Dynamics of the microbial populations of a reclaimed-polder soil under a conventional and a reduced-input farming system

Sod Bid. &o&m. Vol. 23. No. 6. pp. S15-J24. 1991 Printal in Great Britain.All rights-cd

0038-0717/91 53.00 + 0.00 Copyright c 1991 Pergamon Press pk

DYNAMICS OF THE MICROBIAL POPULATIONS OF A RECLAIMED-POLDER SOIL UNDER A CONVENTIONAL AND A REDUCED-INPUT FARMING SYSTEM J. HASSINK,‘~* J. H. OUDE V~~HAAR.* E. H. NUHUS’ and J. A.

VAN

VEEN’

‘Research Institute ITAL. P.O. Box 48. 6700 AA Wageningen and zAgricultural Mathematics Group, P.O. Box 100. 6700 AC Wageningen, The Netherlands (Accepted IO January 1991) Summary-The dynamics of microbial populations (bacteria. actinomycetes and fungi) of a field treated as a conventional farming system was compared with that of a field treated as a reduced-input system. The rhizosphere and root-free zones were investigated separately. Three approaches were used to describe the communities: by means of: (i) activity indices; (ii) a multivariate procedure (canonical correspondence analysis); and (iii) diversity indices. These methods gave complementary information concerning the behavior of the microbial populations. Canonical correspondence analysis proved lo be a powerful tool to indicate difkrences in population characteristics between fields and sampling times. Characteristics of populations changed considerably in time. These changes were larger than differemxs between the two fields. In general, characteristics of populations in the rhitosphere changed more in time than those of populations in the root-free soil. Differences in population characterisk-s between the two fields were larger for fungi than for bacteria and actinomycetes. Al the end of the growing season the fungal root populations in the two fields were significantly different. The ability of the fungi in the root zone of the conventional field to utilize polymeric substrates and aliphatic organic acids decreased strongly in this period. This was not the case in the reduced-input field. The diversity of the bacterial and fungal populations decreased in July and August, the strongest decrease occurring in the rhizosphere of Ihe conventional field. Decrease in diversity appearedlo reflectperiodsof drought that occurredin summer.

lNTRODUCTlON

Intensive arable farming

has caused serious problems

such as contamination of groundwater and the atmosphere, damage to soil structure and environmental side-effects of herbicides and pesticides. These problems were the reason for starting a multidisciplinary research project in the Netherlands, in which the functioning of soil ecosystems in highinput (conventional) and reduced-input arable farming are compared. Reduced-input arable farming is characterized by: (i) reduced input of nutrients and integrated use of manures and fertilizers; (ii) reduced soil tillage; and (iii) reduced use of herbicides and pesticides. The project aims at integrating knowledge on biological, physical and chemical aspects of the C and N turnover in the soil-crop ecosystem(Brussaard et ul., 1988). It is impossible to give a complete characterization of microbial populations in soil. So far, most studies have been restricted lo only a few aspects of the communities. Many studies have focussed on comparing the generic composition of the bacterial populations in the root-free soil with that of the rhizosphere (van Emden, 1972; Vruggink. 1976; Jager and Velvis, 1981). It is now accepted that from an ecological point of view, biochemical and physiological capacities of the populations are of more *Presentaddress:lnsliune for Soil Fertility Research, P.O. Box 30003. NL-9750 RA Haren (Gr). The Netherlands.

interest (Sundman. 1970). The.sc capacities can be determined by subjecting individual isolates (sampled from a population) to a number of tests. On the basis of these potentialities three ways of characterization were used: (i) by means of activity indices of individual characteristics (Hauxhurst et al.. 1981; Gehlen et al., 1985); (ii) by means of multivariate techniques such as factor analysis and principal component analysis whereby combinations of characteristics can be determined (Sundman, 1970; Rosswall and Kvillner, 1978; Bell et al., 1982); and (iii) by means of diversity indices (Hauxhurst et al.. 1981; Gehlen ef al., 1985; Mctzger er al., 1986). We have used these three approaches to describe the dynamics of the microbial communities of the two farming systems on the basis of the results of the first year of the monitoring programme that will be continued for 5 yr. Thus differences between the two fields should be considered not only as the result of these farming systems but also as the result of differences in cropping history. Instead of factor analysis or principal component analysis, we used a different multivariate procedure that consists of two steps. Firstly, the isolates were classified into groups. Groups that are dissimilar contain isolates with different patterns of test responses.Secondly, we used canonical correspondence analysis in order to explore changes in group abundances. The latter technique has recently beem used in ecology to describe effects of environmental factors on species composition (Ter Braak, 1987a).

516

J. HASSINK er al. METHODS

Sampling

Two neighboring fields on a sedimentary calcareous silty loam were treated either as a conventional or a reduced-input farming system from the autumn of 1985 on. The conventional field had been cropped with input of only mineral fertilizers for 32 yr before the start of the introduction of the present farming systems. This field had a lower organic matter content than the reduced-input field, which had received manure in addition to the mineral fertilizer for the same number of years. Details about the previous management and the soil characteristics have been given by Hassink er al. (1991). On both fields winter wheat was grown in 1986. Both fields had an area of 80 x 12 m. The top 25 cm was sampled in April, June, August, September and November of 1986. At every sampling date three plots of 1.5 x 2 m were sampled in both fields. The sample of each plot consisted of 10 mixed samples. In total a sample of a plot weighed approx. 800 g. The plot samples were analyzed separately. Tenfold dilution series were made to isolate bacteria and actinomycetes. Soil (IO g) was shaken for 20 min in a flask containing 100 ml of a 0.1% solution of sodium pyrophosphate and 10 g of gravel. To isolate bacteria. 0.1 ml of several dilutions was plated on TSA-medium of l/IO strength (van Elsas er al., 1986). For each dilution, three plates were prepared. Actinomycctcs wcrc isolated on oatmeal
We aimed at obtaining at least 15-25 bacteria. actinomycetes and fungi from each sample. Tests performed

The isolated bacteria, actinomycetes and fungi were subjected to a series of tests. Most of these tests were carried out in square Petri dishes with 25 compartments. The isolated microorganisms were placed on top of the test medium and after 7 days of incubation observations were made. At the first sampling date, duplicate tests were performed. As these duplicates gave very similar results, single tests were performed on other sampling dates. In the case of tests for antagonism, the isolated actinomycete or fungus was placed on a suitable medium, close to the organism to be tested for its response. Reduction in growth of the test organism was recorded as a positive reaction. The tests included the following: Decomposition (% = w/w) of: (1) polymeric substrates: chitin (0.4%). cellulose and pectin (0.5%. Williams and Wellington, 1982), Tween 80 (I%, Sierra, 1957). xylan (0.5%) and starch (2%. Gehlen er al., 1985), sorbose (0.2%. Harrigan and McCance. 1966). gelatin (I%, Flanagan and Scarborough, 1974); (2) aliphatic organic acids: acetate (0.3%. Flanagan and Scarborough, 1974) citrate (0.3%. Harrigan and McCance, 1966); (3) phcnolic organic acids: gallic acid (0.01%. Flanagan and Scarborough, 1974). protocatcchuic acid (O.Ol%, Sundman. 1968). Metabolism of nitrogen compounds: nitrate reduction (0. I %, Harrigan and McCance. 1966). urcase activity (2%. Hankin and Anagnostakis, 1975). Antagonistic activity against: Bucillus subtilis. Pseudomonas Jluorescens, Fusarium grumineu rum, Rhizocroniu cerealis, Cercosporeila.

Other tests: growth on TSA medium (l/IO strength) with 5 pg chloramphenicol ml-‘, growth on polyethylene glycol (30% or 40% w/w), growth on N-free medium (Aaronson, 1970), dissolution of CaHPO, (Katznelson and Bose, 1959). color of colony. Bacteria were not tested for antagonism, because no response was observed at the first two sampling times. A number of tests (chitin, cellulose, pectin, Tween, xylan, dissolution of CaHPO,) were omitted for fungi because spreading of mycelium made it impossible to observe results. No fungi were tested for gelatin utilization and growth on a medium with chloramphenicol, because all the isolates tested showed a positive reaction. Fungi only were tested for utilization of sorbose. Methods used to characterize microbial populations Activity indices (univariate approach). For every substrate and soil sample, the activity index was calculated as the percentage of microorganisms of the total isolated strains that responded positively. This approach is called a univariate analysis, since it considers the effects for every test separately. Statistical significance of the effects of cultivation method and sampling time were tested by logistic regression analysis (McCullagh and Nelder, 1983).

Effect of farming system on microbial population

517

Table I. Groupmg of isolates using maximal predictive clasr.iBcation. Distributioo of the constructioa crows over the samples

Month

April April April April June June June June

June June Julv July July July July July August August August August Aupst Aunust

Functional group

Field

COPY. COW.

low-i. low-i. cow. CO”Y. cow. low-i. low-i. low-i.

IlOOOWOloooMx)LwooooZOWlO3l~~5lO3W

owooooo123-MOOW000040101101 iacGz3ioo ooooooo(Mooool ltxlooOl0l2~l l00.IYJcOoGltil0 1alol laoloolooooooooooIl~l03cHJoocwll0l2 0?ooooaoO11001oooa(11oocO1101020012210110 02010010l10202lx4l10101otx12

COtI”. CON. cow.

low-i. low-i. low4 CO”“. conv. cow. low-i. low-i. low-i.

Groups that arc charsctcristicfor one al ihe two fields at one of the mnpling dater are underhned.

Comhinurions of po~cnriuli~i~*s (mulrkrinrr ap pmach). Combinations of tcs~s can give additional information on the potential capacities of a population. For instance. if a population has an activity of 0.6 for chitin breakdown and 0.4 for ccllulosc brcakdown. then the fraction of microorganisms Ihilt can break down both substrates is still unknown (it may vary bctwccn 0 and 0.4). To dcscribc the cffccts of time and farming system on thr combination of potential capacities WC used the following two-step

procedure: WC first formed functional groups of microorganisms such that within groups the organisms had similar combinations of test results. To obtain this grouping, we used a non-hierarchical cluster method, known as “maximal prcdictivc classification” (Gower. 1974). This cluster method is specially intcndcd for dichotomous variables. The resulting groups can be interpreted as artificial species. We subsequently used canonical correspondence analysis (Ter Braak, 1986, 1987a) to reveal the elkct of farming system and sampling time on the composition of the groups obtained. To illustrate this two-slep method and the type of conclusions one may derive from it, the following example is prcsentcd. Fungi isolated from root samples in April, June, July and August from the two difTerently managed ticlds were classified into 40 groups on the basis of their responses to I3 tests. The result of classification is shown in Table I. It shows the distribution of each group between the two fields and among the samples within the fields. The groups that are characteristic for one of the two fields at one of the sampling dates are underlined. For example, isolates from group I6 were found only in April (eight fungi were isolated from the conventional field and two from the reduced-input field). The output of Table I was used as input for the canonical correspondence analysis (where field and time are taken as environmental variables). Firstly, this method gives a graphical

rcprcsentation of the diffcrcnccs bctwecn responses to variables, in this cast fields and times of isolation. Secondly it gives a formal significnncc test of thcsc diflcrcnccs. The tcsl is cquivalcnt IO the one proposed by Manly (I 983). The graphical rcprcscntation is an

ordination

diagram (Fig. 1) in which groups and samples arc rcprcscntcd as points. The group points arc intcrprctcd as optima, so the abundance of a group is rclativcly high in samples that lit close to that optimum and lower for more distant sample points. The farther the samples arc scprratcd from each other the fcwcr isolates they have in corrcsponding groups. Figure I shows for instance, that groups 10, 12. 16. 17, 35 and 38 mainly occur on the conventional field in April, Samples from the conventional field in April have the least in common with samples from the same field in August. In order to put more emphasis on the difference between the two fields an analysis for each sampling time separately was also carried out. Diver&y

index.

Isolates were clustered by means cluster analysis. Clusters were formed by means of the average linkage method. They were formed at 75% similarity. At each sampling time isolates from both fields were combined before analysis. The number of clusters and the number of individuals within each cluster were counted for each field separately in order to calculate the Shannon-Weaver diversity index for the two

of a hierarchical

fields: H’ = 3.3219/N (N log N - ni log ni), where N = total number of isolates; ni = total number of isolates of a field in the ith cluster. Compulalfon For the computation of logistic regression analysis and both types of cluster analysis the computer programme package Genstat was used (Genstat

98

a

06

[r-group]

83 -1 I3 .1:

12.

.I?

:

l9

.16

.lO

b

0 W A Ir, 0 .

ccmrnllonal field April reduced-inpulfield Apil conventional field June reduced-inpulfield Juno convenllonalfield July reduced-lnpulfield Juiy

t

convenflonal

*

reduced-inpuf

fleld August field Augus!

Fig. I. Ordination diagram resulting from canonical corrcspondcncc analysis. Fungi isolated from the rhizosphrrt: (a) location of the 40 fungi groups; and (b) location of the soil wmplcs. (Abundance of a group is high for samples close to that group’s location.)

Manual, 1977). The canonical correspondence analysis was performed with the computer programme CANOCO (Ter Braak. 1987b). RESULTS

Characretkalion indices

of the populations by their activity

Firstly we calculated activity indices for every test separately. We found, however, that substrates with homologous chemical structures showed the same pattern of activity index during the season. Therefore, related tests were classified into one group. The following groups of tests were formed: degradation of polymeric substrates, degradation of aliphatic organic acids, degradation of phenolic organic acids. metabolism of nitrogen compounds, antagonistic reactions. and remainder of tests. Degradation of polymeric substrates. The activity indices for the bacterial and actinomycetal rhizosphere populations decreased slightly during the growing season [Fig. 2(a)]. Changes were statistically non-significant.

The activity index of the fungal rhizosphere population of the conventional fidd decreased significantly (P c 0.05) between June and July and remained low in August. This did not occur in the reduced-input field. Differences in activity index of the fungal populations between the two fields were statistically significant (P < 0.05) in July and August. No differences between the two fields were observed for the bacterial and actinomycetal populations. The activity indices of the populations in the non-rooted zone did not change during the season [Fig. 2(b)]. Also no differences between the two fields appeared. Only in November had the fungal population of the rcducedinput field a significantly (P < 0.05) higher activity index. Degradation of afipharic organic aciak The activity indices for the bacterial and actinomycetal rhizosphere populations decreased significantly (P < 0.05) during the season [Fig. 2(c)]. The activity index for the fungal rhizosphere population of the conventional field also decreased significantly (P < 0.05) as it was also observed for the degradation of polymeric substrates by fungi. Again this was not the case for the reduced-input field. The activity index of the fungal rhizosphere populations of the reduced-input field was again significantly (P < 0.05) higher compared

Effect of farming system on microbial population

3 f 2

a

520

J. HASSINK et al.

A

d

a A A

a

_..__._. *4b 6-c

__...

db

%@+@I

5

8

“-.~--~‘~-~‘~~~“~‘._____~_____~.~

n

n

%‘m

n

e

88

0

oi

i 8.

0

@

ao

Fig. 3. Ordination diagram resulting from canonical correspondence analysis. Location of the soil samples: (a) bacteria isolated from the rhitosphere: (b) actinomycetes isolated from the rhizosphere; (c) bacteria isolated from non-rooted soil; (d) actinomycetes isolated from non-rooted soil; and (e) fungi isolated from non-rooted soil.

with the conventional field in July and August. The activity indices of the populations in the non-rooted soil remained constant, except for the fungal population in the conventional field [Fig. 2(d)]. A significant (P < 0.05) decrease in activity index appeared between July and November.

Degradation of phenolic organic acids and metabolism of nitrogen compounds. The populations

of the two fields did not differ in activity index. Also no changes in activity index were observed during the season. Therefore results are not presented.

521

Efkct of farming system on microbial population Oirsity

index (H’) a. Rhiiphere

b. non-rooted

0 Aptll

June

Juhl

AUpi

soil

Sept. dZ

e0 Baci.wnv. g;g Actin.red.krpuI

19 m

Elect.&-Input Fungicow.

?a Actin.conv. hz1 Fungired.jnput

Fig. 4. Shannon-Weaver diversity index (75% similarity) of the bacterial. actinomy~tai and fungal populations in the rhizosphcre (a) and in non-rooted soil (b). First column: field treated as a conventional farming system. Sc~ond column: field treated as a reduced-input farming system.

Anragonbtic ackity. The activity index of bacteria for this group of tests was almost zero and is not included in the results. The antagonistic activity of the fungal populations gcncrally dccrcascd during the growing season. This did not occur for the actinomycctal ~pulations. Dikkcnccs bctwccn the two fields were not observed, thcrcforc results arc not shown. Characterization of the populutions by a multioariate approach (cluster procedure followed by canonical correspondence analysis) Dynamics of the rhkosphere popularions. The characteristics of bacteria, actinomycetes and fungi isolated in April differed from the characteristics of organisms isolated from the rhizosphere in other months [Figs l(b), 3(a), (b)]. The characteristics of the bacterial and actinomycetal populations changed little from June on. As was indicated before. differences between sampling times were larger than differences between the two fields. The only significant difference in characteristics of the populations of the two fields occurred for the fungal populations in April and August (P < 0.1). The fungal spccics composition seemed to be more stable during the growing season in the reduced-input field [Fig. 1(b)]. Dynaorics of the populations in rhe non-roared :one. The characteristics of the fungal and actinomycctal populations changed more than the characteristics of the bacterial populations [Fig. ~(c-c)]. Again for the actinomycetal and fungal populations differences between sampling times were larger than diffcrenccs between the two fields. The characteristics of the fungal populations of the two fields diRered most in June and November (P = 0.12 in June).

Characreri:ation index

of rhc populations by a diversity

The diversity index of the bacterial and fungal populations in the rhizosphcrc was quite low in April, rcachcd a maximum in June and decreased again to reach a minimum in August (Fig. 4). The diversity index of the fungat population in the rhizosphcrc of the conventional field decreased more strongly than that of the rcduccd-input field. This decrease for the conventional field was also observed earlier for the degradation of polymeric substrates and aliphatic organic acids. The diversity index of the actinomycetal populations in the rhizosphere reached a maximum in April. The diversity index of the bacterial populations in the non-rooted soil was high in April and November and reached a minimum during the summer months. The diversity index of the actinomycetal and fungal populations in the non-rooted soil of the two fields did not show any clear pattern. The diversity index of the two fields did not differ significantly.

DtSCC’SSION

Integration of tfre methods to describe rhe dynamics of rhe microbial populations The three difkrent methods used to describe the characteristics of microbial populations all gave complementary information about the functioning of these populations. The activity index gives the potential of a population for a certain function. However, it does not necessarily give an accurate description of the dynamics of a population and the differences

f.

522

iiASSrNK et

d.

soil moisture content (% w/w)

-

convantion0I

April

August

NW

date

Fig. 5. Soil moisture content (0-251311) on an oven-dry basis.

between populations. The multiva~ate approach, consisting of a clustering technique, followed by canonical correspondence analysis, was suitable to describe the changes in the characteristics of populations. The diversity index can give an indication of some form of stress, and the response of a population to this stress (Hauxhurst ef al., 1981). Shfts in characteristics in spring

explain why the utili~tion capacity of these products did not decrease. The change in characteristics of the fungal populations as indicated by canonical correspondence analysis may have been caused by the appearance of new species with a lower capacity for antagonism. The diversity of the fungal populations was slightly increased between April and June.

of the rhizosphere populations

The bacterial populations had a low diversity in April. This indicates that the populations wcrc dominated by a few groups of bacteria. This population had a great ability to dcgradc diffcrcnt subby canonical correspondence strates. Analysis showed that the populations changed considerably bctwccn April and June. Probably new spccics appeared, which rcsultcd in a higher diversity index and a lower ability to degrade aliphatic organic acids. According to Jager and Velvis (1981) and Miller et ul. (1989) the rhizosph~re of young plants is usually dominated by quickly growing organisms such as Pseudomonas sp. Later, slower growing bacteria will appear. Canonical correspondence analysis showed that the actinomycetal and fungal populations also changed markedly between April and June. Actinomycetes isolated in June also had a lower ability to degrade aiiphatic organic acids, compared with actinomycetes in April. The ability to degrade more complex substrates hardly decreased for the bacterial and actinomycetal populations between April and June. It is generally accepted that organic substances that are exuded by plant roots affect microorganisms in the soil surrounding the roots (Katznelson, 1965). Several studies indicated that the proportion of photosynthate that is transferred below ground by an annual crop such as wheat decreases during later growth stages (Martin and Kemp, 1986; Keith et al.. 1986). Root exudates released by healthy plant roots consist mainly of sugars, organic acids and amino acids (Rovira, 1969). This may explain why the bacterial and actinomycetal rhizosphcre populations had the highest activity index on aliphatic organic acids in spring. Phenolic organic acids mainly orig inate from decomposing plant material and animal excreta (Vaughan and Malcolm, 1985). This may

of the rhkosphere populations in summer The canonical correspondcncc analysis and activity indices indicated that the bacterial and actinomycetal ~pulations hardly changed from June on. However, the activity index for the utilization of polymeric substrates and aliphatic organic acids of the fungal population of the conventional field decreased strongly after June. Canonical corrcspondcncc analy sis showed that the fungal population of this field changed between June and July and between July and August, while this did not occur in the reduced-input field. Environmental factors influence rhizospherc populations (Rovird. 1969). In I986 a wet spring was followed by a very dry summer during July and August. Plants were under severe moisture stress, especially in August (Fig. 5). There is conflicting info~ation about the influence of moisture stress on exudation of organic substances. Reid (1974) observed that the exudation of organic acids decreased as the water potential declined from 0.19 to 0.55 MPa. Martin (1977) found that watering of wheat plants decreased the amount of organic substances released from roots. The decrease in activity index for the utili~tion of polymeric substrates and aliphatic organic acids of the conventional field may have been caused by the decreasing activity of the roots in this field due to moisture stress. The conventionally-treated field had a higher moisture stress than the reduced-input field (Fig. 5). This was caused by a lower organic matter content of the former. The diversity indices may help to increase the understanding of the processes that occurred. Atlas (1984) stated that diversity measurements can be used to assess the effects of stress on microbial Shi/ts in churucteristics

populations.

He related diversity

to stability.

Huston

Effect of farming system on microbial population

523

(1979) suggested that the relation between stress and diversity is not that simple. In his view frequency and intensity of stresses are critical and may lead to an increased diversity. In the present study it seems

The stage of plant growth appeared to influence the composition of the microbial populations around the roots but had no effect on the composition of the populations in the non-rooted zone.

that stress situations were reflected by a decrease in diversity. In August the bacterial and fungal biomass decreased significantly (Hassink et 01.. 1991). Actinomycetes are much more tolerant to drought (Waksman. 1959) and probably did not decrease in quantity. In agreement with this, the diversity indices of the bacterial and fungal populations decreased between June and August, especially the diversity index of the fungal population of the conventional field, while the diversity indices of the actinomycetal populations did not decrease.

In another study performed on the same two fields we found that seasonal variations in the size of the microbial populations were considerable (Hassink

Shifts in characteristics non-rooted zone

Acknow~edgemenr-Communication No. 25 of the Dutch Programme on Soil Ecology of Arable Fanning Systems.

of

the populations

in the

The populations in the non-rooted zone are less strongly influenced by the release of organic material by the roots than rhizosphere populations. In general, the populations were subjected to smaller changes than the rhizosphere populations. Both canonical correspondence analysis and activity indices indicated that especially the bacterial populations were rather stable. Differences between the two fields in population characteristics were not clear. Only the fungal populations of the two ficlds differed in Novcmbcr (not significantly). Mcasurcments of the microbial biomass on the same two fields. however. showed that diffcrenccs in the amount of microbial biomass bctwcvn the two fields wcrc clear (Hassink et al.. 1991). This agrees with the results of long-term cxpcrimcnts pcrformcd by Mullcr (1984). who stated that organic manuring affects above all the quuntitativc rather than the qualitative spectrum of the population. The decrease in diversity index of the bacterial populations during the summer was probably caused by the severe drought. At the end of August rain events began and the diversity index of the bacterial populations increased in Scptcmbcr. It is remarkable that canonical correspondence analysis and activity indices did not show any change in characteristics of the bacterial populations during July and August when the size of the populations was dccreascd by a factor of IO and in September when the populations had obtained the original size again. Apparently the majority of the species responded in the same way to drought and to the remoistcning of the soil. Diversity indices thus appear to be a sensitive way to indicate stress situations. We may conclude that the three approaches were useful in describing changes in characteristics of populations. lntcgration of the approaches gave more insight in the dynamics of the populations than considering the approaches separately. Events that occur within a growing season, such as plant growth and drought, dctcrminc the dynamics of microbial populations, rather than historical or present agricultural practices. As the soil sampling sites for a certain sampling date were located close to each other in the ordination diagrams, we conclude that the three separate samples were representative of the microbial populations that wcrc able to grow on the agar used.

et al., 1991). Water stress, in particular, decreased bacterial and fungal populations. Also the size of the microbial biomass was larger on the reduced-input field. The effects of seasonal variations and farming system on the composition of the microbial populations appeared to be very small compared to the quantitative effects.

REFERENCES

Aaronson S. (1970) E.rperimenfal Academic Press. New York.

Microbial

Ecology.

Atlas R. M. (1984) Use of microbial diversity measurements lo assess environmental stress. In Current Perspecfictes in Microbial Ecology. Proceedings of rhe Third Inter national Symposium on Microbial Ecology. Michigan State University (M. C. Klug and C. A. Reddy. Eds). VP. 540-545. American Society for Microbioloav. BeiiC. R.. Holder-Franklin M. A. and Franklin M. (1982) Correlations between predominant heterotrophic bacteria and physicochcmical water quality in two Canadian rivers. Applied and Enaironmenral Microbiology 43. 269-283. Brussaard L.. van Veen J. A., Kooistra M. J. and Lebbink G. (1988) The Dutch Programme on soil ecology ofarable farming systems I. Objoztiva, approach and some preliminary results. Eco/o&ca/ Bu//&s 39. 3540. Domsch K. H. and Gams W. (I96Y) Variability and ootcntials of pectin, xylan. and‘ carboxymethyl&lulo~e decomposition among a soil fungus population. Soil Biolog) & Biochemistry I, 29-36. van Elsas J. D., Dijkstra A. F., Govacrt J. N. and van Vecn J. A. (1986) Survival of Pseudomonas Juvrescens and Bacillus suhrilus introduced into 2 soils of difTerent texture in field microplots. FEMS Microbial Ecology 38. I5 I-160. van Emden J. H. (1972) Soil mycollora in relation to some crop-plants. Orpp/Eppo Bull&in 7. 17-26. Flananan D. W. and Scarborounh A. M. (1974) PhvsioIO&II groups of decompose; fungi on‘ tundra plant remains. In Soil Organisms und Decomposition in Tundra (A. J. Holding. 0. W. Heal, S. F. MacLean and D. W. Flanagan, Eds), pp. 159-181. Tundra Biome Steering Committee. Stockholm. Gehlen M.. Trampisch H. J. and Dorr W. (1985) Physiological characterization of heterotrophic bacterial communities from selected aquatic environments. Microbial Ecology I I, 205-2 19. Genstat Manual (1977) Gensrar-A Generul Slarirtical Program. Oxford Numerical Algorithms Group, Oxford. Cower J. C. (1974) Maximal predictive classification. Biometrics 30. 643-654. Hankin L. and Anagnosrakis S. L. (1975) The use of solid media for demction of enzyme production by fungi. Mycologia 67. 597-607. Harley J. L. and Waid J. S. (1955) A method of studying active mycelia on roots and other surfaces in the soil. Transactions of the British Mycological Society 38. 104-I 18. Harrigan W. F. and McCance M. E. (1966) Loboratory Methods in Microbiology. Academic Press, London.

J. HUSI~ IK

524

Hassink J.. Lebbink G. and van Veen J. A. (1991) Microbial biomass and activity of a reclaimed-poldcr soil under a conventional or a reduced-input farming system. Soil Biology & Biochemistry

23, 507-5 13.

Hauxhurst J. D., Kaneko T. and Atlas R. M. (1981) Characteristics of bacterial communities in the gulf of Alaska. Microbial Ecology 7, 167-182. Huston M. (1979) A general hypothesis of species diversity. 77re American Nururalisr 113, 81-101. Jager G. and Velvis H. (1981) The bacterial flora in and outside the rhizosphere of wheat, grass, sugar beet and potato on a light sandy loam. Instituut voor Bodemvruchtbaarheid, Rapp. 7-8 I. Katznelson H. (1965) Nature and importance of the rhizosphere. In Ecology of Soil-borne Plant Pathogens (K. F. Baker and W. C. Snyder, Eds), pp. 187-209. University of California Press, Berkeley. Katznelson H. and Bose 8. (1959) Metabolic activity and phosphatedissolving capability of bacterial isolates from wheat roots, rhizosphere, and non-rhizosphere soil. Canadian

Journal of Microbiolog_v 5, 79-85.

Keith H., Oades J. M. and Martin J. K. (1986) Input of carbon to soil from what plants. Soil Biology & Biochcmistry 18. 445-449.

Manly B. F. J. (1983) Analysis of polymorphic variation in ditferent types of habitat. Biovwrrics 39. 13-27. Martin J. K. (1977) Effect of soil moisture on the release of organic carbon from wheat roots. Sail Biology & Biochemistry

9. 303-304.

Martin J. K. and Kemp J. R. (1986) The mcasurcment of C transfers within the rhizosphere of wheat grown in held plots. Soil Sinlogy & BicJchcmi.rlr,r18. 103-107. McCullagh P. and Neldcr J. A. (1983) Grnercdi:c*d Lincur Mod&. Chapman & Hall, London. Metzgcr W. C.. Klein D. A. and Rcdentc E. f‘. (1986) Bacterial physiological diversity in the rhizosphere of range plants in rcsponsc to retorted shnlc stress. Applied und &noirannrcw/ul Microhiolu~y 52. 765-770.

Miller tt. J.. Hcnkcn G. and van Van J. A. (1989) Variation and composition of bacterial populations in the rhizosphere of maize, wheat and grass cultivars. Cunudiun Jqrnul

of Microbiology

35. 656 -660.

Mullcr CL (1984) Intluence of mineral fertilization on the biological processes of the soil. In Soil Biology und

El

a/.

Conserration of the Biosphere (J. Szegi, Ed.), pp. 3-28. Akademiai Kiado, Budapest. Nagelde Boois H. M. and Jansen E. (1971) The growth of fungal myahum in forest soil layers. Revue d’Eco/ogie et de Biologie du Sol 4, 509-520.

Reid L. C. P. (1974) Assimilation. distribution and root exudation of “C by ponderosa pine seedlings under induced water stress. P/am Physiology 54, 4449. Rosswall T. and Kvillner E. (1978) Principal components and factor analysis for the description of microbial populations. Advanced Microbial Ecology 2, 148. _ _ Rovira A. D. (1969) Plant root exudates. Eorunicul Rmiew

.

35, 35-57.

Sierra G. (1957) A simple method for the detection of lipolytic activity of microorganisms and some observations on the influence of the contact between cells and fatly substrates. Anronie cun Leeuwenhoek 23, 15-22. Sundman V. (1968) A simple plate test for the determination of protocatechuic acid utilization of soil bacteria. Canadiun Journal

of Microbioloav

14. 88-89.

Sundman V. (1970) Four bac‘ierial soil populations characterized and compared by a factor analytical method. Canadian

Journal of Microbiology

16, 455-464.

Ter Braak C. J. F. (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. &co/og_v67. 1167-l 179. Ter Braak C. J. F. (1987a) The analysis of vegetationenvironment relationships by canonical correspondence analysis. Vegetatio 69. 69-77. Tcr Braak C. J. F. (1987b) CANOCO-A FORTRAN program for Canonical Community Ordination by [partial] [dctrended] [canonicalj correspondence analysis, principal component analysis and redundancy analysis (version 3. I). Agricultural Mathematics Group, Wageningcn. Vaughan D. and Malcolm R. E. (1985) Soil Orgunic Mutter und Biolugicul Activity. Martinus Nijhoff. Dordrccht. Vruggink tl. (1976) lntluence of agricultural crops on the actinomycetcs flora in soil. Plunr und Soil 44, 639 654. Waksman S. A. (1959) The Acrinuntyccrev. Williams & Wilkins, Baltimore. Williams S. T. and Wellington E. M. tl. (1982) Actinomycetes. In Merhodf o/Soil Anulysis (A. L. Page, R. H. Miller and D. R. Keeney. Eds). Soil &knee Society of America, pp. 969-987. American Society of Agronomy, Madison.