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A statistical evaluation of equations for predicting total microbial biomass carbon using physiological and biochemical methods
Agriculture, Ecosystems and Environment, 34 ( i 991 ) 75-86
75
Elsevier Science Publishers B.V., Amsterdam
A statistical evaluation of equations for predicting total microbial biomass carbon using physiological and biochemical methods D.A. Wardle* and D. Parkinson Department of Biological Sciences, Universityof Calgary, 2500 UniversityDrive, N. W., Calgary, Alberta (Canada) (Accepted for publication 5 July 1990 )
ABSTRACT Wardle, D.A. and Parkinson, D., i 991. A statistical evaluation of equations for predicting total microbial biomass carbon using physiological and biochemical methods. Agric Ecosystems Environ., 34: 75-86. The proposed calibration equations for quantifying microbial biomass carbon were considered and variability associated with these methods was assessed., The fumigation-incubation (FI) method depends on a kc factor for biomass C determination. Three kc values are commonly in use, i.e. 0.41, 0.45 and 0.50, but these all have an associated degree of variability. However, values of kc may also vary between certain soil treatments and between soil types. Substrate-induced respiration (SIR) has been calibrated against FI but the strength of the relationship between the two methods is uncertain in most instances because SIR measures glucose-responsive microbial biomass while FI measures chloroform-susceptible biomass. ATP and ninhydrin-extractable N analysis may show strong relationships with FI but only in specific circumstances. Fumigation-extraction (FE) demonstrates uncertain relationships when calibrated against SIR, possibly because FE measures chloroform-susceptible biomass. Calibrations of FE against FI also appear to be uncertain probably because kc and k~ values vary differently across soil types.
INTRODUCTION
Methods for quantifying the soil microbial biomass have been assessed recently by various workers (see Jenkinson, 1988) and it is apparent that physiological and biochemical methods are now used most frequently for this purpose. Fumigation-incubation (Jenkinson, 1966; Jenkinson and Powlson, 1976) was amongst the first b iomass methods, and provides actual mass data against which many recently derived methods have been calibrated. The purpose of this paper is to evaluate the proposed equations for quantifying total microbial biomass C, and to assess the variability associated with the parameters of these equations. Where necessary, the data used to calibrate these equations have been transformed and manipulated in order to satisfy * Present address: Ruakura Agricultural Research Centre, Private Bag, Hamilton, New Zealand. 0167-8809/91/$03.50
© 1991 - - Elsevier Science Publishers B.V.
76
D.A. WARDLE AND D. PARKINSON
the assumptions required for parametric analysis, and, where appropriate, new equations have been derived. FUMIGATION-INCUBATION (FI) METHOD
Microbial biomass C is calculated using a kc factor, i.e. the fraction of microbial biomass C mineralized in 10 days (Jenkinson and Powlson, 1976). Three separate kc values have been proposed, i.e. 0.50 (Jenkinson, 1976; Sorenson, 1987), 0.41 (Anderson and Domsch, 1978a; Robertson et al., 1988) and 0.45 (Oades and Jenkinson, 1979; Powlson et al., 1987) from experiments with pure cultures of bacteria and fungi. The value of 0.50 was first proposed by Jenkinson (1976) based on 13 organisms including four fungi, eight bacteria and one earthworm species. Because fungi appear to be the dominant biomass component in most soils (Parkinson, 1973; Anderson and Domsch, 1975 ) a kc value weighted toward bacteria is probably inappropriate. The percentage of fungal carbon released (average of four species ) was 53.4%; that for bacteria was 48.1%. By varying the bacterial: fungal ratio (from 10: 90 to 50: 50 ) and by providing a measure of variability (Snedecor and Cochran, 1980, pp. 96-98 ) the possible range of kc values was determined (excluding outlying data from Nitrosomonas europaea). The 95% confidence intervals for the kc values across this range of ratios ranged from 0.499 to 0.576, with a mean of 0.53 when a bacterial: fungal ratio of 25 : 75 was used. The value of 0.41 (Anderson and Domsch, 1978a) was based on decomposition of 16 fungal and 12 bacterial species, averaged over four soils and using a bacterial: fungal ratio of I : 3. However, because these ratios may vary both between treatments and between soils, the data presented by Anderson and Domsch (1978a) were recalculated for each of the four soils (and their average ) for a number of bacterial: fungal ratios (Table 1 ). The kc factors for three soils were not significantly different from each other across most of the given bacterial: fungal ratios while the k¢ value for the fourth was significantly lower than all the others for all such ratios. When the variability of all four soils and of the bacterial: fungal ratios is considered, the appropriate kc value could be anywhere between 0.33 and 0.47. The value of 0.45 (Oades and Jenkinson, 1979) was introduced to correct the 0.41 value (Anderson and Domsch, 1978a) for use at 25 °C rather than 22°C. The variability associated with the k~ values currently in use is not excessive and may not be important in comparative studies. However, the k~ value may be influenced by large variations in bacterial: fungal ratios which may result from variations in tillage regime (Hendrix et al., 1986), sulphur content (Bewley and Parkinson, 1985 ) or herbicide addition (Wardle and Parkinson, 1990). Furthermore, it is usually assumed that kc values remain invariant across the range of treatments or soils considered in a given study.
50:50 40:60 30:70 25:75 20:80 10:90
Bacterial: fungal ratio [0.386,0.422] [0.398,0.432] [0.407,0.443] [0.411,0.449] [0.415,0.455] [0.423,0.467]
0.398,0.430 0.405,0.437 0.412,0.444 0.414,0.448 0.417,0.453 0.423,0.461
0.404 0.415 0.425 0.430 0.435 0.445
0.414 0.421 0.428 0.431 0.435 0.442
95% CI
k~
k¢
95% CI
Soil II
Soil I
0.390 0.402 0.413 0.418 0.424 0.435
k¢
Soil III
0.369,0.411 0.382,0.422 0.392,0.434 0.396,0.440 0.401,0.447 0.410,0.460
95% CI
95% CI [0.308, [0.321, [0.333, [0.334, [0.345, [0.356,
k¢ 0.330 0.343 0.356 0.363 0.370 0.383
Soil IV
0.352] 0.365 ] 0.379] 0.387] 0.395] 0.410]
0.385 0.395 0.406 0.411 0.416 0.426
k¢
All soils
[0.325, [0.339, [0.352, [0.359, [0.367, [0.380,
95% CI 0.445 0.452 0.4591 0.462 0.465 0.472
Values for k¢, derived from the data of Anderson and Domsch (1978a), corrected for varying bacterial: fungal ratios, for each of the four soils used and the mean of all four soils
TABLE 1
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~r
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78
D.A. WARDLE AND D. PARKINSON
However, kc varies with such factors as pH (Vance et al., 1987a), soil moisture content (Ross, 1987; Wardle, 1989 ), microbial species composition (Nicolardot et al., 1984) and the physiological condition of the biomass (Ross et al., 1987). Also, kc values vary between soil types (Nicolardot et al., 1984; Table 1 ), and between samples of the same soil type (Wardle, 1989 ). For some soil types, a kc value of 0.41 for incubations at 22°C is probably the most appropriate, because Anderson and Domsch (1978a) provided the most realistic statistical evaluation. However, values of k~ have been determined only for a narrow range of soils and conditions. None of the soils used for determining the three commonly used kc values had over 4% organic carbon, and all but one were arable soils. Van de Werf and Verstraete (1987b) experimentally determined anfsd factor (fraction of microbial biomass catabolized in 5 days; analogous to the kc factor) for seven soils. The mean fSd value was 0.511 with a 95% CI of [0.481.621 ]. The soils used in their determination were relatively heterogeneous with an organic C range from 0.11 to 6.12%. Recalculation of these data indicates that the fsd factor is influenced by soil organic matter content ( Spearmans rank correlation coefficient between OM andfsd = 1.00; P < 0.01; n = 7 ) and may not be appropriate for all soils. SUBSTRATE-INDUCED RESPIRATION (SIR)
Anderson and Domsch (1978b) determined the maximum initial respiratory response of 12 soils to glucose and calibrated these against biomass values determined using FI for the same soils. This yielded the following predictive equation: Y= 4.004X+ 3.7, r = 0.96 where Y=/zg biomass C g soil- t and X = ml CO2 C h - I 100 g soil- i. However, this calibration is problematic because two highly organic soils were included; these soils had substantially higher biomass values than the other 10 and clearly belonged to a different "'population" of soils. Furthermore, the 12 soils included in their analysis were unequally represented, and thus unequally weighted. Data from Fig. 6 of Anderson and Domsch ( 1978b), excluding the two highly organic soils, were reanalysed, giving all soils equal weighting. This resulted in 10 points, i.e. one point per soil. This yields a new equation of: Y=416.7X+ 16.2, r=0.82 However, the value of r has a 95% CI of [0.360, 0.956 ]. Therefore there are insufficient data to determine whether a strong relationship between the two methods exists (Fig. 1 ). Martens (1987) proposed "improvements" (continuous aeration of soil
PREDICTINGTOTALMICROBIALBIOMASSCARBON 1000
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Y=416.7X+16.2
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C02evolution (rnJ, h-IlOOg soil - I ) (X) Fig. 1. Modified calibration o f Anderson and D o m s c h (1978b) for determining microbial biomass using the substrate-induced respiration technique. Dashed lines represent 95% confidence bands for the expected values of Y from any value of X.
samples) to the SIR technique of Anderson and Domsch (1978b) based on 22 soils followingcalibration against FI. The following equation was proposed: Y = 4 9 5 X - 167, r=0.978 Although Martens' (1987) equation does not differ significantly from that of Anderson and Domsch (1978b) (tested using ANCOVA), two "populations" of soils appear to contribute to the calibration curve ( 16 "inorganic" soils of < 3% C and six "organic" soils of > 7% C) and two separate equations can then be presented, i.e. inorganic soils:Y=235X+ 68.7, n = 16, r--0.917 95% CI for r= [0.773, 0.971 ] organic soils: Y = 4 9 0 X - 143, n=6, r=0.974 95% CI for r - [0.776, 0.997] These two equations significantly differ from each other at P = 0.001 (Fig. 2 ) and may be more reliable for the respective groups of soils. Two other studies have included calibrating SIR against other methods. One of these (West and Spading, 1986) involved calibrating SIR against biovolume-derivedbiomass C values, i.e. Y=433 logio W+ 5.92, r=0.84 W=/tl CO2 h - l g- 1soil This equation was based on 14 data points, but only three soils (6, 4 and 4
80
D.A. WARDLEAND D. PARKINSON organic : Y=489.7X-142.7 1600
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inorganic : Y=234.7X+68.7
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Fig. 2. Modified calibration of Martens (1987) for determining microbial biomass C using the substrate-induced respiration technique. Dashed or dotted lines represent 95% confidence bands for the expected values of Y from any value of X.
points from each soil, respectively). This does not fulfil the assumption of non-independenceamongst X and amongst Y values. Furthermore the points from each soil form relatively distinct clusters. The SIR equations derived by West et al. (1986) involved calibration against FI-derived biomass (i.e. Y= 40.92 W+ 12.9, r = 0.93 ) and against bivolume-derived biomass (for the same samples) (i.e. Y= 447 log t0 W+ 112, r=0.91 ). These calibrations involved 12 points but again from only three soils with 5, 4 and 3 data points from each soil, respectively. These calibrations are both strongly influenced by four points from one soil type which form a tight cluster at the lower end of the slope. Other studies have indicated uncertain and poor relationships between FI and SIR (Spading et al., 1986; Wardle, 1989; and data presented by Spading and West, 1988b). Uncertain relationships between FI and SIR may be explained by differences in the components of the microbial biomass included. FI measures those organisms killed by chloroform, including active and some inactive components, although this fumigation may be incomplete (Ingham and Horton, 1987). If the glucose response is restricted primarily to active organisms (van de Werf and Verstraete, 1987a) or r-selected organisms (Gerson and Chet, 1981 ) then SIR may apply only to a fraction of the total microbial biomass. Therefore strong correlations between FI and SIR can only be expected when the fraction of microbial biomass which is glucose-responsive is consistent across samples, or when the range of biomass values is so large that variations in this fraction become insigificant by comparison.
PREDICTING TOTAL MICROBIAL BIOMASS CARBON
81
ATP CONTENT OF SOIL
Soil ATP values were calibrated against FI-derived biomass values for 11 soils (Oades and Jenkinson, 1979) and later modified to include six more points, which yielded an equation of (Jenkinson et al., 1979) Y= 116.3A+43.8, r=0.975, n = 17 where A = A T P in #g g- ' dry weight. The 95% CI for r was found in the present study to be 0.928-0.991 indicating a strong relationship between data from the two methods. Despite this, other studies suggest that this relationship may be much weaker under certain storage conditions and seasonal stresses (Ross et al., 1981; Spading et al., 1981; Ahmed et al., 1982 ), possibly due to different metabolic states of the microbial biomass under different environmental conditions (Ross et al., 1981 ). NINHYDRIN-REACTIVE NITROGEN COMPONENT OF SOIL
Amato and Ladd ( 1988 ) calibrated this method against FI biomass for 25 soils, incubated for 44 and 66 weeks, and proposed this as a method for measuring microbial biomass C. The strongest relationship was for soils incubated for 44 weeks, i.e. Y= 2 4 . 4 N - 56, r=0.96 where N = ninhydrin-reactive N (#g g- ' ) extracted after fumigation. To as1.355
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10.0
15.0
20.0
25.0
30.0
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nitrogen
(lugcJ-Isoil)
(N)
Fig. 3. M o d i f i e d c a l i b r a t i o n o f A m a t o and l_add ( 1988 ) for d e t e r m i n i n g m i c r o b i a l biomass C
using the ninhydrin-extractableN technique. Dashed lines represent 95% confidence bands for the expected value of Yfrom any value of N.
82
D.A. WARDLE AND D. PARKINSON
sess the strength of the relationship between Y and N more thoroughly, data for these two variables were transformed using the log~ transformation (present study) since they were otherwise not normally distributed (tested using the Wilk-Shapiro statistic; Shapiro and Wilk, 1965 ). When this was done the relationship becomes: Y= 7.58N 1355, 95% CI for r = [0.903, 0.980] This curve is not very different from the more easily applied linear form provided by Amato and Ladd ( 1988 ). However, log-log transformation was necessary to place 95% confidence bands about the predicted values of Y (Fig. 3). The determination of microbial biomass C using ninhydrin-reactive N appears to be appropriate for lower but not higher values of biomass (i.e. > 200/tg biomass C g soil- ~) because variability of predicted values of Y increases as N increases. FUMIGATION-EXTRACTION (FE) METHOD
Vance et al. ( 1987b ) calibrated this method against FI using 10 data points (i.e. Y= 2.641I, r = 0.99; V= flush of extractable C following fumigation in/~g g- ~). Because one sample had nearly four times more biomass than any of the others they also proposed an equation using only nine data points (i.e. Y= 2.781I, r = 0.95 ). However, they justified leaving the outlier point on the calibration because it had no major effect on the regression equation. However, in the present study it has been excluded since it renders the data nonnormal. The same results as Vance et al. (1987b) could not be obtained upon recalculation of their data, and the calibration equation obtained in the present study was: Y=3.16V-4.87, r=0.874 95% CI for r = [0.501, 0.973] Because the lower limit of the CI for r is very low (explaining only 25% of the variability in the data set) this study indicates that FE is an uncertain predictor of FI. Tate et al. (1988) also attempted to calibrate FE against FI. From their data the following relationship has been derived (present study): Y= 1.54V+314.8, r=0.730, n = 2 4 Because the value for r is low (explaining only 53% of the variability in the data set) this study also demonstrates FE to be an uncertain biomass predictor of FI. Two studies have also involved calibrating FE against SIR-derived biomass C determined using SIR. One of them (Sparling and West, 1988a) used 26 inorganic soil samples and resulted in the following equation:
PREDICTINGTOTALMICROBIALBIOMASSCARBON
83
Y = 1.85 V+242, r=0.89, 95% for r = [0.776, 0.949]
The lower limit for r indicates that as little as 59% of the total variability in the data set may be explained. Also, in the construction of that calibration curve, 10 of the data points (including all those at the lower end of the curve) represent soils from one agroforestry project, and two other locations were also represented by more than one point. In the present study, the calibration equation was recalculated using the average value for each location as one data point. The equation then becomes: Y=2.41V+116.5, r=0.913, n = 13, 95% CI for r= [0.740, 0.975] The 95% confidence bands for this equation are shown in Fig. 4. Spading and West ( 1988b ), using 11 soils, performed a similar calibration: Y= 1/'/0.39 or Y=2.56V, r=0.93, n = 11 In the present study, the equation was redetermined excluding the other two soils, since they may belong to a different "population" of soils, and had anamalously low values for the C flush determined using FI or FE. This equation becomes: Y=2.68V-44.1, r=0.891, n = 9 95% CI for r = [0.714, 0.997] This equation again indicates an uncertain strength in the relationship between FE and SIR. 1600-
1 /
Y=2.411V+116.5
1400,
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Fig. 4. Modified calibration of Spading and West (1988a) for determining microbial biomass C using the extractable C content of soil. Dashed lines represent 95% confidence bands for the expected value of Y from any value of V.
84
D.A. WARDLE AND D. PARKINSON
Weak interactions may be expected between FE and SIR, since FE measures those microorganisms killed by chloroform (active and probably some inactive) while SIR measures only glucose-responsive biomass (as discussed previously). However, uncertain relationships between FI and FE are more problematic and indicate that the fraction of biomass C extracted using FE (i.e. the kec factors) and the fraction of biomass C evolved as CO2C using FI (i.e. the kc factor) may vary differently across soil samples. This is further supported by studies that have attempted to determine kec values directly in soil. Tate et al. (1988) determined that kec values for individual microbial species may range from 0.13 to 0.34. Sparling and West (1988a) determined that microbial biomass labelled in situ with 14C had k¢c values ranging from 0.25 to 0.38 in different soils. These studies indicate that k~c may be highly variable. CONCLUSIONS
Calibration equations for quantifying total microbial biomass may be relatively weak, especially when their associated variability is taken into account. In part this is probably because most methods may be sensitive to only a certain component of the total microbial biomass. These methods have also been performed mostly on only certain soil types, and mostly inorganic ( < 8% organic C) soils from temperate regions. Calibrations may be influenced by the sampling strategy used for selection of such soils, and it is important for the development of effective calibration equations that the population of soils be defined and independent data points (satisfying assumptions of normality) are extracted from this. REFERENCES Ahmed, M., Oades, J.M. and Ladd, J.N., 1982. Determination of ATP in soils: effect of soil treatment. Soil Biol. Biochem., 14: 273-279. Amato, M. and Ladd, J.N., 1988. Assay for microbial biomass based on ninhydrin-reactive nitrogen in extracts of fumigated soils. Soil Biol. Biochem., 20:107-110. Anderson, J.P.E. and Domsch, K.H., 1975. Measurement of bacterial and fungal contributions for respiration of selected agricultural and forest soils. Can. J. Microbiol., 21 : 314-322. Anderson, J.P.E. and Domsch, K.H., 1978a. Mineralisation of bacterial and fungi in chloroform-fumigated soils. Soil Biol. Biochem., 10:207-213. Anderson, J.P.E. and Domsch, K.H., 1978b. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem., 10:215-221. Bewley, R.J.F. and Parkinson, D., 1985. Bacterial and fungal activity in sulphur dioxide polluted soils. Can. J. Microbiol., 31: 13-15. Gerson, U. and Chet, I., 1981. Are allochthonous and autochthonous soil microorganisms r- and K-selected? Rev. Ecol. Biol. Sol., 18: 285-289. Hendrix, P.F., Parmelee, R.W., Crossley, D.A. Jr., Coleman, D.C., Odum, E.P. and Groffman, P.M., 1986. Detritus food webs in conventional and no tillage ecosystems. Bioscience, 36: 374-380.
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lngham, E.R. and Horton, K.A., "1987. Bacterial, fungal, and protozoan responses to chloroform fumigation in stored soil. Soil Biol. Biochem., 19: 545-550. Jenkinson, D.S., 1966. Studies on the decomposition of plant material in soil. II. Partial sterilisation of soil and the soil biomass. J. Soil Sci., 17: 280-302. Jenkinson, D.S., 1976. The effects ofbiocidal treatments on metabolism in soil. IV. The decomposition of fumigated organisms in soil. Soil Biol. Biochem., 8: 203-208. Jenkinson, D.S., 1988. Determination of microbial biomass carbon and nitrogen in soil. In: J.B. Wilson (Editor), Advances in Nitrogen Cycling. CAB International, Wallingford, UK, pp. 368-386. Jenkinson, D.S. and Powison, D.S., 1976. The effects of biocidal treatments on soil metabolism in soil. V. A method for measuring soil biomass. Soil Biol. Biochem., 8:209-213. Jenkinson, D.S., Davison, S.A. and Powlson, D.S., 1979. Adenosine triphosphate and microbial biomass in soil. Soil Biol. Biochem., 11: 521-527. Martens, R., 1987. Estimation of microbial biomass in soil by the respiration method: importance of soil pH and flushing methods for the measurement of respired CO2. Soil Biol. Biochem., 19: 77-81. Nicolardot, B., Chaussod, R. and Catroux, G., 1984. Decomposition de corps microbiens dans des sols fumig6s au chloroforme: effets du type de soil et de microorganisme. Soil Biol. Biochem., 16" 453-458. Oades, J.M. and Jenkinson, D.S., 1979. Adenosine-triphosphate content of the soil microbial biomass. Soil Biol. Biochem., I l: 201-204. Parkinson, D., 1973. Techniques for the study of soil fungi. Bull. Ecol. Res. Commun. (Stockholm), 17: 29-36. Powlson, D.S., Brookes, P.C. and Christensen, B.T., 1987. Measurement of soil biomass provides an early indication of changes in total soil organic matter due to straw incorporation. Soil Biol. Biochem., 19:159-216. Robertson, K., Schniirer, J., Clarholm, M., Bonde, T.A. and Rosswall, T., 1988. Microbial biomass in relation to C and N mineralisation during laboratory incubations. Soil Biol. Biochem., 20" 281-286. Ross, D.J., 1987. Soil microbial biomass estimated by the fumigation incubation procedure: seasonal fluctuations and influence of soil moisture content. Soil Biol. Biochem., 19: 347404. Ross, D.J., Tate, K.R., Cairns, R. and Meyrick, K., 1981. Fluctuations in microbial biomass indices at different sampling times in soils from tussock grasslands. Soil Biol. Biochem., 13: 109-114. Ross, D.J., Spading, G.P. and West, A.W., 1987. Influence ofFusarium oxysporum age on proportions of C, N, and P mineralised after chloroform fumigation of soil. Aust. J. Soil Res., 25: 363-566. Shapiro, S.S. and Wilk, M.B., 1965. An analysis of variance test for normality (complete samples). Biometrika, 52:591-611. Snedecor, G.W. and Cochran, W.G., 1980. Statistical Methods, 7th edn. The Iowa State University Press, Ames, Iowa. Sorensen, L.H., 1987. Organic matter and microbial biomass in a soil incubated in the field for 20 years with ~4C-labelled barley straw. Soil Biol. Biochem., 19: 39-42. Spading, G.P. and West, A.W., 1988a. A direct extraction method to estimate soil microbial C: calibration in situ using microbial respiration and 14C-labelled cells. Soil Biol. Biochem., 20: 337-343. Spading, G.P. and West, A.W., 1988b. Modifications to the fumigation-incubation technique to permit simultaneous extraction and estimation of soil microbial C and N. Commun. Soil Sci. Plant Anal., 19: 327-344.
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Spading, G.P., Ord, B.G. and Vaughan, D., 1981. Microbial biomass and activity in soils amended with glucose. Soil Biol. Biochem., 13: 99-104. Spading, G.P., Speir, T.W. and Whale, K.N., 1986. Changes in microbial biomass C, ATP content soil phospho-menoesterase and phospho-diesterase activity following air-drying of soils. Soil Biol. Biochem., 18: 363-370. Tate, K.R., Ross, D.J. and Keltham, C.W., 1988. A direct extraction method to estimate soil microbial C: effects of experimental variables and some different calibration procedures. Soil Biol. Biochem., 20: 324-335. Vance, E.D., Brookes, P.C. and Jenkinson, D.S., 1987a. Microbial biomass measurements in forest soils: determination of kc values and tests of hypotheses to explain the failure of the chloroform fumigation-incubation method in forest soils. Soil Biol. Biochem., 19: 689-696. Vance, E.D., Brookes, P.C. and Jenkinson, D.S., 1987b. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem., 19: 703-707. Van de Werf, M. and Verstraete, W., 1987a. Estimation of active soil microbial biomass by mathematic analysis of respiration curves: calibration and test procedure. Soil Biol. Biochem., 19: 261-265. Van de Werf, M. and Verstraete, W., 1987b. Estimation of active soil microbial biomass by mathematic analysis of respiration curves: relation to conventional estimation of total biomass. Soil Biol. Biochem., 19: 267-271. Wardle, D.A., 1989. Influence of environmental factors and herbicide application on the soil microbial biomass. Unpubl. Ph.D. thesis, University of Calgary, Alberta, Canada. Wardle, D.A. and Parkinson, D., 1990. Effects of three herbicides on soil microbial biomass and activity. Plant Soil, 122: 21-28. West, A.W. and Sparling, G.P., 1986. Modifications to the substrate-induced respiration method to permit measurement of microbial biomass in soils of differing water content. J. Microb. Meth., 5: 177-189. West, A.W., Spading, G.P. and Grant, W.D., 1986. Correlation between four methods to estimate total microbial biomass in stored, air dried, and glucose-amended soils. Soil Biol. Biochem., 18: 569-576.
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Elsevier Science Publishers B.V., Amsterdam
A statistical evaluation of equations for predicting total microbial biomass carbon using physiological and biochemical methods D.A. Wardle* and D. Parkinson Department of Biological Sciences, Universityof Calgary, 2500 UniversityDrive, N. W., Calgary, Alberta (Canada) (Accepted for publication 5 July 1990 )
ABSTRACT Wardle, D.A. and Parkinson, D., i 991. A statistical evaluation of equations for predicting total microbial biomass carbon using physiological and biochemical methods. Agric Ecosystems Environ., 34: 75-86. The proposed calibration equations for quantifying microbial biomass carbon were considered and variability associated with these methods was assessed., The fumigation-incubation (FI) method depends on a kc factor for biomass C determination. Three kc values are commonly in use, i.e. 0.41, 0.45 and 0.50, but these all have an associated degree of variability. However, values of kc may also vary between certain soil treatments and between soil types. Substrate-induced respiration (SIR) has been calibrated against FI but the strength of the relationship between the two methods is uncertain in most instances because SIR measures glucose-responsive microbial biomass while FI measures chloroform-susceptible biomass. ATP and ninhydrin-extractable N analysis may show strong relationships with FI but only in specific circumstances. Fumigation-extraction (FE) demonstrates uncertain relationships when calibrated against SIR, possibly because FE measures chloroform-susceptible biomass. Calibrations of FE against FI also appear to be uncertain probably because kc and k~ values vary differently across soil types.
INTRODUCTION
Methods for quantifying the soil microbial biomass have been assessed recently by various workers (see Jenkinson, 1988) and it is apparent that physiological and biochemical methods are now used most frequently for this purpose. Fumigation-incubation (Jenkinson, 1966; Jenkinson and Powlson, 1976) was amongst the first b iomass methods, and provides actual mass data against which many recently derived methods have been calibrated. The purpose of this paper is to evaluate the proposed equations for quantifying total microbial biomass C, and to assess the variability associated with the parameters of these equations. Where necessary, the data used to calibrate these equations have been transformed and manipulated in order to satisfy * Present address: Ruakura Agricultural Research Centre, Private Bag, Hamilton, New Zealand. 0167-8809/91/$03.50
© 1991 - - Elsevier Science Publishers B.V.
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D.A. WARDLE AND D. PARKINSON
the assumptions required for parametric analysis, and, where appropriate, new equations have been derived. FUMIGATION-INCUBATION (FI) METHOD
Microbial biomass C is calculated using a kc factor, i.e. the fraction of microbial biomass C mineralized in 10 days (Jenkinson and Powlson, 1976). Three separate kc values have been proposed, i.e. 0.50 (Jenkinson, 1976; Sorenson, 1987), 0.41 (Anderson and Domsch, 1978a; Robertson et al., 1988) and 0.45 (Oades and Jenkinson, 1979; Powlson et al., 1987) from experiments with pure cultures of bacteria and fungi. The value of 0.50 was first proposed by Jenkinson (1976) based on 13 organisms including four fungi, eight bacteria and one earthworm species. Because fungi appear to be the dominant biomass component in most soils (Parkinson, 1973; Anderson and Domsch, 1975 ) a kc value weighted toward bacteria is probably inappropriate. The percentage of fungal carbon released (average of four species ) was 53.4%; that for bacteria was 48.1%. By varying the bacterial: fungal ratio (from 10: 90 to 50: 50 ) and by providing a measure of variability (Snedecor and Cochran, 1980, pp. 96-98 ) the possible range of kc values was determined (excluding outlying data from Nitrosomonas europaea). The 95% confidence intervals for the kc values across this range of ratios ranged from 0.499 to 0.576, with a mean of 0.53 when a bacterial: fungal ratio of 25 : 75 was used. The value of 0.41 (Anderson and Domsch, 1978a) was based on decomposition of 16 fungal and 12 bacterial species, averaged over four soils and using a bacterial: fungal ratio of I : 3. However, because these ratios may vary both between treatments and between soils, the data presented by Anderson and Domsch (1978a) were recalculated for each of the four soils (and their average ) for a number of bacterial: fungal ratios (Table 1 ). The kc factors for three soils were not significantly different from each other across most of the given bacterial: fungal ratios while the k¢ value for the fourth was significantly lower than all the others for all such ratios. When the variability of all four soils and of the bacterial: fungal ratios is considered, the appropriate kc value could be anywhere between 0.33 and 0.47. The value of 0.45 (Oades and Jenkinson, 1979) was introduced to correct the 0.41 value (Anderson and Domsch, 1978a) for use at 25 °C rather than 22°C. The variability associated with the k~ values currently in use is not excessive and may not be important in comparative studies. However, the k~ value may be influenced by large variations in bacterial: fungal ratios which may result from variations in tillage regime (Hendrix et al., 1986), sulphur content (Bewley and Parkinson, 1985 ) or herbicide addition (Wardle and Parkinson, 1990). Furthermore, it is usually assumed that kc values remain invariant across the range of treatments or soils considered in a given study.
50:50 40:60 30:70 25:75 20:80 10:90
Bacterial: fungal ratio [0.386,0.422] [0.398,0.432] [0.407,0.443] [0.411,0.449] [0.415,0.455] [0.423,0.467]
0.398,0.430 0.405,0.437 0.412,0.444 0.414,0.448 0.417,0.453 0.423,0.461
0.404 0.415 0.425 0.430 0.435 0.445
0.414 0.421 0.428 0.431 0.435 0.442
95% CI
k~
k¢
95% CI
Soil II
Soil I
0.390 0.402 0.413 0.418 0.424 0.435
k¢
Soil III
0.369,0.411 0.382,0.422 0.392,0.434 0.396,0.440 0.401,0.447 0.410,0.460
95% CI
95% CI [0.308, [0.321, [0.333, [0.334, [0.345, [0.356,
k¢ 0.330 0.343 0.356 0.363 0.370 0.383
Soil IV
0.352] 0.365 ] 0.379] 0.387] 0.395] 0.410]
0.385 0.395 0.406 0.411 0.416 0.426
k¢
All soils
[0.325, [0.339, [0.352, [0.359, [0.367, [0.380,
95% CI 0.445 0.452 0.4591 0.462 0.465 0.472
Values for k¢, derived from the data of Anderson and Domsch (1978a), corrected for varying bacterial: fungal ratios, for each of the four soils used and the mean of all four soils
TABLE 1
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~r
t"
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78
D.A. WARDLE AND D. PARKINSON
However, kc varies with such factors as pH (Vance et al., 1987a), soil moisture content (Ross, 1987; Wardle, 1989 ), microbial species composition (Nicolardot et al., 1984) and the physiological condition of the biomass (Ross et al., 1987). Also, kc values vary between soil types (Nicolardot et al., 1984; Table 1 ), and between samples of the same soil type (Wardle, 1989 ). For some soil types, a kc value of 0.41 for incubations at 22°C is probably the most appropriate, because Anderson and Domsch (1978a) provided the most realistic statistical evaluation. However, values of k~ have been determined only for a narrow range of soils and conditions. None of the soils used for determining the three commonly used kc values had over 4% organic carbon, and all but one were arable soils. Van de Werf and Verstraete (1987b) experimentally determined anfsd factor (fraction of microbial biomass catabolized in 5 days; analogous to the kc factor) for seven soils. The mean fSd value was 0.511 with a 95% CI of [0.481.621 ]. The soils used in their determination were relatively heterogeneous with an organic C range from 0.11 to 6.12%. Recalculation of these data indicates that the fsd factor is influenced by soil organic matter content ( Spearmans rank correlation coefficient between OM andfsd = 1.00; P < 0.01; n = 7 ) and may not be appropriate for all soils. SUBSTRATE-INDUCED RESPIRATION (SIR)
Anderson and Domsch (1978b) determined the maximum initial respiratory response of 12 soils to glucose and calibrated these against biomass values determined using FI for the same soils. This yielded the following predictive equation: Y= 4.004X+ 3.7, r = 0.96 where Y=/zg biomass C g soil- t and X = ml CO2 C h - I 100 g soil- i. However, this calibration is problematic because two highly organic soils were included; these soils had substantially higher biomass values than the other 10 and clearly belonged to a different "'population" of soils. Furthermore, the 12 soils included in their analysis were unequally represented, and thus unequally weighted. Data from Fig. 6 of Anderson and Domsch ( 1978b), excluding the two highly organic soils, were reanalysed, giving all soils equal weighting. This resulted in 10 points, i.e. one point per soil. This yields a new equation of: Y=416.7X+ 16.2, r=0.82 However, the value of r has a 95% CI of [0.360, 0.956 ]. Therefore there are insufficient data to determine whether a strong relationship between the two methods exists (Fig. 1 ). Martens (1987) proposed "improvements" (continuous aeration of soil
PREDICTINGTOTALMICROBIALBIOMASSCARBON 1000
79
Y=416.7X+16.2
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C02evolution (rnJ, h-IlOOg soil - I ) (X) Fig. 1. Modified calibration o f Anderson and D o m s c h (1978b) for determining microbial biomass using the substrate-induced respiration technique. Dashed lines represent 95% confidence bands for the expected values of Y from any value of X.
samples) to the SIR technique of Anderson and Domsch (1978b) based on 22 soils followingcalibration against FI. The following equation was proposed: Y = 4 9 5 X - 167, r=0.978 Although Martens' (1987) equation does not differ significantly from that of Anderson and Domsch (1978b) (tested using ANCOVA), two "populations" of soils appear to contribute to the calibration curve ( 16 "inorganic" soils of < 3% C and six "organic" soils of > 7% C) and two separate equations can then be presented, i.e. inorganic soils:Y=235X+ 68.7, n = 16, r--0.917 95% CI for r= [0.773, 0.971 ] organic soils: Y = 4 9 0 X - 143, n=6, r=0.974 95% CI for r - [0.776, 0.997] These two equations significantly differ from each other at P = 0.001 (Fig. 2 ) and may be more reliable for the respective groups of soils. Two other studies have included calibrating SIR against other methods. One of these (West and Spading, 1986) involved calibrating SIR against biovolume-derivedbiomass C values, i.e. Y=433 logio W+ 5.92, r=0.84 W=/tl CO2 h - l g- 1soil This equation was based on 14 data points, but only three soils (6, 4 and 4
80
D.A. WARDLEAND D. PARKINSON organic : Y=489.7X-142.7 1600
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inorganic : Y=234.7X+68.7
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Fig. 2. Modified calibration of Martens (1987) for determining microbial biomass C using the substrate-induced respiration technique. Dashed or dotted lines represent 95% confidence bands for the expected values of Y from any value of X.
points from each soil, respectively). This does not fulfil the assumption of non-independenceamongst X and amongst Y values. Furthermore the points from each soil form relatively distinct clusters. The SIR equations derived by West et al. (1986) involved calibration against FI-derived biomass (i.e. Y= 40.92 W+ 12.9, r = 0.93 ) and against bivolume-derived biomass (for the same samples) (i.e. Y= 447 log t0 W+ 112, r=0.91 ). These calibrations involved 12 points but again from only three soils with 5, 4 and 3 data points from each soil, respectively. These calibrations are both strongly influenced by four points from one soil type which form a tight cluster at the lower end of the slope. Other studies have indicated uncertain and poor relationships between FI and SIR (Spading et al., 1986; Wardle, 1989; and data presented by Spading and West, 1988b). Uncertain relationships between FI and SIR may be explained by differences in the components of the microbial biomass included. FI measures those organisms killed by chloroform, including active and some inactive components, although this fumigation may be incomplete (Ingham and Horton, 1987). If the glucose response is restricted primarily to active organisms (van de Werf and Verstraete, 1987a) or r-selected organisms (Gerson and Chet, 1981 ) then SIR may apply only to a fraction of the total microbial biomass. Therefore strong correlations between FI and SIR can only be expected when the fraction of microbial biomass which is glucose-responsive is consistent across samples, or when the range of biomass values is so large that variations in this fraction become insigificant by comparison.
PREDICTING TOTAL MICROBIAL BIOMASS CARBON
81
ATP CONTENT OF SOIL
Soil ATP values were calibrated against FI-derived biomass values for 11 soils (Oades and Jenkinson, 1979) and later modified to include six more points, which yielded an equation of (Jenkinson et al., 1979) Y= 116.3A+43.8, r=0.975, n = 17 where A = A T P in #g g- ' dry weight. The 95% CI for r was found in the present study to be 0.928-0.991 indicating a strong relationship between data from the two methods. Despite this, other studies suggest that this relationship may be much weaker under certain storage conditions and seasonal stresses (Ross et al., 1981; Spading et al., 1981; Ahmed et al., 1982 ), possibly due to different metabolic states of the microbial biomass under different environmental conditions (Ross et al., 1981 ). NINHYDRIN-REACTIVE NITROGEN COMPONENT OF SOIL
Amato and Ladd ( 1988 ) calibrated this method against FI biomass for 25 soils, incubated for 44 and 66 weeks, and proposed this as a method for measuring microbial biomass C. The strongest relationship was for soils incubated for 44 weeks, i.e. Y= 2 4 . 4 N - 56, r=0.96 where N = ninhydrin-reactive N (#g g- ' ) extracted after fumigation. To as1.355
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10.0
15.0
20.0
25.0
30.0
ninhydrin-reoctive
nitrogen
(lugcJ-Isoil)
(N)
Fig. 3. M o d i f i e d c a l i b r a t i o n o f A m a t o and l_add ( 1988 ) for d e t e r m i n i n g m i c r o b i a l biomass C
using the ninhydrin-extractableN technique. Dashed lines represent 95% confidence bands for the expected value of Yfrom any value of N.
82
D.A. WARDLE AND D. PARKINSON
sess the strength of the relationship between Y and N more thoroughly, data for these two variables were transformed using the log~ transformation (present study) since they were otherwise not normally distributed (tested using the Wilk-Shapiro statistic; Shapiro and Wilk, 1965 ). When this was done the relationship becomes: Y= 7.58N 1355, 95% CI for r = [0.903, 0.980] This curve is not very different from the more easily applied linear form provided by Amato and Ladd ( 1988 ). However, log-log transformation was necessary to place 95% confidence bands about the predicted values of Y (Fig. 3). The determination of microbial biomass C using ninhydrin-reactive N appears to be appropriate for lower but not higher values of biomass (i.e. > 200/tg biomass C g soil- ~) because variability of predicted values of Y increases as N increases. FUMIGATION-EXTRACTION (FE) METHOD
Vance et al. ( 1987b ) calibrated this method against FI using 10 data points (i.e. Y= 2.641I, r = 0.99; V= flush of extractable C following fumigation in/~g g- ~). Because one sample had nearly four times more biomass than any of the others they also proposed an equation using only nine data points (i.e. Y= 2.781I, r = 0.95 ). However, they justified leaving the outlier point on the calibration because it had no major effect on the regression equation. However, in the present study it has been excluded since it renders the data nonnormal. The same results as Vance et al. (1987b) could not be obtained upon recalculation of their data, and the calibration equation obtained in the present study was: Y=3.16V-4.87, r=0.874 95% CI for r = [0.501, 0.973] Because the lower limit of the CI for r is very low (explaining only 25% of the variability in the data set) this study indicates that FE is an uncertain predictor of FI. Tate et al. (1988) also attempted to calibrate FE against FI. From their data the following relationship has been derived (present study): Y= 1.54V+314.8, r=0.730, n = 2 4 Because the value for r is low (explaining only 53% of the variability in the data set) this study also demonstrates FE to be an uncertain biomass predictor of FI. Two studies have also involved calibrating FE against SIR-derived biomass C determined using SIR. One of them (Sparling and West, 1988a) used 26 inorganic soil samples and resulted in the following equation:
PREDICTINGTOTALMICROBIALBIOMASSCARBON
83
Y = 1.85 V+242, r=0.89, 95% for r = [0.776, 0.949]
The lower limit for r indicates that as little as 59% of the total variability in the data set may be explained. Also, in the construction of that calibration curve, 10 of the data points (including all those at the lower end of the curve) represent soils from one agroforestry project, and two other locations were also represented by more than one point. In the present study, the calibration equation was recalculated using the average value for each location as one data point. The equation then becomes: Y=2.41V+116.5, r=0.913, n = 13, 95% CI for r= [0.740, 0.975] The 95% confidence bands for this equation are shown in Fig. 4. Spading and West ( 1988b ), using 11 soils, performed a similar calibration: Y= 1/'/0.39 or Y=2.56V, r=0.93, n = 11 In the present study, the equation was redetermined excluding the other two soils, since they may belong to a different "population" of soils, and had anamalously low values for the C flush determined using FI or FE. This equation becomes: Y=2.68V-44.1, r=0.891, n = 9 95% CI for r = [0.714, 0.997] This equation again indicates an uncertain strength in the relationship between FE and SIR. 1600-
1 /
Y=2.411V+116.5
1400,
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Fig. 4. Modified calibration of Spading and West (1988a) for determining microbial biomass C using the extractable C content of soil. Dashed lines represent 95% confidence bands for the expected value of Y from any value of V.
84
D.A. WARDLE AND D. PARKINSON
Weak interactions may be expected between FE and SIR, since FE measures those microorganisms killed by chloroform (active and probably some inactive) while SIR measures only glucose-responsive biomass (as discussed previously). However, uncertain relationships between FI and FE are more problematic and indicate that the fraction of biomass C extracted using FE (i.e. the kec factors) and the fraction of biomass C evolved as CO2C using FI (i.e. the kc factor) may vary differently across soil samples. This is further supported by studies that have attempted to determine kec values directly in soil. Tate et al. (1988) determined that kec values for individual microbial species may range from 0.13 to 0.34. Sparling and West (1988a) determined that microbial biomass labelled in situ with 14C had k¢c values ranging from 0.25 to 0.38 in different soils. These studies indicate that k~c may be highly variable. CONCLUSIONS
Calibration equations for quantifying total microbial biomass may be relatively weak, especially when their associated variability is taken into account. In part this is probably because most methods may be sensitive to only a certain component of the total microbial biomass. These methods have also been performed mostly on only certain soil types, and mostly inorganic ( < 8% organic C) soils from temperate regions. Calibrations may be influenced by the sampling strategy used for selection of such soils, and it is important for the development of effective calibration equations that the population of soils be defined and independent data points (satisfying assumptions of normality) are extracted from this. REFERENCES Ahmed, M., Oades, J.M. and Ladd, J.N., 1982. Determination of ATP in soils: effect of soil treatment. Soil Biol. Biochem., 14: 273-279. Amato, M. and Ladd, J.N., 1988. Assay for microbial biomass based on ninhydrin-reactive nitrogen in extracts of fumigated soils. Soil Biol. Biochem., 20:107-110. Anderson, J.P.E. and Domsch, K.H., 1975. Measurement of bacterial and fungal contributions for respiration of selected agricultural and forest soils. Can. J. Microbiol., 21 : 314-322. Anderson, J.P.E. and Domsch, K.H., 1978a. Mineralisation of bacterial and fungi in chloroform-fumigated soils. Soil Biol. Biochem., 10:207-213. Anderson, J.P.E. and Domsch, K.H., 1978b. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem., 10:215-221. Bewley, R.J.F. and Parkinson, D., 1985. Bacterial and fungal activity in sulphur dioxide polluted soils. Can. J. Microbiol., 31: 13-15. Gerson, U. and Chet, I., 1981. Are allochthonous and autochthonous soil microorganisms r- and K-selected? Rev. Ecol. Biol. Sol., 18: 285-289. Hendrix, P.F., Parmelee, R.W., Crossley, D.A. Jr., Coleman, D.C., Odum, E.P. and Groffman, P.M., 1986. Detritus food webs in conventional and no tillage ecosystems. Bioscience, 36: 374-380.
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lngham, E.R. and Horton, K.A., "1987. Bacterial, fungal, and protozoan responses to chloroform fumigation in stored soil. Soil Biol. Biochem., 19: 545-550. Jenkinson, D.S., 1966. Studies on the decomposition of plant material in soil. II. Partial sterilisation of soil and the soil biomass. J. Soil Sci., 17: 280-302. Jenkinson, D.S., 1976. The effects ofbiocidal treatments on metabolism in soil. IV. The decomposition of fumigated organisms in soil. Soil Biol. Biochem., 8: 203-208. Jenkinson, D.S., 1988. Determination of microbial biomass carbon and nitrogen in soil. In: J.B. Wilson (Editor), Advances in Nitrogen Cycling. CAB International, Wallingford, UK, pp. 368-386. Jenkinson, D.S. and Powison, D.S., 1976. The effects of biocidal treatments on soil metabolism in soil. V. A method for measuring soil biomass. Soil Biol. Biochem., 8:209-213. Jenkinson, D.S., Davison, S.A. and Powlson, D.S., 1979. Adenosine triphosphate and microbial biomass in soil. Soil Biol. Biochem., 11: 521-527. Martens, R., 1987. Estimation of microbial biomass in soil by the respiration method: importance of soil pH and flushing methods for the measurement of respired CO2. Soil Biol. Biochem., 19: 77-81. Nicolardot, B., Chaussod, R. and Catroux, G., 1984. Decomposition de corps microbiens dans des sols fumig6s au chloroforme: effets du type de soil et de microorganisme. Soil Biol. Biochem., 16" 453-458. Oades, J.M. and Jenkinson, D.S., 1979. Adenosine-triphosphate content of the soil microbial biomass. Soil Biol. Biochem., I l: 201-204. Parkinson, D., 1973. Techniques for the study of soil fungi. Bull. Ecol. Res. Commun. (Stockholm), 17: 29-36. Powlson, D.S., Brookes, P.C. and Christensen, B.T., 1987. Measurement of soil biomass provides an early indication of changes in total soil organic matter due to straw incorporation. Soil Biol. Biochem., 19:159-216. Robertson, K., Schniirer, J., Clarholm, M., Bonde, T.A. and Rosswall, T., 1988. Microbial biomass in relation to C and N mineralisation during laboratory incubations. Soil Biol. Biochem., 20" 281-286. Ross, D.J., 1987. Soil microbial biomass estimated by the fumigation incubation procedure: seasonal fluctuations and influence of soil moisture content. Soil Biol. Biochem., 19: 347404. Ross, D.J., Tate, K.R., Cairns, R. and Meyrick, K., 1981. Fluctuations in microbial biomass indices at different sampling times in soils from tussock grasslands. Soil Biol. Biochem., 13: 109-114. Ross, D.J., Spading, G.P. and West, A.W., 1987. Influence ofFusarium oxysporum age on proportions of C, N, and P mineralised after chloroform fumigation of soil. Aust. J. Soil Res., 25: 363-566. Shapiro, S.S. and Wilk, M.B., 1965. An analysis of variance test for normality (complete samples). Biometrika, 52:591-611. Snedecor, G.W. and Cochran, W.G., 1980. Statistical Methods, 7th edn. The Iowa State University Press, Ames, Iowa. Sorensen, L.H., 1987. Organic matter and microbial biomass in a soil incubated in the field for 20 years with ~4C-labelled barley straw. Soil Biol. Biochem., 19: 39-42. Spading, G.P. and West, A.W., 1988a. A direct extraction method to estimate soil microbial C: calibration in situ using microbial respiration and 14C-labelled cells. Soil Biol. Biochem., 20: 337-343. Spading, G.P. and West, A.W., 1988b. Modifications to the fumigation-incubation technique to permit simultaneous extraction and estimation of soil microbial C and N. Commun. Soil Sci. Plant Anal., 19: 327-344.
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Spading, G.P., Ord, B.G. and Vaughan, D., 1981. Microbial biomass and activity in soils amended with glucose. Soil Biol. Biochem., 13: 99-104. Spading, G.P., Speir, T.W. and Whale, K.N., 1986. Changes in microbial biomass C, ATP content soil phospho-menoesterase and phospho-diesterase activity following air-drying of soils. Soil Biol. Biochem., 18: 363-370. Tate, K.R., Ross, D.J. and Keltham, C.W., 1988. A direct extraction method to estimate soil microbial C: effects of experimental variables and some different calibration procedures. Soil Biol. Biochem., 20: 324-335. Vance, E.D., Brookes, P.C. and Jenkinson, D.S., 1987a. Microbial biomass measurements in forest soils: determination of kc values and tests of hypotheses to explain the failure of the chloroform fumigation-incubation method in forest soils. Soil Biol. Biochem., 19: 689-696. Vance, E.D., Brookes, P.C. and Jenkinson, D.S., 1987b. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem., 19: 703-707. Van de Werf, M. and Verstraete, W., 1987a. Estimation of active soil microbial biomass by mathematic analysis of respiration curves: calibration and test procedure. Soil Biol. Biochem., 19: 261-265. Van de Werf, M. and Verstraete, W., 1987b. Estimation of active soil microbial biomass by mathematic analysis of respiration curves: relation to conventional estimation of total biomass. Soil Biol. Biochem., 19: 267-271. Wardle, D.A., 1989. Influence of environmental factors and herbicide application on the soil microbial biomass. Unpubl. Ph.D. thesis, University of Calgary, Alberta, Canada. Wardle, D.A. and Parkinson, D., 1990. Effects of three herbicides on soil microbial biomass and activity. Plant Soil, 122: 21-28. West, A.W. and Sparling, G.P., 1986. Modifications to the substrate-induced respiration method to permit measurement of microbial biomass in soils of differing water content. J. Microb. Meth., 5: 177-189. West, A.W., Spading, G.P. and Grant, W.D., 1986. Correlation between four methods to estimate total microbial biomass in stored, air dried, and glucose-amended soils. Soil Biol. Biochem., 18: 569-576.