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Effects of agricultural management on Vertosols in Tasmania.

Introduction

Vertosols are clay textured soils with shrink-swell properties that exhibit strong cracking when dry (Isbell 1996). In the northern Midlands of Tasmania, these soils are formed in alluvium on modern floodplains as well as on fan surfaces and valley floors within steeper terrain (Doyle 1993). In south-eastern Tasmania, these soils are formed in alluvium on modern floodplains, on basalt and basaltic colluvium, or on hillslopes derived from dolerite (Holz 1987).

Vertosols in Tasmania have been used for grazing and dryland cropping for many decades. They have been used successfully for dryland cereal production including barley (Hordeum vulgate), wheat (Triticum aestivum), and oats (Avena sativa). Some sites have been irrigated to grow peas (Pisum sativum), brassicas (Brassica oleracea varieties), and poppies (Papaver somniferum).

These soils are imperfectly drained with slow permeability after wetting and crack closure. Vertosols characteristically have a narrow moisture range over which they are suitable for cultivation. Tillage above the plastic limit readily leads to compaction and smearing (Isbell 1997). Vertosols are structurally unstable, tend to slake easily on wetting and are easily compacted. However, they are very resilient and can redevelop a good structure after only a few cycles of wetting and drying (Wenke and Grant 1994). Vertosols in Tasmania are noted for their cloddiness and working difficulty. This has been attributed to heavy stocking when wet, intensive tillage with mouldboard ploughs and powered implements, and shorter fallows than in other parts of Australia (Chilvers 1996). The shorter fallows allow less time for the formation of a natural self-mulched seedbed, and irrigated soils have a lessened opportunity for self-mulching induced by drying. Management guidelines when using these soils for cropping include: cultivate at the friable moisture content, promote surface drainage, avoid wet harvests, avoid stocking when wet, and use the natural tilth with direct drilling of seed rather than cultivating to prepare a seedbed (Chilvers 1996).

Soil degradation has occurred under crop production in Australia because of excessive and inappropriate tillage, and practices such as fallowing and burning of stubble (Hamblin 1991; Chan and Pratley 1998). Tillage breaks up the soil surface, reorganises soil aggregates and porosity, and disturbs macroporosity and beneficial soil fauna. Soil immediately below the cultivated layer can be compacted by heavy machinery and have increased soil strength and density, and reduced porosity and hydraulic conductivity. Hydraulic conductivity, macroporosity, and moisture characteristic of the 0.1-0.2 m layer were found to decrease with increasing time under cultivation on Vertosols in south-eastern Queensland (Connolly et al. 1997). Results reported by So (1990) indicated that surface compaction (0-30 cm), as measured by bulk density and penetration resistance, was a widespread problem on clay soils in southern Queensland. Mechanical tillage was found to decrease bulk density and increase shrinkage potential on a Vertosol in Queensland (McGarry and Smith 1988). Degraded subsoil structure has also been found in Vertosols under both rainfed (Chan et al. 1995) and irrigated farming (McGarry and Chan 1984; McKenzie et al. 1991).

Soil organic matter and fertility commonly decline with cropping on Vertosols (Dalal and Mayer 1986; Skjemstad et al. 1994; Chan 1997; Dalal and Chan 2001). Compared with native pasture sites, cultivated Vertosols in New South Wales have reduced organic matter (up to 40% less), greater pH, less extractable phosphorus (P), and reduced structural stability and biological activity (Chan et al. 1988).

In Tasmania, degradation of a number of properties of Sodosols, Tenosols, Dermosols, and Ferrosols has been associated with cropping intensity, particularly potato production (Sparrow et al. 1999; Cotching et al. 2001, 2002a, 2002b). Negative correlations between organic carbon contents and length of cropping history were also found. No such studies have been conducted on Vertosols in Tasmania.

The objective of this study was to determine differences in soil properties associated with commercial agricultural production on Black Vertosols in the south-east and in the northern Midlands of Tasmania. Vertosols with histories of pasture, rainfed cropping, and irrigated cropping were compared. A wide range of attributes was assessed, which was the approach adopted by Cotching et al. (2001) and Sparrow et al. (1999) in assessing the effects of agricultural management on Sodosols and Ferrosols in Tasmania.

Materials and methods

Site selection

Twenty-one paddocks with haplic, self-mulching, Black Vertosols (Isbell 1996) (Ustic Endoaquerts, Soil Survey Staff 1998) were selected in the south-eastern and northern Midlands districts of Tasmania (Fig. 1 and Table 1). The paddocks had the following management systems: long-term pasture (LTP); rainfed cropping (RC); and irrigated cropping (IC). Each site was selected on the basis of profile morphology to ensure that the soil was black, self-mulching, and uniform to gradational in texture. Sites have been mapped as Canola soils in the northern Midlands (Nicholls 1958; Doyle 1993) and Churchill, Laburnam, Cranston, Basalt 1, and Dolerite soils in south-eastern districts (Holz 1987). LTP paddocks had all been in permanent pasture for at least 7 years prior to sampling. RC paddocks included crops of barley, wheat, oats, and peas. IC paddocks had similar crops to RC plus poppies, pyrethrum, irrigated peas and turf grass, all of which were irrigated when grown in the rotation. These rotations we considered to be representative of practices on these soils. The mean number of years cropped in the last 25 years was significantly less in LTP compared with RC or IC paddocks (1.7, 10.0, and 11.7, respectively, P < 0.001). There was undoubtedly considerable variability in past tillage techniques and timing of operations between sites and so rather than sampling paired sites, we sampled 7 sites in each category.

[FIGURE 1 OMITTED]

Profile description and soil sampling

Sites and soil profiles were described according to McDonald et al. (1990) on 1-m-deep cores of 150 mm diameter taken with a drilling rig. A representative profile description is given in Appendix 1 (other profile descriptions can be obtained from the senior author on request). All data were entered in the Tasmanian Soil Database

Samples were collected in areas away from fencelines, gateways, and headlands. Twenty soil samples were taken at random from an area about 80 by 60 m using a 50-mm-diameter push auger. Samples were combined for each of 2 depths, 0-75 mm and 75-150 mm. These samples were dried at 40[degrees]C, ground to pass a 2-mm sieve, and stored in air-tight containers for further analysis as described below.

A further 10 subsamples of soil from each of the 0-75 mm and 75-150 mm depths were taken at random by spade from the 80 by 60 m sample area and placed in wooden trays to air-dry in preparation for aggregate size and stability measurements (see below).

Chemical tests

The core samples taken by auger were analysed for pH (1:5 [H.sub.2]O), electrical conductivity (EC) (1:5 [H.sub.2]0), extractable P and potassium (K) (Colwell 1963), exchangeable calcium (Ca), magnesium (Mg), sodium (Na), K and aluminium (Al) (Ba[Cl.sub.2]/N[H.sub.4]Cl at pH 7, method 15E1 in Rayment and Higginson 1992), organic C and total nitrogen (method 6B3 in Rayment and Higginson 1992), and permanganate-extractable C (Moody et al. 1997 after Blair et al. 1995). Total exchangeable bases was calculated as the sum of exchangeable Ca, Mg, Na, and K. Carbon fractions from the permanganate determinations were calculated according to Moody et al. (1997), i.e. Fraction 1 (F1) was equal to the C oxidised by 33 mM KMn[O.sub.4] and Fraction 3 (F3) was equal to the C oxidised by 333 mM KMn[O.sub.4].

Biological assessment

Earthworm counts

In August, September, or October 2000, when surface soils were moist, spade squares of soil were excavated to a depth of 200 mm at 15 randomly chosen places at each site. The excavated soil was broken by hand and earthworms extracted and counted.

Seed germination counts

Seed germination counts were conducted on subsamples (100 g) of the surface soil collected for aggregate assessment (Sparrow et al. 1999). Seedlings were counted regularly after emergence, and identified to the species level. This allowed for identification of potential weed species, which may have been associated with particular management histories. We did not count seeds that did not germinate.

Microbial biomass

Subsamples of the air-dried surface soil (0-75 mm) collected for aggregate assessment were re-wet to field capacity with distilled water and incubated for 7 days at 23 [+ or -] 2[degrees]C before microbial biomass was determined by the fumigation-extraction technique of Vance et al. (1987).

Physical tests

Particle size distribution

Clay and silt contents were measured on 50-g subsamples of the samples taken by auger from each transect by the plummet balance method (McIntyre and Loveday 1974) following oxidation of organic matter with hydrogen peroxide. Sand content was calculated by difference.

Aggregate distribution and stability

The air-dry soil from those samples taken by spade was passed through a sample splitter with 40-mm openings. Subsamples of 300-500 g were weighed and placed on a nest of sieves of aperture sizes 9.5, 4.75, 2, 1, 0.5, and 0.25 mm. The sieves were shaken on a mechanical shaker for 10 s and the weight of soil on each sieve after this time was determined. The mean weight diameter (MWD) was calculated as [SIGMA][[mu].sub.i][w.sub.i] where [[mu].sub.i] is the arithmetic mean size for a particular aggregate size range and [w.sub.i] is the proportion of the total sample weight left on the corresponding sieve after sieving (Hillel 1998).

A 200-300 g sample of air-dry whole soil was also sieved under water for 15 min on a nest of sieves of aperture size 4.75, 2, 1, and 0.25 mm after the method of Laffan et al. (1996).

Infiltration

The steady-state infiltration rate under ponded conditions was determined using a disc permeameter placed on either bare soil or clipped pasture depending on the surface cover at the time of testing. The steady-state infiltration rate was found by plotting the cumulative infiltration as a function of time. The slope of this line during the latter stages of the test was the steady-state infiltration rate. Measurements were made at 8 randomly chosen places at each site, and at each place readings were made until flow was steady for at least 10 consecutive readings.

Atterberg limits and linear shrinkage

Liquid and plastic limits were measured on the dried and ground samples from both depths using the Casagrande method (Standards Association of Australia 1991) and the `thread' method (Standards Association of Australia 1995), respectively. Results were expressed on a gravimetric basis. Linear shrinkage was determined as the percentage decrease in length from liquid limit to oven-dry (Standards Association of Australia 1977).

Shear strength and penetrometer resistance

A shear vane with 100-mm blade length was used to estimate soil shear strength at the soil surface and at 100 mm depth. Measurements were made at 10 locations within the sample area at each site. Also at these locations, a recording cone penetrometer (Rimik CP 20) was used to record penetration resistance each 15 mm to a depth of 600 mm. Soils were sampled for moisture content at the same time as the shear vane and penetrometer tests were conducted, as detailed below for water content at field capacity.

Bulk density

Stainless steel cylinders, 75 mm long and 75 mm in diameter, were hammered into the soil at 10 random locations at each site. Cores were collected from 0-75 mm and 75-150 mm depth. Cores with soil intact were excavated and trimmed before being dried at 105[degrees]C, and then weighed.

Water content at field capacity

Soil water tension was recorded by inserting a Quickdraw tensiometer (Soil Moisture Equipment Corporation) to a depth of 100 mm at 3 randomly selected places at each site on 15 September 2000, following winter rainfall and a period of rainfall when 15 mm fell over 6 days, when soil at that depth was anticipated to be at field capacity. Records of rainfall at Cressy Research Station in the northern Midlands show that for the months of June, July, and August prior to sampling, a total of 228 mm rain fell and pan evaporation was 99 mm over the corresponding period. At Jericho, in the south-east, only 94 mm of rain fell and evaporation was 111 mm (Bureau of Meteorology, unpublished data). This was insufficient rainfall to bring soils to field capacity in the south-east in 2000. Soil from 80-120 mm depth was collected, weighed, dried at 105[degrees]C, and re-weighed to determine gravimetric water content. This was converted to a volumetric basis by multiplying by the bulk density as determined above.

Pore space and water retention

Undisturbed soil cores were collected in triplicate from 2 sides of a shallow pit. Stainless steel rings (50 mm diameter by 20 mm deep), with one outer edge bevelled to form a cutting surface, were placed on a shaved soil surface at 3 depths: 50 mm, 100 mm, and 200 mm. The rings were pushed evenly into the soil and the soil cut off a centimetre below the ring. Non-absorbent discs were placed over each end of the core, which was then wrapped in plastic for storage at 4[degrees]C until further testing. Samples were trimmed flush with the ends of the rings prior to placement on filter paper, being wetted by capillarity, and then placed in a pressure plate apparatus (Soil Moisture Equipment Corporation). Moisture contents were measured following successive equilibration at 10 kPa and 100 kPa pressure. Samples were then oven dried at 105[degrees]C to determine dry weight and dry bulk density. Moisture content at 1500 kPa was determined on mixed samples (sieved <2 mm) in a pressure plate apparatus (Soil Moisture Equipment Corporation). The following measures were derived from the soil moisture data (Hillel 1998):

Macroporosity (%vol) = total porosity - (water content at 10 kPa (w/w) x bulk density)

Readily available water (%vol) (RAW) = (water content at 10 kPa (w/w) - water content at 100 kPa (w/w)) x bulk density

Total available water (%vol) (TAW) = (water content at 10 kPa (w/w) - water content at 1500 kPa (w/w)) x bulk density

Particle density

Panicle density was determined by measuring the volume of water displaced by a sample when it was contained in a water-filled bottle of known volume (Blake and Hartge 1986).

Total porosity

Total porosity was calculated from panicle and bulk density as follows:

Total porosity (%vol) = particle density - bulk density/ particle density x 100

Farmer survey

Farmers who managed each site were asked to fill in a scorecard containing 35 questions relating to their perceptions of soil, plant, animal, and water properties for that site (Cotching et al. 2001). For each question farmers scored their soil or site into healthy, impaired, or unhealthy categories and the numbers of answers in each soil health category were counted.

Statistical analyses

All of the data were analysed using residual maximum likelihood (REML) analysis (Steel et al. 1997) plus a Wald statistic for fixed effects because the range of management histories assessed in this study was not equally represented in each district. The REML method splits data into 2 parts:

* treatment contrasts that contain information on the fixed effects (i.e. `Management history' in these data), and

* error contrasts (i.e. all contrasts with zero expectation) that contain information on the random effects (i.e. `Site' in these data).

The purpose of a REML analysis is to:

* study fixed effects, when there are several sources of variability, to determine which, if any, are responsible for significant variation in the response variable, and

* estimate the random effects, and assess the relative importance of those sources of variability in explaining variation in the data.

Management effects were analysed across all sites from both districts in order to give the most reliable analysis with the largest possible data set. Following a significant (P < 0.05) Wald test for fixed effects, mean separation was conducted using least significant differences (P < 0.05). Correlation matrices and linear regressions were calculated for selected data. For the latter, t-tests were used to test for the significance of regression coefficients. Soil profile description data was subjected to chi-square analysis. The residuals from contingency tables of management by response category (e.g. different grades of soil structure) were standardised and examined for departure from independence. The farmer questionnaire response data was subjected to chi-square analysis. A significant chi-square value (P < 0.05) was interpreted as an absence of dependency between management and farmers opinions of the health of their soils. Descriptive statistics for all variables are available on request from the senior author.

Results and discussion

Morphology

A horizons ranged in texture from clay loam to medium heavy clay (Table 1). The Ap horizon was significantly (P < 0.001) thinner in south-eastern Vertosols (12 cm) than in northern Midlands Vertosols (20 cm). The Vertosols in both districts were of alluvial origin, occurring on floodplains, with the source rocks likely to have been dolerite. Differences in clay content may have been due to admixtures of sediments from other source rocks, varying distances from source rocks and location on the floodplain with respect to the energy environment of deposition. We found no significant differences in A horizon thickness between management histories. Differences in A horizon soil structure between LTP and cropped paddocks were visible (Fig. 2). All but one LTP paddock had strongly developed granular structure, whereas cropped paddocks were either massive or had weakly to moderately developed polyhedral, parting to subangnlar blocky or granular structure. LTP paddocks were significantly different to cropped paddocks (P = 0.018). Similar visible differences were found on Tasmanian Ferrosols (Sparrow et al. 1999) and Dermosols (Cotching et al. 2002b) that also had clay loam textured A horizons. No significant differences between management histories were found for moist consistence or numbers of macropores. Good field observations of soil structure have also been found to show meaningful differences between different mechanical treatments of Vertosols in Queensland (McGarry and Smith 1988).

[FIGURE 2 OMITTED]

Chemical tests

Many chemical properties were significantly different between south-eastern and northern Midlands districts (Table 2). The northern Midlands had greater OC, total nitrogen, and carbon fractions F1 and F3, and lesser pH, total bases, and extractable P (75-150 mm). Some of these differences may be due to greater annual rainfall and slightly lower temperatures in the northern Midlands, resulting in more plant biomass being retained in the soil and more leaching. Mean annual rainfall at Cressy in the northern Midlands is 600 mm, compared with 504 mm at Jericho, 549 mm at Sorell, and 562 mm at Cambridge in the south-east, which has a correspondingly shorter growing season (De Rose and Todd 2002). Mean annual temperatures are 11.8[degrees]C at Cressy and 12.0[degrees]C at Cambridge. However, the difference in OC may also have been due to the lesser clay content of south-eastern Vertosols. When the variation in OC (0-75 mm) caused by variation in clay (%) was removed from our analysis, we found that there was no significant difference between districts.

OC levels were similar to those of other clay loam textured topsoils in Tasmania (Sparrow et al. 1999; Cotching et al. 2002b) but much greater than the 0.8-2.2% found in southern Queensland Vertosols (Dalal and Mayer 1986) or the 0.4-1.3% found in New South Wales Vertosols (Chan 1997). Tasmania's lower temperatures could account for greater OC levels than in other States, as organic matter decomposition is slower in temperate than in subtropical regions (Dalal and Chan 2001), but rainfall and length of cropping history may also be important.

We initially found that management history had no significant effect on OC or total nitrogen (P = 0.089 and 0.109, respectively, at 0-75 mm), and we found no significant correlation between the frequency of cropping and OC. However, there was a significant correlation between OC and clay (%) for the south-eastern sites (r = 0.67), and when the variation in OC caused by variation in clay (%) (Christensen and Johnson 1997) was removed for all sites, both RC and IC sites had significantly (P = 0.002) less OC than LTP sites at 0-75 mm (27 and 28% less, respectively) but not at 75-150 mm depth. This agrees with results on Vertosols in southern Queensland (Dalal and Chan 2001; Dalal et. al. 1995) and on other soil types in Tasmania (Sparrow et al. 1999; Cotching et al. 2001) where OC was up to 72 and 40% less, respectively, in cropped paddocks than under long-term pasture. OC on LTP sites is likely to be in equilibrium, where the rate of formation of new OC from organic residues equals the rate of organic matter decomposition (Dalal and Chan 2001). We consider that OC is likely to decrease on cropped sites with increased cropping frequency and we view the lower levels of OC (as low as 2.6% in some northern Midlands paddocks) with concern because many soil attributes that are likely to impact on ease of management and productivity are correlated with OC (Table 3) (Oades and Waters 1991).

IC paddocks had significantly less carbon fraction F1 (south-eastern 31% less, northern Midlands 43% less) than LTP paddocks, and both RC and IC paddocks had significantly less carbon fraction F3 than LTP paddocks in both districts (13-51% less). Although OC was correlated with carbon fractions F1 and F3 (Midlands r = 0.98, Table 3; south-east r = 0.98 and 0.88, respectively), carbon fractions F1 and F3 appear to be more sensitive indicators of change under different management than OC on Tasmanian Vertosols in this study, which is in agreement with Moody et al. (1997) and Sparrow et al. (1999). Carbon fraction F1 and F3 values reported in this study are in a similar range to those reported on clay loam textured Ferrosols and Dermosols (Sparrow et al. 1999; Cotching et al. 2002b), and are greater than those on sandy loam to loam textured Sodosols and Tenosols (Cotching et al. 2001, 2002a).

Total bases were significantly correlated with OC at both sampling depths and in both districts (Table 3 and other data not shown). This confirms the contribution that organic matter makes to cation exchange capacity (Dalal and Chan 2001), even in these soils that are dominated by smectite clays with high charge density.

We found that extractable P and K at 0-75 mm depth were not affected by management history (Table 2), which is consistent with results on other soil types in Tasmania used to grow crops other than potatoes (Cotching et al. 2001, 2002a, 2002b). Significantly greater levels of extractable P and K at 75-150 mm depth at IC sites were probably due to greater fertiliser application under irrigated crops and ploughing under of topdressed surface soil enriched in these fertiliser nutrients. Levels of extractable P on cropped Vertosol paddocks were as great as those in paddocks used for potato growing on other soil types in Tasmania (Sparrow et al. 1999; Cotching et al. 2001, 2002a, 2002b), indicating that high rates of fertiliser have been applied to these Vertosols, even though they are not used for potato growing.

ESP levels of exchangeable sodium at both sampling depths were less than 6% on all but 2 sites and mostly <2%. Consequently no major effects of exchangeable sodium on soil structure were expected.

Biological measures

On the northern Midlands sites microbial biomass C was strongly correlated with macroporosity and TAW, and negatively correlated with cropping frequency (Table 3). We found no such correlations on the south-eastern sites. We found no significant effect of management histories on any of the biological attributes we measured (Table 4). The relatively small sample size in this study may have contributed to this result. However, Table 3 indicates that cropping is having a detrimental effect on microbial biomass C in the northern Midlands (r = -0.83). The decline in biological activity with cropping is consistent with findings on Vertosols under dryland cropping in Queensland (Chan et al. 1988). The lack of effect of management history on worm numbers is in contrast to significant effects found on Ferrosols in Tasmania (Sparrow et al. 1999) but agrees with findings on Sodosols, Tenosols, and Dermosols (Cotching et al. 2001, 2002a, 2002b). Worm numbers at the northern Midlands sites were consistent with numbers reported on other soil types but were less than found at the south-eastern sites. Greater rainfall prior to sampling and greater levels of organic matter in the northern Midlands soils may account for their higher worm numbers. Worm numbers were correlated to pH on the Midlands Vertosols (r = 0.58, Table 3), which agrees with findings on Tasmanian Ferrosols (Sparrow et al. 1999) but not on other Tasmanian soil types (Cotching et al. 2001, 2002a, 2002b).

Physical measures

Many physical properties were significantly different between the south-eastern and northern Midlands districts (Table 5). Northern Midlands paddocks had significantly greater WSA, plastic and liquid limits, total porosity, and total and readily available water storage, and lesser average penetration resistance and linear shrinkage values than southeastern paddocks. Vertosols in the northern Midlands had lesser bulk densities than those in south-east. This was probably due to greater organic matter contents (Table 2) as bulk density was negatively correlated to OC (Midlands r = -0.79, Table 3; south-east r = -0.68 not shown) and organic matter generally reduces the mean density of soils (Hillel 1998). Tillage associated with cropping did not significantly affect bulk density or total porosity at the 2 depths sampled but total porosity was significantly less in IC compared with RC paddocks at 280-300 mm depth (Table 5). This may have been due to subsoil compaction caused by machinery on irrigated wet soil. Some individual bulk density cores had densities as great as 1.3 and 1.5 Mg/[m.sup.3] in the northern Midlands and in south-eastern districts, respectively. Plant root penetration is unlikely to be restricted at such bulk densities on these clay to clay loam textured soils when they are moist, as penetration resistances were < 1800 kPa on all sites at equivalent moisture contents (Figs 3 and 4). There were no other significant differences in porosity or water-holding characteristics between management histories but the northern Midlands Vertosols generally had greater porosities and better water-holding characteristics than the south-eastern Vertosols. We found TAW and RAW to be correlated with OC only on the Midlands Vertosols (r = 0.79 and 0.93, respectively, Table 3).

[FIGURES 3-4 OMITTED]

IC sites had more large aggregates, fewer fine aggregates, and reduced aggregate stabilities compared with other sites in both districts (Table 5), reflecting the impact of machinery and/or tillage on wetter soils, which results in increased cloddiness (Fig. 2). Aggregate stabilities were over 70% in all but the south-eastern IC paddocks (Table 5). Laffan et al. (1996) regarded 70% WSA as indicative of soil with the greatest resistance to breakdown and soil with 30-70% WSA of moderate resistance to breakdown. WSA was correlated with OC on the south-eastern sites (r = 0.72 data not shown) but not on the northern Midlands sites.

Plastic limit was strongly correlated with OC in both districts (south-eastern r = 0.96, northern Midlands r = 0.95). If OC reduces with further cropping, these Vertosols will require longer periods of drying to achieve non-plastic moisture contents, otherwise damage due to traffic and tillage is likely occur (Spoor 1979). Our results for plastic limit and field capacity were obtained on samples from different soil depths and so cannot be compared, but they indicate that these Vertosols are likely to be wetter than the plastic limit in winter and spring due to slow permeability (Isbell 1996). Consequently, tillage in winter and spring is likely to result in smearing and compaction and harvesting equipment on irrigated soils can result in compaction (Chilvers 1996).

Linear shrinkage showed no consistent relationship with management history and was not correlated with number of years cropped. Our values of linear shrinkage (9.8-16.4%) place these soils in the weakly self-mulching category of Grant and Coughlan (1995) and most do not exceed the 12% indicated by Isbell (1996) as being necessary to distinguish soils with vertic properties. Our relatively low linear shrinkage values may be due to the relatively low clay contents of several of the sites because we found a significant correlation between linear shrinkage and clay content (r = 0.048 across all samples). Also, many of the soils sampled in this study had relatively high organic carbon contents, which may have had an influence on the results, even although we found no significant correlation (r = 0.127 across all samples).

RC paddocks had significantly greater infiltration rates than LTP paddocks (Table 5), which we attribute to loosening of the soil surface by tillage as shown by significantly lower shear strength on cropped compared with LTP paddocks. This loosening effect of tillage was significant even although the surface condition of the sites varied between perennial pasture, cereals, peas, and fallow (Table 1). This result is consistent with findings on other Tasmanian soils (Sparrow et al. 1999; Cotching et al. 2001) but is contrary to findings on Vertosols in south-eastern Queensland (Connolly et al. 1997). The beneficial effect of tillage on infiltration rate on cropped sites was not apparent on IC paddocks. We attribute this to the more problematic timing of tillage operations on these paddocks than on drier rainfed sites (Isbell 1997), which can result in smearing and compaction. Although southeastern sites were initially drier than northern Midlands sites, there was no significant difference in infiltration rates between districts. Table 1 shows that sites were at different stages in the tillage cycle, which would have affected shear strength values, but we still found that shear strength was significantly less on cropped sites than LTP sites in the northern Midlands.

Mean penetration resistance showed significant differences between all management histories on the south-eastern Vertosols (Table 5). No significant differences were found for individual depths, but from visual interpretation of penetration resistance profiles (Fig. 3), it appears that the lower mean value in RC compared with LTP paddocks is linked to the loosening effect of tillage. The decrease in penetrometer resistance in IC compared with RC paddocks we attribute to increased subsoil (below 300 mm) moisture in irrigated paddocks resulting in lower penetration resistance, as this is very dependent on soil water content (Cass 1999). This change in subsoil moisture on irrigated sites may have implications for rising groundwater under irrigated cropping on these soils, particularly as ground water is generally within 3 m of the surface in many south-eastern areas of Tasmania (Finnigan 2000). Moisture contents on all northern Midlands sites were wetter than field capacity (data not shown) and so the differences in penetration resistance were more likely to be due to tillage and stock management than to differences in water content. The results in Fig. 4 suggest that the main contribution to the differences in mean penetration resistance (Table 5) came from the surface 120 mm and this was probably due to the loosening effect of tillage in RC and IC paddocks. There was no indication of subsoil compaction in cropped paddocks from penetration resistance results or macroporosity, which was also found to be not significantly different between management histories (Table 5).

Farmers' views

Farmers who managed the sampled paddocks identified a majority of healthy attributes under all management histories (Fig. 5), which we also found on other soils in Tasmania (Sparrow et al. 1999; Cotching et al. 2001, 2002a, 2002b). The level of impaired attributes was similar to that on Tenosols and Dermosols (Cotching et al. 2002a, 2002b) but less than on Sodosols, which are more sensitive to management effects (Cotching et al. 2001). Analysis showed no significant difference in farmer assessment between management histories or between districts. Attributes scored as unhealthy are listed in Table 6. Soil test levels of N, P, and K were identified as unhealthy on some LTP paddocks, which is probably a reflection on the particular sites chosen and their past fertiliser history. The total number of unhealthy attributes, as reported by farmers, was correlated to the number of seeds germinated and negatively correlated to pH only on Midlands Vertosols (Table 3).

[FIGURE 5 OMITTED]

Conclusions

This study shows that at the sites studied, Vertosols in the northern Midlands have many significantly different properties from Vertosols in south-eastern Tasmania. Northern Midlands Vertosols have better physical properties (lesser bulk density and mean penetration resistance, more water-stable aggregates, and greater porosities and water holding capacities), poorer nutrient status (lesser pH, exchangeable bases, and extractable P), and better biological properties (greater OC, carbon fractions F1 and F3, and more worms) than south-eastern Vertosols. Most of these differences we attribute to higher rainfall in the northern Midlands, which gives rise to greater levels of OC and more leaching of soils. Differences in the origin of soil parent materials and cropping history prior to current records may also have contributed.

We found that OC, when adjusted for clay content, was significantly lower in cropped paddocks than under long-term pasture, and because OC was found to be correlated with many physical and chemical soil properties (bulk density, RAW, TAW, pH, TEB, Colwell P, and K), we conclude that rainfed and irrigated cropping puts these Vertosols at greater risk of soil degradation. Although these relationships were not as numerous on Vertosols in south-eastern Tasmania as on Midlands Vertosols, several south-eastern Vertosol soil properties were also correlated with OC (carbon fractions F1 and F3, WSA, bulk density, and plastic limit). We found that nutrient levels in surface layers of cropped paddocks are being maintained rather than increased.

IC paddocks had the greatest MWDs and the greatest proportion of visible clods. Cultivation associated with cropping reduced shear strength and penetration resistance but these benefits were not apparent on irrigated paddocks where smearing and compaction, due to tillage at moisture contents greater than the plastic limit, is more likely to occur. The strong correlation we found between plastic limit and organic C means that declining OC levels associated with cropping will exacerbate the problem of Vertosols having a narrow window of opportunity for tillage at friable moisture contents.

Farmers rated a majority of the soil attributes of soils at all sites as healthy, but strategies for maintaining organic matter levels and minimising clod formation by tillage are essential for long-term sustainable use of these Vertosols.
Appendix 1. Representative profile descriptions

Northern Midlands Region

Grid reference 1: 25000 Delmont Sheet No. 5037: 498946E 5377353N

A1 0-21 cm Moist; black (2.5Y 2/0); clay loam; strongly
 developed fine (5-10 mm) polyhedral plus very
 fine (2-5 mm) granular structure; moderately
 weak (moist); firm penetration resistance; rough
 ped fabric; common fine (1-2 mm) macropores;
 abundant very fine (< 1 mm) live roots; abrupt
 (5-20 mm) smooth boundary
B2 21-54 cm Moist; black (2.5Y 2/0); medium heavy clay:
 strongly developed medium (20-50 mm) prismatic
 structure; moderately firm (moist); stiff
 penetration resistance; smooth ped fabric;
 common distinct dark grey (2.5Y 2/0)
 slickensides coating ped faces; common very fine
 (<1 mm) live roots; clear (20-50 mm) smooth
 boundary
B2g 54-79 cm Moist; olive brown (2.5Y 4/4); medium-heavy clay;
 few fine (<5 mm) distinct dark yellowish brown
 (10YR 3/4) gley mottles; massive; moderately
 firm (moist); very stiff penetration resistance;
 smooth ped fabric; common prominent dark grey
 (10YR 3/1) slickensides coating ped faces; no
 live roots; abrupt (5-20 mm) smooth boundary
Cg 79-95+ cm Moist; dark yellowish brown (10YR 4/6); gritty
 medium clay; Many coarse (>15 mm) distinct grey
 (10YR3/1) gley mottles; massive; very firm
 (moist); very stiff penetration resistance;
 rough ped fabric

South-east Region

Grid reference 1: 25000 Runnymeade Sheet No. 5427: 542975E 5270688N

A1 0-12 cm Moist; black (2.5Y 2/0); medium clay; strongly
 developed very fine (2-mm) granular structure;
 very weak (moist); firm penetration resistance;
 rough ped fabric; abundant very fine (<1 mm)
 live roots; abrupt (5-20 mm) smooth boundary
B21 12-30 cm Moist; black (2.5Y 2/0); heavy clay: massive;
 moderately weak (moist); stiff penetration
 resistance; smooth ped fabric; common faint
 black (2.5Y 2/0) slickensides coating ped faces;
 few fine (1-2 mm) live roots; gradual
 (50-100 mm) smooth boundary
B22 30-85 cm Moist; olive brown (2.5Y2/0); heavy clay; massive;
 moderately weak (moist); stiff penetration
 resistance; rough ped fabric; few very fine
 (<1 mm) live roots; gradual (50-100 mm) smooth
 boundary
C 85-100+ cm Moist; black (2.5Y 2.5/2); heavy clay; massive;
 very firm (moist); very stiff penetration
 resistance; rough ped fabric

Table 1. Site locations and management

Region District Farm Australian map
 grid coordinates

South-east Sorell 1 539079E
 5262845N
South-east Sorell 1 539079E
 5262894N
South-east Richmond 2 534569E
 5274389N
South-east Richmond 3 532612E
 5266453N
South east Tea Tree 4 526871E
 5270033N
South-east Richmond 3 532713E
 5266260N
South-east Sorell 5 542975E
 5270688N
South-east Sorell 6 542949E
 5270301N
South-east Richmond 3 532866E
 5266252N
Northern Poatina 7 498946E
 Midlands 5377353N
Northern Poatina 7 499109E
 Midlands 5377211N
Northern Cressy 8 509249E
 Midlands 5379661N
Northern Cressy 8 509659E
 Midlands 5379955N
Northern Poatina 7 498225E
 Midlands 5377518N
Northern Macquarie 9 5211047E
 Midlands 5369617N
Northern Macquarie 9 521114E
 Midlands 5369641N
Northern Cressy 8 508536E
 Midlands 5378985N
Northern Macquarie 10 515596E
 Midlands 5373117N
Northern Nile 11 526168E
 Midlands 5386322N
Northern Nile 11 526321E
 Midlands 5386261N
Northern Nile 11 526214E
 Midlands 5386132N

Region Management Ground cover when Topsoil field
 sampled texture

South-east LTP Perennial pasture Medium clay
South-east RC Barley Med-heavy clay
South-east IC Barley Medium clay
South-east LTP Perennial pasture Clay loam
South east RC Barley Med-heavy clay
South-east IC Peas Medium clay
South-east LTP Annual ryegrass Medium clay
South-east RC Fallow Medium clay
South-east IC Perennial tuff grass Medium clay
Northern LTP Perennial pasture Clay loam
 Midlands
Northern RC Oat stubble Light clay
 Midlands
Northern IC Annual ryegrass Light clay
 Midlands
Northern LTP Perennial pasture Clay loam
 Midlands
Northern RC Fallow weeds Clay loam
 Midlands
Northern IC Oats + perennial Light clay
 Midlands pasture
Northern LTP Perennial pasture Clay loam
 Midlands
Northern RC Wheat Medium clay
 Midlands
Northern IC Wheat Medium clay
 Midlands
Northern LTP Perennial pasture Medium clay
 Midlands
Northern RC Barley Medium clay
 Midlands
Northern IC Barley Medium clay
 Midlands

LTP, long-term pasture; RC, rain-fed cropping; IC, irrigated cropping

Table 2. Mean values for chemical measures under different management
histories

Management probabilities are analysed across both districts. Within the
rows for each measure, values followed by the same letter are not
significantly different (P > 0.05). Rows with no following letters had
no significant differences between histories. EC, electrical
conductivity; OC, organic carbon

History Depth South-eastern sites
 (mm)
 Long- Rainfed Irrigated
 term cropping cropping
 pasture

[pH.sub.water] 0-75 6.4 6.0 6.5
 75-150 6.2 6.2 6.6
EC (dS/m) 0-75 0.12 0.13 0.11
 75-150 0.11 0.13 0.10
OC (%) 0-75 4.0 4.1 2.6
 75-150 3.3 3.4 2.5
Total nitrogen 0-75 0.30 0.30 0.19
 (%) 75-150 0.24 0.25 0.19
C : N ratio 0-75 13.3 13.6 13.8
 75-150 13.8 13.6 13.5
Carbon fraction
 F1 (mg/g) 0-75 3.6a 3.9ab 2.5b
 75-150 3.0 3.2 2.4
 F3 (mg/g) 0-75 7.4a 6.0b 4.5b
 75-150 5.3 5.1 4.7
Exchangeable
 cations (cmol/kg)
 Ca 0-75 19.3a 13.8b 14.0ab
 75-150 15.4ab 17.8a 14.1ab
 Mg 0-75 13.3a 13.9a 8.3b
 75-150 12.1a 15.2b 8.1c
 K 0-75 0.4 0.6 0.6
 75-150 0.4 0.8 0.7
 Na 0-75 1.0 1.2 0.9
 75-150 0.9 1.2 0.8
 Al 0-75 0.01 0.05 0.01
 75-150 0.02 0.02 0.01
 Total bases 0-75 34.0a 29.6ab 23.8bc
 75-150 28.8ab 35.0a 23.8bc
Extractable P 0-75 53 44 109
 (mg/kg) 75-150 23a 65b 125c
Extractable K 0-75 170 239 229
 (mg/kg) 75-150 146a 136a 278b

History Depth Probability Northern Midlands sites
 (mm) of region
 difference Long- Rainfed
 term cropping
 pasture

[pH.sub.water] 0-75 <0.001 5.6 5.5
 75-150 <0.001 5.7 5.4
EC (dS/m) 0-75 0.776 0.35 0.10
 75-150 0.037 0.27 0.08
OC (%) 0-75 <0.001 7.7 8.0
 75-150 <0.001 5.8 7.1
Total nitrogen 0-75 <0.001 0.64 0.66
 (%) 75-150 <0.001 0.46 0.60
C : N ratio 0-75 <0.001 12.2 12.2
 75-150 <0.001 12.5 11.7
Carbon fraction
 F1 (mg/g) 0-75 <0.001 6.9a 6.2ab
 75-150 <0.001 4.1 4.9
 F3 (mg/g) 0-75 <0.001 15.1a 13.1b
 75-150 <0.001 11.1 11.8
Exchangeable
 cations (cmol/kg)
 Ca 0-75 0.305 15.2a 10.9b
 75-150 0.109 13.9ab 10.3b
 Mg 0-75 <0.001 8.0b 4.8b
 75-150 <0.001 7.8c 4.6d
 K 0-75 0.362 0.6 0.7
 75-150 0.155 0.3 0.4
 Na 0-75 0.002 1.6 0.3
 75-150 0.026 1.7 0.3
 Al 0-75 0.007 0.45 1.62
 75-150 0.032 0.43 2.25
 Total bases 0-75 0.003 25.9abc 18.4c
 75-150 <0.001 24.0bc 17.8c
Extractable P 0-75 0.743 41 84
 (mg/kg) 75-150 0.004 21a 55ab
Extractable K 0-75 0.289 233 292
 (mg/kg) 75-150 0.483 114a 178a

History Depth Northern Management
 (mm) Midlands probability (A)
 sites

 Irrigated
 cropping

[pH.sub.water] 0-75 5.8 0.088
 75-150 5.8 0.059
EC (dS/m) 0-75 0.11 0.817
 75-150 0.09 0.461
OC (%) 0-75 4.6 0.089
 75-150 4.5 0.240
Total nitrogen 0-75 0.41 0.109
 (%) 75-150 0.40 0.224
C : N ratio 0-75 11.6 0.596
 75-150 11.5 0.489
Carbon fraction
 F1 (mg/g) 0-75 3.9b 0.042
 75-150 3.7 0.240
 F3 (mg/g) 0-75 7.4b <0.001
 75-150 8.5 0.543
Exchangeable
 cations (cmol/kg)
 Ca 0-75 16.3ab 0.032
 75-150 16.3ab 0.040
 Mg 0-75 7.5b 0.003
 75-150 7.6c <0.001
 K 0-75 0.7 0.562
 75-150 0.5 0.189
 Na 0-75 0.5 0.130
 75-150 0.5 0.122
 Al 0-75 0.18 0.109
 75-150 0.15 0.329
 Total bases 0-75 25.2bc 0.034
 75-150 25.1b <0.001
Extractable P 0-75 68 0.072
 (mg/kg) 75-150 49ab <0.001
Extractable K 0-75 270 0.540
 (mg/kg) 75-150 221b 0.005

(A) Probabilities associated with Wald statistics from REML analyses,
i.e. the probability that, in the explanatory model for the variable
being analysed (i.e. pH, EC, etc.), the management component = 0.
Where P < 0.05, management is assumed to account for a significant
amount of the variability in the response variable and 1.s.d.
(P = 0.05) is used for mean separation.

Table 3. Correlation matrices for northern Midlands Vertosol
properties, 0-75 mm depth

 Clay% BD PL LL Shrink pH

BD -0.76 1.00
PL 0.37 -0.79 1.00
LL 0.64 -0.87 0.91 1.00
Shrink 0.20 0.20 -0.24 -0.21 1.00
pH -0.59 0.73 -0.84 -0.88 0.33 1.00
TEB -0.36 0.36 -0.12 -0.45 0.29 0.60
Col P 0.54 -0.53 -0.11 0.51 -0.29 -0.47
Col K 0.46 -0.61 0.10 0.58 -0.26 -0.43
Shear -0.20 0.03 0.37 0.24 -0.04 -0.16
WSA -0.40 0.37 0.16 -0.27 0.12 0.09
Inf 0.23 0.06 -0.40 -0.33 0.58 0.33
Tpo 0.70 -0.86 0.75 0.77 -0.25 -0.78
Mpo 0.20 -0.19 0.01 0.03 -0.51 -0.33
TAW 0.51 -0.85 0.83 0.87 -0.12 -0.64
RAW 0.61 -0.81 0.90 0.92 -0.38 -0.78
MWD -0.25 0.48 -0.36 -0.30 0.71 0.37
Wms -0.47 0.24 -0.32 -0.57 -0.18 0.58
Seeds 0.72 -0.76 0.64 0.65 0.04 -0.52
OC 0.51 -0.79 0.95 0.94 -0.46 -0.87
F1 0.51 -0.82 0.95 0.94 -0.47 -0.84
F3 0.40 -0.73 0.91 0.90 -0.56 -0.85
BioC 0.21 -0.48 0.56 0.55 0.28 -0.33
YC -0.01 0.39 -0.39 -0.48 0.09 0.25
Healthy -0.67 0.40 -0.18 -0.31 -0.27 0.31

 TEB Col P Col K Shear WSA Inf

BD
PL
LL
Shrink
pH
TEB 1.00
Col P -0.61 1.00
Col K -0.47 0.83 1.00
Shear 0.31 -0.48 -0.32 1.00
WSA 0.13 -0.80 -0.65 0.59 1.00
Inf -0.14 0.01 -0.11 -0.52 -0.02 1.00
Tpo -0.55 0.56 0.60 -0.28 -0.33 -0.09
Mpo -0.40 0.50 0.28 -0.56 -0.33 -0.11
TAW -0.28 0.24 0.50 0.20 -0.15 -0.21
RAW -0.46 0.57 0.55 0.18 -0.38 -0.39
MWD 0.14 -0.21 -0.15 -0.16 0.03 0.36
Wms 0.31 -0.24 -0.22 -0.25 0.14 0.34
Seeds -0.22 0.11 0.26 0.11 0.01 -0.01
OC -0.59 0.58 0.64 0.21 -0.27 -0.45
F1 -0.46 0.48 0.58 0.31 -0.22 -0.51
F3 -0.51 0.46 0.54 0.36 -0.13 -0.55
BioC -0.02 -0.18 0.21 0.49 0.30 0.00
YC -0.02 0.11 -0.22 -0.68 -0.33 0.18
Healthy -0.11 -0.28 -0.28 0.21 0.41 -0.15

 Tpo Mpo TAW RAW MWD Wms

BD
PL
LL
Shrink
pH
TEB
Col P
Col K
Shear
WSA
Inf
Tpo 1.00
Mpo 0.51 1.00
TAW 0.73 -0.17 1.00
RAW 0.73 0.15 0.79 1.00
MWD -0.37 -0.46 -0.21 -0.44 1.00
Wms -0.28 0.15 -0.34 -0.49 -0.15 1.00
Seeds 0.73 0.02 0.79 0.68 -0.34 -0.29
OC 0.73 0.16 0.79 0.93 -0.44 -0.53
F1 0.72 0.11 0.83 0.94 -0.52 -0.49
F3 0.65 0.12 0.75 0.89 -0.53 -0.47
BioC 0.25 -0.60 0.73 0.30 0.12 -0.24
YC -0.02 0.58 -0.58 -0.33 0.17 0.04
Healthy -0.34 -0.03 -0.24 -0.19 -0.07 0.40

 Seeds OC F1 F3 BioC YC Healthy

BD
PL
LL
Shrink
pH
TEB
Col P
Col K
Shear
WSA
Inf
Tpo
Mpo
TAW
RAW
MWD
Wms
Seeds 1.00
OC 0.55 1.00
F1 0.63 0.98 1.00
F3 0.52 0.98 0.98 1.00
BioC 0.47 0.41 0.45 0.42 1.00
YC -0.26 -0.44 -0.50 -0.53 -0.83 1.00
Healthy -0.30 -0.13 -0.17 -0.08 -0.09 -0.09 1.00

BD, bulk density; PL, plastic limit; LL, liquid limit; shrink, linear
shrinkage; TEB, total exchangeable bases; ColP, Colwell extractable P;
ColK, Colwell extractable K; shear, shearvane 0-100 mm; WSA,
water-stable aggregates; Inf, infiltration; Tpo, total porosity; Mpo,
macroporosity; TAW, total available water; RAW, readily available water;
MWD, mean weight diameter of dry soil aggregates; Wms, total worms;
Seeds, seeds germinating; OC, organic carbon; F1, carbon fraction F1;
F3, carbon fraction F3; BioC, microbial biomass carbon; YC, years
cropped in last 25; Healthy, number of questionnaire responses
`healthy'; where P < 0.05, r > 0.57 (values in bold type)

Table 4. Mean values for biological measures under different management
histories

Management probabilities are analysed across both districts. Within a
row, values followed by the same letter are not significantly different
at P = 0.05. Rows with no following letters had no significant
differences

History South-eastern sites Probability
 of region
 Long- Rainfed Irrigated difference
 term cropping cropping
 pasture

Microbial 176 175 87 0.067
 biomass C
 (mg/kg)
Total worms 55 30 21 0.007
 (per [m.sup.2])
Seed 9 19 7 0.036
 germination
 (counts/tray)

History Northern Midlands sites Management
 probability (A)
 Long- Rainfed Irrigated
 term cropping cropping
 pasture

Microbial 248 201 166 0.086
 biomass C
 (mg/kg)
Total worms 113 114 141 0.726
 (per [m.sup.2])
Seed 51 58 7 0.150
 germination
 (counts/tray)

(A) Probabilities associated with Wald statistics from REML analyses,
i.e. the probability that, in the explanatory model for the variable
being analysed (i.e. adult worms, juvenile worms, etc.), the management
component = 0. Where P < 0.05, management is assumed to account for a
significant amount of the variability in the response variable and
1.s.d. (P = 0.05) is used for mean separation.

Table 5. Mean values for physical measures under different management
histories

Management probabilities are analysed across both districts. Within a
row, values followed by the same letter are not significantly different
(P > 0.05). Rows with no following letters had no significant
differences. MWD, mean weight diameter; WSA, water-stable aggregates

History Depth South-eastern districts
 (mm)
 Long- Rainfed Irrigated
 term cropping cropping
 pasture

Clay (%) 50-70 42ab 63a 37b
Silt (%) 50-70 17ab 23a 13b
Bulk density 0-75 0.98 0.92 1.06
 (Mg/[m.sup.3]) 75-150 1.07 1.06 1.22
Dry agg. MWD 0-75 11.1a 15.1ab 16.6b
 (mm) 75-150 12.7a 18.8b 17.1b
Dry agg. >9.5 0-75 36a 54ab 61b
 mm (%) 75-150 42a 70b 63a
Dry agg. 1-2mm 0-75 11a 9ab 4b
 (%) 75-150 9a 3b 5b
WSA (%) 0-75 78.5ab 77.5ab 48.4c
 75-150 78.8a 79.2a 58.3b
Plastic limit (%) 0-75 29.6 31.1 20.9
Liquid limit (%) 0-75 47.2 59.6 36.4
Linear shrinkage 0-75 11.4a 16.4b 10.5a
 (%)
Infiltration 1098a 1950b 837ab
 (mm/h)
Vane shear 0-100 n.r. n.r. n.r.
 strength (kN) 100-200 n.r. n.r. n.r.
Mean penetration 0-600 1955a 1805b 1375c
 resistance (kPa)
Total porosity 50-70 48.4 56.1 47.5
 (%) 100-120 46.6 50.2 44.7
 280-300 46.3ab 49.0a 41.1b
Macroporosity 50-70 13.1 12.5 10.8
 (%) 100-120 9.9 4.5 7.0
 280-300 2.0 0.2 0.0
Total available 50-70 18.6 21.4 22.8
 water (%) 100-120 17.7 20.7 22.1
 280-300 22.4 22.2 21.2
Readily available 50-70 3.8 3.7 4.7
 water (%) 100-120 2.3 2.4 4.0
 280-300 3.0 2.6 2.9
Field capacity 100-120 n.r. n.r. n.r.
 (v/v%)
Tension at field 100-120 n.r. n.r. n.r.
 capacity (kPa)

History Depth Probability Northern Midlands
 (mm) of region districts
 difference
 Long- Rainfed
 term cropping
 pasture

Clay (%) 50-70 0.243 52ab 64a
Silt (%) 50-70 0.005 18a 22ab
Bulk density 0-75 0.010 0.82 0.78
 (Mg/[m.sup.3]) 75-150 0.002 1.00 0.86
Dry agg. MWD 0-75 0.173 11.0a 11.7ab
 (mm) 75-150 <0.001 10.9a 13.5b
Dry agg. >9.5 0-75 0.161 36a 39ab
 mm (%) 75-150 <0.001 34a 48b
Dry agg. 1-2mm 0-75 0.134 11a 12ab
 (%) 75-150 <0.001 12a 9b
WSA (%) 0-75 <0.001 85.3a 78.9ab
 75-150 <0.001 85.7a 82.4a
Plastic limit (%) 0-75 <0.001 53.6 42.4
Liquid limit (%) 0-75 <0.001 77.3 75.5
Linear shrinkage 0-75 0.002 9.8a 10.2a
 (%)
Infiltration 0.520 584a 2795b
 (mm/h)
Vane shear 0-100 -- 67.2a 26.8b
 strength (kN) 100-200 -- 70.3a 52.7ab
Mean penetration 0-600 <0.001 1148d 984e
 resistance (kPa)
Total porosity 50-70 <0.001 57.8 63.3
 (%) 100-120 <0.001 55.9 60.9
 280-300 <0.001 49.8ab 57.8a
Macroporosity 50-70 0.794 8.9 14.1
 (%) 100-120 0.092 12.7 10.0
 280-300 0.039 4.9 4.8
Total available 50-70 <0.001 36.1 34.3
 water (%) 100-120 <0.001 28.0 34.4
 280-300 <0.001 22.6 30.9
Readily available 50-70 0.019 6.6 7.0
 water (%) 100-120 0.004 6.9 7.0
 280-300 0.051 3.1 4.0
Field capacity 100-120 -- 45.6 46.8
 (v/v%)
Tension at field 100-120 -- 4 5
 capacity (kPa)

History Depth Northern Management
 (mm) Midlands probability (A)
 districts

 Irrigated
 cropping

Clay (%) 50-70 50b 0.029
Silt (%) 50-70 25a 0.034
Bulk density 0-75 0.91 0.212
 (Mg/[m.sup.3]) 75-150 0.92 0.284
Dry agg. MWD 0-75 14.4b 0.038
 (mm) 75-150 14.6b 0.009
Dry agg. >9.5 0-75 51b 0.034
 mm (%) 75-150 51a 0.003
Dry agg. 1-2mm 0-75 8b 0.050
 (%) 75-150 8b 0.045
WSA (%) 0-75 74.9b 0.001
 75-150 82.6a 0.019
Plastic limit (%) 0-75 41.6 0.107
Liquid limit (%) 0-75 60.5 0.097
Linear shrinkage 0-75 10.3a 0.028
 (%)
Infiltration 1525ab 0.031
 (mm/h)
Vane shear 0-100 22.0b <0.001
 strength (kN) 100-200 47.8b 0.041
Mean penetration 0-600 1003e <0.001
 resistance (kPa)
Total porosity 50-70 59.4 0.119
 (%) 100-120 56.7 0.076
 280-300 52.5b 0.016
Macroporosity 50-70 15.4 0.350
 (%) 100-120 11.1 0.517
 280-300 0.9 0.148
Total available 50-70 28.8 0.357
 water (%) 100-120 30.1 0.332
 280-300 28.4 0.429
Readily available 50-70 4.8 0.731
 water (%) 100-120 4.1 0.175
 280-300 3.1 0.321
Field capacity 100-120 41.0 0.489
 (v/v%)
Tension at field 100-120 5 0.713
 capacity (kPa)

n.r., No result.

(A) Probabilities associated with Wald statistics from REML analyses,
i.e. the probability that, in the explanatory model for the variable
being analysed (i.e. infiltration, vane shear strength, etc.), the
management component = 0. Where the probability <0.05, management is
assumed to account for a significant amount of the variability in the
response variable and 1.s.d. (P = 0.05) is used for mean separation.

Table 6. Attributes which farmers scored as unhealthy

Attributes receiving multiple responses are above the dashed line and
those receiving a response from only one farmer are listed below the
line

Long-term pasture Rainfed cropping Irrigated
 cropping

Soil test levels of N, P, & K Aeration Earthworms
 Organic matter
 Hardness

Earthworms Earthworms compaction Aeration
Decomposition of residues Topsoil pH Tillage ease
Topsoil pH Drainage Topsoil pH
General fertility
Drainage
Declining yields


Acknowledgments

We sincerely thank those farmers who allowed us to sample their soils. Financial support was provided by the National Landcare Program of the Natural Heritage Trust. Richard Doyle from the University of Tasmania provided the shear vane. Phil Moody from the Department of Natural Resources, Queensland, organised the tests of microbial biomass, organic carbon, and total nitrogen. Simon Lynch (DPIWE) provided Fig. 1.

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Manuscript received 13 February 2002, accepted 8 July 2002

W. E. Cotching (A), J. Cooper (B), L. A. Sparrow (C), B. E. McCorkell (D), W. Rowley (C), and K. Hawkins (B)

(A) Department of Primary Industries, Water and Environment, PO Box 303, Devonport, Tas. 7310, Australia.

(B) Department of Primary Industries, Water and Environment, PO Box 46, Kings Meadows, Tas. 7249, Australia.

(C) Tasmanian Institute of Agricultural Research, PO Box 46, Kings Meadows, Tas. 7249, Australia.

(D) Department of Primary Industries, Water and Environment, PO Box 44A, Hobart, Tas. 7001, Australia.
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Author:Cotching, W.E.; Cooper, J.; Sparrow, L.A.; McCorkell, B.E.; Rowley, W.; Hawkins, K.
Publication:Australian Journal of Soil Research
Geographic Code:8AUTA
Date:Dec 15, 2002
Words:10544
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