CH₄ and N₂O fluxes from planted forests and native Cerrado ecosystems in Brazil

ABSTRACT

Forest soils are N₂O sources and commonly act as CH₄ sinks. This study evaluated the dynamics of the CH₄ and N₂O fluxes of soils under Eucalyptus plantations and native Cerrado vegetation, as well as possible interactions between environmental factors and fluxes. The study was carried out in the Distrito Federal, Brazil, during 26 months, in three areas: in two stands of the hybrid Eucalyptus urophylla × Eucalyptus grandis, planted in 2011 (E1), and in 2009 (E2) and native Cerrado vegetation (CE). Measurements to determine the fluxes in a closed static chamber were carried out from Oct 2013 to Nov 2015. Soil and climate factors were monitored. During the study period, the mean CH₄ fluxes were –22.48, –8.38 and –1.31 μg CH₄ m^–2 h^–1 and the mean N₂O fluxes 5.45, 4.85 and 3.85 μg N₂O m^–2 h^–1 from E1, E2 and CE, respectively. Seasonality affected plantations in the studied sites. Cumulative CH₄ influxes were calculated (year-1: –1.86 to -0.63 kg ha^–1 yr^–1; year-2: –1.85 to –1.34 kg ha^–1 yr^–1). Cumulative N₂O fluxes in the three sites were ≤ 0.85 kg ha^–1 yr^–1. The change in land use from Cerrado to Eucalyptus plantations did not significantly changed regarding greenhouse gases (GHG), compared to the native vegetation. Flux rates of both gases (N₂O and CH₄) were low. Temporal variations in GHG fluxes and different ages of the stands did not cause significant differences in cumulative annual fluxes.

Eucalyptus; greenhouse gases; forest stand age; savanna

Introduction

Changes in land use have led tropical soils to estimated emissions of 0.2 Gt C yr¹, accounting for 10-30 % of total C emissions from deforestation ( Houghton, 1999 ; Achard et al., 2004 ). In 2010, GHG emissions were estimated at 49 × 10⁹ Mg CO₂eq, of which 21 to 24 % were generated by agriculture, forestry, and other land uses ( Tubiello et al., 2013 ; IPCC, 2014 ). In the context of a low-carbon economy, forest stands can be an option to reduce pressure on the native vegetation and mitigate the effects of climate change ( Bonan, 2008 ). In forest stands, Eucalyptus is the second most commonly planted genus, due to its high adaptability, fast growth, and economic value ( Iglesias-Trabado et al., 2009 ). Moreover, nutrients released in forest litter may enhance stabilization mechanisms of soil organic carbon (SOC) ( Huang et al., 2011 ).

Land-use changes alter chemical, physical, and biological properties of the soil, modifying the GHG fluxes ( Kim and Kirschbaum, 2015 ). In addition, forest type ( Masaka et al., 2014 ) and soil management practices play an important role ( Kim et al., 2016 ), as well as water-filled pore space ( Santos et al., 2016 ; Smith, 2017 ), soil O₂ contents, pH, plants, and N input ( Hickman et al., 2015 ; Carvalho et al., 2017 ). Moreover, long-term N inputs may favor soil C stocks, mainly in litter with a high lignin content ( Grandy and Neff, 2008 ). Microbial communities can be altered by climate warming, N fertilization, pH and the C:N ratio ( Högberg et al., 2007 ; Lucas et al., 2007 ). In particular, metabolic responses of the microbial community to N enrichment are complex and highly variable ( Michel and Matzner, 2003 ).

Native forests and commercial Eucalyptus stands of different ages have been little studied about the potential emission or consumption of GHG, but they are main drives for GHG fluxes in the Cerrado region. This study investigated GHG emissions with a two-year GHG monitoring program in natural and planted forests. The objectives were: (a) evaluate CH₄ and N₂O fluxes of soils under planted Eucalyptus forests of different ages (established in 2009 and 2011) and managements, and under native Cerrado vegetation, (b) describe fluxes and their interactions with seasonality and environmental variables, and (c) determine cumulative N₂O and CH₄ fluxes in soils of Eucalyptus forests of different ages and in native Cerrado vegetation.

Materials and Methods

Description of the study site

The three studied sites were located in the central region of Brazil (Central Plateau) in Paranoá, Distrito Federal ( Figure 1 ). The native forest consisted of an area of 3.5 ha of native Cerrado vegetation (CE) (Latitude 15^o53’45.51” S, Longitude 47^o38’40.69” W; Altitude 930 m a.s.l.) and belonged to the phytophysiognomic formation “cerradão”, a woodland savanna with short semideciduous forest, 10 to 15 m tall, of medium density ( FAO, 2001 ).

Figure 1
– Location of the study site, rural center Quebrada dos Neres, Paranoá, Distrito Federal, Brazil. Source: IBGE (2009).

The planted forest consisted of, respectively, 12 and 19 ha, each with a Eucalyptus urophylla × Eucalyptus grandis hybrid stand: E1- clone EAC 1528 (Latitude 15^o53’06.44” S, Longitude 47^o39’37.10” W; 948 m a.s.l.) and E2 - clone GG100 (Latitude 15^o53’48.24” S, Longitude 47^o38’37.22” W; 946 m a.s.l.).

Tree seedlings were planted in E1 in Dec 2011, at 3.5 m × 1.7 m spacing in a site previously covered with native Cerrado vegetation. Soil tillage consisted of disking and subsoiling in the planting row to a depth of 1.2 m.

The tree seedlings in E2 were planted in Dec 2009 (3.5 m × 1.7 m). The site had previously been used for cropping soybean (2003 to 2005), sorghum (2006), and soybean again (2007-2009). Soil tillage consisted of heavy disk harrowing (width 1.5 m) and opening furrows in the center of the row to a depth of 25 cm.

In the Eucalyptus plantations (E1 and E2), soil acidity was corrected by incorporating dolomitic limestone (2.5 t ha¹) to a depth of 20 cm and with 700 kg ha¹agricultural gypsum applied on the soil surface two months later. Fertilization at planting consisted of NPK (5-25-15), corresponding to 16.52 kg N ha¹. After one year, a side dressing of 60 kg K₂O ha¹ was applied in the form of potassium chloride, 50 kg N ha¹ in the form of urea, and 1 g boron per plant in the form of borax. In Jan 2014, the application of 60 kg K₂O ha¹ was repeated.

The soil of the experimental site was classified as clayey Oxisol (Typic Haplustox) ( Soil Survey Staff, 2006 ). The soil chemical properties and density (0-5 and 5-10 cm depth) are listed in Table 1 . Table 2 shows the litter quality in E1, E2 and CE. The C:N ratio in the litter ranged from 66:1 to 75:1 and the lignin content, from 99.5 to 162.0

Table 1
– Soil chemical properties in two layers (0-5 and 5-10 cm) in Eucalyptus stands (E1, clone EAC 1528 planted in 2011 and E2, clone GG100 planted in 2009); and CE (native Cerrado vegetation), Distrito Federal, Brazil.

Variables		E1	E2	CE	E1	E2	CE
Property	Unit of measurement	Soil depth 0-5 cm			Soil depth 5-10 cm
Organic matter	dag kg–1	3.3	3.0	3.8	2.9	2.6	3.2
pH	(H2O)	5.0	5.4	5.1	4.9	5.3	5.1
P*	mg dm–3	1.5	5.3	1.8	1.4	3.5	1.2
H+Al	mg dm–3	8.2	7.0	9.5	8.3	7.1	8.6
SB	mg dm–3	1.8	4.3	1.3	1.6	2.6	0.8
CEC	mg dm–3	10.0	11.3	10.8	9.8	9.7	9.5
V	%	17.7	38.0	11.8	15.8	26.7	8.7
B	mg kg–1	0.5	1.1	0.5	0.5	0.9	0.5
Zn	mg L–1	0.3	0.6	0.6	0.3	1.3	0.4
Soil density	g cm–3	0.98	0.96	0.97	0.99	0.96	0.98

• P* = phosphor Mehlich-1; H+Al = potential acidity; SB = sum of bases; CEC = cationic exchange capacity; V = base saturation; B = boron; Zn = zinc.

Table 2
– Litter quality in Eucalyptus stands (E1, clone EAC 1528 planted in 2011 and E2, clone GG100 planted in 2009); and CE (native Cerrado vegetation), Distrito Federal, Brazil.

Area	Ls	K	C	N	L	C:N
	Mg ha–1	------------------------- g kg–1 --------------------------
E1	10.8	0.0012	463.4	6.15	99.5	75:1
E2	13.7	0.0009	465.7	7.04	114.6	66:1
CE	7.6	0.0021	460.0	6.53	162.0	70:1

• Ls = litter stock; K = decomposition constant; C = carbon; N = nitrogen L = lignin.

The regional climate is Aw (rainy tropical), according to Köppen-Geiger classification ( Cardoso et al., 2014 ), with two well-defined seasons: dry season (May–Sept) and rainy season (Oct–Apr). The mean annual precipitation observed in the last 40 years was 1345.8 mm ( Silva et al., 2017b ). The precipitation in year-1 and year-2 was 1210.9 and 1305.6 mm, respectively, and > 94 % of the rain was concentrated in the rainy season. The average air temperature was 21.4 and 22.2 °C in year 1 and 2, respectively ( Figure 2 ).

Figure 2
– Precipitation (mm) and air temperature (ºC) from Oct 2013 to Nov 2015, Paranoá, Distrito Federal, Brazil.

Measurements of CH4 and N2O fluxes

The CH₄ and N₂O fluxes were measured from Oct 2013 to Nov 2015, distinguished in year-1 (Oct 2013 to Sept 2014) and year-2 (Oct 2014 to Nov 2015). The years were analyzed separately to identify the behavior of GHG fluxes and contributions of the soil-climate variables.

The closed-chamber method was used for measurements ( Alves et al., 2012 ), with a sampling frequency of three times per month ( Zanatta et al., 2014 ), since the sites with fully established Eucalyptus trees were not fertilized with synthetic N. Three 30 m × 30 m plots were randomly delimited in each site. To ensure representativeness of the system, four closed chambers were installed per plot, two in the Eucalyptus rows and two in-between rows, spaced 10 m. The chambers in the rows did not receive N fertilization after the first experimental year. In CE, four static gas chambers were placed randomly in each plot, resulting in 36 chambers installed in the sites. Each closed chamber consisted of a metal base (0.38 m × 0.58 m) inserted into the soil, and an upper part of PVC (height 9.5 cm), coated with a thermal aluminum blanket, which, together with the metal base, sealed the space covered by the chamber, where the gases accumulated for later collection and determination.

A hole was drilled in the center of the top part of each chamber and connected to a rubber hose and a three-way valve, by which the gas outlet could be controlled at sampling. Digital thermometers were installed to monitor the air temperature within the chambers.

The soil temperature was measured at 5 cm deep with a digital thermometer at the sampling times. The gas samples were captured between 09h00 a.m. and 11h00 a.m., following the recommendation of Alves et al. (2012) , to best represent the daily average flux. The air trapped in the chambers was sampled at 0, 15, and 30 min after closing the device. A 60-mL polypropylene syringe was used, coupled with a three-way valve, in which 30 mL gas samples were collected and transferred to vials. In addition, one sample of atmospheric gas per plot was taken as reference to analyze gas samples. Before and after sampling, the vials were transported in ice-cooled thermal boxes and stored in a refrigerated environment at 16 ºC for measurements.

The CH₄ and N₂O concentrations were determined with a gas chromatograph (Trace 1310 GC ultra) equipped with a Porapak Q column at 65 °C, an electron capture detector (ECD) and a flame ionization detector (FID). The following standards were used: 200, 600, 1000 and 1500 ppb N₂O; and 1000, 5000, 10000 and 50000 ppb CH₄. The calculated detection limit was 51 ppb for N₂O and 145 ppb for CH₄ and the calculated quantification limit 154 ppb for N₂O and 484 ppb for CH₄. The CH₄ and N₂O fluxes were measured by the linear variation in gas concentration in relation to the incubation time in closed chambers, and calculated by Equation (1), as proposed by Bayer et al. (2015) :

$\mathrm{Flux}=\mathrm{\delta C}/\mathrm{\delta t}(\mathrm{V}/\mathrm{A})\mathrm{m}/\mathrm{Vm}$ (1)

where in the flux (µg m²h¹); dC/dt is the change in gas concentration (nmol N₂O and CH₄ h¹) in the chamber in the incubation interval ( t ); V and A are, respectively, the chamber volume (m³) and the soil site covered by the chamber (m²); m is the molecular weight of N₂O or CH₄ (µg), and Vm is the molar volume at the sampling temperature.

The fluxes were calculated for the sampling times 0, 15, and 30 min, expressed in μg N₂O m² h¹ and µg CH₄ m² h¹. The average daily N₂O and CH₄ fluxes were calculated from the average value of the four chambers installed per plot. To determine the cumulative fluxes, the area under the curve was integrated, based on the daily N₂O and CH₄ soil fluxes ( Santos et al., 2016 ). The amount of equivalent carbon (C eq) required to mitigate the cumulative annual fluxes of CH₄ and N₂O was calculated by Equations 2 and 3, respectively.

${\mathrm{CH}}_4=(\mathrm{CAI}*16/12)*\mathrm{GWP}*\mathrm{F}$ (2)

where: CAI is the cumulative annual influx (kg CH₄ ha¹ yr¹); GWP is the global warming potential of CH₄ (25 kg CO₂, IPCC (2007) ); F is the factor 0.273 (used for the conversion from CO₂ to C);

${\mathrm{N}}_2\mathrm{O}=(\mathrm{CAF}*44/28)*\mathrm{GWP}*\mathrm{F}$ (3)

where: CAF is the cumulative annual flux (kg N₂O ha¹ yr¹); GWP is the global warming potential of N₂O (298 kg CO₂, IPCC (2007) ); F is the factor 0.273(used for conversion from CO₂ to C).

Environmental factors

For each gas sampling, soil samples from the 0-5 cm layer were also collected to determine mineral N in the forms of nitrate (NO₃^–) and ammonium (NH₄⁺), at eight points near the chambers, forming a composite sample. From each soil sample, a sub-sample was taken to determine gravimetric soil moisture. For the extraction of NO₃^– and NH₄⁺, we used 50 mL of a solution of 2 mol L¹ KCl , according to the methodology of Bremner and Mulvaney (1982) . The solution was analyzed by spectrophotometry with a system of flux injection analysis (FIA) ( Hambridge, 2007a , b ) to determine NO₃^– and NH₄⁺ concentrations.

Soil particle density was determined by the ring and volumetric flask methods, respectively ( Embrapa, 1997 ). Soil moisture was calculated by oven-drying a soil sub-sample of known weight at 105 ºC for 48 h. From these variables, the water-filled pore space (WFPS in %) was calculated for each gas sampling date and determined by the equation:

$\mathrm{WFPS}=(\mathrm{gravimetric}\mathrm{moisture}\times \mathrm{BD})/[1–(\mathrm{BD}/\mathrm{PD}\left)\right]\times 100$ (4)

where: the gravimetric moisture is expressed in %, BD is the bulk density (g cm³) and PD is the particle density (2.65 g cm³).

The meteorological data were recorded using a datalogger (CR 1000) installed near the study site.

Calculations and statistical analyses

The environmental variables were subjected to the descriptive statistical analysis and applied to the normality test (Shapiro-Wilk), followed by analysis of variance (ANOVA). The daily CH₄ and N₂O fluxes had a non-normal distribution; therefore, the nonparametric Kruskal-Wallis test of medians was performed at 5 % probability to find possible differences between the areas and years studied by comparisons.

The CH₄ influxes and accumulated N₂O fluxes for the sampling dates were calculated by linear interpolation. To compare sites and years, the data of accumulated fluxes and equivalent carbon were subjected to analysis of variance (ANOVA) and the Tukey test ( p < 0.05).

Another analysis evaluated the seasonality effect and the relationship between CH₄ and N₂O fluxes and the environmental variables by the Pearson’s correlation, using the FactoMineR package of program R (version 3.2.2). Only significant correlations are shown in the text.

Results

Temporal variation in CH4 and N2O fluxes and environmental variables

Daily and seasonal CH₄ fluxes for year-1 and year-2 in each site are presented in Figure 3A . Year-1 had annual average of CH₄ fluxes of –35, –3 and –2 μg m² h¹, while year-2 had –22, –8 and –1 μg m² h¹ in E1, E2, and CE, respectively. Regarding the seasonality effect, the average CH₄ fluxes were –32, –12 and 11 μg m² h¹ and –38, 9, and –20 μg m² h¹for year-1, and in year-2, –20, –5 and –6 μg m² h¹ and –29, –17 and –7 μg m² h¹ in the rainy and dry seasons in E1, E2, and CE, respectively ( Figure 3A ). In year-1, significant differences were observed between the environments, where the average CH₄ flux in the rainy season was higher in CE than in E1 ( p = 0.0002) and E2 ( p = 0.0196). In the dry season, the average CH₄ fluxes were higher in E2 ( p = 0.0191).

Figure 3
– (A) Soil fluxes of methane (CH4) and (B) nitrous oxide (N2O) in the Eucalyptus stands E1 (clone EAC 1528, planted in 2011) and E2 (clone GG100, planted in 2009); and in CE (native Cerrado vegetation), Paranoá, Distrito Federal, Brazil.

The mean annual N₂O fluxes were 4, 8, and 3 μg m² h¹ for year-1 and 5, 5, and 4 μg m² h¹ for year-2 in E1, E2, and CE, respectively ( Figure 3B ). Average N₂O fluxes in the rainy season for E1, E2, and CE were, respectively, 1.00, 4.00, and 0.07 μg m² h¹ (year-1) and 7, 4, and 3 μg m² h¹(year-2), and in the dry season 10, 14, and 7 μg m² h¹ (year-1) and 3, 7, and 5 μg m² h¹ (year-2) ( Figure 3B ). In year-1, significant differences between N₂O fluxes were observed in the rainy season, with the highest average N₂O fluxes in E2 ( p = 0.0196). However, in year-2, differences were only significant in the rainy season between the average fluxes in E1 and CE ( p = 0.0273), which were higher for E1.

In all GHG evaluation, an uptake of CH₄ was observed in 44 % of the evaluations in CE, but in 19 % in the Eucalyptus stands. For N₂O, the average fluxes were 5, 6, and 4 μg m² h¹ in E1, E2, CE, respectively. In this study, the results of CH₄ and N₂O fluxes in the Eucalyptus rows and interrows were not shown, since the differences were not significant.

The environmental variables showed that the CH₄ pulse in μg m² h¹ (64 ± 77 in Sept 2014, 131 ± 179 in June 2014 and 85 ± 131 in Sept 2014) coincided with WFPS values of 25 % for E1, 42 % for E2, and 33 % for CE in year-1. In year-2, CH₄ pulses 266 ± 365 (May 2015), 104 ± 429 (Feb 2015), and 156 ± 292 μg m² h¹ (May 2015) coincided with WFPS values of 47 %, 40 %, and 68 % for E1, E2, and CE, respectively ( Figures 3A and 4A ). The N₂O pulses of 39 ± 72 (May 2014), 108 ± 97 (Aug 2014), and 58 ± 87 μg m² h¹ (Sept 2014) coincided with WFPS values of approximately 33 % in all treatments in year-1, while in year-2, the N₂O pulses 21 ± 81 (Feb 2015), 42 ± 65 (July 2015) and 27 ± 83 μg m² h¹ (May 2015) coincided with WFPS values of 37 %, 34 %, and 39 % for E1, E2, and CE, respectively ( Figures 3A and 4A ).

Figure 4
– (A) - Water-filled pore space (WFPS); (B) - nitrate NO3–; (C) - ammonium NH4+ and (D) - soil temperature from Oct 2013 to Nov 2015 in Eucalyptus stands (E1, clone EAC 1528 planted in 2011 and E2, clone GG100 planted in 2009); and CE (native Cerrado vegetation), Paranoá, Distrito Federal, Brazil.

In year-1, the Cerrado was the only site with a correlation of 0.58 ( p = 0.0018) and –0.68 ( p = 0.0015) between the CH₄ flux and WFPS, respectively, in the rainy and dry seasons. Only in E2, correlations were detected between N₂O fluxes and WFPS in the rainy and dry seasons (0.63 ( p = 0.0005) and –0.59 ( p = 0.0041), respectively). In year-2, WFPS ranged from 19 % to 71 % in the rainy and from 30 % to 43 % in the dry season. With regard to correlations, CH₄ and WFPS in CE positively correlated (0.84; p < 0.0001). For N₂O, a correlation with WFPS of 0.62 ( p = 0.0190) was observed in E1, both correlations occurred in the dry season.

In year-1, the soil temperature in all sites remained between 17 and 24 ºC. The highest CH₄ and N₂O pulses occurred at soil temperatures ≥ 19 ºC. With regard to correlations, CH₄ and soil temperature in CE positively correlated (0.65; p = 0.023). In year-2, the soil temperature ranged from 16 to 26 ºC and was correlated with CH₄ flux in E2 (0.59; p = 0.024).

Soil mineral N dynamics

The highest soil NO₃^– and NH₄⁺ concentrations were recorded in the rainy season in all sites ( p < 0.0240) ( Figures 4B and 4C ) and did not coincide with the GHG pulse. In the rainy season of year-1, a correlation of –0.68 between CH₄ × NO₃^– ( p = 0.0004) in E1 was identified of 0.49 and 0.53 between N₂O × NO₃^– ( p = 0.0033), and N₂O × NH₄⁺ ( p = 0.0023) in CE, while in the dry season, the correlation was 0.55 between CH₄ and NO₃^– ( p = 0.0065) in CE.

The ammoniacal N was predominant ( Figure 4C ). The NO₃^–concentrations were higher in the rainy season ( p < 0.0093). The N₂O soil pulse coincided with NO₃^– concentrations < 0.50 mg kg¹of soil and only in some moments, NO₃^– exceeded 2.00 mg kg¹soil ( Figure 4B ). The seasonality effect on NH₄⁺ concentrations differed only in CE, with higher soil concentrations in the dry season ( p < 0.0001), coinciding with higher N₂O pulse in all studied sites. In year-2, NO₃^– and NH₄⁺ soil concentrations were very close between the sites, except for E2, where concentrations were below 1 mg kg¹of soil, from Feb 2015 onwards ( Figures 4B and 4C ). With regard to correlations, E1 was the only area in which N₂O and NO₃^– concentrations negatively correlated (–0.63; p = 0.002) during the dry season.

Cumulative CH4 and N2O fluxes and carbon equivalent (C eq)

In the study period, cumulative fluxes were not influenced by annual variation, age of Eucalyptus stands, or by the replacement of native vegetation for Eucalyptus . For N₂O, variations were 0.33 to 0.85 kg ha¹ yr¹ in year-1 and 0.32 to 0.43 kg ha¹ yr¹ in year-2 ( Table 3 ). The CH₄values were negative, with cumulative influxes of –1.86 to –0.63 kg ha¹ yr¹ in year-1, and –1.85 to –1.34 kg ha¹yr¹in year-2 ( Table 3 ).

Table 3
– Cumulative fluxes and Carbon equivalent (C eq) of N2O and CH4 in Eucalyptus stands (E1, clone EAC 1528 planted in 2011 and E2, clone GG100 planted in 2009); and CE (native Cerrado vegetation) in year-1 and year-2; Distrito Federal, Brazil.

Area	Year-1*
	N2O	C equivalent	CH4	C equivalent
------------------------------------- kg ha–1-----------------------------------------
E1	0.43 (± 0.26)	55 (± 33)	–1.86 (± 0.26)	–16 (± 12)
E2	0.85 (± 0.30)	108 (± 58)	–0.98 (± 0.30)	–8 (± 8)
CE	0.33 (± 0.20)	42 (± 25)	–0.63 (± 0.20)	–5 (± 5)
N	9	9	9	9
P	0.05	0.05	0.05	0.05
Year-2*
E1	0.39 (± 0.18)	52 (± 23)	–1.34 (± 0.36)	–11 (± 3)
E2	0.44 (± 0.01)	58 (± 11)	–1.85 (± 1.40)	–15 (± 11)
CE	0.32 (± 0.01)	43 (± 10)	–1.55 (± 1.68)	–13 (± 14)
N	9	9	9	9
P	0.05	0.05	0.05	0.05

• *Year-1 = Oct 2013 to Sept 2014; Year-2 = Oct 2014 to Sept 2015.

The C eq ranged from 42 to 108 kg ha¹ in year-1 and from 40 to 54 kg ha¹ in year-2. However, on an annual basis, the cumulative C eq for CH₄ was negative in all sites evaluated (–6 to –17 kg ha¹ in year-1; –12 to –17 kg ha¹ in year-2) ( Table 3 ).

The C eq ranged from 42 to 108 kg ha¹ in year-1 and from 40 to 54 kg ha¹ in year-2. However, on an annual basis, the cumulative C eq for CH₄ was negative in all sites evaluated (–6 to –17 kg ha¹ in year-1; –12 to –17 kg ha¹ in year-2) ( Table 3 ).

Discussion

Temporal variability of CH4 and N2O fluxes and environmental variables

The CH₄ influxes were predominant in this study (81 % for E1 and E2, and 57 % for CE), reaffirming that forest soils are common sinks of this gas. The same behavior was observed in other studies ( Godoi et al., 2016 ; Liu et al., 2017 ). In general, well-drained soils consume atmospheric CH₄ ( Ciais et al., 2013 ; IPCC, 2013 ) and indicate CH₄ uptake from the atmosphere mediated essentially by methanotrophic bacteria due to reduced soil water content, favoring diffusion of atmospheric CH₄ into soils ( Hiltbrunner et al., 2012 ). Other studies focused on savannas also mentioned these uptake conditions. In Eucalyptus globulus stands and Australian savanna vegetation, respectively, Livesley et al. (2009) recorded influxes of –7 and –16 μg m² h¹. In areas under cerradão, Siqueira-Neto et al. (2011) reported negative CH₄ fluxes between –93 and –29 μg m² h¹.

The CH₄ pulses in the three sites occurredin the dry season. Priano et al. (2014) found an inverse relation between CH₄ emission rate and WFPS. The results of this study also indicate that wet soils can oxidize as much CH₄ as relatively dry soils, with average WFPS values near 40 % in the study period. Previous reports also demonstrated that peaks of CH₄ soil oxidation occur at some intermediate level of soil water content ( Khalil and Baggs, 2005 ). According to Humer and Lechner (1999) , the optimum saturation degree for oxidation is between 40 and 80 % (moisture content between 25 and 50 %). Moreover, measuring potential methane (CH₄) oxidation rates in semiarid soil, Sullivan et al. (2013) observed that CH₄ oxidation rates were higher in the wet than in the dry season.

During the assessed period, N₂O fluxes in soil under native vegetation (CE) rarely exceeded 10 μg m² h¹. This is attributed to the very low amount of NO₃^– and to the predominant N form (NH₄⁺) ( Figures 3B and 3C ) that did not induce high N₂O emissions. These results were similar to previous descriptions in studies on Oxisols under native Cerrado vegetation, which reported few measurements above 10 μg m² h¹ and average fluxes between 0.6 and 16 μg N₂O m² h¹ ( Siqueira-Neto et al., 2011 ; Santos et al., 2016 ; Carvalho et al., 2017 ).

In year-1, the N₂O fluxes were higher in the dry than in the rainy season. Even under conditions in which fluxes are common (WFPS > 48 %, predominance of NH₄⁺ and soil temperature > 21 ° C), very high fluxes were not observed in the entire dry season, but only in late Aug (08/28/2014). At this time, mineral N exceeded 5.0 mg kg¹soil (lower than in the rainy season) and the soil temperature rose from 17 to 20.3 ºC. From Sept onwards, the soil temperature was 23 ºC. In this period, there was possibly a response in the N₂O pulses to the increase in soil temperature in E1 and CE, however low (< 59 μg m² h¹).

Forest soils in the Cerrado biome usually have low N₂O fluxes, which can be attributed to the physical, chemical, and biological characteristics of the system ( Martins et al., 2015a ; Martins et al., 2015b ; Santos et al., 2016 ). In general, N availability in tropical savanna ecosystems in Brazil is low, since 15 – 37 % of N is resorbed prior to leaf dehiscence ( Nardoto et al., 2006 ) and in the Cerrado, inorganic N is available by mineralization of SOM ( Catão et al., 2016 ). Under undisturbed conditions, N pools are at steady state and production and consumption are equal (Booth, 2005); thus, the annually mineralized inorganic N in unburned Cerrado does not exceed 15 kg ha¹yr¹( Nardoto et al., 2006 ). With these efficient cycling and use mechanisms, little N is lost by leaching or gas transformation ( Bustamante et al., 2006 ).

Under natural conditions, available N in Cerrado soils depends to a large extent on organic sources and litter ( Table 2 ). The equilibrium between mineralization and immobilization depends on the C: N ratio, which is high (> 65:1) in this study and on the material incorporated into the soil, which may induce N immobilization, showing that residue quality also influences N₂O emissions. According to Alluvione et al. (2010), a high C:N ratio may increase N immobilization thus reducing the occurrence of denitrification and consequently of GHG emissions.

Another important factor to be considered is the cycling efficiency. If high, low values of mineral N can be established in the soil, and the N mineralized by decomposition can be absorbed quickly by the plant root system, after nitrification and denitrification ( Ugalde et al., 2007 ). Low rates of N₂O and CH₄ emissions were also documented in other studies on forests in Brazil, Australia, and China. Godoi et al. (2016) observed similar fluxes of CH₄ (–22.7 and –24.4 mg CH₄ m² h¹) and N₂O (5.3 and 5.4 mg N₂O m² h¹), for soils with Acacia and native vegetation, respectively. Werner et al. (2006) observed values near 7 mg N₂O m² h¹in reforested areas in China, under tropical conditions, while Allen et al. (2009) reported a high CH₄ uptake (–1 to –50 µg CH₄ m² h¹) and low N₂O fluxes (–5 to 50 μg N₂O m² h¹) in subtropical Australian soils under Eucalyptus .

In general, when good drainage conditions, which reduce WFPS ( Baggs and Philippot, 2010 ), are combined to a low relative NO₃^– production, the mineral N concentrations rarely exceed the N demand of microorganisms and plant roots ( Martins et al., 2015b ). Although several studies reported correlations between GHGs and mineral N in the soil ( Siqueira-Neto et al., 2011 ; Santos et al., 2016 ; Carvalho et al., 2017 ), and in this study, some correlations between these N forms and gas fluxes were also observed, the gas emission pulses did not occur synchronously with the highest NO₃^– and NH₄⁺ concentrations, which may have reduced the significance of relations.

In this study, the GHG fluxes were low, regardless of the season and year studied, which was mainly associated to WFPS < 50 % and NO₃^– concentrations < 8 mg kg¹. In soils with high permeability, such as in the Oxisol of this study, both WFPS and texture are key factors in N₂O emission. In soils with WFPS > 60 %, denitrification tends to be the predominant process ( Livesley et al., 2009 ; Gregorich et al., 2015) , while in low WFPS soils, ammonia oxidation is favored ( Bateman and Baggs, 2005) . These findings show that Eucalyptus stands of different ages and areas of native Cerrado vegetation probably contribute to reduce N₂O emissions, where no external N sources are provided and the systems depend exclusively on internal nutrient cycling. Furthermore, based on the predominant form of mineral N (NH₄⁺), it is assumed that the studied N₂O emissions may result from nitrification rather than from denitrification processes.

However, it should be considered that transformations of N (immobilization or mineralization) in an ecosystem are coupled with C transformations, especially when organic carbon molecules are converted into CO₂ by soil heterotrophic microbial populations ( McGill and Cole, 1981 ), which can reduce the partial pressure of oxygen and favor denitrification. Significant GHG pulse emissions following the first rains after a dry season, often with a short time lag, have been reported in different seasonally dry ecosystems. The pulses are generally preceded by significant GHG emissions immediately after the soil is re-moistened, due to water-induced activation of soil microbes ( Santos et al., 2016 ).

Studies show that soil moisture expressed by WFPS, soil temperature, and mineral N content are the main variables that control and express GHG emissions ( Bayer et al., 2015 ). Siqueira-Neto et al. (2011) reported divergent observations for native Cerrado vegetation, where lower N₂O emissions were observed during the dry season, indicating that the seasonal variations occur due to the absence of rainfall and consequent reduction in soil moisture.

In this study, no environmental variable stood out as an environmental drive, despite variables with relevant effects on N₂O emissions in agricultural systems found by our research group ( Santos et al., 2016 ; Carvalho et al., 2017 ; Sato et al., 2017 ). Therefore, these results indicate that the lack of consistent environmental effects may be due to both the intrinsic low GHS emission and the high spatial/temporal variability of native and cultivated forest environments in the Cerrado.

Cumulative CH4 and N2O fluxes

The cumulative annual CH₄ fluxes were negative for the areas and years studied ( Figures 4B and 4D ). The cumulative CH₄ flux from Eucalyptus under the conditions assessed shows the crop potential of methane mitigation. These cumulative CH₄ influxes in Eucalyptus plantations and native savanna vegetation are in agreement with reports of emissions from forests and savannas ( Table 4 ) that indicate CH₄ uptake from the atmosphere, since a greater amount was consumed by the environment than the effectively produced quantity ( Bustamante et al., 2012 ).

Table 4
– Literature review of annual or partial rates of CH4 and N2O fluxes in forest soils.

Country	Site	CH4	N2O	Reference
		----- kg ha–1 -----
Brazil	Woodland	-	–0.50	Carvalho et al. (2017)
Brazil	Woodland	-	0.07	Silva et al. (2017a)
Brazil	Cerrado stricto sensu	-	0.55	Sato et al. (2017)
Brazil	Cerrado stricto sensu	-	0.28	Santos et al. (2016)
Brazil	Cerrado stricto sensu	–4.4	0.40	Carvalho et al. (2014)
Brazil	eucalyptus urograndis	-	0.7	Coutinho et al. (2010)
Africa	Savanna vegetation	-	2.33	Castaldi et al. (2013)
Australia	Native Forest (Savanna)	–1.6	0.02	Grover et al. (2012)
Australia	Native Forest (Savanna)	–1.4	0.16	Livesley et al. (2009)
Australia	Eucalyptus globulus	–6.8	0.15	Livesley et al. (2009)
Australia	Pinus radiata	–5.0	0.12	Livesley et al. (2009)

Studies indicate that high soil N mineral contents may stimulate CH₄ oxidation ( Bodelier and Laanbroek, 2004 ; Liu and Greaver, 2009 ). Mineral N seems to be a prerequisite for CH₄ consumption, although the identification of relationships between N availability and CH₄ consumption, as well as the bacteria involved, is still a challenge. For the time being, N must be treated as a potential inhibitor and as a beneficial factor for CH₄ consumption in soils ( Bodelier and Laanbroek, 2004 ). Ammonium can compete with CH₄ for the enzyme methane mono-oxygenase, effectively lowering CH₄ oxidation by methanotrophs in the soil ( Hanson and Hanson, 1996 ).

The N₂O emissions were below 0.86 kg ha¹yr¹for all areas studied ( Figures 4A and 4C ). Other studies also reported cumulative N₂O fluxes below 1 kg ha¹yr¹( Table 4 ). To date, no studies have evaluated soil N₂O fluxes for a period of two years under planted Eucalyptus systems in Brazil. In our study, mainly during the dry season in native Cerrado, N₂O influxes and low nitrate levels were observed. The N₂O influx under native vegetation may be associated to a low N mineral content, in predominantly ammoniacal N, a rapid drainage of soil water to the subsurface layers ( Martins et al., 2015b ; Santos et al., 2016 ; Carvalho et al., 2017 ; Sato et al., 2017 ), and low soil pH ( Lopes and Cox, 1977 ), since nitrification tends to decrease with increasing soil acidity ( Hickman et al., 2014 ).

In an integrated crop-livestock-forest system, Carvalho et al. (2017) observed N₂O fluxes lower than in an integrated crop livestock system. The authors claimed that the presence of Eucalyptus plant residues in the system, which are rich in phenolic compounds and are acidic ( Soumare et al., 2015 ), inhibit the enzyme and microbial activity in the soil ( Chen et al., 2013 ).

Despite limitations of the static chambers in relation to the real conditions of free soil-atmosphere fluxes, these boxes are easy to construct and can be used under different conditions. Therefore, even low-magnitude flows can be detected and information on the spatial variability of emissions is provided, although no significant differences related to the position and no emission pattern could be observed in our study. Other drawbacks refer to variations in daily measurements that are commonly wide, the chamber measurements may be underestimated or overestimated, and the values of standard deviation are generally high. Possibly, the high spatial and temporal variability of the gas emissions was due to the quantity of variables that are interrelated and drive the flow dynamics. However, cumulative N₂O emissions from forest soils and CH₄ influxes were low (< 1.0 kg ha¹), although their variability should not be left unmentioned. In evaluations at 15 positions in natural forests in Germany, Jungkunst et al. (2012) also found high variability and low spatial representativeness of the chambers, attributed to the C:N ratio, N input, and water availability by the authors. However, considering the variations observed, a random distribution of the chambers is suggested, since the measurements seem to be independent from the chamber position and distance from the Eucalyptus trees.

Planting Eucalyptus in areas of former native vegetation or previous agricultural use resulted in no marked differences between cumulative GHG fluxes. From the ecological and environmental viewpoint, greater biodiversity in areas of native vegetation stands out. This similarity in the cumulative GHG fluxes may be related to the stability observed in sites with Eucalyptus stands after planting.

Conclusions

The change in land use from Cerrado to Eucalyptus plantations did not induce significant changes in GHGs, compared to the native vegetation. The flux rates were low for both gases (N₂O and CH₄). The temporal variations in GHG fluxes and the different ages of stands caused no significant differences between cumulative annual fluxes. Our results may be an important contribution to a better understanding of the dynamics of GHG fluxes in commercial forest plantations in the Cerrado region.

Acknowledgements

The study was supported financially by Embrapa Cerrados (Contract Nº 01.11.01.001.0200) Project Emission of Greenhouse Gases, carbon stocks and environmental indicators in the Cerrado Biome (SALTUS) and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

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Edited by

Edited by: Eduardo Alvarez Santos

Publication Dates

• Publication in this collection
  13 Mar 2020
• Date of issue
  2021

History

• Received
  18 Oct 2018
• Accepted
  09 Aug 2019