Abstract Alliaria Petiolata (Garlic

ABSTRACT

ALLIARIA PETIOLATA (GARLIC MUSTARD) RESPONSE TO HERBICIDE AND JUNE PRECIPITATION, AND SUBSEQUENT EFFECTS ON THE FOREST FLOOR COMMUNITY

by Wendy Wenger Hochstedler

The impact of invasive plant species on native plants is largely assumed to be negative, but supporting evidence is sparse. We examined the long-term effects of herbicide on Alliaria petiolata and the subsequent effects on the plant community in southwestern Ohio. November herbicide application effectively killed A. petiolata, but did not reduce recruitment; spring densities of A. petiolata rosettes were not lower in sprayed plots. Only modest differences were noted in forest floor vegetation, suggesting

A. petiolata rosettes competed with other plant species.

We tested the hypothesis that higher June precipitation promotes rosette growth and survival with a rain shelter experiment. The three different water treatments affected soil moisture, but not A. petiolata growth or survival. Dry treatments may not have replicated drought years based on water availability measurements. June precipitation is probably not a reliable predictor of A. petiolata rosette survival in years with above average precipitation.

ALLIARIA PETIOLATA (GARLIC MUSTARD) RESPONSE TO HERBICIDE AND

JUNE PRECIPITATION, AND SUBSEQUENT EFFECTS ON THE FOREST FLOOR

COMMUNITY

A Thesis

Submitted to the

Faculty of Miami University

in partial fulfillment of

the requirements for the degree of

Master of Science

Department of Botany

Wendy Wenger Hochstedler

Miami University

Oxford, Ohio

2006

Advisor ______David L. Gorchov

Reader ______Martin Henry H. Stevens

Reader ______Michael A. Vincent

Table of Contents

Introduction 1 Literature Cited 4

Chapter 1: Alliaria petiolata response to herbicide and subsequent effects 7 on the forest floor community in a deciduous forest in southwest Ohio

Abstract 7 Introduction 8 Methods 10 Results 14 Discussion 16 Literature Cited 22

Chapter 2: The effects of June precipitation on Alliaria petiolata growth, 47 density and survival

Abstract 47 Introduction 47 Methods 50 Results 53 Discussion 54 Literature Cited 56

Conclusion 68 Literature Cited 73

Appendices: Appendix A. Map of Hueston Woods State Park 75 Appendix B. Map of Hueston Woods Nature Preserve, study sites, and plots 76 Appendix C. Sample size for analyses 77 Appendix D. NMDS stress as a function of dimensionality 78 Appendix E. Growth forms of all taxa 79 Appendix F. Mean 2004 peak percent cover 80 Appendix G. Mean 2005 peak percent cover 83 Appendix H. Multiple response permutation procedure results 86 Appendix I. Mean percent cover of each growth form 89 Appendix J. Soil properties 92 Appendix K. Common species observed within precipitation study plots 93 Appendix L. Response variables of A. petiolata and soil water contents 94 Appendix M. Nutrient concentration of water added to plots 96 Appendix N. Pairwise comparisons of soil water content 97 Appendix O. Shelter microclimate measurements 98 Appendix P. Comments on rain shelter design and use 102

ii List of Tables

Chapter 1

Table 1. Survival of A. petiolata from Oct. to May each year 27 Table 2. Effect of treatment on adult A. petiolata cover 28 Table 2. Univariate repeated measures ANOVA of May A. petiolata rosette cover 29 Table 4. Mean plant species richness, 2000–2005 30 Table 5. Shannon-Wiener plant diversity indices, 2000–2005 31 Table 6. Effect of treatment on peak cover 32 Table 7. Contingency table of Podophyllum peltatum presence, old-growth stand 33 Table 8. Contingency table of Podophyllum peltatum presence, second-growth stand 33 Table 9. Contingency table of Stellaria media presence, old-growth stand 34

Chapter 2

Table 1. A. petiolata response variables in dry, average and wet treatments 61

List of Figures

Chapter 1

Figure 1. Mean May A. petiolata adult and rosette cover 35 Figure 2. Mean May A. petiolata adult and rosette density 36 Figure 3. NMDS ordination , 2001–2005 37 Figure 4. Percent cover of spring perennials, old-growth stand 43 Figure 5. Percent cover of spring perennials, second-growth stand 44 Figure 6. Percent cover Podophyllum peltatum 45 Figure 7. Percent cover Stellaria media 46

Chapter 2

Figure 1. Fixed-location rain shelter with sample plot and moisture barrier 62 Figure 2. Calibration of percent and gravimetric soil water content 63 Figure 3. Ambient precipitation, throughfall, and water applied to treatments 64 Figure 4. Weekly soil water content 65 Figure 5. Soil moisture release curve for Russell-Miamian silt loam soils 66 Figure 6. Effect of June water treatments on mean rosette survival 67

iii Acknowledgments

To the following people I am greatly indebted for assistance with the work presented here and for my sanity over the past two years. My advisor Dr. David Gorchov, Associate Professor of Botany, Miami University, has provided invaluable guidance at all stages of this project, including his superlative editing skills which have raised the standard of my writing and made completion of the thesis possible. Brad Slaughter, Adriane Carlson, and Lauren Saunders provided data in addition to what I collected for this research, and Brad helped with plant identification and data collection. Hank Stevens, Assistant Professor of Botany, MU, guided my persistent questions about R programming, provided code for problematic analyses in Chapter 1, and loaned field equipment. Michael Vincent, Curator, Willard Sherman Turrell Herbarium, MU, provided help with plant identification, and Drs. Stevens and Vincent served on my Thesis Committee, providing suggestions for improving this body of work. The Gorchov lab members provided computer advice, valuable comments on manuscripts, and consistent sources of laughter. Field assistants Mark Hochstedler, Elizabeth Valentine, Katy Levings, Jessica Hoisington, Jeremy Ash, Susan Sprunt, Melanie Link-Perez, Xanic Rondon, Greg Osborn, and Erica Cunningham put their life on the line so I would not face the feral hogs of Hueston Woods alone. The Ecology Program at Miami University provided a Research Assistantship, and the Ecology Research Center and staff allowed this research and provided logistical assistance. I thank other labs for their involvement in Chapter 2: Mike Vanni’s lab for water analyses, Jon Costanzo and Scott Johnston for weather data, and Alfred Conklin at Wilmington College, Wilmington, OH for soils advice and use of pressure plate extractors. Botany office staff Barb Wilson and Vickie Sandlin are simply amazing individuals without whom we grad students might wander aimlessly. I am grateful to Wendy Cass, Botanist at Shenandoah National Park, for her enthusiasm and professional mentorship, as well as to plant ecologists Lorna Harder, Clair Mellinger, and Kenton Brubaker for formative educational experiences. Botany comrades, my volleyball team, June Thompsen and Nancy Mumaw supported me with friendship, made me exercise, and provided tasty food. I thank my family and most

iv importantly, Mark Hochstedler, for being impromptu field assistant, personal chef and chauffeur, and for believing in me through it all. Thank you. Funding for this research was provided by MU Department of Botany Academic Challenge, Hudson Garden Club, Ohio Biological Survey, and Garden Club of Ohio. I thank the staff at Hueston Woods State Park and the Ohio Department of Natural Resources for allowing me to conduct this research, and Shenandoah National Park for granting me days of leave to begin data collection.

v INTRODUCTION

Invasions by non-native species are of great concern to biologists, land managers and conservationists. While invasive species are considered to be the second leading cause of biodiversity loss in the United States (Wilcove 1998), claims that invasive plant species cause declines and extinctions of native species is often speculative and evidence is sparse (Davis 2003, Gurevitch and Padilla 2004). For example, most studies documenting compositional and diversity impacts by introduced plant species compare invaded and uninvaded areas and are correlational in nature (Levine et al. 2003). Regardless, an estimated $120 billion in environmental damages and losses are caused by invasive species each year in the United States (Pimentel et al. 2005) and additional knowledge of invasive ecology and impacts on native species is needed to make effective management decisions. To quantify the impacts of an introduced plant species of the eastern deciduous forest floor community, we report here on a long-term field assessment of the competitive ability of Alliaria petiolata (M. Bieb.) Cavara and Grande (Brassicaceae, garlic mustard). Alliaria petiolata is an introduced biennial plant of Eurasian origin which is pollinated by generalist species (Anderson et al. 1996, Cruden and McClain 1996), produces as many as 15,000 seeds per m2 (Anderson et al. 1996), and has a viable seedbank for up to five years (Baskin and Baskin 1992). Because individuals are capable of self-pollination (Anderson et al. 1996, Cruden and McClain 1996), one individual can found a population (Cavers et al. 1979, Baskin and Baskin 1992, Nuzzo 1993, Byers and Quinn 1998) and efforts to control A. petiolata populations require extensive and long- term removal within a target area to be effective (Baskin and Baskin 1992, Nuzzo 1993). Alliaria petiolata populations extend throughout the northern midwest and eastern half of North America and southern Canada (Nuzzo 1991, Welk et al. 2002). Due to its establishment over a wide area and in diverse habitats, use of conventional control methods—herbicide, fire or hand-weeding (Nuzzo 1991, Luken and Shea 2000)—may only slow the spread of populations and are unrealistic methods of eradication (Nuzzo 1993, Drayton and Primack 1999, Skinner and Blossey 2005). Despite this, herbicide

1 effectively controls localized A. petiolata populations (Nuzzo 1996, Carlson and Gorchov 2004), and may be useful in managing small or young populations (Drayton and Primack 1999). Current development of biocontrol agents has the potential to decrease A. petiolata populations on a broad scale (Blossey et al. 2001, Skinner and Blossey 2005). Justification, however, of funding for management, labor and supplies for any control measure, and particularly for introduction of non-native species as biocontrol agents, should require evidence that an introduced species is negatively affecting the resident community or human health and welfare. Considered an invasive species, A. petiolata has been tested for negative interactions on multiple trophic levels. Alliaria petiolata negatively affects the life cycle of native butterflies (Huang et al. 1995), and disrupts arbuscular mycorrhizal fungi associations, reducing growth of native tree seedlings (Stinson et al. 2006). In tests of intratrophic impacts, A. petiolata outcompeted Quercus prinus seedlings, was an equal competitor with Impatiens capensis (Meekins and McCarthy 1999), and cover of annuals, vines and tree seedlings increased over three years where A. petiolata was removed by hand (McCarthy 1997). Further studies need to be conducted for other community species, and over longer time periods to develop a comprehensive picture of A. petiolata impact. In 2000, Carlson & Gorchov (2004) initiated a long-term study to assess competitive effect of A. petiolata, and along with Slaughter (2005) found that spot application of herbicide on A. petiolata in an old-growth and a second-growth stand at Hueston Woods State Park, Preble Co., Ohio, in 2000–2003 did not significantly increase plant species richness or diversity. Species composition was affected by herbicide treatment in 2001 in the old-growth stand, 2002 in both stands, and in 2003 in the old- growth stand according to detrended correspondence analyses. Significantly greater cover of spring perennials was found in the old-growth stand in 2001 and the second- growth stand in 2003 (Carlson and Gorchov 2004, Slaughter 2005). We extend this multi-year experiment as long-term studies add a temporal perspective of ecological processes that have a slow response time or annually fluctuating community dynamics (Hobbie et al. 2003). Three to five years of A. petiolata removal may be required to observe recovery of the forest floor plant community (McCarthy 1997).

2 Alliaria petiolata population densities fluctuate from year to year (Baskin and Baskin 1992, Carlson and Gorchov 2004, Winterer et al. 2005, Slaughter et al. in press). Survival of rosettes from May to October and adult density the following May correlated positively with June precipitation over a five year period (Slaughter et al. in press). Here we tested the hypothesis that heavier June precipitation promoted more extensive root growth enabling rosettes to survive summer drought (Slaughter et al. in press). To eliminate confounding effects of temperature and competition with adult A. petiolata, we tested rosette growth and survival over a single season through a rain manipulation experiment at a site lacking an adult cohort. Testing of this hypothesis is compelling because the ability to predict density would facilitate management of this invasive species. Support of this hypothesis would suggest that control of this invasive by fall herbicide application would be most important and cost effective in years when June precipitation was high (Slaughter et al. in press). Overall, this research has three main objectives. The first objective was to determine if long-term dormant season application of Round-up© herbicide effectively controls A. petiolata populations, continuing the work of Carlson and Gorchov (2004) and Slaughter (2005). The second objective was to assess whether five years of removal of A. petiolata positively affects the forest floor plant community. Focus is on the fourth and fifth years following the first herbicide application, however some analyses are comprehensive in scope and present new analyses for data collected by Adriane Carlson in 2000–2001 (Carlson and Gorchov 2004), Lauren Saunders in 2002 (unpublished data), and Brad Slaughter in 2003 (Slaughter 2005). The third objective is to examine the impact of June precipitation on A. petiolata populations in a temperate deciduous forest understory. These findings will contribute to our understanding of how this species interacts with native communities in its introduced range, as well as to knowledge necessary for informed management decisions.

3 Literature Cited

Anderson, R. C., S. S. Dhillion, and T. M. Kelley. 1996. Aspects of the ecology of an invasive plant, garlic mustard (Alliaria petiolata), in Central Illinois. Restoration Ecology 4:181-191.

Baskin, J. M., and C. C. Baskin. 1992. Seed germination biology of the weedy biennial Alliaria petiolata. Natural Areas Journal 12:191-197.

Blossey, B., V. Nuzzo, H. Hinz, and E. Gerber. 2001. Developing biological control of Alliaria petiolata (M. Bieb.) Cavara and Grande (garlic mustard). Natural Areas Journal 21:357-367.

Byers, D. L., and J. A. Quinn. 1998. Demographic variation in Alliaria petiolata (Brassicaceae) in four contrasting habitats. Journal of the Torrey Botanical Society 125:138-149.

Carlson, A. M., and D. L. Gorchov. 2004. Effects of herbicide on the invasive biennial Alliaria petiolata (garlic mustard) and initial responses of native plants in a southwestern Ohio forest. Restoration Ecology 12:559-567.

Cavers, P. B., M. I. Heagy, and R. F. Kokron. 1979. The biology of Canadian weeds. 35. Alliaria petiolata (M. Bieb.) Cavara and Grande. Canadian Journal of Plant Science 59:217-229.

Cruden, R. W., and A. M. McClain. 1996. Pollination biology and breeding system of Alliaria petiolata (Brassicaceae). Bulletin of the Torrey Botanical Club 123:273- 280.

Davis, M. A. 2003. Biotic globalization: does competition from introduced species threaten biodiversity? BioScience 53:481-489.

Drayton, B., and R. B. Primack. 1999. Experimental extinction of garlic mustard (Alliaria petiolata) populations: implications for weed science and conservation biology. Biological Invasions 1:159-167.

Gurevitch, J., and D. K. Padilla. 2004. Are invasive species a major cause of extinctions? Trends in Ecology and Evolution 19:470-474.

Hobbie, J. E., S. R. Carpenter, N. B. Grimm, J. R. Gosz, and T. R. Seastedt. 2003. The US Long Term Ecological Research Program. BioScience 53:21-32.

Huang, X. P., J. A. A. Renwick, F. S. Chew. 1995. Oviposition stimulants and deterrents control acceptance of Alliaria petiolata by Pieris rapae and P. napi oleracea. Chemoecology 5/6(2): 79-87.

4 Levine, J. M., V. Montserrat, C. M. D'Antonio, J. S. Dukes, K. Grigulis, and S. Lavorel. 2003. Mechanisms underlying the impacts of exotic plant invasions. Proceedings of the Royal Society of London 270:775-781.

Luken, J. O., and M. Shea. 2000. Repeated prescribed burning at Dinsmore Woods State Nature Preserve (Kentucky, USA): Responses of the understory community. Natural Areas Journal 20:150-158.

McCarthy, B. C. 1997. Response of a forest understory community to experimental removal of an invasive nonindigenous plant (Alliaria petiolata, Brassicaceae). Pages 117-130 in J. O. Luken and J. W. Thieret, editors. Assessment and Management of Plant Invasions. Springer, New York.

Meekins, F. J., and B. C. McCarthy. 1999. Competitive ability of Alliaria petiolata (garlic mustard, Brassicaceae), an invasive, nonindigenous forest herb. International Journal of Plant Sciences 160:743-752.

Nuzzo, V. 1993. Distribution and spread of the invasive biennial Alliaria petiolata (garlic mustard) in North America. Pages 137-145 in B. N. McKnight, editor. Biological Pollution: the control and impact of invasive exotic species: proceedings of a symposium held at the University Place Conference Center, Indiana University- Purdue University at Indianapolis on October 25 & 26, 1991. Indiana Academy of Science, Indianapolis.

Nuzzo, V. A. 1991. Experimental control of garlic mustard (Alliaria petiolata, (Bieb.) Cavara and Grande) in northern Illinois USA using fire, herbicide and cutting. Natural Areas Journal 11:158-167.

Nuzzo, V. A. 1996. Impact of dormant season herbicide treatment on the alien herb garlic mustard (Alliaria petiolata (Bieb.) Cavara and Grande) and groundlayer vegetation. Transactions of the Illinois State Academy of Science 89:25-36.

Pimentel, D., R. Zuniga, and D. Morrison. 2005. Update on the environmental and economic costs associated with alien-invasive species in the United States. Ecological Economics 52:273-288.

Skinner, L. C., and B. Blossey. 2005. Testing of biological control agents for garlic mustard nears completion. Ecological Restoration 23:205.

Slaughter, B. S. 2005. The response of Alliaria petiolata (garlic mustard) to herbicide, leaf litter and summer precipitation, and subsequent effects on the forest floor plant community in southwestern Ohio. MS. Miami University, Oxford. 65 pgs.

Slaughter, B. S., W. W. Hochstedler, D. L. Gorchov, and A. M. Carlson. in press. Response of Alliaria petiolata (garlic mustard) to five years of fall herbicide application in a southern Ohio deciduous forest. Journal of the Torrey Botanical Society.

5 Stinson, K. A., S. A. Campbell, J. R. Powell, B. E. Wolfe, R. M. Callaway, G. C. Thelen, S. G. Hallett, D. Prati, and J. N. Klironomos. 2006. Invasive plant suppresses the growth of native tree seedlings by disrupting belowground mutualisms. PLoS Biology 4:e140.

Welk, E., K. Schubert, and M. H. Hoffmann. 2002. Present and potential distribution of invasive garlic mustard (Alliaria petiolata) in North America. Diversity and Distributions 8:219-233.

Wilcove, D. S. 1998. Quantifying threats to imperiled species in the United States. BioScience 48:607.

Winterer, J., M. C. Walsh, M. Poddar, J. W. Brennan, and S. M. Primak. 2005. Spatial and temporal segregation of juvenile and mature garlic mustard plants (Alliaria petiolata) in a central Pennsylvania woodland. American Midland Naturalist 153:209-216.

6 CHAPTER 1

Alliaria petiolata response to herbicide and subsequent effects on the forest floor community in a deciduous forest in southwest Ohio

*The portions of this chapter reporting effects of Alliaira petiolata removal on the forest floor plant community will be submitted for publication with authorship Hochstedler, Slaughter, Gorchov, Saunders and Stevens to Journal of Torrey Botanical Society. The other portions of this chapter, reporting effects of herbicide on A. petiolata, were accepted for publication in Journal of Torrey Botanical Society as Slaughter, Hochstedler, Gorchov and Carlson. For some of the multi-year analyses in this chapter, Adriane Carlson provided data for 2000–2001, Lauren Saunders for 2002, and Bradford Slaughter for 2002–2003. M. Henry H. Stevens provided statistical support for analysis of the community data set. Some of these data were reported in Carlson & Gorchov (2004) and Slaughter (2005), but additional years of data and new analyses enable a more complete presentation of the data in this manuscript.

Abstract The impact of invasive plant species on native plants is largely assumed to be negative, but supporting evidence is sparse. A common control method of non-native plants is herbicide application, but little is known about the effects of these chemicals on non-target plant populations, or differences in these populations before and after control measures are taken. We examined the effects of five years of annual dormant season herbicide treatment on garlic mustard, Alliaria petiolata, an invasive biennial with a seedbank, and on the forest floor community in southwestern Ohio. Alliaria petiolata density and cover, as well as cover of forest floor plant species, were recorded in 50 1 x 1 m plots from 2000–2005, in each of two forest stands in Hueston Woods State Park, Preble and Butler Counties, Ohio. Herbicide treatment of Round-up© on half of the plots each November was effective in killing A. petiolata, but recruitment of this invasive was not reduced—density of first-year rosettes did not differ between sprayed and unsprayed plots. During five years of treatment, only a modest difference was noted in forest floor vegetation, suggesting A. petiolata rosettes were still competing with other plant species. Herbicide control of A. petiolata and assessment of its competitive effect on forest plants will require either more extensive and thorough herbicide application, or treatment of both rosettes and adults.

7 Introduction Biological invasions by non-native plants are of great concern to land managers and conservationists. Once established, these plant populations have the potential to dominate the local flora by reducing survival, fecundity, and regeneration of native species (D'Antonio and Kark 2002, Merriam and Feil 2002, Miller and Gorchov 2004). While some introduced plant species are known to outcompete native species for resources, alter community structure and composition, and change soil function (Levine et al. 2003), few studies have documented decline or extinctions of native plants due to invasive plants (Mack 1985, Davis 2003, Gurevitch and Padilla 2004, MacDougall and Turkington 2005). Investment of land managers’ money and time to control invasive plant species needs to be substantiated with knowledge that these populations are actually causing declines and that removal will have a positive impact on the community (Gurevitch and Padilla 2004). One such invasive plant population, Alliaria petiolata (M. Bieb.) Cavara and Grande (Brassicaceae, garlic mustard), extends throughout the midwestern and northeastern United States and adjacent Canada (Nuzzo 1993, Welk et al. 2002). A native of western Eurasia (Grime et al. 1987, Welk et al. 2002), this species was first recorded in North America in 1868 on Long Island (Nuzzo 1991), possibly introduced for culinary or medicinal purposes (Grieve 1971). Alliaria petiolata has been found to establish not only in disturbed areas along roads, river banks, and forest edges, but also in mature forests stands and dry upland slopes (Cavers et al. 1979, Nuzzo 1991, Byers and Quinn 1998, Carlson and Gorchov 2004). Alliaria petiolata is a biennial; seeds germinate in February or March in southern Ohio, and the juvenile basal rosettes live through the summer and remain green throughout the winter. In their second spring, adults flower (April and May), set seed (June) and die (Anderson et al. 1996). During the spring months, populations contain two cohorts, rosettes and adults, in addition to a seedbank remaining after spring germination (Byers and Quinn 1998). Because this seedbank affects A. petiolata population densities (Drayton and Primack 1999) for up to five years (Baskin and Baskin 1992), long-term eradication measures are necessary to manage populations. Mid-intensity spring fires effectively

8 control both adults and newly germinated seedlings in some (Nuzzo 1991), but not all fire-tolerant communities (Luken and Shea 2000), and are not recommended for ecosystems without a history of fire. A common control method of non-native plants is herbicide application, but information is needed about the effects of these management practices on native plant populations (Nuzzo 1996), and differences in these populations before and after a control measure is initiated (McCarthy 1997). Glyphosate herbicide application in a 1% concentration has been shown to be an effective control against A. petiolata (Nuzzo 1991, Nuzzo 1996, Carlson and Gorchov 2004, Slaughter et al. in press). While spring application controls both adult and rosette cohorts, abundant native spring perennials in leaf may be negatively affected by this non-selective herbicide (Nuzzo 1996). Dormant- season spot application only affects one cohort, but under most conditions does not negatively affect wintergreen species (Nuzzo 1996, but see Carlson and Gorchov 2004), and if repeated annually is expected to reduce seed production and recruitment. Removal of A. petiolata should have positive impacts on native plant populations, as the invasive species can out-compete some native species (Meekins and McCarthy 1999). Carlson & Gorchov (2004) and Slaughter (2005) found that spot application of herbicide on A. petiolata in an old-growth and a second-growth stand at Hueston Woods State Park, Preble Co., Ohio, in 2000–2003 did not significantly increase the plant species richness or diversity. Species composition was affected by herbicide treatment in 2001 in the old-growth stand, 2002 in both stands, and in 2003 in the old-growth stand based on detrended correspondence analysis, and a significantly greater cover of spring perennials was found in the old-growth stand in 2001 and the second-growth stand in 2003 (Carlson and Gorchov 2004, Slaughter 2005). We extend this multi-year experiment begun by Carlson & Gorchov (2004) as long-term studies add a temporal perspective of ecological processes that have a slow response time or annually fluctuating community dynamics (Hobbie et al. 2003). Three to five years of A. petiolata removal may be required to observe recovery of the native plant community (McCarthy 1997). Plant populations in treatment plots had five years of recovery time from A. petiolata invasion by summer 2005, two additional response years (2004 and 2005) since the findings of Slaughter (2005). In this extended study, our objectives were to

9 determine if long-term dormant season herbicide application effectively controls A. petiolata populations, and whether removal of A. petiolata positively affects the forest floor plant community.

Methods

STUDY SITE. This study was conducted in two stands in the Hueston Woods State Nature Preserve within the Hueston Woods State Park (HWSP), Preble and Butler Counties, Ohio. The 16-ha second-growth stand (39°34'33'' to 39°34'31'' N, 84°45'41'' to 84°45'37'' W) was dominated by 50-100 year old Liriondendron tulipifera (tulip tree) and the 20-ha old-growth stand (39°34'07'' to 39°34'00'' N, 84°45'10'' to 84°45'02'' W) was dominated by Fagus grandifolia (American beech) and Acer saccharum (sugar maple) trees with many >200 years old (Runkle et al. 1984). Soils were moderately thick to thin loess over loamy glacial till of the Russell-Miamian series on the uplands of both stands and Casco, Rodman and Fox soils in the drainages of the old-growth stand (Lerch et al. 1969, Lerch et al. 1980, Branco 1992). Alliaria petiolata was recorded in this park as early as 1975 (Baechle, MU! 134273).

EXPERIMENTAL DESIGN. As part of a long-term study, we report here the continuation of a study initiated in 2000 by Carlson and Gorchov (2004). In May 2000, 50 1 x 1 m plots were located in each of the two stands in areas of high A. petiolata density with the stipulation that plots were spaced > 5 m apart and situated away from drainages, trails, and treefall gaps. Within each stand, 25 plots were randomly assigned as spray treatment and the other half as unsprayed control plots. Sample size was reduced in some years due to large limbs falling on plots, and is detailed in Appendix C. Each November after leaf-fall, from 2000 through 2004, A. petiolata individuals in the sprayed plots and in additional 1 m buffer areas surrounding the plots were spot- sprayed using backpack sprayers with a 1% glyphosate solution. The glyphosate solution was prepared by dilution of 0.08 L Roundup© PRO (41% glyphosate, in the form of isopropylamine salt) with 7.6 L water. To ensure all rosettes were sprayed, the herbicide contained blue coloring. Leaf litter within the plots was not manipulated, so A. petiolata individuals covered by leaves were not sprayed unless visible.

ALLIARIA PETIOLATA RESPONSE TO HERBICIDE. Alliaria petiolata adult density was counted each February or March, as well as May and June, 2001–2005. Rosette density

10 was counted in May, June, and October, 2000–2005. Rosettes represented first year plants that emerged following the previous fall’s herbicide application. Percent cover of adults and rosettes was estimated using a point frame (Frank and McNaughton 1990) in early May and late June of each year, 2000–2005. Each plot was sampled with 50 pin drops from a frame 0.85 m above ground level, with each pin touch scored as 2% cover. Because cover was measured at multiple vertical levels, a species’ cover could be greater than 100%. Analyses of A. petiolata response to herbicide were performed using the SAS software, Version 9.1.3 of the SAS System for Microsoft® Windows 2001 (SAS Institute, Inc. Cary, NC). To test the effectiveness of glyphosate on sprayed A. petiolata, we compared the survival from October to May in sprayed versus unsprayed plots. For each year (Oct. 2000–May 2001 through Oct. 2004–May 2005) we calculated survival (May adult density/Oct. rosette density) for each plot and analyzed with randomized complete block ANOVA, with stands as blocks, using SAS proc glm. Survival was square root transformed to meet assumptions of homogeneity of variances. The effect of fall application of glyphosate over five successive years on A. petiolata adult cover each May was assessed with non-parametric tests, because cover was 0% in many plots, particularly in the later years of the study. We used Friedman’s method for randomized blocks (Sokal and Rohlf 1995) with stands as blocks, using SAS proc freq. We tested the effect of glyphosate on May A. petiolata rosette cover across years, with a univariate repeated measures ANOVA with a split-plot design with stands as the split plots, using SAS proc glm. To meet the assumptions of homogeneity of variance, cover values were arcsine square root transformed (Littell et al. 1991). In this analysis the appropriate F test for the effect of treatment uses, as the denominator, the mean square of the plot (stand × treatment) term, to account for the correlated response (in rosette cover) within plots among years.

COMMUNITY RESPONSE TO ALLIARIA PETIOLATA REMOVAL. Percent cover of each species in each plot was estimated with the point frame in early May and late June, 2001– 2005 (2000–2001 data: Carlson and Gorchov 2004; 2002 data: Saunders unpublished; 2002–2003 data: Slaughter 2005). Peak cover was calculated as the greater value from

11 either May or June for each species in each plot (except A. petiolata) for plots that were censused in May and June (Appendix C). We calculated plant species richness and diversity for each plot in 2001–2005. Species diversity of each plot was calculated using the Shannon-Wiener index

(H` = -Σpi[lnpi], where pi = proportion of peak cover accounted for by species i). The effects of stand and treatment on species richness and diversity each year were determined using randomized complete block ANOVAs. To assess treatment effect on forest floor plant community composition, ordination in species space of peak cover of all species (excluding A. petiolata) was performed using nonmetric multidimensional scaling (NMDS) (Kruskal 1964). The metaMDS function in package vegan version 1.8-2 (Oksanen et al. 2006) was used in an R-statistical environment, version 2.2.1 (Anon. 2005). NMDS summarizes ecological community patterns by rank ordering the differences in species composition between plots. Calculations are performed on distance matrices and points moved in ordination space to arrive at solutions of least stress, a measure of how the dissimilarity between the species in the ordination space correlates with the original dissimilarity in the data (McCune and Grace 2002). Thus, stress is a measure of lack-of-fit. NMDS is the preferred ordination method for biotic community data sets because it is non-parametric, well suited to data that are non-normal and have a large proportion of zero values, and has been shown to yield the most accurate representation of the underlying patterns in ecological data (Minchin 1987, McCune and Grace 2002, Brehm and Fiedler 2004). Data from 2000–2003 that were previously ordinated using detrended canonical analysis (DCA) (Carlson and Gorchov 2004, Slaughter 2005) were reanalyzed here using NMDS. Cover data were square root transformed and then standardized using a Wisconsin double standardization (Oksanen 2006) to make species abundances relevant and increase the importance of rare species. The Bray-Curtis index, calculated from the transformed cover data, was used as the dissimilarity measure to construct the distance matrix. To avoid local stress minima, ordinations were run with 100 random starts. Ordinations were assessed for stress as a function of dimensionality, and those with three dimensions (stress: 17.2 - 18.7) selected for additional analyses (Appendix B). All species were included in analyses, as removal of the rare species occurring in < 5% of the plots did not

12 greatly improve stress values. Ordinations were examined for separate groupings of sprayed and unsprayed plots in each stand and year combination. For each year we inspected plots of NMDS Axis 2 vs. 1, 3 vs. 2, and 3 vs. 1, but only Axis 2 vs. 1 plots are presented here, as no patterns were evident in the other plots. The null hypothesis of no difference in species composition between sprayed and unsprayed plots was tested with a multiple response permutation procedure (MRPP) on the Wisconsin double standardized peak percent cover for each year × stand combination. MRPP is a non-parametric multivariate test appropriate for community data sets which fail to meet assumptions of normality or homogeneity of variances (McCune & Grace 2002). MRPP calculates the fraction of permuted pairwise dissimilarities that are less than observed pairwise dissimilarities between the sampling plots (McCune and Grace 2002, Stevens and Oksanen 2006). We performed the MRPP in an R-statistical environment with the mrpp function in package vegan (Stevens and Oksanen 2006) using group size as a weighting factor, a Bray-Curtis distance index, and 10,000 permutations. To assess whether specific growth forms in 2004 and 2005 responded to control of A. petiolata, species were grouped as annuals, graminoids, spring perennials, summer perennial herbs, ferns, vines, shrubs, and trees according to Gleason and Cronquist (1991) (Appendix E). Additionally, herbaceous species in leaf at the time of November herbicide treatment were grouped as “wintergreen species” to assess direct negative impacts of dormant season spraying on non-target species. Treatment effect on peak cover of each growth form and of wintergreen species was tested using a Kruskal-Wallis test with SAS proc npar1way. Because of the trend for increasing divergence of spring perennial cover between sprayed and unsprayed plots in the old-growth stand, we explored whether the change in spring perennial percent cover from 2000 to 2005 differed between the sprayed verses unsprayed plots with a randomized complete block

ANOVA test using SAS proc glm. As the first 2000 census was done too late to pick up the earliest senescing species (Allium tricoccum, Cardamine concatenata, Claytonia virginica, Dicentra spp., Erigenia bulbosa, Erythronium americanum, Floerkea proserpinacoides and Ranunculus abortivus), these were dropped from the spring perennial growth form for this latter analysis.

13 Because cover of Podophyllum peltatum L. (may apple, Berberidaceae) increased in the sprayed plots from 2000–2003 (Slaughter 2005), we collected additional demographic data on this species in 2005 to more fully assess treatment effects. We recorded the number of vegetative ramets, sexual ramets, flowers, and fruits in each plot in May and June 2005. We tested the effect of sprayed versus unsprayed treatments on the presence of P. peltatum in 2005 using a 2 x 2 contingency table and Fisher’s exact test (Zar 1999) with SAS proc freq. We estimated leaf area (A cm2) of each ramet following allometric functions presented in Geber et al. (1997): for vegetative (one leaf) ramets A = – 45.8 +

0.600D1D2) and for sexual (two leaves) ramets A = – 69.6 + 0.702 (D1D2 + D3D4), where diameters (D) were measured in cm along two perpendicular positions on each leaf. Negative leaf areas for the smallest individuals were adjusted to zero area. For those plots in which P. peltatum was present, we tested the effect of treatment on total leaf area using a randomized complete block ANOVA with SAS proc glm. We tested the effect of treatment on the reproductive status using a 2 x 2 contingency table and Fisher’s exact test. Stellaria media, an exotic annual which germinates in late fall or early spring (Defelice 2004), had one of the highest percent covers in the old-growth plots from 2000–2003. We tested whether the change in S. media percent cover from 2000 to 2005 differed between the sprayed verses unsprayed plots with a Kruskal-Wallis test using SAS proc npar1way. To assess the effect of sprayed versus unsprayed treatments on the presence of S. media in the old-growth stand in 2005, we used a 2 x 2 contingency table

and Fisher’s exact test with SAS proc freq. For those plots in which S. media was present, we tested the effect of A. petiolata control on total percent cover using a one-way ANOVA in SAS proc glm.

Results

ALLIARIA PETIOLATA RESPONSE TO HERBICIDE. Fall application of glyphosate was effective in killing Alliaria petiolata. Although some individuals survived spraying, for four out of the five years survival of A. petiolata was significantly lower in sprayed plots, in each case ≤ ⅓ the survival in unsprayed plots (Table 1).

14 May A. petiolata adult cover varied greatly across years in unsprayed plots, particularly in the old-growth stand, but in the sprayed plots declined across years and remained very low, averaging less than 1% in each stand each year from 2003–2005 (Figure 1). Before herbicide application began in Nov. 2000, adult cover (May 2000) was initially similar between treatments, but after treatment commenced it differed significantly between treatments in three of five years (2001, 2003, and 2004) (Table 2). In the other two years (2002 and 2005) adult cover was very low (≤ 4%) in unsprayed as well as sprayed plots in both stands (Figure 1). May A. petiolata rosette cover fluctuated across years, particularly in the old- growth stand, but remained below the initial values of May 2000 (Figure 1). However, there was no significant effect of spray treatment, or treatment × year interaction, in rosette cover (Table 3). Adult and rosette densities changed over years across treatments in patterns similar to that found for adult and rosette cover, except that fluctuations were wider, and final (May 2005) rosette density exceeded initial (May 2000) density in unsprayed plots in the second-growth stand and both sprayed and unsprayed plots in the old-growth stand (Figure 2).

COMMUNITY RESPONSE TO ALLIARIA PETIOLATA REMOVAL. Plant species richness and Shannon-Wiener diversity were significantly higher in the second-growth stand than in the old- growth stand each year (ANOVA species richness: P < 0.008, diversity: P < 0.0009) except 2003 (species richness: P = 0.72, diversity: P = 0.66), but did not differ between sprayed or unsprayed plots in any year (Table 4 and Table 5). Mean percent cover of each species in each stand × treatment combination for 2004 and 2005 are reported in Appendix F and G. NMDS ordinations revealed compositional differences between old-growth and second-growth stands, but not between sprayed and unsprayed plots, for each year from 2001–2005 (Figure 3). NMDS findings were confirmed by MRPP where treatments did not differ in composition in either stand in any year, with the exception of the second- growth stand in 2002 (Table 6, Appendix H). In 2004 and 2005 treatments were marginally different in the old-growth stand. There was no significant effect of spray treatment on the percent cover of any growth form in either stand in 2004 or 2005, except that cover of wintergreen herbaceous

15 species in leaf at time of dormant season herbicide treatment was less in the sprayed plots than the unsprayed plots in the old-growth stand (Kruskal-Wallis P = 0.03) (Appendix I). A trend existed toward greater cover of spring perennials in the sprayed plots in the old- growth stand in 2005 (Figure 4, Figure 5, Appendix I), but change in spring perennial cover from 2000 to 2005 in both stands was not significant (Mean + SE unsprayed: 1.24 + 2.38, sprayed: -0.30 + 2.63; ANOVA df = 1,90, stand: F = 0.00, P = 0.95, treatment: F = 0.22, P = 0.64). Podophyllum peltatum tended to increase in cover in sprayed plots from 2002–2004 in the second-growth stand (Figure 6). However, the presence of P. peltatum in plots was not affected by treatment in 2005 (Table 7 and Table 8). In plots where P. peltatum was present, total leaf area was not different between treatments (ANOVA df = 1,20, stand: F = 1.39, P = 0.25, treatment: F = 0.40 , P = 0.53 ). In the old-growth stand, 2.3% of the Podophyllum peltatum ramets were sexual in the sprayed plots and 6.8% in the unsprayed plots. In the second-growth stand, 8% of the ramets were sexual in the sprayed plots and 20% in the unsprayed plots. In neither stand was reproductive status affected by treatment (Fisher exact tests, old: P = 0.62, second: P = 0.58). Stellaria media tended to increase in cover in the unsprayed plots from 2000 to 2005 in the old-growth stand (Figure 7) and change over this time was different between treatments (Kruskal-Wallis df = 1, χ2 = 3.88, P = 0.0475). In 2005, presence of S. media was not affected by treatment (Table 9), and in plots where S. media was present, percent cover was not different between treatments (ANOVA df = 1, F = 2.76, P = 0.11).

Discussion

ALLIARIA PETIOLATA RESPONSE TO HERBICIDE. Spot-spraying A. petiolata with glyphosate in the fall was effective in the sense of significantly reducing survival of rosettes over the winter and into the following spring. In only one year (2001) was there no significant difference in survival between sprayed and unsprayed plots. While treatment effect was significant in each of the other four years, not all individuals were killed; each year at least 6% of these rosettes survived. These individuals might not have received sufficient herbicide, or they may have escaped spray because they were leafless

16 or buried beneath litter when the plot was sprayed. Earlier spraying, particularly spraying before autumn leaf fall, might increase mortality of A. petiolata, but would expose more native plants to herbicide. Over the course of five years, the herbicide treatment was effective at reducing adult A. petiolata density and cover. Adult cover decreased from 7-8% before herbicide (2000) to less than 1% each year from 2003–2005, when adult A. petiolata cover was 0% in > 45% of the plots in each stand. Adult cover was significantly lower in sprayed plots in three of the five years; the lack of statistical significance in the other two years was due to the extremely low cover in unsprayed, as well as sprayed, plots. Rosette density and cover, on the other hand, were generally not affected by spray treatment. Of course we did not expect the rosette cohort to be directly affected by herbicide, since these individuals were in the seed stage during fall herbicide application. Nevertheless, we expected the dramatic reduction in adult cover and density due to herbicide would greatly reduce seed production and therefore seedling recruitment in the sprayed plots, and the absence of such an herbicide effect begs explanation. One possible reason why rosette density failed to decline over five years of herbicide treatment would be release from inter-cohort competition with adults. If such inter-cohort competition is important, as it is in central Pennsylvania (Winterer et al. 2005), then the smaller number of A. petiolata seeds that would be expected in sprayed plots would have higher germination, establishment, or survival than the larger number in unsprayed plots, because sprayed plots consistently had fewer adults. However, evidence for this inter-cohort competition was not found in this woodlot (Slaughter et al. in press). A second potential explanation is that viable A. petiolata seeds persisted in the soil. After removing every flowering individual from A. petiolata populations for three successive years, Drayton and Primack (1999) found that 25% of these populations persisted and even increased over that timeframe. They concluded that new plants were most likely germinating from a large seed bank. While seeds are thought to be viable in the soil for up to five years, most germinate the first spring, and only very small percentages germinate in subsequent years (Baskin and Baskin 1992). If germination from a seed bank was responsible for recruitment of A. petiolata in sprayed plots, we would expect ever-decreasing numbers of rosettes over the five years of treatment.

17 Instead, A. petiolata rosette density fluctuated in the unsprayed plots, and in the old- growth stand was higher in 2005 (268 individuals/m2) than it was in any other year (Figure 2). Therefore, the seed bank is an unlikely explanation for persistence of A. petiolata in sprayed plots. The most likely explanation for the persistence of A. petiolata rosettes in sprayed plots is seed dispersal from A. petiolata adults growing outside the treated buffer area surrounding each plot. Nuzzo (1999) found that A. petiolata populations spread at an average rate of 5.4 m/year in northern Illinois, primarily through ballistic dispersal of seeds from fruiting adults, but aided by disturbance and seed vectors (including humans). Although off-trail human traffic is prohibited in Hueston Woods State Nature Preserve, seed dispersal is apparently sufficient to spread A. petiolata seeds into our sprayed plots from surrounding unsprayed areas. Therefore, in order for fall herbicide application to control this biennial, larger areas need to be treated.

COMMUNITY RESPONSE TO ALLIARIA PETIOLATA TREATMENT. Suppression of A. petiolata adults in plots sprayed annually since 2000 did not cause a change in forest floor community plant richness, diversity or composition in 2004 and 2005. Only early in the study, in 2002, was there a significant difference in community composition between the sprayed and unsprayed plots, and this was only in the second-growth stand. Similarly, cover of different growth forms did not differ significantly between treatments, despite earlier findings that cover of spring perennials differed between sprayed and unsprayed plots in the old-growth stand in 2001 (Carlson and Gorchov 2004), as did cover of spring perennials and graminoids in 2003 in the second-growth stand (Slaughter 2005). In a similar study, cover of annuals, vines and tree seedlings increased over three years where A. petiolata was removed by hand (McCarthy 1997). We hypothesized that spring perennialss, in particular, would respond to removal of garlic mustard due to competition for light in early spring, however even with reduction of A. petiolata adults in the sprayed plots, consistent change in cover was not observed. Several factors might explain the modest effects on community composition found over the course of this study.

18 One possible reason for minimal community response may have been because the forest floor plant community in the sprayed plots was still affected by A. petiolata. While survival to the adult stage was reduced by the spray treatment, rosette density and cover did not differ between the treatments. Lower diversity indices in years when only the rosette cohort was present (McCarthy 1997) suggest that rosettes compete with the native plants for light or nutrients. In greenhouse experiments A. petiolata outcompeted Quercus prinus seedlings, and was an equal competitor with Impatiens capensis (Meekins and McCarthy 1999). Evidence for allelopathic effects of A. petiolata on seed germination is less conclusive (Kelley and Anderson 1990, McCarthy and Hanson 1998, Prati and Bossdorf 2004), but other Brassicaceae species are known to inhibit germination (Vaughn and Boydston 1997). Alliaria petiolata may also affect other plants indirectly via its effect on mycorrhizal fungi. Like other members of the Brassicaceae, A. petiolata has anti-fungal properties (Roberts and Anderson 2001) due to glucosinolates (Vaughn and Berhow 1999) and perhaps other compounds that may enter the soil as root exudates (Prati and Bossdorf 2004) or from leaf litter (Stinson et al. 2006). One of these glucosinolates, glucotropaeolin, is found at significantly greater levels in rosette roots than adult roots (Vaughn and Berhow 1999), but it is not known if this compound plays a role in the anti- fungal qualities of the root exudates (Stinson et al. 2006). Alliaria petiolata disrupts arbuscular mycorrhizal fungi associations, thereby reducing growth of native tree seedlings (Stinson et al. 2006), and may interfere with other native forest floor herbs with high mycorrhizal dependency. Rosettes remaining in the sprayed plots may have reduced mycorrhizal fungi and in this way indirectly affected the competitive ability of forest floor plant species (Roberts and Anderson 2001). The plant community in the sprayed plots may also have been affected by allelopathic compounds from previously existing A. petiolata individuals, or from individuals located outside the spray shadow. Neither the length of time A. petiolata allelochemicals are retained in the soil, nor the width of the circle of influence of one individual has been established. If allelopathic compounds remain in the soil for several years, or affect plants >1 m away (e.g. via leaf litter), concentrations in our sprayed plots may have been sufficient to suppress other plant species. Due to these factors, future

19 studies using dormant season herbicide to control A. petiolata need to increase the duration of study, or the size of area treated, in order to experimentally assess the effect of A. petiolata on the forest floor plant community. A second possible reason for the modest changes in community composition is herbivory by white-tailed deer, which has been shown to play a large role in understory plant community population dynamics and decrease plant growth and reproduction in areas of high deer densities (Russell et al. 2001). Deer activity is evident in the Hueston Woods Nature Preserve from the abundant deer trails, tracks, and scat present (pers. observ.), although current density numbers are unknown (Lonnie Snow, HWSP, pers. comm. 2006). Rooney et al (2004) found declines in some understory species to be particularly great in areas where hunting was restricted. During this study, we observed top browse on Podophyllum peltatum and Impatiens spp. Greater deer herbivory on plants in the sprayed plots than the unsprayed plots may have masked positive trends of native plant recovery after A. petiolata removal at Hueston Woods. Deer browse on A. petiolata is rare in North America (Cavers et al. 1979, Nuzzo 1991), and higher densities of A. petiolata, particularly the taller adult cohort, may deter deer from browsing other plants in the same area. Plants in the sprayed plots where adult cover was decreased may have been more vulnerable to deer browse. Not all populations of forest floor species responded to A. petiolata control in the same manner. The tendency of Stellaria media cover to remain low in sprayed plots while increasing in unsprayed plots may have been due to direct effects of dormant- season herbicide application. Seedlings were in leaf in November, and may have been killed by glyphosate application. Podophyllum peltatum, however, tended to increase in cover in the sprayed plots with the removal of A. petiolata adults. We attribute this to the large leaf size of P. peltatum relative to other spring perennials. Leaves opening in early spring may have benefited from increased light in the absence of A. petiolata adults, like other spring perennials, but were tall enough to intercept light above growing A. petiolata rosettes in late spring, unlike shorter spring perennials (e.g. Claytonia virginica and Erigenia bulbosa) or emerging summer species (e.g. Impatiens spp., Sanicula spp., and Hydrophyllum appendiculatum).

20 CONCLUSIONS. Our findings have several implications for management and control of A. petiolata, as well as for restoration of invaded forest floor plant communities. Although fall herbicide application greatly reduced adult A. petiolata, the appearance of new rosettes each year means the population of this invasive species would recover as soon as spraying is terminated. Because individuals are capable of self- pollination (Anderson et al. 1996, Cruden and McClain 1996), one individual can restart a population (Cavers et al. 1979, Baskin and Baskin 1992, Nuzzo 1993, Byers and Quinn 1998) and efforts to control A. petiolata populations that fall short of complete and long- term removal within a target area are not likely to be effective (Baskin and Baskin 1992, Nuzzo 1993). Management goals and constraints on time and financial resources will influence the success of herbicide application as a control method. If herbicide use is warranted, application of herbicide earlier in the fall should be considered, to maximize activity of the herbicide and minimize the number of rosettes that escape spray by virtue of being leafless or covered with leaf litter. Treatment may need to be coupled with spot- spaying or hand-removal of remaining adults in early spring to more effectively decrease populations (Nuzzo 1991). If our inference that recruitment of new rosettes is due to seed dispersal from nearby unsprayed areas is correct, then treatment of larger areas is necessary. It should be noted, however, that the management decision to use dormant- season herbicide focuses on the adult life stage of A. petiolata, and may prolong effects rosettes have on forest floor communities. Similar consideration should be taken for other methods of control, including hand-weeding and select biological control agents (Skinner and Blossey 2005). While the continued presence of the rosettes in the sprayed plots made it impossible to determine the full effect of A. petiolata on the forest floor plant community, the modest changes we have documented over this five year study suggest A. petiolata is competing with members of the plant community. Future assessment of native plant response to A. petiolata control measures in the field should be conducted after A. petiolata adult and rosette density has been significantly decreased for multiple years. Further determination of allelopathic properties of A. petiolata, the trophic levels affected, and the length of time and the distance of influence of allelopathic compounds will benefit our understanding of how this species interacts with native communities.

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Zar, J. H. 1999. Biostatistical Analysis, 4th edition. Prentice Hall, Upper Saddle River, NJ. 663+ pgs.

26 Table 1. Survival of Alliaria petiolata from Oct. to May each year averaged across 1 x 1 m plots in unsprayed vs. sprayed treatments, and randomized block ANOVA of each year’s plot-based survival data. Stands (old-growth, second-growth) were blocks. Survival was square root transformed to meet assumptions of homogeneity of variances. See Appendix C for sample size. Bold indicates significance at α = 0.05.

Mean survival ANOVA statistics Source term unsprayed sprayed df MS F P

May 2001 / Oct. 2000 density 0.34 0.10 Stand 1 0.068 1.17 0.2833 Treatment 1 1.479 25.46 <0.001 Error 89 0.058

May 2002 / Oct.2001 density 0.66 0.38 Stand 1 1.073 5.50 0.0223 Treatment 1 0.044 0.23 0.6358 Error 61 0.195

May 2003 / Oct. 2002 density 0.58 0.06 Stand 1 0.153 1.66 0.2020 Treatment 1 4.868 52.99 <0.001 Error 65 0.092

May 2004 / Oct. 2003 density 0.63 0.08 Stand 1 0.284 6.05 0.0159 Treatment 1 7.616 162.11 <0.001 Error 85 0.047

May 2005 / Oct. 2004 density 1.00 0.31 Stand 1 0.053 0.28 0.6018 Treatment 1 2.703 14.25 0.0005 Error 38 0.190

27 Table 2. Effect of treatment (sprayed vs. unsprayed) on adult A. petiolata cover (Fig. 1) on 1 x 1 m plots each May, determined by Friedman’s method for randomized blocks. Stands (old-growth, second-growth) were the blocks. CMH is the Cochran-Mantel- Haenszel Statistic determined from the rank scores. See Appendix C for sample size. Bold indicates significance at α = 0.05.

Year n CMH P

2000 100 0.02 0.88

2001 100 11.8 <0.0001

2002 100 1.54 0.21

2003 93 24.1 <0.0001

2004 90 40.47 <0.0001

2005 91 0.13 0.72

28 Table 3. Univariate repeated measures ANOVA of May A. petiolata rosette cover from 2000 through 2006, analyzed as a split-plot design with stands (old-growth, second- growth) as the split plots. The appropriate F test for “Treatment” (sprayed vs. unsprayed) is that given on the bottom line, where the denominator is the mean square of the plot (stand × treatment) term. Cover was arcsine square root transformed to meet assumption of homogeneity of variances. See Appendix C for sample size. Bold indicates significance at α = 0.05.

Source term df MS FP

Model 109 0.70 5.80 <0.0001

Error 460 0.12

Corrected Total 569

Stand 1 3.10 25.88 <0.0001

Treatment 1 0.10 0.86 0.3550

Year 5 8.65 72.09 <0.0001

Treatment × Year 5 0.23 1.89 0.0952

Plot (Stand × Treatment) 97 0.29 2.41 <0.0001

Hypothesis test using the MS for Plot (Stand × Treatment) as the Error term

Treatment 1 0.10 0.36 0.5524

Table 4. Mean plant species richness, 2000–2005, in sprayed vs. unsprayed 1 x 1 m plots in old-growth and second-growth stands. Statistics are from randomized complete block ANOVA, contrasting treatments, with stands as blocks. See Appendix C for sample size. Bold indicates significance at α = 0.05, and * indicates marginal significance where 0.05 < P < 0.10.

Old-growth Second-growth Stand Treatment Year Sprayed Unsprayed Sprayed Unsprayed df F P df F P

2000 6.6 5.4 10.8 9.6 1, 9948.79 <0.0001 1, 99 3.65 *0.0590 2001 8.9 7.7 11.1 11.4 1, 9918.82 <0.0001 1, 99 0.37 0.54

30 2002 5.4 4.8 8.6 8.8 1, 9954.21 <0.0001 1, 99 0.24 0.63 2003 7.4 7.0 7.8 7.0 1, 91 0.13 0.72 1, 91 1.38 0.24 2004 8.8 8.0 10.1 10.2 1, 887.40 0.0079 1, 88 0.20 0.65 2005 8.7 8.0 10.6 10.5 1, 9013.77 0.0004 1, 90 0.25 0.62

Table 5. Shannon-Wiener diversity indices of plant species, 2000–2005, in sprayed vs. unsprayed 1 x 1 m plots in old-growth and second-growth stands. Statistics from randomized complete block ANOVA, contrasting treatments, with stands as blocks. See Appendix C for sample size. Bold indicates significance at α = 0.05, and * indicates marginal significance where 0.05 < P < 0.10.

Old-growth Second-growth Stand Treatment Year Sprayed Unsprayed Sprayed Unsprayed df F P df F P

31 2000 1.4 1.2 2.1 1.9 1, 9963.20 <0.0001 1, 99 3.79 *0.0544 2001 1.8 1.6 2.0 2.0 1, 9914.61 0.0002 1, 99 1.79 0.18 2002 1.3 1.0 1.7 1.7 1, 9941.73 <0.0001 1, 99 2.38 0.13 2003 1.6 1.5 1.6 1.6 1, 90 0.19 0.66 1, 90 1.30 0.26 2004 1.8 1.5 1.9 1.9 1, 8812.14 0.0008 1, 88 2.47 0.12 2005 1.7 1.4 2.0 2.0 1, 9043.55 <0.0001 1, 90 2.78 *0.0991

31 Table 6. Effect of treatment (sprayed vs. unsprayed) on peak forest floor community cover in the old and second-growth stands as determined by multiple response perumation procedure (MRPP). The MRPP test statistic, A, is the chance-corrected within-group agreement describing the amount of similarity within a group (McCune and Grace 2002). See Appendix C for sample size. Bold indicates significance at α = 0.05, and * indicates marginal significance where 0.05 < P < 0.10.

Stand Year A P

Old-growth 2001 0.0048 0.1088 2002 0.00620.1054 2003 -0.00450.8172 2004 0.0070*0.0989 2005 0.0073*0.0988

Second-growth 2001 -0.0005 0.5241 2002 0.0071 0.0299 2003 0.00170.2903 2004 0.00040.4142 2005 -0.00110.6124

32 Table 7. Contingency table reporting the number of sprayed versus unsprayed plots, with and without Podophyllum peltatum in the old-growth stand. Fisher’s Exact Test found no treatment effect (P = 0.71).

absent present total unsprayed 15 6 21 sprayed 16 4 20 total 31 10 41

Table 8. Contingency table reporting the number of sprayed versus unsprayed plots, with and without Podophyllum peltatum in the second-growth stand. Fisher’s Exact Test found no treatment effect (P = 0.50).

absent present total unsprayed 21 4 25 sprayed 18 7 25 total 39 11 50

33 Table 9. Contingency table reporting the number of sprayed versus unsprayed plots, with and without Stellaria media in the old-growth stand. Fisher’s Exact Test found no treatment effect (P = 0.35).

absent present total unsprayed 9 12 21 sprayed 12 8 20 total 21 20 41

34 Figure 1. Mean May A. petiolata adult and rosette cover in each stand × treatment combination (old-growth unsprayed, old-growth sprayed, second-growth unsprayed, second-growth sprayed), 2000–2005. Means based on 1 x 1 m plots; see Appendix C for sample size.

Old-growth Second-growth

60 60 Unsprayed Sprayed 50 50

40 A. petiolata 40 A. petiolata

30 30

20 20

10 10 percent cover of adultpercent cover of

percent cover of adult 0 0 2000 2001 2002 2003 2004 2005 2000 2001 2002 2003 2004 2005 Year Year 60 60

50 50 rosettes rosettes 40 40

30 30 A. petiolata A. petiolata 20 20

10 10

0 0 percent cover of percent cover of 2000 2001 2002 2003 2004 2005 2000 2001 2002 2003 2004 2005 Year Year

35 Figure 2. Mean May A. petiolata adult (2001–2005) and rosette (2000–2005) density in each stand × treatment combination (old-growth unsprayed, old-growth sprayed, second- growth unsprayed, second-growth sprayed). Means based on 1 x 1 m plots; see Appendix C for sample size.

Old-growth Second-growth

18 18 unsprayed 16 16 sprayed 14 14 ) ) 2 12 2 12 10 10 adult density density adult adult density 8 8 6 6 (individuals/m (individuals/m 4 4 A. petiolata A. petiolata 2 2 0 0 2001 2002 2003 2004 2005 2001 2002 2003 2004 2005 Year Year

350 350

300 300 ) 250 ) 2 250 2

200 200 rosette density 150 rosette density 150 (individuals/m 100 (individuals/m 100

A. petiolata 50

0 0 2000 2001 2002 2003 2004 2005 2000 2001 2002 2003 2004 2005 Year Year

36 Figure 3. Nonmetric multidimensional scaling (NMDS) ordination of peak percent covers of all species except Alliaria petiolata in sprayed (solid symbol) and unsprayed (open symbol) plots in the old-growth (circles) and second-growth (triangles) stands in Hueston Woods State Nature Preserve, OH. The only year when composition in sprayed vs. unsprayed treatments differed significantly based on MRPP (Table 6) was 2002 (in second-growth stand only). Ordinations for the other years (2001, 2003, 2004, and 2005) similarly showed discrimination of old-growth vs. second-growth stands on dimension 1, but no discrimination of treatments, (A) 2001, (B) 2002, (C) 2003, (D) 2004, and (E) 2005. See Appendix C for sample size.

37 A.

38 B.

39 C.

40 D.

41 E.

42 Figure 4. Spring perennial percent cover (mean + SE), old-growth stand, 2000–2005. Means based on 1 x 1 m plots; see Appendix C for sample size. Adapted from Slaughter (2005).

70 Sprayed Unsprayed 60

40 Percent Cover 30

0 2000 2001 2002 2003 2004 2005

43 Figure 5. Spring perennial percent cover (mean + SE), second-growth stand, 2000–2005. Means based on 1 x 1 m plots; see Appendix C for sample size. Adapted from Slaughter (2005).

20 Percent Cover

15 Sprayed 10 Unsprayed 5

0 2000 2001 2002 2003 2004 2005

44 Figure 6. Podophyllum peltatum percent cover (mean + SE) from 2000–2005. Means based on 1 x 1 m plots; see Appendix C for sample size.

9 OG Sprayed OG Unsprayed 8 SG Sprayed SG Unsprayed 7

3 mean percent cover Podophyllum peltatum 2

0 2000 2001 2002 2003 2004 2005

45 Figure 7. Stellaria media percent cover (mean + SE) in the old-growth stand from 2000– 2005. Means based on 1 x 1 m plots; see Appendix C for sample size.

50 Sprayed

Unsprayed 40

30 mean percent cover

Stellaria media 10

0 2000 2001 2002 2003 2004 2005

46 CHAPTER 2

The effects of June precipitation on Alliaria petiolata growth, density and survival

*This chapter has been submitted for publication with authorship Hochstedler and Gorchov to Ohio Journal of Science.

Abstract The factors that determine population dynamics of invasive plant species are not well studied. Alliaria petiolata (garlic mustard), an invasive biennial, exhibits annual fluctuation in rosette and adult density. June precipitation has been found to correlate with rosette A. petiolata density in October and adult density the following May. Since ability to predict density would facilitate management of this invasive species, we experimentally tested the impact of precipitation on A. petiolata rosette growth and survival. Rain was excluded in June 2005 from thirty-six 0.8 x 0.8 m plots in a second- growth woodlot in southwest Ohio. Plots were lined to a depth of 20 cm with a moisture barrier, and randomly assigned to receive a dry (1 cm), average (10 cm) or wet (20 cm) water treatment. In the central 0.25 m2 of each plot we assessed soil moisture, rosette root depth, root and shoot biomass, and survival. Soil moisture content, measured with a time domain reflectometer, was significantly affected by treatment. However, rosette biomass, root length, fruit production and survival did not differ among treatments. Assessment of soil water availability between treatments indicated dry treatments may not have dried the soil as much as occurs in drought years. While the hypothesis that heavier June precipitation enables rosettes to survive summer drought was not supported, it cannot be rejected based on our experiment. June precipitation is probably not a reliable predictor of A. petiolata rosette survival in years with above average precipitation; however the effect of spring drought on A. petiolata requires further investigation.

Introduction Due to the impacts of invasive species on natural communities (Vitousek et al. 1996, Wilcove 1998, Parker et al. 1999, Mack 2000) and economic costs of control

47 (Pimentel et al. 2005), ecologists, conservationists and land managers are concerned about factors that influence population densities of introduced species (D'Antonio and Kark 2002, Mack 2005). The role of abiotic environmental stress (e.g. extremes in temperature, moisture and light) in determining potential invasibility (Burns 2004) as well as distribution (Beerling 1993) and density fluctuations (Winterer et al. 2005) in established invasive populations has important implications for invasive management (Alpert et al. 2000). If spatial or temporal fluctuations in an abiotic factor affect demographic rates, and hence population size of an invasive species, this abiotic factor may have predictive power for decisions regarding management and control of the species (Slaughter et al. in press). A native of western Eurasia, Alliaria petiolata (M. Bieb.) Cavara and Grande (garlic mustard, Brassicaceae) is an invasive understory herb established throughout the northeastern United States and adjacent Canada (Nuzzo 1993). A biennial, seeds germinate in February or March, and the rosettes (juveniles) live through the summer and often remain green throughout the winter. In the spring of the second year, adults flower, senesce, and set seed (Cavers et al. 1979). Some seeds germinate the following spring, while others remain viable in the soil. This seed bank persists about five years (Baskin and Baskin 1992, Byers and Quinn 1998). Most commonly found in shaded riparian, wooded, and roadside areas in the east (Nuzzo 1993, Shuster et al. 2005), A. petiolata populations exhibit higher survivorship and germination in floodplains than in upland forests with generally drier soils, greater light penetration, and absence of disturbance from floods (Byers and Quinn 1998, Meekins and McCarthy 2001). From March to July both first-year rosettes and second-year adults are present, and population densities fluctuate from year to year (Baskin and Baskin 1992, Carlson and Gorchov 2004, Winterer et al. 2005, Slaughter et al. in press). Slaughter et al. (in press) found that both survival of rosettes from May to October and adult density the following May correlated positively with June precipitation over a five year period. For example, in a second-growth stand, rosette survival was lowest (2.5%) following the driest June (6.98 cm) and very high (26.9%) following the wettest June (13.63 cm). They hypothesized moist soil promotes survival of rosettes through the summer, with greater reproduction of A. petiolata following wetter years.

48 While comparisons across years are useful for detecting relationships between weather and population dynamics, establishing cause-and-effect requires controlled studies. In the case of A. petiolata, interannual variation in rosette demography could also be due to variation in temperature or rosette competition with adult A. petiolata, which may co-vary with precipitation. Rain exclosures have been employed in a variety of ecosystems and habitats to manipulate precipitation duration, intensity, and timing in otherwise natural settings (Foale et al. 1986, Owens 2003). Long-term ecosystem studies using permanent rain exclosures have been based in temperate mesic grassland (Harrington 1991, Fay et al. 2000), rangeland (Svejcar et al. 1999) semi-desert grassland (English et al. 2005) , and deciduous forest (Bredemeier 1995, Hanson et al. 1995, Hanson et al. 1998). Small-scale, temporary rain exclosures (Frampton et al. 2000, Flemmer 2003) however, reduce costs and enhance flexibility for short-term ecological studies (Owens 2003). Implementing subcanopy rain shelters in forest stands with considerable shrub growth pose additional logistical problems as shelters either need to be small enough to fit between shrubs, be large enough to cover shrubs, and/or need to preclude rainfall in and around shrub and tree trunks (Jacoby et al. 1988). Multiple small-scale exclosures avoid pseudoreplication in experimental design, an issue of large- scale exclosure designs due to cost constraints (see Hanson et al. 1998). Our objective in this study was to assess the impact of June precipitation on A. petiolata populations in a temperate deciduous forest understory. Specifically, we tested the hypothesis that heavier June precipitation promoted more extensive root growth enabling rosettes to survive summer drought (Slaughter et al. in press). To eliminate confounding effects of temperature and competition with adult A. petiolata, we tested rosette growth and survival over a single season through a rain manipulation experiment at a site lacking an adult cohort. Testing of this hypothesis is compelling because the ability to predict density would facilitate management of this invasive species. Fall season herbicide spraying of rosettes is an effective control method of adult A. petiolata (Carlson and Gorchov 2004, Slaughter et al. in press). Support of this hypothesis would suggest that control of this invasive by fall herbicide application would be most important and cost effective in years when June precipitation was high (Slaughter et al. in press).

Methods

STUDY SITE. This study was conducted in an approximately 90-year, 4 ha woodlot (Vankat and Snyder 1991) 2.5 km NNE of Oxford, Ohio, at the Miami University Ecology Research Center (ERC), Butler Co. (39°30' N, 84°44' W). Long- term (20-year) mean annual precipitation is 92.4 cm and mean annual temperature is 11.4°C. Forest soils are moderately eroded Russell-Miamian silt loams with 2-6% slopes over limestone bedrock (Lerch et al. 1980, Vankat and Snyder 1991) with a mean bulk density of 1.077 g cm-3 (Appendix J). The site was chosen because of its uniform slope, consistent soil type, and protection from the public. Second-growth Acer saccharum and Ulmus rubra were the major canopy dominants, with a dense shrub layer of Lonicera maackii (Amur honeysuckle). Species common in the understory included Parthenocissus quinquefolia, Stellaria media, Sanicula canadense, Pilea pumila, Hackelia virginiana, Polygonum cespitosum, Impatiens spp. and Viola spp. (nomenclature follows Gleason and Cronquist 1991) (Appendix K).

FIELD EXPERIMENT. Thirty-six 50 cm x 50 cm plots were established in areas of rosette density >15 per 0.25 m2 with plot centers > 2.5 m from each other and > 1 m from trees and stems of large Lonicera maackii. Around each plot a fixed-location rain shelter was constructed and covered with a clear polyethylene roof (Harrington 1991, Fay et al. 2000, Hanson et al. 2003, Owens 2003) with open ends to maximize ventilation. Hanson et al. (1998), Harrington (1991), and English et al. (2005) found the effects of polyethylene covers on understory microclimate to be insignificant. Each shelter was constructed of ½ inch PVC, measured 175 x 175 cm, was 100 cm tall at the peak, was oriented north-south, and anchored with landscaping staples at each corner. Each shelter covered a central 80 x 80 cm experimental plot containing a 50 x 50 cm sampling area (Figure 1). Lateral movement of surface and ground water was restricted by a 20 cm deep subsurface barrier of aluminum sheeting installed around the plot (Harrington 1991, Fay et al. 2000, Flemmer 2003, Owens 2003). Trailing vegetation and roots were clipped at the plot edge in order to install the aluminum sheeting and minimize disturbance to the plot interior.

50 Plots were randomly assigned to dry (1cm/month), average (10 cm/month), or wet (20 cm/month) June water treatment to simulate drought, average, and high rainfall for the month of June in southwest OH. Treatments were based on historic state climatology records (Rogers 1993) and June precipitation over the past 20 years at the ERC (Ohio Agricultural Research and Development Center, Ohio State University; mean = 9.7 cm). Treatments did not differ in rosette density at the onset of the experiment (Appendix L). Shelters were installed over plots May 23, 2005; rainfall in May prior to this date was below average. Beginning in June, one-eighth of the assigned water treatment was applied eight times during the month (twice per week) using a low-pressure backpack sprayer and watering can. Water used in the experiment was collected at the ERC from a barn roof. Due to lack of precipitation during the early part of the month, water from a rainwater supply pond was substituted when rains were not frequent. Nutrient concentration in these water sources was low (Appendix M). The polyethylene plastic covering the shelters was wiped every other day to clear the surface of fallen leaves, debris and dust, and checked for holes from fallen branches after each storm. To monitor soil moisture-precipitation relationships in each treatment, soil water content in each plot was measured weekly with a time domain reflectometer (TDR, Moisture Point, Environmental Sensors, Inc.) (Jackson et al. 2000) with 20 cm probes following the procedure of Topp and Davis (1985). Simultaneous sampling of soil water content by destructive gravimetric and TDR methods was conducted at the study site in September 2005 to verify TDR readings; soil cores for gravimetric measurements were collected to a depth of 20 cm and dried at 105˚ C to a constant weight of <0.01% change. The linear relationship between TDR readings and gravimetric measurements indicated consistent readings from the TDR (Figure 2). In order to gauge plant and soil responses to water treatments in rain manipulation experiments, soil water content was assessed in relation to soil water potential as an indicator of water availability (Klute 1986a, Carter 1993, Hillel 1998). Pressure plates were used to determine soil water potential as they allow for the equilibration of soil water in a sample at known pressure which can be subsequently weighed to determine soil water content. This method is advantageous as correlations of soil characteristics are more reliable when measured simultaneously (Phene et al. 1992). Pressure plates

51 accommodate measurement of undisturbed soil samples; undisturbed soil samples are more representative of field conditions because soil structure and pore-size distribution influences soil water holding capacities (Klute 1986b). Undisturbed soil samples (rings: 2.95 cm h x 5.35 cm d) were collected from between 1–7 cm below ground level using a soil core sampler. Soil water potential was measured using 5 and 15 bar pressure plate extractors following Klute (1986b) and Carter (1993). After saturation with distilled water, water was removed from samples at six pressure levels (0.33–15.0 bars) and water content by mass assessed after equilibration at each level of pressure. A soil moisture retention curve was constructed following the procedure of Bruce and Luxmoore (1986) and Carter (1993). The retention curve is reported here as an assessment of plant available water in soils (soil matric potential) over the range of soil water contents observed in the three treatments (see Hanson et al. 1998, English et al. 2005). To assess the reduction of photosynthetic active radiation (PAR) by the polyethylene plastic we measured PAR above and below the plastic in full sunlight using a LI-COR quantum line and point sensor. To assess the effect of shelters on microclimate, we measured the following parameters at 12 non-sheltered sites within the study area: PAR during an overcast day (Gendron et al. 1998), soil temperature with a soil thermometer at depths of 5 cm and 10 cm, and soil water content. At the end of June, rosette density was recorded for each plot, and two rosettes per plot (closest to two predetermined points outside the sampling area) were excavated with a hand trowel to assess root length and root and shoot biomass. Rosettes were rinsed to remove soil particles, root lengths were measured, and roots and shoots were dried in a drying oven to a constant weight. Polyethylene roofs were removed from the shelters at this time, however PVC frames were left in place for the remainder of the study to deter deer access to the plots. In October 2005 and May 2006, density was again recorded. In May 2006 fruits of all sizes were counted in each plot; immature fruits with any brown coloration were not included.

DATA ANALYSIS. The effects of water treatment on soil moisture, rosette growth, survival, density and number of fruits, and on shelter microclimate were determined using one-way ANOVAs (α = 0.05) with SAS software, Version 9.1.3 of the SAS

52 System for Microsoft® Windows 2001 (SAS Institute, Inc. Cary, NC). We also used one-way ANOVAs to assess whether June precipitation affects rosette density on June 30, 2005 (“June”), October 27, 2005 (“October”), and May 31, 2006 (“May 2006”), as well as percent survival from June 1 to each of these three dates. To meet ANOVA assumptions of homoscedasticity, densities were log(x+1) transformed, October and May 2006 survival were arcsine transformed, and root biomass was square root transformed. One outlier was removed from each of the following analyses: root length, root biomass, and shoot biomass.

Results

PRECIPITATION AND SOIL MOISTURE. Precipitation during the month of June was 9.2 cm, 0.8 cm less than the water added to the average treatment (Figure 3). After one outlier was removed from the first week’s measurements, soil in the dry treatment was drier than that in the average treatment during each of the four weeks in June, but soil moisture did not differ between average and wet plots in any of these weeks (Figure 4, Appendix N). Soil water potential was asymptotically related to soil water content (Figure 5).

ROSETTE RESPONSE. Treatments did not differ in density of rosettes on June 30, in October, or in May 2006 (Table 1). Neither did treatments differ in percent survival through June, October, or May 2006 (Figure 6). Treatment did not affect rosette root length, root biomass, or shoot biomass (Table 1). Diseased spots were noted on many rosettes in the plots by mid-June, however these were noted across all treatments with equal prevalence. Treatments did not differ in number of fruits per adult in May 2006 (Table 1), and no differences were noted in relative stage of fruit maturity.

SHELTER AND MICROCLIMATE. Rain shelters were effective at excluding naturally occurring rainfall from sample plots, as evidenced by the decline in soil moisture in the dry plots during and after the rains in the second week of June (Figure 3 and Figure 4) and by the rain shadow seen outside the plots immediately after a rain event. Light was reduced to 89.48 % + 0.26 (mean + SE, n = 32) under the polyethylene sheeting on the shelters (Appendix O), and by potentially more between periods when fallen leaves, debris and dust were cleared from the surface. PAR reaching plots did not differ among

53 treatment plots and non-sheltered ambient sites (df = 3, F = 1.91, P = 0.14). Soil temperatures did not differ among treatment plots and ambient sites (at 5 cm: df = 3, F = 2.01, P = 0.13; at 10 cm: df = 3, F = 1.57, P = 0.2105) (Appendix O). See Appendix P for additional comments on rain shelter design and use.

Discussion June precipitation treatments had no effect on A. petiolata growth, survival or number of fruits, however lack of treatment differences was not because soil moisture was unaffected. The dry treatment was drier than the average and wet treatments, although the latter two did not differ. This suggests that the average treatment supplied water sufficient to saturate the soil. Byers & Quinn (1998) found that rosettes experience greatest mortality during dry summer months, however our soil moisture manipulations in June did not affect root length or biomass, which we hypothesized would influence survivorship during later months of moisture stress. The dry moisture regime may not have been dry enough to avoid low water availability characteristic of a year with a dry June. Soil water content of dry treatments averaged 29.6 % in the first 3 weeks; at these levels soil water availability was about -2 bars, not much lower than the water availability in the average treatment (water content of 35.9%) (Figure 5). Similar results were noted in a forested rain manipulation study by Hanson et al. (1998) where deep soils were significantly different in soil water content, but not in soil water potential. There are reasons to believe that soil water content and water availability in our ‘dry’ treatment were not as low as those that occur in years when June precipitation is low. Throughout June, soil water content in the dry treatment was similar to that at non- sheltered ambient sites, although ambient precipitation was 9 times that of the dry treatment and close to long-term average. This was likely due to the fact that throughfall is less than precipitation, due to interception and stemflow; growing-season throughfall was 76.3% of above-canopy rainfall in a broad-leaved deciduous forest in Japan (Deguchi et al. 2006). Throughfall at our site during June 2005, as measured at a single HOBO weather station (Onset Computer Corp), was 5.54 cm (J.P. Costanzo, unpublished

54 data), 60.2% of precipitation the same month (Figure 3). Since our water addition treatments were based on above-canopy precipitation, rather than throughfall, soils were presumably less dry than they would be in a year when June precipitation equaled 1 cm. Because the dry treatment did not simulate drought conditions, the hypothesis that heavier June precipitation enables A. petiolata rosettes to survive summer drought cannot be rejected based on our experiment. Low June precipitation may reduce rosette survival, but in years when June precipitation is above average it is probably not a reliable predictor of rosette survival. Instead of replicating drought rainfall amounts, withholding water until symptoms of wilting indicate drought-stress may be more effective in inducing extreme conditions (Baruch et al. 2000). Other studies have looked at the impacts of varied precipitation regimes and water availability on invasive population dynamics (Alpert et al. 2000). Compensation and plasticity in invasive populations (Claridge and Franklin 2002) may aid establishment in new habitats and spread of existing populations (Kolar and Lodge 2001). Alliaria petiolata populations seem to compensate for lower survival rates (decreased density) by allocating increased proportions of biomass to reproduction and thus yielding greater seed banks (Byers and Quinn 1998, Meekins and McCarthy 2000). Management practices that reduce survival may not be an effective control method if population-level seed production is not greatly influenced by reduced survival. Year to year variation in moisture may, however, affect reproduction, and future studies should determine more specifically how precipitation patterns and soil moisture availability influence reproduction.

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60 Table 1. Mean and 95% confidence intervals of A. petiolata response variables in dry, average and wet treatments, and one-way ANOVA statistics. Density and fruit number were averaged across 50 x 50 cm sampling areas; root length and root and shoot biomass were averages of two rosettes per plot. There was no significant effect of water treatment on any of these variables (all variables, df = 2).

Dry Average Wet F P

Rosette density, 130.1 ± 33.2 143.3 ± 40.1 145.0 ± 39.8 0.13 0.88 June 2005 Rosette density, 31.3 ± 15.4 21.6 ± 12.6 20.0 ± 11.2 1.01 0.38 October 2005 Rosette density, 19.5 ± 10.2 13.1 ± 8.9 11.7 ± 8.7 0.92 0.41 May 2006 Root length (cm) 9.8 ± 1.1 9.4 ± 1.0 8.8 ± 0.8 1.35 0.27 Root biomass 17.9 ± 6.7 17.7 ± 10.8 16.2 ± 6.7 0.57 0.57 (mg) Shoot biomass 78.1 ± 21.7 60.6 ± 38.1 64.9 ± 26.1 2.07 0.14 (mg) Fruits per 15.4 ± 5.0 19.0 ± 9.4 18.4 ± 9.6 0.21 0.82 individual

61 Figure 1. Fixed-location rain shelter with sample plot (50 x 50 cm) and subsurface moisture barrier (80 x 80 x 20 cm).

62 Figure 2. Calibration of percent soil water content as measured by a time domain reflectometer (TDR, %, volume/volume) with gravimetric soil water content (%, mass/mass) (y = 1.3197x - 3.7548, R2 = 0.9334).

25 TDR water content (%)TDR water 15

5 10 15 20 25 30 35 40 gravimetric water content (%)

63 Figure 3. Weekly ambient precipitation at the ERC from April 1 thru July 28, 2005, throughfall for June 2005, average ambient precipitation for the month of June, and the amount of water applied to each treatment (dry, average, and wet).

8 ambient dry trmt 7 average trmt wet trmt 6 ambient June average throughfall 5

2 Weekly precipitation (cm)

7 1 5 9 1 6 0 4 8

l 2 1 1 3 1 2 i y e r l i a y n e e y y p r l l a u n n u u A p M J u u J J A M J J

64 Figure 4. Weekly soil water content (means + SE) from May 30–July 19, 2005 in treatment and ambient plots. For each date, treatments sharing a letter (a, b, or c) did not have different soil water content levels as determined by Bonferroni (Dunn) t-test (Appendix N). One-way ANOVAs revealed that treatment significantly affected soil water content each week (all ANOVAs df = 3 and P < .0001; week 1: F = 11.01, week 2: F = 13.05, week 3: F = 19.10, and week 4: F = 16.54).

40 Dry Average a a 38 Wet a 36 Ambient a a 34 a,b a b a 32 b,c 30 b

28 b c 26

soil content (%, water v/v) b 24 b b 22

20 l y n n n n ul -Jul Ju J -Ma 5 0 5-Jun 11- 17- 3 11-Ju 17-Ju 23-Ju 29-Ju

65 Figure 5. Soil moisture release curve for Russell-Miamian silt loam soils at study site. Line was fit with a power function, y = -3E+12x-8.2596, R2 = 0.6074.

- 3

- 6

- 9

water potential (bars) potential water 12

- 15

23 26 29 32 35

water content (%, v/v)

66 Figure 6. Effect of June water treatments on mean rosette survival (mean + 1 SE, n = 12 per treatment). One-way ANOVA indicated no difference in survival between treatments (June: df = 2, F = 1.74, P = 0.19; October: df = 2, F = 2.83, P = 0.07; and May 2006: df = 2, F = 1.64, P = 0.21).

100

80 Dry

70 Average

60 Wet

40 Percent survival 30

0 May- Jun-05 Jul-05 Aug-05 Sep-05 Oct-05 Nov-05 Dec-05 Jan-06 Feb-06 Mar-06 Apr-06 May- 05 June 2005 October 2005 May 200606

67 CONCLUSION

In this study, we examined the effects of five years of annual dormant season herbicide treatment on Alliaria petiolata, garlic mustard, and the subsequent effects on the forest floor community in southwestern Ohio. Five years of fall herbicide application (2000-2004) did not eliminate A. petiolata from the sprayed plots in either stand, but adult survival was reduced annually four of the five years in the sprayed plots (not 2002). Adult and rosette cover fluctuated across years in the unsprayed plots; treatment reduced adult cover in most years (2001, 2003, and 2004), but rosette cover was not affected by spray treatment. While we did not expect the rosette cohort to be directly affected by herbicide, we expected the dramatic reduction in adult cover and density due to herbicide would greatly reduce seed production and therefore seedling recruitment in the sprayed plots. We attribute the continued presence of rosettes in the spray plots to seed dispersal from A. petiolata adults growing outside the treated buffer areas surrounding the plots. Because of compensation and plasticity in A. petiolata populations (Byers and Quinn 1998, Meekins and McCarthy 2000, Claridge and Franklin 2002), management practices that reduce survival may not be an effective control method if population-level seed production is not decreased. We also investigated the impact of June precipitation on A. petiolata rosette growth and survival to test the hypothesis that heavier June precipitation enables rosettes to survive summer drought. We did not find that quantity of June precipitation affected growth or survival of A. petiolata rosettes. Soil moisture was affected by treatment, however the dry moisture regime may not have been dry enough to simulate drought conditions. Because of this, the hypothesis that heavier June precipitation enables A. petiolata rosettes to survive summer drought cannot be rejected based on our experiment. Low June precipitation may reduce rosette survival, in agreement with many findings in invasion ecology linking the positive effects of water and invasibility (Alpert et al. 2000). In years when June precipitation is average or above, however, precipitation is probably not a reliable predictor of A. petiolata rosette survival. Year to year variation in moisture may affect reproduction, and future studies should determine more specifically how precipitation patterns and soil moisture availability influence reproduction.

68 Suppression of A. petiolata adults did not cause a change in forest floor community plant richness, diversity or composition in 2004 and 2005. Only early in the study, in 2002, was there a significant difference in community composition between the sprayed and unsprayed plots, and this only in the second-growth stand. Nonmetric multidimensional scaling ordination results showed no differences in community composition where previous detrended correspondence analyses (DCA) had concluded significant treatment affects (Carlson and Gorchov 2004, Slaughter 2005), possibly due to DCA’s lack of robustness and documented failure to accurately display patterns within data (Minchin 1987, McCune and Grace 2002). In the old growth stand, spring perennials tended to increase in cover in the sprayed plots from 2000–2005 and had marginally higher cover in sprayed plots in 2005. In a similar study, cover of annuals, vines and tree seedlings increased over three years where A. petiolata was removed by hand, and significant differences in diversity and community composition were found (McCarthy 1997). This study differed from ours, however, as rosettes were continuously removed from the treatment plots and did not interact with the forest floor plant community throughout the spring, summer and fall. We attribute the compositional differences we observed in the forest floor community to the negative impacts of A. petiolata, but suggest that the reason the changes were so minor was due to the persistence of rosettes in the sprayed plots. As the herbicide treatment was applied in November, rosettes in the sprayed plots may have been directly or indirectly competing with other plant species from the time of germination in March through early fall. In greenhouse experiments A. petiolata rosettes outcompeted Quercus prinus seedlings and were equal competitors with Impatiens capensis (Meekins and McCarthy 1999). Alliaria petiolata may also affect other plants indirectly via its effect on mycorrhizal fungi since, like other members of the Brassicaceae, it has anti-fungal properties (Roberts and Anderson 2001). Alliaria petiolata disrupts arbuscular mycorrhizal fungi associations, thereby reducing growth of native tree seedlings under controlled conditions (Stinson et al. 2006). Alliaria petiolata may interfere with native forest floor herbs with high mycorrhizal dependency. Rosettes remaining in the sprayed plots may have reduced mycorrhizal fungi and in this way

69 indirectly affected the competitive ability of forest floor plant species (Roberts and Anderson 2001). Glyphosate is a non-selective herbicide and may negatively affect species other than A. petiolata that were in leaf at the time of the herbicide application. The sprayed plots had lower cover of these “wintergreen” species than the unsprayed plots in 2005 in the old-growth stand. This effect was also found in 2001 and 2002 in this stand (Carlson and Gorchov 2004, Slaughter and Hochstedler, unpubl. data), but was not found in a comparable study in Illinois (Nuzzo 1996). One of the wintergreen species in this study, an exotic annual, Stellaria media (chickweed), increased in the control plots, but not the sprayed plots, from 2000–2005; the change in cover (2000 to 2005) was significantly different between treatments. When S. media was excluded from the wintergreen species in the analysis of 2005 cover, the remaining species did not show a treatment effect. This suggests that lower S. media cover in the sprayed plots accounted for the negative effects of herbicide application on the wintergreen growth form, and possibly the decrease in the annuals in 2005, as well. In our study area, much of the S. media population germinated in the fall, and seedlings in close proximity to A. petiolata rosettes likely experienced direct mortality due to herbicide exposure. Stellaria media was the second (2004) and third (2005) most dominant species in the old-growth stand, and its increase in cover in the unsprayed plots over the course of this study may have confounded emerging patterns between sprayed and unsprayed plots in the community composition data. We anticipated that cover of forest floor species, except for A. petiolata, would increase in the sprayed plots relative to the unsprayed plots; S. media showed the opposite pattern. It is unlikely, though, that this pattern confounded our interpretations as the effects of treatment were not strong when growth forms were analyzed separately. Stellaria media is commonly documented as a weed in agricultural settings, disturbed areas and waste places (Defelice 2004), but we have found no publications that consider it a potential threat to intact, undisturbed forest floor communities. Similarities of S. media phenology to that of A. petiolata may make it a threat to spring perennial plants, in particular. In our study area, much of the S. media population germinated in the fall, over-wintered and was in leaf at the time of spring perennial emergence, often over-

70 topping native species by early May (pers. obs.). Unlike A. petiolata rosettes, S. media senesces by early June and may not influence growth of the forest floor plant community throughout the summer. It has the ability to form a significant seedbank; as many as 30,400 seeds can be produced per plant, and seed can remain viable in the soil for seven years, and possibly as many as 30 years (Lutman et al. 2002, Defelice 2004), making this plant potentially more difficult to control than A. petiolata. Restoration of areas invaded by A. petiolata should weigh the impacts of other imvasive species common in an area (Slaughter 2005). In addition to S. media, Lonicera maackii (Amur honeysuckle) is an established invasive at Hueston Woods State Park and the surrounding region (Trisel and Gorchov 1994). As an invasive shrub with early leaf expansion, L. maackii may pose a more serious threat to the forest floor plant community than A. petiolata or S. media. Lower cover and species richness of native herbaceous plant species is associated with L. maackii presence (Collier and Vankat 2002), and L. maackii reduces survival of tree seedlings and annuals (Gould and Gorchov 2000, Gorchov and Trisel 2003) and growth and reproduction of perennial herbs (Miller and Gorchov 2004). Future research and restoration of invaded communities should weigh the effects of all invasive species in an area to determine management priority, as well as how multiple invasive species affect the same area (Huenneke and Thomson 1995, Slaughter 2005). The modest compositional differences between treatments in the forest floor plant community suggest A. petiolata is negatively affecting some forest floor plant species. While these findings may help justify research on broad-scale control for A. petiolata, execution of any control measure, particularly introduction of non-native species as biocontrol agents, should also weigh the species’ impact relative to that which a dominant native herb might have on the same community. For instance, Dicentra cucullaria and D. canadensis combined had the highest peak cover of native species in the old-growth stand in 2005, and removal of these species may positively affect the remaining spring flora. Control of Dicentra, however, is not warranted because it is native to the area. When an invasive species dominates a stratum of vegetation, such as the shrub Lonicera maackii, which occurs at much higher densities than native shrubs such as Lindera benzoin (Miller and Gorchov 2004), its control is better justified. Management decisions

71 should consider whether control of an introduced species is inherently necessitated by virtue of being a non-native species, and to what extent evidence of competitive ability and comprehensive impacts on multiple trophic levels, including human health and welfare, should be required (Davis 2003, Gurevitch and Padilla 2004).

72 Literature Cited

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Claridge, K., and S. B. Franklin. 2002. Compensation and plasticity in an invasive plant species. Biological Invasions 4:339-347.

Collier, M. H., and J. L. Vankat. 2002. Dimished plant richness and abundance below Lonicera maackii, an invasive shrub. American Midland Naturalist 147:60-71.

Davis, M. A. 2003. Biotic globalization: does competition from introduced species threaten biodiversity? BioScience 53:481-489.

Defelice, M. S. 2004. Common chickweed, Stellaria media (L.) Vill.—“Mere chicken feed?” Weed Technology 18:193-200.

Gorchov, D. L., and D. E. Trisel. 2003. Competitive effects of the invasive shrub, Lonicera maackii (Rupr.) Herder (Caprifoliaceae), on growth and survival of native tree seedlings. Plant Ecology 166:13-24.

Gould, A. M. A., and D. L. Gorchov. 2000. Effects of the exotic invasive shrub Lonicera maackii on the survival and fecundity of three species of native annuals. American Midland Naturalist 144:36-50.

Gurevitch, J., and D. K. Padilla. 2004. Are invasive species a major cause of extinctions? Trends in Ecology and Evolution 19:470-474.

Huenneke, L. F., and J. K. Thomson. 1995. Potential interference between a threatened endemic thistle and an invasive nonnative plant. Conservation Biology 9:416-425.

Lutman, P. J. W., G. W. Cussans, K. J. Wright, B. J. Wilson, G. McN. Wright, and H. M. Lawson. 2002. The persistence of seeds of 16 weed species over six years in two arable fields. Weed Research 42:231-241.

McCarthy, B. C. 1997. Response of a forest understory community to experimental removal of an invasive nonindigenous plant (Alliaria petiolata, Brassicaceae).

73 Pages 117-130 in J. O. Luken and J. W. Thieret, editors. Assessment and Management of Plant Invasions. Springer, New York.

McCune, B., and J. B. Grace. 2002. Analysis of Ecological Communities. MjM Software Design, Gleneden Beach. 300 pgs.

Miller, K. E., and D. L. Gorchov. 2004. The invasive shrub, Lonicera maackii, reduces growth and fecundity of perennial forest herbs. Oecologia 139:359-375.

Minchin, P. R. 1987. An evaluation of the relative robustness of techniques for ecological ordination. Vegetatio 69:89-107.

Trisel, D. E., and D. L. Gorchov. 1994. Regional distribution, ecological impact and leaf phenology of the invasive shrub, Lonicera maackii. Bulletin of the Ecological Society of America 72:231-232.

74 75 76 Appendix C. Sample size.

Within each stand in Hueston Woods State Nature Preserve, Carlson and Gorchov (2004) established 50 plots, half randomly assigned as sprayed and the other half as unsprayed plots. Over the course of this study, some plots were lost, or affected by treefall or tip-up mounds, and were therefore dropped from the analyses. In 2003, three unsprayed plots and two sprayed plots in the old-growth stand, and two sprayed plots in the second-growth stand, were severely affected before May sampling. One sprayed plot in the old-growth was sampled in May, but was lost to treefall before June sampling, and was therefore used in the analyses of herbicide treatment on A. petiolata (“A. petiolata Control”), but not in community composition analyses based on peak cover from May and June (“Community Composition”). In 2004, two additional unsprayed plots in the old-growth stand were lost and affected by tree fall before May, and one additional sprayed plot was affected by treefall between the May and June sampling. In 2005, we resumed census of the previously lost unsprayed plot in the old-growth stand, but one additional sprayed plot was lost. All 50 plots in the second-growth stand were sampled in 2005.

Sample Size for Analyses 2003 2004 2005 Unsprayed Sprayed Unsprayed Sprayed Unsprayed Sprayed

A. petiolata Control Old-growth 22 23 20 22 21 20 Second-growth 25 23 25 23 25 25

Community Composition Old-growth 22 22 20 21 21 20 Second-growth 25 23 25 23 25 25

77 Appendix D. NMDS stress as a function of dimensionality for each year 2001–2005.

2005 2002

2004 2001

2003

78 Appendix E. Growth forms of all taxa found in sample plots in the old-growth and second-growth stands at Hueston Woods State Nature Preserve, based on (Gleason and Cronquist 1991). Hydrophyllum appendiculatum, a biennial, has been grouped with the spring perennials due to its similar phenology. Galium aparine has been classified as an invasive by some (Haragan 1991, Uva et al. 1997), but considered native by others (Gleason and Cronquist 1991). Spring perennial herbs were conspicuous in March, then flower, fruit, and senesce by late May or early June. Summer perennial herbs were conspicuous in May, then flower, fruit, and senesce by August or September. Taxa in leaf at the time of November herbicide treatment, “wintergreen” species, are noted with an asterisk (*). Introduced species are in bold.

Growth form Taxa included

Annuals Galium aparine*, Impatiens pallida, Pilea pumila*, Stellaria media*

Ferns Botrychium dissectum*, B. virginianum

Graminoids Carex spp.*, and other grass spp*.

Spring perennial Allium tricoccum, Aristolochia serpentaria, Cardamine concatenata, herbs Claytonia virginica, Dicentra cucullaria, D. canadensis, Erigenia bulbosa, Erythronium americanum, Floerkea proserpinacoides, Hydrophyllum appendiculatum, Osmorhiza longistylis*, Podophyllum peltatum, Polygonatum biflorum, Ranunculus abortivus, R. micranthus, R. recurvatus, Sanguinaria canadensis, Senecio obovatus*, Trillium sessile, Viola spp.* Summer perennial Actaea alba, Agrimonia sp., Amphicarpaea bracteata, Arisaema herbs triphyllum, Aster divaricatus*, Circaea lutetiana, Cryptotaenia canadensis*, Eupatorium purpureum, Eupatorium rugosum, Galium circaezans*, Galium triflorum*, Geum spp.*, Hackelia virginiana, Laportea canadensis, Oxalis sp., Panax quinquefolius, Phryma leptostachya, Polygonum virginianum, Sanicula spp.*, Senecio glabellus

Trees Acer negundo, Acer saccharum (including A. nigrum), Aesculus glabra, Asimina triloba, Carpinus caroliniana, Carya cordiformis, Celtis occidentalis, Cornus florida, Crataegus sp., Fagus grandifolia, Fraxinus americana, Juglans nigra, Liriodendron tulipifera, Ostrya virginiana, Prunus serotina, Quercus muhlenbergii, Ulmus rubra

Shrubs Asimina triloba, Lindera benzoin, Lonicera maackii*, Rosa multiflora, Rubus allegheniensis, Rubus sp., Sambucus sp.

Vines Parthenocissus quinquefolia, Rubus flagellaris, Smilax hispida*, Toxicodendron radicans*, Vitis sp.

79 Appendix F. Mean 2004 peak percent cover (+ SE) of species in 1 x 1 m sprayed and unsprayed plots in the Hueston Woods State Nature Preserve.

Species -- 2004 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 20 n = 21 n = 25 n = 23 Acer saccharum 7.50 ± 1.96 14.10 ± 2.67 3.76 ± 1.12 3.83 ± 1.10 Actaea alba 0.30 ± 0.30 0 0.48 ± 0.35 0.26 ± 0.19 Aesculus glabra 0 0 0.32 ± 0.32 0.17 ± 0.17 Agrimonia spp. 0 0 0.16 ± 0.16 0 Alliaria petiolata (adult) 37.10 ± 7.82 0.57 ± 0.24 6.88 ± 1.08 0.70 ± 0.27 Alliaria petiolata (rosettes) 3.80 ± 1.08 3.71 ± 1.06 4.24 ± 1.03 3.74 ± 0.76 Allium tricoccum 0.20 ± 0.20 1.24 ± 0.68 0.48 ± 0.40 0.35 ± 0.24 Amphicarpaea bracteata 0 0 0.16 ± 0.16 0 Arisaema triphyllum 0 0 0 0.26 ± 0.14 Aristolochia serpentaria 0 0 0 0.09 ± 0.09 Asimina triloba 2.80 ± 1.95 2.86 ± 1.46 0.08 ± 0.08 0 Aster divaricatus 0 0 0.40 ± 0.28 0 Botrychium virginianum 0.10 ± 0.10 0 0 0.35 ± 0.20 Cardamine concatenata 1.10 ± 0.49 2.76 ± 0.75 2.16 ± 0.72 1.57 ± 0.72 Carex spp. 1.40 ± 1.06 2.00 ± 1.25 1.04 ± 0.52 1.22 ± 0.56 Carpinus caroliniana 0 0 0.40 ± 0.40 0 Carya cordiformis 0.10 ± 0.10 0 0.40 ± 0.28 0.17 ± 0.12 Celtis occidentalis 0 0 0 0.17 ± 0.12 Circaea lutetiana 0.20 ± 0.20 1.43 ± 1.33 4.16 ± 2.08 2.35 ± 1.43 Claytonia virginica 4.00 ± 0.65 11.14 ± 1.69 3.92 ± 1.00 5.65 ± 0.97 Cornus florida 0 0 0.24 ± 0.24 0 Cryptotaenia canadensis 0.40 ± 0.31 0 2.56 ± 0.86 2.09 ± 0.77 Dicentra sp. 20.60 ± 5.20 17.90 ± 3.47 0.16 ± 0.11 0 Erigenia bulbosa 4.60 ± 1.73 4.95 ± 1.76 0 0

Species -- 2004 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 20 n = 21 n = 25 n = 23 Erythronium americanum 0.20 ± 0.20 4.57 ± 2.83 0 0 Eupatorium rugosum 0.10 ± 0.10 0 0.48 ± 0.33 1.39 ± 1.08 Fagus grandifolia 0.10 ± 0.10 0 0.56 ± 0.48 0 Fraxinus americana 0.70 ± 0.49 0.10 ± 0.10 0.24 ± 0.24 0 Galium aparine 16.30 ± 4.91 6.76 ± 1.90 2.16 ± 0.54 2.09 ± 0.67 Galium circaezans 0 0 0.24 ± 0.18 0.78 ± 0.53 Galium triflorum 0 0 0 0.43 ± 0.31 Geum spp. 0.20 ± 0.20 0.10 ± 0.10 2.72 ± 1.12 1.39 ± 0.53 Grass spp. 3.40 ± 1.73 2.48 ± 1.45 7.28 ± 2.63 4.78 ± 1.14 Hackelia virginiana 0.10 ± 0.10 0 0.72 ± 0.72 0

Hydrophyllum appendiculatum 0.50 ± 0.35 0.48 ± 0.34 0 0.43 ± 0.31 Impatiens pallida 3.60 ± 1.58 8.48 ± 2.85 0.08 ± 0.08 0.17 ± 0.17 Juglans nigra 0 0 0 0.35 ± 0.35 Laportea canadensis 0 0.19 ± 0.19 0 0 Lindera benzoin 0 0 0.56 ± 0.48 5.65 ± 2.75 Liriodendron tulipifera 0 0 0.08 ± 0.08 0.70 ± 0.70 Lonicera maackii 0 0 0.56 ± 0.41 0.26 ± 0.26 Osmorhiza longistylis 3.40 ± 1.98 0.95 ± 0.49 12.64 ± 2.85 10.78 ± 1.93 Ostrya virginiana 0 0 0.56 ± 0.56 0 Panax quinquefolius 0 0 0.16 ± 0.16 0 Parthenocissus quinquefolia 0 0.10 ± 0.10 1.60 ± 0.63 2.78 ± 1.12 Phryma leptostachya 0.80 ± 0.53 0.19 ± 0.13 1.52 ± 0.37 1.91 ± 0.54 Pilea pumila 0.10 ± 0.10 1.71 ± 1.01 0.40 ± 0.23 0.17 ± 0.17 Podophyllum peltatum 4.50 ± 2.00 4.48 ± 2.51 2.56 ± 1.32 4.78 ± 2.08 Polygonatum biflorum 0 0.19 ± 0.19 1.60 ± 0.81 1.65 ± 0.54

Species -- 2004 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 20 n = 21 n = 25 n = 23 Polygonum virginianum 0 0 0.32 ± 0.19 0.09 ± 0.09 Prunus serotina 0 0.29 ± 0.21 1.68 ± 0.82 0.52 ± 0.36 Quercus muhlenbergii 0 0 0.08 ± 0.08 0.09 ± 0.09 Ranunculus micranthus 0 0 0.16 ± 0.11 0.09 ± 0.09 Ranunculus recurvatus 0 0 0.08 ± 0.08 0 Rosa multiflora 0 0 0.16 ± 0.16 1.13 ± 1.04 Rubus allegheniensis 0 0 0.08 ± 0.08 0 Rubus species 0 0 0.16 ± 0.16 0.09 ± 0.09 Sambucus spp. 0 0 0.08 ± 0.08 0 Sanguinaria canadensis 0 0 0 0.09 ± 0.09 Sanicula spp. 0.70 ± 0.51 0 4.32 ± 0.92 2.61 ± 0.90 Senecio glabellus 0.30 ± 0.30 0 0 0 Senecio obovatus 0 0 0.72 ± 0.72 0.43 ± 0.43 Smilax hispida 0 0 0.08 ± 0.08 0.09 ± 0.09 Stellaria media 36.00 ± 12.90 8.48 ± 3.17 0.08 ± 0.08 0.78 ± 0.78 Toxicodendron radicans 0 0 0.24 ± 0.13 0.09 ± 0.09 Trillium sessile 1.60 ± 0.57 1.43 ± 0.46 0 0 Ulmus rubra 0 0 0.64 ± 0.30 1.04 ± 0.60 Viola spp. 1.10 ± 0.64 2.86 ± 1.12 6.64 ± 1.59 9.04 ± 1.62 Vitis sp. 0.30 ± 0.22 0.48 ± 0.27 0.16 ± 0.11 0.43 ± 0.22 Unknown seedling 0 0 0.16 ± 0.16 0.26 ± 0.14

82 Appendix G. Mean 2005 peak percent cover (+ SE) of species in 1 x 1 m sprayed and unsprayed plots in the Hueston Woods State Nature Preserve.

Species -- 2005 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 21 n = 20 n = 25 n = 25 Acer negundo 0.19 ± 0.13 0 0 0 Acer saccharum 4.10 ± 2.04 4.60 ± 2.12 1.36 ± 0.54 2.08 ± 0.65 Actaea alba 0.76 ± 0.76 0 0.88 ± 0.63 0.96 ± 0.75 Aesculus glabra 0 0 0.40 ± 0.40 0 Agrimonia sp. 0 0 0.16 ± 0.16 0 Alliaria petiolata (adult) 5.43 ± 2.66 1.00 ± 0.40 0.56 ± 0.27 0.80 ± 0.40 Alliaria petiolata (rosettes) 32.86 ± 6.38 37.50 ± 5.77 15.20 ± 2.15 10.64 ± 2.25 Allium tricoccum 0.48 ± 0.39 1.20 ± 0.67 0.48 ± 0.48 0.32 ± 0.25 Amphicarpaea bracteata 0 0 0.16 ± 0.16 0 Arisaema triphyllum 0 0 0 0.40 ± 0.26 Asimina triloba 5.33 ± 4.03 4.50 ± 2.28 0 0 Aster divaricatus 0 0 0.56 ± 0.32 0 Botrychium dissectum 0 0 0.08 ± 0.08 0.08 ± 0.08 Botrychium virginianum 0.10 ± 0.10 0 0.08 ± 0.08 0.24 ± 0.13 Cardamine concatenata 1.81 ± 0.63 4.10 ± 1.24 2.56 ± 0.82 1.12 ± 0.42 Carex spp. 1.81 ± 0.86 0.30 ± 0.22 0.96 ± 0.45 1.44 ± 0.67 Carya cordiformis 0.19 ± 0.19 0.10 ± 0.10 0.24 ± 0.18 0.48 ± 0.21 Celtis occidentalis 0 0 0.08 ± 0.08 0.24 ± 0.18 Circaea lutetiana 0.19 ± 0.19 0.80 ± 0.80 1.76 ± 0.70 1.76 ± 0.94 Claytonia virginica 7.71 ± 1.29 17.00 ± 3.62 8.24 ± 1.02 7.20 ± 1.15 Cornus florida 0 0 0.40 ± 0.40 0 Crataegus sp. 0 0 0 0.24 ± 0.24 Cryptotaenia canadensis 0 0 0 0.24 ± 0.24 Dicentra sp. 33.24 ± 10.07 28.50 ± 5.79 0.40 ± 0.28 0.64 ± 0.64

Species -- 2005 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 21 n = 20 n = 25 n = 25 Erigenia bulbosa 4.38 ± 1.11 8.20 ± 2.03 0 0 Erythronium americanum 0.10 ± 0.10 2.40 ± 1.84 0 0 Eupatorium purpureum 0 0 0 0.40 ± 0.28 Eupatorium rugosum 0 0 0 1.92 ± 1.30 Fagus grandifolia 0 0 0.56 ± 0.48 0 Floerkea proserpinacoides 0 0 0 0.08 ± 0.08 Fraxinus americana 1.14 ± 0.53 0.40 ± 0.18 0.80 ± 0.26 0.64 ± 0.28 10.80 ± Galium aparine 15.43 ± 4.53 2.34 7.04 ± 1.65 4.96 ± 1.90 Galium circaezans 0 0 1.28 ± 0.64 0.64 ± 0.40 Galium triflorum 0 0 0.16 ± 0.16 0.16 ± 0.16 Geum spp. 0 0.10 ± 0.10 2.72 ± 0.97 1.60 ± 0.46 Grass spp. 2.19 ± 1.33 1.40 ± 0.92 7.92 ± 2.14 5.20 ± 1.50 Hackelia virginiana 0 0 0.24 ± 0.24 0 Hydrophyllum appendiculatum 0.10 ± 0.10 0.20 ± 0.14 0 0.24 ± 0.24 10.20 ± Impatiens pallida 3.05 ± 1.07 2.66 0.56 ± 0.25 1.04 ± 0.53 Lindera benzoin 0 0.10 ± 0.10 1.04 ± 0.75 3.36 ± 1.78 Liriodendron tulipifera 0.10 ± 0.10 0 0.08 ± 0.08 1.44 ± 1.05 Lonicera maackii 0 0 0.80 ± 0.60 0.08 ± 0.08 Osmorhiza longistylis 1.14 ± 0.64 0.30 ± 0.22 6.80 ± 1.77 7.44 ± 1.51 Ostrya virginiana 0 0 0.24 ± 0.18 0 Oxalis sp. 0 0 0 0.08 ± 0.08 Panax quinquefolius 0 0 0.16 ± 0.16 0 Parthenocissus quinquefolia 0 0.20 ± 0.14 1.68 ± 0.70 3.12 ± 1.24 Phryma leptostachya 0.48 ± 0.24 1.20 ± 0.69 1.92 ± 0.50 2.16 ± 0.54 Pilea pumila 0.10 ± 0.10 0.40 ± 0.40 0.24 ± 0.24 0.16 ± 0.16

84 Species -- 2005 Old-growth Second-growth Unsprayed Sprayed Unsprayed Sprayed n = 21 n = 20 n = 25 n = 25 Podophyllum peltatum 4.10 ± 1.77 4.20 ± 2.24 2.48 ± 1.17 3.28 ± 1.44 Polygonatum biflorum 0 0.10 ± 0.10 1.92 ± 0.94 3.36 ± 0.98 Polygonum virginianum 0 0 0.64 ± 0.30 0.16 ± 0.11 Prunus serotina 0.19 ± 0.13 0 2.08 ± 0.93 0.56 ± 0.18 Quercus muhlenbergii 0 0 0.24 ± 0.13 0 Ranunculus abortivus 0 0 0.16 ± 0.16 0.32 ± 0.25 Rosa multiflora 0 0 0.32 ± 0.32 0 Rubus flagellaris 0 0 0.24 ± 0.24 0 Sanguinaria canadensis 0.10 ± 0.10 0 0 0.40 ± 0.28 Sanicula spp. 0 0.10 ± 0.10 2.72 ± 0.85 3.04 ± 0.70 Senecio obovatus 0 0 0.80 ± 0.72 0.16 ± 0.16 Smilax hispida 0 0 0 0.08 ± 0.08 Stellaria media 34.00 ± 9.96 12.30 ± 4.28 0 0.08 ± 0.08

Toxicodendron radicans 0 0 0.08 ± 0.08 0.16 ± 0.11 Trillium sessile 1.71 ± 0.78 1.60 ± 0.63 0 0 Ulmus rubra 0 0 0.88 ± 0.33 1.20 ± 0.97 Viola spp. 1.14 ± 0.63 3.50 ± 2.10 5.84 ± 1.34 6.08 ± 1.10 Vitis sp. 0.10 ± 0.10 0.40 ± 0.31 0.24 ± 0.13 0.08 ± 0.08

85 Appendix H. Multiple response permutation procedure results for tests of difference between understory community peak cover in the old and second-growth stands in sprayed and unsprayed plots at Hueston Woods State Park, OH, 2001–2005. For each year we show the observed dissimilarity, delta (δ), a histogram of deltas produced from 10,000 random permutations, and P-values (the probability of the expected delta being less than the observed delta), for overall stand effect, overall treatment effect (sprayed vs. unsprayed), and the treatment effect in the second and old-growth stands separately.

2001

86 2002

87 2003

88 2004

89 2005

90 Appendix I. Mean percent cover of each growth form and for Alliaria petiolata in each stand in 2004 and 2005 with Kruskal-Wallis test statistic (df = 1) for difference between sprayed and unsprayed treatments. See Appendix C for sample sizes. Bold indicates significance at α = 0.05. Asterisk (*) indicates marginal significance where 0.05 < P < 0.10.

Old-growth Stand Second-growth Stand Year Growth Form Sprayed Unsprayed χ2 p Sprayed Unsprayed χ2 p

2004 Trees 11.43 9.20 0.1565 0.6924 8.52 9.12 0.0477 0.8271 Shrubs 4.29 1.20 2.6678 0.1024 3.57 3.76 2.6217 0.1054 Vines 0.38 0.40 0.1033 0.7479 2.97 3.28 0.0000 1.0000 Spring perennials 44.00 39.30 0.4262 0.5139 29.65 34.32 0.2996 0.5841 Summer perennials 1.71 2.50 0.0762 0.7825 13.74 19.36 0.0724 0.7879 Annuals 42.95 28.20 0.0386 0.8443 3.39 3.12 0.3727 0.5415 89 Graminoids 2.19 6.10 1.1121 0.2916 9.39 8.32 0.0399 0.8417 Ferns 0 0 -- -- 0.26 0.16 0.0167 0.8972 Wintergreen species 46.76 29.80 0.0246 0.8755 36.96 45.76 0.8459 0.3577

2005 Trees 5.10 5.90 0.0359 0.8496 6.88 7.36 0.0866 0.7685 Shrubs 4.60 5.33 1.2856 0.2569 3.44 2.16 0.0698 0.7916 Vines 0.60 0.10 1.2992 0.2544 3.44 2.24 0.0160 0.8992 Spring perennials 71.30 56.00 3.0588 *0.0803 30.64 29.68 0.1028 0.7485 Summer perennials 2.20 1.43 0.0264 0.8708 13.52 13.36 0.1036 0.7475 Annuals 33.70 52.57 1.4727 0.2249 6.24 7.84 2.7320 *0.0984 Graminoids 1.70 4.00 1.2897 0.2561 6.64 8.88 0.6076 0.4357 Ferns 0.00 0.10 0.9524 0.3291 0.32 0.16 0.2536 0.6146 † Wintergreen species 29.20 55.81 4.5300 0.0333 31.60 38.00 0.9054 0.3413 †When Stellaria media was removed from this growth form, mean percent cover in the sprayed plots = 16.90, unsprayed plots = 21.81; χ2 = 0.70, P = 0.40.

91 Appendix J. Soil properties

Bulk density, a measure of soil structure, is the ratio of the mass of dry solids to the bulk volume of an undisturbed soil sample, including pore space, and is commonly reported as an indicator of compaction for a given soil type (Blake and Hartge 1986). Bulk density measurements were determined according to Blake and Hartge (1986) using a soil core sampler. For the moderately eroded Russell-Miamian silt loam soils at the study site in the 0.4 ha woodlot at the Ecology Research Center (ERC) (Lerch et al. 1980, Vankat and Snyder 1991), mean bulk density = 1.077 g cm-3 + SE 0.027 (n = 10). Soils at the study site of Slaughter et al (in press) at Hueston Woods State Park (HWSP), Preble County and Butler County, Ohio, were also predominantly composed of Russell silt loams (second-growth stand: Russell-Miamian silt loams, not moderately eroded as at the ERC; old- growth stand: Russell-Miamian with Casco, Rodman and Fox soils in the drainages and adjacent slopes) (Lerch et al. 1969, Lerch et al. 1980, Branco 1992). While the soil series at the ERC is similar to that of the second-growth stand at HWSP, the soil variations along the slopes in the old-growth stand and extent of erosion may have caused differences in June water infiltration and availability. These factors did not likely affect A. petiolata rosette survival, however, as both survival in the old-growth and second-growth stands were positively correlated to June precipitation (Slaughter et al. in press) despite these soil variations.

92 Appendix K. Common species observed within 0.5 m x 0.5 m study plots at the Ecology Research Center, and woody species observed within the study site. Nomenclature follows Gleason and Cronquist (1991).

Species in plots Woody species at site

Acer saccharum Acer saccharum

Circaea lutetiana Carya cordiformis

Eupatorium rugosum Celtis occidentalis

Fraxinus americana Fraxinus americana

Geum spp. Lonicera maackii

Hackelia virginiana Maclura pomifera

Impatiens spp. Parthenocissus quinquefolia

Lonicera maackii Prunus serotina

Oxalis spp. Ulmus rubra

Parthenocissus quinquefolia Vitis spp.

Pilea pumila

Polygonatum biflorum

Polygonum cespitosum

Sanicula canadense

Stellaria media

Viola spp.

Vitis spp.

93 Appendix L. One-way ANOVA tables of response variables of A. petiolata and soil water contents at the study site at the Ecology Research Center. Superscripts indicate data transformations to meet ANOVA assumptions of homoscedasticity.

Llog(x+1) Aarcsine Ssquareroot

Density—June 1, 2005 df SS MS F p Treatment 2 15553.1667 7776.5833 0.66 0.5216 Error 33 386554.8333 11713.7828 Corrected Total 35 402108.0000

Density—June 30, 2005L df SS MS F p Treatment 2 0.06252507 0.03126254 0.13 0.8762 Error 33 7.77823348 0.23570404 Corrected Total 35 7.84075855

Density—Oct 27, 2005L df SS MS F p Treatment 2 2.48475719 1.2423786 1.01 0.3765 Error 33 40.73952917 1.23453119 Corrected Total 35 43.22428637

Density—May 31, 2006L df SS MS F p Treatment 2 3.04643413 1.52321707 0.92 0.409 Error 33 54.70935506 1.65785924 Corrected Total 35 57.75578919

Survival—June 1 to June 30 df SS MS F p Treatment 2 1195.36351 597.68175 1.74 0.1919 Error 33 11360.83706 344.26779 Corrected Total 35 12556.20056

Survival—June 1 to Oct 27A df SS MS F p Treatment 2 0.13936435 0.06968218 2.83 0.0732 Error 33 0.81165319 0.02459555 Corrected Total 35 0.95101754

Survival—June 1 to May 31A df SS MS F p Treatment 2 0.09441868 0.04720934 1.64 0.2085 Error 33 0.94722665 0.02870384 Corrected Total 35 1.04164533

94 Root length df SS MS F p Treatment 2 6.55687933 3.27843966 1.35 0.2725 Error 32 77.45054924 2.42032966 Corrected Total 34 84.00742857

Root biomassS df SS MS F p Treatment 2 0.00243438 0.00121719 0.57 0.5695 Error 32 0.06797929 0.00212435 Corrected Total 34 0.07041367

Shoot biomass df SS MS F p Treatment 2 0.00680072 0.00340036 2.07 0.1430 Error 32 0.05260954 0.00164405 Corrected Total 34 0.05941026

Fruit number per individual df SS MS F p Treatment 2 87.4248 43.7124 0.21 0.8155 Error 33 7029.435675 213.013202 Corrected Total 35 7116.860475

Soil moisture Wk 1—June 9 df SS MS F p Treatment 3 536.236494 178.745498 11.01 <.0001 Error 43 698.131591 16.235618 Corrected Total 46 1234.368085

Soil moisture Wk 2—June 14 df SS MS F p Treatment 3 520.080000 173.360000 13.05 <.0001 Error 44 584.726667 13.289242 Corrected Total 47 1104.806667

Soil moisture Wk 3—June 22 df SS MS F p Treatment 3 1398.415833 466.138611 19.10 <.0001 Error 44 1073.823333 24.405076 Corrected Total 47 2472.239167

Soil moisture Wk 4—June 30 df SS MS F p Treatment 3 1109.700833 369.900278 16.54 <.0001 Error 44 984.018333 22.364053 Corrected Total 47 2093.719167

95 Appendix M. Nutrient concentration of water added to plots.

Nutrient content of water from the barn roof and from a rainwater supply pond at the ERC was analyzed with a Lachat QuikChem 8000 FIA+ (Flow Injection Analysis) for

orthophosphate (OrthoP), ammonia (NH4) and combined nitrates and nitrites (NO3/NO2). Results are given as mean + SE; supply pond OrthoP, n = 2 125 mL sample bottles; all others, n = 3 125 mL sample bottles.

OrthoP NH4 NO3/NO2

(ug P/L) (mg N/L) (mg N/L)

Rainwater 7.8747 ± 0.1066 0.4340 ± 0.0036 0.2940 ± 0.0029

Supplypond 4.8845 ± 0.0185 0.0647 ± 0.0064 0.0030 ± 0.0015

96 Appendix N. Pairwise comparisons of soil water content.

Results from pairwise comparisons of soil water content for each week of June 2005 using the Bonferroni (Dunn) t-test. For each week, overall treatment effect (ANOVA F test) was significant, as reported in legend of Figure 4 of Chapter 2. Asterisk (*) indicates a significant difference (α = 0.05) in soil water content between a pair of treatments. Ave = average precipitation treatment, Amb = ambient conditions.

Error Crit Min sig Dry Dry Dry Ave Ave Wet df Error MS value of t diff Ave Wet Amb Wet Amb Amb Week 1 43 16.23562 2.76584 * * * Week 2 44 13.28924 2.76281 4.1117 * * * * Week 3 44 24.40508 2.76281 5.5721 * * * * Week 4 44 22.36405 2.76281 5.334 * * * *

97 Appendix O. Shelter microclimate measurements

To assess the light reduction due to the polyethylene plastic, 32 readings were taken with LI-COR quantum sensors (LI-COR, Inc.) with a 1 m line sensor (LI-191) below the plastic and a point sensor (LI-190) above the plastic, in full sunlight (Figure 1). Photosynthetic active radiation (PAR) under polyethylene plastic was reduced to 89.48 % + 0.26 (mean + SE, n = 32) when measured in full sun.

1350

1345

1340

1335

1330

1325 Point Sensor Point

1320

1315

1310

1305 1280 1285 1290 1295 1300 1305 1310 1315 1320 1325 1330

Line Sensor

Figure 1. Calibration of the LI-COR line and point sensors side by side in full sunlight, n = 15, y = 0.9929x + 32.707, R2 = 0.9959.

98 To assess light differences between sheltered treatment plots and ambient conditions in the forest setting, two readings were taken for each plot and ambient non-sheltered site with the LI-COR line sensor on a cloudy day (Gendron et al. 1998). Simultaneous above-canopy readings were collected from the LI-COR pyranometer sensor (LI-200SZ, LI-COR, Inc.) at the ERC weather station. To incorporate the difference between the line-sensor used under the shelters and the point sensor which collected above-canopy data, above-canopy values were converted based on y = 1.3034x + 21.39 (Figure 2). Shelter values were each divided by the above-canopy reading from the same minute to obtain percent open sky PAR. After removal of one outlier to improve normality, a one-way ANOVA confirmed no difference among treatments (ambient unsheltered sites treated as a fourth ‘treatment’) (Table 1).

Table 1. One-way ANOVA statistics of percent PAR in treatment plots and ambient sites.

Percent PAR df SS MS F p Treatment 3 10.098153.36605 1.91 0.1425 Error 43 75.829631.76348 Corrected Total 46 85.92778

99 1200

1000

800

600 LICOR PAR

400

200

0 0 100 200 300 400 500 600 700 800

Weather station PAR

Figure 2. Calibration of the LI-COR and the ERC light sensors from side-by-side readings, n =

6, y = 1.3034x + 21.39, R2 = 0.9995.

100 To assess shelter effects on soil temperature, soil temperature was collected with a soil thermometer at depths of 5 cm and 10 cm for each plot and at the ambient non-sheltered sites. One-way ANOVA revealed no treatment effect (non-sheltered sites treated as a fourth ‘treatment’) (Table 2), indicating shelters did not increase soil temperature at 5 cm or 10 cm.

Table 2. One-way ANOVA statistics of soil temperature in treatment plots and ambient sites.

Temperature--5 cm df SS MS F p Treatment 3 0.62890630.2096354 2.01 0.1264 Error 44 4.58854170.104285 Corrected Total 47 5.2174479

Temperature--10 cm df SS MS F p Treatment 3 0.18098960.0603299 1.57 0.2105 Error 44 1.69270830.0384706 Corrected Total 47 1.8736979

101 Appendix P. Comments on rain shelter design and use.

The rain shelters seemed well suited for the small-scale short-term nature of this study. Shelters were small enough to be placed between stems of large Lonicera maackii shrubs, however sturdy enough to withstand early summer storms and falling branches of significant size. Experiments extending beyond a month should consider additional support of plastic sheeting to eliminate sagging over time and pooling of water. Future use of this shelter design should consider mounding soil in region of drip-line to slope roof run-off away from experimental plot. Installation of subsurface moisture barriers and distance from sample plot may need to be modified if soils are rocky or if random placement of shelters necessitates closer proximity to trees and shrubs with large roots. (For additional information regarding rain shelter construction, see Dugas and Upchurch 1984, Foale et al. 1986, Jacoby et al. 1988, Kvien and Branch 1988, Harrington 1991, Bredemeier 1995, Hanson et al. 1995, Hanson et al. 1998, Svejcar et al. 1999, Fay et al. 2000, English et al. 2005.)

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Branco, J. C. 1992. Watershed plan and environmental assessment for Four Mile Creek watershed, Ohio and Indiana. Soil Conservation Service, Columbus.

Bredemeier, M. 1995. Experimental manipulations of the water and nutrient cycles in forest ecosystems (patch-scale roof experiments: EXMAN). Agricultural and Forest Meteorology 73:307-320.

Dugas, W. A., and D. R. Upchurch. 1984. Microclimate of a rainfall shelter. Agronomy Journal 76:867-871.

Foale, M. A., R. Davis, and D. R. Upchurch. 1986. The design of rain shelters for field experimentation: a review. Journal of Agricultural Engineering Research 34:1-16.

Gleason, H. A., and A. Cronquist. 1991. Manual of vascular plants of northeastern United States and adjacent Canada, 2nd edition. The New York Botanical Garden, New York.

Hanson, P. J., D. E. Todd, M. A. Huston, J. D. Joslin, J. L. Croker, and R. M. Auge. 1998. Description and field performance of the Walker Branch Throughfall Displacement Experiment: 1993-1996. ORNL/TM-13586, Office of Biological and Environmental Research, United States Department of Energy, Oak Ridge.

Haragan, P. D. 1991. Weeds of Kentucky and Adjacent States: A Field Guide. The University Press of Kentucky, Lexington, KY.

103

Harrington, G. N. 1991. Effects of soil moisture on shrub seedling survival in a semi-arid grassland. Ecology 72:1138-1149.

Jacoby, P. W., R. J. Ansley, and B. K. Lawrence. 1988. Design of rain shelters for studying water relations of rangeland shrubs. Journal of Range Management 41:83-85.

Kvien, C. S., and W. D. Branch. 1988. Design and use of a fully automated portable rain shelter system. Agronomy Journal 80:281-283.

Lerch, N. K., P. E. Davis, L. A. Tornes, E. A. Hayhurst, and N. A. McLoda. 1969. Soil survey of Preble County, Ohio. USGPO, Washington.

Lerch, N. K., W. F. Hale, and D. D. Lemaster. 1980. Soil survey of Butler County, Ohio. USDA Soil Conservation Service, Hamilton.

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