CALIFORNIA STATE UNIVERSITY, NORTHRIDGE

GENETIC VARIATION AND GENE FLOW IN LYONII

() AT SEVEN SITES IN SOUTHERN CALIFORNIA

A thesis submitted in partial fulfillment of the requirements

for the degree of Masters of Science

in Biology

By

Lisa L. Zung

August 2012

The thesis of Lisa L. Zung is approved:

______Dr. David A. Gray Date

______Dr. Paula M. Schiffman Date

______Dr. Jennifer A. Matos, Chair Date

California State University, Northridge

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ACKNOWLEDGEMENTS

This project would not have been possible without the help and support of the following individuals. I wish to thanks my fellow graduate students Taylor Anderson-McGill,

Christopher Bowman-Prideaux, Beck Wherle and Christina McNeal for their advice, and support. I thank Mark Harris and Chris Chabot for their help in troubleshooting my lab protocols, Nikki Osborne for letting me use her lab equipment and her assistance with

Arlequin, and Pavel Lieb for sequencing my samples. I am grateful to Jocelyn Holt and

Tarja Sagar for showing me collecting sites and aiding in my field work. Thank you Dr.

Christy Brigham for your assistance in coordinating with the National Park Service, I would not have been able to collect samples without your help. Thank you Tracy

Valentovitch for your aid in making maps and all other GIS related things. I also wish to thank the CSUN Graduate Studies and Biology Department for financial assistance.

Many thanks to Dr. Dave Gray and Dr. Paula Schiffman for their guidance, advice and editing of this text. I would like to especially thank my mentor Dr. Jennifer Matos for understanding and being patient with me. Finally, I would like to thank my family and friends for their encouragement and patience with the unexpectedly long process this research has been, I truly could not have completed this without their support and love.

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TABLE OF CONTENTS

SIGNATURE PAGE ...... ii

ACKNOWLEDGEMENTS ...... iii

ABSTRACT ...... v

INTRODUCTION ...... 1

METHODS ...... 6

RESULTS ...... 9

DISCUSSION ...... 11

LITERATURE CITED ...... 17

APPENDIX ...... 23

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ABSTRACT

GENETIC VARIATION AND GENE FLOW IN

(ASTERACEAE) AT SEVEN SITES IN SOUTHERN CALIFORNIA

By:

Lisa L. Zung

Masters of Science in Biology

The reduction of suitable habitat due to urbanization is an increasing threat to many native populations. As a result, plant populations that were once continuous have become fragmented into smaller isolated populations. These resulting small populations face reduced gene flow and increased genetic drift, decreasing genetic variability.

Populations with reduced genetic variability are more susceptible to disease and environmental change. Southern California is a region where the encroachment of urban development has taken a heavy toll on native plant populations. In particular,

Pentachaeta lyonii, a native federally listed endangered plant that was once found in many parts of Los Angeles County and southeastern Ventura County now persists in a few locations in the and Simi Hills. The objective of this study was to determine the population structure and estimate gene flow between seven sites where P. lyonii occurred. To accomplish this, DNA was extracted from whole collected at each site, and the nuclear genetic markers internal transcribed spacer 1 and 2

(ITS1 and ITS2) were amplified and sequenced for each sample. The resulting sequences were then compared using an analysis of molecular variance (AMOVA), and used to

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estimate levels of gene flow. A high level of genetic variation was found among sites

(90.82%) with very little variation found within them (9.18%). Gene flow was highly restricted (estimated Nem = 0.03) and there was a high level of genetic differentiation

(FST = 0.91 and GST = 0.89) clustering sites into what seems to be larger northern and southern groups. Because only one set of nuclear molecular markers was assessed, and within these the sequence divergence was less than 1%, additional genetic analyses should be undertaken to verify this difference before developing restoration plans that would involve moving seeds and/or pollen from one area to another. Until more is known about the population genetics of P. lyonii, conservation of its habitat should be a priority.

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INTRODUCTION

As human populations grow, urban centers are expanding and encroaching upon surrounding natural areas. Land that was once covered by large expanses of native vegetation has become a fragmented patchwork with an increasingly urban mix

(Saunders et al. 1991, Collinge 1996, Jaeger 2000, McKinney 2002, Fischer and

Lindenmayer 2007). Species that once had relatively large continuous or patchy distributions have become less abundant and more isolated (Wilcove et al. 1986,

Saunders et al. 1991, McKinney 2002, Riley et al. 2003, Lienert 2004).

In small isolated populations stochastic processes, such as genetic drift, have much greater effects (Shaffer 1987, Ellstrand and Elam 1993, Lienert 2004). Genetic drift is the random change in the allele frequencies from one generation to the next (Hendricks

2005). In large populations the chance that allele frequencies will change significantly due to drift is small, but in small populations the proportional impact of genetic drift can be large, possibly leading to the eventual fixation or loss of alleles (Wright 1949, Lacy

1987, Ellstrand and Elam 1993, Hendrick 2005). As a result, there can be increased differentiation between populations and reduced genetic variability within a population

(Ellstrand and Elam 1993, Hendrick 2005). In small populations, the probability that fixed alleles will be slightly deleterious is greater than in large populations (Lienert

2004). This is because selection is a greater factor than genetic drift in larger populations, so deleterious alleles are more likely to be selected out (Lacy 1987). However, in small populations genetic drift can be a factor that is just as strong as or stronger than selection.

Therefore, alleles that might have been eliminated by selection could become fixed even if they are somewhat deleterious (Ellstrand and Elam 1993). Fixation of these alleles can

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reduce fitness and the consequent loss of genetic variability may hinder the capacity of a population to adapt to a changing environment (Lacy 1987, Ellstrand and Elam 1993,

Young et al. 1996, Lienert 2004, Aguilar et al. 2008).

The effects of genetic drift may be counterbalanced by gene flow. Gene flow is the successful movement of alleles from one population to another through dispersal of individuals or gametes. Gene flow decreases differentiation between populations and can increase genetic variation within populations. Therefore, if there are sufficient levels of gene flow, the negative effects of genetic drift can be reduced (Lienert 2004, Aguilar et al. 2008). In plants, gene flow happens via seeds or pollen and can occur over great distances or can be restricted (Loveless and Hamrick 1984). Seed dispersal is usually more limited than pollen dispersal, so many studies use pollen as a measure of dispersal ability (Ellstrand 1992b, Ouborg et al. 1999).

In wind pollinated species, gene flow may occur over great distances and at significant rates resulting in populations with little genetic differentiation. Examples of this include fragmented populations of Acer saccharum in southeastern Canada (Young et al. 1993) and populations of the tropical tree Milicia excelsa in Cameroon (Bizoux et al.

2009). Even though gene flow is less restricted in wind-pollinated trees, small populations that have a history of fragmentation can have a high degree of differentiation such as in stands of European beech (Fagus sylvatica) in Spain (Jump and Peñuelas

2006) and junipers (Juniperus communis) in Ireland (Provan et al. 2008)

Gene flow is more complicated in species that have animal pollinators, where factors such as foraging distance, may have an effect (Ellstrand and Elam 1993, Steffan-

Dewenter and Tscharntke 1999, Lienert 2004). Pollinators with short foraging distances

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may have a restricting influence on gene flow resulting in populations with a higher degree of genetic differentiation (Loveless and Hamrick 1984). Examples of this include insect pollinated populations of Salvia pratensis, Scabiosa columbaria, and Silene latifolia in the Netherlands (Van Treuren et al. 1991, Barluenga et al. 2011), Pulsatilla vulgaris in Germany (Hensen et al. 2005), and the tropical trees Caesalpinia echinata

(Lira et al. 2003) and Swietenia humilis (Rosas et al. 2011). In contrast, the opposite is true in populations with pollinators that have long foraging distances. These populations tended to have less genetic differentiation among populations (Loveless and Hamrick

1984). For example, the tropical orchid Catasetum viridiflavum has a euglossine bee pollinator which has been shown to fly several kilometers to reach food sources (Janzen

1971, Dressler 1982). Sampled sites were found to have low among-site differentiation, indicating the sites comprised a single panmictic population (Murren 2003).

Pentachaeta lyonii (Asteraceae) is a federally listed endangered annual. It is self- incompatible and relies on generalist pollinators (Keely 1995, Fotheringham and Keeley

1998, U.S. Fish and Wildlife Service 1999, Holt 2011). Plants range in size from 6 to 48 cm tall, and typically flowers from April to June (Thomas 1997). The include both disk and ray flowers with hairy phyllaries. The seeds are also hairy and pappus bristles probably allow for some short distance dispersal. These plants are usually found on clay soils in somewhat disturbed areas between grasslands and more densely vegetated chaparral and coastal sage scrub (Fotheringham and Keeley 1998).

Pentachaeta lyonii once occurred throughout Los Angeles County and southeastern Ventura County, with documented occurrences in the Santa Monica

Mountains, San Pedro, the Palos Verde Peninsula, and Santa Catalina Island. However, as

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the regions became urbanized, many of these populations were extirpated (U.S. Fish and

Wildlife Service 1999, Brigham 2007). Today, the only remaining populations are found on private and public lands in the Santa Monica Mountains and Simi Hills (Thomas 1997,

Brigham 2007). It is unknown whether these populations were once continuous or have been historically patchy, but based on surveys, compiled by Thomas (1997), the distribution has been patchy at least since the late 1980s.

The purpose of this study was to determine the population structure and estimate gene flow between seven known sites of P. lyonii within the Santa Monica Mountains and

Simi Hills. The seven sites were from about 3 to 20 km apart (Table 1), with about 10 km separating the southernmost site near the Simi Hills (SL) and the easternmost site in the

Santa Monica Mountains (KL) (Figure 1). I hypothesized that these distances were enough to restrict gene flow between sites in the Santa Monica Mountains and sites found in and around the Simi Hills, resulting in more genetic differentiation between sites, but little differentiation among sites. Molecular markers internal transcribed spacers 1 and 2

(ITS1 and ITS2) were used to estimate the level of genetic variability within and among sites, and to evaluate levels of gene flow.

ITS1 and ITS2 are non-coding sequences found between sections of the ribosomal genome that code for the small (16s-18s), 5.8s and large (23s-28s) subunits. They are quickly evolving molecular markers that are assumed to be neutral and not directly subject to selection. Therefore, any differences found in these sequences will be from mutation and/or genetic drift (Beebee and Rowe 2004). Although there are other molecular markers more commonly used in population genetic studies, I had consistent success with these markers duplicating polymerase chain reaction (PCR) protocols in the

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lab. Unlike microsatellites, they have established universal primers that are inexpensive to acquire. Also, because ITS1 and ITS2 are nuclear sequences, they are more variable than mitochondrial (mtDNA) or chloroplastic DNA (cpDNA) (Ouborg et al. 1999).

Although not commonly used at the population level, ITS1 and ITS2 have been successfully employed to assess genetic diversity in populations of giant wild clam in the

South China Sea (Yu et al. 2000), Passiflora spp. in Brazil (Mäder et al. 2010), and Pinus rzedowskii in Mexico (Quijada et al. 1998).

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METHODS

Sampling

Entire plants were collected from seven known sites of Pentachaeta lyonii found throughout the Santa Monica Mountains and Simi Hills under a permit issued to the

National Park Service. The sites were: Tierra Rejada in the Simi Hills (SH), Sidlee (SL),

Kirsten Lee (KL), Triunfo Canyon (TC), Cornell Road (CR), Malibu Creek State Park

(MC), and Rocky Oaks (RO) (Figure 1). SH and SL were both located in Ventura County.

SH was the northernmost site (34° 15' 53"N, 118° 51' 18"W) and contained one of the largest patches of plants observed in this study. SL was located in the city of Thousand

Oaks (34° 12' 35" N, 118° 53' 56" W) and contained several small scattered patches. KL,

TC, CR, MC and RO were all located in the Santa Monica Mountains within Los Angeles

County. KL and TC were both located in the city of Westlake Village. KL (34° 7' 46" N,

118° 51' 09" N) consisted of a few small patches while TC (34° 7' 48" N, 118° 49' 16" W) contained about two large dense patches. CR and MC were both located in Agoura Hills.

CR (34° 7' 60" N, 118° 45' 04" W) had several small patches and MC (34° 06' 14" N,

118° 45' 08" W) contained a single medium sized patch. RO was the southernmost site

(34° 05' 56" N, 118° 48' 45" W) and had a single medium sized patch that was smaller and sparser than the patch found in MC. Small patches were only a few m2 in size whereas medium patches were approximately 10-15 m2 and large patches covered 25 m2 or more. All individuals collected for analysis had green leaves and either an intact or a senesced flower head. Individuals were haphazardly collected across each site and placed in labeled bags. All samples were transported to the laboratory under ice and then immediately prepared for DNA extraction.

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DNA extraction

Entire samples (stems, roots, leaves) were frozen in liquid nitrogen and ground with a mortar and pestle. While still frozen each ground plant sample was transferred to a microcentrifuge tube and kept at -80ºC. Extractions were performed either immediately or several months later using a Qiagen Dneasy Plant mini kit following the manufacturer’s protocols and then analyzed for DNA concentration using a NanoDrop

2000 spectrophtotometer.

PCR amplification and Sequencing

ITS1, ITS2, and the 5.8S ribosomal subunit were amplified as a single molecule using primers “ITS-1” and “ITS-4” (White et al., 1990). Amplifications were performed based on Noyes and Riesberg (1999), in 50µL reactions using 20-35 ng of DNA, 5.0µL of

10x PCR buffer (100mM Tris-HCL pH 8.3, 500mM KCL, 15 mM MgCl2), 1.0 µL of

25mM MgCl2, 0.75 µL each of 10mM primers, 0.5 µL of 10mM DNTP mix, and 2.0 units of Taq polymerase.

Amplification cycles were as follows: 1 denaturation cycle of 95ºC for 5 mins, 1 annealment cycle of 55ºC for 1 min and 1 elongation cycle of 72ºC for 1 min; 35 cycles of 95ºC for 1 min, 55ºC for 1 min and 72ºC for min; and a final elongation cycle of 72ºC for 7 min. All cycles were performed in a Stratagene Robocycler Gradient 96. PCR products were purified with a QIAquick PCR Purification Kit or a Sigma GenElute PCR

Clean-up Kit using manufacturer’s protocols.

Sequencing was accomplished by using primers “ITS-1” and “ITS-4” (White et al., 1990). An Applied Biosystems 3130xl Genetic Analyzer was used for sequence

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analysis, and an ABI9700 thermocycler for cycle-sequencing reactions. Sequences were read and manually aligned using BioEdit version 7.0.5.3 (Hall 1999). Associated electropherograms were analyzed for sequence misalignments. Boundaries of ITS1 and

ITS2 were defined by comparing sequenced DNA to published sequences (Noyes and Riesberg 1999).

Data Analysis

Arlequin ver. 3.51.3 (Excoffier and Lischer 2011) was used to perform an analysis of molecular variance (AMOVA) and calculate pairwise FST values to analyze the genetic variability between and within sites. DnaSP ver 5.0 (Librado and Rozas 2009) was used to analyze gene flow by calculating differentiation (GST) and migration rates

(Nem) among sites.

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RESULTS

Sequence Alignment

The entire ITS1, 5.8s subunit, and ITS2 sequence in Pentachaeta lyonii was approximately 620 base pairs (bp) long (GenBank accession number: BankIt1549223

T212 JX273133), 9 bp shorter than a congener, Pentacheata aurea (Noyes and Riesberg

1999). ITS1 was 242 bp long and ITS2 was 209 bp long flanking the 5.8s subunit (168 bp) (Table 2). Out of 163 samples that were sequenced, 126 samples (SH n=18, SL n=27,

KL n=15, TC n=15, CR n=22, MC n=17, and RO n=11) were complete enough for alignment. Sequences from all sites showed no polymorphisms in the ITS1 region, except for a few samples from CR (n=2) and MC (n=5). These samples contained ambiguous electropherograms for ITS1 so misalignments could not be resolved. In the ITS2 region at

434 bp, there was a single consistent polymorphism (G to T) in most of the samples from

SH (n=17) and SL (n=25). There was also a section at approximately 575-580 bp that could not be aligned because of ambiguous electropherograms for several SH (n=2), SL

(n=16), KL (n=4), MC (n=10), and CR (n=12) samples. Of the 126 aligned samples, 125 were used for AMOVA and gene flow analysis. One sample from CR had to be excluded because of missing data from the polymorphic site.

AMOVA and pairwise FST

For the AMOVA, two haplotypes were defined based on the polymorphism found in ITS2 (Table 3). Haplotype sequences did not contain the ITS1, 5.8s subunit and the last

45 bp of ITS2. The resulting sequence consistently had unambiguous electropherograms in all of the samples considered for evaluation (n = 125). All sites contained samples with

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haplotype 1, but SH and SL also contained samples with haplotype 2 (Table 4).

The AMOVA indicated that most of the genetic variation was found among sites

(90.82%) with very little variation within sites (9.18%) (Table 5). There was also evidence of significant population structure (FST = 0.91, P < 0.001). The 5 southerly sites

(CR, KL, MC, RO and TC) were not significantly different from each other (pairwise FST

= 0.00, P > 0.05). SH and SL, the 2 most northern sites, were also not significantly different from each other (pairwise Fst = 0.00, P > 0.05) but they were significantly different from the southerly sites (Table 6).

Gene Flow analysis

Frequencies of haplotypes 1 and 2 were used to estimate gene flow rates and measure differentiation among sites. Analysis of 125 samples from the seven sites show that they were highly differentiated (GST = 0.89), with very little gene flow occurring among them (Nem = 0.03). These results were congruent with the FST value from the

AMOVA.

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DISCUSSION

Sequence alignment

The polymorphism found at 434 bp within the amplified ITS1, 5.8s and ITS2 sequences is a substitution from G to T or T to G and was used to define haplotypes for the AMOVA and gene flow analyses. This substitution was a transversion which is a nucleotide substitution between nucleotide class types. Transversions are not as common as transitions, a substitution within the same class type (Gojobori et. al 1982, Wakeley

1996, Yang and Yoder 1998). In this case, it was a change from a pyrimidine to a purine or a purine to a pyrimidine. It is unknown which direction the substitution occurred, but according to a study conducted by Gojobori et al. (1982), G to T transversions occur at a higher frequency of than most other transversions.

Based on haplotype frequencies, it seems that the G↔T substitution was a nearly fixed point mutation with 92% of SL samples and 94% of SH samples bearing the T variation (haplotype 2), while 100% of CR, KL, MC, RO, and TC had the G variation

(haplotype 1). In addition, the high FST (0.91) also indicates the near fixation of the point mutation within the sites (Avise 2004). This could possibly be due to genetic drift because of the neutral nature of ITS2, but the prior genetic composition of the sites under evaluation is unknown. Therefore, the evolutionary process, whether it was genetic drift, founder’s effect or population bottleneck, cannot be determined.

Genetic variation and gene flow

The AMOVA indicated that there were low amounts of variation within sites where P. lyonii occurred, but a high amount among sites, indicating a clear differentiation

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between sites. The sites seemed to be grouped geographically with southern sites (CR,

KL, MC, RO and TC) not significantly different from each other but significantly different from the northern sites (SH and SL). There was probably enough gene flow occurring among sites within northern and southern groups to explain the low amount of genetic diversity that was observed.

The high genetic differentiation and reduced gene flow among sites of P. lyonii may reflect life history characteristics, such as an annual life cycle, small population sizes, limited pollen and seed movement and patchy distributions. These characteristics have been shown to increase population differentiation (Loveless and Hamrick 1984, Van

Treuren et al. 1991, Hensen et al. 2005, Barluenga et al. 2011). Annual life cycles and small population sizes make populations more susceptible to genetic drift while limited pollen and seed movement, and a patchy distribution reduce gene flow and increase isolation.

The reduction of gene flow due to limited pollen movement may be explained by the pollinators of P. lyonii. Holt (2011) observed that, three of the most common visitors to P. lyonii were small solitary bees (Ashmeadiella californica subsp. californica,

Exomalopsis sp., and Ceratina sp.). Solitary bees have been shown to fly a maximum of

600 m from nesting sites to food patches (Gathmann and Tscharntke 2002), which is much less than the distance between the two closest sites in this study (Table 1).

Therefore, it is very unlikely that pollinators are traveling from one site to another. In addition, P. lyonii pollinators are generalists (Keeley 1995, Fotheringham and Keeley

1998, U.S. Fish and Wildlife Service 1999, Holt 2011), so even if they were able to fly from site to site, they may not visit enough P. lyonii flowers at the next site to

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successfully transfer a significant amount of pollen (Kunin 1993, Jules and Priya (2003).

The high amount of differentiation among populations could also be due to limited seed dispersal (Loveless and Hamrick 1984). It is unknown precisely how P. lyonii seeds are dispersed, but the presence of hairs and a short pappus on the seed suggest that dispersal by animal vectors is possible. Seeds can disperse extremely long distances by adhesion alone (Sorensen 1986, Mouissie et al. 2005). However, the pappus of P. lyonii has been observed to break off easily when touched (Fotheringham and

Keeley 1998), suggesting that dispersal distances are most likely limited. Gravity and movement by harvester ants and granivorous rodents are other possible dispersal mechanisms (U.S. Fish and Wildlife Service 1999). However, seeds dispersed by these means would be unlikely to travel long distances. Brown et al. (1979) cited that harvester ants can forage from sites up to 40 m away, but dispersal distances of this magnitude would not be sufficient to explain the genetic differences observed among P. lyonii sites.

Moreover, Ohkawara et al. (1996) showed that ants moved Erythronium japonica seeds less than 1 m away from possible mother plants and Kalisz et al. (1999) determined that radiolabeled Trillium grandiflorum seeds were moved a maximum of only 10 m away.

Similarly, experiments with seed retention on European wood mouse (Apodemus flovicollis) coats showed that seeds with hairs could travel up to 17 m (Kininiemi and

Telenius 1998). In addition, Hulme (2002) cited several studies that indicated that mean dispersal distances of small seeds by granivorous rodents were relatively short with 7.8-

9.5 m for Purshia tridentata and 9.6 m for Symplocarpus renifolius. Although dispersal distances like these are short, there is a possibility that they are sufficient enough to establish P. lyonii plants at intermediate sites (either undiscovered or now extirpated) in

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between the 7 sites that were sampled for this study. Such intermediate sites could potentially act like “stepping stones for gene flow” and may explain the lack of differentiation between sites within the northern and southern group.

Conservation and management implications

Before a new conservation and/or restoration plan for P. lyonii is put in place, a deeper understanding of the genetic relationships among all P. lyonii sites is needed.

Analysis with plants from other sites, such as the rediscovered Santa Catalina Island population, last recorded in 1931 (Holt 2011), would paint a more complete picture of population structure across the entire range of P. lyonii. Even though the results of this study show a clear differentiation between northern and southern areas, more analysis is needed before this geographic distinction can be considered definitive. Keeley and Swift

(1995) cited an unpublished study of P. lyonii genetic diversity which purportedly found a lack of variation among seven sites. However, measurements of different population parameters can vary depending on the particular molecular markers used (Bossart 1998,

Ouborg et al. 1999). For example, McCauley (1994) found that allozyme data indicated less differentiation among populations of Silene alba (FST = 0.13) while cpDNA estimated more (FST = 0.67). Similarly, Gao et al. (2002) showed that for populations of wild rice (Oryza rufipogon) microsatellite data had more genetic differentiation and diversity than allozyme data. Therefore, in order to accurately assess the genetic structure of P. lyonii sites, analysis with additional molecular markers, such as microsatellites and/or cpDNA should be performed. Microsatellites would provide greater resolution of genetic diversity within sites and cpDNA could give estimates of seed dispersal because

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of the uni-parental inheritance of the chloroplastic genome (Cain et al. 2000, Wang and

Smith 2002, Agarwal et al. 2008).

Once a clearer picture of the genetic make up of P. lyonii sites has been resolved, natural resource managers should try to preserve levels of gene flow estimated from the genetic data. One strategy might involve genetic augmentation by introducing pollen or seeds from other sites to replenish genetic diversity within target sites. In plants where inbreeding depression (a reduction in fitness due to mating with related individuals) is apparent, a single migrant into the population has been shown to increase fitness

(Newman and Tallmon 2001). However, a large number of migrants might result in outbreeding depression (Fisher and Matthies 1997). Outbreeding depression is a decline of fitness in the hybrids from different populations of the same species (Ellstrand 1992a,

Edmands 2007) thereby reducing local adaptations and possibly increasing the risk of local extinction (Newman and Tallmon 2001).

Pentachaeta lyonii populations do not appear to suffer from inbreeding depression

(Holt 2011). Therefore, managers may only need to avoid outbreeding depression. If other molecular markers confirm the findings of this study, then seeds sourced from a site

(or sites) supporting a large number of individuals would probably be the best choice for restoring nearby smaller and possibly extinct sites. For example, Triunfo Canyon, which supported the largest number of P. lyonii individuals in the Santa Monica Mountains observed in this study, might be used to supplement sites nearby such as Kirsten Lee or

Rocky Oaks. Again it is important to keep in mind that this strategy should only be implemented once a better picture of the genetic composition of these sites is resolved.

Maintenance of the existing sites of P. lyonii is of utmost importance. If the

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habitat in which this species is known to occur becomes converted for urban uses, then efforts to restore population genetic variability will be futile. Many previously known populations of P. lyonii have been extirpated by residential and commercial development projects and wildfire control (U.S. Fish and Wildlife Service 1999, Brigham 2007).

However, prioritizing sites to conserve may be difficult due to the sporadic occurrences of P. lyonii at remaining sites. Patches of this species have been discovered in former sites after not being seen for several years such as at Stunt Ranch in 2008 and the rediscovery of a Santa Catalina Island population (Holt 2011). Another issue of concern should be site maintenance, since P. lyonii is a poor competitor with other forbs and non-native grasses

(Fotheringham and Keeley 1998, Moroney et al. 2011). Long-term monitoring and some way to remove competing vegetation will be necessary if P. lyonii is to persist and/or be restored to Southern California.

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Aguilar, R., M. Quesada, L. Ashworth, Y. Herrerias-Diego and J. Lobo. 2008. Genetic consequences of habitat fragmentation in plant populations: susceptible signals in plant traits and methodological approaches. Molecular Ecology 17: 5177-5188.

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APPENDIX

Table 1. The distance (km) between sites in this study.

SH SL TC CR KL MC RO

SH -- SL 6.85 -- TC 15.17 10.85 -- CR 17.46 15.40 6.49 -- KL 15.26 9.82 2.97 9.45 -- MC 20.25 17.40 7.12 3.26 9.76 -- RO 18.80 14.26 3.63 6.83 4.89 5.68 --

Figure 1. Collection sites of Pentachaeta lyonii.

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Table 2. Amplified ITS1, 5.8s subunit and ITS2 sequence. ITS1 is in bold, 5.8s subunit is between *, and ITS2 is underlined.

1 TCGAAGCAGA ACGAAGCAGA ACGACCCGTG AACATGTTAT AACAACAATG 51 TCAGGATGGG TTGAGCATTA GTTCGATTCT CTTGACACCC CGCCGATGAG 101 CGTCCTAGAT GGTATCTTGG CCGTTTATTC GACGTAACAA AACCCGGCAC 151 GGGATGTGCC AAGGAAACTT AAATTGAAGA ATTGCCTGTC TCATGGTGAC 201 CCGTTCGCGG TGTGCTCATG TGGCGTGGCT TCTTTGTAAT CA*CAAACGAC 251 TCTCGGCAAC GGATATCTCG GCTCACGCAT CGATGAAGAA CGTAGCAAAA 301 TGCGATACTT GGTGTGAATT GCAGAATCCC GTGAACCATC GAGTTTTTGA 351 ACGCAAGTTG CGCCCGAAGC CATTTGGCCG AGGGCACGTC TGCCTGGGCG 401 TCACAC*ATCG CGTCGCTCCC ACCAACCCTT CCTGTAGGAT GGTTGGTCGG 451 GGGCGGAGAC TGGTCTCCCG TTTTTCACCG AGCGGTTGGC CGAAATAAGA 501 GCCCCTCTTG ACGGGCGCAC GGCTAGTGGT GGTTGACCAA ACCCAGAAAT 551 CAGTTGTGTG TCTCTTCAAA AGGGTACATC TTAAAAGACC CAATGCGTTG 601 TCATGTAACG ACGCTCGACC

Table 3. Haplotypes 1 and 2. Polymorphism is in bold.

1 h1 ATCGCGTCGC TCCCACCAAC CCTTCCTGTA GGATGGTTGG TCGGGGGCGG h2 ...... T...... 51 h1 AGACTGGTCT CCCGTTTTTC ACCGAGCGGT TGGCCGAAAT AAGAGCCCCT h2 ...... 101 h1 CTTGACGGGC GCACGGCTAG TGGTGGTTGA CCAAACCCAG AAATCAGTTG h2 ...... 151 h1 TGTGTCTCTT CAAAAGG h2 ......

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Table 4. Haplotype frequencies in sequences used for analysis populations.

Population n Haplotype 1 Haplotype 2

Simi Hills SH 18 0.06 0.94 Sidlee SL 27 0.07 0.93 Triunfo Canyon TC 15 1.00 0.00 Cornell Road CR 21 1.00 0.00 Kirsten Lee KL 15 1.00 0.00 Malibu Creek MC 17 1.00 0.00 Rocky Oaks RO 11 1.00 0.00

Table 5. Analysis of molecular variance (AMOVA) using the haplotypes h1 and h2 defined from the ITS2 sequence of seven populations of Penatchaeta lyonii. Degrees of freedom (df), sum of squares (SS), estimates of covariance components (CC), percent of variation (%).

Source of variation df SS CC % P

Among sites 6 24.98 0.24 90.82 < 0.05

Within sites 118 2.80 0.02 9.18 < 0.05

Table 6. Pairwise Fst values between the seven sampled populations of Pentachaeta lyonii.

SH SL TC CR KL MC RO

SH -- SL -0.05 -- TC 0.94* 0.90* -- CR 0.91* 0.95* 0.00 -- KL 0.90* 0.94* 0.00 0.00 -- MC 0.91* 0.94* 0.00 0.00 0.00 -- RO 0.89* 0.93* 0.00 0.00 0.00 0.00 --

* P < 0.05

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