Soil physical and biological quality in a peasant agroforestry system in Southern Brazil

doi:10.21203/rs.3.rs-2239028/v2

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Soil physical and biological quality in a peasant agroforestry system in Southern Brazil

https://doi.org/10.21203/rs.3.rs-2239028/v2

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Agroforestry systems bring together social, economic, and environmental services and can be an alternative for promoting development and sustainability in peasant agriculture. This study aimed to evaluate the soil quality in a peasant agroecological agroforestry intercropped with vegetables (South Brazil). Treatments included an agroforestry row (AFS-R) managed under no-tillage and cultivated with trees for fruit and wood production; an agroforestry inter-row (AFS-I) managed with conventional tillage and cultivated with vegetables; and an area managed with conventional tillage (CT). Soil physical assessments comprised soil bulk density, total porosity, macroporosity, microporosity, bioporosity, mean weight diameter of aggregates, field capacity, aeration capacity, soil saturated hydraulic conductivity, and the visual evaluation of soil structure. Microbiological indicators included soil microbial biomass, basal respiration, microbial quotient, metabolic quotient, soil organic carbon, and the most probable number of nitrogen-fixing, ammonifying, and nitrite-oxidizing bacteria. The results demonstrated that AFS-R management improved several soil physical and microbiological attributes, highlighting the importance of plant diversity, organic residue inputs, and no-tillage for soil quality. On the other hand, the tillage practice contributed to structural and microbiological degradation in CT, and more intensively in AFS-I, indicating that more conservationist soil management, like minimum or no-tillage, might be studied as an alternative for the cultivation of vegetable crops in agroforestry systems.

Soil health

Soil biology

Agroecology

Family farming

VESS

The pressure to increase land productivity is leading to land use intensification by agriculture, with increased use of irrigation, fertilizers, pesticides, and mechanization (Foley et al., 2011), as well as inadequate crop rotation, overgrazing or removal of crop residues (Karlen and Rice, 2015). These practices may contribute to decreasing soil quality (SQ). Soil structure is a component of SQ and regulates processes of water infiltration and retention, gas exchange, nutrient dynamics, and susceptibility to erosion (Rabot et al., 2018), as well as biological attributes such as microbial biomass (Silva et al., 2014; Merlo et al., 2022) and activity (Cui and Holden, 2015).

Agroforestry systems (AFS) are ancient and traditional production systems that are being brought back to current land use and research scenarios to take advantage of their sustainability attributes and benefits (Nair, 2014). AFS consists of the simultaneous cultivation of trees, agricultural species, and sometimes animals in the same cropping area, arranged in interactive combinations to generate a variety of products and goods, as well as environmental and ecological services (Nair et al., 2017). Studies have shown that AFS contribute to the conservation of biodiversity (Udawatta et al., 2019), air and water quality (Jose, 2009), carbon sequestration (Eddy and Yang, 2022) and the reduction of native forests deforestation (Sharma et al., 2016).

Soil physical quality increases in ASF, as a consequence of the action of roots and soil organisms, and organic matter accumulation, which helps decreasing soil erosion processes and improving water quality and quantity (Silva et al., 2011; Guimarães et al., 2014; Cherubin et al., 2019).The constant addition of organic matter from tree pruning and the action of the different sizes and shapes of roots also stimulates nutrient availability and cycling and soil organisms in the ASF, thus improving soil fertility (Froufe et al., 2020; Matos et al., 2022) and biology (Cezar et al., 2015; Beule et al., 2022).

The adoption of AFS may also contribute to economic and social aspects, being promoted as a sustainable production alternative for smallholder farming in Brazil (Bezerra et al., 2019; Shennan‐Farpón et al., 2022). The great diversity of food production in AFS, which comes from annual and vegetable crops, forestry and fruit species harvested at different times of the year, increases smallholder farmer’s income and optimizes family labour. In South Brazil, experiences with agroforestry systems inter-rowed with annual or vegetable crops are carried out in many smallholder farms (Stöcker et al., 2020; Valani et al., 2020).

Soil management of the AFS inter-rows, where vegetables are annually grown, can vary from the management of the rows, where trees are cropped. Vegetable production relies highly on topsoil turning and mixing to prepare the beds for crop growth, especially in organic and agroecological systems (Costa et al., 2018). The impacts of conventional tillage on soil physical attributes in grain and vegetable production systems are well known (Moraes et al., 2016; Norris and Congreves, 2018; Nunes et al., 2020), but there is little information regarding the effects of this kind of practice on the structural and microbiological soil attributes in agroforestry systems. This study aimed to evaluate the soil structural and biological quality of an agroecological agroforestry in South Brazil.

2. 1 Area and treatments

The study was carried out in an agroecological smallholder farm at the Contestado Settlement (25º37’09” S and 49º42’07” W, 910 m above sea level), in the city of Lapa – Paraná State, Brazil. The climate of the region is classified as Cfb (Köppen) (humid subtropical), with annual average rainfall ranging from 1400 to 1600 mm and average annual temperature from 17 to 18°C (Caviglione et al., 2000). The soil is an Inceptisol (Soil Survey Staff, 2014) or Cambissolo Háplico Tb Distrófico (Brazilian Soil Classification) (Santos et al., 2018).

At the farm, soil samples were taken in three areas with different soil management: agroforestry row (AFS-R), agroforestry inter-row (AFS-IR), and area managed with conventional tillage (CT). Granulometric and chemical characteristics of the areas are described in Table 1.

Table 1. Granulometry and chemical characterization of the soil (0-0.2 m) under the areas: agroforestry-row (AFS-R), agroforestry inter-row (AFS-I), and conventional tillage (CT), located in Lapa – PR, Brazil

Soil attributes	AFS-R	AFS-I	CT
Clay (g kg^-1)	268.0	273.3	356.8
Particle density (g cm^-3)	2.4	2.3	2.3
pH^a	5.3	5.4	5.1
Ca²⁺ (cmol_cdm^-3)^b	4.4	4.5	5.9
Mg²⁺ (cmol_cdm^-3)	2.4	2.6	2.8
K⁺ (cmol_cdm^-3)	0.4	0.5	0.1
Al³⁺ (cmol_cdm^-3)	0.0	0.0	0.1
H + Al (cmol_cdm^-3)	5.36	5.48	7.28
P (mgdm^-3)	10.6	7.5	11.8

^ameasured in 0.01 mol L^-1 CaCl₂,^bExchangeable calcium (Ca²⁺), exchangeable magnesium (Mg²⁺), exchangeable potassium (K⁺), aluminium (Al³⁺), potential acidity (H + Al), phosphorus (P)

The agroforestry system was established in 2015 in 0.5 ha on a dairy cattle pasture area. Soil was tilled with plowing and harrowing, lime was applied, and then oat (Avena sativa L.) and vetch (Vicia sativa L.) cover crops were sown. Twelve tree rows were implemented every 6 meters in an East-West direction. In the AFS-R an additional chiseling operation was performed before transplanting, being the soil tilled only at that time. Species for feeding (Acca sellowiana ((O.Berg) Burret), Actinidia deliciosa (A.Chev)), Citrus limon (L.), Citrus reticulata (L.), Citrus sinensis (L.), Eriobotrya japonica ((Thunb.) Lindl.), Eugenia uniflora (L.), Ilex paraguariensis (A.St.-Hil.), Manihot esculenta (Crantz), Musa spp., Passiflora edulis (Sims), Prunus persica, Prunus persica var. nucipersica ((Suckow) C. K. Schneid.0, Psidium cattleianum (Sabine), Schinus terebinthifolius), and for wood (Anadenanthera colubrina ((Vell.) Brenan), Cedrela fissilis (Vell), Eucalyptus sp., Toona ciliate (M.Roem.)) and biomass production (Eucalyptus sp., Morus sp., Musa spp., Sida sp.) are cropped in the rows.

The agroforestry inter-rows (AFS-I) are cultivated with vegetable crops (Allium cepa (L.), Beta vulgaris L., Brassica oleracea L., B. oleracea var. botrytis L., B. oleracea var. italica Plenck, Daucus carota (L.), Dioscorea sp., Eruca sativa (Mill.), Lactuca sativa (L.), Manihot esculenta (Crantz), Solanum lycopersicum (L.)) and beds are prepared annually with a rotary tiller. AFS-I received turkey litter (4.8 Mg ha^-1year^-1) as organic fertilizer and was supplemented with mineral potassium sulphate (0.72 Mg ha^-1year^-1). Turkey litter in AFS-I was incorporated on soil and potassium sulphate were broadcasted to the soil surface and covered with crop residues mowed from the AFS-R tress.

The area under CT covered approximately 0.3 ha and was in fallow before cultivation. Soil was tilled with plowing and leveling harrow 7 months before the experimental evaluations. The crop present at the time of sampling was a landrace corn (Zea mays). After the emergence of corn, fertilization occurred in total area with turkey litter (1.2 Mg ha^-1year^-1).

2.2 Soil sampling and analysis

Each management system was split into six plots and one point per plot was sampled. The undisturbed samples were collected at the 0–0.1, 0.1–0.2 and 0.2–0.4 m soil depths, in volumetric rings (0.05 × 0.05 m of internal diameter and height) using an Uhland auger. Soil monoliths (0.1 × 0.1 m) for aggregate stability analysis were collected at the 0-0.1 m and 0-0.2 m. For soil texture and chemical characterization, five soil disturbed sub-samples were taken at the 0-0.2 m to compose one sample (Teixeira et al., 2017).

Soil sampling for microbiological analysis was carried out at the 0-0.1 m. Six disturbed samples, formed through 10 sub-samples, were collected close to the points of previous soil sampling. At the laboratory, soil biological samples were homogenized, sieved (2 mm) and stored in plastic bags at 4° C until analysis.

The Visual Evaluation of Soil Structure (VESS) was carried out in the field using the method proposed by Ball et al. (2007) and improved by Guimarães et al. (2011).

Saturated hydraulic conductivity (Ksf) was measured in the field by the simplified falling-head (SFH) method (Bagarello et al., 2004). The analysis was carried out at the 0-0.1 m depth, with 12 repetitions due to Kfs high variability. The water volume used to determine the time of infiltration into the soil was 730 mL and the internal area of the metal ring used was 0.3979 m² (internal diameter of 0.208 m), corresponding to a D-value of 0.0214 m (Reynolds and Elrick, 2002). Soil initial volumetric and saturation moisture content for Ksf analysis were determined in the laboratory. The hydraulic conductivity of the saturated soil (Kfs) was calculated (Scarabeli et al., 2018).

Measurements of soil bulk density (BD), total porosity (TP), macroporosity (Ma), microporosity (Mi), field capacity (FC) and aeration capacity (AC) were carried out according to Teixeira et al. (2017) and bioporosity (Bp) according to Andrade et al. (2016). Bulk density was determined by the core method. TP was determined by the relationship between BD and particle density. Bp, Mi, and FC were measured applying the matric heads of -1, -6, and -10 kPa, respectively, in a tension table (model M1-0801, Eeijkamp^®). Ma and AC were estimated based on the differences between Tp in relation to Mi and FC, respectively. Soil organic carbon (SOC) was determined by the colorimetric method after extraction with sodium dichromate (Na₂Cr₂O₇ 0.667 mol L^-1) added in sulfuric acid (5 mol L^-1) (van Raij et al., 2001).

Aggregate stability analysis was carried out by manual fragmentation of the soil monoliths in their weakness plans, followed by sieving (19 mm mesh). Separation of the soil aggregate classes (8–19; 4–8; 2–4; 1–2; 0.5–1; 0.25–0.5 and 0.053–0.25 mm) was performed by wet sieving (Yoder, 1936) with adaptations for tropical soils (Castro Filho et al., 1998). The set of aggregates retained in each sieve was dried at 40 °C, weighted, and the mean weight diameter (MWD) was determined (Castro Filho et al., 1998). The proportions of the classes of large macroaggregates (L MAgg) - 8–19 mm, medium macroaggregates (M-MAgg) - 2–8 mm, small macroaggregates (S-MAgg) - 0.25–2 mm, and microaggregates (MicroAgg) - 0.053–0.25 mm, were also calculated (Ferreira et al., 2018).

Soil microbial biomass of carbon (MBC) was determined by the fumigation–extraction method (Vance et al., 1987) using an extraction coefficient K_C = 0.33 (Brookes et al., 1985). Soil basal respiration (BR) was estimated according to Alef (1995). The microbial quotient (qMic) was determined by the ratio between MBC and SOC (Insam and Domsch, 1988). The metabolic quotient (qCO₂) was calculated by the ratio between BR and MBC (Insam and Haselwandter, 1989). The total organic carbon for microbiological analysis was determined by extraction with potassium dichromate (K₂Cr₂O₇) and subsequent titration with ammonium ferrous sulfate solution (Walkley and Black, 1934).

The number of nitrogen-fixing bacteria (NFB), ammonifying bacteria (AB), and nitrite-oxidizing bacteria (NOB) were estimated by the most probable number (MPN) (Hungria and Araujo, 1994).

2.3 Statistical analysis

Data were submitted to analysis of variance. Residue normality and homogeneity of variances were verified by Shapiro-Wilk and Bartlett tests, respectively. When data transformation was necessary, Box-Cox optimum potency was used. After presuppositions had been verified, F test was performed and when significant (P <0.05), the means were compared by the Tukey test at 5% of probability. A principal component analysis (PCA) was performed to check the relationship among the sampling areas and the structural and microbiological variables, as well as the relationship among the variables at the 0-0.1 m soil layer. The VIF (Variance Inflation Factor) test was performed before PCA to exclude from analysis variables with high collinearity (VIF>20). All statistical analyses were performed using the software R, version 4.0.2 (R Core Team, 2020).

Soil physical variables and soil organic carbon (SOC) showed significant differences among the treatments. Soil BD and TP were affected by the treatments only at the 0-0.1 m soil layer (Table 2). AFS-I increased BD by 7.6 % in relation to AFS-R, which showed the lowest BD value. AFS-R promoted significant increases in TP, with values 9.8 % higher than AFS-I. CT did not differ from AFS-I and AFS-R for both variables.

Table 2. Soil organic carbon (SOC), bulk density (BD), total porosity (Tp), biopores (Bp), macropores (Ma), micropores (Mi), and mean weight diameter of aggregates (MWD) under agroforestry-row (AFS-R), agroforestry inter-row (AFS-I), and conventional tillage (CT).

Soil atributes	Layer (m)	AFS-R	AFS-I	CT	P-value	CV (%)
SOC (g kg^-1)	0-0.10	32.50	31.0	34.1	0.351	11.2
	0.1-0.2 m	25.83	28.50	30.67	0.07	11.65
	0.2-0.4	34.0 a	22.0 c	25.33 b	<0.01	20.85
BD (g cm^-3)	0-0.10	1.05 b	1.13 a	1.07 ab	0.05	4.97
	0.1-0.2	1.15	1.19	1.12	0.32	7.03
	0.2-0.4	1.21	1.24	1.19	0.52	6.80
Tp (cm³ cm^-3)	0-0.10	0.56 a	0.51 b	0.52 ab	<0.05	5.0
	0.1-0.2	0.50	0.46	0.50	0.15	7.18
	0.2-0.4	0.45	0.46	0.50	0.09	7.68
Bp (cm³ cm^-3)	0-0.10	0.15 a	0.08 b	0.06 b	<0.001	8.70
	0.1-0.2	0.10 a	0.05 b	0.03 c	<0.001	20.59
	0.2-0.4	0.06	0.06	0.05	0.47	25.94
Ma (cm³ cm^-3)	0-0.10	0.24 a	0.18 b	0.11 c	<0.001	12.3
	0.1-0.2	0.15 a	0.08 b	0.05 c	<0.001	16.7
	0.2-0.4	0.09	0.08	0.06	0.06	22.2
Mi (cm³ cm^-3)	0-0.10	0.32 b	0.31 b	0.43 a	<0.001	5.90
	0.1-0.2	0.35 b	0.39 b	0.45 a	<0.001	8.80
	0.2-0.4	0.36 b	0.38 b	0.41 a	<0.001	6.50
MWD (mm)	0-0.10	7.43 ab	7.07 b	7.92 a	<0.01	5.35
MWD (mm)	0.1-0.2	8.15 a	6.40 b	7.90 a	<0.01	7.41

Means followed by different letters in line are significantly different (Tukey, P ≤0.05).

The TP distribution, represented by Bp, Ma, and Mi, was significantly influenced by the soil management at the 0-0.1 and 0.1-0.2 m layers, and Mi at the 0.2-0.4 m. AFS-R showed the highest Bp values, increased by 87.5 % and 150% at the 0-0.1 m, and 94% and 177.1% at the 0.1-0.2 m layers in relation to AFS-I and CT, respectively. Regarding soil Ma, AFS-R row showed volumes higher than AFS-I and CT at both soil layers. CT presented the highest values of Mi compared to AFS-R and AFS-I, which did not differ statistically from each other. When compared to CT, AFS-I showed higher values of Ma at the 0-0.1 m, and Ma and Bp at the 0.1-0.2 m layers.

The MWD from AFS-I decreased in relation to CT in all soil layers, and in relation to AFS-R at 0.1-0.2 m layer (Table 2). For both soil depths MWD from AFS-R and CT did not differ from each other. However, in AFS-R the results show an increase in the diameter of aggregates of 0.72 mm at 0.1-0. 2 m layer (Table 2). The MWD alterations were a direct effect of the aggregate classes’ distribution (Figure 1). In both soil layers, CT presented the higher proportion of large macroaggregates (8-19 mm), and AFS-I the lowest values (P <0.05). At 0.1-0.2 m layer AFS-I had an increase in the proportion of medium macroaggregates by 21.70 and 18.50 % (P <0.01) in relation to AFS-R and CT, respectively. Small macroaggregates (0.25-2 mm) and microaggregates (<0.25 mm) presented an opposite behavior than large macroaggregates. AFS-I showed a higher proportion of medium and small macroaggregates and microaggregates regulating the soil structure, mainly at 0.10-0.20 m, when compared to AFS-R and CT.

The agroforestry row presented an overall VESS Sq of 1.47, significantly better than AFS-I (1.8) and CT (2.3) (P <0.001) (Figure 2b). When the average score of each individual soil layer was considered, no differences were found among the treatments for the more superficial soil layer (Figure 2a). However, the second layer (on average below the 0-0.1 m) preserved the overall Sq order of differences (P <0.001), demonstrating that AFS-R maintained a better structural quality in depth compared to AFS-I and CT, with this last one presenting a Sq value of 2.9, which is very close to the limit considered as a good soil structural quality.

SOC was affected by soil management only at the 0.2-0.4 m soil layer (Table 2). AFS-R showed the highest value of SOC, near 55 and 34 % higher than AFS-I and CT, respectively. AFS-I presented a lower SOC than CT at 0.2-0.4 m. It is noteworthy that only for AFS-R, SOC increased 1.04 and 1.32 times at 0.2-0.4 m soil layer, in relation to 0-0.1 and 0.1-0.2 m layers, respectively (Table 2).

AFS-R presented the highest Kfs value, statistically different and approximately two times greater from AFS-I, which showed the lowest Ksf. CT did not differ from the other treatments. In relation to FC, considering the matric head of -10 kPa, CT showed the highest values in relation to AFS-R and AFS-I in all soil layers (Table 3). However, this variation was more expressive at the 0-0.1 m layer (34 and 39% higher than AFS-R and AFS-I, respectively) and reduced gradually to 7 and 14% at the 0.2-0.4 m. AFS-R and AFS-I presented a similar FC, with no significant differences, in all soil layers (Table 3).

Table 3. Field capacity (FC), aeration capacity (AC), and saturated hydraulic conductivity (Kfs) under agroforestry-row (AFS-R), agroforestry inter-row (AFS-I), and conventional tillage (CT).

Soil atributes	Layer (m)	AFS-R	AFS-I	CT	P-value	CV (%)
FC (cm³ cm^-3)	0-0.10	0.33 b	0.29 b	0.39 a	<0.001	8.05
	0.1-0.2	0.33 b	0.39 b	0.44 a	<0.001	9.72
	0.2-0.4	0.35 b	0.36 b	0.43 a	<0.001	7.13
AC (cm³ cm^-3)	0-0.10	0.27 a	0.19 b	0.13 c	<0.001	6.19
	0.1-0.2	0.16 a	0.1 b	0.07 b	<0.001	14.25
	0.2-0.4	0.11	0.10	0.07	0.392	42.80
Kfs (mm h^-1)	0-0.10	806.26 a	428.9 b	728.26 ab	0.021	51.44

Means followed by different letters in line are significantly different (Tukey, P ≤0.05).

Regarding AC, the highest differences among treatments were found at 0-0.1 m soil layer (Table 3). In this layer, AFS-R showed an AC 42.1 and 107.7 % higher than AFS-I and CT, respectively. AC from CT at 0-0.1 m was 46.2 % lower than AFS-I. At the 0.1-0.2 m layer, AFS-R showed the highest values of AC, 60 and 128.6 % higher than AFS-I and CT, respectively. However, at 0.1-0.2 m layer, AFS-I and CT did not differ statistically from each other. No differences were found among the treatments at 0.2-0.4 m.

Considering the microbiological attributes (Table 4), significantly higher values of MBC were detected under AFS-R, followed by AFS-I and CT. In contrast, no differences in BR were found among the treatments. qMic values in AFS-R were twice higher than in AFS-I and in CT, that not differed statistically from each other. AFS-R also showed the lowest qCO₂ values, differing statistically from AFS-I and CT. SOC content at the 0-0.10 m was higher in CT, followed by AFS-R and AFS-I.

Table 4. Soil microbiological attributes at the 0-0.1 m soil layer of an agroforestry-row (AFS-R), agroforestry inter-row (AFS-I), and conventional tillage (CT).

Soil attributes	AFS-R	AFS-I	CT	P-value	CV (%)
MBC^a (mg C kg^-1 soil)	278.61 a	218.01 b	167.27 c	<0.01	12.64
BR (mg C-CO₂ kg^-1 soil h^-1)	2.09	1.88	2.02	0.53	7.72
qMic (%)	1.34 a	0.67 b	0.70 b	<0.01	10.20
qCO₂ (mgC-CO₂ g^-1 MB-C h^-1)	5.15 a	12.18 b	9.50 b	<0.01	11.26
SOC (g kg^-1)	27.35 b	24.88 c	31.22 a	<0.01	5.79
NFB (CFU g^-1 soil)	1.6 × 10³ b	2.7 × 10³ a	6.7 × 10² c	<0.01	16.90
AB (CFU g^-1 soil)	4.8 × 10⁶ a	2.03 × 10⁶ c	3.9 × 10⁶ b	<0.01	13.09
NOB (CFU g^-1 soil)	4.02 × 10⁶	4.5 × 10⁶	3.8 × 10⁶	0.17	12.33

Means followed by different letters in line are significantly different (Tukey, P ≤0.05)

^aSoil microbial biomass (MBC), basal respiration (BR), microbial quotient (qMic), metabolic quotient (qCO₂), soil organic carbon (SOC), nitrogen-fixing bacteria (NFB), ammonifying bacteria (AB), nitrite-oxidizing bacteria (NOB).

The higher NFB was observed under AFS-I, followed by AFS-R and CT. AFS-R presented the highest values of AB, followed by CT and AFS-I. No differences in NOB were observed among the treatments.

The PCA clearly separated the areas (Figure 3). PC 1 explained about 38% of the total variation and distinguished AFS-I from CT, while PC 2 accounted for approximately 30.9% of the total variation and separated AFS-R from AFS-I and CT. AFS-R was associated with macroporosity, bioporosity, saturated hydraulic conductivity, microbial biomass carbon and ammonia-oxidizing bacteria. Fewer variables were associated with AFS-I including bulk density, nitrogen-fixing and nitrite-oxidizing bacteria. Microporosity, field capacity, mean weight diameter, and soil organic carbon were related to CT.

MBC, AB, Kfs and BR showed a strong positive correlation and were negatively correlated with BD, demonstrating that increases in soil bulk density might impact the soil microbial community and its activity, as well as soil water conductivity. Higher MWD values were associated with higher SOC content.

Studies have shown that AFS contributes to the maintenance and enhancement of soil attributes related to soil quality (Cezar et al., 2015; Cherubin et al., 2019; Froufe et al., 2020; Stöcker et al., 2020) since soil management, especially tillage intensity and crop diversity, promotes changes in soil structural attributes, which also influences the chemical and biological soil properties (Kim et al., 2020; Nunes et al., 2020).

AFS-R presented higher TP and lower BD at the superficial layer, an increased volume of pores with large diameter (Ma and Bp) through the soil profile, as well as higher MDW, large and medium macroaggregates (0.1-0.2 m) and a better overall VESS score, which are indicators of increased physical quality. The absence of tillage and the action of the different root systems and soil organisms provided by the diversity of plant species cultivated in the rows, as well as the plant residues added to ASF-R through the pruning practice, may have contributed to these results (Cherubin et al., 2019; Rodríguez et al., 2021). It would also explain some of the physical attributes showing better values in AFS-R compared to the CT area tilled one time after fallow.

On the other hand, the vegetable cropping in agroforestry inter-rows increased soil BD (0-0.1 m) and reduced soil TP (0-0.1 m), Ma and Bp (0-0.2 m) in relation to the row with trees. The TP decrease observed in the surface layer from AFS-R to AFS-I (Table 2) can be attributed to the tillage employed for vegetable cultivation in the inter-rows. Tillage disrupts the bonds between particles in the large macroaggregates (responsible for soil structure stability), rearranging them inside the larger pores (ex. Macropores), with a consequent reduction in TP and an increase in BD (Cavalcanti et al., 2020). This hypothesis can be confirmed by the distribution of aggregate size classes, in which AFS-I presented a reduction in the proportion of macroaggregates and, consequently, an increased number of microaggregates.

Overall, the values of CT soil attributes remained between the AFS treatments. Many of the physical variables in CT were not statistically different from AFS-R, probably due to the short time since the conversion of the area from fallow to agriculture. Moreover, studies have shown that in the short term, tillage increases soil porosity and aeration. Over the years, however, tillage practices end up in physical quality degradation (Haruna et al., 2018; Vizioli et al., 2021), as has occurred in AFS-I.

Most of the significant differences between the areas occurred within the 0-0.2 m soil layer, probably due to this depth being more prone to the rotary tiller action to prepare the horticultural soil beds. A rotary tiller has blades that shred, mix and crumble the soil, breaking soil aggregates excessively and usually forming a subsoil pan at the depth where implement weight is supported (Laudicina et al., 2017). This fact supports our findings for MDW, aggregates size distribution, and VESS Sq among the studied areas, as well as the values of macroporosity below the ideal limits for gaseous exchange and root growth (0.1 m³ m^-3) (Xu et al., 1992) at the 0.1-0.2 m soil layer in AFS-I and CT.

Soil organic carbon did not vary in the more superficial layers, independent of the soil management practices. SOC increases are usually observed in systems with positive carbon balance at the long term. Thus, assessing the effects of vegetable cultivation on agroforestry inter-rows should be carried out over longer periods. This is highlighted by the fact that in conventional tillage systems (i) SOC might be redistributed within the soil profile (McCarty et al., 1998; Ferreira et al., 2018) and (ii) the formation and stability of soil aggregates might be compromised by exposing the physically protected carbon to the soil microbial community (Hok et al., 2021). Soil microbial activity increases due to the aeration and the availability of substrates for their metabolisms, and as result SOC is released from the system as CO₂ (Xiao et al., 2019).

The visual evaluation of soil structure (VESS) demonstrated that soil structure was best following the order AFS-R > AFS-I > CT. AFS-R presented roots and small aggregates in the whole block indicating homogeneity of the soil structure. Less uniformity was observed between AFS-I and CT blocks, with all the sampled points showing two layers of soil with structural differences: a superficial layer visually structureless, consisting with loose soil particles with absence of aggregates, and another layer with firmer, less porous and with bigger aggregates. These differences in the soil profile are characteristic from anthropogenic management, in this case, mainly by the action of mechanization techniques as the rotary tiller, which tends to disrupt soil structure and result in higher Sq values (Guimarães et al., 2017; Cherubin et al., 2019).

The lower Sq found for CT might be an outcome from the poorer Sq attributed to its second soil layer, probably remaining from the previous soil management explored in the area before the fallow period. This finding reinforces the importance of plants root systems for mitigating compaction problems and building soil structure (Zhang and Peng, 2021), considering the lower tillage mobilization in CT, but also the absence of plants with aggressive root systems cultivated in the recent years compared to AFS-I. Despite the differences, all managements where within the range of good soil quality based on the interpretation that Sq < 3 is adequate and means that no management interventions should take place (Ball et al., 2007; Guimarães et al., 2011).

The better structural attributes found in AFS-R may explain its highest AC and Kfs values. The non-mobilization of the soil and the action of roots and edaphic fauna in the tree rows contributed to the formation of large pores (Ma and Bp), through which the movement of air and water mainly occurs (Borges et al., 2019). In AFS-I, pores size continuity may have been impaired due to soil tillage intensity, resulting in lower AC and Kfs values (Dal Ferro et al., 2014; Borges et al., 2019), similarly to the findings of Moraes et al. (2016) which observed doubled values for Kfs in no-till (NT) compared to CT and attributed the results to the higher number and continuity of biopores present in the NT area.

The Kfs in CT was statistically similar to the AFS row and inter-row, probably due to soil tillage practice with plowing and harrowing that, in the short term, reduces Bd, increases soil aeration (Haruna et al., 2018), and the volume of cracks (Lopez-Bellido et al., 2016), implying in higher saturated hydraulic conductivity in the CT area. Besides the lack of differences compared to AFS-R, it is important to remember that the CT area presented critical values (lesser than 0.1 m³ m^-3) for Ma at the 0.1-0.2 layer (Xu et al., 1992), where water infiltration in the soil may be compromised.

PCA showed that the differences in soil management and crop diversity separated the areas regarding soil physical and microbiological quality. Besides, it was evident that soil structure affects soil microbial attributes. Soil aeration and water content are important parameters for plant growth and have also direct effects on soil microbial community (Hungria et al., 2009; Silva et al., 2014), which might explain the negative relationship between BD and Kfs, and MBC. The better structure in AFS-R soil together with the diversified vegetation and mulching may have contributed to the generation of a more beneficial environment for the soil microbial community, being the tree rows more linked to MB-C and qMic. Higher values of qMic suggest more favorable conditions for microbial biomass formation (Babujia et al., 2010), with soil microorganisms increasing the proportion of carbon in its cells in relation to the SOC. On the other hand, AFS-I and CT were more associated with qCO₂, indicating a lower metabolic efficiency, and more intense biological activity for carbon degradation than microbial biomass growth, which might occur in stressful conditions (Bini et al., 2014; Lopes et al., 2021).

These results agree with a range of studies that have shown that conservationist soil management systems provide higher MB-C values and lower RB values, resulting in higher qMic and lower qCO₂ values (Hungria et al., 2009; Silva et al., 2014; Bini et al., 2014; Lopes et al., 2021). In this sense, the absence of differences in BR might have a different interpretation for the areas, revealing a more stable community in AFS-R, and a more stressed community in AFS-I and CT.

In AFS-I, the intense tillage may have promoted a rapid access of the microorganisms to SOC through aggregates breakage and internal carbon exposition along the time, what ended up in the depletion of energy resources and microbial community starving periods (Fiedler et al., 2016). For CT, although SOC was the highest among the areas, the microorganisms were also in a stressful condition, which could be explained by the low organic inputs added to the area and the presence of SOC content in large aggregates (higher MWD values), protected from MB access.

Regarding microbiological attributes linked to N cycling, the higher AB in AFS-R can be an indicative that in the rows, where the input of organic residues is higher and the root system is persistent, ammonium production results from the mineralization of organic matter, and this process acts as an important source of nitrogen to the trees (Beule et al., 2020). On the other hand, BNF was higher in AFS-I what might be a surprising result if we take in account that many studies have shown that conservation soil practices improve BNF compared to tillage (Torabian et al., 2019). However, this finding could be explained by the possible differences in the diversity and the metabolism of the microbial communities in the areas. In environments with more diverse C inputs, as native forests and perhaps AFS-R, microbial communities are usually more diverse and formed by K-strategists, that are less metabolic active, grows slowly and are more adapted to use C sources (Zhou et al., 2018). However, in more simplified and disturbed environments like agricultural sites and in this case AFS-I, r-strategists may dominate, being less generalists in terms of C sources, more active, and growing at higher rates, especially when there is great availability of energy sources (Zhou et al., 2018).

Despite the absence of differences in NOB among the areas, PCA showed that this variable was more associated with AFS-I, possibly due to tillage that mixes soil and disperse soil nitrogen and nitrifiers more uniformly, creating more substrate-rich microsites for NOB development (Liu et al., 2017). NOB was also negatively correlated with SOC, which could be expected since this study focused on autotrophic nitrification (Liu et al., 2017). Once again, CT presented values that can be interpreted as in between the AFS-R and AFS-I areas, showing that with time tillage practices can degrade the soil and highlighting the importance of adequate soil management strategies for achieving soil physical and biological quality in agroecosystems.

Soil structural and biological attributes evaluated in this study indicate a better soil physical and biological quality under the agroforestry tree rows. The lower plant diversity and tillage contributed to structural and microbiological degradation in the first-year conventional tillage area and more intensively in the four years agroforestry inter-row. These results indicate that more sustainable soil practices, like reduced or no-tillage, should be studied and adopted as alternatives for cropping vegetable crops in agroforestry systems.

Acknowledgments

This study was suported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (Capes) - Finance Code 001. The authors would like to thank the farmers that allowed their farms to be sampled and all the people involved in this study, from soil sampling to writing.

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No competing interests reported.

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Soil physical and biological quality in a peasant agroforestry system in Southern Brazil

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