the effect of soil structure differences in a silt loam soil under various farm management systems...

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ELSEVIER Agriculture, Ecosystems and Environment 51 (1994) 227-238 Agriculture Ecosystems & Enwronment The effect of soil structure differences in a silt loam soil under various farm management systems on soil physical properties and simulated land qualities E.C. Vos*, M.J. Kooistra DLO Winand Staring Centre for Integrated Land, Soil and Water Research, P.O. Box 125, 6700 AC Wageningen, Netherlands Accepted 30 March 1993 Abs~a~ Five different farm management systems on the same soil were selected to study the effects of the enhancement of soil organisms on soil structure formation, on soil physical properties and simulated land qualities. The farm management systems were: a conventional high input system (CONV); an integrated system (INT) i.e. reduced N-fertilisation, reduced biocide use and shallower soil tillage; a minimum tillage system (MTnew) with only 7 cm ploughing which was just started; a minimum tillage system (MTold) with the same management over 18 years and a permanent pasture (P). The soil physical properties determined were: water retention and hydraulic con- ductivity curves. The land qualities which were simulated were the workability and the aeration status (air-filled porosity). Water retention and hydraulic conductivities curves of the topsoils (0-25 cm) of the different farm manage- ment systems involved, were different, as were those of the 25-50 cm layer of the arable systems on one hand and pasture land on the other. In the farm management systems, with the highest impact of soil organisms on the soil structure, i.e. pasture land and old minimum tillage, soil physical properties were most favourable for growing crops. The conventional and integrated systems had the least favourable properties. This was also true of the simulated land qualities. In spring the probabilities over a 30 year period, to work in the field (workability), for the old minimum tillage system were about 15% higher than for the integrated and conventional farm management system. Those of the permanent pasture were about 20% higher than the old minimum tillage system. The same trend was shown in autumn at harvest. The old minimum tillage system and permanent pasture had the lowest probabilities of an insufficient air fraction during the growing season. Those of the conventional and integrated systems were 20-40% higher over the growing season. Calculated yields for a potato crop showed the same trend except for MTold which had the lowest yields espe- cially in years with a previous wet winter season. Of all crops potatoes react most sensitively to soil compaction and MTold had the most compacted soil. However, the increase in workability and aeration in this system com- pensated for the calculated yield reduction as the actual yields of CONV and MTold were similar. Consequently, farm management systems stimulating the presence and activities of structure-forming soil fauna * Corresponding author. * Communication No. 65 of the Dutch Programme on Soil Ecology of Arable Farming Systems. 0167-8809/94/$07.00 © 1994 Elsevier Science B.V. All rights reserved SSDI 0167-8809 (94) 08014-Q

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ELSEVIER Agriculture, Ecosystems and Environment 51 (1994) 227-238

Agriculture Ecosystems & Enwronment

The effect of soil structure differences in a silt loam soil under various farm management systems on soil physical properties and

simulated land qualities

E.C. Vos*, M.J. Kooistra DLO Winand Staring Centre for Integrated Land, Soil and Water Research, P.O. Box 125, 6700 AC Wageningen, Netherlands

Accepted 30 March 1993

Abs~a~

Five different farm management systems on the same soil were selected to study the effects of the enhancement of soil organisms on soil structure formation, on soil physical properties and simulated land qualities. The farm management systems were: a conventional high input system (CONV); an integrated system (INT) i.e. reduced N-fertilisation, reduced biocide use and shallower soil tillage; a minimum tillage system (MTnew) with only 7 cm ploughing which was just started; a minimum tillage system (MTold) with the same management over 18 years and a permanent pasture (P). The soil physical properties determined were: water retention and hydraulic con- ductivity curves. The land qualities which were simulated were the workability and the aeration status (air-filled porosity).

Water retention and hydraulic conductivities curves of the topsoils (0-25 cm) of the different farm manage- ment systems involved, were different, as were those of the 25-50 cm layer of the arable systems on one hand and pasture land on the other. In the farm management systems, with the highest impact of soil organisms on the soil structure, i.e. pasture land and old minimum tillage, soil physical properties were most favourable for growing crops. The conventional and integrated systems had the least favourable properties. This was also true of the simulated land qualities.

In spring the probabilities over a 30 year period, to work in the field (workability), for the old minimum tillage system were about 15% higher than for the integrated and conventional farm management system. Those of the permanent pasture were about 20% higher than the old minimum tillage system. The same trend was shown in autumn at harvest. The old minimum tillage system and permanent pasture had the lowest probabilities of an insufficient air fraction during the growing season. Those of the conventional and integrated systems were 20-40% higher over the growing season.

Calculated yields for a potato crop showed the same trend except for MTold which had the lowest yields espe- cially in years with a previous wet winter season. Of all crops potatoes react most sensitively to soil compaction and MTold had the most compacted soil. However, the increase in workability and aeration in this system com- pensated for the calculated yield reduction as the actual yields of CONV and MTold were similar.

Consequently, farm management systems stimulating the presence and activities of structure-forming soil fauna

* Corresponding author. * Communication No. 65 of the Dutch Programme on Soil Ecology of Arable Farming Systems.

0167-8809/94/$07.00 © 1994 Elsevier Science B.V. All rights reserved SSDI 0167-8809 (94) 08014-Q

228 E.C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238

will also stimulate the development of more favourable soil physical properties, such as better aeration and more workable days during the growing season.

Keywords: Farming system, conventional; Farming system, integrated; Soil fauna; Soil physics; Soil structure; Tillage system

1. Introduction

One of the main objectives in the Dutch Pro- gramme on Soil Ecology of Arable Farming Sys- tems concerns the enhancement of the contribu- tion of soil organisms to soil structure formation (Brussaard et al., 1988 ). It was hypothesised that reduced nutrient inputs, reduced soil tillage and reduced use of biocides would lead to an in- creased contribution of soil organisms to soil structure formation and improved associated soil physical properties.

In the Dutch Programme three farm manage- ment systems were compared: a conventional high-input system (CONV), an integrated sys- tem (INT), i.e. a system with reduced N-fertil- isation, reduced biocide use and shallower soil tillage, and a minimum tillage system (MTnew) with only 7 cm ploughing (Lebbink et al., 1994). Of the three farm management systems estab- lished in 1985 in the Dutch Programme, CONV could be considered as being in a stable state be- cause here the farm management system was not drastically changed. INT was expected to ap- proach equilibrium in a few years, whereas MTnew was expected to be unstable for several years (Boersma and Kooistra, 1994).

As soil structure changes evolve over several years (Jongerius, 1970; Kooistra et al., 1985 ) we included in our research two other systems that were considered to be in a stable state, presum- ably showing a high impact of soil organisms on the soil structure: a minimum tillage system (MTold), in which over 18 years the same man- agement had occurred and a pasture land (P) of about the same age. Soil microstructure research revealed that the topsoils (0-25 cm depth) of the five selected systems had different soil struc- tures. Those of MTold and P showed a compa- rable high impact of soil organisms on soil struc- ture (Boersma and Kooistra, 1994). In INT the soil structure was more determined by soil orga-

nisms than in CONV, but considerably less than in the previously mentioned two systems. MTnew showed the lowest contribution of soil organisms to soil structure formation in the top- soil, as evidenced by the study of soil structure (Boersma and Kooistra, 1994). The impact of the different farm management systems on the soil structure was restricted to the topsoils, ex- cept for P where the influence reached to 42 cm depth. Below these depths the geogenetic prop- erties of these young reclaimed soils prevailed. Differences in soil microstructure over the years did not show clear trends. Only the impact of soil organisms on voids with diameters greater than 30 pm in INT changed from less than 2% in 1985 to over 5% in 1990 (Boersma and Kooistra, 1994).

Complementary to the study of Boersma and Kooistra (1994) effects of soil structure differ- ences on soil physical properties were evaluated. Water retention (h-O) and hydraulic conduc- tivity ( k - h ) characteristics were determined in six-fold in several years for soil samples from different depths in all farm management systems (Table 1 ). Here we hypothesise that differences in (micro) structure will lead to differences in soil physical properties (Kooistra et al., 1985; Van Lanen et al., 1992 ). The influence of farm man- agement systems, e.g. tillage, on soil structure is most significant in the top layers of the soil and is expressed in different soil structures (Boersma and Kooistra, 1994). Therefore, we hypothe- sised that the soil physical characteristics of the topsoil (0-25 cm) would be different for all dif- ferent farm management systems. Based on the differences in soil structure, soil physical char- acteristics of the 25-50 cm layer in the arable systems on the one hand and pasture land on the other, were also expected to be different. Below 50 cm depth the soil structure of all systems was thought not to be influenced by the different farm management systems. Based on the geological

E.C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238

Table 1 Sampling information for soil physical characterisation

229

Farm Crop Precrop Year (month) Depth management (cm) system

Number of samples with a content in cm 3 of

2000 300 200

1 CONV Sugar beet Seed-potato 1985 (May) 0-25 25-45 55-75

Winter wheat Sugar beet 1986 (Nov) 55-75 Sugar beet Winter wheat 1987 (Jun) 0-25 Spring barley Sugar beet 1988 (Apr) 0-25

2 INT Sugar beet Seed potato 1985 (May) 0-25 25-45 55-75

Sugar beet Winter wheat 1987 (Jun) 0-25 Spring barley Sugar beet 1988 (Apr) 0-25

3 P Grass Grass 1987 (Aug) 0-25 25-50 50-75

Grass Grass 1988 (Apr) 0-25 25-50 50-75

4 MTnew Sugar beet Spring barley 1987 (Jun) 0-25 25-50

5 MTold Sugar beet Spring barley 1985 (May) 0-25 Lucerne Oats 1987 (Dec) 0-25

2 2 2 2 2 2 2 2 2 4 4 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2 4 4 4

history and soil profile characterisation (Boersma and Kooistra, 1994), taking into ac- count the rather short time span of soil ripening and the high groundwater table (De Vos et al., 1994) only one subsoil layer (50-75 cm) was distinguished for all farm management systems to physically characterise this part of the soil profile.

The differences in soil physical properties were expected to affect land qualities. To estimate their significance for land use purposes, these proper- ties were used to simulate soil-water dynamics over a period of 30 years and to express different soil management practices in terms of effects on land qualities such as workability and aeration status (FAO-UNESCO, 1976; Bouma, 1984; Van Lanen et al., 1987, 1992). When the effects of the different soil structures as a result of the different farm management systems can be ex- pressed in terms of different numbers of worka- ble days and days with limited aeration of the soil, a farm management system with the most

favourable results can be selected for the soil concerned.

2. Materials and methods

2. I. Soils and farm management systems

The field work was carried out at the experi- mental farm "Dr. H.J. Lovinkhoeve", near Marknesse in the Noordoostpolder, The Neth- erlands. This polder was reclaimed in 1942 from a freshwater lake. All farm management systems, including pasture land, were practiced on the same young soils, sedimentary calcareous silt loams classified as Typic Fluvaquents (Soil Sur- vey Staff, 1975 ) or as Calcaric Fluvisols (FAO- UNESCO, 1974). The parent material had the same composition with identical textural com- position, pH and CaCO3 content. Also the drain- age and weather conditions were the same. Hence, differences in soil structure could only be

230 E.C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 22 7-238

attributed to the impact of the different farm management systems which affect the organic matter content and quality, and the activities of structure-forming soil organisms (Kooistra et al., 1989). Since 1985 the crop rotation consisted of winter wheat, sugar beet, spring barley and po- tatoes (Lebbink et al., this volume, pp. 000- 000).

Soil physical characteristics of the topsoil (0- 25 cm), the intermediate layer (25-50 cm) and the subsoil (50-75 cm) of the different farm management systems were measured.

2.2. Soil physical determinations

Laboratory and field Moisture retention data were obtained in the

laboratory using undisturbed soil cores of 7.3 cm diameter and 7.2 cm height (300 cm 3). The water retention curve from h = - 5 to h = - 150 cm was measured by the method of the hanging water column (Stolte et al., 1992). The range up to h = - 8 0 0 cm was measured using series of ten- siometer readings in the drying soil and corre- sponding gravimetric moisture samples (Bouma, 1983; Klute, 1986 ). In the range h = - 800 cm to h = - 16000 cm moisture retention data were ob- tained by the pressure cell method (Klute, 1986; Stolte et al., 1992).

Hydraulic conductivities were measured by applying several methods in large undisturbed soil cores of 20 cm diameter and 20 cm height (6000 c m 3 ). The constant head method was used to measure ksat, the crust test for k between h = 0 cm and h ~ - 60 cm (Booltink et al., 1991; Stolte et al., 1992). On samples of 5 cm diameter and 10 cm height, the hot air method was used for k values when h < - 6 0 cm (Bouma, 1983; Van Grinsven et al., 1985 ).

Measurements were repeated in 1985, 1987 and 1988 (see Table 1 ). In 1985 and 1988 only CONV and INT were characterised physically. In 1987 the soil physical properties of all five systems were measured in connection with soil structure research (Boersma and Kooistra, 1994).

Simulation model To investigate the effects of soil structure dif-

ferences on land qualities such as workability and soil aeration a quantitative procedure (SWANY) was used (Hack-ten Broeke et al., 1989), based on the model SWACROP, which consists of a soil water flow model (SWATRE) and a CROp PRoduction model (CROPR) (Feddes et al., 1978 ). SWATRE (Soil Water Actual Transpira- tion Rate Extended) describes one-dimensional (vertical), transient, unsaturated water flow in a heterogeneous soil-root system using Richard's equation (Belmans et al., 1983; Feddes et al., 1988), which is solved numerically by a finite- difference scheme. The soil is divided into com- partments and the term for root water uptake (sink term) is calculated as a function of the maximum transpiration rate and a reduction factor, which depends on the pressure head in the root zone (Feddes et al., 1988).

SWACROP allows for simulation of only one growing season. SWANY (SWAcrop for a Num- ber of Years) was developed to allow for multi- ple-year simulations to obtain frequency distri- butions of events. SWANY simulates both winter and growing season. The start of the growing sea- son, being the sowing or planting date, is simu- lated by the soil-water model by considering the calculated number of workable days and the re- quired number of days for field operations. The simulated pressure head and the air temperature after sowing or planting determine the crop emergence date. This procedure is crop-specific. From emergence onward, SWANY simulated daily soil water flow and crop growth (Van Wijk and Feddes, 1986; Hack-ten Broeke et al., 1989). At the end of the growing season the crop is har- vested and the model returns to the soil-water simulations for the next winter period. The out- put of SWANY is used to present quantitative measures for workability and aeration.

Calculations were made for a 30 year period using a historical record of weather conditions, from 1951 to 1980, relevant for the area con- cerned. The model computes pressure heads, moisture contents, air-filled porosities, potential and actual transpiration, crop production and groundwater depths as function of depth and

E.C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (I 994) 227-238 231

time. The calculations were made for a potato crop as this is the most sensitive crop in the crop rotation for suboptimal soil structures (Van La- nen et al., 1987). Input data comprised for in- stance the measured 0 - h and k - h relations. Al- though variability of the measured data can be considerable (Bouma and Hack-ten Broeke, 1993), in this study only the average curves of the samples measured in 1987 were used in the simulation model to limit the number output and to focus on the main trend of the different farm management systems.

Validation of the simulation results with mea- sured pressure heads was performed by De Vos et al. (1994), who concluded that, even after a reduction of the hydraulic conductivity charac- teristic in the subsoil with a factor 10, the simu- lation of the water balance was not accurate. In the present paper, the final results of De Vos et al. (1994) were neveilheless taken as a starting point.

the air-filled porosity is above a threshold value the aeration is supposed to be satisfactory for the crop concerned. According to Bakker et al. (1987) a threshold value of 0.09 m 3 m -3 was used in this research. The probabilities of occur- rence of the land qualities values were calculated in the model on a daily basis for a 30 year period. For reasons of simplicity, they were visually pre- sented on a 10 day basis.

The transpiration was calculated as well as productivity in terms of crop yields. Calcula- tions were made for potato crops. Potatoes are more sensitive to soil compaction than winter wheat or sugar beet and therefore more indica- tive for limitations.

For every growing season the moisture deficit was determined as the difference between poten- tial and actual transpiration. Actual water-lim- ited production and actual transpiration of the different farm management systems were compared.

Physical land qualities In this study the relevant land qualities were

considered; i.e. workability and aeration-status (air-filled porosity), as other land qualities, e.g. moisture supply capacity, are not limiting in these soils. The workability of the soil was determined in accordance with the procedure proposed by Van Wijk and Feddes (1986). Calculated daily pressure heads in the topsoil were compared with a critical pressure head, a threshold value char- acteristic for the soils concerned, below which soil conditions allow field operations (Van Wijk and Buitendijk, 1988). Owing to distinguished soil structures by Boersma and Kooistra (1994) dif- ferent thresholds for workability were used. On a soil as found in CONV and INT a threshold of h = - 100 cm was used. For MTnew and MTold a threshold of h = - 8 0 cm and for P a threshold of h = - 70 cm was used. The higher thresholds of the MT systems and P were used because the non-tillage systems had a higher resistance to wheel-loads owing to a more settled structure (Van Wijk and Feddes, 1986; experience of farm manager Lovinkhoeve, 1992 ).

Air-filled porosity at a depth of 5 cm below the surface was used as indicator for aeration. When

3. R e s u l t s a n d d i s c u s s i o n

3. I. Soil physical properties: 0-25 cm layer

The average water retention curves and hy- draulic conductivity curves for the topsoil of the five systems in 1987 are presented in Fig. 1.

From saturation to field capacity ( h = - 100 cm), MTold had the highest water content. CONV and MTnew had the lowest water content in the same range. In the drier part ( h < - 100 cm) of the curves INT had the highest water content. The curves of P, MTnew and CONV formed one cluster. Pasture remained the wet- test and CONV the driest. MTold showed the greatest reduction in soil moisture content at h values lower than - 100 cm (Fig. 1 (A)) .

The shape of curves of MTold and INT dif- fered most. The shape of the water retention curve reflects the amount of water available to the plant. This is revealed in the amount of easily available water (h= - 100 up to h= - 2 5 0 0 cm) and total available water (h = - 100 up to h = - 1 6 0 0 0 cm) to the plant (Table 2). MTold showed the highest amounts of available water

232 E.C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238

10 +5

10+4 .c

10 *3

~ 1o +2

~ lO+1

10+00. 0

Water retention curve A 10 +3

10 *2

._~ 10"0

~" ~. ~ 10 "1

" ' ~ ' % -%. ~ 1°'2

N lO" 3

"~ 10-4

[~ i } / :3:10 .5

, ~ ~ 10,6 0.1 0.2 0.3 0.4 0.5 Water content (cm3/cm 3)

Hydraulic conductivity curve

Legend B . . . . o:3O:u, ,,

Integrated Old minimum Till. Pasture

I I I I I

10 +0 1o +I 10 +2 lO *3 10 +4 10 ÷5

Water pressure head. I h I (cm)

Fig. 1. Water retention (A) and hydraulic conductivity (B) curves of the topsoils (0-25 cm) of the five farm management systems in 1987.

Tabale 2 Available soil water (cm 3 cm -3) between h= - 100 and h= -2500 cm and h= - 100 and h= - 16 000 cm in the topsoils of the five farm management systems

h ranges (cm) Soil water fraction

CONV INT P MTnew MTold

- 100 to - 2500 0.222 0. i 95 0.260 0.224 0.331 - 100 to - 16 000 0.280 0.268 0.320 0.285 0.366

in both h ranges and INT showed the smallest amounts. Statistical analysis of pairwise T-val- ues resulted in a significant difference for MTold compared with CONV (WGsten et al., 1986).

The hydraulic conductivities did not show a clear trend (Fig. I (B) ) . In the wettest part (down to h = - 2 5 cm) MTnew had the lowest hydraulic conductivity and MTold in the range h< - 2 5 cm. The overall curve of P can be con- sidered as the most favourable, based on the high conductivities near saturation and the higher conductivity between h = - 15 and h = - 600 cm, and keeping in mind the relatively higher con- tent of easily available water (Table 2).

3.2. Soil physical properties: 25-50 and 50-- 75 cm layers

The same properties were determined for the intermediate layer (25-50 cm) and the subsoil

(50-75 cm). The results are presented in Fig. 2. The water retention curves of the intermediate layer showed a slightly higher water content in the range from saturation to field capacity than those of the topsoils (cf. Fig. 1 (A)) . The water retention curve of the subsoil showed a still higher water content in this range than those of the intermediate layer. The shapes of the curves in Fig. 2 are not significantly different. This is revealed in the amounts of easily (h = - 100 up to h = - 2 5 0 0 cm) and total ( h = - 1 0 0 up to h = - 16000 cm) available water for these layers (Table 3).

The hydraulic conductivity curves of the ara- ble systems and P in the layer 25-50 cm showed a clear difference in the wet part (Fig. 2 (B) ). P had the highest hydraulic conductivity. This can be attributed to the soil structure, i.e. a medium (20-50 mm ¢) prismatic structure, and the im- pact of soil biota (mainly earthworms) on this

E.C. I"os, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238 233

10 +5

~_u~: 10 +4 ..c

10+3

~o. 10+2

~ 10+1

10+ 0 0.0

Water retention curve

A 10+ 3

10+ 2

.~ 10+0

"~ 10"I

1o.2

• I f ~ u 10. 3

Ii },o, 10-5

t I I I ~ lO. 6 01 0.2 0.3 04 Water content (cm3/cm 3)

Hydraulic conductivity curve

Legend B Intermediate, Arable

. . . . Intermediate, Pasture Subsoil

I I I I I

0.5 10+0 10+1 10+2 10+3 10+4 10+5 Water pressure head, I h I (cm)

Fig. 2. Water retention (A) and hydraulic conductivity (B) curves of the intermediate layer (25-50 cm ) and of the subsoil (50- 75 cm) of the arable systems and pasture land.

Table 3 Available soil water (cm 3 c m - 3 ) of the intermediate layer (25-50 cm) in the arable farm management systems CONV, INT, MTnew and MTold, and pasture and for the subsoil (50- 75 cm) between h= - 100 and h= -2500 cm and h= - 100 and h = - 16 000 cm

h ranges (cm) Soil water fraction

25-50 cm layer 50-75 cm layer

Arable Pasture Subsoil

- 100 to - 2500 0.266 0.293 0.302 - 100 to - 16 000 0.325 0.351 0.380

layer (Boersma and Kooistra, 1994). Under h = - 200 cm they were almost identical.

3.3. Soil physical properties: 0-25 cm layer o f CONV and I N T over the years 1985-1988

As soil structure changes over the years after a change in management practices, soil physical properties of the topsoils were determined be- fore and after the start of the new management practices. The water retention and hydraulic conductivity curves of CONV and INT were de- termined for 1985, 1987 and 1988 (Fig. 3). The water retention curves of CONV hardly changed over the years, thus confirming that this system was in a steady state. This also shows that the variability in CONV was quite small. The corre-

sponding curves of INT had comparable shapes and did not show a clear trend, but showed clear differences, thus confirming that this system had not reached a steady state.

The shape of the curves of CONV remained the same. This is also more or less the case for the curves in INT. The shapes of CONV and INT, however, were different, which is revealed in the amounts of easily ( h = - 100 up to h - - - 2 5 0 0 cm) and total ( h = - 100 up to h = - 16000 cm) available water for the plants (Table 4). In each year the amounts of easily and total available water were greater for CONV than for INT. The data of INT did not show any trend. Although INT had a higher water content as represented in Fig. 3(A) the water available for the plants is more favourable in CONV than in INT.

The hydraulic conductivity curves of CONV and INT (Fig. 3 (B) ) did not show any trend and the variability was small. In the wet range (to h ~ - 20 cm) they differed the most, whereas the spread between the curves of CONV was greater than between those of INT.

3.4. Simulated land qualities

As soil physical properties over the years did not show any trend, simulation of land qualities was calculated with soil physical data of 1987. For that year soil physical data of all farm man- agement systems were available. The soil physi-

234 E.C. Fos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238

I0 +5

v•lO +4

J:=

"~m'10+3

~ 10 +2

10+1

10 +0 0.0

Water retention curve

A

%,.[

L~ I I I f i

0.1 0.2 03 0.4 0.5

Water content (cm3/cm 3)

io+3

10+ 2

u 10 +1

10+0

10.1

i0.2

v -~ 10 .3

"0 10 .4 I

lO-5

lO-6 10+ 0 i0 +I 10+ 2 10 +3 10",.4

Water pressure head, I h I (cm)

Hydraulic conductivity curve

Legend B . . . . Conventional 12B '85

~ Conventional 12B '87 ~ . ~ . . . . Conventional 12B '88 "~%...~ . . . . . . . . Integrated 16A '85

~ ' ~ ' ~ . . . . ............... Integrated 16A '87 ~ . . . . . . Integrated 16A '88

I I i I I

10 +5

Fig. 3. Water retention (A) and hydraulic conductivity (B) curves of the topsoils (0-25 cm ) of the conventional and integrated systems in 1985, 1987 and 1988.

Table 4 Available soil water (cm 3 cm -3) in the topsoils of CONV and INT in 1985, 1987 and 1988 between h= - 100 and h= - 2 5 0 0 cm and h = - 100 and h = - 16 000 cm

h ranges (cm) Soil water fraction

CONV85 CONV87 CONV88 INT85 INT87 INT88

- 100 to - 2 5 0 0 0.232 0.222 0.234 0.164 0.195 0.159 - 100 to - 16 000 0.283 0.280 0.286 0.254 0.268 0.257

cal data of the topsoils of all five farm manage- merit systems were combined with those of the intermediate layer and the subsoil to calculate soil water regimes in vertical columns. For all arable systems the same intermediate layer and for P a different curve was used. The curves used are presented in Fig. 2. Subsoil data were the same for all cases.

Workable days The simulated workable days for the 0-10 cm

layer for growing potatoes in the five farm man- agement systems using a 30 year weather record are presented in Fig. 4.

The curves for the five farm management sys- tems were different. P had the highest occur- rence of workable days throughout the year. CONV and INT had the lowest occurrence of workable days almost throughout the year.

Important periods for the workability of the land when growing potatoes are March and April for planting and the end of September and Oc-

tober for harvesting. In these periods the curves for the different farm management systems showed large differences. The probability of oc- currence of workable days for planting potatoes in April ranged from 18 to 30% for CONV and INT. For P the probabilities of good working conditions ranged from 56 to 75%. The proba- bilities for MTold and MTnew were in between, ranging from 33 to 58%. This can be explained by the higher compactness of the no longer tilled zone of MTnew, which favours the workability of the soil. In MTold, this zone is more open as a consequence of the biological impact on the soil structure (Boersma and Kooistra, this volume, pp. 000-000). In autumn the differences showed the same trend but the probabilities were higher. For CONV and INT they ranged from 40 to 75% and for P from 75 to 90%.

The simulated data are well in agreement with the management experiences at the Lovink- hoeve. Land cultivated by the MTold system is the first on which planting operations can be per-

E,C. Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238 235

100 . . . - - - - ( . . . . . . . . . ,

. " * / , , / a x x ~ " ' , lll~ " ',.

~.~umT~,,. "'~-~ \ ~ 11; \_

20 "¢ ~' Olfl minimum Till. f f "

. . . . . . Pastun~ "-~ . ~ 4 . / ' =~

0 I I I I I I I I I I I I April May June July Aug Sept Oct Nov Dec Jan Febr March

Hydrological year

Probability of occurence of workable days in % per decade for the five different farming systems in a silt loam soil

Fig. 4. Probabilities of occurrence of workable days for the 0- l 0 cm layer in per cent per 10 day period for the five different farm management systems using a 30 year weather record.

formed in the spring, CONV is second, then INT (farm manager Lovinkhoeve, personal commu- nication, 1992). The time at which planting can begin on MTnew varies and depends on the de- gree of slaking of the top layer.

Aeration The results of the simulation of aeration for the

0-10 cm layer for the five farm management sys- tems using a 30 year weather record are given in Fig. 5. The curves for the five farm management systems were different. INT had the highest probability of insufficient aeration, especially in the growing season from April to July, which will result in a restriction of growth. The probability of an air fraction less than 0.09 cm 3 cm-3 for this farm management system ranged from 100% in the first 10 days of May to 73% in the second 10 days of June. This means that this system had the greatest risk of insufficient soil aeration with respect to root and crop growth. CONV had a slightly lower risk of insufficient soil aeration. MTold and P had the lowest probabilities of an insufficient air fraction almost throughout the growing season.

The chance of an insufficient air-filled poros- ity was rather high on these silt loam soils which might give problems with crop growth in wet

years. The probability dropped below 60% in all farm management systems only after the second l 0 days of June. For MTold this had happened by the third 10 days of May. MTold and MTnew showed differences in aeration for the roots. MTold, with its high biological impact on the soil structure, had a distinctively better aeration, es- pecially in spring and autumn.

Transpiration~production The actual yearly transpiration of the crop in

the farm management systems INT, MTnew, MTold and P was compared with that of CONV (100%). The highest transpiration was calcu- lated for P and the lowest for MTold. These re- suits were also reflected in the calculated yields for a potato crop (Fig. 6).

The output of the model showed the lowest yields for MTold and the highest yields for P over the 30 year period. CONV, INT and MTnew had similar yields over the calculated period. Com- pared with CONV, actual production ranged be- tween 70.7 and 131.5% for INT, 71 and 131.5% for MTnew, 61.9 and 131.5% for MTold and 101.3 and 131.5% for P.

The low yields were obtained in years which had a previous wet winter season causing a late sowing date.

236 E.C Vos, M.J. Kooistra / Agriculture, Ecosystems and Environment 51 (1994) 227-238

100

80

~6o

20

....... .. .~-~. ~-

\'),t / z , : / i / . . / / / , ' / p s

. . . . . ' F <..oo \ " k ~K."~ o . . . ~ ' ; ~ s ' 7 . " ' / - - - _ - _ l°ew~emn.t:Tmnualm Till,

~ ~ . : .~y , . , ............... .o,~,,,.,~ o,g, F2,=°..,,,,

I I I I I I 1 I I I I I April May June July Aug Sept Oct Nov Dec Jan Febr March

Hydrological year

Probability of occurence of an airfraction less than 0.09 cm3/cm 3 in % per decade for the five different farming systems in a silt loam soil

Fig. 5. Probabilities of occurrence of adequate aeration in the 0-10 cm layer in per cent per 10 day period for the five different farm management systems using a 30 year weather record.

2 5

g

1 2 1

............... INT

MT new

MT old ...... p

0 i i i L I J i i i I i i i i I i i i i [ i i i i ] i i i i J

1951 1956 1961 1966 1971 1976 1981

Fig. 6. Calculated actual production of potatoes in kilograms per hectare dry matter for the five different farm management systems.

4. Discussion and conclusions

The differences in soil structure observed by macro- and micromorphological methods (Boersma and Kooistra, 1994) arc far more pro- nounced than the soil physical properties of the five farm management systems studied. Part of this can be attributed to the more detailed soil structure study, which distinguishes more layers in the topsoils, with different characteristics. The water retention curves, determined on samples of 7.2 cm height differed more than the hy-

draulic conductivity curves, determined from samples of 20 cm height. An undisturbed col- umn of 20 cm height, however, comprised more layers and the layer with the lowest permeability determines the curves. Samples with a smaller height would have been more adequate.

The soil physical properties of the topsoils were different. The farm management systems with a high impact of soil organisms on the soil struc- ture, P and MTold had the best properties and CONV and INT with the lowest biological im- pact on the soil structure the least favourable.

E. C Vos, M.J. Kooistra /Agriculture, Ecosystems and Environment 51 (I 994) 22 7-238 237

The soil physical properties of INT did not show significant differences or trends in the first 3 years after the start of the integrated farm man- agement system. This can either be due to the al- ready nearly stable state of the soil structure or to the fact that changes in soil structure occur over prolonged periods. As the soil structure re- search (Boersma and Kooistra, 1994) showed an increased contribution of soil fauna on the soil structure in INT the latter is more probable. Moreover, increased faunal activity need not lead directly to better soil physical properties. It de- pends on the kind of structure forming activities, the amount of effect, depths of activity and con- nections with other void systems in the soil. These effects develop over the years.

The simulated land qualities workability and aeration showed the same trend over a 30 year period. The most biologically determined soil structure in an arable system, i.e. MTold, had probabilities of favourable circumstances in spring, which were 15% higher than those of the least biologically determined soil structure of CONV and INT. Those of the permanent pas- ture with a high impact of earthworms were 20% higher than MTold, showing that by aiming for an optimum, biological soil structure, consider- able improvements can be obtained.

In autumn the same pattern was present at harvest time. The probabilities of insufficient aeration during the growing season were lowest and ranged between 18 and 40% in MTold and P. Those of CONV and INT were 20-40% higher over the growing season.

The calculated yearly transpiration and yield for a potato crop in the five farm management systems showed a slightly diverging resuR. P had the highest calculated transpiration and yields; for CONV, INT and MTnew these were similar but lower and for MTold again slightly lower. Potatoes are the most sensitive crop for compac- tion and MTold is the most compacted soil with the lowest conductivities below h = - 2 5 cm.

The calculated lower potato yields occurred in years with a previous wet winter season. In these years, however, the increase in workability and aeration on MTold compensated for the calcu- lated yield reduction as the actual yields on

CONV and MTold were rather similar (farm manager Lovinkhoeve, personal communica- tion, 1990). Moreover, there were no worms in the MTold system, as they had not yet reached this location after the reclamation of the polder (Marinissen, 1991 ). When worms colonise this location, which is likely to occur in the coming years, the hydraulic conductivities below h-- - 25 cm will increase, leading to higher calculated transpirations and yields. Then the actual crop yields are expected to increase above the level of CONV.

Consequently, careful farm management stim- ulating structure-forming soil fauna will result in more favourable soil physical properties which lead to improved land qualities supporting crop growth and development. Based on the results obtained, biological structure improvement needs time and 4 years of a changed farm man- agement is not long enough for a new equilibrium.

Acknowledgements

Brieke Steenhof is warmly thanked for her contributions to the soil physical research and O.H. Boersma for his never lacking support when we were carrying out our field work. Mirjam Hack-ten Broeke is also warmly thanked for her support when running the model SWANY.

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