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Effects of dioecy on population genetic structure in carex scirpoidea michaux ssp. scirpoidea

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Title:
Effects of dioecy on population genetic structure in carex scirpoidea michaux ssp. scirpoidea
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Yarbrough, Stephen L
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English
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88 leaves : ; 28 cm

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Subjects / Keywords:
Carex -- Genetics ( lcsh )
Cyperaccae -- Genetics ( lcsh )
Plant diversity -- Colorado ( lcsh )
Plants -- Reproduction ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Bibliography:
Includes bibliographical references (leaves 83-88).
General Note:
Department of Integrative Biology
Statement of Responsibility:
by Stephen L. Yarbrough.

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|University of Colorado Denver
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ocm45139484
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LD1190.L45 2000m .Y37 ( lcc )

Full Text
EFFECTS OF DIOECY ON POPULATION GENETIC STRUCTURE IN CAREX
SCIRPOIDEA MICHAUX ssp. SCIRPOIDEA
by
Stephen L. Yarbrough
B.A., University of Kansas, 1983
A thesis submitted to the
University of Colorado at Denver
in partial fulfillment
of the requirements for the degree of
Master of Arts
Biology
2000


This thesis for the Master of Arts
degree by
Stephen L. Yarbrough
has been approved
by
Leo P. Bruederle, Ph. D.
Diana Tomback, Ph. D.
Date


Yarbrough, Stephen L. (M.A., Biology)
Effects of Dioecy on Population Genetic Structure in Carex scirpoidea Michaux ssp.
scirpoidea (Cyperaceae)
Thesis directed by Dr. Leo P. Bruederle
ABSTRACT
A strictly dioecious breeding system results in obligate outcrossing in angiosperms.
Supporting this, the population genetic literature reveals that dioecious species tend to
maintain relatively high genetic diversity (P = 65%, A = 2.49, He = 0.297) apportioned
within, rather than among populations (Gsr = 0.204). Allozyme analysis conducted on
five Colorado populations of the dioecious sedge, Carex scirpoidea ssp. scirpoidea
(Cyperaceae), revealed only modest levels of diversity (P = 20%, A = 1.33, Ap = 2.17,
He = 0.068), presumably due to the isolation of these disjunct populations from the
primarily boreal distribution of the species. However, as expected, genetic diversity was
apportioned among individuals within populations (GST = 0.123), with all populations
in Hardy-Weinberg Equilibrium, but slight heterozygous excess. Population
differentiation in C. scirpoidea ssp. scirpoidea was comparable to other dioecious
species, as well as outcrossing, rhizomatous carices (Gsr= 0.159), and wind-pollinated,
outcrossing species (Gsr= 0.099). Dioecy may effectively maintain population genetic
structure in these disjunct Colorado populations of C. scirpoidea ssp. scirpoidea
despite the reduction of genetic diversity driven by biogeographic isolation.
This abstract accurately represents the content of the candidates thesis. I
recommend its publication.
Leo P. Bruederle, Ph. D.
in


DEDICATION
This research is dedicated to my wife and children who have provided me with the
inspiration and perseverance to complete this work.


ACKNOWLEDGMENTS
I would like to thank my advisor, Dr. Leo P. Bruederle, for giving so much of his
own time and expertise to this effort. His instruction and guidance were instrumental
in completing this research. I wish to thank Dr. Diana Tomback for her excellent
instruction in graduate classes and her critical review and input on this thesis. I also
wish to thank the University of Colorado at Denver for providing excellent facilities
and resources with which to conduct the research.


CONTENTS
Figures...................................................................viii
Tables .....................................................................ix
Chapter
1. Introduction............................................................1
1.1 Taxonomy ................................................................2
1.2 Biogeography ............................................................5
1.3 Reproductive Biology ....................................................7
1.4 Research Hypotheses ...................................................11
2. Materials and Methods ..................................................13
2.1 Field Methods .........................................................13
2.2 Laboratory Methods ....................................................16
2.3 Statistical Methods ...................................................17
3. Results.................................................................20
3.1 Genetic Diversity .....................................................20
3.2 Population Genetic Structure ..........................................24
4. Discussion .............................................................31
vi


Appendix
A. Gel and Electrode Buffer Systems and Substrate-Specific Stains ..38
B. BIOSYS Data .....................................................39
C. GENESTAT Data ...................................................60
D. Genetic Diversity and Structure in Dioecious Flowering Plants....64
E. Genetic Diversity and Structure in Monoecious Flowering Plants ..65
F. Genetic Diversity and Structure in Monoecious Carices ...........66
G. Genetic Diversity and Structure in Caespitose Carices ...........67
H. Genetic Diversity and Structure in Rhizomatous Carices...........68
I. Mann-Whitney C/-test Statistical Results .........................69
References ..........................................................83
vu


FIGURES
Figure
1.1 Line drawing of Carex scirpoidea (Cyperaceae). Adapted from Hermann
(1970).......................................................................4
1.2 North American range of Carex scirpoidea ssp. scirpoidea (Cyperaceae).
Adapted from Dunlop (1990)................................................. 6
2.1 Park County, Colorado collection sites for Carex scirpoidea ssp. scirpoidea and
San Juan County, Colorado collection sites for Carex scirpoidea ssp.
pseudoscirpoidea (Cyperaceae)...............................................14
vm


TABLES
Table
2.1 Carex scirpoidea ssp. scirpoidea (Cyperaceae) sites in Park County, CO,
sampled for allozyme analysis ...............................................15
3.1.1 Allele frequencies at seven polymorphic loci in five populations of Carex
scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park County, CO ..........21
3.1.2 Genetic diversity in five populations of Carex scirpoidea ssp. scirpoidea
(Cyperaceae) sampled in Park County, CO .....................................23
3.2.1 Genetic structure in five populations of Carex scirpoidea ssp. scirpoidea
(Cyperaceae) sampled in Park County, CO .....................................25
3.2.2 Wrights fixation indices for polymorphic loci resolved in five populations of
Carex scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park County, CO ....27
3.2.3 Summary ofF-statistics at all loci resolved in five populations of Carex
scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park County, CO...........29
4.0 Comparison of genetic diversity between Carex scirpoidea ssp. scirpoidea
(Cyperaceae) sampled in Park County, CO with other dioecious, wind-pollinated/
outcrossing, monoecious, caespitose, and rhizomatous flowering plants .......36
IX


1. Introduction
Since 1986, a large body of data describing population genetic diversity and structure
in the genus Carex (Cyperaceae) has accumulated. Starch gel electrophoresis and
allozyme analysis have been used primarily to assess systematic relationships and
elucidate genetic structure within and among populations of closely related species of
Carex, such as the C. crinita Lam. complex (Bruederle and Fairbrothers, 1986).
More recently, these data have also been used to study population genetic variation
in rare species, such as C. mitchelliana M. A. Curtis (Bruederle et al., 1989); hybrid
origins of taxa, such as C. membranaceae Hook. utriculata, C. x physocarpoides,
and C. x mainensis (Ford et al., 1993); and finally, to test hypotheses regarding
population genetic structure and breeding system in clonal species, such as C.
bigelowii Torr (Jonsson, 1995; Jonsson et al., 1996).
All of the aforementioned research has considered population genetic variation in
monoecious carices. Monoecy, the condition in which each plant of a species bears
both unisexual male and unisexual female flowers, is the dominant breeding system in
this large genus. However, dioecy has been reported from three sections of the
genus: Scirpinae, Dioicae, and Pictae (Martens, 1939). Dioecy is predicted to have
a significant influence on genetic structure in C. scirpoidea ssp. scirpoidea,
particularly as effected by gene flow.
The primary objective of this research was to study the effect of dioecy on
population genetic structure in a perennial herb. The dioecious sedge, C. scirpoidea
Michaux ssp. scirpoidea, was used as the model system. Although this has not been
previously addressed in Carex, a modest number of investigations have utilized
1


allozyme or RAPD data to study genetic diversity and structure in other dioecious
taxa; these include Populus (Jelinski and Cheliak, 1992), Cecropia (Alvarez-Buylla
and Garay, 1994), Eurya (Chung and Kang, 1994), Buchloe (Peakall et al., 1995),
Schiedea and Alsinidendron (Weller et al., 1996), and Schizopepon (Akimoto et al.,
1999). This research has revealed relatively high levels of genetic diversity, e.g.,
percentage of polymorphic loci (P) = 65%, with the majority of this (approximately
80%) due to differences among individuals within populations. Generally speaking,
populations are poorly differentiated genetically, e.g., mean GST.
Five populations of C. scirpoidea ssp. scirpoidea, representing a disjunct distribution
of this species, were sampled in Park County, Colorado, USA. Starch gel
electrophoresis and allozyme analysis were utilized to gather genotypic data. These
data were then utilized to make comparisons of genetic diversity and apportionment
between C. scirpoidea ssp. scirpoidea and several other taxa of interest.
1.1 Taxonomy
The Canadian single-spike sedge, C. scirpoidea ssp. scirpoidea, is a member of
Carex section Scirpinae Tuckerman, which is comprised of only two species
(Dunlop, 1990): C. curatorum Stacey and C. scirpoidea. Dunlop (1990) further
recognized four subspecies comprising C. scirpoidea: C. scirpoidea ssp. scirpoidea,
C. scirpoidea ssp. pseudoscirpoidea (Rydberg) Dunlop, C. scirpoidea ssp.
stenochlaena (Holm) Mack., and C. scirpoidea ssp. convoluta Kiikenthal.
Section Scirpinae is discriminated from other sections in the genus Carex by the
presence of solitary spikes, unisexual inflorescences, pubescent peryginia, and
2


tristigmatic pistils. Within section Scirpinae, C. scirpoidea is discriminated from C.
curatorum by achenes that fill the peryginia, glabrous adaxial leaf surfaces, and a
primarily arctic and/or alpine distribution. Car ex scirpoidea ssp. scirpoidea may be
differentiated from the other three subspecies of C. scirpoidea by relatively ovate to
obovate peryginia, anthocyanic scale leaves at the base of the culms (i.e.,
aphyllopodic culms), and flat to widely V-shaped leaves. Plants average two to three
decimeters tall.
In Carex, the production of monopodial and sympodial rhizomes, coupled with
variable rhizome length and aerial culm production, results in different growth forms,
i.e., tussock, tufted, caespitose, and rhizomatous (Jermy et al., 1982). Carex
scirpoidea ssp. scirpoidea is a loosely caespitose plant, with short rhizomes present
(Fig. 1.1).
3


Fig. 1.1. Line drawing of Carex scirpoidea (Cyperaceae). Adapted from Hermann
(1970).
4


1.2 Biogeography
Car ex scirpoidea ssp. scirpoidea is generally widespread and contiguous in the
northern latitudes of North America, from the arctic and subarctic, south through the
New England states and much of western Canada. It also occurs in several disjunct
pockets in the Great Lakes region and throughout the Rocky Mountains of the
Western United States (Fig. 1.2). Dunlop (1990) proposed three hypotheses for the
current distribution of C. scirpoidea ssp. scirpoidea. The first hypothesis states that
C. scirpoidea ssp. scirpoidea may have survived glaciation in refugia in the Beringian
area of Alaska, and subsequently migrated south and east. The second hypothesis
states that it survived south of the ice sheets in the Rocky Mountains and
subsequently migrated eastward and north; however, the species is currently poorly
represented in the southern Rocky Mountains compared with Beringia. The third
hypothesis states that the species survived periglacially, having a presence in eastern
North America and elsewhere. In any case, the Colorado populations of C.
scirpoidea ssp. scirpoidea are currently disjunct from other populations of the
species, with presumably little possibility of gene flow among them.
Accessions maintained at the University of Colorado Museum Herbarium (Herbarium
COLO) at Boulder, Colorado, revealed only eight discrete populations of C.
scirpoidea ssp. scirpoidea in Colorado (Ranker, 1997): Mt. Sheridan (Park County,
CO), Horseshoe Mountain Cirque (Park County, CO), High Creek Fen (Park
County, CO), Silverheels Ranch, Fairplay (Park County, CO), Geneva Creek (Park
County, CO), Beaver Creek (Park County, CO), and along the Middle Fork of the
South Platte (Park County, CO).
5


Fig. 1.2. North American range of Carex scirpoidea ssp. scirpoidea (Cyperaceae).
Adapted from Dunlop (1990).
6


Colorado populations of C. scirpoidea ssp. scripoidea are principally found covering
peaty hummocks at the edge of rich to extreme rich fens. These habitats are found in
the upper montane through alpine lifezones, and exist in areas with groundwater
discharge over or through calcareous bedrock or alluvium. In this environment, C.
scirpoidea ssp. scripoidea acts as a calciphile, tolerating high concentrations of
calcium, sodium, and magnesium salts in the peat hummocks. Dunlop (1990) noted
that C. scirpoidea ssp. scripoidea typically occurs on substrates with calcium
concentrations ranging between 2,058 parts per million (ppm) to 2.52%. The
extreme rich calcareous fens of South Park represent the very southern end of the
North American range for this habitat type (Cooper, 1996).
Cooper (1996) suggested that the characteristic flora of South Parks extreme rich
fens is controlled primarily by the peat substrate in which the plants grow. Only
0.3% of Colorados landscape are peatlands, which may explain the restricted
distribution of the species in Colorado. Biogeographically, dioecious species
typically comprise less than 10% of continental floras and temperate island floras
(Bawa, 1980). Locations rich in dioecious species include tropical islands, such as
Hawaii (27.7% of the flora) and New Zealand (>12% of the flora).
1.3 Reproductive Biology
Only seven percent of all genera of flowering plants have one or more dioecious
species, and only an estimated 14,260 of all 240,000 flowering plants species (6%)
are dioecious (Renner and Ricklefs, 1995). In contrast to the small overall numbers
of genera and species exhibiting the dioecious breeding system, Yampolsky and
Yampolsky (1922) reported 37 of 51 plant orders had some dioecious species.
7


Dioecy is very uncommon in the genus Carex, occurring in only three divergent
sections (Martens, 1939). It is thus likely, that dioecy has evolved independently in
these three sections of the genus. Dunlop (1990) found members of section
Scirpinae to be strictly dioecious (obligate outcrossers), with sex expression fixed,
and the ratio of male to female plants approximately 1:1 in most populations.
While strictly dioecious species possess male and female flowers on separate,
unisexual plants, there are other less strict forms of dioecy, including gynodioecy,
androdioecy, subdioecy, and cryptic dioecy. Gynodioecious plants bear either all
female flowers or all bisexual flowers; androdioecious plants bear either all male
flowers or all bisexual flowers; and subdioecious species may have all male or all
female flowered plants, as well as plants with a combination of bisexual and unisexual
flowers; Cryptic dioecy occurs when a species appears to have perfect flowered
(hermaphroditic) plants, but only a single sex is functional. These various forms of
dioecy contrast with monoecy, in which each plant of a species bears unisexual male
flowers and unisexual female flowers; and hermaphroditism, the most common
breeding system, in which all plants of a species bear only bisexual (perfect) flowers
(Yampolsky and Yampolsky, 1922; Lloyd, 1982).
A comprehensive study of the evolution of plant breeding systems began when
Darwin (1877) sought to catalog and evaluate the different systems he had observed.
Darwin remarked that, There is much difficulty in understanding why hermaphrodite
plants should ever have been rendered dioecious. In the intervening years since
Darwins statement, much effort has been applied to understand this breeding system.
It is generally accepted that dioecy evolves in response to selection pressures that
8


favor outcrossing (Baker, 1959; Bawa and Opler, 1975; Charlesworth and
Charlesworth, 1978 and 1979; Grant, 1951; Lloyd, 1975 and 1976; Mather, 1940
and 1973; Smith, 1978; Ross, 1978 and 1980). Studies by Lewis (1942) and
Westergaard (1958) supported the concept that dioecy evolved in several
independent taxa, from hermaphroditic or monoecious ancestors. Charlesworth and
Charlesworth (1978) remarked that it takes two mutations (one causing male sterility
and one causing female sterility) to transform a hermaphrodite or monoecious species
into a dioecious species. The likelihood of these two mutations arising
simultaneously appeared remote to the authors, who therefore assumed dioecy had
evolved from the intermediate condition of gynodioecy. Bawa (1980), who studied
evolutionary pathways leading to dioecy from hermaphroditism, gynodioecy,
androdioecy, monoecy, and heterostyly, argued that the evolution of dioecy should
not be viewed solely as driven by selection pressure for increased outcrossing. Other
factors such as sexual selection, optimization of seed dispersal, role of pollination,
and predation may all be important considerations in the evolution of the dioecious
breeding system.
Population genetic investigations of dioecious species are surprisingly limited.
Jelinski and Cheliak (1992) studied genetic diversity in the clonal pioneer tree species
Populus tremuloides Michx.(Salicaceae). All populations were found to maintain
high levels of genetic diversity (P = 89.1%, A = 2.14, H = 0.319), but deviated
somewhat from Hardy-Weinberg expectations with heterozygote excess (F = -
0.102). Alvarez-Buylla and Garay (1994) investigated the anemophilous tree species
Cecropia oblusifolia Bertol. (Moraceae), documenting a trend toward heterozygous
deficiency, but genetic diversity maintained within, rather than among populations.
9


Chung and Kang (1994) studied the Asian evergreen Eurya japonica Thunb.
(Theaceae). Genetic diversity in this species was also very high (P = 90 100%, A =
3.79, He = 0.462), with less than 7% of the genetic variation found among
populations. Peakall et al. (1995) evaluated two diploid races of the dioecious
shortgrass Buchloe dactyloides Engelmann (Poaceae). This study used allozyme
analysis and RAPD analysis to document a slight trend toward outcrossing (F,s = -
0.08). Weller et al. (1996) studied the Hawaiian genera Schiedea and Alsinidendron
(Caryophyllaceae: Alsinoideae), of which some species are hermaphrodites, some are
gynodioecious, and others are strictly dioecious. In general, selfing species had
lower genetic diversity than outcrossers. The very rare breeding system of
androdioecy was investigated by Akimoto et al. (1999) in Schizopepon
bryoniaefolius Maxim. (Cucurbitaceae), revealing a high degree of population
differentiation (G^ = 0.688). Male plants had an inbreeding coefficient of nearly
zero, while hermaphroditic plants showed significant heterozygous deficiency.
In addition to population genetic research on dioecious species, a number of
investigations have been conducted on obligate outcrossing species, including Liatris
cylindricea Michx. (Asteraceae) (Schaal, 1975), Stepanomeria exigua ssp. carotifera
(Compositae) (Gottlieb, 1975), Gaura longiflora Spach and G. demareei Raven &
Gregory (Onagraceae) (Gottlieb andPilz, 1976), Oenothera L. (Onagraceae)
(Ellstrand and Levin, 1980), Phlox spp. L. (Polemoniaceae) (Schwaegerle et al.,
1986; Levin, 1978), Heuchera spp. L. (Saxiffagaceae) (Soltis, 1985), Lasthenia spp.
(Asteraceae) (Crawford and OmdufF, 1989), and Vaccinium L. sect. Cyanococcus
Gray (Ericaceae) (Bruederle et al., 1991). In each case, the proportion of genetic
diversity among populations was lower than that reported by Hamrick (1983) for
10


outcrossing species (G& = 0.221). These data reveal a strong trend toward
apportionment of genetic diversity (80% or more) among individuals within
populations in outcrossing species.
1.4 Research Hypotheses
A dioecious breeding system results in obligate outcrossing in C. scirpoidea ssp.
scirpoidea. It is therefore hypothesized, that genetic diversity will be apportioned
differently in C. scirpoidea ssp. scirpoidea in comparison to monoecious carices, as
well as other monoecious flowering plants.
Other factors, such as habit, can also be expected to affect genetic structure with
regard to gene flow in Carex. While confounded by a number of other factors,
carices with a caespitose habit have been shown to be predominantly inbred,
presumably due to selfing. Genetic evidence supporting this phenomenon was first
reported by Bruederle (1987), and subsequently by others, including Bruederle and
Jensen (1991). In contrast, rhizomatous carices tend to outcross due to genet
intermingling, yielding higher levels of genetic variation and lower population
differentiation in comparison to those species with the caespitose growth forms. It is
hypothesized that C. scirpoidea ssp. scirpoidea, despite its caespitose habit, will
apportion its genetic diversity within rather than among populations (consistent with
rhizomatous carices) due to the effects of obligate outcrossing.
Many traits may variously affect the amount of genetic diversity maintained by plant
species, e.g., breeding system and life form (Hamrick and Godt, 1990). Notable
among these traits is biogeography. As noted previously, Carex scirpoidea
11


ssp. scirpoidea occurs in widespread, boreal populations; however, Colorado
populations are disjunct from these populations. Thus, it is further hypothesized that
biogeographic isolation will result in lower genetic diversity in Colorado populations
than would be expected for boreal populations.
12


2.
Materials and Methods
2.1 Field Methods
Soluble enzymatic proteins were extracted from leaf tissue harvested from individual
plants of Carex scirpoidea ssp. scirpoidea representing five distinct populations in
Colorado (Fig. 2.1, Table 2.1). Samples were collected from plants that were at least
one meter apart, with samples limited to one flowering culm per plant. A minimum
of 50 plants per population were sampled, with roughly equal numbers of male and
female plants collected. Samples were individually bagged and maintained at
approximately 4C until protein extraction.
The five populations of C. scirpoidea ssp. scirpoidea sampled were designated High
Creek Fen North (Park County, CO), High Creek Fen South (Park County, CO),
Beaver Creek Fen (Park County, CO), Geneva Park Creek (Park County, CO) and
Horseshoe Mountain (Park County, CO). The two High Creek Fen populations
represent the upper montane lifezone, Beaver Creek Fen and Geneva Park Creek are
both from the subalpine lifezone, and the Horseshoe Mountain population represents
the alpine lifezone. Additionally, a population of C. scirpoidea ssp.
pseudoscirpoidea was collected at Stony Pass, in the San Juan Mountains of
Colorado, but was not analyzed as part of this thesis effort (Fig. 2.1).
Voucher specimens for each population were deposited at Herbarium COLO and at
Denver Botanic Garden herbarium (DBG). A Garmin model 38 global positioning
system (GPS) was utilized to determine approximate coordinates of each population
sampled. Field data were recorded in logbooks.
13


COLORADO, USA
High Creek Fen North = I, High Creek Fen South = 2, Beaver Creek Fen ** 3,
Geneva Park Creek = 4, Horseshoe Mountain = 5, Stony Pass 6
Fig. 2.1 Park County, Colorado collection sites for Carex scirpoidea ssp. scirpoidea
and San Juan County, Colorado collection site for Carex scirpoidea ssp.
pseudoscirpoidea (Cyperaceae).
14


TABLE 2.1. Carex scirpoidea ssp. scirpoidea (Cyperaceae) sites in Park County,
Colorado, sampled for allozyme analysis. Note: Stony Pass samples (San Juan
County) of Carex scirpoidea ssp. pseudoscirpoidea have not been analyzed.
Population N Latitude Longitude Legal Description Elevation Lifezone
High Creek Fen North (1) 50 N395'53", T11S.R77W, 2826 m upper
W105587" Sec. 14 montane
High Creek Fen South (2) 50 N39548\ T11S, R77W, 2822 m upper
W1055751" Sec. 14 montane
Beaver Creek Fen (3) 50 N3918'33", T8S, R77W, 3389 m subalpine
wwns" Sec. 31
Geneva Park Creek (4) 50 N3931'9", T6S, R75W, 2949 m subalpine
W 10543'23" Sec. 13
Horseshoe Mountain (5) 50 N3911'35", T10S, R79W 3666 m alpine
W 1069'13"
Stony Pass (6) 100 N374742", T41N.R6W, 3837 m alpine
W10732'57 Sec.20
15


2.2 Laboratory Methods
Methods and materials for allozyme extraction and starch gel electrophoresis
followed Bruederle and Fairbrothers (1986) and Bruederle and Jensen (1991).
Allozymes were extracted from each sample by grinding ~1 cm2 of leaf tissue with
sea sand in an extraction buffer of 0.25 mL of a 0.1 M Tris-HCl extract buffer, pH
7.5 (Gottlieb, 1981), 20% (w/v) PVP-40, and 0.1% 2-mercaptoethanol. Extracts
were absorbed onto 12 x 3 mm wicks cut from chromatography paper (Whatman
No. 17) and stored in a -70 C freezer until electrophoresis.
Starch gel electrophoresis of allozymes utilized 10.5% gels prepared for each of four
gel and electrode buffer systems using hydrolyzed potato starch (Sigma Chemical
Company). The four starch gel and electrode buffer systems utilized were: lithium-
borate pH 7.6/8.0 (Soltis et al., 1983), run at 275 V; histidine-HCl pH 7.0 (Gottlieb,
1981), run at 100 mA; histidine-citrate pH 6.5 (Shields et al., 1983), run at 30 ma;
and tris-citrate pH 7.5 (Soltis et al., 1983), run at 50 mA. Gels were prepared
approximately 12 hours prior to use, allowed to stand covered at room temperature,
and refrigerated (4C) thirty minutes prior to sample application. Sample wicks
were applied to a slit at the cathodal end of the gel, with a bromophenol blue marker
(0.1%) used to monitor progress of the electrophoretic run. Electrophoresis was
conducted at 4C and constant current, with the exception of the lithium borate gel,
which was run at constant voltage, until the dye front had migrated ano dally 9-13
cm. Each gel was sliced horizontally into seven slices, approximately 1.5 mm thick.
End slices were discarded with the remaining slices stained using substrate-specific
stains.
16


Fifteen substrate-specific stains were evaluated for effectiveness in identifying
polymorphic loci (Appendix A). Lithium-borate (pH 7.6/8.0) system gels were
stained for alcohol dehydrogenase (ADH), diaphorase (DIA), malic enzyme (ME),
superoxidase dismutase (SOD), and triose-phosphate isomerase (TP1); histidine-
citrate (pH 6.3) system gels for aldolase (ALD) and phosphoglucomutase (PGM)',
tris-citrate (pH 7.5) system gels for acid phosphatase (ACP), aminotransferase
(AAT), glyceraldehyde-3-phosphate dehydrogenase (G3PDH), and shikimate
dehydrogenase (SDH)', and histidine-HCl (pH 7.0) system gels for malate
dehydrogenase (MDH), menadione reductase (MNP), 6-phosphogluconate
dehydrogenase (PGD), and phosphogluco-isomerase (PGI). Enzyme nomenclature
generally follows that of the International Union of Biochemistry (1984). Data were
collected as individual genotypes for each population.
2.3 Statistical Methods
Statistical analyses were performed on the genotypic data at both the species and
population level. At the population level, percentage of loci polymorphic (P), mean
number of alleles per locus (A), mean number of alleles per polymorphic locus (Ap),
observed heterozygosity (Ha), and expected heterozygosity (He) were calculated.
Chi-square tests were used to evaluate deviations from Hardy-Weinberg Equilibrium.
Mean and standard error values were calculated over all populations for each of the
aforementioned statistics.
At the species level, percentage of polymorphic loci (Ps), mean number of alleles per
locus (A,), mean number of alleles per polymorphic locus (Aps), observed
heterozygosity (ff), and expected heterozygosity (Hes) were calculated, following
17


Hamrick and Godt (1990).
Apportionment of genetic diversity was also determined within and among
populations. Statistical measures of genetic diversity included: average observed
heterozygosity across individual populations (H{), average expected heterozygosity
across individual populations (Hs), average expected heterozygosity for all
populations (HT), proportion of genetic diversity within populations (D^), and
proportion of genetic diversity between populations (GST). Neis (1978) genetic
identity coefficient (I) and genetic distance coefficient (D) were calculated to
describe similarity between populations. Fixation indices (F) were calculated for
each polymorphic locus. Values for this statistic may range from -1 to 1, with
negative F values documenting a tendency toward outcrossing and heterozygous
excess, while positive values reveal inbreeding populations with heterozygous
deficiencies. Summary F-statistics include the measure for reduction of
heterozygosity due to non-random mating in subpopulations (F1S), the measure of
reduction of heterozygosity due to genetic drift and inbreeding in individuals relative
to the total population (FIZ), and the measure of reduction of heterozygosity due to
genetic drift or population differentiation (Fsr). Population genetics statistics were
calculated using BIOSYS-l (Swofford and Selander, 1981) software (Appendix B)
and GENESTAT-PC (Appendix C) software.
Statistical analyses were also performed to compare measures of genetic diversity
and population differentiation among various plant taxa important to this study.
Comparisons of genetic diversity were made between the following groups:
monoecious vs. dioecious flowering plants, monoecious species vs. C. scirpoidea
18


ssp. scirpoidea populations, monoecious carices vs. C. scirpoidea ssp. scirpoidea
populations, dioecious species vs. C. scirpoidea ssp. scirpoidea populations,
caespitose carices vs. C. scirpoidea ssp. scirpoidea populations, and rhizomatous
carices vs. C. scirpoidea ssp. scirpoidea populations. Comparisons of population
differentiation were made between the following groups: monoecious vs. dioecious
species, and caespitose vs. rhizomatous carices. Anderson-Darling normality tests
were conducted on genetic diversity data from all of these groups and several were
revealed to be nonparametric in their distribution. Therefore, Mann-Whitney £/-tests
(a nonparametric test) were selected to reveal differences in pairwise comparisons of
the data (Appendix I). Minitab statistical software was utilized to perform both the
normality and Z7-tests.
19


3.
Results
3.1 Genetic Diversity
Allozyme analysis for the combined five populations of C. scirpoidea ssp. scirpoidea
resolved seventeen putative genetic loci: alcohol dehydrogenase (ADH), aldolase
(ALD), diaphorase (DIA-1, DIA-2, DIA-3), glyceraldehyde-3-phosphate
dehydrogenase (G3PDH-1), malate dehydrogenase (MDH-2, MDH-3, MDH-4),
malic enzyme (ME), 6-phosphogluconate dehydrogenase (PGD), phosphogluco-
isomerase (PGI-2), phosphoglucomutase (PGM-3), shikimate dehydrogenase (SDH),
superoxidase dismutase (SOD-2), and triose-phosphate isomerase (TPI-l, and
TPI-2). Ten of the loci were monomorphic (using no criterion) and, thus,
uninformative for description of genetic structure (ADH, ALD, DIA-l, DIA-2,
G3PDH-1, MDH-2, MDH-4, ME, PGD, and SOD-2). The remaining seven loci
were found to be polymorphic (Table 3.1.1). Five of the seven loci (DIA-2, MDH-2,
PGM-2, TPI-1 and TPI-2) maintained two alleles, while the remaining two
polymorphic loci maintained three alleles each (PGI-2 and SDH).
20


TABLE 3.1.1. Allele frequencies at seven polymorphic loci in five populations of
Carex scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park County, Colorado.
N = number of samples.
Population/ Locus Allele High Creek Fen South High Creek Fen North Beaver Creek Fen Geneva Park Creek Horseshoe Mountain
DU-2 N= 50 N = 46 N= 41 N= 50 N= 50
a 0.090 0.196 0.317 0.390 0.350
b 0.910 0.804 0.683 0.610 0.650
MDH- 3 N= 46 N= 50 N = 50 N= 36 N = 50
a 0.011 0.040 0.000 0.194 0.000
b 0.989 0.960 1.000 0.806 1.000
PGI- 2 N = 49 N= 49 N = 49 N = 49 N = 50
a 0.173 0.122 0.102 0.163 0.000
b 0.745 0.735 0.816 0.806 0.620
PGM-3 N = 49 N= 50 N = 50 N= 49 N = 50
a 0.939 0.980 0.940 0.929 0.990
b 0.061 0.020 0.060 0.071 0.010
SDH N = 46 N = 48 N= 50 N = 47 N= 50
a 0.109 0.000 0.000 0.181 0.000
b 0.891 1.000 1.000 0.819 0.500
TPI-l N = 50 N = 44 N = 50 N = 50 N = 50
a 0.030 0.011 0.000 0.000 0.000
b 0.970 0.989 1.000 1.000 1.000
TPI-2 N= 50 N = 44 N= 50 N = 50 N= 50
a 1.000 0.977 1.000 1.000 1.000
b 0.000 0.023 0.000 0.000 0.000
21


Overall levels of genetic diversity within populations of C. scirpoidea ssp. scirpoidea
were moderate to low, with respect to percentage of polymorphic loci, mean number
of alleles per locus, and mean heterozygosity per locus (Table 3.1.2). Percentage of
loci polymorphic (P) using the 0.05 criterion ranged from 11.76% for the High Creek
Fen North population to 29.41% for the Geneva Park Creek population, with an
overall population mean of 20%. Utilizing no criterion for P, values ranged from
35.29% in the High Creek Fen North and South populations to a low of 17.65% for
the Beaver Creek Fen population. Average number of alleles per locus (A) varied
from 1.24 in the Horseshoe Mountain and Beaver Creek Fen populations to a high of
1.41 in High Creek Fen North and South populations, with a mean value of 1.33 (SE
0.04). The mean value for average number of alleles per polymorphic locus (AJ was
2.17 (SE 0.05). Mean expected heterozygosity per locus (He) ranged from a low of
0.05 for the Beaver Creek Fen population to 0.09 in the Geneva Park Creek
population, with an overall mean He of 0.07 (SE 0.01) or 7%.
22


TABLE 3.1.2. Genetic diversity in five populations of Carex scirpoidea ssp.
scirpoidea (Cyperaceae) sampled in Park County, Colorado. P(M) = percentage of
polymorphic loci using 0.05 criterion, P (no) = percentage of polymorphic loci using
no criterion, A = average number of alleles per locus, AP = average number of alleles
per polymorphic locus, He = expected heterozygosity.
Population A-05) ^ (no) A AP He
High Creek Fen North 11.76 35.29 1.41 (SE.15) 2.17 (SE. 17) 0.06 (SE .03)
High Creek Fen South 23.53 35.29 1.41 (SE.15) 2.17 (SE.17) 0.07 (SE .03)
Beaver Creek Fen 17.65 17.65 1.24 (SE.14) 2.33 (SE .33) 0.05 (SE .03)
Geneva Park Creek 29.41 29.41 1.35 (SE.15) 2.20 (SE .20) 0.09 (SE.05)
Horseshoe Mountain 17.65 23.53 1.24 (SE.ll) 2.00 (SE .00) 0.09 (SE .05)
Population Mean 20.00 28.23 1.33 (SE .04) 2.17 (SE .05) 0.07 (SE .01)
Species 29.41 41.18 1.53 2.29 0.08
23


Species-level statistics revealed a proportion of polymorphic loci of 29.41% and
41.18% in C. scirpoidea ssp. scirpoidea, using the .05 and no criterion, respectively.
This represents an increase of approximately 1.5 times the population mean values.
Similarly, the species-level values for A, (1.53) and Aps (2.29) were larger than
comparable statistics at the population level. Expected heterozygosity at the species
level (Hes) was 0.08 or 8%.
3.2 Population Genetic Structure
An evaluation of apportionment of genetic diversity across all polymorphic loci
revealed 12.3% to be among populations (Gsr= 0.123). That is, approximately 88%
of genetic diversity is attributable to differences among individuals within populations
of C. scirpoidea ssp. scirpoidea. Mean observed heterozygosity across populations
(Hi) was .074 (SE .013), or 7.4%. Expected heterozygosity averaged over all
populations (Hs) was .068 with a standard error of 0.008 (Table 3.2.1). Total
expected heterozygosity (Hi) for all populations was 0.078. These statistics are very
similar, deviating by no more than 1%. This similarity indicates that these
populations are panmictic or randomly breeding (Hj = Hs- HT), supporting the
expectation of Hardy-Weinberg Equilibrium (HWE).
24


TABLE 3.2.1. Genetic structure in five populations of Carex scirpoidea ssp.
scirpoidea (Cyperaceae) sampled in Park County, Colorado. Ha = observed
heterozygosity, He = expected heterozygosity.
Population Observed Heterozygosity Expected Heterozygosity
High Creek Fen North 0.055 (SE 0.030) 0.055 (SE 0.030)
High Creek Fen South 0.058 (SE 0.027) 0.057 (SE 0.027)
Beaver Creek Fen 0.053 (SE 0.032) 0.051 (SE 0.031)
Geneva Park Creek 0.119 (SE 0.053) 0.092 (SE 0.038)
Horseshoe Mountain 0.085 (SE 0.046) 0.086 (SE 0.046)
Population Mean 0.074 (SE 0.013) 0.068 (SE 0.008)
25


However, 15 significant deviations from HWE were revealed for five polymorphic
loci across all five populations using Chi-square tests (A!2). The DIA-2 locus differed
significantly (p > 0.05) from HWE expectations, with slight heterozygous excess in
the High Creek Fen South, Beaver Creek Fen, Geneva Park Creek, and Horseshoe
Mountain populations. The MDH-3 locus differed significantly from expectations (p
> 0.05) in only the Geneva Park Creek population, with slight heterozygous excess
reported. The PGI-2 locus differed significantly from expectations (p > 0.05) in each
of the five populations tested. Interestingly, this locus accounted for slight
heterozygous excess in the High Creek Fen North and Geneva Park Creek
populations, but slight heterozygous deficiency in the High Creek Fen South, Beaver
Creek Fen, and Horseshoe Mountain populations. The PGM-3 locus revealed
significant (p > 0.05) heterozygous excesses in the High Creek Fen South, Beaver
Creek Fen, and Geneva Park Creek populations. Heterozygosity at the SDH locus
was significantly different than expectations (p > 0.05) in the High Creek Fen South
and the Geneva Park Creek populations, with slight heterozygous excess observed in
both populations. The fixation indices revealed that overall, the five populations of
Carex scripoidea ssp. scirpoidea deviated only slightly from Hardy-Weinberg
expectations, with a trend toward heterozygous excess in these populations (Table
3.2.2).
26


TABLE 3.2.2. Wrights fixation indices for polymorphic loci resolved in five
populations of Carex scirpoidea ssp. scripoidea (Cyperaceae) sampled in Park
County, Colorado. An asterisk indicates that the corresponding fixation index value
deviated significantly (p > 0.05) from Hardy-Weinberg expectations.
Population/ Locus High Creek Fen South High Creek Fen North Beaver Creek Fen Geneva Park Creek Horseshoe Mountain
D1A-2 -0.099* 0.033 -0.126* -0.555* -0.187*
MDH-3 -0.011 -0.042 -0.241*
PGI-2 0.050* -0.057* 0.097* -0.202* 0.236*
PGM-3 -0.065* -0.020 -0.064* -0.077* -0.010
SDH -0.122* -0.221* -0.040
TPI-1 -0.031 -0.011
TPI-2 -0.023
Mean/ -0.046 -0.020 -0.031 -0.259 0.000
(SE) (0.026) (0.013) (0.066) (0.079) (0.088)
27


Summary F-statistics for C. scirpoidea ssp. scirpoidea (Table 3.2.3) revealed a trend
(five of the seven polymorphic loci) toward slight outcrossing (F1S and Fir values
slightly less than 1). Exceptions are the SDH and PGI-2 loci, with slightly positive
Fjt values. This is possibly indicative of genetic drift and/or inbreeding at these loci.
Overall population means revealed a slight increase in heterozygosity due to non-
random mating (FIS of -0.097), but a very slight trend for overall inbreeding (Fir =
0.023), due to variation at the SDH locus. Population subdivision (F^) was 10.9%.
28


TABLE 3.2.3. Summary of .F-statistics at all polymorphic loci resolved in five
populations of Car ex scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park
County, Colorado. FIS = reduction in heterozygosity due to non-random mating,
FIT = overall inbreeding coefficient, and iv = population differentiation.
F-statistic
Locus Fa Fit Fsr
DIA-2 -0.222 -0.147 0.062
MDH- 3 -0.192 -0.052 0.118
PGI-2 0.038 0.094 0.058
PGM- 3 -0.062 -0.047 0.014
SDH -0.110 0.208 0.287
TPI-l -0.026 -0.008 0.017
TPI-2 -0.023 -0.005 0.018
Mean -0.097 0.023 0.109
29


Neis genetic identity (Z) and genetic distance (D) were evaluated to determine
proportion of alleles shared by descent between populations. It is clear that all five
populations are very similar genetically. Identities ranged from 0.979 to 0.999, with
a mean identity of 0.990, while distances ranged from 0.001 to 0.021. All five
populations clearly conform to a single subspecies (i.e., C. scirpoidea ssp.
scirpoidea).
30


4. Discussion
A summary of the plant population genetic literature by Hamrick and Godt (1990)
found an average of 34.2% of a populations loci to be polymorphic, average number
of alleles per locus was 1.53, average genetic diversity was 11.3%, and population
differentiation averaged 22.4% (Table 4.0). It is clear that Colorado populations of
C. scirpoidea ssp. scirpoidea harbor less genetic diversity than that found in an
average plant population (P05 = 20%, A = 1.33; He = 6.8%); furthermore, this
species apportions approximately half as much of that diversity among its
populations as compared to other flowering plants.
Several authors, including Jelinski and Cheliak (1992), Alvarez-Buylla and Garay
(1994), Chung and Kang (1994), Peakall et al. (1995), Weller et al. (1996), and
Akimoto et al. (1999), have reported genetic diversity statistics for dioecious species.
These data reveal an average value for P of 64.7%, A of 2.49, and He of 29.7%
(Appendix D). In contrast, genetic diversity statistics for monoecious species reveal
an average value for P of 39.3%, an average A of 1.72, and an average He of 10.4%
(Appendix E). Dioecious species average 1.5 times more polymorphic loci, 1.4 times
the average alleles per locus, and 2.8 times the average expected heterozygosity
compared with monoecious species. The difference in genetic diversity between
dioecious and monoecious flowering plants was tested using nonparametric Mann-
Whitney £/-tests. Statistically significant differences (p < 0.05) were found between
dioecious and monoecious plant species for all genetic diversity parameters tested.
Genetic diversity in Colorado populations of C. scirpoidea ssp. scirpoidea was
revealed to be generally less than that found in other dioecious flowering plants.
31


Dioecious flowering plants average more than three times higher P than that found in
C. scirpoidea ssp. scirpoidea. Likewise, A in dioecious species was nearly twice as
high as that found in Colorado populations of C. scirpoidea ssp. scirpoidea.
Expected heterozygosity in dioecious species is more than four times higher than C.
scirpoidea ssp. scirpoidea. Mann-Whitney 17-tests revealed that C. scirpoidea ssp.
scirpoidea populations are significantly different (p < 0.05) for the parameters P, A,
Ha, and He compared with other dioecious flowering plants.
Genetic diversity in Colorado populations of C. scirpoidea ssp. scirpoidea was
generally less than the average for monoecious flowering plants. Percentage of
polymorphic loci was almost 20% higher in monoecious species (39.3%) versus C.
scirpoidea ssp. scirpoidea populations (20%). Monoecious species had a mean
value for A of 1.72 versus 1.33 in C. scirpoidea ssp. scirpoidea populations.
Average expected heterozygosity was 0.104 (10.4% ) in monoecious species versus
0.068 (6.8%) in C. scirpoidea ssp. scirpoidea populations. Mann-Whitney U-tests
found no significant difference (p > 0.05) in any of the genetic diversity parameters
(P, A, Ha, and He) tested.
Comparisons of genetic diversity between C. scirpoidea ssp. scirpoidea populations
and other carices, all of which are monoecious, (Appendix F) found average values
for P, A, Hm and He to be very similar. Both taxa had approximately 20% of their
loci polymorphic, 1.3 alleles per locus, 7% observed heterozygosity, and 7%
expected heterozygosity. Mann-Whitney 17-tests found no significant differences
32


(p > 0.05) for any of the genetic diversity parameters tested between C. scirpoidea
ssp. scirpoidea and monoecious carices.
Comparisons of genetic diversity were made between caespitose and rhizomatous
carices, and between each of these taxa and C. scirpoidea ssp. scirpoidea
populations. Mean genetic diversity values for caespitose carices included P of
14.4%, A of 1.2, Ha of 0.033, and He of 0.040. In contrast, rhizomatous carices
average a P of 44.5%, A of 1.6, Ha of 0.174, and He of 0.171. Comparing these
data, the rhizomatous carices averaged three times more polymorphic loci, 1.33 times
more alleles per locus, 5.27 times more observed heterozygosity, and 4.27 times
more expected heterozygosity. The Mann-Whitney tZ-test found significant
statistical difference (p < 0.05) between caespitose and rhizomatous carices for each
of the genetic diversity parameters evaluated.
Colorado populations of C. scirpoidea ssp. scirpoidea maintained a greater
proportion of polymorphic loci (20%) than caespitose carices (14%), but
substantially less than rhizomatous carices (44%). Carex scirpoidea ssp. scirpoidea
populations averaged 1.33 alleles per locus, versus 1.2 for caespitose carices and 1.6
for rhizomatous carices. Carex scirpoidea ssp. scirpoidea was determined to have
more than twice as much observed heterozygosity in comparison to caespitose
carices (7.4% vs. 3.3%, respectively), but substantially less than rhizomatous carices
(7.4% vs. 17.4%). The Mann-Whitney ZT-tests found C. scirpoidea ssp. scirpoidea
populations to be significantly different (p < 0.05) in terms of genetic diversity
compared to both caespitose and rhizomatous carices.
33


Few studies have recorded population differentiation data for dioecious flowering
plants. Mean GST value for those taxa that have been studied was 0.204 or 20.4%.
These data indicate that dioecious species tend to apportion genetic diversity within
rather than among populations, supporting expectations. Values for Gst ranged from
a low of 0.029 to a maximum value of 0.688. Because the standard deviation for
dioecious Gsr values is large and the data set is small (N = 4), statistical comparisons
using these taxa are problematic. Hamrick and Godt (1990) report a mean G^ for
wind-pollinated, outcrossing species of 0.099, or 9.9%. The mean G^ for wind-
pollinated, outcrossing species may be more instructive for comparative purposes
due to the greater number of taxa (N = 134) used to arrive at the mean. Population
differentiation data are much more common for monoecious flowering plants. Mean
Gst for a select group of monoecious species (31.2%) revealed a higher degree of
genetic diversity apportioned among populations, as compared to both dioecious and
to wind-pollinated, outcrossing species. The Mann-Whitney 17-test was not able to
find a statistically significant difference between dioecious and monoecious species
for Gsr (p > 0.05).
A review of population genetic structure data for caespitose carices reveals an
average Gsr of 0.462 (Appendix G). This value represents a nearly equal
apportionment of genetic diversity among and within populations of caespitose
carices. Rhizomatous carices, in contrast, have a mean Gsr of 0.159, indicating that
nearly 84% of genetic diversity is apportioned among individuals within populations
(Appendix H). The Mann-Whitney 17-test found caespitose and rhizomatous species
to differ significantly in terms of Gsr (p < 0.05).
34


Population genetic structure in Colorado populations of C. scirpoidea ssp.
scirpoidea is characterized by maintenance of Hardy-Weinberg Equilibrium and
apportionment of genetic diversity (GST = 12.3%) within populations rather than
among them. The Gsr value for C. scirpoidea ssp. scirpoidea is less than that for
monoecious species (Gsr= 31.2%), monoecious carices (Gsr = 38.9%), and other
dioecious species (G^ = 20.4%). The Gsr for C. scirpoidea ssp. scirpoidea does,
however, correspond well with the mean Gsr for wind-pollinated, outcrossing species
(12.3% versus 9.9%). Population genetic structure in C. scirpoidea ssp. scirpoidea
reveals a pattern similar to rhizomatous carices (G^ = 15.9%), with genetic diversity
apportioned within rather than among populations. Caespitose carices maintain more
of their genetic diversity among populations (GST = 46.2%). These data highlight the
confounding aspect of the correlation of growth form and breeding system in the
genus Car ex. Population genetic structure in C. scirpoidea ssp. scirpoidea appears
to be influenced by the obligate outcrossing nature of its breeding system. Not
surprisingly, its caespitose growth form appears to be less important in population
differentiation.
35


TABLE 4.0. Comparison of population-level genetic diversity between Carex
scirpoidea ssp. scirpoidea (Cyperaceae) sampled in Park County, Colorado, USA
and other dioecious, wind-pollinated/outcrossing, monoecious, caespitose, and
rhizomatous flowering plants. Data summarized by Yarbrough from studies by
Jelinski and Cheliak (1992); Alvarez-Buylla and Garay (1994); Chung and Kang
(1994); Peakall, et al. (1995); Weller, et al. (1996); and Akimoto, et al. (1999). **
Data summarized by Yarbrough from studies of 87 separate monoecious species
***Data summarized by Kuchel (1999). **** Data summarized by Hamrick and
Godt, 1990. P = percent polymorphic loci, A = average number of alleles per locus,
He = expected heterozygosity, G57/-Fy7.= population differentiation.
Taxa P A H. He Gst/Fst
C. scirpoidea ssp. scirpoidea 20.0 1.33 0.074 0.068 0.123
Dioecious species* 64.7 2.49 0.281 0.297 0.204
Wind-pollinated, outcrossing species**** 49.7 1.79 0.148 0.099
Monoecious species** 39.3 1.72 0.106 0.104 0.312
Monoecious carices*** 23.6 1.30 0.070 0.073 0.389
Rhizomatous carices*** 44.5 1.6 0.174 0.171 0.159
Caespitose carices*** 14.4 1.2 0.033 0.044 0.462
All Plant Taxa**** 34.2 1.53 0.113 0.224
36


Low levels of genetic diversity in Colorado populations of C. scirpoidea ssp.
scirpoidea may be attributable to several factors, including disjunct biogeography
and the presumed recent evolutionary history of the species. Although no molecular
data are available from the main boreal populations, it is reasonable to assume that
genetic diversity in the biogeographic center for the species is greater, and potentially
much greater, than that found in the disjunct Colorado populations.
The disjunct distribution and caespitose growth form are expected to result in
decreased gene flow and increased inbreeding in plant species. However,
populations of C. scirpoidea ssp. scirpoidea in Colorado maintain a modest level of
genetic diversity, with most of that variation apportioned within populations.
Furthermore, these populations are maintaining Hardy-Weinberg Equilibrium. This
obviously is a result of the dioecious breeding system imparting obligate outcrossing
and promoting the gene flow that prevents these populations from experiencing
inbreeding. Dioecy in this sense, may be a stabilizing force helping to maintain
genetic diversity in populations of C. scirpoidea ssp. scirpoidea.
While this research was not designed to test hypotheses regarding the biogeographic
and recent evolutionary history of C. scirpoidea ssp. scirpoidea, the significantly
lower than expected levels of genetic diversity reported herein do not support
Dunlops (1990) proposed hypothesis of a Southern Rocky Mountain glacial
refugium for this species. Additional research examining genetic diversity in the C.
scirpoidea species complex should be designed to include Beringian and periglacial
populations in order to better test hypotheses concerning this species distribution.
37


Appendix A Gel and Electrode Buffer Systems and Substrate-Specific Stains
lithium-borate pH 7.6/8.0
alcohol dehydrogenase (ADH)
diaphorase (DIA)
malic enzyme (ME)
superoxidase dismutase (SOD)
triose-phosphate isomerase (TP1)
histidine-citrate pH 6.3
aldolase (ALD)
phosphoglucomutase (PGM)
tris-citrate pH 7,5
acid phosphatase (ACP)
aminotransferase (AAT)
glyceraldehyde-3-phosphate dehydrogenase (G3PDH)
shikimate dehydrogenase (SDH)
histidine-HCl pH 7.0
malate dehydrogenase (MDH)
menadione reductase (MNR)
6-phosphogluconate dehydrogenase (PGD)
phosphogluco-isomerase (PGI)
38


Appendix B BIOSYS Data
SSBBBSBB IIZIIII OOOOOOO SSSSSSSS YYY YYY SSSSSSSS 111
SB883SBBS mini ccooooooo SSSSSSSSS YYY yyy SSSSSSSSS 1111
333 BBS iii oco cco sss YVV VT/ SSS 11111
3SB BSB iii coo oco sss 'CTTTr sss 111
3BBBBBBB in coo 000 SSSSSSSS YYY SSSSSSSS XXXXX 111
3BBBBBB8 iii cco oco SSSSSSSS YYY SSSSSSSS xxxxx in
BBS 3EB iii coo 000 sss YYY SSS 111
3BB BSB iii ooo oco sss YYY sss 111
53SBBSB53 mini OOOGOOCOO SSSSSSSSS YYY SSSSSSSSS 1111111
33BBBBBB mini OOOOOOO SSSSSSSS YYY SSSSSSSS 1111111
Release 1.7 University of Illinois 21:05: 1999 04:02:01
Title: SINGLE INDIVIDUAL GENOTYPE INPUT (ALPHABETIC AXLSLIC DSSIGNATICNSJ
Number ot populations (OTU's) = 5
Number of loci * 17
Maximum number of alleles per locus = 3
Output restricted to width of 90 columns
* SINGLE INDIVIDUAL GENOTYPE INPUT (ALPHABETIC ALLELIC DESIGNATIONS)
* Initial Data Step
* 5IOSYS-! Release 1.7 21:06:1999 04:01:01
Input data: Single-individual genotypes
Allelic designations: Alphabetic
Allele frequencies in populations 1 thru 5
locus
Peculation
4
ADH
(N)
A
AID
(N)
DIA-1
(N)
A
DIA-2
50
1.000*
49
1.000
48
1.000
47
1.000
41
1.000
45
1.000
49
1.000
25
1.000
44
1.000
50
1.000
20
1.000
50
1.000
48
1.000
50
1.000
50
1.000
39


I
(N)
A
B
DIA-3
(N)
A
GPD-1
(N)
A
MDH-2
(N)
MDH-3
(N)
A
B
MDK-4
(N)
A
ME
(N)
A
PGD
(N)
PGI-2
(N)
C
p
(M)
3
SDH
(N)
C
SOD-2
(N)
A
TPI-1
(N)
A
30
.090
. 310
48
1.000
25
1.000
46
1.000
46
. Oil
. 989
24
1.000
47
1.000
49
1.000
45
. 173
. 745
. 0S2
49
. 939
. 061
46
. 109
.351
. 000
50
1.000
50
. 030
46
.196
.804
46
1.000
50
1.000
50
1.000
50
.040
.960
50
1.000
44
1.000
48
1.000
49
.122
.735
.143
50
.980
.020
48
.000
1.000
.000
45
1.000
44
.011
41
.317
.683
50
1.000
50
1.000
50
1.000
50
.000
1.000
49
1.000
46
1.000
43
1.000
49
.102
. 316
.082
50
. 940
.060
50
.000
1.000
.000
49
1.000
50
.000
50
.390
.610
50
1.000
50
1.000
50
1.000
36
.194
.806
26
1.000
49
1.000
48
1.000
49
.163
.306
.031
49
.929
.071
47
.181
.319
.000
50
1.000
50
.000
50
.250
. 650
50
1.000
49
1.000
50
1.000
50
.000
1.000
48
1.000
50
1.000
50
1.000
50
.000
. 520
. 380
50
.990
.010
50
.000
.500
.500
50
1.000
50
.000
40


B .570 .383 1.000 1.000 1.000
TPI-2
(N) 50 . 44 50 50 50
A 1.000 .377 1.000 1.000 1.000
B .000 .023 .000 .000 .000
Key to populations
XX + irir-frlririnrie'Xlc*+lr1rir
Original pop. no. Pod. no. on printout Population name
HCES 1 HIGH CREEK SOUTH
HCEN 2 HIGH CREEK NORTH
BCE 3 BEAVER CREEK PEN
GPC 4 GENEVA FARK CREE
HSM 5 HORSESHOE MOUNTA


* SINGLE INDIVIDUAL GENOTYPE INPUT (ALPHABETIC ALLELIC DESIGNATIONS)
* Genetic variability analysis
* BIOSYS-1 Release 1.7 21:06:1355 04:02:01

Allele frequencies and genetic variability measures
Population: HIGH CREEK SOUTH (HCESi
Allele Locus and sampi a SIZc
50 ALD 43 D iJ-t.- 1 43 DIA-2 50 DIA-3 43 GPD-I MDK-2 4 6 MDK-3 45 MDH-4 24
A I.000 1.000 1.000 .030 1.000 1.000 1.000 . Oil 1.000
3 . 000 .000 .000 .310 .000 .000 . 000 . 583 .000
C .000 .000 .000 .000 .000 .000 .000 .000 .000
H .000 .000 .000 .164 .000 .000 . 000 .022 .000
H(unb) .000 .000 . .000 .165 .000 .000 .000 .022 .000
H(D.C.) .000 .000 .000 . 180 .000 .000 .000 .022 .000
41


Locus and samble size
Allele $ PGD 49 PGI-2 49 PGM-3 49 SDH 46 SOD-2 50 T2I-1 50 TPI-2 50
A 1.000 1.000 .173 .939 .109 1.000 .030 1.000
B .000 .000 .745 .061 . 891 .000 .970 .000
C .000 .000 .082 .000 .000 .000 .000 .000
K .000 .000 .408 .115 . 194 .000 .058 .000
H(unb) .000 .000 .413 .116 . 196 .000 .059 .000
H (D. C.) .000 .000 .338 .122 .217 .000 .060 .000
Mean heterozygosity per locus (biased estimate) = '.057 (S.E.
Mean heterozygosity per locus (unbiased estimate) = .057 (S.
Mean heterozygosity per locus (direct-count estimate) = .053
Mean number of alleles per locus = 1.41 (S.E. .15)
Percentage of loci polymorphic (0.95 criterion) = 23.53
Percentage of loci polymorphic (0.93 criterion) = 35.29
Percentage of loci polymorphic (no criterion) = 35.29
Allele frequencies and genetic variability measures
. 027)
. .027)
(S.E. .027)
Population: HIGH CREEK NORTH (HCFN)
Locus and samole size
ADH ALD DIA-1 DIA-2 DIA-3 GPD-1 MDK-2 MDH-3 MDH-4
Allele 47 41 45 46 46 50 50 50 50
A 1.000 1.000 1.000 .196 1.000 1.000 1.000 .040 1.000
3 .000 .000 .000 .304 .000 .000 . 000 . 360 .000
C .000 .000 .000 .000 .000 .000 . 000 .000 .000
H .000 .000 .000 .315 .000 .000 .000 .077 .000
H(unb) .000 .000 .000 .313 .000 .000 .000 .078 .000
K (D. C. ) .000 .000 .000 .304 .000 .000 .000 .080 .000

Locus and sample si ze
ME PGD PGI-2 PGM3 SDK SOD2 TPI-1 TPI-2
Allele 44 48 49 50 48 45 44 44
42


A 1.000 1.000 .122 .980 .000 1.000 .011 .977
3 .000 .000 .735 .020 1.000 .000 .939 .023
C .000 .000 .143 .000 .000 .000 .000 .000
H .000 .000 .425 .039 . 000 .000 .022 .044
H(unb) .000 .000 .429 .040 .000 .000 .023 .045
H(D.C.) .000 .000 .449 .040 . 000 .000 . 023 .045
Mean heterozygosity per locus (biased estimate) = .054 (S.E. .030)
Mean heterozygosity per locus (unbiased estimate) = .055 (S.E. .030)
Mean heterozygosity per locus (direct-count estimate) = .055 (S.E. .030)
Mean number of alleles per locus = 1.41 (S.E. .15)
Percentage of loci polymorphic (0.95 criterion) = 11.75
Percentage of loci polymorphic (0.99 criterion) = 35.29
Percentage of loci polymorphic (no criterion) = 35.29
Allele frequencies and genetic variability measures
Population: BEAVER CREEK FEN (BCE )
Locus and samnie size
ADH ALD DIA-L DIA-2 DIA-3 GPD-1 MDK-2 MDH-3 MDH-4
Allele 49 25 44 41 50 50 50 50 49
A 1.000 1.000 1.000 .317 1.000 1.000 1.000 .000 1.000
2 .000 .000 .000 .633 .000 .000 . 000 1.000 .000
c .000 .000 .000 .000 .000 .000 .000 .000 .000
ji .000 .000 .000 . 433 . 000 .000 . 000 .000 . 000
H(unb) .000 .000 .000 . 438 .000 .000 .000 .000 .000
H (D. C. ) .000 .000 .000 .438 .000 .000 .000 .000 .000

Locus and sample si ze
MS PGD PGI-2 PK4-3 SDH SOD-2 T?I-i Tpi-2
Allele 46 48 49 50 50 49 50 50
A 1.000 1.000 .102 .940 .000 1.000 .000 1.000
B .000 .000 .315 .060 1.000 .000 1.000 .000
C .000 .000 . CS2 . 000 .000 .000 .000 .000
43


H .000 .000 .317 .113 .000 .000 .000 .000
H(unb) .000 .000 .320 .114 .000 . 000 .000 .000
H(D.C.) .000 .000 .236 .120 .000 .000 .000 .000
Mean heterozygosity per locus (biased estimate) = .051 (S.E. .031)
Mean heterozygosity per locus (unbiased estimate) = .051 (S.E. .031)
Mean heterozygosity per locus (direct-count estimate) = .053 (S.E. .032)
Mean number of alleles per locus = 1.24 (S.E. .14)
Percentage of loci polymorphic (0.95 criterion) = 17.55
Percentage of loci polymorphic (0.99 criterion) = 17.55
Percentage of loci polymorphic (no criterion) = 17.55
Allele frequencies and genetic variability measures
Population: GENEVA PARK CREE (GPC )
Locus and sample size
ADK ALD DIA-1 DIA-2 DIA-3 GPD-1 MDK-2 MDH-3 MDH-4
Allele 50 30 50 50 50 50 50 36 26
A 1.000 1.000 1.000 .390 1.000 1.000 1.000 . 194 1.000
3 . 000 .000 .000 .610 .000 .000 . coo . 806 .000
C .000 .000 .000 .000 .000 .000 . 000 .000 .000
H .000 .000 .000 .47 5 .000 .000 . 000 .313 . 000
H(unb) .000 .000 .000 .481 .000 . 000 .000 ' .313 .000
H(D.C.) .000 .000 .000 .740 .000 .000 . 000 .000

Locus and sample size
ME PGD PGI-2 PGM-3 SDK SOD-2 TPI-I T?I-2
Allele 49 48 49 49 47 50 50 50
A 1.000 1.000 .163 . 929 . 181 1.000 .000 1.000
3 .000 .000 .306 . 071 .819 .000 1.000 .000
C .000 .000 .031 .000 .000 .000 .000 .000
H .000 .000 .323 .133 .296 .000 .000 .000
H(unb) .000 .000 .325 .134 .299 .000 .000 .000
H(D.C.) .000 .000 . 3S3 .143 .362 .000 .ooo .000
Mean heterozygosity per locus (biased estimate) = .091 (S.E. .038)
44


Mean heterozygosity per locus (unbiased estimate) = .092 (S.E. .033)
Mean heterozygosity per locus (direct-count escimate) = .119 (S.E. .053)
Mean number of alleles per locus = 1.35 (S.E. .15)
Percentage of loci polymorphic (0.95 criterion) = 29.41
Percentage of loci polymorphic (0.99 criterion) = 29.41
Percentage of loci polymorphic (no criterion) = 29.41
Allele frequencies and genetic variability measures
Population: HORSESHOE MCUNTA (KSM )
locus and samole size
ADH ALD DIA-1 DIA-2 DIA-3 G?D1 MDK-2 MDK-3 MDH-4
Allele 48 50 50 50 50 49 50 50 48
A 1.000 1.000 1.000 .350 1.000 1.000 1.000 .000 1.000
3 .000 .000 .000 . 55 0 .000 .000 . 000 1.000 .000
C .000 .000 .000 .000 .000 .000 . 000 .000 .000
H .000 .000 .000 . 455 .000 .000 .000 .000 .000
H(unb) .000 .000 . 000 . 460 . 000 .000 .000 .000 .000
H(D.C.) .000 .000 .000 .540 .000 .000 .000 .000 .000

Locus and sample si zs
ME PGD PGI-2 PGM-3 SDH SCD-2 TPI-1
Allele 50 50 50 50 50 50 50 50
A 1.000 1.000 .000 .990 .000 1.000 .000 1.000
3 .000 .000 .620 . 010 .500 .000 1.000 .000
C .000 .000 .330 .000 .500 .000 .000 .000
H .000 .000 .471 .020 .500 .000 .000 .000
H(unb) .000 .000 .476 .020 .505 .000 .000 .000
H(D.C.) .000 .000 .360 .020 .520 .000 .000 .000
Mean heterozygosity per locus (biased estimate) = .085 (S.E. .045)
Mean heterozygosity per locus (unbiased estimate) = .036 (S.E. .046)
Mean heterozygosity per locus (direct-count estimate) = .085 (S.E. .046)
Mean number of alleles per locus = 1.24 (S.E. .11)
45


Percentage of loci polymorphic (0.95 criterion) = 17.65
Percentage of loci polymorphic (0.99 criterion) = 23.53
Percentage of loci polymorphic (no criterion) = 23.53
Genetic variability at 17 loci in all populations
(standard errors in parentheses)
Ms s Population an samp! ize per. Locus .e Mean no. of alleles per locus Percentage of loci polymorphic* Mean heterozygosity Direct- HdyWbg count expected**
1. HIGH CREEK SOUTH 45.6 1.4 23.5 .058 .057
( 2.0) ( .1) ( .027) ( .027)
2. HIGH CREEK NORTH 46.9 1.4 11.3 .055 .055
( -7) ( -1) ( .030) ( .030)
3. BEAVER CREEK FEN 47.1 1.2 17.6 .053 .051
( 1.5) ( .1) ( .032) ( .031)
4. GENEVA PARK CREE 46.1 1.4 29.4 .119 .092
( 1.9) ( -1) ! .053) ( .038)
5. HORSESHOE MOUNTA 49.7 1.2 17.6 . 085 .086
( .2) ( .1) ( .046) ( .046)
* A locus is considered polymorphic if the frequency
of the most common allele does not exceed .95
** Unbiased estimate (see Nei, 1978)


* SINGLE INDIVIDUAL GENOTYPE INPUT (ALPHABETIC ALLELIC DESIGNATIONS)
* *
* Test for conformance to Hardy-Weinberg equilibrium *
* *
* BIOSYS-1 Release 1.7 21:06:1999 04:02:01
Levene (1949) correction for small sample sire employed in chi-square analyses
Chi-square test for deviation from Haray-Weinberg equilibrium
***"** v ******* w*'* + ***** + ****
Population: HIGH CREEK SOUTH (HCFS)
46


Locus Class Observed frequency Expected frequency Chi- scuare DF p
DIA-2
A-A 0 .364
A-3 9 8.273
B-3 41 41.364
.431 1 .512
MDH-3
A-A 0 .000
A3 1 1.000
B-3 45 45.000
.000 1 1.000-
PGX-2
A-A 3 1.402
A-3 11 12.794
A-C 0 1.402
B-3 27 27.093
B-C 3 6.021
C-C 0 .289
4.414 3 .220
PGM-3
A-A 43 43.155
A-3 6 5.691
B-5 0 .155
. 172 l .673
SDH
A-A 0 .495
A-3 10 9.011
B-3 36 36.495
. 610 1 .435
TPX-1
A-A 0 .030
A-3 3 2.939
3-3 47 47.030
. 032 .859
Chi-square test with pooling
Population: HIGH CHEEK SOUTH (HCFS)
Observed Locus Class frequency Expected frequency Chi- square DF P
PGI-2 Homozygotes for
47


most common allele 27 27.093
Common/rare
heterozygotes 19 18.814
Rare homozygotes and
other heterozygotes 3 3.093 .005 1 .944
Significance test using exact probabilities
Population: HIGH CREEK SOUTH (HCFS)
Locus R1 R2 R3 p
DIA-2 41 9 0 1.000
MDH-3 45 1 0 1.000
PGI-2 27 19 3 1.000
PG-I-3 43 6 0 1.000
SDH 36 10 0 1.000
TPI-1 47 3 0 1.000
Coefficients for heterozygote deficiency or excess
k-w-** + Tr + Tr-K,mr1r + + ir-H*f*ic*Tryr-*-* + -*iriririr'irir + ir-wl*'ir-wirifw-w-V'wx-ww-*
Population: HIGH CREEK SOUTH (HCFS)
Locus Observed Expected heterozygoses heterozygoses index (F) D
DIA-2 9 8.273 -.099 .088
MDH-3 1 1.000 -.011 .000
PGI-2 19 20.216 . 050 -.060
PGM-2 6 5.591 -,0c; .054
SDK 10 9.011 -.122 .110
TPI-1 3 2.939 -.031 .021
Chi-square irittrirlrieyrirtrfr test for deviation from irlr1eir*irir*lrir-1ririeir + irir*lririririf Kardy-Weinb e rg ecuilibriun
Population: HIGH CREEK NORTH (KCFN)
Locus Observed Class frequency Expected frequency Chi- square DF
DIA-2
48


MDH-3
PGI-2
POT-3
TPI-1
TPI-2
A-A 2 1.681
A3 14 14.637
B-B 30 29.681
A-A 0 .061
A-B 4 3.879
B-3 46 46.061
A-A 2 .680
A-3 0 8.907
A-C 0 1.732
3-3 25 26.351
B-C 14 10.392
C-C 0 .933
A-A 48 48.010
A-3 2 1.980
B-3 0 .010
A-A 0 .000
A-B x 1.000
3-3 43 43.000
A-A 42 42.011
A-3 1.977
3-3 0 .011
:t with pooli ng
.on: HIGH CRE EK NORTH (HCFN)
. 092
.762
. 064
.800
6.644
.084
.010
.919
.000
1.000
.012
.914
Observed Expected Chi-
Locus Class frequency frequency square DJ
PGI-2 Homozygotes for
most common allele 25
Common/rare
heterozygotes 22
Rare homozygotes and
other heterozygotes 2
25.351
19.299
3.351 .992 1 .319
49


Significance test using exact *iritfr'tr'ir^r*iHrie*iririr*irieiHririrtr1Hr*irir Population: HIGH CREEK probabilities NORTH (HCFN)
Locus R1 52 R3 P
DIA-2 30 14 2 1.000
HDH-3 46 4 0 1.000
PGI-2 25 22 2 .467
PGM-3 43 2 0 1.000
TPI-i 43 1 0 1.000
TPI-2 42 2 0 1.000
Coefficients for heterozygote deficiency or excess
Population: HIGH CREEK NORTH (HCFN)
Locus Observed heterozygotes Expected heterozvgotes Fixation index (F) D
DIA-2 14 14.637 .033 -.044
MDH-3 4 3.879 -.042 .031
PGI-2 21.031 -.057 . 045
PGM-3 2 1.980 -.020 .010
TPI-1 x 1.000 -.011 .000
TPI-2 2 1.977 -.023 .012
Chi-square test for deviation from Hardy-Weinberg equilibrium
Population: BEAVER CREEK FEN (3CF )
Locus
DIA-2
PGI-2
Class Observed frequency Expected frequency
A-A 3 4.012
A-B 20 17.975
B-3 IS 19.012
A-A 2 .464
50


A-3 6 8.247
A-C 0 .325
B-B 33 32.577
B-C 8 6.598
C-C 0 .289
PGM-3
A-A 44 44.152
A-3 6 5.697
8-3 0 .152
Chi-square test with pooling
*irlrirKie1r-*nr + -tr-* + lrieiryr'**lr*'*irif*lrir1r
Population: BEAVER CREEK FEN (BCF )
7.115 3 .068
.163 1 .682 -V
Observed Expected Chi-
Locus Class freouer.cy frequency square DF O
PGI-2 Komozygotes for
most common allele 33 32.577
Common/rare
heterozygotes 14 14.S45
Rare hcmozvgotes and
other heterozygotes 2 1.577 .167 1 .633
Significance test using exact probabilities
lrie*Trifr1r-lr-trieieirir1timrirlrTeyeieie,wwirir*lrirlr-xirir-*Tririe-ir*eieir
Population: BEAVER CREEK JEN (SCJ )
Locus R1 R2 R3 O
DIA-2 13 20 3 . 717
PGI-2 33 14 2 . 648
PGM-3 44 5 0 1.000
Coefficients for heterozygote deficiency or excess
Population: BEAVER CREEK FEN (BCF )
Observed Expected Fixation
Locus heterozygotes heterozygotes index (F)
D
DIA-2
20
17.975 -.126 .113
51


PGI-2
14
15.670
.097
-.107
PGM3 6 5.697 -.064 .053
Chi-square test for deviation from Hardy-Weinb erg equilibrium **"******
Population: GENEVA PARK CREE (GPC )
Observed Locus Class frequency Expected frequency Chi- square DF O
DIA-2
A-A 1 7.485
A-3 37 24.030
3-3 12 13.485
14.894 1 .000
MDH-3
A-A 0 1.282
A-3 14 11.437
3-3 22 23.282
1.927 1 .165
PGI-2
A-A 0 1.237
A-3 16 13.031
A-C 0 .495
3-5 30 31.763
B-C 3 2.443
C-C , 0 .031
2.564 3 .446
PGM-3
A-A 42 42.216
A-3 7 6.567
3-3 0 .216
. 246 1 .620
SDK
AA 0 1.462
A-3 17 14.075
B-3 30 31.462
2.138 .144
Chi-square test with pooling

PoDuiation: GENEVA PARK CREE (GPC )

Observed Expected Chi-
Locus Class frequency frequency square DF
52


30
31.763
PGI-2 Homozygotes for
most common allele
Common/rare
heterozygotes 19 15.474
Rare homozygotes and
other heterozygotes 0 1.763 2.664 x .103
Significance test using exact probabilities
#*****ir*t**********ir**#**TnHr******jr***T<*
Population: GENEVA PARK CREE (GPC )
Locus R1 R2 R3 p
DIA-2 12 37 1 .000
MDH-3 22 14 0 .305
PGI-2 30 19 0 .174
PGM-3 42 7 0 1.000
SDH 30 17 0 .319
Coefficients for heterozygote deficiency or excess
1Tir*trlr'trtrfrtr-m*irirlf^-wiciriHHrtrlr-w**ir^lnriririr*'wirtrTr^rfHr-irtrfririnrir*
Population: GENEVA PARK CREE (GPC )
Locus Observed heterozygotes Expected heterozygotes Fixation index (I) D
DIA-2 37 24.030 -. 555 .540
MDH-3 14 11.437 -.241 .224
PGI-2 19 15.969 -.202 .190
PGM-3 7 6.5 67 -.077 . 065
SDH 17 14.075 -.221 .208
Chi-square test for deviation from Kardy-Weinberg equilibrium
Population: HORSESHOE MCUNTA (HSM )
Locus
Class
Observed
frequency
Expected
frequency
Chi-
scuare
DE
DIA-2
53


A-A 4 6.010
A-3 27 22.980
B-3 19 21.010 1.568 1
PGI-2 B-3 22 19.101
B-C 18 23.798
C-C 10 7.101 3.036 1
PGM-3 A-A 49 49.000
A-3 1 1.000
B-3 0 .000 . 000 1
SDK B-3 12 12.374
B-C 26 25.253
C-C 12 12.374 .045 i
Significance test using exact probabilities
irlryctfwir***'*'*'* *'w***Tr**Tr**'*i
Population: HORSESHOE MOUNTA (HSM )
Locus R1 R2 R3 ?
DIA-2 IS 27 4 .343
PGI-2 22 18 10 .130
PGM-3 49 1 0 1.000
SDK 12 26 12 1.000
Coefficients for heterozygote deficiency or exc SSS
ifryr-*-xir-w*1r-xinr *
Populat ion: HORSESHOE MOUNTA (HSM )
Observed Expected Fixation
Locus heterozygotes heterozygotas index (F) D
DIA-2 27 22.980 -.187 .175
PGI-2 18 23.798 . 236 244
PGM-3 1 1.000 -.010 000
SDH 26 25.253 -.040 030
.211
.081
1.000
.833
54


ir'#*'*'***r,*,>r,*ir***'*#*****'**'!ir*,**']lr**'***,#"#T**'**Tr**i*,******"**Tr**'*'*,*Tr'**'**ir*-**
* *
* SINGLE INDIVIDUAL GENOTYPE INPUT (ALPHABETIC ALLELIC DESIGNATIONS) *
* *
* F-Statistics *
#
* BIOSYS-1 Release 1.7 21:06:1999 04:02:01

***^^r^r**!'*****,#*'*****^^**,*1*^llr********W*wHr***w**,^r*,'*r**'*,*'Jr'*1r1P'!r^^!r* + *****
Full output requested
FIS(IK) values
*******'***
Locus: DIA-2
Subpopulation
Allele 1 2 3 4 5
A -.099 3 -.099 .033 -.126 -.555 .033 -.126 -.555 -.187 -.187
Mean -.099 .033 -.126 -.555 -.137
F-statistics for SPir*i^T>fTrie*ir*irTr3e individual alleles
LOCUS: DIA-2
Allele F (IS) F (IT) F (ST)
A -.222 B -.222 -.147 .062 -.147 .062
Mean -.222 -.147 .062
FIS(IK) values
Locus: MDK-3
Subpopulation
Allele 1 2 3 4 5
A -.011 B -.011 -.042 ... -.241 -.042 ... -.241 . .
Mean -.011 -.042 ... -.241
55


F-statistics for individual alleles
irie'iririririfir^HrieWiririfkiriririrff)HHHrfririfleiriHriririr
LOCUS: MDH-3
Allele F(IS) F (IT) F (ST)
A -.192 -.052 . 113
E -.192 -.052 .118
Mean -.192 -.052 . 118
FIS(IK) values

Locus: PGI-2
Subpopulation
Allele 1 2 3 4 5
A .217 ,240 .332 -.195
B -.020 152 .047 -.241 .236
C -.089 ,167 -.089 -.032 .226
Mean. .050 057 .097 -.202 .236
F-statistics for individual ail eles
*,'**'*W*'*,'***W*,'*"*n
LOCUS: PGI-2
Allele F(IS) F(I?) F(ST)
A 127 . 160 . 033
3 -.009 .017 . 026
C .039 .158 . 124
Mean .038 . 094 . 058
FIS(IK) values
Locus: PGM-3
Subpopulation
Allele 12345
56


Subpopulation
Allele 1 2 3 4 5
A B .031 .031 -.011 -.011
Mean .031 -.011
F-statisti cs for individual alleles
LOCUS : TPI-1
Allele F (IS) F (IT)- F (ST)
A B -.026 -.026 -.008 .017 -.008 .017
Mean -.026 -.003 .017
FIS(IK) values
Locus : TPI-2
Subpopulation
Allele i 2 3 4 5
A 3 ... -.023 -.023 . .
Mean .023
F-statistics for i .ndividual alleles *eyrTrTrir+ieTeir^*Trir*-trlr'x +
LOCUS: TPI-2
Allele c (IS) F(IT) FIST)
A B -.023 -.023 -.005 .018 -.005 .018
Mean -.023 -.005 .018
Summary of F-statistics at all loci
57


A -.065 -.020 -.064 -.077 -.010
3 -.065 -.020 -.064 -.077 -.010
Mean -.065 -.020 -.064 -.077 -.010
F-statistics for individual alleles
LOCUS: PGM-3
Allele F(IS) F (IT) F (ST)
A -.062 B -.062 -.047 -.047 .014 .014
Mean -.062 -.047 .014
FIS(IK) values
Locus: SDH
Subpopulat ion
.Allele 1 2 3 4 5
A -.122 3 -.122 C . . -.221 -.221 -.040 -.040
Mean -.122 -.221 -.040
F-scatistics for individual alleles
LOCUS: SDH
Allele F (IS) F(IT) F (ST)
A -.182 -.061 . 102
3 -.110 .173 .255
C -.040 .422 . 444
Mean -.110 .208 .287
FIS (IK) values
********
Locus: TPI-1
58


Locus F(I S) F C IT)' F (ST)
DIA-2 -.222 -.147 .062
MDH-3 -. 1S2 -.052 .118
PGI-2 .038 .094 .058
PGM-3 -.062 -.047 .014
SDH -.110 .208 .287
TPI-1 -.026 -.008 .017
TPI-2 -.023 -.005 .018
Mean -.097 . 023 .109
59


Appendix C GENESTAT Data
CALC WAS CHOSEN
NOGROUPS WAS CHOSEN
Number of loci = 17
Number of populations = 5
LOCUS ALL ELE S
AEK
ALD A
DIA-l n
DIA-2 A 3
DIA-3
GPD-i
MDH-2 * A
MDH-3 5
MDK-4 A
ME A
=GL A
PGE-2 5 C
PGM-3 A 3
TUH A 3 c
SCOZ A
T?I-I A 3
i'r i 2 .A 3
HLE OF ALLELE CUS- EREQUSNCI :-:crs ES KCFN scr G?C KSM
ALLELE M N M N N
AE-H 50 47 49 50 £ P
A 1.000 1.000 1.000 1.000 1.000
.ALL 49 41 25 30 50
A 1.000 1.000 1.000 1.000 1.000
DLA-1 43 45 44 50 50
A 1.000 1.000 1.000 1.000 1.000
DLA2 50 45 41 > 50 50
A 0.090 0.196 0.317 0.390 0.250
3 0.910 0.304 0.683 0.610 0. S50
DIA-3 48 46 50 so 50
60


A 1.000 1.000 1.000 1.000 1.000
GPD-1 25 50 50 50 49
A 1.000 1.000 1.000 1.000 1.000
MDH-2 46 50 50 50 50
A 1.000 1.000 1.000 1.000 1.000
MDH-3 46 50 50 36 50
A 0.011 0.040 0.000 0.194 0.000
B 0.989 0.960 1.000 0.306 1.000
MDH-4 24 50 49 26 4S
A 1.000 1.000 1.000 1.000 1.000
ME 47 44 46 49 50
A 1.000 1.000 1.000 1.000 1.000
PGD 49 48 48 48 50
A 1.000 1.000 1.000 1.000 1.000
PGI-2 49 49 49 49 50
A 0.173 0.122 0.102 0.163 0.000
B 0.745 0.735 0.316 0.806 0. S20
C 0.082 0.143 0.082 0.031 0.380
PGM-3 49 50 50 49 50
A 0.939 0.980 0.940 0.929 0.990
3 0.061 0.020 0.060 0.071 0.010
SDK 46 jg 50 47 50
A 0.109 0.000 0.000 0.131 0.000
B 0.891 1.000 1.000 0.319 0.500
C 0.000 0.000 0.000 0.000 0.500
SOD-2 50 45 49 50 50
A 1.000 1.000 1.000 1.000 1.000
TPI-1 50 44 50 50 50
A 0.030 0.011 0.000 0.000 0.000
B 0.970 0.989 1.000 1.000 1.000
TPI-2 50 44 50 50 50
A 1.000 0.977 1.000 1.000 1.000
61


B
0.000 0.023
0.000
0.000 0.000
GENETIC IDENTITIES (ABOVE) AND GENETIC DISTANCES (BELOW)
KCFS KCFN BCF GPC KSM
HCFS | 0.959 0.596 0.993 0.979
KCFN | 0.001 0.999 0.994 0.981
BCE | 0.004 0.001 0.996 0.981
G?C | 0.007 0.006 0.004 0.930
KSM | 0.021 0.019 0.020 0.020
MATRIX OF GENE IDENTITIES
ADH ALD DIA-l DIA-2 DIA-3 GPD-1 MDH-2 MDH-3
l HCFS | 1.000 1.000 1.000 0.336 1.000 1.000 1.000 0.973
HCFN | 1.000 1.000 1.000 0.685 1.000 1.000 1.000 0.923
3CF | 1.000 1.000 1.000 0.567 1.000 1.000 1.000 1.000
GPC | 1.000 1.000 1.000 0.524 1.000 1.000 1.000 0.687
KSM | 1.000 1.000 1.000 0.545 1.000 1.000 1.000 1.000
MDH-4 ME PGD PGI-2 PGM-3 SDK SOD-2 TPI-1
1 HCFS | 1.000 1.000 1.000 0.592 0.885 0.806 1.000 0.942
HCFN 1 1.000 1.000 1.000 0.576 0.961 1.000 1.000 0.978
BCF 1 1.000 1.000 1.000 0.533 0.337 1.000 1.000 1.000
GPC | 1.000 1.000 1.000 0.677 0.363 0.704 1.000 1.000
KSM 1 1.000 1.000 1.000 0.529 0.930 0.500 1.000 1.000
TPI-2
1 KCFS | 1.000
HCFN | 0.955
BCF 1 1.000
GPC 1 1.000
KSM | 1.000
VERSITY STATISTICS, UNBIASED FOR SAMPLE S IZE
Ks J S Kt Jt Dst CDsc Gst CGsc
I
ADH | 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
ALD | 0.000 1.000 0.000 1.000 0.000 0. 000 0. 000 0.000
DIA-l | 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
62


DIA-2 1 0.373 0.627 0.394 0.606 0.021 0.034 0.054 0.069
DIA-3 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
GPD-1 1 O.COO 1.000 0.000 1.000 0.000 0.000 0.000 0.000
MDH-2 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
MDH-3 1 0.083 0.917 0.093 0.907 0.010 0.011 0.109 0.114
MDH-4 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
ME 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
PGD 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
PGI-2 1 0.3S3 0.607 0.414 0.586 0.021 0.035 0.050 0.065
PGM-3 1 0.083 0.915 0.085 0.915 0.001 0.001 0.006 0.006
SDH 1 0.200 0.300 0.278 0.722 0.078 0.102 0.280 0.314
SOD-2 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
TPI-1 1 0.016 0.984 0.016 0.984 0.000 0.000 0.009 0.009
TPI-2 1 0.009 0.991 0.009 0.991 0.000 0.000 0.000 0.000
GENE DIVERSITY STATISTICS UNBIASED FOR SAMPLE SIZE Ks OVER ALL Js LOCI, Ht Jt Dst CDst GsC CGst
1 0.068 0.932 0. . 076 0.524 0.008 0.008 0.101 0.105
GENE DIVERSITY SAMPLE SIZE AND STATISTICS, UNBIASED POPULATION NUMBER FOR
Ks Js Ht Jt Ds'C CDst Gs t CGst
ADH 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
ALD 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
DIA-1 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
DIA-2 1 0.373 0.627 0.399 0.601 0.026 0.043 0.065 0.034
DIA-3 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
GPD-1 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
MDH-2 1 0.000 1.000 0.000 1.000 0. oco 0. 000 0. 000 0.000
MDH-3 1 0.083 0.917 0.096 0.904 0.012 0.014 0.131 0.137
MDH-4 1 0.000 1.000 0.000 1.000 0.000 0. 000 0. 000 0.000
ME 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
PGD 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
PGI-2 1 0.393 0.607 0.419 0.581 0.025 0.044 0.063 0.081
PS-!-3 1 0.085 0.915 0.085 0.918 0.000 0.000 0.000 0.000
SDH 1 0.200 0.800 0.298 0.702 0.098 0.130 0.328 0.363
SOD-2 1 0.000 1.000 0.000 1.000 0.000 0.000 0.000 0.000
TPI-1 1 0.015 0.934 0.016 0.984 0.000 0.000 0.000 0.000
TPI-2 1 0.009 0.991 0.009 0.991 0.000 0.000 0.000 0.000
GENE DIVERSITY STATISTICS OVER ALL LOCI, UNBIASED FOR SAMPLE SIZE AND POPULATION Ks Js Ht NUMBER Jt Dst CDst Gst CGst
I 0.063
0.S32
0.078
0.S22 0.010 0.010
0.123 0.123
63


Appendix D Genetic Diversity and Structure in Dioecious Flowering Plants
Taxa P A H. Hr Source
Buchloe 54.54 2.92 - 0.14 - - Peakall et al., 1995
Euryajaponica*** 94.17 3.79 0.425 0.462 0.496 0.069 Chung & Kang
Schiedea adamantis** 22 1.56 0.077 - - - Weller etal., 1996
Schiedea globosa* 46.66 1.78 0.192 - - - Weller etal., 1996
Schiedea kealiae* 66.7 2.78 0.322 - - - Weller etal., 1996
Schiedea salicaria** 72.25 2.22 0.304 - - - Weller etal., 1996
Schiedea sarmentosa** 77.8 2.56 0.31 - - - Weller etal., 1996
Schiedea ligustrma*** 66.7 2.44 0.294 - - - Weller etal., 1996
Populus 81.3 2.4 0.32 0.29 0.31 0.03 Jelinski & Cheliak
Cecropia obtusifolia - - - - - 0.029 Alvarez-Buylla &
Schizopepon - - - - 0.358 0.688 Akimoto et al.,
No. of Data Points 9 9 8 3 3 4 Yarbrough
MEAN 64.68 2.49 0.281 0.297 0.388 0.204 Yarbrough
Standard Deviation 21.31 0.653 0.104 0.161 0.097 0.323 Yarbrough
* = subdioecy, ** = gynodioecy, *** = dioecy, ND = no data, P = percent
polymorphic loci, A = avg. # of alleles per locus, Ha = observed heterozygosity, He =
expected heterozygosity, HT = total heterozygosity, Gsr = population differentiation,
Fst = population subdivision.
64


Appendix E Genetic Diversity and Structure in Monoecious Flowering Plants
TAXON P A Ap Ho Ho HI Gst SOURCE
Carex btaetowli 46.7 1.8 2.4 0.163 0.167 SSwiSS 0.05S Jonsson etal. 1996
Carex tasrocarca 48 1.6 22 0.21 022 0266 0.151 McCIintock and Waterway 1993
Carex membranacea 44.4 1.6 xmem 0.153 0.162 0.199 0.183 Pent etal 1991
Carex peifite 44 1.6 2.2 0.22 021 0248 0.181 UcCtinted and Waterway 1993
Carex rotunda 37.2 1.5 .S^ISIS 0.163 0.12 0.148 0.184 Ford etal 1991
Carex sazans 44.S 1.6 0.135 0.146 0.162 0.198 Fend etal 1991
Carex abrupt! 25.8 1.3 2 0 0.064 0.17 0.5 Whitkus 1992
Carex aurea 22.1 1.2 2.1 0.023 0.053 0.173 0282 Unknown
Carex basiantha 40.2 15 JraSStfeSS*1 0.189 0.136 0.156 0.114 Ford etal. 1996
Carex cnnita 2.3 1 2 0 0.007 0.2S8 0.658 Bruederte and Fairbrothere 1986*
Carex cnnita var. brevwraus 1.6 2 0.003 0.006 0.256 0.658 Bruedarto end Faxbrattwre 1986
Carex crYPtotepis 3.5 msmm 0.004 0.011 Unknown
Carex ftava 9.6 1.1 2 0.003 0.018 0.036 0.416 Bnwderte and Jensen 1991
Carex pvnandra 10.2 1.1 2 0.008 0.032 0256 0.658 Bruederte and Feirbromers 1986
Carex avnodynama 3.5 1.1 2 0.095 1 1 sa Waterway 1990
Carex harfordi 4.8 1.1 2 0 0.016 0.052 0.712 Whitkus 1992
Carex turbssma 14.7 1.2 2 0.007 0.036 0.361 Waterway 1996
Carex mteara 19.5 1.2 2.1 0.019 0.047 0.169 0.426 WNttus 1992
Carex mac to via na 0 0 0 6 am&m Whitkus 1992
Carex mendocinensts 27.5 1.3 2.1 0.058 0.06 0.097 0.15 Waterway 1990
Carex misers 34.8 1.4 2.3 0.082 0.082 0.349 0.161 GodtetaL 1998
Carex misara 9.7 1.1 2.2 0.008 0.019 0.043 0.551 Schell and Waterway 1992
Carex mrtchesana 10 1.1 2 0.01 0.037 0.147 0369 Bruederte and Feirttromere 1966
Carex paentachva 6.4 1.1 2 0.001 0.025 0.127 0.603 Whitkus 1992
Carex preslii 10 1.1 2 0 0.04 0.041 rWZ?- Whitkus 1992
Carex subbreeteata 6 1.1 2.2 0 0.006 0.009 Whitkus 1992
Carex stiluses 5.5 1.1 2 0 0.006 0.15 0.967 Whrtkua1992
Carex superata 21.6 1.3 0.114 0.071 0.072 0.011 Ford etal. 1998
Carex vtnduta 13.3 1.1 2 0.02 0.041 0212 0.806 Bruederte end Jensen 1991
Carex wtSdenowil 40 1.5 :ssas3 0237 0.148 0.177 0.167 Ford etal 1998
Vaceinium ellioGi 45 2.08 2.9 0.096 0.151 0.126 Breuderteetal. 1991
Vaccmium mvrtltoides 45 22 2.72 0.14 0.196 0.133 Breuderteetal. 1991
Vaccmium teneltum 54 2.26 2.B8 0.176 jisisS 0212 0.127 Breuderteetal. 1991
Vacctreum antrocoecum 77.28 3m 2.5 028 0 287 Bruederte & Vorsa 1994
Vaccmium boreaie 75.76 2.6 025 0264 Bruederte & Vorsa 1994
Vaccmium caesariense 72.73 2.6 0.244 0276 r&lIXp?kS mam Bruederte & Vorsa 1994
Vaccmium darrowii 64.09 2.8 0.304 0.321 Bruederte & Versa 1994
Vaceinium vaciQans 84.85 3.2 0.316 0.353 Bruederte & Vorsa 1994
Pedculara dasvamha 3 1.03 0 0.016 0.716 Odasz & Savolainen 1996
Ptanapo malar 13.4 ssms ow WoBT 1991
Ptantaao lanceoiata 17.5 0 051 Wolff 1991
Plantaao corenopus 29.5 0.11 Wolff 1991
Schiedea diffusa 0 iPSMS 0 limsmMmm* Welteretal. 1996
Schiedea hooked
Schiedea taalae
Schiedea Qgustrtna
Schiedea ftdgatpi
Schiedea membranacea
Schiedea monnesu
Schiedea rtunalla
Schiedea cube score
Schiedea stellarioides
Schiedea verttciUata
Ateradendren lychnoides
Alsinidendrenobovatuni
Alsimdsndtpn Wnerva
Atemidenflron viscosum
Abronia maerocama
Trifobum amoenum 22.5 125 0.034 0.067
Trifolium afbopgreum 32.5 1.35 0.046 0.086
Trtfolium macraei 18.33 123 r&tiSgS&tif 0.0005 0.0696
Tncvrbs ftava 64.7 2.05 2.86 0.168
Tnewts nana 23.5 124 2.33 0.026
>< .:c\L,A 0.041
44 ::cwbsftRl 0.294 wrlWMarMbwawBOteg
-------'0.322
*** U-J4
WeBeretal. 1996
WeBer etal. 1996
Wetteretat. 1996
Welter etal. 1996
Welter etal. 1996
Welteretal. 1996
Welteretal. 199S
Welteretal 1996
Welteretal 1996
Welteretal 1996
Welteretal. 1996
Welteretal 1996
Welteretal. 1996
WeBeretal 1996
Knapp and Connors 1999
Knapp and Connors 1999
Knapp and Connors 1999
Maid etal. 1999
0.483
Maid etal. 1999
WiKamaon and Worm 1999
Note: Carax data coiected and sunmarized by S. Kuctel Grey sharing no data avaitebte.
65


Appendix F Genetic Diversity and Structure in Monoecious Carices
Taxon P A H0 He ht Gst Source
Carex bigelowii 49 1.8 0.16 0.17 ND 0.06 Jonsson et al., 1996
Carex lasiocarpa 48 1.6 0.21 0.22 0.27 0.15 McClintock and Waterway 1993
Carex membranacea 44 1.6 0.15 0.16 0.20 0.18 Ford et al., 1991
Carex pellita 44 1.6 0.22 0.21 0.25 0.18 McClintock and Waterway 1993
Carex rotunda 37 1.5 0.16 0.12 0.15 0.18 Ford et al., 1991
Carex saxatilis 45 1.6 0!l4 0.15- 0.18 0.20 Ford etal., 1991
Carex abrupta 26 1.3 0 ' 0.06 0.17 0.5 Whitkus 1992
Carex aurea 22 1.2 0.02 0.05 0.17 0.28 Unknown
Carex basiantha 40 1.5 0.19 0.14 0.16 0.11 Ford etal., 1998
Carex crinita 2.3 1 0 0.01 0.26 0.66 Bruederle and Fairbrothers 1986*
Carex crinita var. 1.6 1 0 0.01 0.26 0.66 Bruederle and Fairbrothers 1986
Carex ilava 9.6 1.1 0 0.02 0.04 0.42 Bruederle and Jensen 1991
Carex gynandra 10 1.1 0.01 0.03 0.26 0.66 Bruederle and Fairbrothers 1986
Carex harfordii 4.8 1.1 0 0.02 0.05 0.71 Whitkus 1992
Carex hirtissima 15 1.2 0.01 0.04 ND 0.36 Waterway 1996
Carex integra 20 1.2 0.02 0.05 0.17 0.43 Whikus 1992
Carex mendocinensis 28 1.3 0.06 0.06 0.10 0.15 Waterway 1990
Carex misera 35 1.4 0.08 0.08 0.35 0.16 Godt et al., 1996
Carex misera 9.7 1.1 0.01 0.02 0.04 0.55 Schell and Waterway 1992
Carex mitchelliana 10 1.1 0.01 0.04 0.15 0.37 Bruederle and Fairbrothers 1986
Carex pacystachya 8.4 1.1 0 0.03 0.13 0.80 Whitkus 1992
Carex subfusca 5.5 1.1 0 0.01 0.15 0.97 Whitkus 1992
Carex superata 22 1.3 0.11 0.07 0.07 0.01 Ford et al., 1998
Carex viridula 13 1.1 0.02 0.04 0.21 0.81 Bruederle and Jensen 1991
Carex willdenowii 40 1.5 0.24 0.15 0.18 0.17 Ford et al.. 1998
No. of Data Points. 25 25 25 25 23 25 Yarbrough
Mean 23.60 1.30 0.07 0.073 0.172 0.389 Yarbrough
Standard Deviation 16.09 0.23 0.084 0.065 0.080 0.272 Yarbrough
66


Appendix G Genetic Diversity and Structure in Caespitose Carices
TAXON P% A Ap Ho H. Hr Gyr Reference
Carex abrupta 25.8 1.3 2 0 0.064 0.17 0.5 Whitkus, 1992
Carex aurea** 22.1 1.2 21 0.023 0.053 0.173 0.282 Unknown
Carex basiantha 40.2 1.5 No data 0.189 0.138 0.156 0.114 Ford etal., 1998
Carex crinita 23 1 2 0.003 0.007 0.256 0.658 Bruederle & Fairbrothere, 1986***
Carex crinita var. brevicrinis 1.6 1 2 0 0.006 0.256 0.658 Bruederfe & Fairbrothere, 1986
Carex cryptolepis 3.5 No data 0.004 0.011 No data No data Unknown
Carex flava 9.6 1.1 2 0.003 0.018 0.036 0.416 Bruederle & Jensen, 1991
Carex gynandra 10.2 1.1 2 0.008 0.032 0.256 0.658 Bruederfe & Fairbrothere, 1986
Carex gynodynama 3.5 1.1 2 0 0.095 No data No data Waterway, 1990
Carex harfordii 4.8 1.1 2 0 0.016 0.052 0.712 Whitiais, 1992
Carex hirtissima 14.7 1.2 2 0.007 0.036 No data 0.361 Waterway, 1996
Carex integra 19.5 1.2 2.1 0.019 0.047 0.169 0.426 Whitkus, 1992
Carex macloviana 0 No data 0 0 0 No data Whitkus, 1992
Carex mendocinensis 27.5 1.3 21 0.056 0.06 0.097 0.15 Waterway, 1990
Carex misera 34.8 1.4 23 0.082 0.082 0.349 0.161 Godt, etal., 1996
Carex misera 9.7 1.1 22 0.008 0.019 0.043 0.551 Schell and Waterway, 1992
Carex mrtchelliana 10 1.1 2 0.01 0.037 0.147 0.369 Bruederfe & Fairbrothere, 1986
Carex pacystachya 8.4 1.1 2 0.001 0025 0.127 0.803 Whitkus, 1992
Carex preslii 10 1.1 2 0 0.04 0.041 No data Whitkus, 1992
Carex subbracteata 6 1.1 22 0 0.006 0.009 No data Whitkus, 1992
Carex subfusca 5.5 1.1 2 0 0.006 0.15 0.967 Whitkus, 1992
Carex superata 21.6 1.3 No data 0.114 0.071 0.072 0.011 Ford, etal., 1998
Carex viridula 13.3 1.1 2 0.02 0.041 0.212 0.806 Bruederle & Jensen, 1991
Carex willdenowii 40 1.5 No data 0.237 0.148 0.177 0.167 Ford, et al., 1998
MEAN 14.4 1.2 21 0.033 0.044 0.14 0.462
Standard Deviation 12 0.15 0.09 0.063 0.04 0.094 0.272
Data for this table compiled by S.D. Kuchel, 1999 *** GST value is over all polymorphic loci in complex
P% = percent polymorphic loci
A = Avg. # of alleles per locus
Ap = Avg. # of alleles per polymorphic locus
H0 = observed heterozygosity
H0 = expected heterozygosity
HT = total heterozygosity
G yr = population differentiation
67


Appendix H Genetic Diversity and Structure in Rhizomatous Carices
TAXON P% A AP H0 He Hr G sr Reference
Carex bigelowii 48.7 1.8 2.4 0.163 0.167 No data 0.055 Jonsson et al., 1996
Carex lasiocarpa 48 1.6 2.2 0.21 0.22 0.266 0.151 McClintock & Waterway, 1993
Carex membranaceae 44.4 1.6 No data 0.153 0.162 0.199 0.183 Ford et al., 1991
Carex pellita 44 1.6 2.2 0.22 0.21 0.248 0.181 McClintock & Waterway, 1993
Carex rotunda 37.2 1.5 No data 0.163 0.12 0.148 0.184 Ford et al., 1991
Carex saxatilis 44.5 1.6 No data 0.135 0.146 0.182 0.198 Ford et al., 1991
Mean 44.5 1.6 2.3 0.174 0.171 0.209 0.159
Standard Deviation 4.08 0.1 0.12 0.034 0.038 0.048 0.053
Data for this table compiled by S.D. Kuchei, 1999
= percent polymorphic loci
A = Avg. # of alleles per locus
Ap = Avg; # of alleles per polymorphic locus
H0 = observed heterozygosity
H. = expected heterozygosrt
Ht = total heterozygosity
G S7 = population differentiati
68


Appendix I Mann-Whitney U-test Statistical Results
Worksheet size: 3500 cells
MTB > Retrieve 'C:\THESIS\SCIRP.MTW'.
Retrieving worksheet from file: C:\THESIS\SCIRP.MTW
Worksheet was saved on 4/16/2000
MTB > Mann-Whitney 95.0 DioP' 'MOspP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DioP N = 10 Median = 66.70
MOspP N = 81 Median = 32.50
Point estimate for ETA1-ETA2 is 27.47
95.0 Percent C.I. for ETA1-ETA2 is (5.50,45.29)
W = 650.5
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0159
The test is significant at 0.0159 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DioA' 'MOspA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DioA N = 10 Median = 2.4200
MOspA N = 70 Median = 1.4050
Point estimate for ETA1-ETA2 is 0.7700
95.1 Percent C.I. for ETA1-ETA2 is (0.2998,1.2901)
W = 605.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0037
The test is significant at 0.0036 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DIspHo' 'MOspHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspHo N = 9 Median = 0.3040
MOspHo N = 57 Median = 0.0560
69


Point estimate for ETA1-ETA2 is 0.1720
95.0 Percent C.I. for ETA1-ETA2 is (0.0690,0.2880)
W = 462.5
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0027
The test is significant at 0.0026 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DioHe' 'MOspHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DioHe N = 4 Median = 0.2150
MOspHe N = 45 Median = 0.0640
Point estimate for ETA1-ETA2 is 0.1215
95.3 Percent C.I. for ETA1-ETA2 is (0.0020,0.2950)
W = 155.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0466
The.test is significant at 0.0466 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DioP' 'MoCrxP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DioP N = 10 Median = 66.70
MoCrxP N = 25 Median = 22.00
Point estimate for ETA1-ETA2 is 39.21
95.3 Percent C.I. for ETA1-ETA2 is (24.26,56.71)
W = 286.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0001
The test is significant at 0.0001 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DioA' 'MoCrxA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
70


DioA N = 10 Median = 2.4200
MoCrxA N = 25 Median = 1.2000
Point estimate for ETA1-ETA2 is 1.1200
95.3 Percent C.I. for ETA1-ETA2 is (0.6200,1.4199)
W = 294.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0000
The test is significant at 0.0000 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DIspHo' 'MOcrxHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspHo N = 9 Median = 0.3040
MOcrxHo N = 25 Median = 0.0200
Point estimate for ETA1-ETA2 is 0.1920
95.4 Percent C.I. for ETA1-ETA2 is (0.0770,0.3000)
W = 247.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0005
The test is significant at 0.0005 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DioHe' 'MoCrxHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DioHe N = 4 Median = 0.2150
MoCrxHe N = 25 Median = 0.0500
Point estimate for ETA1-ETA2 is 0.1250
95.4 Percent C.I. for ETA1-ETA2 is (0.0200,0.3220)
W = 95.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0291
The test is significant at 0.0288 (adjusted for ties)
MTB > Mann-Whitney 95.0 'CaesCrxP' 'RhizCrxP';
SUBC> Alternative 0.
71


Mann-Whitney Confidence Interval and Test
CaesCrxP N = 24 Median = 10.00
RhizCrxP N = 6 Median = 44.45
Point estimate for ETA1-ETA2 is -34.10
95.4 Percent C.I. for ETA1-ETA2 is (-39.60,-22.30)
W = 302.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0003
The test is significant at 0.0003 (adjusted for ties)
MTB > Mann-Whitney 95.0 'CaeCrxA' 'RhizCrxA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
CaeCrxA N = 24 Median = 1.1000
RhizCrxA N = 6 Median = 1.6000
Point estimate for ETA1-ETA2 is -0.5000
95.4 Percent C.I. for ETA1-ETA2 is (-0.6000,-0.3000)
W = 301.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0003
The test is significant at 0.0002 (adjusted for ties)
MTB > Mann-Whitney 95.0 'CaespHo' 'RhizHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
CaespHo N = 24 Median = 0.00550
RhizHo N = 6 Median = 0.16300
Point estimate for ETA1-ETA2 is -0.15300
95.4 Percent C.I. for ETA1-ETA2 is (-0.19999,-0.12802)
W = 310.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0014
The test is significant at 0.0013 (adjusted for ties)
MTB > Mann-Whitney 95.0 'CaeCrxHe' 'RhiCrxHe'/
72


SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
CaeCrxHe N = 24 Median = 0.03650
RhiCrxHe N = 6 Median = 0.16450
Point estimate for ETA1-ETA2 is -0.12900
95.4 Percent C.I. for ETA1-ETA2 is (-0.16300,-0.09100)
W = 303.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0004
The test is significant at 0.0004 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpP' 'DioP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpP N = 5 Median = 17.65
DioP N = 10 Median = 66.70
Point estimate for ETA1-ETA2 is -45.78
95.7 Percent C.I. for ETA1-ETA2 is (-63.65,-23.13)
W = 17.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0059
The test is significant at 0.0058 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpA' 1DioA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpA N = 5 Median = 1.3500
DioA N = 10 Median = 2.4200
Point estimate for ETA1-ETA2 is -1.0700
95.7 Percent C.I. for ETA1-ETA2 is (-1.5401,-0.3200)
W = 15.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0027
The test is significant at 0.0026 (adjusted for ties)
73


MTB > Mann-Whitney 95.0 'ScirpHo' 'DIspHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHo N = 5 Median = 0.0580
DIspHo N = 9 Median = 0.3040
Point estimate for ETA1-ETA2 is -0.2250
95.4 Percent C.I. for ETA1-ETA2 is (-0.2670,-0.0210)
W = 19.0 . '
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0164
MTB > Mann-Whitney 95.0 'ScirpHe' 'DioHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHe N = 5 Median = 0.0700
DioHe N = 4 Median = 0.2150
Point estimate for ETA1-ETA2 is -0.1450
96.3 Percent C.I. for ETA1-ETA2 is (-0.4019,0.0100)
W = 17.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0662
The test is significant at 0.0651 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpP' 'MOspP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpP N = 5 Median =
MOspP N = 81 Median =
Point estimate for ETA1-ETA2 is
95.2 Percent C.I. for ETA1-ETA2 is
W = 158.0
17.65
32.50
-12.24
(-47.05,7.65)
74


Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.2762
The test is significant at 0.2761 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpA' 'MOspA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpA N = 5 Median = 1.3500
MOspA N = 70 Median = 1.4050
Point estimate for ETA1-ETA2 is -0.0700
95.1 Percent C.I. for ETA1-ETA2 is (-0.8499,0.2099)
W = 174.5
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.7500
The test is significant at 0.7495 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpHo' 'MOspHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHo N = 5 Median = 0.05800
MOspHo N = 57 Median = 0.05600
Point estimate for ETA1-ETA2 is 0.01600
95.1 Percent C.I. for ETA1-ETA2 is (-0.13101,0.05799)
W = 168.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.7960
The test is significant at 0.7953 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpHe' 'MOspHe';
SUBC> Alternative 0.
75


Mann-Whitney Confidence Interval and Test
ScirpHe N = 5 Median = 0.07000
MOspHe N = 45 Median = 0.06400
Point estimate for ETA1-ETA2 is 0.00700
95.1 Percent C.I. for ETA1-ETA2 is (-0.08800,0.04900)
W = 135.5
Test of ETAl = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.8084
The test is significant at 0.8083 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpP' 'MoCrxP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpP N = 5 Median = 17.65
MoCrxP N = 25 Median = 22.00
Point estimate for ETA1-ETA2 is -2.35
95.5 Percent C.I. for ETA1-ETA2 is (-20.47,12.14)
W = 76.0
Test of ETAl = ETA2 vs. ETAl ~= ETA2 is significant a
t 0.9556
The test is significant at 0.9556 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpA' 'MoCrxA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpA N = 5 Median =
MoCrxA N = 25 Median =
Point estimate for ETA1-ETA2 is
95.5 Percent C.I. for ETA1-ETA2 is
W = 91.0
1.3500
1.2000
0.1100
(-0.1901,0.2501)
76


Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.4694
The test is significant at 0.4639 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpHo' 'MOcrxHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHo N = 5 Median = 0.05800
MOcrxHo N = 25 Median = 0.02000
Point estimate for ETA1-ETA2 is 0.03900
95.5 Percent C.I. for ETA1-ETA2 is (-0.09202,0.06498)
W = 90.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.5043
The test is significant at 0.5009 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpHe' 'MoCrxHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHe N = 5 Median = 0.07000
MoCrxHe N = 25 Median = 0.05000
Point estimate for ETA1-ETA2 is 0.02000
95.5 Percent C.I. for ETA1-ETA2 is (-0.06999,0.05001)
W = 90.5
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.4867
The test is significant at 0.4855 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpP' 'CaesCrxP';
SUBC> Alternative 0.
77


Mann-Whitney Confidence Interval and Test
ScirpP N = 5 Median = 17.65
CaesCrxP N = 24 Median = 10.00
Point estimate for ETA1-ETA2 is 7.88
95.4 Percent C.I. for ETA1-ETA2 is (-4.46,16.05)
W = 101.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.1410
The test is significant at 0.1408 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'ScirpA' 'CaeCrxA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpA N = 5 Median = 1.3500
CaeCrxA N = 24 Median = 1.1000
Point estimate for ETA1-ETA2 is 0.1500
95.4 Percent C.I. for ETA1-ETA2 is (0.0400,0.3100)
W = 116.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0194
The test is significant at 0.0159 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpHo' 'CaespHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHo N = 5 Median = 0.05800
CaespHo N = 24 Median = 0.00550
Point estimate for ETA1-ETA2 is 0.05350
95.4 Percent C.I. for ETA1-ETA2 is (0.03300,0.08500)
W = 116.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0194
78


The test is significant at 0.0181 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpHe' 'CaeCrxHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHe N = 5 Median = 0.07000
CaeCrxHe N = 24 Median = 0.03650
Point estimate for ETA1-ETA2 is 0.03600
95.4 Percent C.I. for'ETA1-ETA2 is (-0.00001,0.06000)
W = 109.5
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0496
The test is significant at 0.0495 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpP' 'RhizCrxP';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpP N = 5 Median = 17.65
RhizCrxP N = 6 Median = 44.45
Point estimate for ETA1-ETA2 is -25.89
96.4 Percent C.I. for ETA1-ETA2 is (-32.64,-14.99)
W = 15.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0081
The test is significant at 0.0080 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpA' 'RhizCrxA';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpA N = 5 Median =
RhizCrxA N = 6 Median =
Point estimate for ETA1-ETA2 is
96.4 Percent C.I. for ETA1-ETA2 is
W = 15.0
1.3500
1.6000
-0.2550
-0.3900,-0.1900)
79


Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0081
The test is significant at 0.0065 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpHo' 'RhizHo';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHo N = 5 Median = 0.05800
RhizHo N = 6 Median = 0.16300
Point estimate for ETA1-ETA2 is -0.10050
96.4 Percent C.I. for ETA1-ETA2 is (-0.15701,-0.04399)
W = 15.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0081
The test is significant at 0.0080 (adjusted for ties)
MTB > Mann-Whitney 95.0 'ScirpHe' 'RhiCrxHe';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
ScirpHe N = 5 Median = 0.07000
RhiCrxHe N = 6 Median = 0.16450
Point estimate for ETA1-ETA2 is -0.09650
96.4 Percent C.I. for ETA1-ETA2 is (-0.15002,-0.05600)
W = 15.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0081
The test is significant at 0.0080 (adjusted for ties)
MTB > Mann-Whitney 95.0 'DIspGst' 'MOspGst';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspGst N = 4 Median = 0.0495
MOspGst N = 49 Median = 0.2000
Point estimate for ETA1-ETA2 is -0.1150
80


95.1 Percent C.I. for ETA1-ETA2 is (-0.3571,0.1879)
W = 61.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.1174
The test is significant at 0.1174 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'DIspGst' 'MOcrxGst';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspGst N = 4 Median = 0.0495
MOcrxGst N = 25 Median = 0.3600
Point estimate for ETA1-ETA2 is -0.1500
95.4 Percent C.I. for ETA1-ETA2 is (-0.5910,0.0592)
W = 35.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.1213
The test is significant at 0.1208 (adjusted for ties)
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'DIspGst' 'CaespGst';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspGst N = 4 Median = 0.0495
CaespGst N = 19 Median = 0.4260
Point estimate for ETA1-ETA2 is -0.2960
95.3 Percent C.I. for ETA1-ETA2 is (-0.6288,0.0300)
W = 28.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.1137
The test is significant at 0.1134 (adjusted for ties)
Cannot reject at alpha = 0.05
81


MTB > Mann-Whitney 95.0 'DIspGst' 'RhizGst';
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
DIspGst N = 4 Median = 0.0495
RhizGst N = 6 Median = 0.1820
Point estimate for ETA1-ETA2 is -0.1145
95.7 Percent C.I. for ETA1-ETA2 is (-0.1550,0.5069)
W = 17.0 . .
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.3374
Cannot reject at alpha = 0.05
MTB > Mann-Whitney 95.0 'CaespGst' 'RhizGst'/
SUBC> Alternative 0.
Mann-Whitney Confidence Interval and Test
CaespGst N = 19 Median = 0.4260
RhizGst N = 6 Median = 0.1820
Point estimate for ETA1-ETA2 is 0.3040
95.5 Percent C.I. for ETA1-ETA2 is (0.0159,0.5280)
W = 280.0
Test of ETA1 = ETA2 vs. ETA1 ~= ETA2 is significant a
t 0.0386
The test is significant at 0.0385 (adjusted for ties)
MTB >
82


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