Iron’s role in soil organic carbon (de)stabilization in mangroves under land use change

Domain: earth_science
Published: 2024-11-30
Editorial outcome: major_revision

Abstract
Mangroves are coastal hotspots for carbon storage and yet face multiple threats from anthropogenic activities. Here we explore the role of iron-mediated organomineral interactions (FeOMIs) in soil organic carbon (SOC) stabilization and their sensitivity to land use change (LUC) in Amazonian mangroves. We show that Fe oxides protect more labile SOC fractions, which would otherwise be vulnerable to biological degradation, with poorly crystalline Fe oxides being the most effective phase for SOC retention. Despite the fragile equilibrium of FeOMI under dynamic redox conditions in mangroves, this balance sustains approximately 8% of total SOC. The studied LUC scenario led to massive loss of FeOMIs as less crystalline phases were either degraded or transformed into more crystalline ones, losing the efficiency in retaining SOC. The conversion of mangroves to pastures and shrimp ponds, which are pervasive globally, triggers important biogeochemical changes, with major implications for the carbon sequestration potential of mangrove soils.

Introduction
Mangrove forests are unique ecosystems offering a variety of key ecosystem services, including nutrient cycling, provision of habitat, food for numerous species, coastal protection, and carbon storage1. These forests store considerable amounts of carbon—11.7 petagrams (Pg), with 10.2 Pg (87%) stored in their soils2. Despite their carbon storage capacity, which occurs under harsh environmental conditions (e.g., high salinity, anoxia, tidal flooding)3, mangroves face substantial threats from human activities4. Land use change (LUC) alone has been responsible for the loss of more than 180,000 hectares of mangrove forests in the past two decades5. Accordingly, the conversion of mangrove forests to agricultural, aquacultural, and urban areas led to the loss of 158 million tons of carbon stocks6.

The Amazonian mangroves are recognized as some of the most carbon-rich forests in the world as their ability to accumulate and retain carbon surpasses up to four times that of the upland Amazon Forest7. However, the Amazonian mangroves face an alarming loss rate of 0.12% per year, representing the emission of nearly 1 Tg CO2e yr−18. The loss of soil organic carbon (SOC) stocks is of special concern since SOC is considered the most stable pool of ecosystem carbon that may persist for centuries to millennia9,10. While the impact of LUC on C stocks of mangroves is well-documented2,11, few studies have explored the biogeochemical processes involved in the (de)stabilization of organic carbon in mangrove soils12. As a result, our understanding of the key mechanisms driving C stock losses in these forests remains incomplete, hindering the establishment of effective conservation, restoration, and adaptation strategies to mitigate loss and enhance recovery of SOC.

SOC stabilization in mangroves, as in other ecosystems, is likely influenced by the complex interplay between organic substrates, microorganisms, environmental variables (e.g., temperature, moisture), and soil physico-chemical properties13. Traditionally, factors such as high primary production, high recalcitrance of the organic substrate and low heterotrophic respiration, due to waterlogging conditions, have been considered as the main factors explaining the usual high SOC contents in mangrove forests. Only recently has attention been directed toward physicochemical stabilization processes (e.g. physical protection, organomineral interactions) which are now gaining recognition12.

Particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) are two key fractions that play a significant role in SOC persistence14. POC generally consists of larger, less decomposed organic fragments, mainly from plant residues. This fraction is more susceptible to microbial decomposition, resulting in a turnover of a few decades14. In contrast, MAOC consists of smaller, more decomposed organic molecules that are tightly bound to soil minerals. This fraction is more stable, with a lifespan ranging from centuries to millennia14,15, since the mineral association offers protection against microbial degradation13,16.

Iron (Fe) oxides, are key minerals involved in the stabilization of SOC in coastal wetland soils and marine sediments17–19. These reactive Fe phases can form stable covalent bonds between their surface hydroxyls and organic functional groups, protecting SOC from microbial degradation17. While in well-drained soils, organic matter typically associates with more crystalline Fe oxides, such as hematite and goethite20,21, in mangrove soils this association probably occurs through co-precipitation with poorly crystalline Fe oxides, such as ferrihydrite and lepidocrocite. This is due to the redox and acid-base oscillations characteristic of mangrove soils, which favor the formation of poorly crystalline oxides over the crystalline ones3,22.

The unique geochemical conditions in mangrove soils cause Fe to cycle constantly between different prevailing Fe solid phases, i.e., Fe oxides and pyrite22 As a result, iron-mediated organomineral interactions (FeOMIs) in these soils form through a different dynamic compared to other waterlogged environments. Considering the drastic geochemical changes associated with LUC in mangroves—such as vegetation removal, drainage, and altered hydrodynamics23,24—further research is necessary to understand the precise impact of LUC on FeOMIs and, consequently, on SOC persistence.

Here we evaluate the impact of LUC, specifically the conversion of mangrove forests into pasture and shrimp ponds, on FeOMIs in Amazonian mangroves (Fig. 1). We aimed to provide a comprehensive investigation of the nature and thermal stability of these associations and hypothesized that FeOMIs are critical to SOC persistence but highly susceptible to LUC. To test our hypothesis, we conducted a thorough analysis by combining physical fractionation of SOC, wet-chemical extractions, thermal and spectroscopic analyzes to probe FeOMIs in Amazonian mangrove soils under LUC.

Results
The nature and stability of FeOMI in mangrove soils
To investigate the mechanisms underlying FeOMIs, we analyzed the samples containing the MAOC fraction from pristine mangrove soils at depths of 0–10, 40–50, and 80–100 cm. These samples underwent Fe sequential extraction, with both Fe and OC concentrations measured at each step. Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetric-Differential Scanning Calorimetry (TG-DSC) were also conducted between extraction steps to gain deeper insights into the contribution of each Fe fraction to organomineral interactions and SOC stability (see the “Methods” section and Fig S1 for further details). We used the ratio of aliphatic C-H (2985–2830 cm−1) relative to carboxylate group (COO-; 1440–1390 cm−1) to assess the degree of organic matter decomposition. A lower ratio suggests increased microbial oxidation, thus increased decomposition25. To assess the thermal stability of Fe-bound OC, we calculated energy density (ED) and the temperature at which half the exothermic energy is released (DSC-T50). Energy density can serve as a proxy for the biochemical complexity of organic matter and its degree of decomposition, where higher ED implies a more complex and less decomposed organic structure26. Similarly, a higher DSC-T50 indicates greater thermal recalcitrance of SOC27.

The progressive extraction of Fe was accompanied by a decrease in OC as evidenced by the reduction in the intensities of organic bands in the FTIR spectra (Fig S2a). Simultaneously, there was expansions and shifts to higher temperatures in the exothermic region related to organic matter oxidation (Fig S2b), as shown by increases in both ED and DSC-T50 (Table S1), implying greater thermal stability of the remaining OC. This increase in thermal stability following the removal of Fe initially appears contradictory since Fe-bound OC is commonly perceived as a highly stable fraction of SOC in coastal and marine environments17,28. A first explanation for this observation would be the catalytic effect of Fe oxides on organic matter oxidation during thermal analysis29. However, when Fe and the associated OC are removed, the remaining OC is still associated with other minerals, such as aluminosilicates, which can also produce a catalytic effect30. Thus, an alternative explanation would involve the different OC composition in MAOC subfractions.

The increased thermal resistance of the remaining OC suggests that Fe binds to thermally and (likely) biologically labile OC. This aligns with the “bioenergetic framework”26,31 and the current paradigm of soil organic matter persistence13,16,32. These perspectives suggest that soil organic matter exists as a continuum, processed by the decomposer community from large biopolymers to small monomers. Depolymerization and oxidation of larger organic molecules solubilize smaller ones, which make them more accessible for microbial uptake if the dissolved organic matter is readily available13. On the other hand, oxidation enhances chemical reactivity of organic compounds by reducing molecular size, increasing polarity, and thus increasing chemical reactivity33. This is crucial for the formation of organomineral interactions, especially those with Fe oxides, which involve ligand exchange reactions with oxygen-bearing organic functional groups21,34.

When compared to POC, MAOC has lower thermal stability, reflected by lower ED and lower activation energy, the latter positively correlated with DSC-T50 26,31. This is because MAOC is composed of easily metabolizable organic molecules with low thermodynamic stability26,31. Thus, a decrease in thermal stability is expected as SOC decomposition progresses, with larger plant biopolymers being processed into smaller and simple molecules35. However, variations in stability within MAOC fractions also exists, depending on its chemical composition36.

Here we observed a positive correlation between DSC-T50 and the CH:COO- ratio (Fig. 2a), meaning that as the CH:COO- ratio increases (i.e., Fe-bound OC is removed), the remaining MAOC becomes more thermally resistant. Similarly, there was an increase in the C:N ratio with Fe-bound OC removal (Fig. 2b). These patterns indicate that Fe-bound OC is more oxidized and degraded, less thermally stable and less energetic than the residual MAOC. Thus, our data show that Fe phases play a key role in protecting a relatively labile SOC fraction in mangrove soils.

The Fe in organomineral complexes (Fecit) was the most abundant fraction, ranging from 3.8 to 5.1 g kg−1 across the three studied depths (Table S1). However, the molar OC:Fe ratios were relatively low (<4.0; Table S1), suggesting that while Fecit is important for organomineral associations due to its high concentration, it isn’t particularly effective at binding OC on a per-unit basis of Fe. The precise mechanism of OC stabilization through association with the Fecit fraction, whether through adsorption or co-precipitation or adsorption, is uncertain. The stabilization could occur either by cation-bridging or co-precipitation with low molecular weight organic compounds37, resulting in the observed low OC:Fe ratio.

There was no evident difference in poorly crystalline (Feasc) and crystalline oxides content (Fcbd), with both ranging between 0.5 and 2.0 g kg−1 (Table S1). However, the Feasc presented the highest OC:Fe ratio (>13), nearly 3 times higher than those of Fcbd. While the OC:Fe ratio alone may not offer definitive information about the types of interactions between Fe oxides and OC—since some reducible Fe may not be associated with OC17—it does suggest that poorly crystalline oxides exhibit a stronger affinity for OC. Indeed, the adsorption capacity of OC on poorly crystalline Fe oxides can be up to three times higher than on crystalline ones, under identical chemical conditions (Table S2), largely due to their higher surface area and smaller particle size38. Additionally, interactions between OC and Fe in poorly crystalline Fe oxides also involve co-precipitation processes20,21, which can immobilize 10 times more OC than adsorption reactions (Table S2). Therefore, our data highlight the critical role of Fe oxides, particularly poorly crystalline phases, in protecting OC in mangrove soils.

Impact of land use change on Fe and SOC biogeochemistry
Conversion of mangroves to pasture and shrimp ponds led to significant changes in the soil geochemical environment as evidenced by the shifts in Eh-pH conditions (Fig. 3). Soil samples from the pristine mangrove and the mangrove adjacent to shrimp ponds were within anoxic to suboxic conditions (Eh -150±96 and -239±89 mV, respectively) and slightly acidic to neutral pH levels (5.8±0.4 and 6.4±0.6, respectively). Such conditions evidence a common soil geochemical environment in mangrove soils favorable to the coupling of iron and sulfate reduction and precipitation of poorly crystalline Fe oxides (see Ferreira et al., 2021). In contrast, the mangrove converted to shrimp pond trended towards more oxidizing conditions (Eh -59±126 mV), mostly within the stability field of crystalline Fe oxides. The physico-chemical changes were more pronounced at the site converted to pasture, where the pH dropped to 4.5±0.5 and Eh increased to 284±34 mV, indicating oxidizing and acidic conditions and, thus, a sharp shift towards the equilibrium of soluble Fe2+.

The observed shifts in Eh and pH were in accordance to changes in Fe geochemistry, which were evident across all soil depths (Fig. 4a). The Fecit (i.e. Fe fraction in organomineral complexes) was the most sensitive to land use change. Mean concentrations of Fecit considering all soil depths decreased progressively from 2.9±1.4 g kg−1 in pristine mangroves to 0.7±0.1 g kg−1 in mangroves converted to shrimp ponds and less than 0.2 g kg−1 in those converted to pasture (Fig. 4b). Additionally, there was an important decrease in Feasc (i.e. poorly crystalline oxides), especially when comparing pristine mangroves (Feasc = 0.8±0.03 g kg−1) to those converted to pasture (0.3±0.1 g kg−1).

The high variability observed in the shrimp pond samples at each depth are likely due to the drainage and refilling activities associated with shrimp pond management, as well as the death of roots due to deforestation and consequently impacting on soil aeration. These factors likely caused Fe segregation, leading to variability in Fcbd concentrations across different depths. Despite large variation, there was an eight-fold increase in mean Fcbd (i.e. crystalline iron oxides) in shrimp ponds in relation to the pristine mangrove and the mangrove adjacent to shrimp ponds (Fig. 4b). This increase is in accordance with the physicochemical conditions (i.e. Eh and pH; Fig. 3) prevailing in the shrimp ponds. Such changes occurred mostly at the expense of the Fecit fraction (Fig. 4b).

Finally, the total extracted Fe (i.e, the sum of Fecit, Feasc, Fcbd) under pasture was at least five times lower compared to pristine mangroves, with most losses occurring in both Fecit and Feasc, with a decrease of more than 75% in both fractions (Fig. 4b).

The conversion of mangroves to shrimp pond and pasture led to substantial loss of SOC (Fig. 5a). While in pristine mangroves SOC was generally greater than 30 g kg−1, in shrimp ponds and pasture SOC decreased to less than 7 g kg−1. Most SOC in mangroves, whether pristine or in forests adjacent to shrimp ponds, was found in the form of MAOC (Fig. 5b). These MAOC concentrations ranged from 17 to 25 g C kg−1 being two-fold higher than those of POC, except in the pasture soil (Fig. 5b). Conversion of mangroves into shrimp ponds led to a substantial loss of both MAOC and POC fractions, reaching levels four times lower than the pristine mangroves (Fig. 5b). The conversion to pasture resulted in more pronounced losses, mostly in the MAOC fraction (<2 g C kg−1; Fig. 5b), indicating that even this presumably stable fraction can be significantly degraded following land use change. Although data on mangrove conversion to pasture in the Amazon is still limited, the observed relative loss of SOC following mangrove conversion to pasture aligns with findings from other regions, where SOC losses are in the range of 80–90%39,40.

In pristine mangroves, Fe-bound OC represented 8.0±2.0% of the SOC (Fig. 5c). However, this fraction proved highly susceptible to land use change, as evidenced by a decrease of 80% in Fe-bound OC observed across all soil depths in the different LUC scenarios (Fig. 5b). Following LUC, the Fe-bound OC (% SOC) varied between 5.3±5.1% for the mangroves converted to shrimp ponds, and 1.0±1.1% for the mangrove forest converted to pasture (Fig. 5c).

Deforestation followed by soil drainage led to oxidizing conditions and were likely the primary drivers of organic matter decomposition and Fe geochemical changes following conversion to shrimp pond and pasture. A first SOC destabilization process involved the oxidation of organic matter in organomineral complexes containing Fe (Fecit). Thus, as organic matter decomposition proceeded in the converted areas, Fecit was progressively precipitated from the soil solution as crystalline Fe oxides (e.g. conversion to shrimp pond) or lost as Fe2+ with water transport (e.g. conversion to pasture).

Another critical process that triggered Fe geochemical changes was the oxidation of pyrite. There was a sharp decrease in pyritic Fe contents from pristine mangroves (mean pyritic Fe = 3.8 g kg⁻¹) to shrimp ponds (0.7 g kg⁻¹) and pasture (<0.01 g kg⁻¹; Fig S3). Pyrite is an easily weatherable mineral under the surface oxidizing conditions and an important precursor for Fe oxides formation in mangrove and other wetland soils41, as expressed in Eq. 1 and 2:

FeS2 + H2O + 7/2 O2 → Fe2+ + 2SO42- + 2H+ (1)

2Fe2+ + 1/2 O2 + 3H2O → 2FeOOH + 4H+ (2)

Typically, as O2 is introduced into soil solution, the reaction produces Fe2+ which is rapidly oxidized, resulting in the preferential neoformation of poorly crystalline oxides rather than crystalline ones42. This was observed in the mangrove soils where the high amounts of organic matter inhibit the formation of crystalline Fe oxides42,43, explaining the higher concentrations of Feasc (Fig. 4). On the other hand, upon mangrove removal, followed by SOC loss through decomposition, crystal nucleation and growth were probably facilitated, favoring the precipitation of Fe2+ as crystalline oxides, likely goethite41,42. This process also explains the observed increase in the Fcbd fraction in shrimp ponds (Fig. 4) where the geochemical conditions indicate favorable conditions to both the formation and stability of crystalline Fe oxides (i.e., pH values close to neutrality and Eh values >+100 mV)38. However, the formation of crystalline Fe oxides did not reverse the loss of Fe-bound OC (Fig. 5c), since these oxides are not as effective as organically complexed Fe and poorly crystalline oxides to immobilize organic matter21.

A similar outcome would, thus, be expected upon the conversion of mangrove forests to pasture; however, the highly oxidizing conditions resulted in further pyrite oxidation (Fig S3), leading to substantial soil acidification (Eq. 1 and 2). The soil pH of ~4.5 in the pasture (Fig. 3) is a record of the acid dissolution of poorly crystalline Fe oxides44 which led to Fe2+ loss with water transport. Although the pH measured was 4.5 at the time of sampling, it is possible that the pH was even lower during periods of pyrite oxidation, leading to more acidic conditions and, consequently, explaining the massive Fe losses (Fig. 4b).

The shifts in Fe oxides crystallinity, upon conversion to shrimp ponds, and the massive Fe losses, upon conversion to pasture, resulted in the destabilization of Fe-bound OC as less crystalline phases were either dissolved or transformed into more crystalline ones, which are less efficient in retaining SOC (Fig. 6).

Implications for future restoration efforts
Our data reveal a dynamic equilibrium between Fe and SOC that maintains a significant pool of a priori labile SOC fraction in pristine mangroves (approximately 8% of total SOC), which is highly susceptible to the geochemical changes promoted by LUC (Fig. 6). These processes have major implications for the restoration and carbon capture in mangrove forests under land use change.

The substantial Fe loss poses a challenge for restoring the overall biogeochemical functioning of these ecosystems. Despite efforts to accelerate forest recovery through reforestation, the re-establishment of the geochemical balance in mangrove soils may be a gradual process. The Fe dynamics in mangrove soils is influenced by the amount and quality of sediments deposited in estuaries22. While mangroves in the Amazon experience relatively high sedimentation rates of approximately 1.5±0.3 cm yr−1 cm45, it strongly outcompetes with equally high erosion rates resulting from anthropogenic impact46. Consequently, the natural replenishment of Fe in mangrove soils is likely to occur in the long-term.

Thus, current restoration approaches, focusing solely on reforestation, may not sufficiently address the geochemical restoration required to reestablish FeOMIs. Given the critical role of these interactions in protecting SOC, we advocate for broader restoration strategies that incorporate not only vegetation management but also interventions aimed at restoring the soil geochemical environment.

Methods
Study area and sampling
The study area is in North Brazil (Pará State) at the Mocajuba-Curuçá estuary (0°42'56“S, 47°54'1“W), east of the mouth of the Amazon River (Fig. 1). The regional climate is tropical monsoon (Am), according to the Köppen classification, with annual rainfall >3000 mm (Andrade et al., 2017). Local mangroves stands average 20 m in height, largely dominated by red (Rhizophora mangle) and black (Avicennia germinans) mangroves and subjected to a tidal range of 0.5–5 m. In the past decades, these mangroves have been experiencing anthropogenic pressure from shrimp farming and conversion to pastures8.

The sampling plots were distributed along the margin of the Furo do Maripanema river, encompassing pristine control mangrove forests and areas converted to shrimp ponds and pasture (Fig. 1). A total of 9 soil cores were collected, including samples from two pristine mangroves, three mangroves adjacent to shrimp ponds, three shrimp ponds, and one pasture (Fig. 1a and b). In each sampling plot, an undisturbed soil core was collected using a stainless-steel sampler for waterlogged soils. Samples were taken at the depths of 0–10, 10–20, 20–30, 30–50, and 80–100 cm. Oxygen-reduction potential (ORP) and pH were measured in the soil samples immediately after collection, using a HANNA HI98121 meter. Redox potential (Eh) was determined based on the reference calomel electrode, adjusted from the ORP platinum electrode by adding +244 mV.

Thereafter, the samples were carefully placed in hermetic sealed plastic bags and transported in thermal containers to ensure their preservation until storage at −20 °C. Subsequently, the frozen samples were transported to the laboratory, where they were stored at −20 °C until subjected to analyzes.

Physical fractionation of SOM
Size fractionation was carried out following a previous method47. Initially, wet soil samples equivalent to 20 g of dry mass were added to centrifuge tubes with 80 ml of deionized water. The vials underwent shaking for 1 hour at 120 rpm, centrifugation for 15 min at 3000 × g and the supernatant was discarded. This step aimed to eliminate soluble salts that could interfere with physical dispersion. Subsequently, the sample was transferred to glass vials, filled with 60 ml of deionized water, and ultrasonic dispersion was performed with an energy input of 350 J ml−1. The vials were surrounded by ice-cold water to avoid overheating during sonication. The resulting suspension was wet sieved through 2000–250, 250–53, and 53–20 μm. The particles retained on the sieves (i.e., all particles >20 μm) contained the particulate organic carbon (POC) fraction. These materials were collected, oven dried at 60 °C, ground and sieved (<150 μm) before organic carbon determination. The suspension containing the particles that passed through the 20 μm sieve were collected in a glass bowl, transferred to centrifuge tubes and subjected to centrifugation (6000 × g for 10 min) to isolate the <20 μm fraction, which contained the mineral-associated organic C (MAOC). This fraction was freeze-dried, ground, and sieved (<150 μm) before analyzes. Since none of the samples showed a reaction with 10% HCl, indicating no need for pre-treatment, they were directly subjected to elemental analyzes. All fractions, including bulk soil samples prior to fractionation, were analyzed for OC content using a Leco TruSpec CHN combustion elemental analyzer.

It is worth noting that this size fractionation method, despite the potential recovery of some fine POC in the <20 μm fraction, is widely accepted for effectively separating POC and MAOC, offering assertive interpretations regarding the ecological functioning of these operational fractions14,48,49. Importantly, this methodology ensures minimal impact on the sample’s chemical composition as no chemicals were added, thus preserving the nature of the organo-mineral associations.

Wet-chemical extractions for assessing FeOMI
The size fraction containing the MAOC underwent a sequential wet-chemical extraction for quantifying and characterizing FeOMI. This method is an adaptation from that developed by Lalonde et al., (2012). consists of sequential extractions with Na-citrate (Fecit), citrate-ascorbate (Feasc) and citrate-bicarbonate-dithionite (Fcbd).

We added 40 ml of solution to 0.50 g of freeze-dried and ground samples in 50 ml centrifuge tubes. The first extraction step was carried out with 0.2 M Na-citrate buffered with citric acid at pH 6.0 (Fecit). In this step, passive Fe is extracted by complexation with citrate, an efficient complexing agent that partially dissolves Fe from the surfaces of poorly crystalline Fe oxides44 and Fe from organo-mineral complexes50,51.

Subsequently, the residue underwent extraction with 0.2 M sodium citrate-0.05 M sodium ascorbate at pH 6.0 (Feasc). This step maintained citrate as a complexing agent and introduced ascorbic acid as a mildly reducing agent. Ascorbic acid reduces poorly crystalline Fe oxides but not crystalline ones, making this extraction specific to poorly crystalline Fe oxides such as ferrihydrite and lepidocrocite51.

For the Fcbd, the residue reacted with 0.27 M trisodium citrate, 0.11 M sodium bicarbonate, and 0.1 M sodium dithionite without heating52. This step was aimed at extracting the remaining Fe oxides, focusing specifically on crystalline Fe oxides such as hematite and goethite.

Control samples were extracted with NaCl at ionic strength equivalent to the “cbd” extraction as organic matter held in the exchange phase could desorb due to ionic strength effects19.

The extractions involved shaking at 160 rpm for 16 h at room temperature, with the residue rinsed with 30 ml of deionized water between each step. Supernatants were separated from the solid fraction through centrifugation at 3000 × g for 10 min and filtered through 0.45 μm glass fiber filters. The solid residue was then rinsed three times with 0.1 M NaCl to eliminate any residual organic reagent that could interfere with further analysis. The Fe content in the extracts was determined using an atomic absorption spectrometer (PerkinElmer 1100B), while the concentration of organic carbon associated with Fe (Fe-bound OC) was calculated accounting for mass losses after the sequential wet-chemical extractions, as in Eq. 3:

Fe-bound OC = (OCi × weighti - OCf × weightf) / OCi × weighti × 1,000 (3)

Where Fe-bound OC is expressed in g kg−1; OCi and OCf are the OC concentration, in %, in the sample before and after the extraction; weighti and weightf are sample weight, in g, before and after the extraction. The results were subtracted from that of the controls to yield the final Fe-bound OC values. We also expressed Fe-bound OC as the relative content in SOC (% SOC) and the ratio between OC and Fe extracted with cbd were expressed as OC:Fe in mol mol−1.

To assess the impact of freeze-drying on potential changes in Fe oxide crystallinity and their extractability, we conducted a control experiment in which both freeze-dried and moist samples were subjected to the same extractions. The same extractions were performed on bulk samples (i.e., without any physical fractionation). There were only small differences in Fe extraction yields, with notable variations observed only in the pasture samples, where Fe-citrate and Fe-citrate-bicarbonate-dithionite were generally higher in moist samples. However, the proportion of Fe extracted across fractions between freeze-dried and moist samples remained very similar. Thus, no significant effect of Fe remobilization was detected across the different Fe fractions. See Tables S3 and S4 for further details.

Another experiment was conducted using subsamples of the MAOC fraction from one of the studied pristine mangroves (00°45'24“S 47°57'19“W) at the depths of 0−10, 40–50 and 80−100 cm, in duplicate, to further investigate the mechanism underlying FeOMI. In this case, the subsamples were analyzed after each step of the sequential extraction (see the scheme in Fig S1). Besides the determination of Fe concentration and Fe-bound OC, the samples were also analyzed for total nitrogen TN. Additionally, composite samples (from the duplicates) underwent infrared and thermal analyzes.

Wet chemical extractions in bulk samples
To estimate the concentrations of reactive Fe—iron phases that are reductively dissolved by sodium dithionite19—and pyritic Fe, we performed a sequential wet chemical extraction on moist bulk samples. The method is adapted from previous methods53,54. The procedure involved adding 30 ml of 0.25 mol L−1 sodium citrate + 0.11 mol L−1 of sodium bicarbonate and 1 g of sodium dithionite to 2 g of sample. The mixture was stirred for 30 min at 75 °C to extract the reactive Fe. Following this, silicate-associated Fe was removed by stirring the sample with 30 mL of 10 mol L−1 HF for 16 hours, and the organic phase was removed by stirring with 10 mL of concentrated H2SO4 for 2 hours. Finally, the pyritic Fe was extracted by stirring the samples with 10 mL of concentrated HNO3 for 2 h at room temperature. The samples were rinsed between each extraction, and the supernatant was collected for Fe determination using atomic absorption spectroscopy (AAS).

Infrared spectroscopy
The samples used in the additional sequential extraction experiment were analyzed through transmission Fourier transform infrared spectroscopy (FTIR) using a Shimadzu FTIR Prestige-21 with a DLATGS detector. The sample was analyzed as KBr pellets and spectra were obtained from 4000 to 400 cm−1 at a resolution of 1 cm−1. Each sample was scanned 64 times and averaged to generate the final spectrum. The spectra were baseline corrected, normalized (min-max) and peak area of the regions of interest were calculated without smoothing. The spectra were subsequently smoothed for improved visual presentation using the Savitzky-Golay method with a quadratic function and 11 data points. All these procedures were done using the Orange 3.36 software. Organic functional group assignments were based on the literature55.

We used the ratio of aliphatic C-H (2985-2830 cm−1) relative to COO- (1440−1390 cm−1) to assess the degree of organic matter decomposition. A decrease in this ratio may reflect increased microbial oxidation and/or decreased plant contribution. This approach follows the same rationale as that of 25,56,57. However, we used the COO- (1440−1390 cm−1) instead of C=O (1760−1550 cm−1), as the latter overlaps with alkenyl (1680–1620 cm−1) and aromatic ring (1615–1580 cm−1) stretches and the region is strongly influenced by mineral interference58, especially considering that we analyzed the MAOC fraction.

Thermal analysis
The same samples used in FTIR analysis were subjected to Thermogravimetric analysis (TG) and differential scanning calorimetry (DSC) to evaluate the thermal stability of MAOC and Fe-bound OC. The thermograms were collected using a Discovery SDT 650 analyzer (TA instruments), under a dry synthetic-air atmosphere consisting of 80% N2 + 20% O2, with a flow rate of 50 mL min−1. The samples were heated from 25 to 100 °C, held isothermally until mass equilibration, then heated to 600 °C at a rate of 10 °C min−1. This approach is often used as a proxy to assess the stability of the organic matter associated with minerals59,60.

An inflection in the raw DSC thermogram was observed near 210 °C, suggesting a shift from endothermic water loss to exothermic organic matter oxidation27. Additionally, the strong inflection around 480 °C indicated the transition from organic matter oxidation to the dihydroxylation of kaolinite (the main clay mineral in the studied soils as confirmed by FTIR analysis, see Fig S4), which occurs around 500 °C61. Thus, these two regions were set as baseline points for organic matter oxidation.

We integrated the DSC heat flux, in mW mg−1, to obtain the total exothermic content, in mJ mg−1, over the exothermic region 210-480 °C. From the total exothermic content, two parameters were derived: the temperature at which half of the total exothermic energy had been released (DSC-T50) and the energy density (ED), in J mg−1 OC. The latter was obtained by dividing the total exothermic content by the OC concentration in (%). All the procedures were made using the Origin 2022b software.

Statistical analysis
To analyze the variation in measured parameters, including iron and carbon fractions, Eh, and pH, we applied Permutational Multivariate Analysis of Variance (PERMANOVA) using the adonis2 function from the vegan package in R. Euclidean distance matrices were computed for each variable, and PERMANOVA was performed to evaluate the effects of site (pristine mangroves, mangroves adjacent to shrimp ponds, shrimp ponds, and pasture) and depth. Site was treated as a fixed factor, while depth was nested within site. The analysis was based on 999 permutations, followed by pairwise comparisons between sites with Bonferroni correction for multiple comparisons. The complete results are available in the “Extended_data” file. Additionally, we performed linear regressions to explore relationships between parameters obtained from TG-DSC, FTIR analyzes, and C:N ratio.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of submitted paper\nTitle: Iron’s role in soil organic carbon (de)stabilization in mangroves under land use change\nAuthors: F. Ruiz, A. Fraga Bernardino, H. Melo Queiroz, X. Luis Otero, C. Rumpel, T. Osório Ferreira\nGeneral comments\nThe authors submitted a manuscript describing the role of iron in the cycling of organic carbon in Brazilian mangroves and\nthe effect of land use change (LUC) on these interactions. They find that LUC leads to large differences in Fe concentrations,\nin the crystallinity of Fe minerals, and in the amount of OC associated with the different fractions of Fe amorphous or\ncrystalline precipitates.\nThis is a solid overall paper, well written and easy to understand even for the non-specialist. I do not have any major\nconcerns therefore this review is short and amounts to a series of minor comments and requests for changes detailed in the\nSpecific Comments section below. The data appears solid, although I feel that the reason(s) for some of the most variable\nresults (high standard deviations) should be explained. The topic is interesting and the experimental design solid, although I\nwould have liked to see more than just one pasture sample being analyzed (the authors should comment on the\nrepresentativity of this single core with respect to other lands converted from mangrove to pasture.\nThe only important concern that I have is linked to the sample preparation prior to the sequential extraction scheme: freeze-\ndrying is known to significantly affect the crystallinity of amorphous and poorly crystalline minerals. The authors have not\naddressed, and should be addressing this point as explained in comment #21 below.\nI recommend publishing this manuscript but only after minor corrections.\nSpecific comments\n1. Abstract, line 7: The result mentioned here is not contrary to prevailing assumptions.\n2. Lines 105-111: The authors should briefly mention the advantages and disadvantages of using thermal resistance as a\nproxy for biological lability in addition to referring to the papers of Plante and al.\n3. Lines 116-119: The increase in stability makes total sense if we assume, as the authors do, that the Fe-associated OM\nfraction is more labile than the non-Fe-associated fraction, as has been shown several times in the past. If the more labile\nFe-associated OM is removed from the total sample, then the residual, non-Fe-associated fraction will appear more\nrefractory, as seen here (and as suggested on lines 129-131).\n4. Lines 134: What “strong correlation”? Figure S2 shows the graphical results from a PCA analysis. Please explain.\n5. Lines 148-151: The OC:Fe ratio is not a reliable clue for the type of interactions between iron (oxyhydr)oxides and OC, as\nexplained in Barber et al. (2017), because a fraction of reducible Fe is found unassociated with OC.\n6. Lines 158-165: This is an elegant way of demonstrating what was already assumed (that OC associated predominantly\nwith amorphous iron (oxyhydr)oxides).\n7. Lines 174-176: There seems to be a slight shift towards more oxidizing conditions indeed, but is this shift significant?\nPlease provide the statistical support for this claim (or lack of support). Given the spread of the data, their overlap also, it is\ndifficult to say whether this shift is statistically significant.\n8. Line 187: What do these average and standard deviation correspond to? All datapoints for the pristine mangrove and\nmangrove adjacent to the shrimp ponds? Please explain.\n9. Lines 187 and 188: Please provide an explanation and a standard deviation for the values for the shrimp ponds and the\npasture.\n10. Lines 190-191: The first two values are not significantly different given the very large standard deviation for the shrimp\nponds. Also, please provide a standard deviation for the pasture sample (again, it is a depth-average average, not a single\ndatapoint).\n11. Figure 4a: How do you explain the very high standard deviations found for the shrimp pond samples at each depth?\nAlso, how do you explain the variations between different depths, also for the shrimp pond? You report a 6-fold decrease in\nFe-citrate concentration between the 30-40 cm layer and the 40-50 cm layer – a huge decrease for two adjacent layers.\n12. Figure 4b: Please add the standard deviations for the pasture sample since the values are depth-averaged.\n13. Lines 207-208: Except for the pasture sample – please specify.\n14. Line 219: Again, please add the standard deviation for the pasture sample here and in Figure 5c.\n15. Lines 259-260: This is entirely speculative as there is no data in this work that suggests oxidation of pyrite, aside from a\ndecrease in pH that could have different causes. Please indicate that this is a speculative explanation in the text.\n16. Line 260: The soil pH is between 4 and 6, with an average of about 5, which is one order of magnitude higher in H+\nconcentration compared to what is written in the paper (which is misleading). On Figure 3, all but one or two datapoints fall\ninto the Fe¬2O3 stability zone rather than the Fe2+ stability zone of the Pourbaix diagram. The pH is probably a little too\nhigh for this explanation to be the only reason for the Fe losses. Can you think of an alternative explanation?\n17. Line 288: This is a high sedimentation rate! Iron being a predominant element in soils of Amazonia (laterite soils), the\nparticles carried by rivers must be enriched in this element, and therefore replenishing the soils’ Fe content following\nremediation should not be a lengthy process. While the concluding remarks on lines 288-297 are true to some extent, they\npaint a darker picture than what the reality probably is. Maybe this should be mentioned?\n18. Line 304: Please explain what “Am” means.\n19. Lines 333-334: This is not clear. The material retained on which one of the sieves? The first one only? Please be more\nexplicit.\n20. Lines 337-338: Please provide the details for the centrifugation step.\n21. Line 339: Freeze-drying changes the crystallinity of iron (oxyhydr)oxides, and thus its extractability with the different\ncomplexation or reducing agents used in this work. Have you run any before/after freeze-drying controls? How do you know\nthen whether the data obtained after freeze-drying the samples is representative of the in situ samples? Please address this\npoint carefully as it could have led to significant changes in the distribution of OC among the different Fe fractions.\n22. Lines 352-373: Please provide the volumes used for the extractions. Also, how did you ascertain that the complexation\ncapacity of Na-citrate at 0.2 M was not surpassed since the initial mass of sediment sieved was 20 g ? The same is true for\nthe other extractions as well (complexation capacity and reduction capacity for ascorbate and dithionite).\n23. Lines 402-411: Please explain how the samples were prepared for FTIR analysis since the absolute peak intensities are\ncompared between samples. Surely there must have been some sort of normalization? Lower intensities could simply mean\nless abundant organic matter in the OM-KBr mix rather that a lower relative abundance of a given functional group.\n24. Table S1, Fe concentration column: The data should have the same number of decimal points throughout. The number\nin the second decimal point should be placed in subscript to indicate that it is indicative only rather than significant.\n25. Figure S2: More explanation about what we are seeing on this PCA graph should be given in the figure caption.", "reviewer_2": "The research presented by Ruiz et al. investigates the role of Fe in SOC (De)stabilization in mangrove forests under LUC. The research is of environmental relevance, however does not add significantly to the existing literature. It is a good study, but in my opinion does not meet the novelty criteria to be published in Nature Communications. I wish you all the best to the team and look forward to reading more about this research in future.", "reviewer_3": "This manuscript investigates the impact of iron-mediated organic-mineral interactions (FeOMI) on the stabilization of soil\norganic carbon (SOC) in Amazon mangrove soils and explores how land use change (LUC) affects this process. The study\ncomprehensively and systematically analyzes the role of iron in the mineral association of organic carbon from multiple\nperspectives, including physical fractionation, chemical composition, and thermal stability. This work has a profound guiding\nsignificance for the exploration SOC stability in mangroves and the protection of soil carbon under land use change.\nHowever, the manuscript still presents numerous issues in terms of overall text composition, figure and table presentation,\nand results analysis.\nMy first concern is that the massive loss of SOC due to LUC was not supported by the mechanism of FeOMI, as proposed by\nthe authors. Conversion of mangroves to shrimp pond and pasture resulted in substantial loss of SOC, especially for the\nMAOC fractions. Although loss of Fe-bound OC might be important in mangrove ecosystem, it’s not sufficient to explain the\ncontribution of FeOMI in loss of MAOC. Providing direct evidence that crystalline iron retains less soil organic carbon would\nstrongly support the authors' viewpoint.\nI agree with first result regarding the critical role of FeOMI in mangrove soils and the explanation that iron binds more labile\ncarbon. However, the evidence for the conclusion that Fe oxides protects more labile SOC fractions was not sufficient. It is\nplausible that Fe oxides affinity for more thermally labile and oxidized organic compounds. But it can also not exclude the\nexplanation that catalytic effect of Fe oxides on organic matter oxidation during thermal analysis. In addition, thermally labile\nOC is not equivalent to labile SOC fraction. It’s better to provide direct evidence that how Fe oxides protect POC and MAOC.\nIn the introduction, it is necessary to briefly describe the important role of mineral protection mechanisms in the stabilization\nof soil organic carbon in mangroves. The relationship between the forms of iron, or their crystallinity, and soil organic carbon\nshould be clearly introduced. Additionally, hypotheses about the impact of land use change on iron and the iron-OM bound\nrelationship should be reviewed with published literature.\nTable S1, which is a key result, is somewhat difficult to understand. The parameters displayed in the table need clarification.\nIt appears that some indicators refer to the extracted portion while others refer to the residual portion. This should be more\nclearly indicated in the table explanation.\nThe discussion on the environmental implications does not seem to independent part. This part does not present any new\nfindings or conclusions. I do not understand what the authors intend to express about the role of the environment in carbon\nsequrestration in mangroves and the iron-OC binding relationship under LUC. Additionally, it is unclear what is meant by\n\"environment\". Supplementing this section with specific facts and relevant data would make it more compelling.\nThere also some other minor errors in the text and figures, such as the lack of a b annotation in Fig.2, and the Table 1\nmentioned in L133 is Table S1. I recommend that the authors thoroughly review the entire text to avoid these errors which\neasily make reader confusing."}, "author_response": "Author’s response to the reviewers\nReviewer #1:\nThe data appears solid, although I feel that the reason(s) for some of the most variable results (high\nstandard deviations) should be explained.\nAuthors’ response:\nWe appreciate the reviewer’s observation and the opportunity to clarify this point. The high standard\ndeviations observed in the studied soils can be attributed to natural spatial variability. This is especially true for\nredox-sensitive elements like Fe, where variability is expected even over small sampling distances, both\nvertically and horizontally, in mangrove soils (Otero et al., 2006). Mangroves are highly dynamic systems, and\nseveral factors—including root density, bioturbation, and tidal oscillation—can increase the variability in the\ndata (Araújo Júnior et al., 2016; Otero et al., 2006).\nImportantly, despite the high standard deviations, our statistical analyses revealed significant\ndifferences between the mangrove sites and the converted areas. This finding reinforces the robustness of our\nresults, as the reviewer noted. To further support this, we have included the complete PERMANOVA test\noutputs for all measured variables in the “Extended_data” file.\nReviewer #1:\nThe topic is interesting and the experimental design solid, although I would have liked to see more\nthan just one pasture sample being analyzed (the authors should comment on the representativity of this\nsingle core with respect to other lands converted from mangrove to pasture.\nAuthors’ response:\nThank you for your constructive feedback. We carefully selected this core to ensure it was\nrepresentative of the broader area of mangrove-converted pastures. Previous work by Bernardino et al. (2024)\ndemonstrated minimal variability in SOC (%) within this pasture area, with SOC values ranging from 0.14 ±\n0.04 to 0.32 ± 0.09 within the first meter (n = 6). Our measured SOC values fall within this range, indicating\nthat the core we analyzed is indeed representative of the larger pasture area.\nAlthough data on mangrove conversion to pasture in the Amazon is still limited, the observed relative\nloss of SOC following mangrove conversion to pasture aligns with findings from other regions, where losses\nare typically in the range of 80-90% (Boone Kauffman et al., 2017; Kauffman et al., 2016). Unfortunately,\ndata on Fe geochemistry and Fe-bound OC is currently lacking, as, to the best of our knowledge, no studies\nhave yet been conducted in this regard. This gap further highlights the originality and importance of the present\nwork.\nWe included a comment on this in lines 230-236.\nReviewer #1:\nThe only important concern that I have is linked to the sample preparation prior to the sequential\nextraction scheme: freeze-drying is known to significantly affect the crystallinity of amorphous and poorly\ncrystalline minerals. The authors have not addressed, and should be addressing this point as explained in\ncomment #21 below.\nAuthors’ response:\nThank you for highlighting this important issue. We acknowledge the potential impact of freeze-drying\non the crystallinity of amorphous and poorly crystalline minerals, which could indeed influence the distribution\nof Fe fractions and associated organic carbon (OC).\nOur method was adapted from Lalonde et al. (2012), which specifically quantifies the OC associated\nwith reactive Fe in marine and coastal sediments. Lalonde’s protocol includes a freeze-drying step, thus, by\nusing this method, we ensure that our results are comparable to previously published data, which is crucial for\nconsistency and comparability across studies.\nThe freeze-drying step was particularly critical in our study because we conducted physical\nfractionation prior to the wet chemical extractions. Thus, it allowed to weight the different size fraction and\ncorrectly quantify the POC and MAOC. Moreover, sample homogenization is essential for the wet chemical\nextraction steps. Without freeze-drying, the samples would have been difficult to homogenize due to\nsedimentation during centrifugation, which could lead to uneven distribution of materials with different\ndensities. This would have compromised the accuracy of our fractionation and subsequent analyses.\nHowever, we recognize the reviewer's concern regarding the possible alteration of Fe fractions due\nto freeze-drying. To address this, we conducted a control experiment comparing moist and freeze-dried bulk\nsamples (without physical fractionation).\nThere were insignificant differences in Fe extraction yields, with notable variations observed only in\nthe pasture samples, where Fe-citrate and Fe-citrate-bicarbonate-dithionite were generally higher in moist\nsamples. However, the proportion of Fe extracted across fractions between freeze-dried and moist samples\nremained very similar. Thus, no significant effect of Fe remobilization was detected across the different Fe\nfractions. Even in the pasture samples, where larger differences were observed, the absolute Fe yield was too\nlow to affect the overall conclusions. See Tables S3 and S4 for further details.\nWe have included this information in lines 426-435.\nReviewer #1:\n1. Abstract, line 7: The result mentioned here is not contrary to prevailing assumptions.\nAuthors’ response:\nWe thank the reviewer’s attention to this detail. To clarify our intended message, we have revised the\nsentence to better convey our findings.\nLines 6-8: “Our results indicate that Fe protects more labile SOC fractions, otherwise vulnerable to\nbiological degradation”.\nReviewer #1: 2. Lines 105-111: The authors should briefly mention the advantages and\ndisadvantages of using thermal resistance as a proxy for biological lability in addition to referring to the papers\nof Plante and al.\nAuthors’ response:\nWe appreciate the reviewer’s suggestion to discuss the advantages and disadvantages of using\nthermal resistance as a proxy for biological lability. In the revised manuscript, we have added a more\ncomprehensive discussion that also addresses the inquiry from reviewer #3:\nLines 122-149: “The increased thermal resistance of the remaining OC suggests that Fe binds to\nthermally and (likely) biologically labile OC. This aligns with the “bioenergetic framework” (Williams et al.,\n2018; Williams and Plante, 2018) and the current paradigm of soil organic matter persistence (Lehmann et\nal., 2020; Lehmann and Kleber, 2015; Schmidt et al., 2011). These perspectives suggest that soil organic\nmatter exists as a continuum, processed by the decomposer community from large biopolymers to small\nmonomers. Depolymerization and oxidation of larger organic molecules solubilize smaller ones, which make\nthem more accessible for microbial uptake if the dissolved organic matter is readily available (Lehmann et\nal., 2020). On the other hand, oxidation enhances chemical reactivity of organic compounds by reducing molecular\nsize, increasing polarity, and thus increasing chemical reactivity (Kleber et al., 2015). This is crucial for the\nformation of organomineral interactions, especially those with Fe oxides, which involve ligand exchange\nreactions with oxygen-bearing organic functional groups (Chen et al., 2014; Gu et al., 1995).\nWhen compared to POC, MAOC has lower thermal stability, reflected by lower ED and lower activation\nenergy, the latter positively correlated with DSC-T (Williams et al., 2018; Williams and Plante, 2018). This is\n50\nbecause MAOC is composed of easily metabolizable organic molecules with low thermodynamic stability\n(Williams et al., 2018; Williams & Plante, 2018). Thus, a decrease in thermal stability is expected as SOC\ndecomposition progresses, with larger plant biopolymers being processed into smaller and simple molecules\n(Barré et al., 2016). However, variations in stability within MAOC fractions also exists, depending on its\nchemical composition (Nguyen et al., 2019).\nHere we observed a positive correlation between DSC-T and the CH:COO- ratio (Fig 2a), meaning\n50\nthat as the CH:COO- ratio increases (i.e., Fe-bound OC is removed), the remaining MAOC becomes more\nthermally resistant. Similarly, there was an increase in the C:N ratio with Fe-bound OC removal (Fig 2b). These\npatterns indicate that Fe-bound OC is more oxidized and degraded, less thermally stable and less energetic\nthan the residual MAOC. Thus, our data show that Fe phases play a key role in protecting a relatively labile\nSOC fraction in mangrove soils.”\nWe hope this explanation clarifies our rationale.\nReviewer #1:\n3. Lines 116-119: The increase in stability makes total sense if we assume, as the authors do, that\nthe Fe-associated OM fraction is more labile than the non-Fe-associated fraction, as has been shown several\ntimes in the past. If the more labile Fe-associated OM is removed from the total sample, then the residual,\nnon-Fe-associated fraction will appear more refractory, as seen here (and as suggested on lines 129-131).\nAuthors’ response:\nWe appreciate this comment.\nReviewer #1:\n4. Lines 134: What “strong correlation”? Figure S2 shows the graphical results from a PCA analysis.\nPlease explain.\nAuthors’ response:\nTo clarify, we have now included linear regression analyses in the main material to demonstrate the\nstrong correlation mentioned. Please check Fig 2.\nReviewer #1: 5. Lines 148-151: The OC:Fe ratio is not a reliable clue for the type of interactions\nbetween iron (oxyhydr)oxides and OC, as explained in Barber et al. (2017), because a fraction of reducible\nFe is found unassociated with OC.\nAuthors’ response:\nWe appreciate your comment and for raising this important discussion. Indeed, as highlighted by\nBarber et al. (2017), a portion of reducible Fe is not directly associated with OC. Consequently, we have\nrevised our manuscript to remove the inference about the nature of this association. Nevertheless, the OC:Fe\nratio remains a useful proxy for understanding the affinity of Fe phases with OC, and our findings are consistent\nwith the existing literature. Specifically, data suggest that associations with poorly crystalline Fe oxides generally\nexhibit higher OC:Fe ratios compared to those with crystalline Fe oxides (Chen et al., 2014; Wagai & Mayer,\n2007), which supports our results. We have updated the manuscript text to address this point more clearly\n(see lines 171-181).\nReviewer #1:\n6. Lines 158-165: This is an elegant way of demonstrating what was already assumed (that OC\nassociated predominantly with amorphous iron (oxyhydr)oxides).\nAuthors’ response:\nWe appreciate the reviewer’s comment.\nReviewer #1:\n7. Lines 174-176: There seems to be a slight shift towards more oxidizing conditions indeed, but is\nthis shift significant? Please provide the statistical support for this claim (or lack of support). Given the spread\nof the data, their overlap also, it is difficult to say whether this shift is statistically significant.\nAuthors’ response:\nWe have performed PERMANOVA tests with the data. The results show that all areas differ regarding\nEh, except Mangroves pristine and Mangroves adjacent to shrimp ponds. As to pH, only pasture differ from\nthe mangroves.\nReviewer #1:\n8. Line 187: What do these average and standard deviation correspond to? All datapoints for the\npristine mangrove and mangrove adjacent to the shrimp ponds? Please explain.\nAuthors’ response:\nWe appreciate the opportunity to clarify this point. We have indicated more clearly our results. Please\nsee lines 203-213. We have also added the summary statistics of all measured variables as well as the\nPERMANOVA results in the “Extended data” file.\nReviewer #1:\n9. Lines 187 and 188: Please provide an explanation and a standard deviation for the values for the\nshrimp ponds and the pasture.\nAuthors’ response:\nWe thank the reviewer’s comment. We have responded to this inquiry above. The revised text was\nadded to lines 203-213.\nReviewer #1:\n10. Lines 190-191: The first two values are not significantly different given the very large standard\ndeviation for the shrimp ponds. Also, please provide a standard deviation for the pasture sample (again, it is a\ndepth-average average, not a single datapoint).\nAuthors’ response:\nWe thank the reviewer for the attention to this point. Indeed, the difference between the pristine\nMangrove and shrimp pond was not significant (p-value = 0.42) due to the large variation in Shrimp pond.\nWe included the standard deviation for pasture. Please note that the values reported are depth-averaged.\nReviewer #1:\n11. Figure 4a: How do you explain the very high standard deviations found for the shrimp pond\nsamples at each depth? Also, how do you explain the variations between different depths, also for the shrimp\npond? You report a 6-fold decrease in Fe-citrate concentration between the 30-40 cm layer and the 40-50\ncm layer – a huge decrease for two adjacent layers.\nAuthors’ response:\nWe acknowledge the reviewer’s inquiry. The high standard deviations observed in the shrimp pond\nsamples at each depth are likely due to the drainage and refilling activities associated with shrimp pond\nmanagement, as well as the death of roots due to deforestation and consequently impacting on soil aeration.\nThese factors likely caused Fe segregation, leading to variability in Fe concentrations across different depths.\ncbd\nThis also explains the significant decrease in Fe concentration between the 30-40 cm and 40-50 cm layers,\ncbd\nwhich is attributed to the heterogeneous distribution of Fe due to these disturbances. Despite these variations,\nour analysis highlights a very clear trend towards higher concentrations of Fe in shrimp ponds. We have\ncbd\nupdated the manuscript (lines 209-217) to better reflect these observations and clarify the depth-related\nvariations.\nReviewer #1:\n12. Figure 4b: Please add the standard deviations for the pasture sample since the values are depth-\naveraged.\nAuthors’ response:\nWe have added the s.d. as suggested.\nReviewer #1:\n13. Lines 207-208: Except for the pasture sample – please specify.\nAuthors’ response:\nWe thank the attention to detail. We have revised the text as suggested.\nReviewer #1:\n14. Line 219: Again, please add the standard deviation for the pasture sample here and in Figure 5c.\nAuthors’ response:\nWe have added the s.d. as suggested. Please note that we have now reported the results as % of\nSOC, in place of % MAOC, to better depict the precise proportion of Fe-bound OC in the soils.\nReviewer #1:\n15. Lines 259-260: This is entirely speculative as there is no data in this work that suggests oxidation\nof pyrite, aside from a decrease in pH that could have different causes. Please indicate that this is a speculative\nexplanation in the text.\nAuthors’ response:\nWe appreciate the reviewer’s comment. To properly address this inquiry, we have performed further\nwet-chemical extractions on bulk samples that confirm our claim. The results are available in the Supplementary\nmaterial (Fig S3). In fact, there was a sharp decrease in pyritic-Fe, as we hypothesized. We have mentioned\nthe results in lines 263-264 and described the method in lines 444-457.\nReviewer #1:\n16. Line 260: The soil pH is between 4 and 6, with an average of about 5, which is one order of\nmagnitude higher in H+ concentration compared to what is written in the paper (which is misleading). On\nFigure 3, all but one or two datapoints fall into the Fe O stability zone rather than the Fe2+ stability zone of\n2 3\nthe Pourbaix diagram. The pH is probably a little too high for this explanation to be the only reason for the Fe\nlosses. Can you think of an alternative explanation?\nAuthors’ response:\nThank you for your comment. The mean pH in the pasture soil was 4.5, which is 1.5–2 units lower\nthan typical mangrove soils, as indicated in the data shared on Figshare (doi:\n10.6084/m9.figshare.27111262). This lower pH is likely due to pyrite oxidation, a process known to\nsignificantly acidify soils.\nAlthough the pH measured at the time of sampling was 4.5, it is possible that pH levels were lower\nduring periods of active pyrite oxidation, resulting in more acidic conditions and potentially greater Fe losses.\nAcidic dissolution of iron oxides under these conditions could explain the Fe depletion observed, even though\nthe pH was somewhat higher during the time of measurement.\nPrevious study have shown that a pH of 4.7 is sufficient to cause substantial Fe dissolution from iron\noxides in environments subject to redox oscillations (Ferreira et al., 2022). Furthermore, while the Pourbaix\ndiagram serves as a useful reference for understanding these processes, it is important to note that the\nboundaries of stability fields for Fe oxides are not sharp. Rather, transitions are gradual, meaning that processes\nsuch as Fe dissolution can still occur near the stability zones.\nWe have updated the text in lines 290-295.\nReviewer #1:\n17. Line 288: This is a high sedimentation rate! Iron being a predominant element in soils of\nAmazonia (laterite soils), the particles carried by rivers must be enriched in this element, and therefore\nreplenishing the soils’ Fe content following remediation should not be a lengthy process. While the concluding\nremarks on lines 288-297 are true to some extent, they paint a darker picture than what the reality probably\nis. Maybe this should be mentioned?\nAuthors’ response:\nWe appreciate the reviewer’s observations and acknowledge the concerns raised about our\ninterpretation of sedimentation rates and Fe replenishment in mangrove soils. We have revised the manuscript\nto reflect these considerations and provide a more nuanced discussion of the challenges and potential for Fe\nreplenishment in the context of mangrove restoration.\nHowever, it is important to emphasize that the Fe content in the studied mangrove soils, as well as\nin the sediments reaching these mangroves, is low. This is primarily due to the geological characteristics of the\nBarreiras Formation in which the surrounding upland soils are developed. These soils are tipically highly\nweathered, with kaolinite as the dominant clay mineral and only minor amounts of Fe and Al oxides (Melo et\nal., 2001). As a result, the mangrove soils in this region are also naturally low in Fe content (Andrade et al.,\n2018).\nPlease refer to the updated text in lines 309-328 for further details.\nReviewer #1:\n18. Line 304: Please explain what “Am” means.\nAuthors’ response:\nThe regional climate is tropical monsoon (Am), according to the Köppen classification. We have\nclarified this in the text (line 355).\nReviewer #1\n19. Lines 333-334: This is not clear. The material retained on which one of the sieves? The first one\nonly? Please be more explicit.\nAuthors’ response:\nWe have clarified this point in the manuscript. All the particles retained in the sieves, i.e., particles >\n20 um) were collected and taken as POC, while the particles that passed through the 20 um sieve were\nconsidered as MAOC. Please see lines 365-367.\nReviewer #1\n20. Lines 337-338: Please provide the details for the centrifugation step.\nAuthors’ response:\nWe appreciate the opportunity to clarify this point. The suspensions were centrifuged at 6,000 x g\nfor 10 minutes. We have added this information in line 370.\nReviewer #1\n21. Line 339: Freeze-drying changes the crystallinity of iron (oxyhydr)oxides, and thus its\nextractability with the different complexation or reducing agents used in this work. Have you run any\nbefore/after freeze-drying controls? How do you know then whether the data obtained after freeze-drying the\nsamples is representative of the in situ samples? Please address this point carefully as it could have led to\nsignificant changes in the distribution of OC among the different Fe fractions.\nAuthors’ response:\nWe thank the reviewer again for raising this concern. We have addressed this inquiry in detail in a\nprevious response. Please, see lines 426-435 and Tables S3 and S4.\nReviewer #1:\n22. Lines 352-373: Please provide the volumes used for the extractions. Also, how did you ascertain\nthat the complexation capacity of Na-citrate at 0.2 M was not surpassed since the initial mass of sediment\nsieved was 20 g ? The same is true for the other extractions as well (complexation capacity and reduction\ncapacity for ascorbate and dithionite).\nAuthors’ response:\nWe appreciate the reviewer’s suggestion and have added further details to the procedure. The\nextraction process involved sequential treatments with Na-citrate (Fe ), citrate-ascorbate (Fe ), and citrate-\ncit asc\nbicarbonate dithionite (Fe ). Specifically, 40 ml of each solution was added to 0.50 g of freeze-dried, ground\ncbd\nsamples in 50 ml centrifuge tubes. The volume:sample ratio of 80:1 is deemed sufficient for the complete\nextraction of Fe phases (Lalonde et al., 2012). We have included these details in lines 388-391.\nReviewer #1:\n23. Lines 402-411: Please explain how the samples were prepared for FTIR analysis since the\nabsolute peak intensities are compared between samples. Surely there must have been some sort of\nnormalization? Lower intensities could simply mean less abundant organic matter in the OM-KBr mix rather\nthat a lower relative abundance of a given functional group.\nAuthors’ response:\nWe appreciate the opportunity to give more details regarding the FTIR treatments. The sample was\nanalyzed as KBr pellets and spectra were obtained from 4000 to 400 cm -1 at a resolution of 1 cm -1. Each\nsample was scanned 64 times and averaged to generate the final spectrum. The spectra were baseline\ncorrected, normalized (min-max) and peak area of the regions of interest were calculated without smoothing.\nThe spectra were subsequently smoothed for improved visual presentation using the Savitzky-Golay method\nwith a quadratic function and 11 data points. All these procedures were done using the Orange 3.36 software.\nThis description is found in lines 461-468.\nReviewer #1\n24. Table S1, Fe concentration column: The data should have the same number of decimal points\nthroughout. The number in the second decimal point should be placed in subscript to indicate that it is indicative\nonly rather than significant.\nAuthors’ response:\nWe thank the reviewer’s attention to this. We have added the second decimal number to the Fe\nresults.\nReviewer #1\n25. Figure S2: More explanation about what we are seeing on this PCA graph should be given in the\nfigure caption.\nAuthors’ response:\nWe appreciate this suggestion We chose to show the linear regressions between the variables of\ninterest instead of using the PCA. We believe that this more clearly illustrate our point. Please refer to Fig 2\nin the main file.\nWe sincerely thank the reviewer for this positive feedback on our manuscript. We are pleased to hear\nthat the paper was found to be well-written and accessible to a broader audience. We have carefully addressed\nall the points raised and appreciate the time and effort taken to review our work. We hope the revisions now\nmeet the reviewer's expectations.\nReviewer #2: The research presented by Ruiz et al. investigates the role of Fe in SOC\n(De)stabilization in mangrove forests under LUC. The research is of environmental relevance, however does\nnot add significantly to the existing literature. It is a good study, but in my opinion does not meet the\nnovelty criteria to be published in Nature Communications. I wish you all the best to the team and look forward to\nreading more about this research in future.\nAuthors’ response:\nWe appreciate the reviewer’s feedback and the recognition of our research’s environmental relevance.\nWhile we value the reviewer’s perspective, we respectfully disagree with the assessment regarding the novelty\nof our work. We would like to highlight key aspects that we believe significantly advance the current\nunderstanding of SOC dynamics in mangrove ecosystems.\nOriginal Contribution to Fe mediated Interactions (FeOMIs) in Mangrove Soils: While the role of Fe\nin stabilizing SOC has been explored in terrestrial ecosystems, our study is the first to examine these dynamics\nspecifically in mangrove soils. To the best of our knowledge only two previous studies assessed Fe-bound OC\nbut it was restricted to quantify this pool (Assavapanuvat et al., 2024; Dicen et al., 2019), and did not assess\nits nature and significance for SOC stabilization. Moreover, the biogeochemical interactions between Fe and\nSOC in Amozonian mangroves, especially under LUC scenarios like conversion to shrimp ponds or pastures,\nremain poorly understood. Our findings on FeOMIs in these environments address this significant knowledge\ngap, suggesting new pathways for SOC (de)stabilization that have not been previously reported.\nNovelty in methodological approach: Our work employs a combination of wet chemical extractions,\nthermal (TG-DSC) analysis, and spectroscopy (FTIR) analysis to investigate Fe-SOC interactions. This\napproach is not restricted to mangrove soils and can be replicated to upland soils, offering a deeper\nunderstanding of the different organomineral interactions that govern SOC persistence across diverse\necosystems.\nEnvironmental implications: The rapid rate of mangrove loss and conversion to other land uses is a\nglobal environmental concern. By addressing how these changes impact SOC dynamics, particularly through\nthe lens of Fe interactions, our study provides important data that can inform conservation and restoration\nstrategies not only in the Amazon but also in other mangrove regions worldwide. This has broader implications\nfor global carbon budgets and climate change mitigation efforts.\nTo further illustrate the novelty of our work, we conducted a search on the Scopus platform. When\nincluding all soil types in research related to organomineral interactions with Fe, 213 articles were found.\nHowever, when \"mangrove\" was added as a keyword, the results dropped to just one article. This demonstrates\nthe uniqueness of our study, which not only focuses on mangrove soils but also delves into the mechanisms\nand stability of Fe-C associations, an area that previous studies have not explored in the same depth.\nWe believe these contributions justify the novelty of our work and its suitability for publication in\nNature Communications. We thank the reviewer once again for his/her valuable feedback and encouragement.\nReviewer #3:\nMy first concern is that the massive loss of SOC due to LUC was not supported by the mechanism\nof FeOMI, as proposed by the authors. Conversion of mangroves to shrimp pond and pasture resulted in\nsubstantial loss of SOC, especially for the MAOC fractions. Although loss of Fe-bound OC might be important\nin mangrove ecosystem, it’s not sufficient to explain the contribution of FeOMI in loss of MAOC. Providing\ndirect evidence that crystalline iron retains less soil organic carbon would strongly support the authors'\nviewpoint\nAuthors’ response:\nWe appreciate the reviewer’s insightful comment and the opportunity to clarify our findings.\nWe acknowledge that the loss of Fe-bound OC is not the sole reason for the substantial loss MAOC\nfollowing land-use change. We focus on Fe-bound OC and we show that the conversion and loss of Fe phases,\nespecially those related to poorly crystalline Fe oxides is a major reason for the loss of OC. Importantly we\ndemonstrate that FeOMI associations, which are generally considered stable, are actually highly susceptible to\nchanges in the geochemical environment resulting from LUC.\nWe demonstrate the importance of poorly crystalline Fe oxides by presenting the OC:Fe ratio from\nour sequential extraction results (Table S2). Specifically, the Fe extracted by citrate-ascorbate (Fe asc) showed\nat least twice as much OC relative to Fe compared to the Fe extracted by citrate-bicarbonate-dithionite (Fe\ncbd). This finding underscores our point about the greater efficiency of poorly crystalline Fe oxides in binding\nOC. Our extraction data also revealed that the OC:Fe ratio for Fe asc was three times greater than for Fe cbd,\nimplying that both adsorption and coprecipitation mechanisms are involved in FeOMIs with poorly crystalline\nFe oxides.\nTo further address the reviewer’s request for direct evidence, we conducted an additional adsorption\nand coprecipitation experiment with goethite and ferrihydrite reacting with humic acid (HA). The detailed\nmethods and results are available in the Supplementary material. The results showed that ferrihydrite adsorbed\napproximately 65 mg HA g⁻¹, while goethite adsorbed only 27 mg HA g⁻¹, indicating that ferrihydrite binds\nthree times more OC than goethite. Moreover, in the coprecipitation experiments, the mean HA coprecipitated\nwith ferrihydrite was approximately 690 mg HA g⁻¹, ten times greater than what was observed in the\nadsorption experiment.\nWe hope that these new data provide the additional evidence required to support our viewpoint and\naddress the reviewer’s concerns.\nWe have updated lines 168-181 to include this discussion.\nReviewer #3:\n“I agree with first result regarding the critical role of FeOMI in mangrove soils and the explanation\nthat iron binds more labile carbon. However, the evidence for the conclusion that Fe oxides protect more labile\nSOC fractions was not sufficient. It is plausible that Fe oxides affinity for more thermally labile and oxidized\norganic compounds. But it can also not exclude the explanation that catalytic effect of Fe oxides on organic\nmatter oxidation during thermal analysis. In addition, thermally labile OC is not equivalent to labile SOC fraction.\nIt’s better to provide direct evidence that how Fe oxides protect POC and MAOC.”\nAuthors’ response:\nThank you for this important inquiry. We appreciate your recognition of the critical role of Fe-\norganomineral interactions (FeOMI) in mangrove soils and we acknowledge the need for further clarification\nregarding our conclusion that Fe oxides protect more labile SOC fractions.\nThe reviewer raises an important question about the potential catalytic effect of Fe oxides on OM\noxidation during thermal analysis. However, when we remove Fe and the associated OM, the remaining OM is\nstill associated with other minerals, which can also produce a catalytic effect (Dembicki, 1992; Faure et al.,\n2006). Therefore, it is less likely that the observed effect is primarily due to catalysis and more likely due to\nOM composition in these different MAOC subfractions, where Fe-bound OC is more thermally labile.\nThis interpretation is supported by the “bioenergetic framework” (Williams et al., 2018; Williams &\nPlante, 2018) and the current paradigm of SOM persistence (Kleber et al., 2011; Lehmann et al., 2020;\nLehmann & Kleber, 2015). This perspective suggests that SOM exists as a continuum, continuously processed\nby the decomposer community from large biopolymers to small monomers. As these compounds become\nincreasingly oxidized and soluble, they become more susceptible to microbial uptake unless they are protected\nfrom decomposition through mineral protection (Kleber et al., 2015).\nDepolymerization and oxidation of larger organic molecules solubilize smaller organic molecules,\nwhich make them more accessible for microbial uptake if the dissolved organic matter is readily available\n(Lehmann et al., 2020). On the other hand, oxidation enhances chemical reactivity of organic compounds by\nreducing molecular size, increasing polarity, and thus increasing chemical reactivity. This is crucial for the\nformation of organomineral interactions, especially those involving Fe, which include ligand exchange with\noxygen-bearing functional groups (Chen et al., 2014; Gu et al., 1995).\nWhen compared to POC, MAOC has lower thermal stability, reflected by lower energy density (ED)\nand lower activation energy, the latter positively correlated with DSC-T (Williams et al., 2018; Williams &\nthermodynamic stability (e.g., high O-alkyl C/aromatic C ratio, a higher proportion of thermally labile materials).\nThus, a decrease in thermal stability is expected as SOM decomposition progresses, with larger plant\nbiopolymers being processed into smaller molecules (Barré et al., 2016).\nAlthough MAOC generally exhibits relatively low thermal stability, different stability is observed within\nthis fraction when different types of bonds occur. For instance, increasing cation-bridging associations lead to\nhigher thermal resistance of adsorbed organic matter (Barreto et al., 2021). Ligand exchange, one of the\nprimary mechanisms of OM bonding with Fe oxides, can have relatively large activation energy for adsorption\n(Nguyen et al., 2018). Based on this rationale, we would expect the DSC-T to decrease after Fe removal,\n50\nas strong covalent ligand-exchange reactions would become less frequent than the weaker bonding (e.g.,\nelectrostatic, van der Waals) more common with the remaining phyllosilicates (Kleber et al., 2021). However,\nwe observed the opposite. Thus, a more plausible explanation for the relative increase in thermal stability after\nthe removal of Fe-bound OC is that this organic fraction had lower thermal stability than the remaining one.\nOur FTIR data further supports this interpretation. Upon removing Fe-associated OC, the COO/CH\nratio decreases, indicating that the more oxidized organic matter (i.e., more decomposed and likely biologically\nlabile) is removed along with Fe. In fact, there is a positive correlation between DSC-T and the CH/COO-\n50\nratio, meaning that as the CH/COO- ratio increases (i.e., Fe-bound OC is removed), the remaining MAOC\nbecomes more thermally resistant (see Fig r1 below), which is can be attributed to the increased relative\ncontent of energetic C—H bonds (Williams et al., 2018) This implies that within the MAOC fraction, there is\na subfraction (i.e., Fe-associated) that is thermally and inherently biologically more labile.\nAnother important piece of evidence we included in our manuscript is the increase in the C/N ratio as\nFe-bound OC is removed, suggesting that the organic matter remaining in the MAOC fraction is less\ndecomposed and more chemically complex than that associated with Fe. In fact, we observed a positive\ncorrelation between the C/N ratio and ED (R2 = 0.39; p-value = 0.02). This further supports our argument\nadj\nthat the effect of organic matter composition on thermal stability is more important than any catalysis reaction\ndue to Fe mineral. Therefore, we can conclude that Fe-bound OC is more decomposed and less complex than\nthe average MAOC, indicating that Fe helps protect an inherently more biologically labile SOC fraction.\nWe have edited lines 118-149 to better clarify the evidence and rationale of our claim.\nWe hope this explanation addresses your concerns and clarifies our conclusions regarding the role of\nFe oxides in protecting a priori labile SOC fractions in mangrove soils.\nReviewer #3:\nIn the introduction, it is necessary to briefly describe the important role of mineral protection\nmechanisms in the stabilization of soil organic carbon in mangroves. The relationship between the forms of\niron, or their crystallinity, and soil organic carbon should be clearly introduced. Additionally, hypotheses about\nthe impact of land use change on iron and the iron-OM bound relationship should be reviewed with published\nliterature.\nAuthors’ response:\nWe appreciate the reviewer’s feedback on the Introduction section. We have revised it to better reflect\nthe current understanding of FeOMIs and to clarify our hypotheses. Please see the revised text in lines 60-77.\nReviewer #3:\nTable S1, which is a key result, is somewhat difficult to understand. The parameters displayed in the\ntable need clarification. It appears that some indicators refer to the extracted portion while others refer to the\nresidual portion. This should be more clearly indicated in the table explanation.\nAuthors’ response:\nThank you for your valuable feedback. We have revised the table legend to clearly distinguish between\nthe parameters related to the extracted portion and those related to the residual portion.\nReviewer #3:\nThe discussion on the environmental implications does not seem to independent part. This part does\nnot present any new findings or conclusions. I do not understand what the authors intend to express about\nthe role of the environment in carbon sequestration in mangroves and the iron-OC binding relationship under\nLUC. Additionally, it is unclear what is meant by \"environment\". Supplementing this section with specific facts\nand relevant data would make it more compelling.\nAuthors’ response:\nWe appreciate the reviewer’s comment. To address the concern that the environmental implications\nsection lacks independence and clarity, we have revised the text to more explicitly discuss the role of\nenvironmental factors—specifically, sediment deposition and Fe dynamics—in the carbon sequestration\nprocess in mangrove ecosystems under land-use change (LUC). We have renamed the section title to\n“Implications for future restoration efforts” to better reflect its intended focus.\nReviewer #3:\nThere also some other minor errors in the text and figures, such as the lack of a b annotation in Fig.2,\nand the Table 1 mentioned in L133 is Table S1. I recommend that the authors thoroughly review the entire\ntext to avoid these errors which easily make reader confusing.\nAuthors’ response:\nThank you for pointing out these issues. We have revised the entirely text, including Table and Fig\nreferences.\nWe would like to thank you for your detailed and helpful feedback. We have revised the manuscript\naccordingly and are confident that we have addressed all the issues raised by the reviewer. Thank you for your\ntime and effort, which have greatly contributed to enhancing the quality of our work."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Review of re-submitted paper\nTitle: Iron’s role in soil organic carbon (de)stabilization in mangroves under land use change\nAuthors: F. Ruiz, A. Fraga Bernardino, H. Melo Queiroz, X. Luis Otero, C. Rumpel, T. Osório Ferreira\nGeneral comments\nThank you for your thorough revision of the manuscript. My main concerns were addressed in detail in this new version.\nI find the changes made to the article satisfactory and thus recommmend its publication in the current form.\nSincerely,", "reviewer_3": "I appreciate the response to my comments. The manuscript has been largely improved."}, "author_response": ""}]

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