Towards a minimum data set to assess soil organic matter quality in agricultural soils

Towards a minimum data set to assess soil organic matter quality in agricultural soils E. G. Gregorich', M.R.Carter2, D. A. Angers3, C. M. Monreall, and B. H' Ellerta

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lQttawa, Ontario, Can-ada KIA 0C6; Agriculture and Agri-Food Canada, Research Branch, ,Cinirtoielown, prin-ce Edward lsland, Canada ClA 7M8;3ste. Foy, Quebec, Canada GlV 2J3; and oLethbridge, Atberta, canadaTlJ 481. Received 9 November 1993, acCepted 6 July 1994. to Gregorich, E. G, Carter, M. R., Angers, D. A., Monreal, C. M. and Ellert, B. H. 1994. Towards a minimum data set measure quality is a composite Soil 74 367-385. Sci. J. Soil Can. asseis soil organic matter quatity ii agricultural soils. minimum of both a soil's ability to funct-ion and how welt it functions, relative to a specific use. Soil quality can beassessed using a has matter organic Soit depth. rooting and pH, bulk density, matter, data set comprisingioil attributes such as texture, organic particular significa-nce for soil quality as it can influenie many different soil properties including other attributes of the minimum may be so data set. Asiessment of soil organii matter is a valuable step towards identifying the overall quality of a soil and informative as to be included in minimum data sets used to evaluate the world's soils. In this review, soil organic matter is considered to encompass a set of attributes rather than being a single entity. Included (particulate) among the attributes and discussed here are total soil organiciarbon and nitrogen, light fraction and macroorganic involved are These attributes enzymes. and carbohydrates soil biomass, mattei, mineralizable carbon and nitrogen, microbial in various soil processes, such as those related to nutrient storage, biological activity, and soil structure, and can be used to establish different minimum data sets for the evaluation of soil organic matter quality.

Key words: Biological activity, minimum data set, nutrient storage, soil organic matter, soil quality, soil structure Gregorich, E. G., Carter, M. R., Angers, D. A., Monreal, C. M. et Ellert, B. H. 1994. Vers l'dtablissement d'un bloc de doni6es de base pour l'6valuation de-la qualitd de la matiEre organique dans les sols agricoles. Can. J. Soil Sci. 74: 367-385. La qualit6 du sol est une mesure synth6tique, ir Ia fois de I'aptitudJdu sol i fonctionner et de son efficacitd relative de fonctionneembrassant des propri6t6s comme -"n1 pour. un usage donn6. Elleieut etie 6valu6e d partii d'un bloc de donn6es minimum La matiEre organique du sol la rhizosphdre. de profondeur la et apparente pH, Ia densit6 la texiure, la matiEre organique, ie y compris rev6t un r6le particulier dans ia qualil6 du sol, en celi qu'elle peut influer sur de nombreuses autres propri6t6s du sol, importante une 6tape est organique la matibre de L'dvaluation minimum. donndes d,autres 6l6ments contenus dans le bloc de

les blocs de donndes dans la caract6risation de la qualit6 globale du sol. Elle peut m6me 6tre assez instructive pour 6tre inclue dans

par qualitd minimums utilis6s pour 6valuer toui les sols de Ia planite. Dans la pr6sente mise au point bibliographique, on entend de la matidre o.guniqu" du sol les r6sultats d'un ensemble de propri6t6s, plut6t qu'un concept unique. Parmi les nombreuses (macroqualit6s de la malibre organique, nous avons retenu ici le carbone et I'azote totaux, la fraction l6gdre et les matidres solides organiques), Ie carbonJet I'azote min6ralisables, la biomasse microbienne, les hydrates de carbone du.sol et les enzymes. Ces pr6pri6t6s interviennent dans divers processus 6daphiques comme le stockage des 6l6ments nutritifs, I'activit6 biologique et la it^itu.e du sol. Elles peuvent ctre uiilis6es pour l;etablissement de blocs de donn6es minimums pour I'6valuation de la qualit6 de la matidre organique du sol.

Mots cl6s: Activit6 biologique, bloc de donn6es minimum, stockage des 6l6ments nutritifs, matidre organique du sol, qualit6 du sol, structure du sol soil formation factors (e.g., parent material and topography), and also to changes related to human use and management (dynamic soil quality) (Pierce and Larson 1993).

Maintaining or enhancing soil quality is a key factor in sustaining the soil resources of the world. High quality soils will not only be better producers of food and fibre for the world's growing population, but will also play a major role

The concept of sustainability implies a passage of time.

Over time a soil may be sustained in its ability to function as a viable component of an ecosystem and/or to produce crops, it may be degraded, or it may be improved or

in stabilizing natural ecosystems and in enhancing air and water quality. Soil quality can be briefly defined as the degree of htness ofa soil for a specific use. Broader definitions describe soil quality as the sustained capability of a soil to accept, store, and recycle water, nutrients, and energy (Anderson and

aggraded. The success of soil conservation efforts and management to maintain soil quality depends on an understanding ofhow soils respond to agricultural use and practice over time. To be useful to these practices, methods to quantify soil quality must assess changes in selected soil attributes over a prescribed period of time, in order to be useful in determining best management strategies. Present approaches to quantify soil quality are concerned

Gregorich 1983). In addition to this, soil quality also addresses the capacity of a soil to retain, disperse and transform chemical and/or biological materials and thus

function as an environmental filter or buffer. The quality of any soil depends in part on the soil's natural or inherent composition (inherent soil qualiry), which is a function of

,U,

with either characterization of different facets or attributes

368

CANADIAN JOURNAL OF SO't SC'ENCE

ofquality (i.e. descriptive approach), or are concerned with the identifrcation of specific indicators or parameters that will assess the ability or capacity of an attribute to function in

a desired manner (i.e. indicative approach). The

latter

approach involves the idea of characterizing a soils' health (Doran and Parkin 1994). Quantif,,ing soil quality requires that a minimum data set be defined, comprisins measures

of

various soil attributes or critical properiies (,.key indicators", Larson and Pierce 1991). Tochiracterize how

that are subject to relatively rapid turnover or are involved with biochemical and/or organo-mineral reactions. These properties also have a functional role in soil and thus may provide information relating to the magnitude of that function in nutrient storage, biological activity and soil structure. For each property the rationale for its use as an indicator and methods for its measurement are provided, along with ways the property can be used to assess changes in soil organic matter quality.

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soil quality changes over relatively short time periods, these

critical properties must be sensitive to chinges in soil management, soil perturbations, and inputs into the soil

ORGANIC MATTER ATTRIBUTES

system. Furthermore it is necessary that each critical property be easily measured, and the measurements be reproduCiUte.

Soil Organic Carbon and Nitrogen Soil organic matter comprises a range of humified

In many

cases the critical property will not be measured directly but by use of an index (an associative property) or

by use of pedotransfer functions that emDloy a related prop€rty (Bouma 1989). Most measures of changes in soil quality are comparative and made with reference to a baseline level. The baseline level may be a different treatment or management, such as the virgin state (e.g., cultivated vs. uncultivated grassland), or it may be a threshold value. Soil organic matter is a key attribute of soil qualiff (Larson and Pierce

source

l99l:

Doran and parkin

lgg4l.ltis the primary of, and a temporary sink for, plant nutrients in

agroecosystems and is important in maintaining soil tilth,

aiding the infiltration of air and water, promotins water

retention, reducing erosion. and controlling the effic"acy and fate of applied pesticides. Assessment of sJil orcanrc marrer is therefore a valuable step towards identiffing"the overall quality of a soil and may be so informative as to be included universally in minimum data sets used to evaluate the soils of the world. Organic matter itself can be characteri zed by measuring several different components which are involved with various soil processes, often in an irrdependent manner. Thus, the multi-faceted role of soil organii matter must be taken into consideration in the assessment of qualitv. This will require the identification of separate minimum data sets to characterize organic matter for the followine functions: soil structure. nutrient storage. and biological a-ctivity. The choice ofattributes for each data set would be based on their

sensitivity

to the specific function and the provision of

available methodology, including ease of dupiication, and facility for accuracy and speed. Recent work in Canada has focused on developing a general framework for evaluating soil quality (Acton ind Padbury 1993) and changes in soil orginic matter under Canadian climate and soil condirions. This review highlights Canadian research on soil organic matter. The objectivei of this review were (l) to outline key attributes which can be used to evaluate soil organic matter quality and (2) to discuss minimum data sets of attributes to quantiff the essential roles

of organic matter in soil. The following properties

are

discussed: soil organic carbon (C) and nitrbgen (N), the light fraction of the soil and macroorganic malter. minera_ lizable C and N. microbial biomass, cirbohydrates. and soil enzymes. Soil organic C and N contents provide a measurement of a soil's total inventory of organii matter, while the remaining properties reflect forms of labile orsanic matter

and

biologically active compounds, including readily decomposable material, plant litter and roots, and dead and living

organisms. The chemically well-defined non-humic substances that contribute to the organic C and N contents in soil consist of low molecular weight aliphatic and aromatic acids, carbohydrates, amino acids, and their polymeric derivatives such as polypeptides, proteins, polysaccharides,

and waxes (Schnitzer 1991). These compounds have a relatively rapid turnover in soil and are used readily as substrates by soil microorganisms. Humic substances make up a significant portion of the total organic C and N in soil (Anderson 1979). They consist of complex polymeric organic compounds with high molecular weight and are intimately associated with soil inorganic constituents. The complex chemical structure of humic substances makes them more resistant to decomposition than the non-humic materials. The methods used to estimate organic C and N are well established and have been used extensively in soil organic matter research. Most humic substances are about 50-58% organic C, which is usually determined by either wet or dry oxidation methods (Tiessen and Moir 1993). In the most commonly used wet oxidation method, organic C is oxidized by potassium dichromate in the presence of sulphuric acid with external heating (Nelson and Sommers 1982). In dry oxidation (combustion) methods, organic C is converted to CO2 by burning the organic matter in air or 02 in a furnace. The evolved CO2 can be measured by (i) titrating the CO2 adsorbed in NaOH with acid, (ii) by thermal conductivity, or (iii) by infrared adsorption meaiurement techniques. Two methods that have been used for over 150 yr for the determination of total N are the Kjehldahl method (a wet-oxidation procedure) and the Dumas method (a drycombustion method) (Bremer and Mulvaney 1982' McGill and Figueiredo 1993). Recently near-infrared reflectance spectroscopic techniques have been used to estimate total C and N in soils (Dalal and Henry 1986; Morra et al. l99l). Organic C and N contents in soil are a result of a complex biochemical interaction between substrate additions of C and N in fertilizers and in plant and animal residues, and losses of C and N through microbial decomposition and mineralization and erosion. Changes in inputs, such as fertilizers and residues (Janzen l987a,b; Campbell et al. 1991a), which

regulate soil microbial activity and mineralization rates, will ultimately be reflected in the total organic C and N content of soil. Moisture and, probably to a greater degree,

GREGOR'CH ET AL.

-

ASSESSMENT OF

temperature are the factors most strongly influencing mineralization rates in soil (Stanford et al. 1973; Stanford and Epstein I9741' Campbell et al. l98l). The relative impact

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of management practices on soil organic C and N levels will change with soil climate. Changes in soil quality are usually assessed by comparing the organic matter parameters between sites subjected to specific agricultural practices and reference sites (Table 1). Comparisons of total organic C and N, for example, have been made between native soil and cultivated soils (Tiessen et al. 1982). as well as between soils under different crop rotations, fertilization regimes, and tillage treatments (Carter and Rennie 1982; Campbell et al. 1986, 199lb). The amount

of organic matter in soil has been compared at different scales; at the landscape (Voroney et

al. 1981; Gregorich

and

Anderson 1985), field plot (Campbell et al. 1991b)' and particle size (Tiessen and Stewart 1983; Gregorich et al. 1989) levels. To accurately assess the effects of land use or management practices on total organic C and N, the thicknesses and bulk densities of the soil layers in the freld must be considered. Because comparisons of changes induced by management practices may be hampered by the changes in the massei of soils under consideration, comparisons are usually based on mass per unit area. Comparisons of the masses of total organic C and N in the A horizon, solum, or on an equivalent mass basis can be made (Ellert and Bettany 1995). The assessment of organic C and N as indicators of soil quality should also include consideration of inherent soil properties and site-specific processes. For example, texture plays an important role in determining the amount of organic matter that may be stabilized in soil. Soils with relatively high clay contents tend to stabilize and retain more organic matter than those with low clay contents (Jenkinson 1977; Ladd et al. 1990). Removal of organic-rich topsoil by erosion is a process that influences the level of organic matter in soil (Voioney et al. 1981; Gregorich and Anderson 1985). Soil redistribution by tillage and water and/or wind erosion can have a major impact on the total amount of soil organic C and N (de Jong and Kachanoski 1988). Therefore estimates of soil erosion and deposition may be required when assessing changes in soil organic matter quality, particularly when comparing land use and management practices that affect the relative area of soil covered by residues' The amount and rate of change in total organic C and N may depend more on the initial levels of these elements Table 1. Total organic C and N along native grassland and cultivated toposequences (from Gregorich and Anderson 1985)

position

A

A horizon

horizon

Mid

44 o4

Lower

95

Upper

Cultivated

Native

Slope

Organic C 1Mg ha-t) .,4 '79

r60 193

Organic N (Mg

Mid

3.4 5.8

Lower

v.5

Upper

61 103

Solum

)6 95

235

ha-t)

6.5

2-.J

13.6 18.5

6.2 9.1

2.5 8.5 20.5

SO't ORGAN//C

MATTER

IN AGRICIJLTURAL

SO'IS

369

than on the treatment or management practlce lmposeo on the soil. Campbell et al. (199la'b) suggested that one reason the effects of fertilization and cultural practices on changes in soil organic C and N in nvo long-teffn crop rotation studies conducted on Chernozemic Black soils over 30 yr were different was because the initial levels of organic matter were different. Thus, soils with relatively high initial levels of organic matter may be less likely to reflect any-perturbations, an-d rnuy require prolonged and intense perturbation to show significant degradation compared to soils with initially lower organic matter contents. itt" C,N ratio may also provide information on the capacity of the soil to store and recycle energy and nutrients ' In agriiultural soils the C:N ratio is relatively constant and is usluatty within a narrow range, from 10 to 12. Jenny (1941) observed that under similar conditions of moisture, the C:N ratio of grassland soils decreases as the mean annual temperature increases, probably as the result of more intensive decomposition of organic matter at higher temperatures' Agriculturil practices such as cultivation, fertilization and ."iidu" management influence the soil C:N ratio' Several studies have sfiown that the C:N ratio becomes narrower with cultivation (Voroney et al. 1981; Campbell and Souster 1982; Bowman et al. 1990). Liang and MacKenzie (1992) reported

that the C:N ratio increased within 3 yr in soils under continuous corn receiving high levels of N fertilizer'

Rasmussen et al. (1980) found that long-term changes in soil C:N ratios were proportional to the rate of N loss; C:N ratios were highest in ioili in which wheat straw was burned and lowest in soils receiving manure or pea vines' They suggested that the residue treatments influenced the C:N ratio because

the turnover of C was delayed by a deficiency of available

N for microbial decomPosition'

Light Fraction and Macroorganic Matter

tigirt fraction and macroorganic matter are mainly plant residuis; however, residues derived from animals and microorganisms may also be present in various stages of decomposition. These pools are significant to soil organic matter turnover in agricultural soils because they serve as a readily decomposable substrate for soil microorganisms and as a short-term reservoir ofplant nutrients. A large portion of the microbial population and enzyme activity in soil is associated with the light fraction (Kanazawa and Filip 1986)' and soil respiration rates are correlated with the light fraction

fhi

content (Janzen et al. 1992). The density and sieving methods used for the physical separation of this fraction of organic matter are straightfoiward, reliable, and reproducible (Gregorich and Ellert 1993). The sieving procedures used to isolate macroorganic matter are the same as those used in particle-size analysis, except that pretreatments for removing organic matter, carbonates, and iron oxides are eliminated' One concern during the wet-sieving step is the possible disintegration of fragilE organic fragments ind subsequent lower recovery of macroorganic matter. The light fraction is isolated from the mineral part of soils bv suspe-nding the soil in a dense liquid (usually between 1'5 una Z.b g cm-3) and leaving the heavy fraction to settle to

370

CANADIAN JOURNAL OF SO't SC'ENCE

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the bottom while the light fraction floats to the surface. A variety of heavy liquids have been used in densimetric

fractionation procedures, including bromoform (Greenland and Ford 1964), carbon tetrachloride (Scheffer lgjl\. and tetrabromomethane/benzene (McKeague l97l). Use of inor_ ganic media, such as NaI, in density separation techniques obviates the problems with toxicity, caibon contamination, and coagulation of suspended particles associated with the use of organic solvents. Light fraction organic matter contains most of the macro_ organic matter, which is that organic matter associated with the sand-sized fraction (50-2000 pm), but the light fraction is also present in all particle-size fractions (Turchenek and

Oades 1979). Thus, the light fraction and macroorganic matter may not be identical because the organic matter adhering to sand grains has a different chemicafcomoosition from that not associated with sand grains (Zhang et l. teSS;. Fllert and Gregorich (1994) reporred that the iwo fractions from 20 soils differed in several iespects (Table 2). Gregorich et al. (1995) observed large (differences between the 6l3C of the light fraction and the macroorganic matter from a soil under maize (Zea mays L.) for 25 yr. The light fraction usually represents 0.1-4% of the total weight of cultivated topsoils but has up to 15 times more C and l0 times more N than the whole soii (Greenland and Ford

l)64; Dalal and Mayer 1986, 1987; Janzen et al. 1gg2). Chemical characterization of the light fraction has indicated that it is in an intermediate state of decomposition between fresh plant tissue and soil organic matter. ine C,N ratio of the light fraction is usually wider than that of the whole soil (Greenland and Ford 1964) and ofthe particle-size fractions, reflecting the dominant influence of plant material on this pool of organic matter. Compared to plant tissue, the light fraction has a relatively narrow C:N ratio (Molloy etil. 1977) and high ash (Malone and Swartout 1969; Spycher et al. 1983), "ontent suggesting that it has undergone some

decomposition and/or humifi cation.

The light fraction and macroorganic matter provide information on the extent to which plint residues have been processed by the decomposer community in soils. These fractions are generally free of mineral particles and therefore lack the protection from decomposition that

such

particles imparr. Thus the light fraction (Sollins et al. l9g4; Bonde et al. 1992) and macroorganic matter (Christensen 1987; Gregorich et al. 1989) have been shown to decompose quickly compared with organic matter in whole soil or Table

2. Comparison

between the mean compositions of macroorganic

MacroorganicMatter Lightfraction Mean 95Vo Clz Mean 95% Cl

% soil mass in fraction 33.1 % soll C in fraction 20.8 C enrichmenty O.73 Ash concentration (%) 93.6

C/N of

fraction

silt fraction had turned over since the start of maize cropping

in an Ontario soil. Janzen etal. (1992) found that ttre ianee oflight fraction C in soils from different cropping rotatiois was twice as great as the range of total organic C content. They also reported that this greater range in light fraction contents allowed a much greater precision to be achieved in the separation of treatment effects. The dominant influence of plant-derived materials in the light fraction is reflected in its response to inputs ofresidue to the soil; its utility as an indicator of organic matter quality in agricultural soils is linked to this factor. For exampie, the amount of light fraction is greater under perennial forages or continuous cropping than under frequent summerfallow (Janzen et al. 1992) and is greater in well-fertilized soils (Shaymukhametov et al. 1984).

The light fraction and macroorganic matter is a valid indicator of soil quality in several respects. As a nonhumified fraction of organic matter, the size of the light fraction is

a

balance between residue inputs and persistence, and decomposition as determined by the soil environment (Gregorich and Janzen 1995). The light fraction and macroorganic matter constitute a relatively large amount of C and N contained in a small mass of soil and may contain a large portion of the total C in soil. Most of this labile material is unprotected by soil mineral particles and has a short turnover time, which gives the light fraction a prominent role as a C substrate and source ofnutrients. This pool is responsive to management practices and may provide an earlier indication of the effects of soil management and cropping systems than the total amount of organic matter in soils.

Mineralizable Carbon and Nitrogen

More than '75% of soil organic matter exists as compounds

matter and Iight fractions in 20 contrasting ioils from Ontario (from Ellert and Gregorich 1994) Variable

associated with mineral particle fractions, despite having a wide C:N ratio. Macroorganic matter is rapidly depleted when a soil is brought under cultivation. A Chernozemic soil cultivated for 4 yr had a light fraction 40% less than a native equivalent, with a 76% smaller light fraction after 90 yr of cultivation (Tiessen and Stewart 1983). Similarly, it is increased rapidly when a degraded soil is put into a continuous forage crop such as alfalfa (Angers and Mehuys 1990). The rate of loss of organic C from the light fraction was 2-l I times greater than that from the heavy fraction in five Australian soils (Dalal and Mayer 1986). Gregorich et al. (1995) reported that more than70% of the C in the light fraction had turned over whereas only 16% of the C associated with the coarse

19.3

z)-+J r6-25 0.58-0.87

9r-96 1'7

295% Confidence Intervals for the means ! %C in fraction/%C in whole soil.

-21

1.31 0.0-2.'7 7.58 4.2-tl 1r.4 8.0- t 5 42.4 37-46 26.4 24-29

that are only slowly decomposable; the remainder is present as readily decomposable or "mineralizable" compounds. This mineralizable fraction contributes to nutrient cycling and is the interface between autotrophic organisms that synthesize complex compounds from inorganic constituents and heterotrophic organisms that decompose the organic compounds and allow the inorganic constituents to be used again. Thus, the amount of mineralizable organic matter in a soil is an indicator of organic matter quality, because it affects nutrient dynamics within single growing seasons, organic mafter content in soils under contrasting management regimes, and C sequestration over extended periods of time.

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GREGOR'CH ET AL.

-

ASSESSMENT OF

Carbon mineralization, determined as the gross flux of CO2 from the mineralizable fraction, indicates the total metabolic activity of the heterotrophic soil organisms. It may also be used to assess other soil biological parameters, including the decay of plant residues, the persistence of organic wastes, the contribution of soil organic matter to atmospheric CO2, and the impact of pollutants on catabolism by soil organisms. Nitrogen mineralization, determined as the net flux of inorganic N from the mineralizable fraction, indicates the balance between gross mineralization and immobilization by soil organisms. The soil microbes immobilize or assimilate a portion of the N derived from decomposing organic matter, and excess N that is not required by the microbes accumulates as inorganic N (Harte and Kinzig 1993). Thus, N mineralization is often measured

to

assess the capacity

of soil

organic matter

to

supply

inorganic N, mainly NO3, which is the main form of plantavailable N and mobile N that leaches through the soil. Isotopic tracers are required to distinguish between gross mineralization and immobilization of N because the two processes occur concurrently as soil organic matter is decomposed. Several approaches, dictated by soil characteristics and study objectives, have been used to measure C and N mineralization in the field and in the laboratory. Lack of a standard method hampers comparisons of results from different studies. Soil incubations, frequently carried out under controlled environmental conditions (temperature, moisture, and aeration) in the laboratory can be viewed as rapid and simple "bioassays" of the actively cycling fractions of soil organic C and N (Andenon 1982; Campbell et al. 1993). Mineralizable C is usually measured as CO2 accumulated in an alkali trap that is sealed within the same chamber as the soil sample, but several other techniques have been used, including scrubbing of CO2 from air passed over incubating soils, measurement of CO2 accumulated in headspace air above incubating soils, and automated methods using

electrolytic detectors or infrared gas analyzers (Sparling and West 1990; Nordgren 1988; Heinemeyer et al' 1989). Mineralizable N is usually measured as inorganic N removed from incubated samples by shaking soils with an extracting solution, such as 2 M KCl, or by gently leaching soils with

solutions, such as

1 mM

CaCl2. Ammonium

is

the

immediate product of amino acid decomposition, but N mineralization is measured as ammonium plus nitrate production because ammonium often is oxidized to nitrate. The limitations of laboratory incubations for assessing N mineralization have been reviewed by Harmsen and van Schreven (1955), Keeney (1980, 1982), and Binkley and Hart (198e). Simple incubations with single time intervals can be used

to estimate the mineralizable fraction, but fluctuations in CO2 and inorganic N arising from microbial dynamics will not be apparent. Changes in mineralization rates are made evident by using incubations with sequential measurements, typically made by trapping CO2 and leaching or extracting inorganic N at periodic intervals. Such time-series measurements often indicate that the release of CO2 and inorganic N from the mineralizable fraction is curvilinear during the

SO't ORGANIC

MATTER

IN AGRICULTURAL

SO'IS

371

incubation. Asymptotic models are sometimes fitted to time series data to estimate the "potentially mineralizable C or N" which are extrapolated estimates of the size of the mineralizable fractions (Campbell et al. 1993)' Mineralizable C or N is usually calculated as the sum of CO2 or inorganic N released during each interval in the incribation, tfie quantities being dependent on the incubation or bioassay conditions used in the determinations' The

duration of,the incubation greatly influences the total amount of mineralizable C and N detected; other influential factors include sample pre-fieaftnent (especially drying)' temperature, moisture. aeration, and measurement interval. In a recent study (Ellert and Gregorich, unpublished data)' close relationihips between the cumulative amounts of C mineralized during22wk and the amounts mineralized during 3 or l0 wk rugg"it that shorter incubations adequately characterized the

mineralizable fraction of soil C (Fig' l). The relationships between cumulative mineralization during 22 wk and 3 or l0 wk, although highly significant (P < 0.0001), were less close for N (Fig. 2) than C (Fie. 1). Mineralizable-C and N may be determined simultaneously in a single incubation, but combined data are rarely reported (Table 3). Under optimal conditions in the laboratory. rates -' d -' of C mineralization typically range fr-om ] to 30 pg I | -' layers' in organic in mineral soils and 150-800 pE g- d Corresoonding rates of N mineralization range from 0'3 to is.s-rt-r in mineral soils and from 3.0 to 15 pg

-2.5 g-r d-T in organic layers (Table 3). Carter and Rennie

(fSAZ) reported greater rates of C and N mineralization in thin layeis of surface soil under zero tillage compared to conventional tillage because crop residues were concentrated at the surface ofzero-tilled soils. Janzen's (1987b) comparisons of crop rotations indicated that the proportions of the total store of C and N in the mineralizable fractions decreased with increasing frequency of fallow, suggesting that fallow

was detrimental to organic matter quality (Table 3). In another study, the amounts of mineralizable C and N were greater in fertilized than unfertilized soils, but the proportions of total soil organic C and N in the mineralizable fractions were similar, because fertilized soils also contained greater

amounts of total C and N (Janzen 1987a). Mineralizable C and N are usually correlated with total soil organic C and N. The quality of the soil organic matter may be distinguished from the quantity by calculating the proportion of ioil organic C or N found in the mineralizable t u"iions. Similar proportions of soil C and N in the mineralizable fractions of soils under contrasting management regimes indicate that, regardless of changes in the absolute quintities of total or mineralizable C and N, the qualiry of t-he soil organic matter has remained unchanged. In a study

of aggregate characteristics (Elliot 1986) macro-aggregates

> O.: mm) in native grassland and cultivated soils contained greater amounts of mineralizable C and N than did microiggregates, but the proportions of total aggregate C and N in itrehineralizable fractions were similar or greater in the micro-aggregates (Iable 3). Macro-aggregates tended to contain Table 3 -ote otganii matter and less sand, but from ttre data in macro-aggregates in matter organic the whether it is unclear was more decomposable than that in micro-aggregates' f

372

CANADIAN JOURNAL OF SO't SC'ENCE

o an 10 o, o)

t_ o t< o o

wk Y = 9.08 + 0.522X ; R2= 0.96

3wk

Y =-12.4 +0.167X:R2=0.88

3000

3

o

o

(r)

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(t) 'r-

2000

o c)

.N

o

.E

1

000

C)

o

(6

E

o 2000

4000

6000

Cumulative C mineralized during 22 weeks (pg g-1 soit

8000

)

l' Relationship between cumulative C mineralized from forest and cultivated soils at nine sites in ontario during long-term incubations and shorter periods (3 or 10 wk) (Ellert and Gregorich, unpublished) Fig'

The C:N ratio of the mineralizable fraction reflects the composition of the active fraction of soil organic matter, but differences may arise from analytical errors, shortages of bioavailable C or N, or the predominance of decomposable residues with a particular C:N ratio. The ratios of C:N mineralized are probably unrealistically narrow in Janzen's study (1987a), because C and N were estimated in separate incubations under slightly different condirions (Table 3). The wide ratios of C:N mineralized and the high proportions of mineralizable C reported by Miller and Johnson (t}Oly reflect analytical problems. The ratios of C:N mineralized ^uy in forest soils and organic horizons are often relatively wide because the soils receive inputs of woody residues with wide, C:N ratios (Table 3). The wide ratios of C:N mineralized in forest soils from Saskatchewan and Ontario were consistent with the cultivation-induced narrowing of the total soil C:N

ratio (Ellert, unpublished). Mineralizable C may be combined with other soil data, such as microbial biomass C, to calculate additional indices

of soil organic matter quality, such as specific respiratory

activity (Anderson and Domsch 1993). The rates of minerali_ zation observed under optimal conditions in the laboratory

are only potentials that are rarely attained under field

conditions. In fact, sub-optimal conditions in the field may

(22wk)

favour the build-up of mineralizable fractions that can be decomposed rapidly under optimal conditions in the laboratory.

Microbial Biomass The importance of microfauna to soil quality has long been recognized (Waksman and Starkey 1924). Microbial biomass

is a critical attribute of soil organic matter quality as it

provides an indication ofa soils' ability or capacity to store and recycle nutrients and energy. As a measure of organic matter quality, it also seryes as a sensitive indicator of change and future trends in organic matter levels and equilibria. Microbial biomass is a key variable of soil organic matter, functioning both as an agent for the transformation and cycling of organic matter and plant nutrients within the soil and as a sink (during immobilization) or source (during mineralization) of labile nutrients. The microbial component accounts for l-3% and 2-6% of soil organic C and N, respectively (Jenkinson 1987). Thus, it serves within the soil as a store of labile organic matter. In addition, microbially mediated N mineralization can provide over 50% of plant N needs annually, while N flux through the microbial biomass can be 2-4 times that of plant uptake (paul and

Voroney 1980).

GREGOR'CH ET AL.

1

a) j

10 1

ASSESSMENT OF

SO't ORGANIC MATTER IN AGRICULTURAL SO'LS 373

75

o o b,

-

50

wk Y = 3.57 + 0.471X; R2= 0.86

3wk y= 4.63 + 0.115 X;R2=

0.53.

at

o o

125 25

3

o Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

(t)

o, '= o=

100 00

-7F

o

.N

E

o

.E

50

zq) o

25

E

()

50

100

150

200

250

300

350

Cumulative N mineralized duting22weeks (pg g-r soil

)

(22 wk) Fig. 2. Relationship between cumulative N mineralized from forest and cultivated soils at nine sites in Ontario during long-term unpublished). (Ellert and Gregorich, incubations and shorter periods (3 or 10 wk)

Due to its dynamic nature, microbial biomass quickly responds to changes in soil management and soil perturbations (Carter 1986) and to soil environment (Insam et al. 1989; Skopp et al. 1990; Duxbury and Nkambule 1994)' The microbial biomass is also sensitive to various toxicities in soil (Domsch et al. 1983; Jenkinson 1987). The utility of the soil microbial biomass measurement is illustrated in its use as an independent parameter to validate organic matter models (Jenkinson 1990; Paustian et al. 1992). Microbial biomass is also related to various soil structure indices (Carter

1992; Angers et al. 1993b). Generally, indirect methods provide easy and efficient means to measure microbial biomass in soil (Brookes 1985; Parkinson and Coleman 1991). The three main indirect methods are: chloroform

fumigation incubation (Jenkinson and Powlson 1976), substrate-induced respiration (Anderson and Domsch I 978), and extractable biomass adenosine 5'-triphosphate (ATP)' The advantages of each method have been reviewed by Jenkinson (1987) and Sparling and Ross (1993). The fumigation technique has the advantage of providing a direct measurement of the C, N, P, and S contents of the microbial

biomass. Recently this method has been improved by eliminating the incubation procedure and directly extracting biomass constituents after removal of the fumigant (Jenkinson

1987). Analytical procedures for fumigation-direct extraction have been summarized recently by Voroney et al. (1993)' Much work has been done to improve the reproducibility of rnicrobial biomass measurements. Direct extraction solved many of the problems associated with the fumigation incubation technique. However, the processing of soil samples can still influence measurements of the labile microbial

biomass (Ross 1992). The main concerns are sieving of sampled soil, soil water content at sampling versus at fumigation, and storage of soil samples prior to analysis (Jenkinson 1987). For soil quality measurements' some degree of standardization in these areas is required. ihe determination of microbial biomass does not by itself provide information on microbial activity (Jenkinson 1987). Some measure of soil microbial biomass turnover, such as CO2-respired or enzyme activity, is required to assess miciobiil activity (Brookes 1985; Anderson and Domsch

1986; Anderson and Domsch 1993; Sparling and Ross 1993). Long-term studies of microbial biomass can provide

information on changes in the amount and nutrient content of biomass over time, which can be associated with differences in microbial activity and organic matter quality (Carter 1986; Duxbury and Nkambule 1994). The absolute amount of biomass at any one time cannot indicate whether

374

CANADIAN JOURNAL OF SO't SC'EA'CE Table

3. Mineralizable C and N determined in laboratorv incubations Mineralization

l,ocation, reference & incubation conditions

Soil

C:N

lYestern Canada: Chernozems under conventionat (CT) or zero (ZT) tillage C-arter a-nd Rennie CT Lethbridge, 0_2

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

12

wk,

25'C

(1982)

Amount mg

Soil

cm

ZT Lethbridge, 0_2 cm CT Melfon, 0-5 cm ZT Melfort, 0-5 cm CT Elstow, 0-5 cm ZT Elstow, 0-5 cm CT Scott, 0-5 cm

ZT Scott, 0-5

cm

9-.g l0.l 9.8 12.5 9.6 10.1 10.2 9.6

g-r"

c l.16

0.092 0.184 0.128 0.190

2.16 1.22

l.2O

c

C:N

Z.O4

1.30 1.68 1.30

rate pg

0.102 0.166 0.100 0.100

12.6 t. 1 10.2 8.8 12.7 13.0 12.2 r2.0

13.8

24.3

1

15.5

20.0 15.5

25.7 14.5

t4.3

Alberta: Dark Brown Chernozems with and without N & p fenilizer Janzen (1987a) 18 wk, 30'C

W,0_10 cm; check

wheat F![W:fallow-wheat-wheat

W:continuous

W, 0_10 cm; fertilized FWW, 0_10 cm; check FWW, 0-10 cm; fertilized

11.0

0.54

lt.l

10.0

0.79 0.51

10.6

0.6'7

g.g

0.79 0.70 o.49 0.42

0.140 0.200

4.0

0.1 15

AA

4.0

0.150

^<

5.3

3.9

+.J 6.3

I -l

Min./totalx

Y

N

1.10 2.19 1.52 2.26 1-21 1.98 l. 19 1.l9 l.l1 1.59 0.91 l. 19

c(%)

N(%)

2.4

t.9

4.3

3.9

0.9

0.8

t.2

1.7

1.6

t.2

3.0

z-5

1.4

1.2 1.3

t.'7 0.8

0.9 0.8 0.9

2.1 2.5 1.8 2.1

Alberta: Dark Brown Chemozems und,er contrasting crop rotations Janzen (1987b) 10 wk, 30'C

W, 0-15

FW:fallow-wheat

cm

FWW-Forage, 0_15

Saskntchewan: Gray htvisols Ellert, unpublished

9 wk, 30'C

cm cm

F!yW, 0_15 FW, 0-15

22 wk, 30"C

Forest LFH Forest Ae, 0-21 cm Recently Cleared,0-15

cm cm

Cultivated, 0-12 cm

30"C

20.i 11.7 17.6 l2.g

16.3 l3.8 t2.t

Forest, 0-15 cm Pasture, 0-15 cm

Ontario : Podzols (Petawawa Forest) Hendrickson and Robinson (1984) Mixed litter

3 wk,

9.g g.g

9.6

Wheat/Fallow, 0-16

Ontario: Gleysols (Plainfeld) Ellert, unpublished

cm

NA NA NA

Mineral soil, 0_5 cm

Mineral soil. 5-10 cm

20.80

NA* l.15 0.80 4.25 2.61 2.32

(1986) d,25"C

pm pm pm am

Grassland, >300 Cultivated, 53-300 Cultivated, )300

g.j 10.0 9.6 10.5

0.056 0.040

330.2

NA

15 15

18.3

0.216

20

0.177 0.183

15

27.6 17.0

IJ

15.1

0.299

61 M 51

0.043 0.068 0.016 0.027

16 t6 19 15

0.021 0.045 0.006 0.013

16.9 tl .4 38.3 24.5

0.31 0.41

!un1a

10

Germida

25"C

(1988)

pm um

Grassland, 25O Cultivated, 25O pm

10.3 l0.g r1.7 10.2

Alpine meadow Dryland wheat Irrigated, noncalcareous Irrigated, calcareous

NA NA NA NA

0.36 0.51 0.23 0.31

6.0

22

0.014 0.008

1.09

9.9 6.9

NA

0.63

0.40

11.2

0.934 0.002 0.078 0.052

saskatchewan: Micro- and nncro-aggregates in native grassrand and curtivated soirs

2 wk,

9.5 10.9 8.7 10.5

18.23

Nebraska: Micro- and mtcro-aggregates in native grassrand and curtivated soils Elliott Grassland, SI_3OO 0.67

20

0.083

0.0&

t2.7

868.0 30.1

t9.2 33.6 54.3 15.5

20.7

36.I 50.8 22.6

3l

.1

1.19 0.91 0.80 o.5'7

1.8 1.6 1.2

1.8 1.5

l. I

1.0

14.83 0.03 1.24 0.83

3.3

3.1

NA 1.7

o.2 2.0

r.7

1.4

| .7 1.0

1.0

2.0

1.9

6.'1

NA NA NA

1.40 15 1.19 1.

t4.23 0.69 o.37 2.15 3.40 0.80 1.35 2.r4 4.46 0.59 1.27

3.0 2.2

1.4

5.4

5-Z

5.6

J.f

2.9

1.4 1.6

2.4 12.2

5.1 7.7 6.5

4.9 2.3

2.7

Colorado: Contasting soils

Miller and Johnson (1964) 2 wk, 30"C, 0.05 bars

Alaska: Organic layers of tundra soils Nadelhoffer et al. (1991) Tussock, Oe+Oa 13 wk, l5'C Slope shrub/lupine, Oe Wet sedge, O Riverside, Oe+Oa

Brazil: Intosol under sugar cane Salcedo et al. (1985)

1l wk,28'C

0-20 cm; check 0-20 cm; 60 kg N/ha

4.42 1.60

2.N 1.19

20.9 r9.7 15.3 19. I

4l.00

9.6 9-6

0.25 0.23

19.00 21.00 14.00

0.058 0.029 0.016 0.028 0.035 0.009 0.090 0.350 0.031 0.028

76 56

126 42

3

15.9

t14.4 142.8 84.6

543 2333 156 tr7

4s0.5

8.2 8.3

3.3

0.40

3.0

0.36

208.8 230.8 153.8

zCumulative amount of C or N mineralized during incubation for the period indicated under ..Incubation Conditions,' vLinear rate calculated as the cumulative amount of c or N mineralizid divided by the duration of the incubation. xProportion of total soil C and N mineralizable during + wt Z8jlto-t]tl'oit organic C or N. wNot available.

: t.*-i,

4.t4 2.04 1. 13 2.O2 0.38 0.10 0.99 3.85

25.0 50.2 43.l q.9

NA NA NA NA

t.4

0.1

3.2

0.0

1.0

0.1 o.7

4.3

1.6

r.2

1.4

GREGOR'CH ET AL.

_

ASSESSMENT OF

SO'LS 375

Generally, a ratio above or below equilibrium would indicate that soil C is increasing (aggrading phase) or decreasing (degrading phase), respectively. However, actual or absolute incieases insoil C would be dependent on overriding climatic

soil organic matter quality is increasing or decreasing' To answer this dilemma, the microbial biomass can be compared

to a related soil parameter. For example, the ratio of microbial biomass C to total organic C (Anderson and

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SO't ORGANIC MATTER IN AGRICULTURAL

of precipitation to potential (Mele and Carter 1993). Overall, deterevapotranspiration factors, such as the ratio

Domsch 1986. 1989: Wu and Brookes 1988; Carter 1991) or the ratio of CO2-C respired to microbial biomass C (Anderson and Domsch 1986, 1990) provides a measure of organic matter dynamics. The latter ratio is well suited for the substrate-induced respiration method, and its application for soil organic matter quality assessment has been addressed by Visser and Parkinson (1992). Generally, changes in the ratio reflect both inputs and outputs of organic matter into the soil and conversion of organic matter to microbial C. Studies using the ratio of microbial biomass C to total organic C have demonstrated the utility of this index to monitor organic matter changes in agricultural systems

mination of these critical values provides information on both microbial biomass dynamics and organic matter equilibria.

Carbohydrates

Carbohydrates represent a significant pool in soil organic matter (5-20% of the total soil organic C). Soil carbohydrates originate from plants, animals, and microorganisms, their composition varying accordingly. Most of the carbohydrate fraction is present as a mixture of complex polysaccharides, which in turn are composed of monosaccharides. Five monosaccharides usually represent more than 9O% of the

(Carter and Rennie 1982; Anderson and Domsch 1989; Carter 1991; Sparling 1992).ln most cases, the ratio must be assessed against a local reference or baseline (e.g., grassland) in the same soil type (Carter 1991). Differences

total hydrolyzable carbohydrates: glucose

dominates,

followed by galactose, mannose, arabinose, and xylose.

Galactose and mannose are believed to be produced mainly by microbes, whereas arabinose and xylose originate mostly from plants (Cheshire 1977). Carbohydrates contribute to soil quality primarily through their role in the formation and stabilization of soil structure. Of all the organic matter fractions in soil, the polysaccharides, because of their chemical structures, are likely to be the most readily available source of energy for organisms (Cheshire 1979). Physical protection of these polysaccharides may, however, reduce this availability. Several approaches have been developed for the determination of soil carbohydrate content, most involving extraction or hydrolysis followed by quantitative determination of the hydiolysed saccharides (I,owe 1993). Sulfuric acid is usually

in soil clay content, mineralogy, and vegetation can influence the proportion of microbial biomass C in total organic C (Sparling 1992). Thus, the application of the ratio index is mainly confined within similar soil types and cropping systems.

Figure 3 illustrates the ratio approach to characterizing changes in organic matter quality under two soil types' In

the Charlottetown fine sandy loam (Orthic Humo-Ferric Podzol) from eastern Canada, an equilibrium ratio value of about 1.2 is associated with 300 p"g g-' microbial biomass C, while in the Kairanga silty clay loam (equivalent to Regosol or Dystric Brunisol) from New Zealand the res[ective values are approximately 1.8 and 620 p'gC g-t.

z-3

1.5

a

s

1O

U)

(t

oo

(d,n

E'-

o

oo

o3.

2.0

a

.9

o o o

o

-o .g

o 0'5

o

o

o

oa jO

.g

c(d

o

C')

o

b) Kairanga Silty ClaY Loam

a) Charlottetown Fine Sandy Loam 0.0

0.0

200

600

0

700

900

1100

Microbial biomass C (Pg g-1 soil) Fig. 3. Comparison of microbial biomass C to organic C in the microbial biomass in cropping systems ( o ) and grassland refe-rence areas systems (adapted from Carter 1J; in two ioil types; (a) Charlottetown fine rundy lourn' data from spring cereals under various tillage(adapted from Sparling 1992). cropping or cereal maize for various time durations from iSgfl; Ol Kairanga silty clay loam: data

376

CANADIAN JOURNAL OF SO'T SC'EVCE

used for hydrolysis; the determination of saccharide content

a;d temperature of

drates can be achieved using a simple sequential treatment,

increased resistance to aggregate-slaking and the carbohydrate content of the soil's heavy fraction extracted with dilute acid

chromatography.

In

general, the amount

of

carbohydrates extracted

increases with the acid concentration

hydrolysis. Satisfactory total hydrolysis of soil carbohy-

starting with concentrated H2SOa, followed by dilute

H2SO4 (Oades etal. 1970; Cheshire 1979). The concen_ trated acid is used to hydrolyse the recalcitrant cellulose.

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

0.5 M). The involvement of

carbohydrates in aggregate stabilization was confirmed with a selective periodate treatment. Roberson et al. (1991) studied the shortterm (2 yr) influence ofcover crops on soil aggregation and soil organic matter fractions. They found that cover crops significantly

can be done colorimetrically or by using gas or liquid

Water at 20oC extracts less than l% of the total carbo_ hydrate content; water at 80oC extracts 5-10%; and acid hydrolysis extracts l0-l0O%, depending on the acid concentration and temperature of reaction. Extractability also varies greatly with soil type. Simple colorimetric methods, variable in their selectivity (Cheshire 1979), are used to determine the total carbohydrate

content of the hydrolyzates. Some methods are subject to interferences (Martens and Frankenberger 1990). Thi most widely used are the anthrone-sulfuric acid (Brink et al. 1960). thealkaline ferricyanide (Cheshire 1979). and the phenoisulfuric acid (Dubois et al. 1956) methods. Gas chroma_ tography (Oades et al. t97O Baldock et al. t9g7) and hr^B]r_performance

liquid chromatography (Angers et al.

1988; Martens and Frankenberger t990) are used if the carbohydrate composition of soil hydrolyzates is of interest. Measurements of carbohydrates are usually done on finelyground air-dry soil and are therefore highly reproducible. Most of the methodological uncertainties irise from the wide variety ofextraction and hydrolysis procedures used. There is a need for standardizing these procedures ifcarbohydrates are to be used for assessing soil quality. Soil carbohydrates have been primarily studied in relation to soil aggregation. Several studies have found sood correla_ tions.betw_een carbohydrate content and soil mairoaggregate stability (Rennie etal. 1954; Acton er al. 1963 Haynesind Swift 1990; Angers et al. 1993b); however, others have not (e.g., Carter et al. 1993). Other components of the soil organic matter such as the hydrophobic aliphatic fraction (Capriel et al. 1990) and fungal hyphae (Tisdall and Oades 197.9) are probably involved in macroaggregate stability. Baldock et al. (1987) compared the effecti of 15 yr of maiie cropping to 15 yr of bromegrass on the water-stable aggre_ gation of a silty loam. They found large differences in soil aggregation induced by the two crops but no difference in

total carbohydrates, and consequently no correlation between the two factors. Their extraction procedure was a complete hydrolysis r ^ing concentrated sulfuric acid. They suggested that if carbohydrate materials were responsible fbr the rapid changes in aggregate stability caused by changes in crop-

ping practices, then a specific component of cirbohydraie

material must be involved. The use of dilute-acid hydrolysis treatmenrs (0.5 M-2.5 M H2SO4) has produced different results from the above. Angers and Mehuys (1989) measured an increase in waterstable aggregation ofa clay soil after only 2 yr ofalfalfa or barley, compared with continuous maize. This increase in water-stable aggregation was concurrent with an increase in carbohydrates as measured by hydrolysis with dilute acid

(2.5 M). They argued that this carbohydrate fraction was mainly composed of microbial extracellular polysaccharides. Their conclusion was supported by the correlation between biomass C and this carbohydrate fraction (r : 0.73x*;. Hot-water extractable carbohydrates change rapidly when cropplng systems are modified, and these changes are correlated with changes in aggregation (Haynes and Swift 1990; Haynes et al. 1991; Angers et al. l993a,b). This carbohydrate fraction may also represent the specific component of carbohydrate material referred to by Baldock et al. (1987). As suggested by Haynes and Swift (1990), this pool probably equates with mucigel, predominantly of microbial origin, and Angers et al. (1993a) found a strong correlation (0.78**) between this carbohydrate pool and microbial biomass C. Angers et al. (1993a) found rhar rhe rario of both mildacid and hot-water soluble carbohydrates to total organic C was greater under no-till than under moldboard-plowed soil after only three cropping seasons (Fig. a), suggesting an enrichment of labile carbohydrates in the organic matter under reduced tillage. Similar results have been obtained previously by Angers and Mehuys (1989), when comparing the effects of cropping to alfalfa (Medicago sativaL.),barIey (Hordeum wlgare L.), and maize on dilute-acid hydrolyzable carbohydrates (Fig. 5). Haynes et al. (1991) also found that hot-water soluble and dilute-acid hydrolyzable carbohydrates changed more rapidly than total organic C when management practices were changed from arable to pasture. These results suggest that these labile fractions ofthe carbohydrate pool could be sensitive indicators of changes in organic mhtter quality, especially in comparisons of cropping systems. The involvement of labile carbohydrates in the short-term changes in aggregate stabilify should reinforce this suggestion. However, there still remain uncertainties as to whether hotwater soluble or dilute-acid hydrolyzable fractions better represent the labile carbohydrate fraction. More experimental work is needed to clarify this point.

Soil Enzymes Soil enzymes are molecular sub-systems of soil organisms that can be used as indicators ofsoil quality iftheir activities are affected by environmental variables and farming practices. Enzymes are biological catalysts that lower the energy required to activate biochemical reactions. Soil enzymes are proteins that are synthesized by plants and soil organisms during metabolism and are found in living organisms (biotic enzymes), or in dead cells of microbial and plant tissues (abiotic enzymes), or complexed with organic and mineral colloids (Dick 1994). The total enzyme activity of a soil depends on the amount of extra- and intra-cellular enzymes (Skujins 1967). A system of heterogeneous soil enzymes operating in a cascade manner controls the decomposition

GREGORICH ET AL.

-

ASSESSMENT OF SO'L ORGANIC MATTER

IN AGRICULTURAL SO'LS 377

dilute acid

hot water 0.70

at,

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o

-ct p

1o.o

H.ffi

0.65

g) (n

o

r::illi'l:

:::i::r.

-c

lari::::

9.5 q o

o

-o

so

0.60

J

(s

o

o-

u)

ct .

-

0)

9.0

0.55

s

o @

MP

MP

CP

CP

NT

TILLAGE TREATMENT MP = MOLD BOARD

PLOWED

CP = CHISEL

PLOWED

NT = NO-TILLAGE

Fig. 4. Effects of 4 yr of tillage practices on the proportion of C present as hot-water extractable and dilute-acid hydrolyzable carbohy-drates ini Kamouraska cliy. The vJrtical bars represent tire Least Significant Differences at the 0.05 level. Adapted from Angers et al. (1993a)' (Based

of

407o

C in carbohydrates.)

of soil organic matter and human-added amendments. Plant residue components must be depolymerized and transformed

before becoming the backbone of soil humus. The enzyme B-glucosidase depolymerizes cellulose into subunits of glucose that can be used by soil heterotrophs as carbon and energy sources. Other important glycosidases are a- and B-galactosidase (Tabatabai 1982). Mineralization of soil organic-N to NHa+ is accomplished by a series of enzymatic reactions involving proteases, deaminases, amidases, and ureases. Arylsulfatase and acid and alkaline phosphomonoesterases control the S and P dynamics in terrestrial ecosystems. Enzyme activities are critical indicators of organic matter quality because enzymes control nutrient release for plant

and microbial growth (Skujins 1978; Burns 1978), gas exchange between soils and the atmosphere (Conrad et al. 1983), and physical soil properties (Martens et al. 1992). Soil enzyme research has been reviewed by Skujins (1967), Burns (1978), and Klein et al. (1985). Recently Dick (1994) suggested that soil enzyme activities be used as biochemical/

biological indicators of soil quality. Methods used to measure the activity of soil enzymes are generally simple, rapid, accurate, and reproducible (Tabatabai

1982; Peterjohn 1991). The activity

of an enzyme

is

determined by measuring product formation or substrate remaining during incubation of soil samples (Tabatabai 1982). Methods have been standardized for substrate concentration, temperature and time of incubation, buffers, and pH. Most standard methods used in terrestrial ecosystem studies involve the incubation of soil samples with a substrate at 37'C for a few hours (Table 4) and have been used successfully in soils differing in parent materials, climatic areas, and agronomic management. The sensitivity of soil enzymes to environmental and farming disturbances can be quantified using two approaches: measuring enzyme-related activities and determining kinetic parameters as defined by the Michaelis-Menten model. In general, soil enzyme activities are directly proportional to the content ofsoil organic matter (Skujins 1967; Frankenberger and Dick 1983; Baligar and Wright l99l; Baligar et al. 1991). Soil enzyme activities are higher in surface than in subsurface horizons and follow the distribution oforganic C in the soil profile (Baligar and Wright l99l; Baligar et al. l99l; Frankenberger and Tabatabai 1991). Erosion and excessive tillage, which decrease soil organic matter content and the thickness of the A horizon, may therefore induce

378

CANADIAN JOURNAL OF SO't SC'ENCE Soil enzyme activities respond to cultivation, additions of

fertilizer and organic amendments. Adenosine deaminase activity has been shown to contribute significantly to N mineralization and was higher in an Andept under forest than under cultivation (Sato et al. 1986). Cultivation of native grasslands and forest ecosystems decreased soil organic C and the activities of dehydrogenase, urease, phosphomono-

ct,

o (u L

o ) -c

esterases, and arylsulfatases in a soil climosequence of the Canadian prairies, and the activity of these enzymes decreased even further in crop rotation systems that include summerfallow (Dormaar 1983; Gupta and Germida 1986). Dehydrogenase and urease activities were lower in a Brown Chernozem fertilized with N and P than in the same soil fertilized only with P (Biederbeck and Campbell 1987). The continuous application of P for 11 yr to soil under continuous

z.s

o

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

-o

o o

7.O

(5

o ;e 6.5

BARE

CORN

BARLEY

ALFALFA

SOIL

CROPPING TREATMENT Fig. 5. Effects of 2 yr of different crops on the proportion of C present as dilute-acid hydrolyzable carbohydrates in a Kamouraska clay. The vertical bar represents the Least Significant Difference

at the 0.05 level. Adapted from Angers and Mehuys (19g9). (Based

of 40% C in carbohydrares.

In

losses in total amount and activity of enzymes by diluting the concentration of organic C in cultivated Ap horizons with

soil from the B horizon. Overgrazing and erosion resulted in decreased enzyme activities in semi-arid soils (Sarkisyan and Shur-Bagdasaryan 1967). Temporal fluctuations of enzyme activities are related mainly to differences in soil moisture and are almost independent of small variations in soil organic C and N (Ross et al. 1984). The temporal and spatial variabilities of soil enzymes are unknown at the landscape level in degrading, sustaining, and aggrading soils and may need to be defined in relation to reference sites before enzyme parameter values are used as indices of soil qualiry.

Table

4. Methods to measure the activity of

wheat and wheat-fallow rotations inhibited the activity of phosphomonoesterases compared to that measured in plots fertilized with N and P. Enzyme activities were found to increase in a Gray Luvisol after additions of NPKS, NS, and manure (Khan 1970). A significant negative correlation between NHa- and L-histidase was found in a Black Chernozem fertilized with NHaNOs at a rate of 70 ke N ha-r iBurton and McGill 1992). Fields cropped to gi"n manure for 27 yr showed significantly higher activities of urease, phosphomonoesterases, and dehydrogenase than those receiving inorganic fertilizers (Bolton et al. 1985), which is consistent with results reported for a Belgian soil

(Verstraete and Voets 1977). comparison with an unamended soil, additions of poultry manure, sewage sludge, barley straw, or fresh alfalfa hay increased the activity of key enzymes of the C, N, P, and S cycles. Addition of plant materials significantly increased B-glucosidase activity relative to that measured with additions of poultry manure and sewage sludge (Martens et al. 1992). Different cropping systems produced a significant effect on B-glucosidase activity within 2 yr, even though there was no measurable difference in total C content (Dick 1994). We hypothesize that kinetic parameters used to characteize

enzyme content and maximum reaction velocity (Vmax), enzyme-substrate affinity (Km), and inhibition reactions (Ki) may be used to assess the change caused by environmental factors, substrates, or chemical compounds added to soils.

some enzymes involved

in the C, N, P and S cycles in terrestrial

Enzyme

Substrate

Incubationz

Dehydrogenase 0-glucosidase

Triphenyltetrazolium P-nitrophenyl - D-glucosidase

37, 24

Urease Protease

Urea Casein

Histidase Glutaminase

50, I

L-histidine

37, 48

L-glutamine Adenosine P-nitrophenylsulfate P-nitrophenylphosphate

tt,I

Nucleosidase

Arylsulfatase Phosphomonoesterases

3't,

1

30,72 37, I 3'7, 72

pH 6.5r, I lx zTemperature ("C) and time (h).

YAcid phosphalase. xAlkaline phosphatase.

ecosysrems

Reference

Casida et al. (1964) Tabatabai (1982) Tabatabai (1982) Ladd and Butler (1972) Frankenberger and Johanson (1982) Frankenberger and Tabatabai (1991) Sato et al. (1986) Tabatabai and Bremner (1970) Tabatabai and Bremner (1969)

GREGOR'CH ET AL.

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ASSESSMENT OF

SO't ORGANIC MATTER IN AGRICULTURAL the tools necessary to provide a picture

In Canadian prairie and boreal soils, Km for arylsulfatase

379

of soil quality.

Components of the data set will change depending on the type ofpicture required and who requires the picture. Thus, the strategy of data sets is dynamic and flexible. They become the means whereby interest groups (e.g., scientists) or society can relate to, utilize, or evaluate soil for a specific reason or purpose. Without data sets, the functional role of soil (in contrast to its analytical parts) remains an enigma.

Ki for urease have been shown to be sensitive to cultivation, management, and additions of substrates (Gupta and Germida 1986; Monreal et al. 1986). Km and Vmax values for arylsulfatase were lower in cultivated than in reference native Chernozems and Gray Luvisols (Gupta and Germida 1986) and were highly correlated with organic C (r' : 0.97 and 0.99, respectively, P < 0.01). Critical Km values for arylsulfatase in cultivated degraded Gray Luvisol and Dark Brown Chernozems ranged between 1.72 and2.67 mM (Fig. 6). The boundaries shown in Fig. 6 are an attempt to separate arylsulfatase kinetic parameters in degraded soils from those in reference or undisturbed soils. Further development of indices for soil quality requires research to more accurately define the boundaries for kinetic parameters in degrading, sustaining, and aggrading systems. and

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SO'IS

The development of minimum data sets involves the selection of a small subset of attributes that will provide a practical assessment of a specific soil organic matter function. Table 5 summarizes the attributes of soil organic matter quality and the most frequently used methods of measurement. Many of the attributes are interrelated and may

be used to estimate other attributes through the use of

matter 'quality' is analogical (rence the use of terms "health"

functional relationships called pedotransfer functions (Bouma 1989; Pierce and Larson 1993). Numerous pedotransfer functions have been developed from information in a specific area or from data on different soil types; a complete list would be extensive and has not been included here. A limited

and "fitness"). Use of analogy underlines that "quality" relates to the value placed by society upon the functions of soil organic matter quality in the environment. It is a way of examining the whole soil, not just its parts. Data sets are

pedotransfer functions are given in Table 5. The attributes listed in Table 5 are not considered a strict "minimum data set" since not all of them are required to

MINIMUM DATA SETS In this review the approach taken to assessing soil organic

number

of

processes that could

be estimated from

Km = 1.9 + 5.9 log (%C) R'= 0.97 Vmax = 88 + 1382 log (%C)

R'?

= 0.99

3 0, x (o

E f

I

EoJ

o f o

t^ (cultivated for 5y, 40y and 69Y)

.t

Organic carbon (%) Fig. 6. Relations between Km, Vmax of arylsulfatase and organic C in Gray Luvisol and Dark Brown Chernozems. Points in the lower left box are data from sites cultivated for 5, 40 and 69 yr (adapted from Gupta and Germida 1986).

380

CANADIAN JOURNAL OF SO'L SC'ENCE Table

5. Attributes of soil organic matter quality, methods, soil organic matter quality indicators, and related pedotransfer functions

attribute

Methodologyz

indicators

Related processes or attributes which can be estimated by pedotransfer functions

Organic C and total N

Wet or dry oxidation

Carbon and nitrogen mass and balance

Soil structure Nutrient supply

Light fraction

Sieving or densimetric fractionation

Plant residue decomposition

Total organic C Soil respiration rate Nutrient supply

Soil incubation

Total metabolic activity of soil organisms Net flux of inorganic N from mineralization and immobilization process

Microbial activity

Carbon and nitrogen in microorganisms Labile carbon and nitrogen

Soil structure Nutrient supply

Soil organic matter

Soil organic matter quality

Mineralizable C

organic matter storage

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and N

Microbial biomass

Fumigation extraction

or substrate- induced respiration

Nutrient supply

Carbohydrates

Hot-water extraction

Soil structure Labile carbon

Soil structural stability

Enzymes

Table 4

K' V.u*,

Biochemical activity Nutrient supply

K;

zMethodology discussed in text.

characterize changes in soil organic matter quality. Different soil processes require different minimum data sets, because

of the multi-faceted role of soil organic matter. Table

6

outlines various minimum data sets for processes involving soil structure, nutrient storage, and biological activity. Soil structural processes, such as the formation and stabilization of aggregates and macropores, are affected by the total

organic matter, microbial biomass, and carbohydrates. Nutrient storage in soils can be assessed by evaluating the quantity of organic C and N. In addition, the total amount of, and the proportion of total organic C and N in, microbial biomass, mineralizable C and N, and the light fraction will also provide information on soil nutrient storase. Attributes

such as microbial biomass, enzymes, and mi-neralizable C and N are measures of biological activity in soils. A holistic approach to assessing soil organic matter quality is important because the suitability of a soil for sustaining

plant growth in agroecosystems is a function, not only of the biological activity, but also of the soil chemical and physical properties. Appropriate use of a minimum data set will depend on how well the relevance of these indicators is interpreted in consideration of the agricultural system of

which they are a part. For example, soil pH, which is Table

6.

Some minimum data sets

for estimating soil organic matter

quality Processes

Minimum data

Soil structure

Total organic C and N

sets

Microbial biomass Carbohydrates

Nutrient storage

Total organic C and N Microbial biomass Mineralizable C and N Light fraction and macroorganic matter

Biological activity

Microbial biomass Enzymes

Mineralizable C and N

substantially lower in soils under blueberries than it is under maize production, plays an critical role in determining the biological activity in soil. Bulk density in soils under different tillage treatments may be substantially different, and accurate comparisons of biological properties may require that the results be expressed on a volumetric basis (Doran and Parkin 1994). Thus, the interpretation ofthe relevance ofbiological indicators in the absence of soil physical and chemical

attributes may be of little value or possibly misleading for assessing soil organic matter quality in agricultural soils.

CONCLUSIONS AND SUMMARY Concerns about the effects of agricultural practices on the environment and the effect of the environment on crop production have kindled interest in quantifying their impact on soil quality. Use of a minimum data set, comprising a number of soil biochemical properties sensitive to manage-

ment, perturbations, and inputs to the soil, is a critical first step for assessing soil quality. Soil organic matter is considered a key attribute of soil quality. In this review, organic matter is characterized to distinguish sub-attributes or biological and biochemical properties that describe the quality of organic matter. Although much progress has been made in determining sensitive indicators of soil organic matter quality, more work is required, for example, to determine the variability of each property in the data set. Each properfy may need to be characterized for its temporal variation during a growing season and for its spatial variation, both laterally across a landscape and vertically through a soil profile. These properties should also be examined in different agriculture systems over a wide range of climatic and soil conditions where it is known that soil quality, and in particular soil organic matter quality, has been affected. Many studies have assessed the response of biological properties to the degradation of soil quality but the response ofthese properties

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GREGORICH ET AL.

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ASSESSMENT OF

to the amelioration of soil quality may be different and should also be characterized. Other key properties could be added to this minimum data set in the future. Water soluble organic carbon (WSOC) is a very active soil organic component, and flow of C through it supplies substrate for biomass turnover (McGill et al. 1986). Thus, WSOC is closely linked to the microbial biomass and in the future could be included in a minimum data set used to assess biological activity in soil. Soil mesoand macrofauna fragment and redistribute plant residues which can enhance decomposition of organic matter and nutrient cycling (Coleman et al 1989; Linden et al. 1994). They can also modiff soil structure through the formation ofmacropores and aggregates (Lee and Foster l99l). Thus' these faunal indicators could be chosen for minimum data

to evaluate nutrient storage and soil structure. The relative molar distribution of amino-acid N has shown sets

promise for describing changes in soil organic matter quality (Campbell et al. 1991b). Measurements of DNA, ATP, and

AEC in soil could potentially be reliable indicators of biological activify (Tsai and Olson 1992, Ciardi et al' 1993). However, more research is required to determine how these properties are affected by agricultural management practices, to establish a standard set of procedural and pretreatment protocols, and to evaluate the quantitative relationships of these attributes to soil quality.

ACKNOWLEDGEMENTS This review is the result of discussions and research by the authors for the Soil Quality Evaluation Program funded through the National Soil Conservation Program' We thank Drs. H.H. Janzen and C.A. Campbell for their thorough reviews of early versions of the manuscript and Dr. D.F. Acton for his able leadership in the SQEP. Acton, C. J., Rennie, D. A. and Paul, E. A. 1963. The relationship of polysaccharides to soil aggregation. Can. J. Soil Sci'

43:2Ol-209. Acton, D. F. and Padbury, G. A. 1993 . A conceptual frame-

work for soil quality assessment and monitoring. Pages 2-l to 2-10 fu D. F. Acton, ed. A program to assess and monitor soil quality in Canada: Soil quality evaluation program summary. Research Branch. Agriculture and Agri-Food Canada, Ottawa, ON. Anderson, D. W. 1979. Processes of humus formation and transformation in soils of the Canadian Great Plains' J. Soil Sci.

30:77-84.

Anderson, D. W. and Gregorich, E. G. 1983' Effect of soil erosion on soil quality and productivity. Pages 105-113 in Soil erosion and land degradation. Proc. 2nd Annual Western Prov. Conf. Rationalization of Water and Soil Research and Management' Prov. Sask., Saskatoon, SK. Anderson, J. P. E. 1982. Soil respiration. Pages 831-871 ln A' L. Page, R. H. Miller and D. R. Keeney, eds. Methods of Soil analysis. Part 2, Chemical and microbiological properties. 2nd ed' Agronomy No. 9. American Society of Agronomy, Inc., Madison,

wI.

Anderson, J. P. E. and Domsch, K. H. f978. A physiological method for quantitative measurement of microbial biomass in soils.

Soil Biol. Biochem. l0 215-221. Anderson, J. P. E. and Domsch, K. H. f986. Carbon assimilation and microbial activity in soil. Zeitschrift ftir Pflanzenerniihrung und Bodenkunde 149: 45'7-468.

SO't ORGANIC MATTER IN AGRICULTURAL

SO'IS

381

Anderson, J. P. E. and Domsch, K. H. 1989' Ratios of microbial biomass carbon to total organic carbon in arable soils' Soil Biol' Biochem. 2l: 471'479.

Anderson, T.-H. and Domsch,

K. H.

1990' Application of

eco-physiological quotients (qCOr and qD) on microbial biomasses from soils oidifferent cropping histories. Soil Biol' Biochem' 22:

25r-255.

K. H. 1993. The metabolic quotient for CO, (qCOr) as a specific activity parameter to assess tire effects of environmental conditions, such as pH, on the microbial biomass of forest soils. Soil Biol. Biochem.25:393-395' Angers, D. A., Bissonnette, N., L6gbre, A. and Samson, N' 1993a. Microbial and biochemical changes induced by rotation and tillage in a soil under barley production. Can. J. Soil Sci' 73: Anderson, T.-H. and Domsch,

39-50. Angers, D. A. and Mehuys, G. R. 19E9. Effects of cropping on carbohydrate content and water-stable aggregation of a clay soil' Can. J. Soil Sci. 69 373-380. Angers, D. A. and Mehuys, G. R. f990. Barley and alfalfa cropping effects on carbohydrate contents of a clay soil and its size

fractions. Soil Biol. Biochem. 22:285-288. Angers, D. A., Nadeau, P. and Mehuys, G. R. 1988. Determination of carbohydrate composition of soil hydrolysates by HPLC' J. Chromatogr. 454 444-449. Angers, D. A., Samson, N. and L6gbre, A. 1993b. Early changes in water-stable aggregation induced by rotation and tillage in a soil under barley production. Can. J. Soil Sci. 73: 51-59' Baldock, J. A.' Kay, B. D. and Schnitzer, M. 19E7. Influence of cropping history and chemical treatments on the water-stable aggregation of a silt loam soil. Can' J. Soil Sci. 67:. 489-499' natigir, V. C. and Wright, R. J. 1991. Enzyme activities in Appilachian soils: l. Arylsulfatase. Commun. Soil Sci' Plant Anal'

22:305-314. Baligar, V. C., Staley, T. E. and Wright, J. R. 1991. Enzyme activities in Appalachian soils: 2. Urease' Commun' Soil Sci Plant Anal.22: 315-322. Biederbeck, V. O. and Campbell, C. A. 1987. Effects of wheat

rotations and fertilization on soil microorganisms and enzymes of a Brown Loam. Pages 153-164 in Markets - Soils and crops' Proceedings of the Soils and Crops Workshop, University of Saskatchewan, Saskatoon, SK' Binkley, D. and Hart, S. C. 1989. The components of nitrogen availability assessments in forest soils. Adv. Soil Sci- lO:57-lI2'

Bolton. H. Jr., Elliot, L. F., Papendick, R. I. and Bezdicek' D. F. 1985. Soil microbial biomass and selected soil enzyme activities: effect of fertilization and cropping practices. Soil Biol'

l7: 297-302. T. A., Christensen' B. T. and Cerri, C. C.

Biochem.

1992' ''C abunnatural by reflected matter as organic soil of Dynamics dince in particle size fractions of forested and cultivated oxisols' Soil Biol. Biochem. 24:. 275-2'l'7 ' Bouma, J. 1989. Using soil survey data for quantitative Iand evaluation. Adv. Soil Sci.9'- l'77-213. Bowman, R. A., Reeder, J. D. and Lober' R. W. 1990. Changes

Bonde,

in soil properties in a Central Plains rangeland soil after 3,20, and 60 years of cultivation. Soil Sci. 150: 851-857. Bremner, J. M. and Mulvaney, C. S. 1982. Nitrogen - Total' Pages 595-624 in A. L. Page, R. H. Miller, and D' R' Keeney, eds. Mettrods of soil analysis . Part2. Chemical and microbiological

properties. 2nd ed. Agronomy No' 9. American Society of Agronomy, Inc., Madison, WI. Biink, R. H. Jr., Dubach, P. and Lynch' D. L. 1960. Measurement ofcarbohydrates in soil hydrolyzates with anthrone' Soil Sci'

89:157-166.

382

CANADIAN JOIJRNAL OF SO'I- SC'ENCE

Brookes, P. C. 1985. Microbial biomass and activity measurements in soil. J. Sci. Food Agric. 36: 269-281. Burns, R. G, 1978. Enzyme activity in soil: some theoretical and practical considerations. pages 295-326 in R. G. Burns, ed. Soil erzymes. Academic Press Inc., London. U.K. Burton, D. L. and McGill, W. B. 1992. Spatial and temporal fluctuation in biomass, nitrogen mineralizing reactions and mineral nitrogen in a soil cropped to barley. Can. j. Soil Sci. 72: 3l_42. Campbell, C. A., Biederbeck, V. O., Schnitzer. M.. Selles. F. and Zentner. R. P. 1986. Effect of6 years ofzero tillase and N fertilizer management on changes in soil quality of an Orthic Brown Chernozem in Southwestern Saskatchewan. Soil Tiltaee Res. 14:

39-52.

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

Campbell, C.

A., Biederbeck, v. O., Zentner, R. p.

and

Lafond, G. P. 1991a. Effect of crop rotations and cultural practices on soil organic matter, microbial biomass and respiration in a thin Black Chernozem. Can. J. Soil Sci. 7l: 363-3i6. Campbell, C. A., Bowren, K. E,, Schnitzer, M., Zentner, R. p. and Townley-Smith, L. l99lb. Effect of croD rotations and fertilization on soil organic matter and some biochemical properties

of a thick Black Chernozem. Can. J. Soil Sci. 7l: 3.:-i-3g.7. Campbell, C. A., Ellert, B. H. and Jame, y. W. 1993. Nitrosen

mineralization potential in soils. pages 341-349 in M. R. Carier, 9d, Soil sampling and methods of analysis. Canadian Society of Soil Science, kwis Publishers, Division of CRC press. Boca Raton.

FL.

Campbell, C. A., Myers, R. J. K. and Weier, K. 19g1. poten_ tially mineralizable nitrogen, decomposition rates and their rela_ tionship to temperature for five eueensland soils. Aust. J. Soil Res. 19: 323-332. Campbell, C. A. and Souster, W. 1982. Loss of organic marter and potentially mineralizable nitrogen from Saskatchewan soils due to cropping. Can. J. Soil Sci. 62 651_656.

Capriel, P.

,

Beck, T., Borchert, H. and Harter,

p.

1990.

Relationship between soil aliphatic fraction extracted with super_ critical hexane, soil microbial biomass and soil aggregate stabiiity. Soil Sci. Soc. Am. J. 54 415-420. Carter, M. R. f986. Microbial biomass as an index for tillaselnluced changes in soil biological properties. Soil Tillage Res.-7:

29-40.

Carter, M. R. 1991. The influence of tillage on the proportion

adenine nucleotides and RNA of Mediterranean soils. Soil Biol.

Biochem. 25:739-746. Coleman, D. C., Brussard, L., Beare, M. H. Beare, Hendrix. P. F., Hassink, J., Heijnen, C. E. and Marinissen, P. F. 1989. Microbial-faunal interactions as they influence soil organic matter dynamics. Pages 175-179 in T. Hattori, Y. Ishida, Y. Maruyama, R. Y. Morita, and A. Uchida, eds. Recent advances in microbial ecology. Proc. Vth Int. Symp. Microbial Ecol., Kyoto, Japan. Conrad, R., Weber, M. and Seiler, W. 1983. Kinetics and electron transport of soil hydrogenases catalyzing the oxidation of atmospheric hydrogen. Soil Biol. Biochem. 15: 167-376. Dalal, R. C. and Henry, R. J. 1986. Simulraneous determination of moisture, organic carbon, and total nitrogen by near infrared reflectance spectrophotometry. Soil Sci. Soc. Am. J. 50: 120-123. Dalal, R. C. and Mayer, R. J. 1986. Long-term trends in fertility of soils under continuous cultivation and cereal cropping in Southern Queensland. IV. Loss of organic carbon from different density fractions. Aust. J. Soil Res. 24:.301-309. Dalal, R. C. and Mayer, R. J. 1987. Long-term rrends in fertility of soils under continuous cultivation and cereal cropping in Southern Queensland. VI. Loss oftotal nitrogen from different particle-size and density fractions. Aust. J. Soil Res. 25:83-93. de Jong, E. and Kachanoski, R. G. 19E8. The importance of erosion in the carbon balance ofprairie soils. Can. J. Soil Sci. 68: I I 1-1 19.

Dick, R. P. 1994. Soil enzyme activities

as indicators

of soil quality.

W. Doran, D. C. Coleman, D. F. Bezdicek, and B. A. Stewart, eds. Defining soil quality for a sustainable Pages 107-124 in J.

environment. Special Pub. 35, Soil Science Society of America Inc.,

Madison, WL Domsch, K. H., Jagnow, G. and Anderson, T.-H. 1983. An ecological concept for the assessment of side-effects of agrochemicals on soil microorganisms. Residue Reviews 86: 65-105. Doran, J. W. and Parkin, T. B. 1994. Defining and assessing soil quality. Pages 3-21 in J.W. Doran, D.C. Coleman, D.F. Bezdicek, and B.A. Stewart, eds. Defining soil quality for a sustainable environment. Special Pub. 35, Soil Science Society

of

America Inc., Madison, WI. Dormaar, J. F. 1983. Chemical properties of soil and water-stable aggregates after sixty-seven years of cropping to spring wheat. plant

of organic carbon and nitrogen in the microbiJ biomass of medium_ textured soils in a humid climate. Biol. Fertil. Soils l1: 135_139.

and Soil 75:51-61. Dubois, M., Gilles, K. A., Hamilton, J. K., Rebers, P. A. and Smith, F. 1956. Colorimetric method for determination of sugars

Carter, M. R., Angers, D. A. and Kunelius, H. T. 1994. Soil

and related substances. Anal. Chem. 28: 350-356. Duxbury, J. M. and Nkambule, S. V. 1994. Assessmenr and significance ofbiologically active soil organic nitrogen. pages 125-146 In J. W. Doran, D. C. Coleman, D. F. Bezdicek, and B. A. Stewart, eds. Defining soil quality for a sustainable environment. Special Pub. 35, Soil Science Society of America, Inc., Madison, WI. Ellert, B. H. and Bettany, J. R. f995. Calculation of organic matter stored in soils under contrasting management regimes. Can.

Carter, M. R. 1992. Influence of reduced tillage systems on organic matter, microbial biomass, macro-aggregate distribution and siruc_ tural stability of the surface soil in a humid climate. Soil Tillase Res. 23: 361-372. structural form and stability. and organic matter under cool-season perennial grasses. Soil Sci. Soc. Am. J. 58: l194-1199. Carter, M. R. and Rennie, D. A. 1982. Changes in soil oualitv under zero tillage farming systems: distribution of-microbial biomass and mineralizable C and N potentials. Can. J. Soil Sci. 62: 5g7_5g1.. Casida, L. E., Klein, D.A. and Santoro, T. 1964. Soil

activity. Soil Sci. 9g:3j l_3j6. Cheshire, M. V. 1977. Origins and stability of soil polysaccharide. J. Soil Sci. 28: 1-10. dehydrogenase

Cheshire, M. V. 1979. Nature and origin of carbohydrates in soils. Academic Press, Inc., London. U.K. Christensen, B. T. 1987. Decomposability of organic matter in particle size fractions from field soils with straw incomoration. Soil Biol. Biochem. 19: 429-435

Ciardi, D,, Ceccanti, B., Nannipieri, p., Casella, S. and Toffanin, A. 1993. Effect of various treatments on contents of

J. Soil Sci. (in press). Ellert, B. H. and Gregorich, E. G. 1994. Management-induced changes in the actively cycling fractions of soil organic matter in Proceedings of the 8th North American Forest Soils Conference. Gainsville, FL. American Society of Agronomy (in press). Elliott, E. T. 1986. Aggregate structure and carbon, nitrogen, and phosphorus in native and cultivated soils. Soil Sci. Soc. Am. J. 50: 627-633. Frankenberger, W. T., Jr. and Johanson, J. B. 1982. L-histidine ammonia-lyase activity in soils. Soil Sci. Soc. Am. I. 46:943-948. Frankenberger, W. T., Jr. and Tabatabai, M. A. 1991. Factors affecting L-glutaminase activity in soils. Soil Biol. Biochem. 23: 875-879.

GREGOR'CH ET AL.

-

ASSESSMENT OF

Frankenberger, W. T., Jr. and Dick, W. A. 19E3. Relationships between enzyme activities and microbial growth and activity indices

in soil. Soil Sci. Soc. Am. J. 47: 945-951. Greenland, D. J. and Ford, G. W. 1964. Separation of partially humifred organic materials from soils by ultrasonic dispersion. Trans. 8th Int. Cong. Soil Sci. Bucharest. ll: 137-147. Gregorich, E. G. and Anderson, D. W. 1985. Effects of cultivation and erosion on soils of four toposequences in the Canadian prairies. Geoderma 36: 343-354.

Gregorich, E. G. and Ellert, B. H. 1993. Light fraction

and

macroorganic matter in mineral soils. Pages 397-407 in M. R. Carter, ed. Soil sampling and methods of analysis. Can. Soc. Soil Sci.. Lewis Publishers, Division of CRC Press, Boca Raton, FL.

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

Gregorich, E. G., Ellert, B. H. and Monreal, C.

M.

1995.

Turnover of soil organic^matter and storage of corn residue carbon estimated from natrual "C abundance. Can. J. Soil Sci. (in press). Gregorich, E. G. and Jaruen, H. H. 1995. Storage of soil carbon in the light fraction and macroorganic matter. In M. R. Carter and B. A. Stewart, eds. Structure and organic matter storage in agricultural soils. Adv. Soil Sci. lrwis Publishers, CRC Press, Boca

Raton, FL (in press). Gregorich, E. G., Kachanoski, R. G. and Voroney, R. P. 1989. Carbon mineralization in soil size fractions after various amounts of aggregate disruption. J. Soil Sci. 40:- 649-659. Gupta, V. V. S. R. and Germida, J. J. 1986. Effect of cultivation on the activity of some soil enzymes. Pages 332-3M in Research

in agriculture. Proceedings of the Soils and Crops

Workshop. University of Saskatchewan, Saskatoon, SK. Gupta, Y. V. S. R. and Germida, J. J. 1988. Distribution of microbial biomass and its activity in different soil aggregate size classes as affected by cultivation. Soil Biol. Biochem. 20:-777-786. Harmsen, G. W. and van Schreven, D. A. 1955. Mineralization of organic nitrogen in soil. Adv. Agron. 7: 299-398. Harte, J. and Kinzig, A. P. 1993. Mutualism and competition between plants and decomposers: Implications for nutrient allocation in ecosystems. Am. Nat. 141: 829-846. Haynes, R. J. and Swift, R. S. 1990. Stability of soil aggregates in relation to organic constituents and soil water content. J. Soil Sci. 41: 73-83. Haynes, R. J., Swift, R. S. and Stephen, R. C. 1991. Influence of mixed cropping rotations (pasture-arable) on organic matter content, water-stable aggregation and clod porosity in a group of soils. Soil Tillage Res. 19: '17-87. Heinemeyer, O., Insam, H., Kaiser, E. A. and Walenzik, G. 19E9. Soil microbial biomass and respiration measurements: An automated technique based on infrared gas analysis. Plant and Soil

116: l9l-195. Hendrickson, O. Q. and Robinson, J. B. 1984. Effects of roots and litter on mineralization processes in forest soil. Plant and SoiI E0:391-405. Insam, H., Parkinson, D. and Domsch, K. H. 1989. Influence of macroclimate on soil microbial biomass. Soil Biol. Biochem.

2l 2ll-221.

Janzen, H. H. 1987a. Effect of fertilizer on soil productivity in long-term spring wheat rotations. Can. J. Soil Sci. 67: 165-174. Janzen, H. H. 1987b. Soil organic matter characteristics after longterm cropping to various spring wheat rotations. Can. J. Soil Sci. 67: 845-856. Janzen, H. H., Campbell, C. A., Brandt, S. A., Lafond, G. P. and Townley-Smith, L. 1992.L\gnt fraction organic matter in soils from long-term crop rotations. Soil Sci. Soc. Am. J. 56: 1799-1806. Jenkinson, D. S. 1977. Studies on the decomposition of plant material in soil. V. The effects of plant cover and soil type on the raC loss ofcarbon from labelled ryegrass decomposing under field conditions. J. Soil Sci. 2E 424-434.

SO't OFGAN'C MATTER IN AGRICULTURAL SO'LS 383 Jenkinson, D. S. 1987. Determination of microbial biomass carbon and nitrogen in soil. Pages 368-386 in J. R. Wilson, ed. Advances in nitrogen cycling in agricultural ecosystems' CAB International,

Wallingford, U.K. Jenkinson, D. S. 1990. The tumover of organic carbon and nitrogen in soil. Phil. Trans. R. Soc. Lond., Series B, Biol. Sciences 329 (1255): 361-368. Jenkinson, D. S. and Powlson, D. S. 196. The effects of biocidal treatments on metabolism in soil. V. A method for measuring soil biomass. Soil Biol. Biochem. 8: 209-213.

Jenny,

H.

1941. Factors

of soil

formation. McGraw-Hill

Publishers, New York, NY. Kanazawa, S. and Filip, Z. l9fl6. Distribution of microorganisms, total biomass, and enzyme activities in different particles of brown

soil. Microb. Ecol. 12:205-215. Keeney, D. R. 1980. Prediction of soil nitrogen availability in forest ecosystems: A Iiterature review. Forest Sci. 26:. 159-171. Keeney, D. R. 19E2. Nitrogen availability indices. hges 7ll:133 in A. L. Page, R. H. Miller, and D. R. Keeney, eds. Methods of soil analysis. Part 2. Chemical and microbiological properties. 2nd ed. Agronomy No. 9. American Society of Agronomy, lnc., Madison, WI. Khan, S. U. 1970. Enzymatic activity in a gray wooded soil as influenced by cropping systems and fertilizers. Soil Biol. Biochem.

2: 137-139. Klein, D. A.,

Sorensen, D.

L. and Redente, E. F.

1985. Soil

enzymes: A predictor of reclamation potential and progress. Pages

l4i-l':1 in R. L.

Tate and D.

L. Klein, eds. Soil reclamation

processes: microbiological analyses and applications. Marcel Dekker

Inc., New York and Basel. Ladd, J. N., Amato, M., Jocteur-Monrozier, L. andVan G€stal'

M.

1990. Soil microhabitats and carbon and nitrogen metabolism'

Trans. Int. Cong. Soil Sci. Kyoto, Japan. III: 82-87. Ladd, J. N. and Butler, J. H. A. 1972. Short term assays of soil

proteolytic enzymes activities using proteins and dipeptide derivatives as substrates. Soil Biol. Biochem. 4: 19-30. Larson, W. E. and Pierce, F. J. 191. Conservation and enhancement of soil quality. Pages 175-203 in Evaluation for sustainable Iand management in the developing world. Int. Board Soil Res. and Management (IBSRAM). Proc. 12 (Vol' 2)' Bangkok, Thailand. Lee. K. E. and Foster, R. C. 1991. Soil fauna and soil structure. Aust. J. Soil Res. 29:745-775. Liang, B. C. and MacKenzie, A. F. 1992. Changes in soil organic carbon and nitrogen after six years of corn production. Soil Sci' 153: 307-313. Linden, D. R., Hendrix, P. F., Coleman, D. C. and van Vliet' P. C. J. 1994. Faunal indicators of soil quality. Pages 91-106 in J. W. Doran, D. C. Coleman, D. F. Bezdicek, and B' A. Stewart, eds. Defining soil quality for a sustainable environment. Special Pub. 35, Soil Science Society of America Inc., Madison, WI. Lowe, L. E. 1993. Total and labile polysaccharide analysis of soils. in M. R. Carter, ed. Soil sampling and methods of analysis, Canadian Society of Soil Science, Lewis Publishers, Division of CRC Press, Boca Raton, FL. Malone, C. R. and Swartout, M. B. 1969. Size, mass, and caloric content ofparticulate matter in old-field and forest soils. Ecology 50: 395-399. Martens, D. A. and Frankenberger, W. T., Jr. 1990. Quantification of soil saccharides by spectrophotometric methods. Soil Biol. Biochem. 8: 1173-1175.

Martens, D. A., Johanson, J. B. and Frankenberger, W. T. 1992. Production and persistence of soil enzymes with repeated addition of organic residues. Soil Sci. 153: 53-61. McGill, W. B. and Figueiredo, C. T. f993. Total nitrogen. Pages

201-211,/, M. R. Carter, ed. Soil sampling and methods of analysis. Canadian Society of Soil Science, Lewis Publishers, Division of CRC Press, Boca Raton, FL.

384

CANADIAN JOIIRNAL OF SO't SC'ENCE

McGill, W. 8., Cannon, K. R., Robertson, J. A. and Cook,

F. D. 1986. Dynamics of soil microbial biomass and water-soluble organic C in Breton L after 50 years ofcropping to two rotatlons. Can. J. Soil Sci. 66: 1-19. McKeague, J. A. 1971. Organic matter in particulate-sized and specific gravity fractions of some Ah horizons. Can. J. Soil Sci.

5l:

499-505.

Mele, P. M. and Carter, M. R. 1993. Effect of climatic factors on the use of microbial biomass as an indicator of changes in soil organrc matter. Pages 57-63 in K. Mulongoy and R. Merckx, eds.

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

Soil organic matter dynamics and sustainability of tropical agricul_

ture. John Wiley & Sons, Chichester and New york. Miller, R. D. and Johnson, D. D. 1964. The effect of soi.l moisture tenslon on carbon dioxide evolution, nitrification, and nitrogen mineralization. Soil Sci. Soc. Am. proc. 2g: 644_647. Molloy, L. G., Bridger, B. A. and Cairns, A. lgi7. Studies on a climosequence of soils in tussock grasslands. 13. Structural carbohydrates in tussock leaves, roots, and litter and in the soil lisht and heavy fracrions. N.Z. J. Sci. 20: 443-451. Monreal C.M., McGiil, W. B. and Nyborg, M. 19g6. Spatial heterogeneity of substrates: Effects on hydrolysis, immobilization and nitrification of urea-N. Can. J. Soil Sci. 66: 499_511. Morra, M. J., Hall, M. H. and Freeborn, L.L. lggl. Carbon and nitrogen analysis of soil fractions using near-infrared reflec_ tance spectroscopy. Soil Sci. Soc. Am. J. 55: 2gg_291. Nadelhoffer, K. J., Giblin, A. E., Shaver, G. R. and Laundre, J. A. 1991. The effects of temperature and substrate quality on element mineralization in six Arctic soils. Ecology 7i: 242-253. Nelson, D. W. and Sommers, L.E, lgg2. Total carbon, organic carbon and organic matter. pages 539-5l-g in A. L. pagel ed. Methods of soil analysis. part 2. Chemical and microbiolosical

properties. Agronomy No. 9. 2nd ed. American Societ! of Agronomy, Inc., Madison, WI. Nordgren, A-. 1988. Apparatus for the continuous, long-term t^n9ltlgrTg_of soil respiration rate in large numbers of samples. Soil Biol. Biochem. 20: 955-95't . Oades, J. M., Kirkman, M. A. and Wagner, G. H. 1970. The use of gasJiquid chromatography for the determination of susars extracted from soils by sulfuric acid. Soil Sci. Soc. Am. proc.l4: 230-235. Parkirson, D. and Coleman, D. S. 1991. Microbial communities, activity and biomass. Agric. Ecosyst. Environ. 34 3_33. Paul, E. A.. and Voroney, R. p. 1980. Nutrient and energy flows through soil microbial biomass. pagesZl5-237 inD. C. Ellwood et al., eds. Contemporary microbial ecology. Academic press, Inc., London, U.K. 'Paustian, K., Parton, W. J. and persson, J. lgg2. Modeline

soil organic Talter in organic-amended and nitrogen fenilized tongl term plots. Soil Sci. Soc. Am. J. 56:4j6-4gg. Peterjohn, W. T. 1991. Denitrification: erzyme content and activity in desert soils. Soil Biol. Biochem. 23: 945_g55. Pierce, F. J. and Larson, W. E. 1993. Developins crireria to

evafuate sustainable land managemenrs. pages i_l+ i, t. U. Kimble, ed. Proceedings of the VIII International Soil Manasement Workshop. Utilization of soil survey information for sustiinable land use. Sacramento, CA. Rasmussen, P. E., Allmaras, R. R., Rohde, C. R. and Roager, N. C. 1980. Crop residue influences on soil carbon and nitrosen in a wheat-fallow sysrem. Soil Sci. Am. J. 44: 596-600. Rennie, D A., Truog, E. and Allen, O. H. 1954. Soil aggrega_ tion as influenced by microbial gums, level fertility and kind of crop. Soil Sci. Soc. Am. proc. 18: 399-403. Roberson, E. B., Sarig, S. and Firestone, M. K. 1991. Cover

crop management of polysaccharide-mediated aggregation in an orchard soil. Soil Sci. Soc. Am. J. 55: 734-'739. Ross, D. J. 1992. Influence of sieve mesh size on estimates of microbial carbon and nitrogen by fumigation-extraction procedures in soils under pasture. Soil Biol. Biochem. 24: 343-350. Ross, D. J., Speir, T. W., Cowling, J. C. and Whale, K. N. 19E4. Temporal fluctuations in biochemical properties of soil under pasture. II. Nitrogen mineralization and enzyme activities. Aust. J. Soil Res. 22:319-330. Salcedo, I. H., Sampaio, E. Y. S. B. and Alves, G. D. f985. Mineralizaqdo do carbono e do nitrog€nio em solo cultivado com cana-de-agricar. ICarbon and nitrogen mineralization in soil cultivated with sugarcane.l Revista Brasileira de Ciencia do Solo 9:

33-38. Sarkisyan, S. S. and Shur-Bagdasaryan, E. F. 1967. Interaction of vegetation and soils on various mountain steppe pastures overgrazed and eroded to different extents. Pochvovednie 12 37-44 Sato, F., Omura, H. and Hayano, K. 1986. Adenosine deaminase activity in soils. Soil Sci. Plant Nutr. 32: 107-112. Scheffer, B. 1977. Stabilization of organic matter in sand mixed cultures. Pages 359-363 ln Soil organic matter studies. Vol. II. IAEA and FAO. Schnitzer, M. 1991. Soil organic matter. The next75 years. Soil Sci. 151: 41-58. Shaymukhametov, M. S., Titova, N. A., Travnikova, L. S. and Labenets, Y. M. f9E4. Use of physical fractionation methods to characterize soil organic matrer. Soviet Soil Sci. 16 ll7-128. Skopp, J., Lawson, M. D. and Doran, J. W. 1990. Steady-state aerobic microbial activity as a function of soil water content. Soil Sci. Soc. Am. J. 54: 1619-1625. Skujins, J. 1967. Enzymes in soil. Pages 371-40'7 in A. D. Mclaren and G. H. Peterson, eds. Soil biochemistry. Marcel Dekker, New York, NY. Skujins, J. f978. History ofabiontic soil enzyme research. pages 295-326in R. G. Burns, ed. Soil enzymes. Academic press, Inc., London, U.K. Sollhs, P., Spycher, G. and Glassman, C. A. 1984. Net nitrogen mineralization from light- and heavy-fraction forest soil organic matter. Soil Biol. Biochem. 16:.31-37. Sparling, G. P. 1992. Ratio of microbial biomass carbon to soil organic carbon as a sensitive indicator of changes in soil organic matter. Aust. J. Soil Res. 30: 195-20'7. Sparling, G. P. and Ross, D. J. f993. Biochemical methods to estimate soil microbial biomass: Current developments and applications. Pages2l-37 in K. Mulongoy and R. Merckx, eds. Soil organic matter dynamics and sustainability of tropical agriculture. John Wiley & Sons, Chichester, U.K. Sparling, G. P. and West, A. W. f990. A comparison of gas chromatography and differential respirometer methods to measure

soil respiration and to estimate the soil microbial

biomass.

Pedobiologia 34: 103-112. Spycher, G., Sollins, P. and Rose, S. 1983. Carbon and nitrogen in the light fraction of a forest soil: vertical distribution and seasonal patterns. Soil Sci. 135:79-87. Stanford, G. and Epstein,E. 1974. Nitrogen mineralization-water relations in soils. Soil Sci. Soc. Am. Proc. 38: 103-107.

Stanford, G., Frere, M. H. and Schwaniger, D. E. 1973. Temperature coefficients of soil nitrogen mineralization. (Soil Sci.

ll5

321-323.

Tabatabai, M. A. and Bremner, J. M. 1%9. Use of p-nitrophenyl phosphate for assay of soil phosphatase activity. Soil Biol. Biochem. l: 301-307. Tabatabai, M. A. and Bremner, J. M. 1970. Arylsulfatase activity of soils. Soil Sci. Soc. Am. Proc. 34: 225-229.

GREGOR'CH ET AL.

_

ASSESSMENT OF

Tabatabai, M. A. 19E2. Soil enzymes. Pages 903-943 in A. L. Page, R. H. Miller, and D. R. Keeney, eds. Methods of soil analysis. Part 2. Chemical and microbiological properties. 2nd ed. Agronomy

No. 9. American Society of Agronomy, Inc., Madison, WI. Tiessen, H. and Moir, J. O. 1993. Total and organic carbon. Pages 187-199 rn M. R. Carter, ed. Soil sampling and methods of analysis. Canadian Society of Soil Science, Lewis Publishers, Division of CRC Press. Boca Raton, FL. Tiessen, H. and Stewart, J. W. B. 1983. Particle-size fractions and their use in studies of soil organic matter: II. Cultivation effects on organic matter composition in size fractions. Soil Sci. Soc. Am.

Can. J. Soil. Sci. Downloaded from pubs.aic.ca by Agriculture and Agri-food Canada on 09/27/11 For personal use only.

J. 47: 509-514. Tiessen, H., Stewart,

J. W. B. and Bettany, J. R.

1982.

Cultivation effects on the amounts and concentration of carbon, nitrogen and phosphorus in grassland soils. Agron. J. 74: 831-835. Tisdall, J. M. and Oades, J. M. 1979. Stabilization of soil aggregates by the root system of ryegrass. Aust. J. Soil Res. 17: 429-441. Tsai, Y-L. and Olson, B. H. 1992. Detection of low numbers of bacterial cells in soils and sediments by polymerase chain reaction.

Appl. Environ. Microbiol. Turchenek, L. W. and Oades, J.

58:. 754-75'1

.

M. 1979. Fractionation of organo-mineral complexes by sedimentation and density techniques. Geoderma

2L:3ll-343.

SO't ORGANIC MATTER IN AGRICULTURAL SO'LS 385 Verstraete. W. and Voets, J. P.1977. Soil microbial and biochemical characteristics in relation to soil management and fertility. Soil

Biology Biochem. 9: 253-258.

Yissei, S. and Parkinson, D. 1992' Soil biological criteria

as

indicators of soil qualiry: soil microorganisms. Am. J. A-ltem. Agnc' t: 53-3 t. Voroney, R. P., Van Veen, J' A. and Paul, E. A. 1981. Organic C dynamics in grassland soils. 2. Model verihcation of cultivation effects and predictions oflong-term erosion influences. Can. J. Soil

Sci. 61: 2ll-224.

Yoroney, R. P., winter, J. P. and Beyaert, R' P' 1993' Soil

microbial biomass C and N. Pages 277-286 in M. R. Carter, ed. Soil sampling and methods of analysis. Canadian Society of Soil Science,

t ewis Publishers, Division of CRC Press' Boca Raton, FL'

R.L. 1924' Microbiological analysis of soil as an index of soil fertility. VII. Carbon dioxide evolution. Soil Sci. 17: 141-161. Wu. J. and Brookes, P. C. 1988. Microbial biomass and organic Waksman, S. A. and Starkey,

matter relationships in arable soils. J. Sci. Food Agric. 45: 138-139.

Zhang, H., Thompson, M. L. and Sandor, J. A. 1988. Compositional differences in organic matter among cultivated and uncultivated Argiudolls and Hapludalfs derived from loess. Soil Sci.

Soc. Am.

J. 52:216-222.