 rcf for 30 min and the supernatants analyzed for Fe(II) using a modified ferrozine

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protocol24 on a Shimadzu-1700 UV-vis spectrophotometer at λ=562 nm. The dry weight of each pellet

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from the centrifugation step was measured to correct for minor differences in suspension density

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between treatments and allow accurate dry-weight normalization. All values are reported as averages of

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triplicate measurements with error bars indicating standard deviation.

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FeIII-reduction rate experiment 6


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To quantify Fe(III) reduction rates midway through the experiment, additional samples were

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oscillated at the three frequencies given above for 28 d and then exposed to 7 d of continuously anoxic

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conditions during which they were sampled for aqueous and acid-extractable Fe(II) every 0.5 d as

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described above. This data captured the iron reduction dynamics during a reducing period and was used

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to parameterize the reduction kinetics in the numerical model described below.

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Citrate-ascorbate extractable Fe To quantify the short-range-ordered solid Fe phases in the samples, we conducted citrate-

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ascorbate extractions46 on freeze-dried soils from the unreacted samples or at the end of the oscillation

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experiment (freeze-dried immediately upon completion of the experiment). Briefly, the samples were

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suspended in a solution containing 0.2 M Na-citrate and 0.05 M ascorbic acid (pH = 6) at a 60:1

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reagent:sample weight ratio. The suspensions were shaken for 16 h on a horizontal shaker and

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centrifuged at 11,000 rcf for 30 min. The supernatants were analyzed for total Fe on an atomic

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absorption (AA) spectrometer (Perkin Elmer, AAnalyst 200).

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Mössbauer spectroscopy and X-ray absorption spectroscopy

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Fe speciation of the soil samples was characterized via 57Fe Mössbauer spectroscopy and X-ray

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absorption spectroscopy (XAS). Details on data collection, analysis, and interpretation are given in the

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Supporting Information (SI) Sections 2 and 3.

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Fe reduction assay: Shewanella incubations We quantified the availability of Fe(III) for microbial reduction by incubating the soil with a

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culture of Shewanella oneidensis MR-1. The purpose of this inoculation experiment was to determine

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whether redox fluctuations altered the iron oxide availability for microbial Fe-reduction. S. oneidensis 7



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MR-1 was used because it is a good model Fe-reducers, capable of fast Fe-reduction and can live in

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both oxic and anoxic conditions. This experiment is performed solely to assess Fe availability across

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treatments, and is not designed to quantify the in situ iron reduction rate. The assay was performed on

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each replicate of soils freeze-dried from the end of the three different oscillation frequencies, the

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anaerobic and aerobic controls, and unreacted soil. Post-oxidation, freeze-dried soil was used to

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maintain consistency across treatments. Shewanella oneidensis MR-1 was grown to stationary phase in

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media containing (per liter): 0.5 g KH2PO4, 1.0 g Na2SO4, 2.0 g NH4Cl, 1.0 g yeast extract, 0.5 mM

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CaCl2, 0.1 mM MgSO4, 10 mM Na-lactate, and 50 mM Fe-citrate. The cells were washed by

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centrifugation at 3,000 rcf for 30 min and resuspended in fresh media without yeast extract. The

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washing step was repeated twice to thoroughly remove spent media, after which 0.9 g of washed cell

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culture was added to 2-mL centrifuge tubes containing 0.1 g of freeze-dried soil so each sample

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contained the same ratio of bacterial culture to soil mass. The cultures were incubated for a week under

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anoxic conditions. Freeze-dried soils with no S. oneidensis inoculation were used as controls. The

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cultures were sampled for acid-extractable Fe(II) by pipetting 0.1 mL of sample from each culture and

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centrifuging at 11,000 rcf for 30 min. The supernatants were poured off and the pellets were re-

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suspended in 0.1 mL of 0.5 M HCl. The suspensions were shaken for 2 h on a horizontal shaker. The

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extracts were then centrifuged at 11,000 rcf for 30 min. Samples were analyzed for acid-extractible

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Fe(II) using the ferrozine protocol described above.

171 172 173

Phosphate extractions Sequential extractions were performed according to Hedley et al.47. A soil mass of 0.01 g was

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sequentially extracted for 16 h (each) on a horizontal shaker with 0.6 mL of ultrapure water, 0.5 M

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NaHCO3, 0.1 M NaOH, and 1 M HCl. After each extraction, the tubes were centrifuged at 11,000 rcf

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for 30 min. In addition, we quantified microbial biomass P following Hedley and Stewert48. Briefly, 1 8


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mL of CHCl3 was added to 0.01 g of soil in a centrifuge tube and capped. The solution was shaken

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periodically over 30 min and then uncapped so that the CHCl3 could evaporate overnight. In all cases,

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supernatants were analyzed for P using a molybdate blue protocol49 on a Shimadzu-1700

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spectrophotometer at λ = 880 nm.

181 182

Phosphate adsorption isotherms

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To assess the adsorption capacity of the soil, we constructed phosphate adsorption isotherms on

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unamended soils. Briefly, 1 mL of 0, 80, 160, 320, and 640 ppm phosphate was added to 0.1 g of each

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freeze-dried soil in a centrifuge tube. The suspensions were shaken on a horizontal shaker for 2 h and

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then centrifuged for 30 min at 11,000 rcf. The supernatants were collected and measured as described

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above.

188 189

Numerical model

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Experiments were simulated with MATLAB (version R2015b) using a simple, parsimonious,

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process-based kinetic model to describe and test mechanisms of microbial Fe(III) reduction, growth of

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the Fe-reducing microbial community, abiotic Fe(II) oxidation by O2, and solid phase partitioning of Fe

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minerals into distinct pools. Redox oscillations are imposed by setting O2 concentrations to 200 μM

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during oxic periods (slightly below saturation) and 0 during anoxic periods, with Fe(II), Fe- reducing

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microbial community, and a fast and a slowly reacting Fe(III) solid phase (FeOxfast and FeOxslow,

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respectively) as state variables. During anoxic periods, the rate of microbial Fe(III) reduction is given

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as:

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Rred = ∑ ki [ BM ] i

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[ FeOxi ] K m, i + [ FeOxi ]

Eq. 1

where ki is a cell specific rate constant, [BM] is the concentration of Fe reducers, and Km(i) is a half 9



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saturation constants and i represents the fast and slowly reacting Fe(III) solid phases, respectively. The

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net growth rate of Fe-reducing microbes (RBM) is set proportional to the Fe reduction rate, RBM = γ Rred

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, with a growth efficiency γ set to 0.06 (based on growth yields from Kostka et al.50). As the oxic

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periods are relatively short in our experiments, no net growth or death of the Fe reducers is considered

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during oxic periods. Under oxic conditions, Fe reduction is set to 0, and the oxidation of Fe(II) is

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implemented following Stumm and Morgan51: 𝑅!" = 𝑘!" 𝐹𝑒 !! 𝑂!

206

Eq. 2

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where the Fe(II) oxidation rate constant kox is set to 3 × 102 M-1 min-1, 1000 fold higher than the value

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reported for homogeneous oxidation kinetics at the pH of 5.5 in our the experiments to accommodate

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heterogeneous reaction rates52. Fast oxidation can promote the production of less ordered and more

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reactive Fe oxides53, 54, thus we partition all the oxidized Fe(II) to the fast pool given the rapid

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oxidation rate observed in our experiment. During our experiments, we routinely observed that a

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portion of the HCl-extractable Fe(II) formed during the anoxic half-cycle is resistant to oxidation,

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resulting in an apparent accumulation of Fe(II) over the course of the experiment. We represented this

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in the numerical model by removing a small portion of the Fe(II) from the reactive pool, which we

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hypothesize results from physical protection (encasement) against oxidation. The rate of Fe(II) encased

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was set to 2% (q) of the rate of iron oxidation to fit the experimental data. Thus, the dynamics of fast

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and slowly reacting Fe(III) solid phases are given by:

218 219

!!"#$!"#$ !" !!"#$!"#$ !"

!"!"

= 1 − 𝑞 𝑅!" − 𝑅!"#

Eq. 3

!"#$ = −𝑅!"#

Eq. 4

220

Initial reducible Fe(III) solid concentrations were based on the observed values of 10 and 140 mmol L-1

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for fast and slowly reacting Fe oxides, respectively, with zero Fe(II). The fast pool represents Fe that

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can be reduced in less than 3-d39; while the slow pool Fe is set to reproduce the Fe(II) plateau levels 10


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observed in the oscillation experiments. To match the Fe reduction rates across all treatments, the two

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model parameters representing kfast *[BM]t=0 and kslow*[BM]t=0 were set to 6 and 1.5 mmol kg-1 d-1 in

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experiments without P additions, and 10 and 2.3 mmol kg-1 d-1 in experiments with P addition,

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reflecting alleviation of P limitation. The fast and slow rate parameters were determined by fitting the

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data from FeIII-reduction rate experiment conducted after 28-days of incubation (see above). All other

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model parameters were identical across all simulations.

229 230

Results and Discussion

231 232 233

Fe reduction dynamics Fe(II) concentrations responded to changing redox conditions (Figure 1) with peak values at the

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end of the anoxic periods and the lowest values after an oxic period. Peak Fe(II) concentrations

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increased from 10 to 148-165 mmol kg-1 soil in the P-amended treatments as the experiment progressed

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through successive redox cycles (Figure 1). The peak Fe(II) concentrations plateaued near 150 mmol

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FeII kg-1 soil after about 1 month and increased only slowly for the remainder of the anoxic half-cycles.

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The phosphate-amended treatments reached this ~150 mmol FeII kg-1 soil plateau at earlier oscillation

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cycles than the unamended treatments, but by the end of the experiment all treatments exhibited similar

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amplitudes of Fe(II) oscillation, except the 3.5 d unamended control soil (Figure 1).

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The increase in peak Fe(II) concentrations was similar across most oscillation frequency

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treatments, despite different anoxic incubation lengths (Figure SI-1). Thus, the time-averaged iron

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reduction rate is lower in treatments with shorter oscillation frequencies, but the similar peak Fe(II)

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concentrations between treatments suggests total Fe reduction extent is independent of oscillation

245

frequency. To assess how the frequency of redox oscillations affected the reduction kinetics, we

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repeated our oscillation experiments (for the phosphorus addition treatments only) initiating a 11



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continuous 2-week anoxic incubation after one month of redox oscillations (Figure 2). By tracking the

248

accumulation of Fe(II) over time (Figure 2), we surmise there are two phases in the production of

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Fe(II) during anoxic incubations: (1) an initial, rapid Fe(II) production interval followed by (2) an

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interval with much slower Fe(II) production that brings the Fe(II) concentrations into proximity of the

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peak Fe(II) concentrations at the end of each anoxic cycle (Figure 1). Irrespective of oscillation

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frequency, a slow Fe-reduction phase (or plateau) occurs after 4 days of anoxic incubation. This plateau

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could explain why all of the phosphate-amended soil slurries had similar peak Fe(II) concentrations

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(even the 3.5-day treatment), as 90% of the plateau FeII concentration is achieved within 3 days of

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incubation (Figure 1). Although the second experiment was only conducted with the P-amended soils,

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we suspect this plateau may not manifest as prominently in the 3.5-d unamended treatment because the

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overall slower Fe reduction rates in the unamended controls.

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Our experiments were conducted on re-wetted soils that were oxidized without subsequent

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drying during the redox oscillations. This experimental design minimized heterogeneity during the

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experiment and tightened reproducibility between replicates, however it may have impacted the iron

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dynamics in two important ways. First, the re-wetting of soils is well known to produce a flush of

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organic carbon55, and thus our treatments likely contain more soluble, labile organic carbon than if we

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had initiated the experiments from a field moist state. This likely provided an excess of electron donor

264

in the form of soluble organic carbon and it may have increased iron availability through complexation

265

or by facilitating electron shuttling relative to the field moist state56-60. Second, oxidizing the samples

266

under saturated conditions represents the common situation in moist soils or near-surface sediments61

267

in which pulses of O2 accompany the infiltration of rainwater—which has high dissolved O2 levels;

268

whereas is our design does not represent as well soil-drying events, where oxidation fronts follow the

269

major fluid flow paths and create a heterogeneous distribution of FeIII phases62.

270 12


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Fe mineral composition To quantify the changes in the availability of Fe for microbial reduction63, we inoculated the

273

same freeze-dried soils (before and after treatment) with S. oneidensis MR-1 in a defined media to

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quantify the rapidly reducible Fe(III) content (Figure 3). The purpose of this experiment was not to

275

simulate Fe-reduction that occurs in the field, but to determine the bioavailability of Fe after exposure

276

to fluctuating redox conditions. The S. oneidensis cultures produced FeII more rapidly following the

277

3.5-day, 7-day, 14-day, and anoxic control slurry incubations than in the oxic control and slurries with

278

soils prior to the oscillation experiments. We found Fe(III) reduction in the non-inoculated soils was

279

negligible compared to that occurring in the inoculated soils. Thus, outside of a possible stimulatory

280

effect of Shewanella on the growth of the native soil bacteria32, we assume the Fe(III)-reduction assays

281

were not biased by differences in soil microbial population or activity.

282

The 3.5-day, 7-day, 14-day, and anoxic control soils exhibited similarly higher rates of Fe(III)

283

reduction in the S. oneidensis assays than the oxic and initial soils (Figure 3, SI section 4). Although

284

each treatment had different redox oscillation periods, all are likely to have similar abundances of

285

recently oxidized Fe(III), as each oscillation treatment reached similar Fe(II) concentration plateaus in

286

their last anoxic cycle, whereas the oxic control and the starting soil had much lower HCl-extractable

287

Fe(II) concentrations. Since we terminated each treatment following an oxidation half cycle (including

288

the anoxic control), the rapid introduction of O2 oxidizes nearly all of the recently produced Fe2+(aq),

289

likely forming a very reactive, short-range-ordered (SRO) phase54.

290

However, we did not find significant changes in Fe mineral composition between treatments

291

using citrate-ascorbate chemical extractions (Figure S2), 57Fe Mössbauer spectroscopy (MBS, SI

292

section 2), or X-ray adsorption spectroscopy (XAS, SI section 3). This suggests one or more of the

293

following: (1) the proportional change in the SRO pool is too small relative to the total background soil

294

Fe in the soil for these chemical and spectroscopic measures; (2) the re-oxidized Fe is more proximal to 13



295

the microbial iron reducers—perhaps precipitating as thin surface coatings on the original SRO-Fe

296

phases, while retaining similar local structure or by forming complexes with extracellular polymeric

297

substances on the bacterial surface64-66; (3) the re-oxidized Fe co-precipitated with organic electron

298

shuttling agents that can increase the availability for microbial reduction without yielding detectable

299

changes in mineral composition.

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Prior work from redox fluctuation experiments illustrates that Fe mineral crystallinity can

301

increase or decrease24, 32, 33, 67, or remain undetected68, although the specific conditions driving the

302

trajectory of mineral change are unclear. Documented increases in Fe mineral crystallinity might be

303

associated with slow or incomplete Fe oxidation. Liptzin and Silver67 found increases in Fe

304

crystallinity when exposing intact, un-homogenized soil samples to redox fluctuations and Thompson

305

et al.24 similarly found Fe crystallinity increases when redox fluctuating soil slurries were exposed to

306

progressive oxidation intended to approximate conditions within an aggregate. Likewise, if the initial

307

phase has very low crystallinity, then exposure to Fe2+(aq) during the anoxic periods may promote

308

increases in crystallinity as Tomaszewski et al.26 showed when exposing ferrihydrite to a redox

309

fluctuating environment. However, decreases in Fe crystallinity have also observed during redox

310

fluctuations, especially when accompanied with soil drying69, 70, or when the starting material is of

311

higher crystallinity32. Furthermore, there are other reports, akin to our study, where changes in Fe

312

crystallinity cannot be detected following redox fluctuations68.

313 314

Process identification

315

We identified process dynamics consistent with the observational data by implementing

316

different processes in a numerical model. Our implementation is able to reproduce the observed

317

increase in Fe(II) concentrations (aqueous plus 0.5M HCl extractable) during the anoxic cycles, as well

318

as the plateau phase revealed in our 2nd experiment (Figure 1). The basic structure of the model 14


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includes two pools of iron with different cell-specific Fe reduction rates (kfast and kslow). This was

320

critical for reproducing the high Fe(II) production rates at the beginning of each anoxic period,

321

followed by slower Fe(II) production rates associated with reduction of the less reactive iron pool.

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A key feature of the whole data set (P-amended and non-amended treatments) is that net Fe(II)

323

production rates increase over the course of the experiment (Figure 1). The initial rates of Fe reduction

324

were ~ 3 mmol Fe(II) kg-1 soil d-1, which are similar to rates measured previously on this soil39.

325

However, during the later half of the experiment, the Fe reduction rates increased to 17-66 mmol FeII

326

kg-1 soil d-1 across all treatments (Figure 4). This increase in peak Fe(II) concentrations over the course

327

of the experiment can be explained by the combined effect of an increased pool of reactive iron

328

oxide—formed during rapid oxidation of Fe(II) accumulated during the anoxic periods—and a minor

329

increase in the activity of the iron reducing community. We measured Fe reduction population densities

330

at the beginning and end of the experiment (Table S1) and found no difference within the log unit

331

precision of our methods, which—consistent with the model simulations—implies the Fe reducer

332

population increased less than tenfold over the course of the experiment. Fe(II) concentrations also

333

increase slightly during the oxic half-cycles over the course of the experiment, amounting to what

334

appears as a upward drifting Fe(II) baseline (Figure 1). This may reflect the formation of a mixed-

335

valance iron mineral, a stable Fe(II)-organic matter complex or an Fe sulfide phase, represented in the

336

model by the partitioning a portion of Fe(II) into a non-oxidizable form that is still extractable via 0.5M

337

HCl (see methods). Thus, in our final model, we assumed that the “active Fe”—defined as Fe that

338

could be mobilized via Fe reduction or other processes within the timescale of our experiment—moved

339

between four reservoirs: (1) a rapidly reducible Fe(III) solid; (2) a slowly reducible Fe(III) solid; (3)

340

dissolved or adsorbed Fe(II); and (4) a non-oxidizable Fe(II) phase. Both Fe(III) solid phases

341

contributed to the trend of increasing FeII peaks over the course of the oscillation experiment. During

342

each oxidation cycle, we partitioned all of the Fe(II) oxidized into the rapidly reducing Fe(III) solid 15



343

phase, hence providing each subsequent simulated reduction cycle with a larger pool of rapidly

344

reducible Fe(III).

345

Page 16 of 29

An alternative explanation for the plateau in Fe(II) concentrations is that sorption of Fe(II) to Fe

346

mineral surfaces may pacify the Fe(III) toward further reductive dissolution. Roden and Zachara2

347

attributed a microbial Fe(III)-reduction plateau they observed in pure culture experiments to this effect.

348

However, in our experiment, peak Fe(II) concentrations clearly increase with subsequent oscillation

349

cycles, suggesting Fe reduction rates across all treatments increased as the experiment progressed

350

(Figure 4).

351

Imposing the above constraints and processes does not yield a model fit to all frequency

352

treatments unless the model parameters are tuned to each treatment. However, by imposing a short

353

suppression of simulated microbial growth at the beginning of each anoxic cycle—representing a

354

predominance of intracellular metabolic adjustments over the formation of new biomass—we can

355

achieve a consistent match with the experimental Fe(II) data. A single global parameter set matches the

356

observations across all oscillation frequencies (Figure 1), except that the P-amended treatments

357

required a higher cell-specific Fe reduction rate than the unamended treatments.

358

Considering first the non-amended treatments, the simulated peak rates of Fe reduction are

359

similar for the 3.5-d and 7-d treatments (peak rates of Fe(II) production ~ 30 mmol kg-1 soil d-1), but

360

substantially slower in the 14-d treatment (peak rates of Fe(II) production ~ 17 mmol kg-1 soil d-1).

361

Because the iron reduction rates are only high during the first ~ 4 days of each anoxic period (Figure

362

4), the 14-d treatment has longer period in which the microbes are largely inactive. With microbial

363

growth linked to metabolic activity, this leads to less growth. Over the course of the experiment, the

364

simulated biomass increased 4.3× in both the 3.5-d and 7-d treatments, compared with an increase of

365

only 2.7× in the 14-d treatment (Figure S3), which in turn leads to lower Fe(II) peak concentrations

16


Page 17 of 29

366


(Figure 1).

367 368 369

Phosphorus considerations Augmenting the soil slurries with phosphate enhanced the production of Fe(II) during the

370

anoxic cycles (Figure 1), suggesting that microbial activity was stimulated. Consistent with this

371

hypothesis, the amount of phosphorus released following exposure to CHCl3 increased over the course

372

of the experiment (Figure S5), suggesting P accumulated in the microbial biomass. No other changes in

373

the phosphorus distributions (based on the Hedley protocol47) were observed in the treatments, with

374

nearly all of the P residing in the NaOH extractable pool (negligible P was found in the aqueous,

375

NaHCO3, and HCl extracts and thus were not reported). NaOH extractable P is considered to be

376

associated with Fe and Al oxide surfaces in the standard interpretation of the Hedley protocol47.

377

Previous measurements of Luquillo soils also found P to be predominately associated with mineral

378

surfaces38, 67. We found there was substantial potential for P uptake in these soils, but the amount and

379

shape of the phosphate adsorption isotherms (which followed typical Langmuir curves) did not differ

380

between treatments and controls (Figure S4, Table S2).

381

The phosphorus addition treatments had higher simulated rates of Fe reduction than the non-

382

amended controls, with peak rates of Fe(II) production ~66, ~52, and ~31 mmol kg-1 soil d-1 for the 3.5-

383

d, 7-d, and 14-d treatments, respectively. Higher cell-specific Fe reduction rate constants are required

384

to match the temporal evolution of Fe(II) oscillations in the P-amended treatments than are required in

385

the non-amended controls (an increase of 66.7% and 50.3% for fast and slowly reacting iron oxides,

386

respectively). Similar to the non-amended treatments, our simulations increase microbial biomass more

387

in the shorter frequency treatments as a direct consequence of their proportionally longer time with

388

access to rapidly reducible iron (Fe(III)RR) than the longer frequency treatments. Over the course of the

389

experiment, the simulated biomass in the P-amended treatments increased 7.0×, 5.1× and 3.2× in the 17



390

Page 18 of 29

3.5-d, 7-d, and 14-d treatments, respectively.

391

This may be the first study illustrating that additions of P promote an increase in Fe(II)

392

production rates in native soils or sediments however, there is a large body of work based on synthetic

393

minerals. In these pure-system studies, addition of phosphate often alters the rate of Fe(II) production,

394

although the direction and magnitude of change is inconsistent, depending on P concentrations, Fe

395

mineral composition and other factors71-78. Our P-amended soils had 6.46 mmol kg-1 soil (or 0.58 mmol

396

L-1 suspension) of P added, which is lower than most of the P amendments used in prior synthetic iron

397

mineral studies—typical P amendments are 2 - 20 mmol L-1 in the suspension74, 75, with 0.4 mmol L-1

398

often considered a low P treatment73. Thus, given the low amount of P added in our treatments, we

399

suspect the increase in Fe(II) production rates results from an alleviation a P limitation on microbial

400

growth, which is consistent with P uptake to the biomass (Figure S5).

401 402

Ecosystem Implications

403

Upland ecosystems are subjected to short periods of anoxia that often lead to some ephemeral

404

iron reduction, which can influence C cycling and the fate of many nutrients and chemicals. We have

405

shown that successive periods of redox fluctuations over a month timescale with ample organic C can

406

increase soil Fe reduction rates, regardless of fluctuation frequency. Thus, Fe reduction rates during the

407

onset of anoxia are strongly coupled to physiochemical dynamics of the recent past. Terrestrial systems

408

exposed to rain events that yield iron reducing conditions and a build-up of Fe(II) thus might be primed

409

for more rapid iron reduction rates than systems emerging from a long drought or with continuously

410

wet soils.

411

The amount of Fe(II) produced following a prolonged anoxic incubation is often predicted

412

through selective extractions (oxalate, citrate-ascorbate, hydroxylamine, etc.) targeting the short-range-

413

ordered (SRO) phases. Our work is consistent with this in that the total amount of Fe(II) produced 18


Page 19 of 29


414

during an anoxic cycle later in the experiment (or in the anoxic control) was similar to the citrate-

415

ascorbate extractable iron (~ 30% of total Fe). However, SRO abundance is a poor predictor of iron

416

reduction rate, because the SRO abundance does not change throughout the experiment, while iron

417

reduction rate changes dramatically. Instead, we propose the availability of SRO phases for Fe

418

reduction is enhanced through rapid oxidation events by atmospheric air (~21% O2), creating a sub-set

419

of rapidly reducible SRO-Fe [Fe(III)RR]. We found Shewanella cultures could reduce Fe(III) much

420

faster from soils exposed to redox fluctuations than from the oxic controls, however we could not

421

detect any corresponding shifts in mineral composition via selective extractions, Mössbauer

422

spectroscopy, or X-ray adsorption spectroscopy. Regardless, by the later half of the experiment nearly

423

the entire SRO Fe pool undergoes reduction within four days.

424

Soils that are frequently exposed to redox fluctuations have a large pool of rapidly reducible

425

iron to transfer electrons to during periods of oxygen depletion—a biogeochemical battery 79 that is

426

recharged by rapid oxidation of previously anoxic pore waters. Our work highlights the importance of

427

identifying the reaction timescales and limiting reactants/catalysts (microbes) in predicting iron

428

reduction rates in soils. Prior work suggests this soil does not have significant C- limitations 39, but we

429

did find the soil responded to P-amendments with more rapid increases in iron reduction rate than

430

unamended soils. The P-amended treatments required a faster cell-specific Fe reduction rate when P

431

was added and suggests iron reducer activity (population growth, CO2 production, etc.) is higher when

432

redox fluctuations occur on timescales similar to the process timescales (length of time to oxidize most

433

of the Fe(II) or the length of time to a Fe(II) concentration pseudo-plateau). Soils that are exposed to

434

near-weekly redox pulsing (due to variable rain events or water-table shifts) may therefore be more

435

dominated by iron biogeochemical dynamics than soils that experience redox shifts only seasonally.

436

19



437

ASSOCIATED CONTENT

438

Supporting Information

439

Four supporting information sections are included: Section 1 contains two additional tables and five

440

additional figures cited in the main text; Section 2 contains a detailed description of the Mössbauer

441

(MBS) characterization of soil Fe; Section 3 contains a detailed description of the XAS

442

characterization of soil Fe and a comparison of the XAS and MBS findings; Section 4 contains a

443

description of the statistical test of Shewanella sp. assay. This material is available free of charge via

444

the Internet at http://pubs.acs.org.

445 446

AUTHOR INFORMATION

447

Corresponding Author

448

*E-mail: [email protected].

449

Notes

450

The authors declare no competing financial interest.

451 452 453 454

ACKNOWLEDGEMENTS We thank Whendee Silver for providing access to the Bisley site; Michelle Scherer, Drew Latta, and

455

Tim Pasakarnis for Mössbauer measurements; Chris Gorski and Prachi Joshi for preliminary

456

electrochemical analyses of these soils; Qing Ma (APS 5-BM-D) and Ryan Davis (SSRL 4-1) for

457

assistance with XAS analysis; and Nehru Mantripragada for laboratory assistance. This work was

458

funded by USDA - NIFA Soil Processes Program AFRI- NIFA Grant no. 2009-65107-05830 to AT

459

and CM; NSF grants EAR-1331841, EAR-1053470, EAR- 1451508, and DEB-1457761 to AT; and

460

NSF OCE-1559087 to YT. Portions of this research were conducted at the Stanford Synchrotron 20


Page 20 of 29

Page 21 of 29

461


Radiation Lightsource (SSRL) and the Advanced Photon Source (APS).

462 463

21



Page 22 of 29

464

References

465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517

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W., Biotransformation of two-line silicaferrihydrite by a dissimilatory Fe(III)-reducing bacterium: Formation of carbonate green rust in the presence of phosphate. Geochim. Cosmochim. Acta 2004, 68, 2799-2814. (75) Borch, T.; Masue, Y.; Kukkadapu, R. K.; Fendorf, S., Phosphate imposed limitations on biological reduction and alteration of ferrihydrite. Env. Sci. Technol. 2007, 41, 166-172. (76) O’Loughlin, E. J.; Boyanov, M. I.; Flynn, T. M.; Gorski, C. A.; Hofmann, S. M.; McCormick, M. L.; Scherer, M. M.; Kemner, K. M., Effects of bound phosphate on the bioreduction of lepidocrocite (γ-FeOOH) and maghemite (γ-Fe2O3) and formation of secondary minerals. Env. Sci. Technol. 2013, 47, 9157-9166. (77) O’Loughlin, E. J.; Gorski, C. A.; Scherer, M. M.; Boyanov, M. I.; Kemner, K. M., Effects of oxyanions, natural organic matter, and bacterial cell numbers on the bioreduction of lepidocrocite (γ-FeOOH) and the formation of secondary mineralization products. Env. Sci. Technol. 2010, 44, 4570-4576. (78) Zachara, J. M.; Kukkadapu, R. K.; Peretyazhko, T.; Bowden, M.; Wang, C. M.; Kennedy, D. W.; Moore, D.; Arey, B., The mineralogic transformation of ferrihydrite induced by heterogeneous reaction with bioreduced anthraquinone disulfonate (AQDS) and the role of phosphate. Geochim. Cosmochim. Acta 2011, 75, 6330-6349. (79) Byrne, J. M.; Klueglein, N.; Pearce, C.; Rosso, K. M.; Appel, E.; Kappler, A., Redox cycling of Fe (II) and Fe (III) in

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magnetite by Fe-metabolizing bacteria. Science 2015, 347, 1473-1476.

632

25



633

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Figure 1

634

Unamended

635 636 637 638 639 640 641 642 643 644

40

0

14

7d

160

28

Days

120 80 40

200

0

7

Days

120 80 40 0

0

7

200

Phosphate amended 14 d

160

Figure 1: Fluctuations and model

120 80 40 200 56

0

14

7d

160

28

42

56

Days

120 80 40

200 14 21 28 35 42 49 56

3.5 d

160

42

2+

200

2+

80

0.5 M HCl extractable Fe -1 mmol kg

120


2+

14 d

160


0.5 M HCl extractable Fe


2+

2+

(mmol kg )

0.5 M HCl extractable Fe 0.5 M HCl extractable Fe 2+ -1 -1 -1 mmol kg mmol kg

2+

200

0

160

7

14 21 28 35 42 49 56

3.5 d

Days

120 80 40

0 14 21 28 35 42 49 56

0

7

Days

14 21 28 35 42 49 56

Days

Figure 1. Fluctuations in FeII concentrations due to redox oscillations with periods of 3.5 d (bottom), 7 d (middle) or 14 d (top). All treatments have the same oxic:anoxic exposure time ratio of 6:1 and the oxic cycles involve exposure to 21% O2. Graphs on the left side are for un-amended slurries and those on the right are for treatments with added phosphorous. Symbols indicate measured values with 1 s.d. error bars based on three replicates. The solid lines represent the numerical model.

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645 646


Figure 2

647

648 649 650 651 652 653 654

Figure 2. FeII-concentrations under anoxic conditions following 28 d of redox oscillations with periods of 3.5 d, 7 d, or 14 d in treatments amended with phosphorous. Error bars are 1 s.d. This data was used to fit the dynamics during the reduction period in the numerical model across all treatments.

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655

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Figure 3

Oscillations & anoxic control after oxidation

Unreacted & oxic control after oxidation

656 657 658 659 660 661 662 663 664 665

Figure 3 Figure 3. FeII concentrations in a liquid culture of S. oneidensis MR-1 incubated with the sole source of ferric iron deriving from freeze-dried soil samples from the indicated redox oscillation treatments and controls (all of which ended with oxic exposure, including the anoxic control). Each data point is the difference in acid-extractable FeII concentrations between inoculated soils and the non-inoculated controls. Error bars are 1 s.d. See SI-Section 4 for more details.

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666


Figure 4

667

Phosphate Amended 80

Net Fe(II) Production Rate -1 mmol kg

40

14 d

30 20 10

Net Fe(II) Production Rate -1 -1 mmol kg d

668 669 670 671 672 673 674 675 676



40

7d

30 20 10 40

3.5 d

30 20 10 0

0

7

14 21 28 35 42 49 56

Net Fe(II) production rate -1 -1 mmol kg d


Unamended

14 d

60 40 20 80

7d

60 40 20

80

3.5 d

60 40 20 0

0

7

14 21 28 35 42 49 56

Days

Days

Figure 4 Figure 4. Net Fe(II) production rates calculated at each time point from the numerical model for the unamended (left graphs) and P-amended (right graphs) treatments. Values shown only for anoxic periods.

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Rapid Iron Reduction Rates Are Stimulated by High ... - Yuanzhi Tang

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