EFFECTS OF INCREASED INUNDATION AND

WRACK DEPOSITION ON A

SALTMARSH PLANT COMMUNITY






by

Patricia M. Tolley




APPROVED BY:


DIRECTOR OF THESIS __________________________________________________

Dr. Robert R. Christian

COMMITTEE MEMBER _________________________________________________

Dr. Mark M. Brinson

COMMITTEE MEMBER _________________________________________________

Dr. Claudia L. Jolls

COMMITTEE MEMBER _________________________________________________

Dr. Kevin O'Brien

CHAIR OF THE

DEPARTMENT OF BIOLOGY _____________________________________________

Dr. Charles E. Bland

DEAN OF THE

GRADUATE SCHOOL ___________________________________________________

Dr. Thomas L. Feldbush


EFFECTS OF INCREASED INUNDATION AND

WRACK DEPOSITION ON A

SALTMARSH PLANT COMMUNITY





A Thesis

Presented To

the Faculty of the Department of Biology

East Carolina University





In Partial Fulfillment

of the Requirements for the Degree

Masters of Science in Biology




by

Patricia M. Tolley

June 1996

TABLE OF CONTENTS

Page

LIST OF TABLES......................................................................................................vii

LIST OF FIGURES.....................................................................................................x

1. INTRODUCTION..................................................................................................1

2. LITERATURE REVIEW........................................................................................3

2.1. Overview of Salt Marshes.........................................................................3

2.1.1. Salt Marsh Development and Stability........................................4

2.1.2. Salt Marsh Hydrology................................................................6

2.1.3. Salt Marsh Zonation...................................................................7

2.2. Defining Stress and Disturbance................................................................9

2.3. Responses of a Salt Marsh Plant Community to Disturbances..................12

2.4. The Impact of a Rise in Sea Level on the Community Structure

of Salt Marshes....................................................................................13

2.4.1. Increased Sea Water Inundation................................................15

2.4.2. Wrack Deposition.....................................................................18

2.5. Plants Associated with a High Salt Marsh Community.............................20

2.5.1. Juncus roemerianus Scheele (Juncaceae)..................................21

2.5.2. Spartina patens (Ait.) Muhl. (Pocaceae)...................................23

2.5.3. Distichlis spicata Raf. (Poaceae)..............................................25

2.5.4. Spartina alterniflora Loisel. (Poaceae).....................................26

2.5.5. Salicornia spp. L. (Chenopodiaceae)........................................27

2.7. Major Points of Literature Review (Summary)........................................28

3. GOALS OF RESEARCH, POSTULATED MECHANISM, AND NULL HYPOTHESES..............................................................................................29

3.1. Postulated Mechanisms...........................................................................29

3.2. Null Hypotheses......................................................................................32

3.2.1. Effect of Increased Inundation on Saltmarsh Vegetation............32

3.2.2. Effect of Wrack Deposition on Saltmarsh Vegetation................32

3.2.3. Combination of Increased Inundation and Wrack Deposition....32

3.2.4 Comparison between the Reference Juncus roemerianus

Populations and the Experimental Controls..............................32

3.3.5. Shading Experiment..................................................................33

3.3. Statement Regarding the Testing of the Hypotheses................................33

4. MATERIALS AND METHODS...........................................................................34

4.1. Site Description......................................................................................34

4.2. Overall Design of Experiment.................................................................36

4.3. Tracking of the Growth and Senescence of Juncus roemerianus Leaves..41

4.3.1. Reference Population of Juncus roemerianus...........................41

4.4. Aboveground Biomass Sampling of the Plots..........................................43

4.5. Vegetative Analysis of Ground Cover in the Plots...................................44

4.6. Annual Net Primary Production (ANPP) of Juncus roemerianus.............44

4.7. Shading Experiment................................................................................46

4.8. Statistical Analysis of Data......................................................................47

5. RESULTS.............................................................................................................51

5.1. Growth and Senescence of Juncus roemerianus......................................51

5.1.1. Maximum Green and Total Heights of Juncus roemerianus......51

5.1.2. Life Table Analysis (Survivorship) of Juncus roemerianus........59

5.1.3. Juncus roemerianus Leaf Densities...........................................82

5.2. Aboveground Biomass............................................................................88

5.2.1. Juncus roemerianus -- 1994 and 1995 Data..............................88

5.2.2. Spartina patens -- 1994 and 1995 Data...................................103

5.2.3. Distichlis spicata -- 1994 and 1995 Data.................................106

5.2.4. Spartina alterniflora -- 1994 and 1995 Data............................108

5.2.5. Scirpus sp. -- 1994 and 1995 Data...........................................108

5.2.6. Salicornia sp. -- 1994 and 1995 Data......................................109

5.2.7. Total Biomass -- 1994 and 1995 Data.....................................109

5.2.8. Reference Biomass -- 1995 Data.............................................111

5.3. Vegetative Analysis of Ground Cover in the Plots..................................111

5.4. ANPP of Juncus roemerianus................................................................115

5.5. Shading Experiment...............................................................................125

6. DISCUSSION......................................................................................................131

6.1. Effect of Increased Inundation on Salt Marsh Vegetation........................135

6.1.1. Increased inundation does not affect the growth

of J. roemerianus....................................................................135

6.1.2. Increased inundation does not affect the senescence

of J. roemerianus....................................................................142

6.1.3. Increased inundation does not affect the growth of S. patens

and D. spicata.........................................................................144

6.2. Effect of Wrack Deposition.....................................................................148

6.2.1. Wrack deposition does not affect the aboveground production

of the plants.............................................................................148

6.2.2. Wrack deposition does not affect the vegetative regrowth of a

plant community.......................................................................151

6.3. Combination of Increased Inundation and Wrack Deposition...................157

6.3.1. Increased inundation and wrack deposition are not

interacting stressors..................................................................157

6.3.2. Increased inundation will not affect the vegetative regrowth

during the first growing season after wrack deposition.............158

6.4. Comparison between the Reference Juncus roemerianus Populations

and the Experimental Controls.............................................................160

6.5. Shading Experiment................................................................................161

7. CONCLUSIONS...................................................................................................163

8. APPENDIX A: DETAILS ON ELECTRICAL AND PUMPING SYSTEMS......167

9. APPENDIX B: SUMMARY OF Juncus roemerianus TAGGED LEAF DATA....170

10. APPENDIX C: AMOUNT OF WATER PUMPED ONTO THE PLOTS............184

11. APPENDIX D: SALINITY AND WELL WATER DEPTH DATA

FROM JUNE TO AUGUST 1995...................................................................187

12. LITERATURE CITED........................................................................................191


LIST OF TABLES

Page

1. Dates of when leaves where tagged and how many leaves where tagged..................42

2. Abbreviations used in Results section and an example of GLM table.......................52

3. Means (standard deviations) of maximum green and total heights for

J. roemerianus................................................................................................54

4. Results of GLM for maximum green and total heights............................................56

5. Results of GLM for reference population versus control plots for

maximum heights.............................................................................................58

6. Life table data for time to maximum green heights and time to death from

maximum green heights for 1994 cohorts........................................................60

7. Life table data for time to maximum total heights and time to death from

maximum total heights for 1994 cohorts..........................................................61

8. Life table data for time to maximum green heights for 1995 cohorts.......................62

9. Life table data for time to maximum total heights for 1995 cohorts........................64

10. Results of LIFEREG procedure for 1994 cohorts................................................67

11. Results of LIFEREG procedure for 1995 cohorts................................................68

12. Results of Chi-square tests for 1994 cohorts.......................................................78

13. Results of Chi-square tests for 1995 cohorts........................................................79

14. Results of LIFEREG procedure for reference populations versus

the control plots..............................................................................................81

15. Results of Chi-square tests for reference populations versus the control plots......83

16. J. roemerianus leaf densities from the experimental plots.....................................84

17. Results of GLM for leaf densities from the experimental plots.............................85

18. J. roemerianus leaf densities from the reference populations and the 1995

nonwrack areas of the control plots................................................................86

19. Results of GLM for reference population leaf densities versus control plots.........87

20. Means (standard deviations) of 1994 biomass samples.........................................89

21. Means (standard deviations) of 1995 biomass samples.........................................91

22. GLM means by flooding and wrack treatments for 1994 biomass samples...........93

23. GLM means by flooding and wrack treatments for 1995 biomass samples...........95

24. Results of GLM for 1994 biomass samples.........................................................97

25. Results of GLM for 1995 biomass samples.........................................................99

26. Significant interactions from the GLM for 1994 and 1995 biomass samples.......101

27. Means (standard deviations) of 1995 reference biomass samples and 1995

nonwrack areas of the control plots biomass samples....................................112

28. Results for GLM reference populations biomass samples versus nonwrack

areas of the control plots biomass samples....................................................113

29. Means (standard deviations) of the percentage of ground cover change from

1994 to 1995 in the experimental plots by flooding and wrack treatments......114

30. Results of GLM for percentage of ground cover change....................................116

31. Means (standard deviations) of frequency, average height, and production-to-

biomass ratio for J. roemerianus...................................................................117

32. Means (standard deviations) of the ANPP for J. roemerianus.............................119

33. GLM means for frequency, average height, production-to-biomass, and

ANPP by flooding and wrack treatments.......................................................122

34. Results of GLM for frequency, average height, production-to-biomass,

and ANPP.....................................................................................................123

35. Means (standard deviations) of frequency, average height, production-to-

biomass, and ANPP for reference populations................................................126

36. Results of GLM for frequency, average height, production-to-biomass, and

ANPP for reference populations versus the control plots................................127

37. Means (standard deviations) for biomass samples from the

shading experiment........................................................................................128

38. Results of GLM for biomass from the shading experiment...................................130

39. Summary of the data collected and statistics used for this thesis..........................132

40. List of biomass and ANPP from other studies and this thesis...............................137

41. Means (standard deviations) of the green heights in the flooded plots for

each sampling date..........................................................................................171

42. Means (standard deviations) of the green heights in the border control plots for

each sampling date..........................................................................................173

43. Means (standard deviations) of the green heights in the control plots for each

sampling date..................................................................................................175

44. Means (standard deviations) of the total heights in the flooded plots for

each sampling date..........................................................................................177

45. Means (standard deviations) of the total heights in the border control plots for

each sampling date..........................................................................................179

46. Means (standard deviations) of the total heights in the control plots for each

sampling date..................................................................................................181

47. Means (standard deviations) of the green and total heights in the reference

populations for each sampling date.................................................................183

48. Pumping activities for 1995.................................................................................185

49. Results of GLM on well water depth and salinity from the experimental plots......190


LIST OF FIGURES

Page

1. Map of the Virginia Coast Reserve Long-Term Ecological Research

(VCR LTER) site.............................................................................................35

2. Map of Brownsville marsh showing the location of the experimental plots and

the reference J. roemerianus populations.........................................................37

3. Design of the experimental plots.............................................................................38

4. Survivorship curves for time to maximum green height for 1994 J. roemerianus

leaves based on flooding treatment...................................................................70

5. Survivorship curves for time to death from maximum green height for 1994

J. roemerianus leaves based on flooding treatment...........................................71

6. Survivorship curves for time to maximum green height for 1995 J. roemerianus

leaves based on flooding treatment...................................................................72

7. Survivorship curves for time to maximum green height for 1995 J. roemerianus

leaves based on cohort number.........................................................................73

8. Survivorship curves for time to maximum total height for 1994 J. roemerianus

leaves based on flooding treatment....................................................................74

9. Survivorship curves for to time to death from maximum total heights for 1994

J. roemerianus leaves based on flooding treatment............................................75

10. Survivorship curves for the time to maximum total height for 1995

J. roemerianus leaves based on flooding treatment............................................76

11. Survivorship curves for the time to maximum total height for 1995

J. roemerianus leaves based on cohort number..................................................77

12. Depth of water below the ground surface in the experimental plots

from June to August 1995...............................................................................188

13. Ground water salinity in the experimental plots from June to August 1995...........189


ACKNOWLEDGMENTS

I could not have accomplished this research without the help, support, and financial assistance of many people. First, I would thank my committee members, Bob, Mark, Claudia, and Kevin. To my advisor, Bob -- Thank-you for getting me "hooked" on research back in the summer of 1993, providing me with the opportunity to work on a thesis project that was perfectly suited for me, and for a copy of Cold Comfort Farm. To Mark -- Thank-you for allowing me to plunder through your enormous selection of papers and for making sure taking a class with you meant I was able to spend lots of time out in the field. To Claudia -- Thank-you for getting me "hooked" even more on research, for always being thorough with your questions and comments, and for allowing me to spend a week at "Bug Camp." To Kevin -- Thank-you for spending all those hours guiding me through the world of statistics and SAS with humor and patience, and I'm sure I would have ended up very lost without your help. To all my committee members -- Thank-you ever so much for being understanding and coming through for me time and time again. It has been my pleasure and honor to have worked with such a wonderful group of people.

I also would like to thank all the people who helped me in the field, in the lab, and with various other aspects of this thesis: ECU Interlibrary Loan Service people, R. Carlson, C. Christian, D. Christian, J. Contable, D. Daniel, G. Dickerson, L. (Peito) Gatti, S. Hamze, J. Holmes, T. Jones, D. Krovetz, J. Porter, D. Richardson, M. Spaulding, R. Stumpf, L. Stasavich, R. Tarnowski, J. Taylor, B. Tolley, J. Tolley, W. Tolley, J. Tomkins, S. Walston, Wetland Ecology Class of 1995, and D. Yozzo. Out of this long list, there are a few people who deserve an extra thanks for putting in overtime: Tammy Jones for spending many hours helping process biomass samples; Jed Tomkins for assisting me in the field during the summer of 1995; my father, Walt Tolley, for assistance with the pump and for building an assortment of items for me; and Dave Yozzo for being my full-time scribe, field partner, and reviewer.

Last, but certainly not least, I would like to thank my financial backers. Funding for this thesis came from the National Science Foundation's Long-Term Ecological Research and Research Experiences for Undergraduates programs, East Carolina University Department of Biology, and my parents.


Patricia M. Tolley. EFFECTS OF INCREASED INUNDATION AND WRACK DEPOSITION ON A SALTMARSH PLANT COMMUNITY. (Under the direction of Dr. Robert R. Christian) Department of Biology, June 1996.

Sea-level rise would increase the inundation frequency of high salt marshes. Furthermore, a rise in sea level may cause an increase in the amount of wrack deposited in a high marsh community. Since changes in sea level occur slowly, communities may also change gradually, in response to increased inundation. Therefore, abrupt disturbances, such as storm induced deposition of Spartina alterniflora wrack, may be necessary to induce rapid changes in saltmarsh plant communities. Previous ecological studies in this area have generally not focused on more than one type of disturbance. Therefore, there is a lack of knowledge on how disturbances interact with each other in eliciting community responses. Furthermore, few studies in salt marshes have investigated the impact of abrupt disturbances which result in change of community structure.

I experimentally manipulated inundation and wrack deposition to discern the individual and combined effects of these factors on high marsh plant species (i.e., Juncus roemerianus, Spartina patens, and Distichlis spicata) at a mainland marsh on the Eastern Shore of Virginia. This two year study involved (1) the experimental pumping of salt water onto the high marsh, (2) experimental placement of S. alterniflora wrack on the plant community, and (3) removing half of the wrack after six months of deposition. The experimental design was a randomized block that involved three flooding treatments (flooded, border control, and control), two wrack treatments (wrack and nonwrack), and three blocks (X, Y, and Z). The data collected from the experimental plots included (1) the tracking of the growth and senescence of J. roemerianus leaves, (2) estimations of growing and senescing J. roemerianus leaf densities, (3) quantification of aboveground biomass (g/m2), (4) vegetative analysis of the change in ground cover, and (5) estimation of the annual net primary productivity (ANPP, g/(m2 x y)) of J. roemerianus. Furthermore, I monitored two additional J. roemerianus populations that were inundated naturally on a daily basis and compared them to the experimental control plots to study the effects of greater, natural inundation on J. roemerianus. I also conducted an experiment to study the effects of shading on the regrowth of J. roemerianus.

The effect of increased inundation on the plant community was species specific. Increased inundation did not significantly affect the aboveground biomass and ANPP of J. roemerianus, but it did result in slower growing and faster senescing J. roemerianus leaves. Furthermore, the reference J. roemerianus populations, which have undergone prolonged flooding (> 2 years), were significantly different from the control plots. Therefore, the growth and senescence rates of J. roemerianus are more sensitive to changes in inundation than aboveground biomass and ANPP; although aboveground biomass and ANPP probably decline with long-term inundation. Increased frequency of inundation decreased S. patens aboveground biomass, but ponding of water increased S. patens aboveground biomass. Increased inundation alone did not cause a significant effect on the aboveground biomass of D. spicata and did not promote the growth of minor species such as short S. alterniflora.

The effects of wrack deposition in reducing the aboveground biomass of the plant community were non-species specific, while regrowth and colonization after wrack deposition were species specific. Six months of wrack deposition significantly reduced the aboveground biomass of the three dominant species. One year after the removal of wrack, the aboveground biomass and leaf densities of J. roemerianus were still significantly lower in the post-wrack areas as compared to the nonwrack areas. In contrast, the aboveground biomass values for S. patens and D. spicata were not significantly lower in the post-wrack areas as compared to the nonwrack areas. Furthermore, living D. spicata biomass was significantly higher in the post-wrack areas. D. spicata also colonized the bare areas where J. roemerianus previously grew.

The interaction between the responses to increased inundation and wrack deposition occurs through time. During periods of deposition, the extreme effect of the wrack on the plants masked any interaction between flooding and deposition. However, after the removal of wrack, increased inundation inhibited D. spicata, a primary colonizing species, from colonizing some of the bare areas. When increased inundation inhibits the colonization of post-wrack areas, peat accumulation may decrease and erosion may increase in the bare areas. This would result in microtopographic changes that may eventually lead to the formation of marsh potholes.

Lastly, shading did not have a significant effect on the regrowth of J. roemerianus after clipping. However, shading inhibited the regrowth of species other than J. roemerianus. This sensitivity of other species to shading may be one reason why J. roemerianus stands are highly monospecific. The possibility of J. roemerianus being able to outcompete other high marsh species via shading deserves further study.

1. INTRODUCTION

The environmental conditions of a salt marsh affect the productivity and survival of halophytes. Chapman (1938) composed a list of factors that regulate the existence of plant species within a marsh. They included such things as tidal patterns, salinity, drainage, water table, precipitation, soil type, evaporation, temperature, and biota. Species survive in the areas of a marsh where they are physically adapted to these various environmental factors (Day et al. 1989).

Because salt marshes are coastal ecosystems, sea-level rise strongly affects them (Parkinson 1994). Thus, a significant rise in sea level would alter the species distribution and abundance, and the resultant community structure of a marsh (Oertel et al. 1992). The increased inundation of the high marsh community would result in longer periods of waterlogged soils which decreases the productivity of some plants (Bertness 1991b, Nyman et al. 1993). Furthermore, plants associated with the low marsh community may invade the high marsh (Adams 1963, Warren & Niering 1993).

Since sea-level rise is occurring slowly, communities may be able to resist the structural changes associated with the gradual increase in inundation. Some of the ways a community is able to resist change is through the accumulation of organic matter, baffle-like stems and leaves, and erosion-resistant roots and rhizomes. Since communities may be able to resist changes, disturbances more abrupt than rising sea level may be necessary to cause changes in high marsh communities (Brinson et al. 1995). An example of an abrupt disturbance is a storm depositing wrack onto a high marsh (Hayden et al. 1992, Brinson et al. 1995). Wrack deposition causes severe vegetation diebacks within the high marsh community (Reidenbaugh et al. 1983, Hartman 1988, Knowles et al. 1991). This type of disturbance creates open areas for new or neighboring species to invade. Distichlis spicata (L.) Greene (salt grass), Spartina alterniflora Loisel. (smooth cordgrass), and Salicornia europaea L. (glasswort) dominate the recolonization of bare soil patches regardless of what species were present originally (Reidenbaugh & Banta 1980, Bertness & Ellison 1987, Hartman 1988, Knowles et al. 1991).

Few studies focus on more than one type of disturbance. Therefore, there is a lack of knowledge on how systems respond to interacting disturbances such as increased inundation and wrack deposition (Lugo 1978, Turner 1988). Furthermore, few studies have investigated the impact of abrupt disturbances which result in a change in saltmarsh community structure (Brinson et al. 1995). This lack of knowledge about how combined disturbances affect the community structure of salt marshes lead to the topic of this thesis. The focus of my thesis research was to study the effects of increased inundation and wrack deposition, singularly and in combination, on the plants of a high marsh community.2. LITERATURE REVIEW

2.1. Overview of Salt Marshes

Intertidal salt marshes, inundated and drained by astronomical tides, are located along temperate coasts. Some salt marshes are among the most productive ecosystems in the world. Primarily, flowering halophytes dominate the vascular plant community of intertidal salt marshes; usually one or a few plants dominate (Mitsch and Gosselink 1993). The physical appearance of salt marshes differs among regions. Along the southeastern Atlantic and Gulf of Mexico coasts, marshes tend to have dense and robust vegetation. Higher-latitude coastal areas generally contain shorter and sparse vegetation (Day et al. 1989, Mitsch and Gosselink 1993).

One noticeable characteristic of salt marshes is the presence of vegetative zonation. This pattern is similar from one marsh to another. Day et al. (1989) cited three spatial scales on which zonation occurs: (1) latitudinal zonation, (2) zonation at the level of the coastal drainage basin, and (3) local zonation. Latitudinal zonation is the result of primary climatic differences. Zonation at the level of the coastal drainage basin is the result of the distance of the vegetation from the tidal creek. With this gradient of inundation, there also is a salinity gradient. Local zonation patterns are the result of local elevation, drainage, soil type, and sources of freshwater and saltwater. These factors affect the growth and reproduction of the different species of marsh plants. Different species vary in their tolerances to degree and duration of inundation and to salinity (Day et al. 1989).

Variations in abiotic factors along a topographic gradient lead to development of distinctive low elevation and high elevation plant communities. Monospecific stands of S. alterniflora often characterize the low marsh community along the Atlantic coast. The soil elevation in this community is low enough to allow for inundation on every high tide. The soil is typically mineral and has little to no peat accumulation. In contrast, Spartina patens (Aiton) Muhl. (saltmarsh hay) and D. spicata or short S. alterniflora typically dominate the high marsh community of Atlantic coast marshes. The high marsh community also may contain monospecific stands of Juncus roemerianus Scheele (black needlerush) or Juncus gerardi. Other taxa such as Salicornia spp. may be present in low numbers. The high marsh community is not inundated as frequently as the low marsh community because it is farther away from the tidal creek and often at a higher elevation. The soil of the high marsh often contains a thick layer of peat (Mitsch & Gosselink 1993).

2.1.1. Salt Marsh Development and Stability

Redfield (1967) cited several interacting factors that influence the development of a prograding salt marsh in New England. These factors included tidal range, physiology of the plants that produce peat in relation to tide levels, sedimentation rates on open tidal flats and within the stands of plants, and the relative change of sea level. Plants that can withstand limited submergence colonize barren areas located at the upper elevational limit for tidal inundation within a marsh. In New England salt marshes, these areas contain S. patens, D. spicata, short S. alterniflora, and a few other minor species. When these plant species die, they add to the peat layers of the high marsh. Tall S. alterniflora grows from the mid-intertidal to low intertidal areas of a marsh high. Mineral sediment accumulates within the low marsh stands of S. alterniflora. This accumulation of sediment eventually will reach the high-water level and become overgrown with high saltmarsh plants. Then organic peat from the death of high saltmarsh plants covers the sediment (Redfield 1967). This simplified outline of events has been the driving theory behind salt marsh development studies. However, Redfield's prograding marsh hypothesis is limited given salt marshes have a larger range of developmental patterns (Stevenson et al. 1986, Brinson et al. 1995).

Brinson et al. (1995) outlined four different patterns to explain how coastal marshes may respond to changes in sea level and sedimentation rates. The patterns were developed based on the slope of the marsh from the edge of the estuary to the terrestrial forest (gentle versus steep) and on the sediment supply (high versus low). The first pattern is a marsh with a gentle slope and a high sediment input, and is what Redfield (1967) described for New England marshes. This first pattern of community response hypothesizes the high marsh would migrate overland into the terrestrial forest. At the same time, the low marsh would be prograding into the estuary (Brinson et al. 1995). The second pattern involves a marsh with a gentle slope and a low sediment input. With these conditions, the high marsh would invade the upland forest while erosion occurred in the low marsh. Several marshes along the Mississippi Delta would fall into this second category. The other two patterns involve a marsh with a steep slope that would prevent the overland migration of the marsh into the upland forest. The marsh edge along the estuarine may be either prograding or eroding depending on the sediment supply. These four different patterns represent the extreme points along a gradient of possible patterns.

Elevational gradients, degree of tidal inundation, and sedimentation rate control the type of marsh environment that will develop for plant colonization. The rate of sea-level rise and sediment accumulation on the surfaces influence the maintenance of marshes (Oertel & Woo 1994). Marshes lining major estuarine systems (i.e., Hudson, Delaware, and Chesapeake estuaries) receive relatively small amounts of sediments from tidal waters. Therefore, the marshes are unable to keep pace with the relative rise in sea level and become submerged. Preservation of these marshes is possible by invasion of the marsh community into upland communities (Oertel & Woo 1994, Brinson et al. 1995). Continued inundation will cause changes in marsh topography and plant community structure (Oertel et al. 1992). However, long-term shifts in plant communities are not predictable, which makes the prediction of successional patterns difficult (Clark 1986, Nuttle et al., in prep).

2.1.2. Salt Marsh Hydrology

Hydrology plays an important role in determining the structure and productivity of coastal ecosystems. Inundation is important for the input of nutrients (Harvey & Odum 1990), the exchange of particulate organic matter (Hemminga et al. 1993), and the addition and removal of salts from the sediment (Hackney & de la Cruz 1978, Nuttle & Harvey 1995). A rise in sea level would alter the hydrology of a marsh by increasing the inundation of higher elevations and possibly raising the water table. By raising the water table, surface runoff will increase, as would duration and amount of saturated areas (Nuttle & Portnoy 1992).

The alteration of the flooding and drainage regimes of a marsh influences primary productivity (Parrondo et al. 1978, Linthurst & Seneca 1980, Mendelson & Seneca 1980, Zedler et al. 1980, Linthurst & Seneca 1981, Wiegert et al. 1983, Seneca et al. 1985, DeLaune et al. 1987, McKee & Patrick 1988, Morris & Haskin 1990, De Leeuw et al. 1990, Strakosch 1992, Reed & Cahoon 1992, Osgood & Zieman 1993). An increase in nutrients and a decrease in salinity may promote an increase in productivity(Parrondo et al. 1978, Linthurst & Seneca 1981, Osgood & Zieman 1993). A decrease in productivity may be the result of prolonged anoxic conditions caused by waterlogging (Mendelssohn & Seneca 1980, Linthurst & Seneca 1981, Weigert et al. 1983, Strakosch 1992). However, the positive increase in productivity associated with increased inundation is not consistent among studies. Some showed an increase in productivity(Strakosch 1992), while others showed a decrease (Zedler et al. 1980, DeLaune et al. 1987, Strakosch 1992, Reed & Cahoon 1992), or no change in productivity (De Leeuw et al. 1990).

2.1.3. Salt Marsh Zonation

Several interacting environmental factors influence the distribution of plants within a salt marsh. These factors include tides, salinity, drainage, aeration, water table, rainfall, soils, evaporation, temperature, and biota (Chapman 1938). Of these factors, tides are the primary factors influencing the distribution of plants within a marsh (Chapman 1938). Because of this idea, many researchers have studied the correlation between tidal inundation and plant distribution within a marsh. The frequency and amplitude of tides and elevation were determined to be the primary factors controlling the distribution of plant species in several North Carolina salt marshes (Adams 1963). Eleuterius & Eleuterius (1979) studied the frequency and duration of tidal inundation and exposure in relation to the dramatic change in vegetation in Davis Bay, Mississippi salt marsh. The change in plant species was from a monotypic zone of S. alterniflora to a monotypic zone of J. roemerianus. Inundation occurred more frequently in the S. alterniflora zone, which was located at a lower elevation than the J. roemerianus zone. Even though parts of these two different zones had different tidal relationships, the abrupt change in plant species did not correlate to the frequency or the duration of inundation. Eleuterius & Eleuterius (1979) suggested that factors other than tides were involved in determining the distribution of plant species.

Research on plant zonation conducted in a New England marsh involved factors associated with inundation such as salinity and substrate redox potential (Bertness & Ellison 1987). In New England salt marshes, S. alterniflora dominates the low marsh community. S. patens and J. gerardi dominate the high marsh (Bertness & Ellison 1987, Lefor et al. 1987, Bertness 1991a) and short S. alterniflora in some marshes (Redfield 1967). Each zone has different characteristic physical factors that are related to tidal inundation. Salinity and substrate redox potential decrease with increasing marsh elevation (Bertness & Ellison 1987). Furthermore, competitive displacement restricted S. alterniflora to the low marsh (Bertness 1991b). In contrast, Bertness (1991b) hypothesized that the restriction of S. patens to the high marsh is because of its limited aerenchyma tissue development.

Interspecific competition also may play an important role in determining plant zonation. Removal and transplant experiments done in a New England high marsh demonstrated that J. gerardi dominated S. patens and D. spicata. Furthermore, S. patens outcompeted D. spicata. However, this is not the case in bare soil patches. D. spicata and S. patens colonize bare soil patches, which are often hypersaline, before J. gerardi is able to grow in these areas. D. spicata and S. patens are more tolerant of high saline conditions then J. gerardi. Furthermore, the colonizing species appear to be able to lower the salinity of the bare soil, therefore, facilitating the growth of J. gerardi into the previously bare areas (Bertness 1991a).

2.2. Defining Stress and Disturbance

Ecologists widely apply the concept of stress to describe patterns occurring in different ecosystems (Lugo 1978). Lugo (1978) defined a stressor as "any condition or situation that causes a system to mobilize its resources and increase its energy expenditure." A stress is the response of an ecosystem to the stressor. An acute stressor is one that stresses an ecosystem for a short period time and the ecosystem is able to recover. Continuous or chronic stressors occur for long periods of time within an ecosystem (Lugo 1978, White 1979). Many organisms are able to adapt and survive within a stressed ecosystem. However, a major result of adaptation to a stressor is a decline in metabolic rates (Parsons 1989). Furthermore, organisms adapted to living in stressful environments are continuously overcoming the stress. For example, salt marsh plants are always dealing with the problems of inundation and salinity even though they may be adapted to survive flooding and salinity (Lugo 1978).

Some stressors are a normal part of an ecosystem while others are infrequent, acute events. Both normal and infrequent stressors cause a loss of energy in the system. Organisms within an ecosystem are usually able to adapt to normal stressors but are not as well adapted to infrequent stressors. Therefore, the effects of normal stressors are not as immediately obvious as infrequent stressors (Lugo 1978).

The effects a stressor has on an ecosystem are the result of several factors. These factors include such things as (1) the intensity of the stressor, (2) multiplicative (effect is greater than the sum of the individual stressors) or additive (effect equal to the sum of the individual stressors) effects on the ecosystem, (3) frequency, (4) ecosystem type, (5) condition of the ecosystem, and (6) the intensities, residual effects, and frequency of other stressors at the time of occurrence (Lugo 1978, Turner 1988). Chronic stressors are usually more harsh on an ecosystem than acute stressors. However, acute stressors still may be very damaging depending on their intensity, timing, and the ability of the ecosystem to recover. Furthermore, if more than one stressor occurs at the same time, the impact may be either additive or multiplicative and cause even more of an energy drainage on the system (Lugo 1978, Turner 1988).

The response of an ecosystem to a stressor may be either positive or negative. An increase in growth and net productivity may occur after some stresses. Disruptive stressors, such as tides and storms, help to remobilize resources within a system and may bring in new resources (Lugo 1978, Odum 1980). Furthermore, species diversity may increase after a disturbance. For example, a storm event may decrease salinity stress and allow for less saline tolerant plant species to invade an area. When normal salinity conditions return, the species diversity of the area will then decrease and return to pre-storm levels (Lugo 1978).

Disturbance is a physical stressor that is external to the community and causes a change in the community structure. A perturbation is the effect of a disturbance (Fahrig 1990). Most researchers do not make the distinction between disturbance and perturbation. Instead researchers tend to use the word "disturbance" for both the cause and the effect. Normally this practice does not cause difficulties (Fahrig 1990).

Traditionally, the term disturbance has been limited to describing infrequent, abrupt events that cause immediate structural changes in communities (White 1979). However, this approach is limiting since disturbances, as with other types of stressors, occur along the gradient of minor to major events (Lugo 1978, White 1979). Furthermore, the biotic structure of the community may promote some types of disturbances. For example, the severity of a fire depends not only on the source of the fire but also the amount and combustibility of organic matter within the community (White 1979).

Although physical factors may stimulate disturbances, the community type may determine the occurrences and the effects of disturbances (White 1979). The types of disturbances affecting a community may vary regionally and within a community as a function of the area's geomorphology and other local variables. Examples of the types of natural disturbances that affect vegetation include the following: fire, wind, ice, cryogenic soil movement, temperature changes, precipitation variability, alluvial processes, coastal processes, dune movement, saltwater inundation, landslides, lava flows, and biotic disturbances (White 1979). Two disturbances commonly associated with salt marshes are saltwater inundation and wrack deposition. I will discuss how these two types of disturbances relate to a rise in sea level in detail later.

2.3. Responses of a Salt Marsh Plant Community to Disturbances

Some disturbances create open areas that may allow for colonization by new or neighboring species. Revegetation often begins in the first growing season after the disturbance. Reidenbaugh and Banta (1980) documented new growth of S. alterniflora on bare soil patches within two years after the disturbance of wrack deposition. Two other species associated with recently disturbed sites are D. spicata and Salicornia europaea. D. spicata is a rapid colonizer, invading areas with vegetative runners. In contrast, S. europaea is a seed colonizer (Ellison 1987, Hartman 1988). However, in a New England marsh, the slower growing S. patens and J. gerardi eventually replaced the colonizing species (Bertness and Ellison 1987). In an irregularly flooded J. roemerianus marsh (Cedar Island, North Carolina), S. patens and other species excluded J. roemerianus from being able to grow in bare patches after a disturbance. Furthermore, J. roemerianus seeds were unable to germinate in open areas (1) with salinities greater than 20 ppt., (2) which were regularly flooded, or (3) which had reduced soils (Knowles et al. 1991).

Few studies focus on more than one type of disturbance (Turner 1988). However, Turner (1988) conducted a study involving multiple disturbances. She experimentally examined the combined effects of clipping, trampling, and fire on the productivity of S. alterniflora. Clipping combined with either trampling or fire reduced the net aboveground primary productivity (NAPP) of S. alterniflora more than predicted. The effect of the combination of trampling and fire was additive on S. alterniflora NAPP. Therefore not all combinations of disturbances produce additive responses. Because of this fact, it is important to understand how disturbances interact in order to predict how a community will respond to disturbances (Turner 1988).

2.4. The Effects of a Rise in Sea Level on the Community Structure of Salt Marshes

Because coastal ecosystems are located at the land-sea ecotone, they are strongly affected by changes in sea level (Parkinson 1994). There are several different ways a salt marsh may respond to a rise in sea level. An important consideration is the marsh's ability to maintain surface elevations relative to the mean high water level. Important factors that determine surface elevations include local submergence rates, sedimentation rates, density and composition of plants, hydrogeomorphic setting, and the type and intensity of human modifications. Furthermore, vertical accretion rates vary both spatially and temporally in marshes. This variation makes it difficult to predict how a marsh will respond to sea-level rise (Kearney et al. 1994).

Since sea-level rise is occurring slowly over a long period of time, rising sea level alone does not alter community structure. Changes in community structure occur with events more abrupt than rising sea level. Altered ecosystem states develop new self-maintaining properties, facilitate plant species replacement, and change sediment conditions (Brinson et al. 1995). For example, patterns of accretion and erosion in one Virginia salt marsh caused the marsh to change from a juvenile foreshore marsh to a creek-drained marsh (Reidenbaugh et al. 1983). Wrack deposition is an abrupt event that causes severe vegetation diebacks and erosion at higher elevations (Reidenbaugh et al. 1983).

The factors that determine and maintain the composition of plant species from estuaries to upland forests differ among the different zones in a marsh (Hayden et al. 1994, Brinson et al. 1995). Brinson et al. (1995) stated "Transitions between states are facilitated by disturbance or exposure to acute stress." The effects of rising sea level can be seen in the following mechanisms for the high marsh: (1) increased levels of brackish water at higher elevations, (2) tidal creek erosion of the marsh surface as it encroaches further into the marsh, and (3) increased water depth which causes increased waterlogging and anoxic conditions. Increased levels of brackish water and waterlogging result in osmotic stress and sulfide toxicity within anoxic conditions in the sediments. Tidal creek erosion of the high marsh causes greater drainage near the edge of the marsh and the movement and suspension of sediments. At lower elevations other mechanisms act to effect change (Brinson et al. 1995).

Currently, there are few studies that have investigated the effects of abrupt events which result in the change of the community structure of coastal marshes (Brinson et al. 1995). The lack of knowledge about ecological and geological processes hinders future predictions of the effect of sea level on coastal ecosystems (Brinson & Moorhead 1989). My work focuses on two processes in the high marsh community that are associated with an increase in mean sea level. These two processes are increased seawater inundation and wrack deposition.

2.4.1 Increased Seawater Inundation

A rise in sea level would cause the erosion of tidal creeks and an increase in the frequency of flooding at higher elevations (Hayden et al. 1994). As a result of the altered inundation patterns, salt marsh plants previously associated with more frequently inundated lower elevations may invade higher elevations (Adams 1963). Furthermore, increased inundation may result in longer periods of waterlogged soils if increased drainage does not occur. The anoxic stress caused by waterlogging may result in a decrease of aboveground primary production by macrophytes. A reduction in aboveground plant growth as a result of increased inundation as been suggested to be one cause of the loss of land in the Terrebonne Basin, Louisiana (Nyman et al. 1993). Plants prevent the loss of land by trapping fine-grain sediments (fine silt and clay) on marsh surfaces (Stumpf 1983, Nyman et al. 1993) and by accumulating organic matter (Moorhead & Brinson 1995). The trapping of sediments and the accumulation of organic matter aid in the vertical accretion of the marsh. A decrease in plant productivity results in limited vertical accretion, which causes an increase in flooding and even greater decreases in primary production (Nyman et al. 1993). A study with S. alterniflora demonstrated this decrease in productivity as a result of standing water. The productivity of S. alterniflora grown in 30 cm to 0 cm of standing water ranged from 0 to 1144 g/m2, respectively (Linthurst & Seneca 1980).

The change in vegetation zonation in Wequetequock-Pawcatuck (Connecticut) tidal marshes over the last forty years has been linked to differential rates of marsh accretion and sea-level rise (Warren & Niering 1993). In the late 1940's, the marshes supported a J. gerardi-S. patens belting pattern characteristic of many New England salt marshes. The areas in most marshes that were once dominated by J. gerardi are now forbs, primarily dominated by Triglochin maritima. The zones previously dominated by S. patens are now composed of a mixture of short S. alterniflora, D. spicata, forbs, and relic stands of S. patens. The surfaces of the marshes are at lower elevations than they were in the 1940's relative to sea-level. The lower elevations caused greater frequency and duration of tidal inundation on the marshes. The change in tidal patterns also resulted in increased peat saturation, salinity, and sulfide concentrations, and a decrease in redox potential. These abiotic and biogeochemical responses to increased inundation initiated a change in plant species composition to one that favored wetter, more open vegetation types dominated by short S. alterniflora and forbs (Warren & Niering 1993).

The effects of increased surface flooding, increased subsurface drainage, and natural hydrology were studied experimentally for three years in a New Jersey salt marsh (Strakosch 1992). The study site was in an area dominated by short S. alterniflora. Although S. alterniflora remained dominant in all treatments, species richness decreased with flooding and increased with drainage relative to the controls. An increase in prolonged waterlogged conditions was presumed to be the main reason for the decrease in species richness. Several different but interrelated factors could have caused the increase in species richness in the drainage treatments -- removal of waterlogging, soil conditions, microtopography, seed source, and the adaptive ability of halophytes. Increased flooding did not have a significant effect on S. alterniflora stem density or belowground biomass. In contrast, increased drainage caused a decrease in stem density and belowground biomass. Increased inundation in areas of short S. alterniflora did not result in the production of tall S. alterniflora. However, the increased inundation did produce a plant community structure similar to the low marsh.

2.4.2. Wrack Deposition

Tidal wrack is composed of dead plant material that forms mats that are carried and deposited onto the marsh surface by winds, tides, and currents (Reidenbaugh and Banta 1980). In Atlantic coast salt marshes, tall S. alterniflora composes most wrack mats; but in some areas, there is a high percentage of Zostera marina present (Reidenbaugh and Banta 1980). In Gulf Coast marshes, dead J. roemerianus leaves compose the wrack mats (Stumpf, personal communication). Standing dead stems of plants break from the marsh surface and float together in mats. In cold climates, ice shearing may enhance this process. When high tides, storms, or wind deposit wrack in the marsh, the vegetation under the wrack dies as a result of compaction and smothering (Reidenbaugh and Banta 1980, Hartman 1984, Knowles et al. 1991). This killing of plants creates barren patches of soil, referred to as "secondary" bare soil since they were previously vegetated (Chapman 1940). A rise in sea level may result in increased disturbance of the high marsh by wrack deposition and intrusion of wrack farther into the marsh (Brinson et al. 1995).

Wrack is often created during the late fall and winter and deposited along the edge of the estuary. Then incoming tides carry the wrack into the marsh. Winter and spring storms produce higher tides that push the wrack farther into the marsh. Wind will bend S. alterniflora stalks toward the upland thus permitting wrack to move over the edge of the estuary and preventing it from being carried back to the estuary when the water recedes (Reidenbaugh and Banta 1980).

S. alterniflora wrack killed large amounts of aboveground vegetation in several studies (Reidenbaugh and Banta 1980, Hartman 1988, Knowles et al. 1991). Reidenbaugh and Banta (1980) found wrack caused complete devegetation in a low marsh on the Delmarva Peninsula during the spring. Furthermore, they found only partial devegetation in the transition zone between the low and high marsh, and partial or complete diebacks in the high marsh. However, the amount of devegetation by tidal wrack varied greatly from year to year depending on the tidal levels in the early spring. The higher the tidal amplitude in the spring, the more severe the dieback recorded. The degree of devegetation caused by wrack also depended on the elevation of the marsh and the time of year the deposition occurred. The most severe diebacks occurred in the low marsh during the spring (Reidenbaugh and Banta 1980).

A three year study of the recolonization of bare soil areas caused by wrack was conducted at the Great Sippewissett salt marsh (Cape Cod, Massachusetts). Hartman (1988) studied the presence of colonizers and abiotic factors in order to determine the causes of the rates and patterns of recolonization. S. alterniflora dominated the regrowth of the bare areas via vegetative expansion. Some colonization of the patches did occur from seed germination of Salicornia spp. The only other colonizer was D. spicata, but it was of minor importance compared to S. alterniflora. This is interesting because S. patens and D. spicata dominated the areas surrounding the open patches with S. alterniflora contributing little to the total biomass of the community. Salinity, sulfide concentrations, and ammonium concentrations from disturbed and undisturbed sites were not significantly different and could not explain the rates and patterns of recolonization. Therefore, the proximity of S. alterniflora and its ability for recolonization by vegetative expansion controlled the rate of recolonization of bare areas (Hartman 1988).

Knowles et al. (1991) concluded disturbance by wrack was the main cause of the mosaic vegetation patterns on Cedar Island (North Carolina), an irregular flooded marsh dominated by J. roemerianus. Mortality rates of plants under experimentally placed wrack were high. Light exclusion, leaf compression, and elevated sulfide levels in the soil were the main causes of the plants' death. Recolonization of the bare soil areas varied based on the location of the bare area. Bare areas that were located close to the edge of the island, and therefore more likely to be inundated, were colonized by D. spicata or persisted as algal pannes. A range of species other than J. roemerianus colonized the bare areas farther inland. These species included S. patens, D. spicata, Fimbristylis spadicea, and Panicum virgatum. Seedlings of J. roemerianus and several annuals were found colonizing bare patches located on elevated hummocks. Once bare patches were colonized by such species as D. spicata and S. patens, J. roemerianus slowly regrew back into these areas so that patch borders remained for decades (Knowles et al. 1991).

2.5. Plants Associated with a High Salt Marsh Community

2.5.1. Juncus roemerianus Scheele (Juncaceae), needlerush or black needlerush

J. roemerianus generally grows in areas of infrequent inundation, such as high marshes, along the Atlantic coast from Virginia to Florida and along the coast of the Gulf of Mexico, between the latitudes of 26o N and 42o N (de la Cruz & Gabriel 1974, Eleuterius 1976). However, sparse populations occur as far north as New Jersey, Long Island, New York, Connecticut, and as far south as Lauguna Madre, Texas, Mexico, and on Caribbean Islands (Eleuterius 1976). J. roemerianus forms patches of monospecific stands that may dominate a marsh or be within marshes where other species dominate. For example along the Gulf Coast, these J. roemerianus stands usually occur in areas where the tidal amplitude is rarely more than 1 m. J. roemerianus grows with S. patens, D. spicata, Spartina cynosuroides, and Scirpus americanus (de la Cruz & Gabriel 1974).

J. roemerianus leaves are tough, long, cylindrical (3-5 mm in diameter), slightly tapered, and terminate with extremely, sharply pointed tips, thus its common name. J. roemerianus grows continuously throughout the year. New growth occurs in the basal region from perennial underground rhizomes (Foster 1968, Seibert 1969, Williams & Murdoch 1972, Anderson 1974, Eleuterius 1975, Giurgevich & Dunn 1978, Snogerup 1993). The maximum rates of growth for J. roemerianus in Mississippi occur from May through July (de la Cruz and Gabriel 1974) and in North Carolina from May to June (Foster 1968). Annual net primary productivity (ANPP) and aboveground biomass of J. roemerianus have been estimated for several different marshes. In North Carolina marshes, ANPP has been estimated between 560 and 1038 g/(m2 x y) (Foster 1968, Murdoch & Williams 1972, Blum et al. 1978, Christian et al. 1990). ANPP for J. roemerianus in one Georgia marsh was from 1500 to 2800 g/(m2 x y) (Gallagher et al. 1980). The aboveground biomass of J. roemerianus in Mississippi marshes ranges from 400 g/m2 to 2000 g/m2 (Eleuterius 1972). Total aboveground J. roemerianus biomass in North Carolina marshes ranges from 35 g/m2 to 2294 g/m2 with standing dead leaves making up most of the biomass (Murdoch & Williams 1972, Cooper & Waits 1973, Blum et al. 1978, Christian et al. 1990, Hook 1991). The large range of numbers reported for marshes located within the same geographic area may be in part the results of differences in the methods used to estimate productivity (Kaswadji et al. 1990).

The gynodioecious flowers of J. roemerianus are unusual for both Juncaceae and salt marsh angiosperms where flowers are normally only perfect. J. roemerianus has both perfect and pistillate flowers but no stamimate flowers. The timing of flowering varies throughout the range of J. roemerianus (Eleuterius 1975). For J. roemerianus populations on the eastern Atlantic, flowering occurs from May until October (Radford et al. 1968). Sexual reproduction may be important in the colonization of new areas while vegetative reproduction is the driving force in maintaining an established population (Eleuterius 1975).

The ionic and anoxic stresses of a salt marsh affect the survival and productivity of J. roemerianus. Ionic stress, caused by high salinities, and anoxic stress, caused by waterlogged soils, have a negative effect on the growth of J. roemerianus (Eleuterius 1984, 1989a & b). In addition to reducing the growth of J. roemerianus, ionic toxicity reduces the number of flowers and seeds produced (Eleuterius 1989b). One adaptation J. roemerianus has to combat ionic stress is the ability to grow deep penetrating specialized roots that go down to areas of lower salinities (Eleuterius 1984). J. roemerianus does not have the ability to secrete salts or block the uptake of ions (Anderson 1974). To counterbalance anoxic stress, J. roemerianus develops aerenchyma (Anderson 1974). Furthermore, one species of Juncus, J. gerardi, is able to actively oxidize the sediments around the rhizomes and roots (Hacker & Bertness 1995). J. roemerianus also may be able to oxidize its rhizomes and roots.

2.5.2. Spartina patens (Aiton) Muhl. (Poaceae), saltmarsh hay, saltmeadow cordgrass, saltmeadow grass

The geographic range of S. patens is greater than the range of J. roemerianus with populations occurring from New England to Florida marshes along the Atlantic coast and in marshes along the Gulf of Mexico. The aboveground biomass of S. patens in a North Carolina marsh was estimated between 230 and 440 g/m2 (Cooper & Waits 1973) and 430 g/m2 for a New England marsh (Nixon & Oviatt 1993) where this species is dominant. Hook (1991) estimated the aboveground biomass for S. patens to range from 3.0 to 21 g/m2 within a J. roemerianus dominated marsh in North Carolina.

Several factors probably interact to influence the primary production of S. patens and limit it to the high marsh communities (Burdick et al. 1989). From recent research with S. patens populations, Bertness (1991b) suggested that this species is restricted to the high marsh because of limited aerenchyma development. Anoxic conditions decrease the growth of S. patens (Smart & Barko 1978). A reduction in soil oxygen levels can initially reduce the photosynthetic activity of S. patens. However, S. patens is able to recover this loss of photosynthetic activity (DeLaune et al. 1990). Furthermore, anoxic conditions stimulate the production of alcohol dehydrogenase (ADH) in S. patens. However, hydrogen sulfide, which accumulates in anoxic soils, inhibits ADH in some plants. The decrease of ADH activity results in lower total adenine nucleotides, adenylate energy charge ratio (AEC), nitrogen uptake, and growth (Koch et al. 1990).

Ionic stress also has a negative effect on the growth of S. patens (Smart & Barko 1978, Pezeshki et al. 1987, Pezeshki & DeLaune 1993, Bandyopadhyay et al. 1993, Broome et al. 1995). The experimental increase of soil salinity from 0 ppt. to 22 ppt. caused a 54 % reduction in the stomatal conductance and a 43 % reduction in net photosynthesis. Furthermore, salt excretion from leaves occurred within three to five days after the salinity was increased (Pezeshki et al. 1987). When tested over a range of salinities, soil hypoxia was determined to be the most important factor controlling nutrient uptake in S. patens. Therefore in submerging coastal ecosystems, increased inundation and decreased soil redox potential are the primary stress factors causing the displacement of S. patens unless salinity levels are extremely high (Bandyopadhyay et al. 1993, Broome et al. 1995).

S. patens has developed some adaptations to ionic stress and anoxic conditions. First, S. patens has the ability to secrete salt out of its leaves through salt glands (Anderson 1974, Queen 1974, Broome et al. 1995) and through its roots (Broome et al. 1995). Furthermore, S. patens is selective in its ion uptake and is able to actively exclude certain ions (Smart and Barko 1978). S. patens does have aerenchyma in its roots (Anderson 1974, Burdick & Mendelssohn 1987, Cooke et al. 1993) though its development is limited (Gleason & Zieman 1981, Bertness 1991b).

2.5.3. Distichlis spicata Raf. (Poaceae), saltgrass or spike grass

The geographic range of D. spicata is similar to the range of S. patens with D. spicata growing in marshes along the Atlantic and Gulf coasts. D. spicata is often found in association with S. patens. The only estimate of aboveground biomass I could find for D. spicata was for two North Carolina marshes where D. spicata ranged from 190 to 240 g/m2 when it was a dominant species (Cooper & Waits 1973) and 0.2 g/m2 within J. roemerianus stands (Hook 1991).

Ionic stress and anoxic conditions have a negative effect on the growth of D. spicata (Smart and Barko 1978). However, D. spicata does have several adaptations for growing and surviving in a salt marsh. It is able to secrete salt (Anderson 1974, Liphschitz & Waisel 1982), is capable of ion exclusion, and has selective ion uptake (Smart & Barko 1978, 1980). D. spicata also is able to increase its succulence (Flower 1985). Under low nitrogen conditions, D. spicata will decrease its aboveground production and increase its belowground production (Smart & Barko 1980). It is often one of the first plants to colonize bare soil patches (Hansen et al. 1976, Hartman 1988, Bertness 1991a, Knowles et al. 1991).

2.5.4. Spartina alterniflora Loisel. (Poaceae), smooth cordgrass

S. alterniflora has been the most widely studied marsh plant. While the tall form of S. alterniflora dominates the low marsh, a short form of S. alterniflora often occurs in the high marsh. The presence of other plants excludes S. alterniflora from the high marsh (Bertness 1988). One of the differences between short S. alterniflora and tall S. alterniflora, besides their location within a marsh, is the amount of nitrogen present within the plants. The short form tends to have less nitrogen and a lower nitrogen metabolism than the tall form (Mendelssohn 1979). High sulfide concentrations (King et al. 1980), low sediment oxidation (Linthurst 1980, King et al. 1982, Howes et al. 1986), and high salinities (Morris & Haskin 1990, Osgood & Zieman 1993) may limit nitrogen uptake by S. alterniflora. The result of a decrease in nitrogen uptake is a reduction in aboveground productivity.

Furthermore, an increase in the peat density of soil may cause a decrease in aboveground production (Bertness 1988). Tall S. alterniflora plants collected from a silt-clay area and a sandy area of the same creek had similar biomasses. Differences in plant size did exist with the silt-clay soil having taller and more robust plants than plants collected from the sandy soil. This shows the importance of substrate type on the allocation of resources (Christian et al. 1983).

Aboveground productivity of S. alterniflora increases with subsurface drainage (Mendelssohn & Seneca 1980, Wiegert et al. 1983, Strakosch 1992), and stagnant conditions decrease productivity (Linthurst & Seneca 1980, Mendelssohn & Seneca 1980, Strakosch 1992). S. alterniflora grown in a greenhouse with aerobic soil had an average of 6.3 times higher biomass than plants grown in an anoxic substrate (Linthurst 1980). In a Louisiana marsh, researchers found a positive correlation between marsh elevation and S. alterniflora growth (Reed & Cahoon 1992).

2.5.5. Salicornia spp. L. (Chenopodiaceae), glasswort

Salicornia spp. are annuals and are associated with high salinity and disturbed areas (Ellison 1987). Salicornia europaea is able to colonize bare patches in salt marshes through the germination of seeds (Ellison 1987, Ungar 1987, Hartman 1988). Provided other species do not invade the patch, S. europaea is able to maintain its productivity. However, other marsh species will rapidly outcompete S. europaea and eventually overgrow the patches if salinity is low (Ellison 1987). Its main adaptation to ionic stress is increased succulence (Flower 1985). However, soil salinity levels do control the growth and survival of Salicornia spp. The main response to high salinity stress is a reduction in plant growth. Mortality occurs at extreme levels of salinities. Density-dependent factors can cause high mortality in some populations (Jefferies et al. 1981) but not in others (Ungar 1987).

2.6. Major Points of Literature Review (Summary)

Several major points were made in this introduction which relate to the theme of this thesis. First, salt marshes have characteristic zonation of macrophytes based on the elevation of the marsh and the frequency of inundation. A rise in sea level could alter the distribution of plants in a marsh. Furthermore, wrack deposition also can alter the plant composition of a salt marsh. However, it is not known whether or not the combination of inundation and wrack would accelerate the change in macrophyte composition.

3. GOALS OF RESEARCH, POSTULATED MECHANISMS, AND NULL HYPOTHESES

The main goal of this investigation was to determine the effects of experimental tidal inundation and wrack deposition on the plants of an organic high marsh. Specifically, I investigated the effects of increased inundation and wrack deposition, individually and in combination, on aboveground growth, senescence, and biomass accumulation and ground cover change after an experimental disturbance. The experiment was set-up as a random block design that contained both J. roemerianus dominated areas and S. patens and D. spicata dominated areas. Estuarine saltwater was pumped onto a third of the plots during the growing seasons. Wrack was placed onto half of each plot and was partially removed after six months. Furthermore, a reference population of J. roemerianus leaves was monitored for comparison with the experimental control. A shading experiment also was set-up to determine the effects of taller J. roemerianus leaves on shorter, younger leaves. The following paragraphs contain the postulated mechanisms for this thesis. The specific null hypotheses are listed at the end of this section.

3.1. Postulated Mechanisms

Christian et al. (1990) and Hook (1991) found no overall significant correlation between production of J. roemerianus along a gradient of hydroperiods and salinity in an irregularly flooded marsh. Nuttle and Harvey (1995) reported flooding in tidal marshes helps to remove salts from marsh soils during periods of reduced evaporation. If the pumping of water onto the plots is able to remove salts from the soil, therefore, reducing the salinity, the growth of J. roemerianus may be greater in the inundated plots than in the border control and control plots. However, since J. roemerianus does not normally grow in regularly flooded areas, a decrease in the production of J. roemerianus in the flooded plots may occur. Furthermore, the inundation may actually increase the salinity, which has been shown to inhibit the growth of J. roemerianus (Eleuterius 1984) and the growth of J. gerardi (Bertness et al. 1992).

Hook (1991) found disturbed sites that receive a greater amount of inundation have a greater susceptibility to decreased growth and increased mortality. Furthermore, J. roemerianus seeds are only able to germinate in bare patches if the areas have salinities less than 20 ppt., are not regularly flooded, and do not have reduced soils (Knowles et al. 1991). Therefore, J. roemerianus regrowth and production in post-wrack areas that are being inundated may be lower than post-wrack areas that are not being flooded.

S. patens and D. spicata are not usually found in regularly flooded areas of salt marshes (Niering & Warren 1980, Bertness 1991a). S. patens appears to be restricted from the low marsh habitat because of unsuitable physical conditions and probably not because of competition with S. alterniflora (Bertness 1991b). Therefore, increased inundation may reduce the aboveground biomass of S. patens and D. spicata in this experiment.

S. patens and D. spicata are two of the dominant colonizing species in disturbed areas in New England salt marshes (Hartman 1988, Bertness & Ellison 1987, Bertness & Shumway 1993). S. patens and D. spicata may competitively exclude J. roemerianus from being able to regrow in patches created by disturbance (Knowles et al. 1991). Furthermore, D. spicata is more tolerant of wrack burial than other plant species and may actually survive short term wrack deposition (Bertness & Ellison 1987). Therefore, S. patens and D. spicata may dominate the recolonization of post-wrack areas regardless of the species dominant in the areas before wrack deposition.

S. alterniflora also may persist after wrack burial (Bertness & Ellison 1987). Furthermore, S. alterniflora is adapted to and thrives in anoxic areas of the marsh that receive frequent flooding (Bertness 1991b). This combination of tolerances may facilitate the establishment of S. alterniflora in disturbed areas especially if those areas already have S. alterniflora present and are being flooded.

Wrack deposition causes high mortality of vegetation through the increase of sulfide levels under the mat (Hartman 1988, Knowles et al. 1991). Even though S. alterniflora is not as sensitive to wrack deposition as other marsh macrophytes, substantial short-term decreases in its production after wrack deposition can occur (Reidenbaugh & Banta 1980). However, if D. spicata and S. alterniflora are able to survive the wrack deposition, their production may be greater in the post-wrack areas than other species since the wrack deposition would reduce competition by killing the more disturbance sensitive species.

3.2. Null Hypotheses

3.2.1. Effects of Increased Inundation on Saltmarsh Vegetation

HO: Increased inundation does not affect the growth of J. roemerianus.

HO: Increased inundation does not affect the senescence of J. roemerianus.

HO: Increased inundation does not affect the growth of S. patens and D. spicata.

3.2.2. Effects of Wrack Deposition on Saltmarsh Vegetation

HO: Wrack deposition will not affect the aboveground production of the plants.

HO: Wrack deposition will not affect vegetative regrowth of a plant community.

(i.e., The pre-wrack species will return in the same abundance in a location

after wrack deposition as compared to the nonwrack areas.).

3.2.3. Combination of Increased Inundation and Wrack Deposition

HO: Increased inundation and wrack deposition are not interacting stressors.

HO: Increased inundation will not affect the vegetative regrowth during the first

growing season after wrack deposition.

3.2.4. Comparison between the Reference J. roemerianus Populations and the Experimental Controls

HO: The growth dynamics (i.e., total height, biomass, survivorship, etc.) of the reference population of J. roemerianus does not differ from the experimental control.

3.2.5. Shading Experiment

HO: Experimental shading does not promote or inhibit the growth of J. roemerianus and other marsh species.

3.3. Statement Regarding the Testing of the Hypotheses

The growth and senescence of J. roemerianus were determined by measuring the total and green heights of tagged leaves in the field through time and aboveground biomass collected at the end of the growing season. The production of S. patens and D. spicata was inferred from aboveground biomass measured at the end of the growing season. The vegetative regrowth of the plots was determined by aboveground biomass at the end of the growing season and vegetative ground cover analysis. The comparison of reference J. roemerianus populations and the experimental controls involved the monitoring of two populations of J. roemerianus that were inundated daily. The effects of shading on marsh plants involved the experimental shading of marsh pants.

4. MATERIALS AND METHODS

4.1. Site Description

The Virginia Coast Reserve - Long-Term Ecological Research site (VCR-LTER) is a 110 km long coastal marine landscape located on the southern end of the Delmarva Peninsula (USGS Nassawadox Quadrangle). The VCR-LTER consists of 14 barrier islands, coastal wetlands, deciduous and evergreen forest, and agricultural fields. The mean elevation for the VCR-LTER is less than 2 m above sea level (Hayden et al. 1994) (Fig. 1).

Brownsville Marsh (37o 27' N, 75o 50' W) is located within the VCR-LTER site. The marsh is an expansive, mainland brackish to salt marsh, whose edge is flooded twice a day by Phillips Creek, which has a tidal range of about 145 cm (Hmieleski 1994). Phillips Creek is part of the Machipongo drainage system. The change in elevation from the marsh to the forested upland is gradual on the north side and steep on the west side. The principal soil types for Brownsville Marsh are Chincoteague, Magotha, Nimmo, and Munden. All of these soil series are characteristic of moderately to poorly drained areas (Hmieleski 1994).

Distinctive plant zonation occurs throughout Brownsville Marsh. The upland forest is dominated by Pinus taeda (loblolly pine). S. patens and D. spicata dominate the organic high marsh of Brownsville. J. roemerianus also grows in the high marsh on peaty


















Fig. 1. Map of Virginia Coast Reserve Long-Term Ecological Research site (VCR-LTER).

deposits (Hmieleski 1994). Short S. alterniflora grows toward Phillips Creek (Brinson et al. 1995). A salt flat has developed in the high marsh. Along the edges of the salt flat, Salicornia sp. is growing with S. patens and D. spicata. The high marsh area is not regularly flooded, being inundated only by extreme high tides. The mineral low marsh of Brownsville is regularly flooded and dominated by S. alterniflora (Blum 1993, Brinson et al. 1995).

4.2. Overall Design of Experiment

A randomized block design was used to test the effects of increased inundation and wrack deposition on a high salt marsh plant community from March 1994 to October 1995. The experimental site was located about 30 m away from Phillips Creek, in an area that is flooded by Phillips Creek only during periods of extreme high tides (i.e., storm tides and extremely high spring tides) (Fig. 2). The experimental area contained both a J. roemerianus dominated community and a S. patens/D. spicata dominated community. The experimental design was composed of three blocks (i.e., block X, block Y, and block Z) with each block containing three 4 m x 3 m plots. Block X contained plots 1-3, block Y contained plots 4-6, and block Z contained plots 7-9. Each plot consisted of a 2 m x 3 m area dominated by J. roemerianus and a 2 m x 3 m area dominated by S. patens/D. spicata. Each block contained three treatments for flooding (i.e., flooding, border control, and control), which I describe in detail later (Fig. 3). The mean elevation above mean sea level of block X was 1.01 m, block Y was 0.975 m, and block Z was 1.03 m.



Fig. 2. Map of Brownsville marsh showing the location of the experimental plots and the reference J. roemerianus populations.


Fig. 3. Design of experimental plots modified from Taylor (1995).

Overall, the mean elevation of the entire experimental site was 1.00 m above mean sea level (Taylor 1995).

Increased inundation was accomplished by pumping water from Phillips Creek through 1.27 cm (3/4 in) PVC pipes up to the experimental plots. Two different types of pumps were used during the experiment. The first pump was a Cimaron 4 in (10.16 cm) SolarSub pump. This pump was used from April 7, 1994, to the beginning of July 1994 when it stopped functioning. The second type of pump was a SolarJack 4 in the SDS series. The SolarJack pump operated from July 23 to September 25, 1994, when it was removed for the winter. The SolarJack pump was reinstalled on March 10, 1995, for the second growing season. A float switch (Thomas Product LTD. model 4200 P/N 24251) was used to activate the pump during both day and night high tides. During 1994 and from March 10, 1995, to June 8, 1995, the pumps were powered by four 12 V DC batteries (Reliant GPR-1285). The batteries were recharged by solar panels (Siemens M55 Solar Electric Module). During 1995, the batteries were no longer fully recharging, and I chose to run the pump directly off the solar panels. Therefore, from June 8, 1995, until the end of the 1995 growing season, the pump moved creek water through the pipes only during daytime high tides. The three plots receiving water from Phillips Creek (i.e., flooded plots) were enclosed by a wood border in order to slow surface runoff. The wood border consisted of strips of plywood 0.90 cm (3/8 in) thick and 20 cm high plywood. Three coats of Thompson's Water Seal were applied to the plywood to prevent decomposition. The strips were buried 10 cm into the ground leaving a 10 cm high border around the plots. Space was left between the strips to allow for the slow drainage of water. To determine if the wood borders and PVC pipes laid across the flooded plots had any effect in the flooded plots, half of the nonflooded plots had wood borders and PVC pipes laid across (i.e., border control plots). The other half of the nonflooded plots did not have a wood border surrounding them or PVC pipes (i.e., control plots). The control plots were delineated by placing PVC pipes at the corners of the plots (Taylor 1995). Therefore, each block contained one flooded plot, one border control plot, and one control plot. Pumping occurred from April 7, 1994, to the first week of July 1994; from July 23, 1994, to September 25, 1994; and from March 10, 1995, to August 20, 1995. The gaps in the pumping were the result of mechanical failures and waiting for the arrival of new parts. Appendix A describes the pumping design in more detail. Appendix C lists the amount of water pumped onto the plots throughout the experiment.

During the week of April 24, 1994, S. alterniflora wrack was placed on the plots to simulate wrack deposition. The wrack covered the left side of each plot facing from a boardwalk (Fig. 3). The S. alterniflora wrack was collected from a deposit near the experimental site from a storm in March 1994. The wrack covered half the J. roemerianus community and half of the S. patens/D. spicata community and was secured with 1.905 cm plastic mesh bird netting and wire to prevent removal. Therefore, each plot had a 4 m x 1.5 m area of stimulated wrack deposition and a 4 m x 1.5 m area of no wrack deposition (Fig. 3). On October 15, 1994, approximately 1 m x 1.5 m of wrack was removed from either end of the 4 m x 1.5 m wrack deposition area within each plot. The remaining wrack within the plots was left and resecured with bird netting and wire.

4.3. Tracking of the Growth and Senescence of Juncus roemerianus leaves

To determine the effects of increased inundation on the growth of J. roemerianus and its regrowth after wrack deposition, I recorded the progress of tagged J. roemerianus leaves throughout the experiment (Christian et al. 1990, Williams and Murdoch 1972). I used a meter stick to measure the height of green portion and the total height of each leaf to the nearest 0.1 cm. Measurements were taken approximately every four weeks from October through April and every two weeks from May through September. Table 1 describes the timing, number, and designation of each cohort. I tagged leaves twice a year since J. roemerianus produces new leaves throughout the spring and summer months. Therefore, tagging twice a year would more accurately reflect the growth pattern of the plants. Appendix B has the details on the exact dates measurements were taken and the means and standard deviations for each cohort and treatment. I measured the leaves on 31 different days over the course of 20 months.

4.3.1. Reference Population of Juncus roemerianus

I also tagged two reference populations of J. roemerianus leaves in areas that were regularly inundated, and, therefore, flooded more often than the control plots (Fig. 2).

Table 1. Dates of when I tagged each cohort of Juncus roemerianus leaves, the cohort's designation, and the number of leaves tagged.




Cohort

Number



Date

Tagged


Initial Height

of Leaves


Area where Leaves were Tagged
Number of Leaves Tagged

per Plot
Number of Leaves Tagged per Flooding Treatment
1
March 26, 1994
< 30 cm
Nonwrack
5
15
2
March 26, 1994
> 30 cm
Nonwrack
5
15
3
July 11, 1994
< 30 cm
Nonwrack
5
15
4
March 4, 1995
< 30 cm
Nonwrack
5
15
5
March 4, 1995
< 30 cm
Post-wrack
5
15
6
July 6, 1995
< 30 cm
Nonwrack
5
15
7
July 6, 1995
< 30 cm
Post-wrack
5
15
TOTALS
35
105
4
March 4, 1995
< 30 cm
Reference Areas
20
20
6
July 6, 1995
< 30 cm
Reference Areas
20
20

The reference populations were designated as reference population A and reference population B. Ten leaves were tagged in each reference population on March 4, 1995, and ten were tagged in each reference population on July 6, 1995 (Table 1). I took measurements of green and total heights at the same time as the leaves in the experimental plots. Appendix B contains the exact dates and means and standard deviations for the leaves from the reference populations.

4.4. Aboveground Biomass Sampling of the Plots

I collected aboveground biomass samples in the plots at the end of the first and second growing seasons. A total of eight 0.0625 m2 aboveground biomass samples were collected in every plot at the end of each growing season. On October 15, 1994, two 0.0625 m2 samples were collected without bias in the following areas: (1) Juncus roemerianus-wrack, (2) J. roemerianus-nonwrack, (3) S. patens/D. spicata-wrack, and (4) S. patens/D. spicata-nonwrack. On September 30, 1995, two 0.0625 m2 samples were collected without bias in the following areas: (1) J. roemerianus-regrowth from wrack deposition, (2) J. roemerianus-nonwrack, (3) S. patens/D. spicata-regrowth from wrack deposition, and (4) S. patens/D. spicata-nonwrack. I did not collect samples from the remaining wrack areas in 1995 because of the lack of plant material in those areas. Also in 1995, four biomass samples were collected in the J. roemerianus reference population. I sorted samples by plant species and into living, dying, and dead plant material. For each sample taken in the J. roemerianus-nonwrack areas, the total and green heights of 20 living (>95% green) and 20 senescing (<95% green) J. roemerianus leaves were measured. The total numbers of living and senescing J. roemerianus leaves also were recorded to determine leaf densities. Once sorted, the plant material was placed in brown paper bags and dried at 85 oC for at least 72 h to ensure complete dryness before weighing. Each type of plant material was weighed inside its bag, and then the bag was weighed. I subtracted the mass of the bag from the total mass (i.e., plant material + bag) to yield the mass of the dried plant material. I converted dried plant masses to g/m2 and leaf densities to number of leaves/m2 by dividing the numbers by 0.0625 m2.

4.5. Vegetation Analysis of Ground Cover in the Plots

Ground cover analysis was done twice (July 11, 1994, and July 24, 1995) and involved placing a 1 m2 quadrat, divided into 100 cm2 grids, over each plot. I would place the quadrat down on the plots, record the species present in each grid, and then move the quadrat down 1 m. I repeated this on both the wrack and nonwrack sides of the plots. This analysis of vegetation included the wrack and nonwrack sides in (1) the area dominated by J. roemerianus, (2) the transition area between the two vegetation types, and (3) the areas dominated by S. patens and D. spicata. I recorded the presence and the absence of each plant species in each grid. The total number of individuals and the relative importance of each species were not recorded.

4.6. Annual Net Primary Production (ANPP) of Juncus roemerianus

I calculated annual net primary production (ANPP, g/(m2 x y)) of J. roemerianus as the product of the annual frequency of replacement of growing leaves (FREQ, number/y), production-to-biomass ratio (P/B, dimensionless), and aboveground biomass (AVE BIO, g/m2). FREQ and P/B were determined from the tagged leaf data, and AVE BIO was determined from the aboveground biomass collections (Christian et al. 1990). I estimated ANPP for both the leaves tagged in the experimental plots and for the leaves tagged in the reference populations.

In order to determine when the leaves began to grow, I extrapolated backwards to T0 assuming a linear relationship between height and time:

T0 = T1 - [H1 x (T2 - T1) / (H2 - H1)]

where T1 = date of tagging; T2 = next sampling date; H1 = height at the day of tagging; and H2 = height at the next sampling. I only used total height measurements to determine T0.

The difference between T0 and the day at which the total height was maximum (Tm) was designated as the replacement time for a leaf and was divided by 365 days/y in order to determine FREQ (Christian et al. 1990).

I considered the total height at Tm as the maximum height (Hm) for each leaf. P/B was calculated by dividing Hm by the average total height (Havg) during the study. Havg was calculated as:

Havg = Sum { [Hi-1 + (Hi - Hi-1) / 2] x (Ti - Ti-1) / (Tm - T0) }

for i = 0 to m

where Hi (cm) = total height at data Ti; and m = sampling date for Hm. I calculated Havg for each leaf from the different cohorts (Christian et al. 1990).

I used the biomass collections from 1994 and 1995 to estimate AVE BIO of growing leaves (g/m2). Since the J. roemerianus leaves reached their maximum green height before they reached their maximum total height, I combined the growing leaf biomass and a percentage of the senescing leaf biomass for AVE BIO. I determined that leaves tended to be approximately 76 % green when they reach their maximum total height using the tagged leaf data. From the measurements of the random senescing leaves from the biomass collections, I was able to estimate that about 55 % of the senescing biomass may have actually been growing leaves. Therefore, I multiplied 55 % by the senescing leaf biomass for each sample and added the product to the biomass of the growing leaf biomass. The sum of these two numbers was used as AVE BIO for the ANPP calculations.

The means of FREQ and P/B for each cohort were used to estimate ANPP. For the cohorts tagged in 1994 (cohorts 1-3), the 1994 AVE BIO was used for the ANPP calculations; and the 1995 AVE BIO was used for the cohorts tagged in 1995 (cohorts 4-7). I used the following equation to calculate ANPP (g/(m2 x y)):

ANPP = FREQ (number/y) x P/B (dimensionless) x AVE BIO (g/m2).

4.7. Shading Experiment

To examine the possible effects of shading by older J. roemerianus leaves on younger J. roemerianus leaves, I performed a shading experiment in two patches of J. roemerianus near the experimental plots. In May 1995, I clipped five 0.0625 m2 areas of J. roemerianus from the edges of each patch. Shading was accomplished by using wooden frames with two layers of window screen on them. This corresponded to approximately a 75 % reduction in light intensity reaching the leaves. Furthermore, two additional wooden frames were made without screen in order to control for the effect of the wooden frames. The placement of the treatments was as follows: shaded area, non-shaded area (i.e., control), wooden frame control, non-shaded area, shaded area. This incomplete block design was used for both patches. An incomplete block design was used because this was only a preliminary study.

I harvested aboveground biomass twice from the shading experiment, first on July 24, 1995, and then on October 14, 1995. Because of the small amount of plant material collected, I sorted the samples into only J. roemerianus material and non-J. roemerianus material. Plant material was placed in a brown paper bag and dried at 85 oC for 72 h to ensure complete dryness before weighing. Each type of plant material was weighed inside its bag, and then the bag was weighed. I subtracted the mass of the bag from the total mass (i.e., plant material + bag) to yield the mass of the dried plant material. Dry plant masses were converted to g/m2 by dividing each mass by 0.0625 m2

4.8. Statistical Analysis of Data

I used the general linear model (GLM) procedure of SAS to analyze most of the data (SAS Institute Inc. 1988). The model for the three-way ANOVA was as follows: BLOCK, FLOODING TREATMENT, WRACK TREATMENT, BLOCK * FLOODING TREATMENT, and FLOODING TREATMENT * WRACK TREATMENT. Significance was accepted at the 0.05 level. Specific relationships among means were determined using the least square means test. The GLM with a three-way ANOVA was used to analyze the following measurements: (1) maximum green heights, maximum total heights, and leaf densities of J. roemerianus; (2) the biomass of each type of plant material, total biomass of each species, and total plant biomass for 1994 and 1995; and (3) FREQ, AVE HT, P/B, and ANPP.

For the comparison of the maximum green and maximum total heights and ANPP of reference populations of J. roemerianus and of the control plots, a two-way ANOVA model was used with GLM and least square means (SAS Institute Inc. 1988). The model for the ANOVA was TREATMENT, COHORT, TREATMENT*COHORT. I compared the biomass samples collected from the reference populations and the control plots using a one-way ANOVA model that examined the effect of TREATMENT only.

I also used a two-way ANOVA with GLM and least square means for the shading experiment (SAS Institute Inc. 1988). The model for the two-way ANOVA was BLOCK, SHADING TREATMENT, and BLOCK*SHADING TREATMENT.

Statistical analysis of growth and senescence data of J. roemerianus leaves involved the use of life table analysis. I used the SAS procedures LIFEREG and LIFETEST (SAS Institute Inc. 1988). The LIFEREG procedure uses parametric models to compare failure-time data. The LIFEREG procedure can handle more complex models than the LIFETEST procedure, which is a nonparametric test. I compared the life table data using the Weibull model command. Since LIFEREG did not reveal any higher order interactions in my data set, I used a Chi-square with one degree of freedom to compare differences of the log-rank values for each variable from LIFETEST. Log-rank values are calculated from the distribution of the data. Furthermore, I ran the stratum (i.e., variable) FLOODING TREATMENT separate from the stratum COHORT; and analysis for the cohorts tagged in 1994 (cohorts 1-3) were done separately from the cohorts tagged in 1995 (cohorts 4-7). The separation of FLOODING TREATMENT and COHORT and the 1994 and 1995 cohorts were done to simplify the model. I compared the amount of time required for a leaf (1) to reach maximum green height, (2) to reach maximum total height, (3) to die from the point of maximum green height, and (4) to die from the point of maximum total height. SAS used censored data up to the point of the censorship. All analyses were performed at a 0.05 level of significance.

I determined the frequency of change in ground cover from 1994 to 1995 for the wrack and nonwrack sides of each plot as a percentage of change using the SAS procedures SORT, PLOT, and FREQ. I compared the percentage of change among the plots using the GLM procedure of SAS (SAS Institute Inc. 1988). The model for the three-way ANOVA for the vegetative analysis was BLOCK, FLOODING TREATMENT, WRACK TREATMENT, BLOCK*FLOODING TREATMENT, and FLOODING TREATMENT*WRACK TREATMENT. Significance was accepted at the 0.05 level. Specific differences among means were determined by use of the least square means test.

5. RESULTS

The results reported here include the analyses of the flooding and wrack treatments and block effect. I discuss interactions between flooding treatment and block and between flooding and wrack treatments only when the components of the interactions were significant by themselves. Table 2 lists the abbreviations I used on the tables and figures and an example of how to read the GLM tables in this Results section.

5.1. Growth and Senescence of Juncus roemerianus

5.1.1. Maximum Green and Total Heights of Juncus roemerianus

Table 3 contains the means and standard deviations for the maximum green and total heights of the J. roemerianus leaves from the experimental plots and the reference populations. Mean maximum green heights ranged from 36.8 to 69.4 cm, and mean maximum total heights ranged from 41.5 to 76.7 cm (Table 3).

For the maximum green and total heights from the experimental plots, the flooding treatment was not significant (Table 4). The cohorts were significantly different from each other. However, most of the differences among the cohorts were the result of when I tagged and not because I tagged the cohort tagged in a nonwrack or post-wrack area. Since the purpose of this thesis was to study flooding and wrack treatments, I will

Table 2. List of abbreviations used in tables and figures and an example of how to read the GLM tables.

Abbreviation
Refers To
F
Flooded plots
B or BC
Border control plots
C
Control plots
N
Nonwrack areas
W
Wrack areas
R
Areas recovering from wrack (post-wrack)
X
Block X
Y
Block Y
Z
Block Z
1
Cohort 1
2
Cohort 2
3
Cohort 3
4
Cohort 4
5
Cohort 5
6
Cohort 6
7
Cohort 7

Table 2, continued

Key:


Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding * Wrack
name of data being tested
p-value for block effect (Significant differences among the blocks)
p-value for flooding treatment (Significant differences among the flooding treatments)
p-value for wrack treatment (Significant differences between the wrack treatments)
p-value for block and flooding treatment interaction
p-value for flooding treatment and wrack treatment interaction


Example:
Biomass
0.08
0.01

(F > C)
0.01

(N > W)
0.90
0.54
no significant differences
Flooded plots have significantly more biomass than the control plots
Nonwrack areas have significantly more biomass than the wrack areas
no significant interaction between block and flooding treatment
no significant interaction between flooding treatment and wrack treatment

Table 3. Means and standard deviations (in parenthesis) of the maximum green and total heights (cm) for each J. roemerianus cohort among the different flooding treatments and for the reference J. roemerianus population. The year and the wrack treatment for each cohort are listed in parenthesis. (94 = leaves tagged in 1994 and 95 = leaves tagged in 1995; N = leaves tagged in the nonwrack areas and R = leaves tagged in the areas recovering from wrack deposition)

Flooding

Treatment
Cohort

Number
Maximum Green

Heights
Maximum Total

Heights
Flooded
1 (94, N)
68.9 (26.4)
73.3 (25.9)
2 (94, N)
69.4 (19.1)
76.7 (18.7)
3 (94, N)
56.9 (18.8)
61.8 (21.6)
4 (95, N)
57.7 (19.4)
66.2 (14.2)
5 (95, R)
52.7 (20.0)
65.3 (16.1)
6 (95, N)
46.5 (16.5)
48.4 (16.6)
7 (95, R)
47.3 (10.8)
50.4 (10.4)
Total
57.0 (20.6)
63.1 (20.3)
Border Control
1 (94, N)
55.8 (16.8)
61.9 (16.0)
2 (94, N)
66.3 (12.4)
74.1 (10.9)
3 (94, N)
52.7 (8.4)
60.8 (10.1)
4 (95, N)
51.6 (15.3)
57.3 (13.8)
5 (95, R)
57.1 (24.1)
66.9 (22.9)
6 (95, N)
39.5 (10.3)
41.5 (11.2)
7 (95, R)
49.5 (11.6)
53.1 (10.4)
Total
56.5 (18.9)
59.4 (16.9)

Table 3, continued.

Flooding

Treatment
Cohort

Number
Maximum Green

Heights
Maximum Total

Heights
Control
1 (94, N)
62.2 (23.9)
68.1 (23.8)
2 (94, N)
67.8 (8.9)
73.5 (8.7)
3 (94, N)
52.2 (18.9)
57.8 (22.8)
4 (95, N)
64.1 (21.8)
70.0 (22.2)
5 (95, R)
48.8 (21.5)
64.0 (22.2)
6 (95, N)
52.2 (11.7)
56.0 (10.3)
7 (95, R)
48.0 (12.2)
53.9 (14.0)
Total
55.5 (17.9)
63.3 (19.5)
Reference A
4 (95, N)
64.8 (19.9)
69.8 (19.4)
6 (95, N)
48.6 (19.9)
50.3 (10.2)
Total
56.7 (17.4)
60.0 (18.1)
Reference B
4 (95, N)
36.8 (15.7)
46.0 (15.5)
6 (95, N)
46.3 (13.4)
49.6 (13.8)
Total
41.6 (15.0)
47.8 (14.4)

Table 4. Results of GLM for maximum green and total J. roemerianus leaf heights. Specific significant differences were determined by least square means and are listed below the GLM values in parentheses.



Block
Flooding

Treatment


Cohort
Block *

Flooding
Flooding

* Cohort
Maximum Green Heights
< 0.01

(Z > Y & X;

Y > X)
0.21
< 0.01

(1 > 3, 5, 6, & 7;

2 > 3, 4, 5, 6, & 7;

3 > 6;

4 > 6 & 7)
0.35
0.36
Maximum Total Heights
< 0.01

(Z > Y & X;

Y > X)
0.15
< 0.01

(1 > 3, 6, & 7;

2 > 1, 3, 4, 5, 6, & 7;

3, 4, & 5 > 6 & 7)
0.34
0.50

only be discussing the significant differences between the nonwrack and post-wrack cohorts that were tagged at the same time (i.e., cohort 4 vs. 5 and cohort 6 vs. 7). The cohorts tagged in the spring of 1995 in the nonwrack (cohort 4) and post-wrack (cohort 5) areas did not have statistically different maximum green and total heights (Table 4). The cohorts tagged in the summer of 1995 in the nonwrack (cohort 6) and post-wrack (cohort 7) areas did not have statistically different maximum green and total heights (Table 4).

Block effect was significant for the maximum heights. Block Z had significantly higher heights than block X and Y. Furthermore, block Y had significantly higher heights than block X (Table 4).

5.1.1.1. Control vs. Reference Population Comparison for Maximum Heights

The treatment effect was significant for the comparison of the maximum green and total heights of the control plots and the reference population. For the maximum green heights, the leaves in reference A and all the control plots were significantly taller than the leaves in reference B. The maximum total heights for reference A and the control plots in block X and Y were significantly higher than reference B (Table 5). The cohort effect was significant for maximum total heights with cohort 4 having significantly taller leaves than cohort 6.

Table 5. Results of GLM for maximum green and total heights of J. roemerianus from the reference populations and from the control plots. Specific significant differences were determined by least square means and are listed under the GLM values in parenthesis.



Treatment


Cohort
Treatment

* Cohort
Maximum Green Heights
0.01

(Reference A, X, Y & Z > Reference B)
0.05

(4 > 6)
0.14
Maximum Total Heights
0.01

(Reference A, X & Y > Reference B)
< 0.01

(4 > 6)
0.17

5.1.2. Life Table Analysis (Survival Data Analysis) of Juncus roemerianus Leaves

Tables 6 through 9 contain the means and standard deviations of the time (days) required for the cohorts to reach their maximum green and total heights from T0 and for the time (days) required for the cohorts to go from the maximum green and total heights to death, respectively. The tables also list the number of censored observations for the time to maximum green and total heights and for the time to death from the maximum heights. Censored observations include leaves that were lost during the study and leaves which were either still growing or senescing when the studied ended in October 1995. In this section, I am using the term "survivorship" in the statistical sense of the word. Therefore, survivorship is the probability of not reaching either a maximum height (green or total) or death from either maximum green or total heights. Tables 8 and 9 contain this information for both the experimental plots and the reference populations.

When studying the data, it is important to keep two facts about the data in mind. First, cohort 2 was tagged in the spring of 1994 and consisted of older leaves. Therefore, the leaves in cohort 2 may have not grown much beyond their tagged heights. Furthermore, since the study ended in the fall of 1995, many of the leaves tagged during 1995, did not completely senesce or even begin to senesce. Because of this, there were not enough data to accurately determine the effects of inundation or wrack deposition on the senescence of the 1995 cohorts. Therefore, the senescing data of the 1995 cohorts are not presented in this thesis.

Table 6. Means and standard deviations (in parenthesis) of the time (days) for the 1994 cohorts to reach the maximum green heights from T0 and the time for the 1994 cohorts to completely senesce from their maximum green heights. The number of censored points for each mean also is listed. The cohorts are listed by flooding treatment. In 1994 leaves were only tagged in nonwrack areas.

Flooding

Treatment


Cohort
Time to Max.

Green Height
Max. Height

Censored
Time to

Death
Death

Censored
Flooded
1
>175 (53)
1
>210 (144)
2
2
347 (131)
0
>188 (87)
1
3
>228 (138)
2
>170 (123)
8
Total
>252 (134)
3
>190 (119)
11
Border Control
1
158 (38)
0
>180 (138)
2
2
509 (477)
0
>176 (87)
2
3
210 (100)
0
>201 (59)
2
Total
292 (317)
0
>185 (99)
6
Control
1
145 (42)
0
187 (116)
0
2
390 (257)
0
204 (101)
0
3
>182 (111)
1
>169 (139)
5
Total
>240 (195)
1
>187 (118)
5

Table 7. Means and standard deviations (in parenthesis) of the time (days) for the 1994 cohorts to reach their maximum total heights from T0 and the time for the 1994 cohorts to completely senesce from their maximum total heights. The number of censored points for each mean also is listed. The cohorts are listed by flooding treatment. The leaves tagged in 1994 were all in the nonwrack areas of the plots.

Flooding

Treatment


Cohort
Time to Max.

Total Height
Max. Height

Censored
Time to

Death
Death

Censored
Flooded
1
236 (119)
0
>178 (131)
2
2
402 (197)
0
>158 (106)
1
3
>304 (137)
2
>95 (85)
2
Total
>316 (166)
2
>143 (112)
5
Border Control
1
202 (70)
0
>136 (125)
1
2
554 (482)
0
130 (91)
0
3
356 (75)
0
>55 (43)
2
Total
371 (314)
0
>107 (98)
3
Control
1
183 (60)
0
149 (116)
0
2
420 (263)
0
174 (104)
0
3
>246 (140)
3
>66 (64)
5
Total
>284 (200)
3
>130 (106)
5

Table 8. Means and standard deviations (in parenthesis) of the time (days) for the 1995 cohorts to reach the maximum green height from T0. The number of censored points for each mean also is listed. The cohorts are listed by flooding treatment, and the wrack treatment for each cohort is listed in parenthesis. (N = nonwrack areas and R = areas recovering from wrack deposition; N/A = not enough data available to report)

Flooding

Treatment


Cohort
Time to Max.

Green Height
Max. Height Censored
Time to

Death
Death

Censored
Flooded
4 (N)
>312 (47)
3
N/A
10
5 (R)
236 (286)
0
N/A
7
6 (N)
>322 (412)
12
N/A
12
7 (R)
>378 (912)
9
N/A
13
Total
>312 (510)
24
N/A
42
Border Control
4 (N)
237 (103)
0
N/A
12
5 (R)
154 (113)
0
N/A
7
6 (N)
>160 (52)
10
N/A
13
7 (R)
>115 (32)
8
N/A
14
Total
>165 (91)
18
N/A
46
Control
4 (N)
>296 (106)
1
N/A
11
5 (R)
156 (69)
0
N/A
5
6 (N)
>162 (34)
11
N/A
15
7 (R)
>136 (53)
10
N/A
13

Table 8, continued.

Flooding

Treatment


Cohort
Time to Max.

Green Height
Max. Height

Censored
Time to

Death
Death

Censored
Control
Total
>188 (94)
22
N/A
44
Reference A
4 (N)
262 (74)
0
N/A
6
6 (N)
>152 (33)
10
N/A
10
Total
>207 (80)
10
N/A
16
Reference B
4 (N)
285 (79)
0
N/A
2
6 (N)
>209 (127)
10
N/A
10
Total
>249 (108)
10
N/A
12

Table 9. Means and standard deviations (in parenthesis) of the time (days) for the 1995 cohorts to reach their maximum total height from T0. The number of censored points for each mean also is listed. The cohorts are listed by flooding treatment, and the wrack treatment for each cohort is listed in parenthesis. (N = nonwrack areas and R = areas recovering from wrack deposition; N/A = not enough data available to report)

Flooding

Treatment


Cohort
Time to Max.

Total Height
Max. Height

Censored
Time to

Death
Death

Censored
Flooded
4 (N)
>341 (39)
4
N/A
7
5 (R)
>261 (286)
4
N/A
7
6 (N)
>333 (440)
12
N/A
15
7 (R)
>388 (914)
13
N/A
13
Total
>331 (516)
33
N/A
42
Border Control
4 (N)
>265 (104)
1
N/A
11
5 (R)
192 (111)
0
N/A
8
6 (N)
>176 (60)
13
N/A
13
7 (R)
>128 (20)
14
N/A
14
Total
>189 (93)
28
N/A
46
Control
4 (N)
>327 (114)
6
N/A
11
5 (R)
>189 (73)
4
N/A
5
6 (N)
>166 (33)
15
N/A
15
7 (R)
>143 (49)
13
N/A
13
Total
>206 (102)
38
N/A
44
Reference A
4 (N)
>276 (73)
4
N/A
7

Table 9, continued.

Flooding

Treatment


Cohort
Time to Max.

Total Height
Max. Height

Censored
Time to

Death
Death

Censored
Reference A
6 (N)
>152 (33)
10
N/A
10
Total
>213 (60)
14
N/A
17
Reference B
4 (N)
>337 (87)
0
N/A
2
6 (N)
>180 (22)
9
N/A
10
Total
>263 (103)
9
N/A
12

The results of the LIFEREG procedure for the 1994 cohorts are listed in Table 10. Flooding treatment was not significant for the time it took leaves to reach their maximum green and total heights. However, the 1994 cohorts in the flooded plots took significantly less time to senesce from their maximum total heights as compared to the leaves in the border control plots (Table 7, Table 10). Time to senesce was not significantly different between the 1994 cohorts in the flooded plots and in the control plots (Table 10). The block effect was significant for the time to maximum heights and for time to death from maximum green heights (Table 10). There were no higher order interactions for the 1994 cohorts.

Flooding and wrack treatments were both significant among the leaves tagged in 1995 (Table 11). Significant differences among flooding treatments were more common in 1995 cohorts than in 1994 cohorts. The leaves in the flooded plots took significantly longer to reach their maximum green heights than the leaves in the border control and control plots (Table 8, Table 11). Furthermore, the leaves in the flooded plots took significantly longer to reach their maximum total heights than the leaves in the border control plots (Table 9, Table 11). The only significant block effect was for the time to maximum total heights for block X versus block Z (Table 11). There were no higher order interactions for the 1995 cohorts.

Table 10. Values for p from the LIFEREG procedure for the 1994 cohorts using the log-likelihood for Weibull without interaction terms. The leaves in the flooded plots were compared to the leaves in the border control and control plots, and block X and Y were compared to block Z.

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Height
Time to

Death
Time to

Max. Height
Time to

Death
Flooded plots vs. Border Control plots
0.26
1.00
0.40
0.01

(BC > F)
Flooded plots vs. Control plots
0.49
1.00
0.14
0.45
Block X vs. Block Z
< 0.01
0.01
< 0.01
0.08
Block Y vs. Block Z
0.98
0.07
0.82
0.72

Table 11. Values for p from the LIFEREG procedure for the 1995 cohorts using the log-likelihood for Weibull without interaction terms. The leaves in the flooded plots were compared to the leaves in the border control and control plots. Cohorts 4, 5, and 6 were compared to cohort 7. Blocks X and Y were compared to block Z.

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Height
Time to

Death
Time to

Max. Height
Time to

Death
Flooded plots vs. Border Control plots
< 0.01

(F > BC)
N/A
0.01

(F > BC)
N/A
Flooded plots vs. Control plots
< 0.01

(F > C)
N/A
0.42
N/A
Cohort 4 vs. Cohort 7
0.04

(4 > 7)
N/A
< 0.01

(4 > 7)
N/A
Cohort 5 vs. Cohort 7
< 0.01

(7 > 5)
N/A
< 0.01

(7 > 5)
N/A
Cohort 6 vs. Cohort 7
0.66
N/A
0.21
N/A
Block X vs. Block Z
0.29
0.38
0.02
0.85
Block Y vs. Block Z
0.39
0.53
0.15
0.56

The survivorship results of the LIFETEST procedure are graphed in Figures 4 to 11. Figures 4 to 11 are the graphs produced by SAS and contain estimated points of failure calculated by the graphical program in SAS. These estimated points of failure are overestimates of time to maximum height and to death. I left the points in the graphs for completeness. The calculated values of the Chi-square tests for the 1994 and 1995 cohorts are listed in Tables 12 and 13, respectively. For the 1994 cohorts, Chi-square tests were done with the flooding treatments only. I compared the flooded plots with border control plots and with control plots. The flooded plots were not significantly different from the border control plots or from the control plots for 1994 (Fig. 4, Fig. 5, Fig. 8, Fig. 9, and Table 12).

For the 1995 cohorts, I compared the flooded plots to the border control plots and control plots. In order to study wrack treatment, I compared the cohorts tagged in the nonwrack areas to the cohorts tagged at the same time in the post-wrack areas (i.e., cohort 4 vs. cohort 5 and cohort 6 vs. cohort 7). The flooding and wrack treatments both produced significant differences for the 1995 cohorts (Table 13). The leaves in the flooded plots took significantly longer to reach their maximum green heights (>312 days) than the leaves in the border control (>165 days) and control plots (>188 days) (Fig. 6). Furthermore, the leaves in the flooded plots took significantly longer to reach their maximum total heights (>331 days) than the leaves in the border control plots (>189 days) and control plots (>206 days) (Fig. 10).


Fig. 4. Survivorship curves for the time (days) it took the 1994 tagged J. roemerianus leaves to reach their maximum green heights from T0 based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots).

Fig. 5. Survivorship curves for the time (days) it took the 1994 tagged J. roemerianus leaves to die from their maximum green heights based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots).


Fig. 6. Survivorship curves for the time (days) it took the 1995 tagged J. roemerianus leaves to reach their maximum green heights from T0 based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots).



Fig. 7. Survivorship curves for the time (days) it took for the 1995 tagged J. roemerianus leaves to reach their maximum green heights from T0 based on cohort number.



Fig. 8. Survivorship curves for the time (days) it took the 1994 tagged J. roemerianus leaves to reach their maximum total height from T0 based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots)



Fig. 9. Survivorship curves for the time (days) it took the 1994 tagged J. roemerianus leaves to die from their maximum total height based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots)



Fig. 10. Survivorship curves for the time (days) it took the 1995 tagged J. roemerianus leaves to reach their maximum total height from T0 based on flooding treatment. (F = flooded plots, BC = border control plots, and C = control plots)



Fig. 11. Survivorship curves for the time (days) it took the 1995 tagged J. roemerianus leaves to reach their maximum heights from T0 based on cohort number.

Table 12. Calculated values from Chi-square tests with 1 degree of freedom for the 1994 cohorts' log-rank values from the LIFETEST procedure. The critical value for a Chi-square with 1 degree of freedom is 3.84 at the alpha level of 0.05.

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Height
Time to

Death
Time to

Max. Height
Time to

Death
Flooded plots vs. Control plots
0.73
0.72
0.72
0.93
Flooded plots vs. Border Control plots
0.03
1.91
0.28
3.34

Table 13. Calculated values from Chi-square tests with 1 degree of freedom for the 1995 cohorts' log-rank values from the LIFETEST procedure. The critical value for a Chi-square with 1 degree of freedom is 3.84 at the 0.05 alpha level.

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Height
Time to

Death
Time to

Max. Height
Time to

Death
Flooded plots vs. Control plots
3.85

(F > C)
N/A
1.75
N/A
Flooded plots vs. Border Control plots
11.29

(F > BC)
N/A
11.67

(F > BC)
N/A
Cohort 4 vs. Cohort 5
24.87

(4 > 5)
N/A
13.18

(4 > 5)
N/A
Cohort 6 vs. Cohort 7
6.59

(6 > 7)
N/A
1.54
N/A

Wrack treatment also produced significant differences among the 1995 cohorts. The cohorts tagged in nonwrack areas (cohort 4 and 6) took significantly longer than the cohorts tagged in the post wrack areas (cohort 5 and 7) to reach their maximum green heights (Fig. 7 and Table 13). The cohort tagged during the spring of 1995 in the nonwrack areas (cohort 4) also took significantly longer to reach its maximum total height than the cohort tagged at the same time in the post-wrack areas (cohort 5) (Fig. 11 and Table 13).

5.1.2.1. Control vs. Reference Population Comparison for Life Table Analysis

Since most of the reference leaves were still growing when the study ended, there was not enough data to accurately interpret possible senescing differences among the control plots and the reference populations. Therefore, I did not report the senescing data in this thesis. The times to maximum green and total heights were significantly different among the control plots and the reference populations. Using LIFEREG, the time it took the control plot of block Z to reach its maximum green and total heights was significantly less than the time it took reference population B to reach its maximum green and total heights (Table 14).

Table 14. Values of p from the LIFEREG procedure using the log-likelihood for Weibull without interactions for the comparison of the control plots with the reference populations. The control plots and reference A were compared to reference B. (N/A = not enough data available)

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Height
Time to

Death
Time to

Max. Height
Time to

Death
Block X's Control plot vs. Reference B
0.91
N/A
0.75
N/A
Block Y's Control plot vs. Reference B
0.20
N/A
0.06
N/A
Block Z's Control plot vs. Reference B
0.02

(Ref. B > Z)
N/A
0.01

(Ref. B > Z)
N/A
Reference A vs. Reference B
0.41
N/A
0.76
N/A

When compared using LIFETEST, both reference populations took significantly longer to reach their maximum total heights than the control plot in block Z. The reference populations and the control plots were not significantly different from each other for the time it took to reach their maximum green heights (Table 15).

5.1.3. Juncus roemerianus leaf densities

Table 16 contains the means and standard deviations for the J. roemerianus leaf densities for the experimental plots. I did not determine the leaf densities for the standing dead leaves; therefore, total leaf density refers to only the growing plus senescing leaves. Flooding treatment did not significantly alter the 1994 or 1995 growing, senescing and total (growing + senescing) leaf densities. Wrack deposition significantly reduced the growing, senescing, and total (growing + senescing) leaf densities for both years. A block effect occurred with the growing and total leaf densities in 1995 with block Z having higher growing and total leaf densities than blocks X and Y (Table 17).

5.1.3.1. Control vs. Reference Population Comparison for Leaf Densities

Table 18 contains the means and standard deviations for the reference populations. Only the growing leaf densities were significantly different among the control plots and the reference populations. All of the control plots had significantly higher growing leaf densities than reference B. Furthermore, block Z had significantly higher growing leaf densities than reference A. Growing leaf densities of reference A were not significantly different from blocks X and Y or from reference B (Table 19).

Table 15. Calculated values from Chi-square tests with 1 degree of freedom on the log-rank values from the LIFETEST procedure comparing the control plots with the reference populations. The critical value for a Chi-square test with 1 degree of freedom is 3.84 at the 0.05 alpha level. (N/A = not enough data available)

Green Heights
Green Heights
Total Heights
Total Heights


Comparisons
Time to

Max. Heights
Time to

Death
Time to

Max. Heights
Time to

Death
Block X's Control Plot vs. Reference B
2.30
N/A
0.17
N/A
Block Y's Control Plot vs. Reference B
2.76
N/A
0.08
N/A
Block Z's Control

Plot vs. Reference B
0.07
N/A
7.13

(Ref. B > Z)
N/A
Reference A vs. Reference B
1.75
N/A
0.22
N/A
Block X's Control Plot vs. Reference A
< 0.01
N/A
0.01
N/A
Block Y's Control Plot vs. Reference A
0.04
N/A
0.87
N/A
Block Z's Control

Plot vs. Reference A
2.90
N/A
6.66

(Ref. A > Z)
N/A

Table 16. Means and standard deviations (in parenthesis) of J. roemerianus leaf densities (number of leaves/m2) from the wrack and nonwrack J. roemerianus dominated areas of the experimental plots for 1994 and 1995. (W-F = wrack areas of the flooded plots, N-F = nonwrack areas of the flooded plots, W-BC = wrack areas of the border control plots, N-BC = nonwrack areas of the border control plots, W-C = wrack areas of the control plots, N-C = nonwrack areas of the control plots, R-F = regrowth areas after wrack deposition in the flooded plots, R-BC = regrowth areas after wrack deposition in the border control plots, and R-C = regrowth areas after wrack deposition in the control plots)



Year
Plant Material


W-F


N-F


W-BC


N-BC


W-C


N-C
1994
Growing
10 (1)
445 (13)
144 (0)
491 (14)
48 (4)
517 (13)
Senescing
118 (7)
560 (17)
576 (0)
456 (13)
24 (2)
507 (11)
Total Growing and Senescing
128 (8)
1005 (30)
720 (0)
947 (21)
72 (6)
1024 (19)
R-F
N-F
R-BC
N-BC
R-C
N-C
1995
Growing
56 (6)
368 (7)
67 (5)
195 (10)
77 (5)
400 (19)
Senescing
40 (4)
576 (7)
77 (8)
403 (18)
80 (4)
408 (13)
Total Growing and Senescing
96 (9)
944 (9)
144 (13)
597 (26)
157 (9)
808 (24)

Table 17. GLM results for the 1994 and 1995 J. roemerianus leaf densities from the experimental plots. Specific significant differences were determined by least square means and are listed below the GLM values in parentheses.



Year


Plant Material


Block
Flooding

Treatment
Wrack

Treatment
Block *

Flooding
Flooding

* Wrack
1994
Growing
0.13
0.72
< 0.01

(N > W)
0.06
0.95
Senescing
0.53
0.54
< 0.01

(N > W)
0.39
0.22
Total Growing and Senescing
0.72
0.17
< 0.01

(N > W)
0.16
0.19
1995
Growing
< 0.01

(Z > X & Y)
0.13
< 0.01

(N > R)
0.68
0.14
Senescing
0.16
0.48
< 0.01

(N > R)
0.15
0.17
Total Growing and Senescing
0.01

(Z > X & Y)
0.27
< 0.01

(N > R)
0.28
0.13

Table 18. Means and standard deviations (in parenthesis) of the reference population J. roemerianus leaf densities (number of leaves / m2) and the densities of the 1995 nonwrack control plots.

Plant Material
Reference A
Reference B
Nonwrack Control
Growing Leaves
240 (158)
88 (57)
400 (19)
Senescing Leaves
640 (430)
392 (79)
408 (13)
Total Growing and Senescing
880 (588)
480 (23)
808 (24)

Table 19. Results of GLM for comparisons of J. roemerianus leaf densities in the control plots with the densities in the reference populations. Specific interactions were determined by least squares means and are listed below the GLM values.

Plant Material
Treatment
Growing Leaves
0.04

(Block X, Y, & Z > Reference B;

Block Z > Reference A)
Senescing Leaves
0.89
Total Growing and Senescing
0.58



5.2. Aboveground Biomass

The means and standard deviations for all the biomass samples collected in 1994 and 1995 are located in Tables 20 and 21, respectively. Tables 22 and 23 contain the biomass means arranged by flooding treatment and wrack treatment for 1994 and 1995, respectively. I included this second set of biomass summary tables to help the reader see the differences or lack of differences among the treatments.

5.2.1. Juncus roemerianus -- 1994 and 1995 Data

5.2.1.1. J. roemerianus in J. roemerianus Dominated Areas

Flooding treatment produced only one statistically significant result for the J. roemerianus in the J. roemerianus dominated areas (Table 24 and Table 25). The 1995 biomass of the senescing leaves (33.18 g/m2) from the control plots was significantly lower than senescing biomass in the flooded plots (196.92 g/m2) and the border control plots (165.25 g/m2). The 1995 biomass of the flooded plots and the border control plots were not significantly different from each other (Table 25).

Wrack deposition significantly reduced the biomass of all three classes of J. roemerianus leaves in 1994 and 1995 in those areas J. roemerianus dominated (Table 24 and Table 25, respectively). In 1994, the wrack deposition reduced the total J. roemerianus biomass to approximately 17 % of the biomass from the nonwrack areas (Table 22). The 1995 total J. roemerianus biomass in the post-wrack areas was equal to only 13 % of the total J. roemerianus biomass in the nonwrack areas (Table 23).

Table 20. Means and standard deviations (in parenthesis) of the 1994 biomass (g/m2) samples collected from the wrack and nonwrack areas of the plots. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., and SL = Salicornia sp.; W-F = wrack areas of the flooded plots, N-F = nonwrack areas of the flooded plots, W-BC = wrack areas of the border control plots, N-BC = nonwrack areas of the border control plots, W-C = wrack areas of the control plots, and N-C = nonwrack areas of the control plots)



Area
Plant

Material


W-F


N-F


W-BC


N-BC


W-C


N-C
JR
JR Growing
6.11 (14.96)
291.31 (174.99)
9.95 (24.36)
307.09 (199.94)
1.25 (2.21)
216.37 (94.41)
JR Senescing
80.11 (80.57)
654.64 (406.65)
71.52 (124.88)
941.63 (165.16)
48.45 (51.63)
499.97 (307.38)
JR Standing Dead
275.89 (195.62)
532.05 (347.63)
214.16 (270.05)
852.08 (456.14)
144.96 (83.24)
655.15 (257.99)
JR Total
362.11 (261.10)
1478.00 (483.06)
295.63 (412.87)
2100.80 (708.80)
194.67 (119.43)
1371.49 (575.21)
SP Living
0.51 (1.24)
4.99 (12.21)
0.64 (1.57)
0.88 (2.16)
10.21 (18.65)
129.20 (172.87)
SP Total
15.92 (37.53)
10.27 (25.15)
2.05 (5.03)
261.44 (366.25)
27.79 (39.95)
283.41 (299.67)
DS Living
0
1.31 (3.20)
1.68 (4.12)
0
12.21 (23.82)
9.17 (22.47)
DS Total
3.09 (7.58)
2.19 (5.36)
2.96 (4.65)
21.92 (45.41)
17.28 (24.86)
12.80 (24.20)
SA Total
0
44.75 (109.61)
0
48.88 (119.73)
0
17.55 (42.98)
SC Total
0
0
0
0
0
0
SL Total
0
0
0
0
0
0

Table 20, continued



Area
Plant

Material


W-F


N-F


W-BC


N-BC


W-C


N-C
JR
All Total
381.12 (261.80)
1535.20 (463.23)
300.64 (412.90)
2433.04 (610.33)
239.73 (139.45)
1685.25 (528.97)
SP/

DS
JR Growing
0
5.41 (13.26)
0
0.88 (2.16)
0
6.72 (16.46)
JR Senescing
0
3.04 (7.45)
17.28 (42.33)
2.61 (6.40)
0
4.64 (11.37)
JR Standing Dead
7.23 (17.70)
8.35 (18.77)
0
2.96 (7.25)
0
6.45 (15.81)
JR Total
7.23 (17.70)
16.8 (39.45)
17.28 (42.33)
6.45 (15.81)
0
17.81 (43.63)
SP Living
28.43 (30.19)
208.80 (109.70)
13.57 (22.53)
457.36 (101.51)
27.63 (45.68)
348.80 (163.10)
SP Total
226.99 (139.47)
620.45 (319.25)
128.69 (101.27)
1065.55 (160.13)
281.39 (110.10)
802.56 (298.92)
DS Living
58.72 (45.05)
98.61 (59.79)
40.05 (46.76)
130.72 (37.58)
57.73 (91.47)
102.56 (57.80)
DS Total
88.37 (74.22)
131.01 (71.78)
54.40 (65.76)
207.84 (66.95)
92.67 (103.56)
173.04 (117.32)
SA Total
0
0
0
0
0
0
SC Total
0
0
0
1.07 (2.61)
0
0
SL Total
0
0
0
0
0
0
All Total
322.59 (208.57)
770.35 (309.45)
200.37 (175.19)
1280.91 (206.49)
993.41 (257.01)
374.05 (130.15)

Table 21. Means and standard deviations of the 1995 biomass (g/m2) samples collected from the wrack and nonwrack areas of the plots. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., and SL = Salicornia sp.; R-F = regrowth after wrack areas of the flooded plots, N-F = nonwrack areas of the flooded plots, R-BC = regrowth after wrack areas of the border control plots, N-BC = nonwrack areas of the border control plots, R-C = regrowth after wrack areas of the control plots, and N-C = nonwrack areas of the control plots)



Area
Plant

Material


R-F


N-F


R-BC


N-BC


R-C


N-C
JR
JR Growing
14.00 (12.58)
299.73 (313.65)
24.16 (24.51)
69.87 (85.02)
17.36 (31.47)
197.20 (112.06)
JR Senescing
42.61 (37.98)
351.23 (198.52)
71.36 (84.80)
259.15 (231.14)
5.86 (9.39)
60.51 (43.06)
JR Standing Dead
93.39 (100.27)
1089.87 (660.82)
174.96 (202.18)
822.03 (734.04)
47.90 (107.37)
629.10 (668.90)
JR Total
150.00 (140.35)
1740.83 (1103.61)
270.48 (311.49)
1151.04 (1020.36)
71.11 (127.25)
886.81 (572.24)
SP Living
21.84 (36.60)
7.71 (16.71)
1.71 (1.12)
124.91 (161.72)
29.36 (46.73)
52.48 (65.00)
SP Total
35.71 (57.41)
40.48 (90.88)
22.40 (23.55)
313.55 (286.07)
32.72 (50.09)
157.28 (189.49)
DS Living
24.56 (27.64)
5.68 (9.11)
14.88 (13.28)
27.52 (34.20)
132.67 (159.05)
29.39 (36.97)
DS Total
20.37 (31.15)
30.21 (31.91)
18.61 (17.76)
67.65 (41.43)
146.53 (168.31)
60.69 (67.40)
SA Total
0
0
0
0
0
64.08 (156.96)
SC Total
0
0
0
0
0
0
SL Total
0
0
0.56 (0.67)
0
5.25 (12.87)
0

Table 21, continued.



Area
Plant

Material


R-F


N-F


R-BC


N-BC


R-C


N-C
JR
All Total
215.39 (127.59)
1801.68 (1075.94)
312.05 (353.47)
1532.24 (898.45)
255.62 (228.14)
1168.86 (577.97)
SP /

DS
JR Growing
0
14.03 (32.89)
0
26.35 (64.54)
0
0.43 (1.05)
JR Senescing
0
21.41 (50.75)
0
0
0
9.65 (10.58)
JR Standing Dead
0.59 (1.44)
118.19 (267.63)
0.40 (0.98)
0.77 (1.89)
0.21 (0.52)
23.97 (34.23)
JR Total
0.59 (1.44)
153.63 (351.20)
0.40 (0.98)
27.12 (64.18)
0.21 (0.52)
34.05 (43.46)
SP Living
190.51 (132.38)
288.80 (169.73)
528.29 (260.26)
348.75 (129.28)
179.47 (106.77)
348.59 (86.11)
SP Total
356.35 (333.71)
952.67 (555.20)
630.99 (234.76)
1042.93 (312.36)
330.03 (254.41)
885.49 (290.66)
DS Living
204.21 (98.90)
90.27 (87.62)
151.92 (113.67)
130.29 (77.82)
249.31 (152.89)
187.73 (79.17)
DS Total
327.33 (146.72)
237.47 (146.16)
229.39 (186.31)
227.76 (72.00)
330.11 (179.57)
358.19 (222.75)
SA Total
0
0
0
0
0
1.79 (4.38)
SC Total
0
2.53 (5.06)
2.03 (2.95)
1.09 (2.68)
0
0
SL Total
4.61 (11.30)
0
0
0
0
0.05 (0.13)
All Total
688.88 (452.63)
1346.29 (616.79)
862.80 (352.94)
1298.69 (311.65)
660.35 (260.52)
1279.57 (367.71)

Table 22. Summary of 1994 biomass (g/m2) means for flooding and wrack treatments. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., and SL = Salicornia sp.; F = flooded plots, BC = border control plots, and C = control plots; W = wrack areas of the plots and N = nonwrack areas of the plots)



Area
Plant

Material


F


BC


C


W


N
JR
JR Growing
148.71
158.44
108.81
5.71
271.59
JR Senescing
367.37
506.57
328.83
66.69
735.15
JR Standing Dead
403.97
533.12
400.06
211.67
679.77
JR Total
920.05
1198.21
783.08
284.13
1650.10
SP Living
2.75
0.76
69.71
3.79
45.02
SP Total
13.09
131.75
155.60
15.25
185.04
DS Living
0.65
0.84
10.69
4.63
3.49
DS Total
2.64
12.44
15.04
7.78
12.30
SA Total
22.37
24.44
8.77
0
37.06
SC Total
0
0
0
0
0
SL Total
0
0
0
0
0
All Total
958.16
1366.81
962.49
307.14
1884.50
SP / DS
JR Growing
2.71
0.44
3.36
0
4.34
JR Senescing
1.52
2.17
2.32
0.58
3.43

Table 22, continued



Area
Plant

Material


F


BC


C


W


N
SP / DS
JR Standing Dead
7.79
1.48
3.23
2.41
5.92
JR Total
12.01
11.87
8.91
8.17
13.69
SP Living
118.61
235.47
188.21
23.21
338.32
SP Total
423.72
597.12
541.97
212.36
829.52
DS Living
31.03
45.73
52.71
26.31
60.00
DS Total
109.69
131.12
132.85
78.76
170.35
SA Total
0
0
0
0
0
SC Total
1.04
0.53
0
0
1.05
SL Total
0
0
0
0
0
All Total
546.47
740.64
683.73
299.00
1014.89

Table 23. Summary of 1995 biomass (g/m2) means for flooding and wrack treatments. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., and SL = Salicornia sp.; F = flooded plots, BC = border control plots, and C = control plots; R = areas of the plots recovering from wrack deposition and N = nonwrack areas of the plots)



Area
Plant

Material


F


BC


C


R


N
JR
JR Growing
156.87
47.01
107.28
18.51
188.93
JR Senescing
196.92
165.25
33.18
39.94
223.63
JR Standing Dead
591.63
498.49
338.50
105.41
847.00
JR Total
945.41
710.76
478.96
163.86
1259.56
SP Living
14.77
62.99
40.92
17.42
61.70
SP Total
37.83
167.97
95.00
30.10
170.43
DS Living
18.20
21.20
81.03
59.42
20.86
DS Total
25.29
43.13
103.61
65.12
49.57
SA Total
0
32.04
0
0
21.36
SC Total
0
0
0
0
0
SL Total
0
0.28
2.63
1.94
0
All Total
1008.53
922.15
712.21
261.02
1500.91
SP / DS
JR Growing
0
0.28
2.63
1.94
0
JR Senescing
10.71
0
4.82
0
10.35

Table 23, continued.



Area
Plant

Material


F


BC


C


R


N
SP / DS
JR Standing Dead
59.39
0.59
12.09
0.40
47.64
JR Total
59.39
13.76
17.13
9.05
51.14
SP Living
239.65
438.52
264.03
299.91
328.71
SP Total
654.51
820.60
607.76
439.12
949.46
DS Living
147.24
141.11
218.52
201.81
136.10
DS Total
282.40
228.57
344.15
295.61
274.47
SA Total
0
0
0.89
0
0.60
SC Total
1.27
1.45
0
0.68
1.14
SL Total
2.31
0
0.03
1.54
0.02
All Total
1017.59
1080.75
969.96
737.34
1308.19

Table 24. Results of GLM for 1994 biomass samples. Specific significant differences were determined by least square means and are listed below the GLM p-values in parentheses. Significant interactions between variables where the individual components were significant are listed in Table 26. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., SL = Salicornia sp.)



Area
Plant

Material


Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding * Wrack
JR
JR Growing
0.03

(Z > X)
0.48
< 0.01

(N > W)
0.38
0.59
JR Senescing
0.28
0.12
< 0.01

(N > W)
0.57
0.15
JR Standing Dead
0.06
0.34
< 0.01

(N > W)
0.04
0.18
JR Total
0.03

(Z > X)
0.07
< 0.01

(N > W)
0.30
0.10
SP Living
0.47
0.04

(C > F & B)
0.10
0.56
0.10
SP Total
0.01

(X > Y & Z)
0.11
0.01

(N > W)
0.31
0.11
DS Living
0.73
0.15
0.81
0.56
0.92
DS Total
0.55
0.41
0.57
0.34
0.44
SA Total
0.83
0.83
0.11
0.26
0.83
SC Total
0.11
0.46
0.13
0.54
0.46
SL Total
All Total
0.19
0.04

(B > F & C)
< 0.01

(N > W)
0.29
0.02

Table 24, continued.



Area
Plant

Material


Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding * Wrack
SP /

DS
JR Growing
0.69
0.69
0.14
0.29
0.69
JR Senescing
0.90
0.94
0.19
0.31
0.77
JR Standing Dead
0.64
0.49
0.43
0.88
0.65
Total
0.92
0.96
0.59
0.19
0.51
SP Living
0.70
0.02

(B > F)
< 0.01

(N > W)
0.60
0.01
SP Total
0.71
0.08
< 0.01

(N > W)
0.03
< 0.01
DS Living
0.04

(X > Y & Z)
0.35
0.01

(N >W)
0.61
0.15
DS Total
0.07
0.76
< 0.01

(N > W)
0.87
0.27
SA Total
SC Total
0.11
0.46
0.13
0.54
0.46
SL Total
All Total
0.29
0.07
< 0.01

(N > W)
0.07
< 0.01

Table 25. Results of GLM for 1995 biomass samples. Specific significant differences were determined by least square means and are listed below the GLM p-values in parentheses. Significant interactions between variables where the individual components were significant are listed in Table 26. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., SL = Salicornia sp.)



Area
Plant

Material


Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding

* Wrack
JR
JR Growing
< 0.01

(Z > X & Y)
0.11
< 0.01

(N > R)
0.62
0.07
JR Senescing
< 0.01

(Z > X & Y)
< 0.01

(F & B > C)
< 0.01

(N > R)
0.06
0.02
JR Standing Dead
0.12
0.36
< 0.01

(N > R)
0.04
0.46
JR Total
0.01

(Z > X)
0.14
< 0.01

(N > R)
0.04
0.18
SP Living
< 0.01

(X > Y & Z)
0.17
0.03

(N > R)
0.16
0.02
SP Total
< 0.01

(X > Y & Z)
0.04

(B > F)
< 0.01

(N > R)
0.17
0.02
DS Living
0.02

(Y > Z)
0.01

(C > B & F)
0.04

(R > N)
< 0.01
0.04
DS Total
0.02

(Y > Z)
< 0.01

(C > F)
0.44
< 0.01
0.03
SA Total
0.38
0.38
0.32
0.42
0.38
SC Total

Table 25, continued



Area
Plant

Material


Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding

* Wrack
JR
SL Total
0.42
0.42
0.28
0.40
0.42
All Total
0.04

(Z > X)
0.35
< 0.01

(N > R)
< 0.01
0.28
SP /

DS
JR Growing
0.17
0.56
0.17
0.66
0.56
JR Senescing
0.36
0.47
0.15
0.42
0.47
JR Standing Dead
0.39
0.38
0.20
0.31
0.38
JR Total
0.25
0.54
0.27
0.40
0.30
SP Living
0.09
< 0.01

(B > F & C)
0.56
0.54
0.02
SP Total
0.26
0.44
< 0.01

(N > R)
0.98
0.74
DS Living
0.60
0.11
0.05

(R > N)
0.06
0.51
DS Total
0.44
0.15
0.65
0.01
0.57
SA Total
0.38
0.38
0.32
0.42
0.38
SC Total
0.01

(X > Y & Z)
0.23
0.53
0.27
0.13
SL Total
0.38
0.38
0.33
0.42
0.37
All Total
0.29
0.81
< 0.01

(N > R)
0.87
0.79

Table 26. A listing of the significant interactions for biomass data from 1994 and 1995. (JR = J. roemerianus, SP = S. patens, DS = D. spicata, SA = S. alterniflora, SC = Scirpus sp., SL = Salicornia sp.)

Year
Area
Plant Material
Block * Flooding
Flooding * Wrack
1994
JR
All
B*N > C*N & F*N
1994
SP / DS
SP Living
B*N & C*N > F*N
1995
JR
JR Senescing
B*N & F*N > C*N
1995
JR
DS Living
C*R > F*N, F*R, B*N, B*R, & C*N
1995
JR
DS Living
Y was always > Z and

C was always

> B & F
1995
JR
DS Total
Y*C > X*B, X*C, X*F, Y*B, Y*F; Z*B, & Z*F

Also in 1995, the flooding-wrack interaction was significant for the senescing leaves. Most of the significance could be linked to the strong effect of the wrack treatment. However, it is noteworthy that the nonwrack areas of the flooded plots and the nonwrack areas of the border control plots had significantly higher biomasses than the nonwrack areas of the control plots. There was not a significant difference between the nonwrack areas of the flooded plots and the nonwrack areas of the border control plots. Furthermore, there was no significant difference among the post-wrack areas of the flooded, border control, and control plots (Table 25).

A significant block effect occurred in 1994 and 1995 for the growing and total J. roemerianus biomasses and in 1995 for the senescing biomass. In 1994, both the growing and total biomass values were significantly higher in block Z than in block X. Block Y was not significantly different from block X or from block Z (Table 24). In 1995, the growing and senescing biomass values were significantly higher in block Z than in block X and Y. The total biomass was significantly higher in block Z than block X, but there was not a significant difference between the total biomass of block Z and the total biomass of block Y. There was not a significant difference between block X and Y in 1995 for the growing, senescing, or total biomass values (Table 25).

5.2.1.2. J. roemerianus in S. patens/D. spicata Dominated Areas

In the S. patens/D. spicata dominated areas, none of the variables significantly altered the biomass of J. roemerianus in 1994 or in 1995 (Table 24 and Table 25, respectively). However, this may be the result of the initial low biomass of J. roemerianus in these areas.

5.2.2. Spartina patens -- 1994 and 1995 Data

5.2.2.1. S. patens in J. roemerianus Dominated Areas

Flooding treatment had a significant effect on S. patens growing in J. roemerianus dominated areas. The 1994 biomass of living S. patens was significantly reduced in the flooded plots (2.75 g/m2) and the border control plots (0.76 g/m2) as compared to the control plots (69.71 g/m2) (Table 24). In 1995, the living S. patens biomass in the flooded (14.77 g/m2), border control (62.99 g/m2), and control (40.92 g/m2) plots did not differ significantly (Table 25). The opposite result occurred with the total S. patens biomass with no significant differences in 1994 but with significant differences in 1995. In 1995, the border control plots (167.97 g/m2) had a significantly higher amount of total S. patens biomass than the flooded plots (37.83 g/m2). The total S. patens biomass of the control plots (95.00 g/m2) did not differ significantly from the border control plots or from the flooded plots (Table 25).

Wrack deposition significantly reduced the living S. patens biomass in 1994 with the biomass from the wrack areas being 92 % lower than the nonwrack biomass (Table 22 and Table 24). The 1995 living S. patens biomass in the post-wrack areas (17.42 g/m2) was significantly less than 1995 nonwrack areas (61.70 g/m2) (Table 23 and Table 25). Wrack deposition did significantly reduce the total S. patens biomass in 1994 and in 1995 (Table 24 and Table 25, respectively). In 1994, the total S. patens biomass was 92 % lower in the wrack areas as compared to the nonwrack areas (Table 22). In 1995, the total S. patens biomass in the post-wrack areas was 82 % lower than the 1995 nonwrack areas (Table 23).

In 1995, the flooding-wrack interaction was significant for total S. patens biomass. The nonwrack areas of the border control plots had significantly higher biomass values than the post-wrack areas of the flooded, border control, and control plots and the nonwrack areas of the flooded and control plots (Table 25 and Table 26).

A significant block effect existed in the total S. patens biomass for 1994 and in the living and total S. patens biomasses for 1995. The block effect was the same among the different biomass samples with the samples collected from block X having significantly higher biomasses than samples collected in block Y and block Z. Furthermore, biomasses from block Y and block Z did not differ significantly from each other (Table 24 and Table 25, respectively).

5.2.2.2. S. patens in S. patens/D. spicata Dominated Areas

The type of inundation had a significant effect both years on the living S. patens biomass in the S. patens/D. spicata areas. In 1994, the border control plots (235.47 g/m2) had significantly higher biomass than the flooded plots (118.61 g/m2). The control plots did not differ significantly from the border control plots or from the flooded plots (Table 24). In 1995, the border control plots (438.52 g/m2) had significantly higher living S. patens biomass than the flooded plots (239.65 g/m2) and the control plots (264.03 g/m2). The flooded plots and the control plots were not significantly different (Table 25). Flooding treatment did not have a significant effect on the total S. patens biomass in 1994 or in 1995 (Table 24 and Table 25, respectively).

Wrack deposition significantly reduced the living and total biomasses of S. patens in 1994 (Table 24). The living S. patens biomass was 93 % lower in the wrack areas than in the nonwrack areas. The total S. patens biomass was 74 % lower in the wrack areas than in the nonwrack areas. In 1995, the living biomass collected from areas recovering from wrack deposition (299.91 g/m2) were not significantly different from the samples collected from the nonwrack areas (328.71 g/m2). However, the total biomass of S. patens in the areas recovering from wrack deposition (439.12 g/m2) was still significantly lower than the total biomass from nonwrack areas (949.46 g/m2) in 1995 (Table 23 and Table 25).

The flooding treatment and wrack treatment interaction was significant in 1994 for the living S. patens biomass (Table 24). The nonwrack areas of the flooded plots had significantly more biomass than the wrack areas of the flooded plots. The nonwrack areas of the border control plots had significantly higher biomasses than the wrack areas of the flooded, border control, and control plots and the nonwrack areas of the flooded plots. The wrack areas of the border control plots had significantly less biomass than the nonwrack areas of the flooded and control plots. The nonwrack areas of the control plots had significantly greater biomass than the wrack areas of the flooded and control plots. The wrack areas of the control plots had significantly less biomass than the nonwrack areas of the flooded plots. Furthermore, the living biomass of the nonwrack areas of the control plots was greater than the living biomass of the nonwrack areas of the flooded plots (Table 24).

There was not a block effect during either year for living and total S. patens biomass samples collected in the S. patens/D. spicata areas (Table 24 and Table 25).

5.2.3. Distichlis spicata -- 1994 and 1995 Data

5.2.3.1. D. spicata in J. roemerianus Dominated Areas

The D. spicata samples collected in 1994 from the J. roemerianus dominated areas did not show any significant results for any of the tested variables (Table 24).

In 1995, flooding treatment had a significant effect on the biomass D. spicata in the J. roemerianus dominated areas. The control plots had significantly higher living D. spicata biomass (81.03 g/m2) than the border control plots (21.20 g/m2) and the flooded plots (18.20 g/m2). The border control and the flooded plots were not significantly different from each other (Table 25). The 1995 total D. spicata biomass also was significantly higher in the control plots (103.61 g/m2) than in the flooded plots (25.29 g/m2) (Table 25).

In 1995, the post-wrack areas had significantly higher living D. spicata biomass (59.42 g/m2) than the nonwrack areas (20.86 g/m2). In contrast to the living biomass, total D. spicata biomass in 1995 did not differ between the nonwrack areas (49.57 g/m2) and the areas recovering from wrack deposition (65.12 g/m2) (Table 25). Furthermore, dead material was only 8 % of the total D. spicata biomass in the post-wrack areas.

A block effect did occur in some of the D. spicata samples collected in the J. roemerianus dominated areas. In 1995, the living biomass and the total biomass from block Y were significantly higher than samples collected from block Z. Block X was not significantly different from block Y or block Z (Table 25).

In 1995, the block and flooding treatment interaction was significant for the living D. spicata biomass. The control plot of block Y had significantly more biomass than the flooded, border control, and control plots of block X and block Z and the flooded and border control plots of block Y (Table 25 and Table 26).

The flooding-wrack interaction was significant for the living D. spicata biomass in 1995. The post-wrack areas of the control plots had significantly higher living D. spicata biomass (132.67 g/m2) than any other flooding treatment and wrack treatment combination (5.68-27.52 g/m2) (Table 21, Table 25, and Table 26).

5.2.3.2. D. spicata in S. patens/D. spicata Dominated Areas

Altered inundation did not have a significant effect on the living biomass or total biomass of D. spicata collected from S. patens/D. spicata dominated areas in 1994 or in 1995 (Table 24 and Table 25, respectively).

Wrack treatment had a significant effect on D. spicata biomass during both years. Wrack deposition significantly reduced the living and total biomass of D. spicata in 1994 (Table 24). The 1994 living D. spicata biomass was 56 % lower in the wrack areas than in the nonwrack areas. The 1994 total D. spicata biomass was 54 % lower in the wrack areas than the nonwrack areas. However, in 1995, the areas recovering from wrack deposition had statistically more living D. spicata biomass (201 g/m2) than the nonwrack areas (136.10 g/m2). The difference between the total D. spicata biomass in the post-wrack (295.61 g/m2) and nonwrack areas (274.47 g/m2) was not statistically different (Table 25).

The only block effect occurred in 1994 with the living D. spicata biomass samples. For the 1994 living biomass samples, the samples collected in block X had a significantly greater biomass than the samples collected in block Y and block Z. Block Y and block Z were not significantly different from each other (Table 24).

5.2.4. Spartina alterniflora -- 1994 and 1995 Data

No significant differences were found among the tested variables for the total S. alterniflora biomass in 1994 or in 1995 for material collected in the J. roemerianus dominated areas or for material collected in the S. patens/D. spicata dominated areas (Table 24 and Table 25, respectively).

5.2.5. Scirpus sp. -- 1994 and 1995 Data

No significant differences were found among the different tested variables for the total Scirpus sp. biomass collected in 1994 from the J. roemerianus dominated areas (Table 24). No Scirpus sp. was collected from the J. roemerianus dominated areas in 1995 (Table 21).

No significant differences were found among the different treatments for the Scirpus sp. biomass collected in 1994 from the S. patens/D. spicata dominated areas (Table 24). In 1995, the only significant effect for Scirpus sp. was block X had a significantly higher biomass than block Y and block Z. There was not a significant difference between block Y and block Z (Table 25).

5.2.6 Salicornia sp. -- 1994 and 1995 Data

Salicornia sp. was present in the J. roemerianus dominated and S. patens/D. spicata dominated areas in 1995 but not in 1994 (Table 23 and Table 22, respectively). However, there were no significant differences among the different tested variables for the total Salicornia sp. biomass in the J. roemerianus dominated and S. patens/D. spicata dominated areas (Table 25).

5.2.7. Total Biomasses -- 1994 and 1995 Data

5.2.7.1. Total Biomass in J. roemerianus Dominated Areas

For the 1994 total biomass collected from the J. roemerianus dominated areas, regardless of plant material type, the border control plots had a significantly higher biomass (1366.81 g/m2) than the flooded plots (958.16 g/m2) and control plots (962.49 g/m2). The flooded and control plots were not significantly different from each other (Table 24). In 1995, the different inundation treatments did not show significant differences in the total biomass collected from the J. roemerianus dominated areas (Table 25).

The wrack treatment significantly reduced the total biomass collected from the J. roemerianus dominated areas in 1994 and in 1995 (Table 24 and Table 25, respectively). Wrack deposition reduced the total biomass of the J. roemerianus dominated areas by 84 % in 1994. The 1995 total biomass of the post-wrack areas was 83 % less than the 1995 total biomass from the nonwrack areas.

The flooding treatment and wrack treatment interaction was significant for the total biomass collected in the J. roemerianus areas in 1994. The nonwrack areas of the flooded plots had significantly higher biomasses than the wrack areas of the flooded and control plots. The nonwrack areas of the border control plots were significantly greater than the nonwrack and wrack areas of the flooded plots and control plots and the wrack areas of the border control plots. The nonwrack areas of the control plots had significantly more biomass than the wrack areas of the flooded, border control, and control plots (Table 24).

There was a block effect in 1995 but not in 1994 for the total biomass collected from the J. roemerianus dominated areas. Block Z had a significantly higher biomass than block X. Block Y was not significantly different from block X or block Z (Table 25).

5.2.7.2. Total Biomass in S. patens/D. spicata Dominated Areas

For the total biomass collected from the S. patens/D. spicata dominated areas, only the wrack treatment had a significant effect (Table 24 and Table 25, respectively). Both the 1994 and the 1995 biomass samples were significantly lower from the wrack areas than from the nonwrack areas (Table 24 and Table 25, respectively). Wrack deposition in 1994 reduced the total biomass from the S. patens/D. spicata dominated areas by 71 % as compared to the nonwrack areas (Table 22). In 1995, the total biomass of the post-wrack areas was 44 % lower than the 1995 total biomass of the nonwrack areas (Table 23)

5.2.8. Reference Biomass -- 1995 Data

Table 27 contains the means and standard deviations for the biomass samples collected from the reference J. roemerianus populations and the nonwrack areas of the control plots in 1995. The only significant treatment effect was with the growing J. roemerianus leaf biomass. The control plot in block Y had significantly more growing leaf biomass than reference B. Furthermore, block Z's control plot had significantly more

growing leaf biomass than block X's control plot and both reference populations (Table 28).

5.3. Vegetative Analysis of Ground Cover in the Plots

The mean percentages and standard deviations (in parenthesis) of change in ground cover from 1994 to 1995 are listed in Table 29 The percentage of change in ground cover

Table 27. The means and standard deviations (in parentheses) of the biomass (g/m2) samples from the reference population of J. roemerianus and the nonwrack controls dominated by J. roemerianus collected in 1995.



Species


Plant Material


Reference A


Reference B
Nonwrack Control
J. roemerianus
Growing
118.72 (84.17)
25.76 (24.66)
197.20 (112.06)
Senescing
374.80 (289.07)
171.36 (56.79)
60.51 (43.06)
Standing Dead
611.92 (632.55)
715.04 (41.63)
629.10 (668.90)
Total
1105.44 (1005.79)
912.16 (9.50)
886.81 (572.24)
S. patens
Living
0
23.20 (32.81)
52.48 (65.00)
Total
10.40 (0)
78.08 (92.32)
157.28 (189.49)
D. spicata
Living
5.28 (7.47)
28.96 (19.46)
29.39 (36.97)
Total
8.00 (11.31)
107.92 (33.83)
60.69 (67.40)
S. alterniflora
Total
22.88 (18.10)
0 (0)
64.08 (156.96)
All
Total
1186.32 (961.10)
1098.16 (48.99)
1168.86 (577.97)

Table 28. Results of GLM for comparison of reference biomass samples and control plots biomass samples for 1995. Specific significant differences were determined by least square means and are listed below the GLM values in parentheses.

Species
Plant Material
Treatment
J. roemerianus
Growing
0.05

(Y > Reference B;

Z > X, Reference A & Reference B)
Senescing
0.22
Standing Dead
0.69
Total
0.82
S. patens
Living
0.08
Total
0.16
D. spicata
Living
0.69
Total
0.15
S. alterniflora
Total
0.51
All
Total
0.30

Table 29. Means and standard deviations (in parentheses) of the percentage of ground cover change based on flooding treatment and wrack treatments between 1994 and 1995. (F = flooded plots, BC = border control plots, and C = control plots; W = wrack areas and N = nonwrack areas)

F
BC
C
W
N
48.71 (23.99)
43.29 (24.34)
42.13 (16.25)
60.69 (10.93)
28.72 (14.81)

for the flooding treatment ranged from 42.13 (16.25) % to 48.71 (23.99) %. There were no statistically significant differences among the three flooding treatments (Table 30). The ground cover of the nonwrack areas of the plots changed 28.72 (14.81) % from 1994 to 1995. The ground cover of the wrack areas of the plots changed 60.69 (10.93) % from 1994 to 1995. The percentage of change in the wrack areas was statistically greater than the change in the nonwrack areas (Table 30). The interaction between flooding treatment and wrack treatment was not statistically significant. The block effect also was significant with block X having significantly more change than block Y and block Z. Block Y and block Z were not significantly different from each other (Table 30).

5.4. ANPP of Juncus roemerianus

Table 31 lists the means and standard deviations for the annual frequency of replacement of growing leaves (FREQ, number/y), the average leaf height (AVE HT, cm), and the production-to-biomass ratio (P/B, dimensionless) for the experimental plots and the reference populations. Table 32 lists the means and standard deviations for the annual net primary productivity (ANPP, g/(m2 x y)) for the experimental plots and the reference populations. Table 33 lists the means generated by the GLM procedure. I included this table in order to clarify differences or the lack of differences among the different tested variables.

Flooding treatment produced significant results only for the annual frequency of leaf replacement. The frequency of the control plots (2.0 / y) was significantly higher than

Table 30. Results of GLM for the percentage of change in ground cover from 1994 to 1995. The specific significant differences were determined by least square means and are listed in parenthesis below the GLM values.



Block
Flooding Treatment
Wrack Treatment
Block * Flooding
Flooding * Wrack
0.01

(X > Y & Z)
0.45
< 0.01

(W > N)
0.80
0.25

Table 31. Means and standard deviations (in parenthesis) of the frequency of a new cohort of J. roemerianus leaves, the average height for each cohort, and the productivity to biomass ratio (P/B) for each cohort among the different flooding treatments. The frequency, average height, and P/B for the reference J. roemerianus leaves also are listed. The year each cohort was tagged and the wrack treatment for each cohort are listed in parenthesis. (94 = leaves tagged in 1994 and 95 = leaves tagged in 1995; N = leaves tagged in nonwrack areas and R = leaves tagged in areas recovering from wrack deposition)

Flooding Treatment
Cohort

Number
Frequency

(# /y)
Average Height

(cm)
P/B

(no units)
Flooded
1 (94, N)
1.9 (0.9)
47.8 (20.5)
1.7 (0.3)
2 (94, N)
1.1 (0.3)
43.1 (11.5)
1.8 (0.2)
3 (94, N)
1.8 (1.6)
47.4 (17.8)
1.3 (0.2)
4 (95, N)
1.1 (0.1)
30.3 (7.4)
2.2 (0.3)
5 (95, R)
2.1 (0.9)
34.8 (14.4)
2.0 (0.5)
6 (95, N)
1.8 (0.7)
24.2 (6.9)
2.0 (0.3)
7 (95, R)
2.3 (0.7)
30.2 (6.8)
1.7 (0.2)
Border Control
1(94, N)
2.0 (0.6)
44.6 (13.2)
1.4 (0.1)
2 (94, N)
1.0 (0.5)
44.7 (8.6)
1.7 (0.2)
3 (94, N)
1.1 (0.3)
48.4 (9.5)
1.3 (0.1)
4 (95, N)
1.4 (0.6)
24.9 (10.9)
2.2 (0.8)
5 (95, R)
2.5 (0.9)
36.3 (17.4)
1.9 (0.4)
6 (95, N)
2.4 (1.2)
23.0 (5.3)
2.0 (0.5)
7 (95, R)
2.9 (0.6)
32.2 (6.5)
1.6 (0.2)
Control
1 (94, N)
2.2 (0.8)
47.5 (19.6)
1.5 (0.3)

Table 31, continued.

Flooding Treatment
Cohort

Number
Frequency

(# /y)
Average Height

(cm)
P/B

(no units)
Control
2 (94, N)
1.1 (0.4)
41.4 (6.9)
1.8 (0.2)
3 (94, N)
2.2 (1.9)
43.8 (21.6)
1.6 (0.5)
4 (95, N)
1.3 (0.5)
33.0 (9.4)
2.2 (0.3)
5 (95, R)
2.3 (1.0)
31.3 (13.2)
2.1 (0.5)
6 (95, N)
2.4 (0.4)
29.8 (6.3)
1.9 (0.3)
7 (95, R)
2.8 (1.0)
32.2 (8.1)
1.7 (0.3)
Reference A
4 (95, N)
1.3 (0.5)
33.8 (8.6)
2.1 (0.5)
6 (95, N)
2.6 (1.0)
36.0 (9.1)
1.4 (0.2)
Reference B
4 (95, N)
1.2 (0.4)
21.9 (8.8)
2.1 (0.3)
6 (95, N)
2.0 (0.2)
35.4 (5.7)
1.5 (0.1)

Table 32. Means and standard deviations (in parenthesis) of the annual net primary productivity (ANPP in g/(m2 x y)) for each J. roemerianus cohort. The year and wrack treatment for each cohort are listed in parenthesis. (94 = leaves tagged in 1994 and 95 = leaves tagged in 1995 and N = leaves tagged in nonwrack areas and R = leaves tagged in areas recovering from wrack deposition)

Flooding Treatment
Cohort Number
ANPP
Flooded
1 (94, N)
2000.6 (263.2)
2 (94, N)
1227.8 (242.4)
3 (94, N)
1499.9 (472.8)
4 (95, N)
1187.3 (868.4)
5 (95, R)
173.0 (131.3)
6 (95, N)
1917.6 (1872.0)
7 (95, R)
146.6 (99.9)
Border Control
1 (94, N)
2257.5 (481.2)
2 (94, N)
1244.6 (126.1)
3 (94, N)
1121.9 (340.9)
4 (95, N)
619.6 (577.3)
5 (95, R)
232.9 (347.2)
6 (95, N)
1228.9 (1039.6)
7 (95, R)
311.5 (487.7)
Control
1 (94, N)
1542.7 (100.2)
2 (94, N)
922.2 (131.4)

Table 32, continued.

Flooding Treatment
Cohort Number
ANPP
Control
3 (94, N)
1622.4 (827.0)
4 (95, N)
624.6 (291.5)
5 (95, R)
82.9 (72.6)
6 (95, N)
1021.3 (575.1)
7 (95, R)
112.4 (136.6)
Reference A
4 (95, N)
941.3 (0)
6 (95, N)
1042.8 (0)
Reference B
4 (95, N)
303.2 (0)
6 (95, N)
371.1 (0)

the frequency of the flooded plots (1.7 / y). The frequency of the border control plots (1.9 / y) was not significantly different from the flooded plots or the control plots (Table 34).

Significant differences for frequency, average height, production-to-biomass, and ANPP were found among the different leaf cohorts. However, most of the differences were the result of when the cohort was tagged and not between the 1995 cohorts tagged in the nonwrack areas (cohorts 4 and 6) versus the 1995 cohorts tagged in the post-wrack areas (cohorts 5 and 7). Since studying the effects of when a cohort was tagged was not one of the goals of this thesis, I will only be discussing the cohort differences that relate to nonwrack versus post-wrack differences.

The frequency of the spring post-wrack cohort (cohort 5, 2.3 / y) was significantly higher than the frequency of the spring nonwrack cohort (cohort 4, 1.3 / y). The frequency of the summer post-wrack cohort (cohort 7, 2.7 / y) was significantly higher than the frequency of the summer nonwrack cohort (cohort 6, 2.2 / y). Therefore, the annual frequency of leaf replacement was statistically higher in the post-wrack areas than in the 1995 nonwrack areas (Table 34). A higher frequency of leaf replacements is the result of faster growth rates. So the leaves in the post-wrack areas were probably growing faster than the leaves in the nonwrack areas during 1995.

For average height, the summer post-wrack cohort (cohort 7) had significantly higher average heights (31.5 cm) than the summer cohort of the nonwrack areas (cohort 6, 25.7 cm). The average heights from the spring cohorts tagged in the nonwrack (cohort 4)

Table 33. Means from the GLM procedure for the frequency (FREQ, # /y), average height (AVE HT, cm), production-to-biomass (P/B, dimensionless), and annual net primary production (ANPP, g/(m2 x y)) of J. roemerianus. The year and wrack treatment for each cohort are listed in parenthesis. (94 = leaves tagged in 1994 and 95 = leaves tagged in 1995 and N = leaves tagged in nonwrack areas and R = leaves tagged in areas recovering from wrack deposition)

FREQ
AVE HT
P/B
ANPP
Flooded plots
1.7
36.9
1.8
1164.7
Border Control plots
1.9
36.3
1.8
1002.4
Control plots
2.0
37.0
1.8
846.9
Cohort 1 (94, N)
2.0
46.7
1.5
1933.6
Cohort 2 (94, N)
1.0
43.1
1.8
1131.5
Cohort 3 (94, N)
1.7
46.6
1.4
1414.7
Cohort 4 (95, N)
1.3
29.5
2.2
810.5
Cohort 5 (95, R)
2.3
34.1
2.0
162.9
Cohort 6 (95, N)
2.2
25.7
2.2
1389.3
Cohort 7 (95, R)
2.7
31.5
1.7
190.2

Table 34. Results of GLM for frequency (FREQ, # /y), average height (AVE HT, cm), production to biomass (P/B, dimensionless), and annual net primary productivity (ANPP, g/(m2 x y)) for J. roemerianus. Specific significant differences were determined by least square means and are listed below the GLM values in parentheses.



Block
Flooding

Treatment


Cohort
Block *

Flooding
Flooding

* Cohort
FREQ
< 0.01

(X > Y & Z)
0.05

C > F
< 0.01

(1 & 3 > 2 & 4;

5, 6 & 7 > 2, 3 & 4;

7 > 1, 5, & 6)
0.72
0.07
AVE HT
< 0.01

(Z & Y > X)
0.92
< 0.01

(1, 2 & 3 > 4, 5, 6 & 7;

5 & 7 > 6)
0.13
0.67
P/B
0.65
0.96
< 0.01

(2 > 3;

4, 5& 6 > 1, 2 & 7;

4, 5, 6 & 7 > 3)
0.38
0.23
ANPP
< 0.01

(Y & Z > X)
0.95
< 0.01

(1 > 2, 3, 4, 5, 6 & 7;

2 > 5 & 7;

3 & 6 > 4, 5 & 7;

4 > 5 & 7)
0.13
0.67

and post-wrack areas (cohort 5) were not statistically different from each other (Table 34).

The production-to-biomass ratio was significantly different between the cohorts tagged during the summer of 1995 (Table 34). The production-to-biomass ratio for nonwrack cohort (cohort 6, 2.2) was significantly higher than production-to-biomass ratio of the post-wrack cohort (cohort 7, 1.7). However, the production-to-biomass ratios for the cohorts tagged in the spring of 1995 in the nonwrack (cohort 4, 2.2) and post-wrack areas (cohort 5, 2.0) were not statistically different from each other.

Lastly, the ANPP of the spring nonwrack cohort (cohort 4, 810 g/(m2 x y)) was significantly greater than the ANPP of the spring post-wrack cohort (cohort 5, 162.9 g/(m2 x y)). The ANPP of summer nonwrack cohort (cohort 6, 1389.3 g/(m2 x y)) was significantly higher than the ANPP of summer post-wrack cohort (cohort 7, 190.2 g/(m2 x y)) (Table 34). Therefore, the ANPP of the J. roemerianus cohorts in the nonwrack areas was significantly greater than the ANPP of the cohorts tagged in the post-wrack areas. This difference in ANPP is largely the result of biomass differences between the nonwrack and post-wrack areas.

A significant block effect occurred with frequency, average height, and ANPP. The frequency of block X was significantly greater than the frequencies of blocks Y and Z. The average height and ANPP of blocks Y and Z were significantly greater than the average height and ANPP of block X (Table 34).

5.4.1. Control Plots vs. Reference Populations Comparison for ANPP

For the 1995 control plots versus the reference populations, there were several significant differences between the cohorts. These differences between cohorts 4 and 6 are the result of when they were tagged and not where they were tagged. Therefore, I will not discuss the cohort differences in this section. The production-to-biomass ratios for the control plots in block Y (2.2) and Z (2.1) were statistically higher than the production-to-biomass ratios for reference populations A (1.8) and B (1.8) (Table 35 and Table 36). ANPP was not significantly different between the control plots and the reference populations at the 0.05 level of significance, but the p-value of 0.07 may indicate a trend. The ANPP of reference population A (992.1 g/(m2 x y)) was much higher than the ANPP of the control plot in block X (358.0 g/(m2 x y)) and reference population B (337.2 g/(m2 x y)). Furthermore, the ANPP of the control plots in blocks Y (976.0 g/(m2 x y)) and Z (1134.8 g/(m2 x y)) were much higher than the ANPP for reference population B (337.2 g/(m2 x y)) (Table 35). Frequency and average height were not statistically different between the control plots and the reference populations (Table 36).

5.5 Shading Experiment

Table 37 lists the means and standard deviations for the two biomass collections (July 24 and October 14, 1995) from the shading experiment. The non-J. roemerianus biomass samples consisted of varying amounts of S. patens, D. spicata, and S.

Table 35. Means from GLM comparison of control plots and reference populations for frequency (FREQ, # / y), average height (AVE HT, cm), production-to-biomass (P/B, dimensionless), and annual net primary production (ANPP, g/(m2 x y)).

Treatment
FREQ
AVE HT
P/B
ANPP
Block X's control plot
1.9
33.6
1.9
358.0
Block Y's control plot
1.9
31.9
2.2
976.0
Block Z's control plot
1.6
28.7
2.1
1134.8
Reference A
1.8
35.0
1.8
992.1
Reference B
1.6
28.7
1.8
337.2



Table 36. Results of GLM for reference J. roemerianus populations versus the experimental control plots for frequency (FREQ, number of cohorts/yr.), average height (AVE HT, cm), production to biomass (P/B, dimensionless), and annual net primary productivity (ANPP, g/(m2 x y)). Specific significant differences were determined by least square means and are listed below the GLM values in parentheses. Significant interactions are discussed in the result section.



Treatment


Cohort
Treatment *

Cohort
FREQ
0.33
< 0.01

(6 > 4)
0.17
AVE HT
0.14
0.56
0.02
P/B
< 0.01

(Control X & Z > Reference A & B)
< 0.01

(4 > 6)
0.18
ANPP
0.07
0.14
N/A

Table 37. Means and standard deviations (in parentheses) of the two biomass (g/m2) collections of the shading experiment.

Collection
Plant Material
Shaded
Frame Control
Control
24 Jul 95
J. roemerianus
121.56 (80.21)
84.72 (36.77)
161.44 (40.76)
Other
14.20 (15.39)
18.80 (1.02)
13.16 (7.82)
All
135.76 (73.24)
93.43 (30.74)
174.60 (40.07)
14 Oct 95
J. roemerianus
93.20 (27.16)
46.40 (11.31)
85.60 (27.97)
Other
8.80 (4.97)
16.00 (2.26)
19.20 (13.89)
All
102.00 (29.94)
51.58 (19.80)
104.80 (38.41)

alterniflora. Shading treatment did not have a significant effect on the regrowth of J. roemerianus. The non-J. roemerianus biomass (19.20 g/m2) from the control areas collected in October was significantly higher than the non-J. roemerianus biomass collected in the shaded areas (8.80 g/m2). The non-J. roemerianus biomass of block 1 also was significantly higher than block 2. Furthermore, the interaction between block and shading treatment was significant for the October non-J. roemerianus biomass. The biomass of block 1's control was significantly higher than the biomass of block 2's shaded area and control. Shading treatment did not have a significant effect on the total biomass for either sampling date (Table 38).

Table 38. Results of GLM for shading experiment. The statistically significant results of the least squares means are listed below the GLM values. The interaction between the block and the shade treatment is explained in the results (S = shaded, F = frame control, and C = control)



Collection


Plant Material


Block
Shading Treatment
Block *

Shading
24 Jul 95
J. roemerianus
0.16
0.38
0.77
Other
0.84
0.86
0.46
All
0.18
0.38
0.88
14 Oct 95
J. roemerianus
0.29
0.27
0.95
Other
0.04

(1 > 2)
0.05

(C > S)
0.01
All
0.27
0.36
0.67

6. DISCUSSION

The focus of my research was to study experimentally the effects of increased inundation and wrack deposition, by themselves and in combination, on the plants of a high salt marsh community in Virginia. This two year study involved (1) the experimental pumping of water onto the high marsh community, (2) placing wrack on the plant community, and (3) removing the half of the wrack after six months of deposition. The data collected from the experimental plots included (1) the tracking of the growth and senescence of J. roemerianus, (2) estimations of growing and senescing J. roemerianus leaf densities, (3) the collection of aboveground biomass samples, (4) vegetative analysis of the change in ground cover, and (5) estimation of the ANPP of J. roemerianus. Furthermore, I monitored two additional J. roemerianus populations that were naturally inundated on a daily basis. I compared these reference J. roemerianus populations to the experimental controls to determine the effects of greater, natural inundation on J. roemerianus. I also designed an experiment during the summer of 1995 to study the effects of shading on the regrowth of plants in the J. roemerianus community. Table 39 summarizes the data, methods, statistics, and basic results of this study.

A record of the amount of water pumped onto the experimental plots is summarized in Appendix C. In Appendix D, I show the depth of water below the surface and salinity as measured during the summer of 1995. The flooded plots had significantly higher water depths and salinities than the border

Table 39. Summary of data, methods, statistics, basic results of this study.

Data Sets
Methods
Statistics Used
Results
Growth and Senescence of J. roemerianus (Life History, Maximum Green and Total Heights)
Collected from March 1994-October 1995; Measured tagged leaves (cm)
Life Table Analysis using LIFEREG and LIFETEST and General Linear Model (GLM)
Flooding and wrack treatments had a significant effect on life history but not on maximum heights.
Aboveground Biomass
Collected September 1994 and October 1995 (g/m2)
GLM
Species specific response to flooding treatments occurred both years. Wrack deposition in 1994 had a non-species specific response. Regrowth and colonization after wrack deposition (1995 data) was species specific.
J. roemerianus Leaf Densities
Collected September 1994 and October 1995 (#/m2)
GLM
The flooding treatments did not have a significant effect on leaf densities but the wrack treatments did for both years.
Vegetative Analysis of Ground Cover
July 1994 and July 1995; Recorded presence vs. absence of species
Determined Frequency of Change and GLM
The flooding treatments did not have a significant effect on ground cover change from 1994 to 1995 but the wrack treatments did have a significant effect.

Table 39, continued.

Data Sets
Methods
Statistics Used
Results
Annual Net Primary Productivity (ANPP), Frequency (#/y), Average Height (cm), Production/Biomass (P/B)
Determined for 1994 and 1995 using tagged leaves and biomass data (g/(m2 x y))
GLM
The flooding treatments affected frequency, and wrack treatments affected ANPP.
Reference J. roemerianus Population
March-October 1995; Measured tagged leaves and collected biomass samples
Comparisons with control plots made with GLM
The reference J. roemerianus populations were significantly different from the J. roemerianus growing in the control plots for a range of tested variables.
Shading Experiment
May-October 1995; Biomass collections made in July and October 1995
GLM
Although shading did not have a significant effect on the growth of J. roemerianus, shading did significantly reduce the aboveground biomass of non-J. roemerianus species.

Table 39, continued.

Data Sets
Methods
Statistics Used
Results
Well Water Depths and Salinity
June-August 1995; Water level below ground surface and salinity of ground water

(Collected by J. Tomkins)
GLM
The flooded plots had significantly higher water depths and salinities than the border control and control plots. The water depths and salinities of the border control plots were significantly greater than those of the control plots.
Amount of Water Pumped onto Plots
March 1994-October 1995 (when pump was running)
N/A
N/A

control and control plots. Furthermore, the border control plots had significantly higher water depths and salinities than the control plots (Appendix D).

Taylor (1995) studied the effects of increased inundation and wrack deposition on nitrification and denitrification within the same experimental plots at which I conducted my work.. Altered inundation did not affect the rates of nitrification or denitrification (Taylor 1995). Higher rates of denitrification were consistently found in the wrack areas than in the nonwrack areas. Only one of the three sampling periods produced statistically higher rates of nitrification in the wrack areas compared to the nonwrack areas. Furthermore, the ranges of nitrification and denitrification rates from the experimental plots were within the ranges reported from other studies (Taylor 1995). From Taylor (1995), I can conclude nitrogen availability was probably not a limiting factor in the recolonization of bare areas after the wrack was removed.

In this Discussion section, I address how I have rejected or failed to reject my previously stated null hypotheses (Section 3.2.) and how related studies compare to my

work. I discuss my work in the context of Brinson and coworkers' (1995) transgression model for salt marshes in the Conclusions section.

6.1. Effects of Increased Inundation on Salt Marsh Vegetation

6.1.1. Increased inundation does not affect the growth of J. roemerianus.

Increased inundation did not affect most of the measured growth parameters of J. roemerianus. However, there are notable exceptions. In 1994, the leaves in the control plots reached their maximum green heights faster than the leaves in the border control plots. During 1995, the leaves in the border control and control plots reached their maximum green heights faster than the leaves in the flooded plots. Furthermore, the 1995 cohorts in the border control plots reached their maximum total heights faster than the 1995 cohorts in the flooded plots. Analyzed another way, the J. roemerianus leaves in the control plots also had a significantly higher number of leaves per year (frequency) than the flooded plots. Therefore, I conclude the growth dynamics but not the overall production (i.e., maximum heights, aboveground biomass, and ANPP) of J. roemerianus leaves are affected negatively by increased inundation. Plants in areas that are less frequently inundated by salt water may have faster growing leaves and slightly more cohorts per year.

Several studies have documented the productivity of J. roemerianus. I found that an especially large number of studies have been conducted on J. roemerianus in North Carolina marshes. However, other than the values reported by Brinson et al. (1995), this study represents the first estimates of J. roemerianus productivity in a Virginia marsh. Furthermore, of the J. roemerianus studies, only Christian et al. (1990) and Hook (1991) tried to correlate the productivity of J. roemerianus to a hydrological gradient; although several studies examined the relationship between salinity and the production of J. roemerianus (Table 40).

Christian et al. (1990) studied the growth, senescence, and decomposition of J. roemerianus along a 1.6 km transect from the edge of an estuary to the marsh interior. The transect encompassed gradients of salinity and hydroperiod and included three

Table 40. Summary of studies that have calculated production of either J. roemerianus, S. patens, or D. spicata. The values from my thesis represent the range of numbers calculated from 1994 and 1995 for the flooding treatments. Unless otherwise noted all studies were conducted in salt or brackish marshes, and the plant material was collected in areas where that species was a dominant.

Species
Study Site
Measurement
Value
Reference
J. roemerianus
NC
Net Leaf Productivity
560 g/(m2 x y)
Foster 1968
J. roemerianus
Freshwater marsh in MS
Aboveground Biomass
400 g/m2
Eleuterius 1972
J. roemerianus
MS
Aboveground Biomass
2000 g/m2
Eleuterius 1972
J. roemerianus

live
NC
Aboveground Biomass
344 g/m2
Williams & Murdoch 1972
J. roemerianus dying
NC
Aboveground Biomass
504 g/m2
Williams & Murdoch 1972
J. roemerianus

dead
NC
Above ground Biomass
1, 604 g/m2
Williams & Murdoch 1972
J. roemerianus
NC
ANPP
754 g/(m2 x y)
Williams & Murdoch 1972
J. roemerianus
NC
Aboveground Biomass
30-80 g/m2 for areas not dominated by J. roemerianus
Calculated from Cooper & Waits 1973
J. roemerianus
NC
Aboveground Biomass
510-800 g/m2 for areas dominated by J. roemerianus
Calculated from Cooper & Waits 1973

Table 40, continued.

Species
Study Site
Measurement
Value
Reference
J. roemerianus living
NC
Aboveground Biomass
24.79-27.71 g/m2
Calculated from Blum et al. 1978
J. roemerianus dead
NC
Aboveground Biomass
635-1066 g/m2
Calculated from Blum et al. 1978
J. roemerianus
NC
ANPP
979-1038 g/(m2 x y)
Blum et al. 1978
J. roemerianus
GA
ANPP
1500-2800 g/(m2 x y)
Gallagher et al. 1980
J. roemerianus growing leaves
NC
Aboveground Biomass
307 g/m2
Christian et al. 1990
J. roemerianus

senescing leaves
NC
Aboveground Biomass
247-723 g/m2
Christian et al. 1990
J. roemerianus standing dead
NC
Aboveground Biomass
774-1264 g/m2
Christian et al. 1990
J. roemerianus
NC
ANPP
720-1511 g/(m2 x y)
Christian et al. 1990
J. roemerianus young leaves
NC
Aboveground Biomass
14.0-20.7 g/m2
Hook 1991
J. roemerianus old leaves
NC
Aboveground Biomass
20.6-35.6 g/m2
Hook 1991
J. roemerianus growing leaves
VA
Aboveground Biomass
107.28-158.44 g/m2
This thesis

Table 40, continued.

Species
Study Site
Measurement
Value
Reference
J. roemerianus senescing leaves
VA
Aboveground Biomass
33.18-506.57 g/m2
This thesis
J. roemerianus standing dead
VA
Aboveground Biomass
338.50-591.63 g/m2
This thesis
J. roemerianus all leaves
VA
Aboveground Biomass
478.96-1198.21 g/m2
This thesis
J. roemerianus
VA
ANPP
846.9-1164.7 g/(m2 x y)
This thesis
J. roemerianus total biomass
VA
Aboveground Biomass
8.91-59.39 g/m2 for areas not dominated by J. roemerianus
This thesis
S. patens
NC
Aboveground Biomass
230-440 g/m2
Calculated from Cooper & Waits 1973
S. patens
New England
Aboveground Biomass
430 g/m2
Nixon & Oviatt 1993
S. patens
NC
Aboveground Biomass
3.0-21.1 g/m2
Hook 1991
S. patens living
VA
Aboveground Biomass
118.61-438.52 g/m2
This thesis
S. patens total
VA
Aboveground Biomass
432.72-820.60 g/m2
This thesis
D. spicata
NC
Aboveground Biomass
190-240 g/m2
Calculated from Cooper & Waits 1973

Table 40, continued.

Species
Study Site
Measurement
Value
Reference
D. spicata
NC
Aboveground Biomass
0.2 g/m2
Hook 1991
D. spicata living
VA
Aboveground Biomass
31.03-218.52 g/m2
This thesis
D. spicata total
VA
Aboveground Biomass
109.69-344.15 g/m2
This thesis
S. alterniflora dominant with extensive stands of S. patens and D. spicata
VA

with mean salinity 10 ppt
Productivity
572 g/(m2 x y)
Mendelssohn & Marcellus 1976
J. roemerianus, S. patens, D. spicata, and others
VA
Aboveground Biomass
400 g/m2
Brinson et al. 1995

distinctive vegetation zones. The aerial ANPP for J. roemerianus ranged from 463 to 1030 g/(m2 x y). There was not a significant correlation between hydroperiod and ANPP (Christian et al. 1990). My study produced similar results with an ANPP range of 846 to 1164 g/(m2 x y), among the flooding treatments and no significant difference among the three flooding treatments. The production-to-biomass ratio for Cedar Island ranged from 1.81 to 2.09 with no statistically significant difference along the transect. My production-to-biomass calculations for flooding treatments were almost identical to the Cedar Island study with flooding treatments averaging a production-to-biomass ratio of 1.8. The frequency of replacement of growing leaves ranged from 1.10 /y to 1.92 /y, on Cedar Island with no significant differences along the transect. The frequency among my flooding treatments again was very similar with a range of 1.7 /y to 2.0 /y. However, unlike the Cedar Island study, I found statistically significant differences among my flooding treatments with the frequency of cohorts for the control plots (2.0 /y) being higher than the flooded plots (1.7 /y). The difference in frequency between the two studies may be the result of how each study was conducted and how the data were analyzed.

The average aboveground biomass of growing J. roemerianus leaves for Cedar Island ranged from 172 to 427 g/m2 with the lowest value at 1590 m away from the estuary and the highest value at 50 m away from the estuary (Christian et al. 1990). Christian et al. (1990) did find a significant correlation between distance and biomass. However, they felt the correlation was more because of extreme values at each end of the transect than differences in hydroperiod. The growing J. roemerianus biomass based on flooding treatment in my study was much lower at 107 to 158 g/m2. I did not find any statistical differences among the flooding treatments for growing J. roemerianus biomass. Furthermore, the differences in biomass of the two studies may be biogeographic. The J. roemerianus in Brownsville marsh is closer to the northern limit of this species than the population on Cedar Island (Eleuterius 1976).

Hook (1991) manipulated local hydrology in 30 cm diameter plots on Cedar Island at 200 m, 800 m, and 1600 m away from the shoreline. He also altered salinity and nitrogen availability at the three different sites. Overall, Hook (1991) found a shift in the control of production from inhibition by inundation or salinity at the edge of the marsh to limitation by nitrogen in the marsh interior. At the 200 m site, the J. roemerianus responded positively to increased elevation but the J. roemerianus at the 800 m and 1600 m sites showed no response to increased elevation. Hook (1991) concluded that his study did not clearly support the idea of a gradient of decreasing stress and increasing production. Furthermore, low J. roemerianus densities appeared to be a factor for the low production in the marsh interior where the production of other species was the highest (Christian et al. 1990, Hook 1991).

6.1.2. Increased inundation does not affect the senescence of J. roemerianus.

Most of the parameters I measured to study the senescence of J. roemerianus did not support the hypothesis that increased inundation affects the senescence of J. roemerianus. These parameters included the time for leaves to completely senesce from their maximum green and total heights, senescing leaf densities, senescing leaf biomass, and standing dead biomass. However, prolonged (> 1 growing season) altered inundation patterns, either by increased flooding (i.e., flooded plots) or increased ponding of water on the marsh surface (i.e., border control plots), may increase the rate of senescence.

Of the all the studies list in Table 40, only Christian et al. (1990) tried to correlate the senescence of J. roemerianus with hydroperiod. The range of average (standard deviation in parenthesis) times for the Cedar Island leaves to completely senesce from their maximum green heights was from 255 (98) days to 369 (61) days for a cohort tagged as young (< 30 cm) (Christian et al. 1990). My cohorts had shorter senescing times than Christian et al. (1990). The range of average (standard deviation) times to completely senesce from maximum green height for the 1994 cohorts was >185 (99) to >210 (144) days among the flooding treatments.

The senescing biomass on Cedar Island ranged from 247 g/m2 at the 1590 m station and to 723 g/m2 at the 50 m station. No significant correlation was found between senescing biomass and location although there was a general decline in senescence and decomposition from the edge of the marsh to its interior (Christian et al. 1990). Furthermore, at most of the stations on Cedar Island senescing biomass exceeded growing leaf biomass. The overall average (standard deviation) for senescing biomass on Cedar Island was 411 (108) g/m2 (Christian et al. 1990). I also found that for the most part the senescing biomass exceeded the growing leaf biomass for Brownsville marsh. The range of average senescing biomass among the flooding treatments for my study was 33.18 g/m2 to 506.57 g/m2.

I found a significant effect of flooding on the 1995 senescing biomass with the flooded plots having significantly higher biomass than the border control and control plots. These differences in results between the Cedar Island study and my research may be linked to geographical differences, differences in typical hydrodynamics, and short term responses to stress. Virginia is close to the northern limit for large stands of J. roemerianus. Therefore, the J. roemerianus in Virginia may have a greater level of climatic stress than the J. roemerianus in North Carolina so that any additional stress from flooding may be harder for the Virginia population to respond to and recover from than the same stress in North Carolina. The differences in normal hydrology also may account for the differences between the two studies. The daily flooding of a J. roemerianus population that is not normally inundated or has standing water on it may stress the plants causing them to senesce.

6.1.3. Increased inundation does not affect the growth of S. patens and D. spicata.

As compared to other studies, S. patens biomass in my study was higher than those reported for other marshes, and the D. spicata biomass was similar to a more limited sampling of other marshes (Table 40). The range of S. patens total biomass in the flooding treatments was 119 to 439 g/m2 for living biomass and 433 to 821 g/m2 for total biomass. Cooper & Waits (1973) found that a salt marsh in North Carolina had a S. patens total biomass range of 230 to 400 g/m2. Nixon & Oviatt (1993) calculated that a marsh in New England had a S. patens total biomass of 430 g/m2. The range of D. spicata biomass from my research was 31 to 219 g/m2 for living biomass and 110 to 344 g/m2 for total biomass. Cooper & Waits (1973) reported that the range of D. spicata total biomass in a North Carolina marsh was 190-240 g/m2. Hook's (1991) total biomass values for S. patens (3.0-21.1 g/m2) and D. spicata (0.2 g/m2) are much lower than other studies. However, this is probably the result of Hook preferentially sampling J. roemerianus dominated areas of the marsh. The S. patens and D. spicata total biomass values collected in my research from the J. roemerianus dominated areas ranged from 0.65 to 168 g/m2 and 2.64 to 104 g/m2, respectively.

Increased inundation negatively affected the aboveground biomass of S. patens in 1994 and 1995 and the biomass of D. spicata in 1995. The 1994 living S. patens biomass in flooded and border control plots in J. roemerianus dominated areas was significantly less than the living biomass in the control plots. For areas dominated by S. patens and D. spicata, the living S. patens biomass was significantly higher in the border control plots than the flooded plots. The total 1995 S. patens biomass in the border control plots of the J. roemerianus dominated areas was significantly higher than the biomass of the flooded plots but not significantly different from the control plots. Furthermore, the 1995 living S. patens biomass in the border control plots was significantly higher than the flooded and control plots. The 1995 living D. spicata biomass in the control plots from the J. roemerianus dominated areas was significantly higher than the living biomass from the flooded and border control plots. The 1995 total D. spicata biomass from the control plots in J. roemerianus areas was significantly higher than the total biomass in the flooded plots. From these results, I conclude that increased inundation decreases the aboveground biomass of S. patens. Furthermore, aboveground growth of S. patens is enhanced in areas where water ponds on the surface (i.e., border control plots). Increased frequency of inundation also negatively affected the growth of D. spicata. However, since the significant differences occurred only in the J. roemerianus dominated areas after the removal of wrack, I believe that inundation inhibits the colonization of bare areas by D. spicata. I will address this idea in more detail under the wrack and flooding-wrack interaction hypotheses.

Few studies have evaluated the effects of increased inundation on the aboveground biomass of S. patens and D. spicata. I am not aware of any other study that evaluated the effects of increased inundation on these two species in Virginia salt marshes although Mendelssohn & Marcellus (1976) studied community production in three different Virginia marshes that had different salinities. Mendelssohn & Marcellus (1976) found higher productivity in two low salinity (4 and 10 ppt) marshes than in a high salinity marsh (30 ppt). However, extensive stands of S. patens and D. spicata were only found in the 10 ppt marsh with S. alterniflora being a dominant component of all three marshes (Mendelssohn & Marcellus 1976).

In this research, increased inundation had a greater effect on the aboveground biomass of S. patens than on the biomass of D. spicata. Several studies have shown that S. patens has a reduced ability to supply oxygen to belowground organs during inundation (Gleason & Zieman 1981, Bertness 1991b) even though increased soil waterlogging does increase aerenchyma development (Burdick & Mendelssohn 1987). Increased flooding and reduced soil redox conditions in a Mississippi Delta marsh were the primary stressors affecting S. patens productivity unless salinity was extremely high (Bandyopadhyay et al. 1993). In a greenhouse experiment, the increased depth of flooding significantly reduced the growth of S. patens. From this and other studies, I can conclude increased tidal inundation decreases the production of S. patens. This reduction in S. patens production is probably the result of a reduced ability to aerate its roots (Gleason & Zieman 1981, Bertness 1991b) or its sensitivity to increased salinities (Pezeshki et al. 1987, Pezeshki & DeLaune 1993, Broome et al. 1995). I did not directly address these factors in my research. The fact that the border control plots had the highest S. patens biomass values may result from the border control plots mimicking higher elevations of the marsh. At elevations higher than where my experimental plots were located, water, either from precipitation or tides, will remain on the surface longer because of the increased distance from the creek and the low slope of the land in most areas (Hmieleski 1994).

Like S. patens, D. spicata is able to supply some oxygen to roots during anoxic soil conditions (Cooke et al. 1993). Furthermore, in a New England salt marsh, D. spicata, as well as S. patens, showed higher growth in the high marsh than in the low marsh when the two species were without competitors (Bertness 1991a). The only study I found which looked at the effects on altered inundation on D. spicata production was Zedler et al. (1980). They found the increases in production by D. spicata and other species when tidal inundation was eliminated and suggested this was the result of (1) the lowering of salinities in the marsh by freshwater runoff and (2) the retention of nutrients within the marsh. More work needs to be conducted on D. spicata in order to determine its limitations to increased inundation. My research clearly showed increased saltwater inundation will inhibit the colonization of bare areas by D. spicata. However, this inhibition may be the result of (1) the increase in the ground water level, and therefore a decrease in soil oxygen, (2) the increase in pore water salinities, as the flooded plots had significantly higher salinities than the border control and control plots (Appendix D), (3) a combination of these two factors, or (4) the effects of other factors which I did not measure.

6.2. Effects of Wrack Deposition

6.2.1. Wrack deposition does not affect the aboveground production of plants.

Six months of wrack deposition significantly reduced the aboveground biomass of the three major plant species (i.e., J. roemerianus, S. patens, and D. spicata) of the experimental plots. The fact that wrack deposition did not significantly impact the minor species (i.e., S. alterniflora and Scirpus sp.) is probably more the result their low initial abundance in the plots. Therefore, in contrast to increased inundation, wrack deposition did not invoke a species specific response in this study.

Although several researchers have studied recolonization after wrack deposition or other disturbances in high salt marsh communities, few have recorded how much plant material is actually killed by wrack deposition. Three studies that have addressed this question in addition to my own work are Reidenbaugh & Banta (1980) in a Virginia S. alterniflora marsh; Hartman (1984) in a New England marsh dominated by S. alterniflora, S. paten, and D. spicata; and Knowles et al. (1991) in an irregularly flooded J. roemerianus marsh in North Carolina. In all of these studies as well as my own, wrack deposition dramatically reduced the aboveground biomass of the plants it covered.

Reidenbaugh & Banta (1980) found that wrack deposition in the low marsh lasting more than a few weeks in the spring caused complete devegetation. In contrast wrack deposition in the mid-marsh usually caused only a partial devegetation. Partial or complete diebacks occurred in the highest elevations resulting in bare soil and low S. alterniflora densities (Reidenbaugh & Banta 1980). Furthermore, the amount of devegetation by wrack varied annually in the S. alterniflora marsh (Reidenbaugh & Banta 1980). In conclusion, they stated the degree of devegetation depends on the marsh elevation and the time of the year of the deposition with the low marsh being the most sensitive area in the marsh and the spring being the most sensitive time of the year.

Hartman (1984) studied the effects of the length of time wrack deposition occurred and the size of the deposition on salt marsh plants. Unlike my research that showed a significant reduction of all plant species after six months of wrack deposition, Hartman (1984) found species specific responses to wrack deposition. Four months or more of wrack deposition dramatically reduced the aboveground biomass of S. patens. However, up to 12 months of wrack deposition did not significantly affect the aboveground biomass of D. spicata (Hartman 1984). Furthermore, S. alterniflora and S. patens coverage decreased within increasing wrack size. In contrast, D. spicata coverage was unaffected by the wrack, and Salicornia europea coverage increased when the coverage of the dominant species decreased (Hartman 1984). She also measured sulfide concentrations under the wrack and found higher sulfide concentrations in the wrack areas than in the nonwrack areas. Knowles et al. (1991) found similar results in North Carolina with sulfide levels being 2.5 times greater in wrack areas than in nonwrack areas. The increased death of plant material appeared to decrease the rate of sulfide oxidation (Hartman 1984). In conclusion, Hartman (1984) stated that the effects of wrack deposition depended on the season during which the deposition occurred and the plant species under the wrack. Furthermore, at least four months of wrack coverage were necessary to significantly alter the vegetation. The effect of wrack deposition was similar throughout the marsh.

The differences between Hartman's study and my work may be the result of several factors. First, we conducted our respective studies in two different marshes. The two marshes may have different proportions of the dominant species. Furthermore, Hartman (1988) examined naturally placed mats of wrack on the marsh surface. In contrast, my study involved experimentally placing wrack on top of the plants. Therefore, the impact of the wrack on the plants may have not been equivalent between the two studies.

Knowles et al. (1991) studied the effects of wrack deposition in the irregularly flooded J. roemerianus marsh on Cedar Island, North Carolina. They experimentally placed wrack on the marsh surface in three different areas of the marsh that were at different distances from the estuary. Wrack was removed after 6 and 12 months. Senescence of J. roemerianus under the wrack began after two months of deposition. In zone 1, which was closest to the estuary, no growing J. roemerianus leaves were observed under the wrack during the experiment. In zone 2, some J. roemerianus leaves managed to survive the deposition by growing up through the wrack. Furthermore, most of the surviving J. roemerianus leaves were located on elevated hummocks. However, only 21 % of the area under six months of wrack deposition was covered by J. roemerianus and only 1 % after 12 months of wrack deposition. The S. patens from the 12 months of deposition in zone 2 had the highest survivorship at 10 %. Wrack killed the aboveground parts of S. patens, but regrowth was able to occur from the belowground rhizomes (Knowles et al. 1991). In the interior of the marsh (zone 3), J. roemerianus coverage was 1-6% for the 6 month treatments and 2% for the 12 month treatments. I also found a dramatic decrease in J. roemerianus after six months of wrack deposition.

6.2.2. Wrack deposition does not affect the vegetative regrowth of a plant community.

Vegetative analysis showed a significant change in ground cover after the removal of wrack. The effects of the wrack deposition were noticeable in the J. roemerianus dominated areas and less so in the areas dominated by S. patens and D. spicata. J. roemerianus leaf densities and aboveground biomass did not recover to pre-wrack levels after one growing season. Furthermore, for the J. roemerianus leaves, there were significant differences among the 1995 leaves tagged in the nonwrack areas and the post-wrack areas for the survivorship data and the ANPP calculations. The rate of growth and the number of cohorts per year for J. roemerianus leaves were higher in post-wrack areas than in nonwrack areas. These differences between the post-wrack and nonwrack cohorts may be the result of a decrease in competition for resources (i.e., light, nutrients) in the less dense post-wrack areas. The low ANPP for the J. roemerianus leaves in the post-wrack was the result of the low aboveground biomass in those areas and not because of slow growing leaves. In contrast to J. roemerianus, the aboveground biomass of S. patens and D. spicata did recover after the removal of wrack. The aboveground S. patens biomass was not significantly different between the nonwrack and post-wrack areas in 1995. The living D. spicata biomass in the post-wrack areas dominated by S. patens/D. spicata was significantly higher than the living D. spicata biomass in the nonwrack areas.

Therefore, I conclude J. roemerianus production is still significantly lower one year after the removal of wrack because of the low numbers of leaves and not because of a slower growth rate. Furthermore, S. patens and D. spicata are able to recover from wrack deposition after one growing season with D. spicata biomass actually being higher in the disturbed areas. It is also noteworthy that S. alterniflora biomass samples were only collected in nonwrack areas, and Salicornia sp. was found only after wrack deposition with most biomass in the post-wrack areas.

Several researchers have studied the recolonization of bare areas after wrack deposition (Reidenbaugh & Banta 1980, Hartman 1984, 1988, Ellison 1987, Bertness & Ellison 1987, Knowles et al. 1991, Shumway & Bertness 1992, Bertness & Shumway 1993). However, most of the research was conducted in New England salt marshes. All of the studies as well as my own work support the idea that recolonization of bare areas will begin within the first growing season after the disturbance. Bare areas created on the marsh surface by wrack are usually not permanent. Recolonization of bare areas usually begins within the first growing season after the removal of wrack. Within a few years, vegetation will cover most bare post-wrack areas.

Even after the removal of wrack, the production of some species may remain low. Reidenbaugh & Banta (1980) found substantial short-term reductions in S. alterniflora production after wrack deposition. Hook (1991) concluded that differences in J. roemerianus production among sites were greatest when factors such as wrack deposition disturb the plants. I also found a reduction in production based on the amount of aboveground biomass for J. roemerianus after the removal of wrack deposition.

Most recolonization of bare areas is accomplished vegetatively and not via seed germination because of low numbers of viable seeds and unfavorable germination conditions (i.e., high salinities) for most salt marsh species (Hartman 1984, 1988, Knowles et al. 1991, Shumway & Bertness 1992). In a Massachusetts salt marsh, vegetative expansion of S. alterniflora accounted for most of the recolonization of the open patches although Salicornia spp. colonization occurred in some areas via seed germination (Hartman 1984, 1988). In contrast, D. spicata and S. patens dominated the recolonization of post-wrack areas in my study. The differences in results are probably related to the difference in the dominant species. In Hartman's marsh, S. alterniflora and S. patens were the dominant species while the marsh within which I worked was dominated by S. patens, D. spicata, and J. roemerianus. The recolonization of small patches in the Massachusetts marsh was controlled primarily by the proximity of S. alterniflora and its vegetative growth abilities (Hartman 1988). If wrack only kills the aboveground plant material, Hartman (1984) suggested that bare patches will return to pre-wrack conditions within two growing seasons for areas dominated by S. alterniflora and S. patens.

In a Rhode Island salt marsh, D. spicata and S. alterniflora were determined to be more wrack tolerant than other species. Therefore, these two species were able to regrow in post-wrack areas (Bertness & Ellison 1987). However, in contrast to Hartman (1984, 1988), D. spicata, and not S. alterniflora, dominated colonization in Bertness & Ellison's study (1987) and in this study. D. spicata is a rapid colonizer, but dominant species can competitively displace it within three to four years (Bertness & Ellison 1987). Further studies demonstrated that S. patens and D. spicata dominate the colonization of post-wrack areas where J. gerardi was dominant before deposition (Bertness & Shumway 1993). In my research, S. patens and D. spicata also colonized the areas that were previously dominated by J. roemerianus.

From work in Rhode Island, it was concluded that Salicornia europaea seedlings often occur in bare areas (Ellison 1987, Shumway & Bertness 1994). In 1995, Salicornia sp. appeared in my experimental plots. Even though the wrack treatment was not statistically significant for this species, it is noteworthy that the post-wrack areas had 1.54 to 1.94 g/m2 of Salicornia sp. while the nonwrack areas had 0 to 0.02 g/m2 of Salicornia sp. (i.e., approximately 1 % of the post-wrack biomass values). The Salicornia sp. that appeared in my experimental plots also germinated from seeds because there was not any Salicornia sp. in or near the plots before the wrack deposition, and Salicornia sp. is not known to colonize vegetatively (Ellison 1987, Shumway & Bertness 1994).

Patch size is important in determining how quickly an area will be revegetated (Hartman 1984, 1988, Shumway & Bertness 1994). Shumway & Bertness (1994) hypothesized that competition controls the colonization of small patches (0.1 m2 areas) while the colonization of large patches (1.0 m2 areas) fosters facilitation. The physical conditions of a patch determine the type of interaction (competition or facilitation) controlling the plants. The larger patches may develop higher salinities than the smaller patches and, therefore, be a more stressful environment and take longer for colonization to occur within them (Shumway & Bertness 1994). Slow rates of colonization may result in changes in the microtopography the open areas. The lack of vegetation in the open areas decreases the amount of peat accumulation and increases the amount of erosion (Hartman 1988, Brinson et al. 1995). Therefore, bare areas may develop into marsh potholes (Brinson et al. 1995). Each of the post-wrack areas in my experiment was approximately 1.5 m2, which may have resulted in harsh physical conditions for colonization (Shumway & Bertness 1994). Furthermore, microtopographic changes may have occurred in the post-wrack areas that were not fully recolonized.

In the Cedar Island marsh, recolonization of the bare areas was slow with S. patens being the primary colonizer. Once S. patens was established in an area, J. roemerianus growth in that area was difficult, allowing non-J. roemerianus species dominated in such areas for years (Knowles et al. 1991). J. roemerianus colonization that did occur at Cedar Island was dominated by tillering. However, seedlings were observed on elevated hummocks in interior areas. In a greenhouse experiment, J. roemerianus seeds collected from Cedar Island were viable but germination was significantly reduced when salinities approached 20 ppt. Therefore, the hummocks probably had lower salinities than other areas of the marsh (Knowles et al. 1991). I did not observe any germination of J. roemerianus in my plots.

Most researchers demonstrate that secondary bare soil patches may persist for two or more years, but most are eventually revegetated (Reidenbaugh & Banta 1980). The rate of recovery is related to the size of the patch (Hartman 1984) and the type of vegetation present in the marsh (Hartman 1984). The dominant plants recolonizing an area depend on the pre-wrack plant composition of the area. In the Virginia marsh where I conducted my research, D. spicata dominated the regrowth after wrack deposition, especially in the areas that were previously dominated by J. roemerianus. S. patens also reclaimed areas where it was dominant before the wrack and had a limited ability to colonize the areas previously dominated by J. roemerianus. J. roemerianus was not able to recover from wrack deposition within one year. Therefore, in contrast to the non-species specific effect of wrack deposition, the regrowth and colonization of bare patches after the removal of wrack is a species-specific response.

6.3. Combination of Increased Inundation and Wrack Deposition

6.3.1. Increased inundation and wrack deposition are not interacting stressors.

The highly significant effect of wrack deposition on plants probably masked most interactions between increased inundation and wrack deposition in 1994. However, in 1994, there were two significant interactions that were supported by the significant values for flooding treatment and wrack treatment by themselves. First, for the total 1994 biomass collected in the areas dominated by J. roemerianus, the nonwrack areas of the border control plots had significantly higher biomass values than the nonwrack areas of the flooded and control plots. This interaction was probably the result of the high amount of standing dead J. roemerianus in the border control plots when the experiment was set up and not an additive or multiplicative effect of the flooding and wrack treatments on the plants.

The flooding-wrack interaction term also was significant for the living 1994 S. patens biomass in the areas dominated by S. patens and D. spicata. The nonwrack areas of the flooded plots had significantly less biomass than the nonwrack areas of the border control and control plots. The wrack areas of the flooded, border control, and control plots were not significantly different from each other. This result supports the idea that the impact of wrack is greater than the impact of altered inundation on salt marsh plants.

6.3.2. Increased inundation does not affect the vegetative regrowth during the first growing season after wrack deposition.

In 1995, there were two significant flooding-wrack interactions for which flooding and wrack treatments were significant by themselves. First, the senescing J. roemerianus biomass in the areas dominated by J. roemerianus was significantly higher in the nonwrack areas of the flooded and border control plots than the nonwrack areas of the control plots. This result suggests prolonged flooding and ponding of water may stress J. roemerianus and, therefore, more leaves would be senescing than growing.

The other significant flood-wrack interaction was with the living D. spicata biomass in the J. roemerianus dominated areas. The living biomass in the post-wrack areas of the control plots was significantly greater than the biomass in all nonwrack areas and the post-wrack areas of the flooded and border control plots. Therefore, increased inundation and the ponding of water on the surface inhibit D. spicata from colonizing bare patches.

Few studies have examined the combined effects of increased inundation and wrack deposition. Knowles et al. (1991) found greatest reduction in plant cover by wrack deposition occurred in the areas closest to the estuary. This area had the longest hydroperiod of those examined (Hook 1991). The wrack crushed the plants underneath it down to the surface of the marsh, which was usually inundated. From my 1994 data, I can conclude that the severe impact of wrack deposition on the salt marsh plants masks any interaction with increased inundation. Even where I did have a significant flooding-wrack interaction in 1994, the significant differences were among nonwrack areas of the plots and not between nonwrack and wrack areas.

Flooding patterns after wrack deposition, however, have a significant effect on the recolonization of bare areas. Increased freshwater inundation decreased salinities and caused a shift from facilitative interactions among species to competition (Bertness & Shumway 1993). This increased growth enabled J. gerardi to competitively exclude S. patens and D. spicata from the bare area. J. gerardi was not able to colonize the areas that were not watered and had high to hypersaline conditions (Bertness & Shumway 1993). Furthermore, a reduction of salinities in the bare areas increased both the emergence and survival of seedlings (Shumway & Bertness 1992). In my study, the flooded plots were watered with saltwater which caused salinities to be significantly higher in the flooded plots than in the border control or control plots (Appendix D). Therefore, the significantly higher D. spicata colonization in the control plots of the areas previously dominated by J. roemerianus was probably the result of open areas with salinities lower than in the flooded and border control plots. However, the increased water levels in the flooded plots also may have played a role. Unfortunately, I am not aware of any papers that have studied the effects of increased inundation and salinity on D. spicata's ability to colonize bare soil patches.

6.4. Comparison between the Reference Juncus roemerianus Populations and the Experimental Controls

6.4.1. The growth dynamics of the reference population of J. roemerianus do not vary from the experimental control.

The experimental control plots differed more from the reference populations than they did from the experimental flooded plots. The maximum heights, leaf densities, and aboveground biomass of the reference J. roemerianus populations were significantly different from the experimental control plots. These results are in contrast to the results of the experimental inundation where no significant differences were found for maximum heights, leaf densities, and aboveground biomass among the three flooding treatments of the experiment. The rates of growth and senescence differed between the reference populations and the control plots and among the experimental flooding treatments. Therefore, a prolonged (> 2 y) history of increased inundation may eventually alter and reduce the production of J. roemerianus in the high marsh. Other area specific factors also may be involved in reducing the productivity of J. roemerianus.

Christian et al. (1990), Hook (1991), and my research were all two year studies on the production of J. roemerianus among different hydrological regimes. As I discussed in detail already, none of these studies showed a direct correlation between increased inundation and J. roemerianus production for all parameters measured. However, some statistically significant differences were found among sites with different flooding regimes after two years of research (Christian et. al 1990, Hook 1991, This thesis). My reference population of J. roemerianus is one of four sites that Robert Christian and Mark Brinson have been monitoring in Brownsville for the past five years. Their five year study has recorded differences in microtopographic changes, ground cover, and plant biomass among sites and in some cases, over time (Brinson & Christian 1995). Brinson et al. (1995) described the area of the marsh where my reference population is located as a mineral low marsh zone. Furthermore, Christian & Brinson (personal communication) have noted a decrease in J. roemerianus distribution in this low marsh area over the past five years. Since I found a greater difference between the experimental control plots and the reference population than between the control plots and the flooded plots, the lack of correlation between inundation frequency and J. roemerianus population may be an artifact of the relatively short time periods of previous studies and this current one. Long-term increases in tidal inundation probably do eventually cause an overall decline in J. roemerianus especially if other stressors are involved (i.e., wrack deposition).

6.5. Shading Experiment

6.5.1. Shading does not promote or inhibit the growth of J. roemerianus or other marsh species.

Shading did not promote or inhibit the growth of J. roemerianus. However, this experiment did suggest that shading may inhibit the growth of species other than J. roemerianus. Therefore, the shading of the ground by taller, older J. roemerianus leaves benefits the shorter, younger leaves indirectly by reducing competition from other plant species. Several studies in a Rhode Island marsh have shown J. gerardi is able to outcompete S. patens and D. spicata when the salinities are not extremely high (Bertness & Ellison 1987, Bertness 1991a, Bertness & Shumway 1993, Shumway & Bertness 1994). However, the reason for J. gerardi outcompeting other species is not known. One possible explanation is that J. gerardi shades its competitors therefore limiting light availability. Ellison (1987) found S. europaea does very well in open patches but is outcompeted for light when other species invade the patches. Perhaps S. patens and D. spicata also are sensitive to shading by the taller Juncus spp., while Juncus spp. do fine under a range of light conditions. This idea of Juncus spp. being able to outcompete other species by limiting light availability deserves further research.

7. CONCLUSIONS

An increase in sea level could result in increased inundation and wrack deposition in the high marsh community (Hayden et al. 1992, Brinson et al. 1995). Increased flooding by tidal waters would result in longer periods of waterlogging in soils (Bertness 1991b, Nyman et al. 1993) and higher salinities (DeLaune et al. 1987). Wrack deposition would result in the death of plants and the creation of bare areas (Reidenbaugh & Banta 1980, Hartman 1988, Knowles et al. 1991, Brinson et al. 1995). Erosion may occur in bare areas that are not rapidly colonized, which may result in the area developing into a marsh pothole (Hartman 1988, Brinson et al. 1995). Both increased inundation and wrack deposition are stressors that may lead to a differential change in productivity of native species (Linthurst & Seneca 1980, Reidenbaugh & Banta 1980, Seneca et al. 1985, DeLaune et al. 1987, Groenendijk et al. 1987, Hartman 1988, Christian et al. 1990, Bertness 1991b, Hook 1991, Knowles et al. 1991, Strakosch 1992, Nyman et al. 1993). This differential response of productivity may change the plant community structure of a marsh (Adams 1963, Warren & Niering 1993).

Inundation is a normal stressor in many marshes, and sea level is rising slowly. Therefore, most saltmarsh plants may be able to adapt to this normal, low impact stress (Lugo 1978, Brinson et al. 1995). Furthermore, the effects of normal stressors are not as immediately obvious as infrequent stressors and may be difficult to detect in short-term studies (Lugo 1978). However, my research and others have shown S. patens is highly sensitive to changes in inundation patterns (Gleason & Zieman 1981, Bertness 1991a & b, Bandyopadhyay et al. 1993) and salinities (Pezeshki et al. 1987, Pezeshki & DeLaune 1993, Broome et al. 1995). Furthermore, this study and others have found J. roemerianus has a mixed response to increased inundation, with a decrease in vigor or no response (Christian et al. 1990, Hook 1991). Longer monitoring of J. roemerianus has shown an overall decline of J. roemerianus patch size with regular inundation (Christian, personal communication). Therefore, I believe long-term increases in the frequency and duration of inundation will eventually decrease the production of J. roemerianus. The response of D. spicata to increased inundation suggests it may be more tolerant than S. patens to low level increases in flooding under normal circumstances. Increased inundation may, however, inhibit D. spicata from colonizing bare soil patches either because of increased anoxic conditions or because of increased salinity associated with increases in inundation. It is noteworthy that increased inundation did not increase S. alterniflora production in the experimental plots. My work showed that the short term effects of increased inundation are species-specific and do not cause the immediate invasion of new species. While I did observe a significant decline in one dominant species (S. patens) in the high marsh community, I did not see an increase in sub-dominant high marsh species (i.e., S. alterniflora). Therefore, I agree with Brinson et al. (1995) that gradual increases in inundation alone do not rapidly alter the composition of the high saltmarsh community.

Wrack deposition is an acute disturbance that dramatically reduces the productivity of most saltmarsh plants (Reidenbaugh & Banta 1980, Hartman 1988, Knowles et al. 1991, this thesis). After the removal of wrack, recolonization of bare areas will begin during the first growing season (Reidenbaugh & Banta 1980, Hartman 1984, 1988, Ellison 1987, Bertness & Ellison 1987, Knowles et al. 1991, Shumway & Bertness 1992, Bertness & Shumway 1993, this thesis). Except for the invasion by Salicornia sp., species already abundantly present in the community dominate the colonization of bare areas. S. patens and D. spicata are able to recover from wrack deposition within one growing season (Hartman 1984, 1988, Shumway & Bertness 1992, Bertness & Shumway 1993, this thesis). However, J. roemerianus and J. gerardi do not recover as quickly (Knowles et al. 1991, Shumway & Bertness 1992, Bertness & Shumway 1993, this thesis). Neighboring species (i.e., D. spicata and S. patens) will colonize post-wrack patches in areas previously dominated by Juncus spp. This shift in the dominant plant species in these areas to a non-Juncus species may last for several years. However, research has shown Juncus spp. may eventually reclaim the areas (Knowles et al. 1991, Shumway & Bertness 1992, Bertness & Shumway 1993). One mechanism that Juncus spp. may use to outcompete other marsh species is shading. As suggested by this thesis, non-Juncus spp. may be more sensitive to shading than Juncus spp.

The effect of more than one stressor on a community at the same time is often greater than the impact of each stressor alone (Lugo 1978, Turner 1988). My thesis researched the combined effects of increased inundation and wrack deposition on high salt marsh plants. Since the impact of wrack deposition greatly exceeds the impact of increased inundation, possible increased inundation and wrack deposition interactions are masked. However, after the removal of wrack from an area, increased inundation may inhibit the colonization of bare areas by some species. For example, D. spicata colonization was significantly lower in the flooded plots than in the control plots.

Increased inundation and wrack deposition interaction may occur through time. Wrack deposition causes devegetation of the marsh surface. If the wrack deposition occurs in an area of the high marsh where inundation is extremely rare, recolonization by high marsh species of the bare areas will occur quickly. However, if the wrack deposition occurs in area where flooding has been increasing, recolonization by high marsh species of the bare areas will be slow if it occurs at all. If wrack deposition continues to create open areas for colonization, and inundation continues to increase; an actual shift in plant community may occur as high marsh species, which tend to decline with increased flooding, are replaced by low marsh species (i.e., S. alterniflora) that are able to colonize the bare soil patches and tolerate the increased inundation. However, this series of events would occur over a long period of time, and other factors not addressed in this thesis may be involved. In conclusion, my research did demonstrate that increased inundation and wrack deposition may cause the redistribution of species within the high marsh community and the decline of some species.

8. APPENDIX A: DETAILS ON ELECTRICAL AND PUMPING SYSTEMS

The float switch connected to the pump was a Thomas Products LTD. model 4200 P/N 24251. The float switch closed the electrical system when the water level rose 0.5 m above mean sea level and activated the pump. In 1995, the float switches were replaced approximately every four to six weeks because of sediment build-up on the switches and corrosion of the switch wires.

Over the two years of the experiment, several different designs for pumping were used. Two different types of submersible pumps and two different types of relay boxes were used during the experiment. The first pump was a Cimaron 4 in (10.16 cm) SolarSub pump and was able to pump 7.57 L/min. This pump was installed on April 7, 1994, and quit working during the first week of July 1994. This pump used a solid state relay (Cyrdom relay). The second pump was a SolarJack 4 in SDS series and was able to pump 9.5 L/min. The SolarJack pump operated from July 23 to September 25, 1994, when it was removed for the winter (Taylor 1995). The SolarJack pump was reinstalled on March 10, 1995, for the second growing season and remained until October 26, 1995. The SolarJack pump used a solid state DC power converter (SolarJack PC10-28H).

In 1994, the power for the pump came from four 12 V DC batteries (Reliant GPR-1285). Two batteries were connected in series, and the two sets were wired in parallel circuits. Four solar panels (Siemens M55 Solar Electric Module) were used to recharge the batteries. The solar panels also were wired so that two panels were in series and the two sets were in parallel circuits. Each panel supplied 24 V DC to the batteries. A charge controller (Sun Selector M-8) controlled the charging of the batteries and was located between the solar panels and the batteries. A 2.44 m galvanized pipe, 10.16 cm in diameter, supported the solar panels. The solar panels and batteries were located half-way between Phillips Creek and the experimental plots. The wire used in the electrical system was 14 gauge.

In 1995, the power for the pump from March 10, 1995, to June 8,1995, was similar to the 1994 design. However, it was noticed that the batteries were not recharging fully and the amount of water being pumped onto the plots was declining. Furthermore, the relay box broke. Therefore, while waiting for a new relay box to arrive the pump was turned on and off manually during periods of daytime high tides. After the installation of a new relay box, the batteries were removed from the system, and the pump ran directly off the solar panels. This modification of the electrical system occurred on July 8, 1995, and remained through the end of the experiment. The relay box was damaged again between August 16 and 20, 1995, presumably by high water produced by Hurricane Felix. It also was realized that the pump was damaged. Therefore, a second SolarJack pump replaced the first SolarJack pump on September 16, 1995, and the new relay box was installed on October 14, 1995.

The pumping system was designed to deliver water to the flooded plots during high tides for approximately 3-4 hours. The flow rate of the Cimaron pump was 2.5 L/min. while the flow rate of the SolarJack pumps was 3.14 L/min. Water flowed through from the pump into a 3/4 in (1.9 cm) diameter hose and then into 3/4 in (1.9 cm) diameter PVC pipes. The PVC pipes ran for approximately 30 m into the middle of the experimental area. Two valved Y-joints split the flow of water into three directions, one running to each of the flooded plots. The PVC pipes going to each of the flooded plots were connected to a T-joint that diverted the water around to each side of the plots. A second set of T-joints was used at the middle of the either side of the plots. A vertical PVC pipe was connected to these T-joints and left open to the atmosphere to balance the water flow on both sides of the plots. A third set of T-joints diverted the water into both the J. roemerianus dominated area and the S. patens/D. spicata dominated area. The PVC pipes within the plots formed a rectangle. The pieces of PVC pipes within the plots had ten holes drilled into the top and bottom of the pipes to allow the water to flow out of the pipes and onto the ground. The holes were approximately 30 cm apart from each other.

9. APPENDIX B: SUMMARY OF Juncus roemerianus TAGGED LEAF DATA

The following tables list the sampling dates for the J. roemerianus tagged leaves and the means and standard deviations for the green and total heights for each cohort. Tables 41, 42, and 43 contain the green heights in the flooding, border control, and control plots, respectively. Tables 44, 45, and 46 contain the total heights in the flooding, border control, and control plots, respectively. Table 47 contains the green and total heights for the reference J. roemerianus populations. If a cohort was not measured on a particular date, I have placed an "NA" in the cohort's column for that date.

Table 41. Dates of J. roemerianus leaf measurements and the means and standard deviations (in parenthesis) of the green heights (cm) for each cohort (1-7) in the flooded plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
19.4 (5.2)
53.2 (9.5)
23 Apr 94
28.5 (9.6)
58.0 (11.8)
28 May 94
40.9 (19.7)
62.8 (17.4)
17 Jun 94
50.9 (24.5)
63.2 (21.9)
8 Jul 94
58.4 (29.6)
61.7 (27.9)
11 Jul 94
NA
NA
17.1 (4.3)
19 Jul 94
57.4 (32.3)
59.7 (30.6)
20.8 (4.8)
6 Aug 94
50.6 (38.1)
62.1 (25.9)
31.3 (6.9)
16 Aug 94
48.9 (40.3)
61.7 (25.5)
34.4 (12.1)
3 Sep 94
48.6 (41.4)
60.8 (31.1)
42.5 (15.0)
17 Sep 94
47.1 (42.0)
57.3 (31.8)
44.3 (16.3)
15 Oct 94
45.2 (42.2)
36.4 (36.2)
45.6 (21.9)
26 Nov 94
40.8 (41.0)
23.9 (34.1)
46.8 (22.7)
18 Dec 94
38.2 (39.6)
19.6 (30.3)
45.8 (23.6)
14 Jan 95
37.0 (38.8)
18.3 (29.1)
46.0 (23.5)
18 Feb 95
26.9 (27.8)
14.5 (26.4)
45.3 (22.3)
4 Mar 95
NA
NA
NA
17.4 (3.1)
16.1 (6.9)
10 Mar 95
24.5 (25.6)
9.0 (17.2)
44.9 (22.2)
NA
NA

Table 41, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
17.2 (25.3)
5.8 (11.4)
45.0 (23.0)
21.8 (4.2)
23.1 (5.9)
13 May 95
15.4 (24.8)
3.4 (9.5)
46.7 (25.9)
30.6 (7.9)
33.6 (13.2)
27 May 95
14.7 (24.3)
1.0 (3.9)
46.2 (27.6)
38.3 (10.6)
39.9 (15.3)
7 Jun 95
13.9 (24.7)
2.9 (8.5)
46.1 (29.1)
42.9 (13.1)
42.0 (19.1)
20 Jun 95
13.0 (22.8)
2.0 (5.5)
45.5 (29.7)
47.1 (15.4)
38.5 (27.4)
6 Jul 95
13.4 (24.0)
0.9 (3.6)
43.3 (31.8)
50.5 (20.3)
37.2 (32.4)
22.8 (5.0)
23.4 (3.8)
23 Jul 95
11.9 (23.8)
0
40.3 (33.7)
51.5 (22.3)
33.2 (35.7)
26.8 (5.9)
29.0 (9.3)
1 Aug 95
12.1 (24.2)
0
39.5 (34.1)
51.0 (23.7)
31.4 (35.8)
30.0 (8.2)
33.0 (10.4)
20 Aug 95
NA
0
29.9 (32.8)
51.1 (24.6)
28.6 (36.1)
33.5 (10.0)
36.7 (12.6)
2 Sep 95
9.0 (19.3)
0
31.2 (36.2)
50.1 (25.4)
27.4 (35.6)
34.5 (13.5)
38.9 (14.7)
16 Sep 95
7.7 (17.0)
0
30.7 (35.5)
48.4 (26.2)
26.5 (35.4)
37.2 (14.8)
40.9 (17.4)
30 Sep 95
5.9 (13.2)
0
29.8 (35.3)
46.2 (27.7)
25.9 (35.4)
39.7 (16.5)
41.2 (18.0)
14 Oct 95
3.3 (12.9)
0
25.1 (33.1)
41.6 (31.3)
24.5 (35.0)
43.2 (22.2)
42.1 (18.8)

Table 42. Dates of J. roemerianus leaf measurements and the means and standard deviations (in parenthesis) of the green heights (cm) for each cohort (1-7) in the border control plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
18.0 (4.8)
54.2 (10.8)
23 Apr 94
29.0 (5.0)
59.0 (10.7)
28 May 94
45.0 (7.1)
61.8 (12.9)
17 Jun 94
46.5 (19.6)
62.5 (14.9)
8 Jul 94
43.7 (28.4)
54.3 (26.7)
11 Jul 94
NA
NA
17.9 (4.9)
19 Jul 94
43.2 (30.4)
53.5 (27.2)
22.0 (5.6)
6 Aug 94
38.3 (33.6)
47.0 (31.5)
31.6 (7.4)
16 Aug 94
34.5 (32.6)
40.5 (29.7)
29.2 (8.4)
3 Sep 94
36.1 (33.1)
43.4 (30.3)
44.2 (9.6)
17 Sep 94
33.0 (31.7)
40.2 (29.4)
46.0 (9.3)
15 Oct 94
29.4 (30.8)
22.5 (28.8)
48.6 (9.3)
26 Nov 94
21.1 (28.5)
14.5 (20.5)
49.0 (10.8)
18 Dec 94
20.5 (26.1)
9.8 (18.5)
49.4 (9.8)
14 Jan 95
17.6 (24.4)
8.8 (17.0)
48.7 (9.8)
18 Feb 95
14.2 (19.4)
5.6 (14.7)
46.2 (9.4)
4 Mar 95
NA
NA
NA
16.0 (4.4)
14.9 (6.7)
10 Mar 95
10.4 (15.3)
5.1 (13.5)
45.5 (9.8)
NA
NA

Table 42, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
9.3 (13.9)
3.7 (14.5)
42.5 (14.9)
20.1 (5.2)
21.4 (8.2)
13 May 95
7.5 (14.5)
2.0 (7.6)
35.4 (16.8)
28.2 (9.4)
35.4 (15.5)
27 May 95
6.4 (11.0)
1.4 (5.4)
24.2 (19.8)
36.2 (12.3)
42.1 (22.7)
7 Jun 95
5.1 (10.8)
0
20.7 (20.4)
39.5 (14.4)
46.7 (26.1)
20 Jun 95
5.0 (10.5)
0
18.1 (21.5)
40.7 (22.2)
48.4 (28.8)
6 Jul 95
3.0 (8.0)
0
9.6 (20.9)
34.7 (29.5)
46.1 (31.9)
18.3 (6.1)
19.2 (4.1)
23 Jul 95
1.64 (6.4)
0
9.6 (20.5)
34.5 (30.0)
39.9 (32.1)
23.1 (6.0)
29.1 (5.1)
1 Aug 95
1.58 (6.1)
0
9.5 (20.9)
33.6 (29.4)
37.3 (33.5)
28.9 (9.0)
33.7 (6.9)
20 Aug 95
1.4 (5.6)
0
9.1 (20.0)
31.1 (28.4)
33.1 (31.1)
31.9 (7.8)
38.5 (12.9)
2 Sep 95
1.1 (4.2)
0
8.6 (19.5)
30.2 (28.5)
29.9 (30.1)
32.9 (9.6)
41.1 (14.3)
16 Sep 95
0.6 (2.5)
0
8.3 (18.8)
28.8 (28.0)
25.0 (28.3)
33.2 (12.2)
42.8 (15.1)
30 Sep 95
0.5 (2.1)
0
8.2 (15.5)
26.6 (28.3)
22.0 (26.0)
34.4 (13.2)
43.8 (16.8)
14 Oct 95
0.2 (0.8)
0
7.9 (17.1)
21.0 (25.6)
16.4 (24.0)
34.1 (16.1)
44.3 (17.9)

Table 43. Dates of J. roemerianus leaf measurements and the means and standard deviations of the green heights (cm) for each cohort (1-7) in the control plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
21.9 (3.7)
55.8 (8.0)
23 Apr 94
34.4 (7.2)
60.9 (9.6)
28 May 94
46.8 (23.0)
60.0 (21.1)
17 Jun 94
46.6 (29.8)
58.6 (22.1)
8 Jul 94
50.5 (33.3)
56.6 (25.1)
11 Jul 94
NA
NA
19.1 (5.4)
19 Jul 94
49.5 (32.8)
56.3 (25.0)
22.5 (6.5)
6 Aug 94
44.8 (33.6)
55.0 (27.5)
33.8 (11.2)
16 Aug 94
46.8 (35.0)
50.4 (29.4)
34.8 (18.7)
3 Sep 94
42.2 (37.1)
19.1 (5.4)
41.0 (22.9)
17 Sep 94
41.2 (36.5)
22.5 (6.5)
42.8 (23.8)
15 Oct 94
34.2 (34.3)
33.8 (11.2)
43.4 (28.3)
26 Nov 94
24.0 (29.6)
34.8 (18.7)
41.4 (29.0)
18 Dec 94
21.9 (28.1)
16.2 (22.0)
41.9 (29.4)
14 Jan 95
19.3 (26.6)
14.5 (20.2)
41.6 (29.2)
18 Feb 95
15.4 (22.0)
11.9 (17.5)
40.6 (28.5)
4 Mar 95
NA
NA
NA
18.5 (3.7)
14.9 (5.3)
10 Mar 95
13.7 (21.2)
7.0 (10.4)
38.5 (28.8)
NA
NA

Table 43, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
10.5 (18.4)
3.0 (8.4)
39.1 (27.7)
23.3 (4.9)
21.5 (6.0)
13 May 95
5.7 (11.9)
1.6 (4.7)
36.2 (27.5)
35.6 (9.5)
31.0 (18.0)
27 May 95
4.0 (9.2)
1.1 (3.0)
33.4 (29.0)
41.5 (17.0)
38.9 (23.5)
7 Jun 95
3.3 (7.9)
0.8 (2.1)
32.5 (28.8)
46.3 (20.9)
39.3 (26.2)
20 Jun 95
0.8 (3.0)
0
27.7 (29.7)
48.1 (24.8)
39.2 (27.7)
6 Jul 95
0
0
24.2 (29.9)
52.0 (28.8)
35.3 (30.6)
22.6 (5.7)
19.3 (5.4)
23 Jul 95
0
0
23.7 (29.9)
48.6 (33.8)
26.4 (32.1)
28.4 (7.0)
28.6 (6.6)
1 Aug 95
0
0
23.4 (30.4)
48.4 (34.9)
23.6 (32.2)
33.4 (7.0)
33.3 (8.3)
20 Aug 95
0
0
21.1 (29.1)
49.6 (35.0)
14.6 (24.5)
40.4 (7.9)
38.7 (12.4)
2 Sep 95
0
0
15.0 (26.8)
48.8 (33.9)
19.8 (29.2)
42.7 (9.7)
39.8 (16.8)
16 Sep 95
0
0
13.6 (26.2)
48.0 (34.0)
15.8 (27.0)
45.2 (11.9)
41.6 (17.7)
30 Sep 95
0
0
13.4 (25.8)
49.4 (33.5)
14.6 (26.3)
47.6 (13.5)
43.1 (18.5)
14 Oct 95
0
0
13.2 (25.3)
45.6 (32.9)
12.9 (24.7)
49.8 (15.9)
43.9 (19.3)

Table 44. Dates of J. roemerianus leaf measurements and the means and standard deviations (in parenthesis) of the total heights (cm) for each cohort (1-7) in the flooded plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
20.0 (5.4)
56.0 (10.6)
23 Apr 94
31.0 (5.6)
63.4 (10.8)
28 May 94
46.3 (11.5)
70.4 (13.7)
17 Jun 94
56.6 (16.0)
74.2 (15.1)
8 Jul 94
65.4 (20.8)
75.5 (16.8)
11 Jul 94
NA
NA
17.1 (4.3)
19 Jul 94
67.9 (21.8)
75.9 (17.3)
21.1 (5.0)
6 Aug 94
70.6 (23.3)
74.2 (19.0)
31.7 (7.0)
16 Aug 94
71.6 (24.2)
74.6 (18.5)
36.4 (8.2)
3 Sep 94
72.3 (24.9)
76.8 (19.2)
44.6 (10.9)
17 Sep 94
72.6 (25.2)
76.1 (18.9)
46.7 (12.0)
15 Oct 94
73.1 (25.7)
74.0 (17.0)
50.5 (14.1)
26 Nov 94
73.2 (25.7)
73.6 (16.5)
52.8 (15.4)
18 Dec 94
73.2 (25.7)
73.7 (16.4)
53.2 (16.5)
14 Jan 95
73.2 (25.8)
73.7 (16.4)
53.7 (16.6)
18 Feb 95
73.2 (25.8)
73.7 (16.4)
54.3 (16.2)
4 Mar 95
NA
NA
NA
18.4 (3.3)
19.0 (8.0)
10 Mar 95
73.2 (25.8)
73.7 (16.4)
54.6 (16.3)
NA
NA

Table 44, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
73.3 (25.8)
73.7 (16.4)
56.7 (17.6)
23.9 (4.0)
26.3 (7.6)
13 May 95
73.3 (25.8)
73.7 (16.4)
59.8 (20.1)
34.1 (5.7)
42.9 (8.1)
27 May 95
73.3 (25.8)
76.3 (18.7)
61.3 (21.1)
42.5 (7.2)
53.4 (8.5)
7 Jun 95
73.3 (25.8)
76.3 (18.7)
62.2 (22.2)
47.9 (8.4)
58.7 (10.2)
20 Jun 95
73.3 (25.8)
76.3 (18.7)
62.7 (22.4)
52.9 (9.5)
62.3 (13.1)
6 Jul 95
73.3 (25.9)
76.3 (18.7)
63.0 (22.9)
58.4 (10.9)
64.7 (15.7)
23.1 (4.7)
23.5 (3.9)
23 Jul 95
73.3 (25.9)
76.3 (18.7)
63.0 (22.9)
61.1 (11.9)
64.2 (16.5)
27.3 (5.8)
31.0 (5.6)
1 Aug 95
73.2 (25.8)
76.3 (18.7)
63.1 (23.0)
61.7 (12.1)
64.4 (16.8)
30.1 (6.5)
35.2 (5.9)
20 Aug 95
73.2 (25.8)
76.3 (18.7)
62.3 (23.9)
63.5 (12.9)
64.5 (16.9)
34.9 (8.4)
40.1 (7.1)
2 Sep 95
73.2 (25.8)
76.3 (18.7)
62.3 (23.9)
64.4 (13.4)
64.6 (17.0)
37.7 (9.9)
43.5 (8.1)
16 Sep 95
73.2 (25.8)
76.3 (18.7)
62.3 (23.9)
64.8 (13.9)
64.6 (17.0)
40.7 (10.6)
46.6 (9.2)
30 Sep 95
73.2 (25.8)
76.3 (18.7)
62.3 (23.9)
65.8 (14.1)
64.7 (17.2)
43.7 (11.8)
48.5 (10.0)
14 Oct 95
73.2 (25.8)
76.3 (18.7)
58.8 (23.8)
63.8 (13.6)
64.6 (17.1)
48.3 (16.8)
50.2 (10.6)

Table 45. Dates of J. roemerianus leaf measurements and the means and standard deviations (in parenthesis) of the total heights (cm) for each cohort (1-7) in the border control plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
18.8 (5.2)
58.3 (10.9)
23 Apr 94
30.3 (5.1)
64.7 (9.3)
28 May 94
47.9 (6.5)
70.7 (9.0)
17 Jun 94
54.7 (9.7)
72.6 (9.9)
8 Jul 94
58.4 (12.8)
73.6 (10.6)
11 Jul 94
NA
NA
17.9 (4.9)
19 Jul 94
59.7 (13.8)
73.9 (10.8)
22.0 (5.6)
6 Aug 94
61.0 (15.1)
74.0 (10.9)
31.6 (9.1)
16 Aug 94
59.5 (14.2)
74.0 (10.9)
29.2 (8.4)
3 Sep 94
61.8 (15.8)
74.0 (10.9)
44.2 (9.6)
17 Sep 94
61.8 (15.9)
74.1 (10.9)
46.0 (9.3)
15 Oct 94
61.9 (15.9)
74.1 (10.9)
48.6 (9.3)
26 Nov 94
61.9 (15.9)
74.1 (10.9)
49.0 (10.8)
18 Dec 94
61.9 (15.9)
74.1 (10.9)
51.5 (9.7)
14 Jan 95
61.9 (15.9)
74.1 (10.9)
51.7 (9.7)
18 Feb 95
61.9 (15.9)
74.1 (10.9)
51.8 (9.7)
4 Mar 95
NA
NA
NA
17.3 (4.8)
16.2 (6.9)
10 Mar 95
61.9 (15.9)
74.0 (10.9)
52.1 (9.4)
NA
NA

Table 45, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
61.9 (15.9)
74.0 (10.9)
53.5 (9.2)
21.9 (5.4)
22.9 (8.6)
13 May 95
61.9 (15.9)
74.0 (10.9)
56.2 (9.4)
32.1 (4.9)
41.1 (11.8)
27 May 95
61.9 (15.9)
74.1 (10.9)
57.6 (9.7)
40.3 (6.6)
51.0 (15.3)
7 Jun 95
61.9 (15.9)
74.1 (10.9)
58.1 (10.0)
44.8 (7.5)
57.7 (17.9)
20 Jun 95
61.9 (15.9)
74.1 (10.9)
58.1 (9.9)
50.5 (10.1)
62.2 (20.0)
6 Jul 95
61.9 (15.9)
74.1 (10.9)
58.2 (9.9)
53.1 (11.5)
64.8 (21.6)
19.0 (6.2)
19.4 (4.1)
23 Jul 95
61.9 (15.9)
74.1 (10.9)
58.2 (10.1)
54.0 (12.5)
64.9 (20.9)
23.6 (6.3)
31.5 (10.4)
1 Aug 95
61.9 (15.9)
74.1 (10.9)
58.2 (10.1)
55.1 (13.0)
66.0 (22.2)
30.1 (9.7)
34.7 (6.0)
20 Aug 95
61.9 (15.9)
74.0 (10.9)
58.2 (10.1)
55.7 (13.5)
66.5 (22.6)
33.6 (7.2)
41.5 (7.9)
2 Sep 95
61.9 (15.9)
74.0 (10.9)
58.2 (10.1)
56.1 (13.7)
66.7 (22.8)
35.7 (8.2)
44.8 (8.4)
16 Sep 95
61.9 (15.9)
74.0 (10.9)
58.1 (10.1)
56.1 (13.7)
66.6 (22.7)
38.0 (8.8)
48.0 (9.3)
30 Sep 95
61.9 (15.9)
74.1 (10.9)
58.1 (10.1)
56.2 (13.9)
66.6 (22.7)
40.5 (9.5)
51.0 (9.9)
14 Oct 95
61.9 (15.9)
74.1 (10.9)
58.1 (10.1)
56.2 (13.9)
66.7 (22.8)
42.8 (10.3)
53.0 (10.4)

Table 46. Dates of J. roemerianus leaf measurements and the means and standard deviations (in parenthesis) of the total heights (cm) for each cohort (1-7) in the control plots.

Dates
1
2
3
4
5
6
7
26 Mar 94
22.7 (3.4)
58.8 (8.7)
23 Apr 94
35.8 (5.7)
65.9 (8.8)
28 May 94
55.2 (12.3)
71.1 (8.2)
17 Jun 94
61.8 (16.3)
72.3 (8.1)
8 Jul 94
67.0 (20.4)
72.9 (8.3)
11 Jul 94
NA
NA
19.1 (5.4)
19 Jul 94
66.3 (21.5)
73.1 (8.4)
22.9 (6.0)
6 Aug 94
65.6 (22.5)
73.3 (8.5)
34.5 (9.9)
16 Aug 94
67.7 (23.4)
73.4 (8.6)
40.7 (12.2)
3 Sep 94
68.0 (23.7)
73.5 (8.6)
46.5 (14.4)
17 Sep 94
68.1 (23.8)
73.5 (8.6)
48.6 (15.3)
15 Oct 94
68.1 (23.8)
73.5 (8.6)
50.9 (18.9)
26 Nov 94
68.1 (23.8)
73.5 (8.7)
50.4 (19.6)
18 Dec 94
68.1 (23.8)
73.5 (8.7)
50.7 (20.9)
14 Jan 95
68.1 (23.8)
73.5 (8.7)
49.9 (21.6)
18 Feb 95
68.1 (23.8)
73.5 (8.7)
51.6 (21.5)
4 Mar 95
NA
NA
NA
19.4 (3.8)
17.3 (5.2)
10 Mar 95
68.1 (23.8)
73.5 (8.7)
51.2 (22.5)
NA
NA

Table 46, continued

Dates
1
2
3
4
5
6
7
14 Apr 95
68.1 (23.8)
73.5 (8.7)
53.5 (22.7)
24.9 (4.9)
25.3 (6.5)
13 May 95
68.1 (23.8)
73.5 (8.7)
54.2 (24.7)
38.1 (7.0)
41.6 (8.4)
27 May 95
68.1 (23.8)
73.5 (8.7)
56.5 (24.8)
46.3 (10.3)
51.4 (13.5)
7 Jun 95
68.1 (23.8)
73.5 (8.7)
56.8 (25.0)
51.9 (13.4)
56.0 (16.0)
20 Jun 95
68.1 (23.8)
73.5 (8.7)
57.1 (25.2)
56.7 (16.4)
60.3 (19.0)
6 Jul 95
68.1 (23.8)
73.5 (8.7)
57.4 (25.5)
62.6 (17.3)
62.4 (20.7)
22.8 (5.9)
19.6 (5.4)
23 Jul 95
68.1 (23.8)
73.5 (8.7)
57.4 (25.5)
66.5 (19.2)
61.2 (20.6)
29.9 (6.5)
29.8 (7.2)
1 Aug 95
68.1 (23.8)
73.5 (8.7)
57.5 (25.7)
70.0 (19.1)
61.3 (20.9)
33.8 (7.1)
34.3 (7.7)
20 Aug 95
68.1 (23.8)
73.5 (8.7)
57.6 (25.7)
69.1 (19.5)
58.4 (20.0)
41.3 (7.9)
44.3 (13.8)
2 Sep 95
68.1 (23.8)
73.5 (8.7)
57.7 (25.8)
68.8 (21.6)
59.5 (21.1)
44.7 (9.1)
47.4 (13.4)
16 Sep 95
68.1 (23.8)
73.5 (8.7)
57.7 (25.8)
68.9 (21.7)
59.5 (21.1)
48.4 (9.9)
50.2 (13.5)
30 Sep 95
68.1 (23.8)
73.5 (8.7)
57.7 (25.8)
71.8 (19.3)
59.7 (21.2)
51.7 (10.0)
52.0 (13.9)
14 Oct 95
68.1 (23.8)
73.5 (8.7)
57.7 (25.8)
72.1 (19.4)
59.7 (21.2)
56.0 (10.3)
53.9 (14.0)

Table 47. The dates J. roemerianus leaves were measured and the means and standard deviations (in parenthesis) for each reference cohort.

Green Heights in cm
Total Heights in cm
Dates
Cohort 4
Cohort 6
Cohort 4
Cohort 6
4 Mar 95
19.9 (4.1)
21.6 (4.2)
14 Apr 95
23.6 (7.3)
28.3 (5.7)
13 May 95
27.2 (17.3)
37.3 (21.1)
27 May 95
32.6 (21.1)
44.1 (11.1)
7 Jun 95
35.4 (24.1)
48.3 (13.5)
20 Jun 95
37.8 (27.1)
51.8 (15.6)
6 Jul 95
37.8 (30.2)
22.1 (6.5)
55.0 (17.9)
22.5 (6.4)
23 Jul 95
33.5 (32.0)
26.7 (8.0)
54.1 (18.8)
28.5 (7.6)
1 Aug 95
37.7 (32.7)
31.9 (6.7)
56.3 (19.3)
32.7 (6.5)
20 Aug 95
NA
NA
NA
NA
2 Sep 95
35.3 (33.6)
39.2 (9.1)
57.0 (20.3)
40.9 (8.0)
16 Sep 95
33.5 (33.9)
42.2 (12.2)
57.5 (20.9)
44.6 (9.4)
30 Sep 95
27.4 (31.8)
43.7 (12.7)
54.7 (19.4)
55.3 (18.7)
21 Oct 95
28.3 (31.1)
47.5 (13.8)
46.6 (9.5)
51.1 (11.0)

10. APPENDIX C: AMOUNT OF WATER PUMPED ONTO THE PLOTS

The record of the amount of water pumped onto the plots during the summer of 1994 is incomplete because of the number of times the pump was not in operation. Pumping occurred during 1994 from April 7 to the first week of July and from July 23 to September 25 (Taylor 1995). Taylor (1995) concluded that based on the predicted tide levels for Phillips Creek all afternoon high tides during June, all high tides during August, and only the week before the sampling period during September would the tides have been high enough to activate the pump. Pumping did not occur during most of July because the pump was not in operation (Taylor 1995).

Better records of the pumping activities were kept during the 1995 field season. Table 48 summarizes the amount of water pumped onto the plots during 1995. The pump was installed in 1995 on March 10 and was removed on October 26, 1995.

Table 48. Record of pumping activities for 1995.




Date


Time

On/Read



Off



Start



Stop
Amount

of Water

(gal.)



Gal / hr.
3/10/95
1:10 PM
N/A
49973
49973
0
3/11/95
10:25 AM
N/A
49973
49973
0
3/31/95
N/A
N/A
49973
49908
65
4/14/95
3:00 PM
N/A
49908
49908
0
4/15/95
10:55 AM
N/A
49908
49373
535
4/15/95
10:55 AM
11:35 AM
49373
49275
98
147
5/11/95
3:30 PM
N/A
49275
44736
4539
5/12/95
10:40 AM
N/A
44736
43862
874
5/13/95
11:50 AM
N/A
43862
42742
1120
5/27/95
1:12 PM
N/A
42742
41661
1081
6/4/95
2:45 PM
N/A
41661
41661
0
6/8/95
4:00 PM
6:25 PM
41661
41477
184
76
6/9/95
4:30 PM
8:20 PM
41477
41214
263
68.6
6/10/95
4:50 PM
9:12 PM
41214
40894
320
73.3
6/13/95
8:05 PM
10:00 PM
40894
40746
148
77.2
6/14/95
9:53 AM
2:00 PM
40746
40369
377
91.6
6/15/95
11:00 AM
12:38 PM
40369
40250
119
72.9
6/16/95
11:41 AM
1:23 PM
40250
40111
139
34.2
6/17/95
12:30 PM
2:48 PM
40111
39966
145
63
6/18/95
1:54 PM
3:33 PM
39966
39846
120
72.7
6/20/95
3:15 PM
6:05 PM
39846
39634
212
74.8
6/21/95
3:55 PM
N/A
39634
39634
0
7/6/95
3:00 PM
N/A
39634
37478
2156
7/7/95
4:55 PM
6:20 PM
37478
37380
98
69.2
7/8/95
4:45 PM
N/A
37380
37368
12
7/9/95
12:00 PM
N/A
37368
36801
567
7/9/95
N/A
N/A
36801
36157
644
7/19/95
3:00 PM
N/A
36157
32342
3815
7/20/95
5:50 PM
N/A
32342
31524
818
7/23/95
5:00 PM
N/A
31524
31069
455

Table 48, continued





Date



Time

On/Read




Off




Start




Stop


Amount

of Water

(gal.)




Gal / hr.
7/24/95
8:15 AM
N/A
31069
30902
167
7/25/95
9:55 AM
N/A
30902
30889
13
7/26/95
1:50 PM
N/A
30889
30880
9
7/28/95
3:30 PM
N/A
30880
30880
0
7/29-31/95
N/A
N/A
30880
30313
567
8/1/95
1:30 PM
3:00 PM
30313
30225
88
58.66667
8/2/95
1:30 PM
6:00 PM
30225
29929
296
8/7/95
12:00 PM
N/A
29929
28729
1200
8/8/95
N/A
N/A
28729
28308
421
8/11/95
1:00 PM
1:00 PM
28308
27138
1170
8/20/95
N/A
N/A
27138
24902
2236
10/14/95
24902
24740
10/21/95
Noon
N/A
24740
24699
41
10/26/95
N/A
N/A
24699
23255
1444
Total =
26,556 gal.
Mean =
75.32 gal./hr.

11. APPENDIX D: WELL WATER DEPTH AND SALINITY DATA FROM JUNE TO AUGUST 1995

PVC wells were placed in the middle of each plot in order to measure salinity and the change in water level within the plots. During the summer of 1995, Jedediah Tomkins served as a Research Experiences for Undergraduate fellow and collected these data. Jedediah measured well water depth with a meter stick and calculated it as depth below the ground surface. Salinity was measured in the field with a refractometer. Figures 20 and 21 show the water depth below the ground surface and salinity through time, respectively. I used a 3-way ANOVA with BLOCK, FLOODING TREATMENT, and SAMPLING DATE for the GLM to analyze the water depth and the salinity measurements taken in the plots. A least square means test was used to determine specific differences for block and flooding treatment. Because water depth and salinity were highly variable throughout the summer, specific differences among the sampling dates were not determined. For both the well water depth and salinity, the flooded plots were significantly greater than the border control plots and the control plots. Furthermore, the border control plots had significantly higher water depths and salinities than the control plots (Table 49). Therefore, the pumping of water onto the flooded plots and the wooden borders surrounding the flooded and the border control plots did cause a significant increase in ground water and salinity during the summer.



Fig. 12. Depth of water from the ground surface measured from wells in the experimental plots during the summer of 1995. (F = flooded plots, BC = border control plots, and C = control plots)



Fig. 13. Salinity measurements taken from the wells in the experimental plots during the summer of 1995. (F = flooded plots, BC = border control plots, and C = control plots)

Table 49. Results of GLM for well water depth and salinity measurements taken in the experimental plots during the summer of 1995. The specific significant differences were determined by least square means and are listed below the GLM values in parenthesis. A least square means test was not run on the sampling dates because of the large number of differences assumed to be present through time.

Block
Flooding Treatment
Sampling Date
Well Water Depth
< 0.01

(Y & Z > X)
< 0.01

(F> B > C)
< 0.01
Salinity
< 0.01

(Y > Z > X)
< 0.01

(F > B > C)
< 0.01

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