Land use change affects soil methane sink capacity of Brazilian biomes

Land use change affects soil methane sink capacity of Brazilian biomes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Land use change affects soil methane sink capacity of Brazilian biomes Leonardo Machado Pitombo, Helio Danilo Quevedo, Diana Signor, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6630160/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Soils are the only biological sink for atmospheric CH₄, making microbial methane consumption a highly relevant process. Land-use change toward agriculture can inhibit this process through the application of ammonium-based fertilizers. To test whether this effect plays a role in land-use changes in Brazilian biomes, we incubated natural and cultivated soils from four endangered Brazilian biomes: Caatinga, Cerrado, Pampas, and Atlantic Forest. Considering only soils that exhibited net CH₄ uptake, soils oxidized an average of 11.9 µg C kg⁻¹ soil day⁻¹. Ammonium sulfate amendment reduced CH₄ oxidation by 33% in pristine soils, while soils from agricultural fields exhibited no methane uptake. Except for soils from the Caatinga biome, pristine soils consumed atmospheric CH₄ and exhibited higher numbers of methanotrophic bacteria compared to managed soils. Our results suggest that a typical nitrogen source supplying NH₄⁺ did not exert as pervasive an effect on CH₄ uptake as did land-use change itself, reinforcing the importance of ecosystem conservation for maintaining the CH₄ cycle. Additionally, soil nutrient availability, particularly micronutrients, may play a key role in stimulating or inhibiting soil methanotrophy. In times of accelerated climate change in the tropics and globally, it becomes crucial to rethink agricultural practices, biomass production models, and patterns of land use and fertilizer application to minimize potential increases in greenhouse gas emissions Caatinga Cerrado Atlantic Forest Pampas Greenhouse gases methanotrophy Figures Figure 1 Figure 2 Figure 3 Introduction Atmospheric concentrations of CO 2 , CH 4 and N 2 O are raising since the 18th century with the beginning of the industrial era, with CH 4 being the most rapidly increasing from 719 ppb in 1750 to 1895 ppb in 2021 (IPCC 2021; Wang et al. 2018; Lan et al. 2022). About 22% of the global warming is attributed to CH 4 in the atmosphere (Wang et al. 2018). Soils are the only biological sink of atmospheric CH 4 , reinforcing their importance for climate regulation (Curry 2007), taken up about 31 Tg CH 4 yr -1 (Kirschke et al . , 2013) An important factor affecting methane-cycling microbes and subsequent CH 4 emissions is the agricultural management and associated vegetation cover (Venturini et al. 2022). The transformation of natural areas into agricultural land is reflected in an increase in CH 4 emission (Carmo et al., 2012; El‑Hawwary et al., 2022). Methane emission is regulated by methane production and oxidation, catalyzed by methanogens and methanotrophs under anoxic and oxic conditions, respectively (Kaupper et al. 2022). Changes in edaphic conditions as well as environmental disturbances can also lead to alterations of production and consumption of CH 4 (Bodelier et al. 2019). Anthropic pressure and demand for biomass has resulted in the continuous declining of natural areas from Amazon Rainforest, Atlantic Forest, Cerrado, Pampas and Caatinga biomes to transform in agricultural areas to produce agricultural commodities using large amount of mineral fertilizer (Silva et al. 2020; Cirne-Silva et al. 2020; Segura-Garcia et al. 2024; Galarza et al. 2023; Macedo et al. 2023). The effects of inorganic nitrogen (e.g., NH 4 + and NO 3 − ) are known to regulate soil CH 4 oxidation via several mechanisms (Kang et al. 2022) and Nitrogen addition negatively affected bacterial and fungal diversity (Lu et al. 2011). The intensity of the impacts depends on the particularity of each ecosystem, management, soil characteristics, pH, temperature and the amount of N fertilizer added (Lee et al. 2023, Lu et al. 2011). Originally covering 150 million ha, the massive conversion of Atlantic Forest occurred up to the beginning of the industrial era (Ribeiro et al. 2009). The other cited biomes are in the frontiers of transition, where the development of new crop varieties and techniques turned agriculture feasible and competitive, overcoming the biomes weather and soil adversities (Beuchle et al. 2015, Lapola et al . 2013). Most of the research and concerns related with land use change from natural areas to agriculture focuses on the Amazon Rainforest (Aleixandre-Benavent et al . 2018), but the other biomes are on the edge of this transition as well (Beuchle et al. 2015, Lapola et al . 2013, Strassburg et al . 2017). For instances, Cerrado and Caatinga lost 26.6 and 9.0 million ha of natural vegetation from 1990 to 2010, respectively (Beuchle et al. 2015). Cerrado, as Atlantic Forest, is hotspot for biodiversity and originally occupies around 200 million ha in Brazil (Strassburg et al. 2017). Caatinga is a Brazilian exclusive biome, occupying around 73.5 million ha under semiarid climate and xeromorphic vegetation consisting of a composition of shrubs and areas of seasonally dry forest (Leal et al. 2005). Despite its extension and peculiarity, the Caatinga has receive little attention from scientists (Santos et al . 2011). Pampas represents the Brazilian sub-tropical native grasslands, which occupies around 13.7 million ha in Brazil and around 25% of its area was already converted to cropped lands up to the beginning of the century (Overbeck et al. 2007). Assessing the impacts of land use change on all the ecosystems services subsidizes the establishment of public policies to reach the balance between the services in natural and managed ecosystems (Adhikari and Hartemink 2016). Among the main and most uncertain impacts of converting natural areas into agroecosystems is the net C and greenhouse gases balance. For instances, land use change would improve C soil stocks in well managed systems, especially in soils planted with perennial crops (Escanhoela et al . 2019, Guo and Gifford 2002). On the other hand, agriculture might reduce soil CH 4 uptake capacity (Levine et al . 2011, Powlson et al. 1997). However, the cause-effect relationship among soil management and CH 4 cycling is not completely clear. For instances, Levine et al . (2011) demonstrated a link between microbial diversity, agriculture history and CH 4 uptake. Reduced CH 4 uptake in agricultural soils can be caused by nitrogen (N) addition because NH 4 + and CH 4 oxidation are homologue functions mediated by the same enzyme in methane-oxidizing bacteria (MOB) (Bodelier 2011), but with no energy benefit. NH 4 + can be oxidized by the enzyme and blocking the oxidation of CH 4 (Bodelier 2011). This hypothesis becomes more intriguing because a strong positive correlation between natural soil NH 4 + and CH 4 uptake was observed by Goldman et al . (1995), but in a N availability range below the amount added in agricultural fields. Up to date no microbial group that promotes beneficial NH 4 + and CH 4 oxidation is known We hypothesize that natural soils oxidize CH 4 but land use change an ammonium-based fertilizer amendment reduces the soil ability to consume CH 4 . We tested this hypothesis on soils from four Brazilian biomes. We used a pairwise scheme comparing adjacent soils from natural sites and agricultural fields from across these biomes (Fig 1). Ammonium sulfate was used to test the effect of NH 4 + addition on soil CH 4 oxidation. The understanding of the impacts of land use change is crucial for calculating its trade-offs and weighing the values of ecosystems services. Materials and Methods Experimental design Soils were sampled in four Brazilian biomes (Atlantic Forest, Cerrado, Caatinga and Pampas), in pairs of natural and cultivated adjacent areas (Fig 1, Table S1, Supplemental material). Independently of crop type, the criterion to fit within the experimental design was to receive fertilizer at least on annual basis. In total, 11 sites fitted within this criterion and comprise 3 sites with perennial crops, 2 sites with semi-perennial crop (sugarcane) and 6 sites with annual or rotational crops. The experimental design includes: natural soil; natural soil amended with N; cropped soil; cropped soil amended with N (4 treatments). Therefore, we can test if either land use or N amendment affects CH 4 uptake by soils. Soil sampling and processing Sampling was carried out during autumn 2016, after crop harvest or during its senescence, avoiding acute and residual fertilizer effects. Composite samples were taken from each site up to the amount of around 20 kg of soil using hand augers (0-20 cm). Samples were brought to the laboratory and air-dried to enable sieving (2mm) and consequently homogenization. Soil available P, Ca 2+ , Mg 2+ , Al +3 , pH and micronutrients were determined according to van Raij et al. (2001). Inorganic N content was determined colorimetrically using soil extracts (2M KCl) based on the methods proposed by Norman et al. (1985) for NO 3 – and by Krom (1980) for NH 4 + . Total soil organic C and N were determined by elemental analyzer (PerkinElmer CHN 2400, Waltham, EUA). Soil texture and chemistry parameters are found in Supplementary material (S2). Microcosms (n=4) for gas measurements were set up as suggested by Pitombo et al . (2018) and were kept in an acclimatized room at 25±2°C. Using soil density, the mass of soil (dry basis) to put in each microcosm was determined in order to reach 300 mL of bulk soil. A pre-incubation period of one week at 40% of soil water-filled pore space (WFPS) was adopted to promote soil microbial community stabilization. Treatments that received N were amended with a (NH 4 ) 2 SO 4 solution to reach 100 mg N kg soil -1 , which is within the concentration regularly found in cropped soils after fertilizer application and used in microcosm experiments. As discussed by Pitombo et al . (2018), this amount is equivalent to 50 kg N ha -1 . Afterwards and for all treatments, WFPS was adjusted to 45%, which is around the optimum condition for soil CH 4 oxidation (del Grosso et al . 2000). Every day, during both the pre-incubation and after the gas sampling, 5 mg of C in the form of an artificial root exudates solution without N (van Zwieten et al . 2014) was added to each microcosm aiming to keep the soil basal respiration. Afterwards, soil moisture was adjusted by replacing the water while weighing the microcosms. Gas analyses After the pre-incubation period, CH 4 fluxes were measured every day during ten days. Microcosms were only closed during sampling to avoid gas saturation. Headspace gas samples were taken at 1; 30; 60 and 90 min after microcosm closure using 20 mL syringes. Methane concentrations were determined by gas chromatography (GC 2014 Shimadzu, Kyoto, Japan) using a flame ionization detector. All the sample volume (20 ml) was injected directly in the chromatograph inlet, which contains a sample loop that standardizes the sample volume carried for analysis. The device was daily calibrated with three certificated standards (0.92; 1.81 and 3.58 ppm) and its limit of quantification is 0.1 ppm for CH 4 . Gas fluxes were calculated with linear regressions of gas concentration over time. Details of sampling, quality control and fluxes calculations are also described by Pitombo et al . (2018). Soil DNA isolation and Real-Time PCR Soil samples from microcosms were frozen at -20°C for molecular analyses after the gas flux measurement period. DNA was extracted from 250 mg of soil using the PowerSoil DNA Isolation Kit (Mobio Laboratories, Carlsbad, USA) according to the manufacturer's protocol. DNA quantity and quality were confirmed in 2% agarose gel and using a Synergy HTX microplate reader (BioTeK Inc., Winooski, Vermont, U.S.A) set for determining absorbance at 230, 260, 280 and 320 nm. Abundances of particulate methane monooxygenase encoding gene from both type I and type II methanotrophs were determined by quantitative real-time PCR. The primer set (pmof1 5’- AACTTCTGGGGNTGGAC-3’and pmor 5’- RCNACGTCNTTACCGAA-3’) was developed by Cheng et al. (1999) and modified by Stoecker et al. (2006), who increased the degeneration degree of the forward sequence. As this primer pair targets both type I and type II methanotrophs, we expected it would be used to assess the overall effects of land use change on methanotrophs abundance. Reactions were performed with a QuantStudio 3 (Applied Biosystems, Foster City, EUA) in the total volume of 10 uL using the SYBR® Green JumpStart™ Taq ReadyMix chemistry, added of the respective reference dye (Sigma-Aldrich, San Luis, EUA). Annealing temperature was at 58°C, data were acquired at extension temperature (72°C) and melting curve analysis was performed to confirm specificity. A pool of sequenced amplicons from environmental samples was used as standard for the gene quantification. Number of amplicons per uL in the standard pool was determined based on fluorescence quantification (Quant-iT™ dsDNA Assay Kit, Invitrogen, Carlsbad, EUA). Standards were analyzed in triplicate while samples in two technical replicates, besides the experimental replication (n=4). Statistical analyses Analysis of variance (ANOVA) followed by Tukey test were used to determine both the pairwise and group differences in CH 4 fluxes within land uses and N addition. The same approach was used to test the land use effect on methane monooxygenase encoding gene abundances. We performed a nonmetric multidimensional scaling ordination (NMDS based on Euclidian dissimilarities of normalized data) to demonstrate whether biomes or soil parameter drive the differences in CH 4 uptake and methane monooxygenase encoding gene abundances. Thereafter, Generalized Linear Mixed Models (Bolker et al . 2009) were used to test the effects of soil parameters on CH 4 oxidation rate. The global model, which is the one that includes all the potential explanatory variables, was fitted using the ‘lme4’ R package version 1.1–10 (Bates et al. 2015). Replicates were included as random effect. Model selection was performed using the Akaike information criterion (AIC) for ranking after running all the model combinations using the ‘MuMIn’ R package version 1.15.6 (Barton 2016). Models coefficients of determination (r 2 ) were determined according to Johnson (2014). We used normalized data (0 to 1) to improve the understanding of the magnitude effect of each explanatory variable on models describing CH 4 uptake. Results Methane flux measurements Results from the incubation experiment are presented in Fig 2. Overall, land use change resulted in significant inhibition of soil CH 4 oxidation (p<0.001). This result is also observed in the pairwise comparison (Fig 2), with exception of the soils from Caatinga and one from the Atlantic Forest biomes, which did not show active CH 4 oxidation irrespective whether they come from native or cropped conditions (Fig 2). Soils under native vegetation displayed mean CH 4 uptake of 7.3 ug C per kg soil -1 day -1 . Considering only soils that presented net CH 4 uptake, soils oxidized 11.9 ug C kg soil -1 day -1 on average. We observed CH 4 oxidation rates of up to 28 ug C per kg soil -1 day -1 (Fig 2, Brasília site – Cerrado bioma). In such conditions CH 4 headspace concentrations in the microcosms decrease to around 0.7 ppm during the 90 min the microcosm remained closed for gas sampling. Nitrogen addition statistically reduced CH 4 oxidation in soils from native sites (p=0.007). Soils that originally oxidized CH 4 with statistical significance passed to oxidize 7.976 ug C per kg soil -1 on average after N amendment, which is equivalent to 33% of inhibition. Additionally, inhibition was statistically significant in all the pairwise comparisons and ranged from 17% to 100% at the Araras and Pelotas sites, respectively (Fig 2). There was no statistical significance of N addition on CH 4 fluxes from cropped soils. Mean fluxes from these soils were -0.2 and -0.4 ug C per kg soil -1 , without and with N addition, respectively. Methanotrophs abundance Land use change reduced abundance of methanotrophs in all soils that actively oxidized CH 4 , with exception of one site from the pampa biome (Fig 2). Interestingly, cropped soils from Caatinga contained higher numbers of methanotrophs than soils under native vegetation (Fig 2). Factors driving CH 4 uptake Nonmetric multidimensional scaling ordination of the methane monooxygenase encoding gene and CH 4 oxidation rate with all measured soil parameters indicated no grouping within biomes and these parameters (Fig 3). The same analysis pointed to the possible effect of sodium (Na) on the lack of CH 4 uptake and low methanotrophs abundance in the soils from Caatinga. The only soils that contain available Na are the ones from this biome. Therefore, the other soils that appear close to the Caatinga soil in the plot are likely more influenced by other factors like soil C, N, NH 4 + and copper (see Fig 3). Thereafter we observed no grouping within biomes and CH 4 oxidation and methanotrophs abundance (Fig 3), we fitted generalized linear mixed models to identify the soil parameters that likely contributed to CH 4 oxidation. Global and best models are presented on Table 1. Parameters with higher values have more effect on soil CH 4 uptake following data normalization. Therefore, the best model indicates low pH, soil C, available Fe and available Cu were the most important factors driving CH 4 oxidation rates in the studied soils. In contrast, available Al, available Mn and available Zn likely inhibit CH 4 oxidation. Table 1. Summary of the global and best models fitted to determine the explanatory variables are related to CH 4 uptake capacity Parameters Global model Best model intercept β 0.095 0.150 soil C 3.968 4.770* P 5.503 0.116 ns Fe 3.085 7.439* Mn -10.582 -8,260* Zn -5.002 -2.432* Cu 9.178* 8.537* Al -11.469* -11.375* N-NH 4 + 1.729 ___ N-NO 3 - 3.522 ___ porosity 0.355 ___ pH -4.307 -3.146 Log pmoA 0.072 ___ AIC -16.3 -23.3 r 2 0.954 0.951 β Positive values indicate the parameter helps to explain CH 4 uptake while negative values indicate they inhibit CH 4 oxidation. NS indicates no significant effect of the parameter in explaining CH 4 uptake despite the parameter is relevant to improve the model likelihood in the best fitted model; *p<0.05 Discussion Our results show that changing natural tropical soils to croplands suppresses methane oxidation activity N addition reduced CH 4 oxidation rates as well but not as strong as land-use change. The differences found in abundance of methanotrophic bacteria with different land use emphasizes the dominant effect of land use on atmospheric methane consumption. In temperate ecosystems this effect is not as pervasive as observed in our study. However, the only exception was the Caatinga biome, from where all the soils did not show consistent methanotrophy. Similar results were observed from in situ measurements performed in the natural Caatinga (Ribeiro et al. 2016),. Semiarid regions cover 18% of global area and together with arid regions they would be an important sink of CH 4 and other trace gases (Galbally et al. 2008). However, our results indicate that the Caatinga soils are do not take up nor emit methane. These soils usually present low C stocks that should be correlated with low soil dissolved organic carbon (DOC) an important substrate and has a positive effect on CH 4 emissions (Wang et al. 2021). Additionally, low nutrient availability can support low primary production. Caatinga has an uneven rainfall regime, with most of the time under negative water balances (Menezes et al. 2012) Although methanotrophy is more intense at the first 10 cm, this process occurs along the soil profile (Hütsch, 1998, Koschorreck and Conrad, 1993, Price et al . 2004). Therefore, we were unable to estimate the field CH 4 uptake based on this microcosm study. Nonetheless, field measurements have being performed in three of the sites from where the soils come from, totaling two under native vegetation and two cropped soils. At the “São Luiz do Paraitinga” site, Carmo et al . (2012) observed annual C-CH 4 mean fluxes of -1.35 mg m 2 day -1 , corresponding to around 5 kg C-CH 4 ha -1 year -1 . In our study, the soil from the same site oxidized 4 ug C-CH 4 kg soil -1 day -1 (Fig 2), which is 3-fold lower than the average observed in all soils. It is worth to mention that Carmo et al. (2012) observed consistent reduction of CH 4 uptake during late spring, together with an unusual pool of soil NH 4 + (~40 mg NH 4 + kg soil -1 ). A soil considered by Tate (2015) as a strong sink of CH 4 oxidizes about 8 kg C-CH 4 ha -1 year -1 (Price et al. , 2004). Based on the relationship between the field and laboratory results, we could highlight the “Aiuruoca”, “Brasília” and “Araras” soils under native vegetation as potential to be an even stronger sink of CH 4 . Forest soils from China have oxidized about 1.2 ug C-CH 4 kg soil -1 day -1 in a laboratory study (Zeng et al . 2019), what is 20-fold lower than the values observed in the three soils within the high methane oxidation rate in this study. Despite it was not included in the Nishisaka et al. (2019) publication, the authors observed the CH 4 balance is virtually neutral at the “Sorocaba” site under native vegetation, in accordance with our microcosm study (Fig 3). Similar results were observed after annual measurements in the cropped soils both at the “Sorocaba” and “Araras” sites (Escanhoela et al. 2019; Pitombo et al. 2017). Soil C, pH and Fe appear as relevant to explain soil CH 4 uptake rates. The modelling results (Table 1) indicate a negative correlation between pH and CH 4 uptake. Porosity regulates the diffusion of the gas in the soil (Striegl 1993). Despite porosity didn´t help to explain CH 4 uptake in soils as expected, soil organic matter was one of the parameters regulating CH 4 oxidation. Organic matter, commonly represented by soil organic C, is the main soil conditioner, regulating water and nutrient availabilities as well promoting soil structure. The availability of labile carbon is essential for the maintenance of methanotrophic organisms and, according to El-Hawwary et al. (2022), abandoned agricultural areas or degraded areas can have their methanotrophic community reestablished with the enrichment of available organic carbon. Next to this, addition of organic residues to soils has been demonstrated to stimulate atmospheric methane uptake by agricultural soils (Ho et al 2015), which can be by changing soil aggregate structure (Van den Bergh et al 2024). This fact is of great importance for the recovery of degraded areas or recompositing of biomes, making it possible to reverse the functionality of the ecosystem in relation to its potential to absorb CH 4 from the atmosphere. Despite the models showed soil porosity alone didn´t effect CH 4 uptake rates, the importance of soil porosity is evidenced with the effects of soil compaction on CH 4 uptake (Sitaula et al. 2000). Therefore, it suggests compaction might be one of the cofactors which lead to the land use chance effect on CH 4 uptake, once soil compaction is one of the effects of agriculture (Soane and van Ouwerkerk 1994). Another cofactor is the addition of N to the system, which, as we show, also has an impact on CH 4 uptake. The other parameters that either likely promote or inhibit methanotrophy are available micronutrients, Al and Na. The natural occurrence of these elements in soils depends mainly on the parent material from which the soil is originated. Sedimentary formations are usually poor while soils originated from basic rocks are rich in micronutrients (Abreu et al . 2012). Despite the authors didn´t present data regarding to micronutrients availability, Singh et al. (2009) observed CH 4 uptake rates higher in volcanic soils than in non-volcanic soils. Therefore, merging pedological mapping with CH 4 uptake rates would improve the bottom-up estimates of the gas turnover. Interestingly, our results indicated available Zn likely inhibit soil CH 4 oxidation rates. This observation corroborates with cell physiology studies that show that Zn is a well-known inhibitor of the particulate methane monooxygenase enzyme (Sirajuddin et al. 2014). On the other hand, Cu is the central component of this enzyme (Ross et al. 2019), and it has been experimentally demonstrated that the elemental amendment can increase soil methanotrophy (Ho et al. 2013b). Also interestingly, it has been suggested that when copper-to-biomass ratio of the cell is low, the iron-dependent methane monooxygenase is expressed (Murrell et al. 2000), corroborating with the statistical contribution of Fe to the soil CH 4 uptake rate. The presence of Fe 3+ (an electron acceptors) can participate in the methane oxidation process and affect CH 4 emissions (Fan et al. 2021; Chen et al. 2022). Additionally, transient conditions would reemerge a group that is not expected to be dominant in determined system, such as after the addition of organic byproducts (Ho et al. , 2019) or in soils subjected to drought and re-watering cycle systems (Cai et al . 2016). This might explain why methanotrophic abundance did not explained a significant amount of the variation observed in methane oxidation rates in this study (Table 1). Part of the quantified microorganisms represent the microbial seed bank, that is dormant up to favorable conditions are established (Lennon and Jones 2011). Notwithstanding, the qPCR results indicate the methanotrophy potential in the soils (Fig 2) and soils with more copies of methane monooxygenase encoding genes also presented greater CH 4 oxidation rates. This assumption is based on the ratio between oxidized CH 4 and methanotrophs abundance. Observing the Fig 2, we might suggest a threshold close to 10 5 copies of methane monooxygenase encoding gene per gram in soils that present an active atmospheric CH 4 uptake. A gram of soil has oxidized 12 ng C-CH 4 day -1 on average and it sustains around of 100 ng of methanothrophs biomass, taking into consideration the bacterial dry cell mass of 1 pg (Sender et al . 2016). The question that arises is if a ratio 10 between biomass and substrate used on a daily basis is enough to sustain the soil methanothroph community. Kolb et al. (2005) estimated that at 25°C, which is our experimental condition, 40 x 10 -18 mol CH 4 cell -1 h -1 would allow the maintenance of the methanotrophic biomass at atmospheric level. This is equivalent to 1 x 10 -10 mol CH 4 g soil -1 day -1 , considering the same 10 5 active cells per gram of soil. However, our soils oxidized 1 x 10 -9 mol CH 4 g soil -1 day -1 , which is 10-fold higher than this theoretical value. Nonetheless, this range coincides with the 540 x 10 -18 mol CH 4 cell -1 h -1 estimated to the maintenance of the USCα cluster (Kolb et al. 2005), the predominant group of methanothrophs in acidic upland soils (Kolb, 2009). Therefore, the amount of CH 4 oxidized in the studied soils is enough to the methanotrophs community maintenance. Additionally, the kinetics of oxidation in the microcosms was much more intense than the observed for the isolate presented in the study of Tveit et al. (2019). While the CH 4 concentration in the headspace of the pure culture decreased from ~1.9 ppm to ~1.4 after 120 days, in one set of microcosms (Brasília site) the CH 4 concentration in the headspace dropped linearly to around 0.7 ppm during the 90 min in all the forty measurements (4 replicates and 10 days). Abundance of methanotrophs in Caatinga soils increased after land use change, unlike the other soils (Fig 2). Cropping these soils under such adverse climatic conditions might increase the ecosystem productivity and consequently the soil microbial biomass. However, this improvement in abundance does not reach the hereby suggested threshold requested to the observation of soil methanotrophy. The presence of facultative methanotrophs may explain the observed unexpected methanotrophy in same environment Several facultative methanotrophs have been isolated. These organisms can use some multi-carbon compounds in addition to methane, often small organic acids, such as acetate, or ethanol (Haque et al. 2020). The methanotrophic community might be impacted by the addition of N to the system. However, we showed N wasn´t the only driver of inhibition of CH 4 uptake. As suggested by Dörr et al . (2010), atmospheric methane oxidisers are oligotrophic species and the increase in soil organic C availability caused by fertile islands shifted the dominant taxa in microbial communities from oligotrophic trace gas oxidizers to copiotrophic organotroph (Li et al 2023). Raising the pH to improve the crop productivity might also increase microbial diversity (Lauber et al. 2009, Mendes et al . 2015) and, therefore, enhance microbial competition once the media becomes less restrictive. As proposed by Ho et al. (2013a), the type II methanotrophs are likely among the stress tolerator group within the Competitor‐Stress tolerator‐Ruderal framework of life strategies. Therefore, an intensive system like cropped soils will be detrimental to the high-affinity methanotrophic community. In cropped sites, besides the physical-chemical factors, like porosity and nutrient availability, ecological interactions might also limit the methanotrophs maintenance and, consequently, CH 4 uptake by soils. There are multiple competing strategies that methanotrophs might be in disadvantage as oligotrophs in an intensified ecosystem. They include space competition by favorable habitats, competition for nutrients other than C, inhibition by secondary metabolites released from other microorganisms and perhaps predation (Hibbing et al. 2009). Nutrient enrichment increases the abundance of nematodes, which are important regulators of soil microbial communities (Thakur et al. 2019). In a rice field soil, Murase et al. (2008) observed that the protozoa from the studied site presented grazing preference on the different bacteria and methanotrophs. Therefore, a specific management that increase nematodes may decrease the methanotrophic abundance. Conclusion Our measurements showed that upland soils in tropical agroecosystems are circum-neutral or a source of CH 4 . In contrast, soils under native vegetation predominantly present consistent methanotrophy. Soils from natural environments also presented higher abundance of methanotrophic bacteria, ratifying that land use change affects methanotrophic microbial communities and therefore biological methane oxidation. In this study we concluded that a typical N source that supplies NH 4 + to the soil has not a pervasive effect on CH 4 uptake capacity as observed for land use change, reinforcing the importance of ecosystem conservation for the CH 4 cycle. We observed that soils rich in micronutrients present the most intense methanotrophy and methanotrophic bacteria abundance. Caatinga soils didn´t consumed CH 4 and this finding should be taken into consideration for reviewing ecosystem services provided by drylands. Land use change results in the alteration of many parameters that are important to CH 4 uptake. Although specific parameters might be isolated in a cause-effect relationship, such as N amendment, compaction and facultative methanotrophs organisms, no parameter might be important the stability of CH 4 uptake or flexible metabolic mechanisms enable microorganisms to adapt in highly heterogeneous soil ecosystems and clime conditions like temperate climate regions. In times of intense climate change in the tropics and on the planet as whole, rethinking agriculture and biomass production models as well as changes in land use and intensive use of mineral fertilizers is emerging nowadays to minimize the potential increase in gas emissions, especially in the tropical areas that are recognized a more vulnerable site in the earth. Declarations Acknowledgements The authors are grateful to FAPESP grant number (12/50694-6), CAPES for the Master’s scholarship granted to HDQ and to CNPq for the Postdoc scholarship granted to LMP (151572/2018-6). Funding This research received financial support from FAPESP (grant 12/50694-6). Scholarships were provided by CAPES (Master’s scholarship to HDQ) and CNPq (Postdoctoral fellowship to LMP, process 151572/2018-6). Conflict of Interest/Competing Interests The authors declare no conflict of interest. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References Abreu, C.A., Valladares, G.S., de Camargo, O.A., dos Santos, G.C.G., Paz-Ferreiro, J. (2012). Total and Available Copper in Some Soil Profile Samples from the State of São Paulo. Communications in Soil Science and Plant Analysis, 43(1), 149–160. https://doi.org/10.1080/00103624.2012.634704 Adhikari, K., Hartemink, A.E. (2016). Linking soils to ecosystem services — A global review. 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Sci Total Environ 773:145629. https://doi.org/10.1016/j.scitotenv.2021.145629 Additional Declarations No competing interests reported. Supplementary Files supplementalmaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6630160","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463216549,"identity":"afd8913b-0575-4c2b-b03b-b015cfae4f89","order_by":0,"name":"Leonardo Machado Pitombo","email":"","orcid":"","institution":"Goiás Sanitation Company","correspondingAuthor":false,"prefix":"","firstName":"Leonardo","middleName":"Machado","lastName":"Pitombo","suffix":""},{"id":463216550,"identity":"7b062568-e500-47be-b516-b8106bff9956","order_by":1,"name":"Helio Danilo Quevedo","email":"","orcid":"","institution":"Federal University of São Carlos","correspondingAuthor":false,"prefix":"","firstName":"Helio","middleName":"Danilo","lastName":"Quevedo","suffix":""},{"id":463216551,"identity":"e3605b4f-0ddd-4bcf-b5b7-1c69d5807977","order_by":2,"name":"Diana Signor","email":"","orcid":"","institution":"Brazilian Agricultural Research Corporation","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"","lastName":"Signor","suffix":""},{"id":463216552,"identity":"cbcd3e39-791c-47f9-8d0e-800c2ac6b76c","order_by":3,"name":"Claudia Fernanda AlmeidaTeixeira-Gandra","email":"","orcid":"","institution":"Universidade Federal de Pelotas","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"Fernanda","lastName":"AlmeidaTeixeira-Gandra","suffix":""},{"id":463216553,"identity":"ff7ee71e-54c8-48d1-909d-e7b025730c45","order_by":4,"name":"Ricardo Hideo Taniwaki","email":"","orcid":"","institution":"Universidade Federal do ABC","correspondingAuthor":false,"prefix":"","firstName":"Ricardo","middleName":"Hideo","lastName":"Taniwaki","suffix":""},{"id":463216554,"identity":"436de3d8-8a85-463a-a6b5-0272fb537757","order_by":5,"name":"Cimélio Bayer","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Cimélio","middleName":"","lastName":"Bayer","suffix":""},{"id":463216555,"identity":"04242e07-6101-4fd3-9cf5-b927955fcdd2","order_by":6,"name":"Paul L. E. Bodelier","email":"","orcid":"","institution":"Netherlands Institute of Ecology","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"L. E.","lastName":"Bodelier","suffix":""},{"id":463216556,"identity":"8506c035-ef53-4ef6-b33e-9e01dbe5476a","order_by":7,"name":"Janaina Braga do Carmo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACxhkQWo6B+QCYkUC0FmMGtgQitTBIQKjEBqK1MM9ufvi5MscmfcMx9ocffu5hyDNvIOSwOceMJc9uS8vdcIzHWLLnGUOxzAFCWmbkMEg2bjucu+F+DxsDzwGGxBmEHAbUwvwTqCXd4Bj7M8Y/RGphA9mSYHCMwYyZOFvmHDOzbNyWZjgT6BdpmQMSxRKEtBjObn58s3GbjTwfMMQ+vjlgk0dYSwMqn6AGBgZ5wkpGwSgYBaNgxAMAz4VAtflbepMAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of São Carlos","correspondingAuthor":true,"prefix":"","firstName":"Janaina","middleName":"Braga do","lastName":"Carmo","suffix":""}],"badges":[],"createdAt":"2025-05-09 15:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6630160/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6630160/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84849647,"identity":"9a6cc153-70b7-4572-9bfd-79c991c2c5f7","added_by":"auto","created_at":"2025-06-18 03:58:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":265561,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the pairs of natural and cultivated adjacent areas where the soils were collected. Coordinates are included as supplementary material (S1).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6630160/v1/a8652496ec3b3029e57721ff.png"},{"id":84849645,"identity":"10b5b72b-e8a1-49ab-a68d-934393351d5b","added_by":"auto","created_at":"2025-06-18 03:58:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":77371,"visible":true,"origin":"","legend":"\u003cp\u003eFluxes of CH4 from cropped soils or under native vegetation, with and without N addition (left panel); and particulate methane monooxygenase abundances in these soils (right panel). Different letters indicate significant differences between treatments (p \u0026lt; 0.05). Each box-plot represents the average of forty gas fluxes measurements (4 replicates x 10 days)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6630160/v1/2bbf118dfad02885f3ce7624.png"},{"id":84849646,"identity":"8a418526-5df4-41c9-885d-843b3866f96e","added_by":"auto","created_at":"2025-06-18 03:58:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":129487,"visible":true,"origin":"","legend":"\u003cp\u003eNonmetric multidimensional scaling of pmoA gene and CH₄ oxidation with soil parameters. Ellipses (95% CI) group biomes: blue = Cerrado, red = Atlantic Forest, purple = Pampa, yellow = Caatinga.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6630160/v1/53de5561f1e8fe1caff035a2.png"},{"id":84849867,"identity":"104818d6-c6bb-4f0c-98d4-e8b594d61af5","added_by":"auto","created_at":"2025-06-18 04:06:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1117692,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6630160/v1/04b8fd70-7593-4344-9da2-d7cf58033717.pdf"},{"id":84849648,"identity":"c48cdcb8-b1cf-4cd3-ac05-30f327743b46","added_by":"auto","created_at":"2025-06-18 03:58:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27555,"visible":true,"origin":"","legend":"","description":"","filename":"supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6630160/v1/cd7d2b4c3bb07dcf9c4ca1c1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eLand use change affects soil methane sink capacity of Brazilian biomes\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAtmospheric concentrations of CO\u003csub\u003e2\u003c/sub\u003e, CH\u003csub\u003e4\u003c/sub\u003e and N\u003csub\u003e2\u003c/sub\u003eO are raising since the 18th century with the beginning of the industrial era, with CH\u003csub\u003e4\u003c/sub\u003e being the most rapidly increasing from 719 ppb in 1750 to 1895 ppb in 2021 (IPCC 2021; Wang et al. 2018; Lan et al. 2022). About 22% of the global warming is attributed to CH\u003csub\u003e4\u003c/sub\u003e in the atmosphere (Wang et al. 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSoils are the only biological sink of atmospheric CH\u003csub\u003e4\u003c/sub\u003e, reinforcing their importance for climate regulation (Curry 2007), taken up about 31 Tg CH\u003csub\u003e4\u003c/sub\u003e yr\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003e(Kirschke\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e, 2013)\u0026nbsp;An important factor affecting methane-cycling microbes and subsequent CH\u003csub\u003e4\u003c/sub\u003e emissions is the agricultural management and associated vegetation cover (Venturini et al. 2022). The transformation of natural areas into agricultural land is reflected in an increase in CH\u003csub\u003e4\u003c/sub\u003e emission (Carmo et al., 2012; El‑Hawwary et al., 2022). Methane emission is regulated by methane production and oxidation, catalyzed by methanogens and methanotrophs under anoxic and oxic conditions, respectively (Kaupper et al. 2022). Changes in edaphic conditions as well as environmental \u0026nbsp;disturbances can also lead to alterations of production and consumption of CH\u003csub\u003e4\u003c/sub\u003e (Bodelier et al. 2019).\u003c/p\u003e\n\u003cp\u003eAnthropic pressure and demand for biomass has resulted in the continuous declining of natural areas from Amazon Rainforest, Atlantic Forest, Cerrado, Pampas and Caatinga biomes to transform in agricultural areas to produce agricultural commodities using large amount of mineral fertilizer (Silva et al. 2020; Cirne-Silva et al. 2020; Segura-Garcia et al. 2024;\u0026nbsp;Galarza et al. 2023; Macedo et al. 2023).\u003c/p\u003e\n\u003cp\u003eThe effects of inorganic nitrogen (e.g., NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e ) are known to regulate soil CH\u003csub\u003e4\u003c/sub\u003e oxidation via several mechanisms (Kang et al. 2022) and Nitrogen addition negatively affected bacterial and fungal diversity (Lu et al. 2011). The intensity of the impacts depends on the particularity of each ecosystem, management, soil characteristics, pH, temperature and the amount of N fertilizer added (Lee et al. 2023, Lu et al. 2011).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOriginally covering 150 million ha, the massive conversion of Atlantic Forest occurred up to the beginning of the industrial era (Ribeiro et al. 2009). The other cited biomes are in the frontiers of transition, where the development of new crop varieties and techniques turned agriculture feasible and competitive, overcoming the biomes weather and soil adversities (Beuchle\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2015, Lapola\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2013). Most of the research and concerns related with land use change from natural areas to agriculture focuses on the Amazon Rainforest (Aleixandre-Benavent\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2018), but the other biomes are on the edge of this transition as well (Beuchle\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2015, Lapola\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2013, Strassburg\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2017). For instances, Cerrado and Caatinga lost 26.6 and 9.0 million ha of natural vegetation from 1990 to 2010, respectively (Beuchle\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2015). Cerrado, as Atlantic Forest, is hotspot for biodiversity and originally occupies around 200 million ha in Brazil (Strassburg\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2017). Caatinga is a Brazilian exclusive biome, occupying around 73.5 million ha under semiarid climate and xeromorphic vegetation consisting of a composition of shrubs and areas of seasonally dry forest (Leal\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2005). Despite its extension and peculiarity, the Caatinga has receive little attention from scientists (Santos\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2011). Pampas represents the Brazilian sub-tropical native grasslands, which occupies around 13.7 million ha in Brazil and around 25% of its area was already converted to cropped lands up to the beginning of the century (Overbeck et al. 2007). Assessing the impacts of land use change on all the ecosystems services subsidizes the establishment of public policies to reach the balance between the services in natural and managed ecosystems (Adhikari and Hartemink 2016).\u003c/p\u003e\n\u003cp\u003eAmong the main and most uncertain impacts of converting natural areas into agroecosystems is the net C and greenhouse gases balance. For instances, land use change would improve C soil stocks in well managed systems, especially in soils planted with perennial crops (Escanhoela\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2019, Guo and Gifford 2002). On the other hand, agriculture might reduce soil CH\u003csub\u003e4\u003c/sub\u003e uptake capacity (Levine\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2011, Powlson et al. 1997). However, the cause-effect relationship among soil management and CH\u003csub\u003e4\u003c/sub\u003e cycling is not completely clear. For instances, Levine\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (2011) demonstrated a link between microbial diversity, agriculture history and CH\u003csub\u003e4\u003c/sub\u003e uptake. Reduced CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake in agricultural soils can be caused by nitrogen (N) addition because NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and CH\u003csub\u003e4\u003c/sub\u003e oxidation are homologue functions mediated by the same enzyme in methane-oxidizing bacteria (MOB) (Bodelier 2011), but with no energy benefit. NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e can be oxidized by the enzyme and blocking the oxidation of CH\u003csub\u003e4\u003c/sub\u003e (Bodelier 2011). This hypothesis becomes more intriguing because a strong positive correlation between natural soil NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and CH\u003csub\u003e4\u003c/sub\u003e uptake was observed by Goldman\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (1995), but in a N availability range below the amount added in agricultural fields. Up to date no microbial group that promotes beneficial NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003eoxidation\u003csub\u003e\u0026nbsp;\u003c/sub\u003eis known\u003c/p\u003e\n\u003cp\u003eWe hypothesize that natural soils oxidize CH\u003csub\u003e4\u003c/sub\u003e but land use change an ammonium-based fertilizer amendment reduces the soil ability to consume CH\u003csub\u003e4\u003c/sub\u003e. We tested this hypothesis on soils from four Brazilian biomes. We used a pairwise scheme comparing adjacent soils from natural sites and agricultural fields from across these biomes (Fig 1). Ammonium sulfate was used to test the effect of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e addition on soil CH\u003csub\u003e4\u003c/sub\u003e oxidation. \u0026nbsp;The understanding of the impacts of land use change is crucial for calculating its trade-offs and weighing the values of ecosystems services.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExperimental design\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoils were sampled in four Brazilian biomes (Atlantic Forest, Cerrado, Caatinga and Pampas), in pairs of natural and cultivated adjacent areas (Fig 1, Table S1, Supplemental material). Independently of crop type, the criterion to fit within the experimental design was to receive fertilizer at least on annual basis. In total, 11 sites fitted within this criterion and comprise 3 sites with perennial crops, 2 sites with semi-perennial crop (sugarcane) and 6 sites with annual or rotational crops. The experimental design includes: natural soil; natural soil amended with N; cropped soil; cropped soil amended with N (4 treatments). Therefore, we can test if either land use or N amendment affects CH\u003csub\u003e4\u003c/sub\u003e uptake by soils.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSoil sampling and processing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSampling was carried out during autumn 2016, after crop harvest or during its senescence, avoiding acute and residual fertilizer effects. Composite samples were taken from each site up to the amount of around 20 kg of soil using hand augers (0-20 cm). Samples were brought to the laboratory and air-dried to enable sieving (2mm) and consequently homogenization. Soil available P, Ca\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e, Al\u003csup\u003e+3\u003c/sup\u003e, pH and micronutrients were determined according to van\u0026nbsp;Raij et al. (2001).\u0026nbsp;Inorganic N content was determined colorimetrically using soil extracts (2M KCl) based on the methods proposed by Norman et al. (1985) for NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026ndash;\u003c/sup\u003e and by Krom (1980) for NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e. Total soil organic C and N were determined by elemental analyzer (PerkinElmer CHN 2400, Waltham, EUA). Soil texture and chemistry parameters are found in Supplementary material (S2).\u003c/p\u003e\n\u003cp\u003eMicrocosms (n=4) for gas measurements were set up as suggested by Pitombo\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (2018) and were kept in an acclimatized room at 25\u0026plusmn;2\u0026deg;C. Using soil density, the mass of soil (dry basis) to put in each microcosm was determined in order to reach 300 mL of bulk soil. A pre-incubation period of one week at 40% of soil water-filled pore space (WFPS) was adopted to promote soil microbial community stabilization. Treatments that received N were amended with a (NH\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e solution to reach 100 mg N kg soil\u003csup\u003e-1\u003c/sup\u003e, which is within the concentration regularly found in cropped soils after fertilizer application and used in microcosm experiments. \u0026nbsp;As discussed by Pitombo et al\u003cem\u003e.\u003c/em\u003e (2018), this amount is equivalent to 50 kg N ha\u003csup\u003e-1\u003c/sup\u003e. Afterwards and for all treatments, WFPS was adjusted to 45%, which is around the optimum condition for soil CH\u003csub\u003e4\u003c/sub\u003e oxidation (del Grosso\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2000). Every day, during both the pre-incubation and after the gas sampling, 5 mg of C in the form of an artificial root exudates solution without N (van Zwieten\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2014) was added to each microcosm aiming to keep the soil basal respiration. Afterwards, soil moisture was adjusted by replacing the water while weighing the microcosms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGas analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the pre-incubation period, CH\u003csub\u003e4\u003c/sub\u003e fluxes were measured every day during ten days. Microcosms were only closed during sampling to avoid gas saturation. \u0026nbsp; Headspace gas samples were taken at 1; 30; 60 and 90 min after microcosm closure using 20 mL syringes. Methane concentrations were determined by gas chromatography (GC 2014 Shimadzu, Kyoto, Japan) using a flame ionization detector. All the sample volume (20 ml) was injected directly in the chromatograph inlet, which contains a sample loop that standardizes the sample volume carried for analysis. \u0026nbsp;The device was daily calibrated with three certificated standards (0.92; 1.81 and 3.58 ppm) and its limit of quantification is 0.1 ppm for CH\u003csub\u003e4\u003c/sub\u003e. Gas fluxes were calculated with linear regressions of gas concentration over time. Details of sampling, quality control and fluxes calculations are also described by Pitombo\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSoil DNA isolation and Real-Time PCR\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSoil samples from microcosms were frozen at -20\u0026deg;C for molecular analyses after the gas flux measurement period. DNA was extracted from 250 mg of soil using the PowerSoil DNA Isolation Kit (Mobio Laboratories, Carlsbad, USA) according to the manufacturer\u0026apos;s protocol. DNA quantity and quality were confirmed in 2% agarose gel and using a Synergy HTX microplate reader (BioTeK Inc., Winooski, Vermont, U.S.A) set for determining absorbance at 230, 260, 280 and 320 nm. Abundances of particulate methane monooxygenase encoding gene from both type I and type II methanotrophs were determined by quantitative real-time PCR. The primer set (pmof1 5\u0026rsquo;- AACTTCTGGGGNTGGAC-3\u0026rsquo;and pmor 5\u0026rsquo;- RCNACGTCNTTACCGAA-3\u0026rsquo;) was developed by Cheng\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (1999) and modified by Stoecker\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (2006), who increased the degeneration degree of the forward sequence. As this primer pair targets both type I and type II methanotrophs, we expected it would be used to assess the overall effects of land use change on methanotrophs abundance. Reactions were performed with a QuantStudio 3 (Applied Biosystems, Foster City, EUA) in the total volume of 10 uL using the SYBR\u0026reg; Green JumpStart\u0026trade; Taq ReadyMix chemistry, added of the respective reference dye (Sigma-Aldrich, San Luis, EUA). Annealing temperature was at 58\u0026deg;C, data were acquired at extension temperature (72\u0026deg;C) and melting curve analysis was performed to confirm specificity. A pool of sequenced amplicons from environmental samples was used as standard for the gene quantification. Number of amplicons per uL in the standard pool was determined based on fluorescence quantification (Quant-iT\u0026trade; dsDNA Assay Kit, Invitrogen, Carlsbad, EUA).\u0026nbsp;Standards were analyzed in triplicate while samples in two technical replicates, besides the experimental replication (n=4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analyses\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of variance (ANOVA) followed by Tukey test were used to determine both the pairwise and group differences in CH\u003csub\u003e4\u003c/sub\u003e fluxes within land uses and N addition. The same approach was used to test the land use effect on methane monooxygenase encoding gene abundances. We performed a nonmetric multidimensional scaling ordination (NMDS based on Euclidian dissimilarities of normalized data) to demonstrate whether biomes or soil parameter drive the differences in CH\u003csub\u003e4\u003c/sub\u003e uptake and methane monooxygenase encoding gene abundances. Thereafter, Generalized Linear Mixed Models (Bolker\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2009) were used to test the effects of soil parameters on CH\u003csub\u003e4\u003c/sub\u003e oxidation rate. The global model, which is the one that includes all the potential explanatory variables, was fitted using the \u0026lsquo;lme4\u0026rsquo; R package version 1.1\u0026ndash;10 (Bates\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2015). Replicates were included as random effect. Model selection was performed using the Akaike information criterion (AIC) for ranking after running all the model combinations using the \u0026lsquo;MuMIn\u0026rsquo; R package version 1.15.6 (Barton 2016). Models coefficients of determination (r\u003csup\u003e2\u003c/sup\u003e) were determined according to Johnson (2014). \u0026nbsp;We used normalized data (0 to 1) to improve the understanding of the magnitude effect of each explanatory variable on models describing CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethane flux measurements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults from the incubation experiment are presented in Fig 2. Overall, land use change resulted in significant inhibition of soil CH\u003csub\u003e4\u003c/sub\u003e oxidation (p\u0026lt;0.001). This result is also observed in the pairwise comparison (Fig 2), with exception of the soils from Caatinga and one from the Atlantic Forest biomes, which did not show active CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003eoxidation irrespective whether they come from native or cropped conditions (Fig 2). Soils under native vegetation displayed mean CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake of 7.3 ug C per kg soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e. Considering only soils that presented net CH\u003csub\u003e4\u003c/sub\u003e uptake, soils oxidized 11.9 ug C kg soil\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eday\u003csup\u003e-1\u003c/sup\u003e on average. We observed CH\u003csub\u003e4\u003c/sub\u003e oxidation rates of up to 28 ug C per kg soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e (Fig 2, Bras\u0026iacute;lia site \u0026ndash; Cerrado bioma). In such conditions CH\u003csub\u003e4\u003c/sub\u003e headspace concentrations in the microcosms decrease to around 0.7 ppm during the 90 min the microcosm remained closed for gas sampling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNitrogen addition statistically reduced CH\u003csub\u003e4\u003c/sub\u003e oxidation in soils from native sites (p=0.007). Soils that originally oxidized CH\u003csub\u003e4\u003c/sub\u003e with statistical significance passed to oxidize 7.976 ug C per kg soil\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eon average after N amendment, which is equivalent to 33% of inhibition. Additionally, inhibition was statistically significant in all the pairwise comparisons and ranged from 17% to 100% at the Araras and Pelotas sites, respectively (Fig 2). There was no statistical significance of N addition on CH\u003csub\u003e4\u003c/sub\u003e fluxes from cropped soils. Mean fluxes from these soils were -0.2 and -0.4 ug C per kg soil\u003csup\u003e-1\u003c/sup\u003e, without and with N addition, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethanotrophs abundance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLand use change reduced abundance of methanotrophs in all soils that actively oxidized CH\u003csub\u003e4\u003c/sub\u003e, with exception of one site from the pampa biome (Fig 2). Interestingly, cropped soils from Caatinga contained higher numbers of methanotrophs than soils under native vegetation (Fig 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactors driving CH\u003csub\u003e4\u003c/sub\u003e uptake\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNonmetric multidimensional scaling ordination of the methane monooxygenase encoding gene and CH\u003csub\u003e4\u003c/sub\u003e oxidation rate with all measured soil parameters indicated no grouping within biomes and these parameters (Fig 3). The same analysis pointed to the possible effect of sodium (Na) on the lack of CH\u003csub\u003e4\u003c/sub\u003e uptake and low methanotrophs abundance in the soils from Caatinga. The only soils that contain available Na are the ones from this biome. Therefore, the other soils that appear close to the Caatinga soil in the plot are likely more influenced by other factors like soil C, N, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and copper (see Fig 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThereafter we observed no grouping within biomes and CH\u003csub\u003e4\u003c/sub\u003e oxidation and methanotrophs abundance (Fig 3), we fitted generalized linear mixed models to identify the soil parameters that likely contributed to CH\u003csub\u003e4\u003c/sub\u003e oxidation. Global and best models are presented on Table 1. Parameters with higher values have more effect on soil CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake following data normalization. Therefore, the best model indicates low pH, soil C, available Fe and available Cu were the most important factors driving CH\u003csub\u003e4\u003c/sub\u003e oxidation rates in the studied soils. In contrast, available Al, available Mn and available Zn likely inhibit CH\u003csub\u003e4\u003c/sub\u003e oxidation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eSummary of the global and best models fitted to determine the explanatory variables are related to CH\u003csub\u003e4\u003c/sub\u003e uptake capacity\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003eGlobal model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003eBest model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eintercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026beta;\u003c/sup\u003e 0.095 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003esoil C\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e3.968 \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e4.770*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e5.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e0.116\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eFe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e3.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e7.439*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eMn\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e-10.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e-8,260*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eZn\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e-5.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e-2.432*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eCu\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e9.178*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e8.537*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eAl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e-11.469*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e-11.375*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eN-NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e1.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e___\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eN-NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e3.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e___\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eporosity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e___\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e-4.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e-3.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eLog pmoA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e___\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e-16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e-23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35.2564%;\"\u003e\n \u003cp\u003er\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.2906%;\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41.453%;\"\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003e\u0026beta;\u0026nbsp;\u003c/sup\u003ePositive values indicate the parameter helps to explain CH\u003csub\u003e4\u003c/sub\u003e uptake while negative values indicate they inhibit CH\u003csub\u003e4\u003c/sub\u003e oxidation. NS indicates no significant effect of the parameter in explaining CH\u003csub\u003e4\u003c/sub\u003e uptake despite the parameter is relevant to improve the model likelihood in the best fitted model; *p\u0026lt;0.05\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results show that changing natural tropical soils to croplands suppresses methane oxidation activity N addition reduced CH\u003csub\u003e4\u003c/sub\u003e oxidation rates as well but not as strong as land-use change.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe differences found in abundance of methanotrophic bacteria with different land use emphasizes the dominant effect of land use on atmospheric methane consumption. \u0026nbsp;In temperate ecosystems this effect is not as pervasive as observed in our study. However, the only exception was the Caatinga biome, from where all the soils did not show consistent methanotrophy. Similar results were observed from \u003cem\u003ein situ\u003c/em\u003e measurements performed in the natural Caatinga (Ribeiro\u0026nbsp;et al. 2016),. Semiarid regions cover 18% of global area and together with arid regions they would be an important sink of CH\u003csub\u003e4\u003c/sub\u003e and other trace gases (Galbally et al. 2008). However, our results indicate that the Caatinga soils are do not take up nor emit methane. These soils usually present low C stocks that should be correlated with low soil dissolved organic carbon (DOC) an important substrate and has a positive effect on CH\u003csub\u003e4\u003c/sub\u003e emissions (Wang et al. 2021). \u0026nbsp;Additionally, low nutrient availability can support low primary production. Caatinga has an uneven rainfall regime, with most of the time under negative water balances (Menezes et al. 2012)\u003c/p\u003e\n\u003cp\u003eAlthough methanotrophy is more intense at the first 10 cm, this process occurs along the soil profile (H\u0026uuml;tsch, 1998, Koschorreck and Conrad, 1993, Price\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2004). Therefore, we were unable to estimate the field CH\u003csub\u003e4\u003c/sub\u003e uptake based on this microcosm study. Nonetheless, field measurements have being performed in three of the sites from where the soils come from, totaling two under native vegetation and two cropped soils. At the \u0026ldquo;S\u0026atilde;o Luiz do Paraitinga\u0026rdquo; site, Carmo\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (2012) observed annual C-CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003emean fluxes of -1.35 mg m\u003csup\u003e2\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e, corresponding to around 5 kg C-CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003eha\u003csup\u003e-1\u003c/sup\u003e\u003csub\u003e\u0026nbsp;\u0026nbsp;\u003c/sub\u003eyear\u003csup\u003e-1\u003c/sup\u003e.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eIn our study, the soil from the same site oxidized 4 ug C-CH\u003csub\u003e4\u003c/sub\u003e kg soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003e(Fig 2), which is 3-fold lower than the average observed in all soils. It is worth to mention that Carmo\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (2012) observed consistent reduction of CH\u003csub\u003e4\u003c/sub\u003e uptake during late spring, together with an unusual pool of soil NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e (~40 mg NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u0026nbsp;\u003c/sup\u003ekg soil\u003csup\u003e-1\u003c/sup\u003e). A soil considered by Tate (2015) as a strong sink of CH\u003csub\u003e4\u003c/sub\u003e oxidizes about 8 kg C-CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003eha\u003csup\u003e-1\u003c/sup\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003eyear\u003csup\u003e-1\u003c/sup\u003e (Price\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e, 2004). Based on the relationship between the field and laboratory results, we could highlight the \u0026ldquo;Aiuruoca\u0026rdquo;, \u0026ldquo;Bras\u0026iacute;lia\u0026rdquo; and \u0026ldquo;Araras\u0026rdquo; soils under native vegetation as potential to be an even stronger sink of CH\u003csub\u003e4\u003c/sub\u003e.\u0026nbsp;Forest soils from China have oxidized about 1.2 ug C-CH\u003csub\u003e4\u003c/sub\u003e kg soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e in a laboratory study (Zeng\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2019), what is 20-fold lower than the values observed in the three soils within the high methane oxidation rate in this study.\u0026nbsp;Despite it was not included in the Nishisaka\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (2019) publication, the authors observed the CH\u003csub\u003e4\u003c/sub\u003e balance is virtually neutral at the \u0026ldquo;Sorocaba\u0026rdquo; site under native vegetation, in accordance with our microcosm study (Fig 3). Similar results were observed after annual measurements in the cropped soils both at the \u0026ldquo;Sorocaba\u0026rdquo; and \u0026ldquo;Araras\u0026rdquo; sites (Escanhoela\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2019; Pitombo et al. 2017).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSoil C, pH and Fe appear as relevant to explain soil CH\u003csub\u003e4\u003c/sub\u003e uptake rates. The modelling results (Table 1) indicate a negative correlation between pH and CH\u003csub\u003e4\u003c/sub\u003e uptake. Porosity regulates the diffusion of the gas in the soil (Striegl 1993). Despite porosity didn\u0026acute;t help to explain CH\u003csub\u003e4\u003c/sub\u003e uptake in soils as expected, soil organic matter was one of the parameters regulating CH\u003csub\u003e4\u003c/sub\u003e oxidation. \u0026nbsp;Organic matter, commonly represented by soil organic C, is the main soil conditioner, regulating water and nutrient availabilities as well promoting soil structure. The availability of labile carbon is essential for the maintenance of methanotrophic organisms and, according to El-Hawwary et al. (2022), abandoned agricultural areas or degraded areas can have their methanotrophic community reestablished with the enrichment of available organic carbon. Next to this, addition of organic residues to soils has been demonstrated to stimulate atmospheric methane uptake by agricultural soils (Ho et al 2015), which can be by changing soil aggregate structure (Van den Bergh et al 2024). This fact is of great importance for the recovery of degraded areas or recompositing of biomes, making it possible to reverse the functionality of the ecosystem in relation to its potential to absorb CH\u003csub\u003e4\u003c/sub\u003e from the atmosphere.\u003c/p\u003e\n\u003cp\u003eDespite the models showed soil porosity alone didn\u0026acute;t effect CH\u003csub\u003e4\u003c/sub\u003e uptake rates, the importance of soil porosity is evidenced with the effects of soil compaction on CH\u003csub\u003e4\u003c/sub\u003e uptake (Sitaula\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2000). Therefore, it suggests compaction might be one of the cofactors which lead to the land use chance effect on CH\u003csub\u003e4\u003c/sub\u003e uptake, once soil compaction is one of the effects of agriculture (Soane and van Ouwerkerk 1994). Another cofactor is the addition of N to the system, which, as we show, also has an impact on CH\u003csub\u003e4\u003c/sub\u003e uptake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe other parameters that either likely promote or inhibit methanotrophy are available micronutrients, Al and Na. The natural occurrence of these elements in soils depends mainly on the parent material from which the soil is originated. Sedimentary formations are usually poor while soils originated from basic rocks are rich in micronutrients (Abreu\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2012). Despite the authors didn\u0026acute;t present data regarding to micronutrients availability, Singh et al. (2009) observed CH\u003csub\u003e4\u003c/sub\u003e uptake rates higher in volcanic soils than in non-volcanic soils. Therefore, merging pedological mapping with CH\u003csub\u003e4\u003c/sub\u003e uptake rates would improve the bottom-up estimates of the gas turnover. Interestingly, our results indicated available Zn likely inhibit soil CH\u003csub\u003e4\u003c/sub\u003e oxidation rates. This observation corroborates with cell physiology studies that show that Zn is a well-known inhibitor of the particulate methane monooxygenase enzyme (Sirajuddin et al. 2014). On the other hand, Cu is the central component of this enzyme (Ross\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2019), and it has been experimentally demonstrated that the elemental amendment can increase soil methanotrophy (Ho\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2013b). Also interestingly, it has been suggested that when copper-to-biomass ratio of the cell is low, the iron-dependent methane monooxygenase is expressed (Murrell\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2000), corroborating with the statistical contribution of Fe to the soil CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake rate. The presence of Fe\u003csup\u003e3+\u003c/sup\u003e (an electron acceptors) can participate in the methane oxidation process and affect CH\u003csub\u003e4\u003c/sub\u003e emissions (Fan et al. 2021; Chen et al. 2022).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Additionally, transient conditions would reemerge a group that is not expected to be dominant in determined system, such as after the addition of organic byproducts (Ho\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e, 2019) or in soils subjected to drought and re-watering cycle systems (Cai\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2016). This might explain why methanotrophic abundance did not explained a significant amount of the variation observed in \u0026nbsp; \u0026nbsp;methane oxidation rates in this study (Table 1). Part of the quantified microorganisms represent the microbial seed bank, that is dormant up to favorable conditions are established (Lennon and Jones 2011). Notwithstanding, the qPCR results indicate the methanotrophy potential in the soils (Fig 2) and soils with more copies of methane monooxygenase encoding genes also presented greater CH\u003csub\u003e4\u003c/sub\u003e oxidation rates. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis assumption is based on the ratio between oxidized CH\u003csub\u003e4\u003c/sub\u003e and methanotrophs abundance. Observing the Fig 2, we might suggest a threshold close to 10\u003csup\u003e5\u0026nbsp;\u003c/sup\u003ecopies of methane monooxygenase encoding gene per gram in soils that present an active atmospheric CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003euptake. A gram of soil has oxidized 12 ng C-CH\u003csub\u003e4\u003c/sub\u003e day\u003csup\u003e-1\u003c/sup\u003e on average and it sustains around of 100 ng of methanothrophs biomass, taking into consideration the bacterial dry cell mass of 1 pg (Sender\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2016). The question that arises is if a ratio 10 between biomass and substrate used on a daily basis is enough to sustain the soil methanothroph community. Kolb\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (2005) estimated that at 25\u0026deg;C, which is our experimental condition, 40 x 10\u003csup\u003e-18\u003c/sup\u003e mol CH\u003csub\u003e4\u003c/sub\u003e cell\u003csup\u003e-1\u003c/sup\u003e h\u003csup\u003e-1\u003c/sup\u003e would allow the maintenance of the methanotrophic biomass at atmospheric level. This is equivalent to 1 x 10\u003csup\u003e-10\u003c/sup\u003e mol CH\u003csub\u003e4\u003c/sub\u003e g soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e, considering the same 10\u003csup\u003e5\u003c/sup\u003e active cells per gram of soil. However, our soils oxidized 1 x 10\u003csup\u003e-9\u003c/sup\u003e mol CH\u003csub\u003e4\u003c/sub\u003e g soil\u003csup\u003e-1\u003c/sup\u003e day\u003csup\u003e-1\u003c/sup\u003e, which is 10-fold higher than this theoretical value. Nonetheless, this range coincides with the 540 x 10\u003csup\u003e-18\u003c/sup\u003e mol CH\u003csub\u003e4\u003c/sub\u003e cell\u003csup\u003e-1\u003c/sup\u003e h\u003csup\u003e-1\u003c/sup\u003e estimated to the maintenance of the USC\u0026alpha; cluster (Kolb et al. 2005), the predominant group of methanothrophs in acidic upland soils (Kolb, 2009). Therefore, the amount of CH\u003csub\u003e4\u003c/sub\u003e oxidized in the studied soils is enough to the methanotrophs community maintenance. Additionally, the kinetics of oxidation in the microcosms was much more intense than the observed for the isolate presented in the study of Tveit et al. (2019). While the CH\u003csub\u003e4\u003c/sub\u003e concentration in the headspace of the pure culture decreased from ~1.9 ppm to ~1.4 after 120 days, in one set of microcosms (Bras\u0026iacute;lia site) the CH\u003csub\u003e4\u0026nbsp;\u003c/sub\u003econcentration in the headspace dropped linearly to around 0.7 ppm during the 90 min in all the forty measurements (4 replicates and 10 days).\u003c/p\u003e\n\u003cp\u003eAbundance of methanotrophs in Caatinga soils increased after land use change, unlike the other soils (Fig 2). Cropping these soils under such adverse climatic conditions might increase the ecosystem productivity and consequently the soil microbial biomass. However, this improvement in abundance does not reach the hereby suggested threshold requested to the observation of soil methanotrophy. The presence of facultative methanotrophs may explain the observed unexpected methanotrophy in same environment\u0026nbsp;\u0026nbsp; Several facultative methanotrophs have been isolated.\u0026nbsp;These organisms can use some multi-carbon compounds in addition to methane, often small organic acids, such as acetate, or ethanol (Haque et al. 2020).\u003c/p\u003e\n\u003cp\u003eThe methanotrophic community might be impacted by the addition of N to the system. However, we showed N wasn\u0026acute;t the only driver of inhibition of CH\u003csub\u003e4\u003c/sub\u003e uptake. As suggested by D\u0026ouml;rr\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e (2010), atmospheric methane oxidisers are oligotrophic species and the increase in soil organic C availability caused by fertile islands shifted the dominant taxa in microbial communities from oligotrophic trace gas oxidizers to copiotrophic organotroph (Li et al 2023). Raising the pH to improve the crop productivity might also increase microbial diversity (Lauber\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2009, Mendes\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al\u003cem\u003e.\u003c/em\u003e 2015) and, therefore, enhance microbial competition once the media becomes less restrictive. As proposed by Ho\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. (2013a), the type II methanotrophs are likely among the stress tolerator group within the Competitor‐Stress tolerator‐Ruderal framework of life strategies. Therefore, an intensive system like cropped soils will be detrimental to the high-affinity methanotrophic community. \u0026nbsp;In cropped sites, besides the physical-chemical factors, like porosity and nutrient availability, ecological interactions might also limit the methanotrophs maintenance and, consequently, CH\u003csub\u003e4\u003c/sub\u003e uptake by soils. There are multiple competing strategies that methanotrophs might be in disadvantage as oligotrophs in an intensified ecosystem. They include space competition by favorable habitats, competition for nutrients other than C, inhibition by secondary metabolites released from other microorganisms and perhaps predation (Hibbing\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2009). Nutrient enrichment increases the abundance of nematodes, which are important regulators of soil microbial communities (Thakur\u003cem\u003e\u0026nbsp;\u003c/em\u003eet al. 2019). In a rice field soil, Murase et al. (2008) observed that the protozoa from the studied site presented grazing preference on the different bacteria and methanotrophs. Therefore, a specific management that increase nematodes may decrease the methanotrophic abundance.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur measurements showed that upland soils in tropical agroecosystems are circum-neutral or a source of CH\u003csub\u003e4\u003c/sub\u003e. In contrast, soils under native vegetation predominantly present consistent methanotrophy. Soils from natural environments also presented higher abundance of methanotrophic bacteria, ratifying that land use change affects methanotrophic microbial communities and therefore biological methane oxidation. In this study we concluded that a typical N source that supplies NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e to the soil has not a pervasive effect on CH\u003csub\u003e4\u003c/sub\u003e uptake capacity as observed for land use change, reinforcing the importance of ecosystem conservation for the CH\u003csub\u003e4\u003c/sub\u003e cycle. We observed that soils rich in micronutrients present the most intense methanotrophy and methanotrophic bacteria abundance. Caatinga soils didn\u0026acute;t consumed CH\u003csub\u003e4\u003c/sub\u003e and this finding should be taken into consideration for reviewing ecosystem services provided by drylands. \u0026nbsp;Land use change results in the alteration of many parameters that are important to CH\u003csub\u003e4\u003c/sub\u003e uptake. Although specific parameters might be isolated in a cause-effect relationship, such as N amendment, compaction and facultative methanotrophs organisms, no parameter might be important the stability of CH\u003csub\u003e4\u003c/sub\u003e uptake or flexible metabolic mechanisms enable microorganisms to adapt in highly heterogeneous soil ecosystems and clime conditions like temperate climate regions. In times of intense climate change in the tropics and on the planet as whole, rethinking agriculture and biomass production models as well as changes in land use and intensive use of mineral fertilizers is emerging nowadays to minimize the potential increase in gas emissions, especially in the tropical areas that are recognized a more vulnerable site in the earth.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to FAPESP grant number (12/50694-6), CAPES for the Master\u0026rsquo;s scholarship granted to HDQ and to CNPq for the Postdoc scholarship granted to LMP (151572/2018-6). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received financial support from FAPESP (grant 12/50694-6). Scholarships were provided by CAPES (Master\u0026rsquo;s scholarship to HDQ) and CNPq (Postdoctoral fellowship to LMP, process 151572/2018-6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest/Competing Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbreu, C.A., Valladares, G.S., de Camargo, O.A., dos Santos, G.C.G., Paz-Ferreiro, J. (2012). Total and Available Copper in Some Soil Profile Samples from the State of S\u0026atilde;o Paulo. 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PMID: 35337832.\u003c/li\u003e\n\u003cli\u003eWang J, Cai C, Li Y, Hua M, Wang J, Yang H, Zheng P, Hu B (2018) Denitrifying anaerobic methane oxidation: a previously overlooked methane sink in intertidal zone. Environ Sci Technol 53(1):203\u0026ndash;212. https://doi.org/10.1021/acs.est.8b05742\u003c/li\u003e\n\u003cli\u003eWang Y, Hu Z, Shen L, Liu C, Islam ARMT, Wu Z, Dang H, Chen S (2021) The process of methanogenesis in paddy felds under different elevated CO\u003csub\u003e2\u003c/sub\u003e concentrations. Sci Total Environ 773:145629. https://doi.org/10.1016/j.scitotenv.2021.145629\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Caatinga, Cerrado, Atlantic Forest, Pampas, Greenhouse gases, methanotrophy","lastPublishedDoi":"10.21203/rs.3.rs-6630160/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6630160/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSoils are the only biological sink for atmospheric CH₄, making microbial methane consumption a highly relevant process. Land-use change toward agriculture can inhibit this process through the application of ammonium-based fertilizers. To test whether this effect plays a role in land-use changes in Brazilian biomes, we incubated natural and cultivated soils from four endangered Brazilian biomes: Caatinga, Cerrado, Pampas, and Atlantic Forest. Considering only soils that exhibited net CH₄ uptake, soils oxidized an average of 11.9 µg C kg⁻¹ soil day⁻¹. Ammonium sulfate amendment reduced CH₄ oxidation by 33% in pristine soils, while soils from agricultural fields exhibited no methane uptake. Except for soils from the Caatinga biome, pristine soils consumed atmospheric CH₄ and exhibited higher numbers of methanotrophic bacteria compared to managed soils. Our results suggest that a typical nitrogen source supplying NH₄⁺ did not exert as pervasive an effect on CH₄ uptake as did land-use change itself, reinforcing the importance of ecosystem conservation for maintaining the CH₄ cycle. Additionally, soil nutrient availability, particularly micronutrients, may play a key role in stimulating or inhibiting soil methanotrophy. In times of accelerated climate change in the tropics and globally, it becomes crucial to rethink agricultural practices, biomass production models, and patterns of land use and fertilizer application to minimize potential increases in greenhouse gas emissions\u003c/p\u003e","manuscriptTitle":"Land use change affects soil methane sink capacity of Brazilian biomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 03:58:43","doi":"10.21203/rs.3.rs-6630160/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"575cc2f1-f4b7-408f-b20c-f656dcab10bf","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T01:53:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 03:58:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6630160","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6630160","identity":"rs-6630160","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}