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I".

This is to certify that the

dissertation entitled

The Bionomics of Acarina

Associated With Selected Turfgrasses

presented by

Saad ELSayed Salem

has been accepted towards fulfillment
of the requirements for

Ph.D. Zoology

degree in

 

 

/

/
[A 4/1 I ’ (/AI'A/AJ
ajorp .fessor

‘\

1

Date 10/12/1989

MS U is an Affirmative Action/Equal Opportunity Institution 042771

 

h‘

 

 

F LIBRARY I
Michigan State

‘ University

1‘

 

 

PLACE IN RETURN BOX to remove We checkout irom your record.
TO AVOID FINES retun on or before due due.

DATE DUE DATE DUE DATE DUE

— l:_"

 

 

 

 

 

 

 

 

 

 

 

 

 

__:§

 

 

 

 

MSU le An Afflrmdive ActioNEquel Opportunity Inethion
cWMt

THE BIONOMICS OF ACARINA ASSOCIATED
WITH SELECTED TURFGRASSES

By
Saad ELSayed Salem

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Zoology

1989

l/\

p/L’Tdv)

ABSTRACT

THE BIONOMICS OF ACARINA ASSOCIATED
WITH SELECTED TURFGRASSES

BY

Saad ELSayed Salem

The present study assessed population density, seasonal
fluctuation, and vertical distribution of selected genera
and species of Acarina inhabiting the soil under six species

of turfgrass.

During both study years (1985 and 1986) Acarina were
the dominant soil artheopods. Within Acarina, Prostigmata
were most numerous, followed by Mesostigmata; Cryptostigmata

ranked third and Astigmata fourth.

Data obtained on several of the most abundant genera
and species were subjected to detailed analyses. Results
indicated distinct differences between the studied taxa.
While some showed no preference for either of the sampled
strata (0-15 and 16-30 cm depth), Enpgggg spp. for instance

were clearly upper horizon dwellers. Seasonal patterns of

abundance were synchronous in 1985 and 1986 for Egpodes spp.
and Megs bedtgrfiiensis but not for others. For several
taxa, significant relationships between abundance and soil

moisture and temperature were established.

Most importantly, turfgrass species exerted a
significant influence on abundance and distribution of
several taxa. Smooth bromegrass and Kentucky blues grass

were generally favorable to figggxdagia spp. and

Bhodagarellus silesiacue: highest abundance of the
predaceous gypgagpig agglgifig; was recorded under tall

fescue, while Megs W seemed to be numerous

under redtop.

Further studies of functional relationships between
root system characteristics, associated microflora and

arthropod population dynamics are recommended.

4 ./‘0‘

”3'5?le —-':2
an. die name 0/04“ Lg; moat mull/Jane! Lg; mod gene/Lean!

 

DEDICATION

To my mother, for her love and support
(May Allah forgive her and let her
soul rest in peace)

11'

ACKNOWLEDGMENTS

The author wishes to express his sincere gratitude and
appreciation to the members of his doctoral committee and
especially to professor, Dr. Richard J. Snider, Chairman;
for his valuable advice, guidance, encourage, and help

during the course of this study.

Grateful acknowledgment is also expressed to professor,
Dr. Paul E. Rieke for his effort to provide the study area
and a Valuable source for information about turfgrasses and

soil.

The author wishes to extend his sincere appreciation to
Dr. IRenate Snider' for’ her’ assistance, encouragement and
moral support: and to professor, Dr. Julius R. Hoffman for
his assistance and for serving on my guidance committee.
Special thanks to professor, Dr. John Gill for his

assistance and help with statistical analyses of this study.

My deep appreciation to my wife Hania for her unlimited
patience, encouragement and understanding, and to mw'
children Hanan and Amal, who sacrificed their precious

moments of fatherly companionship.

iii

List

List

III.

IV.

TABLE OF CONTENTS

of Tables . . . . . . . . . . . . . . . . . . . . VII
of Figures . . . . . . . . . . . . . . . . . . . . IX
INTRODUCTION . . . . . . . . . . . . . . . . . . . . 1
REVIEW OF LITERATURE . . . . . . . . . . . . . . . . 3

Horizontal patterns and effect of plant covers on
population dynamics of arthropods . . . . . . . . . 3

Seasonal fluctuation and vertical distribution of
soil arthropod population . . . . . . . . . . . . . 8

Effect of ecological factors on soil arthropod
population dynamics . . . . . . . . . . . . . . . . 13

MATERIALS AND METHODS . . . . . . . . . . . . . . . 20
1. Site description . . . . . . . . . . . . . . . 20
2. Description of grassplant covers . . . . . . . 22
3. Soil analysis . . . .h. . . . . . . . . . . . 23
4. Soil temperature . . . . . . . . . . . . . . . 26
5. Soil moisture . . . . . . . . . . . . . . . . 26
6. Precipitation . . . . . . . . . . . . . . . . 27
7. Sampling and extraction methods . . . . . . . 27
8. Slides mounting technique . . . . . . . . . . 29
9. Statistical analysis . . . . . . . . . . . . . 30
RESULTS AND DISCUSSION . . . . . . . . . . . . . . 31
1. Ecological parameters . . . . . . . . . . . . 31

1.1 Soil Temperature . . . . . . . . . . . . . 31

iv

1.2 Soil Moisture . . . . . . . . . . . .
1.3 Precipitation . . . . . . . . . . .
Distribution and dynamics of Acarina . .

A. Existence Percentage of acarina order .

B. Order Prostigmata . . . . . . . . . . . . . . . .

8.1

Effect of grass covers on population
dynamics of Prostigmata . . . . . . . . .

B.2 Biweekly fluctuation of prostigmatid mite
populations . . . . . . . . . . . . . . .
B.3 Vertical distribution of prostigmatid mite
populations . . . . . . . . . . . . . . .
C. Suborder: Heterostigmata . . . . . . . . . . .
C.1 Genus Targgngmgg . . . . . . . . . . . . .
C.2 Effect of grass covers on population
dynamics of Taxggngmgg spp. . . . . . . .
C.3 Biweekly fluctuation of Ta;§___mg§ spp.
populations . . . . . . . . . . . . .
C.4 Vertical distribution of Ia1__n§mg§ spp.
populations . . . . . . . . . . . . .
C.5 Genus flgkgzdania . . . . . . . . . . . . .
C.6 Effect of grass covers on population
dynamics of fiakgxgania spp. . . . . . . .
C.7 Biweekly fluctuation of figkgggania spp.
populations . . . . . . . . . . . . .
C.8 Vertical distribution of Bakerggnig spp.

populations . . . . . . . . . . . . . . .

D. Suborder: Eupodina . . . . . . . . . . . . . . .

D.1

D.2

Effect of grass covers on population
dynamics of Eupgggg spp. . . . . . . . .

Biweekly fluctuation of Enpgggs spp.
populations . . . . . . . . . . . . . . .

38

38

4O

4O

40

43

43

46

55

55

55

58

58

65

65

68

68

78

78

78

D.3 Vertical distribution of Egpgggg spp.
populations . . . . . . . . . . . . . . . . . 86

Family: Tydeidae . . . . . . . . . . . . . . . . . 9o

E.1 Effect of grass covers on population '
dynamics of Iyggug bedfordiensis . . . . . . 90

E.2 Biweekly fluctuation of Tydeus bedfordignsis

populations . . . . . . . . . . . 95
E.3 Vertical distribution of ngeu§ bgd£_rdi§n_i_
populations . . . . . . . 95

E.4 Effect of grass covers on population dynamics

of Metanronematue leusghieneus . . . - - . - .102
3.5 Biweekly fluctuation of netapronematus

leugghippgg_ populations . . . . . . .102
E.6 Vertical distribution of ugtangngmatug
leugghippggs populations . . . . . .105

Order: Hesostigmata . . . . . . . . . . . . . . . .112

E.1 Effect of grass covers on population

dynamics of Bhodasarellu§.sile§ia§u§ - - - - 112

F.2 Biweekly fluctuation of Bhodagarellug
silegiaggg populations . . . . . . . . . . . .117

E.3 Vertical distribution of Bhodagazellus
silesiagus populations . . . . . . . . . . . .117

F.4 Effect of grass covers on population

dynamics of fiypgagpig aguleifgz. . . . . . . .122
F.5 Biweekly fluctuation of nypgaspis aguleifer

populations . . . . . . . . 125
F.6 Vertical distribution of flypgaspis a_uleifer
populations . . . . . . . . . . . 125

SUMMARY AND CONCLUSION . . . . . . . . . . . . . .135

BIBLIOGRAPHY O O O O O O O O O O O O O O O O O O O 14 0

vi

VII 0 APPENDICES O O O O O O O O O O O O O O O O O O O O 14 5

APPENDIX A: Tables of sample means per grass
and date C O O O O O O O O O O O O O O 1 4 6

APPENDIX B: Anova tables . . . . . . . . . . . . .163

APPENDIX C: Correlation and multiple regression
analysis . . . . . . . . . . . . . . .172

vii

10.

11.

12.

13.

14.

LIST OF TABLES

List of turfgrass species in the study area . . .

Average percentage of soil organic matter content
under different grasses . . . . . . . . . . . . .

Average recorded soil temperature (0C) and
moisture during 1985 . . . . . . . . . . . . . .

Average recorded soil temperature (0C) and
moisture during 1986 . . . . . . . . . . . . . .

Relative dominance of Acarina orders in 1985
and 1986 O O O O O O O O O O O O O O O O O O O O

Population densities iSE/m2 of Prostigmata in
each soil stratum under different grasses . . . .

Mean seasonal density /m2 :SE of Prostigmata in upper

and lower strata; data from all grasses lumped .

Relative dominance of Heterostigmata genera in
1985 and 1986 O O O O O O O O O O O O O O O O O O

Population densities iSE/m2 of Iazggngmgg spp.
in each soil stratum under different grasses . .

Mean seasonal density /m2 18E of Targgngmgg spp.
in upper and lower strata: data from all grasses
lumped O O O O O O O O O O O O O O O O O O O O O

Population densities iSE/m2 of fiakgrgania spp.
in each soil stratum under different grasses . .

Mean seasonal density /m2 18E of nakgzgania spp.
upper and lower strata: data from all grasses
lumped O O O O O O O O O O O O O O O O O O O O O

Relative dominance of Eupodina genera in 1985
and 1986 O O O O O O O O O O O O O O O O O O O O

Population densities iSE/m2 of Egpgggg spp.
in each soil stratum under different grasses . .

viii

Page

20

25

32

35

41

44

47

.56

59

61

69

71

79

81

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

Mean seasonal density /m2 18E of Eupgggfi spp.
in upper and lower strata: data from all grasses
lumped O O O O O O O O O O O O O O O O O O O O O O O 8 3

Relative dominance of species in the family Tydeidae
in 1985 and 1986 O O O O O O O O O O O O O O O O O O 91

Population densities iSE/m2 of Tygggg bedfordignsis

in each soil stratum under different grasses . . . . 93

Mean seasonal density /m2 18E of Tygggs bedfordiensis

in upper and lower strata: data from all grasses
lumped O O O O O O O O O O O O O O O O O O O O O O O 9 6

Population densities :SE/m2 of Metaprgngmatus
leugghippeus in each soil stratum under different

grasses O O O O O O O O O O O O O O O O O O O O O O 103

Mean seasonal density /m2 38E of m
leugghippeus in upper and lower strata: data from
all grasses lumped . . . . . . . . . . . . . . . . .106

Relative dominance of species of order Mesostigmata
in 1985 and 1986 O O O O O O O O O O O O O O O O O O 113

Population densities iSE/n2 of Rhodagarellus silesiagus

in each soil stratum under different grasses . . . .115

Mean seasonal density /m2 18E of Rhggagarellug
fiilgsiagug in upper and lower strata: data from
all grasses lumped . . . . . . . . . . . . . . . . .118

Population densities iSE/m2 cf nypgagpis agnleifg;
in each soil stratum under different grasses . . . .126

Mean seasonal density /m2 iSE of fiypgaspifi aguleife:

in upper and lower strata; data from all grasses
lumped O O O O O O O O O O O O O O O O O O O O O O O 128

APPENDIX A: Tables of sample means per grass and date . .146

APPENDIX B: Anova tables . . . . . . . . . . . . . . . . 163

APPENDIX C: Correlation and multiple regression

analysis . . . . . . . . . . . . . . . . . . 172

ix

10.

11.

12.

13.

14.

15.

LIST OF FIGURES

Page
Diagram of the 6 sample blocks and their
different grass covers . . . . . . . . . . . . . . . 21
Diagram of soil core device . . . . . . . . . . . . .28

Average recorded soil temperature and moisture of
the 0 - 15 cm stratum during 1985 . . . . . . . . . 33

Average recorded soil temperature and moisture of
the 16 - 30 cm stratum during 1985 . . . . . . . . . 34

Average recorded soil temperature and moisture of
the 0 - 15 cm stratum during 1986 . . . . . . . . . .36

Average recorded soil temperature and moisture of
the 16 - 30 cm stratum during 1986 . . . . . . . . . 37

Amount of precipitation received in the study
area during 1985 and 1986 . . . . . . . . . . . . . 39

Relative dominance (t) of acarine orders (all
grasses lumped) . . . . . . . . . . . . . . . . . . 42

Prostigmata densities /m2 in both soil strata under
different grass covers . . . . . . . . . . . . . . 45

Biweekly fluctuation of Prostigmata during 1985,
all grasses combined . . . . . . . . . . . . . . . 48

Biweekly fluctuation of Prostigmata during 1986,
all grasses combined . . . . . . . . . . . . . . . 49

Vertical distribution of Prostigmata during 1985
and 1986, all grasses combined . . . . . . . . . . 51

Mean seasonal densities of order Prostigmata under
different grasses at each depth during 1985 . . . . 53

Mean seasonal densities of order Prostigmata under
different grasses at each depth during 1986 . . . . 54

Relative dominance (%) of heterostigmatid genera in
1985 and 1986 O O O O O O O O O O O O O O O O O O 57

X

16. Taxggngmgg spp. densities /m2 in both soil strata
under different grass covers . . . . . . . . . . . 60

17. Biweekly fluctuation of Ia;_gngmg§ spp. during 1985,
all grasses combined . . . . . . . . . . . . . 62

18. Biweekly fluctuation of Iazggngmns spp. during 1986,
all grasses combined . . . . . . . . . . . . . 63

19. Vertical distribution of Targgngmug spp. during 1985
and 1986, all grasses combined . . . . . . . . . . .64

20. Mean seasonal densities of Tagsgngmgg spp. under
different grasses at each depth during 1985 . . . . 66

21. Mean seasonal densities of Iazggngmgg spp. under
different grasses at each depth during 1986 . . . . 67

22. figkgzganig spp. densities /m2 in both soil strata
under different grass covers . . . . . . . . . . . 70

23. Biweekly fluctuation of Bakgxgania spp. during 1985,
all grasses combined . . . . . . . . . . . . . . 72

24. Biweekly fluctuation of figkgzggnia spp. during 1986,
all grasses combined . . . . . . . . . . . . . . . 73

25. Vertical distribution of Bakgzggnia spp. during 1985.
and 1986, all grasses combined . . . . . . . . . . .74

26. Mean seasonal densities of Bakgngania spp. under
different grasses at each depth during 1985 . . . . 76

27. Mean seasonal densities of Bakezdania spp. under
different grasses at each depth during 1986 . . . . .77

28. Relative dominance (%) of Eupodina genera in 1985
and 1986 O O O O O O O O O O O O O O O O O O O O O 80

29. Egpgges spp. densities /m2 in both soil strata under
different grass covers . . . . . . . . . . . . . . 82

30. Biweekly fluctuation of Eupgggg spp. during 1985, all
grasses combined . . . . . . . . . . . . . . . 84

31. Biweekly fluctuation of Enpgggg spp. during 1986, all
grasses combined . . . . . . . . . . . . . . . 85

32. Vertical distribution of Eupgggg spp. during 1985. and
1986, all grasses combined . . . . . . . . . . . . 87

xi

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

49.

Mean seasonal densities of Eupodgg spp. under
different grasses at each depth during 1985 . . . . 88

Mean seasonal densities of Egpgggg spp. under
different grasses at each depth during 1986 . . . . 89

Relative dominance (%) of selected species of Tydeidae
in 1985 and 1986 O O O O O O O O O O O O O O O O O 92

Tydgus bedfordiensis densities /m2 in both soil

strata under different grass covers . . . . . . . . 94
Biweekly fluctuation of Tygggg bggfigzdiengis during
1985, all grasses combined . . . . . . .97
Biweekly fluctuation of Iygggfi hggfigzgigngig during
1986, all grasses combined . . . . . . . .98
Vertical distribution of Tygggfi begfigzgigngig during
1985 and 1986, all grasses combined . . . . . . 99

Mean seasonal densities of Iygggg bggfgzgiengis under
different grasses at each depth during 1985 . . . .100

Mean seasonal densities of Iygegfi bggfgrgigngig under
different grasses at each depth during 1986 . . . .101

leggghippgng densities /m2 in both soil

strata under different grass covers . . . . . . . .104

Biweekly fluctuation of Meteoronematus leusohinneus

during 1985, all grasses combined . . . . . .107
Biweekly fluctuation of Metanronematus leucohinneus
during 1986, all grasses combined . . . . . .108

Vertical distribution of Meteoronematus leusohineeus
during 1985 and 1986, all grasses combined . . . . 109

Mean seasonal densities of Motocronematus leucohieeeus
under different grasses at each depth during 1985 . 110

Mean seasonal densities of Motocronematus leucohipeeus
under different grasses at each depth during 1986 . 111

Relative dominance (%) of selected species of
Mesostigmata in 1985 and 1986 . . . . . . . . . . .114

silesiaggg densities /m2 in both soil
strata under different grass covers . . . . . . . .116

xii

50.

51.

52.

53.

54.

55.

56.

57.

58.

59.

60.

Biweekly fluctuation of Bhodasarellus silesiasus

during 1985, all grasses combined . . . . . .119
Biweekly fluctuation of Bhodagarelluslsilesiagus
during 1986, all grasses combined . . . . . .120

Vertical distribution of Rhodagarellus silesiacus
during 1985 and 1986, all grasses combined . . . . 121

Mean seasonal densities of Bhodagazgllug gilggiagug
under different grasses at each depth during 1985 . 123

Mean seasonal densities of Bhodagazellug gilgsiagug
under different grasses at each depth during 1986 . 124

aguleifg: densities /m2 in both soil strata

under different grass covers . . . . . . . . . . . 127
Biweekly fluctuation of fiypgaspis aggleifig: during
1985, all grasses combined . . . . . 129
Biweekly fluctuation of fiypgaspig aggleifg; during
1986, all grasses combined . . . . . . 130
Vertical distribution of fiypggfinig agnleifg; during
1985 and 1986, all grasses combined . . . . . .131

Mean seasonal densities of fiypgaspig agglgifig; under
different grasses at each depth during 1985 . . . . 133

Mean seasonal densities of flypgggpifi agglgifig; under
different grasses at each depth during 1986 . . . . 134

xiii

I . INTRODUCTION

The edaphic ecosystem is profoundly marked by a great
number of dependent interrelations. we are constantly
confronted with many functional relationships that mites
share with other organisms. Therefore, the study of soil
mites must fundamentally be an ecological one. Soil mites
have wide spatial and temporal distributions, great species
diversity, and narrow ecological sensitivity making them a

prime candidate for ecological studies.

Turfgrass is a complex system consisting of roots,
stems, and leaves of grass plants together with a tightly
intermingled. layer' of'ldead and. living roots, stems and
organic debris commonly called thatch. This habitat
supports a diverse assemblage of invertebrates (Streu, 1973:
Cockfield. and Potter 1983). ' Taxa that are present in
turfgrass include Annelida, Nematoda, Diplopoda, Protura,
Acarina and Collembola: they are considered important to
plant-litter decomposition and nutrient recycling in soil
communities. These animals aid the decomposition process by
fragmenting and conditioning plant debris in their guts
before further breakdown by microflora (Lofty, 1974:

Wallwork, 1983). They are also responsible for disseminating
1

bacteria and fungi, enriching the soil and mixing organic

materials into the soil while migrating vertically.

Distribution and abundance of soil animals are
determined by a large number of factors, among the abiotic
factors, soil moisture, temperature, pH and organic matter

are highly important (Hagvar and Abrahamsen, 1980).

From a survey of literature, it was found that little
has been done in studying population dynamics of soil
organisms inhabiting turfgrass systems. Therefore this study

was undertaken to answer the following questions:

1. What is the effect of different grass covers on the
abundance of the most dominant prostigmatid and

mesostigmatid mite species and genera?

2. What are the seasonal dynamics of selected mite
species and genera in relation to major ecological

factors?

3. What is the vertical distribution of selected mite
species and genera in relation to major ecological

factors?

II. REVIEW OF LITERATURE

1. o tt 5 la t covers on

The importance of habitat has been emphasized by
Southwood (1977). It remains as a basic step in the concrete
study of any ecosystem. However, ecosystem descriptions, as
with any system, depends on the selected space-time

resolution level.

Dillon and Gibson (1962) reported that the Isotomidae
(Collembola) and Eupodidae (Acarina) were overwhelmingly
dominant families in an old meadow. They found that an
unusual feature was the virtual absence of Oribatei, which
was possibly related to soil dryness. They also stated that
populations of both Collembola and Acarina fluctuated with
time and showed no regular seasonal rhythm and the vertical
movements of almost all species occurred from time to time
with no seasonal regularity: there was no evidence that the
changes as a whole bore any simple relationship to
fluctuation of soil temperature, moisture, pH or organic
content. They also reported that among mesostigmatid mites,

Rhodacaridae were exceptional in being most numerous.

Christiansen, in the case of Collembola, (1964) summed
up the connection with macroflora by saying that there is
generally a moderate amount of correspondence between plant
cover and collembolan association, but little evidence of
restriction of individual Collembola species to one species

of plant.

Christen (1974) ‘ stated that it is general knowledge
that numbers of soil microarthropods vary under different
types of plant cover. Pasture crops with dense root systems
generally can be expected to support larger populations than

cultivated row crops, thus reflecting root influence.

Alejnikova and Utrobina (1975) said that the variety of
soil invertebrate species increase in the same way as their
density reaching a maximum under perennial grass and in
field plantations. They also pointed out that plant cover
effects were most striking in the case of microarthropods,
in particular when they compared population density and
group composition in four crop rotations. Depending on plant
cover, dominance of individual species also changed. The
authors suggested that, since plant cover greatly affected
soil animal population structure, man could control soil
animals and ultimately soil fertility by changing farm crop

composition.

Krivolutsky (1975) reported that oribatid mite
population density was highest in forest soils and lowest in
desert. soils. His studies suggested. that oribatid. mites

could be used as a soil type bioindicator.

Singh and Pillai (1975) studied microarthropod
population density in a wide variety of habitats and found
that Acari were the most dominant group in all habitats,
ranging from 45.5 to 71.7% of the total fauna, while
Collembola ranged from 11.9 to 41.7%. They also noticed that
Collembola and Oribatei were dominant in higher organic
matter soils, while Prostigmata predominated in soils, poor

in organic matter.

Loring et al. (1981) stated that no-till plots had
stable populations of Collembola and. Acarina ‘which
fluctuated regularly. Plowed plots exhibited a sharp
decrease in populations, followed by a sharp increase in
populations, followed by a sharp increase in populations

toward the end of the growing season.

Petersen (1982) stated that great diffrences have been
found between population fluctuations of individual acarine
orders. Thus, data compiled for Prostigmata and Astigmata
provided a number of examples of density changes, one month

with several thousands/m2 and virtual absence of members of

these taxa in another month. Contrary to this,
Cryptostigmata and Mesostigmata generally showed moderate
changes in population size. For collembola and Acari,
woodland sites showed weaker annual amplitudes in population
density than non-wooded sites. By comparing tropical and
temperate regions, he was able to say that in most cases
grassland sites in tropical regions showed higher
fluctuatios than temperate grassland sites. Observed
differences between communities were explained mainly as
diffrences in environmental stability under, the infuence of

local climate, soil properties and degree of exposure.

Whelan (1985) sampled. the herbs and soil of three
grassland sites each month for one year. The soil also was
sampled to a depth of 7.6 cm, then divided into two
subsamples of 3.8 cm each. Peak populations of Acari were
recorded in the summer months which corresponded with high
herb populations. Permanent pasture had high populations in

the soil especially in the 3.8 - 7.6 cm stratum.

Whelan (1986) then reported that populations in
herbaceous stratum, were dominated by microphytophagous and
panphytophagous species while microphytophagous and

predacious species dominated the soil populations.

Hendrix et al. (1986) suggested that the decomposition
processes of no-tillage agroecosystems were functionally
similar to those occurring in natural systems, where gradual
decay of organic matter and slow nutrient release from plant
residues is under the control of soil fauna as well as

microflora.

Curry and Mbmen (1988) studied the arthropod fauna of
managed grassland 2.5 and 6 years old; unmanaged 6 years old
grassland: and an old field margin on reclaimed cutaway
peat. They recorded 209 species or higher taxa including 5
new species. Mean collembolan population densities reached a
maximum in the 2.5 year site, while a minimum was recorded
in the old field margin. Meesostigmata dominated all
habitats except the 2.5 years-old site where Astigmata were

most abundant.

Sheals (1957) suggested that seasonal fluctuations of
soil Cryptostigmata in uncultivated grassland where caused
by movement to other habitats for reproduction. Hayes
(1963), Wood (1967) and Imxton (1972) suggested that depth
distribution of mite species may be controlled by a complex
of physiological and behavioral characteristics. Importance
of food selection and influence of relative humidity and

temperature also appeared to be considerable.

Hayes (1965) stated that all species of phthiracarid
mites occurred predominantly in litter and humus with no
real seasonal differences. Madge (1965) reported the highest
number of oribatid mites during winter (November-February)
and the lowest during late summer and fall (July-October) at

Rothamsted Experimental Station.

Fujikawa (1970) recorded the average population density
(individual no. /20cm2) of the upper 15 cm of soil over 15
sampling occasions was 13.8:6.9 in a natural Picea forest.
The most complex faunal composition was observed in the

natural mixed ferest. In most cases the population density

in the upper 5.0 cm layer of soil was significantly greater

than that in the 5-10 cm and 10-15 cm strata.

Anderson (1971) suggested that vertical distribution of
Oribatei was governed more by selection of certain food
materials and characteristics of soil horizons than by

physical characteristics of their environment.

Usher (1971) mentioned that of 22 mesostigmatid species
studied, seasonal distribution Was detected in 15 species.

Only 5 of these showed single annual maximum population

densities. The mesostigmatids Egrgamaggg lappgniggg and
Egigaia transigalag were autumn species, since their maximum

population size was recorded during September, October and
November. W sp. was a winter species with maximum
population during January and February. Argtgseigg
man: and W m were summer species. He
also observed that, among mesostigmatid populations, there
was no intense vertical stratification during periods of
suitable climatic conditions. However, when climatic factors
became less suitable: the animals migrated, downwards,

establishing a more defined vertical stratification.

Wallwork (1972), in his study of distribution patterns
and population dynamics of microarthropods in juniper litter
and underlying mineral soil, pointed out that peak densities

10

occurred in April and December. The December peak was
produced mainly by population increases in mineral soil,
whereas the April peak reflected population increases in

litter.

Price (1973) reported prostigmatid adaptations to xeric
conditions, and cautioned against shallow sampling which can
result in substantial underestimates of total soil
microarthropod populations. Fujikawa (1974) compared
oribatid faunas from different microhabitats in a forest
floor. He found that each stratum contained a particular
fauna, and the number of individuals as well as species of
oribatid mites in litter stratum was comparable to that

observed in soil strata.

Pande and Berthet (1975) found no statistically
significant correlation between species size and their depth
penetration, although it remains generally true that larger
species dominate the surface layers of soil (Stepanich

1975).

Aitchison (1979) investigated snow cover effects in
southern Manitoba, and found that the families Eupodidae,
Rhagidiidae and Parasitidae were some of the most abundant
winter-active groups. She also found no correlation between

number of trapped mites and below-snow temperature.

11

Zacharda (1979a.) stated that some rhagidiids were
polyvoltine and.that the occurrence of their developmental
stages was season-independent. On the other hand some
species were monovoltine with strictly season-dependent life
cycles: adults of species inhabiting dry habitats, e.g.,
xerotherm grassy steppes and rocky dry steppes, occured
predominantly in winter and disappeared during spring and

summer .

Holt (1981) suggested that vertical distribution of
adult Cryptostigmata was highly correlated with percent
organic matter, and distribution of larger individuals
appeared not to be influenced by pore size or total soil
porosity. Distribution of numerous smaller Cryptostigmata
appeared to be influenced by availability of smaller soil

pores.

Salem ( 1981) recorded monthly fluctuations in
population densities of tarsonemid mite species in relation
to soil temperature and moisture in Egypt. He reported that
the highest population densities of Acarina groups occurred

in spring and fall.

Darlong and Alfred. (1982) found a general trend for

mean total populations of soil arthropods to increase in

12

both forest and Jhum sites with the advent of the warm and
rainy season. This decreased with the advent of the dry and
cold season. He also saw seasonal variations among different
soil arthropod groups which may have been due to vertical

movements.

Leetham and Milchunas (1985) suggested that composition
and distribution of soil microarthropods on the semiarid
shortgrass steppe was a function of tradeoffs between
resource availability and environmental benignity mediated
through body size constraints on the ability to withstand

cycles of anhydrobiosis.

13

3. 7‘ = O ‘ e 0‘ -. o. o : or ‘9, -. 0.0-!

According to Andrewartha and Birch (1954) population
size is determined by four components of the environment:
weather, food, other animals and pathogens, and locus.
Individual importance of these components may vary between
different populations in different habitats. For terrestrial
animals, variation of specific physical conditions (climate)
greatly influences all parameters of population growth. The
combination of soil moisture and temperature is' the most

important factor for soil animals.

Many studies have demonstrated that soil arthropods are
non- randomly distributed. The following is a review of the

factors causing this non-randomness.

Loots and Ryke (1967) obtained a highly significant
correlation value of 0.90 between the ratio of Oribatei:
Trombidiformes and the percentage of organic matter in
different soils. Oribatei dominated in soils with high
organic matter, whereas Trombidiformes were more abundant in
soils with low percentage of organic materials. They
suggested that small species of trombidiforms might feed on
protozoa and bacteria which are present in small pore

spaces.

14

Bursell (1970) found that moisture deficiency could be
an important mortality factor. Mukharji and Singh ( 1970)
stated that there was a direct correlation between soil
moisture content, temperature and arthropod population
dynamics. They concluded that as soil moisture increased,
arthropod. populations simultaneously increased and vice-

versa .

Butcher et al. (1971) summarized that the majority of
Collembola and Cryptostigmata studies reviewed, reported an
aggregated distribution of individuals within the three
dimensional environment of the soil. They concluded that
aggregation tendencies could be attributed to "water,
temperature, time of day, microclimate, season, food source,
microflora, vegetation, etc....." and that the reliability
of estimating each of these influences depended in part upon
the extent to which individual investigator, sought to

document their speculations, inferences or conclusions.

Chernova et al. (1971) in Russia found that both
numbers and biomass of micro-arthropods increased with a
rise in organic matter content. Edwards and Lofty (1971) in
England reported that some soil-inhabiting invertebrates
survived extreme heat or cold in an active phase. But this
was unusual, more often they became inactive and aestivated,

coincident with adverse periods, or survived as eggs or

15

pupae. Some species avoided extreme temperatures at the soil
surface by moving down into soil strata where temperatures
were less extreme and much more stable until the surface

again became acceptable.

The same authors also commented that changes in
temperature can influence numbers of soil-inhabiting
invertebrates not only directly, but also indirectly by
changing the moisture content of soil. Most dry soils have a
specific heat of only about 0.2 cal./g so that they warm up
rapidly when exposed to the sun. Increasing their moisture
content increased thermal capacity, and warming up took
place less rapidly. Wet soils also had a greater thermal
conductivity than dry soils so that temperature gradients in
them were less than those in dry soils. All these factors
may influence the effects of extreme temperature on

invertebrates in soils.

Metz (1971) reported that substrate moisture content
determines, to a large degree, number of micro-arthropods.
On several occasions, his litter samples from Loblolly pine

forest floors after several weeks of drought yielded very

16

few mites: 2 days after wetting a square meter of the floor
with 20 liters of water, from 5 to 10 times more mites were

recovered.

The same author described a laboratory experiment to
determine survival and movement of mites under different
moisture regimes. Groups of mites, including seven species
of Oribatei, were shown to move between mineral soil and
organic layers as moisture conditions changed. Mesostigmata
had a better survival rate than either Oribatei or

Trombidiformes.

Usher (1975) demonstrated a relationship between
numbers of arthropods and soil moisture or soil temperature,
while Plowman (1979) was unable to find any such
relationships. The former author (1976) indicated that
patchy distribution of either food or soil water was the

most likely cause of soil arthropod aggregations.

Wallwork (1976) suggested that correlation between
environmental factors and species assemblages were of
limited value because a complexity of environmental factors
acted upon the species and because of different

physiological tolerances of different species.

17

Mitchell (1979) pointed out that a forest soil was a
mosaic of biotic and abiotic components, arranged
differentially with respect to horizontal and vertical
distribution and 'temporal patterns. Of’ the abiotic
parameters, temperature and moisture seemed especially
critical in affecting physiological activity and
distribution of oribatids. Depth was a complex variable
linked with a number of components, all of which may affect
both inter-and intra- specific oribatid distribution. Food
was probably the most important factor affecting the biology
of oribatids. The distribution and population dynamics of
microphytophages may be directly related to availability of

microbial food resources.

Regniere (1980) said. that soil insects ‘were highly
dependent on soil moisture which had direct effects on egg

development and hatching.

Joosse (1981) stated that population changes of some
collembolan species were infuenced by an interacting complex
of biotic and physical factors, which varied according to

environmental favourability.

Luxton (1981) concluded that environmental variables
such as precipitation and litter fall may exert important

short-term infuences on some populations, and that the same

18

species in different environments may not always be

confidently compared to a single phenological pattern.

Whitford et al. (1981) have shown that in desert
ecosystems, mites, Collembola and nematodes all reacted,
very quickly to simulated rainfall, increasing significantly

in litter within an hour after it was moistened.

Petersen (1982) reported a high proportion of
prostigmata and a relatively low ratio of Collembola to
total Acarina in shortgrass steppe. He attributed this to a
negative correlation between acarine density and soil
moisture, and a positive correlation between collembolan

density, soil moisture and organic matter.

Boyne and Rain (1983) studied the development and
fecundity of Nggggiulgg .fallagig under various relative
humidity levels and found them similar for all relative
humidity ranges tested, except at the lowest range (60-65%).

There none of the individuals survived to maturity.

Mitra et al. (1983) stated that in grassy plots, higher
temperature and Run. resulted in an increase in number of
Collembola, while lower temperature and R.H. were preferred

by Acarina.

Hagvar (1984) studied "6 common mite species in

Norwegian coniferous forest soils." He found that the

19

abundance of these species in different soils was related to
a number of soil chemical factors. Their occurrence was also
related to soil and humus types, plant communities and soil

fertility.

III. MATERIALS AND METHODS

1. ' es ' t' n:

This study was conducted at the Hancock Turfgrass
Research Center, located on the campus of Michigan State
University. To study the effects of turfgrass types on the
bionomics of soil acarina, 6 grasses were seeded into plots

during 1982, and are listed in Table 1.

Table 1: List of turfgrass species in the study area

 

 

Common Name Scientific Name
Smooth bromegrass Bromus inermis
Kentucky bluegrass .293 protengis
Orchardgrass Qagtylis glgmezata
Timothy mm matches

Tall fescue Egstuga armadinageae
Redtop Agrgstis alba

 

The turf blocks measured 8.2 m by 9.1 m with the long
axis running north to south (Figure 1). All blocks were

mowed at a height of 10.2 cm on 8 May, 1983 and 10 May 1984

20

21

osomou name

mmoumcuenouo

 

 

asuoaaa

 

-neumosnn axosuso.

 

sample blocks and their different

Diagram of the 6
grass covers.

Figure 1.

22

and were then kept without any treatment until sampling

began in 1985.
2. Bescrietion_2f_grassplant_soxers
A. Smooth bromegrass (firgmgg ingzmis)

Forms an upright, coarse textured turf which spreads
vegetatively by vigorous, fleshy rhizomes that fomm a firm

sod. Root system extensive.

B Kentucky bluegrass (29a protengig)

Forms a medium textured, green to dark turf of good
shoot. density. The extensive root system in concentrated
primarily in the upper 15-25 cm of the soil profile, some
roots may penetrate to depths of 40 to 60 cm under mowed

conditions. Root system persists as a perennial.

C- Orchardgrass (Bactylis.glomerata)

The texture of this grass is quite coarse with leaves
folded in the bud shoot and sheaths distinctly compressed.
It forms an open sod of low shoot density. Orchardgrass is
basically a bunch-type grass since it has neither rhizomes
nor stolons. Orchardgrass has rapid early spring growth, its
drought tolerance is greater than that of timothy but not as

good as that of smooth bromegrass.

23

0. Timothy (Ehleum snatches)

This grass tend to behave as a bunch type with poor sod
forming qualities. Leaves frequently have a grayish-green
appearance. The root system is shallow, fibrous and replaced

annually.

E. Tall fescue (fiestas; arundinaseae)

Forms a turf of very low shoot density and has dark
green leaves. The root system. is extensive, coarse and

deeper than most cool season turf grass.

r. Redtop (Agnostic alba)

Forms a stemmy, coarse textured, open turf of low shoot

density. The root system is regenerated annually.

3. Soil_Analysis:

After Tullgren extraction of arthropods, the first 36
soil samples obtained from the study site were composited,
passed through a 2-mm sieve and subsampled. Soil pH, K, Ca,
Mg, and P were determined according to routine methods of
the Soil Testing Laboratory of Michigan State University.
Soil pH was determined in 1:1 water suspension, using a
Beckman zeromatic glass electrode pH meter. Phosphorus was

extracted with Bray p-1 reagent using a 1:8 soil to solution

24

ratio: available K, Ca, and Hg with 1-0 N NH4 OAC (pH 7.0)

using 1:8 soil to solution ratio.

The study area's soil type is fine loamy, mixed, Mesic
Aeric Ochraquairs (formerly Capac Sandy Clay Loam). The soil
texture is classified as sandy clay loam, with pH of 7.3.
Soil chemical test results for available nutrients were as
follows:

available P = 173 lb/A

exchangeable K = 280 lb/A

available Ca

4480 lb/A

available Mg 547 lb/A

Soil organic matter contents also were determined
according to routine methods of the Soil Testing Laboratory

of Michigan State University as follows:

Reagents:
1. 0.5 M NaZCrZO7: Dissolve 149 g of NaZCr207 2 H20 in water
and dilute to 1 liter.

2. H2504, concentrated, 96%.

Procedure:

1. Using an NCR-13 1-g scoop, scoop 1 g of soil into a 50-mL
Erlenmeyer flask, using standard scooping techniques.

2. Add 10 mL of NaZCr207 solution by means of dispenser.

3. Add 10 mL of concentrated sulfuric acid, using a suitable

dispenser. A supply of 2% NaHCO3 should be readily

5.

6.

25

available to nutralize spilled acid on skin, clothing, or
lab bench.

Allow to react for 30 minutes.

Dilute with 15 mL of water and mix.

Allow to stand three hours or overnight.

Transfer 10 mL (or other suitable volume) of clear
supernatant into a colorimeter tube. This can be

accomplished conviniently by use of a pipette bank set to

dip a suitable distance into the supernatant solution.

Care must be taken not to disturb the sediment on the

bottom of the flask.

The blue color intensity of the supernatant is read on a

colorimeter at 645 nm, with the reagent blank set to give
100% transmittance (or 0 absorbance). The instrument is

calibrated to read percent organic matter (or tons per

acre) from a standard curve prepared from soils of known

organic matter content.

Soil organic matter averaged between 3.2% and 3.7%

(Table 2), indicating good uniformity among turf blocks.

26

Table 2: Average percent of soil organic matter under
different grasses.

 

Grasses % of Organic matter % of organic matter
0-15 cm stratum 15-30 cm stratum
Smooth bromegrass 3.4 3.2
Kentucky bluegrass 3.2 3.3
Orchardgrass 3.6 3.7
Timothy 3.6 3.7
Tall fescue 3.3 3.5
Redtop 3.6 3.6

4. W:

A Yellow Springs telethermometer with a 12 cm probe was
used to record soil temperature after allowing it to
equilibrate in the soil for at least 1/2 hour. Temperature
was measured at two depths: 7.5 cm and 23.5 cm on each

sampling date under each grass.

5. W:

On each biweekly sampling date, 1 sample from each
depth layer under each grass was placed in tightly covered
containers, 6.5 cm high by 9 cm diameter: samples were

weighed wet, oven-dried at 60°C oven for one week or until

27

no further weight loss occurred, and re-weighed. Percent

soil moisture was obtained by using the following equation:

% soil moisture 100[(wet weight-dry weight)/ dry weight].

6. 23212113111211:

Precipitation data were obtained from the U. S.
National Weather Service, South Farm Station, which is very

close to the study area.

7. Sa pling and extraction methods:

Three replicate samples per date, cut in half to
provide subsamples of the upper and lower profile (0 - 15
and 16 - 30 cm) were taken from each turf block using a
metal coring device with a diameter of 6 cm and a height of
15 cm with a tapered interior edge to relieve compression of
the core (Figure 2). Thirty-six samples were thus taken on a
biweekly schedule from April 15 to December 1, 1985 and from
April 1 until December 1, 1986. Samples were sealed in
plastic bags and were transported in an ice chest to prevent

temperature-induced mortality before extraction.

Extraction was initiated less than one hour after
collection by using Tullgren funnels. To provide heat, each
funnel had a 25-watt light bulb connected to a rheostat. A
labelled vial with a solution of 1% glycerin in 95% ethanol

was placed beneath each funnel. Soil cores were extracted

28

 

 

 

 

 

 

 

 

 

: 40.56!!! . -. _
Q 1
20cm
J—H it
22:03
*S'cmr' it

Figure 2. Diagram of soil core device.

29

for 72 hours, heat intensity being gradually increased to

maximum during this time.

Collected animals were initially separated into
collembolan families, mite orders, spiders, centipedes,
millipedes and other arthropods. Two orders of mites,
Mesostigmata and Prostigmata, were separated and mounted on
slides for further identification to genus and species

levels.

8. W:

All specimens of the orders Mesostigmata and
Prostigmata were mounted for further identification as

follows:

1. Clearing in a solution of 10% KOH for 10 minutes.

2. Washing in distilled water for 5 minutes.

3. Mounting in a drop of Hoyer’s media on a glass slide,
straightening the specimens’ appendages, then covering them
with coverslips of size 00.

4. Heating in a 50°C oven overnight, then ringing the covers
with nail polish for a permanent seal. The collections were
deposited at the laboratory of Invertebrate Zoology,

Michigan State University.

3o
9. Wis:

Split-plot analysis of variance was used to test the
effects of the three main factors included in this study:
grass type, biweekly sampling dates (season) and profile

depth, along with their interactions.

Tukey’s Test was used for comparison among means
whenever significant differences occurred. Correlation
analysis and multiple regression were used to study
relationships among population density, % soil moisture and
soil temperature. ANOVA tables of split-plot and multiple
regression analysis, and results of simple correlations, are

given in appendices.

IV. RESULTS AND DISCUSSION

1. W
1.1. W

Since temperature did not differ significantly with
grass type, the data presented in Tables 3 and 4 are
averages for each depth and date of 1985 and 1986. However,
soil temperatures were significantly different among
sampling dates ( two-way analysis of variance ). In 1985,
the highest temperatures were recorded on July 1, July 15
and Aug 1, at approximately 27°C for the 0 - 15 cm stratum
(Figure 3), and at slightly over 25°C for the 16 - 30 cm
stratum. Soil temperature started to decrease beginning
October 1, 1985, with only 1°C being recorded on December 1

(Figure 4).

In 1986, the highest recorded soil temperature occurred
on July 15, with an average of approximately 28°C in the
upper soil stratum, while it was slightly over 25°C in the
16 - 30 cm stratum. Temperature began decreasing in early
October until it dropped to less than 1°C in November and

December (Figures 5 and 6).

31

32

 

 

 

 

Table 3: Average recorded soil temperature ('C) and
moisture during 1985.
==-Li 0 - 15 cm #74:; 16 - 30 cm
Moisture Temp 'C Moisture Temp 'C

Dates Mean SD Mean SD Mean SD Mean SD
Aprl 1 --- --- --- --- --- --- --- ---
Aprl 15 15.9 $1.7 12.0 $0.5 17.7 $1.0 8.5 $0.4
May 1 16.0 $1.7 12.9 $0.4 13.3 $1.1 11.8 $0.4
May 15 13.8 $1.6 16.3 $0.8 11.3 $1.0 13.6 $0.5
June 1 10.6 $1.2 16.7 $0.6 9.6 $1.3 14.0 $0.5
June 15 13.8 $1.8 17.3 $0.4 10.8 $1.0 15.7 $0.5
July 1 6.4 $1.1 26.3 $0.5 8.0 $1.1 22.9 $0.3
July 15 11.2 $1.4 26.5 $0.3 7.0 $1.4 25.3 $0.3
Aug 1 6.5 $1.1 26.3 $0.4 5.4 $1.0 23.6 $0.3
Aug 15 11.2 $1.1 21.6 $0.4 9.8 $1.2 18.3 $0.2
Sept 1 14.2 $1.4 25.4 $0.3 13.7 $1.4 21.7 $0.6
Sept 15 10.2 $0.9 19.5 $0.5 10.7 $1.4 17.9 $0.3
Oct 1 15.1 $0.7 11.2 $0.3 12.9 $0.8 10.1. $0.1
Oct 15 12.8 11.0 12.2 10.2 12.2 20.9 11.1' 10.1
NOV 1 16.6 $0.4 11.3 $0.3 15.6 $1.1 10.1 $0.2
NOV 15 16.2 $1.3 12.1 $0.3 14.4 $1.1 10.2 $0.2
Dec 1 16.9 $3.1 0.9 $0.1 14.8 $2.4 2.2 $0.1

 

Each mean derived from 6 measurements/date.

 

 

33

°/o Moisture and Temperature C
1st depth 1985

 

 

 

 

 

 

 

 

 

 

 

 

Moisture % Temperature C
20 30

............ '1 ................. / \¥/\ - /\/
\ 11/ A\ /\/ .............. -20
10 J VAV \A/t
. I ' \ '10

5 .....

............................................................ ....5
0 I I I I I F F T I I I I I r I PO

A A M M J .1 J J A A S S 0 O N N D

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

5 5 5 5 5 5 5 5
date

—— 96 Moisture —+— Temperature C

Figure 3. Average recorded soil temperature and moisture of the
0 - 15 cm stratum during 1985.

34

°/o Moisture and Temperature C
2nd depth 1985

Moisture % Temperature C
18 30

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

—— % Moisture —*— Temperature C

Figure 4. Average recorded soil temperature and moisture of the
16 - 30 cm stratum during 1985.

Table 4: Average recorded soil temperature (°C) and
moisture during 1986.

 

 

 

 

 

0 - 15 cm 16 - 30 cm
Moisture Temp 'C Moisture Temp 'C
Dates Mean SE Mean SE Mean SE Mean SE
m =— I
Aprl 1 15.9 $1.4 11.7 $0.2 14.8 $0.9 8.2 $0.2
Aprl 15 15.7 $1.4 13.4 $0.2 13.7 $1.4 12.4 $0.5

May 1 12.7 $1.6 11.5 $0.5 11.3 $1.4 9.6 $0.5

May 15 16.7 $1.9 19.8 $0.3 14.5 $1.6 17.3 $0.3
June 1 9.2 $1.6 20.4 $0.2 11.5 $1.5 18.4 $0.3
June 15 14.2 $1.3 20.6 $0.3 14.1 $0.8 19.4 $0.1
July 1 12.7 $1.0 19.6 $0.2 14.3 $0.7 18.6 $0.1
July 15 13.4 $1.0 27.6 $0.3 14.5 $0.3 25.3 $0.3
Aug 1 13.4 $2.0 22.7 $0.3 11.7 $1.7 21.2 $0.2
Aug 15 12.6 $1.8 23.3 $0.4 11.0 $1.5 22.0 $0.3

'Sept 1 15.9' 12.2 18.6 10.1 13.7 :1.7 17.5 30.1

Sept 15 16.9 $1.8 17.1 $0.4 15.3 $1.0 15.5 $0.1

Oct 1 21.0 $2.5 13.5 $0.8 17.8 $1.2 14.0 $0.6
Oct 15 16.5 $0.8 10.1 $0.4 15.2 $1.0 9.1 $0.2
Nov 1 19.4 $1.1 9.0 $0.8 15.4 $0.5 9.0 $0.3
NOV 15 15.4 $1.1 1.0 $0.2 14.1 $0.7 1.6 $0.3

Dec 1 17.5 $2.1 1.4 $0.2 16.1 $1.7 2.3 $0.2

 

36

% Moisture and Temperature C
131 depth 1986

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Moisture 16 Temperature C
25 30
/\ 22
20 /[ \\/\ / \
......... ._44—‘4\\\F , L120
,2 fivfl >(
//\\/W \\
101/‘\\(_ V
-10
5“ 1.5
0 I I I I I i I I T I I 0
A A M M J J J'J A A S S D
1 1 1 1 1 1 1 1 1 1 1 1 1
5 5 5 5 5 5
depth

— 16 Moisture —+— Temperature C

Figure 5. Average recorded soil temperature and moisture of the
0 - 15 cm stratum during 1986.

37

% Moisture and Temperature C
2nd depth 1986

 

 

  
 
 
  

 

 

 

Moisture 16 Temperature C
20 30
i /\ .................. _ 25
/\ / \A J
- 20
- 15

 

.......................................................

 

..............................

 

 

 

 

0 I I I I j I I I I I I T I II 0
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date
— 96 Moisture —i— Temperature C
Figure 6.

Average recorded soil temperature and moisture of the
16 - 30 cm stratum during 1986.

38

1.2. 5.911.821.5521:

Percent soil moisture under different grass covers for
the two depth strata is given in Table 3 and 4. Since
statistical analysis ( two-way analysis of variance )
revealed no differences among grass blocks, but soil
moistures differed with sampling dates, data presented in
Figures 3, 4, 5, and 6 are averages derived from all

grasses in 1985 and 1986.

In 1985, the driest period occurred between July 1 and
August 15 at both depths. Percent soil moisture ranged from
4.1% to 22.2% in 1985, while in 1986 it ranged from 9.1% to

24.4%. Overall, 1985 was drier than 1986.

1.3. W

Rainfall is presented. as totals for the: two weeks
preceding sampling dates (Figure 7). In 1985 the periods of
April 16 to May 1 and June 16 to July 1 were drier than in
1986, with precipitation ‘totalling 0.48 cm, and 0.58 cm
respectively. In general, lower rainfall resulted in lower
soil moisture at all depths in 1985 (Figures 3 - 6). The
driest period in 1986 occurred between October 16 and

November 1, with 0.8 cm rainfall.

39

20
15

 

w 5
Eu 20.

02
3:5

fly :5

.2. 1
633

0
4|

5.

.u mO— |>OZ£
.>OZm—I .>ozm
..z.ipr_
HUD m-iw UO~
HUO pimmmwp
.me 91¢me
mum 702m—
.OD< 9.09%
86. —i..5_..w—
15.. 91.52
JDH 7233.
233—1232
231229
>32 m_l><2~
>42 Wanda—
.m n2»... Tam/R
.. . . 74.37%.

\J‘“

nu

Amount of precipitation received in the study area

during 1985 and 1986.

Figure 7.

40

The four orders of Acarina, Prostigmata, Mesostigmata,
Cryptostigmata and Astigmata, occurred under all six species
of grasses at Hancock Turfgrass Research Center. The
relative numerical distribution among these mite orders
(Table 5 and Figure 8) in 1985 and 1986 revealed that
Prostigmata were the most dominant, followed by
Mesostigmata; Cryptostigmata ranked third and Astigmata were
the least dominant in both years. It is also clear (Table 5)
that the density of Acarina in 1986 was doubled over 1985:
this may be related to the fact that 1985 was hotter and

drier than 1986.

8W

Prostigmatid mites were the most prevalent group
present under turfgrass in the study area. Within this order
in which basic body morphology is subject to diverse
modifications, four suborders (cohorts) were recorded. The
suborder Heterostigmata was most dominant, followed by
Eupodina; Endeostigmata and Raphignathae were found in very

low numbers.

41

Table 5. Relative dominance of Acarina orders in 1985 and

1986.
1985 1986

Mite orders N % N %
Prostigmata 4006 63.8 11456 83.0
Mesostigmata 1690 26.9 1201 8.9
Cryptostigmata 498 7.9 798 5.9
Astigmata 88 1.4 83 2.2
Total 6282 13478

N = the total number of specimens obtained per year.

42

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©®®— mmwmfl

89:950on @om 55:950on

         

mm
05 30 MW w

azm< 72...,

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$589691

 

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Split-plot analysis of variance of prostigmatid counts
revealed no significant differences (p > 0.25) between
grasses in 1985 (Table 6 and Figure 9). For 1986, analysis
showed very marginal differences (p < 0.25) between grasses
in accommodating prostigmatid populations. For both strata
combined, smooth bromegrass harbored the highest numbers of
Prostigmata (28100/m2), followed by Kentucky bluegrass
(24650/m2); the extensive root system and vigorous fleshy
rhizomes of these two grasses may provide rich habitats for
prostigmatid populations. Tall fescue harbored the lowest
population (10450/m2); this grass also has an extensive root
system, but it can penetrate to depths below 40 cm: the
rhizosphere. of tall fescue may' therefore not. have been

completely sampled in this study.

3.2. 3 W“. ‘2 --. 01‘ e 92- °Il!-.,,°_ .009- '_ '1‘

Date effects were significant at p <0.001 in both years
(App. B). Although overall numbers of prostigmatids were
more than doubled in the second year of the study, seasonal
abundance patterns of 1985 (Figure 10) were repeated in 1986
_(Figure 11) . Density maxima occurred in July and October,
followed by population declines in late fall. Increased
rainfall in 1986 seems to have been a contributing factor

toward larger populations in July of that year; its effect

44

Table 6: Population densities $SE/mz of Prostigmata

in each soil stratum under different grasses.

 

 

 

 

 

1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm

Grasses Mean SE Mean SE Mean SE Mean SE

==s 2.====.=.======._..==_. 4-

Sm. bg 4900 $700 3700 $1050 8800 $1550 19300 $8950
Ky. bg 4350 $700 2750 $ 450 16750 $8650 7900 $1150
Ordgrs 5050 $800 1750 $ 350 5650 $ 800 7450 $1800
Timthy 3550 $500 1950 $ 300 8450 $1200 8200 $1600
Tl Fse 4400 $950 2350 $ 450 4950 $ 900 5500 $1300
Redtop 4250 $700 2800 $ 550 9750 $2550 9600 $2700

 

N = 48 for 1985, 51 for 1986

  
 

45

Order Prostigmata
1985

 

- 0-15 cm
\\\\‘ 16-30 cm

 

Grass Species

 

 

 

 

1986
Density (Thousands)
20
1 - o-15 cm
15-30 cm
16 ................
10 . ............................
5 . .....

 

 

0..
arms. K. B. Orch. Tim. T. F. M19
Grass Species

Figure 9. Prostigmata densiti 2 ' -
. es /m in both soil str
different grass covers. ata under

46

was then amplified in a second wave of reproduction which
led to an all-time population peak of 87700/m2 on October 1

(Figure 11).

8.3. W:

Using lumped data from all grasses, split-plot analysis
of variance (App. B) showed highly significant depth effects
for prostigmatid populations in 1985 (p < 0.001). On all
sampling dates, Prostigmata were more numerous in the 0 - 15
cm stratum than in the 16 - 30 cm layer (Table 7, Figure
12) . As previously mentioned, precipitation was low
throughout 1985 and did not penetrate deeply, as evidenced
by low soil moisture (Table 3). Higher moisture in the upper
stratum, and its potential effect on the mites' food sources
(fungi and bacteria), were probably the main driving

variable for prostigmatid distribution.

For 1986, statistical analysis (App. 8) showed no
significant difference between depths. Prostigmatids
occurred in almost equal densities in both strata.
Occasionally, populations were higher in the 16 - 30 cm
stratum, on dates when soil temperatures were high (Table 7
and Figure 12) . Higher precipitation in 1986, penetrating
deeply through both sampled strata, apparently resulted in

relatively even mite distribution.

Table 7: Mean seasonal density /m2

47

$SE of Prostigmata in

 

 

 

 

upper and lower soil strata; data from all
grasses lumped.

===l 1985 1986

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean ' SE
Aprl 1 --- --- -7- --- 10100 $ 3650 8000 $ 2400
Aprl 15 4550 $1350 2650 $ 750 2600 $ 700 2700 $ 1000
May 1 3250 $ 750 1950 $ 550 2600 $ 500 1650 $ 350
May 15 4600 $ 900 1600 $ 500 2650 $ 900 1250 $ 450
June 1 5250 $1050 2450 $ 750 4400 $ 1100 3900 $ 1100
June 15. 5050 $1150 2550 $ 750 9950 $ 1700 17050 $ 3200
July 1 8850 $1700 4350 $ 950 8200 $ 2000 9900 $ 2550
July 15 5850 $1400 3300 $1000 21550 $ 5450 25000 $ 3000
Aug 1 3600 $ 750 1400 $ 250 13700 $ 2050 14000 $ 3450
Aug 15 3450 $1300 1600 $ 500 10450 $ 1850 10150 $ 2450
Sept 1 2050 $1000 1650 $ 450 4350 $ 1250 5050 $ 900
Sept 15 2700 $ 700 900 $ 200 10350 $ 1350 6650 $ 1400
Oct 1, 6050 $ 950 4000 $ 950 37350 $24400 50350 $24950
Oct 15 5700 $2100 5200 $2500 - 5800 $ 1500 4550 $ 1100
Nov 1 3200 $ 950 2600 $ 800 5050 $ 1400 2050 $ 250
Nov 15 3400 $ 650 3150 $ 900 2800 $ 600 1350 $ 350
Dec 1 3400 $ 900 1200 $ 500 2100 $ 800 750 $ 150

 

N = 18 per date and depth

 

 

48

Order Prostigmata
1985

density (thousands)

 

‘14

3:- ________ /\
H

 

 

 

 

 

 

4 H
2 ...............................
OIIIIIFIIfiIITIII
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date

Figure 10' Biwa9kly fluctua
tion of Pro
grasses combined. Stigmata during 1985' all

49

Order Prostigmata
1986

density (thousands)

 

100

80 _ ....................... . .........................................

 

60

........... . 7:
20 A22

 

 

 

 

-‘J>
cn-43» 4
.13: m
Ch-‘i: 5
.1t. d
-Ac.

 

(”=1‘_ -
0.4:. A

date

Figure 11. Biweekly fluctuation of Prosti

gmata during 1986, all
grasses combined. “

50

No correlation between abundance and temperature could
be obtained for either depth and either year; i.e., large
populations during hot as well as cool seasons (Figures 10
and 11) were most likely the result of inherent reproductive

patterns, irrespective of temperature.

For the 0-15 cm stratum, but not for the lower layer,
positive correlations to soil moisture existed in both
years. Together with the between-year differences discussed
above (upper stratum preferred by Prostigmata in 1985, when
rain did not penetrate deeply), this indicates that moisture

was a significant determinant of vertical distribution.

With respect to potential effects of grass types,
split-plot analysis of variance showed significant
interaction among grass types, sampling dates and depths in
both years. Grass-specific population means for each date
and depth were then compared ( App. A) using Tukey’s 95%
MSD. For 1985, mean abundance of Prostigmata under
orchardgrass in the upper soil stratum on July 1 was
significantly different only from that under smooth
bromegrass. On October 15, mite density under tall fescue
was higher than under all other grasses (Figure 13). In the
lower soil stratum during 1985, there were no differences
between population densities under the six grasses, with one

exception: on October 15, mean density under smooth

51

OnhrPnuMumns
«nus

 

“NM

 

I“- mas-Ce-

 

 

‘~“.
V““~.‘t‘.

o \~“~‘~
‘\r‘.‘~“““‘~
““““‘~

0“

" .‘“\

. V“\

m i V“:‘““\

, V““.‘““|
l1 ‘-‘~“
V““~\

“ “‘L

““‘\

on... It s - e e

u r .‘-“\0

 

d d
3 o

‘ ‘ pone.

0'
“I.
"1-
o...
0‘
.7.
.1-
A1...
A1.
Iv“
Ive-
J1.
Ice-
“a...
u.-
‘1.
A'

“MR

 

dell-m W)

unman—

-o-Ce-

 

 

 

 

 

 

 

 

 

 

Vertical distribution of Prostigmata during 1985 and

1986» all grasses combined.

Figure 12.

52

bromegrass was significantly higher than all other recorded

densities (App. A and Figure 13).

In 1986, the only differences among densities occurred on
October 1, when Prostigmata were significantly more numerous
under Kentucky bluegrass (0 - 15 cm layer, Figure 14). In
the lower stratum on the same date, mean population density
was much higher under smooth bromegrass than under all other

grasses (App. A and Figure 14).

53

Order Prostigmata
1985 0-15 cm

density (x500)

   

36
30
26
20
‘5 .. . . .. . . Mine
10 :2 g; 2;”: , i2: 1.1.?
5 :-: :-; :- '- :- . -:- -; -: -: '-: .. '- '-
0
AAMMJJJJAAOSOONND
13131113131313.1111
date
1985 16-30 cm
density (x500)

 

 

 

 

 

 

eeeee

     
  

 

 

 

 

$1202 _ /l
é I

Kl'w'w
AAMMJJJJAASSOONMD

 

     
   
  

 

m
...........
..........
........,...

 

I." n/I'Z /,
I: ‘a‘gi‘i';3|nga§§‘ti

-—

  
 

_lu ln'lg'lwli
i “91'“! ”fl

  
 

  
 

  

 

11111111
15151151515151.5151
date

Figure 13. Mean seasonal densities of order Prostigmata under
different grasses at each depth during 1985.

54

Order Prostigmata
1988 0-15 cm

density (x500)

   

soo
soo
zoo
zoo
15° 2. 2. Rdtop
1oo I 1:11:15.

0
A A II.‘ J J J 11 A A1331: 0 C11! N D

11111111
15151515151515151
date

1986 18-30 cm
density (x500)

 

 

 

4001

 

 

 

200“

 

 
 
 
   

— I
.222. |_1_ .14
— — — .
‘jjr fl:
2'» “MAW ~“‘ 333“": 4.5119 mum"
E51011”: luiji

  

 

A Ail! M .l J J .l A Ail! 8 €113 N I! 0

11111111
16151516151616151
data

Figure 14. Mean seasonal densities of order Prostigmata under
different grasses at each depth during 1986.

55

OW

Heterostigmata were dominant among prostigmatid mites.
The suborder was represented by nine genera, two of which
were most prevalent in both 1985 and 1986: W spp.
and W spp. Table 8 and Figure 15 show dominance
percentages of these two genera among .total Heterostigmata

in 1985 and 1986.

C.1. W3

W spp. constituted the highest proportion of
Heterostigmata (37.4% in 1985 and 71.2% in 1986), with an
approximately seven-fold increase in total numbers (Table
8). A possible cause for this increase in 1986 may have been
higher precipitation and higher soil moisture, which allowed
growth of fungal and bacterial colonies, the main food
sources of the species in this genus. Further studies

studies would be required to validate this suggestion.
C020 -I‘ '7 ’ 1“ °V’ ‘ 'l 2'! " °_ :,‘°!‘l!_‘ ‘9...-

Split-plot analysis of variance revealed very little
difference (p <0.25) among grasses in accommodating
maisonemns spp. populations in 1985. In 1986, there was no
evidence at all of differences (p >0.25) among grasses.
However, smooth bromegrass seemed to support the highest

populations in both years, with 2250/m2 and 17150/m2

56

Table 8. Relative dominance of Heterostigmata genera in
1985 and 1986.

1985 1986
Genera N % N %
Tarsonemus 891 37.4 6727 71.2
Bakerdania 395 16.6 446 4.7
Scutacarus ‘ 355 14.9 321 3.4
Other genera 743 31.1 1953 20.7
Total 2384 9447

N - the total number of specimens obtained per year.

57

, .oomu oco mama
cw ouocoo puuosafiumououoc up .«v mococfieoo o>fiuo~om .mH shaman

     

      

     

omae. . mmae
moamwwsoow Ecumenism. o wwmo o @3
oaocwwmmofo fl-w m; c a E ////4. ,2 mnemoosoow
///////2 ///////\\\\\h
moEocomzfl ego

569.038. 1

mcmEmzmotoEI

58

respectively (Table 9 and Figure 16). This may be related to
the extensive, fleshy rhizome system of this grass which

could promote fungal and bacterial colonies.

Split-plot analysis of variance, using combined data
from all grasses (App. B), showed highly significant
differences (p <0.001) among population densities on
different dates. In 1985, Tarsonemus spp. showed two
prolonged peaks, one from early June until late July. The
second peak occurred throughout October (Table 10 and Figure

17).

In 1986, Tarsonemus spp. again exhibited two peaks, on
July 15 and October 1 (Table 10 and Figure 18). The pattern

observed in 1985 was thus essentially repeated in 1986.

C.4. ‘1 e_ 9 9- on O’ a Ol‘u-‘ 9° 90!- . 01?:

Highly significant density differences (p <0.005) with
depth occurred in 1985, but not in 1986 (p >0.50) (App. B).
In 1985, Tarsonemus spp. were found in higher numbers in the
upper soil stratum throughout most dates (Table 10 and
Figure 19) possibly related to low precipitation and
insufficient penetration of water into soil. In 1986,
although depth was not a significant factor, higher

abundances were recorded for the lower soil stratum on 7 out

Table

9: Population densities $SE/m’

59
Of Tarsonemus SPP-

in each soil stratum under different grasses.

 

 

 

 

 

 

1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Grasses Mean SE Mean SE Mean SE Mean SE
=——=========L ===a==============================
Sm. bg 1400 $450 850 $250 3000 $600 14150 $8000
Ky. bg 1050 $250 550 $150 10850 $7350 3650 $650
Ordgrs 800 $150 450 $150 3050 $600 4250 $1450
Timthy 650 $150 450 $100 3850 $800 5250 $1300
Tl Fse 750 $150 500 $100 2400 $600 3000 $1050
Redtop 1000 $200 800 $250 5600 $2000 6850 $2300

N 8 48 in 1985,

 

51 in 1986

60

Genus Tarsonemus

Density

 

- 0-16 cm
.\\\\‘ 16-30 cm

 

 

 

 

 

 

 

SmB. KB. Oroh. Tim. T. F. ndtp
Grass Species

1988

Density (Thoussnds)

 

- o-15 cm
\\\\\ 15-30 cm

 

 

 

 

 

 

 

 

 

‘ 8111.3. K.B. Orch. Tim. T. F. Rdtp
Grass Species

Figure 16. Tarsonemus spp. densities /m2 in both soil strata under
different grass covers.

61

 

 

 

 

Table 10: Mean seasonal density /m‘ $SE of Tarsonemus spp. in
upper and lower soil strata: data from all
grasses lumped.
1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm

Dates Mean SE Mean SE Mean SE Mean SE
Aprl l --- --- --- --- 800 $250 800 $250
Aprl 15 1000 $450 950 $400 350 $100 850 $650
May 1 900 $300 400 $150 400 $200 200 $100
May 15 1000 $250 300 $100 700 $250 550 $300
June 1 1350 $300 1150 $450 1850 $750 1400 $400
June 15 1950 $650 800 $300 4700 $1100 9950 $2350
July 1 1350 $300 1500 $300 4800 $1300 6650 $2100
July 15 1450 $700 1150 $500 15350 $4150 17900 $2400
Aug 1 300 $250 200 $100 6100 $1400 10200 $3250
Aug 15 100 $ 50 100 $ 50 3800 $850 6150 $2150
Sept 1 1100 $850 450 $200 1200 $500 850 $350
Sept 15 450 $300 150 $ 50 5350 $950 4000 $950
Oct 1 1200 $300 650 $200 30500 $20700 42950 $22250
Oct 15 1150 $250 650 $300 2050 $600 1450 $300
Nov 1 650 $200 600 $150 2600 $1150 850 $150
Nov 15 800 $200 450 $300 1000 $350 300 $150
Dec 1 200 :100 100 1 so 200 1100 150 :50

m

N:

18 per data and depth

62

Genus Tarsonemus

 

 

 

   

 

 

 

 

 

1985
density
3000
2500.4 ...................... 7 ..........
2000.. .........................................
15004 2- ................................................................
1000—i ........................................................................................................................................................
500... ................................................... . ...............................................................................
it
0 I T I I I r I I I I I I I I I
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date
Figure 17. Biweekly fluctuation of Tarsonemus spp. during 1985,

all grasses combined.

63

Genus Tarsonemus
1986

density (thousands)

 

8O

 

 

60 .1... ..............

 

40.. .............

 

 

 

 

 

 

 

(n-sc. —

date

Figure 18. Biweekly fluctuation of Tarsonemus spp. during 1986,
all grasses combined. - '

64

Gumn1hnnwumn
1mm

 

'7

u

llama Elena-

‘1

"WV“\
1‘~“‘\

1 I “‘~“\
p‘.‘“‘~t

. s

" 1“~\

\‘

i‘t‘k

 

t
‘ “‘-~““‘-
““‘~‘\
V-----S
.“L

" “‘.‘.

. V“~‘~‘~‘~

 

 

 

 

m m

a q a
m m 0
'

0e...

 

(“wanna-a)

 

-e-e a five-0e.

 

 

 

 

 

 

 

 

Ilzflgngmng spp. during 1985.
, all grasses combined.

Vertical distribution of

and 1986

Figure 19.

55

of 17 sampling dates. However, it seems that W
spp. freely inhabited both strata in 1986 because of more

evenly distributed moisture (Figure 19).

Soil temperature and moisture were not correlated to
abundances at either depth, indicating that density changes
were probably due to seasonal events of reproduction and

mortality inherent in the members of this genus.

Anova. (App. B) of' densities under’ each turfgrass
revealed very little interaction (p<0.25) between grasses
and dates in 1985 and none at all in 1986, although
abundance estimates for either stratum differed between
grasses on several dates. In general, significantly higher
densities occurred mainly under smooth bromegrass and
Kentucky bluegrass (Figures 20 and 21) , again indicating
that these grasses provide advantageous below-ground
habitats for' Tarsonemus spp. Although overall abundance
appeared modulated by grass species, lack of grass/date
interaction points out the basically similar seasonal

fluctuation patterns of Tarsonemus spp. under all grasses.

C-S. W

C.6. 7‘ 0 - ass 0 ‘ 01 0’1‘ “ - =z.‘ 211°: 99.

Split-plot analysis of variance showed highly

significant differences (p <0.001) between grasses in

66

Genus: Tarsonemus
1985 0-15 cm

density (x500)

 

1985 ' 16-30 cm
density (x500)

 

 

 

 

 

   
 

 

 

 

  
  
    

  
  
 

 
  
   

 
  

 
  
   
  
   

 

 

  
  

     
    
 

   

 

 

1° - ...-:3. ......-.. ll

8 «FE . -!|l—

. . - I IL. "

4 as"... _. ; :ZII-— II-i'I-J—I =17I— ?I!-I-‘—‘—/ I!I_ _
l7]:;//jg IA? ... / 1w .114—711:. F.”

2 .1"... _ {ALI/Ea Z 3:; I‘m 7: ..—.. 'mi — "UTmthy
‘ u—eI .mI -n'l . a! E :1: lg. ‘0': I I fiI—ir Wong.

aa-I 'I' --‘==-' 5 282039

 

    
 

0"
AAMMJJJJAASSOONND
1 1 11111 1
15151515151516151

date

Figure 20. Mean seasonal densities of Tarsonemus spp. under
different grasses at each depth during 1985.

67

Genus: Tarsonemus
1986 0-15 cm

density (x500)

300

250 '

200

150 a,‘,=,
100 “.5” =:::’ =:’

4954::
=5: =
5:6 ' ' a

 

AAMMJJJJAABSOONND

11111111
16161616161616161
date

1986 16-30 cm
density (x500)

...............................

  
   
 
 
   

350

300 ', ....................

250 ’3

200 ” . A

15° =-.‘;: i 42:5 Rd!”
100 6:: =7 3?; 5: ‘I’lFo

, =7 5 a :1: a a a Tillflly
6° . 4:: = =7 .; ._ a a a cue.
O a = ' " " a a a a W 59

Saba
AAHMJJJJAABSOONND
11111111
16161516161616151
data

Figure 21. Mean seasonal densities of zgxggngmgg spp. under
different grasses at each depth during 1986.

68

supporting W spp. populations in both 1985 and
1986. The highest abundance of figkggggnig spp. was recorded
for Kentucky bluegrass with 1300/m2 and 1750/m2 in 1985 and
1986 respectively, possibly related to the extensive root
system of these species. The lowest population density was
recorded for redtop, the species with the deepest-ranging
root system of all grasses investigated (Table 11 and Figure

22).

Densities of Bakerdania spp. differed between dates in
1985 and 1986 (P <0.001). Highest abundances were recorded
at the beginning of each season (2000/m2 in 1985 and'ZSSO/m2
in 1986) , followed by moderate fluctuations throughout the
rest of each year. On December 1, increased densities of
1450/m2 in 1985 and 1100/m2 in 1986 were again recorded
(Figures 23 and 24), indicating a pattern consistent between

years.
C.8. ‘1 — 0. ‘ .-_ 0! 0 :._1- 0...!-_ ‘90 .009- -_ 01:.

Vertical distribution of the genus differed greatly
(p <0.005) with depths in both 1985 and 1986. W
spp. preferred the upper soil stratum throughout all dates
except on June 1, June 15 and September 1 in both 1985 and

1986 (Table 12 and Figure 25).

69

Table 11: Population densities $SE/ma

of Bazerdania spp.

in each soil stratum under different grasses.

 

Grasses

Sm. bg

Ky. bg

Ordgrs

Timthy

Tl Fse

Redtop

N = 48 for 1985, 51 for 1986

 

 

O - 15 cm
Mean

800

550

500

300

300

150

SE

 

3200

i200

i100

1100

i100

$100

16 - 30 cm
Mean SE
300 $50
750 £200
100 £50
100 :50
200 :50
50 :50

 

m

1986
0 - 15 cm 16 - 30 cm

Mean SE Mean SE
500 1150 350 :100
1200 1350 550 :150
200 $100 so :50
750 :250 250 :100
250 :150 so —-
100 :50 So :50

70

Genus Bakerdania
1985

0011117

 

1000‘
- 0-16 cm

““31960cm

 

800‘

 

000 n’

 

4°04, ...........

 

 

 

 

 

 

 

 

 

suns. KB. Oven. Tim. 11?. Hip
Grass Species

1986

 

1400 ‘
- 0-16 cm

1200 .. 15-30 cm

 

 

1000" ....................

 

 

 

 

 

 

 

 

 

 

 

Sana. K.B. Oren. Tim. 1'.F. M19
Grass Species

Figure 22. aakggggnia spp. densities /m2 in both soil strata under
different grass covers.

ll

1!

71

 

 

 

 

 

 

Table 12: Mean seasonal density /m2 :53 of Bakerdania spp. in

upper and lower soil strata: data from all

grasses lumped.

1985 1986

O - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 --- --- --- --- 1800 £600 750 i400
Aprl 15 1450 :550 550' :200 1050 :550 400 :200
May 1 150 £100 500 1250 550 £250 200 i100
May 15 650 £200 100 £100 150 £100 150 i100
June 1 150 £100 200 £100 400 £150 650 1250
June 15 200 £100 800 £400 100 £50 150 1100
July l 200 £100 150 £100 300 £150 250 i100
July 15 100 $50 150 150 200 1150 50 :50
Aug 1 100 $50 0 -- 250 £150 50 :50
Aug 15 250 £150 50 :50 750 $600 150 thO
Sept 1 150 £100 200 £150 150 £150 200 i150
Sept 15 150 1100 0 -- 700 $400 150 thO
Oct 1 550 1200 350 1150 150 t100 50 :50
Oct 15 750 £200 100 150 150 1100 50 :50
Nov 1 300 $100 200 $150 200 1100 50 :50
Nov 15 650 1200 250 1100 650 $300 400 i200
Dec 1 1100 1450 350 $300 1100 1500 O --
N = 18 per date and depth

72

Genus Bakerdania

 

 

 

 

 

 

 

 

 

1985
density
2500
2000~
1500.. .................................. f
1000-
500
O IIIITTIIIITTITI
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date

Figure 23. Biweekly fluctuation of Bakerdania spp. during 1985,
all grasses combined.

73

Genus Bakerdania

 

 

 

 

 

 

 

 

 

 

1986
density
3000
2500 .....................
2000.. .................................................................
1500.. ..............................................................................
1000
«5CH3 \¥{
0 TITIIVII.ITTITTI_
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date
Figure 24. Biweekly fluctuation of flaggzdanig spp. during 1986,

all grasses combined.

 

 

 

-H- mm.-

74

 

lei-117

“‘.‘~ u e- .

Gnnann
V
t
0
1

NBC

 

 

fl ‘-~‘\ lieu

 

 

.9..-
i
J
1
I

 

 

 

 

 

 

1-\ a I.

 

H .‘~“~ ‘ee.

“““‘~‘\ ‘ '

 

“I!

 

 

Vertical distribution of Bakerdania spp. during 1985.

and 1986, all grasses combined.

Figure 25.

75

Since populations tended to peak in early and late
season of both years (Figures 23 and 24), it is not
surprising that correlations between abundance and
temperature were negative. In 1985, a significant
relationship between densities and moisture of the upper
stratum existed, partially explaining mid-summer population

declines during this low precipitation year.

Interaction between grasses, dates and depths was also
significant. With a single exception (smooth bromegrass),
date-specific comparisons strongly indicated that Kentucky
bluegrass supported the largest numbers of Bakerdania spp.
(Figure 26). On several dates in 1986, Kentucky bluegrass
again proved superior in terms of abundances of Bakerdania

spp. (Figure 27).

 

76

Genus: Bakerdania

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1985 0-15 cm
density (1:500)
10 ,
‘ .1 E 65:64:7- 5 - Ramp
'1 E a . T Ttth.
':_ z e e L m y
2 if: 2 _ g . a : '_ 011195
0 f1 Tfi I F1 I I rfigi l r l r 1 8059
A A u M J J J J A A s s o O N N o
1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1
date
1985 16-30 cm
density (x500)
8 .1 ’: ......................
‘ '7': I; a a- 2 131.7355 I
E E a ... :9 =7 fizz—=72: “6'09
. : 1 ==4=r¢=r==.31r=. 2 "F.
2 -- ° : ° . . g, ._._, as: : :: mm!
333 .. : i :1: 23:3 a ‘5' E31 .-::3:1 I: ”0:295
0 f I. l.' Tat, I. I. Friar r [:5 I. I I. 1:3“!09
.A A M M J J .I.J A A s s o o u N D
1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1
date
Figure 26. Mean seasonal densities of Bakerdania spp. under

different grasses at each depth during 1985.

77

Genus: Bakerdania

 

 

 

 

 

 

 

 

 

 

 

 

 

1986 0'15 cm
density (x500)
1°? .1.
3‘". E :

g; ,. == ' = I m
4 ._E: E 5.: page , 1113.9
2.1313 {1% : :. : : . Tmthy

33E :3: 3 2 _ 2 . is :15; . : ”0:19.
0 1.1“Tal'VIIT I Tar. 1:??r f1. 1.. 1 8.09.
A A M H J J J J A A 3 8 O O N N 0
1 1 1 1 1 1 1 1
1 6 1 0 1 5 1 0 1 0 1 0 1 0 1 6 1
date
1986 16-30 cm

density (x500)

 

...................

0 ..........
5.
‘.
3‘

. Ham
2 "Fe
1 =5 Tmthy
o =::.=:::==:ZI==' a‘

AAMHJJJJAASSOONND

1 1 1 1 1 1 1 1
15151515151515151
date

Figure 27. Mean seasonal densities of Bakerdania spp. under

different grasses at each depth during 1986.

78

D. Suborderi_fiungdina

The suborder Eupodina (excluding the family Tydeidae
which is treated separately in this study ) was represented
by 5 genera: Ennodes spp.. Qoscenngdes spp-. Bhagidia spp..
gggggxnggidia spp. and Ezgyngtgg spp. The relative dominance
of these genera recorded in Table 13 and illustrated
graphically in Figure 28. The genus W was dominant

with 55.7% and 45.5% in 1985 and 1986 respectively.

D-l. Bffe9t_9f_srass.292srs.2n_densities_2f Ennodes sun»:

Grass cover had a significant effect (p <0.001) on
Eupgggg spp. populations in 1985. The highest densities were
obtained for orchardgrass with 850/m2 followed by tall
fescue *with 700/mz, while ‘the lowest abundance occurred

under redtop with ZOO/m2, (Table 14 and Figure 29).

In 1986, no significant differences among grasses
existed. However, the highest density now occurred under
redtop with 4OO/m2 while the genus was essentially absent

under Kentucky bluegrass (Table 14).

0-2 Bigeeklx_flu9fuafi2n_2f_Bupgdes_§nni_pgnnlatigns=

As shown in Figure 30 and 31, We: spp.abundances
varied greatly over each season (date effects significant at
p <0.001). Population peaks were observed in July of 1985

and August of 1986, with occassional complete disappearance

79

Table 13. Relative dominance of Eupodina genera in 1985

and 1986.
1985 1986

Genera N % N %
Eupodes 301 55.7 137 45.5
Cocceupodes 97 18.0 50 16.6
Rhagidia 94 17.4 44 14.6
Coccorhagidia 16 3.0 2 0.7
Ereynetus 32 5.9 68 22.6
total 540 301

N a the total number of specimens obtained per year.

80

.wmmd
0:5 mama ca chocoo ocfipomom uo Aav monocusoc o>uuo~om .om Guamfim

©®©P mee
No .5800 0.3 .923

v.2 .omcm .
F onoooo
9mm .55 m o

     

  

m ..ooooo .2
0.9 9.0 >oem.‘

mocooaooooo

of. 8685 So 8585

mEcoozm.

81

Table 14: Population densities $SE/mz of Eupgggg spp.
in each soil stratum under different grasses.

 

1985 1986

 

 

 

     
 

 

 

 

     

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Grasses Meanfid__SE_~Mean__ SE f Mean” ___SE _Mean SE
Sm. bg 300 £50 50 :50 150 £100 0 --
Ky. bg 450 £100 50 -- 50 -- 50 :50
Ordgrs 850 £200 0 -- 150 :50 O --
Timthy 400 :150 so ' -- 250 $100 so --
Tl Fse 700 £200 50 :50 250 :50 50 --
Redtop 200 :50 50 150 400 1150 O --

 

   

N 8 48 for 1985, 51 for 1986

82

Genus Eupodes
1985

0011th

 

1000 "
- 0-16 cm

\\\\‘ 15-30 cm

 

 

 

 

 

..............................

 

 

 

 

 

 

 

 

 

 

8111.8. Ice. Otch. Tim. 1’.F. Rdtp
Grass Species

 

 

 

 

 

 

 

 

 

1986
500-
- 0-15 cm
15-30 cm
400::
300:
200«-
100‘, ..........................................................................
OJ

 

 

 

 

 

 

 

8111.3. K.B. Orch. Tim. T.F. Rdtp
Grass Species

Figure 29. Egpgggg spp. densities /m2 in both soil strata under
different grass covers.

83

Table 15: Mean seasonal density /mz

$SE of Eupodes spp. in

 

 

 

 

upper and lower soil strata: data from all
grasses lumped.
1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 --- --- ‘--- --- 200 £100 50 :50
Aprl 15 150 2100 o -- o -- o —-
May 1 150 2100 50 :50 100 :50 . 100 :50
May 15 350 £150 100 1100 100 £100 0 --
June 1 1100 £350 0 -- 50 :50 0 --
June 15 400 £150 100 150 0 -- O --
July 1 1850 £550 50 £50 150 $100 0 --
July 15 950 £250 0 -- 200 £100 50 :50
Aug 1 300 £150 50 :50 650 £200 50 :50
Aug 15 700 $200 50 :50 1050 £450 200 1100
Sept 1 200 1100 o -- 350 1150 o I--
Sept 15 350 1150 0 -- 200 £100 0 --
Oct 1 250 1100 O -- 50 :50 O --
Oct 15 300 £100 50 :50 50 150 0 ~-
NOV 1 200 $150 0 -- 50 :50 O --
Nov 15 200 £100 50 £50 200 £100 0 --
Dec 1 400 ‘1200 100 1100 150 1150 O --

   

N

18 per date and depth

84

Genus Eupodes

 

 

 

 

 

 

 

 

 

1985
density
2000
1500.. ...........................
1000.. ......................... , ................. _ ...................................
500
0 ITIITJIFTIITITI
AAMMJJJJAASSO-ONND
11111111111111111
5 5 5 5 5 5 5 5
date

Figure 30. Biweekly fluctuation of Eupodes spp. during 1985, all
grasses combined.

85

Genus Eupodes
1986

density

1400

 

 

 

 

 

 

 

 

 

 

 

Til ilililiIiT
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date
Figure 31.

Biweekly fluctuation of Buggies spp. during 1986, all
grasses combined. . ‘

86

(Figure 31) . In both years, maximal abundances coincided
approximately with the highest temperatures of the season

(Figure 3-6).

D.3 WWW:

Statistical results indicated a pronounced vertical
stratification for the genus (p < 0.001). Throughout all
dates, Eupodes spp. were found in much higher densities in
the upper soil stratum (Table 15 and Figure 32). Zero counts
were frequently recorded for the lower stratum (on 43% of
all sampling occassions in 1985, and 59% in 1986). Clearly,

Eupodes spp. were upper soil dwellers.

Consistantly, in both years and at both depths,
population abundance was positively correlated to
temperature and negatively to moisture (App. C). These
temperature relations simply indicated that the genus was
not adversely affected by high temperatures, allowing

population maxima to occur in mid-season.

Grass-specific seasonal abundances (Figures 33 and 34),
tested by Tukey's MSD (App. A), showed no differences
between orchardgrass and tall fescue for the upper soil
stratum. On several dates, however, these two grasses
supported significantly higher populations than any other
turf species. Orchardgrass and tall fescue thus seemed to

provide the best habitats for Eupodes spp. In the lower soil

87

 

 

 

 

 

 

 

Guuofiumxno
1985
don-In
an
- a m“.-
an
‘a ‘ II...IIOIDO”O.“QJIOI coo...-
mqmn ................................
l i (J
r l s -. l _ _S
AAUIJJJJAAIIOGNNI
11111111111111!!!
I I I I I I I I
“MI
“I!
an

-I-i- flit-ao-

 

 

 

 

 

 

 

 

 

 

Figure 32. Vertical distribution of Engage; spp. during 1985. and
1986, all grasses combined.

88

Genus: Eupodes
1985 0-15 cm

density (x500)

12
1o ”

 

ON‘O.

AAHMJJJJAASSOONND
11111111
16161618151515161

(flue

1985 16-30 cm

density (x500)

0.. .-
0.’ '
0.. .
0.. .
0.3 .- "i 'I - av - - a, - a 1116.“,
. a 1- a a 4:: a a :7 =7
0'2 g 3;? - - - - - - - - T11"!!!
0.1 ’ - - 7 - - - - - -
0

    

eaaaj‘ 2:: =7: 2' aaaaaa W59

A A u n J J J J A A a a o o a u o
1 1 1 1 1 1 1 1
1 o 1 a 1 c 1 a 1 a 1 o 1 o 1 a 1
data

Figure 33. Mean seasonal densities of Enpgggg spp. under different
grasses at each depth during 1985.

89

Genus: Eupodes
1986 0-15 cm

density (x500)

     

7
G
5
4
2 " _ ==¢= 'nro
- 4' , -- Tum,

1 - -- --
0 ca: gag" " a gag:

AAMHJJJJAACCOONND

1 1 1 1 1 1 1 1
15151516151315151
date
1986 16-30 cm

density (x500)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1.2 a
‘ db .. '. , ........ .
. . . ,
... '3' ...' :
0.. «in ..V '4 ................................ :
‘. _. _. ,
...' ..I.' .' p:
0.. .h >:
.' >0
' O
o ‘ ..n. . c - - - :
' 3 a 4:? a a a a A: .
D 9
0‘2. ° -------aljl° ------- om.

 

 

 

 

 

aaaaaaaaa " 55:55:75 ”.9

o- 8- DO
A A U H J J J J A A 8 8 O O N N D
1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 C 1 C 1
6816

Figure 34. Mean seasonal densities of Eupodes spp. under different
grasses at each depth during 1986.

90

layer, poorly populated by these mites, no grass specific

differences existed.
B. Family: Tydeidae

The classification of this family is in a state of
flux. Most authors recognize 25 genera and more than 200
named species. It is unclear whether species complexes with
discrete patterns and habitats exist or whether they are
ubiquitous and nearly omnivorous. Tydeidae can be
predacious, fungivorous or facultatively phytophagous and
have a cosmopolitan distribution (Kethley 1982). In this
study the family Tydeidae alone comprised 15.4% (1985) and
10.0% (1986) of all prostigmatids, and was the dominant
family in the suborder Eupodina. Two species of this family
occurred regularly throughout most sampling dates, in both
years= Mess (Lam) Wiesel; Evans and
W W Treat. Dominance of these two
species within the family was 33.5% and 25.4% for I.

W and 29.5% and 29.3% for M- We in
1985 and 1986 respectively (Table 16 and Figure 35).

E.1. “' 0' 0 2‘ OV‘ ‘ 0! 909. a 01 Q tau. ‘ Of t‘u

In both years, grass type significantly affected
population densities of I. W. Redtop supported
the highest numbers (approximately 700/m2) (Table 17 and

Figure 36). Redtop has a root system which is regenerated

91

Table 16. Relative dominance of species in the family
Tydeidae in 1985 and 1986.

1985 1986
Genera N % N %
I. bedfordiensis 185 33.5 281 25.4
n. lggggnippggs 163 29.5 324 29.3
other species 205 37.0 500 45.3
Total 553 1105

N a the total number of specimens obtained per year.

92

1 , .owmn use mood :
meowmoxa no mwdowmw omuowamm uo Aw. oococuaoo m>wuoumm .mn wusvfim

.2 ©ma_ mwa_

9:
$6on $50 3.0on 650

   

  

m . ow
momQQEooog
mimEocotQEmE A .2
q 2 n .2 1 momQQEooo$
mtmcmuouocomo $26232me moemEmcouQSmE
mambfi womb?

mam—goo? ”3:5“.

93

Table 17: Population densities $SE/ma of Tyggus bggfgggiegsjs
in each soil stratum under different grasses.

 

1985 1986

 

 

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Grasses Mean SE Mean SE Mean SE Mean SE

 

Sm. bg 250 :50 ‘100 :50 150 :50 200 :50
Ky. bg 150‘ :50 100 :50 150 :50 150 :50
Ordgrs 100 :50 100 :50 250 :100 I 100 :50
Timthy 150 :50 150 :100 200 :50 250 :100
T1 Fse 100 :50 150 :100 300 :100 350 :100
Redtop 450 :200 200 :100 400 :100 300 :100
.=.............=......... _..._.

 

 

N - 48 for 1985, 51 for 1986

94

Tydeus bedfordiensis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1986
Ouufly
500-
- 0-15 cm
10-30 cm
400«'
30011
200‘, fiim
100‘“ ..... .1
0 " l I,
11F. Rd“:
iansss'Spmxfles
1888
Danny
500-
- 0-16 cm
15-30 cm
400«
300-~
zoo‘VWm
100-" “
O ' r—‘ L,

 

 

 

 

 

 

 

 

ems. K.B. Gen. Tlm. 1’.F. m.
GuassISpmmwss

Figure 36. Tygggs bedfordiensis densities /m2 in both soil strata
under different grass covers.

95

annually and thus leaves plenty of plant residues which may

support fungal colonies, which may be the potential food
sources for T. 12551311112115.15-

E-2- W
m:

Population densities of I. W differed
greatly (p <0.001) over time in both years. In 1985, highest
abundance occurred on July 1, with pronounced lows or
complete absence in the fall (Figure 37) . The pattern was
repeated in 1986, although the summer peak was more
prolonged and slightly bimodal (Figure 38). The species was
thus most numerous during hot and dry periods, dramatic mid-
season increases most likely being due to a single maximum

in reproductive activity.

E.3. WWW:

Megs bedfordiensis populations essentially did not
differ between depths (Table 18 and Figure 39), showing no

persistent preference for either soil stratum.

As expected in view of the species’ mid-summer
population jpeaks (Figures 37 and 38), relations between
abundances and edaphic factors were analogous to those
encountered in Eupodes spp.: consistently, populations at
both depths were positively correlated to temperature, and

negatively to moisture (App. C).

96

Table 18: Mean seasonal density /m2 $SE of Iyggus bggjgggigflggg
in upper and lower soil strata; data from all grasses

 

 

 

 

lumped.
1985 1986

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 0 -- o -- 100 :50 100 :50
Aprl 15 300 :100 100 :50 50 :50 100 :50
May 1 300 1150 150 £100 100 :50 100 :50
May 15 250 :150 100 :100 100 :50 0 --
June 1 100 :100 0 -- 150 :50 200 :50
June 15 ' 0 —- 50 :50 650 :250 850 :300
July 1 1000 1500 850 £350 500 :250 350 i100
July 15 200 £100 150 :50 650 1200 600 :250

Aug 1 350 £100 200 £50 1000 £300 400 :250

Aug 15 200 :100 150 :100 300 :100 300 :100
Sept 1 0 -- 0 -- 50 :50 400 :150
Sept 15 50 :50 150 :100 50 :50 100 :100
Oct 1 150 :50 100 :50 150 :50 200 :100
Oct 15 100 :50 50 :50 100 :100 50 :50
Nov 1 50 :50 0 -- 0’ --0 100 :50
Nov 15 50 :50 0 -- 100 :50 0 --
Dec 1 100 :50 0 -- 50 :50 50 :50

 

   

 

18 per date and depth

2 i
u:

97

TYde U5 bedfordiensis
1985

density

 

2000

 

1500

 

1000

 

500

 

 

 

 

date

Figure 37. Biweekly fluctuation of Ixfigns bedfordiensis during.
1985, all grasses combined.

98

Hide U5 bedfordiensis
1986

density

 

:_               [I
/ 1 \                     
/
/

EH30 _ ..........

160C)" ..............................................

 

400 /‘

 

 

 

 

Clo—(q _
0—0 g. _-
O'lrdm _-

date

Figure 38. Biweekly fluctuation of 219:3: hggfgxgigngig during
1986, all grasses combined.

99

nubulbanEMMuuu
1986

an!"

 

-o-uc- ESSIu-uca

 

 

 

 

 

 

 

 

1200

m qp-oo-~auuuuun see.- .. ......

a“ ‘ e... .u .

‘4

D II
"....
I I.
0....
o la
'1‘
' Is
All
‘ II
11...
l- I.

.J 1.
U1!
I I
All
A ...

1986

 

density

 

Gnu-um

-Hle.

 

 

‘
K

“\

“

“s

“l

 

 

m V“.‘ ‘1“‘.

~|W~1~LU

 

hill 1 m ‘~“L‘.‘“\
11111111111111
“-‘~‘L
‘-‘.--‘~““-§
. 1“~
m 1
W .‘8
1111

‘~\

‘ eqoeeeeeeeee on I

 

1300

1000

I“ "
w q pus-OIOUOIIO'eIIII ee-ee e

D .I
"In.
N I.
0.1.
o ..e
.1.
‘ |
All
A I
.41.
..- I.
Idle.
... I.
III
H I
A1.
A ...

during

Vertical distribution of Tyfigns

Figure 39.

1985 and 1986, all grasses combined.

100

Tydeus bedfordiensis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1985 0-15 cm
density (x500)
-
101
s-5
5.1;"
"'" as: 4:52:35 4:755 Ramp
. r :7: a: ca: / TIP.
24.- 33-- aaafiaga/ 1.111111,
n.: Vi ----- - W“
I I I I f r I I I I I I I I r I I
AAUUJJJJAA83°ONND
1 1 1 1 1 1 1 1
15151515151515151
date
1985 16-30 cm
density (x500)
5—
31F-;I.x‘
2"" a: -.-=/ R0109
a a aaaa/ T'F.
1-11- 5555/ TIIIUIY
‘ a C;C ‘- 13‘,» ’1;I_ --- ONO.
0 ‘ aaaaa i‘i' a: :=“ === “'ngg
I I I I 7 I I T I I I I T if I I I
A A H H J J J J A A 3 0 O N N D
1 1 1 1 1 1 1 1
15151515151515151
date

Figure 40. Mean seasonal densities of rygggg bedfordiensis under
different grasses at each depth during 1985.

101

Tydeus bedfordiensis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1986 0-15 cm
density (x500)
a
41
3 c1:- .......
2 _‘_ - a E - a
" " ‘Eynfl$”°
1:. ‘= =: . : a a 5", 1mm
- ' 323 i , II- a mo
0 f I I I I I I I I F I I T I I I I a no
A A u u J J J J A A s s o o N
1 1 1 1 1 1 1 1
1 s 1 e 1 s 1 a 1 a 1 s 1 s 1 s 1
(”Re
1986 16-30 cm
density (x500)
s
4
.3 ' i
2 .. a a as a - s-T'ermp
“ :1 ans V a .
a .1; . ‘ ‘ 5‘ a a 5 Int“?
‘ - =7 E11: ‘ TEUZ-aa ”or“.
A A u M J J J J A A s s o o N N 0
1 1 1 1 1 1 1 1
1 s 1 5 1 a 1 s 1 a 1 s 1 s 1 a 1
(hue

Figure 41. Mean seasonal densities of Tyggng bedfordiensis under
different grasses at each depth during 1986.

'102

Redtop was the only grass species singled out from all
others in terms of supporting the highest densities of I.
bggjgggignsig. On several dates, and more often in the upper
than in the lower stratum, abundances were significantly
higher under redtop (App. A, Figures 40 and 41).

£04. --‘ 9 9 -“ 9V‘ ‘ 9! 1-11.9- ‘ 9.1- 2.9 91":

In 1985, densities of M. lgggghippggg were almost equal
under the six grasses. In 1986, weak differences (p <0.1)
among grasses existed: Kentucky bluegrass supported highest
numbers with a yearly mean of 800/m2, while lowest mean
density was recorded under tall fescue (Table 19 and Figure

42).

Much as in other mite taxa, seasonal abundance
estimates fluctuated greatly during each year (p < 0.001) .
Unlike other taxa, however, seasonal density patterns were
highly discrepant between years (Figures 43 and 44). Early
and late-season population lows provided the only points of
similarity. Density maxima of 1985 occurred in July, while
the. single pronounced. increase of 1986 was recorded in

October.

No explanations are readily apparent. One may
speculate, however, that the species is physiologically
(reproductively) flexible; and /or that changing below

Table 19: Population densities +SE/m’
lgngghippgng in each soil stratum under different

grasses.

103

 

Of MESQEIQDQEQEB§

 

I

 

 

1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Grasses Mean SE Mean SE Mean SE Mean SE
Sm. bg 200 :50 100 :50 500 :200 100 :50
Ky. bg 150 :50 50 :50 500 £300 300 :100
Ordgrs 100 :50 100 :50 300 +150 350 :150
Timthy 100 :50 250 +100 100 :50 450 :300
T1 Fse 50 :50 150 :50 50 :50 150 :50

 

N = 48 for 1985,

51 for 1986

104

Me tapronema tus Ieucohippeus

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1985
Density
350
.1 - 0-160111
300 ‘“ 15-30 cm
200-- SS'“
200-L §§ SS"
1501’ §§ §§“'
i \M
50" ”u n
01‘ 1 . r r. *5
me. me. Oren. Tim. T.F. Mtp
Grass Species
1988
Density
800-
III 046¢m1
500 5‘ 16-30 cm
400‘. ..........
300‘, ...........
........... .... k
200-'
100. “I 1 ............
01

 

 

 

 

 

 

 

8111.8. K.8. 0:011. 1111:. T.F. Rdtp
Grass Species

Figure 42. ugtgngngmgggg legggnippgns densities /m2 in both soil
strata under different grass covers.

105

ground conditions under the six grasses, which had not been
mowed or otherwise treated since May 1984, had some effect
on this particular species. The latter interpretation is
supported by a general shift in yearly mean densities,
populations increasing under smooth bromegrass, Kentucky

bluegrass and orchardgrass (Table 19).

E.6 V‘fi. -_ . .0. 0! 0 v‘ -. oo‘u-_ .‘ ‘5 01 .09“

The species was distributed almost equally over depths
in both years, although in July and August of 1985 the lower

stratum seemed to be preferred (Table 20 and Figure 45).

Given the mid summer peak of u. lguggnippeus in 1985,
it is not surprising that densities were positively
correlated to temperature, and negatively to moisture during
that year (App. C). With no significant relationships
emerging for 1986, it seems that the explanatory power of
edaphic 'variables for’ either' densities or ‘vertical

distribution was generally weak.

With respect to grass-specific vertical distribution,
no clear trends emerged. At either depth, and on several
dates, populations were highest under any one of the six
grasses (Figures 46 and 47). No clear preference for any

grass species or grass related depth could be shown.

 

Table

106

20: Mean seasonal density /m’ :58 of Metangggmaggg

lgugghippgus in upper and lower soil strata;
from all grasses lumped.

data

 

 

 

 

 

 

 

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 --- --- --- --- 50 :50 50 :50
Aprl 15 150 :50 so :50 50 :50 50 :50
May 1 100 £100 50 150 150 :50 100 :50
May 15 200 £100 50 :50 0 -- 50 150
June 1 300 :150 350 :150 o -- 50 :50
June 15 ’ 50 :50 150 :100 100 :50 0 --
July 1 400 :150 450 :200 50 :50 so :50
July 15 100 :50 550 :200 100 :50 150 :50
Aug 1 200 1100 200 150 300 £200 50 :50
Aug 15 100 :50 450 £300 100 1100 150 150
Sept 1 o -- 100 :100 850 :350 400 :150
Sept 15 50 £50 100 150 400 :150 200 1100
Oct 1 150 :50 100 :50 200 $100 650 :250
Oct 15 0 -- 0 -- 2050 $850 2150 1800
Nov 1 150 :50 o -- 300 :150 200 :100
Nov 15 50 :50 0 -- 50 150 0 --
Dec 1 0 -- 0 -- o -- o --

 
 
 

N

18 per date and depth

 
   

 

107

Metapronematus leucohippeus

 

 

 

 

 

 

 

 

 

 

1985
density
1000
...- ................... ii ....................................
600 ...............
4c“)- ......................................................
200... .......... V
0 I I I I I I I I I I I I ‘I r
AAMMJJJJAASSOONND
11111111111111111
5 5 5 5 5 5 5 5
date
We

Figure 43. Biweekly fluctuation of
during 1985, all grasses combined.

108

Metapronematus Ieucohippeus
1986

density (Thousands)

 

 

 

 

 

 

 

 

 

 

 

date

Figure 44. Biweekly fluctuation of Mesaprgngmatus lsngghinngufi
during 1986, all grasses combined.

109

MenuommumnlusoMHMMI
NE!

“W

 

-0-Ce- m0...

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

“I!

 

-§Iu ES“.-

 

 

 

 

use

 

 

1000

 

 

 

 

 

AAHHJJJJAAIIOONND
1 11 11 11 11 11 11 11 11
I I I I I I I I
dd.

Figure 45. Vertical distribution of Metanrgngna§n§ leugghinnsns

during 1985 and 1986, all grasses combined.

110

Metepronemstus Ieucohippeus
1885 0-15 cm

density (x600)

 

AAUHJJJJAAISOONND

11111111
1I1I1I1I1I1I1I1I1
date

1985 16-30 cm
density (x500)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1A A u n J J .I.IIA1A I I 0 0 u N o
1 1 1 1 1 1 1 1
1 I 1 I 1 I 1 I 1 I 1 I 1 I 1 I 1
(ENG
Figure 46. Mean seasonal densities of Metangngmatns
under different grasses at each depth during 1985.

111

Me tepronema tus Ieucohippeus
1988 0-15 cm

density (x500)

   
  
 
 

14
12
10
I
. 41,-; a a :fi: - Rdtop
4 a a a a a TI F.
- av - - - ° III“,
0 = a a (:7 a a ' a 50

 

AAMMJJJJAASIOONND

1 1 1 1 1 1 1 1
18181818181818181
date

1988 18-30 cm
density (x500)

- ----
---
=====
Gaga-g a

a are- _
aaaaaaaaaaaa

AAouJJJAAssoouuo
11111111
18181818181818181

date

 

Figure 47. Mean seasonal densities of

Metanzensmetus
under different grasses at each depth during 1986.

112

KW

Mesostigmata ranked second among Acarina, after
Prostigmata; their relative dominance was 26.9% and 8.9% of
total mites in 1985 and 1986 respectively. Two species of
the mesostigmatids occurred regularly throughout this study:
W W Willmann with 79.1% and 76.6% in
1985 and 1986, and fiypgaspig agglgifg; Canestrini with 7.0%
and 6.8% dominance. All other species together constituted
13.9% of total Mesostigmata in 1985 and 16.6% in 1986 (Table
21 and Figure 48). All species recorded in this study are
free-living and soil-inhabiting mites except for Dgzmgnygsus
gelling; Degeer which is known to be ectoparasitic on birds
and mammals. However, it has been stated by Gilyarov (1977)
that its accidental appearance in soil is possible, The
species made up only 2% of total mesostigmatids in 1985 and
3.3% in 1986. The mites probably dropped off birds and

mammals visiting the study area.

F.l. " 0‘ - 2?‘ 0 ‘I_ 0: :-u3‘ ‘ 0' {909: s ‘ _f

Highly significant differences existed among grasses
(p <0.001) in accommodating W 51135135115
populations in both years. Lumped over both depths, highest
density in 1985 was found ‘under smooth. bromegrass with

$150/m2 followed by orchardgrass with 4600/m2. Least numbers

113

Table 21. Relative dominance of species of order Mesostigmata
in 1985 and 1986.

1985 1986
species N % N %
3. silesiagus 1326 79.1 911 76 6
a. aguiifer 113 7.0 81 6 8
0- selling: 34 2.0 39 3.3
other species 198 11.9 158 13 3
total 1676 1189

N = the total number of specimens obtained per year.

4.
1
1.

.omaa.o:s mama :« suseofiunomez
no mmaowem omuoeumm uo Auv mocncwEOG 0>Hus~0m .we endows

Z ©w9 mm?

      

      

6:33 . 535%
2 EQQOQAI at mammogf
MISSED 6.“ wasted,
@3939:qu mamgcmEqu
«.2 mo_oooam49:o

3.0on 550

o . QR d - ON
msomummtm maofimmtm
mbtmtmomooct mstoumombocm

mofimow EmEmzmomoE

115

Table 22: population densities :SE/mz of Bhedasarsllus
silgsiagus in each soil stratum under different grasses.

n

 

 

 

1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm

Grasses Mean SE Mean SE Mean SE Mean SE

ejii pitE====a=fl_=====_,_====._====.____=======
Sm. bg 2100 i500 3050 11000 1050 $350 1000 i450
Ky. bg 900 i350 1500 i450 1200 $300 1000 :250
Ordgrs 1750 i400 2850 $800 1650 1500 1150 £300
Timthy 600 £200 350 $100 750 :150 550 :150
T1 Fse 400 £150 50 150 200 £100 200 :50
Redtop 100 £50 100 :50 100 150 100 :50

 

N - 48 for

 

116

Rhodacarellus slleslacus

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1985
Density
3800 5
- 0-1I on
30001“ """" 18-30 cm
2500 .+ .......
2000 -’
1800 a i
1000‘“ ...........
m - I...
o .1
8m. 8. K. B. 0:011. 1111:. T. F. Hdtp
Grass Species
1986
Density
2000 a
- 0-1I cm
18-30 cm
1800 -“
1000 -‘ ’
800 a "
o- , . M
8m. 8. K. B. Oren. Tim. 1’. F. fidtp
Grass Species
Figure 49. Engggggggllgs silggiaggg densities /m2 in both soil~

strata under different grass covers.

117

were recorded for redtop with 200/m2. In 1986, orchardgrass,
Kentucky bluegrass and smooth bromegrass all harbored large
populations, while the lowest numbers again occurred under
redtop with 200/m2 (Table 22 and Figure 49). Between - year

numerical relationships were thus relatively stable.

F.2- W:

The species underwent large-scale numerical
fluctuations during both years. In 1985 (Figure 50)
densities peaked in October and November, but were low
earlier in season. By contrast, highest abundances occurred
in..April and. May in 1986 (Figure 51), followed. by low

densities during the remainder of the year.

Much as in n. W, and equally difficult to
explain without knowledge of the species' biological
characteristics, seasonal density patterns of 3 111351393:
were thus very dissimilar from year to year. It is possible
that the 1985 drought delayed reproduction of both species
until the fall, and that the resulting population increase

carried over into the spring of 1986.

F.3 V‘ ' a q '9- 0| 0’ 19's:

Only for 1986 could a significant effect of depth be
shown for the species. In the first half of the 1985 season,

3. gilgsiaggs were more numerous in the upper stratum, while

118

 

 

 

 

 

Table 23: Mean seasonal density /m3 :83 of

gilesiagus in upper and lower soil strata;
data from all grasses lumped.
1985 1986
0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 --- --- --- --- 1750 i450 3650 $1300
Aprl 15 650 £300 300 1150 2800 $800 2150 1600
May 1 1800 £900 600 i250 3100 $1200 850 1400
May 15 900 :250 400 1200 1400 £750 250 i100
June 1 300 £200 50 i 50 400 :250 400 i300
June 15 1700 £900 600 :250 600 £300 50 150
July 1 900 :250 600 £200 400 £200 50 :50
July 15 900 £450 400 $150 350 $200 100 150
Aug 1 1200 $500 1200 £500 600 £150 200 :50
Aug 15 600 £450 900 £400 800 £200 250 1100
Sept 1 550 $450 400 £150 400 :250 200 :150
Sept 15 950 1750 450 £200 600 $300 250 1350
Oct 1 2100 i700 2600 11250 150 $100 150 1100
Oct 15 800 2200 4650 $2600 100 £50 450 3350
Nov 1 550 $200 4000 11950 350 1200 300 1100
Nov 15 600 $200 1850 $550 200 £100 300 1300
Dec 1 1250 i750 2100 $600 50 :50 400 :150
N = 18 perIdgte and dept;l

119

Rhodacarell US 51119517 acus
1985

 

density (Thousands)
6

 

 

 

 

 

 

 

 

 

ollllllllilllgng
AAMMJJJJAASSOONND
1 l 1 l l 1 l l
15151515151515151

date

Figure 50. Biweekly fluctuation of Bhodaggzgllns‘silesiagns during
1985, all grasses combined.

120

Rhodacarel! US 511951 acas
1986

 

density (Thousands)
6

 

 

.......................................

 

 

 

 

 

 

 

 

 

 

 

3 .................................................................................

2... ...............................................................................................................

1.. ................

01114-11111111111

AAMMJJJJAASSOONND
1 l 111 l l 1

15151515151515151

date

Figure 51. Biweekly fluctuation of Bhodagargllns 3113513933 '
during 1986, all grasses combined.

121

madman swam

1985

deuiiy (Items)

 

 

  

 

NNNNK NNNN

 

 

 

‘

NN

NVNN

 

-0-IIII EDI-III-

 

 

 

 

 

 

D I.
Mil
I ...
01..
o I.
.II‘
I I.
All
A II
Jlo'
DO II
.1...
l- ..I
“1‘
u .1
An...
A I

1986

density (tunnel)

 

 

-e-Isn EDI-III.

 

1““““‘§‘§§““§§

 

 

q
3

1‘ ~ I
1‘1‘~‘t
s

““.“K

.‘g

 

a

“ “\1‘~|

u‘~“~\““““

II o

D I.
'1‘
I ...
0.1.
0 II
.18.
I I.
‘1‘
A ..I
...-II.
J ...
J18
..- .1
“In.
I ...
AI.‘
A ...

Vertical distribution of Bhodaggrgllns silgsiggng

during 1985 and 1986, all grasses combined.

Figure 52.

122

the opposite was true in October and November (Table 23 and
Figure 53). Throughout most 1986 dates, however, the species

clearly preferred the upper layer (Figure 52).

To some degree edaphic variables can be used to explain
differences in vertical distribution. Population density in
the lower stratum in 1985 was positively correlated to soil
moisture, and negatively to temperature. The negative
density / temperature relationship was confirmed with 1986
data, indicating some sensitivity of the species to high

temperature and low moisture.

Single data tests of mean numbers of B. W
under each turf grass showed significant differences between
grasses on several dates and at both depths. In general
(Figures 53 and 54), smooth bromegrass, Kentucky bluegrass
and orchardgrass were the three species which harbored

larger populations than any of the other three.

F-4- WW1:

Grass species differed. considerably in ‘terms of .H-
agulifie; populations associated with them (p <0.001) in both
years. Tall fescue *was clearly' the leader, followed by
redtop (Table 24 and Figure 55) . Under all other grasses,
numbers of H. agglgifig; were insignificant.

123

Rhoacarellus silesiacus
1985 0-15 cm

density (x500)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

14
12
10
l
C
4
2
0

A A U H J J J J A A 8 3 O O N N D

1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1
date
1985 16-30 cm
density (X500)

50- ...
so ~--‘°' E§§§
20"” ---------- .3231 9 “hp

a a 3.;- 1'".
‘0‘. g . .‘t.:. on

' =="‘=. 1‘ a” KVDJ”

o r I F r fr 1 I f I I i I 1 T r j?— “ b.

A A H H J J J J A A 8 3 O O N N D

1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1
date

Figure 53. Mean seasonal densities of Baggagargllns
under different grasses at each depth during 1985.

124

Rhoacarellus silesiacus

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1986 0-15 cm
density (x500)
201
161‘."
104' :.-:- a a -
'ij . I a a, E's-‘5 T|$¢bp
1:1 213- o a: .
was 2:: :2 ; : a - may
:3: :f: :f: : . 3 a t =- . OM90
0 3: :1 i-S :65' :7 ‘ aaaaaEg/ ”:9
AAHMJJJJ A88 0 no
1 1 1 1 1 1 1 1
15151515151515151
date
1986 16-30 cm
density (x500)
zo‘fiiéfy.”fz
1°‘L----a--- _;;T% — .: “up
2:; s \:\ ===m =4I’:4I‘_L QEL Q-4_u '/7I Tm
54332 .3 till—1:: ail—‘\ 11:12} 03"”
$.aplfi? A_5:av=vfi =v m 'u a! as
0;,91?????57????==aug°
AAMMJJJJAABSOONND
1 1 1 1 1 1 1 1
15151515151515151

date

Figure 54. Mean seasonal densities of Bhodagazgllna
under different grasses at each depth during 1986.

125

mm; 39313113: is a predator which feeds on mature

and immature stages of small arthropods. Tall fescue has an
extensive root system which penetrates deeply and may create
spaces offering relatively free movement to a hunting
species. Whether it also harbors large populations of
potential prey such as Collembola would have to be

clearified in more comprehensive studies.
F.5 :‘w1-. ‘ - _, 'on .- 119-279 T a - - ‘- 909, : .,;

Even under tall fescue, abundance of n. 5931131131 was
relatively low, which is not. unusual for' an obligatory
predator. Using data from all grasses per date, a. agglgifig;
abundance was found to fluctuate almost randomly in both
years, with no distinct or repeated pattern (Figures 56 and

57) .

v.5 WWI:

Poplation densities differed significantly between
depths (p <0.001). At virtually' all times, the species
preferred the 0-15 cm stratum (Table 25 and Figure 58).
Further studies would be necessary in order to correlate
this preference with the distribution of pore space and
potential prey. The latter is probably an important
determinant of the predator's vertical distribution, since
neither temperature nor moisture were related to H,

agnlgifg; densities at either depth.

Table 24: Population densities $SE/ma of Hingasnis aculifer
in each soil stratum under different grasses.

 

1985 1986

 

 

0 - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Grasses Mean SE Mean SE Mean SE Mean SE

 

Sm. bg 0 -- O -- O -- o --
Ky. bg 100 :50 so -- so -- o --
Ordgrs 0 -- o -- o -- o --
Timthy 0 -- so -- so :50 o --
Tl Fse 850 1200 100 :50 400 :100 o --
Redtop 100 150 50 -- 250 :50 o --

 

N a 48 for 1985, 51 for 1986

 

127

Hypoaspis sou/eifer

 

 

 

 

 

1985
Denflty
1000 -
- 0-16 cm
1o-ao om
BOOs'
600"
400 -

 

 

 

 

 

 

3111.3. Ice. Oren. 11m. T.F. Rdtp
Grass Species

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1986
Danny
600 -
- 0-16 cm
15-30 cm
400 -
300 -‘
200-'
100- . 1 ...........
o .11

8111.3. K.B. Oroh. Tim. T.F. Rdtp
Grass Species

Figure 55. _nypgggp13 agnlizg; densities /m2 in both soil strata -
under different grass.covers.

128

Table 25: Mean seasonal density /m’ $SE of flypggfipig aculifier
in upper and lower soil strata: data from all
grasses lumped.

 

 

 

 

1985 1986
O - 15 cm 16 - 30 cm 0 - 15 cm 16 - 30 cm
Dates Mean SE Mean SE Mean SE Mean SE
Aprl 1 --- --- --- --- 200 £100 50 :50
Aprl 15 50 :50 50 $50 100 150 50 :50
May 1 100 :50 50 150 50 :50 O ,--
May 15 50 £50 50 :50 O -- 0 --
June 1 50 :50 O -- 100 :50 O --
June 15 300 £150 50 :50 50 :50 0 --
July 1 0 -- 50 :50 0 -- 0 --
July 15 200 £150 50 :50 200 $100 0 --
Aug 1 o -- o '-- 200 :150 o --
Aug 15 200 1150 50 :50 400 1200 50 :50
Sept 1 400 1350 O -- 350 £150 0 --
Sept 15 50 150 50 :50 150 1100 O --
Oct 1 500 :250 50 :50 0 -- O --
Oct 15 400 2200 50 150 150 £100 0 --
Nov 1 200 1150 50 150 50 :50 O --
NOV 15 200 :150 100 150 0 -- 0 --

Dec 1 50 :50 50 150 150 £100 0 --

 

129

Hypoaspis aculeifer
1985

density

 

600

 

150(1- ................................................

 

 

400

 

300 .. .........................................

71 _
........... A ........ : .............................

ft; v V

 

 

 

 

 

(IN-‘9. r-
aid) 1—
0.. m r-

1

date

Figure 56. Biweekly fluctuation of fixpgagpis agnlifg; during 1985,.
all grasses combined.

130

H ypoaspis aculeiter

 

 

 

 

 

 

 

 

1986

density
500
400- ............ . K ................................... , ........ . .......
30C) ..........................................
a:
200 .................................
100

011 114111
AAMMJJJJAAS

l 1 1 l 1
15151515151

 

date

Figure 57. Biweekly fluctuation of Hypggfipis agulifgr during
1986, all grasses combined.

130

H ypoaspis aculeifer
1986

density

 

500

 

‘40:)- ...............................................

 

 

300

 

 

200

 

 

100

 

 

 

 

0 l l _l L j l 1

l 1 l l l

1 5 1 5 1 5 1 5 1 5
date

Figure 57. Biweekly fluctuation of Hypggfipifi agglifg: during
1986, all grasses combined.

131

Ermaamucruumbr
1986

 

density

 

-I-I en SSH-8 en

 

 

 

‘5

"5“

. ... quest-u

“

“‘

“\

“1

N

\'

‘\

‘k

‘\

 

600

”a d ....................-....... . u...

.................. ........

d

I II
o...-
o I.

' II
A...-
‘ II

J...
Jul.
1.1
“I.
I...
an..-...
A...

1986

 

 

density

mil-l en

-I-Icn

 

 

 

 

 

 

”0‘ "
\

 

all

Mil
' lo
0...!
0 i

‘ I.
All

1....-

Vertical distribution of 33393331: agnlifg: during 1985

and 1986, all grasses combined.

Figure 58.

132

Grass-specific mean densities (Figures 59 and 60)
differed on more than 30% of all dates in each year. As
expected, tall fescue was invariably associated with the
highest densities of H. agglgifig; on all occassions.

133

Hyp oaspis acuieifer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

   

 

 

 

 

 

 

 

 

1985 0-15 cm
density (x500)
. .1 1 .........
6-0". ._ ......... . .........................
‘dr- ............................................... . ..........
a-¥,#' ‘
3 . :- 4=r a: a M159
2"- :zaaaaaa =7==7===7¢=I T'F.
= a Tmthy
1 al- a ee 00 a e a a a e a ee 0 a 00 a e Odo.
aazaaazaaaaaa“ =7: ”'9
0 I I I I I I I I I I I I I T I 8- .9
A H H J J J J A A 5 3 O O N N D
1 1 1 1 1 1 1 1
5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1
d3“!
1985 16-30 cm
density (x500)
00. .‘
0.1
0.. ° ........................
0.. .............. 1 .......................
00‘ _. a ..
:7 a a =1» :_. . :7
0'2 .."'/V--a4_:=r-aaa-a¢_gi a. “It“,
0.1 " can-" gag-caa’fi; 5° ONO.
aaazaaaaaaaaaaa W59
0 ’ T I I I r I I r f I I I I I r I I Sill b.
A A M M J J J J A A 5 5 O O N N D
1 1 1 1 1 1 1 1
1 5 1 5 1 5 1 5 1 5 1 5 1 5 1 5 1

data

Figure 59. Mean seasonal densities of 32293321; agglifg: under
different grasses at each depth during 1985.

134

H ypoaspis aculeifer

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1986 0-15 cm
density (x500)
..... E
H .ggL—a “up
. E=a===a=.¢:‘ aaaeaae/ 01595
a =:=:=s=:=:=f=r=':='%r:=r=:='.=':=:=—/:=s.u§°
AAUHJJJJAASSOONND
1 1 1 1 1 1 1 1
15151515151515151
date
1986 16-30 cm
density (x500)
1
use '
1
0.3
o: ",9,#‘ FL
°-“ '_ _ - .11.:‘2192 ail-.222," Rates
0‘ " aaaaaaaaaaaaaaaaatnF.
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Figure 60. Mean seasonal densities of fiypgaspia agnlifez under
different grasses at each depth during 1986.

V. SUMMARY AND CONCLUSION

The present study presents data on the distribution and
abundance of selected taxa of Acarina obtained from soil
samples taken from plots planted with six turfgrasses. Data
were gathered for a two-year period (1985 and 1986), with
samples taken at biweekly intervals from April to December
of each year. Soil temperature and moisture were monitored

concurrently.

Acarina, more numerous than any other soil arthropods
extracted from samples, were dominated by Prostigmata.
Mesostigmata ranked second, while Cryptostigmata constituted
less than 8% of all mites. Numbers of Astigmata were
negligeable. Prostigmata have been shown to predominate in
soils poor in organic matter. Soils in the study area were
not particularly poor, but were certainly lower in organic
matter than for instance, the A horizon of forest, where

Cryptostigmata tend to dominate.

Mite densities were generally much higher in the second
year. In agreement with Mukharji et a1. (1970), this was
probably due to increased rainfall and higher soil moisture.

However, between-year discrepancies varied with taxon,

135

136

ranging from ‘very small differences in abundance (e.g.

Eupodes spp.) to more than 20-fold increase in W

spp. at the time of maximum population density.

Seasonal abundance jpatterns observed in 1985 were
usually repeated in 1986. Prostigmata as a group showed two
main density maxima, in June - July and september - October.
In 1986, the second of these peaks seemed to be due mainly
to one of the constituent prostigmata genera, namely
Igrggngmgg spp. Bakerdania spp.tended to be most numerous in
April, while Eupodes, spp. increased dramatically in mid-
season.

W W provided an exception, in
that the timing of population maxima differed between 1985
and 1986. Undoubtedly, some species thus reproduced at the
same time each year, contributing to the synchronicety of
population fluctuations. Others, prostigmatids as well as
mesostigmatids, may have been either more flexible, or more
dependent on suitable climatic conditions, resulting in
irregular seasonal rhythms. Large fluctuations over time, as
well as absence of a regular rhythm, have also been

described by Dillon et a1. (1962).

Clear preference for upper soil stratum, was exhibited

by Eupodes spp. and the predaceous mesostigamtid flypgggpig
W. In other taxa, soil moisture deficits in 1985

137

(particularly in the 16-30 cm stratum, to which rainfall did
not. penetrate) contributed. to slight shifts in ‘vertical
distribution. Although differences were not always
significant, both downward movement in response to more
evenly distributed moisture in 1986, and preference for the
upper, relatively moister stratum in 1985, were observed.
Migration of mites in reaction to moisture gradients has
also been discussed by Sheals (1957) and Usher (1971). The
latter author in particular concluded that Mesostigmata
showed no distinct vertical stratification during periods of

suitable climatic conditions.

Several authors have commented on the difficulty of
distinguishing the relative importance of the many factors
anad interactions which determine population fluctuations of
mites (Wallwork 1976; Sheals 1957; Dillon et al. 1962). In
the present study, temperature and /or moisture were

frequently correlated to seasonal abundance.

These edaphic variables generally explained less than
30% of observed variation, and interpretaion must be
cautious. In the case of ‘Egpggeg spp., for example, a
positive relationship between temperature and abundance
indicates that the animals were not adversely affected by
high temperatures, but does imply a causative effect. In

general, however, temperature and moisture were shown to

138

contribute significantly to seasonal as well as year-to-year

differences in density.

With regard to the central question, i.e., the
potential effect of grass species on mite populations, there
is almost no published work to draw on. Alejnikova et a1.
(1975) found that different plant covers greatly affected
the structure of soil animal populations. More pertinent,
Christen (1974) concluded that pasture crops with dense root
systems supported the largest populations of soil
arthropods.

The present study, given that soil type, climate,
etc... were the same for all turf blocks, does not allow
some general conclusions with respect to turfgrass effects.
For several mite taxa, smooth bromegrass, Kentucky bluegrass
and orchardgrass led in terms of supporting highest
populations. Tall fescue was preferred by W
agnlgifez, and redtop by Tygegg bedfordiensis in both years.

The first three of these grasses have extensive root
systems which may promote fungal and bacterial colonies on
which microbial feeders could thrive. W spp. and
Bakerdania spp. fall in this category (Kethley 1982).
Interpretaion becomes tenuous in cases where yearly

abundance shifted between grasses: this occurred in two taxa

139

for which feeding preferences are not known, Eupodes spp.
and W W. Apparently, interactions
between climatic factors, root development and the mites'
food sources allowed them to be more flexible in terms of

population growth under different grasses.

Annual versus perennial root systems surely result in
differing patterns of seasonal root distribution, turnover
and decay. Redtop with its annual roots promoted populations
of Iyggug bedfordiensis, a probable fungivore (Kethley
1982): a postulated system-specific fungal flora, differing.
from that under other grasses, may explain the tight link

between this mite species and redtop.

The present study must be considered a pilot effort,
aimed at a single faunal complement (Acarina). Without
extensive investigation of other faunal and floral system
components, any discussion remains conjectural, however,
that significant three-way interactions (grass x dates x
depths) existed for every single investigated taxon, in one
or some times both years. These results again indicate that
turfgrasses differ in the below-ground habitats they create,
leading to grass—specific variability in vertical
distribution, seasonal fluctualtion, and overall abundance

of many mite taxa.

BIBLIOGRAPHY

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Alejnikova, M. M. and N. M. Utrobina. 1975. Changes in the
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A P P E N D I X A

Tables of sample means per grass and date

146

147

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l
15

1 :
15

1

1
15 :

1

1 :
15

1 :
15

l

15 5 S

1. .1 11

11
dfiYYmmUUSEfiflttvvc
pp uuuuee C009
AAMMJJJJAASSMONND

16-30 cm

1985

Rdtop

Ky bg Ordgr Tnthy T1 Fe

Sn bg

o.o.o.nu.o.0.0.nv.nv.nv.0.33nv.o.3
1o.o.o.nv.0.0.nv.o.0.nv.nu.nv.nv.o.nv.

7703000007000077
0.0.nv.nU.1AU.nU.o.nU.1o.nu.o.o.o.nU.

nv.-I.0.O.o.o.o.o.o.nu.o.o.nv.o.o.o.
nu.11o.o.o.nv.o.nv.nv.nv.o.nv.nv.nv.nu.

nU.3nU.nv.o.nU.O.nv.nv.nv.0.3o.3ql.nv.
2nv.0.nu.nv.o.o.nu.o.o.o.o.nv.o.o.nv.

7730330033007773
120.1nl.o.10.nu.o.nv.30.10.3

3703070033033700
1001111000000010

l
15 :
l
1 :
1
15 :
1
1
15 :
1
15 :
1 :

15 u u u

11
mmyymmmmuqmmtuwwu
AAMMJJJJAASSMONND

Tukey's MSD - 3.6

1152

0 - 15 cm

Genus: Bakerdania
1986

Rdtop

Tl Fe

Tmthy

Ordgr

Ky bs

Sm bg

30300003070303303
1.0000000000000000

77003330070000003
41.100000000000000

73037030337033030
10000002001600055

33333300000300030
00200000100100000

73037000030030700
8.3302020070111017

70007300700030303
4.3010010100000110

1 :
15 :
1
15 :
1
1 :
15 :
1 :
1 :
15 :
1 :
15 :
l :

1.5 5 5

1. .1 1.
11
fiuYYmmUUSSfifltcvvc
D.D.a u u u u e e c c o o e
AA.Auunm.J.J.J.J.A.A.a.anunununun.

16-30 cm

1986

Rdtop

T1 Fe

Tmthy

Otdgr

Ky bs

Sn bg

30007300000000000
00001000000000000

00700000000300000
ooooooooooooooooo

00030000307337070
00000010011100020

07007030000000000
ooooooooooooooooo

03077707337000300
52113100000000010

70007070070030300
32101010000000010

1
15

1 :
15

1

1 :
15 :

1 :

1
15 :

1
15 :

1 :

1.:. fi. .5

1. 1. 1.
1.1.
.1.1 a o vav. t t
mmyymmuuwnwwuawwu
AAMMJJJJAASSOONND

Tukey's MSD - 4.7

153

0 - 15 cm

Eupodes
1985

Genus:

Rdtop

Ky b3 Ordgr Tnthy T1 Fe

Sm bg

nv.0.nv.o.o.nu.«l.o.«J.«l.«JnU.«J.«l.«I.nU.
0.nu.o.nv.nU.o.o.o.1nv.o.o.O..LnU.o.

nv.nv.nv.o.«J.o.o.nv.«J.o.«J.«I.«J.o.«I.«J.
0000104012101000

O.«I.«J«Jo.«l.o.nu.nv.nv.nv.«J.nU.nU.nv.nv.
nan.16nv.2nv.lo.nv.nv.nu.o.o.nv.1

«I.«J.«J.3«I.nv.nU.nv.«I.nU.«I.«J«J.«J«I.«J.
0013173110111002

nv.«I.«J.«J.nv.o.nv.o.«J.nv.«I.o.o.«J.«J.nU.
ltlJlZlmlnwmmnmman.

nv.nv.nv.«Jnu.«JO.q/«I.o.«J.«I.«J.nU.nv.nU.
nv.nv.o.nv.1.«0.«J.1nU.o.o.o.o.nU.nU.1

1 :
15 :
1 :
15 :
1 :
1 :
15 :
1 :
1 :
15 :
l :
15 :
1 :

15 5 5

1 l 1
11
“HMHVJVJW mmUmU.5.5mwMPt.c v v c
D.n. u u u u e e c c o o e
A.Aumum.urur.J.A.AnananunvN"N3D

16-30 cm

. 1985

Rdtop

Tl Fe

Tnchy

Ordgr

Ky b3

Sn b3

o.nv.nv.nv.«J.o.o.nU.nU.0.nU.0.«Jo.nU.«I.
AU.nv.nU.nU.o.nv.o.o.o.o.nU.o.o.o.o.nU.

o.o.o.nv.nv.o.nv.«J.o.nv.o.o.o.o.«J.«I.
nv.0.0.o.nu.nv.nu.nv.o.nv.nv.nu.o.0.o.o.

0370000000000000
0000000000000000

0.0.o.nv.nU.nv.o.o.nv.o.o.o.nU.nU.nU.nU.
nU.nU.0.0.nv.nv.o.nU.nv.nv.nv.nv.nU.nU.0.o.

nU.«J«I.nU.nv.0.nv.nU.o.nU.0.nv.o.nv.o.nu.
nU.nU.0.nU.0.nU.nU.O.nU.nU.O.nv.O.nU.nU.nU.

AU.nU.O.AU.«I.«J.nU.nU.«I.nv.nU.nU.nv.nv.nU.o.
o.nu.o.nU.nv.nU.O.nU.nv.nU.O.nU.nU.o.nu.nv.

1
15 :
1
15 :
1 :
1 :
15 :
1 :
1
15 :
1
15 :
1 :

1n u u

11
mmymemmuummuuwwu
AAMMJJJJAASSOONND

Tukey's MSD - 2.5

1154

O - 15 cm

Genus: Eupodes
1986

Rdtop

Ky b3 Ordgr Tmthy T1 Fa

Sn b3

00000070700300003
00010002160100010

00000033070033000
1.0000000212000000

70700000700700007
00000000031000011

70303070333000030
00000000001000000

00300000300000300
ooooooooooooooooo

00003000030300000
00000000310000000

1 :
15 :
1 :
15 :
1 :
l
15 :
1
1
15 :
1
15 :
1 :

15 5 5

1. .1 .1
11
fifiYYmmUUESWflttvvc
v.9. a u u u u e e c o o e
.A_Aumun.J.J.J.J.A.A.5.a.w.uuunu.u

16-30 cm

1986

Rdtop

Ky bg Ordgr Tnthy T1 Fe

Sn bg

00000000330000000
00000000000000000

00700003000000000
00000000000000000

00300000070000000
00000000000000000

00000000000000000
00000000000000000

«Joooooooooooooooo
00000000010000000

00000000030000000
00000000000000000

1
15 :
1
1 :
1
15 :
1
1
15 :
1
15 :
1 z

1n um u

11
umyymmmm%wmmauwwu
“fiAnmnm.J.J.J.J.A.A.a.anunununun.

Tukey's MSD - 1.99

155

m
c
5
1.
«
nu
S
.m
e
4.
d 5
r.a
0.9
c.1.
.a
e
.D
e
v.
T

Rdtop

T1 Fe

Tnthy

Ordgr

Ky bg

Sn b3

«I.nv.o.«I.o.nU.nv.«I.«J.nU.o.«J«J.«J.o.«I.
nv.1«o.o.o.0n1«o.nu.o.nv.nv.o.o.o.nv.

«I.nu.o.nU.nv.nU.O.nU.nU.0.«JnU.«I.nv.nU.nU.
nu.nv.o.nv.o.1nv.nu.o.nu.nu.o.o.nv.o.nv.

«JOOOOOOJJOOOOOOO
0010010000010000

o.nv.0.nv.nv.«J.nU.«I.nU.nv.nU.«JnU.nU.0.0.
nu.10.0.0.0.nu.10.nv.nv.nv.nv.nv.nv.nv.

o.«I.nv.o.0.nU.«I.nv.«Jo.nu.o.o.nu.«J.o.
an.20.0.nv.nU.o.nu.o.nU.nv.nU.O.nv.nv.

«I.«I.nv.«I.nU.«I.o.«J«JO.nU.«J.nU.nv.«J.«J.
nU.nU.nv.o.o.o.1«.11L.nu.o.nv.nv.o.o.nU.

1 :
15
1
15 :
1
1
15 :
1
1 :
15 :
1
15 :
1

1.:. <5 <5

1. 11 1.
1.1.
unYYmmUUSSflmccvvc
pp Una UGO COO
AAthJJJMASSWONNN

16-30 cm

1985

Rdtop

T1 Fe

Tmchy

Ordgr

Ky b3

Sm bg

April 1 :

«I.o.nv.nu.o.nv.o.«l.o.nv.«J.«J.nv.nU.nv.nv.
AU.0.0.nv.nV.40.0.nv.o.nv.nU.o.o.nU.nu.

1.7.nvnvnvnvnu15nvnununununvnunu
nununununuaanunununununununununu

o.«J«JnU.o.«J.0.«J.«I.nU.O.«JO.O.o.nU.
0.0.0.0.nw2nan.0.0.10.0.nU.nU.nu.

0.«I.nu.o.o.o.«J«J.nU.nv.nv.nv.nU.nv.o.nu.
nv.nv.nU.nU.0.10.0.1nv.nv.nv.nv.o.o.o.

nv.«JO.nv.«JO.«/.«JO.AU.O.«J.AU.o.O.nv.
nv.0.1nv.nU.o.o.o.o.nU.o.o.nU.O.o.nv.

«JnU.nU.O.nv.o.«I.«J.AU.nU.«I.nU.«I.nU.O.nv.
0.0.nv.o.nv.o.nu.o.o.nv.o.o.nu.o.nv.nu.

1
15
1 :
15
1
1 :
15 :
1 :
1 :
15 :
1 :
15 :
1 :

u .5. u
«ll... Cflyy for.
myymwmuumanwwaawwu
AMMJJJJAASSOONND

Tukey's MSD a 2.2

156

O - 15 cm

Tyeus bedfordiensis
1986

Rdtop

T1 Fe

Ordgr

Ky b8

Sn bg

Tmthy

00773307770037000
00000332100000000

00000003330300000
00000022220010000

30033737303000070
00000000200000000

30003307730030030
00000101300000000

37307073000000003
00000200000000000

00003703000007030
00000000200000000

1 :
15 :
1 :
15 :
1 :
1 :
15 :
1 :
1
15 :
1
15 :
1 :

1.5 5 5

1. 1. 1.
Hum“ c e vav. c t
r r v.v.m m.1.1 z.z.n.n.t t v v c
PP u usac ooo
AAMMJJmJMAssomNND

16°30 cn

1986

Rdtop

Tl Fe

Tmthy

Ky b3

Sn b3

Ordgr

33003370077030330
00001001590001.0000

03000007730003700
00000313100100000

33300333000003003
00000400010000000

00703703030000300
00000001000000000

00000030030000000
00000100005301.0000

33007770070000000
00000011001000000

1 :
15 :
1 :
1 :
1 :
15 :
1 :
1 :
15 :
1 :
15 :
1 :

1m an n
nu ..yy cc
mwyymmuuuuwwaawwu
.A.Aumnm.J.J.J.J.A.A.a.a«u«uuuuunu

Tukey's MSD - 2.4

157

O - 15 cm

Metaproneuatus Leucohippeus
1985

Rdtop

Tnthy T1 Fe

Ordgr

Ky bg

Sn b;

April 1 :

3703000000000000
0000020000000000

«J.G.o.nU.«J.nv.o.nU.«J.nv.nU.nU.nU.«J.o.o.
nv.0.o.nv.nU.1«nU.nv.o.nU.nv.nv.o.o.nU.0.

O.«I.«I.o.nv.nv.nv.nU.«J.o.o.«JnU.«I.nU.nv.
nU.0.nv.nU.nU.nU.nU.1«o.0.nU.o.nU.o.o.nU.

nu.nv.o.nv.o.«l.o.nv.o.nv.nv.nv.o.30.o.
nU.nv.1nU.nU.1nv.nv.o.o.nU.nv.nU.0.0.nv.

«I.nv.nU.«J.o.nv.nv.«Jo.o.o.«J.o.nU.«J.nv.
nv.nv.1nv.nU.nv..LnU.nv.nv.nU.10.nv.nv.nv.

«J.G.nv.«I.«Jo.«J.«J«I.o.«JO.o.«Jo.O.
0.nu.nv.2nv.nv.o.lnu.nv.nu.o.nv.o.nu.nu.

1 :
15 :
1
15 :
1
1
15 :
1
1
15 :
1
15 :
1 :

.5 a. .5

1. 1. 1.

1
fiYYmmUUSSWthvvc
D. u u c e o e
_Aumnm.J.J.J.J_m.m.5.5.w.wnmuu.u

16-30 cm

1985

Rdtop

Inthy T1 Fe

Ordgr

Ky bs

Sn b3

«J«Jo.«l.o.«l.o.«J.«J.o.nu.o.o.o.o.nu.
0000021040000000

nv.nv.o.o.«J.nv.nv.«J«I.nv.0.«I.o.nv.o.o.
nv.o.nv.10.1nu.o.0.nv.o.nv.nv.o.o.o.

«J.G.«JO.3«J.O.«J.O.«J.«J.«J.0.0.0.0.
0.0.0.11nv.«J0.0.10.0.0.0.0.nu.

nU.nU.Av.«J.«J«J«JO.«/.O.nu.o.o.o.o.o.
nU.0.0.nU.nv.nv.o.10.nU.o.0.nU.0.0.o.

0007000000300000
0.0.0.0.nwo.1nv.nv.nv.nu.nu.o.nv.o.o.

fififiJfiJfiJflfiJfinmnmnNnv.
o.nU.nv.O.o.1«1nv.o.nU.nv.o.nU.0.nU.o.

1
15

1 :
15

1

1
15 :

1

1 :
15 :

1
15 :

1

1m u u

an
muyyWWMMuummauww.
AAMMJJJJAASSOONND

Tukey's MSD - 1.9

158

0 - 15 cm

Metaproncuatus Laucohippcus
1986

Rdtop

Ky bg Ordgr Tmchy T1 Fe

Sn bg

0-.-.
.

00300333770303700
00000000000011000

00700700000030700
ooooooooooooooooo

30700303300300000
00000000000001000

00300007707007000
00000000006101000

00000000007777000

OOOOOOOOOOIZOHIOO

03000000070377330
00000000202008100

1 :

1 :
15 :

1 :

1
15

1 :
15

1

1
15 :
1
15 :

15 5 5

«l. 1 1

1.1.
fifiYYmmUUSSflflttvvc
n.n.a a u u u u e e c c o o e
AuAuMuMu1.1.1.1.Aunucucunvnvuunnn.

16-30 cm

1986

Rdtop

11 Fe

Tnthy

Ordgr

Ky bg

Sn bg

30307000033030300
00000000000031000

07300003337003300
00000000000001000

00000037000370000
00000000000004000

00000003077370000
00000000001025100

00330003330033300
00000000002212000

00000000000003700
00000000000002000

1 :
15

1 :
15

1

1
15 :

1

1 :
15 :

1 :
15 :

1 :

1n u u
11
mMyymmmmuummuuww“

Tukey’s MSD - 3.9

O - 15 cm

1985

159
Rhoacarellus silesiacus

Ordgr Tnchy Tl Fe Rdtop

Ky b5

Sn bg

0.«J«J0.nv.o.nu.nv.nv.o.o.nv.«J.o.«J.nU.
nv.nv.0.o.nu.nv.nu.nu.nu.o.o.nv.1.o.1.o.

«I.nv.nU.«I.nU.nv.«I.nU.«J.o.nv.«J.«J.«I.o.o.
20.nv.9mnv.«Jo.nU.nv.nv.o.nU.1.nv.1..o.

«J.«J.AU.0.«I.«I.«I.AU.«I.O.O.«J.«J.«I.O.«I.
0.0.«lnv.nv.1..1.so.nv.o.anv.1.nv.nv.

«J«I.«I.fiv.«I.«I.nU.nU.«/.«I.O.O.«I.«I.O.«I.
lilmslhzsmonomzmaz

AU.nv.o.nU.nU.«J.«J.«I.o.o.«I.«J«I.«JO.nU.
1.320030100111201.

7377033777730377

OZAOJIASOSOUZIOO

1
15 :
1
15 :
1 :
1
15 :
1
1 :
15 :
1 :
15 :
1 :

15 5 5

«l. l 1
11..
fiufiuvlv.m mmwmuaagam.w;c..u.v.c
D.D. a u u u u a e c c o o e
AAAnmun.J.J.J.J.A.A.a.a«unununun.

16-30 cm

1985

Rdtop

T1 Fe

Tnchy

Ordgr

Ky be

Sn bg

0.0.o.nv.nu.o.nu.o.o.nv.nU.«J.nv.«J.«/.AU.
nU.nU.o.O.o.o.nv.nv.o.nU.o.nv.1.0.o.1..

0000000000000030
o.nv.nU.nU.o.o.nU.o.nv.nU.o.o.nU.1.o.1.

0.«I.«J.nU.«I.«I.o.nU.O.«I.«J«J«I.«J«I.«J.
o.o.o.o.o.nu.o.21.o.o.1.o.o.o.1.

«I.«J.«JO.flv.0.«J«J«JO.«J«J.«/.«J«I.O.
01.204215519584976

o.«I.«Jo.nv.«I.o.O.«J.nU.«J.0.«J.«J«Jnv.

«4.0.nv.o.nv.2250.1.nv.mm2524

o.«I.o.«J«J.o.«I.o.o.o.«I.«J.o.«I.«I.«I.

1
15

1 :
15

1

1 :
15 :

1 :

1 :
15 :

1 :
15 :

1 :

1m u u

1.1.
mmyyWWMMuummtcwwu
AAMMJJJJAAssmMNND

Tukayls MSD - 11.7

m
c
S
1.
o
«u
c
a
.1.
s
e
1.
4.
8,0
A.
”.9
1.1.
nu 1.
,b e
1. r
a
c
8
mm

Rdtop

Ky bg Ordgr Tnchy Tl Fe

Sn bg

70000003300730000
00000000010000000

07000707000300300
1.0000200010000000

03703377777307730
«1.3100022114300000

33730333000003070

37330773030033307
9.5411100320110310

73703300333000030
78400010110000000

1 :
15 :
1 :
15 :
1 :
1 :
15 :
1 :
1 :
15 :
1 :
15 :
1 :

1.5 5 5

1. 1. 1.
1.1.
fiuflquvam m.WJU:8.5"Pth.t v v c
9.9. u u u u a e c o o c
_A.Aumnm.J.J.J.J.A.A.5«a.u.wuuuu.u

16-30 cm

1986

Rdtop

Tnchy T1 Fe

Ordgr

Ky be

Sn b3

00000000000337330
00000000000000001

00003000000003330
03000000000101000

77300037000073700
«1.0000000022103032

03330000030077307

9n611000100003040

37307333070003373
86103000100402111

73370300307300330

flJZIOOOOOOOOOOOOO

1 :
15 :
1 :
15 :
1 :
1 :
15 :
1 :
1 :
15 :
1 :
15 :
1 :

15 5 5

1 1 1
nu ecY.Y ct
rryymm1188ppttvvc
pp uuueeccoo
AAMMJJhJAASSOONNm

Tukey’s MSD a 7

161

O - 15 cm

Hypoaspis aculifer
1985

Rdtop

Tl Fe

Tnchy

Ordgr

Ky b3

Sn b;

April 1 :

nU.nv.nU.«J.«J.nU.nU.0.0.«I.nv.nU.«J.O.0.nU.
nU.nU.nU.nu.nv.o.1.nv.nv.nU.nU.o.o.nU.nv.nv.

3«I.O.«J.o.nv.«I.nU.nv.0.o.«I«J.«I.«I.«J.
0000301024054120

o._nU.nU.O.nU.nU.o.nv.o.o.o.nv.nU.o.nU.nv.
o._nU.nU.nv.nv.nU.nv.nU.nu.nv.nv.nU.nv.o.nU.nv.

0000000030000000
0000000000000000

nv.«J.«Jnv.«J.nv.nv.nv.«Jnv.«J«Jnv.«J.nU.«J
o.nv.nv.o.nv.nU.o.nv.o.o.nU.«U.nU.O.nv.nv.

nu.o.o.nu.o.nU.nv.o.o.nv.o.nv.nv.«Jnv.nU.
nv.nU.nv.nu.nU.nv.o.nU.nv.nU.nv.nU.nU.o.nv.o.

1
15

1 :
15

1

1 :
15 :

1 :

1 :
15 :

1.:
15 :

1 :

S 5 S

1. a. 1.

1
fiYYmmUUSBflflttvvc
P nu eeccooo
AMMJJJJMMSSOONND

16-30 cm

1985

Rdtop

T1 Fe

Inthy

Ordgr

Ky be

Sn bg

0.«J.«J.nv.nu.o.nv.o.«Jnv.o.nU.0.nv.«JnU.
nv.nu.nv.o.nv.o.nv.o.nv.o.o.nu.nv.o.0.o.

3000000030730073
nU.0.0.nU.nU.o.o.nU.nv.o.o.o.o.nU.0.nv.

0000037000000000
0000000000000000

0000000000000300
0000000000000000

0.0.nv.nU.«Jo.nv.nv.nv.nU.0.0.«Jo.nv.«J.
nU.nU.o.nv.nv.nv.o.o.nv.o.o.nU.o.o.nv.o.

nv.o.o.o.o.nu.0.o.o.nv.nv.nv.nv.«J.o.o.
nu.0.o.nv.nu.o.o.o.nU.«U.o.o.nv.nv.nU.nU.

1
15 :
1
15 :
1 :
1 :
15 :
1 :
1
15 :
1
15 :
1 :

1n u u
nu ceYY cc
”WYmeMMWWQWctwwm
AAmuJJJJAAssmmNND

Tukey’s MSD - 1.8

162

0 - 15 cm

1986

Hypoaspis aculifer

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1986

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A P P E N D I X B

ANOVA Tables

163

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164

Factor A: grass type

Factor 8: date

Factor C: core # (replicate)

Factor D: depth

Order: Prostigmata 1985
A N A L Y S I S o F V A R I A N C E T A B L E
Degrees of Sun of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 481.306 96.261 1.2984 0.2229
Factor B 15 4013.882 267.592 3.5953 0.0000
AB 75 7643.306 101.911 1.3711 0.0156
21(C/AB) 192 14294.333 74.450
Factor D 1 2025.000 2025.000 29.6289 0.0000
AD 5 265.938 53.188 0.7782
BD 15 673.389 44.893 0.6568
ABD 75 7137.340 95.165 1.3924 0.0373
EZ 192 13122.333 68.345
Total 575 49656.826
1986
A N A L Y S I S o F V A R I A N C E T A B L E
Degrees of Sun of Mean F
Source Freedom Squares Square Value Prob

Factor A 5 23251.778 4650.356 1.8489 0.1228
Factor B 16 257824.882 16114.055 6.4030 0.0000
AB 80 221482.667 2768.533 1.1000 0.3918
El(C/AB) 204 513380.333 2516.570
Factor D 1 221.281 221.281 0.0837
AD 5 19363.464 3872.693 1.4648 0.2028
BD 16 9483.163 592.698 0.2242
ABD 80 326833.758 4085.422 1.5453 0.0077
22 204 539340.333 2643.825
Total 611 1911181.66O

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165

Factor A: grass type
Factor 8: date
Factor C: core # (replicate)
Factor D: depth
Tarsonsmns spp. 1985
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 86.813 17.363 1.8310 0.0280
Factor B 15 394.000 26.267 2.7714 0.0000
AB 75 834.854 11.131 1.1745 0.0034
El(C/AB) 192 1820.333 9.481
Factor D 1 65.340 65.340 9.6825 0.0021
AD 5 10.931 2.186 0.3240
BD 15 59.549 3.970 0.5883
ABD 75 573.514 7.647 1.1332 0 2477
32 192 1295.667 6.748
Total .575 5141.000
1986
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 10318.596 2063.719 1.1111 0.3848
Factor B 16 190463.042 11903.940 6.4091 0.0000
AB 80 153937.487 1924.219 1.0366
21(C/AB) 204 378896.333 1897.334
Factor D 1 1177.779 1177.779 0.6039
AD 5 17327.289 3465.458 1.7768 0.1191
BD 16 6796.304 424.769 0.2178
ABD 80 242394.461 3029.931 1.5535 0.0071
22 204 397885.667 1950.420
Total 611 l399196.959

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Factor A: grass type
Factor B: date
Factor C: core # (replicate)
Factor D: depth
Bakerdania Spp. 1985
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 94.938 18.988 7.6117 0.0000
Factor B 15 135.194 9.013 3.6133 0.0000
AB 75 234.618 3.128 1.2547 0.0559
E1(C/AB) 192 479.333 2.495
Factor D 1 19.507 19.507 8.3788 0.0042
AD 5 28.556 5.711 2.4531 0.0350
BD 15 78.493 5.233 2.2477 0.0063
ABD 75 236.444 3.153 1.3541 0.0513
32 192 447.000 2.328
Total 575 1753.750
1986
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 191.366 38.273 8.8931 0.0000
Factor B 16 212.418 13.276 3.0856 0.0000
AB 80 451.190 5.640 1.3100 0.0232
81(C/AB) 204 877.999 4.304
Factor D 1 49.471 49.471 12.5522 0.0005
AD 5 27.392 5.478 1.3900 0.2294
BD 16 82.418 5.151 1.3070 0.1952
ABD 80 228.719 2.859 0.7254
£2 204 804.000 3.941
Total 611 2924.974

166

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Factor A: grass type

Factor B: date

Factor C: core # (replicate)

Factor D: depth

£929.02: 899- 1985
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 29.175 5.835 5.0831 0.0004
Factor B 15 112.512 7.501 6.5347 0.0000
AB 75 203.186 2.709 2.3608 0.0000
E1(C/AB) 192 220.333 1.148
Factor D 1 120.085 120.085 99.2382 0.0000
AD 5 35.592 7.118 5.8826 0.0000
BD 15 116.054 7.737 6.3938 0.0000
ABD 75 206.436 2.752 2.2746 0.0000
E2 192 232.333 1.210
Total 575 1275.707
1986
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob

Factor A 5 9.078 1.816 2.5031 0.0317
Factor B 16 54.493 3.406 4.6947 0.0000
AB 80 59.310 0.741 1.0213 0.4430
El(C/AB) 204 148.333 0.726
Factor D 1 20.497 20.497 28.2523 0.0000
AD 5 9.229 1.846 2.5441 0.0293
BD 16 30.781 1.924 2.6517 0.0008
ABD 80 61.493 0.769 1.0595 0.3678
32 204 148.000 0.725
Total 611 540.882

167

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168

Factor A: grass type
Factor : date
Factor : core # (replicate)
Factor D: depth
12513115 bedfordiensis 1985
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 13.583 2.717 2.7717 0.0400
Factor B 15 105.771 7.051 9.7860 0.0000
AB 75 189.250 2.523 3.5012 0.0000
31(C/AB) 192 138.334 0.720
. Factor D 1 2.507 2.507 2.1979 0.1398
AD 5 7.931 1.586 1.3906 0.2295
BD 15 3.215 0.214 0.1879
ABD 75 60.347 0.805 0.7054
32 192 219.000 1.141
Total 575 739.938
1986
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 15.714 3.143 2.8930 0.0121
Factor B 16 136.951 8.559 7.8788 0.0000
AB 80 93.147 1.164 1.0261 0.2694
El(C/AB) 204 221.667 1.087
Factor D 1 0.132 0.132 0.1268
AD 5 4.054 0.811 0.7765
BD 16 21.729 1.358 1.3007 0.1991
ABD 80 123.585 1.545 1.4795 0.0147
E2 204 213.000 1.044
Total 611 829.979

169

Factor A: grass type
Factor B: date
Factor C: core # (replicate)
Factor D: depth
M222222222212§ 122222122222 1985
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A N 5 4.467 0.893 1.2865 0.2574
Factor B 15 36.679 2.445 3.5215 0.0000
AB 75. 64.894 0.865 1.2469 0.0933
21(C/AB) 192 133.333 0.694
Factor D 1 0.766 0.766 1.1308 0.2889
AD 5 7.286 1.457 2.1523 0.0610
BD 15 14.262 0.951 1.4043 0.1483
ABD 75 61.186 0.816 1.2049 0.1570
E2 192 130.000 0.677
Total 575 452.873
1986
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 23.765 4.753 1.8711 0.1878
Factor B 16 582.526 36.408 14.3339 0.0000
AB 80 360.846 4.511 1.7840 0.0226
E1(C/AB) 204 518.333 2.541
Factor D 1 0.418 0.418 0.1330
AD 5 35.503 7.101 2.2575 0.0501
BD 16 19.859 1.241 0.3946 '
ABD 80 493.552 6.169 1.9614 0.0001
32 204 641.667 3.145
Total 611 2676.471

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170

Factor A: grass type
Factor B: date
Factor C: core # (replicate)
Factor D: depth
WW 1935
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 2234.625 446.925 17.6043 0.0000
Factor B 15 1201.438 80.096 3.1552 0.0001
AB 75 4535.042 60.467 2.3829 0.0000
81(C/AB) 192 4878.331 25.387
Factor D 1 65.340 65.340 2.5577 0.1114
AD 5 185.389 37.078 1.4514 0.2077
BD 15 1125.882 75.059 2.9381 0.0003
ABD 75 5386.389 71.819 2.8112 0.0000
32 192 4905.000 25.547
Total 575 24513.437
1986
A N A L Y S I S 0 F V A R I A N C B T A B L B
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 561.459 112.292 11.9434 0.0000
Factor B 16 1485.059 92.816 9.8730 0.0000
AB 80 2259.902 28.249 3.0052 0.0000
31(C/AB) 204 1918.331 9.402
Factor D 1 16.668 16.668 1.8635 0.1737
AD 5 17.577 3.515 0.3930
BD 16 437.137 27.321 3.0545 0.0001
ABD 80 816.451 10.206 1.1410 0.2298
22 204 1824.667 8.944
Total 611 9336.920

171

Factor A: grass type

Factor B: date

Factor C: core # (replicate)

Factor D: depth

1122222212 22211121: 1985

A N A L Y S I S 0 F V A R I A N C E T A B L E

Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob
Factor A 5 59.431 11.886 20.1376 0.0000
Factor B 15 14.215 0.948 1.6322 0.0816
AB 75 65.514 0.874 1.5034 0.0210
El(C/AB) 192 111.667 0.582
Factor D 1 10.563 10.563 17.6348 0.0000
AD 5 43.958 8.792 14.6783 0.0000
BD 15 14.049 0.937 1.5637 0.0870
ABD 75 65.431 0.872 1.4565 0.0213
82 192 115.000 0.599
Total 575 499.826
1986
A N A L Y S I S 0 F V A R I A N C E T A B L E
Degrees of Sum of Mean F
Source Freedom Squares Square Value Prob

Factor A 5 15.270 3.054 14.4100 0.0000
Factor B 16 8.641 0.540 2.5533 0.0061
AB 80 26.536 0.332 1.5733 0.0465
Bl(C/AB) 204 43.300 0.212
Factor D 1 8.708 8.708 35.5267 0.0000
AD 5 12.028 2.406 9.8147 0.0000
BD 16 7.209 0.451 1.8383 0.0283
ABD 80 24.556 0.307 1.2523 0.1057
E2 204 50.000 0.245
Total 611 196.279

APPENDIX C

Correlation and multiple regression

analysis

172

173

Data tile : PRO85
Title : Prostigmata 1985 depth 1

Function : CORR
Data case no. 1 to 192

 

 

t moisture -

 

Variable 7 Average - 12.96

Variance I 12.80

core meane

Variable 9 Average - 8.83

Variance - 41.79

Number . 96

Covariance - -5.33 Correlation - -0.230
Intercept - 14.22 Slope - -0.416 Standard Error - 0.181
Student's T value - 2.295 Probability - 0.024
temperature

Variable 8 Average - 16.76

Variance - 49.34

C02. meane

Variable 9 Average - 8.83

Variance - 41.79

Number - 96

Covariance - 5.20 Correlation - 0.114

Intercept - 7.07 Slope - 0.105 Standard Error - 0.094
Student's T value - 1.117 Probability - 0.267

Data tile : PR085
Title : Prostigmata 1985 depth 2

Function : CORR
Data case no. 1 to 192

t moisture

 

Variable 7 Average - 11.44

Variance - 9.65

core meanm

Variable 9 Average - 5.08

Variance - 29.13

Number - 96

Covariance - -0.02 Correlation - -0.001

Intercept - 5.11 Slope - -0.002 Standard Error - 0.179
Student's T value - 0.014 Probability - 0.989

temperature —— V‘—
Variable 8 Average - 14.81

Variance - 38.75

core means

Variable 9 Average - 5.08

Variance - 29.13

Number - 96

Covariance - -0.45 Correlation - -0.013

Intercept - 5.25 Slope - -0.012 Standard Error - 0.089

Student's T value - 0.129 Probability - 0.897

 

174

Data tile : PR086
Title : Prostigmata 1986 depth 1

Function : CORR
Data case no. 1 to 204

 

 

t moisture
Variable 7 Average - 15.24
Variance - 10.07

core means
Variable 9 Average - 18.12
Variance - 1273.68

Number - 102

 

Covariance - 23.39 Correlation - 0.207

Intercept - -l7.29 Slope - 2.324 Standard Error - 1.101
Student's T value - 2.111 Probability - 0.037

temperature

Variable 8 Average - 15.35

Variance - 52.32

core means

Variable 9 Average - 18.12

Variance - 1273.68

Nunber - 102

Covariance - 39.76 Correlation - 0.154
Intercept - 6.45 Slope - 0.760 Standard Error - 0.488
Student's T value - 1.559 Probability - 0.122

 

Data tile : PR086
Title : Prostigmata 1986 depth 2

Function : CORR
Data case no. 1 to 204

 

4 moisture

Variable 7 Average - 14.05
Variance - 4.56

core means

Variable 9 Average - 19.32
Variance - 1558.81

Nulber - 102
Covariance - 14.00 Correlation - 0.166

Intercept - -23.80 Slope - 3.069 Standard Error - 1.823

 

Student's T value - 1.684 Probability - 0.095
temperature

Variable 8 Average - 14.18

Variance - 43.68

core means

Variable 9 Average - 19.32

Variance - 1558.81

Number - 102
Covariance - 59.79 Correlation - 0.229
Intercept - -0.09 Slope - 1.369 Standard Error - 0.581

Student's T value - 2.354 Probability - 0.021

175

Data tile : PROBS
Title : Prostigmata 1985 depth 1

Function : MULTIREG
Data case no. 1 to 192
t moisture
temperature

core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sun of Squares d1 Mean Square F Signit
Regression 228.259973 2 114.12999 2.84 0.064
Residual 3741.569890 93 40.23193
Total 3969.829863 95
Data tile : PROBS
Title : Prostigmata 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
t moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum o: Squares dt Mean Square F Signir
Regression 1.235773 2 0.61789 0.02 0.979
Residual 2766.262757 93 29.74476
Total 2767.498531 95
Data tile : PROB6
Title : Prostigmata 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
t Ioisture
tesperature
core means
ANALYSIS OF VARIANCE TABLE
Sum ot Squares d! Mean Square F Signit
Regression 14611.674291 2 7305.83715 6.34 0.003
Residual 114029.727936 99 1151.81543
Total 126641.402229 101
Data tile : PROB6
Title : Prostigmata 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCB TABLE
nit
Sum of Squares d: Mean Square _-5 ______ §£2____
6.35 0.003
Regression 17906.378353 2 gigg-igggg
Residual 139533.594896 99 .

Total 157439.973252 lOl

 

176

Data tile : TAR885
Title : Tarsonemus 1985 depth 1

Function : CORR
Data case no. 1 to 192

t moisture

 

Variable 7 Average - 12.96

Variance - 12.80

core means

Variable 9 Average - 1.88

Variance - 4.50

Number - 96

Covariance - -0.49 Correlation - -0.064

Intercept - 2.37 Slope - -0.038 Standard Error 8 0.061
Student’s T value - 0.621 Probability - 0.536

temperature

Variable 8 Average - 16.76

Variance - 49.34

core means

Variable 9 Average - 1.88

Variance - 4.50

Number - 96

Covariance - 1.30 Correlation - 0.088

Intercept - 1.44 Slope - 0.026 Standard Error - 0.031
Student's T value - 0.852 Probability - 0.397

 

Data tile : TARS85
Title : Tarsonemus 1985 depth 2

Function : CORR
Data case no. 1 to 192

 

4 moisture

 

Variable 7 Average - 11.44

Variance - 9.65

core means

Variable 9 Average - 1.20

Variance - 2.38

Number - 96

Covariance - -0.81 Correlation - -0.169

Intercept - 2.16 Slope - -0.084 Standard Error - 0.051
Student's T value - 1.660 Probability - 0.100

temperature

Variable 8 Average - 14.81

Variance - 38.75

core means

Variable 9 Average - 1.20

Variance - 2.38

Nulber - 96

Covariance - 1.28 Correlation - 0.133

Intercept - 0.72 Slope - 0.033 Standard Error - 0.025

Student's T value - 1.301 Probability - 0.196

 

177

Data tile : TARS86
Title : Tarsonemus 1986 depth 1

Function : CORR
Data case no. 1 to 204

 

 

t moisture

Variable 7 Average . 15.24

Variance - 10.07

core means

Variable 9 Average . 9.60

Variance - 850.54

Number - 102

Covariance - 22.76 Correlation - 0.246

Intercept - -24.84 Slope - 2.261 Standard Error - 0.891

 

Student's T value I 2.538 Probability - 0.013
temperature

Variable 8 Average - 15.35

Variance - 52.32

core means

Variable 9 Average - 9.60

Variance - 850.54

Number - 102

Covariance - 25.71 Correlation - 0.122
Intercept - 2.06 Slope - 0.491 Standard Error - 0.400
Student's T value - 1.228 Probability - 0.222

 

Data tile : TAR886
Title : Tarsonemus 1986 depth 2

Function : CORR
Data case no. 1 to 204

 

{undisture

Variable 7 Average - 14.05
Variance - 4.56

core means

Variable 9 Average - 12.38
Variance - 1199.79

Number - 102
Covariance - 12.35 Correlation - 0.167

Intercept - -25.64 Slope - 2.706 Standard Error - 1.599

 

Student’s T value - 1.693 Probability - 0.094
temperature

Variable 8 Average - 14.18

Variance - 43.68

core means

Variable 9 Average - 12.38

Variance - 1199.79

Number - 102
Covariance - 45.56 Correlation - 0.199
Intercept - -2.41 Slope - 1.043 Standard Error - 0.514

Student's T value - 2.031 Probability - 0.045

 

178

Data tile : TAR885
Title : Tarsonemus 1985 depth 1

Function : MULTIREG
Data case no. 1 to 192
t soisture

temperature
core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sum of Squares d: Mean Square F Sign1t
Regression 3.274534 2 1.63727 0 36 0.699
Residual 423.757789 93 4.55654
Total 427.032323 95
Data tile : TARSBS
Title : Tarsonemus 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d: Mean Square F Signit
Regression 6.490968 2 3.24548 1.37 0.258
Residual 219.754219 93 2.36295
Total 226.245187 95
Data tile : TAR586
Title : Tarsonemus 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
t moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d: Mean Square F Signit
Regression 10531.555803 2 5265.77790 6.92 0.002
Residual 75373.442769 99 761.34791
Total 85904.998572 101
Data tile : TAR886
Title : Tarsonemus 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
t moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d! Mean Square F Signit
Regression 11703.541025 2 5851.77051 5.29 0.007
Residual 109474.790499 99 1105.80596

Total l21178.331523 lOl

179

Data tile : BAM85
Title : Bakerdania 1985 depth 1

Function : CORR
Data case no. 1 to 192

 

 

t moisture

Variable 7 Average - 12.96

Variance - 12.80

core means

Variable 9 Average - 0.87

Variance - 1.87

Number - 96

Covariance - 1.31 Correlation - 0.268

Intercept - -0.46 Slope - 0.103 Standard Error - 0.038

 

 

Student's T value - 2.699 Probability - 0.008 _ ----
temperature

Variable 8 Average - 16.76

Variance - 49.34

COT. BOOM

Variable 9 Average - 0.87

Variance - 1.87

Number - 96

Covariance - -3.62 Correlation - -0.377

Intercept - 2.10 Slope - -0.073 Standard Error - 0.019
Student's T value - 3.944 Probability - 0.000

 

Data tile : BAK85
Title : Bakerdania 1985 depth 2

Function : CORR
Data case no. 1 to 192

 

 

--- _..._._....__._

t moisture

Variable 7 Average - 11.44

Variance - 9.65

core means

Variable 9 Average - 0.50

Variance - 0.97

Number - 96

Covariance - 0.46 Correlation - 0.151

Intercept - -0.04 Slope - 0.048 Standard Error - 0.032

 

Student's T value - 1.479 Probability - 0.143

temperature

Variable 8 Average - 14.81

Variance - 38.75

core means

Variable 9 Average - 0.50

Variance - 0.97

Number - 96

Covariance - -1.18 Correlation - -0.192

Intercept - 0.95 Slope - -0.030 Standard Error - 0.016

Student's T value - 1.899 Probability - 0.061

180

Data tile : BAK86
Title : Bakerdania 1986 999th 1

Function : CORR
Data case no. 1 to 204

 

1 moisture

Variable 7 Average I 15.24
Variance I 10.07

core means

Variable 9 Average I 1.01
Variance I 3.18

Number I 102

 

Covariance I 0.31 Correlation I 0.054

Intercept I 0.55 Slope I 0.030 Standard Error I 0.056
Student’s T value I 0.542 Probability I 0.589

temperature

Variable 8 Average I 15.35

Variance I 52.32

core means

Variable 9 Average I 1.01

Variance I 3.18

Number I 102

Covariance I I2.50 Correlation I I0.194
Intercept I 1.74 Slope I I0.048 Standard Error I 0.024
Student's T value I 1.974 Probability.- 0.051.

 

Data tile : BAK86
Title : Bakerdania 1986 depth 2

Function : CORR
Data case no. 1 to 204

 

t moisture

Variable 7 Average I 14.05
Variance I 4.56

core means

Variable 9 Average I 0.44
Variance I 0.77

Number I 102

 

Covariance I I0.07 Correlation I I0.039

Intercept I 0.67 Slope I I0.016 Standard Error I 0.041
Student’s T value I 0.391 Probability I 0.696

temperature

Variable 8 Average I 14.18

Variance I 43.68

core means

Variable 9 Average I 0.44

Variance I 0.77

Number I 102
Covariance I I0.41 Correlation I -0.071
Intercept I 0.58 Slope I I0.009 Standard Error I 0.013

Student's T value I 0.715 Probability I 0.476

 

1131

 

 

 

 

 

 

 

 

 

 

 

 

Data tile : BAM85
Title : Bakerdania 1985 depth 1
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares dt Mean Square F Signit
Regression 25.224584 2 12.61229 7.70 0.001-
Residual 152.4274ll 93 1.63900
Total 177.651995 95
Data tile : BAK85
Title : Bakerdania 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d: Mean Square F Signit
Regression 3.410317 2 1.70516 1.79 0.172
Residual 88.371215 93 0.95023
Total 91.781532 95
Data tile : BAN86
Title : Bakerdania 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d1 Mean Square F Signif-
Regression 12.326013 2 6.16301 1.98 2:144
Residual 308.445622 99 3.11561 -———g
Total 320.771635 101 --
Data tile : BAR86
Title : Bakerdania 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
' nit
Sum 01 Squares 6! Mean Square F 51?...-
- " 0 46 0.634
Regression 0.708368 2 3°33;;:
Residual 76.584558 99 -
roggl 77.292926 101 _____-__-___-,_--

 

182

Data tile : EUPOD85
Title : Eupodes 1985 depth 1

Function : CORR
Data case no. 1 to 192

8 moisture

 

Variable 7 Average I 12.96

Variance I 12.80

core means

Variable 9 Average I 0.98

Variance I 2.43

Number I 96

Covariance I -1.83 Correlation I -0.327
Intercept I 2.83 Slope I I0.l43 Standard Error I 0.043
Student's T value I 3.358 Probability I 0.001
temperature

Variable 8 Average I 16.76

Variance I 49.34

601'. means

Variable 9 Average I 0.98

Variance I 2.43

Number I 96

Covariance I 3.07 Correlation I 0.280

Intercept I -0.06 Slope I 0.062 Standard Error I 0.022

Student's T value I 2.825 Probability I 0.006

Data tile : EUPODBS
Title : Eupodes 1985 depth 2

Function : CORR
Data case no. 1 to 192

8 moisture

 

 

 

 

Variable 7 Average I 11.44

Variance I 9.65

core means

Variable 9 Average I 0.07

Variance I 0.03

Number I 96

Covariance I I0.03 Correlation I -0.046

Intercept I 0.10 Slope I -0.003 Standard Error I 0.006
Student's T value I 0.450 Probability I 0.654

temperature ......
Variable 8 Average I 14.81

Variance I 38.75

core means

Variable 9 Average I 0.07

Variance I 0.03

Number I 96

Covariance I I0.15 Correlation I -0.136

Intercept I 0.12 Slope I -0.004 Standard Error I 0.003

Student's T value I 1.332 Probability I 0.186

183

Data tile : EUP0086
Title : Eupodes 1986 depth 1

Function : CORR
Data case no. 1 to 204

 

8'moisture
Variable 7 Average I 15.24
Variance I 10.07

core means
Variable 9 Average I 0.41
Variance I 0.72

Number ' 102'

 

Covariance I I0.47 Correlation I -0.174

Intercept I 1.11 Slope I I0.046 Standard Error I 0.026
Student's T value I 1.764 Probability I 0.081

temperature

Variable 8 Average I 15.35

Variance I 52.32

core means
Variable 9 Average I 0.41
Variance I 0.72

Number I 102

Covariance I 1.35 Correlation I 0.221
Intercept I 0.01 Slope I 0.026 Standard Error I 0.011
Student's T value I 2.266 Probability I 0.026

 

Data tile : EUPOD86
Title : Eupodes 1986 depth 2

Function : CORR
Data case no. 1 to 204

8 moisture“-

Variable 7 Average I 14.05
Variance I 4.56

core means

Variable 9 Average I 0.04
Variance I 0.02

NUIDOF I 102

 

Covariance I I0.10 Correlation I I0.296

Intercept I 0.34 Slope I -0.021 Standard Error I 0.007
Student's T value I 3.103 Probability I 0.002

temperature

Variable 8 Average I 14.18

Variance I 43.68

core means

Variable 9 Average I 0.04

Variance I 0.02

Number I 102
Covariance I 0.17 Correlation I 0.168
Intercept I -0.01 Slope I 0.004 Standard Error I 0.002

Student’s T value I 1.709 Probability I 0.090

 

11234

Data File
Title

EUPODBS
Eupodes 1985 depth 1

Function MULTIREG
Data case no. l to 192

8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE

Sum of Squares

 

 

 

 

 

 

 

 

dt Mean Square F Signit
Regression 25.691795 2 12.94590 5.66 '6.0
Residual 205.345776 93 2.20602 \1_ 0‘
Total 231.237572 95
Data tile : EUPOOBS
Title : Eupodes 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum 02 Squares dt Mean Square F Signit
Regression 0.195179 2 0.09759 3.19 0.046
Residual 2.843137 93 0.03057
Total 3.038316 95
Data tile : EUPODB6
Title : Eupodes 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core leans
ANALYSIS OF VARIANCE TABLE
Sum 02 Squares dt Mean Square F Signit
Regression 4.107435 2 2.05372 2.97 0.056
Residual 68.342847 99 0.69033
Total 72.450202 101
Data tile : EUPODB6
Title : Eupodes 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares dt Mean squat. F signit
Regression 0.223976 2 0.11199 5.17 0.007
Residual 2.144259 99 0-02166
Total 2.368235 101

 

185

Data tile : 71065
Title : Tydeus bedfordiensis 1985 depth 1

Function : CORR
Data case no. 1 to 192

 

 

8 moisture

 

Variable 7 Average I 12.96

Variance I 12.80

core means

Variable 9 Average I 0.39

Variance I 0.98

Number I 96

Covariance I -0.83 Correlation I -0.235
Intercept I 1.23 Slope I -0.065 Standard Error I 0.028
Student's T value I 2.340 Probability I 0.021
temperature

Variable 8 Average I 16.76

Variance I 49.34

core means

Variable 9 Average I 0.39

Variance I 0.98

Number I 96

Covariance I 1.29 Correlation I 0.186

Intercept I -0.05 Slope I 0.026 Standard Error I 0.014

Student's T value I 1.833 Probability I 0.070

Data tile : TYD85
Title : Tydeus bedfordiensis 1985 depth 2

Function : CORR
Data case no. 1 to 192

 

8 aoisture

 

Variable 7 Average I 11.44

Variance I 9.65

core means

Variable 9 Average I 0.26

Variance I 0.36

Number I 96

Covariance I -0.54 Correlation I I0.289
Intercept I 0.89 Slope I I0.056 Standard Error I 0.019
Student's T value I 2.927 Probability I 0.004
temperature

Variable 8 Average I 14.81

Variance I 38.75

core means

Variable 9 Average I 0.26

Variance I 0.36

Number I 96

Covariance I 1.16 Correlation I 0.312

Intercept I I0.19 Slope I 0.030 Standard Error I 0.009
Student's T value I 3.188 Probability I 0.002

186

Data tile : TY086
Title : Tydeus bedfordiensis 1986 depth 1

Function : CORR
Data case no. 1 to 204

 

8 moisture

Variable 7 Average I 15.24
Variance I 10.07

core means

Variable 9 Average I 0.47
Variance I 0.67

Number I 102

 

Covariance I I0.66 Correlation I -0.253

Intercept I 1.47 Slope I -0.065 Standard Error I 0.025
Student's T value I 2.616 Probability I 0.010

temperature

Variable 8 Average I 15.35

Variance I 52.32

core means

Variable 9 Average I 0.47

Variance I 0.67

Number I 102
Covariance I 2.51 Correlation I 0.425
Intercept I -0.26 Slope I 0.048 Standard Error I 0.010

Student's T value I 4.694 Probability I 0.000

 

Data File : TY086
Title : Tydeus bedfordiensis 1986 depth 2

Function : CORR
Data case no. 1 to 204

 

8 moisture-

Variable 7 Average I 14.05
Variance I 4.56

core means

Variable 9 Average I 0.44
Variance I 0.64

Number I 102

 

Covariance I I0.18 Correlation I I0.108

Intercept I 1.01 Slope I I0.040 Standard Error I 0.037
Student's T value I 1.088 Probability I 0.279

temperature

Variable 8 Average I 14.18

Variance I 43.68

core means

Variable 9 Average I 0.44

Variance I 0.64

Number I 102
Covariance I 2.05 Correlation I 0.389
Intercept I I0.22 Slope I 0.047 Standard Error I 0.011

Student's T value I 4.220 Probability I 0.000

 

187

Data tile : TYD85
Title : Tydeus bedfordiensis 1985 depth 1

Function : mung
Data case no. 1 to 192

8 moisture

temperature
core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sum of Squares a: Mean Square F Signit
Regression 5.184013 2 2.59201 2.75 0.069
Residual 87.577983 93 0.94170
Total 92.761996 95
Data tile : TYDBS
Title : Tydeus bedfordiensis 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum 01 Squares dt Mean Square F Signit
Regression 3.573563 2 1.78678 5:48_ 0'023.
Residual 30.313570 93.\ 0.32595 ‘1- 3-". ’
Total 33.887133 95
Data tile : TY086
Title : Tydeus bedtordiensis 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum ot Squares d: Mean Square F Signit
Regression 9.728057 2 4.86403 8.82 0.000
Residual 54.591595 99 0.55143
Total 64.319652 101
Data tile : TYD86
Title : Tydeus bedfordiensis 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d! Mean Square F Signit
Regression 12.619627 2 6.30981 11.39 0.000
Residual 54.822701 99 0.55376

Total

67.442329 lOl

188

Data tile : META85
Title : Metapronematus leucohippeus 1985 depth 1

Function : CORR
Data case no. 1 to 192

8 moisture

 

Variable 7 Average I 12.96

Variance I 12.80

core means

Variable 9 Average I 0.24

Variance I 0.22

Number I 96

Covariance I I0.40 Correlation I -0.235

Intercept I 0.64 Slope I -0.031 Standard Error I 0.013
Student's T value I 2.347 Probability I 0.021

temperature

Variable 8 Average I 16.76

Variance I 49.34

core means

Variable 9 Average I 0.24

Variance I 0.22

Number I 96

Covariance I 0.57 Correlation I 0.172

Intercept I 0.05 Slope I 0.012 Standard Error I 0.007
Student's T value I 1.692 Probability I 0.094

 

Data tile : META85
Title : Metapronematus leucohippeus 1985 depth 2

Function : CORR
Data case no. 1 to 192

 

 

8 moisture

 

Variable 7 Average I 11.44

Variance I 9.65

core means

Variable 9 Average I 0.32

Variance I 0.44

Number I 96

Covariance I I0.61 Correlation I I0.298
Intercept I 1.05 Slope I -0.064 Standard Error I 0.021
Student's T value I 3.026 Probability I 0.003
temperature

Variable 8 Average I, 14.81

Variance I 38.75

core means

Variable 9 Average I 0.32

Variance I 0.44

Number I 96

Covariance I 1.62 Correlation I 0.392

Intercept I ~0.30 Slope I 0.042 Standard Error I 0.010
Student's T value I 4.135 Probability I 0.000

 

_ ‘m-e.I¢ -- «_-- — -

189

‘0

Data tile : META86
Title : Metapronematus leucohippeus 1986 depth 1

Function : CORR
Data case no. 1 to 204

 

8 moisture

Variable 7 Average I 15.24
Variance I 10.07

core means

Variable 9 Average I 0.56
Variance I 2.57

Number I 102
Covariance I 0.51 Correlation I 0.101

Intercept I I0.22 Slope I 0.051 Standard Error I 0.050

 

Student’s T value I 1.015 Probability I 0.313
temperature

Variable 8 Average I 15.35

Variance I 52.32

core means

Variable 9 Average I 0.56

Variance I 2.57

Number I 102

Covariance I I0.67 Correlation I I0.058
Intercept I 0.75 Slope I I0.013 Standard Error I 0.022
Student’s T value I 0.580 Probability I 0.563

 

Data tile : META86
Title : Metapronematus leucohippeus 1986 depth 2

Function : CORR
Data case no. 1 to 204

 

 

8 moisturd

Variable 7 Average I 14.05

Variance I 4.56

core means

Variable 9 Average I 0.50

Variance I 2.44

Number I 102

Covariance I 0.59 Correlation I 0.178

Intercept I I1.33 Slope I 0.130 Standard Error I 0.072

 

Student's T value I 1.810 Probability I 0.073

temperature

Variable 8 Average I 14.18

Variance I 43.68

core means

Variable 9 Average I 0.50

Variance I 2.44

Number I 102

Covariance I -0.98 Correlation I -0.095

Intercept I 0.82 Slope I -0.022 Standard Error I 0.024

Student's T value I 0.952 Probability I 0.343

 

190

Data tile : META86
Title : Metapronematus leucohippeus 1986 depth 1

Function : MULTIREG
Data case no. 1 to 204

8 moisture

temperature
core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sum 08 Squares d2 Mean Square F Signir
Regression 2.720023 2 1.36001 0.52 O 5"—
Residual 256. 906296 99 2. 59501 ' 94
Total 259.626319 101
Data tile : META86
Title : Metapronematus leucohippeus 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares d: Mean Square F Signir
Regression 8.252352 2 4.12618 1.72 0.185
Residual 237.689479 99 2.40090
Total 245.941831 101
Data tile : META85
Title : Metapronematus leucohippeus 1985 depth 1
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares 68 Mean Square F Signit
Regression 1.164362 2 0.58218 2.73 0.071
Residual 19.845688 93 0.21339
Total 21.010050 95
Data File : META85
Title : Metapronesatus leucohippeus 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares dt Mean Square F Signit
Regression 6.435465 2 3.21773 8.48 0.000
Residual 35.302509 93 0.37960
Total 41.737974 95

 

191

 

 

 

 

 

Data file : RHODBS
Title : Rhodacarellus silesiacus 1985 depth 1
Function : CORR
Data case no. 1 to 192
8 moisture - _“
Variable 7 Average I 12.96
Variance I 12.80
core means
Variable 9 Average I 1.97
Variance I 7.58
Number I 96
Covariance I 0.24 Correlation I 0.024
Intercept I 1.73 Slope I 0.019 Standard Error I 0.079
Student's T value I 0.233 Probability I 0.816
temperature
Variable 8 Average I 16.76
Variance I 49.34
core means
Variable 9 Average I 1.97
Variance I 7.58
Number I 96
Covariance I I1.40 Correlation I I0.072
Intercept I 2.44 Slope I I0.028 Standard Error I 0.040
Student's T value I 0.702 Probability I 0.485
Data file : RHOD85
Title : Rhodacarellus silesiacus 1985 depth 2
Function : CORR
Data case no. 1 to 192
8 moisture
Variable 7 Average I 11.44
Variance I 9.65
core means
Variable 9 Average I 2.64
Variance I 43.90
Number I 96
Covariance I 4.38 Correlation I 0.213
Intercept I I2.56 Slope I 0.454 Standard Error I 0.215
Student's T value I 2.110 Probability I 0.037
temperature
Variable 8 Average I 14.81
Variance I 38.75
core means
Variable 9 Average I 2.64
Variance I 43.90
Number I 96
Covariance I -7.37 Correlation I -0.179
Intercept I 5.45 Slope I I0.190 Standard Error I 0 108
Student's T value I 1.761 Probability I 0.081

 

192

 

 

 

 

 

'
Data tile : RNOD86
Title : Rhodacarellus silesiacus 1986 depth 1
Function : CORR
Data case no. 1 to 204
8 moisture
Variable 7 Average I 15.24
Variance I 10.07
core means
Variable 9 Average I 1.65
Variance I 9.49
Number I 102
Covariance I I0.71 Correlation I I0.072
Intercept I 2.73 Slope I I0.070 Standard Error I 0.097
Student's T value I 0.726 Probability I 0.469
temperature
Variable 8 Average I 15.35
Variance I 52.32
core means
Variable 9 Average I 1.65
Variance I 9.49
Number I 102
Covariance I I0.07 Correlation I -0.003
Intercept I 1.67 Slope I I0.001 Standard Error I 0.043
Student's T value I 0.031 Probability I 0.976
Data tile : RNODB6
Title : Rhodacarellus silesiacus 1986 depth 2
Function : CORR
Data case no. 1 to 204
4 ”156?.“
Variable 7 Average I 14.05
Variance I 4.56
core means
Variable 9 Average I 1.32
Variance I 8.92
Number I 102
Covariance I 0.26 Correlation I 0.041
Intercept I 0.52 Slope I 0.057 Standard Error I 0.140
Student's T value I 0.410 Probability I 0.683
temperature
Variable 8 Average I 14.18
Variance I 43.68
core means
Variable 9 Average I 1.32
Variance I 8.92
Number I 102
Covariance I -4.99 Correlation I I0.253
Intercept I 2.94 Slope I I0.114 Standard Error I 0.044

Student’s T value I 2.613 Probability I 0.010

 

193

Data tile : RNODa5
Title : Rhodacarellus silesiacus 1985 depth 1

Function : MULTIREG
Data case no. 1 to 192
8 moisture

temperature
core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sum of Squares d: Mean Square F Signit
Regression 4.767810 2 2.38391 0.31 0.734
Residual 715.581552 93 7.69443
Total 720.349362 95
Data tile : RM0085
Title : Rhodacarellus silesiacus 1985 depth 2
Function : MULTIREG
Data case no. 1 to 192
8 soisture
temperature
core aeans
ANALYSIS OF VARIANCE TABLE
Sum 01 Squares d8 Mean Square F Signit
Regression 193.465039 2 96.73252 2.26 0.110
Residual 3977.333892 93 42.76703
Total 4170.798931 95
Data File : RN0086
Title : Rhodacarellus silesiacus 1986 depth 1
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares 6! Mean Square F Signir
Regression 6.356084 2 3.17804 0.33 0.719
Residual 952.290545 99 9.61910
Total 958.646629 101
Data tile : RNOD86
Title : Rhodacarellus silesiacus 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core seans
ANALYSIS OF VARIANCE TABLE
Sum of Squares d2 Mean Square F Signit
Regression 58.855384 2 29.42769 3.46 0.035
Residual 841.818774 99 8.50322

Total 900.674158 lOl

Data tile
Title

Function
Data case no.

Nypaspis aculiter 1985 depth 1

 

8 moisture
Variable
Variance I

core means
Variable
Variance I

Number I 96

Covariance I

Intercept I

Student's T value I

Correlation I
Standard Error I

Probability I

0.027

 

temperature
Variable
Variance I

core means
Variable
Variance I

Number I 96

Covariance I

Intercept I

Student's T value I

Data tile
Title : Hypaspis aculifer 1985 depth 2

Function
Data

Correlation I
Standard Error I
Probability I

 

8 moisture
Variable
Variance I

core means
Variable
Variance I

Number I 96

Covariance I

Intercept I

Student’s T value I

0.014

 

Correlation I
Standard Error I
Probability I

 

temperature
Variable
Variance I

core means
Variable
Variance I

NUIDCE I 96

Covariance I
Intercept I

Student's T value I

Correlation I
Standard Error I

Probability I

0.003

 

195

 

 

 

 

 

 

Data tile : NYPA86
Title : Nypaspis aculiter 1986 depth 1
Function : CORR
Data case no. 1 to 204
8 moisture
Variable 7 Average I 15.24
Variance I 10.07
core means
variable 9 Average I 0.25
Variance I 0.31
Number I 102
Covariance I 0.01 Correlation I 0.007
Intercept I 0.23 Slope I 0.001 Standard Error I 0.017
Student’s T value I 0.072 Probability I 0.943
temperature
Variable 8 Average I 15.35
Variance I 52.32
core means
Variable 9 Average I 0.25
Variance I 0.31
Number I 102
Covariance I 0.53 Correlation I 0.132
Intercept I 0.10 Slope I 0.010 Standard Error I 0.008
Student's T value I 1.327 Probability I 0.188
Data tile : NYPA86
Title : Mypaspis aculifer 1986 depth 2
Function : CORR
Data case no. 1 to 204
8 moisture '___—_”---L_tm___~_ —
Variable 7 Average I 14.05
Variance I 4.56
core means
Variable 9 Average I 0.01
Variance I 0.00
Number I 102
Covariance I -0;01 Correlation I I0.077
Intercept I 0.05 Slope I -0.002 Standard Error I 0.003
Student's T value I 0.770 Probability I 0.443
temperature
Variable 8 Average I 14.18
Variance I 43.68
core means
Variable 9 Average I 0.01
Variance I 0.00
Number I 102
Covariance I -0.02 Correlation I I0.042
Intercept I 0.02 Slope I I0.000 Standard Error I 0.001
Student's T value I 0.424 Probability I 0.672

 

196

Data tile : NYPA85
Title : Nypaspis aculirer 1985 depth 1

Function : MULTIREG
Data case no. 1 to 192

8 moisture
temperature
core means

ANALYSIS OF VARIANCE TABLE

 

 

 

 

 

 

 

Sum of Squares a: Mean Square F Signit
Regression 0.386077 2 0.19304 0.21 0.810
Residual 84.882119 93 0.91271
Total 85.268196 95
Data tile : MYPA85
Title : Nypaspis aculiter 1985 depth 2
Function : MULTIREO
Data case no. 1 to 192
8 moisture
tesperature
core means
ANALYSIS OF VARIANCE TABLE
Sum of Squares dt Mean Square F Signit
Regression 0.024148 2 0.01207 0.46 0.634
Residual 2.451452 93 0.02636
Total 2.475600 95
Data tile : HYPA86
Title : Nypaspis aculiter 1986 depth 1
Function : MULTIREC
Data case no. 1 to 204
8 moisture
temperature
core means
ANALYSIS OF VARIANCE TABLE
Sum 02 Squares a: Mean Square F Signit
Regression 0.684911 2 0.34246 1.12 0.331
Residual 30.315637 99 0.30622
Total 31.000548 101
Data tile : NYPA86
Title : Nypaspis aculiter 1986 depth 2
Function : MULTIREG
Data case no. 1 to 204
8 moisture
temperature
core seans
ANALYSIS OF VARIANCE TABLE
Sum of Squares dt Mean Square F Signit
Regression 0.004460 2 0.00223 0.53 0.588
Residual 0.414058 99 0.00418
Total 0.418518 -101

"I1111111111“

 

 

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