RAPID EVOLUTION IN A CROP-WEED COMPLEX ( SPP.)

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

By

Lesley Geills Campbell, M. S.

* * * * *

The Ohio State University 2007

Dissertation Committee: Approved by: Professor Allison Snow, Adviser

Professor Lisle Gibbs ______Professor Maria Miriti Adviser Evolution, Ecology, and Organismal Biology Graduate Program

ABSTRACT

The development and adoption of transgenic crops with novel traits has raised awareness of the potential for weed populations to evolve increased weediness after hybridization with cultivated relatives. I explored the evolutionary and ecological consequences of gene flow between crop (Raphanus sativus) and its weedy relative (wild radish, R. raphanistrum).

Hybridization may generate the genetic and phenotypic variation necessary for an evolutionary response by weeds. First, I imposed artificial selection on wild and hybrid lineages for four generations for early flowering a potentially advantageous trait for weeds. Hybrid lineages evolved more rapidly under selection for early flowering and rapidly recovered a wild-type phenology and fertility. Second, I established replicated wild and hybrid populations in agricultural landscape and measured their evolutionary response to natural conditions after three generations. Natural conditions favoured larger in both wild and hybrid populations. However, because an advantageous trait, large size, had been transferred to hybrid populations, hybridization resulted in significantly larger hybrid than wild weeds and accelerated weed evolution.

Further, I asked whether environmental context affected the success of hybrid relative to wild radish. Using a response surface competition experiment, I examined the consequences of competition on life history and lifetime fecundity of hybrid and wild

ii plants. Hybrid plants were less competitive than wild plants. With increasingly competitive conditions, differences in hybrid and wild life history and fecundity were reduced. Therefore, competition may promote the introgression of crop alleles into weed populations. In a second experiment, I examined the consequences of geographic location on fecundity of hybrid and wild plants by conducting two common garden experiments in disparate locations within the geographic range of wild radish (Michigan, California). In

Michigan, hybrids had lower fecundity than wild plants, but, in California, hybrids had significantly greater fecundity and survival than wild plants, suggesting hybrids may displace wild relatives in some environments.

In summary, I present new evidence for a role of hybridization in the evolution of agricultural weeds by measuring the rate of hybrid evolution relative to wild ancestors and exploring the environmental contexts that facilitate crop trait introgression into weed populations.

iii

DEDICATION

For the patience of my mothers – Gladys, Phoebe, Claudette, Ellie, Pauline, Barb, Ellen, and Jay – and the eagerness of my Dad.

iv ACKNOWLEDGMENTS

My heartfelt thanks goes to Allison Snow for her encouragement, enthusiasm, and guidance during the past five years. I am also extremely fortunate to have worked with

Julie Ketner, Maria Miriti, Caroline Ridley, and Patty Sweeney as collaborators.

Committee members Lisle Gibbs, Libby Marschall, and Maria Miriti contributed immensely by reading proposals, critiquing papers, and, most importantly, by providing support and food for thought. The members of the Snow lab, Mike Reagon, Su Su, Patty

Sweeney, Yifru Teklu, Yan Jin, Jill Johnson, Kristin Mercer, Sarena Selbo, and Lawrence

Spencer, as well as the graduate associates of EEOB had a profound impact on my work through important discussions in forming many of the ideas I present and constructive criticisms of the work in early and late stages. I also very much appreciate the careful eye of Don Campbell who read and commented on each chapter.

My sincere thanks also goes to the undergraduate researchers who worked so diligently with me on these projects: Karen Alofs, Anna Babayan, Marie Burleson, Sarah

Clark, Nora Curiel, Alex DeCamp, Holly Eisel, Erin Hill, Scott Gifford, Julie Ketner,

Nicholas Marsh, Nana Masuda, Kate Mollohan, Sarah Pfingsten, Retika Rajbhandari,

Soja Sekharan, Missy Schneider, Danielle Smith, Nicole Smith, Karl Toth, Kaushik

Vedam, Jenny Waterbury, David Yang. The Bonnett, Brubacher, Dotski, Gregory, Ginop,

Hartman, Jarman, Jurek, Phelps, Reimann, Romanik, Schreier, Stempky, and Sterzik

v families generously shared their farmland, time, and local knowledge. The University of

Michigan Biological Station community (especially Knute Nadelhoffer, Kari Slavik, Lisa

Readmond, Richard Spray, Tony Sutterly, Bob Vandekopple, Chris Vogel, and Ken

Willoughby) and Cathy Drake, Rene Madsen, and Joan Leonard of the Ohio State

University played fundamental roles in the success of these projects. Stauf’s coffeehouse,

Soul Sista’s and the Huntsville Public Library provided comfortable and welcoming writing spaces.

The work presented here was financially supported by the US Department of

Agriculture, a National Science Foundation Doctoral Dissertation Improvement Grant,

Janice Carson Beatley Herbarium Fund, University of Michigan Biological Station, The

Nature Conservancy, The Ohio State University Mary S. Muellhaupt Presidential fellowship, Sigma Xi, and the Henry Gleason Fellowship.

Finally, a special thanks goes to my family – Tom, Phoebe, and Dad. Without your emotional and, at times, physical support, I could not have realized this goal. Thank you for the freedom to pursue my own path - such a rare luxury in this world.

Thank you, thank you, thank you.

vi VITA

April 7, 1975 Born – Hamilton, Ontario, Canada 1998 B.S. Biology, University of Guelph, Canada 1998 – 2001 Graduate Teaching and Research Associate, University of Guelph, Canada 2001 M.S. Botany, University of Guelph, Canada 2001 – 2005 Graduate Teaching and Research Associate, The Ohio State University, USA 2006 – present Mary S. Muellhaupt Presidential Fellow, The Ohio State University, USA August 11, 2006 Married (Thomas A. Waite) – Columbus, Ohio, USA

PUBLICATIONS Research Publications

1. Husband, B. C., and L. G. Campbell. 2004. Population genetic and demographic responses to novel environments: implications for ex situ plant conservation. In Ex Situ Plant Conservation Symposium: Strategies for Survival. Eds E Guerrant Jr, K. Havens, M. Maunder. Island Press. Pp. 231 - 266. 2. Snow, A. A., and L. G. Campbell. 2005. Can feral become weeds? In Crop Ferality and Volunteerism. Ed. J. Gressel. CRC Press. Pp. 193-208. 3. Campbell, L. G., and B. C. Husband. 2005. Impact of clonal growth on effective population size in Hymenoxys herbacea (Asteraceae). Heredity 94 (5): 526-532. 4. Campbell, L. G., A. A. Snow, and C. E. Ridley. 2006. Weed evolution after crop gene introgression: greater survival and fecundity of hybrids in a new environment. Ecology Letters 11 (9): 1198-1209. 5. Waite, T. A., and L.G. Campbell. 2006. Controlling the false discovery rate in molecular ecology: an alternative to Bonferroni. Ecoscience 13(4): 439-442. 6. Campbell, L. G., and A. A. Snow. 2006. Competition alters life history and increases the relative fecundity of crop-wild radish hybrids (Raphanus spp.). New Phytologist doi: 10.1111/j.1469-8137.2006.01941.x

FIELDS OF STUDY

Major Field: Evolution, Ecology, and Organismal Biology

vii TABLE OF CONTENTS

Page ABSTRACT………………………………………………………………………………ii DEDICATION……………………………………………………………………………iv ACKNOWLEDGEMENTS……………………………………………………………….v VITA……………………………………………………………………………………..vii LIST OF TABLES………………………………………………………………….…..…x LIST OF FIGURES……………………………………………………………………...xv

Chapters:

1. Introduction.……………………………………………………….……………..1 1.1 Ecological implications of hybridization – GEOs as one applied example…2 1.2 Raphanus as a model for the analysis of the consequences of gene flow…...3 1.3 Emerging experimental methods………………………...………………….6 1.4 Objectives……...……………………………………………………………7

2. Rapid evolution of phenology increases the fertility of crop-wild hybrids..…..9 2.1 Abstract..…………………………………………………………………….9 2.2 Introduction………………………………………………………………...10 2.3 Materials and Methods..………….………………………………………...13 2.4 Results………………………………………………………………..…….17 2.5 Discussion..…………………………………………………………..…….18 2.6 Acknowledgements………………………………………………………...22 2.7 Tables………………………………………………………………………24 2.8 Figures……………………………………………………………………...25

3. When divergent life histories hybridize: insights into weed evolution………29 3.1 Abstract…………………………………………………………………….29 3.2 Introduction………………………………………………………………...30 3.3 Materials and Methods...…………………………………………………...33 3.4 Results……………………………………………………………………...42 3.5 Discussion…………………………………………………………………..47 3.6 Acknowledgements………………………………………………………....55 3.7 Tables……………………………………………………………………….57 3.8 Figures……………………………………………………………….……..63

viii 4. Competition alters life history and increases the relative fecundity of crop- wild hybrids (Raphanus spp.)……..…………………………………………...71 4.1 Abstract……………………………………………………………………71 4.2 Introduction.………………………………………………..…………..….72 4.3 Methods ……………………………………………………………………76 4.4 Results……………………………………………………………………...86 4.5 Discussion …………………………………………………………………90 4.6 Acknowledgements………………………………………………………...94 4.7 Tables………………………………………………………………………95 4.8 Figures……………………………………………………………………106

5. Weed evolution after crop gene introgression: greater survival and fecundity of hybrids in a new environment …...…………………………….………….112 5.1 Abstract…………………………………………………………………..112 5.2 Introduction………………………………………………………………113 5.3 Methods…………………………………………………………………..115 5.4 Results……………………………………………………………….…...124 5.5 Discussion…………………………………………………………….….127 5.6 Acknowledgements………...…………………………………………….132 5.7 Tables……………………...……………………………………………..133 5.8 Figures……………………………………………………………………145

6. Feral radishes (Raphanus sativus; ) as weeds?………………..152 6.1 Abstract…………………………………………………………………...152 6.2 Introduction……………………………………………………………….153 6.3 Materials and Methods……………………………………………………156 6.4 Results…………………………………………………………………….166 6.5 Discussion………………………………………………………………...169 6.6 Acknowledgements……………………………………………………….175 6.7 Tables……………………………………………………………………..177 6.8 Figures……………………………………………………………………183

7. Prospectus……………………………………………………………………...186 7.1 Synthesis………………………………………………………………….186 7.2 Implications….……………………………………………………………188 7.3 Future work……………………….……………………...……………….189 7.4 Conclusions….....…………………………………………………………191

BIBLIOGRAPHY………………………………………………………………………192

ix LIST OF TABLES

Table

2.1 Estimated rates of evolution of plants experiencing selection for early flowering (Early) in hybridizing (Hybrid) and nonhybridizing (Wild) weed lineages. See methods for selection protocol.…………………………………...24

3.1 Summary of wild and hybrid lineages included in the common garden. Ancestors represent the first generation wild and hybrid plants that initiated both the natural selection (Natural) and artificial selection (Random, Early flowering, Large size) lineages………………………………..57

3.2 Effects of hybridization (Wild, Hybrid), natural and artificial selection (Early flowering, Large size) and random mating (Random) on two life history traits and three fitness components in wild and crop-wild hybrid lineages. Replicate lineages were represented by N individuals in a common garden. Superscripts denote data also found in either A) Chapter 5; or B) Chapter 2……………………………………………………………..…58

3.3 Summary statistics for the fit of the path analytic models for each biotype……..61

3.4 Estimated rates of evolution for age and size at reproduction in G4 wild and hybrid populations relative to a randomly mating population………………62

4.1 Maximum likelihood estimates of the competitive coefficients and model estimates of wild and hybrid biotypes as measured by the number of seeds produced per plant. In parentheses, we present the 95% confidence intervals for each parameter estimate……………………………………………95

4.2 Pre-competition seedling biomass of wild and advanced-generation crop- wild hybrid plants. Superscripts indicate significant differences among populations within a biotype. Population averages are presented with number of samples (N) and estimates of standard error (SE)…………………...96

4.3 Percentage of pollen grains that are fertile in wild and advanced- generation crop-wild hybrid plants. Superscripts indicate significant

x differences among populations within a biotype. Population averages are presented with number of samples (N) and estimates of standard error (SE)………………………………………………………………………………97

4.4 A comparison of life-history traits and lifetime fecundity of wild and hybrid populations grown in a competition experiment in Michigan. We performed a repeated measures ANOVA for each trait for two biotypes (Within-subjects effect). Three populations of wild plants were paired to compete with three populations of hybrid plants (Pop. Pair). Plants were exposed to variation in plant density (Density = 1, 2, 4, or 8 plants per pot) and hybrid frequency (Hybrid freq. = 100% hybrid plants per pot or 50% hybrid plants per pot). F statistics are presented; to indicate significant differences: ns represents p > 0.10, + represents p < 0.10, * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001…………………………….98

4.5 Summary statistics of several key life-history traits and fitness components for F3 wild (W) and hybrid (H) plants. Plants were grown in a common garden at three plant densities and three biotype frequencies (intrawild–, intrahybrid– and inter–biotype) after experiencing natural conditions as three populations (Pop.) per biotype in Michigan for two years. Each site was represented by N plants per treatment………………….…99

4.6 Summary statistics for the fit of the path analytic models for each biotype. The root mean square error of approximation (RMSEA) together with its 95% confidence interval and P-value is a measure of the fit between the observed covariance matrix and the one predicted by the model (where a good fit is indicated by RMSEA values close to zero; range = 0 to 1). The fit of the tested model is also measured by a comparison of its Akaike Information Criterion (AIC) value is to the AIC of the saturated model; if they are similar, as measured by the 95% CI of the Model AIC, then the proposed model is a good fit to the data. For the wild and hybrid models being compared, ‘saturated’ refers to a model with all paths allowable, which has no degrees of freedom and perfect fit; ‘model’ is the partially constrained path analytical model actually being tested………………………..101

4.7 Indirect effects of plant density (Density) and focal plant age (Age) and size (Size) at reproduction on focal plant age and size at reproduction, and lifetime fecundity calculated for wild and F3 hybrid plants using the path analytic models in Figure 4.2…………………………………………………...102

xi 4.8 Summary of 12 competition studies of fecundity of crop-wild hybrids relative to their wild parent. Studies were included only if they concerned hybrids between a cultivated and wild relative and if they measured hybrid seed production under intra- and inter-biotype competition environments. Gen. = Hybrid generation studied. With/Without = comparisons were made between competitive environments with either no competition or some competition, RP = replacement series, A= additive series [density varied but no frequency treatments], Hexagonal = Hexagonal plot design for a neighborhood competition experiment, RS = response surface where density and frequency of biotypes were varied independently of each other. Traits measured: S = Number of seeds, F = Number of flowers or flower heads, B = Above-ground biomass. No data = The comparison was not made in the study, Similar = fitness of hybrid was similar to wild plant, Reduced = hybrid fitness was lower than wild fitness, Greater = hybrid fitness was higher than wild fitness, Lower = Hybrid relative fitness was lower under inter-biotype competition conditions than under intra-biotype competition conditions, Same = Hybrid relative fitness was unaffected by type of competition environment, Higher = Hybrid relative fitness was higher under inter-biotype competition conditions than under intra-biotype competition conditions…………………………………………...103

5.1 Environmental differences between the two common garden experiments……133

5.2 Summary statistics of fitness components for G1 and G4 wild and hybrid plants and their competitor oats. Plants were grown in two common gardens (Michigan, California) before (G1) and after (G4) experiencing natural conditions as four populations (Pop.) per biotype in Michigan for three years. Each site was represented by N plants in the common garden; n/a indicates not applicable……………………………………………………..134

5.3 Analysis of Biotype × Environment interactions (B × E) in wild and hybridizing radish. We tested for differences in fitness components between two common gardens which included two biotypes and four populations (Pop) per biotype (Bio) and the interaction of garden by biotype to test for B x E…………………………………..……………………137

5.4 A comparison of fitness components for wild and hybrid G4 populations in common gardens in Michigan and California. We performed linear mixed model ANOVAs for four components of fitness for two biotypes (wild and hybrid), and four populations within each biotype. The plants were equally

xii distributed among 21 blocks within the Michigan garden and 10 blocks within the California garden……………………………………………………138

5.5 Summary of 24 studies of relative fecundity of crop-wild hybrids compared to that of the wild parent. Studies were included if they measured the number of seeds produced by both hybrids and wild parents. No data = hybrids were not grown in more than one location or under multiple environmental treatments such as disease pressure, competition or application, Yes = relative hybrid fitness was dependent on location or environmental treatment, No = relative hybrid fitness was independent of location or environmental treatment, Potentially = the data presented suggest that hybrid relative fitness differed among locations or environmental treatment but was not statistically tested……………………….140

6.1 Economically important traits and average age at flowering for ten cultivated radish varieties (Raphanus sativus). Plants were grown in a complete random design common garden with five plants per variety represented in each of ten blocks. Average values represent the estimated marginal means based on an analysis of variance accounting for radish type, radish variety nested within radish type, and block. Statistically significant differences among cultivars for days to first flower are represented by superscript letters beside the average values. Sample sizes for each variety range from 44 to 50 plants and total N = 478………………...177

6.2 Phenotype and lifetime fecundity of feral (C1), introgressed (C4, C5) and randomly mated (Control) lineages in a common garden in Michigan, USA. Plants were equally distributed among 10 blocks within the garden and means were calculated as averages of block averages…………………….178

6.3 A comparison of phenotypic and lifetime fecundity of randomly mated, feral, and introgressed populations in a common garden in Michigan, USA. We performed multivariate ANOVA for each trait including the four populations (Pop). The common garden was arranged in a complete randomized design with 10 Blocks. F statistics are presented; to indicate significant differences: ns represents p > 0.05, * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001. The randomly mated populations were not included in the pollen fertility analysis. Average values are reported in Table 6.2……………………………………………….179

xiii 6.4 A comparison of age at flowering and lifetime seed production of crop populations that experienced selection for advanced flowering and no selection controls grown in a common garden environment in Michigan. We performed a multivariate ANOVA for each trait for the two Selection Treatments. Three replicate lineages of randomly mated plants were compared with three replicate lineages of selected plants (Replicate). The common garden was arranged in a complete randomized design with ten Blocks………………………………………………………………………..…181

6.5 A comparison of age at first flower for ten cultivated varieties of Raphanus sativus that were grown in a common garden in Columbus, Ohio. We performed a nested ANOVA that considered the economically important trait of the cultivar (Trait Group, described in Table 1) and Variety nested within trait group. The common garden was arranged in a complete randomized block design with ten blocks……..…………………….182

xiv

LIST OF FIGURES

Figure

2.1 Artificial selection experimental design. Each F2 plant was randomly assigned to one of two selection treatments and one of three replicates within each selection group. Each lineage in each generation was initially composed of 130 to 160 plants and ten percent of each cohort was selected to produce the following generation………………………………………..……25

2.2 Age at flowering for selected and randomly mating control lineages of wild and crop-wild hybrid radishes after three generations of selection for earlier flowering …………………………………………………………………26

2.3 Pollen fertility and fruit set of early flowering and randomly mated wild and F5 hybrid lineages …………………...………………………………………27

2.4 Phenotypic variation among wild-type (W Control) and early flowering hybrid (H Early) lineages before (F2) and after 1 (F3) or 2 (F4) generations of selection. Ellipses delimit the 95% confidence limits of the phenotype of each lineage ………………………………………………………………….28

3.1 Solved path analytic models of the effects of age and size at reproduction on wild and hybrid fitness for the linear selection coefficient analysis following natural selection. Wild and hybrid populations had experienced selection for three generations in natural conditions. A. Solved path diagram for wild radish () plants, N = 156; B. Solved path diagram for advanced-generation hybrid radish (R. raphanistrum x R. sativus), N = 205. Dashed lines indicate negative effects (ρ) and the value beside the arrow and the width of the arrow indicates the magnitude of the effects. Black lines indicate the effect was significantly greater or less than zero (P≤0.05). Grey lines indicate the the effect was not significantly different from zero (P > 0.05). Variation due to error is not included for simplicity; C. Graphical comparison of the magnitude of effects in the solved wild and hybrid path diagrams. Error bars represent the 95% confidence interval of the effects……………………….63

xv

3.2 Estimates of the selection coefficients (β*), indirect selection, and the selection differentials (or total selection, s*) on age and size at reproduction in wild and advanced-generation hybrid plants. A. Estimates of direct selection; B. Estimates of indirect selection; C. Estimates of total selection. Error bars represent the 95% confidence intervals of the mean………65

3.3 Response to selection on age at reproduction and size at reproduction of four wild (black circles) and four advanced-generation hybrid (grey squares) populations after three generations of natural selection. Error bars represent 95% CI of the population means. Evidence of a significant response to selection is the deviation of each population average from the expected average phenotype of a randomly mating population (solid line in corresponding color) and its 95% confidence interval (shaded areas). Sample sizes as in Table B1……………………………………………………..67

3.4 Fitness consequences of heritable variation for advanced reproduction (Early) and large size at reproduction (Large) relative to randomly mating lineages (Control) and naturally selected lineages (Natural) of wild (black bars) and hybrid plants (gray bars). Sample sizes as in Table B2. Error bars represent the 95% CI of the mean………………………………………….69

4.1 Schematic diagram of the experiment. The first-generation (F1) was created by cross-pollinating wild plants (W) with either wild or cultivated (C) radish pollen to create wild and hybrid (H) biotypes. Six isolated field populations of wild biotypes (W1 – W3) or hybrid biotypes (H1 – H3) were maintained for three years; small squares represent populations of the two biotypes. In 2004, a response surface competition experiment with plant density (1, 2, 4 plants per biotype) and biotype frequency treatments (inter-biotype, intra-biotypeWild, or intra-biotypeHybrid) was composed of F3 plants from each population. In the competition experiment, dark grey squares represent competition treatments and light grey squares represent no competition treatments. The numbers within the matrix positions describing the replacement series competition experiment represent the number of plants per growth container…………………………………………106

4.2 Direct and indirect effects of plant density and biotype frequency on age and size at flowering and lifetime fecundity of F3 (a) wild and (b) hybrid plants. In the solved path diagram for maximum likelihood linear analysis of hybrid relative performance, dashed lines indicate negative coefficients and the width of the arrow indicates the strength of the effect (ρ). xvi

Significant effects are presented as black lines. Non-significant effects are presented as grey lines. Figure (c) compares the strength of the correlation (ρ) between models (a) and (b). Error bars represent the 95% CI of the mean and non-overlapping CI indicate a significant difference in the strength of the relationship. This analysis included only inter-biotype competition conditions…………………………………………………………107

4.3 Comparison of life-history traits and lifetime fecundity of wild and hybrid plants grown under intra-biotype (Hybrid frequency = 0% or 100%) and inter-biotype competition conditions (Hybrid frequency = 50%) at four plant densities. Bars represent trait means; error bars represent the SE of the mean. Since populations did not differ significantly for most traits, estimates of relative fecundity are based on averages of 36 pots per biotype where population is pooled (n ≈ 36 individuals per biotype, biotype frequency and plant density)………………………………………….110

5.1 Schematic diagram of the experiment. The first-generation (G1) was created by cross-pollinating wild plants (W) with either wild or cultivated (C) radish pollen to create wild and hybrid (H) biotypes. Eight isolated field populations of wild biotypes (W1 – W4) or hybrid biotypes (H1 – H4) were maintained for four years; small squares represent populations of the two biotypes. In 2005, common gardens in Michigan and California were composed of G4 plants from each population. The Michigan common garden also included plants representing G1 founders of the eight populations……………………………………………………………………..145

5.2 Annual population growth rate (r) of four wild and four hybrid populations grown in isolated agricultural fields in Michigan over three one-year intervals (r = ln(Nt) – ln(Nt-l), where Nt is population size in year t and Nt-1 is population size in the preceding year t-1). Error bars represent 95% CI of the mean (N = 4)……………………………………………………147

5.3 Parallel evolution of hybrid populations (H1-H4) over four years (2002 – 2005). (A) Average frequency of white-flowered plants (N = 1340 – 4277). Reference line at 0.75 is the null Hardy-Weinberg expectation (after the G1 generation) of white flower color frequencies. (B) Average proportion of fertile pollen (sample sizes as in Table 5.2). From 2002 to 2004, pollen was collected from plants from the artificial field populations. In 2005, pollen was collected from the common garden

xvii

experiments in Michigan and California. See Table 5.2 for fertility of wild pollen for G1 and G4 plants…………………………………………………….148

5.4 Relative survival and fecundity of wild and hybrid plants grown in two common gardens including G1 (= F1) hybrids and fourth-generation (G4) hybrids from the Michigan common garden, and G4 hybrids from the California common garden. Hybrid trait values were standardized such that wild plants have an average fitness value of unity (reference line). Bars show means of mean relative success within experimental blocks; error bars represent ± 1 SE. To indicate significant differences between wild and hybrid fitness, + represents P = 0.052, * represents P < 0.05, ** represents P < 0.01, *** represents P < 0.001, based on ANOVAs (Table 1). Analysis for survival: NWild = 4, NHybrid = 4, Michigan - Mann-Whitney U statistic = 4.0, P = 0.34; California - Mann-Whitney U statistic = 0.000, P = 0.029)………………………………………………………………………150

6.1 Population dynamics of field populations of introgressed and feral Raphanus sativus. A. Estimates of annual population size (lines) and flower color allele frequencies (pie charts). Black lines represent feral populations and gray lines represent introgressed populations (R. sativus x R. raphanistrum). Frequency of white-petal color alleles are represented by white areas; frequency of yellow-petal color alleles are represented by the gray areas and the numeric value. B. Annual date of first flowering. Black bars represent feral populations; gray bars represent introgressed populations……………………………………………………………………..183

6.2 Selection for early flowering (Early) altered A) flowering phenology and B) lifetime fecundity compared to randomly mating populations (Control). Bars represent means; error bars represent the 95% CI of the mean; for each Replicate lineage, N ≈ 50…………………….…………………………..185

xviii

CHAPTER 1

INTRODUCTION

“A trickle of genes so slight as to be without any practical taxonomic result might still be many times more important than mutations in keeping up the basic variation of the parental species… In such a variable environment species that (through introgression) are able to achieve a great increase in genic variability should be at a selective advantage.”

With the above reasoning, Edgar Anderson (1949, pp. 62-3) provoked evolutionary biologists and inspired the development of a sub-discipline of evolutionary biology, evolution via hybridization. Since then, evolutionary ecologists have asked whether inter-specific gene flow via hybridization and subsequent introgression is a biologically important mechanism for the acquisition of genetic adaptations by natural plant populations. Although evolutionary botanists recognized the importance of rare events of introgression in the evolution of many plant groups early in the development of the field (e.g., Lotsy 1916; Anderson 1949; Stebbins 1959; Grant 1981), only recently has it been recognized that introgression can occur frequently and may produce viable, even highly-adapted, offspring (e.g., Arnold 1997, 2006; Rieseberg et al. 1999).

1

1.1 Ecological implications of hybridization – GEOs as one applied example

The introduction, development, and adoption of genetically engineered organisms

(GEOs) and, specifically, transgenic crops with novel traits has raised awareness of the

potential for hybridization to transfer a transgene construct from the modified crop into

wild relatives of that crop (e.g., Ellstrand and Hoffman 1990; Davis et al. 1999; Snow et

al. 1999, 2003; Desplanque et al. 2002; Halfhill et al. 2005, Watrud et al. 2004).

Subsequently, a selective advantage may be imparted to the recipients of the transgene

(Davis et al. 1999; Snow et al. 2003; Desplanque et al. 2002), by altering their biology

and influencing their ecological relationship with non-hybridized wild genotypes and

other members of their ecological community (e.g., negative effects on insects: Anderson

et al. 2004 but see Dively et al. 2004; altered competitive ability: Halfhill et al. 2005).

Among many possibilities, this process could 1) facilitate the evolution of weedier wild

relatives, 2) alter plant-environment interactions, or 3) threaten biodiversity by causing

the extinction of one or both parental species.

The probability that any trait, transgenic or not, could be transmitted from crops

to their wild relatives will depend on their co-occurrence, their synchronous flowering,

the successful transfer of pollen, and the ability of crop pollen to successfully fertilize

ovules that become viable embryos. Also, first-generation hybrid seeds must be able to

germinate and exhibit the trait in the resulting plant. For such a trait to be maintained

over the long term, crop-wild hybrid individuals need to be successful pollen donors,

seed producers, or both. If other hybrid individuals have been locally produced or when

the trait carrier is self-compatible, the trait may be transferred to the F2 generation.

However, it is more likely that the trait would be introgressed into the recipient species as

2

a result of backcrossing, given the relative frequency of hybrid individuals within wild populations.

Although crop traits are often considered maladaptive for weeds, repeated cases of conventional crop alleles persisting in weeds have been documented using both neutral molecular markers and visually assessed phenotypic markers (e.g. canola: Hansen et al.

2001; sunflower: Whitton et al. 1997; radish: Snow et al. 2001). The introgression of single-gene transgenic traits, such as herbicide tolerance, insect resistance and disease resistance, may lead to even greater fitness advantages in hybridizing populations than conventional crop traits (Davis et al. 1999; Desplanque et al. 2002; Snow et al. 2003).

Unfortunately, it is currently difficult to predict the circumstances under which crop traits will readily introgress into populations of wild relatives. Long-term studies documenting the fitness consequences of gene flow for early- and late-generation crop-wild hybrid plants, the demographic consequences of gene flow for population growth rates, and relative advantage of crop traits in wild populations are pieces of information needed for risk assessment of crop-to-wild gene flow (Pilson and Prendeville 2004).

1.2 Raphanus as a model for the analysis of the consequences of gene flow

Crops share common ancestors with certain wild plants (van Raamsdonk and van der Maesen, 1996; Ellstrand 2003). Although relatively recent domestication may have imposed different selective environments, crops and wild relatives retain a number of common characteristics, often including morphology, environmental tolerance and breeding system. Often these related cultivated and wild taxa still grow in the same geographic location where they originated (e.g., maize: Fukunaga et al. 2005; Baltazar et

3

al. 2005; wheat: Weissmann et al. 2005; cucurbits: Arriaga et al. 2006 ; beets:

Desplanque et al. 1999). Their hybridization may give rise to crop-weed complexes, causing the introgression of crop characters into weed populations and vice versa (van

Raamsdonk and van der Maesen, 1996; Muira and Terauchi 2005). This process may have occurred over an extended period of time and, in the case of crop breeding, has been exploited to increase the success of conventional crop breeding programs (e.g., herbicide- resistant sunflower: Al-Khatib et al. 1998; insect-resistant cabbage: Ellis et al. 2000; cold-tolerant sorghum: Dweikat 2005; virus resistance in celery: D’Antonio et al. 2001; review: Rao et al. 2003).

Cultivated radish (Raphanus sativus) is an ancient crop that appears to have multiple, independent origins in Eurasia and Eastern Asia from several wild species including Raphanus raphanistrum, R. maritimus, R. landra (Crisp 1995, Yamagishi &

Terachi 2003). The wild relatives are members of the tribe Brassicaceae, family

Cruciferae and all have 2n = 18 chromosomes (Lewis-Jones et al. 1982). In North

America, radish has a number of inter-compatible wild and cultivated relatives either within the same or closely related genera, including wild radish (Raphanus raphanistrum), Brassica rapa, B. oleracea, B. nigra, Sinapis arvensis and S. alba. The extent of successful hybridization among these species varies widely (e.g., Lui et al.

2003, Scheffler & Dale 1994); radish most successfully hybridizes spontaneously with R. raphanistrum. Inter-specific hybridization most easily produces R. raphanistrum x R. sativus hybrid offspring (e.g., Snow et al. 2001) relative to other potential inter-specific hybridization events that could occur in North America (e.g., Lelivelt et al. 1993; Rieger et al. 2001). When R. sativus is the pollen donor, the chances of R. sativus x R.

4

raphanistrum hybridization occurring will depend on the relative amounts of crop and

conspecific pollen: both distance between crop and wild radish and the frequency of wild

and cultivated radish affect the rate of hybridization (Klinger & Ellstrand 1994, Lee &

Snow 1998).

Wild radish (Raphanus raphanistrum, or Jointed Charlock) is considered to be

among the worst weeds worldwide (Holm et al. 1997). It occurs in agricultural fields of

small grains and forage crops, in waste areas, and sheltered beaches in many temperate

areas of the world. Originally from Europe, this plant has colonized North America,

South America, Australia, Africa and eastern Asia (Mekenian & Willemsen 1975; Holm

et al. 1997; Huh & Ohnishi 2002). Several weedy characters may contribute to the

success of wild radish as an agricultural weed. First, it can disperse its seeds widely by

mimicking the shape and size of small grains making it difficult to exclude from seed

grain (Holm et al. 1997). Second, large numbers of seeds may remain dormant for many

years in infested fields (Mekenian & Willemsen 1975). Third, it is a strong competitor

with other crop plants (Blackshaw et al. 2005; Norsworthy 2003; Weaver & Ivany 1998).

Fourth, it has demonstrated its ability to rapidly respond to selection by evolving

herbicide resistance in several populations (Monjardino et al. 2003).

In North America, wild radish is found in the western and eastern coasts and the

northern mid-west states (Schroeder 1989; Kercher & Conner 1996; Panetsos & Baker

1967). Both wild and cultivated radish were introduced to California in the 19th century

(Bolander 1870; Brewer et al. 1876; Panetsos and Baker 1967). Hybridization among the two taxa appears to have resulted in the extinction of R. raphanistrum from the state

(Hegde et al. 2006). In California, populations of “wild radish” appear to only include

5

hybrid individuals (Hegde et al. 2006). Panetsos & Baker (1967) concluded that hybridization between Raphanus sativus and R. raphanistrum “appears to have been a major factor in converting the erstwhile crop plant, R. sativus, into a highly successful weed.” Klinger & Ellstrand (1994) demonstrated that these hybridizing wild radish populations have the potential to become more fecund after persistent gene flow from their crop parent.

1.3 Emerging experimental methods

Does hybridization stimulate plant, and specifically weed, evolution? To begin to answer this question and to explore the ecological and evolutionary consequences of hybridisation between wild and crop radish, we evaluated crop-wild radish hybrids grown in replicated populations, across five generations, under several ecological scenarios.

Although laboratory and glasshouse tests of inter-specific compatibility and estimates of the fecundity of early generation hybrids can provide initial data for risk assessment, these experimental approaches cannot always be extrapolated to provide a realistic assessment of the situation in the field, under agricultural conditions, over longer time horizons.

Selection experiments – Evolution by natural and artificial selection has been repeatedly documented in natural and laboratory populations respectively (Kingsolver et al. 2001; Bone and Farres 2001; Conner 2003; Reznick and Ghalambor 2005).

Laboratory or artificial selection experiments allow us to evaluate cause and effect relationships because of the planned experimental design. On the other hand, field observations provide us an opportunity to measure the rate and magnitude of selection in

6

nature. However, few studies are genuine natural selection experiments that are designed and executed under natural conditions. These selection experiments allow us to more directly evaluate the factors that cause evolution by natural selection and enable us to test evolutionary theory (e.g., life-history theory) under conditions which will expose the trade-offs associated with a trait. Here, we use both artificial and natural selection studies in complementary experiments to begin to understand the evolution potential of hybrids and the phenotypic and fitness consequences of hybridization.

Experimental hybridization – Although selection experiments have increased our understanding of the process of phenotypic evolution in natural populations, these experiments have been limited by the phenotypic diversity found within populations.

Those traits most important to adaptation and speciation are often fixed within populations, depending on the genetic correlations among the traits (Gustafson 1986,

Falconer and Mackay 1989). To increase phenotypic diversity within populations, and therefore, potentially increase our understanding of selection Lexer et al. (2003) suggested the use of experimental hybridization. The use of experimental hybridization has also increased the range of values for particular traits within segregating populations of hybrids thus increasing the sensitivity of assays for evolutionary potential (Lexer et al.

2003).

1.4 Objectives

The primary purpose of this research is to re-examine the general hypothesis of

Ellstrand & Schierenbeck (2000, 2006) that hybridization stimulates the evolution of invasive weeds and the more specific hypothesis of Panetsos & Baker (1967) that

7

hybridization between Raphanus raphanistrum and R. sativus has led to the evolution of a invasive weedy hybrid derivative. My research explored six questions to expand the knowledge of the evolutionary and ecological consequences of hybridization gene flow from cultivated plants to wild populations.

1. Does hybridization increase the phenotypic variation found within weed

populations? (Chapters 2, 3)

2. Does hybridization enhance the ability of weed populations to evolve in response

to selection? (Chapters 2, 3)

3. Does hybridization enhance the competitive ability of weed populations?

(Chapters 4-6)

4. Does crop-to-wild gene flow enhance the fecundity of weed populations?

(Chapters 3-6)

5. Does hybridization alter the population dynamics of weed populations? (Chapters

5, 6)

6. Are open-pollinated crop plants likely to become feral weed populations?

(Chapter 6)

Several chapters of this dissertation have been published, submitted for publication, or are being prepared for publication and have multiple authors, including Julie M.

Ketner (Chapter 2), Caroline E. Ridley (Chapter 5), Allison A. Snow (Chapters 2-6), and

Patricia M. Sweeney (Chapters 2-3). Appropriate acknowledgment of their contributions are located within footnotes of each chapter.

8

CHAPTER 2

RAPID EVOLUTION OF PHENOLOGY INCREASES THE FERTILITY OF

CROP-WILD HYBRIDS 1

2.1 Abstract

Hybridization between crops and their wild relatives may accelerate the evolution of

undesirable “superweeds”. However, introgression will be liminted unless hybrid

offspring can regain high fertility and evolve an adaptive phenotype. Using hybrids of

wild radish (Raphanus raphanistrum) and cultivated radish (R. sativus), we measured

response to selection for a wild-type trait, early flowering. We performed three

generations of selection for earlier flowering in wild and hybrid lineages, and compared

selected versus randomly-mated, control lineages. Hybrid control lineages flower ~8 days

later and have ~10% lower pollen fertility and ~7% lower fruit set (proportion of flowers

setting fruit) than wild plants. Wild and hybrid lineages responded to selection for earlier

flowering and hybrid lineages rapidly evolved a flowering phenology similar to their

weedy parents. Simultaneously, two correlated fertility traits evolved. Pollen fertility and

fruit set, increased in early flowering hybrid lineages and was similar to pollen fertility

and fruit set of wild lineages. Our findings show that early-generation crop-wild hybrids

1 L. G. Campbell, A. A. Snow, P. M. Sweeney, and J. M. Ketner. Rapid, ecologically relevant evolution increases the fertility of crop-wild hybrids. In prep. 9

can rapidly recover a wild-type phenotype and high fertility via strong selection, even in the absence of back-crossing.

2.2 Introduction

One potential risk associated with the use of genetically modified crops is the transfer of crop genes via hybridization into populations of wild relatives (Colwell et al.

1985; Ellstrand & Hoffman 1990; Snow & Moran Palma 1997; Ellstrand et al. 1999;

Stewart et al. 2003; Snow et al. 2005). Crop genes that enhance yield or confer resistance to , disesase, or insect pests could potentially increase the survival and fecundity of non-cultivated species (Snow & Moran Palma 1997; Snow et al. 2003). This may make existing weeds more difficult to control or enhance weediness in species that are not currently problematic weeds (Gressel 1999, although see Bergelson 1994).

Resulting economic and environmental damage could potentially equal or exceed economic and ecological benefits achieved through genetic improvement of the crop

(Wolfenbarger & Phifer 2000; Smyth et al. 2002; Hails 2000; Pilston & Prendeville

2004). Consequently, it is important to determine if weed evolution via crop-wild hybridization will have important ecological, evolutionary, and/or economic consequences.

Although many crops and related weed taxa co-occur and hybrids are frequently reported (reviewed in Ellstrand et al. 1999; Jarvis & Hodgkin 1999; Hails & Morley,

2005), crop-to-wild gene flow may not necessarily result in a successful and persistent transfer of traits between taxa. Introgression, the incorporation of genes from one species

10

into another, is, in part, governed by internal genetic interactions determining reproductive compatibility or barriers to gene flow (Arnold 1997; Piálek & Barton 1997).

Hybridization may be maladaptive for weedy relatives of crops when it results in reduced reproductive potential or reduced fertility (Snow et al. 2001; Yamashita et al. 2005; Al-

Ahmad et al. 2006). However, when selection on fertility or correlated traits is strong, hybrids may rapidly recover fertility and become fully compatible with wild parental taxa

(Brown & Brown, 1996; Ungerer et al. 1998; Campbell et al. 2006). Therefore, it is important to determine to what degree reproductive incompatibilities limit the successful introgression of crop alleles into wild populations.

Introgression is also limited by external ecological factors affecting the strength of natural selection on hybrids (Arnold 1997; Wu & Campbell 2006; Whitney et al.

2006). Introgression of crop alleles in wild populations is expected to occur rapidly when crop traits are selectively advantageous (Snow et al. 2003, Miura & Terauchi 2005) or when crop traits are linked to selectively advantageous wild traits (Rosenthal et al. 2005).

In addition, selectively neutral, unlinked traits may also rapidly introgress, limited only by rates of gene flow (Reichman et al. 2006). Selectively disadvantageous traits will likely introgress at a slower rate, if at all (Haygood et al. 2004). Hybrids located in “wild” environments may experience directional selection for the wild phenotype and yet still preserve certain crop-derived traits. Therefore, it is important to demonstrate that genes from one parental taxon can persist in populations of another, even under selective environments that may eliminate many, if not most, crop-derived traits.

We studied the evolution of hybrid populations in Raphanus spp. (wild and cultivated radish) under directional selection for one aspect of the wild phenotype,

11

flowering phenology. Wild radish (Raphanus raphanistrum) is an economically important, panmictic, annual weed that is a model system in plant evolutionary ecology

(e.g., Stanton and Young 1994; Conner et al. 1996a, b, 1997; Agrawal et al. 2004; Walsh et al. 2004; Irwin and Strauss 2005). R. raphanistrum flowers early in the growing season whereas the cultivated radish (Raphanus sativus) has experienced strong selection for delayed flowering to favor the production of an economically valuable, enlarged hypocotyls. The F1 hybrid of these taxa flowers later than its wild parent (Snow et al.,

2001.). A fertile, invasive hybrid of these two species has evolved in California and hybrid populations have replaced R. raphanistrum (Hegde et al. 2006) This hybrid, while distinct from both parental species, has a flowering phenology more similar to its wild parent than cultivated parent. Although R. sativus and R. raphanistrum are considered inter-fertile, early generation hybrids have reduced pollen fertility, commonly producing approximately 50–60% aborted pollen grains (Snow et al. 2001; Campbell et al. 2006).

Reduced pollen fertility in Raphanus hybrids is due to heterozygosity for a reciprocal translocation that affects chromosome pairing during meiosis (Panetsos and Baker 1967).

However, Campbell et al. (2006) found that experimental populations of hybrid radish recovered relatively high pollen fertility within a few generations.

Early flowering is selectively advantageous for both wild and hybrid radish because plants can complete their life cycle before being killed by frost, drought, or crop harvest, even when germination is induced later in the growing season (Snow et al.

2001). Therefore, rapid evolution of early flowering in early generation hybrids will increase the probability of crop allele persistence. However, this rapid phenological

12

evolution may have correlated phenotypic and fitness consequences for traits that are closely linked to loci controlling flowering phenology.

What is the rate of evolution of crop-wild hybrids compared to their wild relative under selection for early flowering? Does rapid life history evolution for either of the two traits also facilitate rapid fertility evolution? Does selection for a wild-type phenotype eliminate all crop-derived traits? The research presented here addresses these questions using an artificial selection experiment where we imposed selection for early flowering in both wild and hybrid lineages over four generations. We then measured the phenotypes of wild and crop-wild hybrid plants in a common garden to determine the magnitude of response to selection and the phenotypic and fitness consequences for correlated and uncorrelated traits.

2.3 Materials and Methods

2.3.1 Study Organism

Wild radish, Raphanus raphanistrum, and its cultivated relative, Raphanus sativus, are well suited for experimental gene flow and artificial selection experiments because they are easily grown in large quantities, reproduce quickly, are interfertile, can be pollinated without cross-contamination (self-incompatible), and possess simply inherited, rapidly-assessed, species-specific markers (Snow et al. 2001; Warwick and

Francis 2005, Campbell et al. 2006). Further, their growth forms and life histories are divergent. Raphanus raphanistrum grows a rosette with a thin, fibrous taproot, bolts within a few weeks after germination and initiates flowering soon after. On the other

13

hand, crop breeding has emphasized delayed bolting in Raphanus sativus (Curtis, 2003;

Snow and Campbell, 2005).

2.3.2 Seed Sources and Base Generation

In 2001, we collected seeds from several hundred plants in a natural R.

raphanistrum population in Pellston, MI, USA (homozygous for the recessive yellow

petal color allele as in Campbell et al. 2006). In a greenhouse in Columbus, OH, 100

wild plants were hand-pollinated with either wild pollen to create the F1 wild biotype or

crop pollen to create the F1 hybrid biotype. We harvested crop pollen from 100 “Red

Silk” R. sativus plants (homozygous for the white petal color allele) (Harris-Moran Seed

Co., Modesto, USA). Maternal parents were randomly assigned pollen donors from

concurrently flowering plants. As these plants are self-incompatible, we used physical

separation and unpollinated flowers to ensure that crosses were uncontaminated. Below,

we refer to these radish biotypes as wild or hybrid based on hybridization in this first

generation.

We started the selection experiment in the F2 generation. F2 seeds were produced

from 100 F1 wild x F1 wild, and 100 F1 hybrid x F1 hybrid crosses in the same growth room and under similar environmental conditions as the parental generation. We randomly assigned F2 plants to one of two selection treatments (early flowering and no

selection control) and further to one of three replicate lineages for each selection

treatment, for a total of 12 lineages (Figure 2.1). The three replicate lineages per selection

treatment and the control selection treatments allowed us to exclude drift as the

14

evolutionary cause of the change in the characters. In each lineage in the F2 generation, there were 140 plants.

2.3.3 Selection Environment

During the experiment, plants were grown in Cone-tainers (Steuwe and Sons,

Corvallis, OR), filled with standard potting soil, so we could simultaneously raise several

th thousand plants. The planting dates for the F2, F3, and F4 generations were February 13

– 18th, 2003, November 10th – 17th, 2003, and August 17th – 20th, 2004 respectively. We

randomly repositioned the unmeasured plants within the greenhouse every two weeks in

order to reduce the effects of any variation in light, watering, and other environmental

conditions of the greenhouse.

2.3.4 Measurements and Artificial Selection

For the F2, F3, and F4 generations, each lineage was initiated with at least 225

seeds, from 100, 16, and 13 parental plants respectively. Two weeks after planting,

ungerminated seeds were discarded and we reduced the size of every lineage to that of

the smallest lineage, maintaining equally sized lineages. In the F2, F3, and F4 generations,

each lineage included 160, 130, and 140 plants, respectively. Each generation, we

recorded the dates of germination and anthesis, and size at anthesis of each plant. Age at

flowering was calculated as the difference, in days, between germination and anthesis.

The length of the longest leaf at first flower served as a measure of plant size at

flowering. We imposed truncation selection on each of the 12 lineages each generation

(F2 – F4). We selected the 10% earliest flowering individuals for early lineages and

15

randomly selected 10% of the randomly mating lineages to produce the following

generation. Selected plants were cross-pollinated within a lineage in a complete diallel

design. We collected a pollen sample from each selected plant to assess pollen fertility.

After staining (Alexander 1969), pollen fertility was assessed by counting the proportion

of aborted grains in samples of at least 100 grains per plant.

2.3.5 Common Garden

We measured phenotypic traits of the F5 generation in a common garden at the University of Michigan Biological Station in Pellston, MI (42°35’N, 84°42’W). Each wild lineage was represented by 42 plants and each hybrid lineage was represented by 84 plants.

Plants were arranged in a randomized, complete block design. We recorded the dates of germination and anthesis, and size at anthesis for each plant, as described above. We also collected pollen from 40 plants per lineage to estimate pollen fertility as described above.

Finally, we measured fruit set as the proportion of flowers that set fruit (Data on plant fecundity are included in Chapter 3). Three plants did not flower before the first hard frost (September 16th – 20th) and were excluded from the experiment. A detailed

description of the common garden methods can be found in Chapters 3 and 5.

2.3.6 Analysis

To determine if lineages responded to selection for earlier flowering and whether

biotypes differed in their response to selection, we compared their phenotypes using an

ANOVA for each trait (age at flowering, pollen fertility, fruit set). We compared the

values for each biotype, selection treatment, replicate within selection treatment, and

16

block. If the ANOVA revealed significant differences among lineages for a particular

trait, a series of planned nonorthogonal pairwise comparisons was made.

2.4 Results

Early flowering hybrid lineages evolved more rapidly than early flowering wild lineages.

By the F5 generation, hybrid early lineages flowered eleven days earlier than hybrid

control lineages whereas wild early lineages flowered four days earlier than wild control

lineages (figure 2.2; Biotype × Selection treatment interaction: F1,3.8= 13.56, p=0.023).

Hybrid control lineages flowered an average of 7.8 days after wild control lineages.

Hybrid early flowering lineages flowered 1.1 days after early flowering wild lineages.

The flowering phenology of hybrid early flowering lineages overlapped the flowering

phenology of wild control lineages (95% CI – Hybrid Early: 27.9 – 31.9 days; Wild

Control: 31.3 – 35.3 days). In general, hybrid lineages flowered later than wild lineages

(Biotype: F1,3.8= 25.34, p=0.009) and early flowering lineages flowered earlier than

control lineages (Selection: F1,4.2= 21.15, p=0.009). Age at reproduction did not differ

among replicates within treatments (p=0.12) but did differ among blocks (F20,11.8= 5.05, p=0.009). Of all the interaction effects, we only found significant variation among replicates within selection by biotype treatments (F4,80.4= 6.41, p<0.001). Therefore, early

flowering hybrid lineages rapidly evolved a wild-type flowering phenology.

Selection for early flowering in hybrid lineages coincided with a recovery of

pollen fertility and fruit set (figure 2.3a,b; Selection: F1,2.6 = 21.45, p=0.027). Early

flowering hybrid lineages regained pollen fertility (79.7%), similar to randomly mating

wild lineages (p=0.323). In contrast, by the F5 generation, hybrid control lineages

17

produce significantly fewer fertile pollen grains (69.9%) than randomly mating wild

lineages (82.7%; Biotype: F1,2.1= 26.52, p=0.032). Similarly, hybrid lineages set fewer

fruit per flower (44.4%) than wild lineages (50.7%; Biotype: F1,3.3 = 21.79, p=0.015), but

two replicates (replicates 2, 3) regained high fruit set when selection favored earlier

flowering hybrids (50.3%; Biotype × Selection × Replicate interaction: F2,35.3 = 7.98,

p=0.001). In replicate one, fruit set did not differ significantly between hybrid selected

and unselected treatments. Therefore, as hybrids evolved a wild-type flowering

phenology, they also rapidly regained wild-like fertility.

Initially, wild and hybrid lineages possessed significantly different life history

traits (figure 2.4). F2 hybrids flowered later and were larger at flowering than wild plants.

After just one generation of selection for early flowering, hybrid lineages evolved almost identical life histories to wild control, with almost identical flowering phenologies and size at flowering. Early flowering hybrid had become virtually indistinguishable from wild randomly mating lineages as a result of strong directional selection. We have demonstrated that cryptic hybrids can easily and rapidly evolve in the absence of back- crossing to the wild relative (or repeated bouts of gene flow).

2.5 Discussion

Early-generation crop-wild hybrids are often poorly adapted to the habitat of their wild parent because of the disruption of coadapted gene complexes (Orr 1995; Turelli and Orr

2000; Marr et al. 2002), the creation of maladapted genotypes (Demuth and Wade 2005), or reduction in fertility through a variety of mechanisms. However, some segregating genotypes may possess the trait combinations to cope with, if not thrive in, these

18

conditions. Our results demonstrate that, within 1-3 generations of strong selection for a wild-type flowering phenology, all three hybrid lineages had evolved a wild-type phenotype. Hybrids evolved more rapidly wild plants, as expected, and, when hybrid lineages were selected to flower earlier, hybrid pollen fertility and fruit set increased significantly. This suggested that the reciprocal translocation, which causes low fertility in early-generation hybrids, was no longer present after selection for an apparently linked trait, early flowering. We suggest that, although backcrossing could facilitate the rapid evolution of a wild-type phenotype in hybrid lineages, selection on segregating hybrid phenotypes may be an equally important mechanism for the evolution of cryptic hybrids in natural populations.

2.5.1 Rapid, Adaptive Evolution

Rates of evolution resulting from artificial selection experiments can be used as a frame of reference for how fast plants can potentially evolve in the field (Bone and Farres

2001). We imposed relatively strong selection pressures on wild and hybrid lineages and produced rapid evolution of focal and correlated characters (Table 2.1). Age at flowering in early flowering hybrid lineages evolved 1.5 times more rapidly than the flowering phenology of early flowering wild lineages in our study followed by evolution of a correlated trait, leaf length at flowering, in the same lineages (Haldane 1949, Gingerich

1983). These rates of evolution are comparable to rates of evolution of herbicide resistance and pathogen resistance in Lolium rigidum, Bromus tectorum, and Linum marginale (139 – 606 darwins; Bone and Farres 2001; Powles et al. 1998; Mallory-Smith

19

et al. 1999; Burdon and Thompson 1995). As expected, in our study hybridization resulted in lineages that most rapidly responded to selection pressure.

The evolutionary potential to evolve earlier flowering may be fundamental for hybrid success and, ultimately, for rates of introgression. Weeds, including R. raphanistrum, often exhibit rapid growth and early flowering, whereas the flowering phenology of crops, such as radish, is often delayed when the economically important trait is vegetative (Doebley 1992; Doebley et al. 1997, Chapter 3). Therefore, hybrid fecundity, relative to wilds, may be limited by an intermediate flowering phenology and may benefit from rapid evolution toward a parental phenotype, depending on the host environment (Snow et al. 2001; Campbell and Snow 2006). If crop-wild hybrids can evolve quickly from maladaptive intermediates to adaptive phenotypes (which may or may not resemble one of the two parents), population sizes may grow more rapidly than anticipated and weed problems may quickly become difficult to control. In a previous experiment, we found that although increasing competitive conditions delay flowering in

R. raphanistrum and advanced-generation hybrids, those plants that flowered earliest, wild or hybrid, were most fecund (Campbell & Snow 2006). Therefore, rapid evolution of early flowering in early generation hybrids could increase the probability of crop allele persistence.

2.5.2 Correlated fertility evolution

Commonly, selection imposed on one trait results in correlated changes in other traits, revealing genetic correlations among traits. In our selection experiment, several traits evolved in response to direct selection on flowering phenology in both wild and hybrid

20

lineages. We detected a life-history trade-off between age and size at reproduction in both hybrid and, to a lesser degree, wild lineages. We also detected an increase in pollen fertility and fruit set in hybrid lineages. These results suggest that at least part of the rapid recovery of pollen fertility documented in experimental hybrid radish populations (e.g.,

Campbell et al. 2006) may be associated with selection for earlier flowering.

Correlated evolution in response to selection may have a significant impact on the introgression of crop-specific traits after selection for a weedy phenotype. Upon selecting for a wild-type flowering phenology, hybrid radishes also apparently possessed the wild- type reciprocal translocation, patterns of fruit set, and plant size. Were any apparent crop- derived traits retained? Cultivated and wild radish populations differ in flower petal color, a simply inherited trait. Raphanus sativus plants often have white petals while R. raphanistrum populations are generally characterized by yellow petals (Panetsos and

Baker 1967; Kercher and Conner 1996; Snow et al. 2001). Presence of yellow carotenoid pigment is a recessive Mendelian trait, with white dominant over yellow (Stanton 1987).

Experimental hybrid populations have shown variation in the introgression of the white petal alleles (e.g., Panetsos and Baker 1967; Kercher and Conner 1996; Snow et al. 2001;

Campbell et al. 2006) and multiple hypotheses about the mechanisms governing the allele’s frequency have been proposed (e.g., Lee and Snow 1998; Irwin et al. 2003). In this experiment, wild lineages were composed of 100% yellow-flowered plants for the entire experiment. According to Hardy-Weinberg expectations, F2 hybrid lineages should have consisted of 25% yellow flowered plants and 75% white flowered plants and the actual frequencies did not differ from this. By the F5 generation, there were 62-79?% and 68-70% white flowered plants in the early flowering and control lineages. Therefore,

21

although linkage disequilibrium had an apparently strong effect on some crop-derived traits, it did not eliminate all crop-derived traits. However, given that QTL’s of domestication traits are not randomly or evenly distributed throughout the genome, but rather occur as linked clusters in certain regions of chromosomes (Cai & Morishima,

2002; Paterson, 2002; Ross-Ibarra 2005), we expect that the joint processes of crop-wild hybridization and strong selection could quickly eliminate most domestication traits if linked to a selectively deleterious trait.

2.5.3 The relative importance of back-crossing versus selection in introgression

When hybrids that closely resemble one parental taxa, either in genotype or phenotype, are discovered in natural populations, workers immediately assume that back-crossing was an important mechanism in the process of hybrid evolution. We have demonstrated that this need not be the case. Hybrids may rapidly evolve a wild-type phenotype in the absence of back-crossing. This may be especially true if selection for wild-type phenotypes also favors wild-type fertility. As proposed by Chapman & Burke

(2006) and Seehausen (2004), selection is an under appreciated mechanism in the evolution of viable and persistent populations of crop-wild hybrids. Therefore, asymetrical introgression is not necessarily due to uneven gene flow but rather could be solely due to selection.

2.6 Acknowledgements

We thank J. Leonard, UMBS staff, T. Waite, and many student researchers for logistical assistance. The United States Department of Agriculture (Grant #2002-03715),

22

University of Michigan Biological Station, National Science Foundation DDIG (DEB-

0508615), OSU Presidential Fellowship, and The Nature Conservancy (Michigan) financially supported this research. Thanks to H.L. Gibbs and K. Mercer for comments.

23

2.7 Tables

Lineage Trait Darwins (x 10-3)§ Haldanes†

Hybrid Early Age at flowering 263.58 0.47

Hybrid Early Size at flowering 258.91 0.09

Wild Early Age at flowering 172.03 0.25

Wild Early Size at flowering 82.51 0.10

Hybrid Early Pollen fertility 43.77 0.04

Table 2.1. Estimated rates of evolution of plants experiencing selection for early flowering (Early) in hybridizing (Hybrid) and nonhybridizing (Wild) weed lineages. See methods for selection protocol.

§ darwins = (ln(x2) – ln(x1))/t (Haldane, 1949) where x1 is the mean trait value for control lineages and x2 is the mean trait value of selected lineages, t is the time in millions of years (4 years)

† haldanes = ((x2/sp)-(x1/sp))/g (Gingerich 1983) where sp is the pooled standard deviation of the populations’ trait values, g is the number of generations since the separation of the populations.

24

2.8 Figures

F2 F3 F4 F5 Replicate 1 Early Replicate 2 flowering

Wild (F2) Replicate 3

Replicate 1

Greenhouse Field garden Randomly Wild ♂ Replicate 2 mating × Replicate 3 Wild ♀ F2 F3 F4 F5 Replicate 1 × Early

Replicate 2 flowering Crop ♂ Replicate 3

Hybrid (F2) Replicate 1 Greenhouse Field garden Replicate 2 Randomly mating Replicate 3

Figure 2.1. Design of Artificial Selection Experiment. Each F2 plant was randomly assigned to one of two selection treatments and one of three replicates within each selection group. Each lineage in each generation was initially composed of 130 to 160 plants and ten percent of each cohort was selected to produce the following generation.

25

50

F5 Wild

45 F5 Hybrid

ays)

d 40

ering ( 35 ow

l f

e at 30 g A

25 Control Early

Selection treatment

Figure 2.2 Age at flowering for selected and randomly mating control lineages of wild and crop-wild hybrid radishes after three generations of selection for earlier flowering.

26

1.0 0.6 Control

Early 0.5

0.8

0.4 ers that set fruit 0.5 0.3

0.2

0.3

0.1 Proportion of fertile pollen grains Proportion of flow

0.0 0.0 Wild Hybrid Wild Hybrid

Biotype

Figure 2.3 Pollen fertility and fruit set of early flowering and control wild and F5 hybrid lineages.

27

450 F2 H Early F H Early 400 3 F4 H Early

350 F2 W Control F3 W Control

mm) 300 F4 W Control

h ( 250 ngt

e 200 l 150 Leaf 100 50 0 0 20 40 60 80 100 120 Age at flowering (days)

Figure 2.4 Phenotypic variation among wild-type (W Control) and early flowering

hybrid (H Early) lineages before (F2) and after 1 (F3) or 2 (F4) generations of selection.

Ellipses delimit the 95% confidence limits of the phenotype of each lineage.

28

CHAPTER 3

WHEN DIVERGENT LIFE HISTORIES HYBRIDIZE: INSIGHTS INTO

ADAPTIVE LIFE-HISTORY TRAITS IN AN ANNUAL WEED2

3.1 Abstract

Colonizing weed populations face novel selective environments, which may drive

rapid shifts in life history. These shifts may be amplified when colonists are hybrids of

species with divergent life histories. Selection on such phenotypically diverse hybrids

may create highly fecund weeds. To measure the strength of selection on age and size at

maturity in weed populations, we created F1 hybrids of wild radish, an early flowering,

small-stemmed weed, and its late-flowering, large-stemmed crop relative (Raphanus

spp.). We then established replicate wild and hybrid populations in an agricultural

landscape. After three generations of natural selection, hybrid plants still initiated

reproduction later and at a larger size than wild plants. Selection favored larger plants in

both wild and hybrid populations. Advanced reproduction was advantageous in hybrid

populations, while delayed reproduction was advantageous in wild populations. We also

measured the fitness consequences of directional selection and hybridization in an

artificial selection experiment; wild and hybrid lineages were selected for either advanced

reproduction or large size at reproduction. Large plants were most fecund whereas early-

2 L. G. Campbell, A. A. Snow, and P. M. Sweeney. in prep. When divergent life histories hybridize: insights into adaptive life-history traits in an annual weed. 29

flowering plants were least fecund, regardless of lineage. Our findings demonstrate that hybridization between species with divergent life histories may catalyze the rapid evolution of adaptive weed phenotypes.

3.2 Introduction

As we begin to grasp the full impact of weed invasions, an understanding of what makes a plant invasive has become more valuable. Many workers have analyzed floras to understand which phenotypic and life history traits are associated with weeds (e.g., Baker

1965; Crawley et al. 1996; Daehler 1998; Williamson and Fitter 1996; Randall and

Hoshovsky 2000; Sutherland 2004; Muth and Pigliucci 2006). A recurring conclusion is that early reproduction or large size are two of the many adaptive life history strategies of weeds. However, most reports on the topic examine life history variation at the taxonomic level of species (but see Rejmanek and Richardson 1996, Daehler 1998; Muth and Pigliucci 2006). Because certain plant families tend to generate more weedy species than others (Daehler 1998), and many authors fail to incorporate phylogenetically independent methods into their analyses, current conclusions concerning the adaptiveness of “weedy” life history traits may be inaccurate. Rather, weed taxa may exhibit similar life histories simply due to shared ancestry rather than the adaptiveness of the life history traits (Gould and Lewontin 1979). Analyses of closely related species that control for phylogenetic nonindependence may yield more meaningful insights into the evolutionary implications of age and size at maturity for weeds (Rejmanek and Richardson 1996, Sans et al. 2004; Muth and Pigliucci 2006).

30

Variation in age at maturity can have significant consequences for individual fitness and population growth. By maturing early, individuals shorten generation time and increase their probability of surviving to reproduce (Bell 1980, Cole 1954, Lewontin

1965, Hamilton 1966, Roff 1992, Stearns 1992). Alternatively, individuals may exhibit higher initial fecundity, in the form of higher quality offspring or increased future fecundity, by delaying reproduction and allocating additional time and resources to growth (Bell 1980, Stearns 1992). If, however, these traits have a significant, positive effect on fitness, their heritability may be low (Roff and Mousseau 1987; Mousseau and

Roff 1987). Therefore, in species or lineages that lack substantial amounts of heritable variation in age or size at maturity, it is difficult to determine the mechanisms that may have influenced their evolutionary trajectory and current constraint. As a solution, recent reviews have suggested the use of hybridization to create greater variation in the phenotype of interest, followed by artificial selection to examine the trait’s heritability, genetic correlations, and possible life history trade-offs (i.e. Lexer et al. 2003; Brakefield

2003). When hybridization occurs between species with diverse life histories, the individual offspring will be phenotypically variable. Populations created with this initial diversity will have the opportunity to evolve along diverse life-history trajectories.

Crop-to-wild gene flow is one model system in which hybridization between two species may lead to rapid evolution of life history and other fitness-related traits.

Cultivated plants are often sexually compatible with their wild relatives and yet exhibit dramatically different life histories. Age at maturity is routinely altered through crop breeding programs depending on the desired agronomic product. If a plant is cultivated to produce seeds, such as annual maize (Zea mays), age at maturity is often selected to

31

become earlier than wild relatives (e.g., one maize progenitor is the perennial Z. diploperennis; Wang et al. 1999). Alternatively, if a plant is grown for vegetative portions, such as biennial sugar beet (Beta vulgaris ssp. vulgaris), age at maturity is usually selected to be delayed relative to wild species (the sea beet, B. vulgaris ssp. maritima, is an annual plant; Viard et al. 2002). Although their life histories may differ, many pairs of crop-wild taxa have overlapping flowering phenologies, easily hybridize, and produce relatively fecund offspring (e.g., Ellstrand 2003). Therefore, crop-wild complexes may be useful for furthering our theoretical and empirical understanding of plant life history.

In addition to altering the life history of hybrid offspring, crop-wild hybridization may also create weedy derivatives (e.g., Ellstrand et al. 1999; Coulibaly et al. 2002;

Viard et al. 2002). Several studies have demonstrated long-term introgression of crop alleles into weed populations (e.g., canola: Hansen et al. 2001; sunflower: Whitton et al.

1997; radish: Snow et al. 2001), suggesting crop-wild hybridization may persistently alter the evolutionary trajectory of weed populations. Further, isolated, invading hybrid populations may experience strong selection over short time scales (Thompson 1998;

Sakai et al. 2001; Hänfling and Kollman 2002; Lee 2002; Allendorf and Lundquist 2003).

The interaction of hybridization and selection may significantly change the population dynamics of these introduced taxa, altering patterns of invasion and establishment.

3.2.1 Research Objectives

To examine the effect of hybridization on life history evolution and weed evolution in wild and crop-wild hybrid radish, we describe the phenotypic diversity

32

created after hybridization, the phenotypic constraints created by genetic correlations, the selection gradients imposed on the heritable life history traits by natural selection, and the fitness consequences of divergent and extreme life histories created by artificial selection.

Our previous research has measured the lifetime fecundity of wild and hybrid plants’ after experiencing natural selection for several generations (Chapters 4, 5) and the evolutionary response of wild and hybrid lineages to three generations of artificial selection for early flowering and large size (Chapter 2). Here we build on this work to determine: 1) the fitness consequences of artificial selection for early flowering and large size in an annual weed (Raphanus raphanistrum) and its hybrid progeny (R. raphanistrum x R. sativus) and 2) the evolutionary response of wild and hybrid populations to three generations of natural selection. By using this complementary approach, combining the results of artificial selection and natural selection experiments, we provide a novel, comprehensive investigation into the adaptiveness of age and size at maturity for an annual weed.

3.3 Materials and Methods

3.3.1 Study organism

As a model system, we used the crop-wild complex of cultivated radish

(Raphanus sativus), an open-pollinated vegetable selected for large, colorful roots and high levels of seed production (Snow and Campbell, 2005) and its weedy relative, wild radish (R. raphanistrum, also known as jointed charlock), a cosmopolitan, agricultural weed that also colonizes disturbed sites and coastal beaches (Warwick and Francis,

2005). These two radish species have emerged as model systems in plant evolutionary

33

ecology and in the assessment of ecological consequences of crop-to-wild gene flow

(e.g., Conner and Via, 1993; Klinger and Ellstrand 1994; Mazer 1987; Stanton 1987).

While R. raphanistrum and R. sativus share many phenotypic characters, they exhibit

divergent life histories in at least two key traits. First, many Raphanus sativus cultivars

develop red, swollen hypocotyls and large rosettes whereas R. raphanistrum plants form

narrow, branching, white taproots and reproduce at smaller rosette sizes. Second,

although both species are annuals in temperate climates, R. raphanistrum flowers earlier

than cultivated radish (Panetsos and Baker 1967). In Michigan, USA, R. raphanistrum

“bolt” a few weeks after germination, when the primary flowering shoot emerges from

the rosette. Selective breeding has led to relatively delayed bolting and flowering in

Raphanus sativus (Curtis 2003).

Originally native to Europe, both species were introduced into California, USA by

the 19th century (Panetsos and Baker 1967). Since then, descendants of the original

populations of crop-wild radish hybrids, known as wild or feral R. sativus, appear to have

displaced the original populations of R. raphanistrum in California, to become a regionally important weed (Ball et al. 2000, Snow et al. 2001, Hegde et al. 2006).

3.3.2 Experimental populations

Detailed descriptions of the wild and hybrid lineages are available in Chapter 5

(natural selection), Chapter 2 (artificial selection), and a brief summary is presented in

Table 3.1. Briefly, both natural and artificial selection lineages were generated by hand- pollinating 100 wild R. raphanistrum plants with 1) wild pollen to create first generation wild biotype populations, or 2) pollen from 100 R. sativus var. “Red Silk” plants (Harris-

34

Moran Seed Co., Modesto, USA) to create first generation (F1) hybrid biotype

populations. Based on hybridization in this first generation, we refer to radish biotypes as

wild or hybrid. A representative sample of F1 wild and hybrid plants was reserved for the

common garden described below to estimate the phenotype of first-generation plants

prior to experiencing natural or artificial selection.

The natural selection lineages, which were maintained in the field, were

established as four first-generation wild populations (W1, W2, W3, W4 ) and four first- generation hybrid populations (H1, H2, H3, H4) in meadows or agricultural fields in

Emmett and Cheboygan counties, MI, in 2002 (Appendix A, fig. A1). To restrict

unintended gene flow, these eight lineages were isolated from each other and local wild

radish populations by at least one km. Each lineage was started by planting 50-60

seedlings (a minimum of 42 survived to reproduce) in a recently tilled 15 m x 15 m

fertilized plot (Slow-release Osmocote 19-6-12, 22.7 kg per site; Scotts Miracle-Gro Co.,

Marysville, USA). Each spring through 2004, the plots were tilled, fertilized, and hand-

weeded to promote population persistence. Otherwise, the natural selection lineages were

exposed to naturally occurring , disease, herbivores, weather, and competition.

Artificial selection greenhouse lineages were initiated in the F2 generation, after

100 individuals from each F1 biotype were cross-pollinated (Chapter 2). Over three generations of selection, lineages were started with 130-200 individuals and subjected to strong selection for age or size at first flowering by selecting a subset of individuals

(10%, selection differential ≅ 1.3) that flowered the earliest or, in a separate lineage, that had the longest leaves within their lineage. To exclude drift as the evolutionary mechanism, we created three independent lineages for each combination of biotype (wild

35

or hybrid) and selection protocol (earlier reproduction, large size at reproduction, or controls), for a total of 18 lineages. We were successful in creating lineages with heritable variation for earlier reproduction or larger size (Chapter 2, Table 3.2). Control lineages experienced no selection but were propagated with a subset (10%) of randomly chosen individuals from each replicate each generation and experienced random mating for three generations (F5 = G5). Therefore, variation among control lineages is expected to represent the variation in evolutionary trajectory of randomly mated populations that have not experienced selection. We assume, if these randomly mated populations adapted to greenhouse conditions, this had only minor effects on the life-history traits of interest.

In this study, we use these control lineages not only to determine the fitness consequences of selection on fitness in the artificial selection experiment, but also to determine the expected variation in life-history traits without selection in advanced generation hybrid lineages.

3.3.3 Common garden

We measured the lifetime fecundity of individuals from the wild and hybrid artificial selection lineages, the life-history traits of individuals from the wild and hybrid natural selection lineages, and both the lifetime fecundity and the life-history traits of first generation ancestors of all the lineages in one common garden (Table 3.1). In the selection gradient analysis below, we also used previously published data on the lifetime fecundity of the wild and hybrid natural selection lineages (Chapter 5). As in Chapters 4 and 5, the common garden was located at the University of Michigan Biological Station in Pellston, Michigan, USA (See Appendix A for details). The proximity of the natural

36

selection lineage sites to the common garden helped to assure that the phenotypic

variation observed was typical.

In 2004, we collected seeds from the wild and hybrid natural selection lineages

(See Chapter 5). Because radish seeds may remain dormant for several years, we cannot

assume each lineage was composed on only one generation (e.g., all F4). Therefore, we

refer to each year’s lineage as G1, G2, G3, and G4, recognizing that the G4 (=F4) may

represent a mixture of earlier and later generations. G4 seeds for the common garden were

collected directly from G3 plants. Also in 2004, we collected F5 (=G5) seeds from F4

(=G4) artificial selection lineage plants (See Chapter 2).

The garden included G1 wild and hybrid ancestors of the natural and artificial

selection experiments, G4 wild and hybrid natural selection lineages, and the G5 wild and hybrid artificial selection lineages (See Appendix B, Table 3.2 for final sample sizes of each population). The common garden was organized in a complete randomized design and representatives of each genotype were equally allocated to 21 blocks in the garden.

3.3.4 Phenotypic measurements

Each seed was weighed prior to planting. Date of germination was recorded daily for the first two weeks after planting and date of first flowering was recorded daily for each plant. Age at reproduction was calculated as the difference between the date of flowering and the date of germination. Plant size on the first day of flowering was measured as the stem diameter just below the cotyledons using digital callipers (Chicago

Brand Industrial, Inc., Fremont, CA). In Chapter 2, plant size was assessed by length of the longest leaf, which is correlated with stem diameter (Wild: Pearson’s R2 = 0.39, P <

37

0.001, N = 169; Hybrid: Pearson’s R2 = 0.77; P < 0.001, N = 313). Here we used stem diameter as a proxy for size as it exhibited higher heritability than leaf length (Campbell, unpub.).

In the common garden, survival after transplantation was nearly 100% so survival was not included in the description of individual fitness. As measures of lifetime fecundity, we recorded flower number, seeds per fruit, and seed production. First, we counted number of flower pedicles and fruits on harvested plants. To estimate the number of seeds per plant, we multiplied the average number of seeds per fruit (for ten randomly chosen fruits per plant) by the number of fruits. Seeds per plant were used as a proxy for individual fitness by numerical dominance although we recognize that this may not have long-term evolutionary significance (Murray 1990, 1992).

3.3.5 Statistical analysis

Prior to analysis, age at first flower, stem diameter, number of seeds per plant and number of flowers per plant data were natural log transformed to normalize the data (See

Stanton and Theide 2005 for potential implications). Seeds per fruit data was normally distributed and required no transformations prior to analysis.

3.3.5.1 Effect of Natural Selection on Trait Means Correlations

First, we compared the two life-history traits across generations, populations, and biotypes. To determine the initial consequences of hybridization, we compared G1 wild and hybrid age and size at reproduction using a multivariate ANOVA. Next, we compared the age and size at reproduction among biotypes (wild, hybrid) for the

38

advanced-generation randomly mating and natural selection lineages using an

unbalanced, nested ANOVA that included biotype and lineage within biotype as fixed

effects and block as a random effect. Variance of random effects was estimated using

restricted maximum likelihood methods (REML). In addition, we estimated the

phenotypic correlations between traits for each generation of each biotype using

Pearson’s r.

3.3.5.2 Path analytic estimate of the magnitude of natural selection

We assessed the adaptive consequences of trait evolution after hybridization by

comparing the strength of selection acting on wild and hybrid natural selection lineages

estimated using a path analytic approach (Schiener et al. 2000, 2002). Scheiner et al.

(2002) demonstrated that path analysis reduces environmental biases in selection

coefficient estimates for traits of California wild radish (R. sativus) and we follow their

approach here. As a measure of maternal environment and early plant condition, we used

seed biomass (Mazer 1987, Stanton 1984, Mazer and Wolfe 1998).

Separate linear, path analytic models for each biotype were constructed based on

biological knowledge of the study system with distinct hierarchical a priori expectations

(Scheiner et al., 2000; using Procedure RAMONA, SYSTAT). Although many trait correlations are frequently nonlinear, the majority of the relationships studied here were linear, after standardization of the data (Campbell, unpub). We used a model proposed developed in Chapter 4 that described how morphological traits related to measures of reproductive success under competitive conditions in G3 wild and hybrid natural selection lineages. We slightly modified the model by removing all reference to variation in the

39

competitive environment to reflect the current common garden experiment. In the model,

seed biomass affected plant age and size at reproduction (stem diameter). Changes in

plant size directly affected plant age. In turn, both of these traits directly affected total

number of flowers per plant and number of seeds per fruit. Finally, number of flowers per

plant and number of seeds per fruit directly influenced the number of seeds per plant. The

resulting causal model is illustrated in figures 1A and 1B. In the analysis, we used data

from 156 wild plants and 205 hybrid plants for which we had measurements for every

trait. In each case, model performance was evaluated by criteria based on the SYSTAT

output (See Appendix C for goodness of fit estimates).

For age and size at reproduction, we estimated the selection differentials (s*), an

indication of the total strength of linear selection on the traits of each biotype, and

selection gradients (β*), a partitioning of selection into direct and indirect effects.

Selection coefficients (β*) were calculated as the sum of the indirect effects of the traits on fitness (as described in Schiener et al. 2000). Along a single path, coefficients were multiplied, while separate paths were summed. According to the path model, there were no direct effects of age and size at reproduction on fitness. The magnitude of indirect selection (including noncausal, spurious or correlated effects) was calculated by following the paths backwards one trait of interest and then forward through alternative paths to relative fitness (as described in Scheiner et al. 2000). Finally, we calculated the selection differential (s*), or total selection, on each trait by summing direct and indirect selection (Scheiner et al. 2000).

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3.3.5.3 Estimating response to natural selection

To determine whether biotype influenced response to natural selection in the two

life-history traits, we calculated the mean and 95% confidence interval of the age and size at reproduction of each natural selection and artificial selection randomly mated lineage.

Advanced-generation wild and hybrid lineages were expected to resemble advanced- generation, artificial selection randomly mated lineages, if selection had no effect on life history. We interpreted consistent directional deviations from the control lineages as a response to selection. Variation among replicates (i.e., W1 vs. W4) within treatments (i.e.,

random mating versus natural selection) was interpreted as variation due to genetic drift.

Finally, differences among biotypes (wild vs. hybrid) determine the effect of biotype on

the response to selection of the two life history traits. Although segregation distortion in

advanced-generation hybrids cannot be decisively ruled out as a source of phenotypic

change, this approach will yield insights into the magnitude of response that may be

expected from ‘natural’ crop-wild hybrids versus their randomly mating relatives.

3.3.5.4 Fitness consequences of artificial selection

To test for differences in lifetime fecundity among the three types of artificially

selected life-history lineages (Random, Early flowering, Large size), we ran a nested

ANOVA for each fitness component. Biotype and selection treatment were fixed effects.

Replicate nested within selection treatment and block were random effects. Analyses

were performed using SAS Proc GLM. If the P-value for an interaction was less than 0.2,

follow-up analyses for wild and hybrid lineages were performed separately.

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3.4 Results

3.4.1 Variability and constraint of wild and hybrid phenotypes

To determine if hybridization generated phenotypic diversity in age and size at

reproduction, we compared the phenotypes of the first-generation (G1 = F1) hybrid plants

and wild progenitors. G1 hybrids initiated flowering at a size 1.79 times larger than G1 wild plants (F1,80 = 79.997, P < 0.001, Table 3.2). In addition, initiation of flowering was

delayed by 13 days in F1 hybrids as compared to F1 wild plants (F1,8 = 132.87, P < 0.001).

Age and size at reproduction were more variable in F1 hybrid plants than wild plants

(Table 3.2).

As expected, G5 randomly mated lineages continued to grow to a larger size and flower later than advanced-generation wild lineages. On average, plants from G5 hybrid random lineages initiated flowering significantly later (12 days) than comparable G5 wild

plants from random lineages and were three times more variable in flowering phenology

than those wild plants (F1,4 = 77.02, P < 0.001, Table 3.2). Further, randomly mated hybrids initiated flowering at a significantly larger size (40% larger) and their size at reproduction was more than eight times more variable than randomly mated wild plants.

(F1,4 = 61.71, P < 0.001). Replicate lineages within biotypes varied significantly for both age and size at reproduction (Age: F4,77 = 8.98, P < 0.001; Size: F4,77 = 16.24, P < 0.001).

The variation among replicates within biotypes is likely due to genetic drift.

G4 hybrid plants from the natural selection lineages flowered later and grew larger

than analogous G4 wild plants. G4 hybrid plants delayed flowering by 8 days relative to wild plants (F1,6=71.1, P < 0.001, Table 3.2). Further, G4 hybrids initiated flowering at a

significantly larger size than that of wild plants (F1,6=88.5, P < 0.001). Variation in age

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and size at reproduction in G4 hybrid experimental weed populations was similar to that

of G4 wild experimental weed populations yet lower than that of the G4 randomly mating

hybrid lineages. Replicate populations within biotypes did not significantly differ in age

or size at reproduction (Age: F6,478=0.61, P=0.73; Size: F6,478=0.86, P <0.53). As

expected, the variation among replicates within biotypes is lower in the natural selection

lineages than the randomly mated lineages.

To determine whether the evolution of traits may be constrained by genetic

correlations between age and size at reproduction, we estimated the phenotypic

correlations between traits for each biotype and generation. The correlation between age

and size at reproduction in F1 wild plants was not significant (Pearson’s r = -0.025, P =

0.873, N = 42) whereas it was strongly positively correlated in F1 hybrid plants (r =

0.693, P < 0.001, N = 42). Plants from both G4 wild and hybrid natural selection lineages exhibited a significant positive correlation between age and size at reproduction; however the correlation was 2.5 times stronger in hybrid populations than wild populations (rWild =

0.201, P = 0.012, N = 156; rHybrid = 0.739, P < 0.001, N = 205). Therefore, the evolution

of age and size at reproduction may be more constrained by phenotypic correlations and a

life-history trade-off in hybrid populations than in wild populations and more constrained

by a lack of phenotypic variation in wild populations than in hybrid populations.

3.4.2 The strength of natural selection on weed phenotypes

Using a path analytic approach, we measured the strength of natural selection

acting on age and size at reproduction in G4 wild and hybrid lineages (see Table 3.3 for

model goodness of fit). Direct selection on age and size at reproduction was considerable

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(fig. 1). However, it was not necessarily consistent between biotypes. The positive effect

of size at reproduction on number of flowers tended to be greater in hybrids than wild

plants (fig. 1C; ρWild = 0.33, ρHybrid = 0.50). Further, the effect of age at reproduction on

relative fitness, through number of flowers per plant, was significantly greater in wild

than hybrid plants. In the wild model, age at reproduction had a positive effect on number

of flowers (ρ = 0.22) whereas in the hybrid model, age at reproduction did not affect

number of flowers per plant (ρ = -0.02). Finally, the negative effect of age at reproduction

on number of seeds per fruit was significantly less than zero in the hybrid model (ρHybrid =

-0.19) whereas selection was not significantly different from zero in the wild model (ρWild

= -0.12). These differences in the strength of selection on age and size at reproduction reveal how selection changed after hybridization.

From this path analysis, the direct selection coefficient (β*) for size at reproduction was positive and stronger in hybrid populations (β* = 0.35) than wild populations (β* = 0.25) (fig. 2). In contrast, selection for age at reproduction differed in direction for the two biotypes. Wild populations experienced positive directional selection (β* = 0.09) whereas hybrid populations experienced negative directional selection for age at reproduction (β* = -0.04). Indirect selection was negligible for size at reproduction in both wild and hybrid populations (fig. 2; Wild: -0.002, Hybrid: 0.0005) and for age at reproduction in wild populations (Wild: 0.004). However, indirect selection on age at reproduction in hybrid populations was large, positive, and in direct conflict with the direction of direct selection for early flowering (fig. 2; Hybrid: 0.24).

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Therefore, total selection (s*) imposed on both natural selection wild and advanced generation hybrid lineages was for delayed flowering and larger size at reproduction (fig.

2).

The results of these analyses also provide us with working hypotheses about the fitness consequences of selection imposed on these life history traits (Conner 1996). For instance, selection for large size should produce plants with many flowers and high fecundity relative to selection for earlier flowering. However, only selection for large size on hybrid plants, versus wild plants, should result in fewer seeds per fruit. Below we test these predictions by measuring the fitness consequences of artificial selection for advanced reproduction and large size at reproduction.

3.4.3 Response to selection

We defined strong evidence for selection as strong deviations of the natural selection lineages from the expected phenotype of the randomly mating lineages.

Average natural selection phenotypes that deviated significantly from the 95% confidence interval (CI) of the randomly mated lineages represent significant responses to selection. Weaker evidence for selection was interpreted as average phenotypes of the natural selection populations whose confidence intervals partially overlapped with the

95% CI of the expected phenotype. We found strong evidence that hybrid plants responded to natural selection for larger size relative to the randomly mating populations but little evidence that wild populations responded to selection on plant size, even though

β* and s* was strong and positive (fig. 3). In three of the four wild populations, we found strong evidence that plants responded to selection for delayed reproduction relative to the

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randomly mating populations. Finally, two of the four hybrid populations responded to selection for delayed reproduction, and the other two hybrid populations provided weaker evidence for a response to selection, relative to the randomly mating populations (fig. 3).

Therefore, most lineages responded to natural selection in the predicted directions.

3.4.4 Fitness consequences of divergent and extreme life histories

By creating lineages with heritable life-history variation, we could determine the adaptiveness of alternative weed strategies, early flowering or large size (Conner 2003).

Artificial selection for large size in wild lineages resulted in plants with significantly more flowers per plant than randomly mating lineages or early flowering lineages (figs.

4B,C, Table 3.2; F2,6 = 14.30, P = 0.005). However, selection for either large size or advanced flowering did not significantly alter number of seeds per plant nor average number of seeds per fruit in wild lineages (Seeds per plant: F2,6 = 3.9, P = 0.08; Seeds per fruit: F2,6 = 0.03, P = 0.97). In contrast, selection for large size in hybrid lineages resulted in plants with significantly more flowers per plant and fewer seeds per fruit than randomly mating lineages or early flowering lineages (Flowers per plant: F2,6 = 28.89, P

= 0.0008; Seeds per fruit: F2,6 = 6.24, P = 0.03) resulting in no difference in the number of seeds per plant between large and randomly mating lineages (Table 3.2). Selection for earlier reproduction in hybrid lineages resulted in fewer seeds per plant than control lineages (Hybrid: F2,6 = 11.51, P = 0.0088). Therefore, large size benefits this weedy annual more than early flowering.

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3.5 Discussion

This study set out to examine how hybridization and selection on life-history traits interact to drive the evolution of weeds. We used a complementary approach by measuring the magnitude of natural selection imposed on two key life-history traits and the fitness consequences of heritable variation in those two traits. Although hybridization did not significantly alter the amount of phenotypic variation found in advanced- generation weed populations, it immediately shifted the G1 population mean age and size at reproduction, making the weeds larger and delaying their reproduction. In the natural selection lineages, selection strongly favored larger plants in both wild and hybrid populations; however, only hybrid populations strongly responded to this selection.

Additionally, direct selection favored delayed reproduction in wild populations and indirect selection favored delayed reproduction in hybrid populations. Over three generations, both biotypes responded to some degree by delaying reproduction. Divergent life histories, created by artificial selection, had dramatic fitness consequences that were consistent across biotypes. Plants that were large at reproduction were most fecund whereas plants with advanced reproduction were least fecund. Together, these results suggest that hybridization between species with divergent life histories may catalyze the rapid evolution of adaptive weed phenotypes.

3.5.1 Measurements of selection in natural plant populations

Our study was unique in its approach to measuring the magnitude of natural selection on life history traits because of its experimental nature. Instead of measuring

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selection in natural populations, we explicitly created experimental populations to measure selection. To our knowledge, this is the third such selection experiment (sensu stricto Reznick and Ghalambor 2005; e.g., guppies: Endler, 1980, Reznick et al. 1990,

Anolis lizards: Schoener and Schoener 1983, Losos et al. 1997, 2001) and the only to estimate selection in experimental plant populations. Comparable studies, though not formal field selection experiments, have measured selection in association with a dated event and appropriate controls in plant and non-plant populations (e.g., Caroll et al. 2003, reviewed in Bone and Farres 2001, Kingsolver et al. 2001). Our approach was also unique because, through the process of hybridization, we created weed phenotypes that did not naturally occur within the region. This method was a useful tool for measuring selection on relatively invariant traits within populations, as suggested by Lexer et al.

(2003). This work revealed that weedy radish populations would benefit from the introgression of “large size” and “delayed reproduction” traits, such as those found in populations of cultivated relatives.

The magnitude of linear direct selection imposed on age and size at reproduction in the experimental populations was comparable to other published studies. Kingsolver et al. (2001) reported a mean value of β = |0.22| for 993 estimates of linear selection gradients (median = |0.16|) and Geber and Griffin (2003) reported a similar mean value of

|0.2| for 653 estimates of linear selection gradients in plant populations (median = |0.12|).

Direct selection on size at reproduction in this study was higher than these average values

* * for both wild and hybrid populations (β Wild = 0.25; β Hybrid = 0.35). Yet, direct selection on age at reproduction was lower than this average value for both wild and hybrid

* * populations (β Wild = 0.09; β Hybrid = -0.04). In contrast to the results of Kingsolver et al. 48

(2001) and similar to the results of Geber and Griffin (2003), we found that indirect selection constituted a large proportion of the total selection (s*) imposed on age at reproduction in hybrid populations. This may be due to the genotypic correlation between age and size at reproduction (Chapter 2). Geber and Griffin (2003) found that indirect selection appeared to reinforce direct selection (i.e., similar direction of selection).

However, the relatively weak direct selection for earlier flowering in hybrid radish populations was countered by the relatively strong indirect selection for delayed flowering, resulting in total selection favoring an apparently non-adaptive flowering schedule.

Many studies of selection have revealed inter-annual variation in the magnitude of selection (recent examples include: Klips et al. 2005, Price et al. 2005, Inouye et al. 2002,

Weis et al. 2005). Our study reflects selection in only one year. However, the pattern of selection across multiple populations was consistent, even though these populations had independently evolved for three generations (fig. 3). Further, populations generally showed a significant deviation from the expected phenotype in the direction of selection in the current year’s study. This suggests that consistent directional selection had been acting on these traits for several generations. Finally, our results are consistent with previous estimates of selection on various traits in Raphanus populations. For instance,

Conner et al. (1996) found that selection on flower production was always positively associated with female fitness and strong in Raphanus raphanistrum (β = 0.70 in two of

* * three years measured, compared with the current study β Wild = 0.50, β Hybrid = 0.77). The phenotypic correlations found in this study were also consistent, in magnitude and direction, with those measured in a previous experiment conducted with G3 plants from 49

the experimental populations a year earlier, in 2004 (Chapter 4). Given that the results of many studies suggests that selection may vary dramatically, this collection of work suggests that the relationship between certain phenotypic traits and fitness is remarkably constant in Raphanus across years, locations, populations, and laboratories, especially given its environmentally sensitive phenotype (e.g., Williams and Conner 2001; Wolfe and Mazer 2005, Murren and Pigliucci 2005).

3.5.2 Life history strategies of weeds

There have been repeated attempts to identify adaptive traits for weeds and invasive plants with the intention of anticipating which introduced species will become problematic weeds (e.g., Baker 1965, Sutherland 2004, Gerlach et al. 2003; ). However, to date, the surveys have had limited predictive success (Enserink 1999; Mack et al.

2000). Even when phylogenetic nonindependence is appropriately considered, this method may not provide the answers necessary to reliably predict invasive weed phenotypes. Rather, these approaches may provide descriptions of model weeds too general to be accurate. We echo the suggestion of Mack (1996), Grotkopp et al. (2002), and Muth and Pigliucci (2006) – global explanations, and therefore global life histories, of successful weeds may not exist. Rather, careful consideration of the adaptive significance of life history to smaller categories of weeds (i.e., annuals, or Asteraceae) may provide more insights into adaptive weed strategies (e.g., Brock et al. 2005, Burns

2004; Grotkopp et al. 2002; Muth and Pigliucci 2006). To our knowledge, this is the first experimental manipulation of plant life histories belonging to one evolutionary lineage that possesses both weedy plants and lineages with divergent life histories. As a result,

50

this study provide unique insights into the relative benefit of size and age at reproduction for weeds.

Our results suggest that, weedy Raphanus species benefit more from large size at reproduction than advanced reproduction as selection strongly favored large plants with relatively delayed reproduction. While cultivated R. sativus routinely experiences selection for delayed flowering (Curtis 2003), one might expect selection to favour early flowering in weedy radish populations (e.g., Mazer 1987). Yet, several other studies have documented a positive correlation between age and size at reproduction in Raphanus spp. and one study has documented similar selection gradients (e.g., Jablonski 1997, Scheiner et al 2002). In fact, Scheiner et al. (2002) found evidence for selection for both delayed reproduction (β* = 0.03-0.08) and large size in R. sativus (β* = 0.13-0.15). Large size appears to provide a significant fitness advantage for wild radish. Under natural conditions, large size may also provide individuals with a competitive advantage

(Chapter 4). Delayed flowering appears to be a simple bi-product of both environmentally plastic and genetically inherited correlations with large size (Chapters 2,

4). The relative importance of this life history tradeoff may be a function of the environment in which the trade-off is evaluated (e.g., Reznick et al. 2000). Stronger direct selection for advanced flowering, and therefore a reversal of the direction of total selection) may occur if environmental conditions in our plots changed (e.g., in the frequency of disturbance [Meerts 1995], herbicide application [Mortimer 1997], herbivory [Juenger and Bergelson 2000]) Further, environmentally dependent differences in fecundity may be due to the effect of context-specific tradeoffs. Future

51

work will examine whether a dramatic change in the relative fitness of hybrids when grown in two disparate locations was a consequence of changes in life-history tradeoffs

(Chapter 5). Although natural selection favoured large size in both wild and hybrid populations, only hybrids demonstrated a strong response whereas and wild plants did not respond to natural selection in this study. These results are consistent with results from an artificial selection study where wild lineages exhibited a smaller response to selection for large size than hybrid lineages when we imposed extremely strong selection on the trait

(Chapter 2). Therefore, hybridization may facilitate the evolution of a large and successful weed (Chapter 5, although see Bergelson 1994).

3.5.3 Adaptive evolution in hybrids

The significance of hybridization as a general mechanism of the evolution of natural populations remains unclear (Rieseberg 1991 and refs. therein). However, relatively rapid evolution has been documented following hybridization. Carney et al.

(2000) measured the degree of similarity between hybrids and their parental populations,

Helianthus bolanderi and H. annuus. Depending on the location, it was estimated that populations had evolved at a rate of 6.42–19.68 darwins (0.0220–0.0486 haldanes, Bone and Farres 2001). However, it is difficult to determine whether this rate of evolution occurred due to the normal processes of selection (i.e., because novel gene combinations within hybrid populations allowed evolution to occur rapidly) or hybridization (e.g., phenotypic by-products of hybrid incompatibilities such as heterosis or outbreeding depression). Here we document rates of evolution in the wild radish experimental field populations that vary between 13 to 33 darwins for size at reproduction (0.06 – 0.16

52

haldanes) and between 22 to 37 darwins for age at reproduction (0.19 – 0.30 haldanes;

Table 3.4). In contrast, hybrid populations evolved at a rate of 53 to 80 darwins for size at reproduction (0.21 – 0.15 haldanes) and 15 to 30 darwins for age at reproduction (0.11-

0.16 haldanes; Table 3.4). As we calculated the rate of evolution based on the phenotype of randomly mating wild and hybrid populations, we suggest that the elevated rate of evolution for leaf length in hybrid populations under natural conditions may be due to the novel genome combination of cultivated and wild radishes rather than a by-product of hybridization.

Heterosis, a temporary increase in the number of heterozygous loci, is expected to increase the size of hybrids, relative to their parental lineages because deleterious recessive alleles have been effectively hidden by dominant nondeleterious alleles (Kirk et al. 2005, Rhode and Cruzan 2005). Many crop-wild hybrids, including radishes, exhibit this increased size (Snow et al., 2001, Chapter 5). However, this study provides evidence that if heterosis is indeed the cause of the increased size in hybrids, the effect should be significantly reduced in advanced-generation hybrids in a randomly mating population.

However, the advanced generation hybrids found in the experimental field populations were significantly larger than the randomly mating population, suggesting that size differences among wild and hybrid populations was, in part, adaptive. Selection in field populations of hybrids may be selecting for one of two things. First, selection may be continuing to favor heterozygous plants, similar to the effects of heterosis seen in first generation hybrids. Alternatively, hybridization may have led to the introgression of crop traits that produce large plants. Either scenario suggests that the introgression of crop alleles contributed to the evolution of adaptive weed phenotypes and we recommend that

53

future experimental designs take this possiblility into account (e.g., Rhode and Cruzan

2005).

In experimental field conditions, wild and hybrid populations differed in their response to putatively identical selection pressures (fig. 3). This is likely because hybrid populations exhibit higher heritabilities for both age and size at reproduction in artificial selection lineages (Chapter 2) and biotypes differ in the phenotypic correlations of age and size at reproduction with various components of fitness (figs. 1,4, Chapter 4). For instance, our path analytic model suggested that selection for larger size at reproduction should have a stronger negative effect on seeds per fruit and stronger positive effect on number of flowers per plant in hybrid populations than wild populations (fig. 1C). These changes may be common consequences of hybridization that have important consequences for adaptive evolution of hybrids. Murren et al. (2002) found that

Brassicaceaous hybrid species exhibited a higher number of phenotypic correlations than either of their parental taxa. Further, populations that have experienced recent outbreeding events, tend to exhibit higher heritabilities than more inbred populations

(Swindell and Bouzat 2005; Syafaruddin et al. 2006). Finally, hybrid populations may exhibit greater responses to selection than parental populations (Carney et al., 2001).

3.5.4 Conclusions

The natural selection experiment revealed that adaptive evolution may proceed more rapidly in crop-wild hybrid populations than in populations of their wild progenitors. Although the artificial selection protocol imposed unnatural population sizes

54

and population structure (e.g., Shaner and Marshall, 2003; Chapter 5), the fitness response of the artificial selection lineages apparently represented the response of weedy radishes in the field. Together with the adaptive evolution demonstrated by the natural selection populations, we have demonstrated that wild and hybrid populations will respond predictably to specific selection pressures (e.g., Rosenthal et al. 2005). Future studies that evaluate crop-wild hybrids could provide insight into the adaptiveness of extremely large size and biennial life histories for these weeds. Further, assessing the consequences of variation in life history for population dynamics will be important in determining the fitness and invasiveness of these extreme genotypes (Murray 1990, 1992;

Bergelson 1994). In summary, we argue that experimental manipulation of life histories provides important insights into the drivers of evolutionary response and should stimulate the development of plant life history theory.

3.6 Acknowledgements

The Bonnett, Brubacher, Dotski, Gregory, Hartman, Phelps, Schreier, Stempky, and Sterzik families generously shared their farmland. We thank the staff of the

University of Michigan Biological Station, J. Leonard, N. Marsh, N. Smith, T. Waite, and many student researchers for their help in the greenhouse, field, and lab. Thanks to K.

Nadelhoffer and R. Mack for their support. Funding was provided by the US Department of Agriculture (#2002-03715), University of Michigan Biological Station, The Nature

Conservancy of Michigan, National Science Foundation (DEB-0508615), The Ohio State

University Presidential Fellowship, The OSU College of Biological Science, Janice

55

Carson Beatley Endowment, and Sigma Xi. Many thanks to D. Roff, S. Scheiner, B.

Shipley, T. Waite, and the Snow lab group for useful discussions.

56

3.7 Tables

Biotype Selection Generations of Generation in No. of replicate treatment selection Common Garden lineages Wild Ancestors 0 1st 1 Natural 3 4th 4 Random 3a 5th 3 Early flowering 3 5th 3 Large size 3 5th 3 Hybrid Ancestors 0 1st 1 Natural 3 4th 4 Random 3a 5th 3 Early flowering 3 5th 3 Large size 3 5th 3

Table 3.1 Summary of wild and hybrid lineages included in the common garden.

Ancestors represent the first generation wild and hybrid plants that initiated both the natural selection (Natural) and artificial selection (Random, Early flowering, Large size) lineages. a Note that these populations did not experience selection but rather random mating for three generations.

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Biotype Wild Selection Ancestral Natural Random Lineage All All 1 2 3 4 All 1 2 3 N 42 4 42 42 42 44 3 41 42 43 Stem 3.8 3.9 3.7 3.9 4.0 3.8 3.5 3.6 3.4 3.5 diameter (0.16,0.19) (0.06, (0.17) (0.21) (0.17) (0.19) (0.06, (0.13) (0.15) (0.18) at 0.03) 0.03) flowering (mm) (SE,CoV) Age at 35 38 39 37 37 38 34 35 32 34 flowering (0.6, 0.08) (0.5, (1.0) (0.8) (1.1) (0.8) (0.8, (1.0) B (0.6) B (0.8) (SE, 0.03) 0.04) B CoV) N 42 4 42 42 42 44 3 41 42 43 No. seeds 4.1 (0.2)A 4.1 4.1 4.0 4.1 4.3 3.8 3.2 3.9 4.2 / fruit (0.1)A (0.2) A (0.2) A (0.2) A (0.2) A (0.3) (0.2 (0.2) (0.1) (SE) No. 383 (39)A 382 373 381 411 364 345 283 378 374 flowers / (17)A (33) A (38) A (35) A (35) A (31) (31) (35) (40) plant (SE) No. 746 (60)A 767 679 754 833 799 631 472 729 691 Seeds/ (37)A (55) A (81) A (76) A (79) A (80) (67) (75) (69) plant (SE)

Continued

Table 3.2 Effects of hybridization (Wild, Hybrid), natural and artificial selection (Early

flowering, Large size) and random mating (Random) on two life history traits and three

fitness components in wild and crop-wild hybrid lineages. Replicate lineages were

represented by N individuals in a common garden. Superscripts denote data previously published in either A) Chapter 5; or B) Chapter 2.

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Table 3.2, continued.

Biotype Wild Selection Early flowering Large Lineage All 1 2 3 All 1 2 3 N 3 42 42 43 3 41 42 42 Stem diameter 3.2 (0.15, 0.08) 3.0 3.5 (0.13) 3.2 4.4 3.8 5.4 4.1 (0.20) at flowering (0.10) (0.09) (0.50, (0.16) (0.34) (mm) 0.19) (SE,CoV) Age at 30 (0, 0) 30 30 (0.4) B 30 43 41 49 40 (0.9) B flowering (SE, (0.5) (0.3) (2.8, (0.6) (1.4) CoV) B B 0.11) B B N 3 42 42 43 3 41 42 42 No. seeds / 3.8 (0.1) 3.6 3.8 (0.2) 4.0 3.9 4.3 3.9 3.4 (0.2) fruit (SE) (0.2) (0.1) (0.3) (0.2) (0.2) No. flowers / 280 (32) 230 340 (32) 270 544 507 559 567 (55) plant (SE) (20) (27) (19) (40) (54) No. Seeds/ 549 (70) 420 662 (56) 564 965 1038 1061 796 (74) plant (SE) (41) (60) (85) (100) (115)

Biotype Hybrid Selection Ancestral Natural Random Lineage All All 1 2 3 4 All 1 2 3 N 42 4 84 82 83 81 3 84 84 84 Stem diameter 6.8 (0.40, 6.4 6.4 6.5 6.0 6.7 4.9 6.2 4.0 4.5 at flowering 0.24) (0.15, (0.38) (0.57) (0.36) (0.54) (0.70, (0.33) (0.14) (0.26) (mm) 0.05) 0.24) (SE,CoV) Age at 48 (1.0, 46 46 46 44 47 42 47 38 40 flowering (SE, 0.09) (0.6, (1.1) (1.4) (1.3) (1.8) (2.9, (2.0) (1.3) (1.5) CoV) 0.03) 0.12) B B B N 42 4 84 83 84 82 3 48 47 47 No. seeds / 3.5 (0.1) 3.4 3.6 3.4 3.5 3.3 3.7 3.3 3.8 3.9 fruit (SE) A (0.1) (0.1) (0.1) (0.1) (0.2) A (0.2) (0.2) (0.2) (0.2) A A A A No. flowers / 641 (62) 558 535 634 485 577 512 623 444 467 plant (SE) A (29) (49) A (76) A (44) A (56) A (56) (75) (53) (55) A No. Seeds/ 879 (99) 685 637 802 567 736 647 813 534 585 plant (SE) A (39) (50) A (111) (43) A (87) A (84) (111) (59) (62) A A

Continued

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Biotype Hybrid Selection Early flowering Large Lineage All 1 2 3 All 1 2 3 N 3 84 84 84 3 84 84 84 Stem diameter at 3.3 3.3 (0.07) 3.4 3.1 8.9 (1.06, 9.7 10.2 6.8 (0.32) flowering (mm) (0.09, (0.20) (0.06) 0.21) (0.65) (0.59) (SE,CoV) 0.05) Age at flowering 31 (0.7, 32 (0.4) B 30 30 57 (2.7, 58 61 52 (1.1) B (SE, CoV) 0.04) (0.3) (0.3) 0.08) (1.5) (1.6) B B B B N 3 40 37 36 3 40 36 38 No. seeds / fruit 3.8 4.1 (0.1) 3.5 3.9 3.0 (0.1) 3.2 3.1 2.8 (0.2) (SE) (0.2) (0.2) (0.2) (0.2) (0.2) No. flowers / plant 189 168 (16) 246 152 695 (84) 558 847 680 (88) (SE) (29) (33) (17) (58) (96) No. Seeds/ plant 326 272 (23) 440 267 796 (106) 699 1008 680 (91) (SE) (57) (47) (27) (72) (101)

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Biotype RMSEA Confidence Saturated AIC Model AIC interval for (95% CI) RMSEA (P-value of perfect fit) Wild 0.085 0 – 0.092 0.271 0.275 (0.633) (0.239–0.362) Hybrid 0.000 0.000 – 0.046 0.206 0.227 (0.95) (0.189–0.303)

Table 3.3 Summary statistics for the fit of the path analytic models for each biotype. The root mean square error of approximation (RMSEA) together with its 95% confidence interval and P-value is a measure of the fit between the observed covariance matrix and the one predicted by the model (where a good fit is indicated by RMSEA values close to zero). The fit of the tested model is also measured by a comparison of its Akaike

Information Criterion (AIC) value is to the AIC of the saturated model; if they are similar, as measured by the 95% CI of the Model AIC, then the proposed model is a good fit to the data. For the wild and hybrid models being compared, ‘saturated’ refers to a model with all paths allowable, which has no degrees of freedom and perfect fit; ‘model’ is the partially constrained path analytical model actually being tested.

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Population Darwins§ (x 10-3) Haldanes‡ Age at Size at Age at Size at reproduction reproduction reproduction reproduction W1 36.90 13.39 0.3002 0.0628 W2 21.77 25.41 0. 2207 0.0968 W3 26.91 32.88 0.1910 0.1569 W4 30.28 16.54 0.3004 0.0689 Avg G4 W 28.96 22.05 0.2531 0.0963 H1 24.49 67.09 0. 2131 0.2130 H2 22.84 70.37 0. 1595 0.1529 H3 15.36 53.25 0.1114 0.1770 H4 30.25 80.06 0.1600 0.1853 Avg G4 H 23.23 67.69 0.1610 0.1821

Table 3.4 Estimated rates of evolution for age and size at reproduction in G4 wild and

§ hybrid populations relative to a randomly mating population. darwins = (ln(x2) –

ln(x1))/t (Haldane, 1949) where x1 is the mean trait value for control lineages and x2 is

the mean trait value of selected lineages, t is the time in millions of years (4 years)

† haldanes = ((x2/sp)-(x1/sp))/g (Gingerich 1983) where sp is the pooled standard deviation of the populations’ trait values, g is the number of generations (4 generations) since the separation of the populations.

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Figure 3.1 Solved path analytic models of the effects of age and size at reproduction on wild and hybrid fitness for the linear selection coefficient analysis following natural selection. Wild and hybrid populations had experienced selection for three generations in natural conditions. A. Solved path diagram for wild radish (Raphanus raphanistrum) plants, N = 156; B. Solved path diagram for advanced-generation hybrid radish (R. raphanistrum x R. sativus), N = 205. Dashed lines indicate negative effects (ρ) and the value beside the arrow and the width of the arrow indicates the magnitude of the effects.

Black lines indicate the effect was significantly greater or less than zero (P≤0.05). Grey lines indicate the the effect was not significantly different from zero (P > 0.05). Variation due to error is not included for simplicity; C. Graphical comparison of the magnitude of effects in the solved wild and hybrid path diagrams. Error bars represent the 95% confidence interval of the effects.

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Number

A. Wild of seeds -0.12 Age at per fruit -0.23 0.32 maturit Seed 0.19 0.22 -0.22 Number biomass of 0.22

0.11 Size at maturity 0.50 Number 0.32 of flowers

B. Hybrid Number of seeds -0.19 Age at per fruit -0.09 0.30 maturit -0.02

Seed Number biomas -0.19 0.68 of -0.01 0.14 Size at maturity Number 0.77 ρ < 0.2 0.50 of 0.2 ≤ ρ < 0.4 flowers 0.4 ≤ ρ < 0.6 0.6 < 0.8 ≤ ρ 0.8 ≤ ρ < 1.0 Seed → Size Hybrid

Seed → Age Wild C. Comparison of Wild and Hybrid Path diagrams Size → Age

Size → Seeds / fruit

Age → Seeds / fruit

Size → No. flowers

Age → No. flowers

Seeds / fruit → No. flowers

Seeds / fruit → Rel. fitness

No. flowers → Rel. fitness

64 -0.5 -0.25 0 0.25 0.5 0.75 1

Figure 3.2 Estimates of the selection coefficients (β*), indirect selection, and the selection differentials (or total selection, s*) on age and size at reproduction in wild and advanced-generation hybrid plants. A. Estimates of direct selection; B. Estimates of indirect selection; C. Estimates of total selection. Error bars represent the 95% confidence intervals of the mean.

65

0.5 0.5 Hybrid A. B. Wild 0.4 0.4

*)

β 0.3 0.3

0.2 0.2

0.1 0.1

0 0

Magnitude of indirect selection Magnitude of direct selection ( -0.1 -0.1 Age Size Age Size 0.5

C.

0.4

0.3

0.2

0.1

0 Magnitude of total selection (s*)

-0.1 Age Size

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Figure 3.3 Response to selection on age at reproduction and size at reproduction of four wild (black circles) and four advanced-generation hybrid (grey squares) populations after three generations of natural selection. Error bars represent 95% CI of the population means. Evidence of a significant response to selection is the deviation of each population average from the expected average phenotype of a randomly mating population (solid line in corresponding color) and its 95% confidence interval (shaded areas). Sample sizes as in Table B1.

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6.5 Size at reproduction 6

5.5

5

(mm) 4.5

4

3.5 Stem diameter at first flower 3 1 2 3 4

/ H / H / H / H 1 2 3 4 W W W W

Population

50 Age at reproduction

45

40

35

Age at first flower (days)

30

1 2 3 4

/ H / H / H / H 1 2 3 4 W W W W Population

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Figure 3.4 Fitness consequences of heritable variation for advanced reproduction (Early) and large size at reproduction (Large) relative to randomly mating lineages (Control) and naturally selected lineages (Natural) of wild (black bars) and hybrid plants (gray bars).

Sample sizes as in Table B2. Error bars represent the 95% CI of the mean.

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4.5 Seeds per fruit

4 3.5 3

2.5

2 1.5 1

0.5 0 Control Early Large Natural

800 Flowers per plant

700

600

500 400 300

200

100

0 Control Early Large Natural

1200 Seeds per plant

1000

800

600

400

200

0 Control Early Large Natural

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CHAPTER 4

COMPETITION ALTERS LIFE HISTORY AND INCREASES THE RELATIVE

FECUNDITY OF CROP-WILD RADISH HYBRIDS (RAPHANUS SPP.)3

4.1 Abstract

The evolutionary impact of crop-to-wild gene flow depends on the fitness of hybrids under natural, competitive conditions. We measured the performance of third- generation (F3) hybrids (Raphanus raphanistrum x R. sativus) and weedy R. raphanistrum to understand how competitive interactions affect life history and relative fecundity. Three wild and three F1 crop-wild hybrid radish populations were established in semi-natural, agricultural conditions in Michigan, USA. Two years later, we measured the effects of competition on life-history traits and fecundity of F3 progeny in a common garden experiment. Third-generation hybrid plants generally produced fewer seeds per fruit and set fewer fruits per flower than wild plants, resulting in lower lifetime fecundity.

With increasing competition, age at reproduction was delayed and relative number of seeds per fruit was reduced in wild plants, and differences between hybrid and wild fecundity diminished. Competition may enhance the fecundity of advanced-generation

3 L. G. Campbell, and A. A. Snow. 2006. Competition alters life-history traits and increases the relative fecundity of crop-wild hybrids (Raphanus spp.). New Phytologist: in press. 71

hybrids relative to wild plants by reducing differences in life history, potentially promoting the introgression of crop alleles into weed populations.

4.2 Introduction

Spontaneous hybridisation among crops and their wild relatives may promote the rapid evolution of weeds (e.g., Ellstrand et al., 1999). As recent advances in genetic engineering and breeding have introduced novel, transgenic traits into crops, ecologists have asked whether subsequent gene flow could lead to the introgression of dominant, single-gene traits into populations of wild relatives that occur near crops (e.g., in rice,

Gealy et al., 2003; sunflower, Snow et al., 2003; and squash, Fuchs et al., 2004).

Transgenic traits such as resistance to diseases, herbivores, and insects could enhance fitness in some cases and might allow weedy relatives to become more abundant (Snow et al., 2003). Meanwhile, little is known about the potential for complex, quantitative crop traits to enhance the fecundity of wild relatives. Although hybridisation with some cultivated plants may reduce the fitness of weeds in natural environments (e.g., Stewart et al., 2003), possible benefits of crop-wild hybridisation for weeds suggest this phenomenon should not be overlooked (e.g., Boudry et al., 1993; Miura & Terauchi,

2005; Chapter 5). Studies of advanced-generation hybrids find that some inter-specific hybrid genotypes persist for multiple generations under certain environmental conditions and therefore long-term gene introgression is possible (Lexer et al., 2003). Introgression may lead to trait combinations that enhance fecundity, competitiveness, and/or pest resistance, and these advantageous genotypes may be able to invade new habitats because

72

of their superior weediness (Rhymer & Simberloff, 1996; Ellstrand & Schierenbeck,

2000; Hauser et al., 2003, Whitney et al., 2006).

Performance measures of late-generation hybrids under “realistic” environmental conditions are fundamental to understanding how crop-wild hybridisation may alter the phenotype and fecundity of weeds (Lexer et al., 2003). Superior performance of crop- wild hybrids has been detected in a few cases where fecundity, number of flowers, or above-ground biomass were used as estimates of lifetime fitness (e.g., Klinger &

Ellstrand, 1994; Pertl et al., 2002; Vacher et al., 2004). Although examples of superior performance of hybrids are rare, a growing number of studies show that hybrid fitness depends on genotype, generation, and environment (e.g., Lexer et al., 2003; Campbell et al., 1998; Hauser et al., 2003). However, most studies involve only early-generation hybrids that may display either heterosis, a transient condition that may overestimate the probability of persistence of crop genes within weed populations (reviewed in Arnold &

Hodges, 1995; Arnold, 1997), or outbreeding depression, a transient condition that may underestimate the probability of persistence of crop genes within weed populations (e.g.,

Ellstrand, 1992).

The fecundity and resulting evolutionary impact of crop-wild hybrids may depend on their ability to compete with wild relatives, given that crop allele introgression will inevitably lead to populations composed of both wild and crop-wild hybrid plants

(Vacher et al., 2004). Predicting the probability of crop allele introgression and the population dynamics of weeds may be accomplished by modelling plant competition with individual performance values derived from plant competition studies (Pascual &

73

Kareiva, 1996; Damgaard, 1998). Many studies have attempted to estimate hybrid success under competitive conditions (e.g., Halfhill et al., 2005; Mercer, 2005; for more examples, see Discussion) and often conclude that, based on the relative number of seeds produced per plant, hybrids are less competitive or equally as competitive as wild taxa

(but see Hauser et al., 2003). Alternatively, the effect of competition on the population growth rates of crop-wild hybrids and wild plants may be predicted using mathematical models to provide insights into the long-term evolutionary impact of introgressed alleles

(Volterra, 1926; Damgaard 1998; Hauser et al., 2003).

Many studies of plant competitive ability, fecundity, and invasiveness have attempted to detect the life-history strategies that contribute to successful competitors and invaders (e.g., Rejmánek & Richardson, 1996; Gerlach & Rice, 2003). One approach involves comparative studies of weedy and non-weedy species (Baker, 1965; Crawley et al., 1996; Williamson & Fitter, 1996; Sutherland, 2004). However, it may be more meaningful to examine the life-history traits of a group of closely related species to determine which traits contribute to weediness (Mack, 1996; Grotkopp et al., 2002).

Specifically, identification of successful weed life-history strategies may depend on the complex interactions between the weed phenotype and environment. Small differences in the life-history traits of a plant, such as the timing of germination or reproduction, may interact with the competitive environment to influence at a small scale, plant fecundity, and at a larger scale, plant distributions and abundance (Sans et al., 2004).

In this study, we used plants from experimental populations of the weedy annual

Raphanus raphanistrum and its crop-wild hybrid offspring (R. raphanistrum x R. sativus) to investigate both the effects of competition on hybrid fitness and how fitness

74

differences between wild and hybrid plants may be altered by variation in the competitive

environment. Raphanus raphanistrum is a well-established model system in studies of plant evolution and ecology that has been used to evaluate the ecological consequences of crop-to-wild gene flow (e.g., Klinger et al., 1991; Snow et al., 2001, Hedge et al., 2006).

We estimated the competitive ability of two “biotypes”, wild R. raphanistrum and

advanced-generation crop-wild hybrids, using a response surface competition experiment.

We also explored how life-history traits and fecundity were affected by varying density

and biotype frequency. We used a path analytic approach to test a model of causal

interactions among life-history traits and fecundity (Shipley, 2000), derived from a

combination of previous path analytical studies of Raphanus (Scheiner et al., 2002) and

our own experience with this system. Finally, we discuss the potential implications of

these processes for the introgression of crop alleles into weed populations.

Specifically, we asked the following questions:

1. What is the lifetime fecundity of crop-wild hybrids relative to their wild

relatives, and under which competitive conditions is the relative fecundity of

advanced-generation hybrids maximised?

2. Is crop-wild hybrid radish as competitive as its weedy progenitor, as measured

by competition coefficients?

3. Does competition affect the relative fecundity of wild and hybrid plants by

altering their size or age at reproduction?

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4.3 Materials and Methods

4.3.1 Study system

Raphanus raphanistrum (wild radish or jointed charlock) is a widespread weed of

Eurasian origin that occurs in agricultural fields, disturbed areas, and coastal beaches

(Holm et al., 1997; Warwick & Francis, 2005). With its long-lived seed bank, early

emergence after tilling, and annual growth habit, R. raphanistrum is a difficult weed to

manage, especially in cereal crops (Warwick & Francis, 2005). Raphanus raphanistrum

grows a rosette with a thin, fibrous taproot. In Michigan, the plants “bolt” within a few

weeks after germination, when the primary flowering shoot emerges from the rosette.

Raphanus sativus, the cultivated relative of wild radish, is an open-pollinated crop with

large roots, delayed flowering, and high levels of seed production (Snow & Campbell,

2005).

Raphanus raphanistrum and R. sativus are self-incompatible, insect-pollinated,

and interfertile (Snow & Campbell, 2005). Interspecific hybrids between Raphanus

raphanistrum and R. sativus are heterozygous for a reciprocal translocation that affects

chromosome pairing during meiosis (Panetsos & Baker, 1967). Typically F1 hybrids produce approximately 50–60% aborted pollen grains (Snow et al., 2001). We found that

F1 hybrids can produce as many seeds as their wild relative (but see Snow et al., 2001),

and in some environments the fitness of advanced-generation hybrids may greatly exceed

that of their weedy progenitor (Chapter 5).

Cultivated and wild radish species were introduced into California by the 19th

century, and Panetsos & Baker (1967) suggested that “introgression of raphanistrum

characters appears to have been a major factor in converting the erstwhile crop plant, R.

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sativus, into a highly successful weed.” In fact, descendants of crop-wild hybrids, known

as wild or feral R. sativus, appear to have displaced the original populations of R.

raphanistrum in California during the past few decades (Snow et al., 2001; Hedge et al.,

2006).

4.3.2 Seed sources for experimental populations

In 2001, we collected seeds from several hundred plants in a natural population of

wild R. raphanistrum in an agricultural field in Pellston, MI, USA. In a greenhouse at

Ohio State University (Columbus, USA) we germinated and grew 100 wild plants and

hand-pollinated them with either wild pollen to create F1 wild biotypes or crop pollen to

create F1 hybrid biotypes. Crop pollen was obtained from 100 “Red silk” R. sativus

plants (Harris-Moran Seed Co., Modesto, USA), a common, contemporary variety.

Below, we refer to radish biotypes as “wild” or “hybrid” based on hybridisation in this

first generation.

4.3.3 Establishment of experimental populations

In 2002, we established three F1 wild populations (W1, W2, W3) and three F1 hybrid populatsions (H1, H2, H3), in Emmett and Cheboygan counties, MI (Fig. 4.1; part

of a larger study described in Chapter 5). The six populations were separated from each

other and from local wild radish populations by at least one km, which is far enough to

avoid unintended gene flow via pollinators (Ellstrand & Marschall, 1985). On May 20th,

2002, wild and hybrid seeds were planted in 300 mL of PRO-MIX ‘BX’ peat (Premier

Horticulture Ltd., Rivière-du-Loup, Canada) in biodegradable fiber pots that were

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maintained in a greenhouse at the University of Michigan Biological Station (UMBS),

Pellston, MI (Jiffy Products of America, Inc., Norwalk, OH, USA). Three weeks later,

each field population was created by planting 50-60 seedlings in a recently tilled 15m x

15m plot fertilised with slow-release Osmocote (19N-6P-12K, 22.7 kg per site; Scotts

Miracle-Gro Co., Marysville, OH, USA). No resident wild radish plants emerged from

the seed bank at these plots. The number of surviving experimental plants that reproduced

at each plot ranged from 42-60 in 2002, and reached several thousand plants per

population in subsequent years (Chapter 5). Each spring through 2004, the plots were

tilled, fertilised and hand-weeded for two weeks to simulate agricultural management and

to promote population persistence. Otherwise, the populations experienced natural

weather conditions, competing plants, herbivores, pathogens, and pollinators (primarily

native bees, European honey bees, and syrphid flies; as in Lee & Snow, 1998).

4.3.4 Competition experiment

4.3.4.1 Seed sources

In 2003, we collected F3 seeds directly from F2 plants growing in the three wild and three hybrid populations for the competition experiment (Fig. 4.1). We collected twenty-one seeds from ten fruits on each of 30 mothers in each population to obtain a diverse group of plants in the experiment. Hereafter, we refer to F3 hybrid plants as

‘hybrids’ or ‘advanced-generation hybrids’.

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4.3.4.2 Common garden

In a response surface competition experiment, we varied the density and frequency of each biotype independently to estimate the competitive ability of wild and hybrid biotypes by estimating their competition coefficients (Fig. 4.1; Damgaard, 1998;

Inouye, 2001). We measured the lifetime fecundity of F3 plants in a common garden at

UMBS. Plants from each wild population were paired to compete with plants from one hybrid population to determine whether interactions between biotypes depended on the pairs of source populations. Population pairs were haphazardly assigned. The response surface experiment included eleven treatments that varied both plant density and biotype frequency (Fig. 4.1). The garden was arranged in a complete randomized block design where each treatment was replicated 12 times, once per block; a total of 396 pots and

1621 plants were included in the experiment.

Seeds were planted in 22.3 mL of PRO-MIX ‘BX’ peat in seed trays in a greenhouse at UMBS in early May 2004. The emergence date of each seedling was noted. The seedling emergence dates of competing plants differed by no more than one day, so these data will not be considered further. Once seedlings had developed their first true leaves, each seedling was transplanted into a PVC bottomless tube pot (30 cm tall,

10.16 cm diameter) filled with 1.5l of local sandy soil and topped with 0.5l PRO-MIX

‘BX’ peat, allowing plant roots to grow into local soil. The garden area was cleared of vegetation, levelled and roto-tilled to promote uniform garden conditions. Pots were separated by 30 cm and the use of large tube pots minimised root competition among plants in neighboring pots. In each pot, wild plants were planted at one of four densities: zero, one, two, or four plants. In the same pot, hybrid plants were also planted at one of 79

the same four densities. Therefore, total plant density ranged from 1 plant per pot, with

no competition, to eight plants per pot (Fig. 4.1). This range represents densities seen in

natural populations of R. raphanistrum (Campbell & Snow, unpub.). Six seedlings died within the first week after transplanting and were replaced. If pots contained only one biotype, we refer to them as intra-biotype competition treatments and if they contained both biotypes, we refer to them as inter-biotype competition treatments. For the inter- biotype competition pots, seedlings were arranged such that neighbouring plants were the opposite biotype. In both intra- and inter-biotype competition pots, seedlings were planted in a circular pattern.

Plants were watered daily until August 31st and no fertiliser was added.

Insecticide (0.0033% esfenvalerate, 20g/9.5L, Scotts Miracle-Gro Co., Marysville, USA)

was used to control insect herbivory once during the first month after transplantation,

when herbivory was highest (primarily flea beetles). Aphids were present at low densities

later in the season but did not colonise any plant heavily. Pollinators were very abundant

throughout the experiment, as in Lee & Snow (1998). Plants were individually harvested

as they senesced until the first hard frost when we harvested all remaining plants

(September 16th – 20th). Harvested plants were dried at 60ºC.

4.3.4.3 Pre-competition Measurements and Analysis

To account for pre-existing conditions before exposure to competition, we asked whether

biotypes exhibited differences in seedling biomass by randomly selecting an additional

15 seedlings per wild or hybrid population and harvesting their above-ground biomass

prior to transplanting. Each sample was dried at 60˚C and weighed. A nested ANOVA

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was used to evaluate differences in pre-transplantation seedling above-ground biomass between biotypes and populations within biotypes.

4.3.5 Competition Measurements and Analysis

For each plant, we recorded age at first flower, stem diameter at first flower (an index of overall plant size), pollen fertility, flower number, fruit number, number of seeds per fruit, and above-ground vegetative biomass. Survival after transplanting was nearly

100% and will not be considered further. Twenty-five of the 1621 plants in the experiment did not flower during the growing season and those were significantly more likely to be hybrid than wild plants (rank sum test, P = 5.34 x 10-6). Plants that did not flower were removed from the following analyses. Age at first flower was calculated as the number of days between seedling emergence and anthesis. Stem diameter at first flower was used as an index of plant size because it is heritable (Campbell & Snow, unpub.) and was strongly correlated with length of longest leaf at flowering (rWild = 0.61,

P < 0.001; rHybrid = 0.62, P < 0.001) and flower number (Fig. 4.2). Stem diameter was measured on the first day of anthesis, using digital callipers at the point of attachment of the cotyledons.

To measure pollen fertility, we collected pollen from one flower on each hybrid plant and 10 wild plants per population. Because wild pollen fertility is uniformly high, a smaller sample size was justified (Chapter 5). After staining (Alexander, 1969), pollen fertility was assessed with a compound microscope as the proportion of aborted grains in samples of at least 100 grains per plant.

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To measure fruit set and fecundity, we counted number of flower pedicles and fruits per plant. Fruit set was calculated as number of fruits produced divided by number of flowers. To estimate the number of seeds per plant, we multiplied the average number of seeds per fruit (for ten randomly chosen fruits per plant) by the number of fruits.

Finally, all fruits and leaves were removed from the plants and we weighed the remaining above-ground biomass (g) of each dried plant. Above-ground vegetative biomass was strongly correlated with the number of flowers per plant for both wild (R2 = 0.95) and hybrid plants (R2 = 0.89) so we report only the number of flowers per plant (data available from the authors upon request). As plants growing in the same pot were not independent, the data used in our analyses were averages of each fitness component for each biotype within a pot. We transformed data for most measured characters because of deviations from either the assumption of normality or that of homoscedasticity for the analyses below. The transformations were chosen so as to reduce or eliminate these problems, following the suggestions of Zar (1999). Average number of seeds per fruit was normally distributed and required no transformations prior to analysis. Data on age at first flower, stem diameter at first flower, number of seeds per plant, and number of flowers per plant were natural log transformed and pollen fertility data were arcsine square root transformed to normalise the residuals. All analyses were performed using

SPSS (v.13, SPSS Inc, Chicago, USA) or SYSTAT (v. 11.00.01, SYSTAT Software Inc.,

Richmond, USA).

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4.3.5.1 Quantifying competitive ability

To summarise plant-plant interactions within and between biotypes, we estimated

the competition coefficients for each biotype from a hyperbolic competition model using

data from all eleven plant density and biotype frequency treatments. A modified version

-1 of Damgaard’s (1998) model was used: Yi = (ai +bi(Di +cijDj + eiDiDj)) where Yi

represented the number of seeds per plant type i, Di corresponded to density of plant type

i, cij symbolised the competition coefficient of biotype j on biotype i, ei signified the

correlation coefficient between yield of i and density of i, ai, and bi were shape

parameters of the effect of density on number of seeds per plant of plant type i. If cij < 1, then intra-biotype competition affects the fecundity of species j more than inter-biotype competition. If cij > 1, then inter-biotype competition affects the fecundity of species j

more than intra-biotype competition (Damgaard, 1998). Maximum likelihood estimates

of the parameters were calculated assuming normally distributed residuals using the

nonlinear regression function (Levenberg-Marquardt estimation method) in SPSS.

4.3.5.2 Effect of competitive environment on lifetime fecundity

To test for differences in lifetime fecundity between wild and hybrid biotypes

across population pairs, plant density, and biotype frequency treatments, we used an

unbalanced, repeated-measures ANOVA. Wild and hybrid plants within a pot were inter-

dependent; therefore, we used a repeated measures ANOVA, so that biotype and all its

interactions were considered within-subject factors. We used a subset of the data,

excluding pots with a density of three, because these frequencies were not represented at

any other density (Fig. 4.1). Population pair, biotype frequency, and plant density were

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considered to be fixed, between-subjects effects, block was a random, between-subjects effect, and the comparison between biotypes within a block was a fixed, within-subjects effect. In a preliminary analysis, block interactions were found to be insignificant and were removed from the final model (Campbell, unpub.). Variance of the random effect was estimated using restricted maximum likelihood methods and will not be considered further.

Pollen fertility was found to be insensitive to competition in the above analyses so we abandoned the within-pot repeated-measures design of the competition experiment.

Instead, we focused on the hierarchical design of the original field experiment; replicate wild and hybrid populations were derived from a common wild or hybrid seed source in the F1 generation and therefore population effects were nested within biotypes (Fig. 4.1).

We tested for differences in pollen fertility between wild and hybrid plants using a nested

ANOVA that included biotype and population nested within biotype as fixed effects and block as a random effect in the ANOVA model. Variance of the random effect was estimated using restricted maximum likelihood methods.

4.3.5.3 Quantifying the indirect effects of competition

Path analysis can be used to test causal hypotheses and judge their ability to predict an observed covariance structure among a set of variables (Shipley, 2000).

Models are constructed based on biological knowledge of the study system and are often used to gain insights into the biological mechanisms producing observed phenomena

(e.g., Conner et al., 1996a; Scheiner et al., 2000; Scheiner et al., 2002; Pigliucci &

Kolodynska, 2006). The path analytic approach is also compatible with the response

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surface design of our experiment, allowing us to explore the fitness consequences of a greater diversity of plant densities and hybrid frequencies that are incompatible with the conventional analysis of variance performed above. With this analysis, our goal was to examine how age at flowering, size at flowering, and lifetime fecundity were affected by hybridisation and competition treatments.

We analysed the fitness consequences of competition for each biotype separately with distinct hierarchical a priori expectations using linear path analysis (Scheiner et al.,

2000; using Procedure RAMONA, SYSTAT). Again, we used the mean phenotype values for each biotype within each pot. We began by considering a model proposed by

Scheiner et al. (2002) that described the relationships of morphological traits to measures of reproductive success in wild Raphanus sativus. In their model, plant size at flowering had a direct effect on two later characters, total number of flowers per plant and number of seeds per fruit. Age at flowering indirectly affected average number of seeds per fruit.

Finally, number of flowers per plant and number of seeds per fruit directly influenced the number of seeds per plant. We modified the model to include the particular set of traits we had measured and incorporated variables that described the competitive environment.

We allowed plant density and hybrid frequency to directly influence all traits. After an initial analysis, we removed all causal linkages deemed redundant by SYSTAT and non- significant paths (P-value > 0.1) with ρ (rho) less than 0.1. This improved the fit of our model (see below for a description of how we estimated model fit). The model fit was also improved by incorporating the effect of competitor size and age on the focal biotype size and age, even after including plant density and biotype frequency. The resulting causal model is illustrated in Fig. 4.2.

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We then estimated this causal model for both wild and hybrid datasets. In the analysis, we used data from 222 pots that contained both wild and hybrid plants (i.e., only inter-biotype competition conditions) and for which we had records for all traits. To quantitatively summarize the relative importance of the indirect pathways to lifetime fecundity, we multiplied together causally linked path coefficients. In each case, model performance was evaluated by criteria based on the SYSTAT output. The root mean square error of approximation (RMSEA) assesses a given model’s fit to the observed covariance matrix while accounting for the number of parameters embedded in the model itself (0 < RMSEA < 1). We also report Akaike’s information criterion (AIC) values for two models, our model and a saturated model. The saturated model is similar to the model being tested but it includes all possible paths from each variable to every other variable, yielding an over-parameterised model with the maximum possible fit. If the tested model captured the causal structure sufficiently well, its AIC is expected to fall within the confidence interval of the saturated model.

4.4 Results

4.4.1 Competitive ability of wild and hybrid plants

Wild plants generally produced more seeds per plant than hybrids (Fig. 4.3).

Based on lifetime seed production, the competitive coefficient of wild plants on the fecundity of hybrid plants was 1.63 (95% CI: 1.15 – 2.11), a significantly greater value than the competitive coefficient of hybrid plants on wild plants, which was 0.59 (95% CI:

0.41 – 0.76) (See Table 4.1 for estimates of other parameter estimates). These values suggest that the competitive ability of one hybrid plant is approximately equivalent to a

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fraction (~0.6) of one wild plant. In other words, hybrid competitors had a significantly

larger negative effect on the fecundity of hybrids than on wilds, and the same was true for

wild competitors.

4.4.2 Response of life-history traits and lifetime fecundity to competition

Before competition occurred, hybrid plants exhibited an early advantage over

wild plants. Seedling biomass differed significantly among populations within biotypes

-6 (Table 4.2, F4,203 = 8.16, P = 4.0 x 10 ) and advanced-generation hybrid seedlings had

greater biomass than wild seedlings (Table 4.2, F1,4 = 7.49, P = 0.05).

The pollen fertility of hybrids was significantly lower than that of wild plants (F1,4

= 12.1, P = 0.025; Table 4.3). Pollen fertility did not differ among competition treatments

(Plant density: F3,2 = 0.03, P = 0.99; Hybrid frequency: F1,2 = 0.08, P = 0.80; Density x

Frequency: F1,2 = 0.01, P = 0.93), nor among source populations within biotypes (F4,261 =

1.43, P = 0.16).

Wild and hybrid plants differed significantly in life history and lifetime fecundity

(Fig. 4.3). Hybrids flowered significantly later (P < 0.001), and grew to a larger stem diameter before flowering than wild plants at most densities (P < 0.001, Fig. 4.3, Table

4.4, 4.5). Flower number was not significantly different between wild and hybrid plants

(P > 0.10). Yet, wild plants produced more seeds per plant than hybrids (P < 0.001),

perhaps because they set more fruits per flower (P < 0.001) and more seeds per fruit than

hybrids (P < 0.001, Table 4.4).

As plant density increased, the differences between biotypes in age and size at

flowering, and seeds per fruit were diminished (Fig. 4.3, Table 4.4, 4.5). Increased

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density delayed age at flowering in wild plants but not hybrid plants (P < 0.001) and simultaneously reduced size at flowering more in hybrid plants than wild plants (P <

0.001). Hybrid plants responded to inter-biotype competition conditions by flowering significantly earlier and becoming marginally significantly smaller than in intra-biotype competition conditions whereas wild plants did not (Age at flowering: P < 0.001, Size at flowering: 0.05 < P < 0.10). Finally, the number of seeds per fruit and fecundity of hybrid plants was less sensitive to changes in density and competition type than wild plants (Seeds per fruit: P < 0.01; Seeds per plant: 0.05 < P < 0.10, Table 4.4, Fig. 4.3).

This result reveals that hybrid plants responded to competitive conditions differently than wild plants. The fitness consequences of these life history and fecundity responses to competitive conditions are explored further in the path analysis below.

4.4.3 Indirect effects of competition on lifetime fecundity

As R. raphanistrum and wild R. sativus are model organisms for plant population biology, it was feasible to build a causal model relating life-history traits to lifetime fecundity in a way that would allow us to predict, with reasonable accuracy, the observed covariance matrices for both wild R. raphanistrum and hybrid plants grown across a gradient of competitive environments. Judging from a variety of indices, our models fit the data reasonably well (RMSEAWild = 0.08 [95% CI: 0.032–0.125]; RMSEAHybrid =

0.075 [95% CI: 0.034–0.114]; See Appendix 4.6 for other estimates).

The path analyses of wild and hybrid focal plants were very similar (Fig. 4.2), with generally small, non-significant differences in the magnitudes of the path coefficients (Fig. 4.2c). Further, the magnitudes of path coefficients shared by the two

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models (e.g., Density → Hybrid age) were statistically similar, again suggesting that the models were robust (Fig. 4.2c). Increased density generally delayed flowering and decreased plant size. This led to reductions in the number of flowers per plant and the number of seeds per fruit, both of which were positively correlated with the number of seeds per plant.

Although wild and hybrid plants generally responded similarly to competition, path analysis revealed a few key differences (Fig. 4.2). Density was more strongly correlated with size at flowering in hybrid (ρ = -0.64) versus wild plants (ρ = -0.29).

Further, size at flowering and age at flowering were more strongly correlated in hybrid (ρ

= 0.66) versus wild plants (ρ = 0.52). Yet, density was more strongly correlated with age at flowering in wild (ρ = 0.52) versus hybrid plants (ρ = 0.27). Finally, age at flowering was more strongly correlated with number of seeds per fruit in hybrid (ρ = -0.49) versus wild plants (ρ = -0.35). The differences observed between wild and hybrid path diagrams may provide biological mechanisms to explain the relative increase in hybrid fitness with increased density found with the above analysis of variance. Specifically, several life history traits of wild and hybrid plants differed in their response to competition.

The path analysis revealed direct effects of competition conditions on the life history of wild and hybrid plants and direct and indirect effects of changes in life history on the lifetime fecundity of wild and hybrid plants (Fig. 4.2, Table 4.7). In wild plants, the magnitude of the direct effect of density was larger on age at reproduction than size at reproduction whereas the opposite was true for hybrid plants. Interestingly, for both biotypes, the trait least sensitive to changes in density had the largest direct effect on lifetime fecundity. Indirect effects of age and size at reproduction on lifetime fecundity 89

were small for both wild and hybrid plants. Consequently, the total effect of age and size at reproduction on lifetime fecundity largely reflected their direct effects on lifetime fecundity (Fig. 4.2, Table 4.7).

4.5 Discussion

Our study shows that competitive conditions may increase the evolutionary impact of advanced-generation crop-wild hybrids through indirect effects on life history traits. These traits include age and size at flowering, and seeds per fruit (i.e., clutch size).

Based on lifetime fecundity, hybrids had less competitive impact on wild plants than the competitive effect of wild plants on hybrids (Table 4.4, Fig. 4.3). As expected, increased density reduced the fecundity of wild and hybrid plants (Table 4.4), a result consistent with previous competition studies of Raphanus (Uthus, 2001; Wolfe & Mazer, 2005).

However, increasingly competitive conditions had a greater negative effect on the lifetime fecundity of wild plants than on hybrid plants (Table 4.4: Biotype x Density x

Hybrid freq. Interaction). Therefore, relative hybrid fecundity was maximised under more intense competitive conditions (Fig. 4.3).

A common purpose of competition experiments is to anticipate the dynamics of natural plant communities. The probability of species coexistence is estimated using a competition model under a range of simplified environments and is encapsulated by the competition coefficient parameter (Damgaard, 1998; Inouye, 2001). Estimating competition coefficients may improve predictions of persistence of crop alleles within weedy populations across generations and the success of hybrids within weedy populations over a growing season. Yet, despite the abundance of empirical studies on

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the effect of competition on crop-wild hybrid fecundity (Table 4.8), only one other study

has expressed hybrid competitive ability in terms of competition coefficients (Hauser et

al., 2003). Hauser et al. (2003) found that the competitive ability of F1 hybrids (Brassica rapa x B. napus) was greater than that of the wild parents (cwild,hybrid = 5.80, chybrid,wild =

0.12), in contrast to our study. High competitive ability of early-generation hybrids will

be important to the early stages of crop gene introgression; however, the persistence of

crop genes within weed populations also depends on the competitive ability of advanced-

generation hybrids when growing near its wild relative as well as with other weed species

(e.g., Vacher et al., 2004). Further, the accuracy of competition models in predicting

community dynamics will be limited by the ability of experimental designs to represent

the complexity of field conditions, including differential herbivory, seed longevity,

emergence dates, and multi-species communities.

Highly competitive conditions, like those one might find in a natural weed

population, may facilitate the introgression of crop alleles into weedy populations by

increasing the relative fecundity of hybrids (Fig. 4.3). In the literature, this is a common

but under-appreciated result (Table 4.8). When crop-wild hybrid performance is

compared to wild taxa under increasingly competitive conditions, the difference between

hybrid and wild genotypes is often reduced by competition (e.g., Snow et al., 1998;

Uthus, 2001; Guéritaine et al., 2002, Mercer, 2005; Halfhill et al., 2005). However, in

this collection of studies, imposing competition on hybrid plants rarely, if ever, reversed

the relative performance of hybrids compared to their wild relative (Table 4.8). That is,

hybrids that possessed reduced relative fitness without competition do not exhibit

superior fitness under competitive conditions. These results suggests that hybrid success

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in natural populations is unlikely to be limited by density alone but that hybrid relative fitness may be promoted by increased density.

Although hybrids were generally poor competitors, as described by their competition coefficient, their relative performance was enhanced when grown in mixed pots of wild and hybrid plants rather than purely hybrid pots. This, too, is a common result of competition studies (Table 4.8). Typically, hybrids of several crop-wild complexes, under at least some densities, tend to be more successful, although not superior, under inter-biotype versus intra-biotype competition conditions (e.g., Van gaal et al., 1998; Pertl et al., 2002; Hauser et al., 2003; Al-Ahmad & Gressel, 2006).

Although our analysis of variance was limited to two frequencies (50% and 100%), the path analysis confirmed this trend continues when hybrids are grown under other hybrid frequencies (33% and 66%). Under inter-biotype competition, the hybrids initiated reproduction at a smaller size and assumed a more “wild-like” appearance than under intra-biotype competition. These findings suggest that the rate of introgression in wild populations will be highest when hybrids grow in mixed populations. This finding supports previous hypotheses about the evolution of weedy R. sativus in California.

Panetsos & Baker (1967) speculated that hybridisation with R. raphanistrum allowed cultivated radish to evolve into “a highly successful weed.” Recently, Hegde et al.

(2006) used field observations, morphological data, and allozyme frequencies to conclude that hybrid populations of crop-wild genotypes have displaced ancestral populations of weedy R. raphanistrum in California. This suggests that the relative fitness of crop-wild hybrids within wild radish populations was sufficiently high so as to promote coexistence of biotypes and crop allele persistence.

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Although the effect of competition on the relative fecundity of our crop-wild hybrids was apparent from an analysis of variance, the results of the path analysis contributed several novel insights into the indirect, but causal, consequences of competition on relative hybrid performance via its effects on life history (Fig. 4.2). While the phenotypic correlations of wild and hybrid plants often responded similarly to density, we were able to detect key differences that may ultimately have led to differences in the response of fecundity to density treatments. Age at flowering in wild plants was more sensitive to changes in density than hybrid plants. The delay in flowering induced by high density in wild plants resulted in a significant decrease in number of seeds per fruit in wild plants and ultimately a reduction in lifetime fecundity of wild plants. At the same time, size at flowering in hybrids was more sensitive to changes in density than wild plants and was significantly reduced at high densities, suggesting that hybrids tended to advance flowering, increase seeds per fruit and flower production at high density. Therefore, increasing density altered life history, resulting in wild plants that more closely resembled hybrid plants and vice versa. In future studies, it will be important to incorporate more life-history traits, including timing of germination and seedling growth, in order to fully understand the competitive dynamics between wild and hybrid plants within a population (Guéritaine et al., 2003; Hooftman et al., 2005).

Competition had a dramatic effect on the life history of both wild and hybrid plants. Although hybrids began as bigger seedlings they had less competitive impact on neighbours than wild plants. This suggests that competitive dominance may be due to different patterns of resource allocation, further reinforcing the idea that changes in life- history are likely to change performance. Another intriguing result, emerging from both

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path analyses and ANOVA, was that greater density significantly delayed flowering in wild plants but not in hybrids, and that increased density decreases size at flowering more in hybrid plants than wild ones. These results suggest that hybridization may alter both the average phenotype of weeds and the plasticity of those traits (Pigliucci &

Kolodynska, 2006).

In summary, we demonstrate through both experimental manipulations and literature review that competition may indirectly impact the relative performance of hybrids and their wild relatives, via its effect on life history, potentially enhancing hybrid fitness in weed populations. We suggest that subsequent competition experiments evaluate those life-history traits most affected by competition and the consequences of plant-plant interactions for the introgression of crop traits into wild populations. Studies that consider the effect of competition on both absolute and relative hybrid fecundity will provide more comprehensive predictions of the ecological consequences of crop gene introgression into wild populations (Damgaard, 1998; Lexer et al., 2003).

4.6 Acknowledgements

The Bonnett, Dotski, Hartman, Phelps, Schreier and Stempky families generously shared their farmland. We thank the staff of the UM Biological Station, J Leonard, J

Ketner, M Schneider and A Babayan for their help in the field and lab and T Waite for statistical advice. The US Department of Agriculture (Grant #2002-03715), UMBS, OSU

Presidential Fellowship, Nature Conservancy of Michigan, Janice Carson Beatley

Endowment and Sigma Xi supported this research. Many thanks to the Snow lab group for suggestions that greatly improved the ms.

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4.7 Tables

Biotype Parameter Value (95% CI) Wild Competition coefficient (c hybrid,wild) 1.63 (1.15 – 2.11) Correlation between Yield and density of wild -0.30 (-0.42 – -0.18) plants (e hybrid,wild) a 0.15 (0.14 – 0.16) b 0.017 (0.012 – 0.021) Hybrid Competition coefficient (c wild, hybrid) 0.59 (0.41 – 0.76) Correlation between Yield and density of hybrid -0.15 (-0.21 – -0.09) plants (e wild, hybrid) a 0.14 (0.13 – 0.15) b 0.025 (0.018 – 0.032)

Table 4.1. Maximum likelihood estimates of the competitive coefficients and model estimates of wild and hybrid biotypes as measured by the number of seeds produced per plant. In parentheses, we present the 95% confidence intervals for each parameter estimate.

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Biotype Population N Pre-competition Biomass (mg) (SE) d Wild W1 15 10.1 (0.8) c W2 15 15.2 (0.7) c W3 15 14.8 (0.7) Average W 45 13.6 (0.4)

b Hybrid H1 15 17.5 (1.1) a H2 15 22.2 (1.1) b H3 15 17.7 (1.0) Average H 45 18.9 (0.6)

Table 4.2. Pre-competition seedling biomass of wild and advanced-generation crop-wild hybrid plants. Superscripts indicate significant differences among populations within a biotype. Population averages are presented with number of samples (N) and estimates of standard error (SE).

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Biotype Population N Pollen fertility (%) (SE) a Wild W1 13 81 (5) a W2 11 86 (3) a W3 15 83 (4) Average W 39 83 (1)

b Hybrid H1 125 72 (2) b H2 124 73 (2) b H3 132 68 (2) Average H 381 71 (1)

Table 4.3. Percentage of pollen grains that are fertile in wild and advanced-generation crop-wild hybrid plants. Superscripts indicate significant differences among populations within a biotype. Population averages are presented with number of samples (N) and estimates of standard error (SE).

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Source dfH,E

eter

er w diam plant flo Fruit set Flowers / Age at first Seeds / fruit Seeds / plant F F Stem F F F F Between-subjects effects: Hybrid freq. 1, 10 1.34 ns 2.85 ns 3.29 + 1.76 ns 0.22 ns 3.93 + Density 81.55 93.96 9.17 * 134.17 3, 10 3.84 * 4.63 * *** *** *** Pop. Pair 2, 10 4.09 * 2.31 ns 3.89 + 20.85 * 0.12 ns 2.68 ns Hybrid freq. × 0.18 ns 8.03 + 1, 10 0.16 ns 1.58 ns 0.07 ns 1.70 ns Density Hybrid freq. × 0.84 ns 5.28 + 10, Pop. Pair × 1.68 ns 0.95 ns 1.49 ns 0.71 ns 184 Density Within-subjects effects: Biotype 101.73 150.38 195.34 120.79 32.53 1, 10 1.48 ns *** *** *** *** *** Biotype × Hybrid 3.76 + 1, 10 11.00 *** 0.08 ns 5.41 ns 2.37 ns 0.69 ns freq. Biotype × Density 3, 10 4.42 *** 9.00 ** 0.50 ns 3.78 ns 1.87 ns 0.05 ns Biotype × Pop. 0.70 ns 2, 10 0.70 ns 2.32 ns 1.42 ns 0.58 ns 1.97 ns Pair Biotype × Density 3.61 + 1, 10 7.35 ** 0.14 ns 6.04 + 8.72 ** 4.32 + × Hybrid freq. Biotype × Density 10, × Hybrid freq. × 0.20 ns 0.82 ns 1.33 ns 2.05ns 0.54 ns 1.10 ns 184 Pop. Pair

Table 4.4 A comparison of life-history traits and lifetime fecundity of wild and hybrid populations grown in a competition experiment in Michigan. We performed a repeated measures ANOVA for each trait for two biotypes (Within-subjects effect). Three populations of wild plants were paired to compete with three populations of hybrid plants (Pop. Pair). Plants were exposed to variation in plant density (Density = 1, 2, 4, or 8 plants per pot) and hybrid frequency (Hybrid freq. = 100% hybrid plants per pot or 50% hybrid plants per pot). F statistics are presented; to indicate significant differences: ns represents p > 0.10, + represents p < 0.10, * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001.

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Table 4.5 Summary statistics of several key life-history traits and fitness components for

F3 wild (W) and hybrid (H) plants. Plants were grown in a common garden at three plant densities and three biotype frequencies (intrawild–, intrahybrid– and inter–biotype) after experiencing natural conditions as three populations (Pop.) per biotype in Michigan for two years. Each site was represented by N plants per treatment.

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Pop. Hybrid Density N Age at Stem Average no. No. of Fruit set No. of seeds pair frequenc first diameter of seeds per flowers (SE) (%) (SE) (SE) y flower at first fruit (SE) (days) flower (SE) (mm) (SE) Wild Hybrid Wild Hybrid Wild Hybrid Wild Hybrid Wild Hybrid Wild Hybrid

0 or 100 % 47 8.6 11.6 4.4 3.4 389 494 40 599 638 1 10 57 (5.1) 34 (5) (2.4) (1.1) (1.3) (0.6) (0.4) (53) (74) (4) (89) (154) 45 5.6 5.0 3.9 177 208 42 352 259 2 12 61 (5.6) 8.5 (0.9) 28 (2) (1.6) (0.4) (0.4) (0.3) (16) (33) (3) (56) (46)

1 45 4.0 4.1 3.0 102 160 43 182 123 4 11 68 (4.4) 6.4 (0.4) 25 (2) (0.9) (0.2) (0.2) (0.3) (9) (21) (2) (24) (16) & W

1 50% 44 5.1 4.3 3.3 158 318 47 290 283 2 12 55 (4.3) 8.9 (1.2) 32 (3) H (2.6) (0.5) (0.4) (0.4) (31) (63) (5) (64) (55) 47 4.1 3.6 3.0 110 136 42 197 4 12 59 (3.1) 5.5 (0.3) 25 (2) 86 (11) (1.6) (0.4) (0.3) (0.3) (17) (23) (2) (35) 48 4.1 3.7 3.2 57 42 95

8 12 69 (3.6) 4.3 (0.3) 78 (13) 27 (2) 57 (6) (1.6) (0.3) (0.3) (0.2) (12) (3) (21) 0 or 100 % 45 6.8 12.9 4.8 3.7 307 354 46 611 436 1 12 60 (4.9) 33 (3) (2.6) (0.5) (1.4) (0.5) (0.3) (40) (38) (4) (67) (79) 43 5.1 4.3 3.1 210 232 48 422 216 2 12 61 (4.3) 9.3 (0.5) 30 (2) (1.9) (0.4) (0.3) (0.3) (32) (26) (2) (76) (19)

2 44 4.3 4.5 2.6 115 45 223 118 4 11 67 (2.5) 6.6 (0.4) 94 (15) 36 (3) (1.5) (0.1) (0.2) (0.3) (14) (3) (44) (23) & W

2 50% 49 5.3 10.2 4.9 3.0 212 193 58 564 181 2 13 69 (5.6) 31 (4) H (2.1) (0.4) (1.2) (0.4) (0.3) (52) (47) (11) (212) (46) 46 4.9 3.4 3.2 105 149 44 168 123 4 12 56 (4.2) 5.2 (0.3) 29 (2) (1.9) (0.5) (0.2) (0.4) (17) (19) (2) (25) (16) 47 4.2 3.5 3.3 48 39 76

8 13 59 (3.1) 3.9 (0.2) 83 (15) 34 (2) 78 (16) (1.3) (0.2) (0.2) (0.3) (7) (3) (11) 0 or 100 % 39 6.2 10.7 5.5 4.2 533 449 50 1379 551 1 11 49 (4.7) 36 (3) (1.3) (0.5) (1.5) (0.6) (0.7) (102) (58) (3) (308) (46) 42 5.2 4 3.4 211 311 44 360 367 2 11 62 (3.3) 8.8 (0.9) 36 (4) (1.9) (0.4) (0.3) (0.3) (16) (52) (3) (44) (70)

3 42 4.2 3.9 2.7 130 140 41 196 125 4 12 61 (3.6) 6.1 (0.3) 33 (3) (0.9) (0.2) (0.2) (0.2) (12) (11) (2) (23) (20) & W

3 50% 40 5.1 4.3 3.3 239 228 48 452 172 2 11 56 (7.1) 7.5 (0.9) 27 (3) H (1.6) (0.4) (0.4) (0.5) (48) (59) (5) (96) (25) 41 66 (6.0) 4.6 5.3 (0.5) 4.0 3.3 106 133 43 190 137 4 11 37 (4) (1.3) (0.3) (0.4) (0.3) (15) (13) (2) (20) (22) 46 61 (2.8) 4.2 4.2 (0.3) 3.4 3.3 64 108 41 117

8 11 31 (1) 90 (32) (1.4) (0.2) (0.2) (0.3) (18) (37) (3) (42) 0 or 100 % 43 55 (2.8) 7.1 11.7 4.9 3.8 408 429 46 863 536 1 33 35 (2) (1.4) (0.4) (0.8) (0.3) (0.3) (43) (33) (2) (124) (56) 44 61 (2.6) 5.3 8.8 (0.4) 4.5 3.5 199 250 44 379 281 2 35 33 (2) (1.0) (0.2) (0.2) (0.2) (13) (23) (2) (35) (30) 44 65 (2.1) 4.2 6.4 (0.2) 4.2 2.8 115 132 41 200 122 4 34 31 (1) (0.7) (0.1) (0.1) (0.2) (7) (10) (1) (18) (11) 50% 45 61 (3.4) 5.2 8.9 (0.7) 4.5 3.2 203 244 51 443 211 36 30 (2) Average 2 (1.4) (0.2) (0.2) (0.2) (26) (33) (5) (87) (27) 45 60 (2.6) 4.5 5.3 (0.2) 3.7 3.2 107 140 41 185 115 4 35 33 (2) (1.0) (0.2) (0.2) (0.2) (9) (11) (1) (16) (10) 8 36 47 63 (1.9) 4.1 4.1 (0.1) 3.5 3.3 56 34 95

89 (13) 34 (2) 75 (11) (0.8) (0.1) (0.1) (0.2) (7) (1) (15)

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Biotype RMSEA Confidence Saturated Model AIC interval for AIC (95% CI) RMSEA (P-value) Wild 0.081 0.032 – 0.125 0.570 0.573 (0.087) (0.475–0.737) Hybrid 0.075 0.034 – 0.114 0.407 0.425 (0.098) (0.354–0.542)

Table 4.6 Summary statistics for the fit of the path analytic models for each biotype. The root mean square error of approximation (RMSEA) together with its 95% confidence interval and P-value is a measure of the fit between the observed covariance matrix and the one predicted by the model (where a good fit is indicated by RMSEA values close to zero; range = 0 to 1). The fit of the tested model is also measured by a comparison of its

Akaike Information Criterion (AIC) value is to the AIC of the saturated model; if they are similar, as measured by the 95% CI of the Model AIC, then the proposed model is a good fit to the data. For the wild and hybrid models being compared, ‘saturated’ refers to a model with all paths allowable, which has no degrees of freedom and perfect fit; ‘model’ is the partially constrained path analytical model actually being tested.

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Direct Indirect Total Age Age Age Size Size Size Lifetime Lifetime Lifetime fecundity fecundity fecundity Causal factors A) Wild: Density 0.417 -0.138 -0.341 – – – 0.417 -0.138 -0.341 Age – – -0.244 – 0.466 -0.027 – 0.466 -0.271 Size 0.466 – 0.301 – – 0.034 0.466 – 0.335 B) Hybrid: Density 0.268 -0.635 -0.483 – – – 0.268 -0.635 -0.483 Age – – -0.413 – 0.660 -0.062 – 0.660 -0.475 Size 0.660 – 0.192 – – -0.004 0.660 – 0.188

Table 4.7 Indirect effects of plant density (Density) and focal plant age (Age) and size

(Size) at reproduction on focal plant age and size at reproduction, and lifetime fecundity calculated for wild and F3 hybrid plants using the path analytic models in Figure 4.2.

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Table 4.8 Summary of 12 competition studies of fecundity of crop-wild hybrids relative

to their wild parent. Studies were included only if they concerned hybrids between a

cultivated and wild relative and if they measured hybrid seed production under intra- and

inter-biotype competition environments. Gen. = Hybrid generation studied. With/Without

= comparisons were made between competitive environments with either no competition

or some competition, RP = replacement series, A= additive series [density varied but no

frequency treatments], Hexagonal = Hexagonal plot design for a neighborhood

competition experiment, RS = response surface where density and frequency of biotypes

were varied independently of each other. Traits measured: S = Number of seeds, F =

Number of flowers or flower heads, B = Above-ground biomass. No data = The

comparison was not made in the study, Similar = fitness of hybrid was similar to wild

plant, Reduced = hybrid fitness was lower than wild fitness, Greater = hybrid fitness was

higher than wild fitness, Lower = Hybrid relative fitness was lower under inter-biotype

competition conditions than under intra-biotype competition conditions, Same = Hybrid

relative fitness was unaffected by type of competition environment, Higher = Hybrid

relative fitness was higher under inter-biotype competition conditions than under intra-

biotype competition conditions. a In this study, the effect of competition was confounded with the effect of site since the without and without studies were conducted in two different locations. b In this study, the two biotypes were both hybrids – IMI- resistant

and IMI-susceptible hybrids of H. annuus and H. annuus or H. petiolaris. c Hybrids

contained the Bt transgene. d Hybrids were transgenically mitigated with a dwarfing gene

e intended to reduce their fitness. This study included no pure plots of F1’s however there

were plots that had higher and lower frequencies of hybrids. At high density, hybrids had

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higher fitness under inter-biotype competitive conditions and at low density, hybrids had

lower fitness under inter-biotype competitive conditions. f In this study, the effect of

competition was confounded with the effect of site since competition was imposed in the

field while the without competition study was performed in a greenhouse.1 Snow et. al.

1998, 2 Massinga et al. 2005, 3 Mercer 2005, 4 Van gaal et al. 1998, 5 Guéritaine et al.

2002, 6 Pertl et al. 2002, 7 Guéritaine et al. 2003, 8 Hauser et al. 2003, 9 Vacher et al.

2004, 10 Halfhill et al. 2005, 11 Al-Ahmad and Gressel 2006, 12 Uthus 2001, 13 Campbell

& Snow this ms.

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. ype spp nt T e itness under m Gen. itness highest i ing density Family which type of y id f id f competition competition? Wild relative xper Cultivated var Traits measured E under Hybr to wild with no / low Hybr Hybrid fitness relative

Helianthus H. annuus F1 A F Reduced Higher with annuus1a competition 2b H. annuus H. annuus, F1 RP S No data Same 2b H. annuus H. petiolaris F1 RP S No data Same 3 teraceae H. annuus H. annuus F1 A S Reduced Higher with

As competition Echinacea E. purpurea F1 A B, Similar Highest at medium Inter purpurea4 F density Brassica R. BC6napus A S Reduced Higher with napus5 raphanistrum competition 5 B. napus R. BC6 raph A S Similar Highest at low raphanistrum density 6 B. napus B. rapa F1 RS S, Condition- Frequency- See PA dependent, dependent, Higher below e Lower under low density 7 B. napus R. F1 A B Reduced Higher without raphanistrum competition 7 B. napus R. F1 A B Reduced Highest at low raphanistrum density 8 g B. napus B. rapa F1 RS S Condition- Highest at high Inter dependent density 8 B. napus B. rapa BC1rapa RS S Density- Highest at low Intra dependent density 8 B. napus B. rapa BC1napus RS S Reduced Highest at low density 8 caceae i B. napus B. rapa F2 RS S Density- Highest at low s dependent density 8 Bras B. napus B. rapa BC2rapa RS S Reduced Highest at intermediate density 9 B. napus B. rapa F1 A B Greater Highest at high density 10c B. napus B. rapa BC2F2 A B Reduced Higher with competition 11 B. napus B. rapa F2 RP S Reduced Inter 11 B. napus B. rapa F2BC1 RP S Reduced Inter 11d B. napus B. rapa F2 RP S Reduced Inter 11d B. napus B. rapa F2BC1 RP S Reduced Inter 12 R. sativus R. F1 A S Reduced Higher with raphanistrum competition 12 R. sativus R. BC1 A S Reduced Higher with raphanistrum competition 13 h R. sativus R. F3 RS S Reduced Higher with Same raphanistrum competition

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4.8 Figures

Greenhouse Experimental Competition experiment

populations 2004 2001 F3 F0 2002 2003 No. Hybrid No. Wild / pot C♂ F1 F2 × / pot 0 1 2 4 W♀ H1 H2 H3 H1 H2 H3 0 - 1 2 4 × W1 W2 W3 W1 W2 W3 1 1 2 3 - W♂ 2 2 3 4 - 4 4 - - 8

Figure 4.1. Schematic diagram of the experiment. The first-generation (F1) was created by cross-pollinating wild plants (W) with either wild or cultivated (C) radish pollen to create wild and hybrid (H) biotypes. Six isolated field populations of wild biotypes (W1 –

W3) or hybrid biotypes (H1 – H3) were maintained for three years; small squares represent populations of the two biotypes. In 2004, a response surface competition experiment with plant density (1, 2, 4 plants per biotype) and biotype frequency treatments (inter- biotype, intra-biotypeWild, or intra-biotypeHybrid) was composed of F3 plants from each population. In the competition experiment, dark grey squares represent competition treatments and light grey squares represent no competition treatments. The numbers within the matrix positions describing the replacement series competition experiment represent the number of plants per growth container.

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Figure 4.2. Direct and indirect effects of plant density and biotype frequency on age and size at flowering and lifetime fecundity of F3 (a) wild and (b) hybrid plants. In the solved path diagram for maximum likelihood linear analysis of hybrid relative performance, dashed lines indicate negative coefficients and the width of the arrow indicates the strength of the effect (ρ). Significant effects are presented as black lines. Non-significant effects are presented as grey lines. Figure (c) compares the strength of the correlation (ρ) between models (a) and (b). Error bars represent the 95% CI of the mean and non- overlapping CI indicate a significant difference in the strength of the relationship. This analysis included only inter-biotype competition conditions.

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Figure 4.2, cont.

ρ ≤ 0.2 (a) Focal biotype = Wild 0.2 < ρ ≤ 0.4 Hybrid 0.4 < ρ ≤ 0.6 age Wild number of 0.6 < ρ ≤ 0.8 seeds per fruit ρ > 0.8 Wild age Frequency Wild number of seeds Density Wild size Wild number of flowers Hybrid size (b) Focal biotype = Hybrid

Wild age Hybrid number of seeds per Hybrid fruit Frequency age

Hybrid number of seeds Density Hybrid size Hybrid number of flowers

Wild size

Continued

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Figure 4.2, cont.

(c) Comparison of Wild and Hybrid responses to competition Focal biotype = Wild Focal biotype = Hybrid

Density W size

Density Hsize Density W age Density H age

H frequency W size H frequency H size

H frequency W age ys wa H frequency H age th W size W age al pa

us H size H age

Ca Competitor size Focal Age Competitor size Number of flowers

Competitor age Focal Age Density Number of flowers Age Number of flowers

Size Number of flowers

Age Seeds per fruit Number of flowers Number of seeds Seeds per fruit Number of seeds 0 1 -1 0.2 0.4 0.6 0.8 -0.8 -0.6 -0.4 -0.2

Path coefficient, ρ

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Figure 4.3 Comparison of life-history traits and lifetime fecundity of wild and hybrid plants grown under intra-biotype (Hybrid frequency = 0% or 100%) and inter-biotype competition conditions (Hybrid frequency = 50%) at four plant densities. Bars represent trait means; error bars represent the SE of the mean. Since populations did not differ significantly for most traits, estimates of relative fecundity are based on averages of 36 pots per biotype where population is pooled (n ≈ 36 individuals per biotype, biotype frequency and plant density).

110

70 13

g Biotype

) s Wild y 11 60 da Hybrid (

g 9

50 7 e at flowerin 40 g 5 A

Stem diameter at flowerin

30 3 500 60

lant p 400 50

er p 300 40 200 Fruit set (%) 30 100

Number of flowers 0 20 6 1000

800 5 er fruit p 600 4 400

3 Number of seeds 200

Number of seeds

2

0 . - - - r r r p Intra- Inte Intra- Intra- Inter- Intra- Inter- Inter- Inte Inte Type of competition Type of competition No comp. No com

1 2 4 8 1 2 4 8 Plant density Plant density

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CHAPTER 5

WEED EVOLUTION AFTER CROP GENE INTROGRESSION: GREATER

SURVIVAL AND FECUNDITY OF HYBRIDS IN A NEW ENVIRONMENT4

5.1 Abstract

Crop-wild hybridization may produce offspring with lower fitness than their wild parents due to deleterious crop traits and outbreeding depression. Over time, though, selection for improved fitness could lead to greater invasiveness of hybrid taxa. To examine evolutionary change in crop-wild hybrids, we established four wild (Raphanus raphanistrum) and four hybrid radish populations (R. raphanistrum × R. sativus) in

Michigan, USA. Hybrid populations exhibited increased pollen fertility and similar population growth rates to wild populations across four generations. We then measured hybrid and wild fitness components in two common garden sites within the geographic range of wild radish (Michigan and California). Advanced-generation hybrids had slightly lower lifetime fecundity than wild plants in Michigan, but exhibited ~270% greater lifetime fecundity and ~22% greater survival than wild plants in California. Our results support the hypothesis that crop-wild hybridization may create genotypes with the potential to displace parental taxa in new environments.

4 L. G. Campbell, A. A. Snow, and C. E. Ridley. 2006. Weed evolution after crop gene introgression: greater survival and fecundity of hybrids in a new environment. Ecology Letters 9: 1198-1209. 112

5.2 Introduction

Weed populations can evolve rapidly when confronted with novel environments

(e.g., Clements et al. 2004), and a better understanding of the mechanisms and rates of weed evolution could aid in limiting or at least anticipating this process. Hybridization may contribute to adaptive evolution, and specifically weedy plant evolution, in two ways

(e.g., Anderson & Stebbins 1954, Ellstrand & Schierenbeck 2000). First, hybridization may generate novel adaptations via transgressive segregation. When segregating hybrids exhibit extreme phenotypes, rapid and adaptive phenotypic shifts may enhance the fitness of weedy hybrid lineages in certain environments (Rieseberg et al. 1999, Lexer et al.

2003a). Second, hybridization may transfer adaptations that could lead to range expansions and extensive weed invasions (e.g., Ellstrand & Schierenbeck 2000) and/or increased fecundity and weediness of local populations (Ellstrand et al. 1999, Snow et al.

2003).

Many studies have attempted to quantify the fitness implications of hybridization between crops and weeds (reviewed by Ellstrand 2001, Hails & Morley 2005). However, inferences about the fitness of advanced-hybrid generations often remain tentative because most experimental studies have used F1 hybrids, which may exhibit transient heterosis or hybrid breakdown (Burke & Arnold 2001, Arnold & Hodges 1995, Lexer et al. 2003b, Rhode & Cruzan 2005). Ideally, experiments should evaluate fitness components of F2- and later-generation hybrids under natural conditions. Such experiments may provide better predictions of crop allele persistence in wild populations because they incorporate the effects of natural selection, while accounting for partial genetic barriers to introgression such as outbreeding depression (Burke & Arnold 2001).

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The development and adoption of transgenic crops with novel fitness-related traits

has raised awareness of the potential for increased weediness after crop-wild

hybridization (Ellstrand 2003, Pilson & Prendeville 2004, Snow et al. 2005). Although

some argue that the introgression of domesticated traits creates maladapted crop-wild

hybrids with low fitness (e.g. Stewart et al. 2003), conventional crop alleles are known to

persist in weed populations (e.g., canola: Hansen et al. 2001; sunflower: Whitton et al.

1997; radish: Snow et al. 2001). Theory predicts such alleles will become common if they provide a fitness advantage, or rare if they are deleterious (e.g., Barton 1993, Haygood et al. 2004). The introgression of single-gene transgenic traits, such as herbicide tolerance, insect resistance, and disease resistance, may lead to even greater fitness advantages in hybridizing populations than conventional crop traits (Davis et al. 1999, Snow et al.

2003, Desplanque et al. 2002). Therefore, it is important to understand the fitness implications of crop gene introgression into natural weed populations over many generations. However, replicated, long-term experiments that test for fitness consequences of crop-to-weed introgression are generally lacking. As a result, it is currently difficult to predict whether the introgression of conventional crop traits (much less transgenic traits) could lead to the evolution of weedier populations (Snow et al.

2003).

Here we present the first long-term, experimental study of naturally evolving crop-wild hybrid populations. We established artificial populations of wild and hybrid radishes in agricultural fields in northern Michigan, USA, in 2002. For four years, we quantified their population growth rates and documented pollen fertility and flower petal color evolution under natural conditions. We then compared lifetime fecundity of F1 and

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advanced-generation hybrids relative to non-hybridized wild radish in a local common garden experiment in Michigan (MI). In addition, we measured relative fecundity of wild radish and advanced-generation hybrids in southern California (CA), representing a disparate location within the geographic range of wild radish (Fig. 5.1). Our results demonstrate the value of following the evolution of constructed weed populations to evaluate the role of hybridization in adaptive evolution, and the importance of measuring fitness components in multiple locations to assess potential ecological risks.

5.3 Methods

5.3.1 Study system

Raphanus raphanistrum (wild radish or jointed charlock) is a cosmopolitan, annual weed of Eurasian origin that occurs in agricultural fields, disturbed areas, and coastal beaches (Holm et al. 1997, Snow and Campbell 2005). With its long-lived seed bank, high genetic variability, and early emergence after soil disturbance, R. raphanistrum is a difficult weed to manage, especially in cereal crops (Warwick &

Francis 2005). The cultivated relative of wild radish, Raphanus sativus, is an open- pollinated crop often selected for large, colorful roots, delayed flowering, and high levels of seed production. Long-distance seed dispersal of weedy radish seeds is common

(Kercher & Conner 1996), potentially allowing hybrid genotypes to reach novel environments.

Both R. raphanistrum and R. sativus are self-incompatible, insect pollinated, and interfertile (Warwick & Francis 2005). Cultivated and wild radish species were introduced into California by the 19th century, and Panetsos & Baker (1967) suggested

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that “introgression of raphanistrum characters appears to have been a major factor in

converting the erstwhile crop plant, R. sativus, into a highly successful weed.” In fact,

descendants of crop-wild radish hybrids, known as wild or feral R. sativus, appear to have

displaced the original populations of R. raphanistrum in California during the past few decades (Snow et al. 2001, Hegde et al. 2006).

Raphanus has emerged as a model system in plant evolutionary ecology and has been particularly useful for evaluating the ecological consequences of crop-to-wild gene flow (e.g., Klinger & Ellstrand 1996, Snow et al. 2001, Hegde et al. 2006), although there are no immediate plans to create transgenic radish varieties (Biosafety Clearing-House, http://bch.biodiv.org/; accessed May 22, 2006). Flower petal color frequencies differ

between species and can be used as a crop-specific marker (Snow et al. 2001). Raphanus

sativus has white, pink, or purple flowers whereas R. raphanistrum generally has yellow

flowers or more rarely, white, pink, or bronze flowers (Panetsos & Baker 1967, Kay

1976, Kercher & Conner 1996). White flower color exhibits simple Mendelian

dominance over yellow carotenoid pigment (Panetsos & Baker 1967). The genetic basis

of pink hues is more complex (Stanton 1987), so this trait was not used as a genetic

marker in the current study.

5.3.2 Experimental approach

To investigate ecological and evolutionary consequences of crop-wild

hybridization, we created replicated artificial populations of wild and hybrid radishes in

agricultural fields in Michigan, USA, in 2002. We measured changes in population size,

pollen fertility, and flower petal color frequencies under natural conditions over four

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years. To quantify evolutionary changes in fitness components, we grew wild plants, F1

hybrids, and advanced-generation hybrids in a common garden experiment in northern

Michigan in 2005. Also, to determine the importance of environmental context to relative

fitness of advanced-generation hybrids compared to wild plants, we measured their

survival and fecundity in a novel and distant location in southern California, within the

geographic range of weedy radishes (Fig. 5.1).

5.3.3 Seed sources for replicated populations

In 2001, we haphazardly collected seeds from several hundred plants in a natural

population of wild R. raphanistrum plants (homozygous for the recessive yellow petal

color allele) in an agricultural field in Pellston, MI, USA. In a greenhouse at Ohio State

University, we hand-pollinated 100 wild plants with either wild pollen to create F1 wild

biotypes or crop pollen to create F1 hybrid biotypes. Crop pollen was harvested from 100

“Red Silk” R. sativus plants (Harris-Moran Seed Co., Modesto, USA), a common,

contemporary variety that is homozygous for white petal color (as in Snow et al. 2001) .

Below, we refer to radish biotypes as ‘wild’ or ‘hybrid’ based on hybridization in this

first generation.

5.3.4 Establishment of replicated populations in Michigan

In 2002, we established four first-generation wild populations (W1, W2, W3, W4) and four first-generation hybrid populations (H1, H2, H3, H4) in agricultural fields in

Emmett and Cheboygan counties, MI (Fig. 5.1). To restrict unintended gene flow, these

eight populations were separated from each other and from local wild radish populations

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by at least one km. First, wild and hybrid seeds were planted in PRO-MIX ‘BX’ peat

(Premier Horticulture Ltd., Rivière-du-Loup, Canada) in Jiffy fiber pots (Jiffy Products of

America, Inc., Norwalk, USA) in May 2002, in a greenhouse at the University of

Michigan Biological Station (UMBS), Pellston, MI. Three weeks later, each population

was started by planting 50-60 seedlings in a recently tilled 15 x 15 m plot fertilized with

slow-release Osmocote (19N-6P-12K, 22.7 kg / site; Scotts Miracle-Gro Co., Marysville,

USA). No resident wild radish plants emerged from the seed bank at these plots. The

number of surviving experimental plants that reproduced at each plot was no less than 42.

Each spring through 2005, the plots were tilled, fertilized, and hand-weeded for

approximately two weeks to simulate agricultural management and to promote population

persistence. Otherwise, the populations were exposed to naturally occurring weather

conditions, competing plants, herbivores, pathogens, and pollinators (primarily native

bees, syrphid flies, and honey bees; as in Lee and Snow 1998).

5.3.5 Yearly surveys of replicated populations in Michigan

We estimated population size, frequency of white-flowered plants, and pollen

fertility of each population annually. Estimates of population size were based on direct

counts when < 1000 plants were present or subsampling when populations were larger.

For the latter, we determined the average number of plants in 49 one-m2 quadrats per site

and multiplied this value by the total area. Annual population growth (r) was calculated

as the difference in natural log-transformed population size (N) for yeart and yeart-1.

As in Snow et al. (2001), flower color provided a crop-specific genetic marker.

During peak flowering (June 25th - July 4th), we estimated the proportion of plants with

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white flowers in each hybrid population. White-flowered plant frequencies were based on

direct counts or subsamples as described above. We grouped pink-flowered individuals

with white-flowered plants and pink-yellow flowered individuals with yellow-flowered

plants (as in Snow et al. 2001).

Interspecific hybrids between Raphanus raphanistrum and R. sativus are

heterozygous for a reciprocal translocation that affects chromosome pairing during

meiosis (Panetsos & Baker 1967). Typically F1 crop-wild hybrids produce approximately

50–60% aborted pollen grains (Panetsos & Baker 1967, Snow et al. 2001). To monitor pollen fertility evolution, we collected pollen from one flower on each plant at each site in 2002. In 2003 and 2004, we divided each population into ten parallel transects and sampled ten plants at equidistant intervals along each transect. In 2005, pollen was collected from a random subsample of plants involved in the Michigan and California common gardens (see below). After staining (Alexander 1969), pollen fertility was assessed using a compound microscope to count the proportion of aborted grains in samples of at least 100 grains per plant.

To test whether population growth rates and evolutionary trajectories for flower color frequency and pollen fertility were similar among hybrid populations over four years, we ran a Type III repeated-measures ANOVA in which population was a fixed effect and year was the repeated measure. We defined population as a fixed effect to make explicit comparisons among populations within biotypes (defining population as a random effect did not change our conclusions). Both pollen fertility and white flower color frequency were arcsine square root transformed to normalize data, and population growth rates were normally distributed.

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5.3.6 Common garden experiments

In 2005, we measured the lifetime fecundity of individuals from the four wild and

four hybrid populations in two common gardens (Fig. 5.1). The MI common garden was

located at UMBS in Pellston, MI (42°35’N, 84°42’W) and the CA common garden was

located at the Agricultural Experiment Station of the University of California at Riverside

in Riverside, CA (33°58' N, 117°17'W). The gardens differed most conspicuously in their

growing season and moisture availability, with less water available to plants grown in

California (See Table 5.1 for a summary of differences). Also, in Michigan plants were

grown in open-bottom pots with two competing oat plants in each pot; in California,

however, plants were grown directly in local soil with 30 cm between plants (see below).

Therefore, differences in the results from the two common gardens could be due to both

local abiotic and biotic conditions, as well as differences in below- and above-ground

competition environments. At both sites, plants were arranged in a randomized, complete

block design.

5.3.6.1 Common garden seed sources

In 2004, we collected seeds from the four wild and four hybrid populations for the

common garden experiments. Because radish seeds may remain dormant for several

years, we cannot assume each population was composed of only one generation of

hybrids (e.g., all F4). Therefore, we refer to each year’s population as G1, G2, G3, and G4

(Fig. 5.1), recognizing that each generation beyond G1 (= F1) may represent a mixture of

earlier and later generations. G4 seeds for the common garden studies were collected

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directly from G3 plants. We collected one seed per fruit from 6 fruits on each of 30 plants in each wild population, and 12 fruits per plant from 30 plants in each hybrid population. We used twice as many seeds from hybrids because we expected their pollen fertility to be variable, due to the reciprocal translocation, and this could obscure fitness differences between biotypes. Seeds were equally divided between the two common gardens.

5.3.6.2 Michigan common garden

This experiment included two individuals per G4 wild population and four individuals per G4 hybrid population in each of 21 blocks, resulting in 504 G4 plants. The garden also included 42 G1 wild plants and 42 G1 hybrids, two plants per biotype per block, to determine the fitness differences among wild and hybrid biotypes during the first generation.

Seeds were planted in 300 mL of PRO-MIX ‘BX’ peat in Jiffy fiber pots in a greenhouse at UMBS in early May 2005. Four cultivated spring oat seeds (Avena sativa,

Blaskowski’s Feed & Seed, Cheboygan, USA) were included in each fiber pot to provide a uniform level of competition, and oat density was thinned to two seedlings per pot. The garden area at UMBS was cleared of vegetation, levelled, and roto-tilled twice. After the seedlings developed their first true leaves, each fiber pot was transplanted into a PVC bottomless tube pot (46 cm tall) filled with 1.7l of local sandy soil surrounding the fiber pot, allowing plant roots to grow into local soil. Pots were separated by 30 cm and the use of large tube pots minimized root competition among neighbors. Seedlings that died within the first week after transplanting were replaced. Plants were watered daily for the 121

first month and every other day until August 31st. On June 18th, 13 mg of fertilizer (Slow-

release Osmocote) was added to each pot because the local soil was sandy and nutrient

poor. Insecticide (0.0033% esfenvalerate, 20g/9.5L, Scotts Miracle-Gro Co., Marysville,

USA) was used to control insect herbivory three times during the first month after

transplantation, when herbivory was highest. Aphids were present at low densities later in

the season but did not colonize any plant heavily. Pollinators were abundant throughout

the experiment, as in Lee and Snow (1998). Plants were individually harvested as they

senesced, until the first hard frost (September 16th – 20th), when we harvested all remaining plants. Harvested radish and oat plants were dried at 60º C.

5.3.6.3 California common garden

The CA garden included 10 randomized blocks of five individuals per G4 wild population and ten individuals per G4 hybrid population, totalling 600 individuals.

On December 31, 2004, seeds were planted in individual cells containing 22.7 cm3 of dry,

sterilized UC Soil Mix III, a sand/peat moss mix supplemented with micronutrients

(Matkin & Chandler 1967; Blackmore 128DS flats, Blackmore Co., Belleville, USA).

The flats were placed in a greenhouse and were watered with a dilute nutrient solution

(100ppm, 21-5-20 Peters EXCEL with N, Grace-Sierra Horticultural Products Company,

Milpitas, CA). At the two-leaf stage, seedlings were transplanted into a tilled field at 30

cm intervals in blocks of six rows with ten plants per row at the University of California

Riverside Agricultural Experiment Station. Neighboring radish plants may have

experienced some root competition in this experiment.

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Seedlings were watered every other day for the first week to promote survival and the plot received overhead irrigation once a week during weeks without rain (March 8 -

May 2). To prevent birds from damaging radish fruits, we constructed an exclosure of metal fence posts with cables to support nylon bird netting. The netting was 19 cm mesh, allowing pollinators but not birds into the exclosure (note: bird predation was not observed in Michigan). Pollinators were abundant. Blocks were hand-weeded and sprayed with 0.0033% esfenvalerate to control flea beetles on March 8 and with Crymax

(2.1 g/l, Ecogen Inc., Langhorne, PA) to control diamondback moth larvae on March 21.

Plants were harvested and dried after the majority had senesced (June 10-14).

5.3.7 Measurement and analyses of fitness components

For each common garden, we recorded survival, pollen fertility, flower number, seed production, and above-ground vegetative biomass per plant. A rank sum test was used to compare proportion of plants that survived and flowered at each site. Plants that died before anthesis or did not flower before the end of the experiments were removed from the following analyses. During the field season, we estimated pollen fertility for a subset of plants from each garden, as described above. For harvested plants, we counted numbers of flower pedicels and fruits per plant. Fruit set was calculated as number of fruits produced divided by number of flowers. To estimate the number of seeds per plant, we multiplied the average number of seeds per fruit (for ten randomly chosen fruits per plant) by the number of fruits. Percent fruit set was normally distributed and required no transformations prior to analysis. However, number of seeds per plant and number of flowers per plant were natural log transformed, and pollen fertility data were arcsine 123

square root transformed. Transformations were similar for both common gardens, but for

California the residuals of the number of seeds per plant was normally distributed when

Log10 transformed. All analyses were performed using SPSS (v.13, SPSS Inc., Chicago,

USA).

To test for differences in lifetime fecundity between G1 wild and hybrid plants, we ran a linear mixed model ANOVA for each fitness component. Biotype was considered to be a fixed effect and block was a random effect. Variance of random effects was estimated using restricted maximum likelihood.

To test for differences in lifetime fecundity between G4 wild and hybrid plants grown in the two locations, we used a linear mixed model ANOVA. After detecting a biotype by garden interaction, we ran separate analyses for each garden. For each G4 common garden, we ran a linear mixed model ANOVA for each fitness component. The unbalanced nested ANOVA included biotype and population within biotype as fixed effects and block as a random effect. Variance of random effects was estimated using restricted maximum likelihood.

5.4 Results

5.4.1 Growth rates of wild and hybrid populations

Population growth rates did not differ significantly between wild and hybrid populations between 2002 and 2005 (F1,4=0.62, P=0.48; Fig. 5.2). In the second year, population growth rate was significantly greater than the third and fourth years for both biotypes (F2,8=20.48, P=0.001), when population sizes reached ~13,000–109,000 plants.

The interaction between year and biotype was not significant (F2,8=1.04, P=0.40).

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5.4.2 Evolution of flower color and pollen fertility in hybrid populations

G1 hybrid populations had white (or pink) flowers because white is dominant over

yellow and the crop parents were homozygous for the white allele. Under Hardy-

Weinberg assumptions, we expected subsequent generations to be composed of 75%

white-flowered plants and 25% yellow-flowered plants and we found this to be true (Fig.

5.3A). After the G1 generation, color composition remained statistically constant across populations (P=0.30) and years (P=0.37), with no interaction between population and year (P=0.68).

G1 hybrid populations had lower pollen fertility than wild plants and their pollen

fertility increased over generations (Fig. 5.3B). Hybrid pollen fertility increased

significantly over four years (P=0.008) and differed significantly among populations

(P<0.001) because one hybrid population (H4) had significantly lower pollen fertility than

H2 and H3 (Table 5.2). There was no year-by-population interaction for pollen fertility

(P=0.13), suggesting that, although pollen fertility differed among populations, the

evolutionary trajectory of pollen fertility did not.

5.4.3 Relative fitness of G1 crop-wild hybrids in Michigan common garden

All G1 wild and hybrid plants survived to flower. In the garden, G1 hybrids had

22% lower pollen fertility than G1 wild plants (F1,58=68.2, P<0.001; Fig. 5.4, Table 5.2).

However, G1 hybrid seed production did not differ significantly from that of wild plants

(F1,20=0.31, P=0.59). G1 hybrids had 12% lower fruit set compared to wild plants

(F1,83=17.4, P<0.001), 15% fewer seeds per fruit (Tables 5.2) and produced ~170% more

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flowers than wild plants (F1,63=17.4, P<0.001). Therefore, although G1 hybrids had lower

fruit set than wild plants, they had similar seed production, perhaps due to their greater

flower production (Fig. 5.4). Further, although G1 hybrids produced 300% more above-

ground biomass than wild plants, the companion oat plants growing with G1 wild and

hybrid plants did not differ in biomass (Table 5.2).

5.4.4 Relative fitness of advanced-generation hybrids in common gardens

5.4.4.1 Environmentally dependent G4 hybrid fecundity

The combined ANOVA of the G4 datasets of wild and hybrid plants revealed

significant biotype-by-garden interactions for number of seeds per plant (P=0.002),

number of flowers per plant (P=0.003), and percent fruit set (P=0.003), but not for pollen

fertility (P=0.702; Table 5.3). Given the significant interaction, these differences were

explored for each common garden experiment in the following analyses.

5.4.4.2 Michigan common garden

Within the MI garden, G4 biotypes did not differ in proportion of plants that survived to flower (Fig. 5.4). Within each biotype (wild vs. hybrid), populations were not significantly different in pollen fertility, number of seeds per plant, percent fruit set, or number of flowers per plant (Tables 5.2, 5.4). Therefore, the mean fecundity values summarized below are based on pooled data from the four populations of each biotype.

G4 hybrids had 15% lower pollen fertility than wild plants (Fig. 5.4, Table 5.2,

5.4). Hybrids produced ~11 % fewer seeds than wild plants, despite the fact that they

produced ~1.5 times more flowers per plant (Fig. 5.4). Lower fecundity in hybrids was

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apparently due to lower fruit set than wild plants and fewer seeds per fruit. Hybrids

produced 214% more above-ground biomass than wild plants (Table 5.4), but the

biomass of competing oat plants did not differ significantly between biotypes (Table 5.2).

5.4.4.3 California common garden

Biotypes differed in several important ways in the CA garden. In California, G4

hybrids were 22% more likely to survive to reproduce than wild plants (Fig. 5.4). Again,

within biotypes, there was no significant difference among populations in pollen fertility,

number of seeds per plant, percent fruit set, or number of flowers per plant (Table 5.2,

5.4). Unlike the MI garden, G4 hybrids produced more than twice as many seeds and four

times more flowers than wild plants, and G4 hybrids and wild plants had similar percent fruit set and number of seeds per fruit (Fig. 5.3, Table 5.2, 5.4). Similar to the MI garden,

G4 hybrids exhibited significantly lower pollen fertility than wild plants and produced

253% more above-ground biomass than wild plants (Table 5.4).

5.5 Discussion

5.5.1 Evolutionary consequences of hybridization

Our results suggest that crop-wild hybridization can create opportunities for

increased fitness by generating evolutionary changes that are advantageous in new

environments. Specifically, hybrid lineages had 22% greater survival and produced ~

270% more seeds per plant relative to wild lineages in California. In Michigan, where

they originated and evolved for three generations, hybrids had similar survival to wild

plants and produced ~11% fewer seeds per plant. Although we cannot identify the

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reasons for these differences (Table 5.1), we were surprised by the strength of genotype-

by-environment interactions on lifetime fecundity. These unexpected consequences of

hybridization are consistent with the hypothesis that the evolution of weeds can be

stimulated by hybridization among disparate source populations (e.g., Anderson &

Stebbins 1954, Ellstrand & Scheirenbeck 2000).

G1 and G4 hybrid plants produced far more flowers and biomass than wild plants

in both common gardens (Fig. 5.2). Male fitness could be enhanced with more flowers,

especially when pollen fertility of hybrids improves over time, as we observed. Greater

flower production of crop-wild radish hybrids was reported by Snow et al. (2001) and

Klinger and Ellstrand (1994), who studied hybrids between California genotypes of wild

R. sativus and the crop. Because this phenomenon is consistent across taxa, location, and

generation, transgressive segregation is an unlikely cause (Rieseberg et al. 1999). One

explanation for the persistent hybrid advantage in both gardens may be the introgression

of beneficial genes from cultivated radish (e.g., Ellstrand & Schierenbeck 2000). We

hypothesize that crop-wild hybrids may be “pre-adapted” to thrive in new locations, in

part because many economically important crops are bred for broad environmental

tolerance and hybridization may transfer such traits to crop-wild hybrid progeny

(Chloupek & Hrstkova 2005). A second possible explanation for larger size and flower

production of G1 hybrid genotypes is heterosis (Rhode & Cruzan 2005). The lasting advantage of G4 hybrid plants in the Michigan garden could be due to heterotic effects of greater allelic diversity and heterozygosity. Heterosis may depend on environmental conditions (e.g., Welker et al. 2005) and may have influenced differences in the relative fitness of hybrids in California vs. Michigan. In any case, the hybrid advantage in flower

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production was much greater when G4 plants were grown in the California common garden than in Michigan (Fig. 5.2). Further studies are needed to explore the extent of environmental effects on the relative fitness of crop-wild hybrids. Given the striking effect of environment on hybrid fitness in this study, we expect even larger fitness differences under a wider range of experimental conditions.

Hybrid fitness may be influenced by several important factors not considered in our common garden experiments, including early life-history components such as seed dormancy, longevity, and seedling establishment (e.g., Hooftman et al. 2005), effects of crop and wild parental taxa germplasm diversity (e.g., Ungerer & Rieseberg 2005), and competitive interactions of crop-wild hybrids and their wild parents (including above- and below-ground competition as well as pollen competition) (e.g., Vacher et al. 2004).

Nonetheless, our findings support previous hypotheses about the evolution of weedy R. sativus in California. Panetsos and Baker (1967) speculated that hybridization with R.

raphanistrum allowed cultivated radish to evolve into “a highly successful weed.” Also,

Hegde et al. (2006) used field observations, morphological data, and allozyme

frequencies to conclude that hybrid populations of crop-wild genotypes have displaced

ancestral populations of weedy R. raphanistrum in California. Ellstrand and

Schierenbeck (2000) speculated that hybrid populations of California wild radish may be more weedy and invasive than either of their parent taxa (R. raphanistrum and R. sativus), but studies of demographic processes are needed to test this assumption (Hails and Morley 2005, Snow and Campbell 2005).

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5.5.2 Implications for risk assessment of transgenic plants

Our study was motivated by concerns about the evolution of weedy species and the introgression of crop traits (including transgenes) into wild populations. In radish, results of this and past studies (Klinger & Ellstrand 1996, Snow et al. 2001, Hedge et al.

2006) suggest that: 1) cultivated and wild populations easily hybridize, 2) first-generation crop-wild hybrids are relatively fecund, 3) populations of hybrids can persist for many generations and their growth dynamics are similar to those of wild populations, 4) hybrid populations rapidly evolve increased pollen fertility and produce large quantities of seeds despite retaining high frequencies of crop-specific alleles, and 5) relative hybrid fitness may differ dramatically among environments (e.g., Michigan vs. California). These results highlight the importance of risk assessment across environmental gradients and future studies should include a greater diversity of locations in order to assess the generality of these results. Introgression of fitness-enhancing transgenes into wild populations may further enhance the fecundity of hybrid populations (e.g., Snow et al.

2003, Fuchs et al. 2004).

Measuring the fitness of weedy hybrids across multiple environments is an important goal in assessing the evolutionary effects of (trans)gene flow from crops to their wild relatives. Gene flow between crops and weeds could become more common as human-mediated movement of propagules increases the rate of long-distance dispersal of weed seeds (Ellstrand & Schierenbeck 2000). By comparing wild and hybrid performance in two locations within the geographic range of weedy Raphanus, we tested the dependence of relative hybrid fecundity on environmental conditions. Although this is a common practice in studies estimating the stability of natural hybrid zones, using

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multiple sites to assess crop-wild hybrid fitness is rare (Table 5.5 lists several studies

where genotype by environment interaction appear to affect crop-wild hybrid fitness but

this was not tested statistically). Instead it is more common to grow crop-wild hybrids

within one location under several experimental treatments (e.g. competition [Hauser et al.

2003, Mercer et al. 2006], disease pressure [Fuchs et al. 2003], or herbicide application

[Mercer 2005]).

Studies of F1 hybrids can provide tentative predictions of the effects of

hybridization (Arnold & Hodges 2001, Lexer et al. 2003b), but our study demonstrates

the importance of including advanced-generation hybrid lineages in risk assessment

research, especially lineages that are permitted to evolve for several generations under

field conditions. The persistence of white-flowered plants, and hence a crop-specific

allele, at such high frequencies (75% of plants within each hybrid population exhibited

the crop-specific trait) was unexpected, given that Snow et al. (2001) documented a

decline in white-flowered plants in BC hybrid radish populations. Over time, pollen

fertility increased, suggesting that natural selection was acting on traits associated with

fecundity. Although G4 hybrid fecundity was somewhat lower than that of their wild

relative in the Michigan common garden, yearly population surveys confirmed that

hybrid populations can persist in natural environments, and their population sizes were

similar to those of the wild biotypes. The fecundity of advanced-generation hybrids (> F2 or BC1) is rarely measured in studies of crop-wild hybrids (Table 5.5; but see Guèritaine

et al. 2002, Hauser et al. 2003, Halfhill et al. 2005), and descriptions of the population

dynamics of advanced-generation hybrids are less common.

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In summary, by incorporating genotype-by-environment interactions, advanced- generation hybrids, and measurements of multiple fitness components, we may be better equipped to determine the ecological consequences of crop-wild hybridization in

Raphanus and other crops. Ultimately, data on both hybrid fitness and growth rates of hybrid populations are needed to determine whether crop-wild hybridization leads to the evolution of more abundant and invasive weeds.

5.6 Acknowledgements

The Bonnett, Brubacher, Dotski, Gregory, Hartman, Phelps, Schreier, Stempky, and Sterzik families generously shared their farmland. We thank the staff of the UM

Biological Station and UC Riverside Agricultural Experiment Station, J. Leonard, and many student researchers for their help in the field and lab. Funding was provided by the

US Department of Agriculture (Grant #2002-03715), University of Michigan Biological

Station, National Science Foundation Environmental Biology Program (DEB-0508615), an Ohio State University Presidential Fellowship, The Nature Conservancy of Michigan, the OSU College of Biological Science, Janice Carson Beatley Endowment, and Sigma

Xi. Thanks to T. Waite, H.L. Gibbs, E. Marschall, the Snow lab group, T. Coulson, and three anonymous reviewers for commenting on the manuscript.

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5.7 Tables

Environmental condition Michigan California Quantity of rainfall 31.3 cm 30.5 cm Periodicity of rainfall Evenly distributed Most within first two months Length of field season ~5 months (May – ~5 months (January – September) May) Daylength at start of field 14.5 hr ~ 10 hr season Daylength at end of field 11.75 hr 14.5 hr season Apparent cause of Heavy frost Drought senescence Regularity of supplemental Daily for first month, Every other day for first watering otherwise every other day week, once per week otherwise Plant container (to limit Tube pot, radishes No container, plants competition among competed with two oat transplanted directly into radishes) plants per pot soil Supplemental nutrients Applied to young plants Applied to seedlings Dominant herbivores Flea beetles, aphids Flea beetles, diamond back moth larvae

Table 5.1 Environmental differences between the two common garden experiments.

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Table 5.2 Summary statistics of fitness components for G1 and G4 wild and hybrid plants

and their competitor oats. Plants were grown in two common gardens (Michigan,

California) before (G1) and after (G4) experiencing natural conditions as four populations

(Pop.) per biotype in Michigan for three years. Each site was represented by N plants in

the common garden; n/a indicates not applicable. § Pearson’s correlation coefficient (r) between number of flowers per plant and above-ground biomass was greater than 0.85 for wild or hybrid G1 or G4 plants grown in Michigan or California.

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Table 5.2, cont.

§ § SE) (± SE) (± SE) (g) (± SE) Number of Number of / plant (± SE) (%) (± SE, N) Pollen fertility Above-ground Fruit set (%)(± flowers / plant radish biomass Oat biomass (g) Number of seeds seeds/fruit (± SE) Biotype Pop. N Michigan common garden G1 42 879 (99) 641 (62) 41 (1) 7.5 (1.0) 1.0 (0.03) 3.5 (0.1) 59 (2, Hybrid 42) G1 Wild 42 746 (60) 383 (39) 53 (2) 2.5 (0.3) 1.1 (0.04) 4.1 (0.2) 81 (2, 29) H1 84 637 (50) 535 (49) 43 (2) 6.0 (0.7) 1.0 (0.03) 3.6 (0.1) 71 (3, 55)

d H2 83 802 (111) 634 (76) 41 (1) 6.4 (0.8) 1.0 (0.04) 3.4 (0.1) 71 (2, 58)

Hybri H3 84 567 (43) 485 (44) 44 (2) 5.0 (0.5) 1.0 (0.03) 3.5 (0.1) 75 (3, 4

G 53) H4 82 736 (87) 577 (56) 43 (2) 6.3 (0.8) 1.1 (0.04) 3.3 (0.2) 67 (3, 54) G4 H 333 685 (39) 558 (29) 43 (1) 6.0 (0.4) 1.0 (0.02) 3.4 (0.1) 71 (1, Avg 220) W 42 679 (55) 373 (33) 50 (2) 2.7 (0.2) 1.1 (0.05) 4.1 (0.2) 86 (2, 1 40)

W 42 754 (81) 381 (38) 54 (2) 2.8 (0.4) 1.1 (0.04) 4.0 (0.2) 88 (2, 2 37) Wild

4 W 42 833 (76) 411 (35) 52 (2) 2.8 (0.3) 1.1 (0.06) 4.1 (0.2) 0.85 G 3 (3, 40) W 44 799 (79) 364 (35) 52 (2) 2.7 (0.3) 1.0 (0.04) 4.3 (0.2) 0.86 4 (2, 42) G4 W 169 767 (37) 382 (17) 52 (1) 2.8 (0.1) 1.1 (0.02) 4.1 (0.1) 86 (1, Avg 159)

Continued

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Table 5.2, cont.

California common garden H1 88 1344 868 42 24 (4.2) n/a 3.4 (0.1) 73 (2, (206) (156) (2) 71) H2 85 707 526 41 18 (2.4) n/a 3.1 (0.1) 69 (2, (105) (65) (2) 73)

Hybrid H3 91 1051 752 41 27 (4.1) n/a 3.4 (0.1) 72 (2, 4

G (219) (110) (2) 82) H4 88 1208 795 41 27 (4.9) n/a 3.9 (0.2) 72 (2, (160) (115) (2) 76) G4 H 35 1080 737 41 24 (2) n/a 3.4 (0.1) 71 (1, Avg 3 (90) (58) (1) 302) W1 30 272 161 43 8.4 (1.6) n/a 3.0 (0.3) 0.90 (73) (29) (5) (0.03) W2 32 227 174 33 7.3 (1.0) n/a 2.9 (0.3) 0.82 (53) (28) (4) (0.05) Wild

4 W3 41 555 265 41 9.8 (2.2) n/a 3.8 (0.3) 0.87 G (125) (55) (4) (0.05) W4 37 484 217 41 11.7 n/a 3.9 (0.3) 0.78 (111) (39) (4) (2.5) (0.07) G4 W 14 401 209 40 9.5 (1) n/a 3.4 (0.1) 84 Avg 0 (52) (21) (2) (2.5)

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Source df Num df Denom F P-value A. Number of seeds per plant a Garden 1 1 1.0 0.49 Bio 1 7 20.9 0.003 Garden × Bio 1 5 34.8 0.002 Pop (Bio) 7 5 1.0 0.521 Garden × Pop (Bio) 5 949 1.3 0.26 B. Number of flowers per plant b Garden 1 1 1.1 0.49 Bio 1 7 172.1 < 0.0001 Garden × Bio 1 5 27.4 0.003 Pop (Bio) 7 5 0.3 0.91 Garden × Pop (Bio) 5 978 1.7 0.13 C. Percent fruit set c Garden 1 1 1.7 0.42 Bio 1 7 8.1 0.025 Garden × Bio 1 5 29.9 0.003 Pop (Bio) 7 5 2.9 0.13 Garden × Pop (Bio) 5 978 0.4 0.85 D. Pollen fertility d Garden 1 1 0.1 0.81 Bio 1 7 57.4 0.0001 Garden × Bio 1 5 0.2 0.70 Pop (Bio) 7 5 0.8 0.60 Garden × Pop (Bio) 5 978 1.2 0.32

Table 5.3 Analysis of Biotype × Environment interactions (B × E) in wild and hybridizing radish. We tested for differences in fitness components between two common gardens which included two biotypes and four populations (Pop) per biotype (Bio) and the interaction of garden by biotype to test for B x E. a R2 = 0.215, b R2 = 0.284, c R2 =

0.305, d R2 = 0.291.

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Table 5.4 A comparison of fitness components for wild and hybrid G4 populations in common gardens in Michigan and California. We performed linear mixed model

ANOVAs for four components of fitness for two biotypes (wild and hybrid), and four populations within each biotype. The plants were equally distributed among 21 blocks within the Michigan garden and 10 blocks within the California garden.a R2 = 0.327, b R2

= 0.336, c R2 = 0.429, d R2 = 0.450, g R2 = 0.148, h R2 = 0.183, i R2 = 0.172, j R2 = 0.179.

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Source DfHypothesis DfError F P-value MICHIGAN A. Number of seeds per plant a Biotype 1 6 13.25 0.01 Population (Biotype) 6 469 0.56 0.77 B. Number of flowers per plant b Biotype 1 6 5.82 0.052 Population (Biotype) 6 473 1.19 0.31 C. Pollen fertility c Biotype 1 6 59.37 0.0003 Population (Biotype) 6 356 1.01 0.42 D. Percent fruit set d Biotype 1 6 72.29 0.0001 Population (Biotype) 6 469 0.86 0.53 E. Above-ground biomass e Biotype 1 6 49.78 0.00081 Population (Biotype) 6 472 0.75 0.61 F. Average number of seeds per fruit f Biotype 1 6 41.72 0.00065 Population (Biotype) 6 474 0.82 0.56 CALIFORNIA A. Number of seeds per plant g Biotype 1 6 33.50 0.001 Population (Biotype) 6 455 1.52 0.17 B. Number of flowers per plant h Biotype 1 6 105.86 <0.0001 Population (Biotype) 6 478 0.98 0.44 C. Pollen fertility i Biotype 1 6 18.59 0.005 Population (Biotype) 6 334 0.72 0.64 D. Percent fruit set j Biotype 1 6 1.5 0.27 Population (Biotype) 6 478 0.78 0.58 E. Above-ground radish biomass k Biotype 1 6 56.3 0.0003 Population (Biotype) 6 461 0.741 0.62 F. Average number of seeds per fruit m Biotype 1 6 0.0063 0.94 Population (Biotype) 6 473 4.95 0.00006

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Family Cultivated Wild relative Hybrid Did hybrids Did hybrid spp.Ref. produce relative Generation more (↑), fitness less (↓) or differ equivalent among (=) seeds per treatments plant relative or to wild locations? parent? Alliaceae Allium A. F1 ↓ No data ramosum 1 scabriscapu m Asteraceae Echinaceae E. purpurea F1 ↓ No purpurea “White swan” 2 H. annuus H. annuus F1 ↓ Potentially 3 H. annuus H. annuus F1 ↓ Potentially 4 H. annuus H. annuus F1 ↓ Yes 5‡

Lactuca L. serriola F2, BC1 F2 ↓, BC1 = No data sativa 6

Continued

Table 5.5 Summary of 24 studies of relative fecundity of crop-wild hybrids compared to that of the wild parent. Studies were included if they measured the number of seeds produced by both hybrids and wild parents. No data = hybrids were not grown in more than one location or under multiple environmental treatments such as disease pressure, competition or herbicide application, Yes = relative hybrid fitness was dependent on location or environmental treatment, No = relative hybrid fitness was independent of location or environmental treatment, Potentially = the data presented suggest that hybrid relative fitness differed among locations or environmental treatment but was not statistically tested.

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Table 5.5 continued

Brassicaceae Brassica B. rapa, B. F1 ↓ No data napus7 nigra, Sinapsis arvensis B. B. rapa, B. F1 ↓ No data campestris nigra, 7 Sinapsis (=B. rapa) arvensis 8 * B. napus B. rapa BC2 = No data 9 B. napus B. rapa F2 ↓ No data 9 B. napus B. rapa BCrapa♀ ↓ No data 9 B. napus B. rapa BCrapa♂ ↓ No data 9 B. napus B. rapa BCnapus♀ ↓ No data 9 B. napus B. rapa BCnapus♂ = No data 10 B. napus B. rapa F1 ↑ at high Potentially density, frequency- dependent at low density 11 B. napus B. rapa F1, F2, F1: ↑ in Yes BC1, BC2 mixed stands but = in pure stands, F2: = in pure stands, BC1: = in pure stands and ↓ in mixed stands, BC2: = in pure stands 12 B. napus B. rapa F2 ↓ No data B. napus Raphanus R-OBC6, ↓, ↓,=, = No 13† raphanistrum S-OBC6, R-RBC6, S-RBC6 14 B. napus R. F1, F2 ↓ No data raphanistrum 15 B. napus B. rapa F2, BC2 ↓ Yes

Continued 141

Table 5.5 continued R. sativus R. sativus F1 ↑ No data 16 R. sativus R. F1 ↓ No data 17 raphanistrum R. sativus R. F1, BC1 ↓ Yes 18 raphanistrum Cucurbitaceae Cucurbita C. pepo ssp. F1 ↓ Potentially pepo 19 ovifera var. texana C. pepo C. pepo ssp F1, BC1, ↑ under high Yes 20** ovifera var. BC2 virus texana pressure, ↓ under low virus pressure 21 Poaceae O. sativa O. rufipogon F2 ↑ (Seeds per Yes panicle) 22 O. sativa O. rufipogon F1 ↓ No data Sorghum S. halapense F1 = No data bicolor 23 Triticum Aegilops BC1 ↓ No data aestivus 24 cylindrica

1Yamashita, K., H. Tsukazaki, and A. Kojima. 2005. Interspecific hybrids between amphimictic diploid chinese chive (Allium ramosum L.) and A. scabriscapum Bois. et Ky. J. Jap. Soc. Hort. Sci., 74: 127–133. 2Van gaal, T.M., S.M. Galatowitsch, and M.S. Strefeler. 1998. Ecological consequences of hybridization between a wild species (Echinaceae purpurea) and related cultivar (E. purpurea, "White Swan"). Sci. Hortic., 76: 73–88. 3Cummings, C.L., H.M. Alexander, A.A. Snow, L.H. Rieseberg, M.J. Kim, and T.M. Culley. 2002. Fecundity selection in a sunflower crop-wild study: Can ecological data predict crop allele changes? Ecol. Appl. 12: 1661–1671. 4Snow, A.A., P. Morán Palma, L.H. Rieseberg, A. Wszcelaki, and G.J. Seiler. 1998. Fecundity, phenology and seed dormancy of F1 hybrids in sunflower (Helianthus annuus, Asteraceae). Am. J. Bot. 85: 794–801. 5 Mercer, K.L. 2005. Evolutionary consequences of gene flow from crop to wild sunflowers: studies of fitness, herbicide resistance and seed germination. Ph.D. dissertation. University of Minnesota, St. Paul, MN, 128 pp.

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6Hooftman, D.A.P., J.G.B. Oostermeijer, M.M.J. Jacobs, and H.C.M. Den Nijs. 2005. Demographic vital rates determine the performance advantage of crop-wild hybrids in lettuce. J. Appl. Ecol. 42: 1086–1095. 7Brown, J. and A.P. Brown. 1996. Gene transfer between canola (Brassica napus L. and B. campestris L.) and related weed species. Ann. Appl. Biol. 129: 513–522. 8Mikkelsen, T.R., B. Andersen, and R. B. Jorgensen. 1996. The risk of transgene spread. Nature 380: 31. 9 Hauser, T.P., R.G. Shaw, and H. Ostergard. 1998. Fitness of F1 hybrids between weedy Brassica rapa and oilseed rape (B. napus). Hered., 81: 429–435. 10Pertl, M., T.P. Hauser, C. Damgaard, and R.B. Jørgensen. 2002. Male fitness of oilseed rape (B. napus), weedy B. rapa and their F1 hybrids when pollinating B. rapa seeds. Hered., 89: 212–218. 11Hauser, T.P., C. Damgaard, and R.B. Jørgensen. 2003. Frequency-dependent fitness of hybrids between oilseed rape (Brassica napus) and weedy B. rapa (Brassicaceae). Am. J. Bot. 90: 571–578. 12 Hauser, T.P., R.B. Jørgensen, and H. Ostergard. 1998. Fitness of backcross and F2 hybrids between weedy Brassica rapa and oilseed rape (B. napus) Hered. 81: 436–443. 13Guèritaine, G., M. Sester, F. Eber, A.M. Chevre, and H. Darmency. 2002. Fitness of backcross six of hybrids between transgenic oilseed rape (Brassica napus) and wild radish (Raphanus raphanistrum). Mol. Ecol. 11: 1419–26. 14Darmency, H., E. Lefol, and A. Fleury. 1998. Spontaneous hybridizations between oilseed rape and wild radish. Mol. Ecol. 7: 1467–1473. 15 Al-Ahmad, H., and J. Gressel. 2006. Mitigation using a tandem construct containing a selectively unfit gene precludes establishment of Brassica napus transgenes in hybrids and backcrosses with weedy Brassica rapa. Plant Biotech. J. 4: 23–33. 16Klinger, T., and N.C. Ellstrand. 1994. Engineered genes in wild populations: fitness of weed-crop hybrids of Raphanus sativus. Ecol. Appl. 4: 117–120. 17Snow, A.A., K.L. Uthus, and T.M. Culley. 2001. Fitness of hybrids between weedy and cultivated radish: Implications for weed evolution. Ecol. Appl. 11: 934–943. 18 Uthus, K. L. 2001. The potential for introgression of cultivated radish (Raphanus sativus) alleles into wild radish (R. raphanistrum) populations. Ph.D. dissertation. The Ohio State University, Columbus, OH, 94 pp. 19Spencer, L.J., and A.A. Snow. 2001. Fecundity of transgenic wild-crop hybrids of Cucurbita pepo (Cucurbitaceae): implications for crop-to-wild gene flow. Hered. 86: 694–702. 20Fuchs, M., E.M. Chirco, J.R. Mcferson, and D. Gonsalves. 2004. Comparative fitness of a wild squash species and three generations of hybrids between wild x virus- resistant transgenic squash. Environ. Bio. Res. 3: 17–28.

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21Oard, J., M.A. Cohn, S. Linscombe, D. Gealy, and K. Gravois. 2000. Field evaluation of seed production, shattering, and dormancy in hybrid populations of transgenic rice (Oryza sativa) and the weed, red rice (Oryza sativa). Plant Sci. 157: 13–22. 22Song, Z.P., B.-R. Lu, B. Wang, and J.K. Chen. 2004. Fitness estimation through performance comparison of F1 hybrids with their parental species Oryza rufipogon and O. sativa. Ann. Bot. 93: 311–316. 23Arriola, P.E., and N.C. Ellstrand. 1997. Fitness of interspecific hybrids in the genus Sorghum: Persistence of crop genes in wild populations. Ecol. Appl. 7: 512–518. 24Guadagnuolo, R., D. Savova-Bianchi, and F. Felber. 2001. Gene flow from wheat (Triticum aestivum L.) to jointed goatgrass (Aegilops cylindrica Host.), as revealed by RAPD and microsatellite markers. Theor. Appl. Genet. 103: 1–8. *This included only plants that displayed characteristics of B. campestris. ‡This included hybrids that were susceptible and resistant to imidazolinone herbicides. †This included hybrids that were susceptible (S) and resistant (R) to the herbicide glufosinate–ammonium and were produced on Brassica napus cytoplasm (OBC) and Raphanus raphanistrum cytoplasm (RBC). Also note that there is a low probability of introgression here (e.g., Darmency et al. 1998). ** This included hybrids that were transgenic for virus resistance.

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Figure 5.1 Schematic diagram of the experiment. The first-generation (G1) was created by cross-pollinating wild plants (W) with either wild or cultivated (C) radish pollen to create wild and hybrid (H) biotypes. Eight isolated field populations of wild biotypes (W1

– W4) or hybrid biotypes (H1 – H4) were maintained for four years; small squares represent populations of the two biotypes. In 2005, common gardens in Michigan and

California were composed of G4 plants from each population. The Michigan common garden also included plants representing G1 founders of the eight populations.

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G0 ♂ ♀ ♂ W × W × C

W H

G1

W1 H1

H2 W2 2002

H3 W3 G1

W4 H4

W1 H1

H2 W2 2003

H3 W3 G2

W4 H4

W1 H1

H2 W2 2004

H3 W3 G3

W4 H4

CA common garden (G4): W1 H1 • 2 biotypes (W, H) • 4 populations / biotype H2 W2 2005

H3 W3 G4 W H MI common garden: 4 4 • 2 generations (G1, G4) • 2 biotypes (W, H) • 4 populations / biotype

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9.0 Wild )

r 7.5 Hybrid 6.0

4.5

3.0

1.5

0

Annual population growth rate ( -1.5

-3.0

2002 – 2003 2003 – 2004 2004 – 2005

Year interval (Yeart-1 – Yeart)

Figure 5.2 Annual population growth rate (r) of four wild and four hybrid populations grown in isolated agricultural fields in Michigan over three one-year intervals (r = ln(Nt)

– ln(Nt-l), where Nt is population size in year t and Nt-1 is population size in the preceding year t-1). Error bars represent 95% CI of the mean (N = 4).

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Figure 5.3 Parallel evolution of hybrid populations (H1-H4) over four years (2002 –

2005). (A) Average frequency of white-flowered plants (N = 1340 – 4277). Reference line at 0.75 is the null Hardy-Weinberg expectation (after the G1 generation) of white

flower color frequencies. (B) Average proportion of fertile pollen (sample sizes as in

Table 5.2). From 2002 to 2004, pollen was collected from plants from the artificial field

populations. In 2005, pollen was collected from the common garden experiments in

Michigan and California. See Table 5.2 for fertility of wild pollen for G1 and G4 plants.

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1.0 0 ▲■◊ Ε A

■ H1 0.9 9 Ε H2 ◊ H3 ▲ H4

0.8 8

Ε ▲ ▲■◊ ▲ ■ ■ ◊Ε 0.7 7 ◊Ε

0.6 6

Proportion of white-flowered plants 2002 2003 2004 2005

0.8 H1 ■ B ▲◊Ε H2 Ε ◊ ◊ H ◊ ▲■Ε 3 ■Ε 0.7 H4 ▲ ■ ▲ Ε ◊ CA ■ 0.6 MI Ε ▲ ◊ ▲ Common Pollen fertility 0.5 gardens ■

MI Field populations 0.4

2002 2003 2004 2005

Year 149

Figure 5.4 Relative survival and fecundity of wild and hybrid plants grown in two common gardens including G1 (= F1) hybrids and fourth-generation (G4) hybrids from the

Michigan common garden, and G4 hybrids from the California common garden. Hybrid trait values were standardized such that wild plants have an average fitness value of unity

(reference line). Bars show means of mean relative success within experimental blocks; error bars represent ± 1 SE. To indicate significant differences between wild and hybrid fitness, + represents P = 0.052, * represents P < 0.05, ** represents P < 0.01, *** represents P < 0.001, based on ANOVAs (Table 1). Analysis for survival: NWild = 4,

NHybrid = 4, Michigan - Mann-Whitney U statistic = 4.0, P = 0.34; California - Mann-

Whitney U statistic = 0.000, P = 0.029).

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4 4 G1 hybrids (= F1) in Michigan 3 3

*** 2 2

*** ** 1

0 0 4 4 G4 hybrids in Michigan

3 3

2 2 +

*** *** ** 1

0 0 Relative to wild plants 4 4 G4 hybrids in California 3 3

2 2

* ** *** *** 1

0

0 t

y

Survival Fruit set

Pollen fertilit Seeds per plant Flowers per plant 151

CHAPTER 6

FERAL RADISHES (RAPHANUS SATIVUS; BRASSICACEAE) AS WEEDS?5

6.1 Abstract

Unharvested crop seeds can create nascent feral populations, but the population dynamics and relative fitness of feral plants are poorly understood. In three experiments, we explored the potential for Raphanus sativus to become a feral weed, given that closely-related taxa (R. raphanistrum and the California wild radish) are well- documented weeds. First, we followed the persistence of five feral experimental populations of a common variety (Red Silk) for three generations, within the geographic range of R. raphanistrum (Michigan, USA). Three of the five populations went extinct.

While extant, feral populations flowered approximately one month later than local wild populations, and many individuals failed to flower. The two remaining populations grew rapidly following inadvertent hybridization with R. raphanistrum, and evolved earlier flowering. Second, using the Red silk variety, we applied three generations of selection for either earlier flowering or random mating. Selected lineages flowered ~5 days earlier than randomly mated lineages and produced ~1.9 times more seeds in a common garden experiment. In a third experiment, we found that other radish varieties (daikon, podding,

5 L. G. Campbell and A. A. Snow. in prep. Feral radishes (Raphanus sativus; Brassicaceae) as weeds? 152

and oilseed) flowered up to 18 days earlier than European red-rooted varieties and may

be more likely to become feral weeds. For cultivated R. sativus to become a serious feral

weed, populations need to evolve earlier flowering. This may be most easily

accomplished via the transfer of flowering genes via hybridization with early flowering

cultivars or R. raphanistrum.

6.2 Introduction

Crop ferality and volunteerism are well-known phenomena in agriculture (e.g.,

Cussans, 1978; Ogg and Parker, 1989; Crawley and Brown, 1995; Mack and Erneberg,

2002; Anderson and Soper, 2003; Emms et al., 2005; Gressel, 2005; Pujol et al., 2005).

Volunteer plants occur when anomalous crop plants grow in the midst of a monoculture of a different crop. Crop fields are inoculated when large quantities of crop seeds are routinely yet inadvertently dropped on the ground during harvest (e.g., canola harvesting practices drop > 103 seeds/acre; Smyth et al., 2002; Gulden et al., 2003). Although

perhaps less noticeably and at lower densities, feral plants sometimes colonize field

margins, kitchen gardens, ditches, disturbed areas, and wild spaces (e.g., Crawley and

Brown, 1995, 2004; Heenan et al., 2004; Lumaret et al., 2004; Ulloa et al., 2006).

Maintenance of domestication traits will depend on the strength of selection on those

traits and the rate of gene flow with other individuals of their same cultivar, same crop, or

inter-compatible wild relatives (e.g., Mekuria et al., 2002; Bond et al., 2004; Lumaret et

al., 2004; Ulloa et al., 2006; Warren and James, 2006). Yet, distinct from their crop

ancestors, these feral plants reproduce independently of the agricultural management

upon which they depended as crop plants (sensu Gressel, 2005).

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The recent development of genetically engineered (GE) crops, especially herbicide-resistant cultivars, has led to the recognition that feral plants may create new environmental and crop-weed management risks in intensive agricultural systems, potentially offsetting the benefits of these crops for growers, agro-chemical companies, and conservation managers (e.g., Williamson, 1993; Timmons et al., 1996; Smyth et al.,

2002; Gressel, 2005). Yet, non-GE feral crops may also create economic, evolutionary, and ecological challenges for intensive agriculture producers and conservation managers

(Sukopp and Sukopp, 1993; Gressel, 2005). Non-GE feral crops routinely naturalize in introduced areas (e.g., Mack and Erneberg, 2002; Tabuti et al., 2004; Heenan et al., 2004) and may become invasive weeds (e.g., Conifers: Richardson and Rejmánek, 2004;

Legumes: Emms et al., 2005). Feral plants may harbor diseases or insect pests and cause economic damage to neighboring crop fields (Pares et al., 1997; Gardiner et al., 2003) or damage native assemblages of organisms that interact with the feral plants (e.g., Sukopp and Sukopp, 1993; Warren and James, 2006). By identifying crops that may be more likely to produce persistent feral populations, we may be able to preemptively avoid this ecological and economic damage.

To identify crops that may become serious agricultural weeds, it useful to focus on cultivated plants that are less domesticated, such as radish rather than more domesticated plants such as maize or sorghum. Here, we provide an example using cultivated radish (Raphanus sativus) and its sexually compatible, wild relative, Raphanus raphanistrum. Radish is an ancient crop cultivated around the world (Crisp, 1995) and, recently, volunteer plants resistant to ALS herbicides have been documented in fields in southern Brazil (Heap, 2006; Snow and Campbell, 2005). Its wild relative, Raphanus

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raphanistrum (wild radish or jointed charlock), is among the world’s worst weeds due to damage it causes to small grain and vegetable crops, especially in Canada, USA, Europe,

Australia, and South Africa (Cheam and Code, 1995; Holm et al., 1997, Warwick and

Francis, 2005). Further, the hybrid offspring of R. sativus and R. raphanistrum is a highly successful weed in some environmental contexts (Panetsos and Baker, 1967; Klinger and

Ellstrand, 1994; Chapters 4, 5).

By comparing the phenotypes of Raphanus sativus and R. raphanistrum, we may gain insights into which traits limit the evolution of feral weeds (as in Claessen et al.,

2005a, b). Weedy R. raphanistrum produces a thin tap root before flowering early in the growing season (Campbell et al., unpub.). Cultivated R. sativus delays flowering relative to R. raphanistrum and produces an enlarged hypocotyl and root. The higher allocation of resources to reproduction in R. raphanistrum rather than growth, which is characteristic of R. sativus, may ensure that weeds reproduce before crop fields are sprayed, harvested, or they are killed by frost. Further, the R. raphanistrum phenotype promotes seed dispersal through early abscission of fruits that break into single-seeded sections, protection of seeds from herbivory and enforcing dormancy with thick woody fruit capsules, and staggered seed germination, making it more difficult to eradicate annual populations in infested areas (Panetsos and Baker, 1967; Reeves et al., 1981; Roberts and

Neilson, 1981; Barrett, 1983; Roberts and Boddrell, 1983; Chancellor, 1986).

Several quantitative observational studies address the viability of feral plant populations (e.g., Crawley and Brown, 1995, 2004; Pessel et al., 2001; Heenan et al.,

2004). More recently, other studies have adopted a manipulative approach to understanding the potential for crop ferality (Lutman et al., 2003; Harker et al., 2005)

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Here, we add to this literature through a series of three experiments. We ask “Can populations of feral radishes persist and become weedy?” and follow the evolution of several phenotypic traits during the de-domestication process. First, we measured the population growth rates and individual fitness of populations that had evolved under semi-natural conditions for three generations. Second, we used an artificial selection experiment to measure how much heritable variation crop radishes possess for a key life- history trait that limits their fecundity, age at flowering. Third, we asked how much variation in age at flowering is there among cultivated varieties of radish with the hope of identifying cultivars that might be most likely to produce feral weed populations.

6.3 Materials and Methods

We established experimental field populations of feral plants and allowed them to grow and reproduce over three generations under semi-natural conditions. We followed their population dynamics and evolution and ultimately compared the lifetime fecundity of individuals from three persistent populations in a common garden. In a second experiment, we performed an artificial selection experiment to measure the evolutionary potential of crop populations experiencing selection for advanced reproduction (earlier flowering) and measured the fitness consequences of phenology evolution. In a third experiment, we compared the flowering phenology of ten varieties of cultivated radish to determine the potential for certain cultivate radish varieties to become feral.

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6.3.1 Experimental field populations

6.3.1.1 Seed source

In 2001, we haphazardly chose 150 of “Red silk” Raphanus sativus seed, a

common self-incompatible cultivated radish variety (Harris-Moran Seed Co., Modesto,

USA). In a greenhouse at Ohio State University, we cross-pollinated 100 crop plants to

create F1 crop plants. Maternal parents were randomly assigned pollen donors from the

group of concurrently flowering plants. “Red Silk” is a common, contemporary radish

variety that is homozygous for white petal color (as in Snow et al., 2001; Campbell et al.,

2006).

6.3.1.2 Establishment of replicated populations

In 2002, we established five first-generation (F1) feral populations (C1, C2, C3, C4,

C5), one in each of five meadows in Emmett and Cheboygan counties, MI. The locations

of the populations were separated by > 1km to restrict unintended gene flow among

experimental populations and local wild radish populations. We planted F1 seeds in PRO-

MIX ‘BX’ peat (Premier Horticulture Ltd., Rivière-du-Loup, Canada) in Jiffy fiber pots

(Jiffy Products of America, Inc., Norwalk, USA) in May 2002, in a greenhouse at the

University of Michigan Biological Station (UMBS), Pellston, MI. At each site, we

planted 50-60 seedlings in a recently tilled 15 x 15 m plot fertilized with slow-release

Osmocote (19N-6P-12K, 22.7 kg / site; Scotts Miracle-Gro Co., Marysville, USA). No

resident wild radish plants emerged from the seed bank at these plots. In 2003, two

populations had declined in size so that there were less than 10 seedlings emerging from

the seed bank (C2, C3). To promote the persistence of these two populations, we added 25

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seedlings to each population (C1-C5) from the original seed source. Each spring through

2005, the plots were tilled, fertilized, and hand-weeded for approximately two weeks to

simulate agricultural management and to promote population persistence. Otherwise,

plants were exposed to naturally occurring weather conditions, competing plants,

herbivores, pathogens, and pollinators (primarily native bees, syrphid flies, and honey

bees; as in Lee and Snow 1998).

6.3.1.3 Yearly surveys of replicated populations

We estimated population size, date of first flowering, and frequency of yellow- flowered plants of each population annually. Estimates of population size were based on direct counts when less than 1000 plants were present or subsampling when populations were larger. For the latter, we determined the average number of plants in 49 one-m2 quadrats per site and multiplied this value by the total area. Each spring, we visited populations every third day prior to flowering to observe the date of first flowering of each population.

As in Snow et al. (2001), flower color provided a crop-specific genetic marker and, because we had created populations of previously cultivated R. sativus, plants we did not

expect yellow flowered plants to appear in the populations. However, in 2004, when

yellow-flowered plants appeared in two feral populations (C4, C5), we estimated the

proportion of plants with yellow flowers during peak flowering (June 25th - July 4th).

Yellow-flowered plant frequencies were based on direct counts or subsamples as described above. Because the inheritance of pink pigmentation is more complex (Stanton,

1987), we grouped pink-flowered individuals with white-flowered plants and pink-yellow

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flowered individuals with yellow-flowered plants (as in Snow et al., 2001). In 2004 and

2005, flower color allele frequencies were estimated using Hardy-Weinberg expectations.

6.3.2 Artificial selection experiment

6.3.2.1 Seed source

The F2 generation was the base generation for the selection experiment and was produced from 100 F1 crop x F1 crop crosses in the same room and under similar

conditions to that of the parental generation. We randomly assigned F2 plants to one of

two selection treatments (early flowering and no selection control) and to one of three

replicate lineages for each selection treatment, for a total of 6 lineages. The three

replicate lineages allowed us to exclude drift as the evolutionary cause of the changes in

flowering phenology. In each lineage in the F2 generation, there were 140 plants.

Plants were grown in Cone-tainers (Steuwe and Sons, Corvallis, OR), filled with

standard potting soil (PRO-MIX BX peat, Premier Horticulture Ltd., Rivière-du-Loup,

Canada), so that we could simultaneously raise several hundred plants. The planting dates

th th th th for the F2, and F3 generations were November 10 – 17 , 2003 and August 17 – 20 ,

2004 respectively. We randomly repositioned the unmeasured plants within the

greenhouse every two weeks in order to reduce the effects of any variation in light,

watering, and other environmental conditions of the greenhouse. Additionally, the three

replicates served as blocks in the experiment and each replicate occupied two adjacent

greenhouse benches. Each generation of selection was completed in approximately 6

months.

159

For the F2 and F3 generations, every lineage was initiated with at least 225 seeds.

Two weeks after planting, seeds that had not germinated were discarded and we reduced

the size of every lineage to the size of the smallest lineage to maintain equally sized

lineages. In each generation, we recorded the date of germination and flowering for each

plant in each generation. Age at flowering (days) was estimated as the difference between

the first day of flowering and the date of germination. We imposed truncation selection

on each of the six lineages each generation (F2, F3). We selected the 10% most extreme

phenotypes for early lineages and randomly selected 10% of the control lineages to

produce the following generation. Selected plants were cross-pollinated in a complete

diallel.

6.3.3 Common garden of experimental field and artificial selection plants

This common garden included five fourth-generation individuals from each field

population and five fourth-generation individuals per artificial selection lineage in each

of ten blocks, resulting in 450 plants in a complete randomized block design.

6.3.3.1 Seed sources

In 2004, we collected seeds from the remaining feral population (C1) and the two introgressed populations (C4, C5). Because radish seeds may remain dormant for several

years, we cannot assume each population was composed of only one generation of

hybrids (e.g., all F4). Therefore, we refer to each year’s population as G1, G2, G3, and G4 , recognizing that each generation beyond G2 (= F2) may represent a mixture of earlier and

later generations. G4 seeds for the common garden were collected directly from G3

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plants. We collected one seed per fruit from 3 fruits on each of 30 plants in each

experimental field population.

We also included F4 plants from the artificial selection experiment in the common garden. Just like the plants from the experimental field populations, the artificial selection plants had experienced three generations of experimental selection. We collected one seed per fruit from 3 fruits on each plant in each lineage.

6.3.3.2 Common garden

Seeds were planted in 300 mL of peat (PRO-MIX BX) in fibre pots (May 3rd -

May 10th, 2005) with four oat seeds (Avena sativa, Blaskowski’s Feed and Seed,

Cheboygan, USA) in a greenhouse at UMBS. Cultivated spring oats were added as a

uniform competitor and their density was thinned to one oat per pot. Two weeks later,

once seedlings developed their first true leaves, each fibre pot was transplanted into 4L

plastic pots (Hummert International, Earth City, Missouri, USA) filled with a local

mixture of 3.7L of local sandy soil that surrounded the fibre pot, allowing plant roots to

grow into local soil. Pots were separated by 30 cm and the use of large pots served to

reduce root competition among neighbors. The garden area was level and the soil had

been thoroughly roto-tilled twice to ensure uniformity within the garden. Seedlings that

died within the first week after transplanting were replaced. Plants were watered daily for

the first month and every other day until August 31st. Insect herbivory was kept at low levels using an insecticide (0.0033% esfenvalerate, Scotts Miracle-Gro Co., Marysville,

OH, USA). This was applied once every two weeks during the first month after transplanting, when herbivory was highest. Aphids were present at low densities later in

161

the season but did not colonize any plant heavily. Pollinators were abundant throughout

the experiment, as in Lee and Snow (1998). Plants were individually harvested as they

senesced until the first hard frost when we harvested all remaining plants (September 16th

– 20th).

6.3.3.3 Data collected

For each plant, we recorded age at first flowering, flower color, pollen fertility,

flower number, seed production, and above-ground vegetative biomass per plant. All

plants survived to reproduce during the experiment. Interspecific hybrids between

Raphanus raphanistrum and R. sativus are heterozygous for a reciprocal translocation

that affects chromosome pairing during meiosis (Panetsos and Baker, 1967). Typically F1

crop-wild hybrids produce approximately 50–60% aborted pollen grains (Panetsos and

Baker, 1967; Snow et al., 2001; Campbell et al., 2006). During the field season, we

collected pollen from two flower on each plant and assessed pollen fertility using a

compound microscope to count the proportion of aborted grains in stained samples of at

least 100 grains per plant (Alexander, 1969). At harvest, we measured the diameter of

each plant’s root and categorized root color as white or red. We counted the number of

flower pedicels and fruits per plant. Fruit set was calculated as number of fruits produced

divided by the number of flower pedicels. To estimate the number of seeds per plant, we

multiplied the number of fruits by the average number of seeds per fruit, estimated from

ten randomly chosen fruits per plant.

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6.3.3.4 Analysis of the magnitude of phenotypic change after artificial selection

To control for environmentally induced phenotypic changes across the generations (e.g., yearly environmental differences in greenhouse and field conditions), we standardized age at flowering for each individual plant (as in Delph et al., 2004). Age at flowering was inverse transformed to make the residuals normally distributed. Then, the standardized phenotypic trait value for each plant was calculated by subtracting the mean value of the control line from each individual’s trait value, and this difference was divided by the observed standard deviation of this trait in the control line. We used the mean and standard deviation of the wild control replicate lineage corresponding to each selection lineage within a generation.

To determine if plants responded to selection, we compared the standardized phenotypic values for age at first flower using repeated measures ANOVA for each trait.

We compared the values over three generations (repeated measures) and paired the selection treatments (control and early flowering) within replicates. Selection was expected to accentuate differences between selection treatments over generations.

6.3.3.5 Analysis of fitness consequences of selection–

Percent fruit set was normally distributed and required no transformations prior to analysis. However, number of seeds per plant and number of flowers per plant were natural log transformed, and pollen fertility data were arcsine square root transformed.

All analyses were performed using SPSS (v.13, SPSS Inc., Chicago, USA).

To test for differences in lifetime fecundity among the G4 feral population and the

two G4 introgressed populations, we ran a linear mixed model ANOVA for each fitness

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component. Population was considered to be a fixed effect and block was a random

effect. Variance of the random effect was estimated using restricted maximum likelihood.

To test for differences in lifetime fecundity among the F4 artificial selection lineages, we ran a linear mixed model ANOVA for each fitness component. Selection treatment was considered to be a fixed effect and replicate lineage and block were random effects. Variance of random effects was estimated using restricted maximum likelihood.

6.3.4 Variation in age at flowering among cultivated varieties experiment

6.3.4.1 Seed sources

We chose a ten Raphanus sativus cultivars to include a diversity of radishes

(Table 6.1). The specific radish varieties were chosen for two reasons. First, we sampled

from the diversity of radish varieties, given their diverse history of crop breeding.

Therefore, we have chosen the following major groups from which to select varieties:

European red, Daikon, Podding, and Forage/Leafy. Second, we selected varieties from

within those major groups whose descriptions suggested short generations. For each

variety, we included 50 plants in the common garden. In the common garden, which was

arranged in a complete randomized block design, five plants per variety were randomly

assigned to one of ten blocks.

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6.3.4.2 Common garden

Seeds were planted in 300 mL of peat in fibre pots (PRO-MIX ‘BX’, Jiffy, April

6th, 2005) in a greenhouse at the Ohio State University, Columbus, USA. Emergence

date of each radish seedling was noted. Plants received only the fertilizer in the peat

mixture. Once seedlings developed their first true leaves (April 18th – 20th), each fibre pot

was transplanted directly into the ground at the Ohio State University’s Agricultural

Waterman Farm. To minimize competition among neighbors, plants were separated by

0.5 m within a row and rows were separated by 1-m. The garden area was level and the

soil had been thoroughly tilled to ensure uniformity within the garden. Seedlings that

died within the first week after transplanting were replaced. Plants were watered once per

week for the first month of the experiment. Every other day, we censused the garden for

flowering plants and noted the date of first flowering for each plant. Once a plant

flowered, it was removed from the garden. Age at flowering was calculated as the

number of days between emergence and flowering. All plants had initiated flowering by

June 29th, 2005. Twenty-one plants died during the experiment and were excluded from

analyses.

6.3.4.3 Analysis

To determine which type of radish and varieties within types of radish initiated flowering first, we ran a Type III nested ANOVA where the dependent variable was age at first flower, type of radish and variety nested within type of radish were fixed effects and block was a random effect. Age at first flowering, across all of the varieties, followed

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a normal distribution and was not transformed prior to analysis. Variance of random

effects was estimated using restricted maximum likelihood.

6.4 Results

6.4.1 Population dynamics of feral and introgressed experimental plots

In 2002, we established five feral radish populations, each with 50-55 plants (Fig.

1A). By 2004, two populations (C2, C3) were extinct, even after an attempt, in 2003, to

sustain their populations with additional seedlings. The three remaining populations

persisted through 2005. One of these populations (C1) grew to 149 plants in 2003,

declined to 9 plants in 2005, and went extinct in 2006. In the two remaining populations

(C4, C5), yellow-flowered plants appeared in 2004, revealing that these populations had experienced some level of introgression from wild populations. Yellow-flower color allele frequencies in these populations suggest that in 2004, 7-14 % of the alleles within the population had Raphanus raphanistrum origin and this frequency grew in the following year to as high as 18%. The introgressed populations grew to peak population sizes of 7839 plants (C4) and 502 plants (C5) (Fig. 6.1A). Thus, the only populations that

persisted were the two that hybridized with R. raphanistrum.

From 2002 to 2004, the date that the first plant flowered in the persistent feral population, C1, did not change substantially (Fig. 6.1B). In 2002, the introgressed

populations, C4 and C5, flowered synchronously with C1. By 2004, C4 and C5 flowered

30 days earlier than the C1 (Fig. 6.1B). In 2002, between 80% to 100% of plants in C1,

C4, and C5 initiated flowering during the peak flowering period of wild radish within the region. By 2004, 97% and 98% of plants in C4 and C5 respectively initiated flowering

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during the peak flowering period, whereas only 65% of the plants in C1 initiated

flowering during the same period.

6.4.2 Phenotype and lifetime fecundity of feral plants

The phenotype and lifetime fecundity of feral and introgressed field populations

differed significantly from each other and the control populations (Tables 6.2, 6.3). Plants

from the feral population initiated flowering three days earlier than control populations (P

< 0.001) and five to seven days later than the introgressed populations (P < 0.001). The

introgressed populations had significantly smaller root diameters at harvest than either

the feral population (P < 0.001) or the control populations (P < 0.001) but did not differ

from each other (P = 1). Finally, the competing oats of control populations were largest

whereas the companion oats of one introgressed population were significantly smaller

than those of both the feral (P < 0.001) and control populations (P < 0.001), suggesting

introgressed populations were most competitive and randomly mated populations were

least competitive (Tables 6.2, 6..3).

Plants from the experimental field populations (C1, C4, C5) produced significantly

more seeds per plant than the control populations (P < 0.044). However, there was no

significant difference among experimental field populations in the number of seeds per

plant (P ≥ 0.06), although population C4 produced 54% more seeds than plants from other populations. Plants from one introgressed population (C4) produced significantly more

flowers (P < 0.002) and above-ground vegetative biomass (P < 0.004) than plants from

other populations. Within the common garden, the feral population had significantly

higher pollen fertility than plants from either introgressed population (P > 0.001). Control

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populations also exhibited lower fruit set than the feral population and one introgressed population (P < 0.01) and fewer seeds per fruit than the feral population (P < 0.001).

Otherwise, populations did not differ significantly in fruit set or seeds per fruit (Tables

6.2, 6.3).

6.4.3 Response to artificial selection

The radish cultivar “Red silk” responded to artificial selection for earlier flowering and, therefore, possessed heritable variation for age at first flower (Fig 6.2).

Plants that were selected to flower early flowered five or six days earlier than paired control lineages in two of the three replicate lineages (P < 0.001, Table 6.4). However, in the third replicate lineage, control and early flowering lineages did not differ in date of first flower (P = 1) suggesting that the third early selection treatment lineage did not possess heritable variation for age at first flower.

Further, we found that earlier flowering could be selectively advantageous for these radishes (Fig. 6.2, Table 6.4). Early flowering lineages, on average, exhibited significantly higher lifetime fecundity (number of seeds per plant) than control lineages

(P = 0.012). Although, again, the fecundity of early replicate lineage three did not differ significantly from the fecundity of the control lineage.

6.4.4 Variation in age at flowering among crop varieties

Across the cultivated varieties of Raphanus sativus, age at first flowering ranged from 45 days to 81 days in the Ohio common garden. There was a significant difference among trait groups for the average age at first flower (P = 0.002, Table 6.5). Daikon and

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Podding radish varieties flowered earliest (Table 6.1), on average, while European red radish varieties flowered latest. Radish varieties within trait groups differed significantly in their average age at first flower (P < 0.001). Specifically, China Express flowered eight days earlier than Early Daikon. There were no significant effects of block, block by trait group interactions or block by variety within trait group interactions (Table 6.5).

6.5 Discussion

6.5.1 Persistence of feral populations

Our efforts to establish feral radish populations were partially successful; one of three non-hybridized feral field populations persisted for three generations (Figure 6.1).

Nevertheless, hybridized feral populations were much easier to establish and grew vigorously, as predicted by Panetsos and Baker (1967) and Ellstrand and Schierenbeck

(2000, 2006). Many plants in feral populations had swollen roots and failed to flower or fruit before the growing season ended. Yet, the introgressed populations flowered a month earlier than the feral population and only 3-16 days later than nearby experimental wild populations described in Campbell et al. (2006). In a milder climate, a biennial phenotype and feral populations might persist; we predict that locations with mild winters or the winter warming scenarios associated with global climate change might facilitate the evolution of non-hybridized feral radishes.

Although one might assume that escaping crop plants require intensive management to persist, the body of literature on volunteerism, ferality, and suggests otherwise. For instance, there is an extensive body of literature studying the persistence of feral populations of oilseed rape (Brassica napus), a distant relative of

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radish (e.g., Crawley and Brown, 1995, 2004; Lutman et al., 2003; Bond et al., 2004;

Heenan et al., 2004). Feral populations are often found in previously cultivated fields and

roadside verges (Lutman et al., 2003; Heenan et al., 2004; Crawley and Brown, 2004). In

general, feral populations of B. napus are ephemeral and not self-sustaining (λ < 1), but can persist for up to a decade (Simard et al., 2002; Bond et al., 2004; Heenan et al., 2004;

Roller et al., 2004; Crawley and Brown, 2005). High density and persistent populations are generally due to spillage during harvest and transport (Crawley and Brown, 2005), the possession of herbicide resistant traits (Roller et al., 2004), or soil disturbance providing conditions with low competition (Claessen et al., 2005a) and exposing previously dormant seed banks (Lutman et al., 2003).

To our knowledge, non-hybridized feral Raphanus sativus populations persist in

Japan and Brazil (Yamaguchi and Okamoto, 1997; Heap, 2006). In Japan, feral R. sativus populations grow in roadside ditches near fields of cultivated daikon radish (Yamaguchi and Okamoto, 1997). Daikon landraces are propagated from seeds harvested from selected plants that are transplanted as dormant tap roots or are retained in a managed but untilled portion of field. Biennial, feral daikon have small, branched roots and are considered by farmers to both “contaminate” and enhance the genetic diversity of landraces (Yamaguchi and Yanagi, 1995; Yamaguchi and Okamoto, 1997).

In Brazil, feral R. sativus populations have apparently evolved resistance to ALS- inhibiting herbicides in southern Brazil (Heap, 2006, pers. comm.. G. Theisen, Fundacep

Fecotrigo, Cruz Alta, Brazil). Since 1980, no-till agriculture has predominated in southern Brazil and a R. sativus forage cultivar, called “turnip” or “forrageiro”, is widely planted as a cover crop. Where forrageiro occurred as a volunteer weed in summer crops,

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it was often treated with various herbicides. By 2001, feral R. sativus acquired resistance to several ALS-inhibiting herbicides in the southern state of Rio Grande do Sul. Based on photographs of the flowers and fruits of these plants (see Heap, 2006), and information provided by G. Theisen, feral R. sativus does not appear to have the constricted fruits or yellow flower pigmentation that are common in R. raphanistrum, suggesting these are non-hybridized feral populations.

6.5.2 The impact of age at flowering on the evolution of ferality

Coordinated breeding efforts have generally focused on developing delayed bolting and flowering in many varieties and the evolution of early flowering may be one of the first traits required for the establishment of volunteer and feral radish populations.

Earliness in days to flowering appears to be a highly heritable, dominant trait that is controlled by a few major genes in radish (Yoon and Pyo, 1977; Campbell et al., in review) and this was certainly true for two of the three replicated lineages of “Red silk” in our artificial selection experiment. Further, natural selection in field populations appears to have favored earlier flowering times. When grown in a common garden, the feral population (C1) flowered significantly earlier than randomly mated populations. Earlier flowering genotypes exhibited significantly higher fecundity than randomly mated lineages, suggesting that advancing date of first flower by only 5 or 6 days provides significant adaptive advantages for lineages possessing that trait. In the sections below, we discuss several scenarios under which feral radishes may evolve earlier flowering.

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6.5.3 Importance of cultivar identity in predicting escape

Because date of flowering strongly influences the lifetime fecundity of feral plants, early flowering radish cultivars may be the most likely sources of feral radish populations. In our survey of ten radish cultivars, we found several varieties of daikon, podding, and forage radishes flower earlier than the European red radish varieties. It is perhaps not coincidental that the documented occurrences of non-hybridizing feral radish involve similar types of radishes (Daikon: Yamaguchi and Okamoto, 1997; Forage:

Heap, 2006). We propose that cultivated varieties that can easily evolve wild-type roots and earlier flowering may become short-lived annuals can be identified as latent weeds

(Banga, 1976; Yamaguchi and Okamoto, 1997; Rabbani et al., 1998). We suggest that this transition may occur more easily in small-rooted varieties (e.g., podding, forage) than in large-rooted radishes (European, Daikon).

The maintenance of genetic diversity within weed populations can enhance their ability to evolve in synchrony with changing environmental conditions associated with the agroecosystem in which they grow, including various methods of weed management, and changing pest populations (Lambrinos, 2004). Therefore, the mere existence of diverse radish cultivars, each possessing unique traits (Rat and Evans 1981) and genetic diversity (Ellstrand and Marshall, 1985; Muminovic et al., 2005), may promote ferality in radish.

6.5.4 Hybridization increases invasiveness of radishes

Thus far, we have only considered the potential of non-hybridizing feral populations to become weedy. However, the unintentional, spontaneous introgression of

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wild alleles into the initially non-hybrid feral populations permit us to explore the weed potential of hybrid feral populations. Along with other published studies (Panetsos and

Baker, 1967; Klinger and Ellstrand, 1994; Hedge et al., 2006; Campbell et al., 2006) our results suggest that introgression of wild alleles into feral populations facilitated 1) the establishment of feral populations in Michigan and California, 2) earlier flowering, 3) increased competitive ability and 4) higher population growth rates in introgressed versus feral radish populations. Together, these results suggest that this external “trigger” contributes significantly to the evolution of weedy feral populations of R. sativus.

Hybridizing feral radish populations have been reported in both Europe (Trouard-

Riolle, 1914) and North America (Fernald, 1950; Panetsos and Baker, 1967; Munz,

1973). Further, wild R. sativus var. hortensis f. raphanistroides, a biennial plant, is common in Japan and Korea along beaches, cliffs, abandoned fields, and other ruderal areas, and sometimes occurs adjacent to cultivated daikon radishes (Yamaguchi and

Okamoto, 1997; Huh and Ohnishi, 2001, 2002). An intriguing study by Yamagishi and

Terachi (2003) suggests that these populations are derived mainly from R. raphanistrum rather than R. sativus.

Hybridized populations of feral radish in California are particularly well studied

(e.g., Panetsos and Baker, 1967; Klinger and Ellstrand, 1994; Hedge et al., 2006).

Raphanus sativus and R. raphanistrum first appeared in California in the 19th century

(Panetsos and Baker, 1967). These taxa hybridized such that distinct populations of R. raphanistrum have largely disappeared, while R. sativus plants bearing occasional traits from the weed (e.g., yellow petal color) are common (Panetsos and Baker, 1967; Hedge et al., 2006). In addition, California populations have non-swollen roots and early

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flowering, similar to R. raphanistrum. These feral radishes can occur as an agricultural

weed (Witson, 1996). However, they are most common in ruderal and disturbed natural

areas, including coastal dune habitats (e.g., Munz, 1973; Panetsos and Baker, 1967;

Steven A. Fennimore, University of California at Davis, pers. comm. to AAS; AAS

personal observation) and feral R. sativus is listed as an invasive plant (TNC,

http://tncweeds.ucdavis.edu/esadocs/raphsati.html, accessed October 27, 2006).

Panetsos and Baker (1967) concluded that hybridization between feral R. sativus

and weedy R. raphanistrum “appears to have been a major factor in converting the erstwhile crop plant into a highly successful weed”. Citing Panetsos and Baker (1967),

Ellstrand and Schierenbeck (2000, 2006) went a step further to argue that hybridization was a stimulus for the evolution of invasiveness in R. sativus. However, their criterion for

“invasiveness” was that the hybrid derivative “must replace at least one of its parent taxa

or invade a habitat in which neither parent is present.” In this case, feral R. sativus has

displaced weedy R. raphanistrum (Hedge et al., 2006), but it is not clear whether this

process caused new problems in natural or agricultural areas. Hybridization may have

made it easier for R. sativus to establish feral populations that sometimes occur as weeds.

In terms of agricultural areas, feral populations of R. sativus are regarded as problematic

weeds in California (Witson, 1996), and experimental hybrids may be more fecund than

their wild parent, R. raphanistrum (Campbell et al., 2006). Further, feral R. sativus can

benefit from further episodes of hybridization with the crop, because F1 plants produced

more seeds than local genotypes of wild R. sativus (Klinger and Ellstrand, 1994), but it is

not known whether this translates into increased “invasiveness” (Bergelson, 1994).

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6.5.6 Feral radishes as weeds?

Our results suggest that Raphanus sativus is capable of establishing semi- persistent volunteer and feral populations, but does not appear to be a serious agricultural weed in early generations after escape from cultivation. Rather, non-weedy feral radish populations might be considered “incipient” weeds. Some populations may evolve into vigorous weeds given an advantageous combination of environmental conditions and genetic diversity, as occurred in no-till rotations in Brazil (Heap, 2006; Snow and

Campbell, 2005) and this process may be accelerated by high rates of gene flow from diverse cultivars or weedy R. raphanistrum. Given that agriculture disperses seeds over great distances (Cain et al., 2000; Garnier and Lecompte, 2006), feral populations of R. sativus may eventually encounter favorable conditions for invasion and rapid expansion.

However, for cultivated radishes to become feral and evolve into agricultural weeds, strong selection is needed to remove deleterious crop traits and to increase the frequencies of “weedy” traits. Thus, radishes appear to show a weak tendency to evolve ferality independently and a strong tendency for the evolution of weediness after hybridization with their wild relative, R. raphanistrum.

6.6 Acknowledgements

The authors thank H. L. Gibbs and D. Campbell for comments on previous versions of this manuscript; the Ginop, Reimann, Sterzik, Jarman, Jurek and Romanik families for sharing their farmland; J. Leonard for help with greenhouse experiment; the staff of the University of Michigan Biological Station (UMBS), N. Marsh, and T. Waite for help with the field experiments; and our many student researchers for their hard work.

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This work was supported by USDA grant 2002-03715, UMBS and the Nature

Conservancy, and NSF grant 0508615.

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6.7 Tables

Type Useful part Radish variety Supplier Age at flowering (days, SE) Statistical diff. European red Swollen hypocotyl Scarlet globe a 71 (0.5) e Heritage Scarlet globe 69 (0.5) f b Red silk c 70 (0.5) e,f Cherry belle a 70 (0.5) e,f Daikon Root China Express d 52 (0.5) a Early Daikon d 60 (0.5) c Podding Seed pod Madras podding b 58 (0.5) b Rat's tail b 56 (0.5) b Forage/Leafy Leaf Oilseed e 59 (0.5) b,c Pearl leaf d 62 (0.5) d

Table 6.1 Economically important traits and average age at flowering for ten cultivated

radish varieties (Raphanus sativus). Plants were grown in a complete random design

common garden with five plants per variety represented in each of ten blocks. Average

values represent the estimated marginal means based on an analysis of variance

accounting for radish type, radish variety nested within radish type, and block.

Statistically significant differences among cultivars for days to first flower are

represented by superscript letters beside the average values. Sample sizes for each variety

range from 44 to 50 plants and total N = 478. Seed Suppliers: a Ferry-Morse Seed

Company, Inc; b Bountiful gardens, Willits, CA; c Harris-Moran Seed Co., Modesto,

USA; d Evergreen Y.H. Enterprises, Anaheim, CA; e NextHarvest, Gautier, MS.

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Trait Population Control (SE) C1 (SE) C4 (SE) C5 (SE) N 143 49 50 48 Age at flowering (days) 60 (0.4) c 57 (0.6) b 50 (0.6) a 52 (0.6) a Root diameter at harvest 27.4 (1.0) c (mm) 23.8 (1.4) b 12.7 (0.7) a 12.6 (0.8) a Seeds per plant 125 (12) b 257 (44) a 397 (68) a 212 (37) a Flowers per plant 183 (11) b 194 (21) b 397 (43) a 225 (25) b Seeds per fruit 3.0 (0.1) b 3.9 (0.2) a 3.3 (0.2) a,b 3.4 (0.2) a,b Fruit set (%) 30.5 (1.2) b 38.8 (2.1) a 38.0 (2.1) a 33.1 (2.1) a,b Pollen fertility (%) n/a 71.7 (2.1) a 60.8 (2.7) b 61.7 (3.6) b Above-ground biomass (g) 2.9 (0.2) b 3.5 (0.4) b 6.8 (0.8) a 3.8 (0.5) b Oat biomass (g) 2.6 (0.1) b 2.1 (0.2) a,b 1.6 (0.1) a 1.9 (0.1) a

Table 6.2 Phenotype and lifetime fecundity of feral (C1), introgressed (C4, C5) and randomly mated (Control) lineages in a common garden in Michigan, USA. Plants were equally distributed among 10 blocks within the garden and means were calculated as averages of block averages.

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Table 6.3 A comparison of phenotypic and lifetime fecundity of randomly mated, feral,

and introgressed G4 populations in a common garden in Michigan, USA. We performed

multivariate ANOVA for each trait including the four populations (Pop). The common

garden was arranged in a complete randomized design with 10 Blocks. F statistics are

presented; to indicate significant differences: ns represents p > 0.05, * represents p < 0.05,

** represents p < 0.01, *** represents p < 0.001. The randomly mated populations were not

included in the pollen fertility analysis. Average values are reported in Table 6.2. a Age at reproduction: R2 = 0.573 (Adjusted R2 = 0.505) b Root diameter at harvest: R2 = 0.549

(Adjusted R2 = 0.477); c Seeds per plant: R2 = 0.280 (Adjusted R2 = 0.165); d Flowers per

plant: R2 = 0.387 (Adjusted R2 = 0.289); e Fruitset: R2 = 0.241 (Adjusted R2 = 0.121); f

Seeds per fruit: R2 = 0.258 (Adjusted R2 = 0.140); g Pollen fertility: R2 = 0.278 (Adjusted

R2 = 0.070); hAbove-ground biomass: R2 = 0.371 (Adjusted R2 = 0.272); i Oat biomass:

R2 = 0.345 (Adjusted R2 = 0.242).

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Trait Source df F-statistic Age at flowering a Pop 3 83.92*** Block 9 3.00**

Pop x Block 27 1.50 ns Error 246

Root diameter b Pop 3 67.62*** Block 9 6.90*** Pop x Block 27 1.24 ns Error 246 Seeds per plant c Pop 3 13.85*** Block 9 3.17** Pop x Block 27 0.76 ns Error 246 Flowers per plant d Pop 3 13.38*** Block 9 6.99*** Pop x Block 27 1.02 ns Error 246 Fruit set e Pop 3 5.70*** Block 9 0.56 ns Pop x Block 27 2.02** Error 246 Seeds per fruit f Pop 3 13.85*** Block 9 3.17** Pop x Block 27 0.76 ns Error 246 Pollen fertility g Pop 2 5.74** Block 9 1.36 ns Pop x Block 18 1.02 ns Error 101 Above-ground biomass h Pop 3 12.84*** Block 9 5.90*** Pop x Block 27 1.16 ns Error 246 Oat biomass i Pop 3 13.61*** Block 9 4.44*** Pop x Block 27 1.20 ns Error 246

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Source df MS F P-value Age at flowering a Selection treatment 1 0.23 42.18 <0.001 Replicate 2 0.02 2.94 0.055 Selection treatment x Replicate 2 0.09 15.78 < 0.001 Block 9 0.02 3.53 < 0.001 Error 274 0.01 Number of seeds per plant b Selection treatment 1 6.80 6.37 0.012 Replicate 2 3.14 2.94 0.054 Selection treatment x Replicate 2 8.48 7.95 < 0.001 Block 9 6.44 6.03 < 0.001 Error 274 1.07

Table 6.4 A comparison of age at flowering and lifetime seed production of crop populations that experienced selection for advanced flowering and no selection controls grown in a common garden environment in Michigan. We performed a multivariate

ANOVA for each trait for the two Selection Treatments. Three replicate lineages of randomly mated plants were compared with three replicate lineages of selected plants

(Replicate). The common garden was arranged in a complete randomized design with ten

Blocks. a R2 = 0.29 (Adjusted R2= 0.25); b R2= 0.23 (Adjusted R2 =0 .19)

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Source DFNum DFDenom Mean Square F P-value Trait group 3 6 6130.917 19.50 0.0017 Variety (Trait group) 6 54 314.434 31.26 6.77 x 10-16 Block 9 54 9.489 0.94 0.50 Trait group × Block 27 54 5.840 0.58 0.94 Variety (Trait group) × Block 54 378 10.059 0.93 0.62 Error 378 10.781

Table 6.5 A comparison of age at first flower for ten cultivated varieties of Raphanus sativus that were grown in a common garden in Columbus, Ohio. We performed a nested

ANOVA that considered economically important trait of the cultivar (Trait Group, described in Table 1) and Variety nested within trait group. The common garden was arranged in a complete randomized design with ten blocks.

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Figure 6.1 Population dynamics of field populations of introgressed and feral Raphanus sativus. A. Estimates of annual population size (lines) and flower color allele frequencies

(pie charts). Black lines represent feral populations and gray lines represent introgressed populations (R. sativus x R. raphanistrum). Frequency of white-petal color alleles are represented by white areas; frequency of yellow-petal color alleles are represented by the gray areas and the numeric value. B. Annual date of first flowering. Black bars represent feral populations; gray bars represent introgressed populations.

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8000 A.

C4 6000 14%

4000 18%

2000

600

C5

7% 400 10% Number of plants per population

200

0% C1 C2 C 0 3 2002 2003 2004 2005 Year July 31 B. July 21

July 11

July 1

June 21 Date of first flowering June 11 C C1 C2 C3 C4 C5 C1 2 C4 C5 C1 C4 C5 June 1 2002 2003 2004 Year

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70 600 A. Control B.

60 Early

r

50 r plant 400 s pe flowe

40 d rst i 30 see 200 20 Days to f

10 Number of

0 0 1 2 3 12 3 Replicate lineages

Figure 6.2 Selection for early flowering (Early) altered A) flowering phenology and B) lifetime fecundity compared with randomly mating populations (Control). Bars represent means; error bars represent the 95% CI of the mean; For each Replicate lineage, N = 50.

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CHAPTER 7

PROSPECTUS

“I know my corn plants intimately, and I find it a great pleasure to know them”.

Barbara McClintock (Keller 1983, p. 198).

7.1 Synthesis

After five years of living amongst radishes, I have watched individuals grow large and laden with fruits while others flower early and half-heartedly reproduce and nascent populations swell in size while others shrink to extinction. Our discoveries of why these processes occur have been artificially separated into distinct chapters and, briefly below, I weave them back together to give you my synthetic impression of the evolutionary and ecological implications of hybridization and selection for weedy radishes.

As one might expect, hybridization both increased the allelic and quantitative trait variation within weed populations whereas selection reduced this variation. Logically, chromosomal arrangements that reduced male fertility disappeared relatively quickly when exposed to both natural selection and artificial selection for early flowering

(Chapters 2, 5, 6). Surprisingly, white-petal color, a crop-specific trait, persisted at

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relatively high frequencies in field populations and increased in frequency under artificial selection for large size (Chapters 2, 5). Further, hybridization shifted the mean phenotype of weed populations – early-generation hybrids flowered later and at a larger size than their wild counterparts and earlier than their crop counterparts (Chapters 2, 3, 4, 6).

Hybridization enhanced the ability of weed populations to respond to selection.

Hybrids responded more rapidly to selection for early flowering than either wild or crop ancestors (Chapters 2, 3, 6). Further, hybrids exhibited a more extreme size than wild plants when exposed to either selection for large size or to natural selection in field populations (Chapters 2, 3). This again suggests that crop-specific traits, this time the quantitative trait large size, may prove advantageous to weeds.

We found that hybrid fecundity can equal or exceed wild fecundity in some contexts. First generation hybrids had equivalent fecundity to wild plants perhaps because heterosis helped to compensate for lower fertility (Chapter 5). However, advanced- generation hybrids often had reduced fecundity relative to wild plants in common gardens in Michigan (Chapters 3, 4, 5). Yet, differences in lifetime fecundity disappeared or were reversed under experimentally controlled conditions that altered specific life-history traits, either plastically (such as competition or transplantation to California) or evolutionarily (such as artificial selection; Chapters 3, 4, 5, 6).

These individual lifetime fecundity results were consistent with our observation that experimental populations of R. raphanistrum and advanced-generation hybrids grew and expanded at the same rate (r)(Chapter 5). Further, those populations of feral plants that could evolve to flower earlier persisted, whereas those that did not went extinct

(Chapter 6).

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7.2 Implications

Crops are often thought to be maladapted to most environments outside of the highly managed agro-ecosystems in which they have evolved (Allard 1988; Chloupek and Hrstkova 2005). Only recently, ecologists have recognized the advantages that cultivated traits may provide weeds. Generally, this work has focused on simple traits, with one or a few loci controlling inheritance. For instance, to experimental weed populations, crop-weed hybridization has contributed resistance to diseases (Fuchs et al.

2004), insects (Snow et al. 2003), and herbicides (Boudry et al. 1993; Gealy et al. 2003), and the ability to mimic the crop, becoming ‘invisible’ to humans removing weeds from a field (Miura and Terauchi 2005). In short, crop-weed hybridization can sometimes provide weeds with the ability to evade premature death. However, increasing the ability to survive to reproduction does not necessarily make a weed weedier. Here we have shown that the inheritance of a crop-derived quantitative trait, large size, may directly lead to increased fecundity in weeds. Larger hybrid weeds produced more flowers than control lineages, and tended to produce more seeds than control lineages. This study suggests that crop-wild hybridization may have far more complex ecological and evolutionary consequences than previously measured.

Predicting which immigrant taxa will become has proved to be a difficult task (Mack 1996; Daehler 1998; Colautti et al. 2006). Explaining why that tiny portion of species succeeded is even more the work of optimists (Rejmánek and

Richardson 1996; Crawley et al. 1996; Willis et al. 2000; Thuiller et al. 2006). In a review published just before we started this work, Ellstrand and Schierenbeck (2000)

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hypothesized that hybridization between disparate source populations (including species) could promote the evolution of invasiveness and presented several cases where hybridization preceded the emergence of successful invasive populations, including the

California wild radish (a hybrid complex of R. sativus x R. raphanistrum; Hedge et al.

2006).

Our results certainly support the proposal that hybrid radish is more successful than wild radish in California. However, our results suggest that the success of hybrids is context dependent and therefore I propose that the evolution of invasiveness via hybridization is also context dependent. This suggestion makes the Ellstrand &

Schierenbeck (2000, 2006) hypothesis slightly more complex. First, disparate source populations must make initial contact; Ellstrand & Schierenbeck (2000, 2006) described the period before this initial contact as the lag period. Second, hybridization must result in hybrids that can displace either one or both parental species to create an invasive species. However, the context-dependent success of hybrids may serve to prolong the latent or lag period of the putative invader.

7.3 Future work

Here, the possibilities are endless. So, I deliberately sidestep the most obvious and global suggestions for future research, to focus on my three favorite questions immediately arising from this work – the evolution of alternate life-histories, the consequences of life history on demography, and the genotypic response to new environments.

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A life-history trade-off between age and size at flowering appears to be a strong force in limiting the evolution of hybrid radishes. In order to be large, a radish delays flowering and allocates resources to growth. However, if the delay is too long, the radish risks missing the growing season and failing to reproduce. Therefore, an ideal weedy radish would evolve an alternate life history - flowering early and growing to a large size before flowering. Further, direct selection favors earlier flowering in field populations of hybrids but earlier flowering fails to evolve, apparently because of the strong selection for large size and the genetic correlation between the two traits. I hypothesize that the current wild radish phenotype, which tends to not exhibit a strong trade-off between age and size at reproduction, is the best approximation of the ideal or “ecologically relevant phenotype” that the weed can muster (sensu Brakefield 2003). To test this hypothesis, I suggest creating this ideal phenotype using artificial selection and measuring the success of this phenotype under ecologically relevant scenarios to weedy radish.

Although we have repeatedly found that hybridization and life history evolution have affected lifetime reproductive success (Chapter 3, 4, 6), these processes may not have contributed to increased weediness or invasiveness (Bergelson 1994). Instead, a measure of population growth (λ) may be a better measure of genotype success (Murray

1990, 1992). Demographic matrix population models provide a precise and mathematically tractable method of simulating the growth of stage-structured populations over discrete periods of time (Caswell 2001). Life Table Response Experiments (LTREs,

Caswell 1989) allow quantitative comparisons of population growth rates across a diversity of ecological contexts. I plan to use an LTRE approach to understand how

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hybridization and alterations to life history could affect the local proliferation or weediness of wild radish.

Finally, in Chapter 5, in Michigan we found, hybrid plants had 11% lower reproductive success than wild plants whereas, in California, hybrid fecundity was more than twice that of wild plants. Since life history has such a large impact on fecundity, I hypothesize that the life-history strategy of hybrids was a more successful strategy in

California than the life-history strategy of wild plants and vice versa in Michigan. I propose to explore this hypothesis using a reaction norm approach (Schlichtling and

Pigliucci 1998). Common seed families were planted in each location, California and

Michigan, and I will explore the life history response of family-wise genotypes to the two environments to understand the differences in survival and reproductive success.

7.4 Conclusions

Weeds, plants out of place and causing ecological harm, are an increasing part of ecosystems worldwide. Increasingly, we are aware of our role in their success (Arnold

2004; Palumbi 2001). Perhaps, by accumulating knowledge of their ecology and evolution, we will better anticipate changes that increase the success of weeds.

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