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Effects of no-tillage and strip-intercropping on corn and soybean fauna
Tonhasca, Athayde, Jr., Ph.D.
The Ohio State University, 1991
UMI 300 N. Zeeb Rd. Ann Arbor, MI 48106 EFFECTS OF NO-TILLAGE AND STRIP-INTERCROPPING
ON CORN AND SOYBEAN FAUNA
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of the Ohio State University
By
Athayde Tonhasca Jr, B.S., M.S,
*****
The Ohio State University
1991
Dissertation Committee: Approved by
R. B. Hammond
D. J. Horn
E. E. Regnier /f- Adviser B. R. Stinner D nent of Entomology To Gustavo Tetzner, in memoriam VITA
September 7, 1959...... Born - Sao Paulo, Brazil
1982 ...... B.S., University of Sao
Paulo, Sao Paulo, Brazil
1982-1985...... Agronomist, Sao Paulo
State Extension Service
1985-1987...... M.S., Mississippi State
University, Mississippi
State, MS
1988-1991...... Graduate Research
Associate, Department of
Entomology, The Ohio
Agricultural Research
and Development Center,
The Ohio State
University, Wooster, OH
FIELD OF STUDY
Major field: Entomology
iii TABLE OF CONTENTS
DEDICATION ...... ii
VITA ...... iii
LIST OF TABLES ...... vi
LIST OF FIGURES ...... viii
INTRODUCTION ...... 1
CHAPTER PAGE
I. The Effects of Strip-intercropping and No-tillage on Some
Pests and Beneficial Organisms of Corn in Ohio
Introduction ...... 4
Materials and Methods ...... 4
R e s u l t s ...... 10
D i s c u s s i o n ...... 14
II. Response of Soybean Fauna to Two Agronomic Practices
Increasing Agroecosystem Diversity
Introduction ...... 34
Materials and Methods ...... 35
R e s u l t s ...... 39
D i s c u s s i o n ...... 46
III. Diversity Analysis of a Carabid Beetle Assemblage Under
Diversified Agroecosystems
Introduction ...... 77 Materials and Methods ...... 79
R e s u l t s ...... 81
D i s c u s s i o n ...... 85
SUMMARY ...... 113
APPENDICES PAGE
A. Results of analyses of variance for
organisms sampled by sweep net ...... 114
B. Results of analyses of variance for
organisms sampled by D-vac...... 118
C. Results of analyses of variance for
organisms sampled by direct counts . . . 1 2 0
D. Results of analyses of variance for
organisms sampled by pitfall traps . . . 1 2 1
E. Results of analyses of variance for
organisms sampled by quadrat samples . . 125
BIBLIOGRAPHY ...... 128
v LIST OF TABLES
TABLE PAGE
1. Analyses of variance results for armyworms, cutworms
and s l u g s ...... 19
2. Analyses of variance results for the European corn borer . 20
3. Summary of the agronomic parameters for c o r n ...... 21
4. Soybean fauna and sampling methods ...... 53
5. Responses of the soybean fauna to tillage and
cropping systems ...... 56
6 . Possible positive affects to the soybean fauna
resulting from tillage and intercropping practices .... 60
7. Most abundant weeds ...... 62
8 . Summary of trends for diversity factors for
17 taxa from soybean foliage f a u n a ...... 63
9. Summary of trends for diversity factors for
11 taxa from soybean soil f a u n a ...... 64
10. Carabid species collected by pitfall traps ...... 92
11. Spearman's rank correlations between treatments for
the dominant carabid species ...... 94
12. Means and standard deviations of the dominant carabid
species showing response to the tillage system factor
in 1988 ...... 95
vi 13. Means and standard deviations of the dominant carabid
species showing response to the tillage system factor
in 1989 ...... 96
14. Means and standard deviations of the dominant carabid
species showing response to the tillage system factor
in 1990 ...... 97
15. Means and standard deviations of the dominant carabid
species showing response to the cropping system factor . . 98
16. 1988 means and standard deviations for diversity
indices of the carabid assemblage ...... 99
17. 1989 means and standard deviations for diversity
indices of the carabid assemblage ...... 1 0 0
18. 1990 means and standard deviations for diversity
indices of the carabid assemblage ...... 1 0 1
19. Results of diversity indices for two hypothetical
carabid communities ...... 1 0 2
vii LIST OF FIGURES
FIGURE PAGE
1. Spatial arrangement of the 24 plots ...... 22
2. Results of adult counts and root damage evaluation
for the Western corn rootworm ...... 24
3. Three years results of the western corn rootworm adult
counts and root damage for each corn p l o t ...... 26
4. Number of plants damaged by first generation
European corn borers ...... 28
5. Frequency distribution of plants infested by second
generation European corn borers ...... 30
6 . Mean corn yield for each treatment ...... 32
7. Densities of the green cloverworm measured by sweep
net samples ...... 65
8 . Densities of the green cloverworm and anthocorid bugs
measured by sweep net samples ...... 67
9. Densities of the bean leaf beetle measured by sweep
net samples ...... 69
10. Densities of the Japanese beetle measured by sweep
net samples ...... 71
11. Densities of the potato leafhopper measured by D-vac
s a m p l e s ...... 7 3
12. Mean soybean yield for each treatment ...... 75
viii 13. Relative number of the dominant carabid species ...... 103
14. Carabid richness ...... 105
15. Carabid evenness ...... 107
16. Dominant carabid species in each treatment ...... 109
17. Dendogram of carabid species clustering analysis .... Ill
ix INTRODUCTION
In the study of agroecosystems, the intuitive concept of "balance of nature" formalized as the diversity-stability theory (MacArthur 1955) was translated into the hypothesis that diversification of crops would increase the diversity and stability of insects populations. Stability may be defined as a function of resilience, resistance and variability
(Pimm 1984), but for agroecosystems, stability usually refers to reduction of pest outbreaks. Pimentel's (1961) seminal paper on the insect community of cole crops fostered the paradigm, and subsequent work on community ecology of agroecosystems has demonstrated reduced herbivory in some diversified systems, particularly when specialist species are involved (reviewed in Altieri and Letourneau 1982, and Risch et al. 1983).
However, although diversification increases the number of niches with resulting diversification of the insect fauna (Murdoch et al. 1972), there is little evidence for a stabilizing effect (van Emden and Williams 1974,
Murdoch 1975, Redfearn and Pimm 1987). In fact, diversity-stability concepts are of little use on highly disturbed systems like agricultural fields, when instability is oftentimes desired as when insecticides are used to reduce a damaging pest population (Goodman 1975, Murdoch 1975).
Support for the hypothesis of reduced pest outbreaks in agriculture as a consequence of diversification many times originates from studies on cole crops, which have a unique fauna because of their close association with
1 2
Cruciferae plants (Root 1973). Additionally, few researchers have
observed the effects of different systems on a single insect species
(Andow et al. 1986) or were conducted in a scale similar to agricultural
conditions. Bach (1980) and Kareiva (1983) suggested that the inability
to predict the effects of diversity is due to the confounding nature of
most manipulative experiments. This is true if the objective is to
explain reduced herbivory where reduction of herbivory occurs, but as the
main objective of the hypothesis is to predict the outcome of diversity
for purposes of pest reduction in agriculture, more systems simulating as
close as possible field crop systems should be tested.
I applied two agronomic practices likely to increase agroecosystem
diversity (no-tillage and strip-intercropping) on the two major row-crops
in Ohio, corn (Zea mays L.) and soybean (Glycine max Merrill).
Conservation tillage methods (reduced tillage or no-tillage) are
being used increasingly in the United States, with the main objectives of
controlling erosion and saving energy (Phillips et al. 1980). Lessiter
(1983) estimated that about 35% of all the corn and soybean planted in the
United States is now being grown under conservation tillage.
Intercropping and other multiple-cropping practices are almost restricted
to the tropics, where those systems have some agronomic, environmental and
social advantages (Francis 1989). Nonetheless, double-cropping wheat and
soybean is a common practice in the southeast United States (Francis
1989), and strip-intercropping of corn and soybean has been tried empirically as an alternative to monocultures in the midwest ("The New
Farm" Feb. 1986, "The Ohio Farmer" April 1988).
Reduced-tillage practices increase the structural diversity at the 3
soil level (more crop residues), modify species and structural diversity
at the canopy level (changes in the weed population), are likely to change
the microclimate (soil temperature), plant physiology (water absorption),
plant architecture, and plant size (Phillips et al. 1980, Stinner and
House 1990). As for intercropping, there are changes in plant quality
(due to patterns of light, water and nutrients absorption), plant
diversity, and patch size (Francis 1989). Therefore, no-tillage and
intercropping practices concurrently affect plant diversity, patch size
and plant quality, factors of resource concentration likely to alter
insect densities (Kareiva 1983).
This study had two main objectives. First, to test the hypothesis
that diversification of corn and soybean crops through tillage and
intercropping practices will reduce the incidence of herbivores and
increase the incidence of natural enemies. This hypothesis was addressed by quantifying the populations of the most common herbivores and natural
enemies in corn (Chapter I) and soybean (Chapter II) crops. Second, I
examined the suitability of diversity indices as parameters of community
structure, using the carabid beetle assemblage sampled by pitfall traps
(Chapter III). This was done by comparing the results of diversity
indices for each treatment with independent measures of richness, evenness and dominance. CHAPTER I
The Effects of Strip-intercropping and No-tillage
on Some Pests and Beneficial Organisms of C o m in Ohio
Introduction
Conservation-tillage and multiple-cropping practices result in changes
in the factors influencing resource concentration, and therefore may
affect density of pests and other organisms (Kareiva 1983). There is
little information about the effects of multiple cropping on corn insects,
but reduced-tillage practices are expected to increase the incidence of
some pests such as black cutworm (Aerotis jpsilon [Hufnagel]), armyworm
(Pseudaletia unipuncta [Haworth]) and slugs. However, for other important
pests such as corn rootworms (Diabrotica spp.) and the European corn borer
(Ostrinia nubilalis [Hubner]) the responses to tillage treatments have been inconsistent (Musick 1987, Stinner and House 1990). The objective of
the research presented in this chapter was to observe the impact of no-
tillage and strip-intercropping practices on the corn fauna, as these agronomic practices are likely or possible to be implemented on a large scale in Ohio.
Materials and Methods
Agronomic practices. The study was conducted from 1988 through 1990 on land located at the Ohio Agricultural Research and Development Center,
4 5
Wooster, Ohio. The experiment site had been planted with no-tillage corn
under no-tillage for two years before this study, and it was surrounded by
farmland (mostly corn and soybean) in an approximate 0.5 km radius. Corn
and soybean were planted on 24 plots (18.2 x 15.8 m each) arranged as a 3
x 2 factorial design with four blocks (Fig. 1). Each plot had 24 rows
(76.2 cm width) orientated from east to west to maximize light
interception. Factors were cropping systems (corn monoculture, soybean monoculture and corn-soybean in strip-intercropping) and tillage systems
(no-tillage and conventional tillage). Conventional tillage consisted of
plowing with a mold-board plow and disking before planting, and in no-
tillage plots planting was done directly into the stubble. The strip-
intercropping system was established by alternating three 4-row strips of
each crop (Fig. 1), an array compatible with the machinery available.
Corn variety 'Pioneer 3780' was planted at a rate of 5.1 plants/m in 1988, and it was replaced by variety 'Pioneer 3552' in 1989 and 1990 because the
first variety was no longer available. Soybean variety 'Asgrow 3127' was planted at a density of 33 plants/m. Planting dates were 5 May in 1988,
17 May in 1989 and 14 May in 1990. Plots and strips were rotated in 1989 and 1990. In 1988 and 1990, areas of corn were treated with recommended pre-emergence herbicides (alachlor 2.2 kg [AI]/ha, cyanazine 2.2 kg
[AI]/ha, and paraquat 0.56 kg [AI]/ha). For areas with soybean, cyanazine was substituted by linuron (0.56 kg [AI]/ha). The herbicide treatment was not sufficient to significantly reduce the infestation of Canada thistle,
Cirsiuro arvense (L.) Scop., in 1988, probably a consequence of propagules accumulation from past years. Therefore, glyphosate (33% solution) was hand-sprayed two weeks after planting on areas of heavy infestation. In 1989 rains prevented herbicide treatment until the crops had germinated,
so plots were sprayed with paraquat (1.1 kg (AI]/ha) after the crops were
shielded by metallic strips placed over the crop rows. After these
chemical treatments, weeds were controlled by hand weeding, only to
maintain the weed canopy below the crops' level and therefore reducing
competition for light. The vegetation outside the plots was periodically controlled by disking the alleys between plots and mowing the grassy boundary surrounding the experimental area. Six weeks after planting, all plots received a broadcast application of P (58.0 kg/ha) and K (58.0 kg/ha), and corn plots and strips received nitrogen fertilizer (117.4 kg
N/ha). Because of low rainfall during the early season of 1988, plots were irrigated at two 24-h periods one week apart in late June.
Average plant size and yield were calculated using corn plants that had been collected to sample the second generation of the European corn borer (see below). The corn ears were shelled and weighed, and one 100-g grain sample per plot was dried at 60 °C until constant weight to determine moisture content. Grain weight (g/10 plants) was corrected to 15.5% moisture (a standard value for corn storage), and together with the average number of plants per row allowed estimation of yield (kg/ha).
Sampling. Arthropods and damaged plants were counted on 20 consecutive plants per row at two randomly selected sites per plot.
Within each plot, the first four rows on each side and an approximately 2 m section at the beginning of each row were not sampled to reduce edge effect. Each plant was initially scanned from top to bottom, and then the whorl and leaves were examined for an average of 15 seconds per adult plant. Flying insects were not counted, and when the plants were too tall, only leaves up to about 1.8 m were examined. Therefore, decreased
accuracy can be expected when the western corn rootworm was abundant, as
this insect readily takes flight when disturbed, or for late season
samples, when much of a plant was not examined. However, as there was no
indication of a systematic bias reducing sampling precision, visual counts
were considered reliable to detect treatment differences.
During early season (from plant emergence to late June), damage caused by cutworms (mostly the black cutworm) was estimated every two weeks by
r the number of plants cut or damaged at their base, and damage caused by
the armyworm was assessed by the number of plants shewing characteristic
injury on leaves and whorls. Stalk borers (Papaipema nebris [Genee]) were present in all three years but at insignificant levels, therefore not included in the sampling. In 1988, ladybugs (mostly Coleomegilla maculata
[DeGeer]), Japanese beetles (Poplllia laponica Newman), stink bugs
(Acrosternum hilare [Say] and Euschistus servus [Say]), tarnished plant bugs (Lvpus lineolaris Palisot de Beauvois) and first generation of the
European corn borer were sampled weekly from 30 June to 1 September.
Spiders were included in the sampling scheme in 1989 and 1990, conducted from 5 July to 1 September in both years. Japanese beetles, plant bugs and stink bugs are general feeders and are not considered to be pests of corn, but they were sampled because their abundance could provide evidence for treatment effects. Flea beetles (mostly the corn flea beetle,
Chaetocnema pulicaria Melsheimer) and Anthocoridae bugs (Orius spp.) were common, but the visual samples were not considered suitable to estimate densities of such small and highly mobile insects. Beginning on the second week of July in all three years, the western corn rootworm 8
(Diabrotica virelfera virgifera LeConte) was sampled weekly for five weeks. The numbers of the northern corn rootworm (D. barbieri Smith and
Lawrence) and the southern corn rootworm (D. undecimpunctata howardi
Barber) were low in all three years, and are not reported. Density of the
European corn borer was estimated by counting the number of plants with evidence of feeding and fresh frass in the whorl. This method was considered a reliable method of sampling, as inspection of a 2 0 -plants sample with that combination of signs revealed European corn borer larvae in all plants.
In late July of each year, five randomly chosen corn plants per plot had their root systems evaluated for rootworm damage using Hills and
Peters' (1971) damage scale. Adult corn rootworm counts and root damage evaluation in 1989 suggested that cropping system affected rootworm oviposition (see Results); therefore, eggs were sampled in \pril of 1990, before the tillage operations. Eight soil cores of 331 ml each were collected randomly at a depth of 13 cm from each monoculture plot, and 16 cores were collected from each intercropping plot (eight cores from each crop). The soil was thoroughly mixed, and two-500 ml sub-samples per plot were processed by Shaw's et al. (1976) method of egg extraction. For assessing the European corn borer second generation, corn plants were collected during late season (15, 7, and 20 September for the three consecutive years) and dissected. Twenty plants per plot were examined in
1988, and 10 plants per plot were examined in 1989 and 1990. The results were expressed in number of plants infested per 1 0 plants, number of larvae per 10 plants, and number of larvae per 10 infested plants. As plants were significantly damaged by slugs in the early season of 1989, 9 plots were evaluated by an arbitrary defoliation scale, from zero to three
(0: little damage, up to 5% defoliation; 1: visible damage, 5-10% defoliation; 2: significant damage, 10-50% defoliation, and 3: severe damage, more than 50% defoliation). Slugs were counted at three sites per plot during the night after the damage evaluation (17 June), and were expressed in numbers per row-meter.
Analysis. Analyses of variance (ANOVA) were performed on the total numbers of damaged plants, species or taxa collected per plot over the season. Examination of the data indicated different requirements to comply with the assumptions of the ANOVA. Therefore, before analyses the numbers of western corn rootworm adults were transformed into log (x+1 ) and the numbers of the remaining arthropods, slugs, rootworm eggs, damaged plants and plants/m were transformed into ,/X±0.5. Results of yield and plant size were analyzed using untransformed values. Because this study focused on corn fauna only, analyses were performed as a 2 by 2 factorial
(monoculture and intercropping, conventional tillage and no-tillage) with blocks, and when there was a significant value for the interaction effect
(tillage by cropping system), means for each treatment were separated by the Least Significant Difference (LSD) test. The results of root damage scale and plant damage were analyzed by Friedman's 2-way ANOVA test, and means were separated by the corresponding multiple-comparison procedure
(Daniel 1978). Association between plant parameters and western corn rootworm and European corn borer (the most abundant insects) were investigated by correlation analyses. 10
Results
The number of plants damaged by cutworms and armyworms was
significantly higher in no-tillage than in conventional tillage plots in
1988 (Table 1), with armyworms causing heaviest damage on 14 June and 30
June. Fewer plants were attacked by cutworms, with visible damage on 14
June only. In 1989, armyworm damage was notable on only one sampling date
(19 June), with no-tillage treatments showing significantly higher damage
than conventional tillage (Table 1) . There was no noticeable infestation
of cutworms. The numbers of slugs were significantly higher on the no
tillage treatment than on conventional tillage in 1989 (Table 1), a result
supported by the estimation of defoliation (although the visual evaluation also reflected less important damage from other pests, such as armyworms).
The defoliation score of corn plants in no-tillage plots was 2.9 ± 0.4, significantly higher ( % 2 - 7.91, df - 3, P < 0.05 Friedman's test; X2o 95
- 7.81) than of corn in conventional tillage plots (2.0 ± 1.4). There were no measurable infestations of cutworms, armyworms or slugs during
1990.
The adult population of the western corn rootworm was high in 1988, with about twice as many beetles In conventional tillage plots than in no- tillage plots (Fig. 2: F - 14.31; df - 1, 9; P - 0.005). There was an overall reduction in the western corn rootworm density in 1989, and significantly higher numbers of beetles were found on intercropped corn than on monocultures (Fig. 2: F - 39.85; df - 1, 9; P - 0.001). However in 1990, the ANOVA indicated a significant value for the interaction effect (F - 28.62; df - 1, 9; P - 0.0007), and means separated by the LSD test showed that the intercropped-conventional tillage treatment had a significantly higher number of beetles than the other three treatments
(Fig. 2). An average of one beetle per plant is recommended as the
threshold for economic damage in the following year (Turpin 1972, Willson
and Eisley 1987), although Foster et al. (1986) questioned the reliability
of scouting adults to predict economic damage. If the threshold is valid,
crop rotation was not sufficient to reduce the incidence of western corn
rootworm below the economic level on intercropped corn in 1989, nor on
intercropped-conventional tillage corn in 1990 (Fig. 2). The root damage evaluation supported in part the results of adult counts; there were no differences in root damage in 1988, but the damage on intercropped corn in
1989 was bordering the economic threshold suggested by Turpin et al.
(1972). Damage on intercropped-conventional tillage plots was significantly higher than on monoculture plots (x2 - 8.82, df - 3, P < 0.05
Friedman's test; X20 95 “ 7.81) (Fig. 2). The results from 1990 were similar, again with significantly higher damage on intercropped- conventional tillage (x2 - 14.80, df - 3, P < 0.01 Friedman's test; x2q 99
- 11.30). Root damage and adult counts were significantly correlated during all three years (1988: r - 0.520; 1989: r - 0.921; 1990: r - 0.720;
P < 0.05 after the Bonferroni adjustment, n - 16 for each year).
Considering the results for all plots during three years, about 79.2% of the results for root damage and adult counts coincided in determining infestation above or below economic levels (Fig. 3), a highly significant result according to a chi-square test of independence (x2 - 15.63, df - 1,
P < 0.005; x2o 995“ 7.88). There were more rootworm eggs in the soil collected from areas planted with corn in the year before, with intercropped corn showing higher numbers (10.5 ± 8.4 eggs per liter of 12
soil) than monoculture corn (4.0 ± 3.0), although not statistically
significant (F - 3.67; df - 1, 9; P - 0.08). There were 2.5 ± 3.2
rootworm eggs per liter in the soil collected from areas planted with
intercropped soybean in the year before, significantly more (F — 4.78; df
- 1, 9; P — 0.05) than the 0.1 ± 0.3 eggs found in monoculture soybean.
There were no significant differences for the tillage effect or
interactions.
In 1988 the numbers of the European corn borer-first generation were
negligible, but about 29% of the corn plants were infested by the second
generation. There was significantly higher infestation (F - 10.14; df -
1, 9; P - 0.01) of the second generation in conventional tillage plots
(3.7 ± 0.6 infested plants/10 plants) than in no-tillage plots (2.2 ±
0.9). The number of larvae per 10 plants was also higher in conventional
tillage plots (Table 2). The highest density of the European corn borer
occurred in 1989, both for first and second generations (Table 2).
However, only the first generation indicated a significant tillage effect,
a result more apparent on earlier counts (Fig. 4). For the second generation, 6 6 % of the plants had European corn borer larvae, but with no significant differences between treatments. In 1990, there was again higher numbers of the first generation on conventional tillage, but the number of second generation larvae per 1 0 plants was significantly higher only for the conventional tillage-monoculture treatment (Table 2), and the overall infestation rate was 69%. There were no significant differences for the number of larvae per infested plants in any year, with 1.5 ± 0.3 larvae per plant in 1988, increasing to 2.0 ± 0.6 in 1989 and 2.0 ± 0.4 in
1990. 13
Japanese beetles, stink bugs and spiders were not affected by
treatments in any of the three years. Ladybugs and plant bugs responded
to treatments in 1990 only; there were 5.5 ± 2.0 ladybugs in conventional
tillage plots, a significantly higher value (F - 5.18; df - 1, 9; P -
0.05) than in no-tillage plots (3.8 ± 1.4). Plant bugs were affected by
tillage and cropping system (tillage: F - 50.05; df - 1, 9; P - 0.002;
cropping system: F - 9.34, df-1, 9; £ - 0.01), with 5.4 ± 1.6 and 1.5 ±
0.7 plant bugs per 20 plants for no-tillage and conventional tillage plots
respectively, and 4.4 ± 2.3 and 2.5 ± 1.9 plant bugs for monoculture and
intercropping plots.
There was a trend for infestation of European corn borer on taller
plants in 1988 and 1990 (Fig. 5) , as 21 and 50% of the plants in the 150-
2 0 0 cm range were infested in both years respectively, but increasing to
40 and 76.6% infestation of plants in the 200-250 cm range. These results
were statistically different when analyzed by a chi-square test (1988: x2
- 4.59, £ < 0.05, df - 1, x20 95 - 3 . 84; 1990: x2 - 10.40, £ < 0 .0 1 , df -
1. X2q 99 “ 6.63). However, correlation analyses between number of European
corn borer per 10 plants and plant height indicated differences for 1990
only (r - 0.598, £ - 0.01, n - 16). There were no treatment differences
in plant height in 1988, but in 1989 plants were taller in conventional
tillage (F - 5.46; df-1, 9; £ - 0.04) and in monocultures (F - 5.62; df
— 1, 9; £ - 0.04). Similar results were found in 1990, with significantly higher results for monocultures (F - 7.74; df - 1, 9; P - 0.02) and a
trend for higher plants on conventional tillage (F - 4.37; df - 1, 9; £ -
0.06). 14
Table 3 is a summary of the agronomic parameters for the three years.
There were no significant treatment differences in 1988, with a slight
indication of interaction (£ - 3.50; df - 1, 9; £ - 0.09) between tillage
and cropping system for yield results (Fig. 6 ). In 1989, the conventional
tillage plots had greater yield (6,248 ± 1,389 kg/ha) than no-tillage
plots (5,262 ± 922 kg/ha; F - 5.12; df - 1, 9; £ - 0.05) (Fig. 6 ). Also,
there were significantly more (F - 15.62; df-1, 9; £ - 0.0001) plants/m
in conventional tillage plots (3.7 ± 0.3) than in no-tillage plots (2.7 ±
0.3). In 1990, there were no significant differences for total yield
despite a trend for higher production on conventional tillage (F - 4.27;
df-1, 9; £ - 0.07) (Fig. 6 ), but grain weight per plant was higher on
conventional tillage (139.8 ± 28.3 g/plant) than on no-tillage (106.8 ±
19.9 g/plant; £ — 6.13; d f — 1, 9; £ - 0.03). For the three years, yield was not correlated either with root damage and western corn rootworm
numbers or with European corn borer numbers. Also, there was no
correlation between western corn rootworm root damage and adult counts and yield for the following year.
Discussion
Cutworms, armyworms and stalk borers are some of the insect pests of greatest concern in conservation-tillage systems (Musick 1987, Stinner and
House 1990). However, despite the higher incidence of cutworms and armyworms on no-tillage corn, their damage was only bordering the economic levels of 20-25% of plants damaged by armyworms and 3-5% of plants damaged by cutworms as suggested by Wilson et al. (1980). Slugs however were a serious problem for no-tillage corn and soybean in 1989, with severe 15
damage in some spots. Although there was an overall reduction of plant
population from 1988 to 1989 (Table 3), which could be attributed to low
germination, the differences between tillage treatments in 1989 can be partially credited to slugs. There was above normal precipitation during
May and June (297.2 mm, about 47% more than the period's average), creating favorable conditions for the slug population at the seedling stage which is highly susceptible to damage. The overall slug population measured by pitfall traps was highest in 1990 (Chapter II) , but they occurred mostly at later stages of the growing season and no detectable damage to the crops was observed.
The results of adult counts and root damage suggest that both conventional tillage and intercropping have a positive effect for the western corn rootworm. The higher incidence of adults on conventional tillage versus no-tillage but no differences in root damage in 1988 support Gray and Tollefson's (1987) hypothesis that there is reduced survival of corn rootworms in no-tillage systems, which may be associated with higher weed density (Johnson et al. 1984). However, there was no significant tillage treatment effect in 1989. Despite an overall reduction of western corn rootworm numbers as a consequence of crop rotation, there was higher incidence of adults and damaged roots on intercropped corn, with both measurements indicating densities near or above the economic level. Apparently, females dispersing from corn strips laid enough eggs on soybean strips to maintain damaging levels on the corn strips in the following year, as corn rootworm adults commonly disperse to feed on other crops (Shaw et al. 1978). On corn-soybean rotation systems, rootworms have increased survival in soybean fields containing volunteer 16
corn (Shaw et al. 1978), and Intercropping plots may have acted as a
soybean crop "infested" by corn. The results of egg counts support this
hypothesis, as does the number of adults collected in sweep net samples
from soybeans (unpublished data). For example, on 24 August, 1990, there
were 15.6 ± 8.9 adults collected per sample (80 sweeps/plot) on
intercropped plots, but only 3.5 ± 2.7 adults on soybean monoculture.
Another possible factor for higher numbers of the western corn rootworm on
intercropped corn could be larval dispersal: Short and Luedtke (1970)
reported distances of up to 0 . 8 m from egg hatch to adult emergence sites.
The 3.0-m corn strips could have been insufficient in preventing larval migration to corn strips in the following year. In 1990, intercropped-
conventional tillage corn had the highest values of adults and root
damage, again suggesting that both practices have a beneficial impact on western corn rootworm survival. Despite infestations above the economic
level, there was no clear association between western corn rootworm and yield. Apparently, variables such as weather and agronomic practices obscure the expected effect of yield reduction. Nonetheless, the three- year results for the conventional tillage factor suggest that
intercropping had a slightly lower yield than monoculture (Fig. 6 ), a possible consequence of greater western corn rootworm damage (Fig. 2).
In earlier reports on the potential effects of reduced-tillage practices on corn insects, Musick and Petty (1973) and Gregory and Musick
(1976) predicted that the incidence of European corn borer would increase under conservation tillage because of greater survival of overwintering larvae in corn stalks and weed stubble in the field, and longer predisposition of the crop to second generation larvae due to slower crop development. However, infestation from adjacent fields may neutralize the
effects of stubble destruction on conventional tillage (Wilson et al.
1980). Berry and Ghidiu (1989) reported that crop rotation combined with
tillage treatments affected European corn borer populations in six out of
eight years of observations, but not in a clear pattern. My results
indicate that the European corn borer population was generally reduced by
no-tillage practices. Because no-tillage corn has a slower development
and concentration of the aglucone DIMBOA (which confers resistance to the
European corn borer) is usually inversely proportional to plant height
(Showers et al. 1983), corn under conventional tillage could provide a more favorable substrate for the insect. This hypothesis is supported by
the fact that differences in damage between tillage treatments caused by
the first generation in 1989 (the highest density) were more evident
during earlier stages of plant development. However, despite a trend for higher numbers of European corn borer on taller plants, plant height was not a conclusive factor in determining level of infestation for a given
treatment in 1988 nor in 1989. Only in 1990 was there an apparent association between individual plant height and infestation levels. The
European corn borer is very susceptible to environmental conditions
(Showers et al. 1983, Jarvis and Guthrie 1987), one possible reason for low densities in 1988, as there was below normal rainfall during early season. An additional reason for lower numbers of the first generation in
1988 could be a higher rate of predation; sweep net samples from soybean revealed a high population density of Orius spp. (see Chapter II), which is capable of exerting a strong impact on the European corn borer (Jarvis and Guthrie 1987). Higher densities in 1989 and 1990 could have 18
influenced plant size effect. As infested plants are less attractive to
ovipositing moths (Everett et al. 1958), the more even distribution of the
European corn borer across different plant sizes could be a result of
fewer ideal oviposition sites.
In summary, tillage had a greater impact on the corn fauna included in
this study than cropping system. Cutworms, armyworms and slugs were favored by no-tillage, although only slugs could be considered a serious pest during an exceptionally wet early season. European corn borer and western corn rootworm densities were generally reduced on no-tillage plots, although the results were not consistent for the three years. The results for ladybugs and plant bugs should be viewed with caution, because of their low numbers (particularly in 1988, a likely consequence of a very dry season), and because of statistically significant results in 1990 only. Although there were no conclusive correlations with yield, this study suggests that western corn rootworm densities may be increased by the strip cropping practice employed here, despite crop rotation. 19
Table 1. ANOVA results for armyworms, cutworms and slugs In 1988 and
1989 (there were no measurable infestations in 1990). Means (number of damaged plants/ 2 0 plants for armyworms and cutworms, slugs/row-meter for slugs), standard deviations and £ values are for the tillage effect (NT - no-tillage, CT - conventional tillage), df — 1, 9
1988 1989
X FP X F P
armyworms NT: 3.5 (2.3) 17.85 0.05 NT: 1.6 (1.2) 7.22 0 . 0 2
CT: 1.0 (0.7) CT: 0.4 (0.8)
cutworms NT: 0.9 (1.4) 5.24 0.05
CT: 0.1 (0 .2 )
slugs NT: 1.5 (0.7) 6.73 0.04
CT: 0.5 (0.5) 20
Table 2. ANOVA results for the numbers of European corn borer larvae per 10 plants. Means, standard deviations and F values are for the tillage effect except for the second generation in 1990, where F reflects interaction effect and means were separated by the Least Significant
Difference test (NT - no-tillage, CT - conventional tillage, IC - intercropping, MC - monoculture), df - 1, 9
first generation second generation year X F PX FP
1988 CT: 5.9 (1.8) 7.48 0.02
NT: 3.3 (1.8)
1989 CT: 4.5 (1.6) 5.11 0.05 CT: 13.6 (6.7) 0.12 0.7
NT: 2.6 (1.1) NT: 13.2 (5.0)
1990 CT: 1.1 (0.3) 16.22 0.003 CT-MC: 21.7 (4.8) 4.61 0.04
NT: 0.3 (0.3) CT-IC, NT-MC,
NT-IC: 11.4 (3.8) 21
Table 3. Summary of the agronomic parameters for corn for three years.
Means and standard deviations are for the overall experiment
year yield (g/plant) plants/m yield (kg/ha) plant height (cm)
1988 105.8 (15.6) 4.1 (0.3) 5,741 (1,259) 195.3 (4.3)
1989 138.3 (29.1) 3.2 (0.3) 5,755 (1,247) 223.0 (6.1)
1990 123.3 (29.1) 3.5 (0.2) 5,579 (1,239) 220.5 (6.7) Figure 1. Spatial arrangement of the 24 plots. East to west alleys were
4.0 m wide, and north to south alleys were 3.0 m wide.
22 23
f ~ i CORK CONVENTIONAL TO lA aE
E M CORN. NOHLAGE SOYBEAN. CONVEWTIOHALTIUAGE
SOYBEAN NOTtUAQE
Fig. 1 Figure 2. Western corn rootworm : results of adult counts during highest infestation (1988: July 26; 1989 and 1990: August 3) and root damage evaluations. MC — monoculture, IC - intercropping, NT = no-tillage, and CT - conventional tillage. The dotted lines indicate the economic thresholds, and vertical lines are standard deviations.
24 09
ROOT DAMAGE 8CALE i. 2 Fig. 2 6 6 ■ ■ - - 1988 1988 991990 1989 991990 1989 b b b b V/Z/A YZZZh H H MC-CT MC-CT IC-CT IC-NT MC-NT IC-CT T 1C-N MC-NT 25 Figure 3. Three years results of adult counts and root damage evaluation of western corn rootworm for each corn plot. The dotted lines represent the economic thresholds.
26 ROOT DAMAGE
N3 'vj Figure 4. Number of plants damaged by the first generation of the
European corn borer (ECB) per 10 plants in 1989 and 1990. NT - n o tillage, CT - conventional tillage. Vertical lines are standard errors.
28 ECB/10 PLANTS EC8/10 PLANT8
e o 0 e « © h e « e o o o so 1 ©s © o *T) o 1 1 1_ H- OQ
01
a* o
01
»• o
0 01
w o I
a 3
K> LjO Figure 5. Frequency distribution of plants infested by second generation European corn borers on plant height classes in 1988, 1989 and
1990.
30 31
i a 2 2 JO KANT HMHT M
2 23 KANT HMHT M
Fig. 5 Figure 6. Average yield of corn for each of the four treatments: MC ■= monoculture, IC - intercropping, NT - no-tillage, and CT - conventional tillage.
32 33
k0 /h* 1998
7.000 NT CT «/>oo
CT 0 , 0 0 0
NT
4.000 MC 1C
kf/ha 199#
7,00c CT CT M>oo
NT 0.000 NT
4*00 MC 1C
kQ/ho 1990
7.000 CT
• * 0 0 CT
1 . 0 0 0 NT NT
4JXX> MC 1C
Fig. 6 CHAPTER II
Response of Soybean Fauna to Two Agronomic
Practices Increasing Agroecosystem Diversity
Introduction
Studies of plant species diversity and structural diversity affecting insect communities have significant value because they are part of the broader debate over the importance of biotic or abiotic factors that regulate populations. For agroecosystems, numerous studies (reviewed in
Altieri et al. 1978 and Altieri and Letourneau 1982) support the resource concentration hypothesis (Root 1973), which predicts reduced numbers of herbivores (particularly specialist species) on diversified systems because of an "associational resistance" (Tahvanalnen and Root 1972) provided by non-hosts. However, there are studies indicating that diversified agroecosystems may increase densities of specialist herbivores
(Capinera et al. 1985, Letourneau 1986), and increase (Marston et a l .
1979) or reduce (Andow et al. 1986) densities of both pests and natural enemies. Reduced tillage and multiple cropping systems can alter several agronomic variables (Phillips et al. 1980, Francis 1989), with possible impact on the insect fauna. However, I believe that it is unlikely that all these factors will affect different species in different systems in a way to provide a predictable pattern. The effect of separate aspects of heterogeneity may be the reason why closely related species sometimes give
34 35
inconsistent responses to diversification (e.g. Bach 1988). Some studies
of agroecosystem diversity have led to the conclusion that each case is
unique, and generalizations are thus difficult (Cromartie 1975, Nordlund
et al. 1984, Letourneau 1986, Kareiva 1987, Andow 1988). In this chapter,
I observed the effects of two specific aspects of agroecosystem
diversification (no-tillage and intercropping) on the most abundant
invertebrate fauna of soybean.
Materials and Methods
Agronomic practices. Details of the experimental design and agronomic
practices were given in Chapter I. In addition, I used the Braun-Blanquet
scale (DIgby and Kempton 1987) to estimate weed populations. Soybean yield was estimated by harvesting and processing in a mechanical thresher
four 1-m rows per plot. One 100-g grain sample per plot was dried at 60°C until constant weight to estimate moisture content, and grain weight was corrected to 13% moisture, a standard value for grain storage.
Sampling. The objective of sampling was to survey thoroughly the most abundant macroarthropod fauna of soybean, so several methods were used: direct counts, suction trap (D-vac), sweep net, pitfall traps and quadrat
samples. The organisms sampled were grouped in the most accurate
taxonomic classification that could be practically determined, therefore most economically important organisms were identified to species level whereas other organisms were grouped from genus to class only. Diptera was the only abundant macroarthropod group not included, except for syrphid and tachinid flies. The taxonomic groups were divided into three feeding guilds: herbivores (defoliators and sap feeders), natural enemies 36
(predators and parasitoids), and generalists. Feeding habit information was based on Borror et a l . (1981) and Dindal (1990). Table 4 lists the taxonomic groups, guilds and sampling methods used. In some cases, a particular taxon was predominant within a group, which is also indicated in Table 4. Spiders, Hymenoptera and Phalangidae were ecologically divided into soil and foliage dwellers, a division supported by taxonomical differences at least for spiders and Hymenoptera (Table 4) .
The guild classification was somewhat arbitrary: slugs, for example, are general feeders, but they were included in the herbivore guild because of the damage they caused to the crops in 1989 (see Results section). Other organisms such as Carabidae and Phalangidae were classified as generalists because of their broad feeding range, despite the possible predatory role of some species.
For all sampling methods, the first four rows at each side of every plot and an approximate 2.0 m section at the beginning of each row were excluded from sampling to reduce edge effect. Details of each method are described below.
Sweep net. Samples were taken by 20 alternate sweeps with a 38-cm diameter sweep net across one row on four rows per plot. Methodological details of sweep net sampling followed Kogan and Pitre (1980). In intercropping plots, there were only eight rows (two strips) of soybean available for sampling because of the border rows. At each sampling date, two rows per strip were chosen at random for sampling. For the monoculture plots, two rows were chosen at random, but the other two sampling sites were located within two rows from the randomly selected rows. I used this procedure to reduce differences between intercropping 37 and monoculture due to spatial concentration of samples. If rows in the monoculture plots were chosen at random from the sixteen rows available for sampling, walking along the rows during sampling would likely disturb the fauna in the monoculture plots less than in the intercropping plots.
Samples were pooled by plot, bagged and frozen for later count and identification. Sampling was restricted to dry, calm days, usually done during early afternoon, when dew had evaporated. Samples were taken biweekly at five dates in 1988 starting on 15 July, weekly for eleven weeks in 1989 starting on 2 July, and weekly for ten weeks starting on 17
July in 1990.
Suction trap. In 1988 we used a D-vac sampler (backpack model) to sample ten whole plants per row on two rows per plot. This method had low efficiency, therefore it was modified by sampling plants at uniform height on two entire rows per plot (one row per available strip in intercropping plots) in 1989 and 1990. Details of whole plant and entire row sampling are given in Kogan and Pitre (1980). I took five biweekly samples in
1988, starting on 8 July. In 1989 and 1990 samples were taken weekly, eleven times starting on 26 June in 1989 and ten times starting on 27 June in 1990. Sampling patterns and weather constraints for D-vac followed the same procedures as for sweep net sampling.
Direct counts. This method was used to sample soybean early in the season, when larger insects were easily counted and plants were too fragile to be sampled by sweep net. Plants were visually scanned and subsequently leaves and stems were examined. In 1988 a sample consisted of twenty plants searched per row, repeated four times per plot. In 1989 and 1990, I counted the number of insects in two rows per plot. Samples 38 were taken weekly for four weeks in 1988 starting on 14 June, for five weeks in 1989 starting on 8 June, and for five weeks starting on 6 June in
1990. Because of a heavy slug infestation during the early season of
1989, damage was estimated on 20 June by a 0 to 3 defoliation scale (0 - little damage, up to 5% defoliation; 1 - visible damage, 5-10% defoliation; 2 - considerable damage, 10-50% defoliation, and 3 - severe damage, more than 50% defoliation). The estimation was done by examining plants on four 1-m row sections on each plot.
Pitfall traps. The epigeal fauna was sampled by two pitfall traps per plot. Traps consisted of 11-cm diameter plastic cups filled with about
100 ml of a water and ethylene glycol mixture (1:1). After each sampling period (48 h), the traps' contents were pooled by plot, washed in a 48 mesh sieve, and the organisms sorted were stored in alcohol for later identification. I took seven samples each year from June trough September at approximately two-week intervals, starting on 1, 18 and 14 June for the three consecutive years.
Quadrat samples. Because of the drawbacks of pitfall sampling
(Greenslade 1964), quadrat samples were used as an alternative method.
The epigeal fauna was searched in each plot in a randomly chosen 1.0 m2 area between rows to about 1 cm deep in the soil. I took five samples in
1988 (13 June, 2 and 18 July, 2 and 22 August), three samples in 1989 (28
June, 10 July, 1 August), and three samples in 1990 (28 June, 26 July, 25
August).
Analysis. Analyses of variance (ANOVA) were performed on total numbers of each taxon collected over the season to detect the organisms' overall response to treatment effect. However, for noticeable treatment 39
effects during part of the season, ANOVA were performed on the numbers of
each taxon at each sampling date. Most variables with significant results
for total numbers were also significant on at least one sampling date.
Because means and variances were correlated for most data, ANOVA were
performed on transformed data (log [x+1]). For pitfall trap and quadrat
samples, collected from corn and soybean, ANOVA were performed on a 3 by
2 factorial design with three cropping systems (soybean, corn and strip-
intercropping) and two tillage systems (conventional tillage and no
tillage). Degrees of freedom were 2, 1, 3 and 15 for cropping system,
tillage system, replication and error, respectively. Consequently,
"cropping system" for soil organisms actually reflected crop species preference. When there were significant differences for the cropping
system factor or interactions, means were separated by the Least
Significant Differences test (LSD). For the results of the remaining
sampling methods, collected from soybean only, analyses were done on a 2 x 2 factorial design with two cropping systems (monoculture and
intercropping) and two tillage systems. Degrees of freedom were 1, 1, 3 and 9 for cropping system, tillage system, replication and error, respectively.
Results
The ANOVA results for total numbers of every taxon showing statistically significant results (P < 0.05) in at least one year are given in the Appendices A through E, and a summary of the responses to treatments based on the statistical significance level is given in Table
5. From those taxa sufficiently abundant to be analyzed statistically
(Table 4), stink bugs, Hemiptera and Staphylinidae showed no response to 40
treatments in any year.
Sampling methods results. The results of sweep net and D-vac samples based on responses to treatment effects were consistent for the tarnished plant bug, Homoptera and Nabidae (Table 5). For the remaining five taxa sampled by both methods (green cloverworms, potato leafhoppers,
Anthocoridae, spiders and Hymenoptera) , the results were less consistent.
Studies comparing both sampling methods (Kogan and Herzog 1980) suggested that D-vac generally is more reliable than sweep net for sampling small size organisms and organisms located deep in the canopy. However, D-vac results for the green cloverworm corroborates the age-class bias demonstrated by Pedigo et al. (1972); Lepidoptera larvae in D-vac samples were always of small size (up to about 0.8 cm) even when sweep net samples and direct observations indicated the presence of larger larvae. Irwin and Shepard (1980) reported higher reliability of sweep net than D-vac for sampling Orius spp., which concentrate on the upper portion of soybean plants. Therefore, further discussion of results will be based on D-vac samples for the potato leafhopper, spiders and Hymenoptera, and on sweep net samples for green cloverworm and Anthocoridae.
Comparisons between direct counts and sweep net or D-vac samples are not possible because sampling dates did not overlap; nonetheless, there were equivalent results for the striped flea beetle and the grape colaspis, but not for the bean leaf beetle (Table 5). Because direct counts were restricted to early season when the bean leaf beetle density was relatively low, I considered sweep net results as more representative than direct counts. 41
For the epigeal fauna, quadrat and pitfall samples gave equivalent results for slugs, ants and beetles but not for Carabidae (in 1988 only), millipedes, and centipedes. As for millipedes and centipedes, their numbers were constantly low in quadrat samples. Analysis of the Carabidae fauna (see Chapter III) revealed that both sampling methods yielded quite different species composition, possibly reflecting differences between diurnal species (quadrat samples) and nocturnal species (pitfall traps).
Therefore, it was not possible to determine whether discrepancies between methods resulted from sampling efficiency or dial periodicity. Although quadrat samples are an absolute sampling method, I considered pitfall traps more suitable for sampling nocturnal arthropods.
Responses to treatments. The seasonal distributions of the green cloverworm during the three years based on sweep net samples are shown in
Figure 7. There were no significant treatment effects in 1988, when green cloverworm density was lowest of any year, with a peak infestation of 5.9
± 4.2 (mean + standard deviation) larvae per sample. Anthocoridae bugs
(mostly the minute pirate bug), common predators of soybean Lepidoptera
(Mayse 1978, Barney et al. 1984), may have had a significant effect on green cloverworm populations, particularly in 1988 (Fig. 8). The highest green cloverworm infestation occurred in 1989, with a maximum density of
39.4 ± 12.8 larvae per sample and significantly higher numbers in intercropping plots (Table 5). Mayse (1978) suggested that high green cloverworm populations on soybean planted in narrow rows are a consequence of microclimate factors, which could explain higher numbers in intercropped soybean (e.g., more shade and reduced wind speed). However, although those environmental factors could be expected to be more 42
prevalent in no-tillage plots, there were significantly more green
cloverworm larvae in conventional tillage than in no-tillage plots in
1990, when there was a maximum infestation of 8.1 ± 5.1 larvae per sample.
There were no noticeable infestations of the fungus Nomuraea rilevi
(Farlow) Sampson in any year, although it frequently causes significant
mortality on green cloverworm populations (Hammond 1987).
Bean leaf beetle populations measured by sweep net samples were
significantly higher in no-tillage than in conventional tillage plots in
1988, but the tillage effect was reversed in 1989 (Table 5). The maximum
density in 1988 was 18.6 ± 11.4 beetles per sample, increasing to 34.4 ±
22.4 beetles per sample in 1989. There were significant differences in
precipitation during early season of both years (see below), and as soil
moisture and temperature are important factors for the survival of bean
leaf beetle eggs (Marrone and Stinner 1983), the dry early season in 1988
may have contributed to the overall low population levels and higher
survival in no-tillage plots (Fig. 9). There were no treatment
differences in 1990 when population densities were equivalent to 1988
values (maximum of 17.7 ± 9.7 beetles per sample), and rainfall was close
to the average. Troxclair and Boethel (1984) reported more bean leaf
beetles in no-tillage soybean during early season, but higher numbers in
conventional tillage later in the season, when densities of the insect
were higher. The opposite results between 1988 and 1989 may reflect a
complex response to treatments as a function of population density.
Direct counts also revealed dissimilar results along the season; on 22
June 1989, there were 12.4 ± 4.3 beetles per row in no-tillage plots,
significantly higher (F - 10.34; df - 1, 9; P - 0.01) than in conventional 43 tillage plots, with 6.3 ± 2.9 beetles per row. Two weeks later, there were 7.1 ± 2.0 beetles per row in conventional tillage plots and 4.6 ± 2.5 beetles per row in no-tillage plots (Z - 9.60; df - 1, 9; £ - 0.01).
Grasshoppers and the Japanese beetle were the herbivores causing the most visible damage to soybean, but not at the economic level in any year.
Intercropping has been reported to reduce Japanese beetle movement, whereas no-tillage and intercropping were expected to increase the numbers of Japanese beetle and grasshoppers (Table 6). However, treatment effects were significant in 1990 only, when the Japanese beetle and grasshoppers had respectively their lowest and highest population levels of any year.
Both insects were positively affected by no-tillage treatment, and
Japanese beetle numbers were also higher in intercropping than in monoculture plots (Table 5, Fig 10).
Striped flea beetle and grape colaspis were sporadic during the three years. Striped flea beetle densities were high during the early season of
1988, low in 1989, and high during late season of 1990. The results of visual counts and D-vac samples for this insect indicated positive effects of conventional tillage and intercropping (Table 5) . As for the grape colaspis, it had significant densities in 1988 and 1990 only, with visual counts and sweep net samples indicating higher numbers in no-tillage and intercropping treatments (Table 5).
Slugs were more prevalent in no-tillage plots than in conventional tillage plots in all three years. Despite the highest density occurring in 1990, damage to soybean plants was serious in 1989 only, when the peak infestation occurred during early season. Soybean seedlings had an average defoliation score of 2.1 ± 0.3 in no-tillage plots and 0.9 ± 0.5 44 in conventional tillage plots, significantly different by the Mann-Whitney test (n, - n2 ~ 8, U - 60.5, P - 0.01). Although comparisons are difficult because of different plant density and biomass, slug damage was apparently heavier on soybean than on corn.
D-vac samples indicated reduced potato leafhopper populations in no- tillage treatments in all three years, and in intercropping treatments in
1989 and 1990 (Table 5, Fig. 11). However, other Homoptera and the tarnished plant bug were more abundant in no-tillage plots (Table 5). The probable reason for tillage treatment differences among sap feeders was the higher weed density in no-tillage plots. Weeds are alternate hosts to
Cicadellidae, Cercopidae and the tarnished plant bug, but have a negative effect on colonization, dispersal and reproduction of the potato leafhopper (Table 6).
Intercropping had a general positive effect for most of the natural enemies sampled, particularly in 1989 (Table 5). Corn plants may have acted as wind breaks increasing the concentration of insects on strips of soybean (Mayse and Price 1978) , or may have created a more favorable environment with more shade and lower temperatures (Letourneau 1987, Andow
1988). Spiders and Nabis spp. comprise a large part of the natural enemies in soybean systems (Shepard et al. 1974, McPherson et al. 1982), therefore the presence of corn may increase predation rates on the soybean fauna.
Ants, beetles (excluding Carabidae and Staphylinidae), tiger beetles and soil spiders were usually more abundant in no-tillage plots, a richness trend found by several researchers (Stinner and House 1990 and references therein). The accumulation of plant residues on the soil surface probably Is the main reason for higher diversity of soil fauna in
conservation tillage systems, as many of the most abundant beetles and
ants apparently feed on fungi, seeds and decomposing organic matter
(Borror et al. 1981, Dindal 1990). Homoptera were collected in
significant numbers in pitfall traps in all three years, with
significantly greater numbers in no-tillage treatments. The abundance of
Cicadellidae and Cercopidae in pitfall traps suggests that these insects
occupy lower portions of the canopy in comparison to other sap-feeders
(Table 4), which were almost absent from pitfall trap collections. Soil
Hymenoptera, mostly belonging to the superfamily Proctotrupoidea, was the
most abundant group present in pitfall catches, with significantly higher
densities in conventional tillage plots in 1989 and 1990; they were also more abundant in corn than soybean plots in 1988 and 1990 (Appendix D).
Proctotrupoidea are mostly egg parasites of spiders and insects (Clausen
1940, Borror et al. 1981), but there was no apparent correlation between
Hymenoptera and spiders or any group of soil organisms.
Agronomics. The three years had significant differences in rainfall
during early season (May and June), a critical period for crop
development. The precipitation during those two months in 1988 was only
22.3% of normal levels (202.7 mm, 50-year average). In 1989 there were excessive rains (146.6% of the average), and 1990 was closer to a regular year (92.5% of the average). Weed populations exhibited the expected species shift in reduced-tillage systems (Koskinen and McWhorter 1986), with increased dominance of some weed species from 1988 to 1990 (Table 7).
Despite higher weed biomass in no-tillage plots, there were no detectable differences in weed species composition between no-tillage and 46 conventional tillage in 1988 and 1989. In 1990 however, conventional tillage plots were infested predominantly by grass species, whereas in no tillage plots broadleaves and grasses were equally present.
Yield results are shown in Figure 12. conventional tillage plots had higher yield than no-tillage plots in 1988, although the results were only bordering the statistical significance level (F - 4.70; df - 1, 9; P -
0.056). In 1989, tillage and cropping system factors were significant
(tillage system: F - 9.03; df - 1, 9; P - 0.01. Cropping system: F -
11.32; df - 1, 9: P - 0.008), and in 1990 only cropping system was significant (F - 23.93; df - 1, 9; P - 0.009). If we consider yield as an estimate of plant biomass, these results suggest that sampling could be biased, as sweep net and D-vac samples are affected by canopy density
(Kogan and Pitre 1980). However, correlation analyses between yield and taxa numbers for each year indicated no sign of bias.
Discussion
The validity of the results reported here as real trends for the soybean fauna is based on two assumptions: first, treatment effects were good representations of habitat diversity, and second, plot size was sufficient to reproduce the agroecosystem environment, an important constraint of this type of study (Kareiva 1983). A comparison of general trends from some of the fauna sampled with published studies (Table 6) indicated a similarity of results, suggesting that plot size did not have a strong effect on the fauna.
Among the 23 taxa with significant response to any of the treatment factors based on the most efficient sampling method (see Results section) and sampled for more than one year (all taxa from Table 4, excluding the
striped flea beetle and Carabidae), only eight had consistent results for
more than one year. Grape colaspis, slugs, tarnished plant bugs, ants and
beetles were always more abundant in no-tillage than in conventional
tillage plots, potato leafhopper and centipedes were always more abundant
in conventional tillage, and foliage spiders had greater density in
intercropping than in monoculture (some of these results are based on two
years only). The general low constancy of results could be a consequence
of low power of the statistical analyses, i.e., it could be the outcome of
low probability of correctly rejecting the hypothesis of no treatment
differences. For the a level and sample size used here, statistical power
is generally low (Cohen 1988, Table 8.3.12), indicating low reliability in
accepting the null hypothesis. However, I share Rotenberry and Wiens'
(1985) concern with the difficulties in estimating the "effect size" (or
a specific alternative hypothesis) needed to calculate power, particularly because small changes in effect sizes result in large changes in the probabilities of a type II error (Cohen 1988). The variability among
taxon and between years (see Appendices) makes the estimation of a reasonable effect size even more complex. Nonetheless, the data suggest
that the hypothesis of lack of consistency is reasonable. If I increase
the acceptance level to a - 0.10 (therefore increase power), about 50% of the taxa (12 out of 23) have inconsistent results; for a - 0.20, still more than a third (9 out of 23) of the taxa have inconsistent results (see
Appendices). Therefore, I concluded that the lack of agreement in the results actually reflected temporal variability, possibly a consequence of contingencies not controlled in the experiment. This variability is 48
illustrated by the seasonal and annual distributions of the four most abundant herbivore species (Figs. 7, 9, 10 and 11). Some species could have been affected by weather patterns (e.g. , the green cloverworm and the bean leaf beetle), predation (e.g., the green cloverworm), or shift of host plants for those species that feed to a large extent on weeds (e.g., the Japanese beetle and the striped flea beetle). Grossman (1982) and
Grossman et al. (1982) discussed the commonness of stochastic or non equilibrium communities, and they proposed that the widespread use of deterministic models to describe and explain patterns in nature results from the convenient assumption of predictability. We suggest that the
"stochasticity" ensues from uncontrolled events which are more rule than exception in the field situation. Testing ecological theories requires replication in time, but this aspect has been neglected (Tilman 1989) in studies of agroecosystem diversification (Kareiva 1983).
Despite low constancy, we could assume that significant results at any year reflect a trend towards treatment effects. Under this criteria, the
28 taxa sampled could be arranged according to their responses to treatment effects. Foliage organisms were influenced by tillage and cropping systems (Table 8), but cropping system had no effect on soil organisms (Table 9) . Most taxa had higher numbers on diversified treatments, supporting the theory of greater diversity in more complex habitats.
The resource concentration hypothesis (Root 1973) predicts that herbivores, particularly specialists, have lower numbers in diverse systems. Host specialization is not easily defined, and feeding exclusively on one species, one genus, or one family has been used as a criterion for monophagy (Fox and Morrow 1981). From the 12 most abundant soybean herbivores in this study, none is strictly limited to one plant species or genus (Deitz et al. 1976, Carter et al. 1982). At the family level, green cloverworm, bean leaf beetle and grape colaspis could be considered oligophagous because of their preference for legumes (Deitz et al. 1976, Carter et al. 1982). Considering the hosts available within the experimental area, the green cloverworm can be regarded as monophagous because it was observed feeding on soybean only. Bean leaf beetle, grape colaspis, and potato leafhopper can be considered oligophagous, as the first two species were occasionally observed feeding on corn, and few potato leafhoppers were found (apparently feeding) on corn and weeds. The remaining herbivores showed no preference for soybean; the striped flea beetle fed extensively on Canada thistle and lambsquarters, the Japanese beetle fed on both crops (preferentially on corn during the silking period) and on Pennsylvania smartweed, and the remaining herbivores fed on both crops and weeds. From the four species more likely to have their numbers reduced in diversified habitats according to Root's (1973) hypothesis (green cloverworm, bean leaf beetle, grape colaspis and potato leafhopper), the green cloverworm was negatively affected if tillage system is considered as a diversity factor but positively affected by intercropping; the potato leafhopper was negatively affected by cropping system and tillage system as criteria for diversity. The bean leaf beetle had no clear response, and the grape colaspis was more abundant in no- tillage and intercropping treatments. Apparently, herbivores followed the general pattern of increased numbers in diversified systems (Tables 8 and Rlsch et al. (1983) surveyed 150 published studies dealing with the
effects of agroecosystem diversification, comprising 198 herbivore
species. Of these, 53% had decreased numbers in diversified systems, 20%
showed a varied response, 18% had increased numbers, and 8% showed no
response. These results are often cited as evidence for the beneficial
effects of diversity, because of the 53:20:18:8 ratio of the species
responses. But the important question is, as asked by Risch and co
authors themselves, do diversified agroecosystems lower pest populations?
The answer was: yes, 53%, and no (or not necessarily), 47%: hardly an
evident trend. The resource concentration and enemies hypotheses (Root
1973) have received support from experimentation, but they offer only
tentative explanations for reduced herbivory on systems where there is such an effect due to diversification. The logical structure is not
"because heterogeneity reduces pests, there are two hypotheses to explain
it", but "if heterogeneity reduces pests, there are at least two hypotheses to explain it". The resource concentration has been the object of broad generalizations from theory without enough empirical support
(Kareiva 1983, Andow 1988), and despite their strengths, Root's hypotheses still have to be further elaborated. Some herbivorous species require separate areas for breeding and foraging (Wiklund 1977), which can be facilitated by diversification. Some oligophagous insects, being closely associated with their hosts, may be little affected by other plant species in the process of host location (Sheehan 1986, Lambert et al. 1987).
Specialist natural enemies may have reduced efficiency in host location in diverse systems (Sheehan 1986), and polycultures may reduce the chances of general predators encountering prey because of increased plant density 51
(Risch et a l . 1982). Andow (1983) suggested that host-finding ability and vagility are other major factors determining the response to diversity besides host range.
Even conceding that diversity may have adverse effects regarding pest populations and that more information is needed, some studies concentrate on describing and enumerating only the cases where diversity was beneficial. Perhaps this bias is due to the attractiveness of the diversity-stability theory, the potential agronomic, economical and social advantages of crop diversification (Francis 1989) , or the influence of
"stability" as consistency of production (Marten 1988), a characteristic often found in diversified systems (Vandermeer 1989). This partialism perhaps has restrained the publication of negative data, which has been mistakenly disregarded in ecology (Price et al. 1984). The practical result is that the general recommendation of diversity as a method to reduce pest populations in some systems may have an adverse effect, or at best may not work.
Price (1984a, p. 447) proposed the individualistic response hypothesis, in which "the community is an assemblage of species whose individuals react to resources in an idiosyncratic manner, largely independently of the other species present". This view is not new in the study of ecosystems, but it has not received enough consideration (Price
1984b). The complex interactions of several components in different environments do not allow the simplistic "diversity-pest reduction" formula to have strong predictable power. It is obvious that not every single system can be tested by experiments, but we need to increase the level of particularity in order to find biologically significant cause- 52
effect relationships. The dogma of diversity-stability-pest reduction
reflects in certain ways Clement's (1905) holistic and predictive view of communities, which strongly influenced ecological thought. His concepts were so appealing that it took more than 30 years for Gleason's challenge on Clement's ideas to be accepted. For Gleason (1939, p. 108), "since every community varies in structure, and since no two communities are precisely alike, or have genetic or dynamic connection, a precisely logical classification of communities is not possible". Gleason was referring to plant communities, but an extension can be made to insect communities. To deny any order or classification seems too extreme, but the point is that generalizations can be very misleading. 53
Table 4. Soybean fauna and sampling methods: 1- sweep net; 2- D-vac; 3- direct counts; 4- pitfall traps; 5- quadrat samples. (*) indicates that the taxon was too scarce to be analysed statistically. The dominant groups within a taxon are indicated by brackets
Common name taxon sampling method
Herbivores (defoliators)
Green cloverworm Plathvnena scabra (F.)
Bean leaf beetle Cerotoma trifurcata (Foster)
Japanese beetle Popillia japonica Newman
Grasshoppers Melanonlus spp.
[M. differentialis (Thomas)]
Grape colaspis Colaspis brunnea (F.) , 3
Striped flea beetles Phvllotreta spp. *,2, 3
Slugs Gastropoda , 5
Mexican bean beetle Epilachna varivestis Mulsant *
Velvetbean caterpillar Anticarsia gemmatalis Hiibner
Soybean looper Pseudoplusia includens (Walker)
Southern corn rootworm Diabrotica undecimpunctata Barber
Herbivores (sap feeders)
Potato leafhopper Empoasca fabae (Harris)
Tarnished plant bug Lvpus lineolaris (Palisot de Beauvois)
Stink bugs Pentatomidae f Euschistus servus (Say),
Acrosternum hilare (Say)]
Homoptera [Cicadellidae, Cercopidae] , 2, 4 54
Table 4 (continued)
Hemiptera [Miridae, Piesmatidae,
Berytidae, Thyreocoridae] 1, 2
Natural enemies (predators)
Nablds Nabis spp. [N. roselnennis Reuter] 1, 2
Anthocorids Orius spp. [0. Insidiosus (Say)] 1, 2
Lady beetles Coleomegllla spp.[C. maculata (DeGeer)] 1
Spiders (soil) [Lycosidae] 4, 5
Spiders (foliage) [Tetragnathidae, Salticidae, Thomisidae] 1, 2
Tiger beetles Cicindela punctulata Olivier 4
Rove beetles Staphylinidae 4, 5
Centipedes Chilopoda 4, 5
Big-eyed bugs Geocoris spp. 1*
Predaceous carabids Lebia spp., Leptotrachelus spp. 1*
Spined soldier bug Podisus maculiventris (Say) 1*
Assassin bugs Reduviidae 1*
Syrphid flies Syrphidae 1*
Lacewings Chrysopidae 1*
Natural enemies (parasitoids)
Hymenoptera (soil) [Scelionidae, Diapriidae, Chalcidoidea] 4
Hymenoptera (foliage) [Braconidae, Ichneumonidae] 1, 2
Tachinid flies Tachinidae 1*
Generalists
Phalangids (soil) Phalangidae 1
Phalangids (foliage) Phalangidae 4 55
Table 4 (continued)
Carabids Carabidae 4, 5
Ants Formicidae [Forraicinae, Myrmicinae] 4, 5
Millipedes Diplopoda 4, 5
Beetles Coleoptera [Scarabaeidae, Anthicidae,
Curculionidae, Tenebrionidae,
Chrysomelidae] 4, 5 56
Table 5. Responses of the soybean fauna (Table 4) to tillage and cropping systems. Significantly higher results based on analysis of variance (P < 0.05) for no-tillage (NT) or conventional tillage (CT), and
intercropping (IC) or monoculture (MC) are indicated by sampling method and year. (0) means no significant effect, and (I) indicates interaction effect. If the numbers were too low to be analyzed in a given year, that is denoted by (*), and if the taxon was not sampled, (-) was used.
Description of taxa and sampling methods are given in Table 4
Sampling TILLAGE SYSTEM CROPPING SYSTEM
Taxon method 1988 1989 1990 1988 1989 1990
Green cloverworm 1 0 0 CT 0 IC 0
2 0 0 - 0 0
Bean leaf beetle 1 NT CT 0 0 0 0
3 0 0 * MC 0 *
Japanese beetle 1 0 0 NT 0 0 IC
Grasshoppers 1 * 0 NT * 0 0
Grape colaspis 1 NT NT * 0 IC *
3 * NT * * IC * 57
Table 5 (continued)
Striped flea beetle 2 CT *
3 CT * * IC *
Slugs 4 NT NT NT 0 0
5 * NT NT 0 0
Potato leafhopper 1 CT 0 CT 0 0 MC
2 CT CT CT 0 MC MC
Tarnished plant bug 1 NT NT 0 0
2 NT NT 0 0
Homoptera 1 NT 0 0 0
2 NT 0 0 0
4 NT NT NT 0 0
Nabids 1 0 0 0 IC 0
2 0 0 IC 0
Anthocorids 1 I 0 CT I IC 0
2 0 CT 0 IC 0 0
Lady beetles 0 0 NT IC IC 0 58
Table 5 (continued)
Spiders (soil) 4 NT 0 NT 0 0 0
5 NT 0 NT 0 0 0
Spiders (foliage) 1 0 0 0 0 IC 0
2 0 0 IC IC
Tiger beetles 4 0 NT 0 0 0 0
Centipides 4 CT * CT 0*0
5 NT * * o * *
Hymenoptera (soil) 4 0 CT CT 0 0 0
Hymenoptera (foliage) 1 NT 0 0 0 IC 0
2 0 NT NT 0 IC IC
Phalangids (soil) 4 0 CT 0 0 0 0
Phalangids (foliage) 1 0 0 0 IC IC 0
Carabids 4 0 0 0 0 0 0
5 NT 0 0 0 0 0 59
Table 5 (continued)
Ants 4 NT NT NT 0 0 0
5 NT NT NT 0 0 0
Millipides 4 0 CT 0 0 0 0
5 NT NT * 0 0 *
Beetles 4 NT NT NT 0 0 0
5 NT NT NT 0 0 0 60
Table 6. Possible positive effects to the soybean fauna resulting from
tillage and intercropping practices, based on results from literature (*)
organism practice and possible factors reference (*)
Reduced or no-tillage
Bean leaf beetle soil moisture and temperature 8, 14
Japanese beetle alternative hosts (weeds) 9, 5
Grasshoppers crop residue and weed biomass 5, 13
Slugs crop residue and weed biomass 4
Lveus s p p . alternative hosts (weeds) 5
Homoptera broadleaf weeds 6
Nabis spp. grassy weeds 2, 12
Orius s p p . grassy weeds 2, 10, 12
Lady bugs weeds 12
Conventional tillage
Potato leafhopper reduced weed vegetation 1, 7
Intercropping
Green cloverworm narrow rows 9
Spiders narrow rows 11
Spiders, wasps windbreaks 10
Monoculture
Japanese beetle facilitation of dispersion 3
(*): 1 - Barney and Pass 1987; 2 - Barney et al. 1984; 3 - Bohlen and
Barrett 1990; 4 - Hammond 1987; 5 - Hammond and Stinner 1987; 6 - Kemp and 61
Table 6 (continued)
Barrett 1989; 7 - Lamp et al. 1984a; 8 - Marrone and Stinner 1983; 9 -
Mayse 1978; 10 - Mayse and Price 1978; 11 - McPherson et al. 1982; 12 -
Shelton and Edwards 1983; 13 - Sloderbeck and Edwards 1979; 14 - Troxclair and Boethel 1984. 62
Table 7. Most abundant weeds, classified by the Braun-Blanquet scale:
1 - abundant and with very low cover, or less abundant with high cover, but always less than 5% of total area; 2 - very abundant and less than 5% cover, or 5-25% cover; 3 - 25-50% cover; 4 - 50-75% cover
No-tillage
weed species 1988 1989 1990
Canada thistle, Cirsium arvense (L.) Scop. 4 3 4 commom dandelion, Taraxacum officinale Weber 1 1 4 common lambsquarters, Chenopodium album L. 3 2 2 fall panicum, Panicum dichotomiflorum Michx. 2 2 3
Pennsylvania smartweed, Polygonum pensvlvanicum L. 3 2 2 pigweeds, Amaranthus spp. 3 2 2 quackgrass, Agropvron repens (L.) Beauv. 2 3 4 yellow foxtail Setaria lutescens (Weigel) Hubb. 2 2 3
Conventional tillage
Canada thistle, Cirsium arvense (L.) Scop. 3 2 commom dandelion, Taraxacum officinale Weber 1 1 common lambsquarters, Chenopodium album L. 1 1 fall panicum, Panicum dichotomiflorum Michx. 1 3
Pennsylvania smartweed, Polygonum pensvlvanicum L. 2 1 pigweeds, Amaranthus spp. 2 2 2 quackgrass, Agropvron repens (L.) Beauv. 2 2 3 yellow foxtail Setaria lutescens (Weigel) Hubb. 2 1 2 63
Table 8. Summary of trends for diversity factors (no-tillage and
intercropping) for 17 taxa from the foliage fauna (Table 4), based on analysis of variance
natural
effect herbivores enemies generalists total
increased 5 2 0 7 no-tillage decreased 3 1 0 4
uncertain 3 2 1 6
increased 4 5 1 10 intercropping decreased 1 0 0 1
uncertain 6 0 0 6 64
Table 9. Summary of trends for diversity factors (no-tillage and intercropping) for 11 taxa from the soil fauna (Table 4) , based on analysis of variance
natural
effect herbivores enemies generalists total
increased 1 2 3 6 no-tillage decreased 0 2 2 4
uncertain 0 1 0 1
increased 0 0 0 0 intercropping decreased 0 0 0 0
uncertain 1 5 5 11 Fig. 7. Densities of the green cloveworm measured by sweep net samples for each treatment: no-tillage, monoculture (----); conventional tillage, monoculture(--- ); no-tillage, intercropping (----- ); conventional tillage, intercropping (.... ). Vertical lines are standard errors.
65 O' © o m 8 M O I* 8 »• m 8 s m * O M •» S 8 f*
JULIAN DATE 2 2 MEAN NUMBER PER SAMPLE OQ Fig. 8. Densities of the green cloverworm (----) and anthocorid bugs
(----) measured by sweep net samples. Vertical lines are standard errors.
67 n O 00 o o to m s I* o o M to to m O o s S W M m MEAN NUMBER PER SAMPLE O to s w M
JULIAN DATE 00 00 Fig. 9. Densities of the bean leaf beetle measured by sweep net samples for each treatment: no-tillage, monoculture ( ); conventional tillage, monoculture( ); no-tillage, intercropping (----- ); conventional tillage, intercropping (.... ). Vertical lines are standard errors.
69 O < i m < m e o m m x m m MEAN NUMBER PER SAMPLE
JULIAN DATE H* OQ Fig. 10. Densities of the Japanese beetle measured by sweep net samples for each treatment: no-tillage, monoculture ( ); conventional tillage, monoculture( ); no-tillage, intercropping (----- ); conventional tillage,
intercropping (.... ). Vertical lines are standard errors.
71
NJ 0*1 o m s o o m o 10 w m
JULIAN DATE 2 2 MEAN NUMBER PER SAMPLE OQ Fig. 11. Densities of the potato leafhopper measured by D-vac samples for each treatment: no-tillage, monoculture ( ); conventional tillage, monoculture( ); no-tillage, intercropping (----- ); conventional tillage, intercropping (.... ). Vertical lines are standard errors.
73 O it M to O o MEAN NUMBER PER SAMPLE « to m o M o o to «*
JULIAN DATE H- OQ Fig. 12. Mean soybean yield for each of the four treatments: NT-MC - no-tillage, monoculture; CT-MC - conventional tillage, monoculture; NT-IC
- no-tillage, intercropping; CT-IC - conventional tillage, intercropping.
Vertical lines are standard errors.
75 76
kg/ha 1988 4400
•400
CT CT •400 NT NT 140 0 MC 1C
kg/ha 1989
4400 CT
NT •400 CT NT <400
1400 MC IC
kg/ha 1990
4400
•400 CT NT NT <400 CT
1400 MC IC
Fig. 12 CHAPTER III
Diversity Analysis of a Carabid Beetle
Assemblage under Diversified Agroecosystems
Introduction
Despite a "c’iversity" of interpretations (Hurlbert 1971) , the concept
of community diversity is generally accepted as a combination of species number (richness) and their relative abundance (evenness), and diversity
indices attempt to express both measures in a single value (Pielou 1977).
However, reviews and discussions of diversity indices (Whittaker 1972,
Peet 1974, Southwood 1978) suggest that these statistics are of limited value in describing communities, mainly because of intrinsic characteristics such as dependence on sample size (Peet 1975) and species distribution (May 1975) or bias towards rare or abundant species
(Whittaker 1972). Even disregarding these disadvantages, the question of biological significance remains: the expression of a subjective concept such as diversity into a single variable may be misleading, and it is not a substitute for a fuller description of the community (May 1981, Wolda
1983).
The distribution of relative abundance of species in most large communities is accounted for by a few dominant and rare species, with the majority of species being of intermediate abundance. However, assemblages with a small number of species in early successional stages or in polluted
77 78
environments have a much larger fraction of dominant species (May 1981).
In these communities, estimating the relative abundance and understanding
the role of individual species could be more useful than determining presence or abundance of rare species with small contribution to ecological processes. If the species assemblage is to be considered as a unit, the components of diversity (richness and evenness) can be analyzed independently, as done by Sanders (1968) and Wolda (1983). These individual measures were used here and compared to diversity indices in the analysis of a carabid beetle assemblage collected in pitfall traps from agricultural fields. Data from similar studies (Esau and Peters
1975, Hsin et al. 1979, Dritschilo and Wanner 1980, Barney et al. 1984,
Whitford and Showers 1987) indicated that a "typical" carabid community has approximately four species comprising 80% of the total number of individuals, a degree of dominance suggesting a community in early successional stage.
Diversity of insect populations has been correlated with heterogeneity of the environment and plant species richness and attributed to increased number of ecological niches (Murdoch et al. 1972) ("plant diversity" and
"insect diversity" are commonly used as expressions of number of species; for the sake of consistency, "diversity" here will be used only to express the combination of richness and evenness). In agriculture, plant species and structural richness are increased by polyculture (more than one crop grown simultaneously in the same area [Kass 1978]) and by reduced tillage operations. Both practices were used here to observe the impact of habitat structure and plant species richness on carabid beetles, a group of insects frequently used for measuring intrinsic habitat characteristics 79
(Dritschilo and Erwin 1982).
Materials and Methods
Sampling. Carabid beetles were collected for 48-h at each sampling date by two pitfall traps per plot (one trap for each crop in the strip- intercropping plots). Traps consisted of plastic cups (11 cm diameter, 8 cm high) filled with about 100 ml of a 1:1 water and ethylene glycol mixture. The epigeal fauna was sampled seven times each season (June through September) at approximately two-week intervals. Adult carabids were sorted from the samples, pooled for each plot and stored in alcohol for later identification. Identifications were done to species level, with the exceptions of Amara spp. and Tachvs spp.(sensu lato).
Conclusions were based on the assumption that sampling accurately measured population parameters (abundance and richness), although a relative underestimation could be expected for no-tillage plots because of greater levels of ground cover (Greenslade 1964). Nevertheless, pitfall traps are suitable for estimating activity level, and this could be more important than actual population density when considering resource utilization (Lenski 1982). Furthermore, pitfall traps have been the standard method for analyzing carabid populations, allowing comparisons between studies. Quadrat samples were tried as an alternative method (see
Chapter II), but it resulted in few species collected, certainly reflecting the nocturnal habit of most carabids.
Analyses. The number of individuals (N) and number of species (S) collected over each season were used to calculate diversity by Shannon-
Weaner and Simpson indices, a index of Fisher et al. (1943), and Berger 80
and Parker's (1970) dominance index. All formulae followed Southwood's
(1978) notation, with the Simpson index used in the 1 - D form. I chose
these indices because Shannon-Weaner (HI) and Simpson (D) are the most
frequently used, the dominance index (d) of Berger and Parker is regarded by May (1975, 1981) as the best option among the available indices, and
the a index of Fisher and collaborators is considered by Southwood (1978)
to be the most appropriate choice for describing most communities. The
results of N, S., and diversity indices for each year were analyzed by analysis of variance (ANOVA). When the cropping system factor or
interaction (cropping system x tillage system) was considered statistically significant (P < 0.05), means for each cropping system or each treatment were separated by the Least Significant Difference test
(LSD). Values of a are generally normally distributed (Taylor et al.
1976), as well as repeated measures of (Magurran 1988). However, examination of the data suggested that, with the exception of N, all parameters fitted a Poisson distribution. Therefore, ANOVA of S, HJ_, D, d and a were performed on raw data, and acceptance or rejection of the null hypothesis (£ < 0.05) was confirmed by ANOVA on transformed data
(,/x±0.5). The values of N were analyzed after a log (x+1) transformation. Analyses of variance were performed for species with at least 30 individuals accumulated over the season, a restriction intended to reduce the risk of false conclusions based on rare species which are particularly subject to random effects of sampling. Occurrence of zeros in all replications of a given treatment, a situation occasionally present, would limit the efficacy of ANOVA despite the transformations.
Thus, the data were also analyzed by Wilcoxon matched-pair signed-rank 81
(WMS) test (Daniel 1978), with data paired by tillage factors (which had
greater effect on carabid species than cropping systems) and using
sampling dates as replicates. Therefore, we assumed independence of
successive samples for the non-parametric test, based on the high mobility
of carabids and the two-week interval between samples. We evaluated the
similarity between treatments regarding carabid species composition by a
cluster analysis, using the single linkage method (Wilkinson 1989, p.
343). Additionally, species evenness was analyzed by Sander's (1968) method of plotting relative richness against relative abundance.
Results
A total of 4,678 carabids from 36 species were collected in three years (Table 10). As there were no significant treatment differences in
total numbers captured in any year, carabid beetles as a group were considered equally distributed across treatments. Twenty-one species
(58.3%) were collected in all three years; however, if those species with no more than six individuals (average of 1 /treatment) at any given year are considered rare and excluded from the analysis, the species overlap for the three years increase to 86.9%. There were seven dominant species in 1988, comprising 79.7% of all carabids, five dominant species in 1989
(78.6% of the total), and six dominant species in 1990 (80.1%, although
Amara spp. comprised more than one species). "Dominant species" were arbitrarily established as the number of species that made approximately
80% of the collection. Figure 13 suggests similarity of species composition for the three years, although the volume of rainfall differed greatly (see Chapter II) . Some of the dominant species are also common in 82 other Midwest states (Dritschilo and Wanner 1980, Best et al. 1981), an indication of similarity on a larger geographic scale. No species fluctuated greatly in numbers from year to year: among the dominant species, Abacldus permundus (Say) varied most, with an approximate tenfold reduction in numbers from 1988 to 1989. These results suggest that there was spatial and temporal homogeneity in the carabid community in the area studied.
However, a different picture emerges from rank correlation analysis, one of the methods for studying community similarity (e.g. Grossman 1982).
Spearman's correlation analyses of abundance of the dominant species
(Table 11) for each year suggest that assemblages between treatments generally were not similar as evidenced by the absence of significant correlations in most cases (the drawbacks of multiple comparisons were not considered), although the statistical value of rank correlations should be viewed with caution (Jumars 1980). The variation in ranks may be attributed in part to random effects of sampling, but there were distinct treatment differences for individual species. All six dominant species responded to tillage effect in at least one year (Tables 12, 13 and 14).
Scarites substriatus Haldeman and Pterostichus chalcites Say were captured in higher numbers in conventional tillage plots, reflecting actual habitat preference at least for P. chalcites, which was observed several times entering holes and crevices on the bare soil of conventional tillage treatments, whereas most of the remaining dominant species were found on patches of weeds or debris. Among the less common species, Aponuro cupripenne (Say) was more numerous in no-tillage plots in 1988 (F - 8 .8 6 ,
P — 0.007), and Anisodactvlus sanctaecrucis F. was mere abundant in no- 83
tillage plots in 1990 (F — 7.62, £ - 0.01). There was not total agreement
on the results of ANOVA and WMS tests. The non-parametric test is
basically a measure of consistency of trend; a significant value for no
tillage, for example, indicates that this treatment consistently yielded
higher numbers throughout the season, despite not being significantly
different from conventional tillage treatments when tested by ANOVA.
Carabid counts showed high variability, possibly a consequence of their
aggregated distribution (Best et al. 1981), which may have contributed to
the lack of significance in some of the ANOVA. Considering the cropping
system factor, P. chalcites was always more abundant in soybean plots, with significant results in 1988 and 1989 (Table 15). Tachvs spp. was more abundant in corn plots than soybean or intercropping plots in 1988 (F
- 13.20, JP - 0.008) as well as Cvclotrachelus sodalis (LeConte) in 1990
(Table 4). Amara spp., Bembidion quadrimaculatum (L.), Agonum placidum
(Say), Stenolophus comma F. , Bembidicn rapidum LeConte, and Harpalus affinis Schrank were trapped in sufficient numbers to be analyzed in one or more years (Table 10), but there were no significant results for tillage or crop treatments.
Despite no statistical differences in total number of species, a curve of number of species accumulated over number of individuals, resembling a
"species-area" curve (Fig. 14), suggested that no-tillage had a greater richness than conventional tillage in all three years. The analysis of species evenness showed reduced equitability for soybean treatments when compared to the other cropping systems in 1988, and for soybean and intercropping treatments when compared to corn in 1990; no notable differences were found in 1989 (Fig. 15). Greater convexity of the 84
curves, departing from the complete evenness line, indicates lower
equitability (curves drawn for the tillage factors exhibited similar shape
between treatments for all three years). The reduced evenness on soybean
and intercropping plots can be attributed mostly to the dominance level of
P. chalcites in soybean/ conventional tillage in 1988 and in soybean and
intercropping/conventional tillage in 1990 (Fig. 16). Cluster analysis
revealed a higher dissimilarity of soybean/conventional tillage and to a
lesser extent intercropping/conventional tillage from the other treatments
for the three years' results (Fig. 17).
The richer fauna in no-tillage plots should result from a more complex
habitat, which is in accordance with some other studies (Liss et al.
1986). However, only H_j_ indicated lower diversity for the conventional
tillage factor in 1988, although d and D detected an interaction effect
between tillage and cropping system effects, with lower carabid diversity
in soybean-conventional tillage plots. (Table 16). There were no
significant results for any diversity index in 1989 (Table 17). In 1990,
D and d did not detect treatment differences, but H and a indicated lower
carabid diversity in soybean and intercropping plots (Table 18) . The rank
of species abundance indicated that this carabid assemblage could be
described by a geometrical or a log series distribution, for which the a
index should be the most suitable measure of diversity (Fisher et al.
1943). However, the values of a were strongly correlated with richness, hence unfit to describe a richness-evenness balance. This could be a
result of the relatively small sample size, because a is appropriate only
for large samples (Taylor et a l . 1976, Pielou 1977). The plot of a as a
function of N and S from Fisher et al. (1943, Table 8 ) shows that for the 85
range of S (8-17) and N (21-117) used in the analysis, a is strongly
dependent on S.
Discussion
The resulting lack of statistical significance of treatment effects on
carabids as a group differs from other studies reporting greater abundance
of carabid individuals and species in reduced tillage systems (reviewed in
Stinner and House 1990). Some of the most abundant species found in this
study may travel several meters a day (Best et al. 1981), so dispersal may
account for homogeneity of treatments, suggesting that plots did not reach
the "patch size threshold" (Kareiva 1985). Nonetheless, there were
significant differences at the species level, particularly between tillage
treatments. Stinner et al. (1984) proposed that tillage practices affect
arthropods indirectly, especially through their influence on the weed
population. Fields of reduced tillage have more weeds, a situation
favorable to Harpalus pensvlvanicus DeGeer (Hsin et al. 1979, Whitford and
Showers 1987), the most common species in this study. On the other hand, plots under conventional tillage may have created the open-field environment preferred by P. chalcites (Esau and Peters 1975, Best et al.
1981). The responses of P. chalcites. C. sodalis and Tachvs spp. to crops were not expected, and no correlate with these preferences was found.
Carabids are not considered to be host-plant specific (but see Hemenway and Whitcomb 1967), and their distribution patterns are responses to physical (Thiele 1977) and chemical (Evans 1982) stimuli. The specific responses to those stimuli probably resulted in microhabitat selection within the experimental area. Levins and Wilson (1980) suggested that the 86 mosaic of microhabitats within the apparently homogeneous agricultural field is one possible reason for species coexistence and reduced competition.
Carabids as a group have been frequently considered predators, and conclusions about their possible impact as natural enemies have been drawn based on this assumption. But carabids have a wide range of food items, and their grouping in the predatory guild (sensu Root 1973) is an oversimplification; the term "predaceous carabids" is a misnomer (Erwin
1973), and "omnivorous carabids" would be a more realistic description
(Lindroth 1961-1969, Davies 1953, Johnson and Cameron 1969, Kirk 1982).
Some species are considered agricultural pests, such as Stenolophus lecontei Chaudoir (the seedcorn beetle) and Clivina impressifrons LeConte, and even among the possible predators, there are particularities to be considered: B. auadrimaculatum. for example, may feed on eggs of agricultural pests (Lund and Turpin 1977, Kirk 1982), but some species of the genus Tachvs are possible predators of Staphylinid beetles (Thiele
1977), a group considered beneficial because of several predaceous species. Three of the most abundant species in our study, H. pensvlvanicus. P. chalcites and S. substriatus. had their food preferences scrutinized by Best and Beegle (1977), who concluded that the beetles are opportunistic feeders. However, the results of their food preference tests indicated that "scavengers" might be a better definition, the same term used by Dawson (1965) when studying feeding habits of another eight carabid species. Other studies suggested that from the six dominant species, H. pensvlvanicus is primarily a seed eater with little potential as a predator, while P. chalcites and C. sodalis probably have the greatest predatory capability (Blatchley 1910, Lindroth 1961-1969, Johnson
and Cameron 1969, Best and Beegle 1977, Lund and Turpin 1977). As
soybean/conventional tillage and intercropping/conventional tillage were
mostly dominated by P. chalcites. and both treatments comprised a somewhat
distinct cluster of species, the ecological implications of carabid
communities on these treatments can be very different from the remaining
treatments. Price (1984) pointed out the importance of knowing the
resources utilized by species in the study of communities, a matter
particularly relevant when potential agents of biological control are
involved. Patterns of resource utilization are not necessarily
taxonomically related, a factor that led Jaksic (1981) and Hawkins and
MacMahon (1989) to question the significance of guild analyses based on
taxocenes. Jaksic (1981) suggested that "community" should be reserved to
describe assemblages of interacting species only, regardless of their
taxonomic affinity. Within the perspective of resource utilization,
"carabid community" is an artificial classification, and measurements of
diversity may have little significance.
Grossman (1982) and Grossman et al. (1982) suggested that some
communities may be organized randomly, with presence and abundance of
species being a function of environmental conditions and mostly
independent of other species; such a model allows little prediction of community structure. This view of "stochastic communities" (Grossman
1982) with low degree of predictability is a development of Gleason's
(1939) and Andrewartha and Birch's (1954) concepts of individualistic, density-independent communities, which have received increased attention from insect ecologists (Price 1983, Strong et al. 1984, Liss et a l . 1986). 88
Carabids in particular are believed to be affected mostly by density
independent factors (Thiele 1977, den Boer 1980; but see Lenski 1982), and some circumstantial evidence supports the view that density dependent factors such as competition are not prevalent. Kirk (1982) noted several species sharing the same refuge in the soil, and I observed different species scavenging the same prey at the same time in the field.
The results of diversity indices indicated higher sensitivity to differences in evenness than to differences in richness and strong dependance on the abundance of a single species. If carabids are typically represented by a few highly dominant species subject to independent seasonal variability, giving the community a different configuration each year, richness and evenness (and therefore diversity) have a strong random component. Root (1973) considered unrealistic the characterization of communities based on richness and evenness because of species' independent response to weather. Even considering that fluctuation in numbers reflects normal variability, i.e., communities are predictable (Lawton and Gaston 1989), diversity indices are bound to reflect a temporary condition, as few studies describe diversity patterns over a long period of time. The dependence of the diversity indices considered here to the abundance of the dominant species is exemplified in
Table 19. Community 2 has lower diversity (except by o) than community 1 despite ten more species (c.a. 4% more individuals), consequence of a more even distribution of the dominant species in community 1. Furthermore, these indices may lead to conclusions that are in disagreement with evidence from other parameters sometimes much more sound. Dritschilo and
Erwin (1982) applied different indices to two independent sets of data on 89
carabid communities, and they concluded that the indices failed to detect
differences among treatments, even when number of species and abundance
combined indicated otherwise. The primary empirical use of diversity
indices has been as environmental indicators, such as assessment of water
quality (Magurran 1988). Even for that objective, some authors question
the utility of diversity indices and suggest that species distribution,
richness and simple measures of dominance provide most of the necessary
information (Magurran 1988 and references cited herein). In systems where
few species are strongly dominant such as carabids, Collembola (Vegter et
al. 1988), and spiders (Agnew and Smith 1989), the analysis of individual
species abundance and their ecological roles and requirements is more
important than values of diversity indices.
Nonetheless, it would be reasonable to consider a community to have
greater diversity if it has more species, regardless of their relative
abundances. Species number has an intuitive priority in the consideration
of diversity; we call a tropical forest "more diverse" than a temperate
forest because the first has more species, no matter how they are
distributed. Following this intuitive line, one could argue that the
question of "are there any" precedes "how many". Number of species
reflects two important ecological features: genetic singularity and
habitat structure. Richness is the most sound expression of genetic
diversity because it quantifies the biological unit, the species. Also,
the presence of a given species indicates that there is a portion of the
environment reserved for it, under Gause's (1934) and Hutchinson's (1957) principles of niche exclusion. A community with ten species where a
dominant one comprises 90% of the total number of individuals still has a 90
greater number of niches than a community with nine species equally
distributed. Hill (1973) argued that richness is strongly affected by
rare species, but these are the ones that contribute most to community
diversity (Whittaker 1965). The use of richness as a measure of diversity provides direct information and is considered by some to be the most
appropriate measure of community structure (Peet 1974, Whittaker 1972, May
1981). However, richness depends on sample size and is also a function of evenness: the less evenly distributed the species are, the greater sample sizes are required to reveal rare species (Peet 1974, Whittaker 1972).
The usual analysis of carabid communities, done by simultaneous and equal samples (normally number of pitfall traps) of different habitats or treatments and repeated over a period of time reduces the error in estimating richness. Spatial and temporal replication reduces the probability of rare or aggregated species being undetected, but there is always the possibility of missing rare species or counting transient ones.
For example, I collected one Galerita 1 anus F. individual, which is a forest species usually not found in agricultural fields (F. F. Purrington, personal communication). Nonetheless, even if species numbers cannot be precisely determined, it can be useful for comparative analyses.
Understanding community organization requires primarily an explanation of genetic variability (in ecological or evolutionary terms) and resource partitioning. Therefore, models and theories of community diversity are clearly or implicitly concerned with species richness, even when "species diversity" is used (e.g. MacArthur and Wilson 1967, Connell 1978, Strong et al. 1984), and for some, richness is diversity (Berger and Parker 1970,
Hurlbert 1971). Loehle (1988) recognized the importance and lack of 91 precise terminology in ecology, and pointed out that much debate occurs
over matters that do not have precise definitions, such as niche,
stability, and diversity. The use of "diversity" (accepting the general concept) when "richness" is meant results in improper inferences about both richness and evenness. Therefore, when the richer tropical forest
is referred to as more diverse, it is as though there is a suggestion that some density dependent factor such as predation or competition is acting upon species evenness (of course the actual or assumed role of predation or competition is irrelevant for the argument). In order to avoid the already confusing ecological terminology, the more precise (or less ambiguous) term "richness" should be used, although under the assumption that it is the major determinant of diversity.
Concluding, I suggest that the search for "community structure" through diversity indices has little use because these statistics solely express a momentary mathematical combination of the number of species present in the sample and their relative proportion. Resource utilization, temporal and spatial distributions, interactions, and separate characteristics of dominance and richness are more meaningful aspects of a species assemblage. If a single value must be used to describe it, the number of species is the most appropriate. 92
Table 10. Carabid species collected by pitfall traps each year, total numbers, percentage and accumulated percentage (%ACC.) of the dominant species. (*) indicates values lower than 0 .1 %
Species 1988 1989 1990 TOTAL%%ACC.
Harnalus Densvlvanicus DeGeer 341 198 340 897 19.1 19.1
Cvclotrachelus sodalis (LeConte) 171 332 258 761 16.2 35.3
Pterostichus chalcites Sav 2 2 1 125 372 718 15.3 50.6
Chlaenius tricolor Dejean 157 257 171 585 12.5 63.1
Abacidus permundus (Sav) 251 29 104 384 8 . 2 71.3
Scarites substriatus Haldeman 97 72 47 216 4.6 75.9
Amara spp. 34 40 105 179 3.8 79.7
Bembidion auadrimaculatum (L.) 127 26 18 171 3.6
Aeonum placidum (Sav) 17 94 36 147 3.1
Anisodactvlus sanctaecrucis F. 53 15 30 98 2 . 1
Tachvs s d d . (sensu lato) 53 14 27 94 2 . 0
Aeonum cuoripenne (Sav) 34 1 2 2 2 6 8 1.4
Bembidion rapidum LeConte 30 6 27 63 1.3
StenoloDhus comma F. 34 5 14 53 1 . 1
Harpalus affinis Schrank 7 6 38 51 1 . 1
Dvschirius elobulosus Sav 27 7 11 45 0.9
Pterostichus lucublandus Sav 17 6 12 35 0.7
Colliurus oensvlvanica (L.) 15 6 6 27 0 . 6
Haroalus herbivagus Sav 2 3 2 0 25 0.5
Bembidion versicolor (LeConte) 2 19 0 2 1 0.4 93
Table 10 (continued)
Clivina impressifrons LeConte 7 4 5 16 0.3
Bradycellus rupestris Say 7 0 2 9 0 . 2 o Clivina bipustulata (F.) 3 1 4 8 ro
Agonum affine Kirby 0 1 6 7 0 . 1
Harpalus fulgens Csiki 2 0 2 4 *
Patrobus longicornis Say 2 0 0 2 *
Acupalpus partiarius (Say) 0 0 2 2 *
Stenolophus ochropezus Say 0 0 2 2 *
Badister notatus Haldeman 1 0 0 1 *
Acupalpus pauperculus (Dejean) 0 1 0 1 *
Galerita janus F. 0 1 0 1 *
Stenolophus rotundicollis Haldeman 0 0 1 1 *
Microlestes brevilobus Lindroth 0 0 1 1 *
Amphasis sericea (Harris) 0 0 1 1 *
Pterostichus mutus Say 0 0 1 1 *
Harpalus caliginosus (F.) 0 0 1 1 * 94
Table 11. Spearman's rank correlations between treatments for the dominant species (80% of total catch) and probability levels (P)
Treatments 1988 P 1989 P 1990 P
corn/soybean 0.214 NS 0.600 NS 0.771 * corn/intercropping 0.536 NS 0.900 * 0.657 NS soybean/intercropping 0.857 * 0.500 NS 0.943 * conventional/no-tillage 0.357 NS 0.700 NS 0.084 NS
(n - 7) (n - 5) (n - 6 )
* - P < 0.05; NS - not significant, P > 0.05. 95
Table 12. Means and standard deviations of the dominant species showing
response to the tillage factor (NT: no-tillage, CT: conventional till,age)
in 1988, and probability levels for analyses of variance (ANOVA) and
Wilcoxon matched-pair signed-rank test (WMS). There were no significant
interactions
Species: X H. pensvlvanicus NT: 15.5 (4.9) 0.1 > 0 . 0 5 CT: 12.9 (5.1) C . sodalis NT: 9.1 (4.0) 0.003** 0.03* CT: 5.2 (2.9) C. tricolor NT: 8 . 8 (3.8) 0.008** 0 .01* CT: 4.2 (3.3) P. chalcites NT: 7.1 (7.6) 0.08 0.03* CT: 11.3 (12.7) A. permundus NT: 12.3 (3.8) 0.04* > 0.05 CT: 8 . 6 (4.2) S . substriatus NT: 2.6 (1.9) 0.04* 0.05* CT: 5.5 (2.9) Table 13. Means and standard deviations of the dominant species showing response to the tillage factor (NT: no-tillage, CT: conventional tillage) in 1989, and probability levels for analyses of variance (ANOVA) and Wilcoxon matched-pair signed-rank test (WMS). There were no significant interactions Species: X (SD) ANOVA WMS H. nensvlvanicus NT: 10.5 (3.9) 0.003** 0.03* CT: 6 . 0 (3.5) C. sodalis NT: 15.2 (9.5) 0.5 0.04* CT: 1 2 . 2 (6 .2 ) C. tricolor NT: 1 2 . 6 (5.6) 0.07 0.05* CT: 8 . 8 (6 .1 ) P. chalcites NT: 2 . 1 (3.0) 0 .0 1 * > 0 . 0 5 CT: 8.3 (9.7) A . permundus NT: 1.7 (1.3) 0.05* 0.03* CT: 0.7 (0.5) S. substriatus NT: 2.3 (1.5) 0 . 1 0.04* CT: 5.5 (2.9) Table 14. Means and standard deviations of the dominant species showing response to the tillage factor (NT: no-tillage, CT: conventional tillage) in 1990, and probability levels for analyses of variance (ANOVA) and Wilcoxon matched-pair signed-rank test (WMS). There were noi significant interactions Species: X (SD) ANOVA WMS H. nensvlvanicus NT: 13.7 (5.0) 0 . 6 > 0.05 CT: 14.5 (5.4) C. sodalis NT: 13.2 (5.6) 0.006** > 0.05 CT: 8.3 (5.0) C. tricolor NT: 7.9 (3.6) 0 . 2 > 0.05 CT: 6.3 (5.8) P. chalcites NT: 3.5 (5.2) 0 .0 0 2 ** 0.03* CT: 27.5 (34.2) A. nermundus NT: 4.9 (3.7) 0 . 6 > 0.05 CT: 3.7 (2.3) S. substriatus NT: 1.3 (1.4) 0 .0 1 ** 0.05 CT: 5.5 (2.9) 98 Table 15. Means and standard deviations of the two dominant species showing response to cropping system (C: corn, S: soybean, I: intercropping), and probability levels of the analysis of variance (ANOVA) . Means separated by the LSD test P. chalcites C. sodalis X (SD) ANOVA X (SD) ANOVA C: 3.7 (3.5) b C: 7.7 (2 .6 ) a 1988 S: 16.6 (14.7) a 0.007** S: 7.0 (5.3) a NS I: 7.2 (5.6) ab I: 6 . 6 (4.1) a C: 3.2 (5.6) b C: 14.9 (1 0 .6 ) a 1989 S: 9.0 (9.9) a 0.04* S: 9.9 (5.8) a NS I: 3.4 (6.4) b I: 14.0 (7.4) a C: 5.4 (6 .6 ) a C: 7.2 (5.2) a 1990 S: 23.5 (29.4) a NS S: 13.5 (5.1) a 0.009** I: 17.6 (35.8) a I: 11.5 (5.6) a Table 16. 1988 means and standard deviations for diversity indices (N - number of individuals; S - number os species; H *- Shannon-Weaner; D - Simpson; d - Berger and Parker; a - Fisher et al.) for each treatment (C - corn, S - soybean, I - intercropping, NT - no-tillage, CT - conventional tillage). (*) indicates significant higher means for the tillage factor; letters indicate means separated by the LSD test for when cropping system or interaction were significant. N S Hl(1) D<2 > d<3> a C-NT 69.2 (11.2) 13.2 (0.9) 2 . 2 0 (0 .2 2 ) * 0.86 (0.03) b 0.23 (0.04) b 4.80 (0.92) C-CT 74.0 (17.0) 14.7 (2.2) 2.29 (0.24) 0.86 (0.04) b 0.24 (0.10) b 5.27 (0 .8 8 ) S-NT 85.5 (23.4) 14.2 (2.6) 2.17 (0.20) * 0.85 (0.03) b 0.23 (0.06) b 4.95 (0.84) S-CT 65.2 (23.2) 1 1 . 0 (2 .2 ) 1.82 (0.79) 0.77 (0.26) a 0.40 (0.05) a 3.95 (1 .0 0 ) I-NT 75.7 (16.9) 14.2 (2.1) 2.31 (0.24) * 0.86 (0.03) b 0.24 (0.05) b 5.32 (0.97) I-CT 59.7 (1.9) 12.2 (1.3) 2.16 (0.09) 0 . 8 6 (0 .0 2 ) b 0.21 (0.03) b 4.70 (0.69) tillage; F - 4.48, P - 0.03. interaction; F - 5.67, P - 0.01. interaction; F - 5.80, P - 0.01. vo VO Table 17. 1989 means and standard deviations for diversity indices. See Table 16 for details. NS HI D d a C-NT 66.0 (21.9) 11.7 (2.4) 1.93 (0.37) 0.80 (0.07) 0.33 (0.12) 4.22 (0.85) C-CT 51.2 (9.7) 1 0 . 0 (0 .0 ) 1.83 (0.08) 0.78 (0.03) 0.36 (0.08) 3.92 (0.55) S-NT 51.2 (8.5) 1 1 . 0 (1 .6 ) 1.97 (0.25) 0.80 (0.05) 0.32 (0.99) 4.77 (1.43) S-CT 58.5 (10.3) 11.7 (1.2) 1.98 (0.19) 0.81 (0.05) 0.31 (0.08) 4.52 (0.81) I-NT 53.2 (11.3) 10.5 (1.3) 1.85 (0.14) 0.79 (0.03) 0.33 (0.05) 4.02 (1.05) I-CT 39.7 (12.7) 9.2 (0.9) 1.79 (0.09) 0.77 (0.03) 0.40 (0.04) 4.00 (0.66) 100 Table 18. 1990 means and standard deviations for diversity indices. See Table 16 for details. N S Hl<1> D d «<2 > C-NT 56.2 (10.7) 14.2 (0.9) 2 . 2 0 (0.18) a 0.85 (0.04) 0.28 (0 .1 2 ) 6.37 (1.42) a C-CT 56.0 (17.5) 14.5 (1.9) 2.30 (0.15) a 0.86 (0.04) 0.24 (0.08) 6.85 (2.51) a S-NT 71.5 (19.7) 14.5 (1.9) 2 . 2 2 (0 .1 1 ) b 0 . 8 6 (0 .0 2 ) 0.23 (0.06) 5.60 (0.99) b S-CT 96.2 (41.4) 13.0 (1.8) 1.78 (0.32) b 0.75 (0.10) 0.40 (0.15) 4.30 (0.90) b I-NT 52.2 (22.4) 11.7 (1.5) 1.96 (0.11) b 0.82 (0 .0 2 ) 0.28 (0.04) 4.62 (0.36) b I-CT 84.5 (59.3) 12.5 (2.4) 1.98 (0.37) b 0.79 (0.11) 0.33 (0.20) 4.92 (1.91) b (1): cropping system; F - 3.67, P - 0.05. *2} cropping system; F - 3.50, P - 0.05. 102 Table 19. Results of diversity indices for two hypothetical communities given the numbers of the four dominant species (A, B, C, and D) , which make about 80% of the community. S is the total number of species, and N is the total number of individuals. community 1 community 2 (S -50, N - 5,000) (S - 60, N - 5,210) sp. numbers sp. numbers A 1,500 HI- 2.27 A 2,500 HJ_- 2.24 B 1,500 D - 0.80 B 700 D - 0.73 C 500 d - 0.30 C 700 d - 0.48 D 500 a - 7.7 D 100 a - 9.5 HShannon-Weaner, D - Simpson, d - Berger and Parker, and a - Fisher et al. Fig. 13. Relative number (%) of the dominant species for three years. H.pen - Harpalus pensvlvanicus: C.sod - Cvclotrachelus sodalis; P.cha - Pterostichus chalcites: C.tri - Chlaenius tricolor: A.per - Abacidus permundus; S .sub - Scarites substriatus. 103 104 Ao m % m Jo 2 3 &6 1989 1990 Fig. 13 Fig 14. Carabid richness: average number of species (S) accumulated over total numbers (N) for the seven sampling dates during each year. Solid lines represent no-tillage, and broken lines represent conventional tillage. Bars are standard deviations. 105 106 *•-- io- ■ o 00 100 100 too 000 N to to- - 10-- 00 too too too N iiT 1990 to 10 - - 10-• 0 00 100 100 too too Fig. 14 Fig. 15. Carabid evenness: relative number of species (S) plotted against relative number of individuals (N) as a measure of evenness of the carabid assemblage on three cropping systems: (— ) corn monoculture, (••) soybean monoculture, and (— ) corn-soybean intercropping. The diagonal "base line" indicates complete evenness. 107 108 D l l 100 * M •0 00 " 40 •0 0 (0 40 00 « 0 10*0 100 « M 00- - 4 0 - ■ 00 00 40 00 00 100 % 0 Itto 100 0 M 0 0 - 4 0 " «0" 0 to 40 00 00 100 « 0 Fig. 15 Fig. 16. Dominant species in each treatment: C - corn, S - soybean, I — intercropping, NT - no-tillage, CT - conventional tillage. Dominance was defined as Nd/NT, where Nd - number of the dominant species and NT - total number of carabids. 109 DOM NANCE DOMWANCE DOMINANCE 990000 • O o » b - h i» V 5 h P j» • • « oo e o o o o s k> ~ b b k fc i s o * 00*0 e o • t o i— i— r « CO « 3 T □ □ E3 3 M M m a > » Fig. 17. Dendogram of the clustering of the six treatments using Euclidean distance and single linkage (nearest neighbor) method. See Fig. 16 for definition of treatments. Ill 112 1988 9- m ------ WIT ------ O-KT ------O-OT ------ W JT ------•-CT ------0.0 16.0 1989 MIT O-OT 6.0 10.0 1990 MIT l-CT o.o 20.0 Fig. 17 SUMMARY This study can be viewed as an pragmatic attempt to observe the effects of no-tillage and strip intercropping on pests and natural enemies of corn and soybean; however, my intentions were to test ecological theories regarding agroecosystems. Under the strictly practical perspective, the results indicated no-tillage treatment as beneficial to some soil pests (cutworms, armyworms, slugs) and with variable effect on different species of foliar herbivores. The strip-intercropping system was inefficient for reducing western corn rootworm infestation (especially on conventional tillage plots), despite crop rotation. Under the ecological perspective, I concluded that responses to diversification for most taxa examined were idiosyncratic, possibly reflecting uncontrolled factors. Nonetheless, data supported the theory of higher arthropod diversity in diversified agroecosystems, but there was no strong evidence for reduction of herbivory. In fact, most herbivores followed the trend for higher numbers in diversified plots. Additionally, the analysis of the carabid beetles assemblage suggested that diversity indices were strongly influenced by a single species. Considering the characteristics of some natural communities, such as dominance of a few species, the natural fluctuation of their relative abundance and their wide range of resource utilization, I suggested that separate analyses of dominance and richness are more appropriate than composite diversity indices. 113 Appendix A. Results of the analysis of variance for organisms sampled by sweep net. Analyses performed on transformed data (log [x+1]), and F and P values values are given for T - tillage factor, S - cropping system factor, and I — interaction. Means (numbers/80 sweeps) and standard deviations are given for each treatment: NT-MC - no-tillage, monoculture; CT-MC - conventional tillage, NT-IC - no-tillage, intercropping; CT-IC - conventional tillage, intercropping. Significant higher (P < 0.05) means within factors are indicated by (*). For significant interactions, means were separated by the Least Significant test. (----) indicates that the organism was not sampled or were at low densities Green clovervorm 1988 1989 _1990 X (SD) X (SD) X (SD) NT--MC: 13.5 (7.2) 82.5 (2 1 .7) 21.7 (13.2) CT--MC: 1 0 . 0 (2.9) 97.5 (17. 7) 40.5 (20.1)* NT-■IC: 18.2 (4.5) 109.2 (29. 8 )* 23.2 (10.0) CT-•IC: 11.2 (5.0) 129.7 (26. 9)* 40.7 (3.7)* 3.73, P - 0 08 P - E t “ Et - 4.17, 0.07 ET 9.83, P - 0.01 Es - 2.30, P - 0 2 Es - 9.57, P - 0 . 0 1 ES 0.18, P - 0.7 E, “ 1.14, P - 0 3 E, - 0 .0 1 , P - 0.9 E, 0.43, P - 0.5 Bean leaf beetle _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 64.5 (16.7)* 105.0 (42.9) 43.7 (21.2) CT-MC 37.0 (9.2) 151.7 (75.3)* 40.2 (14.9) NT-IC 46.7 (22.5)* 82.5 (12.1) 45.2 (17.8) CT-IC 37.5 (6.2) 142.5 (95.4)* 41.4 (12.6) 7.32, P - 0.02 ET - 4.72, P - 0.05 ET 0.07, P - 0.8 2.04, P - 0.2 Es £s - 0.68, P - 0.6 Es 0.19, P - 0.7 2.73, P - 0.1 - 0.11, P - 0.7 E. El E, 0 .02 , P - 0.9 114 115 Appendix A (continued) Japanese beetle _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 147.0 (52.5) 180.7 (21.1) 132.2 (46.4) CT-MC: 152.7 (23.2) 189.2 (37.3) 64.2 (14.9) NT-IC: 157.7 (106.0) 236.0 (96.7) 203.7 (47.2)*-* CT-IC: 197.0 (39.0) 199.2 (47.5) 124.7 (27.6) FT - 1.22, P - 0.3 ■ 0.09, P - 0.7 El 16.30, P - 0.003 Fs - 0.35, P - 0.6 Fs - 0.83 P - 0.6 £s 14.58, P - 0.004 F, - 0.43, P - 0.5 F, - 0.34, P - 0.6 £l 0.48, P - 0.5 Grasshoppers _1988 JL989 _1990 X (SD) X (SD) X (SD) NT-MC 3.2 (0.9) 16.2 (4.4)* CT-MC 6.0 (3.1) 2.2 (1 .2) NT-IC 3.2 (2.9) 20.7 (3.6)* CT-IC 4.7 (1.5) 3.5 (2.5) FT - 4.05, P - 0.07 Ft -38.24, P - 0.0003 Fs - 0.40, P - 0.5 Fs - 0.54, P - 0.5 F, - 0.01, P - 0.9 F, - 0.02, P - 0.9 Grape colaspis _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 7.0 (4.5)* 1.7 (1.7) CT-MC 6.7 (5.1) 1.0 (0 .8) NT-IC 10.0 (4.8)* 11.2 (4.3)*-* CT-IC 3.2 (2.2) 2.7 (4.2) 6.48, P - 0.03 t -T F - 7.48, P - 0.02 £ s 0.10, P - 0.7 Fs -16.06, P - 0.01 £i 3.83, P - 0.08 F, - 3.59, P - 0.08 Potato leafhopper 1988 1989 1990 X (SD) X (SD) X (SD) NT-■MC: 74.2 (34.3) 180.2 (49. 9) 113.2 (42. 4) CT-■MC: 146.2 (51.4)* 2 2 1 . 2 (35. 3) 344.7 (82. 7) •*-* NT-■IC: 54.2 (8.3) 208.2 (24. 1 ) 84.2 (16. 0 ) CT-•IC: 128.7 (63.1)* 256.5 (64. 0 ) 206.5 (67. 2 ) -28.64, P - 0.007 - 3.96, P - 0 .07 -40.93, P - 0 £ t FT .0003 - 2.08, P - 0.2 P - £s £s - 2 .1 0 , 0 .2 £ s - 6.34, P - 0 .03 - 0 .1 2 , P - 0.7 - 0.04, P - 0 .8 - 0.72, P - 0 .6 £i E| 116 Appendix A (continued) Tarnished plant bug _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 46.0 (9.3)* 22.2 (4.8)* CT-MC: 25.0 (9.0) 9.7 (0.9) NT-IC: ______34.2 (12.0)* 29.0 (12.9)* CT-IC: 23.2 (6.7) 11.2 (4.3) FT - 8.97, £ “ 0.01 Ft -28.11, P - 0.0008 Fs - 1.14, P - 0.3 Fs - 0.95, P - 0.6 F, - 0.65, P - 0.5 F, - 0.17, P - 0.7 Homoptera _1988 JL989 _1990 X (SD) X (SD) X (SD) NT-MC: 91.2 (24.8)* 42.5 (10.7) CT-MC: 61.5 (17.5) 31.0 (2.2) NT-IC: ______67.5 (21.6)* 38.2 (10.9) CT-IC: 58.0 (5.4) 38.7 (11.1) FT - 6.14, P - 0.03 Ft - 1.16 , P - 0.3 Fs - 2.85, £ - 0.1 Es - 0.12, P - 0.7 E, - 2.24, E - 0.2 F, - 1.41, P - 0.3 Damsel bugs 1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 15.0 (5.0) 17.5 (6.2) 5.5 (4.7) CT-MC: 15.7 (7.1) 18.7 (4.5) 5.7 (3.9) NT-IC: 17.7 (12.7) 23.0 (6.7)* 5.2 (0.5) CT-IC: 24.5 (14.0) 29.2 (9.7)* 6.2 (4.5) “ 0.17, P - 0.7 FT - 1.53, E - 0.2 Ft - 0.02, P - 0.9 Is “ 0.24, P - 0.6 Fs - 6.94, £ - 0.03 Fs - 0.12, P - 0.7 El “ 0.19, P - 0.7 F, - 0.30, P - 0.6 F, - 0.16, P - 0.7 Anthocorldae _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 93.0 (10.5) a 48.7 (5.3) 15.2 (5.8) CT-MC: 108.0 (26.3) ab 48.5 (2.5) 26.2 (4.8)* NT-IC: 124.2 (36.3) a 56.5 (10.5)* 17.5 (8 .6 ) CT-IC: 84.5 (22.7) b 61.0 (8.5)* 20.2 (1.5)* IT - 1.30, P - 0.3 Ft - 0.42, £ - 0.5 Ft - 8.69, P - 0.02 Is - 0 .0 1 , P - 0.9 Fs - 8.72, P - 0.01 Fs - 0.23, P - 0.6 Ei - 5.39, P - 0.04 F, - 0.45, P - 0.5 F, - 1.85, P - 0.2 117 Appendix A (continued) Lady beetles _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 1.7 (1.7) 2.0 (1.4) 5.7 (0.9)* CT-MC 3.2 (3.3) 2.0 (1.4) 4.0 (2.2) NT-IC 8.0 (5.8)* 6.0 (3.4)* 11.0 (5.3)* CT-IC 5.7 (1.2)* 4.5 (1.7)* 4.0 (3.5) - 0.20, £ - 0.7 IT - 0.05, £ - 0.8 6.81, £ - 0 . 0 IT It - - 0 . 0 2 Is 8.61, £ - Eg - 8.16, £ - 0 . 0 1 Is “ 0.55, £ - 0.5 S' — 0 6 8 0.6 ]-I . , £ - F, - 0.18, £ - 0.7 Ii " 1.45, £ - 0.2 Spiders _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 12.0 (2.9) 22.2 (4.8) 26.7 (7.1) CT-MC 9.0 (0.8) 18.7 (2.1) 25.5 (6.1) NT-IC 13.5 (0.6) 34.0 (8.9)* 27.5 (3.6) CT-IC 11.5 (6.5) 31.0 (10.2)* 30.2 (1.2) - 1.95, P - 0.2 FT - 1.13, £ - 0.3 0.06, £ - 0.8 IT I t " Is - 0.15, £ - 0.7 £s -13.21, £ - 0.006 Is " 1.37, £ - 0.3 0.05, P - 0.8 Fj - 0.04, £ - 0.8 I| — Ii “ 0.38, £ - 0.5 Hymenoptera _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 19.7 (8.4)* 26.0 (5.0) 19.7 (5.8) CT-MC 14.7 (4.4) 22.5 (5.2) 19.5 (5.7) NT-IC 25.2 (3.9)* 34.5 (5.2)* 27.5 (6.5) CT-IC 16.5 (4.6) 31.7 (7.8)* 19.0 (1.4) - 5.25, £ - 0.04 FT - 1.23, £ - 0.3 2.23, £ - 0.2 I t I t " - Is 1.92, £ - 0.2 Fs - 7.61, £ - 0.03 Is “ 2 .0 2 , £ - 0.2 - II 0.44, £ - 0.5 F, - 0.06, £ - 0.8 Ii - 2.06, £ - 0. 2 Phalangidae _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 7.5 (1.3) 7.0 (2.9) 4.0 (3.5) CT-MC 5.7 (1.7) 3.2 (3.4) 5.7 (2.9) NT-IC 17.0 (7.3)* 12.5 (1.4)* 5.0 (1.4) CT-IC 11.7 (7.1)* 11.5 (1.3)* 9.0 (3.4) - 2.63, P - 0.1 FT - 2.62, £ - 0.1 I t I t " 3.28, £ - 0.1 Is L0.31, £ - 0.01 Fs -14.49, £ - 0.004 F - 2.53, £ - 0.1 - 0.13, £ - 0.6 I. F, - 4.14, £ - 0.07 II - 0.01, £ - 0.9 Appendix B. Results of the analysis of variance for organisms sampled by D-vac. Means are numbers/10 plants in 1988, and numbers/2 rows in 1989 and 1990. See Appendix A for details Striped flea beetle _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 8.2 (5.0) CT-MC 22.5 (20.8)* NT-IC 8.0 (7.2) CT-IC 19.7 (6 .6 )* Et - 6.99, P - 0.0001 Es - 0.10, P - 0.9 E, - 0.31, P - 0.6 Potato leafhopper _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 13.7 (5.4) 534.2 (97.5) 416.2 (69.2) CT-MC 30.2 (6.5)* 794.0 (140.6)*-* 878.5 (191.9)*-* NT-IC 9.5 (2.4) 443.0 (47.5) 342.0 (30.3) CT-IC 29.2 (9.1)* 635.2 (159.3) 579.0 (221.8) £t -31.42, P - 0.006 Ft -16.65, P - 0.03 e t -27.03, P - 0.0008 Es - 1.17, P - 0.3 Fs - 5.26, P - 0.04 Es - 7.57, P - 0.02 E, - 0.48, P - 0.5 Fj - 0.10, P - 0.7 E, - 1.29, P - 0.3 Tarnished plant bug _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 39.7 (5.8)* 57.2 (8.1)* CT-MC 27.0 (5.3) 22.0 (8.7) NT-IC 46.5 (14.3)* 59.2 (10.2)* CT-IC 36.7 (10.3) 18.7 (3.0) Et - 7.83, E - 0.02 Et - 70.81, I - 0.0001 Fs - 3.51, P - 0.09 Es - 0.10, P - 0.7 F, - 0.51, P - 0.5 E, - 0.31, P - 0.6 Homoptera _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 103.0 (27.1)* 178.5 (53.3) CT-MC 61.0 (2 2 .8 ) 148.7 (32.3) NT-IC 125.5 (55.5)* 227.2 (86.3) CT-IC 72.2 (23.4) 224.5 (85.1) Ft -18.89, P - 0.002 Et - 0.32, P - 0.6 Fj - 1.89, P - 0.2 Es - 2.75, P - 0.1 Fj - 0.01, P - 0.9 Ei - 0.16, P - 0.7 118 119 Appendix B (continued) Damsel bugs JL988 JL989 _1990 X (SD) X (SD) X (SD) NT-MC: 19.5 (6 .6 ) 9.2 (4.6) CT-MC: 24.2 (8.3) 6.5 (3.4) NT-IC: ______23.7 (3.1)* 11.2 (3.8) CT-IC: 37.0 (12.3)* 8.5 (4.3) Ft - 3.78, P - 0.08 F t - 3.44, P - 0.09 £s - 4.55, £ - 0.05 Fs - 2.28, P - 0.2 Ei - 0.38, P - 0.5 F, - 0.01, P - 0.9 Anthocoridae _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 4.5 (1.0) 79.2 (5.7) 42.0 (9.4) CT-MC: 6.0 (2.4) 99.7 (13.2)* 38.5 (3.3) NT-IC: 8.2 (6.5)* 73.2 (15.4) 38.2 (11.5) CT-IC: 9.2 (2.1)* 87.0 (6.7)* 33.0 (6.4) Ft - 1.74, P - 0.2 Et “ 7.48, P - 0.02 F, - 0.56, P - 0.5 Fs - 7.70, P - 0.04 E s “ 2.27, P - 0.2 Fs - 1.13, P - 0.3 F, - 0.01, P - 0.9 E, " 0.06, P - 0.8 F, - 0.04, P - 0.8 Spiders _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 45.2 (7.4) 41.0 (6.7) CT-MC: 41.0 (5.6) 40.7 (4.6) NT-IC: ______61.7 (4.6)* 47.5 (5.2)* CT-IC: 61.5 (6.5)* 46.7 (6.4)* FT - 0.57, P - 0.5 FT - 0.03, P - 0.9 Fs -28.86, P - 0.0007 Fs - 5.22, P - 0.05 F, - 0.44, P - 0.5 F, - 0.02, P - 0.9 Hymenoptera 1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 17.2 (2.5) 173.5 (36.2) 318.0 (44.5) CT-MC: 25.2 (6 .0 ) 140.2 (26.6) 247.7 (17.1) NT-IC: 22.2 (1 2 .6 ) 215.5 (40.3)*-* 339.5 (36.5)*-* CT-IC: 36.7 (2 1 .0 ) 167.7 (26.1) 305.7 (36.5) 1.62, P - 0.2 FT -21.97, P - 0.001 Ft -10.16, P - 0.01 £s - 2.76, P - 0.1 Fs -17.15, P - 0.003 Fs - 6.28, P - 0.03 £| “ 1.62, P - 0.2 F, - 0.17, P - 0.7 F, - 1.60, P - 0.2 Appendix C. Results of the analysis of variance for organisms sampled by direct counts. Means are numbers/20 plants in 1988, and numbers/row in 1989 and 1990. See Appendix A for details Bean leaf beetle _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 0.7 (0.4)* 33.6 (10.9) CT-MC 0.4 (0.3)* 33.5 (3.4) NT-IC 0.2 (0 .2) 33.2 (6.4) CT-IC 00.6 (0 .1) 30.1 (9.2) - 0.69, P - 0.6 £ t - 2.39, P - 0.1 ET ES “ 5.78, P - 0.04 Es - 2.11, P - 0.2 0.51, P - 0.5 - 2.02, P - 0.2 El “ Ei Striped flea beetle _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC 0.0 CT-MC 1.2 (1-4) NT-IC 0.2 (0.1) CT-IC 3.9 (1.3)*-* ET ■33.68, P - 0.0004 Es ■10.97, £ - 0.009 Ei ■ 4.17, P - 0.07 Grape colaspis _1988 _1989 _1990 X (SD) X (SD) X (SD) NT-MC: 1 . 2 (0 .6 ) b CT-MC: 1.5 (3.0) b NT-IC: 5.1 (1.5) a CT-IC: 1.2 (0 .6 ) b Et " 6.11, £ - 0.03 Eg - 6.11, £P - 0.03 F t - 5.16, £P - 0.05 120 Appendix D. Results of the analysis of variance for organisms sampled by pitfall traps. Means (numbers/2 traps) and standard deviations are given for two crops (C - corn, S - soybean, I - intercropping) under two tillage systems (NT - no-tillage, CT - conventional tillage). See Appendix A for details Slugs _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT 7.0 (4.2)* 29.2 (8.4)* 38.7 (19.7)* S-NT 14.5 (3.0)* 27.7 (17.2)* 37.5 (11.4)* I-NT 11.4 (4.5)* 25.7 (5.2)* 35.2 (11.3)* C-CT 5.7 (3.5) 6.0 (5.2) 20.0 (9.4) S-CT 5.0 (4.8) 15.0 (10.5) 15.5 (1 1 .1 ) I-CT 7.0 (2 .8 ) 6.0 (5.8) 20.2 (1 0 .2 ) - 9.53, P - 0.007 Ft -26.16, P - 0.0003 Ft -28.48, P - 0.0 £ s " 1.37, P - 0.3 Fs - 0.89, £ - 0.6 Zs - 0.54, P - 0 . 6 - 2.50, P - 0.1 F, - 1.49, P - 0.2 F, - 0.98, P - 0 . 6 Homoptera _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 27.0 (10.4)* 33.5 (16.7)* 31.5 (1 0 .8 )* S-NT: 32.2 (6.5)* 21.7 (3.6)* 29.7 (8 .6 )* I-NT: 32.6 (12.8)* 22.5 (9.5)* 17.0 (4.7)* C-CT: 10.7 (5.0) 8.2 (3.8) 7.0 (2.3) S-CT: 19.2 (8 .8 ) 17.2 (1 2 .2 ) 7.7 (4.6) I-CT: 17.9 (4.2) 9.5 (6.5) 7.5 (2 .6 ) Ft -17.64, P - 0.001 Ft -13.32, P - 0.003 Ft -47.55, P - 0.0 Fs - 2.39, P - 0.1 Fs - 0.55, P - 0.6 Fs - 0.94, P - 0.6 F, - 0.58, P - 0.6 F, - 1.20, P - 0.3 F, - 1.51, P - 0 . 2 Spiders _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT 84.0 (34.2)* 30.5 (11.5) 44.0 (19.1)* S-NT 68.5 (9.1)* 34.7 (10.6) 45.7 (13.6)* I-NT 97.2 (29.9)* 41.5 (25.5) 41.7 (16.5)* C-CT 66.7 (27.0) 23.5 (3.7) 21.7 (7.4) S-CT 48.5 (19.1) 27.5 (3.1) 21.7 (4.3) I-CT 38.1 (10.7) 27.5 (18.4) 30.0 (20.4) -12.31, P - 0.003 2.77, P - 0.1 -11.69, -T P - 0.004 £s - 1.03, P - 0.4 0.76, P - 0.5 Is - 0.06, P - 0.9 - 1.98, P - 0.2. 0 .02 , P - 0.9 - 0 .22, P - 0.8 121 122 Appendix D (continued) Tiger beetle 1988 1989 1990 X (SD) X (SD) X (SD) C-NT: 4.2 (2.4) 0.7 (0.5)* b 3.2 (2.4) ab S-NT: 5.0 (2.4) 8.5 (10.4)* a 2.2 (2 .1 ) b I-NT: 10.0 (6 .1 ) 6.7 (5.0)* a 5.5 (4.5) ab C-CT: 4.0 (3.8) 0.5 (0.6) b 2.7 (4.3) b S-CT: 4.0 (4.0) 1.5 (1.3) a 6.2 (0.9) a I-CT: 3.5 (1.4) 3.2 (6.5) a 7.5 (2 .6 ) ab Ft - 3.74, P - 0.07 FT - 9.93, P - 0.007 - 0 .1 1 , E t P - 0.7 Fs - 1.17, P - 0.3 Fs - 5.09, P - 0.02 Es - 1.70, P - 0.2 F, - 0.75, P - 0.5 F, - 1.66, P - 0.2 E, — 3.61, P - 0.05 Centipedes _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 5.7 (2.9) 2.0 (0 .8 ) S-NT: 2.5 (2.4) 1.2 (1 .2 ) I-NT: 6.2 (2.5) 0.7 (1.5) C-CT: 16.2 (13.1)* 4.2 (1.7)* S-CT: 14.7 (2 .1 )* 2.0 (1.4)* I-CT: 13.2 (9.0)* 3.2 (4.6)* Ft -20.06, £ - 0.0007 E t - 5.16, P - 0.04 Fs - 0.94, P - 0.6 Es aw 2.80, P - 0.09 F, “ 2.33, P - 0.1 Ei — 0 .2 2 , P - 0.8 Hymenoptera _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 100.5 (37.9) a 145.7 (48.2) 167.7 (43.9) a S-NT: 64.0 (13.2) b 1 1 1 . 0 (28.0) 84.5 (16.6) b I-NT: 92.6 (31.7) ab 100.5 (14.7) 107.7 (69.7) b C-CT: 143.5 (76.2) a 146.5 (40.2)* 247.2 (75.9)* a S-CT: 70.2 (3.9) b 130.5 (42.2)* 138.0 (34.1)* b I-CT: 92.0 (8 .8 ) ab 189.2 (56.8)* 155.7 (23.8)* b I T - 1-27, P - 0.3 Ft - 4.27, P - 0.05 Et - 9.18, P - 0.008 I s - 5.02, P - 0.02 Fs - 0.90, P - 0.6 E s - 6.14, P - 0.01 F, - 0.36, P - 0.7 F, - 2.09, P - 0.1 E, «■ 0.09, P - 0.9 123 Appendix D (continued) Phalan^idae _1988 _19Z9 1990 X (SD) X (SD) X (SD) C-NT: 31.2 (8 .8 ) 9.2 (2.9) 42.0 (27.2) S-NT: 39.5 (14.7) 19.5 (10.1) 45.5 (9.3) I-NT: 38.4 (8.2) 16.2 (9.8) 40.7 (1 1 .1 ) C-CT: 34.5 (8.2) 18.2 (7.4)* 25.0 (5.8) S-CT: 36.5 (8.3) 25.2 (4.8)* 46.2 (13.6) I-CT: 30.6 (10.6) 23.5 (18.7)* 39.2 (5.5) - 0.56, P - 0.5 £ t FT - 4.87, P - 0.04 Ft - 1.08, P - 0.3 ES - 0.79, P - 0.5 Fs - 2.54, P - 0.1 Fs - 3.46, P - 0.0 - 1.46, P - 0.3 Ei F, - 0.36, P - 0.7 F, - 0.96, P - 0.6 Ants _1988 JL989 _1990 X (SD) X (SD) X (SD) C-NT: 117.0 (28.1)* 55.7 (14.3)* 73.5 (30.0)* S-NT: 84.5 (15.1)* 76.0 (37.2)* 46.0 (2 2 .8 )* I-NT: 91.2 (35.4)* 82.7 (49.4)* 59.5 (37.4)* C-CT: 93.2 (34.0) 33.2 (12.3) 31.0 (10.4) S-CT: 46.2 (24.9) 38.7 (14.2) 28.5 (9.7) I-CT: 69.9 (28.7) 50.2 (16.5) 24.0 (1 1 .0 ) E t -13.90, P - 0.002 Ft -25.18, P - 0.0003 Ft -27.15, P - 0.0 Es - 7.83, P - 0.06 Fs - 2.76, P - 0.06 Fs - 2.07, P - 0.1 E, - 1.89, P - 0.2 F, - 0.39, P - 0.7 F, - 1 .1 2 , P - 0.3 Millipedes _1988 _1989 1990 X (SD) X (SD) X (SD) C-NT: 6.5 (4.3) 3.7 (4.3) 5.0 (4.5) S-NT: 9.2 (4.8) 6.2 (3.7) 6.7 (5.0) I-NT: 9.1 (5.2) 5.2 (4.0) 3.0 (2 .2 ) C-CT: 7.0 (5.9) 46.2 (32.4)* 3.5 (2 .1 ) S-CT: 4.0 (2.6) 20.7 (21.0)* 4.7 (2.4) I-CT: 5.6 (2.1) 23.5 (18.0)* 9.5 (6 .2 ) E t - 2.87, P - 0.1 Ft -19.07, P - 0.0008 Ft - 0.94, P - 0.6 Es - 0.24, P - 0.8 Fs - 0.05, P - 0.9 Fs - 0.60, P - 0.6 E, - 0.81, P - 0.5 F, - 2.25, P - 0.1 £, - 1.93, P - 0.2 124 Appendix D (continued) Beetles JL988 1989 1990 X (SD) X (SD) X (SD) C-NT 83.5 (23.7)* 32.0 (1 0 .8 )* 33.2 (5.6)* S-NT 78.2 (5.9)* 25.0 (7.0)* 39.5 (15.7)* I-NT 80.4 (14.9)* 2 0 . 0 (2.9)* 34.5 (5.4)* C-CT 52.0 (8.0) 15.7 (5.9) 24.7 (5.6) S-CT 38.7 (7.9) 14.0 (6 .2 ) 29.2 (5.7) I-CT 55.0 (14.0) 15.5 (2.4) 24.5 (6 .6 ) -38.83, £ - 0.0001 Ft -15.11, £ - 0 . 0 0 2 13.97, £ - 0 . 0 0 2 Fs - 1.98, £ - 0.2 Fs - 0.92, £ - 0 . 6 1.39, £ - 0.3 F, - 1.37, £ - 0.3 £ - 0.4 0 .1 1 , F, - 1.08, Ei £ - 0.9 Appendix E. Results of the analysis of variance for organisms sampled by quadrat samples. Means (numbers/1 m2) and standard deviations are given for two crops (C - corn, S - soybean, I - intercropping) under two tillage systems (NT - no-tillage, CT — conventional tillage). See Appendix A for details Slugs _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 7.5(4.8)* 9.0 (4.6)* S-NT: 7.7 (3.6)* 6 .0 (1 .0 )* I-NT: 5.5 (3.1)* 6.3 (3.2)* C-CT: 0.7 (0.9) 1.0 (1 .0 ) S-CT: 2.7 (2 .2 ) 3.0 (2 .6 ) I-CT: 0.2 (0 .6 ) 0.3 (0 .6 ) Ft -40.48, £ - 0 . 0 0 0 1 Ft -27.64, £ - 0 . 0 0 1 Fs - 2.63, £ - 0. 1 Fs - 1.08, £ - 0.2 F, - 0.51, £ - 0.6 F, - 0.11, £ - 0.7 Spiders 1988 1989 1990 X (SD) X (SD) X (SD) C-NT 10.7 (6 .0 )* 2.7 (1.5) 2.2 (0.5)* S-NT 6.7 (2 .2 )* 3.7 (3.8) 3.2 (1.7)* I-NT 8.7 (2.9)* 2.7 (2 .1 ) 2.5 (1.3)* C-CT 2.2 (2 .2 ) 1.0 (1 .0 ) 1.0 (1.4) S-CT 2.7 (0.9) 1.7 (1.5) 1.2 (0.5) I-CT 2.7 (3.0) 2.7 (0 .6 ) 1.0 (1.4) -28.25, £ - 0 . 0 0 0 2 Ft - 1.43, P - 0.2 Ft - 5.24, £ - 0.04 £ t £s - 0 .0 1 , £ - 0.9 Es - 0.40, £ - 0.7 Fs - 1.90, £ - 0.6 - 0.93, F, - 0.60, £ - 0 . 6 £ - 0.5 El £ - 0.6 F, - 0.44, Centipedes 1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT 8.2 (4.9)* S-NT 6.2 (2.9)* I-NT 7.5 (4.8)* C-CT 2.7 (1 .2 ) S-CT 2.0 (1.4) I-CT 1.5 (1.3) Ft -18.06, £ - 0 . 0 0 1 Fs - 0.53, £ - 0.6 F, - 0.31, £ - 0.7 125 126 Appendix E (continued) Carabldae _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 9.5 (3.7)* 5.7 (1.1) 10.0 (2.3) S-NT: 9.0 (4.1)* 6.0 (4.3) 4.0 (2.8) I-NT: 12.2 (5.2)* 7.7 (3.8) 8.5 (1.7) C-CT: 2.2 (0.9) 5.3 (3.0) 5.0 (2.7) S-CT: 0.7 (0.5) 1.7 (0.6) 8.5 (4.9) I-CT: 2.5 (1.7) 4.0 (4.0) 4.0 (5.6) Ft -54.04, P - 0.0001 FT - 3.14, £ - 0.1 f t - 2.63, P - 0.1 Fs - 0.70, P - 0.5 JEs — 2.11, P - 0.1 £s - 1.93, P - 0.2 F, - 0.78, P - 0.5 F, - 0.40, P - 0.6 £i - 0.13, P - 0.6 Ants _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 17.0 (3.8)* 6.7 (2.3)* 3.2 (1.7)* S-NT: 12.5 (5.2)* 10.3 (1.1)* 5.2 (2.9)* I-NT: 14.7 (6.5)* 13.3 (7.1)* 7.0 (9.0)* C-CT: 3.2 (3.3) 0.7 (0.6) 2.7 (1.1) S-CT: 0.5 (1.0) 3.0 (1.0) 0.7 (0.5) I-CT: 1.5 (1.7) 1.3 (1.5) 2. 2 (2 .2 ) Ft -99.85, P - 0.0001 FT -46.19, P - 0.001 - 7.81, P - 0.03 I t Fs - 3.09, P - 0.07 Fs - 3.08, P - 0.09 Is - 0.12, P - 0.7 F, - 0.56, P - 0.6 F, - 1.19, P - 0.3 Ii - 1.43, P - 0.2 Millipedes _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 9.7 (9.4)* 2 . 0 (1 .0 )* S-NT: 7.7 (9.5)* 5.0 (4.0)* I-NT: 6.5 (5.4)* 1 . 0 (1 .0 )* C-CT: 0.0 0.7 (0.6) S-CT: 0.2 (0.5) 1 . 0 (1 .0 ) I-CT: 0.0 0.3 (0.6) Ft -53.81, P - 0.0001 Ft - 9.26, P - 0.01 Fs - 0.06, P - 0.9 Fs - 2.99, P - 0.09 F, - 0.09, P - 0.9 F, - 0.23, P - 0.8 127 Appendix E (continued) Beetles _1988 _1989 _1990 X (SD) X (SD) X (SD) C-NT: 16.7 (2.5)* 6.3 (3.0)* 3.7 (2.2)* S-NT: 12.5 (4.2)* 6.7 (1.1)* 7.5 (8.7)* I-NT: 8.5 (3.7)* 7.7 (1.1)* 6.7 (3.8)* C-CT: 4.5 (1.0) 0.3 (0.6) 2.0 (0) S-CT: 2.5 (1.3) 2.3 (1.5) 0.7 (0.5) I-CT: 0.5 (0.6) 1.0 (1 .0) 3.9 (2.8) Ft -98.97, P - 0.0001 Ft -48.55, P - 0.0001 Ft 13.22, P - 0.006 Fs - 6.63, P - 0.06 Fs - 2.19, P - 0.2 Fs 1.13, P - 0.3 Fj - 1.84, P - 0.2 F, - 1.54, P - 0.3 F, 0.05, P - 0.9 BIBLIOGRAPHY Agnew, C. 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