Response of soil microbial biomass and activity to agricultural de-intensification over a 10 year period

Soil Biology & Biochemistry 33 (2001) 2105±2114

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Response of soil microbial biomass and activity to agricultural de-intensi®cation over a 10 year period C. Emmerling a,*, T. Udelhoven b, D. SchroÈder a a

b

Department of Soil Science, University of Trier, UniversitaÈtsring 15, 54286 Trier, Germany Department of Remote Sensing, University of Trier, UniversitaÈtsring 15, 54286 Trier, Germany Received 4 February 2000; received in revised form 9 July 2001; accepted 8 August 2001

Abstract Soil microbial properties, such as microbial biomass and microbial activity, are suitable indicators to predict soil biological status as a part of soil fertility after transition from high-input agricultural systems to low-input systems. These criteria were applied to evaluate how agricultural de-intensi®cation as practiced by the integrated farming system (IFS) of Germany differ from the conventional agricultural system (CFS) over long-term investigation. The study was multi-factorial, covering agricultural management, spatial as well as temporal variability. Therefore, the research included nine different locations with a wide range of soil types, soil textures of the top horizons, parent materials, climatic conditions, along with the individual impact of farmers over a ten year period. In sum, the mean pH values, the mean amounts of microbial biomass (estimated from maximal initial responses) and soil organic matter, mean Cmic-to-Corg ratio, and mean dehydrogenase activity of the nine locations were almost identical in both systems. The amounts of soil organic matter, microbial biomass and Cmic-to-Corg ratio increased 10±15% in the integrated management treatment compared with the conventional management system starting from the ®fth year of investigation. Conversely, during the ®rst 4 years of the investigation the examined parameters were slightly increased in the conventional management system. The differences in dehydrogenase activity between both systems changed from year to year. No differences between both systems were found for the pH values of the investigated soils. Beyond that, the factor soil texture of the top horizon (expressed as the clay content) was highly signi®cant for the amounts of the investigated parameters. During the 10 year investigation period, differences between both management systems in particular years were related to the cultivation of intermediate crops and conservation tillage practices. q 2001 Elsevier Science Ltd. All rights reserved. Keywords: Agricultural de-intensi®cation; Microbial biomass; Microbial activity; Spatial variability; Temporal development; Sustainable agriculture

1. Introduction Sustainable agriculture is one of the main scienti®c topics in soil ecological investigations world-wide. In addition to organic farming, the conceptual frame of integrated agricultural management, including integrated pest management (IPM), is one common strategy for sustainable agriculture. In Germany, the integrated farming system (IFS) is regulated by several legal guidelines. N-fertilization is limited by speci®c amounts of N-fertilizer depending on the crop type and is based on N-analysis of soils in spring. Nmin-balances are prescribed. Crop protection in the IFS is based on IPM grounded in speci®c environmental protection criteria. Beyond this, IFS is characterized by conservation tillage practices and the consideration of intermediate crops * Corresponding author. Tel.: 149-651-201-2238; fax: 149-651-2013809. E-mail address: [email protected] (C. Emmerling).

within the crop rotation schedule. The basic aim of agricultural de-intensi®cation is the replacement of external regulations through chemical (mineral N fertilizers, pesticides) and mechanical inputs stimulating biological processes in the soil and the functions that are governed by soil organisms. In the last two decades, much has been published indicating the signi®cance of soil microbial properties, such as soil microbial biomass, microbial activities and enzyme activities, for agricultural ecosystem function and overall soil fertility in different intensive agricultural management systems (Powlson et al., 1987; Anderson and Domsch, 1990; Brussaard, 1994; Swift, 1994; Lundquist et al., 1999; Wardle et al., 1999). However, the relationship between agricultural extensi®cation and the biodiversity of soil organisms on one hand and the maintenance of biological functions on the other hand is still not clear (Pankhurst et al., 1996; Giller et al., 1997). While cultivation-induced changes in total organic matter requires

0038-0717/01/$ - see front matter q 2001 Elsevier Science Ltd. All rights reserved. PII: S 0038-071 7(01)00143-2

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Table 1 Experimental design of the investigation `Integrated farming system Rhineland-Palatinate (1986±1995)' with indication of the different locations, landscapes, soil types and parent materials, and soil texture of the investigated top horizons Factors

Location and landscape

Farming system Conventional

Integrated

Further characteristics Location

Landscape

Soil type (parent material)

Soil texture (top horizon)

Holzweiler Wittlich Sobernheim Emmelshausen Biebrich Rommersheim Dudenhofen Speyer Steinwenden

Eifel Eifel-Moselle East-HunsruÈck East-HunsruÈck Westerwald-Taunus Rhinehesse East-Palatinate East-Palatinate West-Palatinate

Haplic stagnogley (windblown silt over tertiary clay) Luvi-cambisol (iron-rich micaceous sandstone) Cambisol (iron-rich micaceous sandstone) Haplic stagnogley (windblown silt over tertiary clay) Haplic stagnogley (windblown silt) Humic cambisol (windblown silt over tertiary limestone) Luvisol (sandy river sediments) Cambisol (windblown and river sediments) Cambisol (windblown silt over iron-rich sandstone)

Lu Ls3 Ls3 Lu Lt2 Lt3 Sl2 Sl3 Lu

Rotation schedule Cultivation system Fertilization Crop protection

Con®ned crop rotation, intermediate fruits are not system-inherent Ploughing in almost every year Intensive, especially N Intensive, without attention to environmental-protection criteria

Rotation schedule Cultivation system Fertilization Crop protection

Versatile crop rotation, cultivation of intermediate crops Conservation tillage is system inherent After soil analysis, especially N, Nmin balance is prescribed Integrated pest management (IPM) on the basis of environmental-protection criteria

lengthy periods, soil microbial biomass and activity and the relation of Cmic to total soil organic carbon (Cmic/Corg ratio) have been found to be more sensitive indicators of soil agricultural practices with short-term reactions. Changes are induced by tillage practices (e.g. Lynch and Panting, 1980; Hendrix et al., 1986; Doran, 1987), input of fertilizers (Fauci and Dick, 1994; Giller and Cadisch, 1995), organic residues (e.g. Friedel et al., 1996), pesticides (e.g. Cervelli et al., 1978) and crop rotation (e.g. Elliott et al., 1987; Anderson and Domsch, 1989a). Evidence shows a close relationship of soil microbial properties to various edaphic factors, e.g. pH level, soil organic matter and texture (e.g. Anderson and Domsch, 1993; Stotzky, 1997), and modifying factors such as climate (Insam et al., 1989), soil moisture and soil temperature regimes (Sarathchandra et al., 1989; Wardle, 1992). Hence, microbial properties are suitable predictors of soil biological status as a part of soil fertility after transition from high-input agricultural systems to lowinput systems. As Wardle et al. (1999) pointed out, longterm investigations are necessary for microbial studies in order to discern the effects of different intensive agricultural managements on soil microbial properties (Powlson and Johnston, 1994). Therefore, a 10 year comparative study of adjacent conventional and integrated managed soils at nine different locations in Rhineland-Palatinate, Germany is presented. The study focused on soil microbial biomass and microbial activity. Consequently, the design was multi-factorial, covering soil management system and location (including soil type, soil texture, climatic condition). The objective was to investigate the long-term in¯uence of agricultural

de-intensi®cation on soil microbial properties. Additionally, the number of different locations was increased in order to obtain thorough results, taking into account also the factor of climate. Moreover, the study includes the in¯uence of individual farming practice behaviour. 2. Material and methods 2.1. Research design During a 10 year period from 1986 to 1995, nine locations in Rhineland-Palatinate, Germany were examined. Each location consisted of adjoining conventional and integrated plots managed by only one farmer. The study was multifactorial and covered soil management systems (conventional versus integrated; inclusive cultivation, tillage and plant protection procedures), location (including soil type, soil texture, climatic condition) and sampling depth (0-15 and 15-30 cm). The test range was designed as a strip system, with ®eld strips of 0.5 ha each (Table 1). 2.2. Locations and soils The investigation represented a wide scale of soil types, soil textures of the top horizons and parent materials of Rhineland-Palatinate, Germany. The examined types include cambisols, luvisols, haplic stagnosols, as well as transition types of the soil types mentioned above (Table 1). The soil texture of the top horizon varied from loamy sand, sandy loam and silt loam to silty clay loam. The clay content of the top horizon varied in a range of 8±38%. The

C. Emmerling et al. / Soil Biology & Biochemistry 33 (2001) 2105±2114

locations are part of seven natural landscapes of RhinelandPalatinate (Table 1). Apart from management systems, soil types and parent materials, the different climatic conditions of the locations are taken into consideration for a proper description of the soil microbiological properties. For example, the location Rommersheim represents a very dry region in Rhineland-Palatinate with a mean annual precipitation of 500 mm year 21. Hence, the investigated humic cambisols showed a relative high organic matter content of approximately 1.4±1.5% Corg. 2.3. Management systems The 3±5 year rotation schedule of the integrated managed plots comprised intermediate crops like legumes and grain legumes, particularly mustard, phacelia and beans. In some years, green manure (Emmelshausen), or `Landsberger' mixture (Steinwenden), or white clover (Speyer) were cultivated. The conventionally managed plots were cultivated mostly without intermediate crops. At the locations Holzweiler, Rommersheim and Speyer, crop rotation was dominated by winter grain (winter wheat, winter rye, winter barley) and sugar beets. The rotation schedules in Dudenhofen, Wittlich and Steinwenden included winter rape or maize next to winter grain. The remaining locations stood out due to the dominating summer grain and the more diverse crop rotations. The main crops were the same in both management systems. At several locations (Holzweiler, Biebrich), soil tillage was less intensive in the integrated managed plots compared to the conventionally managed ones. For example, a topsoil cultivator or for several years a stubble cultivator (Speyer, Sobernheim), a chisel plough (Sobernheim, Wittlich) or a compact cultivator (Steinwenden) for conservation tillage were used. The conventional farming system was characterized by an intensive input of mineral fertilizers, especially N, whereas in the integrated farming system N-fertilization was restricted for various crops and was based on a Nanalysis of soils in spring. In the conventional farming system, crop protection is intensive without any attention to environmental protection criteria. In contrast, crop protection in the integrated farming system is based on integrated pest management (IPM) grounded in speci®c environmental protection criteria. 2.4. Methods of soil analysis For soil microbiological analysis, soil samples were taken from each plot from 0±15 and 15±30 cm depth each year in spring at the beginning of the vegetation period. After thoroughly sieving ,2 mm, soil samples were pre-incubated at 168C for 14 days. Soil moisture was adjusted to 40±50% of the maximum water holding capacity (WHC). The WHCs of the soils were measured as stored water by percolation tests. During the analytical period, the soil samples were stored at 48C. The pH was determined potentiometrically in a 0.01 M

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CaCl2 solution with a glass electrode. The soil organic matter content (Corg) was measured as loss of ignition at 11008C in carbonate-free soil samples with a CHN-analyser, Fa. Haereus (until 1990) and a Leco-RC 412 analyser. The amount of microbial biomass was calculated by the substrate-induced respiration method as detailed by Anderson and Domsch (1978) using 50 g (d.w.) subsamples. The maximal initial response (CO2) of the soil samples after the addition of an optimal concentration of glucose were analysed with a WoÈsthoff Ultragas U3SB-analyser (until 1991) and an infrared-gas analyser (Heinemeyer et al. 1989). The dehydrogenase activity was determined using 5 g subsamples on a dry weight basis. 2.5. Data analysis The effect of the management system, soil texture, and sampling depth of the top horizons on the soil microbial parameters was investigated using a multivariate analysis of variance. Since no within-location replication in each ®eld strip was considered, the sampling strategy follows a pseudo-replicated design. The General Linear Model (GLM) for repeated measurements was used for that purpose. In a `repeated measures' design each participant provide a response at different times. The time aspect, the within-subject factor, was de®ned by 10 categories describing the 10 year sampling period. Orthogonal polynomial transformations were used as contrasts to decompose the within-subject factor in nine new variables, one variable for each degree of freedom of the within-subject variable. The polynomial transformations represent trend components of increasing order of the time aspect. An additional variable is created for the average of the within-subject factor. The variance analysis is performed on the transformed variable rather than on the original within-subject variable. The between-subject factors dividing the data set into sub-groups were the soil texture of the top horizons (three categories), the management system (two categories), and the sampling depth (two categories). The dependent soil parameters in the design were pH, Corg, Cmic, Cmic/Corg and dehydrogenase activity. Preconditions for multivariate variance analysis are independent measurements between the different subgroups. This precondition is normally violated in designs with replicated measurements. Nevertheless, the respective F-tests result in correct decisions if the variances and the correlation structure of the treatment levels are homogeneous (Bortz, 1999). Violations of this precondition results in progressive decisions of the respective F-tests. The consequence is that the H1-hypothesis is more often accepted than expected on the nominal a -level. This means that the univariate F-tests examining the signi®cance of the within-factor would overestimate the strength of the relationships. Mauchly's Test of Sphericity tests the H0-hypothesis that

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Table 2 Mauchly's Test of Sphericity. Huynh±Feldt's e was used to adjust the degrees of freedom in the ANOVA analysis Within subject effect

Variable

Mauchly W

Approx. chi-square

Df

Sig.

Epsilon (e ) Huynh±Feldt

Time

pH Corg Cmic Dehydrogenase Cmic/Corg

0.008 0.018 0.005 0.003 0.022

80.675 67.688 87.414 95.886 63.802

44 44 44 44 44

0.001 0.016 0.000 0.000 0.034

0.945 1.000 0.974 0.775 1.000

the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. Unsystematic variations of heterogeneous correlations are compensated in practice by an adjustment of the degree of freedom in the univariate F-tests. This reduction is achieved by weighting the normal degree of freedom by a factor of e (e , 1), this means the enumerator and denumerator degrees of freedom in the respective F-tests are decreased. The more the circularity assumption is violated, the less is e . The Huynh±Feldt epsilon (Huynh and Feldt, 1976), one of the more commonly used correction formulas, was applied. A multiple comparison between three categories of the soil texture for the ®nal year, 1995, was performed by an ANOVA and a post-hoc Bonferroni test. A Spearman correlation analysis was used to test the relationship between the investigated data. For statistical analysis, SPSS (10.0) software package was used.

3. Results 3.1. General survey The sphericity assumption (P , 0.05) of the variance± covariance matrices of all cells in the factor design matrix was not met for any dependent variable (Table 2), so the Huynh±Feldt e correction to the degree of freedoms was applied. Averaging the nine locations, the mean pH value of the top soils was 6.52 and the mean Corg content was 1.09%. The mean amount of soil microbial biomass (Cmic) was 442.5 mg C g soil 21 and the mean Cmic/-to-Corg ratio of the investigated soils was 4.05%. The mean amount of dehydrogenase activity was 116.3 mg TPF g soil 21. The univariate ANOVA results of the time within effect and the interactions with the between effects are shown in Table 3. The main effect of time of measurement was

Table 3 Univariate ANOVA results using the time within-subject effect. Only simple interactions between time and the between-subject effects are listed. All higher order interactions (time £ sampling depth £ soil texture, time £ sampling depth £ management system, time £ soil texture £ management system, time £ sampling depth £ soil texture £ management system) were not signi®cant for any soil parameter. The sums of squares (SS) and df for the univariate test of the time within-subject effect were found by adding the sums of squares and df for the single degree of freedom test of the time contrasts (SStime ˆ SSlinear 1 SSquadratic 1 SScubic 1 ´´´ 1 SSorder9) Source

Variable

Typ III sum of squares

Df

Mean squares

F

Sig.

Time

pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg

3.621 2.267 418,248.842 75,810.502 90.086 0.398 0.164 50,326.983 5845.082 7.536 4.850 0.366 401,940.384 65,800.833 25.115 0.294 7.001 £ 10 22 92,962.577 4825.206 7.996

8.502 9.000 8.763 6.977 9.000 8.502 9.000 8.763 6.977 9.000 17.005 18.000 17.526 13.954 18.000 8.502 9.000 8.763 6.977 9.000

0.426 0.252 47,730.106 10,865.599 10.010 4.676 £ 10 22 1.820 £ 10 22 5743.261 837.751 0.837 0.285 2.033 £ 10 22 22,934.501 4715.478 1.395 3.459 £ 10 22 7.779 £ 10 23 10,608.789 691.576 0.888

6.123 21.429 3.645 9.608 9.461 0.672 1.549 0.439 0.741 0.791 4.101 1.730 1.752 4.170 1.319 0.497 0.662 0.810 0.612 0.840

0.000 0.000 0.000 0.000 0.000 0.725 0.134 0.909 0.637 0.625 0.000 0.038 0.036 0.000 0.180 0.866 0.743 0.604 0.745 0.580

Time £ sampling depth

Time £ soil texture

Time £ management system

C. Emmerling et al. / Soil Biology & Biochemistry 33 (2001) 2105±2114

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Table 4 Test of the between-subject effects, based on the averaged time contrasts Source

Variable

Typ III sum of squares

Df

Mean squares

F

Sig.

Sampling depth

pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg pH Corg Cmic Dehydrogenase Cmic/Corg pH

0.623 1.734 £ 10 22 86,515.445 12,889.271 3.908 103.689 5.975 6,523,860.209 440,763.480 292.690 8.719 £ 10 23 9.895 £ 10 22 39,867.092 865.511 0.392 0.571 8.329 £ 10 22 262,782.709 16,703.030 13.013 7.206 £ 10 25

1 1 1 1 1 2 2 2 2 2 1 1 1 1 1 2 2 2 2 2 1

0.623 1.734 £ 10 22 86,515.445 12,889.271 3.908 51.845 2.987 3,261,930.105 220,381.740 146.345 8.719 £ 10 23 9.895 £ 10 22 39,867.092 865.511 0.392 0.285 4.165 £ 10 22 131,391.355 8351.515 6.506 7.206 £ 10 25

0.391 0.031 0.469 0.592 0.498 32.504 5.290 17.697 10.126 18.666 0.005 0.175 0.216 0.040 0.050 0.179 0.074 0.713 0.384 0.830 0.000

0.539 0.863 0.501 0.451 0.488 0.000 0.014 0.000 0.001 0.000 0.942 0.680 0.647 0.844 0.825 0.838 0.929 0.502 0.686 0.451 0.995

Corg Cmic Dehydrogenase Cmic/Corg pH

4.250 £ 10 22 64,034.072 6374.861 1.868 0.198

1 1 1 1 2

4.250 £ 10 22 64,034.072 6374.861 1.868 9.882 £ 10 22

0.075 0.347 0.293 0.238 0.062

0.787 0.562 0.594 0.631 0.940

Corg Cmic Dehydrogenase Cmic/Corg pH

1.269 £ 10 22 4823.384 879.458 0.456 2.664 £ 10 22

2 2 2 2 2

6.346 £ 10 23 2411.692 439.729 0.228 1.332 £ 10 22

0.011 0.013 0.020 0.029 0.008

0.989 0.987 0.980 0.971 0.992

Corg Cmic Dehydrogenase Cmic/Corg

4.919 £ 10 22 53,982.989 9163.707 0.837

2 2 2 2

2.460 £ 10 22 26,991.495 4581.854 0.418

0.044 0.146 0.211 0.053

0.957 0.865 0.812 0.948

Soil texture

Management system

Sampling depth £ soil texture

Sampling depth £ mangement system

Soil texture £ mangement system

Sampling depth £ soil texture £ management system

signi®cant in regard to all dependent soil parameters (P , 0.05). Signi®cant interactions between the withinsubject effect and the between-subject effects were only time £ soil texture with respect to the pH value and the amounts of Corg, Cmic, and dehydrogenase activity. The tests of the between-subject effects, summarized in Table 4, con®rm that only the soil texture, not the management system and sampling depth, had a signi®cant effect on the variability of the investigated soil parameters. 3.2. Comparison of the two management systems over the 10 year investigation period In sum, all investigated parameters showed no signi®cant differences between the two management systems. There were marked seasonal differences in the investigated parameters during the 10 year observation period in both management systems. The range of the amount of microbial biomass of the nine locations over the years was, for

example, 383.3 (1988) to 503.4 mg g soil 21 (1995) for the IFS, and 377.1 (1994) to 511.2 mg g soil 21 (1986) for the CFS, respectively. The mean pH values, the mean amounts of microbial biomass and soil organic matter, mean Cmic-toCorg ratio, and mean dehydrogenase activity of the nine locations were almost identical in both systems (Fig. 1). The amount of soil organic matter, microbial biomass, and Cmic-to-Corg ratio increased 10±15% in the integrated management treatment compared to the conventional management system starting from the ®fth year of investigation (Fig. 1). Conversely, during the ®rst 4 years of the investigation the examined parameters were slightly increased in the conventional management system (Fig. 1). The differences in dehydrogenase activity between both systems changed from year to year. No differences between either system were found for the pH values of the investigated soils. Only a small number of locations showed significant differences between the treatments in particular years. For example, at Wittlich the amounts of soil organic matter

2110 C. Emmerling et al. / Soil Biology & Biochemistry 33 (2001) 2105±2114 Fig. 1. Mean amounts (^S.D., n ˆ 9) of Corg, microbial biomass, Cmic-to-Corg ratio, and dehydrogenase activity of conventional and integrated managed soils from nine locations in Rhineland-Palatinate, Germany, during the 10 year investigation period.

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Fig. 2. Box plots of the amounts of soil organic matter (Corg), microbial biomass (Cmic), Cmic-to-Corg ratio and dehydrogenase activity in relation to the soil texture of the investigated top horizons on the ®nal sampling date (April 1995). Different letters indicate signi®cant differences between the three classes of soil texture; ANOVA and Bonferroni post-hoc test, P , 0.05; n ˆ 20 (Lt 2,3; Lu), n ˆ 8 (Ls and Sl). Lt ˆ clayey loam; Lu ˆ silty loam; Ls ˆ sandy loam; Sl ˆ loamy sand.

and dehydrogenase activity were signi®cantly higher in the soils of the conventional farming system. In contrast, at Steinwenden the Corg content was signi®cantly increased in the IFS. 3.3. Spatial variability Due to the high heterogeneity of the investigated soils, the soil texture of the top horizon was categorized into three classes based on the clay content (silty to clayic loams, sandy loams, loamy sands). As pointed out above, the soil texture was the only between-subject factor that had a signi®cant in¯uence on the investigated soil parameters (Table 4). Since this factor had three categories, post-hoc comparisons were performed using the Bonferroni adjustment for multiple comparisons to show which differ with respect to the dependent variables. The in¯uence of the soil texture of the top horizon was particularly signi®cant concerning the amount of soil

organic matter, microbial biomass, Cmic-to-Corg ratio, and dehydrogenase activity of the investigated soils (Fig. 2). The amount of soil microbial biomass decreased signi®cantly from the silty and clayey loams to the sandy loams and to the loamy sands. The Corg content was signi®cantly decreased in the loamy sand and sandy loam soils, whereas the Cmic-to-Corg ratio and dehydrogenase activity were signi®cantly decreased in the loamy sand soils compared to the others (Fig. 2). For example, at the ®nal sampling date in April 1995, mean dehydrogenase activities ranged from 51.3 ^ 15.0 mg TPF g soil 21 in loamy sand soils to 170.4 ^ 51.9 and 200.6 ^ 69.8 mg TPF g soil 21 in sandy loam and silty to clayey loam soils, respectively. The Spearman correlation coef®cients between the Corg content and microbial parameters on one hand and the clay content on the other hand were rS ˆ 0.554** (Corg), rS ˆ 0.679** (Cmic), rS ˆ 0.456** (Cmic/Corg) and rS ˆ 0.606** (dehydrogenase), respectively.

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4. Discussion In averaging the nine locations, the mean amount of microbial biomass (Cmic) of 442.5 mg C g soil 21 was characteristic for arable soils in western Germany. Joergensen (1995) determined for arable soils (n ˆ 27) a mean amount of microbial biomass of 345 mg Cmic g soil 21. The mean Cmic/Corg ratio of 4.05% was relatively high in the present study. Anderson and Domsch (1989a) calculated from numerous data in the literature a mean Cmic/Corg ratio for arable soils of 2.36% for monocultured soils and 2.90% for soils under crop rotation. After organic fertilization, the Cmic/Corg quotient increased, and after green manure the ratio was 4.04%. Joergensen (1995) found a mean Cmic/Corg ratio for arable soils of 2.2% (n ˆ 27). Furthermore, MaÈder et al. (1993) determined a mean Cmic/Corg quotient from 2.35% to 2.7% in conventionally managed soils of the D.O.K. study. Methodological causes might be responsible for the relative high ratio in our study since some of the soil samples from the top horizon showed a signi®cant content of carbonates. According to this, an unknown amount of abiotic CO2 release from these samples probably occurred, especially in those years when the samples were analysed with the WoÈsthoff equipment. Based on the soil microbial parameters, the multifactorial analysis of variance did not reveal any signi®cant difference between the two management systems. Nevertheless, the methods used in our study are proper because their indicator function for long-term effects of different management systems on soil microorganisms and the microbiological processes that they govern was proved earlier (Powlson et al., 1987; MaÈder et al., 1995; Franzluebbers et al., 1995). The soil management (Beck, 1991), fertilization (Ladd, 1985; Sparling, 1981) or crop protection procedures in particular affected the biomass and activity of the soil micro¯ora (SchroÈder, 1979; Schuster and SchroÈder, 1990) and enzyme activities (Cervelli et al., 1978). The small differences between the two investigated management systems are to be attributed therefore especially to the fact that in the IFS during the 10 year observation period the reduced input of agro-chemicals had no positive effects on the amounts of microbial biomass and the microbial and enzyme activities at the nine examined locations. Some IFS plots, when soil conserving tillage practice was carried out, showed a signi®cant difference in microbial biomass, the Cmic/Corg ratio and the dehydrogenase activity between the upper and lower top horizon in the integrated managed soils. These are well known phenomena of conservation tillage procedures (Doran, 1980, 1987; Friedel et al., 1996; Kandeler and BoÈhm, 1996). Results from comparative research of CFS and IFS in the Netherlands over a decade showed a slight increase in soil organic matter, a higher amount of biomass and activity of soil organisms in the IFS (Brussaard, 1994; Zwart et al., 1994). The authors discerned basic differences in the living conditions of the soil food web between both management

systems in supplement of additional population-ecological investigations (De Ruiter et al., 1994; Didden et al., 1994). In a long-term ®eld investigation of conventionally and integrated managed soils of the `Lauterbach project', the mean decomposition rate of buried cellulose paper was higher in integrated managed soils than in conventionally managed ones during a 7 year investigation period. However, the mean differences between the two different treatments were not statistically signi®cant (El Titi and Landes, 1990). Results from investigations of Haider (1992) also emphasize no signi®cant differences in the speci®c metabolic ef®ciency of soil microorganisms and the microbial C assimilation between integrated and conventional soil managements. The soil texture of the top horizon supplied the largest signi®cant differences to the investigated parameters. The clay content was throughout the highest determining factor for the distinctness of pH values, organic matter contents and microbial properties. This underlines the necessity to carry out these studies at many sites. The microbial biomass, microbial activities, as well as enzyme activities are affected indirectly by the soil texture and its in¯uence on the soil structure (aggregation) and several dependent soil properties such as soil water, air and heat dynamics (Hoffmann, 1986; Anderson and Domsch, 1989b). Usually, a close relationship exists between the quantity and quality of the soil organic substance and the quantity and metabolic activity of the microorganisms (Anderson and Domsch, 1989a; Joergensen 1995). Merckx et al. (1985); van Veen et al. (1985), among others, suggested strong positive correlations between the clay content and the soil microbial biomass. However, Sparling (1981); Veremans et al. (1989) did not ®nd this correlation for sandy soils. Kaiser et al. (1992) suggested that the relationship between the bio-physical environment of sandy soils and the microbial biomass and the organic matter turnover seems to be more complex in sandy than in clayey soils. However, an increase of microbial activity with increasing clay content must be restricted to soil samples which were sieved before soil analysis. Results of soil microbial activity from undisturbed aggregated soil samples, which were not sieved before analysis, showed a signi®cant decrease in microbial activity (respiration, nitri®cation, dimethysulphoxide reduction activity) compared with sieved soil samples on the same soil weight bases (Emmerling et al., 1996). These results indicate a high signi®cance of biophysical and edaphic factors on soil microbial activity under ®eld conditions. The deviation of the various parameters from the total average value of the nine investigated locations (Fig. 1) re¯ects the sum of the abiotic and edaphic factors and the climatic conditions at the various locations (Smith and Paul, 1990; Insam et al., 1989; Sarathchandra et al., 1989; Wardle, 1998). For instance, at ®ve of the nine locations, Holzweiler, Emmelshausen, Sobernheim, Steinwenden and Wittlich, the amounts of microbial biomass were almost identical to the total average value. The soils were silty to sandy loamy

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haplic stagnogleys and (luvi-) cambisols which are in¯uenced by wind-blown silt in the top horizon (Table 1). At Dudenhofen and Speyer the amounts of microbial biomass were approximately 50% lower than the total average value. These soils are loamy±sandy cambisols and luvisols. In our study, there was a strong temporal variation in the investigated soil microbial properties over the 10 years. For example, the microbial biomass data can be split into two parts. During the ®rst 4 years, except 1987, mean amounts were higher in CFS than in IFS. In the following 6 years, the results were conversely increased in IFS. This was probably due to the cultivation of intermediate crops and conservation tillage leading to a slow increase in the amount of soil C and the overall quality of soil organic matter. Therefore, as already pointed out by Wardle (1998); Wardle et al. (1999), our data from the 10 year investigation period indicate the signi®cance of temporal variability in microbiological data sets and the need for long-term investigations. However, we suggest that our results be viewed more fundamentally, as soil from nine different locations was examined. 5. Conclusions In sum, the differences between IFS and CFS were quite small. Therefore, we suggest that the reduction of chemical inputs in the IFS is not suf®cient for future sustainable agriculture from a soil microbiological point of view. In practice, in the integrated farming system, more attention should be focused on diverse crop rotation, intermediate and cover crops, conservation tillage and organic matter application in order to stimulate microbial functions in these soils. Acknowledgements The study was ®nancially supported by the Ministry of Economics, Traf®c, Agriculture & Viticulture, RhinelandPalatinate, Germany. We thank the National Of®ce for Crop Farming and Plant Protection, Mainz, Rhineland-Palatinate, for their cooperative help and Nicola Wermbter, University of Trier, Soil Science Dep., for reliable work and assistance with the study. References Anderson, J.P.E., Domsch, K.H., 1978. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biology & Biochemistry 10, 215±221. Anderson, T.H., Domsch, K.H., 1989a. Ratios of microbial biomass carbon to total organic carbon in arable soils. Soil Biology & Biochemistry 21, 471±479. Anderson, T.H., Domsch, K.H., 1989b. Der Ein¯uû des BodengefuÈges auf mikrobielle Stoffwechselleistungen. Mitteilungen Deutsche Bodenkundliche Gesellschaft 59, 523±528. Anderson, T.H., Domsch, K.H., 1990. Application of ecophysiological

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