The effect of organic matter on the structure of soils of different land uses

Soil & Tillage Research 114 (2011) 183–192

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The effect of organic matter on the structure of soils of different land uses Erika Tobiasˇova´ Department of Pedology and Geology, Faculty of Agrobiology and Food Resources, Slovak Agricultural University, Tr. A. Hlinku 2, 949 76 Nitra, Slovak Republic

A R T I C L E I N F O

A B S T R A C T

Article history: Received 30 November 2010 Received in revised form 18 April 2011 Accepted 13 May 2011 Available online 14 June 2011

In this study, the soil structure of two soils (Haplic Chernozem and Eutric Fluvisol) of different land uses (forest, meadow, urban and agro-ecosystem – consisted of four crop rotations) in Slovakia was compared. The soil aggregate stability was determined with a dependence on the chemical composition of plant residues. The quantity and quality of the organic matter was assessed through the parameters of the C and N in size fractions of dry-sieved and water-resistant aggregates. The soil structure of the forest ecosystem was evaluated as the best of all of forms of land use. Differences in the soil structure under the grass vegetation of a meadow (natural conditions) and urban ecosystem were also recorded. The agroecosystem was characterised by a higher portion (55.95%) of the most valuable (agronomically) waterresistant aggregate size fraction of 0.5–3 mm. Values of the carbon management index showed that the larger water-resistant aggregates were, the greater were the changes in the organic matter (r = 0.680, P < 0.05). In addition, a smaller content of dry-sieved aggregates of the 3–5 mm size fraction was observed with higher contents of soil organic carbon (SOC) (r = 0.728, P < 0.05) and labile carbon (CL) (r = 0.760, P < 0.05); there were also greater changes in the soil organic matter and vice versa, higher contents of SOC (r = 0.744, P < 0.05) and CL (r = 0.806, P < 0.05) greater contents of dry-sieved aggregates of size fraction 0.5–1 mm. The soil structure of agro-ecosystem was superior at a higher content of cellulose (r = 0.712, P < 0.05) in the plant residues. The higher content of cellulose and hemicellulose in the plant residue of a previous crop was reflected in a smaller CL content in the water-resistant aggregates (r = 0.984, P < 0.05). A correlation was observed between a high content of lignin in the plant residue and a smaller SOC content in the water-resistant aggregates (r = 0.967, P < 0.05). Lastly, a higher content of proteins in the plant residues (r = 0.744, P < 0.05) supported a greater content of drysieved aggregates of the 0.5–1 mm size fraction. ß 2011 Elsevier B.V. All rights reserved.

Keywords: Soil structure Soil aggregates Soil organic matter Labile carbon Labile nitrogen Plant residues

1. Introduction Degradation of soil physical properties is closely linked with the reduction of its organic matter concentration, which is essential to aggregation (Zeytin and Baran, 2003), and the latter is critical to stabilisation of carbon (C) pool through physical protection within aggregates (Balabane and Plante, 2004). The stability of soil aggregates depends not only on the quantity, but also on the quality, of the input of organic matter (Tisdall and Oades, 1982; Sˇimansky´ and Zaujec, 2009). Different fractions of organic matter participate in the formation and stabilisation of soil aggregates in different ways (Roberson et al., 1991); furthermore, the soil structure of agro-ecosystems is different from the soil structure of natural ecosystems. In natural ecosystems, factors such as soil type and texture composition contribute to the formation of the soil structure, whereas in agro-ecosystems, humans alter the soil

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structure through the burial of various crop residues (Zaujec and Sˇimansky´, 2003), the application of organic fertilisers (Tejada and Gonzalez, 2005), and cultivation (Atkinson et al., 2009). The sustained addition of crop residue increases the organic carbon content, particularly in the surface layer of soil, which supports the creation of a new soil layer with better and more stable aggregates (Martı´nez et al., 2008). Crop rotation also affects the percentage share of water-resistant aggregates of sizes from 2.00 to 6.30 mm and <0.25 mm and mean weight diameter (Sˇimnasky´ et al., 2008; Martins et al., 2009). The distribution of aggregate fractions has shown that the soil under natural vegetation has a higher aggregate stability (83% of the soil matrix in macroaggregates) (Barreto et al., 2009). The objectives of this study were as follows: (i) to compare the soil structure in two soils under different land uses, (ii) to assess the quantity and quality of the organic matter through the parameters of carbon and nitrogen in size fractions of dry-sieved and water-resistant aggregates, and (iii) to determine the influence of the chemical composition of plant residue on soil aggregate stability.

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The studied areas are located in the Podunajska lowland. Localities of Eutric Fluvisols (WRB) (agro-ecosystem, forest ecosystem, and meadow ecosystem) are present on the Podunajska flat, all of the ecosystems of Haplic Chernozems (WRB) and the urban ecosystem on the Podunajska hill. Geological substrates of the Podunajska lowland are neogene clays, sands and gravels, which are covered with loess and loess loam in most such areas. Fluvial sediments are found along the rivers Vah and Nitra. The relief of the Podunajska plain is monotonous. On the Podunajska flat, the relief is mostly wavy and covered with loess and loess loam. In some places above the surface, neogene rafts of clays, sands or gravels are found. The Podunajska hill is covered with valleys and neogene formations. The sampling places on the Eutric Fluvisols are situated near the flat areas on the Vah and Nitra rivers. Localities of Haplic Chernozems are situated on slight slopes with exposure to the SW (forest and meadow ecosystems and agroecosystem) and to the NE (urban ecosystem). The average annual temperatures of the studied areas are 9.7 8C (Nitra), 9.8 8C (Sala), 9.7 8C (Mocenok), and 10.4 8C (Komjatice), and the average rainfall per year is 580 mm (Nitra), 568 mm (Sala), 560 mm (Mocenok), and 566 mm (Komjatice) (Korec et al., 1997).

community was represented by Geranium robertianum, Viola sylvatica, Veronica chamaedrys, Glechoma hederacea, Pulmonaria officinalis, Asarum europaeum and various types of grasses. In the forest ecosystem on the Eutric Fluvisol, the dominating trees were Alnus glutinosa, Populus nigra, and Salix alba; the shrub vegetation was represented by Swida sanguinea; and the herbal community was represented by Urtica dioica, Lamium maculatum, G. hederacea, Galium verum, Ficaria bulbifera, P. officinalis, Symphytum officinale, Stellaria holostea, Impatiens noli-tangare, Ranunculus repens, and Chelidonium majus. In the meadow ecosystem on the Haplic Chernozem, the dominating species were the plant grasses, Thlaspi perfoliatum and Trifolium hybridum. In the meadow ecosystem on Eutric Fluvisol, the diversity of plants was higher and, in addition to the grasses, Taraxacum officinale, Trifolium repens, Carduus personata, and Medicago lupulina were also dominating herbs. In the urban ecosystem on the Haplic Chernozem, the vegetation consisted mostly of grasses with the presence of other herbs, such as Amarantus retroflexus, Cirsium arvense, Tanacetum vulgare, Raphanus raphanistrum, Tithymalus cyparissias, Vicia hirsute, Melilotus alba, Convolvulus arvensis, Berteroa incaca, and Achillea millefolium; on the Eutric Fluvisol, in addition to the grasses, there were herbs such as Geranium pratense, Cichorium intybus, T. officinale, Lotus corniculatus, Anthyllis vulneraria, T. repens, and A. millefolium. The vegetation in the agro-ecosystems is given by the crop rotations (Table 1).

2.2. Experimental details

2.3. Soil samples and analytical methods used

The experiment included four types of ecosystems, which present different land uses and management (FE, forest ecosystem; ME, meadow ecosystem; UE, urban ecosystem; AE, agro-ecosystem) of two soil types (HC, Haplic Chernozem; EF, Eutric Fluvisol) (Fig. 1). The agro-ecosystem included four crop rotations for the Eutric Fluvisol (EF-01–04) and Haplic Chernozem (HC-01–04). The forest ecosystems were natural forests with human control; the meadow ecosystems were created by man 30 years ago; and the urban ecosystems presented soils of urban landscape (grasses in a town influenced by human activities). The fields in agroecosystems were located in different farms under real production conditions. The vegetation in the forest, meadow and urban ecosystems was described by the dominating trees and herbs with dependence on the soil types and areas. In the drier areas of the Podunajska lowland, oak forests exist, and along the Vah River, floodplain forests are preserved. In the forest ecosystem on Haplic Chernozem, the dominating tree was Quercus daleschampii; the shrub vegetation was represented by Crataegus laevigata, Hedera helix, Prunus spinosa, and Robinia pseudoacacia; and the herbal

The soil samples for soil structure determination were collected in three replicates to a depth of 0.30 m in four different ecosystems (forest, meadow, urban and agro-ecosystem); in the agroecosystems, collections were also made in different fields with different crop rotations and different applications of farmyard manure (Table 1). All of the samples were taken from a depth of 0.3 m, dried in a constant-temperature room of 25  2 8C, and for chemical analyses also grinded. The basic chemical properties of the soils in the individual variants are characterised in Table 2. The soil organic carbon (SOC) was determined by wet combustion (Orlov and Grisˇina, 1981), the total nitrogen (NT) was determined by the Kjeldahl method (Bremner, 1960), the pH of the soil was potentiometrically measured in a supernatant suspension of a 1:2.5 soil:liquid mixture. The liquid is either 1 mol dm 3 KCl (pHKCl) (van Reeuwijk, 2002). Carbonates were determined by volumetric methods (using a simple calcimeter), based on the CO2 evolution after reactions with HCl (diluted with water in a 1:3 ratio) (Allison and Moodie, 1965). The cation exchangeable capacity (CEC) was determined according to the Pfeffer method (Jackson, 2005), and the sum of exchangeable cations

2. Materials and methods 2.1. Characteristics of the territory

Fig. 1. Localities of the Haplic Chernozem (1 – Mocˇenok, 2 – Komjatice) and Eutric Fluvisol (3 – Sˇal’a, 4 – Nitra).

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Table 1 Crop rotations of the fields of Eutric Fluvisol and Haplic Chernozem and doses of farmyard manure (FYM). EF-01a

Winter wheat (Triticum aestivum) + 40 t ha Sugar beet (Beta vulgaris) Maize (for silage) (Zea mays) Winter barley (Hordeum vulgare) Maize (for silage) + 40 t ha 1 FYM Sugar beet Winter wheat Winter wheat + 40 t ha 1 FYM Sugar beet Spring barley Winter wheat Maize (for silage) + 40 t ha 1 FYM Sugar beet Maize (for silage) Winter wheat + 40 t ha 1 FYM Sugar beet Winter barley + 20 t ha 1 FYM Maize (for silage) Winter wheat + 40 t ha 1 FYM Sugar beet Winter wheat Winter barley + 40 t ha 1 FYM Sugar beet Maize (for silage) Spring barley + 25 t ha 1 FYM Winter wheat Sunflower Winter wheat + 35 t ha 1 FYM

EF-02

EF-03

EF-04

a b

1

HC-01b

FYM

Sugar beet Maize (for silage) Maize (for silage) + 40 t ha 1 FYM Sugar beet Winter wheat + 40 t ha 1 FYM Maize (for silage) Spring barley Maize (for silage) Sugar beet Maize (for silage) Maize (for silage) Sugar beet Spring barley + 40 t ha 1 FYM Maize (for silage) Maize (for silage) Maize (for silage) Spring barley + 40 t ha 1 FYM Sugar beet Winter barley Maize (for silage) Sunflower (Helianthus annuus) Winter wheat + 40 t ha 1 FYM Sugar beet Maize (for silage) Sunflower Winter wheat Winter wheat Winter rape (Brassica napus var. napus)

HC-02

HC-03

HC-04

EF-01–EF-04 – different crop rotations of fields on Eutric Fluvisols. HC-01–HC-04 – different crop rotations on fields in Haplic Chernozems.

Table 2 Chemical properties of the Haplic Chernozem and Eutric Fluvisol with different land uses in agro-ecosystems. SOCi (g kg a

HC-01 HC-02 HC-03 HC-04 HC-FEb HC-MEc HC-UEd EF-01e EF-02 EF-03 EF-04 EF-FEf EF-MEg EF-UEh a b c d e f g h i j k l

20.5 21.0 20.3 21.0 22.3 22.1 23.0 15.0 19.0 15.3 12.3 29.5 21.1 19.4

1

)

pH

CO32 (%)

CECj (mmol kg

5.8 6.6 6.5 4.5 5.7 7.6 7.7 7.1 7.2 7.4 7.5 7.6 7.5 6.9

0.2 0.2 0.2 0.1 0.1 3.0 2.0 5.0 2.6 1.4 3.5 10.0 2.4 0.5

140 156 148 117 168 120 164 115 192 117 89 132 176 188

1

)

Sk

C:N (g kg

128 149 140 91 141 117 161 112 189 113 86 128 174 185

10.3 10.7 10.9 10.8 11.4 8.5 8.9 8.3 8.4 8.4 7.7 9.4 8.1 8.2

1

)

NTl

P

K

2.0 2.0 1.9 1.9 2.0 2.6 2.6 1.8 2.3 1.8 1.6 3.1 2.6 2.4

0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

0.5 0.3 0.4 0.3 0.2 0.7 0.3 0.2 0.2 0.2 0.3 0.4 0.2 0.8

HC-01–HC-04 – different crop rotations of fields of Haplic Chernozem. HC-FE – forest ecosystem on Haplic Chernozem. HC-ME – meadow ecosystem on Haplic Chernozem. HC-UE – urban ecosystem on Haplic Chernozem. EF-01–EF-04 – different crop rotations of fields on Eutric Fluvisol. EF-FE – forest ecosystem on Eutric Fluvisol. HC-ME – meadow ecosystem on Eutric Fluvisol. HC-UE – urban ecosystem on Eutric Fluvisol. SOC – soil organic carbon. CEC – cation exchange capacity. S – sum of exchangeable cations (Ca2+, Mg2+, K+, and Na+). NT – total nitrogen.

(S) was calculated from the CEC and hydrolytic acidity (van Reeuwijk, 2002). P and K were determined according to the Mehlich 3 extractant (Jackson, 2005). The particle size distribution was determined after dissolution of CaCO3 with 2 mol dm 3 HCl and decomposition of the organic matter with 30% H2O2. After repeated washing, samples were dispersed using Na(PO3)6. Silt, sand and clay fractions were determined according to the pipette method (van Reeuwijk, 2002). Average contents of fractions were: in the Haplic Chernozem – sand 10.85  3.11%; silt 50.92  5.97%; 18.41  2.41% and in the Eutric

Fluvisols – sand 14.89  3.89%; silt 43.31  10.04%; clay 18.07  3.62%. To determine the stability of the soil structure, the soil samples were dried at constant room temperature (25  2 8C) and then divided by the sieve (dry and wet sieve) to size fractions of the net aggregates (Sarkar and Haldar, 2005). The aggregate stability index (Sw) (Henin et al., 1969), the coefficient of vulnerability (Kv) (Valla et al., 2000), the index of crusting based on textural composition and soil organic matter (Ic) (Lal and Shukla, 2004), and the critical soil organic matter content (St) according to Pieri

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Table 3 Statistical evaluation of nitrogen parameters in dry-sieved aggregates. Factors Soils HCa EFb Land use FEc AEd MEe UEf Aggregate size 20–7 mm 7–5 mm 5–3 mm 3–1 mm 1–0.5 mm 0.5–0.25 mm

NTg (g kg

1

NLh

NNLi

L Nj

LINk

NPIl

NMIm

2.3a 2.5b

0.1a 0.1a

2.2a 2.2a

0.05a 0.04a

101.5b 78.0a

1.0b 0.8a

99.4b 63.7a

2.6b 2.3a 2.3a 2.4a

0.1a 0.1a 0.1a 0.1a

2.3b 2.2ab 2.1a 2.2ab

0.05a 0.04a 0.05a 0.04a

– 92.5a 99.7a 77.1a

– 0.9a 0.8a 0.9a

– 83.7a 86.9a 74.0a

2.3a 2.3a 2.3a 2.4a 2.4a 2.5b

0.1a 0.1a 0.1a 0.1a 0.1a 0.1a

2.2ab 2.1a 2.1a 2.1a 2.2ab 2.5b

0.04a 0.05a 0.05a 0.05a 0.04a 0.04a

76.9a 88.8a 75.2a 95.7a 86.8a 115.3b

0.9a 0.9a 0.9a 0.9a 0.9a 0.9a

71.1a 78.5a 73.4a 85.5a 84.1a 96.5a

)

Different letters (a and b) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC – Haplic Chernozem. b EF – Eutric Fluvisol. c FE – forest ecosystem. d AE – agro-ecosystem. e ME – meadow ecosystem. f UE – urban ecosystem. g NT – total nitrogen. h NL – labile nitrogen. i NNL – non-labile nitrogen. j LN – lability of nitrogen. k LIN – index of nitrogen lability. l NPI – nitrogen pool index. m NMI – nitrogen management index.

(1991) were calculated as well. In the structural and water-resistant aggregates, the following were determined: the SOC by wet combustion (Orlov and Grisˇina, 1981); the labile carbon (CL) by KMnO4 oxidation (Loginov et al., 1987); the NT by the Kjeldahl method (Bremner, 1960); and the potentially mineralisable nitrogen (NL) (Standford and Smith, 1978). In the aggregates, the non-labile carbon (CNL), lability of carbon (LC), index of carbon lability (LIC), carbon pool index (CPI), carbon management index (CMI), non-labile nitrogen (NNL), lability of nitrogen (LN), index of nitrogen lability (LIN), nitrogen pool index (NPI), and nitrogen management index (NMI) were also calculated (Blair et al., 1995). Plant residues were analysed according to the method of Beloserski and Proskuryakov (1956). The obtained data were analysed using Statgraphic Plus statistical software. A multifactor ANOVA model was used for individual treatment comparisons at P < 0.05, with separation of the means by Tukey multiple-range test. Correlation analysis was used to determine the relationships between the chemical properties and parameters of soil structure stability. Significant correlation coefficients were tested at P < 0.05 and P < 0.01. 3. Results and discussion 3.1. The structure and properties of aggregates and organic matter in soils of different land uses The soil structure stability differed with the land use. Differences were observed in the contents of soil organic C (SOC), total N and their labile forms in fractions of dry-sieved (Table 3) and water-resistant (Table 4) aggregates. The highest proportions of SOC (24 g kg 1), total N (2.6 g kg 1) and their labile forms (CL 4.0 g kg 1 and NL 0.12 g kg 1) were in the dry-sieved aggregates from the forest ecosystem (Table 3), which is in consistent with the results of Barreto et al. (2009). This supposes that there moreover fungal hyphae, have participated in the aggregate formation, which, according to Tisdall and Oades (1982) are temporary organic-binding agents. The highest contents of

total organic C and total N and their labile forms were found in smaller aggregates, which is in contrast with the results of Six et al. (1999). It is possible that at first stages smaller aggregates were formed in long-time period and then these became the cores of larger aggregates, which formed mainly through short-time by binding agents such as fungal hyphae, which stabilised also microaggregates in macro-aggregates Tisdall and Oades (1982). Larger aggregates were subjected to higher changes, which were confirmed by the values of the carbon management index (CMI). With a dependence on the soil type, a higher, statistically significant content of labile C was found in the dry-sieved aggregates of the Haplic Chernozem (3.36 g kg 1) than that found in the Eutric Fluvisol (2.51 g kg 1). The organic substances in the Eutric Fluvisol were more stabilised by clay and carbonates, which constituted a higher proportion of this soil; this result was consistent with Eustehues et al. (2003), who have attached importance to clay particles in the formation of organo-mineral particles. In the case of water-resistant aggregates (Table 4), a statistically significant effect assigned to the land use was recorded. The highest content of the SOC and its labile fractions in waterresistant aggregates was characterised for the forest ecosystem. The next highest contents of labile C were found in the agroecosystem and in the urban ecosystem, and the lowest was found in the meadow ecosystem. However, the lowest values of CMI were recorded in the meadow ecosystem and the highest in the urban ecosystem. Caravaca et al. (2002) have described the largest stability of aggregates in the root zone, which was a confirmation of the results of Haynes and Beare (1997), who described the action of the root biomass and fungal hyphae. It is true, however, that there are differences between grasses in a natural condition and those in conditions influenced by man. Human activities modify the soil environment and, in some cases, can lead to an indirect influence on the soil aggregate stability. In the urban ecosystem, the soil moisture was more suitable, which indicated that the conditions in the urban ecosystem were better than those in the

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Table 4 Statistical evaluation of carbon parameters in water-resistant aggregates. Factors Soils HCa EFb Land use FEc AEd MEe UEf Aggregate size 3–2 mm 2–1 mm 1–0.5 mm 0.5–0.25 mm <0.25 mm

SOCg

CLh (g kg

20.8a 19.3a

1

LICk

CPIl

CMIm

CNLi

LCj

3.0a 2.7a

17.9a 16.6a

0.5a 0.2a

72.9a 86.5a

0.8a 0.9a

97.0a 81.6a

23.0b 19.4ab 17.4a 20.5ab

3.8b 3.0ab 1.8a 2.8ab

19.2b 16.6ab 15.7a 17.6ab

0.2b 0.2b 0.1a 0.2b

– 91.8a 61.6a 85.7a

– 0.9a 0.8a 0.9a

– 79.2a 50.8a 138.1b

20.4a 20.0a 19.2a 18.4a 22.4b

2.9a 2.9a 2.8a 2.7a 3.0a

17.5a 17.2a 16.4a 15.8a 19.5b

0.2a 0.2a 0.2a 0.2a 0.2a

63.7a 79.4a 70.4a 72.7a 112.3a

0.9a 0.8a 0.8a 0.9a 0.9a

61.2a 77.0a 76.9a 79.8a 151.8b

)

Different letters (a and b) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC – Haplic Chernozem. b EF – Eutric Fluvisol. c FE – forest ecosystem. d AE – agro-ecosystem. e ME – meadow ecosystem. f UE – urban ecosystem. g SOC – soil organic carbon. h CL – labile carbon. i CNL – non-labile carbon. j LC – lability of carbon. k LIC – index of carbon lability. l CPI – carbon pool index. m CMI – carbon management index.

meadow ecosystem, where microbial activity decreased during dry periods. It has been reported that a lower availability of nitrogen (Daufresne and Loreau, 2001) or a higher concentration of soil solution during a dry period can cause a decrease in microbial activity. Higher contents of C and lower changes presume that more C is stabilised in aggregates, where it is protected against oxidation (Balabane and Plante, 2004). Although root exudates contribute to a higher content of SOC, not all of the C becomes a part of aggregates. Root exudates are the most readily available source of C for soil microorganisms, and the bulk of exudate components decompose before incorporation into aggregates. A more significant change in the C was also observed in the agroecosystem than in the urban ecosystem, but this was likely due to the application of farmyard manure (Kalbitz et al., 2003) or the ploughing of crop residues (Morel et al., 1991), which are sources of labile forms of C. In relation to the various sizes of the aggregates, a statistically significant effect of the CMI was recorded (Table 4). In essence, the larger the aggregates were, the larger the changes in the organic substances were; this observation was in agreement with the studies of Jastrow (1996). The highest content of labile C was found in the smallest fraction of aggregates, which is consistent with the findings of Bravo-Garza et al. (2010), who reported that a higher content of intra-aggregate particulate organic matter was found in aggregates that were smaller. However, the C in these aggregates was subjected to the least amount of change. One explanation may be the fact that in this fraction do the labile organic substances became the cores of aggregates, which are surrounded by mineral particles that would physically protect labile organic substances from the decomposition activity of soil organisms. According to Santos et al. (1997), clay flakes form a protective coating against to the next colony of bacteria, and this would inhibit the decomposition of soil organic matter located inside. In situations in which conditions for the physical protection of organic matter do not exist, more stabilised organic substances in relation to the stability of aggregates become more important. In this case, a statistically significant dependence on non-labile

nitrogen and various sizes of aggregate fractions were recorded (Table 3). Non-labile nitrogen is present mainly in humus substances, which play an important role in the formation of the soil structure. Tarchitzky et al. (2000) have suggested that the distribution of humus substances, including humic acids and fulvic acids, in aggregates is a result more of the original coatings of the humic particles than of their action in the bonding of soil particles. In contrast, Piccolo et al. (1997) showed that humic acids can be adsorbed onto clay particles by polyvalent cations, which means that under conditions of higher carbonate contents, they can also be included in aggregates. Agronomically, the most valuable aggregates are waterresistant aggregates of size fractions from 0.5 to 3 mm. The highest content of this aggregate fraction was found in the agroecosystems, with an average of 55.95%. The second highest abundance was found in the forest ecosystem (47.00%), followed by the 33.52% content for the meadow ecosystem; the lowest content (28.74%) was found in the urban ecosystem. When considering the impact of humans with regard to the forest ecosystem, as in arable lands, the content of the most favourable fraction was not reduced but was increased. However, comparing the meadow ecosystem with the forest ecosystem, the content of this fraction was smaller, while it was clearly the lowest in the urban ecosystem. It follows that suitable land use can both prevent the loss of favourable aggregates and also increase their amounts. This is a result of both the chemical composition of plant residue (Martens, 2000) and the application of organic fertilisers, because, according to Debosz et al. (2002), carbohydrates of microbial origin resist degradation better than carbohydrates of plant origin do. This may explain the higher stability of soil aggregates in agroecosystems, because farmyard manure is a source of large amounts of microorganisms. The influence of organic substances of plant origin on the stability of soil aggregates is different as well. Some of these substances, such as polysaccharides, act like temporary components for the production of aggregates (Tisdall and Oades, 1982; Kay, 1998), while others, such as phenols, polyphenols (Martens,

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Table 5 Correlations between organic substance contents in crops and the contents of dry-sieved aggregate fractions. 20–7 (mm) Maltose and hexose Starch Proteins Cellulose Hemicellulose Lignin *

7–5

0.26 0.13 0.49 0.47 0.15 0.25

5–3

0.14 0.10 0.53 0.49 0.15 0.21

3–1

0.37 0.16 0.39 0.13 0.14 0.21

1–0.5

0.24 0.27 0.52 0.50 0.04 0.20

0.5–0.25

0.10 0.23 0.74* 0.37 0.02 0.01

0.33 0.39 0.06 0.37 0.42 0.44

<0.25 0.31 0.40 0.17 0.51 0.55 0.49

P < 0.05.

2000) and lignin (Magill and Aber, 1998), support the formation of more resistant aggregates. The importance of proteins is usually mentioned only marginally in the literature, but in the case of the dry-sieved aggregates, a statistically significant positive correlation (Table 5) between 0.5 and 1 mm fraction and the protein contents was observed. A statistically significant dependence between the individual size fractions of the dry-sieved aggregates (3–5 mm and 0.5– 1 mm) and the C parameters was noted (Table 6). The correlation with the size fraction of 3–5 mm was negative; that is, the higher the content of the SOC (including its labile fraction), the smaller the content of aggregates of this fraction size. Conversely, the 0.5– 1 mm aggregate fraction showed a positive correlation, which indicated that the higher the content of the SOC (including its labile fraction), the higher the content of this aggregate fraction in the soil. Taken together, this indicates that organic substances mainly support the formation of smaller dry-sieved aggregates. In larger aggregates, there is a higher mineralisation of the organic matter (Jastrow, 1996), which results in the disruption of the aggregates. Therefore, the contents of smaller aggregates can increase after the disruption of larger aggregates. Greater changes in the soil organic matter in the larger aggregates were also noted. Addiscott (1995) has reported a positive correlation between the values of the CMI and the formation of soil aggregates. In the present study, a correlation with the formation of soil aggregates was found with the nitrogen pool index (NPI) (Table 6). The stability of the dry-

sieved aggregates can immediately change with an increase in the soil moisture (Attou and Bruand, 1998), which may partly compensate just organic matter. However, it is more objective to assess the quantity of waterresistant aggregates. Soil organic matter plays a very important role in the stability of water-resistant aggregates, as indicated by Canto´n et al. (2009). In the present study, a statistically significant effect of the N parameters was recorded (Table 6). The content of the water-resistant 2–3 mm aggregate fraction showed a negative correlation with the labile N content, the lability of N and the index of N lability, suggesting that the higher the content of labile N, the lower the content of larger size fractions of water-resistant aggregates. When labile fractions of soil organic matter are physically protected (i.e., surrounded by clay particles), aggregation may continue, but if the labile fractions are available for decomposition, the aggregates are disrupted (Bronick and Lal, 2005). In particular, the labile C in ploughed soils is more exposed to microbial activity (La Scala et al., 2008). Overall, the labile forms of C and N contributed to the formation of less-stable aggregates. Parameters that characterised the stability and water resistance of the soil structure (Table 7) were evaluated according to the coefficient of vulnerability (Kv) and the aggregate stability index (Sw), which are commonly used indicators (Valla et al., 2000; Boru˚vka et al., 2002). On the Haplic Chernozem in the forest ecosystem, a nearly optimal value of the Kv was recorded. These values were only

Table 6 Correlations between the parameters of the carbon and nitrogen and fractions of dry-sieved and water-resistant aggregates. Dry-sieved aggregates (mm) 20–7 SOCa C Lb L Cc LICd CPIe CMIf NTg NLh L Ni LINj NPIk NMIl a

0.16 0.00 0.10 0.00 0.03 0.01 0.42 0.14 0.40 0.40 0.01 0.56

7–5

5–3

0.33 0.54 0.64 0.28 0.53 0.51 0.31 0.21 0.38 0.08 0.54 0.59

SOC – soil organic carbon. CL – labile carbon. c LC – lability of carbon. d LIC – index of carbon lability. e CPI – carbon pool index. f CMI – carbon management index. g NT – total nitrogen. h NL – labile nitrogen. i LN – lability of nitrogen. j LIN – index of nitrogen lability. k NPI – nitrogen pool index. l NMI – nitrogen management index. * P < 0.05. ** P < 0.01. b

0.73* 0.76* 0.75* 0.46 0.76* 0.75* 0.34 0.28 0.10 0.47 0.76* 0.13

Water-resistant aggregates (mm) 3–1 0.18 0.02 0.07 0.12 0.01 0.05 0.54 0.02 0.33 0.27 0.01 0.45

1–0.5 0.58 0.74* 0.81* 0.50 0.71* 0.73* 0.01 0.30 0.31 0.24 0.72* 0.51

0.5–0.25 0.59 0.39 0.26 0.14 0.45 0.40 0.61 0.54 0.22 0.07 0.41 0.20

<0.25 0.10 0.27 0.35 0.04 0.27 0.24 0.25 0.36 0.53 0.34 0.32 0.19

3–2 0.32 0.35 0.35 0.07 0.40 0.31 0.06 0.79* 0.86** 0.71* 0.42 0.15

2–1 0.11 0.02 0.02 0.04 0.03 0.03 0.25 0.65 0.56 0.70 0.06 0.17

1–0.5 0.24 0.31 0.34 0.13 0.29 0.30 0.04 0.70 0.73* 0.62 0.34 0.08

0.5–0.25 0.28 0.26 0.22 0.36 0.38 0.21 0.20 0.35 0.45 0.2 0.35 0.54

<0.25 0.02 0.08 0.10 0.52 0.06 0.12 0.31 0.48 0.66 0.74* 0.04 0.06

E. Tobiasˇova´ / Soil & Tillage Research 114 (2011) 183–192 Table 7 Parameters of the soil structure of Haplic Chernozems and Eutric Fluvisols with different land uses. Factors Land use Agro-ecosystem Forest ecosystem Meadow ecosystem Urban ecosystem Soils Haplic Chernozems Eutric Fluvisols

Kva

Swb

Icc

Std (%)

4.32b 1.08a 1.67a 1.11a

0.98b 1.48a 1.19b 1.20b

1.15b 0.79a 1.03b 1.10b

4.16a 7.44c 5.51b 4.77a

2.28a 1.81a

1.05a 1.39a

1.10a 0.94a

4.79a 6.15b

Different letters (a, b, and c) between the factors show statistically significant differences (P < 0.05) – Tukey test. a Kv – coefficient of vulnerability. b Sw – aggregate stability index. c Ic – index of crusting. d St – critical soil organic matter content.

slightly higher in the urban ecosystem and were substantially higher in the meadow ecosystem. Barreto et al. (2009) have determined that the best soil structure is found under natural vegetation. This was found to be the case for the forest ecosystem in the present study, but according to the Kv, the soil structure in the meadow ecosystem was worse than in both the forest and urban ecosystems. According to Angers and Caron (1998), the penetration of roots into the soil can contribute to the fragmentation of soil aggregates, which may provide a reason for the inferior soil structure in the meadow ecosystem than in the forest ecosystem. A more extensive root system is also the reason for longer dry periods (as more water may be removed from the soil), which cause the disruption of aggregates, and this may explain the poorer soil structure in the meadow ecosystem than in the urban ecosystem with better moisture conditions. A positive correlation was also observed between the Kv and the lability of N (Table 8), which is in consistent with the theory of Golchin et al. (1994), which states that the C from proteins and carbohydrates is utilised at a faster rate than more recalcitrant compounds such as polyphenols. The Sw also indicated that the most favourable conditions were found in the forest ecosystems of both soil types (Table 7). In all of the ecosystems, more favourable values for Sw were found in the Eutric Fluvisol. There were differences in the carbonate content between the soils, and a greater impact of carbonates on the soil aggregation was mainly observed in the comparatively carbonaterich Eutric Fluvisol. Carbonates have been shown to increase the

Table 8 Correlations between the parameters of carbon and nitrogen and the parameters of soil structure stability. Kva SOCe CLf LCg NTh NLi LNj a

0.49 0.09 0.41 0.60 0.11 0.83*

Swb 0.51 0.09 0.06 0.53 0.15 0.64

Kv – coefficient of vulnerability. Sw – aggregate stability index. c Ic – index of crusting. d St – critical soil organic matter content. e SOC – total organic carbon. f CL – labile carbon. g LC – lability of carbon. h NT – total nitrogen. i NL – labile nitrogen. j LN – lability of nitrogen. * P < 0.05. ** P < 0.01. b

Icc 0.63 0.38 0.28 0.43 0.00 0.54

Std 0.85** 0.10 0.07 0.75* 0.29 0.50

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stability of aggregates in arid areas (Amezketa, 1999), but in this study, the carbonates may have exerted an influence by increasing the pH, which may contribute to an increase in the microbial activity and, thus, indirectly to an increase in the soil organic matter (Haynes and Naidu, 1998). A very important parameter for the assessment of the soil structure is the index of crusting (Ic). Clearly, the lowest Ic (Table 7) for both soil types was found in the forest ecosystem. For the other ecosystems, differences were also recorded for the individual soil types. It has been shown that the Ic is mainly influenced by the textural composition and the content of soil organic matter (Lal and Shukla, 2004). For the Ic, the ranking for the Eutric Fluvisol was as follows: the meadow and urban ecosystems were followed by the forest ecosystem, and the highest values were in the agroecosystem. In the case of this soil type, an influence by the soil texture was clearly manifested. On the Haplic Chernozem, the effect of the soil organic matter was more marked. The highest content of organic matter was found in the forest ecosystem, where the Ic was also the lowest, followed by the meadow ecosystem, with the second highest content of organic matter. The Ic and content of organic matter did not correspond in the cases of the urban ecosystem and agro-ecosystem. A lower C content was recorded in the agro-ecosystem, but the Ic was lower as well. This may be the result of the aeration caused by cultivation (Sˇimnasky´ et al., 2008). In an urban ecosystem, the content of the clay fraction was not the highest, but the content of the sand was the lowest, which also contributed to a greater susceptibility for soil compaction. In the case of the critical soil organic matter (St), as a stable soil structure can be assess the structure of the forest ecosystem (Table 7). On the Eutric Fluvisol (Table 8), the St correlated with the SOC and total N, but there was no correlation with the labile forms of C and N. 3.2. The effect of crop rotation on the structure of aggregates and the properties of the organic matter Statistically significant differences in the soil structure were observed in the case of individual fields in the agro-ecosystem (Tables 9–11) because the aggregate dynamics also depend on crop rotation (Jarecki and Lal, 2003), which affects the soil through the chemical composition of crop residues (Martens, 2000). In the case of the Haplic Chernozem, the influence of individual crops was clearly demonstrated by their chemical composition. Table 9 Statistical evaluation of the carbon parameters of the individual fields on Haplic Chernozems and Eutric Fluvisols in dry-sieved aggregates. Fields

SOCc (g kg

HC-01a HC-02 HC-03 HC-04 EF-01b EF-02 EF-03 EF-04

22.5b 20.3a 20.5a 22.7b 18.8bc 20.1c 14.5a 17.4b

1

)

CLd

CNLe

L Cf

LICg

CPIh

CMIi

5.0b 3.8a 3.7a 4.1a 1.9b 1.9b 1.5a 1.8ab

17.5ab 16.5a 16.8a 18.4b 16.8b 18.2c 13.0a 15.6b

0.3b 0.2a 0.2a 0.2a 0.1a 0.1a 0.1a 0.1a

114.0a 93.9a 88.6a 90.4a 74.2a 66.3a 75.1a 74.5a

0.9a 0.8a 0.8a 0.9a 0.8bc 0.9c 0.6a 0.7b

104.1b 77.5a 73.7a 83.3a 60.1a 57.5a 46.7a 56.0a

Different letters (a, b, and c) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC-01–HC-04 – different crop rotations of fields of Haplic Chernozem. b EF-01–EF-04 – different crop rotations of fields of Eutric Fluvisol. c SOC – soil organic carbon. d CL – labile carbon. e CNL – non-labile carbon. f LC – lability of carbon. g LIC – index of carbon lability. h CPI – carbon pool index. i CMI – carbon management index.

E. Tobiasˇova´ / Soil & Tillage Research 114 (2011) 183–192

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Table 10 Statistical evaluation of the nitrogen parameters of the individual fields on Haplic Chernozems and Eutric Fluvisols in dry-sieved aggregates. NTc (g kg

Fields a

HC-01 HC-02 HC-03 HC-04 EF-01b EF-02 EF-03 EF-04

1

)

2.5a 2.3a 2.3a 2.3a 2.6b 2.6b 2.0a 2.0a

NLd

NNLe

L Nf

LINg

NPIh

NMIi

0.1a 0.1a 0.1a 0.1a 0.1a 0.1a 0.1a 0.1a

2.4a 2.2a 2.2a 2.2a 2.4b 2.5b 1.9a 1.9a

0.04a 0.04a 0.04a 0.04a 0.05b 0.03a 0.05b 0.06c

91.0a 103.9a 100.3a 105.0a 89.4ab 66.1a 100.5b 122.6c

1.0a 1.0a 1.0a 1.0a 0.9b 0.9b 0.7a 0.7a

94.5a 98.9a 95.0a 101.8a 79.4bc 58.9a 66.1b 84.9c

Different letters (a, b, and c) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC-01–HC-04 – different crop rotations of fields of Haplic Chernozem. b EF-01–EF-04 – different crop rotations of fields of Eutric Fluvisol. c NT – total nitrogen. d NL – labile nitrogen. e NNL – non-labile nitrogen. f LN – lability of nitrogen. g LIN – index of nitrogen lability. h NPI – nitrogen pool index. i NMI – nitrogen management index.

Table 12 Correlations between the soil organic carbon, labile carbon and carbon pool index in water-resistant aggregates and the organic substance contents in crops with dependence on decomposability and silt.

HCa SOCc CLd CPIe EFb SOC CL CPI a b c d e f g h *

Table 11 Statistical evaluation of the carbon parameters of the individual fields on Haplic Chernozems and Eutric Fluvisols in water-resistant aggregates. Fields

SOCc (g kg

HC-01a HC-02 HC-03 HC-04 EF-01b EF-02 EF-03 EF-04

21.7ab 21.0ab 20.7a 23.4b 20.0c 21.3c 13.0a 16.3b

1

)

CLd

CNLe

LCf

LICg

CPIh

CMIi

4.2a 4.1a 3.8a 4.4a 1.7b 2.3c 1.5a 1.9b

16.7a 17.2ab 16.9ab 18.9b 14.4b 19.0c 11.6a 14.4b

0.3a 0.2a 0.2a 0.2a 0.1a 0.1a 0.1a 0.1a

119.1a 109.3a 106.7a 129.6a 66.8a 68.3a 71.3a 75.6a

0.9a 0.9a 0.9a 1.0a 0.8a 1.0b 0.6a 0.8a

99.6a 94.4a 88.8a 125.2a 52.0a 70.1a 44.8a 58.2a

Different letters (a, b, and c) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC-01–HC-04 – different crop rotations of fields of Haplic Chernozem. b EF-01–EF-04 – different crop rotations of fields of Eutric Fluvisol. c SOC – soil organic carbon. d CL – labile carbon. e CNL – non-labile carbon. f LC – lability of carbon. g LIC – index of carbon lability. h CPI – carbon pool index. i CMI – carbon management index.

Lignin is resistant to decomposition, and it was observed that the higher the content of lignin for an entire crop rotation, the lower the SOC content was in the water-resistant aggregates (Table 12). This result is in contrast with the study of Caesar-TonThat (2002), who described the impact of lignin on the formation of soil aggregates as positive due to mucilages and similar substances, which are a by-product of lignin decomposition and contribute to soil aggregation. The labile C content in the water-resistant aggregates revealed a negative correlation with the moderately decomposable substances (cellulose and hemicellulose); in this case, the crucial factor was not an average of the crop rotation, but rather the crop residue of the previous crop (Table 12). When the content of these polysaccharides was high, the content of the C labile fraction in the aggregates was low. However, Soon and Arshad (2002) recorded that, in the case of higher contents of easily decomposable organic substances in the chemical composition of crop residues, the C content was shown to be lower. In the Eutric Fluvisol, the particle size distribution clearly showed a greater effect than did the soil organic matter. When the content of silt in the texture composition was high, the CPI values were also high (Table 12). This is a greater size fraction than that described by Bosatta and A˚gren (1997) or Jastrow (1996), who have

Average contents for crop rotation of field

Contents in previous crops

C1f

C1

C2g

C3h

C2

Silt

C3

0.45 0.58 –

0.90 0.76 –

0.97* 0.76 –

0.81 0.11 –

0.58 0.98* –

0.75 0.81 –

0.94 0.51 0.89

0.44 0.91 –

0.05 0.55 –

0.08 0.38 –

0.78 0.30 –

0.56 0.50 –

0.05 0.02 –

0.91 0.91 0.99*

HC – Haplic Chernozems. EF – Eutric Fluvisols. SOC – total organic carbon. CL – labile carbon. CPI – carbon pool index. C1 – easy decomposable substances. C2 – medium decomposable substances. C3 – hardly decomposable substances. P < 0.05.

reported on the positive influence of the clay fraction on the organic matter in the formation of stabile macro-aggregates. The Kv in the fields exhibited average fluctuations within a relatively wide range of values, from 2.34 for field HC-04 to 6.50 for HC-01 (Table 13). For field HC-04, winter wheat was grown during the two years prior to the study, whereas spring barley was grown in field HC-02 during the previous year; however, the highest Kv values were recorded in fields HC-03 and HC-01, where the previous crop was maize. On the Eutric Fluvisol, the soil texture had more impact than did the crops. It was observed that Kv approached a value of 1.0 as the percentage of silt and clay increased. For all of the fields except for the EF-02 field, where the previous crop was maize, the previous crop was winter wheat. In the case of the Haplic Chernozem, the values for Kv were the worst where maize was the previous crop, while in the Eutric Fluvisol, the most favourable values for Kv were in the maize fields. Thus, a more significant factor affecting the Kv was the soil texture rather than the crop itself. According to Czarnes et al. (2000), differences in the stability of the soil structure can be caused by alternating wet-dry cycles in the root zone, which, in some cases, tends to increase the stability of some aggregates and decrease the stability of others, with a dependence on the proportion of the clay fraction. In the Table 13 Parameters of the soil structure of Haplic Chernozems and Eutric Fluvisols in different fields. Factor

Kvc

Swd

Ice

Stf (%)

Crop rotation HC-01a HC-02 HC-03 HC-04 EF-01b EF-02 EF-03 EF-04

6.50c 4.15b 4.80b 2.34a 4.25b 2.25a 2.99a 6.18c

0.86a 1.09a 0.97a 0.99a 0.92a 1.08a 1.08a 0.91a

4.06a 5.09a 4.76a 4.47a 3.03a 4.22a 3.92a 3.72a

1.03a 1.00a 0.97a 0.83a 1.46b 1.73b 1.15a 1.05a

Different letters (a, b, and c) between the factors show statistically significant differences (P < 0.05) – Tukey test. a HC-01–HC-04 – different crop rotations of fields on Haplic Chernozem. b EF-01–EF-04 – different crop rotations of fields on Eutric Fluvisol. c Kv – coefficient of vulnerability. d Sw – aggregate stability index. e Ic – index of crusting. f St – critical soil organic matter content.

E. Tobiasˇova´ / Soil & Tillage Research 114 (2011) 183–192 Table 14 Correlations between the contents of organic substances in crops and the parameters of soil structure stability. Kva Maltose and hexose Starch Proteins Cellulose Hemicellulose Lignin a b c d *

0.07 0.16 0.063 0.71* 0.11 0.21

S wb 0.21 0.32 0.41 0.52 0.41 0.40

Icc 0.55 0.20 0.22 0.57 0.50 0.56

S td 0.32 0.48 0.55 0.17 0.42 0.40

Kv – coefficient of vulnerability. Sw – aggregate stability index. Ic – index of crusting. St – critical soil organic matter content. P < 0.05.

case of the Eutric Fluvisol, it can be supported by the plant roots and also the clay and silt fractions. Singer et al. (1992) have described the decrease of aggregate stability by the clay fraction: in conditions of higher moisture, clay particles absorb water, and they separate from other particles. These conditions are characteristic for the Eutric Fluvisol during some periods of the year. Therefore, the different effects of crops may be recorded with a dependence on the soil type, which had significantly different textural compositions. In this case, this explains the more significant influence of the soil texture, compared with the crop, on the coefficient of vulnerability. A statistically significant relationship between the Kv and cellulose content in the chemical composition of the crop residue for an entire crop rotation was also observed (Table 14), which is consistent with the results of Martins et al. (2009), who have described the influence of crops on the stability of aggregates through the hydrolysable polysaccharides, but not the cellulose. In contrast, there are many studies that have demonstrated the importance of polysaccharides in organic-binding agents, which are important for the stabilisation of macro-aggregates (Spaccini et al., 2004; Liu et al., 2005; Mirjam et al., 2008), but in all of these cases, there were easily hydrolysable, water- or acid-extractable polysaccharides present. 4. Conclusion In all of the ecosystems, more favourable soil structure was in the Eutric Fluvisol. The soil structure of the forest ecosystem was evaluated as the best of all of the forms of land use examined in this study. The agro-ecosystem was characterised by a higher portion of the most valuable (agronomically) water-resistant aggregate size fraction, 0.5–3 mm. Higher contents for the SOC and CL were associated with a smaller content of the 3–5 mm dry-sieved aggregate size fraction and greater contents of dry-sieved aggregates of the 0.5–1 mm size fraction. The values of the CMI showed that the greater changes in the organic matter were correlated with larger, water-resistant aggregates. The soil structure was better at a higher content of cellulose in the plant residue. The higher contents of cellulose and hemicellulose in plant residues of a previous crop were reflected in a smaller CL content in the water-resistant aggregates. A higher content of lignin in the plant residue was associated with a smaller SOC content in the water-resistant aggregates, while a high content of proteins in the plant residue supported a greater content of the 0.5–1 mm dry-sieved aggregate size fraction. Acknowledgements This project was supported by the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak

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