Soil N₂O emissions in integrated crop-livestock-forestry: A review

ABSTRACT

Integrated crop-livestock-forestry (ICL/ICLF) can enhance resource use efficiency in agricultural production. However, these systems exert complex effects on soil processes and properties, consequently influencing greenhouse gas (GHG) emissions. This systematic literature review evaluated N₂O emissions in ICL/ICLF resulting from nitrogen (N) fertilizer application, compared them with non-integrated systems, and discussed factors affecting emission rates. Cumulative N₂O emissions were extracted from the reviewed studies. Descriptive, exploratory, and inferential statistical analyses were conducted to compare N₂O emissions between the cultivation systems, and the N₂O emission factor (N₂O-EF) was calculated. Total N₂O emissions were estimated by summing emissions from excreta deposited on soil in ICL/ICLF systems and indirect emissions, following the IPCC methodology. The observed N₂O-N emissions (n = 533) showed high variability, ranging from 0.04 to 12.3 kg ha^-1 annually in ICL/ICLF. No significant difference was detected between the mean N₂O emissions in ICL/ICLF (1.74 ± 0.20 kg ha^-1) and non-integrated systems (1.87 ± 0.45 kg ha^-1). Nitrous oxide emissions demonstrated a linear relationship with the applied rate of N fertilizer, resulting in N₂O-EFs of 1.0 % (±0.24 %) in ICL/ICLF and 0.80 % (±0.41 %) in non-integrated systems. Most studies reported comparable N₂O emissions across both systems; only a few found lower emissions in ICL/ICLF, while one study noted increased emissions relative to non-integrated systems. Factors such as soil compaction, grazing intensity, carbon (C) and N mineralization, N use efficiency, abundance of soil microorganisms, and soil temperature influenced N₂O emissions in ICL/ICLF. Estimated total N₂O emissions (including observed fertilizer, excreta, and indirect emissions) ranged from 0.8 to 5.3 Mg ha^-1 yr^-1 of CO_2eq in ICL/ICLF and from 0.4 to 6.1 Mg ha^-1 yr^-1 of CO_2eq in non-integrated systems. Plant diversity in ICL/ICLF may help mitigate GHG emissions by enhancing soil C storage, increasing CO₂ removal via trees, and promoting biological nitrification inhibition. Accurately comparing N₂O emissions between cultivation systems remains challenging due to uneven experimental treatments and multifactorial study designs.

Keywords
net zero; low carbon emission; ABC+ Plan; Sustainable Production Systems; Practices - Products - Processes

INTRODUCTION

Anthropogenic activities account for 43 % of global nitrous oxide (N₂O) emissions, with agricultural nitrogen (N) inputs making up 52 % of these human-derived emissions. This leads to an annual surplus of N₂O-N of 4.3 Tg yr^-1 in the atmosphere (Tian et al., 2020). The increase in population and higher demand for meat and dairy products have substantially increased N₂O emissions (ONU, 2019). Atmospheric N₂O levels are rising at a rate greater than predicted, with emissions surpassing those projected even under the highest representative concentration pathway scenario (RCP 8.5) for climate change between 2000-2020 (Tian et al., 2020).

Soil N₂O emissions are a major source of greenhouse gases (GHGs) in agriculture. They make up 27 % of GHGs from intensive beef production (Beauchemin et al., 2010) and 37 % from wheat production (Biswas et al., 2008). Prior studies used an N₂O emission factor (EF) of 1 % of applied N fertilizer (IPCC, 2006), later refined to 0.5 % (0.0–1.1 %) for dry climates and 1.6 % (1.3–1.9 %) for wet climates (IPCC, 2019). Thus, N₂O emissions are highly uncertain but remain a substantial contributor to agricultural GHG output.

Emissions of N₂O from soil has high spatial and temporal variability, and it is influenced by management, climate, and soil properties. For example, in the Cerrado region of Brazil, the average N₂O-EF form N fertilizer is lower than 1 % of the N applied but can range from 0.01 % to 4.6 % (Carvalho et al., 2013, 2014; Lessa et al., 2014; Martins et al., 2015; Sato et al., 2017; Silva et al., 2017; Mascarenhas et al., 2020; Sousa et al., 2021; Carvalho et al., 2024; Angnes et al., 2025). Nitrous oxide emissions are driven by complex soil processes, involving mainly nitrification and denitrification besides other N transformation pathways such as nitrifier denitrification, dissimilatory reduction of nitrate to ammonium, chemo-denitrification, and co-denitrification (Figure 1) (Stevens and Laughlin, 1998; Hayatsu et al., 2008; Spott et al., 2011; Müller et al., 2014). Therefore, assessing the N₂O emission factor (N₂O-EF) based on regional soil and climate conditions, as well as management practices, is important.

Figure 1
Soil N transformations, related genes, and N₂O emission pathways: nitrification (1); denitrification (2); dissimilatory reduction of nitrate to ammonium (3); nitrifier denitrification (4); co-denitrification (5); and chemo-denitrification (6).

Many nations have pledged to reduce GHG emissions. In Brazil, the government updated the ABC+ plan (Brazilian Agricultural Policy for Climate Adaptation and Low Carbon Emission) for the 2020-2030. This plan encourages farmers to adopt and maintain Sustainable Production Systems – Practices, Products, Processes (SPS_ABC) on agricultural land, with the potential to reduce 1,042 Tg CO_2eq. The SPS_ABC includes measures such as restoring degraded pastures, using no-till systems, biological N fixation, and crop-livestock or crop-livestock-forestry integration (ICL/ICLF) (MAPA, 2022).

Policies that support and incentivize the adoption of low C emission agricultural technologies are crucial for driving meaningful reductions in greenhouse gas emissions from the sector. While consumer choices can contribute to lower GHG emissions, barriers such as higher costs often limit widespread uptake, especially among lower-income households. Well-designed policies can help bridge this gap by making sustainable technologies more accessible and affordable for all producers and consumers. By encouraging broader adoption, these policies not only support environmental goals but also ensure that the transition to low-carbon agriculture is equitable and inclusive, maximizing the benefits for society.

The adoption of ICL/ICLF may reduce fertilizer inputs, increase soil health and soil C stocks, and improve agricultural product footprints (Hendrickson et al., 2008; Alves et al., 2017a; Brewer and Gaudin, 2020; Lal, 2020). The integration of crop and livestock production started with smallholder farmers, improving resource use in a circular way by using crop residues to feed animals and livestock manure as fertilizer for crops (Alves et al., 2017a), characterized by the succession of annual crops with pasture for ruminant animals. There is a great variety of integrated farming systems worldwide, from annual crops intercropped with grasses like corn with brachiaria, through crops and cover crops for silage production, to crop-dairy-fish-poultry integration (Carvalho et al., 2014; Carvalho et al., 2017; Li et al., 2017; Abagandura et al., 2019; Paramesh et al., 2019; Pilecco et al., 2019; Lazcano et al., 2022; Santos et al., 2022).

The ICL/ICLF has complex effects on soil properties and subsequently on N₂O emissions. In a site-specific study, for example, grazing in ICL increased N demand and decreased N₂O emissions compared with ungrazed pasture (Piva et al., 2019). To the contrary, another study reported that grazing increased soil compaction and N₂O emissions (Piva et al., 2014). The ICLF lowered soil temperature due to tree shading, which reduced N₂O emissions (Nogueira et al., 2016). However, it also reduced crop root growth and impacted the N cycle (Bieluczyk et al., 2021). Understanding how ICL/ICLF impact N₂O emissions can aid efforts to mitigate emissions and lower agriculture C footprint.

The ICL/ICLF offers a sustainable way to intensify agriculture by boosting crop yields while reducing impact on the environment (Alves et al., 2017a). A meta-analysis found that ICL generally produces yields similar to non-integrated systems; however, using single-purpose crops in ICL, rather than dual-purpose, can result in 5 % higher yields on loamy soils compared with non-integrated systems (Peterson et al., 2020). In this way, ICL can reduce GHG emission intensity (kg CO_2eq per kg of product).

This study differs from previous GHG assessments of ICL/ICLF (Sousa et al., 2021; Leite et al., 2023; Bieluczyk et al., 2024; Berdjour et al., 2025), since we compared N₂O-EFs from fertilizer application in ICL/ICLF and non-integrated systems, exploring the mechanisms involved. Understanding how ICL/ICLF can influence the dynamics of soil N₂O emissions can help elucidate their effects and inform strategies to mitigate these emissions.

We hypothesized that: N₂O emissions from fertilizer N application in ICL/ICLF and non-integrated systems are similar; the multiple effects of ICL/ICLF on soil properties influence N₂O emissions both ways, leading to periods of increases and reductions; and the N₂O-EF from fertilizer in ICL/ICLF is slightly lower than the 1 % IPCC default factor. This review aims to compare N₂O emissions from N fertilizer use in ICL/ICLF and non-integrated systems (e.g., only crop, only pasture); to examine how ICL/ICLF affects soil properties and influences N₂O emissions; and to estimate total N₂O emissions (direct and indirect) from N input in ICL/ICLF and non-integrated systems.

MATERIALS AND METHODS

Compilation of studies and review

Peer-reviewed articles were searched in Web of Science using the terms “integrat*” AND “crop” AND “livestock” OR “agrosilvopast*” (Topic) AND “N₂O” OR “nitrous oxide” (Topic). The terminology is consistent with standard nomenclature used in Brazilian agriculture. In total, 133 articles were found until February 2026, showing high diversity. The studies were filtered according to the following criteria: field experiments, N₂O measurements for more than 120 days (crop season), integrated crops on the same land, treatments with three or more replicates, and presence of pasture for ruminant animals (cattle or sheep). The ICL studies with swine, fish, and poultry were excluded.

Of the 133 articles, 24 matched the criteria and were analyzed (number of observations = 533), with 18 studies from Brazil, five from the United States, and one from South Africa (Figure 2 and Table 1). Data were extracted from the studies, including information on crops and animals, experimental treatments, N source, N rate, N₂O emissions (kg ha^-1), N₂O emission factor (% of applied N), measurement period, and reference (Table 1). When two studies reported the same experiment, we selected the study covering the longer N₂O evaluation period to avoid double counting, such as in the case of Sato et al. (2017, 2019) and Carvalho et al. (2022, 2024).

Table 1
Nitrous oxide (N₂O) emissions from N fertilizer in integrated crop-livestock-forestry (ICL/ICLF)

ICL/ICLF	Location	Climate	Soil	Treatment	N source	N rate	N2O	Measurements		Reference
						kg ha-1		crop	days
Wheat / Pea and barley or sunflower or corn or cover crops (cattle)	46º 53’ N, 102º 49’ W, USA	Continental with moist springs, relatively dry summers, and cold and snowy winters	Frigid Typic Haplustolls, Frigid Vertic Argiustolls	Wheat – CC	No N	0	0.67	all	120	Abagandura et al. (2019)
				Wheat	No N	0	0.57	all	120
				Pea/Barley	No N	0	1.07	all	120
				Sunflower	No N	0	0.50	all	120
				Cover crops	No N	0	0.75	all	120
				Corn	No N	0	0.72	all	120
Corn, black oat / Guinea grass (cattle) / Eucalyptus	25º 23.5’ S, 49º 07.5’ W, Brazil	Subtropical humid mesothermic	Dystric Cambisol with a clay texture	CR	Urea	495	7.00	all	365	Amadori et al. (2022)
				Pasture	Urea	495	11.75	all	365
				ICL	Urea	495	8.11	all	365
				ILF	Urea	495	7.00	all	365
				ICLF	Urea	495	8.52	all	365
Soybean / Black oat (cattle)	27º 16.4’ S, 50º 30.2’ W, Brazil	Humid subtropical	Dystric Cambisol with a clayey texture	Non graz 0	Urea	0	1.55	all	365	Bratti et al. (2022)
				Non graz 75	Urea	75	1.71	all	365
				Non graz 150	Urea	150	2.02	all	365
				Mod. graz 0	Urea	0	1.56	all	365
				Mod. graz 75	Urea	75	1.93	all	365
				Mod. graz 150	Urea	150	1.93	all	365
				Int. graz 0	Urea	0	1.52	all	365
				Int. graz 75	Urea	75	1.92	all	365
				Int. graz 150	Urea	150	2.16	all	365
Soybean / Corn and brachiaria (none), or cotton and fallow	17º 22’ S, 51º 29’ W, Brazil	Humid tropical	Typic Hapludox with clayey texture	CR	-	92	0.57	all	365	Carvalho et al. (2014)
				Pasture	No N	0	1.67	all	365
				ICL	-	222	2.00	all	365
Corn and triticale / Bromegrass, switchgrasses (cattle)	41º 09.3’ N, 96º 26.8’ W, USA	Mean annual rainfall of 747 mm and temperature of 9.9 °C	Mesic Pachic Argiudoll, mesic Vertic Argialboll, mesic Mollic Hapludalf	Corn non graz	UAN	252	3.52	all	210	Christenson et al. (2021)
				Corn graz	UAN	252	12.30	all	210
				Bromegrass	-	56	5.50	all	210
				Switchgrass 1	-	56	1.00	all	210
				Switchgrass 2	-	56	1.90	all	210
Corn / Brachiaria (cattle)	16º 30’ S, 49º 17.5’ W, Brazil	Tropical with dry winter	Typic Hapludox, clay	ICL	Urea	145	1.64	B	240	Corrêa et al. (2016)
Maize, Soybean / Ryegrass (sheep)	30º 05’22” S, 51º 39’08” W, Brazil	Humid subtropical	Acrisol with a sandy clay loam texture	Non graz 1st year	Formulation, Urea	320	3.06	all	365	Bastos et al. (2026)
				Graz low 1st year		320	4.10	all	365
				Graz mod 1st year		320	2.87	all	365
				Rot low 1st year		320	3.15	all	365
				Rot mod 1st year		320	2.96	all	365
				Non graz 2nd year	Urea	150	1.77	all	330
				Graz low 2nd year		150	3.97	all	330
				Graz mod 2nd year		150	2.50	all	330
				Rot low 2nd year		150	3.08	all	330
				Rot mod 2nd year		150	2.64	all	330
				Non graz 3rd year	Urea	150	0.62	all	365
				Graz low 3rd year		150	0.96	all	365
				Graz mod 3rd year		150	0.78	all	365
				Rot low 3rd year		150	1.06	all	365
				Rot mod 3rd year		150	0.98	all	365
Soybean / Brachiaria (cattle) / Eucalyptus	15º 35.5’ S, 14º 42.5’ W, Brazil	Tropical with dry winter	Oxisol, with clayey texture	ICL	Urea	200	2.84	all	425	Carvalho et al. (2017)
				ICLF	Urea	130	2.01	all	425
Soybean / Sorghum and grasses (none)	15º 39’ S, 47º 44’ W, Brazil	Tropical with dry winter	Oxisol, clayey	CC1 1st year	Formulation	3.6	0.83	all	335	Carvalho et al. (2022, 2024)
				CC2 1st year	Formulation	3.6	1.32	all	335
				ICL1 1st year	Formulation	3.6	0.46	all	335
				ICL2 1st year	Formulation	3.6	0.68	all	335
				CC1 2nd year	Formulation	3.6	0.56	all	270
				CC2 2nd year	Formulation	3.6	0.74	all	270
				ICL1 2nd year	Formulation	3.6	0.52	all	270
				ICL2 2nd year	Formulation	3.6	0.60	all	270
Vineyard / Cover crops (sheep)	35º 38.2’ N, 120º 51.8’ W, USA	Mediterranean with an annual average temperature of 15.3 °C and average annual rainfall of 364 mm	Thermic Calcic Pachic Haploxerolls, Shallow Calcic Haploxerolls	Graz ws 1st year t	Compost	-	2.55	all	120	Lazcano et al. (2022)
				Non graz ws 1st year t	Compost	-	1.99	all	120
				Graz ds 1st year t	Compost	-	0.08	all	120
				Non graz ds 1st year t	Compost	-	0.08	all	120
				Graz ws 2nd year t	Compost	-	0.68	all	120
				Non graz ws 2nd year t	Compost	-	0.12	all	120
				Graz ds 2nd year t	Compost	-	0.35	all	120
				Non graz ds 2nd year t	Compost	-	0.43	all	120
				Graz ws 1st year nt	Compost	-	1.22	all	120
				Non graz ws 1st year nt	Compost	-	0.34	all	120
				Graz ds 1st year nt	Compost	-	0.06	all	120
				Non graz ds 1st year nt	Compost	-	0.10	all	120
				Graz ws 2nd year nt	Compost	-	2.57	all	120
				Non graz ws 2nd year nt	Compost	-	1.89	all	120
				Grazing ds 2nd year nt	Compost	-	0.2	all	120
				Non graz ds 2nd year nt	Compost	-	0.17	all	120
Corn and soybean or wheat and cover crops / Grassland (cattle)	46º 46.2’ N, 100º 54’ W, USA	Mean annual rainfall of 419 mm and temperature of 5 °C	Frigid Typic and Pachic Haplustolls	Crop graz	No N	0	2.60	all	365	Liebig et al. (2020)
				Crop non graz	No N	0	2.50	all	365
				Grass graz	No N	0	0.40	all	365
				Grass non graz	No N	0	0.30	all	365
Wheat (W) and canola (C)/ Cover crop (L) and medic (M) pasture (sheep)	33.277 ºS, 18.704 ºE, South Africa	Mediterranean	Stagnic Lixisol and Leptic Lixisol, sandy loam texture	WWWC	Urea, MAP	341	0.14	all	365	Matthews et al. (2025)
				WCWL	Urea, MAP	244	0.31	all	365
				WMCM	Urea, MAP	74	0.42	all	365
Soybean / Corn and brachiaria (cattle) / Eucalyptus	11º 52.2’ S, 55º 35.4’ W, Brazil	Tropical with dry winter	Typic Hapludox, clay	Pasture	-	45	1.15	all	365	Nascimento et al. (2020)
				CR	-	189	1.40	all	365
				ICLF	-	189	1.27	all	365
Soybean / Corn and brachiaria (none) / Eucalyptus	11º 51' S, 55º 35' W, Brazil	Tropical with dry winter	Typic Hapludox, clay	CR	Urea	300	1.40	all	365	Nogueira et al. (2016)
				Pasture	No N	0	0.29	all	365
				ICLF	Urea	300	0.37*	all	365
Soybean, corn, wheat, oats / Brachiaria (cattle) / Eucalyptus	23º 31.2’ S, 50º 35.4’ W, Brazil	Humid Subtropical, Oceanic climate, without dry season with hot summer	Typical Hapludox	CR ws	Urea	360	0.52	all	180	Pereira et al. (2022)
				Pasture ws	No N	0	0.49	all	180
				ICLF ws	Urea	360	0.37	all	180
				CR ds	Urea	360	0.35	all	180
				Pasture ds	No N	0	0.10	all	180
				ICLF ds	Urea	360	0.10	all	180
Soybean / Ryegrass (none)	29º 42.8’ S, 53º 42.4’ W, Brazil	Humid subtropical	Typic Hapludalf	CR yr1	Urea	40	1.10	all	365	Pilecco et al. (2019)
				ICL 1 yr1	Urea	60	0.76	all	365
				ICL 2 yr1	Urea	60	0.94	all	365
				CR yr2	Urea	60	1.23	all	365
				ICL 1 yr2	Urea	60	0.88	all	365
				ICL 2 yr2	Urea	60	1.07	all	365
Corn / Ryegrass (cattle)	24º 47.8’ S, 49º 57.7’ W, Brazil	Humid Subtropical, Oceanic climate, without dry season, with temperate summer	Umbric Ferralsol	CR	Urea	165	1.26	all	365	Piva et al. (2014)
				ICL	Urea	225	4.26*	all	365
Corn or beans / Ryegrass and oats (sheep)	25º 33’ S, 51º 29’ W, Brazil	Humid Subtropical, Oceanic climate, without dry season with temperate summer	Ferralsol	ICL graz	Urea	112	0.80	all	300	Piva et al. (2019)
				ICL non graz	Urea	112	2.09*	all	300
Soybean / Black oat (cattle)	27º 18.4’ S, 50º 38’ W, Brazil	Humid Subtropical, Oceanic climate, without dry season with temperate summer	Ferralsol	ICL non graz	No N	0	2.60	all	365	Ribeiro et al. (2020)
				ICL graz 0.10 m	No N	0	2.60	all	365
				ICL graz 0.20 m	No N	0	2.20	all	365
				ICL graz 0.30 m	No N	0	1.90	all	365
Soybean, oats / Brachiaria (cattle)	22º 16.9’ S, 54º 48.3’ W, Brazil	Mesothermal, humid climate with hot summers and dry winters	Oxisol	CR	No N	0	0.57	S	150	Salton et al. (2014)
				ICL	No N	0	0.49*	S	150
Soybean, corn / Sorghum and brachiaria (cattle)	15º 39’ S, 47º 44’ W, Brazil	Tropical with dry winter	Typical Oxisol	CR-t	Formulation	225	2.55	all	365	Sato et al. (2017, 2019)
				CR-nt	Formulation	225	1.90	all	365
				ICL	Formulation	225	1.52*	all	365
				CR-nt	Formulation	100	0.90	SG+B	150
				ICL	Formulation	100	0.79*	SG+B	150
Corn, oats / Cover crops (cattle)	44º 20.2’ N, 96° 48.2’ W, USA	Continental temperature with warm, humid summers and snowy winters	Frigid Udic Haploborolls	Leg. graz S1	-	140	1.50	all	240	Singh et al. (2020)
				Leg non graz S1	-	140	1.60	all	240
				Grass graz S1	-	140	2.00	all	240
				Grass non graz S1	-	140	2.20	all	240
				Leg graz. S2	-	145	2.11	all	240
				Leg non graz S2	-	145	2.18	all	240
				Grass graz S2	-	145	1.70	all	240
				Grass non graz S2	-	145	2.20	all	240

• ^*
  Significant difference between ICL/ICLF and crop rotation (CR). CC: continuous crop; yr: year; ws: wet season; ds: dry season; t: till; nt: no-till; Leg: legumes cover crops; Mod: moderate; Int: Intensive; graz: grazing; S: site; B: brachiaria; R: ryegrass; SG+B: sorghum and brachiaria; Rot: rotational, MAP: monoammonium phosphate; -: no available/applicable data.

The ICL/ICLF involve different characteristics between the studies, such as climate, soil, crops and management. The crops included soybeans, corn, wheat, oats, cotton, and vineyards. Different grasses were integrated in the systems with rotation or intercropping, such as brachiaria, guinea grass, bromegrass, switchgrass, ryegrass, cover crops, legumes, and oats. The livestock included cattle, sheep, or no animals. In ICLF studies, eucalyptus was included as a forestry component (Table 1).

Emissions of N₂O were measured across all crops throughout the year in most studies, whereas fewer than 10 % of the data corresponded to a crop season timeline. Experimental treatments included crops separately, continuous crops, ICL/ICLF, rotational systems, grazing intensities, dry and wet seasons, and different years. Nitrogen fertilizers used were urea, urea ammonium nitrate, urine, compost, and formulated fertilizers (Table 1).

Nitrous oxide data from non-integrated systems (e.g., crop rotation, pasture) were grouped and compared with integrated systems during the data analysis. A systematic review was conducted to explore studies that evaluated N₂O emissions in ICL/ICLF. Other studies were analyzed that investigated the effect of ICL/ICLF on soil properties with influence on N₂O emissions.

Figure 2
Locations of experimental sites with N₂O measurements in integrated crop-livestock-forestry (ICL/ICLF).

RESULTS

N₂O assessment

Cumulative N₂O emissions (kg ha^-1 of N₂O-N ) and standard deviation (SD) were extracted from the studies. All studies measured N₂O fluxes by the static chamber method. The average SD from the studies was calculated and used when not available in certain studies. Cumulative N₂O data reported only in figures were extracted using WebPlotDigitizer (Rohatgi, 2019). Data extracted from the studies included: reference, site location, climate classification, soil type, treatments, crops and livestock used, livestock unit (head ha^-1), fertilizer source, fertilizer N rate (kg ha^-1), N₂O measurement time (days), and number of replicates. The cumulative N₂O emissions were compared using the reported data, which corresponded mostly to an annual basis, while fewer than 10 % referred to a crop season. A data frame was created in Excel® software for data analysis.

Descriptive, exploratory, and inferential statistical analyses were conducted to compare cumulative N₂O emissions between the cultivation systems. The N₂O data were summarized and visualized using boxplot (medians, means, interquartile range, and 5th and 95th percentiles). Data were checked for normality using Shapiro-Wilk test, and subsequently analyzed using the non-parametric Kruskal-Wallis (K-W) test (p<0.05).

The N₂O-EF was calculated by adjusting a linear model to N₂O emissions as a function of N applied as fertilizer. The N₂O-EF (% of N applied) corresponded to the slope of the linear regression (f = ax + y0) of N₂O emissions (kg ha^-1) in function of N rate applied (kg ha^-1), where it was adjusted for each system separately (ICL/ICLF and non-integrated). The regression slopes (ax) and the y-intercept (y0) were compared between the systems; differences were considered significant if the coefficients ± standard deviations did not overlap. Studies without N application or with very low N rates (e.g., 3.6 kg ha^-1) were not considered for calculating the N₂O-EF. The number of observations (n) was 87 in the non-integrated systems and 127 in ICL/ICLF.

Statistical analyses and graphics were performed using R software version 4.4.1 (R Core Team, 2024) including the “ggplot2” package (Wickham, 2016), and Sigma Plot software version 12.5 (Ferreira, 2011).

Total N₂O estimation from N input

Nitrous oxide emissions (direct and indirect) were estimated for all N input sources when not measured in the studies, such as from excreta deposition on soil in ICL/ICLF. Nitrous oxide emissions from excreta deposited on soil were estimated according to equation 11.2 (Supplementary Materials) from Tier 2 and 11.5 (Supplementary Materials) from Tier 1 (IPCC, 2019), considering animal density (454 kg live weight), and N excretion rate according to animal category and region listed in table 10.19 (IPCC, 2019) and N₂O-EF of 0.6 % for wet climate (IPCC, 2019). The N excretion from the category “other cattle in a high productivity system” was assumed when not reported in the studies (IPCC, 2019). The fraction of excreta deposited on soil was considered as 100 %. The average stocking density of the studies was calculated and used when not reported, which corresponded to 2.11 livestock units ha^-1.

Indirect N₂O emission was estimated according to equations 11.9 and 11.10 (Supplementary Materials) of Tier 1, considering N losses of NH₃ volatilization and of NO₃^- leaching (IPCC, 2019). The N loss of NH₃-N was considered as 15 % of N applied for urea fertilizer and as 21 % for manure; the N loss of NO₃^- leaching was assumed 24 % of N applied for all N sources; the N₂O-EFs default values were considered as 1.4 % for NH₃-N and 1.1 % for NO₃^--N leaching (IPCC, 2019).

Total N₂O emissions in ICL/ICLF corresponded to the sum of the direct N₂O emission from fertilizer (observed and extracted from studies), the estimated direct N₂O emission from manure, and the estimated indirect N₂O emissions from fertilizer and manure. In non-integrated systems, the estimated N₂O emissions were calculated considering the measured N₂O emission from N fertilizer and the estimated indirect N₂O. The N₂O emission was converted to CO_2eq considering the warming potential (100 years) of N₂O as 273 (IPCC, 2021).

DRIVERS OF N₂O EMISSIONS IN ICL/ICLF

N₂O emissions in ICL/ICLF

Cumulative N₂O-N emissions ranged from 0.04–12.3 kg ha^-1 in ICL/ICLF, and 0.1–11.75 kg ha^-1 in non-integrated systems. The average N₂O emission was 1.74 ± 0.20 kg ha^-1 of N₂O-N in ICL/ICLF and 1.87 ± 0.45 kg ha^-1 in non-integrated systems, without difference between them (p<0.05) (Figure 3). Similar results were recently reported in a meta-analysis, with no difference in N₂O emissions between integrated and non-integrated systems (Berdjour et al., 2025). Nitrous oxide emissions increased linearly with N input rates in both ICL/ICLF (R² = 0.33; p<0.001) and non-integrated systems (R² = 0.18; p<0.10). The equation angular coefficients were 0.0080 and 0.0103 kg of N₂O, corresponding to N₂O-EF of 0.80 % (±0.41 %) and 1.03 % (±0.24 %) of N applied, respectively (Figure 3). The N₂O-EFs closely matched the IPCC default value of 1.0 % (0.01–1.8 %) (IPCC, 2019). The y-intercepts were 0.322 (±0.543) and 0.583 (±1.095) for ICL/ICLF and non-integrated systems, respectively (Figure 4). Therefore, based on the mean ± standard error, the N₂O-N emissions were similar in ICL/ICLF and non-integrated systems. Nitrous oxide emissions from ICL/ICLF were similar to non-integrated systems in most of the revised studies (Table 2). Of 12 studies comparing these systems, seven found no difference, four reported 14–74 % lower N₂O emissions in ICL/ICLF than in non-integrated systems, and one found a 238 % higher emission in ICL/ICLF (Table 2). Lower N₂O emissions in ICL/ICLF were attributed to lower soil temperature, higher N demand by grass due to grazing, denitrification of N₂O to N₂ due to soil compaction, lower leaf fall and N mineralization, no incorporation of crop residues, and higher C stability. Conversely, elevated N₂O emissions observed in ICL/ICLF were explained by higher N application rate and soil compaction due to grazing (Table 2).

Figure 3
Cumulative N₂O emissions from N fertilizer application in integrated crop-livestock-forestry (ICL/ICLF) and non-integrated systems. Dashed lines represent system means and dots the 5th and 95th percentiles. Numbers of observations are shown in parentheses. ns: no significant differences by K-W test at p<0.05.

Figure 4
Cumulative N₂O emissions as a function of N fertilizer application rate in integrated crop-livestock-forestry (ICL/ICLF) and non-integrated systems.

Table 2
Difference in N₂O emissions from N fertilizer between integrated crop-livestock-forestry (ICL/ICLF) and non-integrated systems

ICL/ICLF	Non-integrated	Difference in N2O	Reason	Reference
		%
Soybean / Corn and brachiaria (none) / Eucalyptus	Soybean / Corn and brachiaria	-74	Lower soil temperature in ICL due to forestry	Nogueira et al. (2016)
Corn / Ryegrass (cattle)	Corn / Ryegrass	+238	Higher N rate and soil compaction in ICL due to grazing	Piva et al. (2014)
Corn or beans / Ryegrass and oats (sheep)	Corn or beans / Ryegrass and oats (ungrazed)	-62	Higher N demand in ICL due to plant regrowth / Denitrification of N2O to N2 due to soil compaction	Piva et al. (2019)
Soybean, oats (no-till) / Brachiaria (cattle)	Soybean, oats (till)*	-14	Leaf fall and higher N mineralization in non-integrated	Salton et al. (2014)
Soybean, corn (no-till) / Sorghum and brachiaria (cattle)	Soybean, corn (till) * / Sorghum and brachiaria	-40	Incorporation of crop residues in non-integrated	Sato et al. (2017)

• ⁺
  increase;
• ^-
  reduction.
• ^*
  No differences were reported when comparing both systems under no-till.

Soil temperature in ICL/ICLF influencing N₂O emissions

Soil temperature can be reduced due to tree shading in ICLF, decreasing N₂O emissions (Nogueira et al., 2016). The shade of trees in ICLF can reduce root density in corn intercropped with grasses, thereby affecting soil C and nutrient cycling and potentially influencing N₂O emissions (Bieluczyk et al., 2021). Soil temperature can stimulate microbial activity, increasing N₂O emissions (Castaldi, 2000; Lai et al., 2019). High correlation coefficients (R² = 0.64 to 0.79) between soil temperature and N₂O emissions were also reported in temperate climates in tree cultivation (Xue et al., 2019).

An increase in N₂O emission (0.2 to 5.9 ng g^-1 h^-1 N₂O-N) with increasing soil temperature (2 to 40 °C) was observed in an incubation experiment in forest soils, with different N₂O emission pathways occurring in non-integrated and forestry systems (Castaldi, 2000). In the soil of non-integrated systems, both nitrification and denitrification processes increased with temperature, while in forest soil only nitrification increased (Castaldi, 2000). On the other hand, in a study with two forest soils, the nitrification (autotrophic) process increased and the denitrification decreased with rising temperature in one soil, while the opposite occurred in another soil (Zhang et al., 2019). It is probable that the higher organic C content of one soil (82 g kg^-1) favored denitrification and heterotrophic nitrification compared with the other forest soil (60 g kg^-1). Nevertheless, total N₂O emissions, independently of the pathway, increased as soil temperature rose.

Soil compaction in ICL/ICLF and related N₂O emissions

Grazing in ICL/ICLF increases soil bulk density, hence contributing to soil compaction (Tracy and Zhang, 2008; Abdalla et al., 2021). Cattle grazing in ICLF (soybean-palisade grass-eucalyptus), for instance, increased soil bulk density by up to 40 % (0.94 to 1.32 g dm^-3) compared with native vegetation at soil layers of 0.00-0.10 m (Sousa Neto et al., 2014). The same authors also reported that, consequently, grazing increased soil penetration resistance (0.29 to 0.88 MPa) and decreased total porosity (0.64 to 0.50 m³ m^-3). Similarly, Abdalla et al. (2021) reported that grazing corn residues (1200 cattle ha^-1 for 3 days) increased soil penetration resistance from 150 to 200 N cm^-2, and decreased soil water content from 22 to 19 %. Tracy and Zhang (2008) observed increased soil penetration resistance in ICL (corn–oat–pasture; 2.5 cattle ha^-1) compared with continuous corn at 0.00-0.23 and 0.24-0.46 m soil layers; and Martins et al. (2016) reported, also in ICL (soybean–black oats with ryegrass; 3 cattle ha^-1) decreased soil moisture, affecting physiological processes in soybeans due to a reduction in leaf water potential and an increase in leaf temperature, which may impact N₂O emissions. Grazing (3 cattle ha^-1) in ICL (soybean–black oats with ryegrass) decreased soil moisture, affecting physiological processes in soybeans by reducing leaf water potential and increasing leaf temperature (Martins et al., 2016), which may impact N₂O emissions.

Soil compaction caused by grazing in ICL/ICLF can lead to increased N₂O emissions (Piva et al., 2014; Christenson et al., 2021). However, it may also decrease N₂O emissions due to a greater conversion of N₂O to N₂ (Piva et al., 2019). In a study with stover grazing in corn (4.4 cattle ha^-1 for 7-16 days), N₂O emissions increased by three times (3.5 to 12.3 kg ha^-1) compared with no grazing due to soil compaction and N addition from excreta (Christenson et al., 2021). Similarly, three times higher N₂O emission was observed in ICL (corn – ryegrass) relative to continuous cropping (1.26 to 4.26 kg ha^-1), which was attributed to higher N input (225 kg ha^-1 vs. 165 kg ha^-1) and soil compaction in ICL (Piva et al., 2014). In both studies, the effect of soil compaction was not isolated from the elevated N input, however, while N₂O emissions increased three times, N input was only 36 % higher (Piva et al., 2014).

On the other hand, ICLF, compared with a reference pasture, could improve other soil physical parameters such as increasing available water and aeration, due to higher macro- and microporosity by increasing large water-stable aggregates (87 to 95 %) (Moura et al., 2023). In their study, the authors attributed the improvements in soil physical properties to eucalyptus cultivation in ICLF. Increased aeration in ICLF could lead to lower N₂O emissions, as these emissions decrease when soil moisture is reduced (Vargas et al., 2014).

N use efficiency and genes abundance on N₂O emission in ICL/ICLF

Nitrogen use efficiency by crops can be higher in ICL/ICLF due to grazing activity, which may affect N₂O emissions. Sheep grazing reduced N₂O emissions by 62 % in an ICL compared with no grazing (corn – ryegrass with oats), and the reduction was attributed to plant regrowth stimulated by grazing, which in turn increased N demand (Piva et al., 2019). Sheep grazing increased N availability (soil and plant uptake) on green manure crops compared with no grazing in ICL and increased wheat and fall rye production (Cicek et al., 2014), likely because N is broken down more efficiently in the animal rumen than by soil microbes, which means that grazed cover crops supply more N than those left ungrazed. Additionally, higher shoot N content in black oats in grazed plots compared with ungrazed ones was attributed to higher N availability due to animal excreta (Bratti et al., 2022). The intercropping of corn with legumes (pigeon pea) and sheep grazing in ICL likely stimulated root growth by promoting factors such as phytohormones, and then improved N use efficiency (NUE) by up to 30 % compared with intercropped grasses (palisade) (Costa et al., 2021). Improvements in N use efficiency due to grazing may reduce N₂O emissions.

Grazing in ICL may promote the full denitrification process, leading to the reduction of N₂O to N₂ (Piva et al., 2019). However, Zhong et al. (2014) observed the effect of grazing only on the abundance of the amoA (ammonia monooxygenase, increase) gene of ammonia-oxidizing bacteria (AOB), but not on narG (nitrate reductase) and nosZ (nitrous oxide reductase), genes encoding denitrification (Figure 1), nor on N₂O emissions. The nosZ gene encodes N₂O transformation to N₂ in denitrifying microorganisms, which might result in reduced N₂O emissions. Portilho et al. (2018) observed an increase in amoA and nosZ abundances in ICL after three years, but N₂O emissions were not evaluated. In another study, however, simulated trampling increased nosZ gene abundance in grassland soil, but it also increased N₂O emissions (Treweek et al., 2016). Yet another study reported that ryegrass increased denitrifying microorganisms and reduced N₂O emissions compared with bare soil (Wang et al., 2021a). On the contrary, Zhang et al. (2021) found that the exclusion of sheep grazing increased nirk (nitrite reductase) and nosZ gene abundances and reduced N₂O emissions compared with continuous grazing. Therefore, grazing was shown to have a dual effect, increasing N₂O emissions due to soil compaction and gene abundance, and reducing them through better NUE. Moreover, denitrification, heterotrophic nitrification, and co-denitrification may be relevant N₂O pathways in ICL/ICLF due to high organic C and N levels and should be further evaluated.

N₂O emission due to C and N mineralization

Crop residues can increase N₂O emissions of agricultural systems due to N mineralization (Hansen et al., 2019). In a meta-analysis, immature crop residues containing easily degradable compounds increased N₂O emissions, while mature residues with more recalcitrant compounds had no effect (Abalos et al., 2022). Nitrogen mineralization can be higher in non-integrated systems due to leaf fall or residue incorporation, increasing N₂O emissions compared with ICL (Salton et al., 2014; Sato et al., 2017). However, severe grazing defoliation can increase soil labile C, potentially increasing N₂O emissions (nirk/nosZ) in ICL/ICLF (Kelly et al., 2022). Several studies reported higher C and N availability, organic matter as well as N mineralization and dissolved/labile C and N in ICL compared with non-integrated systems (Acosta-Martínez et al., 2004; Tracy and Zhang, 2008; Carvalho et al., 2010; Tian et al., 2010; Sant-Anna et al., 2017; Franzluebbers et al., 2020; Dhaliwal et al., 2021; Denardin et al., 2022; Oliveira et al., 2022). This suggests that the levels of readily degradable C and N are higher in ICL compared with non-integrated systems, which may contribute to increased emissions of N₂O. Cardoso et al. (2022), studying ICLF in Brazil, measured lower N₂O emissions compared with pasture in the first two years, however, in the following two years, the opposite was observed. The authors attributed the reduction in N₂O emissions in the first years to high N demand by the trees, and the increase in N₂O later to N mineralization from eucalyptus leaf residues of high N content and high soil moisture from low evapotranspiration. Higher soil C in ICL/ICLF, on the other hand, was shown to have a negative correlation with N₂O emissions (Sato et al., 2019; Carvalho et al., 2024).

Estimated total N₂O emission and GHG mitigation strategies in ICL/ICLF

The estimated direct N₂O emission from manure deposited on soil was approximately 300 kg ha^-1 yr^-1 of CO_2eq. Indirect N₂O emissions ranged from 171 to 1,340 kg ha^-1 yr^-1 of CO_2eq, while total N₂O emissions varied between 830 and 5,353 kg ha^-1 yr^-1 of CO_2eq (Table 3). On average, direct N₂O emissions were 896 kg ha^-1 yr^-1 of CO_2eq from fertilizer and 309 kg ha^-1 yr^-1 of CO_2eq from manure. The mean indirect N₂O emission was 574 kg ha^-1 yr^-1 of CO_2eq. These accounted for 50, 18, and 32 % of the total estimated N₂O emissions (1,779 kg ha^-1 yr^-1 of CO_2eq) in ICL/ICLF, respectively. In non-integrated systems, average direct N₂O emissions from fertilizer were 1,009 kg ha^-1 yr^-1 of CO_2eq (69 %), and indirect emissions were 454 kg ha^-1 yr^-1 of CO_2eq (31 %), with total N₂O emissions (direct + indirect) ranging from 433 to 6,075 kg ha^-1 yr^-1 of CO_2eq and a mean of 1,463 kg ha^-1 yr^-1 of CO_2eq. Total N₂O emissions can substantially affect the GHG balance in ICL/ICLF systems. Consequently, implementing mitigation strategies within integrated systems is essential for reducing GHG emissions from agricultural production.

Table 3
Estimated total N₂O emissions in integrated crop-livestock-forestry

System	Stocking rate	N2O				Reference
		Fertilizer(1)	Manure(2)	Indirect(2)	Total
	head ha-1	______________ kg ha-1 yr of CO2eq
ICL	2.11	3479	324	1308	5111	Amadori et al. (2022)
ILF	2.33	3003	358	1340	4701
ICLF	2.33	3655	358	1340	5353
ICL	2.11	665	324	301	1290	Bratti et al. (2022)
	2.11	734	324	454	1511
	2.11	867	324	606	1797
	2.11	669	324	301	1295
	2.11	828	324	454	1606
	2.11	828	324	606	1758
	2.11	652	324	466	1442
	2.11	824	324	454	1602
	2.11	927	324	606	1857
ICL	2.11	858	324	553	1735	Carvalho et al. (2014)
ICL	2.11	1313	324	952	2589	Bastos et al. (2026)
	2.11	1759	324	952	3035
	2.11	1231	324	952	2507
	2.11	1351	324	952	2627
	2.11	1270	324	952	2546
	2.11	759	324	606	1690
	2.11	1703	324	606	2633
	2.11	1073	324	606	2003
	2.11	1321	324	606	2252
	2.11	1133	324	606	2063
	2.11	266	324	606	1196
	2.11	412	324	606	1342
	2.11	335	324	606	1265
	2.11	455	324	606	1385
	2.11	420	324	606	1351
ICL	2.50	1218	384	764	2366	Carvalho et al. (2017)
ICLF	1.58	862	243	491	1596
ICL	2.11	197	324	309	830	Carvalho et al. (2022)
	2.11	292	324	309	924
	2.11	223	324	309	856
	2.11	257	324	309	890
ICL	2.11	60	324	995	1379	Matthews et al. (2025)
	2.11	133	324	797	1254
	2.11	180	324	452	956
ICLF	3.77	545	579	752	1876	Nascimento et al. (2020)
ICLF	2.94	159	452	1031	1642	Nogueira et al. (2016)
ICL	2.11	326	324	423	1073	Pilecco et al. (2019)
	2.11	403	324	423	1151
	2.11	378	324	423	1125
	2.11	459	324	423	1206
ICL	1.70	1828	261	700	2789	Piva et al. (2014)
ICL	2.11	343	324	529	1196	Piva et al. (2019)
	2.11	897	324	529	1750
ICL	2.11	1115	324	301	1741	Ribeiro et al. (2020)
	3.00	1115	461	428	2004
	2.40	944	369	343	1655
	1.20	815	184	171	1171
ICL	2.11	652	324	556	1532	Sato et al. (2017)
ICL	2.11	644	324	460	1427	Singh et al. (2020)
	2.11	686	324	460	1470
	2.11	858	324	460	1642
	2.11	944	324	460	1728
	2.11	729	324	466	1519
	2.11	944	324	466	1733
	2.11	905	324	466	1695
	2.11	935	324	466	1725

• ⁽¹⁾
  Observed data.
• ⁽²⁾
  Estimated.

Removal of CO₂ through timber harvesting can result in negative or neutral GHG emissions from ICLF systems. This mechanism enhances the sustainability of the livestock sector, exemplified by the production of carbon-neutral beef (Torres et al., 2015; Alves et al., 2017b; Oliveira et al., 2020; Lucchese-Cheung et al., 2021). The ICLF also promotes improved animal welfare, as lower body temperatures are maintained under the shade of the forestry component compared with open pastures without trees (Alves et al., 2017b; Karvatte et al., 2021). In Brazil, Embrapa developed the carbon-neutral beef certification, which mandates adherence to sustainable practices, monitoring of soil organic C, calculation of neutralized C, assurance of C stocks for timber products, compliance with national regulations, and periodic audits (Alves et al., 2017b).

Long-term experiments (up to 22 years) in ICL/ICLF have reported increases in soil C stocks ranging from 0.15 to 2.85 Mg ha^-1 yr^-1 of C (Carvalho et al., 2010, 2014; Piva et al., 2014; Sant-Anna et al., 2017; Bieluczyk et al., 2020; Ribeiro et al., 2020; Oliveira et al., 2022, 2024; Damian et al., 2023). However, soil C sequestration is primarily governed by intrinsic soil properties, climate, and management practices, which may limit its potential for further reducing CO₂ emissions (Lal, 2004).

Other strategies include the use of additives that reduce both N₂O and enteric CH₄ emissions. For example, nitrification inhibitors can lower N₂O emissions from fertilizer and manure by over 50 % in grazing systems (Soares et al., 2023). Enteric CH₄ emissions can also be reduced by approximately 30 % with the use of 3-nitrooxypropanol as a feed additive (Kebreab et al., 2023). Thus, adopting targeted management techniques within agricultural systems can significantly enhance the sustainability of livestock production.

Integrating specific plant species into ICL/ICLF can also result in the production of root exudates with biological nitrification inhibitor (BNI) activity, thereby reducing N₂O emissions (Subbarao et al., 2013; Sato et al., 2017). The BNIs had been identified in over 20 plant species, including brachiaria, ryegrass, sorghum, corn, and rice. These compounds inhibit key enzymes in the nitrification process, namely, ammonia monooxygenase and hydroxylamine oxidoreductase (Subbarao et al., 2013; Wang et al., 2021b; Saud et al., 2022). In specific cases, however, as reported by Canisares et al. (2021), corn–brachiaria intercropping has demonstrated lower BNI potential and higher N₂O emissions than monocropped corn, likely due to increased N availability from brachiaria residue decomposition following desiccation in the first season. Thus, further research is needed to elucidate BNI dynamics in ICL/ICLF entirely.

CONCLUSIONS

Integrated systems (Integrated Crop-Livestock, ICL / Integrated Crop-Livestock-Forestry, ICLF) affect soil properties and nitrous oxide (N₂O) emissions in more diverse ways than non-integrated systems, making direct comparison challenging. The emission factor from fertilizer N₂O was 1.03 % (±0.24 %) for ICL/ICLF and 0.80 % (±0.41 %) for the non-integrated systems, with no difference between them (n = 533). In four studies, N₂O emissions were reduced in ICL/ICLF compared with non-integrated systems, while in seven studies no difference was reported, and only one study reported an increase in N₂O emissions. The reductions of N₂O emissions were attributed to lower soil temperature, presence of biological nitrification inhibitor (BNI) compounds due to higher plant diversity, and better nitrogen use efficiency (NUE) compared with non-integrated systems. On the other hand, ICL/ICLF may increase N₂O emissions due to increased gene abundance, soil compaction from trampling, and increased soil organic carbon (C) and nitrogen (N) compounds. Further research should investigate denitrification, heterotrophic nitrification, and co-denitrification as potentially relevant N₂O pathways in ICL/ICLF systems, given the elevated levels of organic C and N.

The limitations of studies evaluating N₂O emissions in ICL/ICLF may be related to the uneven treatments between ICL/ICLF and non-integrated systems, and the difficulty of analyzing multifactorial experiments. The studies comparing N₂O emissions in ICL/ICLF and non-integrated systems included other different factors that may have influenced their effect, such as conservationist practices (no-till vs. till), application of different N rates, different crops in the sequence, as well as diverse and insufficient lengths of the evaluation period (some months instead of an entire year or more). In addition, ICL/ICLF have other N inputs besides N fertilizer, such as the deposition of animal excreta. Furthermore, studies comparing ICL/ICLF with non-integrated systems should evaluate N₂O emissions preferably in the long-term time scale.

FUNDING

This study was financed by the Funding Authority for Studies and Projects (FINEP/CT – AGRO/FNDCT, Cooperation Agreement No. 01.22.0080.00, Ref. 1219/21). Besides, the authors acknowledge the financial support provided for the SENSE project (ID 109) through the partners of the 2021 Joint Call of the Cofund ERA-Net SusCrop (Grant No. 771134), FACCE ERA-GAS (Grant No. 696356), ICT-AGRI-FOOD (Grant No. 862665) and SusAn (Grant No. 696231) and by the New Zealand Government to support the objectives of the Global Research Alliance on Agricultural Greenhouse Gases. Furthermore, we acknowledge the support from the National Institute of Science and Technology in Low Carbon Emission Agriculture (INCT-ABC) sponsored by CNPq (Grant No. 406635/2022-6). JRS received a fellowship from the Sustainable “Rural Sustentável—Cerrado” Project in partnership with the Inter-American Development Bank (IDB), the U.K. Government, the Brazilian Ministry of Agriculture, the Brazilian Institute for Development and Sustainability (IABS), and the ICLF Network Association. BJRA and BEM received fellowships from CNPq (Grant No. 315503/2023-8 and 311851/2026-6, respectively).

How to cite:

Soares JR, Alves BJR, Freitas ACR, Madari BE, Jantalia CP. Soil N₂O emissions in integrated crop-livestock-forestry: A review. Rev Bras Cienc Solo. 2026;50:e0250155. https://doi.org/10.36783/18069657rbcs20250155

DATA AVAILABILITY

The data will be provided upon request.

SUPPLEMENTARY DATA

Supplementary data to this article can be found online at https://www.rbcsjournal.org/wp-content/uploads/articles_xml/1806-9657-rbcs-50-e0250155/1806-9657-rbcs-50-e0250155-suppl01.pdf

SUPPLEMENTARY MATERIALS

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*

Corresponding author: e-mail: [e-mail]

Editor:

José Miguel Reichert https://orcid.org/0000-0001-9943-2898 and Jeferson Dieckow https://orcid.org/0000-0002-3025-4402

Publication Dates

• Publication in this collection
  19 Oct 2026
• Date of issue
  2026

History

• Received
  25 Aug 2025
• Accepted
  27 Feb 2026