EXAMINING THE LINK BETWEEN MACROPHYTE DIVERSITY, BACTERIAL
DIVERSITY, AND DENITRIFICATION FUNCTION IN WETLANDS
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
The Degree of Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Janice M. Gilbert, B.E.S., B.Ed., M.E.S., M.S.
*****
The Ohio State University
2004
Dissertation Committee:
Professor Virginie Bouchard, Adviser Approved by
Professor Serita D. Frey, Co-adviser
Professor Olli H. Tuovinen
Professor Frederick C. Michel, Jr. Adviser
Environmental Science Graduate Program ABSTRACT
The relationship between aquatic plant (macrophyte) diversity, bacterial diversity, and
the biochemical reduction of nitrate (denitrification) within wetlands was examined.
Denitrification occurs under anoxic conditions when nitrate is reduced to either nitrous
oxide (N2O), or dinitrogen (N2). Although previous studies have identified physical and
chemical factors regulating the production of either gas in wetlands, the role that
macrophyte diversity plays in this process is not known. The central hypothesis, based
on the niche-complimentarity mechanism, was that an increase in macrophyte diversity
would lead to increased bacterial diversity, increased denitrification, and decreased N2O flux. This hypothesis was investigated in two mesocosm studies to control environmental conditions while altering macrophyte functional groups (FG) and functional group diversity. In Study #1, five macrophyte functional groups (clonal dominants, tussocks, reeds, facultative annuals, and obligate annuals) were each represented by two species.
Fifty-five mesocosms with 5-6 replicates of 0, 1, 2, 3, 4, or 5 macrophyte FG (0-10 species) were established in the spring of 2001 and sampled in August 2001, September
2001, and April 2002. In Study #2, the clonal dominants were removed and forty-eight mesocosms with 6 replicates of 0, 1, 2, 3, or 4 macrophyte FG (0-8 species) were established in May 2002 and sampled in August and September 2002, and April 2003. In both studies, in situ denitrification, denitrification potential, sediment and interstitial
ii water C pools, and bacterial biomass were measured. In Study #2, bacterial gDNA diversity using terminal restriction fragment length polymorphism (TRFLP) was also analyzed. Results showed no evidence of altered detrital C pools, denitrification flux, bacterial diversity or bacterial community composition due to macrophyte functional group diversity. However, distinct differences between individual macrophyte functional groups occurred. The tussocks and reeds exhibited higher denitrification function while the obligate annuals emitted significantly higher in situ N2O after nitrate addition. These results occurred despite no evidence for differences in bacterial diversity or bacterial community composition.
These findings suggest that macrophyte community composition rather than diversity plays an important role in regulating denitrification and N2O emissions, and therefore has potentially important implications for a number of environmental issues pertaining to wetland mitigation, water quality, and global climate change.
iii
DEDICATION
This dissertation is dedicated to my family who in numerous ways have made this long and important journey possible. Some are now with me only in spirit, Peter D. Fenton and Carl E. Stewart, but all have taken important turns as the wind beneath my wings.
Thank you.
iv
ACKNOWLEDGMENTS
I wish to thank my advisors Serita Frey and Virginie Bouchard for their time, guidance, encouragement, patience, and thought provoking discussions. I could not have found two more dedicated and interesting ecologists to be mentored by. You both taught me a great deal and I certainly grew under your tutelage.
I also wish to thank my two committee members Olli Tuovinen and Frederick Michel who both contributed significant time, input, and encouragement which greatly enhanced this research project.
I am indebted to numerous people for their technical support and expertise including
Jerome Rigot, Bert Bishop, Carl Cooper, Doug Beak, Jeanne Durkalski, and Dedra
Woner.
Heartfelt thanks to my friends and fellow graduate students for many hours of field and laboratory help as well as contributions to the research through ideas and stimulating conversations: Dan Fink, Aaron Friend, Lisa Gardner, Tanna Holtz, Katie Hossler,
Angelique Keppler, Mel Knorr, Rachel Lee, Becky Lippmann, Oor Nicomrat, Julie
Pearson, Kelly Powell, Pascal Puget, Sharon Reed, Gregg Sablak, Rod Simpson, Alba
Skorupa, Jamie Smialek, Sandrine Vandichele, Tonia White-Burford, the Waterman
v Farm Crew: Mark, Darren, Ken and Dave, and my office mate and fellow molecular warrior, Wendy Gagliano.
I would also like to thank 3 ladies in the School of Natural Resources office for their assistance, happy disposition, and encouragement throughout my time here, Mary
Emmenegger, Pat Patterson, and Pat Polczynski.
Many thanks to Rob McCartney and Mariana Asumendi at Kurtz Bros., Inc. for their help getting the mesocosm project started and with donations of soil. Thank you also to
Andy at Savko, and Bob Webb at Columbus Irrigation for their interest in this project, great savings on supplies, and helpful information.
Funding from the following sources was extremely appreciated: Environmental Science
Graduate Program, School of Natural Resources, OARDC Research Enhancement
Competitive Grants Program, Graduate School Research Alumni Award, and OSU
Presidential Fellowship.
And, last but certainly not least, I would like to thank profusely the following for their unending support, encouragement and help in ways too numerous to mention. Without you all, the completion of this dissertation would not have been possible: my fantastic family Enie, Greg, Sandy, Tom, Tanner, Nicole, Andrew, Nancy, Sam, Owen, Sharron,
Allan, Shelley, Brian, Joanne, Rob,Vivian, Connie, Ruth, the Deys, and the Stewarts; my wonderful friends Lisa Mutchler, Frenchie, Dave Culver, and the ‘Lorimer Lake Gang’.
vi VITA
Citizenship……………………..Canadian
1993……………………………Honours B.E.S., University of Waterloo
1994……………………………B.Ed, Brock University
1997……………………………M.E.S. Environmental Studies, University of Waterloo
2000……………………………M.S. Environmental Science, The Ohio State University
1995-1997……………………..Graduate Teaching and Research Assistant, University of Waterloo
1998-present …………………..Graduate Teaching and Research Associate, The Ohio State University
PUBLICATIONS
Research Publication
1. Gilbert, J.M., B.G. Warner, R. Aravena, J.C. Davies, and D. Brook. 1998. Mixing of floodwaters in a restored habitat wetland in Northeastern Ontario, Wetlands 9(1):106- 117.
FIELDS OF STUDY
Major Field: Environmental Science
vii TABLE OF CONTENTS
Page Abstract...... ii Dedication...... iv Acknowledgments...... v Vita...... vii List of Tables ...... x List of Figures...... xii
Chapters: 1...... Introduction...... 1 2. Examining the relationships between macrophyte functional groups, macrophyte functional group diversity, and denitrification in wetlands ...... 7 2.1 Abstract...... 7 2.2 Introduction...... 10 2.3 Methods...... 15 2.3.1 Study site and experimental design...... 15 2.3.2 Sediment and interstitial water C and N ...... 18 2.3.3 In situ denitrification...... 20 2.3.4 Denitrification potential ...... 22 2.3.5 Gas sample analysis ...... 23 2.3.6 Statistical analyses ...... 23 2.4 Results...... 24 2.4.1 Macrophyte functional group comparisons ...... 24 2.4.1.1 Interstitial water and sediment characteristics ...... 24 2.4.1.2 In situ denitrification...... 27 2.4.1.3 In situ denitrification with added nitrate...... 29 2.4.1.4 Denitrification potential...... 30 2.4.1.5 Denitrification flux per C pools ...... 31 2.4.2 Macrophyte functional group diversity comparisons ...... 39 2.4.2.1 Interstitial water and sediment characteristics ...... 39 2.4.2.2 In situ denitrification...... 44 2.4.2.3 In situ denitrification with added nitrate...... 48 2.4.2.4 Denitrification potential...... 50 2.4.2.5 Denitrification flux per C pools ...... 53 2.4.3 Factors influencing denitrification function...... 62 2.5 Discussion...... 66 viii 2.5.1 Macrophyte functional groups: C pools and denitrification ...... 66 2.5.2 Macrophyte functional group diversity: C pools and denitrification...... 73 2.5.3 Nitrous oxide flux ...... 78 2.5.4 Other factors...... 79
3. Testing the niche differentiation mechanism: The link between macrophyte functional group diversity, bacterial diversity, and denitrification function in wetland sediments...... 83 3.1 Abstract...... 83 3.2 Introduction...... 85 3.3 Methods...... 90 3.3.1 Experimental design...... 90 3.3.2 Bacterial diversity ...... 93 3.3.3 Bacterial community composition ...... 95 3.3.4 Denitrification function...... 95 3.3.4 C pools, macrophyte biomass and C:N composition...... 98 3.3.6 Statistical analyses ...... 99 3.4 Results ...... 102 3.4.1 Bacterial diversity...... 102 3.4.2 Bacterial community composition...... 105 3.4.3 Denitrification function...... 111 3.4.4 C pools, macrophyte biomass and C:N composition...... 113 3.4.5 Relationships between bacterial diversity and denitrification function, C pools, macrophyte biomass and macrophyte diversity...... 115 3.5 Discussion...... 117 3.5.1 Bacterial diversity ...... 117 3.5.2 Bacterial diversity and denitrification flux ...... 123 3.5.3 Bacterial community composition and denitrification...... 125 3.5.4 Diversity and stability...... 130 4.0 Conclusions...... 135
Bibliography ...... 139
Appendix A: Mesocosm data Study #1 and Study #2 ...... 161 Appendix B: TRFLP data ...... 167 Appendix C: Mesocosm design for Study #1 and Study #2 ...... 242 ix LIST OF TABLES Table Page
2.1 Physical and chemical characteristics of sediment used in mesocosms ...... 15
2.2 Species selected to represent macrophyte functional groups...... 17
2.3 Interstitial water and sediment characteristics for macrophyte functional groups, Study #1 ...... 26
2.4 Interstitial water and sediment characteristics for macrophyte functional groups, Study #2 ...... 27
2.5 Interstitial water and sediment characteristics, macrophyte functional group diversity treatments, Study #1 ...... 40
2.6 Interstitial water and sediment characteristics, macrophyte function group diversity, Study #2...... 41
2.7 Interstitial water and sediment parameters in relation to macrophyte functional group ...... 42
2.8 Relationship between macrophyte functional group diversity and in situ denitrification flux per unit DOC, labile C, bacterial C, root biomass, and total plant biomass...... 55
2.9 Relationship between macrophyte functional group diversity and denitrification potential flux per unit DOC, labile C, bacterial C, root biomass and total biomass ...... 59
2.10 Relationships between denitrification and C pools...... 64
2.11 Highest predictor variable for in situ denitrification and denitrification potential for each sampling period...... 65
x LIST OF TABLES cont’d Table Page
3.1 Physical and chemical characteristics of sediment used in all mesocosms ...... 91
3.2 Similarity of terminal restriction fragments between treatments and original sediment...... 104
3.3 Simpson’s reciprocal index for bacterial diversity within each treatment...... 105
3.4 Similarities in bacterial community composition within and between treatments and original sediment...... 106
3.5 Bacterial species/genera common to all replicates and treatments...... 108
3.6 Genera containing denitrifiers in each treatment...... 109
3.7 Denitrification gas flux per treatment...... 112
3.8 C pools and plant C:N ratios for functional groups and functional group diversity treatments...... 114
3.9 Spearman’s rank order for terminal restriction fragments regressed with denitrification gas flux, sediment and water C, macrophyte C:N, and macrophyte biomass for all treatments ...... 116
xi LIST OF FIGURES
Figure Page
1.1 Conceptual diagram ...... 4
2.1 Photograph of mesocosms at peak biomass, September 2001...... 16
2.2 In situ denitrification, macrophyte functional groups...... 28
2.3 In situ N2 and N2O after nitrate addition...... 29
2.4 Denitrification potential for each macrophyte functional group, Study #1 and Study #2 ...... 31
2.5 In situ denitrification per unit DOC, labile C, bacterial C and root and total plant biomass for Study #1 and Study #2 ...... 34
2.6 In situ N2 and N2O after nitrate addition for each macrophyte functional group per unit DOC, labile C, bacterial C, and root and total plant biomass ...... 36
2.7 Denitrification potential in each macrophyte functional group per unit DOC, labile C, bacterial C, and root and total plant biomass, Study #1 and Study #2 ...... 38
2.8 In situ denitrification per diversity treatment and as a function of the number of functional groups, Study #1 ...... 46
2.9 In situ denitrification per diversity treatment and as a function of the number of functional groups, Study #2 ...... 47
2.10 In situ denitrification with nitrate addition for each diversity treatment and as a function of diversity...... 49
2.11 Denitrification potential in each diversity treatment and as a function of diversity, Study #1...... 51
xii LIST OF FIGURES cont’d.
Figure Page
2.12 Denitrification potential for each diversity treatment and as a function of diversity, Study #2...... 52
2.13 In situ denitrification flux per unit DOC, labile C, bacterial C, and root and total plant biomass, Study #1 and Study #2...... 54
2.14 In situ N2 and N2O per unit DOC, labile C, bacterial C, and root and total plant biomass ...... 57
2.15 Denitrification potential in the macrophyte functional group diversity treatments per unit DOC, labile C, bacterial C, and root and total plant biomass, Study #1 and Study #2...... 60
3.1 Photograph of mesocosms, August 2002...... 92
3.2 Average terminal restriction fragments per treatment ...... 103
3.3 Pearson’s correlation dendrogram showing bacterial community similarity between treatments ...... 107
3.4 Number of identified genera within each treatment containing known denitrifier species...... 110
3.5 Suggested relationship between degree of microbial difference with habitat and species area curves for obtaining optimum microbial diversity...... 121
3.6 Variance in denitrification flux relative to macrophyte functional group diversity...... 132
3.7 Variance in bacterial diversity relative to macrophyte functional group diversity...... 133
xiii
CHAPTER 1
INTRODUCTION
The vast majority of the general public, and hence governing institutions, appear to
maintain purely anthropocentric perspectives that require a valuation of benefits provided
by natural systems in order to justify their protection. Such utilitarian views put the
impetus on scientists to demonstrate clear connections between ecosystem function and
the services that benefit the public at large. Although ecologists are in agreement that the
loss of species due to human activity is unacceptable, attempts to scientifically
demonstrate the importance of biodiversity for maintaining ecosystem health remain
elusive. As a result, a series of debates occurred in the late 1990’s and early 2000’s
among some leading ecologists when the findings of a few studies, demonstrating positive links between diversity and ecosystem function, were being used to influence
public policy (Naeem et al. 1999, van der Heijden 1999, Wardle 1999, Kaiser 2000,
Wardle et al. 2000a, Loreau et al. 2001).
From the large collection of studies attempting to link biodiversity and ecosystem
functions over the past decade and a half, five main theoretical mechanisms have been
proposed to explain the lack of cohesiveness in results. They are: 1) niche-
differentiation in which species within a community utilize available resources in a complementary fashion, and have a positive impact (Hooper 1998, Lawton 2000); 2) sampling effect where the addition of a strong competitor has a large positive impact
1 (Tilman et al. 1997); 3) inverse sampling effect whereby highly competitive species are
present which do not have a large effect (Hooper and Vitousek 1997, Engelhardt and
Ritchie 2001, 2002); 4) indirect sampling effect in which species facilitate the presence
of other species that have a positive influence (Chapin et al. 1997, Downing and Leibold
2002, Engelhardt and Ritchie 2001); and 5) averaging effect or null hypothesis where
there is no increase in ecosystem function with increasing diversity (Vitousek and Hooper
1994, Wardle et al. 1997, Laakso and Setala 1999).
The majority of biodiversity studies have focussed on terrestrial ecosystems such as grasslands or forests. Far fewer biodiversity studies have been conducted in aquatic ecosystems such as wetlands, although since the early 1980’s, research into the benefits that wetland ecosystems provide has been extensive. It is now well accepted that wetlands are among the most valuable and productive ecosystems on earth. They function as important carbon sinks and pollution buffers, they improve water quality and flood control, and as well, provide valuable wildlife habitat. Wetlands are important contributors to the economy through tourism and recreation and are intimately related to some of the world’s greatest environmental concerns such as freshwater supply, energy use, and the quality of our atmosphere (National Wetlands Working Group 2000). The acknowledged benefits provided by wetlands has lead to federal mitigation laws in the
United States requiring the replacement of naturally occurring wetlands that have been destroyed due to human activity. However, a recent report commissioned by the National
Research Council, has stated that mitigation wetlands exhibit far less macrophyte (aquatic plant) diversity than the natural wetlands they replace (Zedler et al. 2001a).
2 Macrophyte diversity within wetlands is known to impact wildlife diversity by providing a greater variety of food, resting, nesting, and staging habitat (Kent 1994,
Whitman et al. 1995, Kusler and Kentula 1998, Denny 1994, National Wetlands Working
Group 2000, Zedler et al. 2001b). What is not known, is how macrophyte diversity affects microorganism diversity and the microbially mediated processes that occur in wetlands such as the decomposition related function, denitrification.
Denitrification is an anaerobic process whereby denitrifying bacteria convert nitrate
- (NO3 ) to the gases nitric oxide (NO), nitrous oxide (N2O), and dinitrogen (N2) which are
subsequently released to the atmosphere. Nitric oxide is short-lived, however N2O is an important trace gas that, along with CO2 and CH4, influences the earth’s radiation balance
and global climate. Thus, considerable emphasis is currently being placed on
understanding the factors influencing the production of N2O. Recent evidence within
terrestrial ecosystems suggests that disturbance of natural vegetation communities
impacts denitrifier communities, and in turn, the ratio of N2O:N2 (Cavigelli and
Robertson 2000, 2001). No studies, of which this author is aware, have examined how
shifts in macrophyte diversity within wetlands influence the quantity and quality of
carbon sources, which in turn, may alter the composition of the denitrifier community and the relative production of N2O versus N2.
The objectives of this research were to determine the impact of macrophyte functional
group diversity on C pools, sediment bacterial diversity and denitrification in wetlands
(Figure 1.1). The central hypothesis, based on the niche-differentiation mechanism, was that a shift in macrophyte functional group diversity would significantly impact N2O and
N2 fluxes due to changes in the quantity and/or quality of plant biomass inputs into the 3 sediment C pool. It was also expected that significant differences between the individual
macrophyte functional groups in C pools and denitrification flux would be evident.
Aboveground Plant Biomass N2O, N2 sediment / water interface Belowground Plant Biomass
Detrital C Pools
Bacterial Diversity
Figure 1.1. Conceptual diagram of the link between macrophytes, detrital carbon (C) pools, bacterial diversity and denitrification flux in a wetland system.
This dissertation has two main chapters. Chapter 2 examines the link between macrophyte functional groups and functional group diversity on denitrification in two
studies. The first study included five macrophyte functional groups with two species
each representing clonal dominants, tussocks, reeds, facultative annuals, and obligate 4 annuals. The clonal dominants were strong competitors and high biomass producers.
Because of this result, any increase in denitrification across the diversity gradient could
be attributed to either niche-differentiation or a sampling effect (Tilman et al. 1997). A
sampling effect occurs when an ecosystem function increases with diversity due to the fact that a higher diversity system has a higher probability of containing a species with a large positive impact on the function measured. In the second study, the clonal
dominants were removed and detection of the niche-differentiation mechanism was
anticipated whereby species within a community utilize available resources in a complementary fashion, and have a positive impact on ecosystem functions (Hooper
1998, Lawton 2000). Neither mechanism was observed in the two studies, rather an averaging effect took place in which there was no increase in ecosystem function with increasing diversity (Vitousek and Hooper 1994, Wardle et al.1997, Laakso and Setala
1999). However, distinct differences between the macrophyte functional groups for
denitrification function were apparent. These main findings are discussed.
Chapter 3 examines the link between macrophyte functional groups and functional
group diversity with bacterial diversity and denitrification flux. This examination took
place in the second mesocosm study, without the clonal dominants. It included analysis
of the C pools, bacterial diversity and community composition, in situ N2O and N2 fluxes and denitrification potential in relation to the monoculture macrophyte functional groups and across the macrophyte functional group diversity gradient. It was determined that bacterial diversity and denitrification function were not affected by macrophyte functional group diversity. However, there were differences in the communities of
5 denitrifying genera and in denitrification fluxes between the macrophyte functional groups.
This research provides information pertinent to understanding the relationship between macrophyte functional groups, macrophyte functional group diversity, bacterial gDNA diversity and bacterial community composition with denitrification function. This knowledge may be used to inform scientists, policy makers and the general public about the positive and negative aspects of macrophyte diversity in freshwater wetland systems as it relates to problems associated with mitigation issues and global climate change.
6
CHAPTER 2
EXAMINING THE RELATIONSHIP BETWEEN MACROPHYTE FUNCTIONAL
GROUPS, MACROPHYTE FUNCTIONAL GROUP DIVERSITY AND
DENITRIFICATION IN WETLANDS
2.1 ABSTRACT
Aquatic plant (macrophyte) functional group diversity was manipulated in two
mesocosm studies to examine the link between biodiversity and function in wetland
sediments. Mesocosms were used instead of natural wetlands to control environmental
factors and consisted of 416.7 L oval tubs which were place in the ground at the
Waterman Agricultural and Natural Resources Laboratory, Ohio State University. The first study included 60 mesocosms with 5-6 replicates of controls (no plants), 5 macrophyte functional groups (FG) with two species each representing clonal dominants, tussocks, reeds, facultative annuals, and obligate annuals and randomly selected combinations of 2 FG, 3 FG, 4 FG and all 5FG. All mesocosms were filled with the same sediment and flooded with 7 cm of overlying water. In the second study, the clonal dominant FG was removed and there were 6 replicates per treatment for a total of 48 mesocosms. The central hypothesis was that a positive relationship between macrophyte functional group diversity and the decomposition related function, denitrification would occur. This hypothesis was based on the niche-complimentarity mechanism whereby
7 species within a community utilize available resources in a complementary fashion with a resultant positive impact on ecosystem processes. It was anticipated that there would be significant differences between the macrophyte functional groups in the quantity and/or quality of C pools. As the diversity of functional groups increased, it was expected that the variety of carbon substrates would also increase, thereby supporting a higher number
and diversity of microorganisms including denitrifying bacteria. As a result, increased
denitrification and decreased N2O flux was anticipated. Results showed no clear
evidence for increased bioavailable C or denitrification across the macrophyte functional
group diversity gradient in either study. However, some differences were apparent
between the individual macrophyte functional groups. The clonal dominant treatment
consistently showed significantly higher sediment labile C concentrations than all but the
-1 obligate annuals. At macrophyte peak biomass, values ranged from 288 µg CO2-C g
-1 dry sediment in the reeds to 339 and 327 µg CO2-C g dry sediment in the clonal
dominants and obligate annuals; respectively. However, the higher labile C was not
reflected in higher bacterial biomass or denitrification flux. For both studies, when
significant differences in denitrification flux were measured, the tussocks and reeds
consistently showed the highest values. In situ denitrification at macrophyte peak
-2 -1 biomass for Study #2 was lowest in the facultative annuals (658 µg N-N2 m day ) and
-2 -1 -2 obligate annuals (1679 µg N-N2 m day ) and highest in the tussocks (2148 µg N-N2 m
-1 -2 -1 day ) and reeds (2095 µg N-N2 m day ). Denitrification potential was significantly
different only in the second study with the reeds higher than all but the tussocks at 56.9
-2 -1 and 45.5 mg N-(N2 + N2O) m day ; respectively. The obligate annuals were
8 -2 -1 intermediate (43.4 mg N-(N2 + N2O) m day ), while the facultative annuals were lowest
-2 -1 (21.7 mg N-(N2 + N2O) m day ). In the second study, significantly higher N2O flux
-2 -1 was also observed from the obligate annuals at 4.8 mg N-N2O m day compared to
-2 -1 0.8 –1.1 mg N-N2O m day in the other macrophyte functional groups. This research
suggests that niche-complimentarity is not a mechanism linking macrophyte functional group diversity to denitrification within freshwater wetland sediments. The data overall supports the averaging effect whereby no increase in ecosystem function occurs with increasing macrophyte diversity. However, community composition appears to play a role since distinct differences were observed between the macrophyte functional groups for denitrification flux and the obligate annuals had significantly higher N2O flux.
9 2.2 INTRODUCTION
Concern over the escalation of habitat destruction and species extinctions due to human
activity has led to an increase in biodiversity studies since the early 1990’s. These
investigations provide some insight into the relationship between biodiversity and
ecosystem function; however, they have not exhibited consistently clear patterns. While some studies have detected direct links between increasing biodiversity and increasing ecosystem function (Vitousek and Hooper 1994, Tilman et al. 1997, Hooper and
Vitousek 1998, Naeem et al. 1999, Hector et al. 2000, Ghilarov 2000, Engelhardt and
Ritchie 2001, Tilman et al. 2001, Jonsson and Malmqvist 2003, Zak et al. 2003), others
have detected idiosyncratic relationships (Degens 1998, Mikola and Setala 1998,
Bardgett and Shine 1999, Nilsson et al.1999, Griffiths et al. 2000), or no relationships
(Naeem et al. 1994, Huston 1997, Wardle et al. 1997, Hector 1998, Laakso and Setala
1999, van der Heijden 1999, Wardle 1999, Kaiser 2000, Wardle et al. 2000a).
Five main theoretical mechanisms have evolved to explain the link between
biodiversity and ecosystem functions: 1) niche-differentiation in which species within a
community utilize available resources in a complementary fashion, and have a positive
impact (Hooper 1998, Lawton 2000); 2) sampling effect where the addition of a strong
competitor has a large positive impact (Tilman et al. 1997); 3) inverse sampling effect
whereby highly competitive species are present which do not have a large effect (Hooper
and Vitousek 1997, Engelhardt and Ritchie 2001, 2002); 4) indirect sampling effect in
which species facilitate the presence of other species that, in turn, have a positive effect
(Chapin et al. 1997, Downing and Leibold 2002, Engelhardt and Ritchie 2001); and 5)
averaging effect or null hypothesis in which there is no increase in ecosystem function 10 with increasing diversity (Vitousek and Hooper 1994, Wardle et al.1997, Laakso and
Setala 1999).
The majority of biodiversity related research has focussed on terrestrial ecosystems such as grasslands or forests where species richness is highest at intermediate levels of biomass (Grime 1979, Keddy 1990, Lawton 2000, Loreau et al. 2001). Far fewer examinations of biodiversity have occurred within aquatic ecosystems such as wetlands, where vegetative biomass is commonly higher in communities dominated by a single species (Wetzel 1983, Wetzel 1988, Moore 1990). Within wetlands, abiotic forces often seem to override biotic forces and hydrology is the key factor regulating plant diversity and productivity (Mitsch and Gosselink 2000). Due to the anoxic conditions within the sediment, these systems are generally characterized by organic matter accumulation and nutrient storage (Moore 1990). Whether these fundamental differences influence the link between biodiversity and function in wetlands differently than in terrestrial ecosystems has yet to be determined.
Of the few investigations examining biodiversity in wetlands, consistently clear patterns have not emerged. In tidal marshes, enhanced recruitment, more complex canopies, increased biomass, and increased N accumulation was related to increased plant diversity (Zedler et al. 2001b). Within freshwater wetlands, both indirect and inverse sampling effects were noted (Englehardt and Ritchie 2002). As submersed aquatic plant diversity increased so did biomass production (above- and belowground) and nutrient retention (nitrate and phosphorus). This was attributed to the presence of inferior competitors that facilitated system productivity and nutrient retention. In mesocosms simulating pond food webs, in which species richness and composition across multiple 11 trophic levels were manipulated, both idiosyncratic and indirect sampling effects on
productivity were observed (Downing and Leibold 2002). The composition of species
within trophic levels had equal or greater effects than richness per se. Furthermore, species richness, and associated changes in species composition, affected wetland
ecosystem attributes through indirect effects and trophic interactions.
No known studies have specifically examined the link between aquatic plant
(macrophyte) diversity and the decomposition related function, denitrification.
Denitrification in wetlands is regulated by organic matter quality, oxygen, and nitrate
concentrations (Schipper et al. 1993, Groffman et al. 1996, D’Angelo and Reddy 1999).
The lability of carbon is of greater importance than the quantity in regulating denitrifier
response (Schipper et al. 1994). A continual input of nitrate to a dominantly anaerobic
and organic-C rich environment creates a high selection pressure in favor of bacteria
capable of nitrate respiration since the energy yield using nitrate as an electron acceptor is
quite high (Schipper et al. 1993). Denitrifying bacteria are presumed to out-compete
other anaerobic bacteria for organic-C and nutrients in such environments.
Investigations with cultured denitrifying bacteria have determined that oxidized
nitrogen provides electron acceptors and is reduced by microbial enzymes (Ye et al.
1994). Some denitrifiers possess the whole complimentary suite of enzymes: nitrate
reductase, nitrite reductase, nitric oxide reductase, and nitrous oxide reductase that
sequentially reduce nitrate → nitrite → nitric oxide → nitrous oxide → dinitrogen. Other
denitrifiers possess only a few of these enzymes. In denitrifiers with the ability to
produce the nitrous oxide reductase enzyme, pH values below 4, O2 levels above 0.2 g/L,
and low C:N ratios negatively impact production resulting in increased nitrous oxide flux 12 (Firestone et al. 1980, Howard-Williams 1985, Vitousek et al. 1997). These environmental factors differ in the degree to which they affect nitrous oxide reductase enzyme activity within different denitrifying species (Ye et al. 1994).
Resent studies within terrestrial ecosystems suggest that denitrification function may be altered by factors altering microbial communities. Distinct differences in total denitrification flux, nitrous oxide emissions, and denitrifier community composition was observed in two adjoining fields differing in disturbance regimes and plant species
(Cavigelli and Robertson 2000, 2001). As well, denitrification decreased as microbial diversity decreased within a terrestrial sediment (Griffiths et al. 2000).
The goal of this research was to examine the link between macrophyte functional group diversity and individual macrophyte functional groups on the denitrification process.
Macrophyte species alone and in various combinations have a direct influence on the heterogeneity of organic material available to microorganisms and account for large differences in detrital dynamics within wetlands (Findlay et al.1990). Therefore, altering the quantity and/or quality of organic substrates by changing macrophyte diversity may impact denitrification.
Macrophyte functional group diversity was examined instead of species diversity per se because the magnitude of the effect of diversity on ecosystem functioning depends on the magnitude of interspecific differences within the species pool (Tilman 1999). A diversity of functional groups, based upon morphological and physiological traits, ensures greater differences among treatments. Unlike in naturally occurring wetlands, where hydrology controls community composition and diversity, we manipulated macrophyte diversity and controlled hydrology. Research within terrestrial ecosystems that have manipulated 13 diversity counter to patterns often observed in nature have been useful in revealing some
underlining mechanisms linking diversity and function (Loreau et al. 2001).
The impetus for our study originates from the knowledge that mitigation laws continue
to result in the replacement of a high percentage of naturally occurring, high macrophyte
diversity wetlands with low macrophyte diversity created systems (Zedler et al. 2001a).
The impact of this practice upon biogeochemical functions that improve water quality such as nitrate removal via denitrification or on N2O flux is far from being understood.
Our central hypothesis, based on the niche-differentiation mechanism, was that there
would be a positive relationship between macrophyte functional group diversity and
denitrification function. We had three working hypotheses:
H1: Differences between the individual macrophyte functional groups in the quantity
and/or quality of C to the sediment would be reflected in differences in denitrification
rates. The rationale for this hypothesis was that diverse plant species are known to
provide different C substrates which alter microbial communities within the root
zone.
H2: As macrophyte functional group diversity increases so would denitrification
function. The rationale for this hypothesis was that higher plant functional group
diversity would lead to a greater variety of labile carbon sources which should support
a higher number and diversity of microorganisms including denitrifying bacteria.
H3: As macrophyte functional group diversity increased, nitrous oxide flux would
decrease. It was expected that a greater diversity of denitrifying bacteria with
metabolically diverse systems would increase nitrous oxide reductase enzymes
leading to greater reduction of nitrous oxide to dinitrogen. 14 2.3 METHODS
2.3.1 Study site and experimental design
The 3 working hypotheses were tested in two separate mesocosm studies at the
Waterman Agricultural and Natural Resources Laboratory, Ohio State University,
Columbus, Ohio, USA. Mesocosms were used to control environmental conditions including sediment type and depth, water source and depth, and nutrient conditions while altering only macrophyte functional groups and functional group diversity. The mesocosms consisted of 416.7 L heavy duty oval tubs (130 cm x 86 cm x 51 cm) which were placed in the ground to moderate sediment temperatures (Figure 2.1). Each mesocosm was filled with the same sediment to a depth of 44 cm and flooded with well water to an overlying depth of 7 cm. Sediment with low initial total C content was selected to allow for C inputs from plants to be measurable. Initial sediment characteristics differed for Study #1 and Study #2 (Table 2.1). The sediment was changed for the second study to a lower sediment C concentration.
Study % % % U.S.D.A % % Cation exchange % Base # sand silt clay texture pH C N capacity saturation class Cmol / kg K Ca Mg 1 42 26 32 clay loam 7.3 4.0 0.26 131 6 74 20 2 32 30 38 clay loam 7.5 2.5 0.12 170 3 81 16
Table 2.1: Physical and chemical characteristics of sediment used in mesocosms.
15
Figure 2.1: Photograph of mesocosms at peak biomass, September 2001, Waterman
Agricultural and Natural Resources Laboratory, Ohio State University, Columbus, Ohio.
16 The macrophyte functional groups were based upon morphological and physiological traits as per Boutin and Keddy (1993) with two species representing each functional group (Table 2.2). For the first study, functional groups included clonal dominants, tussocks, reeds, facultative annuals and obligate annuals. In the second study, the clonal dominants were removed since they were highly competitive, represented the bulk of plant biomass, and reduced diversity effects when present (see Bouchard et al. in prep.).
Macrophyte Species Functional Group Study #1 Study #2 Tussock Juncus effusus Juncus effusus Juncus canadensis Juncus canadensis Reed Iris versicolor Iris versicolor Asclepias incarnata Acorus calamus Facultative annual Mimulus ringens Mimulus ringens Eupatorium perfoliatum Lycopus americanus Obligate annual Bidens cernua Bidens cernua Eleocharis obtusa Eleocharis obtusa Clonal dominant Spartina pectinata Schoenoplectus tabernaemontani
Table 2.2: Species selected to represent macrophyte functional groups. Clonal dominants were not present in the second study.
Five or six replicate mesocosms were used for each treatment consisting of controls
(no macrophytes), the individual functional groups (FG), random selections of 2 FG combinations, 3 FG combinations, 4 FG combinations (highest diversity treatment in
Study #2) and 5 FG (highest diversity treatment in Study #1). Study #1 had a total of 60 mesocosms that were sampled when all macrophyte species had reached peak biomass in early September 2001and again the following spring (April 2002). Study #2 had a total 17 of 48 mesocosms that were sampled after plants were established (August 2002), when
all macrophyte species had reached peak biomass in early September 2002, and the
following spring (April 2003).
All macrophyte species were obtained as either bare root plants or plugs from Acorus
Restoration (www.ecologyart.com\ acorus), Walsingham, On, Canada; Envirotech
Consultants Inc.(www.envirotechcon.com) Columbus, OH; and Ernst Conservation
Seeds (www.ernsteed.com), Meadville, PA. Species were planted randomly throughout
each mesocosm with equal numbers of plants representing each functional group. Initial
plant densities per mesocosm were 18-21. Density changed throughout the study period
due to propagation which altered species richness particularly when clonal dominants were present although diversity was maintained. Invading, non-study species were removed weekly.
For both studies, in situ denitrification, denitrification potential, labile C, bacterial
- biomass, sediment total C and N, interstitial water NO3 , and dissolved organic C (DOC)
were analyzed. In Study #2, differences between treatments for in situ N2 and N2O fluxes after nitrate addition was also examined. Above- and belowground biomass was collected for both studies during macrophyte peak biomass in September 2001 and
September 2002. These results can be found in Bouchard et al. (in prep.).
2.3.2 Sediment and interstitial water C and N
Four sediment cores (2.5 cm dia) were collected randomly from within each mesocosm to a depth of 10 cm, bulked and stored in airtight bags at 4oC. Sub-samples were used to
analyze denitrification potential, bacterial biomass, labile C, and C:N ratios. 18 Total bacterial biomass in the first study was determined from sediment sub-samples
collected only in September 2001 using epifluorescence microscopy coupled with
computer assisted image analysis (Frey et al. 1999). Active bacterial biomass was estimated in the second study by substrate induced respiration (SIR; Anderson and
Domsch 1978, West and Sparling 1986). For each sample, 10 g of sediment was placed
into a 60 ml serum bottle. Twenty ml of glucose solution at a concentration of 3 mg
glucose/ml (equivalent to 6 mg/g dry soil) was added and allowed to equilibrate
uncapped for 30 minutes. The bottles were then sealed and incubated at 25oC for 2.5 hrs.
Headspace gas samples were analyzed immediately using a LI-COR CO2 Analyzer.
Labile C was determined from 10 g of field wet sub-sample which was placed in a 20
ml specimen cup and then into a 1 L glass Mason jar. Twenty ml of autoclaved DI water was added to the jar bottom to prevent sediment drying throughout the incubation period.
Each jar was flushed with zero grade air for 1 min and sealed with a lid containing a luer
lock that allowed for headspace gas sampling. The jars were incubated at 25oC and every
3-5 days, 2 ml of headspace gas was collected and immediately measured for CO2 using a
LI-COR CO2 Analyzer. After each sampling event, the jars were opened, flushed for
1 min with zero grade air, and then re-sealed. The incubation continued until CO2
production leveled off (~ 30-37 days). Labile C was estimated as the cumulative CO2-C
evolved over the incubation period.
Sediment C:N was measured on air-dried sub-samples from which pebbles, roots, and other non-soil material were removed. Each sample was ground to a fine powder using a
ball-mill grinder and stored at room temperature in scintilation vials until analysis. Total
19 sediment C and N was determined by dry combustion using a Carlo-Erba Analyzer
(Thermo Quest, NC 2100, CE Elantech Instruments).
Interstitial water was collected from each mesocosm at the 10 cm sediment depth from
inside each of the two sampler tubes prior to in situ denitrification gas sampling. The
water collected was bulked into 50 ml Nalgene bottles and immediately kept cool until
transport to the laboratory where they were stored at 4oC. Within 24 hrs of collection,
water samples were filtered using 0.45 µm Whatman glass microfibre filters and split into
two sub-samples. Samples to be analyzed for dissolved organic carbon (DOC) were
stored at 4oC and, within 48 hrs of collection, were analyzed on a Dohrman TOC
- o Analyzer, DC-190. Samples for NO3 determination were stored at –20 C until colormetry analysis on a Zellweger Analytics, Lachat Instrument.
2.3.3 In situ denitrification
In situ denitrification was determined using the acetylene block method as described by
Knowles (1990) and Mosier and Klemedtsson (1994). Two 61 cm length x 10 cm
diameter polyvinylchloride (PVC) sampling tubes were permanently placed within each
mesocosm to allow for gas sampling without sediment disturbance. Below the 10 cm
sediment depth the sampling tubes had openings to allow for root intrusion. Each
sampling tube had a 2.2 cm diameter hole at the sediment/water interface to reduce water
stagnation during non-sampling periods. Prior to gas sampling, all mesocosms were
drained and refilled with well water. The hole in the sampler tube was plugged and
acetylene gas (C2H2) was bubbled into the sediment in the sampling tube at the 10 cm
depth on a 10% v/v ratio (180 ml/sampler). Preliminary tests determined C2H2 20 concentration as optimal. The tubes were sealed with an airtight cap and gas samples were extracted via a rubber septum located in the cap’s center. Headspace gas was collected using a 60 cc syringe after pumping 3 times to mix the air inside the sampling tube. In situ gas sampling protocol differed for the two studies. For Study #1, 15 ml of gas sample was collected from each of the two sampler tubes per mesocosm and bulked into a 20 ml evacuated glass vial. All in situ denitrification flux was N-(N2O + N2) since
N2O and N2 was not differentiated. In Study #2, C2H2 was only added to one sampler
tube per mesocosm. From each sampler tube 30 ml of headspace gas was collected and
stored separately in evacuated glass vials. Gas collected without C2H2 allowed for the determination of the actual N2O emitted. The difference between N2O measured from the
sampler tube receiving C2H2 and the sampler tube without C2H2, was assumed to be N2 gas production. No N2O was detected above the ambient concentrations of the
surrounding air, therefore all in situ denitrification was N-N2 for Study #2. Gas sampling
times were 6 and 24 hours after C2H2 addition as determined optimum for flux calculations. Sediment temperature at the 10 cm depth was measured for each mesocosm
during the September 2002 and April 2003 in situ denitrification gas sampling events.
For the second study, an additional in situ denitrification experiment took place under higher nitrate concentrations than those occurring naturally. The same sampling protocol was carried out for in situ denitrification sampling described above with the exception that a 4 ml/L nitrate solution was added to each sampler tube. This concentration is an average value found in rivers throughout Ohio (Debrewer et al. 1999). The assay took place 24 hrs after the last sampling period for in situ denitrification. Prior to adding the nitrate solution all sampling tubes were opened and all mesocosms were drained and 21 refilled with well water. Both N2O and N2 were measurable after nitrate addition. The
N2O produced was assumed to result entirely from denitrification and not nitrification.
Although N2O flux from nitrification has been observed in laboratory experiments, the
production of this greenhouse gas under anoxic field conditions has not been clearly
established (Henault et al. 1998). In situ N2O from wetland sediments is presumed to
derive entirely from denitrification due to the low redox potentials (Reddy et al. 1989,
Groffman 1991).
2.3.4 Denitrification potential
Denitrification potential (denitrification enzyme activity, DEA) was determined using a modified method adopted from Tiedje et al. (1989) and Schipper et al. (1993). For each mesocosm sediment sample collected as described above, a 20 g sub-sample was placed into a 60 ml serum bottle and sealed. The headspace was flushed with argon for 2.5 min to create anoxic conditions. Five ml of distilled water containing 0.5 mg KNO3 was then added. Glucose was not added, as is usually stated in the DEA protocol to assess differences in C availability to the denitrifiers due to our treatments alone. Acetylene was injected at a 5 ml volume (10% v/v ratio). Samples were incubated at 25oC in the
dark on a shaker table at 200 rev. min-1 for 2 hrs. Gas samples were collected from the
headspace at 15 and 120 min as determined optimum and stored in a 2.0 ml Vacutainer
serum bottle. The ratio N2O:N2 was not determined, and therefore, all denitrification potential flux calculations are expressed as N-(N2O + N2).
22 2.3.5 Gas sample analysis
All denitrification gas samples were measured for N2O concentrations on a gas
chromatograph. Samples from Study #1 were analyzed on a Hewlett-Packard, GC-ECD
system with carrier gas 95% argon and 5% methane and a flow rate of 18 ml/min.
Column temperature was 70oC and the detector temperature was 400oC. Column specs were: Alltech 1m x 2 mm i.d. stainless steel precolumn in combination with a 3 m x 2 mm i.d. analytical column. Both columns were packed with Porapak Q (80/100 mesh).
Samples from Study #2 were analyzed on a Shimadzu 14C with a carrier gas of 95%
argon and 5% methane and a flow rate of 32 ml/min. Column temperature was 40oC andthe detector temperature was 300oC. The column specs were: 2 columns; Alltech,
Porapak Q 80/100, 6’ x 1/8” x 0.085” stainless steel; column flow rate: 2.3 ml/min. All
flux calculations for in situ denitrification and denitrification potential were performed as
per Mosier and Klemedtsson (1994).
2.3.6 Statistical analyses
Minitab 13.1 was used for all analyses. Data sets were tested for normal distributions
using the Anderson-Darling test. Analysis of variance (ANOVA) was analyzed using
Fishers individual error rate with confidence intervals of 95% (CI 0.95) as were
regressions (CI 0.95) and best subsets regressions (CI 0.95). A Model 1 linear regression
was used to analyze all data from all sampling periods for each study. All data was
combined per analysis regardless of sampling treatment to identify relationships between
denitrification and C pools independent of macrophyte functional group or functional
group diversity treatments. For the best subsets regression the combination of factors
23 producing the highest R2 value were selected.
2.4 RESULTS
2.4.1 Macrophyte Functional Group Comparisons
2.4.1.1 Interstitial water and sediment characteristics.⎯ Interstitial water DOC was
significantly higher in the facultative annual and reed functional groups than the obligate annuals or clonal dominants at the macrophyte peak biomass sampling period for our first study (no data were available for the tussocks). Values ranged from 81 mg/L in the clonal dominants to 227 mg/L DOC in the facultative annuals (Table 2.3). The following spring, there was a large decline in DOC for all functional groups with ranges of 30 - 58 mg/L DOC and no significant differences between functional groups. In the second study, the facultative annuals once again showed the highest interstitial water DOC values for each sampling period. Significant differences between the functional groups were noted in both September and April. These values ranged from a high of 114 mg/L for the facultative annuals to a low of 15 mg/L DOC for the tussocks in September and a high of 83 mg/L for the facultative annuals to a low of 18 mg/L DOC for the reeds in
April (Table 2.9).
Interstitial water nitrate concentrations were slightly above detection limits at the peak biomass sampling period in Study #1 for all functional groups with no significant differences between them (Table 2.3). The following spring, the facultative annuals and
- -1 tussocks had significantly higher concentrations at 0.09 and 0.08 mg N-NO3 L ; respectively. The reeds, clonal dominants, and obligate annuals ranged between 0.02 –
- -1 0.06 mg N-NO3 L . In the second study, differences between the macrophyte functional 24 groups were only significant in September and April (Table 2.4). During macrophyte
peak biomass, nitrate concentrations were below detection limits for the facultative
- annuals and obligate annuals while the reeds and tussocks had 0.02 and 0.06 mg N-NO3
L-1; respectively. The following spring, concentrations increased within all functional
groups and the tussocks and reeds had significantly higher values at 0.43 and 0.32 mg N-
- -1 - -1 NO3 L ; respectively compared to 0.18 mg N-NO3 L in the facultative annuals and
- -1 0.14 mg N-NO3 L in the obligate annuals.
Sediment labile C was significantly lower in the reeds during macrophyte peak biomass
-1 in Study #1 with a value of 288 µg CO2-C g dry sediment compared to the clonal
-1 dominants and obligate annuals with the highest values at 339 and 327 µg CO2-C g dry
sediment; respectively (Table 2.3). The following spring, the clonal dominants had
-1 significantly higher labile C than the other 4 functional groups with 408 µg CO2-C g dry
-1 sediment compared to ranges of 274 - 311 µg CO2-C g dry sediment. In the second
study, there were no significant differences between any of the functional groups for sediment labile C during any of the three sampling dates (Table 2.4). Values overall
-1 were highest in August with ranges of 134 - 222 µg CO2-C g dry sediment and then
-1 dropped in September with ranges of 114 - 137 µg CO2-C g dry sediment. A further
-1 drop occurred the following April with ranges of 100 - 119 µg CO2-C g dry sediment.
Total bacterial C in the first study was only analyzed during macrophyte peak biomass
with no significant differences between the functional groups evident (Table 2.3). Values
ranged from 169 - 230 µg C g-1 dry sediment. Active bacterial biomass in Study #2
increased from August to September and again in April (Table 2.4). No significant
25 differences existed between the functional groups in either August or September with
-1 -1 ranges of 25 - 28 µg CO2-C g dry sediment and 40 – 60 µg CO2-C g dry sediment;
respectively. Significant differences were noted in April. The facultative annuals had the
-1 highest active bacterial C values at 117 µg CO2-C g dry sediment followed by the
-1 -1 obligate annuals (108 µg CO2-C g dry sediment) and the tussocks (88 µg CO2-C g dry
-1 sediment). The reeds had the lowest values with 67 µg CO2-C g dry sediment.
Sediment C:N ratios were not significantly different between the functional groups for either study. In Study #1, C:N ranged from 24 - 27 in September and 20 – 23 in April
(Table 2.3). In Study #2, C:N ranged from 21 - 22 in August, 20 - 22 in September, and
18 - 19 in April (Table 2.4). For both studies, the decline in C:N ratios from September to April was due to a slight decrease in sediment C and not an increase in N.
Interstitial Water Sediment Macrophyte Sample DOC Nitrate Labile C Bacterial C C:N -1 Functional dates mg/L mg/L µg CO2-C µg C g dry ratio Groups g-1 dry sed sed Tussock Sep 0.09 ±0.01 318 ±6ab 214 ±10 26 ±2 Apr 42 ±12 0.08 ±0.01b 281 ±14 b 20 ±1 Reed Sep 170 ±43ab 0.07 ±0.01 288 ±14b 169 ±8 25 ±1 Apr 30 ± 5 0.02 ±0.00b 311 ±20b 22 ±1 Facultative Sep 227 ±26a 0.08 ±0.01 308 ±14ab 182 ±15 26 ±1 annual Apr 58 ±12 0.09 ±0.01a 301 ±25b 23 ±2 Obligate Sep 107 ±17bc 0.07 ±0.01 327 ±11a 196 ±29 27 ±1 annual Apr 47 ±9 0.06 ±0.01b 274 ±15b 22 ±1 Clonal Sep 81 ±13c 0.08 ±0.01 339 ±12 a 230 ±7 24 ±1 dominant Apr 34 ±7 0.03 ±0.01b 408 ±40a 20 ±1 Mean ±1 SE, n = 5; values with different letters are significantly different at P < 0.05 for that sampling date. Bacterial C was not measured for April 2002; DOC for tussocks was not measured in September 2001.
Table 2.3: Interstitial water and sediment characteristics per macrophyte functional
group, Study #1. 26 Interstitial Water Macrophyte DOC Nitrate functional mg/L mg/L groups August September April August September April Tussock 66 ±18 15 ±1b 19 ±3b 0.25 ±0.20 0.06 ±0.02a 0.43 ±0.15a Reed 75 ±3 30 ±4b 18 ±4b 0.13 ±0.08 0.02 ±0.01b 0.32 ±0.06a Fac ann 99 ±17 114 ±27a 83 ±12a 0.03 ±0.03 ND 0.18 ±0.09b Ob ann 73 ±13 57 ±20b 59 ±9a ND ND 0.14 ±0.04b Sediment Labile C Bacterial C C:N -1 -1 µg CO2-C g dry sed µg CO2-C g dry sed ratio Aug Sep April Aug Sep April Aug Sep April Tussock 222 ±40 137 ±19 19 ±10 25 ±7 49 ±12 88 ±7ab 21 ±1 20 ±4 18 ±1 Reed 195 ±27 114 ±9 100 ±4 26 ±4 40 ±5 67 ±12b 21 ±1 20 ±1 18 ±1 Fac ann 134 ±32 114 ±7 104 ±5 26 ±5 60 ±8 117 ±6a 21 ±1 20 ±1 19 ±1 Ob ann 185 ±24 119 ±9 106 ±8 28 ±3 51 ±6 108 ±9a 22 ±1 22 ±7 19 ±1 Mean ± 1 SE, n = 6; values with different letters are significantly different at P < 0.05 for that sampling date; ND refers to values below detection limits (<0.01 mg/L); Fac ann = facultative annuals, Ob ann = obligate annuals.
Table 2.4: Interstitial water and sediment characteristics for macrophyte functional
groups, Study #2.
2.4.1.2 In situ denitrification.⎯ In Study #1, in situ denitrification at macrophyte peak
biomass was not significantly different between the macrophyte functional group treatments (Figure 2.2a). The following spring differences did occur with the tussocks
-2 -1 (830 µg N-(N20 + N2) m day ) showing a significantly higher flux than all but the
-2 -1 facultative annuals (618 µg N-(N20 + N2) m day ) while the clonal dominants and
-2 -1 obligate annuals both had an in situ denitrification flux of 24 µg N-(N20 + N2) m day .
The clonal dominants and obligate annuals also exhibited a large seasonal decline in flux
(98.4%) between September and April.
27 In situ denitrification in the second study was highest in mid summer (August) and again the following spring (April) although there were no significant differences between the functional groups during these times (Figure 2.2b). Significant differences did occur during the macrophyte peak biomass sampling date in September. At this time, the
-2 -1 -2 facultative annuals (658 µg N-N2 m day ) and obligate annuals (1679 µg N-N2 m
-1 -2 -1 day ) had the lowest in situ denitrification while the tussocks (2148 µg N-N2 m day )
-2 -1 and reeds (2095 µg N-N2 m day ) had the highest. Sediment temperatures were monitored during both the September and April in situ sampling events for the second study and were not significantly different between treatments for either sampling date.
Temperatures ranged from 22 - 28oC in September and 18 - 21oC in April.
Study #1 Study #2 1200
-1 7000 a a Sep'01 Aug' 02 b
day 1000 6000 Apr' 02 -2 -1 Sep'02 800 5000
day Apr' 03
O) m ab -2 2 4000
600 m 2
+ N 3000 2 bc a a b 400 2000 g N-N b g N-(N 200 1000 cc 0 0 tussock reed facultative obligate clonal tussock reed facultative obligate annual annual dominant annual annual
Macrophyte Functional Groups
Figure 2.2: In situ denitrification per macrophyte functional group, Study #1 (a) and Study #2 (b). Mean ± 1 SE, Study #1: n = 5; Study #2: n = 6. Values with different letters are significantly different at P < 0.05 for that sampling date. 28 2.4.1.3 In situ denitrification with added nitrate.⎯ Total in situ denitrification increased in all functional groups after nitrate addition by more than 75% in both September and
April. Significant differences between the functional groups occurred in both sampling dates for in situ N2 and in September only for in situ N2O. The obligate annuals
consistently had higher N2 and N2O fluxes than the other three functional groups for both
sampling dates (Figure 2.3a,b). September in situ N2 fluxes ranged from 30.4 mg N-N2
-2 -1 -2 -1 m day in the facultative annuals to 61.3 mg N-N2 m day in the obligate annuals.
The following spring, in situ N2 fluxes declined in all treatments but the obligate annuals
-2 -1 were still significantly higher with 27.4 mg N-N2 m day compared to 10.6 – 15.9 mg
-2 -1 N-N2 m day in the other functional groups.
In situ N2O fluxes at macrophyte peak biomass were significantly higher in the obligate
-2 -1 -2 -1 annuals with to 4.8 mg N-N2O m day compared to 0.8 – 1.1 mg N-N2O m day in the other three functional groups. The following spring, N2O fluxes declined and were not
significantly different between all four macrophyte functional groups.
80 a 7 a a 70 Sep'02 b 6 Sep'02 -1 60 Apr'03 -1 5 Apr'03 day 50 day -2 ab -2 4 m
2 40 b b O m a 2 30 3 20 b b 2 mg N-N b b b 10 mg N-N 1 b 0 0 tussock reed facultative obligate tussock reed facultative obligate annual annual annual annual Macrophyte Functional Groups
Figure 2.3: In situ N2 (a) and in situ N2O (b) after nitrate addition for each macrophyte
29 functional group. Mean ± 1 SE, n = 6; values with different letters are significantly different at P < 0.05 for that sampling date.
2.4.1.4 Denitrification potential. ⎯ In the first study, no significant differences in denitrification potential were detected between any of the functional groups for either sampling period (Figure 2.4a). At macrophyte peak biomass, fluxes ranged from 3.5 -
-2 -1 4.9 mg N-(N2 + N2O) m day . The following spring, fluxes ranged from 2.5 - 5.3 mg
-2 -1 N-(N2 + N2O) m day . Denitrification potential in the second study was higher for all
four functional groups during the peak biomass sampling period in September compared
to the other two sampling periods (Figure 2.4b). At this time, the reeds had significantly
-2 -1 higher fluxes than all but the tussocks with 56.9 and 45.5 mg N-(N2 + N2O) m day ;
respectively. The obligate annuals showed intermediate values (43.4 mg N-(N2 + N2O)
-2 -1 -2 m day ) while the facultative annuals had the lowest values (21.7 mg N-(N2 + N2O) m day-1). The following spring denitrification potential declined in all four functional groups, although it was significantly higher again within the tussocks and reeds. Fluxes
-2 -1 ranged from a low of 3.5 mg N-(N2 + N2O) m day in the facultative annuals to a high
-2 -1 of 12.1 mg N-(N2 + N2O) m day in the tussocks.
30 Study #1 Study #2 7 70 a a Aug'02 b -1 6 Sep'01 -1 60 Sep'02
day Apr'02 ab day -2 5 -2 50 Apr'03 b
O) m 4
O) m 40 2 2
+ N 3 30 c + N 2 2 2 20 a a b mg N-(N 1 mg N-(N 10 b 0 0 tussock reed facultative obligate clonal tussock reed facultative obligate annual annual dominant annual annual
Macrophyte Functional Groups
Figure 2.4: Denitrification potential for each macrophyte functional group for Study #1
(a) and Study #2 (b). Mean ± 1 SE, Study #1: n = 5, Study #2: n = 6; values with different
letters are significantly different at P < 0.05 for that sampling date.
2.4.1.5 Denitrification flux per C pools.⎯ For both studies we examined the differences
between macrophyte functional groups for in situ denitrification and denitrification
potential per unit of interstitial water DOC, sediment labile C, bacterial C, root biomass
and total plant biomass. No clear trends were evident in either study indicating consistent
differences between the macrophyte functional groups. In the study with clonal
dominants, in situ denitrification flux per unit DOC at macrophyte peak biomass was not
significantly different between the functional groups (Figure 2.5a). The following spring,
-1 -2 significant differences were evident with ranges 0.59 µg N-(N2 + N2O) mg/L DOC m
-1 -1 -2 -1 day in the obligate annuals to 27.24 µg N-(N2 + N2O) mg/L DOC m day in the
tussocks. In the second study, in situ denitrification per unit DOC was consistently higher in the tussock and reed functional groups for all three sampling dates although this 31 difference was not always significant (Figure 2.5b). The highest values occurred in the
-1 -2 -1 spring with the reeds (186 µg N-N2 mg/L DOC m day ) and tussocks (128 µg N-N2
-1 -2 -1 -1 mg/L DOC m day ) significantly higher than the obligate annuals (46 µg N-N2 mg/L
-2 -1 -1 -2 -1 DOC m day ) and facultative annuals (34 µg N-N2 mg/L DOC m day ).
In situ denitrification per unit labile C was not significantly different for any of the
macrophyte functional groups during macrophyte peak biomass for Study #1 (Figure
2.5c). Low in situ denitrification at this time for all treatments may explain this result.
-1 -2 -1 Values ranged from 0.00 - 0.10 µg N-(N2 + N2O) mg labile CO2-C m day . The
following spring, the tussocks had significantly higher values at 0.14 µg N-(N2 + N2O)
-1 -2 -1 mg labile CO2-C m day while the lowest values occurred for the obligate annuals
-1 -2 -1 (0.002 µg N-(N2 + N2O) mg labile CO2-C m day ). In the second study significant
differences between the four macrophyte functional groups for in situ denitrification per unit labile C were only evident during macrophyte peak biomass. The facultative annuals and obligate annuals showed a significantly lower flux than the tussocks and reeds
(Figure 2.5d).
No significant differences existed between the macrophyte functional groups for in situ denitrification per unit bacterial C in Study #2 (Figure 2.5e). Values were highest in the obligate annuals, clonal dominants, and facultative annuals, although there were large within treatment variance for each of these functional groups. In the second study, large variances within functional group replicates also occurred and in situ denitrification per unit bacterial C was only significantly different between the four functional groups during peak biomass in September. At this time, the facultative annuals showed the
32 -1 -2 -1 lowest values (0.97 µg N-N2 mg bacterial CO2-C m day ) and the reeds the highest
-1 -2 -1 (4.67 0.92 µg N-N2 mg bacterial CO2-C m day ; Figure 2.5f). Significant differences were not detected between macrophyte functional groups in either study for in situ denitrification per unit macrophyte root or total biomass (Figures 2.5g,h).
In the second study, under nitrate addition conditions, in situ denitrification per unit
DOC, labile C, bacterial C and root and total plant biomass showed different results. The tussocks and obligate annuals had significantly higher in situ N2 flux per unit DOC
during peak biomass, but this declined substantially the following spring (Figure 2.6a).
Nitrous oxide flux per unit DOC was highest for the obligate annuals at peak biomass,
although this was not significantly different than the other three functional groups for
both sampling periods (Figure 2.6b). In situ N2 flux per unit labile C was highest for the
obligate annuals both macrophyte peak biomass and the following spring, although
differences were only significant in April (Figure 2.6c). In situ N2O per unit labile C was
significantly higher for the reeds and tussocks during peak biomass with no differences
for the spring sampling period (Figure 2.6d). In situ N2 and N2O flux per unit bacterial C
were both highest in the obligate annuals during peak biomass, although only
significantly so for N2O flux per unit bacterial C (Figures 2.6 e,f).
33 Study #1 Study #2
-1 45 250 a a Sep'01 a b day 40 Aug'02 -2 Apr'02 35 day-1 200 Sep'02 -2 30 a Apr'03 DOC m -1 25 b 150 a DOC m DOC 20 b -1 ) mg/L 100
2 b 15 c b mg/L 2
O+N 10 2 50 b 5 b b g N-N c gN(N µ µ 0 0
-1 0.25 4 Sep'01 c Aug'02 d -1 day -2 0.20 a Apr'02 Sep'02 day b -2 3 Apr'03 0.15 labile C m -1 2 a a labile C m
0.10 -1 ) mg 2 b mg
bc 2
O+N 1 2 0.05 b
c c g N-N µ g N(N
µ 0.00 0
-1 0.25 e -1 16
day Sep'01 Aug'02 f -2 day 14 0.20 -2 Sep'02 12
-C m Apr'03 2 0.15 10 bacterial C m bacterial C
-1 8 0.10 a
) mg 6 bacterial CO 2 -1 ab 4 bc O+N mg
2 0.05 2 2 c g N(N g N-N
µ 0.00 µ 0
4.0 20 -1 g h Sep'01 18 root biomass -1
day 3.5 -2 Sep'01 16 total biomass 3.0 day -2 14 2.5 12
biomass m 2.0 -1 10 biomass m ) g 2 1.5 -1 8 g 2 6
O+N 1.0 2 4
0.5 g N-N µ 2 g N(N µ 0.0 0 tussock reed facultative obligate clonal tussock reed facultative obligate annual annual dominant annual annual Macrophyte Functional Groups
Figure 2.5: In situ denitrification per unit DOC for Study #1 (a) and Study #2 (b); per unit
34 labile C for Study #1 (c) and Study #2 (d); per unit bacterial C for Study #1 (e) and
Study #2 (f); and per unit root and total plant biomass for Study #1 (g) and Study #2 (h).
Mean ± 1 SE, Study #1: n = 5, Study #2: n = 6; values with different letters are
significantly different at P < 0.05 for each sampling date. DOC was not analyzed for the tussocks in Sep. 2001 and Bacterial C was not analyzed in Apr. 2002.
For both studies, analysis of the differences between macrophyte functional groups in
denitrification potential per unit DOC, labile C, bacterial C and root and total plant biomass showed no consistent trends. Denitrification potential per unit DOC was not significantly different between any of the five functional groups for either sampling date in Study #1 (Figure 2.7a). Significant differences were noted in the second study during both the peak biomass and spring sampling dates. For both of these times, the tussocks showed significantly higher flux per unit DOC than either the facultative annuals or the
obligate annuals with the reeds at intermediate values (Figure 2.7b).
Analysis of denitrification potential per unit labile C showed no significant differences
between any of the macrophyte functional groups in the first study including the clonal
dominants, which by far had the highest belowground biomass (Figure 2.7c). Significant
differences did occur between the functional groups in the second study during peak
biomass with the tussocks, reeds and obligate annuals showing a higher flux per unit
labile C than the facultative annuals (Figure 2.7d).
35 -1 -1 3500 300
day b day a a Sep'02
Sep'02 -2 -2 3000 a 250 Apr'03 2500 Apr'03 200 2000 DOC m DOC m -1 -1 150 1500 ab 100
ppm 1000 2 O ppm
b 2 500 50
g N-N 0 g N-N u 0
tussock reed facultative obligate u tussock reed facultative obligate annual annual annual annual -1 -1 60 1.8 a a cdSep'02
Sep'02 day 1.6 day -2
-2 50 Apr'03 1.4 Apr'03 40 1.2 1.0 30 labile C m labile C m a 0.8 -1 -1 b 20 0.6
mg b b 2
b O mg 0.4
b 2 10 0.2
g N-N 0 0.0 g N-N u
tussock reed facultative obligate u tussock reed facultative obligate annual annual annual annual -1
160 -1 e 12
day Sep'02
140 day f -2 Sep'02
-2 a Apr'03 10 120 Apr'03 -C m -C 2 m -C 100 2 8
80 6 60
bacterial CO 4 bacterial CO -1 40 -1 b bb
mg 2
2 20 O mg 0 2 0 g N-N
u tussock reed facultative obligate
g N-N tussock reed facultative obligate annual annual u annual annual -1 -1 1200 35 a root biomass g day root biomass a h day
1000 -2 30 -2 total biomass total biomass 800 25 20 600 biomass m
biomass m 15
-1 b -1 400 g
2 10 O g a b a b 2 b a 200 b 5 b b b b b b g N-N g N-N
u 0 0 u tussock reed facultative obligate tussock reed facultative obligate annual annual annual annual Macrophyte Functional Groups
Figure 2.6: In situ N-N2 flux with nitrate addition for each macrophyte functional group 36
per unit: DOC (a), labile C (c), bacterial C (e), root and total plant biomass (g); and in
situ N-N2O flux with nitrate addition per unit: DOC (b), labile C (d), bacterial C (f), and
root and total plant biomass (h). Mean ± 1 SE, n = 6; values with different letters are
significantly different at P < 0.05 for each sampling date.
Significant differences between the macrophyte functional groups for denitrification potential per unit bacterial biomass was only noted in the second. For both macrophyte peak biomass and spring sampling dates (Figure 2.7 e,f) the reeds had significantly higher flux per unit bacterial biomass while the facultative annuals had the lowest.
For both studies, the facultative annuals consistently had the highest denitrification potential per unit root and total plant biomass than all of the other functional groups
(Figure 2.7g,h). Significant differences however, were only noted in Study #1 with the facultative annuals exhibiting at least five times more flux per root biomass and four times more flux per total plant biomass than the other four functional groups.
37 Study #1 Study #2 300 4000 -1 a - Sep'01 a Aug'02 b day day 3500 -2 250 Apr'02 -2 Sep'02 3000 Apr'03 200 ab DOCm
DOC m DOC 2500 -1 -1 b
150 20001 ) mg/L ) mg/L 2
2 1500 100 O+N
O+N 1000
2 aa 2 50 500 c gN(N gN(N b b µ µ 0 0
180 -1 2.5 c -1 d Sep'01 160 Aug'02 day day -2 2.0 Apr'02 -2 140 Sep'02 Apr'03 120 1.5
labile C m 100 labile C m -1 -1 80
1.0 ) mg ) mg 2 2 60 a O+N 2 O+N 40 a a 2 0.5 20 b g N(N µ g N(N
µ 0.0 0
3.5
-1 160 -1 e a f Sep'01 Aug'02 day day 3.0 140 -2 -2 Sep'02 120 2.5 Apr'03 100 bact C m bact C m 2.0 b -1 -1 80 b 1.5 ) mg ) mg 2 2 60 1.0 b
O+N 40 O+N 2 2 0.5 20 ab a c bc g N(N g N(N µ µ 0.0 0
-1 80
-1 1000 a g h root biomass 900 root biomass
day 70 day -2 total biomass -2 800 total biomass 60 700 50 600 biomass m biomass 40 m biomass
-1 500 -1 ) g ) g
2 400 30 a 2 300 O+N
20 O+N 2 b 2 200 10 b b b b b b 100 g N(N
b g N(N µ 0 µ 0 tussock reed facultative obligate clonal tussock reed facultative obligate annual annual dominant annual annual
Macrophyte Functional Groups
Figure 2.7: Denitrification potential in each macrophyte functional group per unit: DOC, 38 Study #1 (a) and Study #2 (b); labile C, Study #1 (c) and Study #2 (d); bacterial C, Study
#1 (e) and Study #2 (f); root and total plant biomass, Study #1 (g) and Study #2 (h). Mean
± 1 SE, Study #1: n = 5, Study #2: n = 6; values with different letters are significantly
different at P < 0.05 for each sampling period. Bacterial C was not analyzed in Apr.
2002.
2.4.2 Macrophyte Functional Group Diversity Comparisons
2.4.2.1 Interstitial water and sediment characteristics.⎯ Significant differences in
interstitial water DOC between the diversity treatments only occurred the first study.
During macrophyte peak biomass, the highest values occurred in the lower diversity treatments while the lowest values were determined in the highest diversity treatments
(Table 2.5). The controls and 1 FG diversity treatment had 187 and 160 mg/L DOC;
respectively while the highest diversity treatment (5 FG) had a concentration of 65 mg/L
DOC. The following spring, DOC values for all treatments were substantially lower with
ranges from 31-54 mg/L DOC and were not significantly different. In Study #2, there
was also a trend toward decreasing interstitial water DOC concentrations with increasing
functional group diversity although there were no significant differences between the
diversity treatments for any sampling period (Table 2.6). Values ranged from 55 - 92
mg/L DOC in August, 31–98 mg/L DOC in September, and 37–58 mg/L DOC in April.
For both studies, there was a negative correlation between DOC and macrophyte
functional group diversity during macrophyte peak biomass and no relationship the
following spring (Table 2.7). It appears that when plants are in the growth phase, as 39 diversity increases, DOC decreases although this relationship is not very strong with the
R2 value only ranging between 12–25.
Functional Interstitial Water -1 group diversity DOC mg/L N-NO3 mg/L treatments September April September April Controls 187 ±14a 43 ±11 0.10 ±0.02a 0.07 ±0.01a 1 FG 160 ±18a 42 ±4 0.08 ±0.01b 0.06 ±0.01b 2 FG 131 ±37ab 31 ±8 0.08 ±0.01b 0.03 ±0.00b 3 FG 78 ±13b 44 ±8 0.06 ±0.01b 0.04 ±0.00b 4 FG 92 ±9ab 35 ±6 0.06 ±0.01b 0.04 ±0.01b 5 FG 65 ±2b 54 ±7 0.07 ±0.01b 0.04 ±0.01b Functional Sediment group Labile C Bacterial C C:N -1 -1 diversity µg CO2-C g dry sed µg C g dry sed ratio treatments September April September September April Controls 314 ±28 297 ±15 b 220 ±26 27 ±1 22 ±2 1 FG 316 ±6 315 ±14 b 198 ±8 26 ±0 22 ±1 2 FG 331 ±17 331 ±36 ab 234 ±8 25 ±1 20 ±1 3 FG 345 ±12 358 ±39 ab 233 ±48 25 ±1 22 ±2 4 FG 320 ±19 417 ±38 a 193 ±25 26 ±1 22 ±1 5 FG 363 ±12 379 ±31 ab 245 ±23 27 ±1 22 ±1 Mean ± 1SE, n = 6 except controls: n = 5, 1 FG: n = 25; 1 FG represents reeds, tussocks, obligate annuals, facultative annuals and clonal dominants; bacterial C not determined for April 2002; FG refers to functional group; Values with different letters are significantly different at P < 0.05 for the sampling period.
Table 2.5: Interstitial water and sediment characteristics for Study #1.
40 F Interstitial Water - G DOC mg/L N-NO3 mg/L # Aug Sep Apr Aug Sep Apr C 92 ±10 98 ±14 58 ±9 0.04 ±0.04 ND 0.21 ±0.05 1 79 ±7 58 ±12 46 ±7 0.09 ±0.05 0.01 ±0.00b 0.26 ±0.05 2 61 ±11 54 ±19 49 ±9 0.31 ±0.49 ND 0.18 ±0.06 3 63 ±9 33 ±7 37 ±9 0.63 ±0.49 0.07 ±0.05a 0.37 ±0.13 4 55 ±6 31 ±8 38 ±6 0.13 ±0.13 ND 0.13 ±0.03 Sediment F Labile C Bacterial C C:N -1 -1 G µg CO2-C g dry sed µg CO2-C g dry sed ratio # Aug Sep Apr Aug Sep Apr Aug Sep Apr C 203 ±27 122 ±10 105 ±4 31 ±5 61 ±3 112 ±8 20 ±0.3 20 ±0.5 15 ±0.3b 1 183 ±16 120 ±6 107 ±3 26 ±2 52 ±3 95 ±6 21 ±0.3 21 ±0.4 18 ±0.5a 2 223 ±10 127 ±9 106 ±7 19 ±4 53 ±4 86 ±5 21 ±0.7 21 ±0.8 17 ±0.5ab 3 189 ±14 105 ±14 105 ±6 21 ±4 55 ± 9 96 ±11 21 ±0.6 20 ±0.6 17 ±0.5ab 4 144 ±41 101 ±14 120 ±16 24 ±2 40 ±6 107 ±8 22 ±0.9 21 ±0.6 17 ±0.8ab Mean ± 1 SE, n = 6; C = control, 1 FG represents reeds, tussocks, obligate annuals, and facultative annuals; ND = below detection limits (<0.01 mg/L); Values with different letters are significantly different at P < 0.05 for sampling period.
Table 2.6: Interstitial water and sediment characteristics for functional group diversity
treatments, Study #2.
Interstitial water nitrate values for all treatments in Study #1 were just above detection
limits (0.01mg/L) for both sampling periods (Table 2.5). Values were significantly
higher in the controls for both September and April. In September, nitrate concentration
- -1 - -1 in the controls was 0.10 mg N- NO3 L compared to 0.06 - 0.08 mg N-NO3 L in the other treatments. The following spring, the controls had a concentration of 0.07 mg N-
- -1 - -1 NO3 L compared to 0.03 – 0.04 mg N-NO3 L in the other treatments. Well water,
which was frequently added to all mesocosms, was not analyzed for nitrate at macrophyte
- -1 peak biomass, but was determined to have a concentration of 0.67 mg N-NO3 L the following spring. For Study #2, there were no significant differences between diversity
41 treatments for interstitial water nitrate concentrations in either August or April although
differences were present for the September sampling period (Table 2.6). At this time,
- -1 nitrate was below detection limits (<0.01 mg N-NO3 L ) in the controls, 2 FG, and 4 FG
diversity treatments, was just detectable in the 1 FG diversity treatment, and was 0.07 mg
- -1 N-NO3 L in the 3 FG diversity treatment. For all diversity treatments, concentrations
- -1 were higher in the spring with ranges between 0.13 - 0.37 mg N-NO3 L . In both
studies, there was no correlation between interstitial water nitrate concentrations and
macrophyte functional group diversity evident (Table 2.7).
Study Sample Interstitial Water Sediment - No. date DOC NO3 Labile C Bacterial C C:N R2 P R2 P R2 P R2 P R2 P Sep 0.25 <0.001 0.12 <0.01 0.11 <0.01 0.01 0.21 0.00 0.89 1 April 0.00 0.63 0.04 0.09 0.15 <0.01 0.00 0.81 Com- 0.05 0.04 0.06 <0.01 0.14 <0.001 0.00 0.83 bined Aug 0.12 0.01 0.01 0.23 0.03 0.30 0.04 0.10 0.08 0.25 2 Sep 0.12 0.01 0.05 0.28 0.03 0.13 0.05 0.08 0.00 0.87 April 0.01 0.23 0.00 0.82 0.03 0.29 0.00 0.90 0.00 0.82 Com- 0.09 <0.01 0.01 0.19 0.01 0.39 0.01 0.40 0.00 0.48 bined Bacterial C data was not measured in April 2002
Table 2.7: Interstitial water and sediment parameters in relation to macrophyte functional
group diversity.
Sediment labile C values in September, Study #1 were the highest in the 5 FG diversity treatments although not significantly so (Table 2.5). Values ranged from 314 µg CO2-C
-1 -1 g dry sediment in the controls to 363 µg CO2-C g dry sediment in the 5 FG treatment.
-1 The following spring, the 4 FG diversity treatment (417 µg CO2-C g dry sediment) 42 -1 showed significantly higher values than the controls (297 µg CO2-C g dry sediment) and
-1 1 FG diversity treatments (315 µg CO2-C g dry sediment). In Study #2, labile C
concentrations in the macrophyte functional group diversity treatments were not
significantly different for any of the sampling periods (Table 2.6). Concentrations were
-1 highest in all treatments in August with ranges between 144 - 223 CO2-C g dry
-1 sediment. In September, concentrations ranged from 101-127 µg CO2-C g dry sediment
-1 and the following spring, concentrations ranged from 105-120 µg CO2-C g dry
sediment. A positive relationship between labile C and macrophyte functional group
diversity was only observed in Study #1, although the low R2 value suggested no causal
relationship (Table 2.7).
In both studies, bacterial biomass was not significantly different between the diversity
treatments. Total bacterial biomass in Study #1 ranged between 193 – 245 µg C g-1 dry sediment during the macrophyte peak biomass sampling period (Table 2.5). In the second study, the lowest active bacterial biomass occurred in August (19 - 31 µg CO2-C
-1 -1 g dry sediment) and the highest in April (86 - 112 µg CO2-C g dry sediment) with
-1 intermediate values in September (40 – 61 µg CO2-C g dry sediment; Table 2.6). No
relationship between bacterial C and macrophyte functional group diversity was apparent
for any sampling period in either study (Table 2.7).
Sediment C:N ratios were not significantly different between the diversity treatments in
either study. For Study #1, ratios ranged from 25 - 27 at peak biomass and 20 - 22 in the
spring (Table 2.5). In the second study, sediment C:N ratios in August and September
ranged between 20 – 22 (Table 2.6). The following spring, all of the diversity treatments
43 had significantly higher C:N ratios with 17-18 compared to the controls with 15. A slight
drop in the C:N ratio from fall to spring occurred for both studies and was due to a
reduction in sediment C and not an increase in sediment N. For Study #1, sediment C was ~ 4.4 % in September and ~ 3.7% in April while sediment N remained around 0.17%
for both sampling periods. In Study #2, sediment total C ranged from 2.4 - 2.8% in
September and 2.2 - 2.6% in April while total sediment N ranged from 0.12 - 0.13% in
September and 0.13 - 0.14% in April. No relationship between sediment C:N ratios and
macrophyte functional group diversity was evident in either study (Table 2.7).
2.4.2.2 In situ denitrification.⎯ The highest in situ denitrification occurred during
macrophyte peak biomass in Study #1. At this time, the second highest diversity
treatment (4 FG) had significantly higher fluxes than all other diversity treatments with
2 -1 2 -1 1182.2 µg N-(N2 + N2O) m day compared to 121.5 µg N-(N2 + N2O) m day in the 1
2 -1 FG diversity treatment and 256.7 ± 116.6 µg N-(N2 + N2O) m day in the 3 FG diversity treatment (Figure 2.8a). The lowest flux occurred in the controls with 34.7 µg
2 -1 N-(N2 + N2O) m day . The following spring, in situ denitrification dropped
considerably in all treatments with the highest total flux occurring in the controls (781.2
2 -1 µg N-(N2 + N2O) m day ), and the lowest occurring in the 2 FG diversity treatment
2 -1 (57.4 µg N-(N2 + N2O) m day ). Although a significant, positive relationship occurred
between in situ denitrification across the diversity gradient during peak biomass, this trend reversed during the following spring, and regressions combining both sampling dates showed no significant relationship (Figure 2.8b).
44 In Study #2, a significant difference between the diversity treatments for in situ N2 flux was only noted in April (Figure 2.9a). At this time, the 2 FG, 3 FG and 4 FG diversity
2 -1 treatments had the highest fluxes with 5152, 5662, and 5527 µg N-N2 m day ; respectively. The 1 FG treatments and controls showed the lowest fluxes at 2704 and
2 -1 2295 µg N-N2 m day ; respectively. Evidence for increased in situ denitrification flux across the macrophyte diversity gradient was only noted in the spring (Figure 2.9b).
When the August, September and April sampling periods were combined, no statistically significant relationship occurred.
45 1600 a a 1400 Sep'01 Apr'02 1200 1000 800 600 -1 400 b day b b -2 b 200 b ) m 2 0 O+N 2 2500 b Sep'01
g N-(N 2000 Apr'02
1500
1000 Sep 500 Apr 0 012345 Macrophyte functional group diversity treatments
Figure 2.8: In situ denitrification for each diversity treatment (a), and as a function of the number of functional groups (b), Study #1. Mean ± 1 SE, n = 6 except controls: n = 5, 1
FG: n = 25. 0 = controls, 1 FG = tussock, reed, facultative annuals, obligate annuals, clonal dominants; September 2001: R2 = 12, P <0.01; April 2002: R2 = 0.08, P=0.02; both sampling periods combined P = 0.77.
46 8000 Aug'02 a a 7000 a Sep'02 a 6000 Apr'03 5000
4000 b b 3000 2000 -1 1000 day
-2 0 m
2 16000 Aug'02 b 14000
g N-N Sep'02 12000 Apr'03 10000 8000 Apr 6000 4000 Aug 2000 Sep 0 01234 Macrophyte functional group diversity treatments
Figure 2.9: In situ denitrification for each diversity treatment (a), as a function of the
number of functional groups (b), Study #2. Mean ± 1 SE, n = 6 except 1 FG: n = 24; 0 =
controls, 1 FG = tussock, reed, facultative annual, obligate annual; August: P = 0.30;
September: P = 0.10; April: R2 = 0.31, P < 0.001; three sampling dates combined: R2 =
0.04, P = 0.02.
2.4.2.4 In situ denitrification with added nitrate.⎯ With nitrate addition, total in situ
denitrification in all diversity treatments increased more than 97% in September and
47 more than 84% the following spring. Despite the large increases in in situ denitrification,
no significant differences between the diversity treatments for N2 or N2O occurred at
either sampling period (Figures 2.10a,b). No significant differences between diversity
treatments in the N2: N2O ratio were evident. As well, there was no significant
relationship between in situ N2 or N2O fluxes with macrophyte functional group diversity in either September or April (Figure 2.10c,d). Nor, was there a significant relationship in total denitrification flux and macrophyte functional group diversity for both sampling periods combined.
48 In situ N2 Flux with nitrate added In situ N2O Flux with nitrate added 60 6 Sep'02 ab 50 5 Sep'02 Ap'03 Ap'03 40 4 30 3 20 2 10 1 -1 -1 0 0 day day -2 -2 0FG 1FG 2FG 3FG 4FG 0FG1FG2FG3FG4FG m 2 O m 120 2 12 Sep'02 c Sep'02 d 100 10 mg N-N
Apr'03 mg N-N Apr'03 80 8 60 6 Sep 40 4 Sep 20 Apr 2 Apr 0 0 0123401234
Macrophyte functional group diversity treatments
Figure 2.10: Macrophyte functional group diversity treatments after nitrate addition for in situ N2 flux (a), and in situ N2O flux (b) in situ N2 flux as a function of the number of macrophyte functional groups (c), and in situ N2O flux as a function of the number of macrophyte functional groups (d). Mean ± 1 SE, n = 6 except 1 FG = 24; 0 = controls, 1
FG = tussock, reed, facultative annuals, obligate annuals. P > 0.05 for all regressions.
49 2.4.2.4 Denitrification potential.⎯ In Study #1, denitrification potential was significantly higher in the highest diversity treatment (5 FG) than all other diversity treatments during macrophyte peak biomass (Figure 2.11a). At this time, flux for the 5
2 -1 FG diversity treatment was 8.4 mg N-(N2 + N2O) m day compared to ranges of 4.4 -
2 -1 5.7 mg N-(N2 + N2O) m day in the other diversity treatments. The following spring, no significant differences between the diversity treatments was evident. There was a positive relationship between denitrification potential and macrophyte functional group diversity in both September and April, and also for the two sampling periods combined
(Figure 2.11b). The R2 value, however was too low to suggest causality. In our second study, denitrification potential was higher in all treatments at peak biomass compared to mid summer or the spring, but there were no significant differences between diversity treatments for any of these sampling periods (Figure 2.12a). Fluxes ranged from 12.4 -
2 -1 2 -1 19.2 mg N-(N2 + N2O) m day in August, from 27.1 - 42.6 mg N-(N2 + N2O) m day
2 -1 in September and from 4.2 - 7.6 mg N-(N2 + N2O) m day the following spring. There was no increase in denitrification potential across the diversity gradient for any sampling period or all three sampling dates combined (Figure 2.12b).
50 12 a Sep'01 a 10 Apr'02
8 b a a b 6 b ab b b abc bc 4 c
-1 2 day
-2 0 ) m 2 18 b 16 Sep'01 O+N 2 14 Apr'02 12
mg N-(N 10 8 Sep 6 Apr 4 2 0 012345 Macrophyte functional group diversity treatments
Figure 2.11: Denitrification potential (a), and denitrification potential as a function of the number of macrophyte functional groups (b), Study #1. Mean ± 1 SE, n = 6 except 0 FG:
n = 5, 1 FG: n = 25; 0 = controls, 1 FG = tussock, reed, facultative annuals, obligate
annuals, clonal dominants. ANOVA P < 0.05; Regression results: September: R2 = 0.19,
P = 0.001; April: R2 = 0.18, P = 0.001; sampling periods combined R2 = 0.16, P < 0.001.
51 60 Aug'02 a 50 Sep'02 Apr'03 40
30
20 -1 10 day -2
) m 0 2 90 O+N
2 Aug'02 b 80 Sep'02 70 Apr'02
mg N-(N 60 50 Sep 40 30 20 Aug 10 Apr 0 01234 Macrophyte functional group diversity treatments
Figure 2.12: Denitrification potential (a) and as a function of the number of macrophyte functional groups (b), Study #2. Mean ± 1 SE, n = 6 except 1 FG: n = 24; 0 = controls, 1
FG = tussock, reed, facultative annual, obligate annual; P > 0.05 for ANOVA and regressions.
52 2.4.2.5 Denitrification flux per C pools.⎯ Analysis of in situ denitrification flux per unit
DOC in Study #1 showed significant differences between the diversity treatments in
September only. At this time, the 4 FG diversity treatment was significantly higher than the other diversity treatments (Figure 2.13a). A trend toward increasing in situ denitrification flux per unit DOC with increasing diversity also occurred at this time
(Table 2.8). The following spring, this trend was reversed with the controls and 1 FG diversity treatments showing higher in situ denitrification flux per unit DOC. With both sampling periods combined, no significant relationship was evident. In the second study, significant differences between the treatments only occurred in April (Figure 2.13b) with the 2 FG, 3 FG, and 4 FG diversity treatments showing significantly higher in situ denitrification flux per unit DOC than the 0 FG and 1 FG diversity treatments. This was also the only time in which there was a significant relationship between in situ denitrification flux per unit DOC relative to the functional group diversity treatments.
In situ denitrification flux per unit labile C for Study #1 was significantly higher in the second highest diversity treatment (4 FG) during macrophyte peak biomass (Figure
2.13c). The following spring, in situ denitrification flux per unit labile C was significantly higher in the controls. A significant relationship between in situ denitrification flux per unit labile C and macrophyte functional group diversity was only evident in September (Table 2.8). For Study #2, significant differences between treatments for in situ denitrification flux per unit labile C occurred only in April with the higher diversity treatments showing the higher values (Figure 2.13d). This was also the only time that a significant relationship across the diversity gradient was observed (Table
2.8). 53 Study #1 Study #2 -1 45 250 a -1 a b day Sep'01 Aug'02 -2 40 a a day Sep'02 35 Apr'02 -2 200 Apr'03 30 DOC m
-1 150 25 DOC m ab 20 -1
) mg/L 100 2 15 mg/L
a 2 b O+N
2 10 50 b b 5 b b g N-N
b µ
g N-(N 0
µ 0
-1 0.40 40 c -1 Aug'02 d day 0.35 Sep'01 a 35 a -2 a day
Apr'02 -2 Sep'02 0.30 30 Apr'03 ab 0.25 25 labile C m
-1 0.20 20 labile C m
-1 abc
) mg 15 2 0.15 b mg b 2 10 O+N 0.10 b b 2 b b a b b 5 bc c ab
g N-N b ab 0.05 b b b µ g N-(N 0 0.00
-1 0.50 45 a e -1 f 0.45 40 Aug'02 day Sep'01 -2
0.40 day Sep'02
-2 35 0.35 30 Apr'03 0.30
bact C m 25 -1 0.25 bact C m
-1 20
) mg 0.20 2 b 15 0.15 mg 2
O+N b 2 b 10 0.10 b a a a
0.05 b g N-N 5 b b µ g N-(N
µ 0.00 0 -1 0.9 10 g -1 a h day 0.8 root biomass 9 root biomass -2
total biomass day 0.7 -2 8 total biomass 0.6 7 0.5 6 biomass m
-1 5 0.4 biomass m ) g 4 2 0.3 -1 ab g 3 2 O+N
2 0.2 2 b b 0.1 g N-N 1 µ
g N-(N 0.0
µ 0 1FG 2FG 3FG 4FG 5FG 1FG 2FG 3FG 4FG Macrophyte functional group diversity treatments
Figure 2.13: In situ denitrification flux: per unit DOC Study #1 (a) and Study #2 (b);
54 per unit labile C Study #1 (c) and Study #2 (d); per unit bacterial C Study # 1 (e) and
Study #2 (f); and per unit root and total plant biomass Study #1 (g) and Study #2 (h).
Mean ± 1 SE, n = 6 except 0 FG: n = 5 and 1 FG: n = 25; 0 FG = controls, 1 FG = clonal dominant, tussock, reed, facultative annual, and obligate annual; Bars with different letters are significantly different at P<0.05 for that sampling period.
Macrophyte FG diversity versus in situ denitrification flux per unit: Study Sample DOC Labile Bacterial Root Total plant # dates C C biomass biomass R2 P R2 P R2 P R2 P R2 P 1 Sep 0.40 <0.001 0.28 <0.001 0.08 0.05 0.03 0.18 0.04 0.15
Apr 0.07 0.04 0.09 0.02
Com- 0.01 0.62 0.11 0.001 bined 2 Aug 0.01 0.22 0.14 <0.01 0.00 0.72
Sep 0.00 0.97 0.01 0.47 0.01 0.35 0.13 0.01 0.13 0.01
Apr 0.17 0.03 0.10 0.03 0.22 0.001
Com- 0.02 0.11 0.03 0.02 0.01 0.55 bined Bacterial C data was not collected for Study #1 in April 2002 and root and total plant biomass is for macrophyte peak biomass periods only.
Table 2.8: Relationship between macrophyte functional group diversity and in situ
denitrification flux per unit DOC, labile C, bacterial C, root biomass, and total plant biomass.
55 In situ denitrification per unit bacterial biomass was significantly higher in the 4 FG
diversity treatment in Study #1 (Figure 2.13e) although there was no relationship with
macrophyte functional group diversity (Table 2.8). In the second study, the 2 FG, 3 FG
and 4 FG diversity treatments showed significantly higher in situ denitrification flux per unit bacterial C than the controls and 1 FG diversity treatment (Figure 2.7f). The relationship with macrophyte functional group diversity was significant both for August and April (Table 2.8); however, the low R2 value in each case did not suggest causality.
In situ denitrification per unit root biomass and total plant biomass for both studies was
calculated at macrophyte peak biomass. In Study #1, no significant difference between
diversity treatments for either in situ denitrification flux per root biomass or total biomass
was evident (Figure 2.13g), nor was there a correlation with macrophyte functional group
diversity (Table 2.8). In the second study, the 1 FG diversity treatment had a
significantly higher N2 flux per unit root biomass than the 3 FG and 4 FG diversity
treatments, but this was not the case for total biomass (Figure 2.13h). There was a trend
showing increasing N2 flux per root biomass and total biomass with decreasing
macrophyte functional group diversity, although this relationship was not significant
(Table 2.8).
With nitrate addition, in situ N2 flux per unit DOC (Figure 2.14a), labile C (Figure
2.14b), bacterial C (Figure 2.14c) and root and total plant biomass (Figure 2.14d) was not
significantly different between the diversity treatments. In all cases, variance between
replicates for each treatment was quite high.
56 4000 -1 250 -1 Sep'02 a Sep'02 e
3500 day day Apr'03 -2
-2 200 Apr'03 3000
2500 150 DOC m DOC m 2000 -1 -1 1500 100 mg/L 2 1000 O mg/L 2 50 500 g N-N g N-N µ 0
µ 0 0FG 1FG 2FG 3FG 4FG 0FG 1FG 2FG 3FG 4FG
-1 9
-1 180 8 Sep'02 f 160 Sep'02 b day -2 day Apr'03
-2 7 140 Apr'03 6 120 a 5 100
labile C m 4 -1
labile C m 80 -1 60 3 ab mg O mg
2 2 40 2 b b b 20 1 g N-N 0 g N-N 0 µ µ 0FG 1FG 2FG 3FG 4FG 0FG 1FG 2FG 3FG 4FG
350 -1 12 -1 c Sep'02 a g
Sep'02 day day
300 -2 -2 10 Apr'03 Apr'03 m 2
250 m -C 2 8 200 6 b
150 bact CO bact C-CO -1 -1 4 b 100 b mg 2 0 mg
2 b 50 2 g N-N g N-N µ
0 µ 0 0FG 1FG 2FG 3FG 4FG 0FG 1FG 2FG 3FG 4FG
14 450 -1 -1 root biomass 400 root biomass d h
day 12
day -2 total biomass
-2 350 total biomass 10 300 250 8
200 biomass m 6 biomass m -1 -1 150 g
O g 4 2 100 2 2 50 g N-N g N-N µ 0 µ 0 1FG 2FG 3FG 4FG 1FG 2FG 3FG 4FG Macrophyte Functional Group Diversity Treatments
Figure 2.14: In situ N-N2 flux with nitrate addition per unit DOC (a), labile C (b),
57 bacterial C (c), root and total plant biomass (d); and in situ N-N2O flux per unit DOC (e),
labile C (f), bacterial C-CO2 (g), and root and total plant biomass (h). Results are from
Study #2 only. Mean ± 1 SE, n = 6 except 1 FG: n = 24; 0 FG = controls, 1 FG =
average values for tussock, reed, facultative annual, obligate annual. Values with
different letters above bars are significantly different at P < 0.05.
After nitrate addition, in situ N2O flux per unit DOC (Figure 2.14e), labile C (Figure
2.14f), bacterial C (Figure 2.14g), and root and total biomass (Figure 2.14h) was only significantly different between diversity treatments in September. At this time, the highest diversity treatment (4 FG) was significantly higher in in situ N2O flux per units
labile C and bacterial C than the 1 FG, 2 FG, and 3 FG diversity treatments. No
significant correlations were evident for in situ N2 or N2O fluxes per unit DOC, labile C,
bacterial C, root biomass and total plant biomass with macrophyte functional group
diversity for any sampling period or for all sampling periods combined (data not shown).
Analysis of denitrification potential per unit DOC, labile C, bacterial C, root biomass
and total biomass for both studies were not consistent (Figure 2.15). Denitrification
potential per unit DOC was significantly correlated to increasing macrophyte functional
group diversity during peak biomass in the first study (Table 2.9).
58 Macrophyte FG diversity versus denitrification potential flux per unit: Study Sample DOC Labile Bacterial Root Total plant # date C C biomass biomass R2 P R2 P R2 P R2 P R2 P 1 Sep 0.26 0.001 0.44 <0.001 0.09 0.01 0.03 0.13 0.06 0.08
Apr 0.04 0.07 0.10 0.01
Com- 0.07 0.01 0.02 0.28 Bined 2 Aug 0.04 0.11 0.03 0.13 0.04 0.11
Sep 0.05 0.08 0.05 0.08 0.02 0.19 0.07 0.05 0.12 0.02
Apr 0.00 0.82 0.05 0.09 0.00 0.95
Com- 0.02 0.07 0.04 0.01 0.01 0.11 bined Bacterial C data was not measured April 2002 and root and total plant biomass is for peak biomass periods only; Study #1: Sep., Apr., n=54, combined n=108; Study #2: Aug., Sep., Apr., n=46, combined n=138.
Table 2.9: Relationship between macrophyte functional group diversity and denitrification potential flux per unit DOC, labile C, bacterial C, root biomass, and total plant biomass.
At this time, denitrification potential per unit DOC was significantly higher in the 4 FG and 5 FG diversity treatments than the other diversity treatments (Figure 2.15a). No significant differences between the diversity treatments were evident the following spring. In the second study, denitrification potential per unit DOC was the highest for all treatments at macrophyte peak biomass although there were no significant differences between treatments at this time (Table 2.9). Significant differences were only noted in
August with the 2 FG diversity treatment higher than the controls, 1 FG, and 3 FG diversity treatments (Figure 2.15b).
59 Study #1 Study #2
250 -1 3500 -1 a Sep'01 a Aug'02 b day day
-2 3000 -2 200 Apr'02 Sep'02 2500 Apr'03 DOC m DOC m 150 -1 2000 -1 ab 1500 )mg/L
ab 2
) mg/L 100 2 b 1000 O+N
2 a O+N
2 b 50 b 500 ab b b b g N-(N µ
g N-(N 0
µ 0 -1 70 -1 2.5 d Sep'01 c day Aug'02 -2
day 60 -2 2.0 Apr'02 Sep'02 50 a Apr'03 a labC m -1 lab C m lab C 1.5 40 -1
) mg 30 2 ) mg
2 1.0 20 O+N 2 O+N b 2 b 0.5 b b 10 g N-(N g N-(N 0 µ µ 0.0 -1 -1 4.5 120 day f
e -2 day 4.0 Sep'01 Aug'02 -2 100 Sep'02 a 3.5 m -C 2 3.0 80 Apr'03
bact C m 2.5 b -1 bact CO 60 b 2.0 -1
) mg b 2 40 b 1.5 ) mg 2 1.0 O+N
2 20 O+N 0.5 2 0.0 0 g N-(N g N-(N µ µ -1 25 -1 400 g h day root biomass day root biomass
-2 350 20 -2 total biomass 300 total biomass 15 250 200 biomass m biomass biomass m biomass -1 10 -1 150 ) g ) g 2 2 100 5 O+N O+N 2 2 50 0 0 gN-(N g N-(N
µ 1FG 2FG 3FG 4FG
1FG 2FG 3FG 4FG 5FG µ
Macrophyte functional group diversity treatments
Figure 2.15: Denitrification potential per unit DOC for Study #1 (a), Study #2 (b); per
60 unit labile C Study #1 (c), Study #2 (d); per unit bacterial C Study #1 (e), Study #2 (f); and per unit root and total plant biomass Study #1 (g), Study #2 (h). Mean ± 1 SE;
Study #1: n = 6 except 0 FG: n = 5, 1 FG: n=25; Study #2: n = 6 except 1 FG: n = 24.
Study #1: 1 FG = clonal dominant, tussock, reed, facultative annual, and obligate annual;
Study #2: 1 FG = tussock, reed, facultative annual, and obligate annual. Values with different letters are significantly different at P < 0.05.
There was no relationship evident between denitrification flux per unit DOC and macrophyte functional group diversity (Table 2.9).
Analysis of denitrification potential flux per unit labile C in Study #1 showed the controls and 1 FG diversity treatments to be significantly higher than the higher diversity treatments at macrophyte peak biomass only (Figure 2.15c). At this time, there was also a significant, negative relationship between macrophyte functional group diversity and flux per unit labile C (Table 2.9). The following spring, flux per unit labile C was higher in all diversity treatments, but they were not significantly different. There was no evidence of a relationship between macrophyte functional group diversity and denitrification potential per unit labile C (Table 2.9). In the second study, significant differences between diversity treatments for denitrification potential per unit labile C were not apparent (Figure 2.15d). Flux per unit labile C showed similar trends in the 2
FG, 3 FG and 4 FG diversity treatments for all sampling periods and the ranges within treatment replicates were high. There was also no significant relationship between macrophyte functional group diversity and denitrification potential flux per unit labile C for any sampling period, or for all sampling periods combined (Table 2.9). 61 Denitrification potential per unit bacterial C was not significantly different between any of the treatments in the first study (Figure 2.15e). Also, there was no relationship between denitrification potential flux per unit bacterial C and macrophyte functional group diversity. In the second study, significant differences between diversity treatments were only noted in August with the 2 FG diversity treatment showing a significantly higher flux per unit bacterial C than all other treatments (Figure 2.15f). As with Study
#1, there was no relationship between denitrification potential flux per unit bacterial C and macrophyte functional group diversity (Table 2.9).
Differences between the diversity treatments for denitrification potential flux per unit root biomass or total plant biomass were not evident in either Study #1 (Figure 2.15g) or
Study #2 (Figure 2.15h). In both studies, denitrification potential per unit root biomass was consistently higher in the 1 FG diversity treatment, but there was a high variance within replicates for all treatments. There was no indication of a relationship between denitrification potential flux per unit root biomass or per unit total plant biomass with macrophyte functional group diversity (Table 2.9).
2.4.3 Factors influencing denitrification function
Significant relationships between in situ denitrification and denitrification potential with the C pools (DOC, labile C, bacterial C, sediment C:N ratios, root biomass and total plant biomass) in Study #1 were not evident (Table 2.10). In the second study, significant relationships between in situ denitrification (nitrate addition) with bacterial C
(R2 = 0.23), and sediment C:N ratios (R2 = 0.22) were observed. The R2 values and lack
62 of similar results in Study #1 suggests there were other influences on denitrification
function besides these factors.
A best subsets analysis also did not indicate any consistent combinations of factors
influencing denitrification function in either study (Table 2.11). The strongest
relationship (R2 = 0.55) occurred in Study #1 for denitrification potential at macrophyte
peak biomass with the six factors: macrophyte functional group diversity, labile C,
bacterial C, sediment C: N ratios, aboveground plant biomass, and root biomass. The
strongest relationship in Study #2 (R2 = 0.48) occurred for in situ denitrification in April
with macrophyte functional group diversity, labile C, bacterial C, and sediment C:N.
Overall, relatively low predictability values emerged for both studies which ranged from
R2 = 0.12 to R2 = 0.55 further suggesting the influence of other factors on denitrification within our treatments.
63 Study #1 Study #2 Regression Parameters R2 P R2 P In situ denitrification vs DOC 0.02 0.10 0.01 0.22 In situ denitrification vs labile C 0.00 0.48 0.02 0.16 In situ denitrification vs bacterial C 0.00 0.84 0.02 0.12 In situ denitrification vs sediment C:N 0.00 0.76 0.05 0.01 In situ denitrification vs roots* 0.00 0.73 0.01 0.64 In situ denitrification vs total plant biomass* 0.00 0.53 0.01 0.52 In situ denitrification nitrate added vs DOC 0.00 0.90 In situ denitrification nitrate added vs labile C 0.03 0.11 In situ denitrification nitrate added vs bacterial C 0.23 <0.001 In situ denitrification nitrate added vs sediment C:N 0.22 <0.001 In situ denitrification nitrate added vs roots* 0.00 0.78 In situ denitrification nitrate added vs total plant biomass* 0.01 0.46 Denitrification potential vs DOC 0.00 0.62 0.05 0.02 Denitrification potential vs labile C 0.07 0.01 0.01 0.33 Denitrification potential vs bacterial C 0.02 0.30 0.16 <0.001 Denitrification potential vs sediment C:N 0.00 0.98 0.07 <0.001 Denitrification potential vs roots* 0.01 0.56 0.03 0.33 Denitrification potential vs total plant biomass* 0.02 0.36 0.09 0.06 Regressions included all data for all sampling dates for each study. No in situ denitrification with nitrate addition was available for Study #1. Regressions∗ with root and total plant biomass are for peak biomass sampling dates only (Study #1: Sep. 2001; Study #2: Sep. 2002).
Table 2.10: Relationships between denitrification and C pools.
64 Effect Cause Factors Factors - 2 Study Date Denitri- FG DOC Lab NO3 Bact C:N Shoot Root R fication No. C C #1 Sep in situ √ √ √ √ √ √ √ 11.8 potential √ √ NI √ √ √ √ 55.0 Apr in situ √ √ NI NI NI 20.6 potential √ √ NI NI √ NI NI 26.0 #2 Au in situ √ √ NI NI 11.5 potential √ √ NI √ √ NI NI 27.0 Sep in situ √ √ √ √ √ √ 34.0 potential √ NI √ √ √ 37.7 Apr in situ √ √ √ √ NI NI 47.5 potential √ √ NI √ NI NI 44.3 All cause factor variables were analyzed in the Best subsets regression except where indicated as not included (NI). R2 values denote the best predictor relationship obtained with the cause factors denoted by a check mark (√). Blank cells indicate that particular cause factor as not included within the best subsets - regression result. FG # = functional group number, lab C = labile C, NO3 = interstitial water nitrate, Bact C = bacterial C, C: N = sediment C: N ratio, shoot = aboveground plant biomass, root = root biomass.
Table 2.11: Highest predictor variables for in situ denitrification and denitrification potential for each sampling period.
65 2.5 DISCUSSION
The central hypothesis was based on the concept of niche-complimentarity in which the
community performance becomes greater than the sum of each individual in monoculture
and N + 1 species or functional groups out perform N (Tilman et al. 2001). It was
expected that there would be differences in the quantity and/or quality of C between the
macrophyte functional groups. These differences were anticipated to result in a greater
variety of bioavailable C to the sediment microbial community as macrophyte functional
group diversity increased, thereby enhancing the decomposition related process
denitrification. For both studies, no clear patterns indicating differences between the macrophyte functional groups in C pools or denitrification emerged. With few exceptions, C pools and denitrification fluxes were no different in the diversity treatments than they were within the monoculture functional groups. Evidence for reduced N2O flux across the macrophyte functional group diversity gradient was also not apparent.
However, there were differences between the monoculture macrophyte functional groups suggesting that community composition played a role. These three main findings are discussed below.
2.5.1 Macrophyte Functional Groups: C pools and Denitrification
The first working hypothesis stated that there would be significant differences between the macrophyte functional groups in C pools, and in turn, denitrification function. The selection of macrophyte functional groups rather than individual species was intended to obtain a larger separation along the niche-space continuum in order to observe greater effects due to functional group assemblages on ecosystem processes (Lawton 2000). In
66 other words, the use of functional groups with larger differences separating them should
promote a greater degree of measurable differences. Our functional groups were based
on dissimilarities in traits including life span, total above-and belowground biomass
allocation, photosynthetic area, crown cover, total number of tillers and shoots, diameter of belowground rhizomes and roots and relative growth rates (Boutin and Keddy 1993).
These differences were expected to manifest between seasons. In the mesocosms, at macrophyte peak biomass, the majority of available C was expected to be through root exudates and decomposition of organic matter present within the sediment while the standing biomass would be contributing little C (Beauchamp et al. 1989). The following spring, the senesced plants, including the standing dead and sloughed plant material, was expected to contribute to C availability. Therefore, during plant growth the macrophytes with higher root biomass would be expected to provide higher C through root exudation, while in the spring, differences between the macrophytes for plant matter decay would be expected to influence bioavailable C.
All species selected for our two studies were rooted emergent macrophytes even though a variance in plant architecture (submerged, floating, emergent), is generally observed within naturally occurring wetlands. Examination of decomposition rates for macrophytes has determined floating-leaved plants to contain the least amount of structural tissue and to decay most rapidly followed by submersed and then emergent species (Godshalk and Wetzel 1978, Webster and Benfeld 1986). None-the-less, we would still anticipate some differences between the emergent macrophytes for root exudates and total plant decomposition. Segments along one emergent macrophyte
Phragmites, differed considerably in quality, breakdown rates, and nutrient dynamics 67 (Gessner 2000) and differences in litter quality and exudation of organic compounds from roots of different species are known to affect mineralization rates (Chapin et al. 1997).
Some differences between the monoculture functional groups for DOC and labile C in
Study #1 and DOC and bacterial C in Study #2 were measured. DOC was consistently higher within the facultative annuals for both studies during macrophyte peak biomass.
This particular functional group also had the lowest above- and belowground biomass of all the treatments. These higher DOC concentrations may be indicative of lower microbial utilization since bacterial biomass was not significantly lower in this treatment.
Or, it may be due to differences in DOC composition between the macrophyte functional groups. In most aquatic systems, DOC has two distinct pools of dissolved compounds, one labile and one refractory (Moran and Hodson 1990). The labile fraction of DOC as a percentage of total DOC is ~14-19% in freshwaters (Sondergaard and Middelboe 1995).
Differences in bacterial utilization of DOC may result from inherent differences in DOC composition since vascular plant derived detritus are likely to be more recalcitrant due to the influence of lignin, whereas algal derived humic substances contain relatively more aliphatic properties (Moran and Hodson 1990). In wetland ecosystems characterized by submerged macrophytes, the extremely high surface area of living and senescing and dead tissues within the water column promotes the development of a highly mutualistic attached microbial community as well as acting as a source of DOC (Wetzel and
Sondergaard 1998). Nutrients within senescing macrophytes and their epiphytic microflora are displaced to the sediment surfaces and recycled. Although the water column within our mesocosms was fairly shallow, with depths never exceeding 7 cm, there would still be sediment/water column interactions occurring and algae blooms 68 appeared to be consistently higher within the facultative annuals possibly adding to DOC
concentrations. The activity of extracellular enzymes has also been identified as a rate- limiting step in bacterial utilization of DOC (Sondergaard and Middelboe 1995). Also, the lack of an appropriate N and P source could, for a period, perturbate the stoichiometry of bacterial substrate utilization and allow accumulation of DOC. Mineralization rates within the facultative annual treatment may have been dampened due to the lack of root biomass and senescent organic matter. A rapid and continuous buildup of water extractable C was observed following nitrate disappearance during anaerobic decomposition of alfalfa and straw (deCatanzaro and Beauchamp 1985).
Differences in the labile C pools between the macrophyte functional groups were only significant in the first study although these differences did not appear to correlate with plant biomass. For instance, the clonal dominants had higher root biomass on average than the other four macrophyte groups combined, although labile C was not any different than the tussocks, facultative annuals, or obligate annuals. Significant differences in labile C were not observed until the following spring when the clonal dominants had significantly higher labile C concentrations than the other functional groups. However, this did not result in higher in situ denitrification or denitrification potential. In fact, the tussocks and facultative annuals both had significantly higher in situ denitrification at this time. The limited availability of nitrate may have been the rate limiting step explaining low in situ denitrification within the clonal dominant treatment despite what appeared to be sufficient bioavailable C. Denitrification is complicated by the fact that although plants offer microbes energy in the form of litter and root exudates, they also compete for nutrients (Mikola and Setala 1998). Denitrification in the short-term may actually be at 69 odds with plant productivity especially if denitrifiers and plants are both competing for a
limited resource such as nitrate (Hooper and Vitousek 1998). Furthermore, clonal
dominant species are known to be strong competitors for dissolved nutrients (Kadlec and
Knight 1996). However, this does not explain the lack in differences between the clonal
dominants and the other macrophyte functional groups for denitrification potential since
this assay has non-limiting nitrate and plants are not present. Bacterial biomass was not
any different in the clonal dominants than it was within the other functional groups which
may partly explain this result. As well, the fact that there was not more bacterial biomass accompanying the significantly higher plant biomass and labile C within the clonal dominants hints at the complexity of ecosystem processes and suggests that these two factors may not always be directly related (Beauchamp et al. 1989). A syntrophism is known to exist between denitrifying bacteria and anaerobic cellulose fermentors.
Denitrifiers use the breakdown products of the cellulases as well as the products of fermentation. For example, acetate C is a product of fermentation and therefore, cannot be used as an energy source by fermentative bacteria while glucose can be used by both fermentators and denitrifiers. However, the fermentators appear to be better competitors than the denitrifiers for glucose since more efficient nitrate removal from wastewater occurred with acetate rather than glucose as an energy source. Furthermore, this occurred despite the fact that three times as much C is required to produce microbial biomass from acetate than with glucose (Stouthamer 1976).
Another complication is that bacterial community consumption of simple organic compounds differ in their half saturation constant (Ks) depending upon the dominant
microbial population’s affinity for the substrate (Sondergaard and Middelboe 1995). 70 Studies have shown different Ks values for identical compounds in different systems.
Hence, there are numerous complex relationships between plants and microbial
communities that tend to confound analysis of decomposition related processes such as
denitrification. It has been suggested that in ecosystems, such as grasslands, where one
growth form tends to dominate, short-term effects on litter decomposition are likely to be relatively small, yet complex (Hobbie 1996). In one study, plant productivity did not correlate with resource use due to a number of factors including the interplay between microbes and plants for available resources (Hooper and Vitousek 1998). Despite these complexities, the lack in differences between the tussocks, reeds, facultative annuals and obligate annuals in both of our studies suggests that differences in their C pools were not significant enough to be detected using our methods. At macrophyte peak biomass, all four functional groups had similar labile C, bacterial C, sediment C:N ratios, and with the exception of the facultative annuals, similar DOC.
The lack of detection of differences in the C pools may have been due to the fact that the majority of important decomposer activity within aquatic ecosystems appears to be occurring within the water column on submerged plant material (Webster and Benfield
1986, Wetzel and Sondergaard 1998). Much more fundamental structuring of microbial metabolism and biochemical cycling occurs from the development of submerged macrophyte communities (Wetzel and Sondergaard 1998). Available oxygen within the water column promotes rapid decomposition of organic matter by the microflora as well as shredders, grazers and macroinvertebrates, while detrital metabolism is slower and more evenly sustained on a much larger organic reserve (Wetzel 1995). For instance, during seagrass decomposition within coastal wetlands, water column bacteria were 71 observed to function as the link in the transfer of primary production to aquatic food webs and not the bacteria associated with detrital particles (Blum and Mills 1991). Also, within freshwater microcosms, where the diversity of producers (green algae) and decomposers (heterotrophic bacterial) was manipulated, significant treatment effects of algal species richness on mean number of organic carbon sources used was indirectly affected by the impact of producer diversity on bacterial communities (Naeem et al.
2000). It was noted that bacterial exploitation of organic carbon sources were the link between decomposer diversity and algal production within the water column. As well, in a mesocosm study using rooted submerged macrophytes, it was observed that plant biomass and phosphorus retention increased with increased species diversity although these results were relative to water column characteristics and not sediment (Engelhardt and Ritchie 2001). It appears that by the time plant litter has been degraded to the point where it is utilized by the heterotrophic microbial community within sediments, little of the original character of the particular plants remain, and highly labile portions are readily taken up, whatever the source (Schipper et al. 2001).
Given the lack of differences in C pools between the macrophyte functional groups, it should not be surprising that few differences were observed in denitrification fluxes.
When significant fluxes were noted, it was within the tussocks and reeds suggesting that the differences in traits between the macrophyte functional groups does manifest in differences in denitrification. Since the C pools do not explain these results, the interactions between the plants, microbial consortia, mineralization rates, competition, and rhizosphere oxic/anoxic zones must all contribute to the complexity and understanding of these links. 72 2.5.2 Macrophyte Functional Group Diversity: C pools and Denitrification
The second working hypotheses stated that an increase in macrophyte functional group diversity would enhance C pool quantity and/or quality due to niche complimentarity and thereby result in increased denitrification function. However, there was no evidence of a relationship between labile C pools and macrophyte functional group diversity. If niche
complimentarity occurred within these treatments, it would be expected that labile C
would increase across the diversity gradient. This would be related to increased plant
biomass (Tilman et al. 1997, Hooper and Dukes 2004) and/or increased diversity of C
sources because of increased macrophyte diversity (Chapin et al. 1997). In the first
study, there was a significant increase in macrophyte biomass across the diversity
gradient (Bouchard et al., in prep). This result was attributed to the clonal dominants that
represented the bulk of plant biomass within all diversity treatments when present, and
indicated the occurrence of a sampling effect.
The removal of the clonal dominants in the second study resulted in greater evenness
between all functional groups in the diversity treatments thereby providing an
opportunity to observe the occurrence of niche-complimentarity. However, there were no
observed differences in labile C across the macrophyte functional group diversity
gradient. Nor, were there any differences in bacterial C, DOC or sediment C:N ratios.
These results suggest that, rather than niche-complimentarity, there was an averaging
effect.
Results from a number of diversity studies indicate that there is no relationship
between plant species diversity or plant functional group diversity and sediment
decomposition related processes. The majority of studies examining relationships 73 between plant functional group diversity and ecosystem function have focussed on
terrestrial ecosystems (Tilman et al. 1997, Hooper and Vitousek 1998, Wardle et al.
1999, Hector et al. 2000). Functional group criteria for these studies were based upon
characteristics relevant to nutrient cycling such as phenology, rooting depth, root: shoot ratio, size and leaf C:N content, resource requirements, seasonality of growth, and life
history. Despite differences in the type of plant functional groups, similar conclusions
were made with regard to decomposition and belowground processes. In all cases, the diversity of functional groups did not impact decomposition processes. Rather, individual functional groups with particular functional traits had a greater impact upon the ecosystem process being measured. Wardle et al. (1999), suggest that plant functional group diversity has little impact belowground due to the nature of decomposition processes. These processes are regulated by the magnitude of the active soil microbial biomass, the biomass and populations of soil animals that catalyze its turnover, and the structure of the decomposer food web.
In other studies, decomposition processes relative to species diversity, rather than
functional group diversity, have shown both non-additive effects and idiosyncratic
responses across the diversity gradient (Chapman et al. 1988, Blair et al.1990, Fyles and
Fyles 1993, Naeem et al. 1994, Rustad 1994, Wardle and Nicholson 1996, Wardle et al.
1997, Hooper and Vitousek 1998, Bardgett and Shine 1999, Nilsson et al.1999, Schipper
et al. 2001). In boreal forests, plant litter diversity and composition were not linked to
soil microbial biomass or activity (Nilsson et al. 1999). In some cases individual species
effects and litter mixing effects were important, but few general patterns emerged and the
nature of significant effects were summarized as idiosyncratic. Within microcosms 74 simulating grassland systems using a diversity of litter types, treatments varied in the nature of the effects of each added species and were attributed to plant functional characteristics rather than diversity per se (Bardgett and Shine 1999). Increasing species richness of plant litter beyond two species did not result in predictable changes in ecosystem properties and litter diversity tended to have both negative and positive effects on the soil microbial biomass. In a study examining terrestrial microcosms, in which plant and animal diversity was manipulated, short-term decomposition rates differed among treatments but not consistently (Naeem et al. 1994). As well, long-term decomposition showed no significant diversity treatment effects. In all cases individual species effects appeared to play a much larger role and helped to explain the idiosyncratic results obtained within the diversity treatments.
Despite the fact that our research was specific to wetland ecosystems, there appears to be commonalties with terrestrial ecosystems for some factors related to decomposition.
We observed similar results to those occurring within sediments in boreal forests (Nilsson et al. 1999) and grasslands (Wardle et al. 1997) in that bacterial biomass was unaffected by plant diversity treatments. We also found similar results to those of Wardle et al.
(1999) in relation to sediment C:N with functional group diversity showing no impact on this ratio. Wardle et al. (1999) suggested this result was due to the fact that sediment C:N tends to reflect longer term changes than those which take place within the course over a two year study. It was also indicated that a buffering effect due to residual C may have been masking detection of differences due to treatments of the measured parameters.
We also observed a buffering effect particularly within the controls despite the low initial C within our sediments (Study #1, 4.0% C; Study #2, 2.5% C). The controls 75 contained no macrophytes yet the sediment C pool was sufficient to support heterotrophic
denitrification since flux was measured during all sampling periods. In fact, in all cases,
flux was no different in the controls than within treatments with one or more macrophyte functional group present. It appears that even with low C concentrations, the bioavailable
portion available to denitrifiers was sufficient. Since the sediment in the mesocosms
contained considerably less organic matter than the 12 - 20% or greater typically found in naturally occurring wetlands (Mitsch and Gosselink 2000), a relatively low threshold level of organic matter may be sufficient for denitrification function.
Given the fact that we did not observe differences in the C pools across the diversity gradient, it is not surprising that increased macrophyte functional group diversity did not result in increased denitrification function. At macrophyte peak biomass, in both studies, in situ denitrification was not any higher within the treatments containing all functional groups than within the individual macrophyte functional group treatments. This was also the case in Study #2 for in situ denitrification flux after nitrate addition, and denitrification potential. The only time increased denitrification was related to increased macrophyte functional group diversity occurred in the first study for denitrification potential. This result may be explained by a niche-complimentarity effect since the denitrification potential assay ensures conditions are similar for each sample including non-limiting nitrate concentrations. Theoretically, the only differences between the samples is the amount of C available to the denitrifiers to use as an energy source and/or the denitrifier communities themselves. All things being equal, it would be expected that the treatments with more bioavailable C would promote higher denitrification potential flux. However, the more likely explanation, since only two of the six replicates in this 76 highest diversity treatment were driving this average upward, is due to the nature of the
complexities involved in denitrification.
It is not uncommon for studies examining denitrification to be hindered by high spatial
and temporal variability even with intensive sampling (Murray et al. 1995). Denitrifying
‘hotspots’ are known to exist, particularly around roots, which tends to hinder attempts to
quantify denitrification rates with field scale variables (Groffman 1991, Groffman et al.
2000). The main factors known to influence denitrification in wetlands are nitrate, labile
carbon, sediment redox potential, pH, and temperatures (Groffman et al. 1992, Schipper
et al. 1993, Hanson et al. 1994, Lindau et al. 1994, DeLaune et al. 1996, Tomaszek et al.
1997, D’Angelo and Reddy 1999). During all sampling periods for our two studies, the
range in temperatures and pH were well within those considered as non-inhibiting for
denitrifying bacterial activity. Also, sediments were always flooded during in situ
denitrification flux measurements to promote low redox with evidence of anoxic
conditions in extracted sediment cores. We did find interstitial water nitrate concentrations to be low and possibly limiting for in situ denitrification. This was evident in the second study in which greater than 85% increases in flux were noticed after a nitrate solution of 4 mg/L was added to each mesocosm. However, significant differences between the diversity treatments were still not evident.
With few exceptions, no relationships between denitrification flux and any of the sediment or interstitial water C pools were observed. Of the ten denitrification flux analyses that took place, no two showed the same suite of best predictor variables.
77 2.5.3 Nitrous oxide flux
Our third working hypothesis stated that there would be a reduction in N2O flux as
diversity increased. This was based on the premise that increased macrophyte functional
group diversity would increase C pools promoting greater bacterial diversity, and in turn,
greater denitrifier diversity with the ability to produce more active nitrous oxide
reductase enzymes. In situ N2O flux was only detected in the second study after nitrate
was added to the mesocosms, although there were no significant differences observed in
N2O across the diversity gradient. Significant differences in the in the N2:N2O ratios were
also not detected. There was however, significantly higher N2O flux in one of the
monoculture macrophyte groups. During macrophyte peak biomass, the obligate annuals
emitted significantly higher flux of this greenhouse gas than the other macrophyte
functional groups. The following spring, the obligate annuals also had a higher in situ
N2O flux than all other treatments, although this was not significantly different.
One explanation for the obligate annuals emitting higher N2O may be that they did not up-take the available nitrate as readily as the other macrophyte functional groups.
Denitrifiers exposed to high nitrate concentrations are known to produce higher nitrous oxide fluxes. This would also explain the higher N2O fluxes occurring within the
controls in which no plants were present. Another explanation may be that for certain
macrophytes, high plant density and the associated extension of roots into the substrate,
may act as effective conduits for gas transport and higher denitrification rates (Reddy et
al. 1989, Buresh et al.1993, Comin et al. 1997). Eleocharis spp. are known to possess
influx and efflux culms with humidity induced flow as the dominant mechanism for
convection of methane (Grosse et al. 1996). These rates were found to be 15 times 78 greater than those for ebullition directly from the sediment. We did not monitor N2O flux from the entire plants so we do not know if there are significant differences between the treatments for this efflux mechanism. Aquatic plants are known to promote a short circuiting of trace gas flux through their roots (Singh 2000).
2.5.4 Other factors
The duration of our study may have been too short to assess differences between the macrophyte diversity treatments in terms of contributions to the sediment organic C pools. However, in both studies by macrophyte peak biomass time, all mesocosms which covered a relatively small area (surface area = 0.82m2, volume = 0.42m3), were completely filled with macrophytes for all treatments with one exception. This occurred
in Study #1 when the facultative annuals did not grow well and total biomass was low
(see Bouchard et al., in prep). Furthermore, significant differences between the
treatments for DOC and labile C were detected. Conclusions from two long-term studies suggest that increasing the length of our two studies may not have changed the results. In
one 7 year study, changes in soil microbial communities and the key ecosystem processes
they mediate, such as carbon and nitrogen cycling, within grassland soils were
significantly altered by plant community richness. However, this finding was attributed
to higher levels of plant production associated with greater diversity and not plant
diversity per se (Zak et al. 2003). The results of an 8 year study examining plant
productivity within grasslands determined that diversity effects were restricted to
particular species combinations or environmental conditions and not diversity alone
(Hooper and Dukes 2004). 79 Since we did not include perturbations, as other diversity studies have done (Griffiths
et al. 2000, Wardle et al. 2000, Pfisterer and Schmid 2002), we do not know if
denitrification function would differ across the diversity gradient under changing
environmental conditions. It is hypothesized that the presence of a higher diversity of
species, which overlap in function but have different tolerances to different stresses,
ensure that function will be maintained or recover quicker. Some studies suggest that
disturbance to ecosystems resulting in changes within the microbial communities may
alter key functions such as denitrification. Denitrifier communities within adjacent
plowed and successional fields were determined to be distinctly different (Cavigelli and
Robertson 2000, 2001). The community of denitrifiers within the less disturbed
successional field had relatively more active nitrous oxide reductase, and therefore, more
potential to reduce N2O to N2 than denitrifiers in the tilled agricultural field. As well, denitrifiers in the tilled soils were found to be more sensitive to oxygen inhibition of
enzyme activity involved in N2O production (nitrate reductase, nitrite reductase, and
nitric oxide reductase) than denitrifiers in the successional field. In another study,
distinct denitrifier communities were observed within two agricultural soils in which N2O
was the dominant product of denitrification in the one and N2 gas was the dominant
product in the other (Cheneby et al. 1998). Furthermore, in a study monitoring the
effects of reduced soil microbial diversity on the stability of key soil processes, no direct
relationship between diversity and function was detected (Griffiths et al. 2000).
Denitrification decreased as biodiversity decreased while some broad-scale functional
parameters increased as biodiversity decreased including microbial growth on added
nutrients and decomposition rates of plant residues. The impact of perturbations on 80 denitrifier communities within wetlands, and the role that macrophyte diversity plays, has
yet to be explored. We do know that macrophyte functional group community
composition plays a larger role in denitrification function than diversity when
environmental conditions remain constant.
It appears that the role macrophytes play with regard to denitrification function is not
just relevant to C pools, but also to the complex interactions that occur between the plants
and the decomposer community. This not only includes the microbial consortia which all
partake in the microbial loop cycling of nutrients (Wetzel and Sondergaard 1998), but
also other groups including microarthropods and higher nematodes that affect N mineralization rates and availability (Blair et al. 1990) all of which has yet to be explored.
In summary, this research suggests that niche-complimentarity is not a mechanism linking macrophyte functional group diversity to denitrification within freshwater wetland sediments. Since there was no evidence of increased denitrification or bioavailable C across the macrophyte functional group diversity gradient, the results support the averaging effect or null hypothesis whereby no increase in ecosystem function occurs with increasing macrophyte functional group diversity. However, community composition does appear to be important since the functional group, obligate annuals, emitted significantly higher N2O flux than the other macrophyte functional
groups. This finding suggests that wetlands with higher macrophyte diversity would tend
to offset the presence of a monoculture that emits higher flux of a greenhouse gas while
not altering denitrification function. We did not test the effect of disturbance on the
relationship between macrophyte diversity and denitrification and therefore, the role that 81 macrophyte functional group diversity would play in ameliorating environmental disturbance that may impact denitrification function within wetlands has yet to be investigated. Although individual species may match the performance of higher diversity assemblages, no single species excels in all functions (Zedler et al. 2001b).
82
CHAPTER 3
TESTING THE NICHE-DIFFERENTIATION MECHANISM: THE LINK BETWEEN
MACROPHYTE FUNCTIONAL GROUP DIVERSITY, BACTERIAL DIVERSITY,
AND DENITRIFICATION FUNCTION IN WETLAND SEDIMENTS
3.1 ABSTRACT
Plant diversity effects on soil microbial communities and associated functions remains poorly understood (Shipper et al. 2001, Johnson et al. 2003, Nannipieri et al. 2003).
In this study, the relationship between aquatic plant (macrophyte) functional group (FG)
diversity, bacterial gDNA diversity, bacterial community composition, and denitrification
function in wetland sediments was evaluated. Using mesocosms, that allowed for control
of sediment type, water source, and nutrient conditions, 8 treatments were established
consisting of controls (no plants), four macrophyte functional groups (tussock, reed,
facultative annuals and obligate annuals), and combinations of 2 FG, 3 FG and all 4 FG.
There were three replicate mesocosms per treatment. All analyses occurred during
macrophyte peak biomass in September 2002 and included in situ denitrification, in situ
denitrification with nitrate addition, denitrification potential, labile C, sediment C:N,
active bacterial biomass, and interstitial water DOC. Also, bacterial diversity and
bacterial community composition were determined by analysis of terminal restriction
fragment length polymorphism (TRFLP) of 16S rRNA genes.
83 The central hypothesis was that a positive relationship between macrophyte functional group diversity and bacterial diversity (including denitrifiers) would exist due to niche-
complimentarity between macrophyte functional groups thereby resulting in enhanced C
pools. As a result, it was expected that denitrifier diversity and active nitrous oxide
reductase enzymes would increase and be reflected in increased denitrification and
decreased N2O flux. Results showed no increase in in situ denitrification or
denitrification potential or decrease in N2O flux across the macrophyte functional group
diversity gradient. Nor, were there differences in the C pools measured. There were
however, significant differences in denitrification function between the monoculture
macrophyte treatments with the reeds and tussocks showing higher in situ denitrification
and denitrification potential than the facultative annuals or obligate annuals treatments.
Furthermore, the obligate annuals had significantly greater in situ N2O flux. No
significant differences were detected in the number or sizes of terminal restriction
fragments (TRFs) between the treatments indicating that there were no differences in
bacterial diversity or community composition. However, the identified portion of the
bacterial gDNA, based upon TRF similarities to sequenced bacteria in the RDP data base,
suggested that there were some differences in the denitrifier communities between the
treatments. Our results suggest that sediment bacterial diversity and denitrification
function are not linked to macrophyte functional group diversity, and while the
monoculture macrophyte functional groups do not differ in bacterial diversity, they do
differ in N2O flux. Therefore, increased macrophyte diversity would dampen the existence of macrophyte monocultures that may promote trace gas flux while not altering denitrification function. This finding has implications for wetland mitigation practices, 84 which to date, commonly result in wetlands exhibiting low macrophyte diversity and is
also relevant to issues pertaining to global climate change.
3.2 INTRODUCTION
Mechanisms relating plant diversity to microbial diversity, and in turn, ecosystem
function, have yet to be elucidated. There are three main hypotheses regarding the
potential impact a loss of plant diversity may have on belowground microbially mediated processes. One hypothesis is that microbial diversity in an ecosystem is never so impoverished that the microbial community cannot play its full part in biogeochemical cycling (Meyer1993, Andren et al.1995, Beare et al.1995, Finlay et al.1997, Giller et al.
1997). A second, is that our lack of understanding of the unculturable microbes, estimated at between 90% to 99.9% of the total microbial community, necessitates that we cannot assess the impact a loss of diversity may have using culture based approaches
(Freckman 1994, Brussaard 1997, Freckman et al. 1997; Wall 1999, Wall and Moore
1999, Breznak, 2002). And a third, is that many decomposition- related biological
processes such as oxidation, mineralization, and denitrification are performed by such a
large and diverse group of microbes that they are not likely to be impacted by a loss in
microbial diversity; however, other processes such as methanogenesis or biodegradation
of xenobiotics, that are performed by a smaller group of microbes, would be expected to
be impacted by a loss in diversity (Heywood and Watson 1995, Schimel 1995, Groffman
and Bohlen 1999).
Both positive and negative effects on decomposition have been detected in response to changes in plant litter type diversity (Chapman et al. 1988, Fyles and Fyles 1993, Wardle 85 et al. 1997, Nilsson et al. 1999), as were no responses (Blair et al. 1990, Rustad 1994).
As well, live plant diversity manipulations showed idiosyncratic responses in
decomposition rates with plant composition playing a much larger role than plant
diversity per se (Naeem et al. 1994, Wardle and Nicholson 1996). For example, plant
diversity lead to increased resource use by both microbes and plants and increased
nutrient cycling within a grassland (Hooper and Vitousek 1998). However, plant
composition explained much more about the measured nutrient cycling processes than diversity. Over a 7 year span, Zak et al. (2003) observed microbial community biomass, respiration, and fungal abundance to significantly increase with greater plant diversity in grasslands (Zak et al. 2003). Although these results were attributed to increased plant biomass with increased diversity, inexplicable increases in N mineralization rates also occurred which were not explained by increased biomass alone.
Plants play a key role in supplying C to the soil and it is estimated that over 80% of plant litter is decomposed by microorganisms (Bardgett and Shine 1999, Brussaard et al.
1997, Groffman and Bohlen 1999, Wallace et al. 1999). Diverse plant communities are
hypothesized to sustain greater microbial diversity than monocultures due to large
quantitative and qualitative differences in the root exudates and nutrient status of
individual plant species (Hobbie 1996, Wardle et al. 1997, Hooper and Vitousek 1998,
Bardgett and Shine 1999, Laakso and Setala 1999, Hector et al. 2000, Johnson et al.
2003). However, no studies to date have shown conclusive evidence linking plant
diversity with altered microbial diversity and function. Over a 4 year period in a
grassland ecosystem, no relationship was apparent between bacterial diversity and plant
diversity (Johnson et al. 2003). In fact, microbial biomass was significantly greater 86 within monocultures of grass species while bacterial diversity was significantly greater in the sedge and bare soil treatments than in the highest diversity treatments. In another grassland ecosystem, plant species richness and functional diversity showed a positive effect overall for catabolic activity and diversity (Stephan et al. 2000). However, these results were for culturable bacteria only, and represents a small fraction of in situ populations.
Investigations linking diversity and function within freshwater systems have also provided inconclusive results. Productivity across multiple trophic levels in pond food webs was either idiosyncratic (unpredictable changes) or increased with respect to species richness (Downing and Leibold 2002). But, the composition of species exhibited equal or more effect than the average effects of richness alone. When aquatic microbial diversity including producers, herbivores, bacterivores, and predators were manipulated to create a biodiversity gradient, ecosystem respiration became more predictable with increased biodiversity (McGrady-Steed et al. 1997). However, nonlinear effects of biodiversity on decomposition of particulate matter and resistance of communities to invasion were also observed.
Although numerous investigations have examined denitrification within wetland ecosystems, the importance of macrophyte diversity to this decomposition related process has yet to be elucidated. It is well known that organic carbon availability is one of the most important factors affecting denitrifying activity in soils (Myrold and Tiedje 1985,
Beauchamp 1989) and, the lability of carbon is of greater importance than the quantity in regulating denitrifier response (Schipper et al. 1994). Macrophyte species alone and in various combinations have a direct influence on the heterogeneity of organic material 87 available to microorganisms accounting for large differences in detrital dynamics within
wetlands (Findlay et al. 1990).
Denitrifying bacteria have also been well studied. They are ubiquitous, numerous and
estimated to compose 10% of the known microbes (Zumft 1992). However, only a very
small number of microbes have been identified, and the majority of these are cultured in
laboratories (Hawksworth and Kalin-Arroyo 1995, Wall 1999). Of the denitrifiers that
have been studied, it is known that oxidized nitrogen provides electron acceptors and is
reduced through enzymes (Beauchamp et al. 1989, Ye et al. 1994). Some denitrifiers
possess the whole complimentary suite of enzymes: nitrate reductase, nitrite reductase,
nitric oxide reductase, and nitrous oxide reductase which sequentially reduce nitrate →
nitrite → nitric oxide → nitrous oxide → dinitrogen. Other denitrifiers possess only a
few of these enzymes. In denitrifiers, that have the ability to produce the nitrous oxide reductase enzyme, studies have shown that pH values below 4, O2 levels above 0.2 mg/L,
and low C:N ratios negatively impact production resulting in increased nitrous oxide flux
(Firestone et al. 1980, Howard-Williams 1985, Vitousek et al. 1997). In addition, these
environmental factors have different effects on nitrous oxide reductase enzyme activity
within different denitrifying species (Ye et al. 1994).
Distinct differences in total denitrification flux, nitrous oxide emissions and denitrifier community composition were measured within two adjoining fields differing in
disturbance regimes and plant species (Cavigelli and Robertson 2000, 2001). In addition, denitrification decreased as microbial diversity decreased within terrestrial sediments
(Griffiths et al. 2000). These results suggest that aboveground processes do impact
denitrifier populations and alter function. 88 The goal of this research was to examine the relationship between macrophyte functional
group diversity, bacterial diversity, and denitrification in wetland sediments. Functional
group diversity was analyzed instead of species diversity to avoid difficulties associated
with the separation of observed responses due to the functional traits of one or more
species as diversity increased (Hooper and Vitousek 1998). Since the magnitude of the
effect of diversity on ecosystem functioning depends on the magnitude of interspecific
differences within the species pool, a diversity of functional groups, based upon
morphological and physiological traits, ensures greater differences among treatments
(Tilman 1999).
A better understanding of the role macrophyte functional group diversity plays in
denitrification function and in the production of the trace gas nitrous oxide is highly relevant particularly with regard to issues pertaining to human induced global climate change issues (Vitousek et al. 1997). Furthermore, within the past decade, mitigation of natural wetlands has increased resulting in these wetlands exhibiting low macrophyte diversity (Zedler et al. 2001a). Additional research is required to determine if wetlands with low plant community diversity limit or modify function or negatively impact decomposition processes resulting in higher emissions of nitrous oxide and/or a reduction in denitrification function.
The central hypothesis was that a positive relationship between macrophyte functional group diversity and bacterial diversity (including denitrifiers) would occur resulting in greater denitrification function and lower nitrous oxide production. This hypothesis was tested using a combination of molecular analysis of terminal restriction fragment length polymorphism (TRFLP) of 16S rRNA genes and metabolic analyses (denitrification flux) 89 to directly link macrophyte functional group diversity to bacterial diversity and
denitrification gas flux.
3.3 METHODS
3.3.1 Experimental design
The central hypothesis was tested in mesocosms instead of naturally occurring wetlands
to control environmental conditions including sediment type and depth, water source and
depth, and nutrient conditions while altering only macrophyte functional groups (FG) and
FG diversity. The mesocosms were located at the Waterman Agricultural and Natural
Resources Laboratory, Ohio State University, Columbus, Ohio, USA. They consisted of
416.7 liter heavy duty oval tubs (130 cm x 86 cm x 51cm) which were placed in the ground to moderate temperature effects. Each mesocosm was filled with the same sediment to a depth of 44 cm and flooded with well water to an overlying depth of 7 cm.
Water levels were maintained through precipitation and well water addition. Sediment was of terrestrial origin and chosen based upon low initial total soil C (2.5%) to allow detection of macrophyte C inputs (Table 3.1).
A total of 8 treatments were used consisting of controls (no plants), four individual functional groups (tussocks, reeds, facultative annuals and obligate annuals), and random selections of 2 FG combinations, 3 FG combinations and all 4 FG (Figure 3.1). There were 6 replicate mesocosms per treatment of which 3 were randomly selected specifically for this study for a total of 24 mesocosms. Selection of the macrophyte functional groups was based upon the work of Boutin and Keddy (1993). Two rooted emergent species represented each functional group as follows: 1) tussocks- Iris versicolor, Acorus 90 calamus; 2) reeds- Juncus effusus , Juncus canadensis; 3) facultative annuals- Mimulus ringens, Lycopus americanus; and 4) obligate annuals- Bidens cernua, Eleocharis obtusa.
All species were obtained as either bare root plants or plugs from Acorus Restoration
(www.ecologyart.com/acorus), Walsingham, On, Canada; Envirotech Consultants Inc.
(www.envirotechcon.com) Columbus, OH; and Ernst Conservation Seeds
(www.ernsteed.com), Meadville, PA. Species were planted randomly throughout each
mesocosm at the beginning of June 2002. Initial plant densities per mesocosm were 18 –
20 although this density was not maintained due to propagation. Invading, non-study
species were weeded out on a weekly basis.
% % % U.S.D.A % % Cation Exchange % Base saturation sand silt clay texture pH C N Capacity K Ca Mg class Cmol / kg 32 30 38 clay loam 7.5 2.5 0.12 170 2.9 81 16
Table 3.1: Physical and chemical characteristics of sediment used in all mesocosms.
91 Fac ann. 4 FG
3 FG Tussock Ob ann. Reed
0 FG
2 FG
Figure 3.1: Photograph of wetland mesocosms in August 2002. One replicate from each of the eight treatment types is identified. 0 FG = controls (no plants), Ob ann. = obligate annual, Fac ann.= facultative annual, 2 FG represents a combination of two randomly selected functional groups (shown are the reeds and facultative annuals), 3 FG represents a combination of three randomly selected functional groups (shown are tussock, obligate annuals and facultative annuals), and 4 FG represents the highest diversity treatment with all four functional groups present (tussocks, reeds, facultative annuals and obligate annuals).
92 3.3.2 Bacterial diversity
Sediment samples for analysis of bacterial diversity were collected in September
2002 from four randomly selected areas within each mesocosm when all macrophytes had reached peak biomass. Four sediment cores (2.5 cm dia) were collected to a depth of
10 cm, bulked in airtight plastic bags, and immediately stored at 4oC. Within 48 hrs of
collection, ~ 40 g of sediment was placed into 60 ml plastic scintillation vials and frozen
using liquid N to prevent bacterial cell wall lysing. The vials were stored at –20oC until
DNA extraction. A sample of the original sediment was also preserved for analysis.
Bacterial community structure was characterized by analysis of terminal restriction
fragment length polymorphisms (TRFLP) of 16S rRNA genes (Marsh 1999). This
technique provides insight into the structure and diversity of microbial communities
through the comparison of lengths of restriction digested PCR products fluorescently
tagged at 5’ and 3’ terminis. Genomic DNA (gDNA) was extracted from the samples
using the MoBio Soil DNA isolation kit (MoBio Laboratories, Solana Beach, CA)
following the stated protocol with slight modifications for DNA extraction optimization.
Bacterial gDNA concentrations were quantified by fluorescence spectrophotometry using
100 µl Pico Green (Molecular Probes, Eugene Oregon), 98 µl TE buffer and 2 µl gDNA
per sample at 260 nm and 280 nm absorbance (Bioassay Reader, Perkin Elmer).
Samples were adjusted to 2 ng/µl using LSTE buffer. These samples were then
polymerase chain reaction (PCR) amplified using 11F forward and 907R reverse tagged
primers with the following sequences: 11F : 5’-GTTTGATCMTG GCTCAG-3’; 907R:
5’-CCGTCAATTCMTTTRAGTTT-3’ (M=A or C R=A or G) in a PTC-100
Programmable Thermal Controller thermocycler (MJ Research Inc.). The forward primer 93 was labelled with HEX while the reverse primer was labelled with FAM. Amplified
DNA size and presence was verified using gel electrophoresis and cleaned using
Millipore Microcon PCR filter units. The cleaned PCR products were quantified using
the Pico Green method as stated above. PCR products were digested with one of three
restriction enzymes; Hha1, Msp 1 and Rsa 1 at 37 oC for 3 hr and 75 oC for 20 min. After
digestion, the samples were stored at –20oC and transported to The Ohio State University
Plant Genomics Laboratory where the lengths and fluorescence of fragments was
determined using an ABI 3700 DNA Analyzer. A positive control (Xanthomonas
campestris pv. Vesicatoria strain #110c) with known base pair (bp) lengths was used to
test the procedure. The best results were obtained using a double injection of 0.5 µl
sample at 2000 volts for 100 seconds. An internal lane size standard GeneScan -500 LIZ
(Applied Biosystems) was used with labeled fragments of 35, 50, 75, 100, 139, 150, 160,
200, 250, 300, 340, 350, 400, 450, 490, and 500 bases. For each sample, terminal restriction fragment (TRF) peak areas and lengths (bp) were obtained along with
electropherograms using the computer software Genotyper 3.7 (ABI Prism). All peaks
with identical sizes to the standards were removed to reduce standard inclusion in sample
analysis. Peaks less than 100 fluorescent units were removed as background. The sizes
of the peaks considered were from 35 to 500 bp.
94 3.3.3 Bacterial Community Composition
TRFs obtained were compared to those generated by simulated amplification and digestion of 16S RNA gene sequences in the ribosomal gene database using the program
FRAGSORT (Michel and Sciarini 2003). FRAGSORT matches terminal restriction fragment sizes to a database containing sizes of previously identified and sequenced bacteria for the same forward and reverse primers and enzymes. TRF length uncertainty values used were 0.1, 2, 4, and 6 for base pair lengths of 1, 200, 400, and 600; respectively. Only those bacterial species or genera matching all three fragment ribotypes (identical matches in TRFs for each of the 3 enzymes used for either the forward or reverse primers) were considered. The term, operational taxonomic unit
(OTU), was used in lieu of species and/or genera when describing and comparing populations and communities. The species concept for bacteria is obscure and it is not possible to differentiate whether or not three fragment ribotype matches are over estimating the number of bacterial species actually present due to the fact that more than one species may have the same match (Ovreas 2000). Lists of identified bacteria are located in Appendix C. Genera containing known denitrifier species were determined based on 16S rRNA gene sequences from Zumft (1992, 1997).
3.3.4 Denitrification function
All denitrification fluxes were obtained during macrophyte peak biomass, September
2002. In situ denitrification was determined using the acetylene block method as described by Knowles (1990) and Mosier and Klemedtsson (1994). Two 61cm length x
10 cm diameter polyvinylchloride (PVC) sampling tubes were permanently placed within 95 each mesocosm to allow for gas sampling without sediment disturbance. Each PVC tube
had a 2.2 cm diameter hole at the sediment/water interface to allow water to flow in and
out, reducing stagnation during non-sampling periods. Prior to gas sampling, all
mesocosms were flushed with well water and filled to capacity. The holes in the PVC sampler tubes were plugged with rubber stoppers and acetylene gas (C2H2) was gently
bubbled into the sediment contained within the PVC tubes at a 10 cm depth on a 10% v/v ratio (180 ml per sampler). The sampler tubes were sealed with an airtight cap and gas samples were extracted from the headspace via a rubber septum located in the cap. Gas samples were collected using a 60 cc syringe after pumping 3 times to mix the air inside the sealed tube. A 30 ml gas sample was collected per sampler tube and stored in a 20 ml evacuated glass vial. Only one sampler tube per mesocosm received the acetylene gas.
Gas collected from the sampler without C2H2 added allowed for the determination of
actual N2O emissions. The difference in N2O concentrations between the sampler tube
receiving C2H2 and the sampler tube that did not, was assumed to be N2. Optimum
sampling times were 6 and 24 hours as determined during a preliminary experiment.
Nitrous oxide was not detected above ambient, background values, therefore all flux
values were N-N2.
In situ denitrification under higher nitrate concentrations than those occurring naturally
were also monitored. The same sampling protocol was carried out as stated for in situ
denitrification described above with the exception that 4 ml/L of nitrate solution was
added to each sampler tube. This concentration is an average value found in rivers
throughout Ohio (Debrewer et al. 1999) and was used to assess differences between treatments when nitrate became available. This analysis took place 24 hrs after the last 96 sampling period for in situ denitrification. Prior to the nitrate solution addition, all PVC
sampling tubes were opened and all mesocosms were flushed and refilled with well
water. Both N2O and N2 fluxes were determined for this particular assay.
To determine denitrification potential (ie. denitrification enzyme analysis or DEA) we
used slightly modified methods from Tiedje et al. (1989) and Schipper et al. (1993). A
20 g sediment subsample (from the same bulked sediment used for TRFLP analysis) was placed into a 60 ml serum bottle and sealed. The headspace was flushed with argon for
2.5 min to create anoxic conditions and 5 ml of distilled water containing 0.5 mg KNO3 was then added. Glucose was not added as stated in DEA protocol to assess the differences in C availability to the denitrifiers due to our treatments alone. Five ml (10% v/v ratio) of acetylene was injected. All samples were incubated at 25oC in the dark on a
shaker table at 200 rev/min for 2 hrs. Gas samples were collected from the headspace at
15 and 120 min and stored in a 2.0 ml Vacutainer serum bottle. Flux calculations were
based on N2O concentrations at these two sample times as determined optimum. For this
assay the N2O: N2 ratio was not assessed and therefore, all denitrification potential flux
was assumed to consist of both gases.
All gas samples were measured for N2O concentrations on a Shimadzu 14C gas
chromatograph with a carrier gas of 95% argon and 5% methane and a flow rate of 32
ml/min. The column temperature was 40oC and detector temperature 300oC. Two
columns were used (Alltech, Porapak Q 80/100, 6’ x 1/8” x 0.085” stainless steel) with a flow rate of 2.3 ml/min. Flux calculations for both in situ denitrification assays as well as denitrification potential were performed as per Mosier and Klemedtsson (1994).
97 3.3.5 C pools, macrophyte biomass and C: N composition
Sub-samples from the same bulked sediment samples used for TRFLP analysis and
denitrification potential were analyzed for bacterial biomass C, labile C, and total C and
N. Active bacterial biomass was estimated by substrate induced respiration (SIR)
(Anderson and Domsch 1978, West and Sparling 1986). For each sample, 10 grams of
sediment was placed into a 60 ml serum bottle. Twenty ml of glucose solution at a concentration of 3 mg/ml (equivalent to 6 mg/g dry soil) was added and allowed to equilibrate uncapped for 30 min. The bottles were then sealed and incubated at 25oC for
2.5 hrs. Headspace gas samples were analyzed immediately using a LI-COR CO2
Analyzer.
Labile C was determined using an incubation method. Ten grams of field wet sub- sample was placed into a 20 ml specimen cup and sealed in a 1 L glass Mason jar. The jar was flushed with zero grade air for 1 min and sealed with a lid containing a luer lock which allowed sampling of headspace gas. Incubations were maintained at 25oC.
Headspace gas was collected every 3-5 days and immediately measured for CO2 using a
LI-COR CO2 Analyzer. After each gas sampling event, the jars were re-flushed for 1 min
with zero grade air and re-sealed. The incubation sampling continued until CO2
production leveled off (35 days). Labile C was estimated as the cumulative CO2-C
evolved over the incubation period. Sediment moisture was maintained throughout the
incubation by adding 20 ml of autoclaved DI water to the bottom of each jar.
Sediment C:N was determined on air dried, finely ground sub-samples from which
pebbles, roots, and other non-soil material were removed. Samples were stored at room temperature in scintilation vials until analysis. Total sediment C and N was determined 98 by dry combustion using a Carlo-Erba Analyzer (Thermo Quest, NC 2100, CE Elantech
Instruments).
Interstitial water was collected prior to in situ denitrification sampling in each mesocosm at the 10 cm sediment depth inside each of the 2 PVC sampling tubes. The water collected was bulked into a 30 ml Nalgene bottle and immediately kept cool until transport to the laboratory where they were stored at 4oC. Within 24 hrs of collection,
water samples were filtered using 0.45 µm Whatman glass microfibre filters and split into
two sub-samples. Samples to be analyzed for dissolved organic carbon (DOC) were
stored at 4oC. Within 48 hrs of collection, these samples were analyzed on a Dohrman
- o TOC Analyzer, DC-190. Samples analyzed for NO3 were stored at –20 C until
colormetry analysis on a Zellweger Analytics, Lachat Instrument.
Macrophyte above- and belowground biomass per treatment is detailed in Bouchard et
al. (in prep.). Macrophyte C and N composition was analyzed by dry combustion using a
Carlo-Erba Analyzer (Thermo Quest, NC 2100, CE Instruments). The C:N ratios of the
two species representing each macrophyte functional group were averaged.
3.3.6 Statistical analyses
All denitrification and C pool data were tested for normality using the Anderson-
Darling test (Minitab 13.1). Differences in numbers of TRFs, denitrification fluxes, C
pools, and macrophyte biomass between monoculture treatments and between diversity
treatments (including controls) were analyzed using one-way Fisher’s ANOVA with a
confidence interval of 95% (Minitab 13.1 Statistical Software). For bacterial diversity
assessment, the number of TRFs for each sample for the three enzymes used and the 99 forward and reverse primers were totalled. ANOVA was tested using the average values
for each treatment (n=3 for all treatments except reed, n=2).
Similarity values (Sab) of the TRFs were obtained through the statistical program
available at http://rdp.cme.msu.edu/html/analyses.html. This program analyzes the
similarities between TRF peak presence or absence for each sample and gives a value
between 0 (no similarities) and 1 (identical). TR Fragment length uncertainty values for
TRF lengths were 0.1, 2, 4, and 6 for 1, 200, 400, and 600 fragment sizes respectively
(these are the same base pair error ranges used for bacterial identification in the program
FRAGSORT). This data was summarized by calculating the means of the data obtained
for all 3 enzymes and the forward and reverse primers for each treatment.
Bacterial diversity was further analyzed using Simpson’s reciprocal index (1/D) which
takes into account both species richness and evenness (Magurran 1988). This index is
based on the probability of any two individuals, that are drawn at random from an
infinitely large community, belonging to different species. The value of the index starts
with 1 as the lowest possible figure and increases with increasing diversity. The TRFs
obtained with the forward primer and Hha1 enzyme provided the highest fragment
numbers overall and were used in these calculations. All TRFs within 2 Bps were
combined. The percent of the total fluorescence intensity for each TRF was used as the
n, while N = 100% in the equation: D = ∑(n/N)2. The D value for each replicate sample was used to obtain an average Simpson’s reciprocal value and standard error for each treatment.
It is recognized that the number of naturally occurring bacterial species, or numbers of
individuals from a sample, is much greater than that indicated by the number of TRFs due 100 to inherent problems with extraction and amplification (see Borneman et al. 1996, Suzuki
and Giovannoni 1996, Dunbar et al. 2000, Martin-Laurent et al. 2001). Therefore, the
information provided by the TRFLP analysis was used to compare diversity between
treatments under the following assumptions: 1) The number of TRFs obtained from the
Hha 1 enzyme digestion was a surrogate for the number of species; 2) the area under a
particular TRF peak represents the abundance of that species; 3) the total number of
individuals within a sample is proportional to the total area of all TRF peaks in that
sample normalized to 100%, and 4) since all samples were treated the same with the
TRFLP protocol and replicates were used to represent each treatment, inherent problems
with the method would pertain to all samples.
Bacterial community similarity between treatments was also determined using the
statistical package of Bionumerics 3.50 (Applied Maths, Inc). This analysis is based
upon a comparison of TRFLP profile data. A matrix and dendrogram were produced
using the TRF information based on the Hha1 enzyme and forward primer TRFLP
profile. The dendrogram shows the Pearson’s correlation similarity values between
individual samples based on densitometric curves using the unweighted pair group
method of arithmetic averages (UPGMA; Liu et al., 1997; Michel et al., 2002). The
matrix summarizes mean (±1 SE) Pearson’s correlation similarity values of the replicates
for all treatments.
Spearman’s rank order correlations (Minitab 13.1) were used to determine relationships
between TRFs and in situ denitrification, in situ denitrification with nitrate addition, denitrification potential, bacterial biomass, labile C, sediment and macrophyte C:N ratios,
101 macrophyte above- and belowground biomass, and macrophyte diversity for all
treatments.
3.4 RESULTS
3.4.1 Bacterial diversity
There were no significant differences in the total number of TRFs per treatment
indicating that bacterial diversity within all 8 treatments was similar (Figure 3.2). The
number of TRFs obtained with the forward primer ranged from 97 – 133 for the Hha1
enzyme and 84 - 128 for the Msp 1 enzyme, to 64 -148 for the Rsa1 enzyme. For the
reverse primer, the number of TRFs were lower ranging from 65 - 92 for the Hha1 enzyme, 56 - 70 for the Msp1 enzyme, and 46 - 74 for the Rsa1 enzyme.
Similarity values comparing TRFLP profiles also showed no significant differences
between treatments (Table 3.2). In some cases similarities were less within treatment
replicates than they were between treatments. The lowest similarities occurred among
the replicates of the 2 FG diversity treatment while the highest similarity occurred
between the obligate annuals and the 3 FG diversity treatments. Similarity values also
indicated that the treatments were not significantly different with the original sediment of
terrestrial origin that used in each mesocosm.
102
180 Hha1 r 160 Msp1 140 Rsa1
120 100 80
60 40
20
0 TRFs per enzyme, forward prime forward enzyme, per TRFs OS Controls Tussock Reed Fac ann Ob ann 2FG 3FG 4FG
120
r 100
80
60
40
20
prime reverse enzyme, per TRFs 0 OS Controls Tussock Reed Fac ann Ob ann 2FG 3FG 4FG Treatments
Figure 3.2: Terminal restriction fragments (TRFs) for each enzyme (Hha1, Msp1, Rsa1) for the forward primer (a) and reverse primer (b). Mean ± 1 SE, n = 3 except reed (n = 2) and OS (n = 0); OS = original sediment; ANOVA, P > 0.05.
103
C T R Fa Ob 2FG 3FG 4FG C 0.75 (0.03) T 0.76 (0.03) 0.77 (0.03) R 0.76 (0.03) 0.78 (0.02) 0.76 (0.03) Fa 0.75 (0.03) 0.81 (0.02) 0.80 (0.02) 0.81 (0.03) Ob 0.79 (0.03) 0.78 (0.03) 0.81 (0.02) 0.78 (0.03) 0.82 (0.03) 2FG 0.78 (0.02) 0.79 (0.02) 0.78 (0.02) 0.79 (0.03) 0.79 (0.03) 0.74 (0.03) 3FG 0.78 (0.02) 0.79 (0.02) 0.81 (0.02) 0.81 (0.02) 0.83 (0.02) 0.79 (0.03) 0.81 (0.02) 4FG 0.77 (0.03) 0.79 (0.02) 0.78 (0.02) 0.80 (0.02) 0.79 (0.03) 0.79 (0.02) 0.81 (0.02) 0.76 (0.03) OS 0.75 (0.03) 0.75 (0.03) 0.75 (0.04) 0.74 (0.03) 0.77 (0.03) 0.75 (0.03) 0.75 (0.04) 0.75 (0.03)
Mean (± 1 SE) calculated from TRF Bp lengths and areas for all three enzymes (Hha1, Msp1, Rsa1) and both forward and reverse primers; 1 = identical and 0 = no similarities; n = 3 except reed (n = 2) and original sediment (n = 1); ANOVA, P = 0.91; C = controls; T = tussock; R = reed; Fa = facultative annuals; Ob = obligate annuals; 2 FG = 2 functional groups; 3 FG = 3 functional groups; 4 FG = 4 functional groups; OS = original sediment.
Table 3.2: Similarity of TRFLP profiles between treatments and original sediment.
The Simpson’s reciprocal index (1/D) also indicated similar TRF richness and evenness between treatments (Table 3.3). There were no significant differences in TRF based bacterial diversity between either the monoculture macrophyte functional groups, the diversity treatments or all eight treatments combined. The obligate annuals had the lowest diversity index while the 2 FG diversity treatment had the highest. There was no evidence of an increase in bacterial gDNA diversity across the macrophyte functional group diversity gradient.
104 Treatments 1/D Original sediment 41.89 Control 49.23 ± 9.65 Tussock 48.34 ± 7.58 Reed 44.90 ± 5.24 Facultative annual 54.92 ± 1.79 Obligate annual 41.67 ± 0.63 2 FG 55.38 ± 11.04 3 FG 44.77 ± 6.53 4 FG 51.15 ± 7.33 Mean ± 1 SE, n = 3 except reed (n = 2) and original sediment (n = 1); where D = ∑(n/N)2 (n = percent area of the total for each TRF; N = 100% ); ANOVA, P = 0.77.
Table 3.3: Simpson’s reciprocal index of bacterial diversity within each treatment based
on number and abundance of Hha1 TRFs.
3.4.2 Bacterial community composition
The closest similarities in bacterial community composition occurred between the
original sediment and the controls and between the reed replicates, with 82%. The lowest
similarity occurred between the original sediment and the facultative annuals at 42%
(Table 3.4). Despite these ranges, there were no significant differences for percent
similarity between any sets of treatment comparisons. The variance in bacterial
community composition was just as high within treatments as it was between and no
clustering of all 3 treatment replicates was evident (Figure 3.3).
105
control tussock reed fac ann ob ann 2FG 3FG 4FG control 77 (4) tussock 64 (7) 50 (15) reed 62 (2) 56 (4) 82 fac ann 52 (4) 57 (6) 66 (5) 62 (6) ob ann 72 (3) 60 (7) 67 (6) 53 (5) 58 (2) 2FG 78 (4) 57 (7) 57 (3) 45 (4) 68 (4) 67 (6) 3FG 67 (7) 60 (7) 56 (3) 56 (5) 61 (6) 63 (7) 54 (12) 4FG 63 (7) 61 (7) 65 (5) 62 (5) 60 (6) 58 (7) 62 (7) 53 (10) OS 82 (2) 61 (13) 53 (7) 42 (6) 68 (10) 77 (10) 66 (15) 58 (12)
Mean (± 1 SE) of Pearson’s similarity values for OTUs obtained with Hha1 enzyme, forward primer between treatments; n = 3 except reeds (n = 2) and OS (n =1); 0 FG = controls, T = tussock, R = reed, Fa = facultative annual, Ob = obligate annual, FG = functional groups, OS = original sediment; ANOVA, P = 0.13
Table 3.4: Similarities in bacterial community composition within and between
treatments and the original sediment.
106
HhaI-F
Pearson correlation [0.0%-100.0%]
45 50 55 60 65 70 75 80 85 90 95 100 4Fg. C. T. C. 2Fg. 3Fg. 3Fg. Ob. OS. 2Fg. C. T. Ob. 2Fg. R . Ob. R. 4Fg . Fa. Fa. . Fa T. 4Fg. 3Fg.
Figure 3.3: Similarity dendrogram of TRFLP profiles in bacterial community between
individual samples. Correlation is calculated from Pearson similarity values based on
TRFs obtained for the Hha1 enzyme, forward primer for each replicate in each diversity treatment. The 8 diversity treatments are: T = tussocks, R = reeds, Fa = facultative annuals, Ob = obligate annuals, C = controls, 2 FG = 2 functional groups, 3 FG = 3 functional groups, 4 FG = 4 functional groups, OS = original sediment.
107 Far more species and/or genera were listed as being potentially present within each sample for the forward primer than the reverse. The same was true for the percentage of
PCR product identified which ranged between 65 – 80% for the forward primer and 19 –
28% for the reverse. Eleven of the identified species/genera were present within 100% of all replicates and treatments (Table 3.5). Of these eleven, three genera are known to contain denitrifiers. When the list was expanded to include species/genera common to at least 2 of the 3 replicates for all treatments and at least 7 of the 8 treatments, a total of
154 were identified. Identification of the TRFs consistent with denitrifiers present within at least one replicate in each treatment revealed eleven denitrifier associated TRFs which were common to all treatments (Table 3.6). In addition to these eleven, the tussocks had
7 genera for a total of 18 which represented the highest denitrifier total while the reeds had the lowest with a total of 13. Similar denitrifier TRFs were observed in the obligate annual and 4 FG treatments with denitrifier TRFs from 4 identical genera present.
Species or Genera Bacillus spp.* Burkholderia EN-B3* Clone HSTPL69. Endosymbiont of mealybug (Dysmicoccus neobrivipes). Lawsonia intracellularis str. 1482/89 NCTC 12656 (T). Leptothrix spp. Nitrosomonas europaea strains Rhodobacter capsulatus str. ATH. 2.3.1 ATCC 11166 (T)* Spirillum spp. Sutterella spp. Symbiont of Crithidia sp. Unidentified bacterium DNA for 16S ribosomal RNA. Results are from the program FRAGSORT; *represents known denitrifiers.
Table 3.5: Bacterial species/genera common to all replicates and treatments.
108 All Treatments Acidovorax, Aquaspirillum, Bacillus, Burkhoderia, Campylobacter, Cytophaga, Pseudomonas, Ralstonia, Rhodobacter, Roseobacter, Vibrio Tussock Reed Facultative annual Obligate annual Alcaligenes Blastobacter Flexibacter Blastobacter Blastobacter Hyphomicrobium Shewanella Flexibacter Flexibacter Sphingobacterium Sphingobacterium Hyphomicrobium Paracoccus Rhodopseudomonas Shewanella Control 2 FG 3 FG 4 FG Alcaligenes Alcaligenes Flavobacterium Blastobacter Flexibacter Aquifex Flexibacter Flexibacter Shewanella Rhodopseudomonas Hyphomicrobium Sphingobacterium Shewanella Shewanella Sphingobacterium Sphingobacterium
Table 3.6: Denitrifier organisms consistent with TRFs found in all 3 digestions. Only genera are provided. Lists represent denitrifier genera present within at least one treatment replicate.
There were no significant differences between the treatments in the total numbers of genera containing known denitrifiers due to the high variance within treatment replicates
(Figure 3.4).
109 20 18 16 14 12 10 8 6 4 2 # TRFs consistent with denitrifiers with denitrifiers # TRFs consistent 0 OS Control Tussock Reed Fac ann Ob ann 2FG 3FG 4FG Treatments
Figure 3.4: Number of genera known to contain denitrifiers consistent with Hha1,
Msp 1, and Rsa 1 TRFs found within each treatment. Mean ±1 SE, n = 3 except reed (n =
2) and OS (n = 1); OS = original sediment, Fac ann = facultative annuals, Ob ann = obligate annuals; ANOVA P > 0.05.
110 3.4.3 Denitrification Function
No difference was observed in in situ denitrification flux between the macrophyte
functional group diversity treatments. A significant difference in in situ denitrification
was only noted between the monoculture macrophyte treatments (Table 3.7). The reeds
-2 -1 and tussocks had the highest in situ denitrification at 2.2 and 2.3 mg N-N2 m day ;
-2 -1 respectively while the facultative annuals (0.6 mg N-N2 m day ) and obligate annuals
-2 -1 (1.0 mg N-N2 m day ) were significantly lower.
In situ denitrification increased within all treatments after nitrate addition. However, there were no significant differences between the macrophyte diversity treatments in N2
-2 -1 flux which ranged between 29.7 - 47.1 mg N2-N m day . There were significant
differences in N2 flux between the monoculture functional groups. The obligate annuals
-2 -1 exhibited significantly higher flux at 61.2 mg N-N2 m day than the reeds and
-2 -1 facultative annuals with 30.9 and 30.4 mg N2-N m day ; respectively. The tussocks
-2 -1 showed intermediate fluxes with 40.0 mg N2-N m day .
In situ N2O was only measurable above ambient concentrations after nitrate addition.
At this time, significant differences in N2O were only detected between the monoculture
functional groups with the obligate annuals emitting four times more N2O than the
tussocks, reeds, or facultative annuals (Table 3.7).
111 In situ Denitrification In situ N2 In situ N2O Treatments denitrification potential flux nitrate flux nitrate flux mg N addition addition -2 -2 -2 mg N-N2 m (N20 + N2) m mg N-N2 m mg N-N2O day-1 day-1 day-1 m-2 day-1 Tussock 2.3 ±0.3a 45.5 ±3.2ab 40.0 ± 4.2ab 1.1 ±0.2b Reed 2.2 ±0.2a 56.9 ±7.0a 30.9 ± 3.4b 0.8 ±0.1b Facultative annual 0.6 ±0.2b 21.7 ±3.8c 30.4 ± 4.1b 1.1 ±0.2b Obligate annual 1.0 ±0.5b 43.4 ±2.4b 61.2 ±14.5a 4.8 ±1.5a Control 1.4 ±0.2 27.1 ±2.4 36.5 ± 5.1 2.8 ±0.8 1 FG 1.3 ±0.2 42.6 ±3.4 40.7 ± 4.8 2.0 ±0.5 2 FG 0.9 ±0.3 37.4 ±7.8 29.7 ± 4.8 1.7 ±0.5 3 FG 0.7 ±0.4 42.7 ±5.2 42.7 ± 9.4 1.1 ±0.4 4 FG 1.0 ±0.3 37.8 ±5.0 47.1 ± 8.1 4.6 ±0.8 mean ± 1 SE, n = 3; Significant ANOVA results determined for monoculture macrophyte functional groups only; values with different letters are significantly different at P < 0.05; FG = macrophyte functional groups, 1 FG = tussock, reed, facultative annual and obligate annuals combined.
Table 3.7: Denitrification gas flux per treatment
-2 -1 Denitrification potential ranged from 37.4 – 42.7 mg N (N2O + N2) m day in the
macrophyte functional group diversity treatments and no significant differences were
evident (Table 3.7). There were significant differences for denitrification potential
-2 between the macrophyte functional groups. The reeds with 56.9 mg N (N2O + N2) m
-1 -2 day were significantly higher than the facultative annuals (21.7 mg N (N2O + N2) m
-1 -2 -1 day ) and obligate annuals (43.4 mg N (N2O + N2) m day ) while the tussocks had
-2 -1 intermediate fluxes (45.5 mg N (N2O + N2) m day ).
112 3.4.4 C Pools, macrophyte biomass and C: N composition
Significant differences in bacterial biomass C, labile C and sediment C:N ratios were
not evident between any of the monoculture macrophyte functional groups or macrophyte
functional group diversity treatments (Table 3.8). Bacterial biomass C was actually
highest in the controls while the lowest values were noted in the reeds. Labile C values
were the highest within the tussocks and lowest within the highest diversity treatment (4
FG). For all eight treatments, sediment C:N ratios were quite similar, ranging from 20-
22.
Significant differences were observed between the treatments for interstitial water DOC
concentrations. The facultative annuals had significantly higher DOC than all other
treatments with 114 mg/L compared to ranges of 15 - 57 mg/L in the monoculture
functional groups and 31 - 52 mg/L in the diversity treatments. The controls had the
second highest DOC concentrations with 98 mg/L.
- Interstitial water NO3 concentrations were not significantly different between any of the monoculture or diversity treatments and ranged from 0.09 mg/L to below detection
(< 0.01 mg/L; data not shown).
Plant C:N ratios were significantly different between the macrophyte functional groups. The facultative annuals had the highest ratio at 68, the tussocks showed an intermediate ratio at 53 while both the reeds and obligate annuals had the lowest with 32 and 46; respectively (Table 3.8).
Details pertaining to macrophyte biomass are located in Bouchard et al. (in prep.). The tussocks had significantly higher root biomass (627 g/m2) than the reeds (279 g/m2) or facultative annuals (69 g/m2) while the obligate annuals (560 g/m2) showed intermediate 113 values. The facultative annuals had significantly lower total biomass (above-and
belowground) with 196 g/m2 compared to the reeds (926 g/m2), tussocks (1030 g/m2), and
obligate annuals (1095 g/m2). For the macrophyte functional group diversity treatments, the 4 FG diversity treatment had significantly higher root biomass (901 g/m2 ) than the 2
FG diversity treatment (459 g/m2), while the 3 FG diversity treatment was intermediate
(558 g/m2). There was a significant, positive relationship (R2=0.25; P = 0.05) between increasing root biomass and increasing macrophyte functional group diversity. There was a similar trend for total plant biomass with the 4 FG diversity treatment showing significantly higher values (1454 g/m2) than the 2 FG diversity treatment (927 g/m2) and the 3 FG diversity treatment at intermediate values (1038 g/m2).
Treatments Bacterial Labile C Sediment Interstitial Plant biomass C C: N water DOC C: N -1 -1 µg C-CO2 g µg C-CO2 g Ratio mg/L Ratio dry sediment dry sediment Tussock 49 ±12 137 ±19 20 ±3.8 15 ± 1c 53 ±3b Reed 40 ± 5 114 ± 9 20 ±0.7 30 ± 4c 42 ±2c Facultative annual 60 ± 8 114 ± 7 20 ±0.6 114 ± 27a 69 ±6a Obligate annual 51 ± 6 119 ± 9 22 ±6.6 57 ± 20bc 36 ±1c Control 61 ± 3 122 ±10 20 ±0.5 98 ± 14ab 2 FG 53 ± 4 127 ± 9 21 ±0.8 54 ± 19bc na 3 FG 55 ± 9 105 ±14 20 ±0.6 33 ± 7c na 4 FG 40 ± 6 101 ±14 21 ±0.6 31 ± 8c na mean ± 1 SE, n = 3; na = data not available; P>0.05 between treatments for bacterial C, labile C, and sediment C: N ratios; values with different letters are significantly different at P < 0.05.
Table 3.8: C pools and plant C:N ratios for functional groups and functional group (FG)
diversity treatments.
114 3.4.5 Relationships between bacterial diversity and denitrification, C pools,
macrophyte biomass and macrophyte functional group diversity
Total bacterial diversity, as reflected in TRF numbers, was significantly yet negatively
correlated to in situ denitrification and in situ N2O flux after nitrate addition (Table 3.9).
However, there were no significant correlations between total TRFs per treatment with in situ N2 flux after nitrate addition or denitrification potential. As well, there were no
significant correlations between total TRFs per treatment with bacterial biomass,
sediment labile C, plant C:N ratios, above-and belowground macrophyte biomass or
macrophyte functional group diversity. The only parameter with a positive correlation to
TRF numbers was sediment C:N ratios. However, sediment C:N ratios were not
significantly correlated to above-and belowground macrophyte biomass, macrophyte C:N
ratios, interstitial water DOC, sediment labile C or bacterial biomass (data not shown).
Relationships between the number of genera containing known denitrifiers within each
treatment and denitrification (in situ N2 flux, in situ N2O and N2 flux with nitrate addition,
and denitrification potential) were also not evident (data not shown).
115 TRFs regressed with Parameters: rs values P In situ denitrification -0.41 0.05 Denitrification potential 0.12 0.60 In situ N-N2 flux – nitrate addition -0.27 0.21 In situ N-N2O flux - nitrate addition -0.44 0.03 Bacterial Biomass C 0.01 0.97 Labile C -0.13 0.54 Sediment C:N ratios 0.50 0.02 Interstitial water DOC -0.20 0.36 Macrophyte C:N ratios 0.00 0.78 Macrophyte aboveground biomass 0.02 0.36 Macrophyte belowground biomass -0.01 0.98 Total macrophyte biomass -0.03 0.89 Macrophyte species number 0.23 0.29 Macrophyte functional group 0.23 0.29 number analysis included controls, n = 23 except with macrophyte C: N, n = 11.
Table 3.9: Spearman’s rank order (rs) for terminal restriction fragments (TRFs) regressed with denitrification gas flux, sediment and water C, macrophyte C: N, and macrophyte biomass for all treatments combined.
116 3.5 DISCUSSION
Bacterial diversity, as represented by TRFs, was predicted to increase as macrophyte
functional group diversity increased due to niche-complimentarity within the root matrix.
It was expected that niche-complimentarity would result in: 1) increased opportunity for
C exudation, 2) increased C substrate composition, 3) increased oxic/anoxic microsites,
and 4) increased decomposition due to differentiation within the microbial consortia. As
a result of these four factors, increased denitrification function and decreased nitrous oxide flux were expected. However, there was no evidence to suggest that bacterial
diversity or denitrification function increased as a result of increasing macrophyte functional group diversity. Furthermore, although differences were observed in denitrification flux between the individual functional groups, differences in bacterial
diversity were not evident. Our results suggest that: a) sediment bacterial diversity and
denitrification function are not linked to macrophyte functional group diversity; and, b)
while individual macrophyte functional groups do not appear to affect bacterial diversity,
they do impact denitrification function. These two main conclusions are discussed
below.
3.5.1 Bacterial diversity
The lack of differences in bacterial diversity between the 8 treatments may be
explained by a number of factors. It was anticipated that morphological and
physiological differences between the macrophyte functional groups would manifest in
differences within the C pools and impact bacterial diversity. However, differences
between the monoculture functional groups for labile C, sediment C:N ratios and 117 bacterial biomass were not observed. These similarities occurred despite differences in root biomass since the tussocks, obligate annuals, and reeds all had significantly higher root biomass than the facultative annuals. As well, no differences were observed between the macrophyte functional group diversity treatments for labile C, sediment C:N ratios, or bacterial biomass.
These results suggest that the residual C within the original sediment (4.2 mg/g organic
C ) already supported a diverse bacterial consortia. This was particularly evident in the controls since bacterial biomass and bacterial diversity were no different than they were within the treatments with macrophytes. There is some evidence to suggest that a relatively low level of sediment C is sufficient to sustain high microbial diversity.
Examination of glacier forelands, differing in ages from 6 - 150 years, showed functional diversity of soil microflora to reach a steady state after 50 years of organic matter accumulation which amounted to between 2.7 and 3.6 mg/g of organic C (Tscherko et al.
2003). Organic matter accumulation beyond these values, no matter the source, did not result in increased microflora functional diversity. This was measured as either microbial processes (N mineralization, ammonium oxidation, arginine deaminase) or soil enzyme activity (protease, urease, xylanase, phosphatase, arylsuphatase). Furthermore, bacterial diversity differed between samples differing in C, although there were no differences between the samples with similar C contents (Zhou et al. 2002). Preliminary evidence suggests that there is a ‘hyperdiversity’ of microbial species including substrate specialists and generalists within non-extreme environments of sufficient C (Meyer 1993,
Bianchi and Bianchi 1993, Beare et al. 1995, Finlay et al. 1997). This ‘hyperdiversity’
118 may not allow for subtle differences in diversity or composition to be detected with the tools presently available.
Substrate linkages between the whole consortia of microbial functional groups, which may be present such as N-fixers, nitrifiers, denitrifiers, heterotrophs, sulphate/sulphur reducers to name a few, are connected and reliant upon the resultant element cycling
(Paerl and Pinckney 1996). In an exhaustive summary of numerous studies examining microbial diversity and function in a pond in the UK, microbial diversity was always high
(Findlay et al. 1997). It was suggested that reciprocal interactions between microbial activity and the physical-chemical environment created a continuous turnover in microbial niches which were always filled. Within aquatic sediment microzones, microbial diversity is promoted since it appears advantageous for microbes to conduct one specific function or transformation well, rather than cover a broad spectrum of incompatible biochemical processes (Paerl and Pinckney 1996).
Bacterial diversity and community composition in archived samples of the original sediment placed in each of our mesocosms was not significantly different than it was within the 8 treatments. This was the case even though each mesocosm had been flooded for more than 14 weeks and all but the controls had macrophytes present. Although this result was not expected it may be explained by the fact that bacterial communities respond quickly to perturbations partly due to the fact that they have a fast growth rate
(Ovreas 2000). In addition, microbial communities tend to have a high degree of adaptability. Microbial diversity along an oxygen gradient or within pockets of differing
Eh allows for biochemical diversification. This provides flexibility for inducible
119 enzymes and processes that can be activated or inactivated depending upon oxygen, Eh,
pH, light, temperature or other physiochemical gradients.
It may be that the inability to detect differences in bacterial diversity between the 8
treatments was due to the nature of microbial ecology. Detection of in situ species is not
straight forward for a host of reasons. The number of particular bacterial genera or
species may fluctuate temporally since shifts in community composition are dynamic.
Abiotic changes within the microenvironment may reduce rRNA as a result of a
downshift of growth rates and low metabolic activities, with the result that in situ
assessment of activity and viability is extremely difficult (Edwards 1999). There are also
some issues regarding the limitations of available tools for analyzing bacterial diversity.
Molecular methods, such as TRFLP, are reliant upon extraction of sufficient rDNA to
PCR amplify. The genetic material of some bacterial species within our treatments may
not have been amplified either due to low concentrations or bacterial cell walls were not
lysed. There are also inherent variations in the extent to which different restriction
enzymes reveal sequence variation (Dunbar et al. 2000).
We did not sample temporally and therefore do not know if seasonal changes in
bacterial community diversity or composition due to treatment effects took place. The
fact that we sampled when all macrophytes had reached their peak in biomass production, and that we also had replicates for each treatment, allows us to be fairly confident that our results for this comparative study are valid. To date, there are few guidelines directing how many replicates or samples are required from an area under study to accurately reflect the microbial diversity present (Franklin and Mills 2003). In fact, a comprehensive microbial community analysis is a new concept to the microbiologist 120 (Tiedje 1995). Little is known about the rates of microbial extinction, rates and range of microbial dispersal, and rates and range of gene transfer among microorganisms (Tiedje
1995). Microbial diversity may be expected to increase or decrease correspondingly with increasing or decreasing environmental differences (Figure 3.5a). Since our mesocosms were similar in all respects except the type and diversity of macrophyte functional groups present, it was expected that random sampling of sediment cores from four areas within each mesocosm would enable sufficient analysis of bacterial differences between the treatments. As well, the analysis of three replicates per treatment would ensure fairly rigorous sampling and represents a larger replication than is typical for this type of study.
a b Degree of microbial difference
major minor estimated OTU and n maximum major r mino OTU number
Degree of environmental environmental difference of Degree 0 Sample number (n)
Figure 3.5: Suggested relationship between the degree of microbial difference and the degree of difference between the microbial habitats in which the organisms are found
(after Tiedje 1995) (a); and Species area curve for obtaining maximum microbial
121 diversity (operational taxonomic units (OTU)) with optimum sample collections (after
Colwell and Coddington 1995)(b).
It could be argued that the obtainment of optimum sampling size is not possible since
the sampling scale at which microbial diversity is required to provide useful information
has yet to be determined. In fact, it has been suggested that not until at least one site is fully inventoried will there be a known biota against which the efficacy of different sampling, isolation and assessment methods can be tested and, extrapolative methods calibrated for the assessment of species richness in other sites (O’Donnell et al. 1995).
The number of samples required to truly represent the maximum bacterial diversity
within a system, using OTU area curves (which are analogous to species area curves used
in macroorganism diversity studies), have yet to be developed (Figure 3.5b). Until then,
it is unmanageable to conduct a comprehensive microbial diversity study at the scale of
grains of sand or within all possible hosts (Tiedje 1995). Or, at the other end of the scale,
to conclude that all proteobacteria occupy all of the world’s soils and waters since this is
not a very useful resolution. For now, understanding the sources of variability and,
sampling with that in mind, should be adequate if relating diversity to function (Tiedje
1995). As a general rule of thumb, organisms that are closer in space tend to be more
similar. It has been suggested that a survey is essentially complete, if little can be gained
by further sampling and it would be a waste of time and money to continue (Colwell and
Coddington 1995). Since our data not only entailed analysis of bacterial diversity, but
also its’ link with denitrification flux, useful information was obtained regardless of the
122 uncertainties inherent with these types of studies and also despite the fact that
measurements were taken only at macrophyte peak biomass.
3.5.2 Bacterial diversity and denitrification flux
Our data suggest that bacterial diversity was sufficient to provide similar denitrification
function within all macrophyte functional group diversity treatments as evidenced by no
increase in flux across the diversity gradient. However, differences were measured
between the monoculture functional groups with respect to all denitrification fluxes.
Furthermore, although there was no evidence of decreased N2O flux with increasing
functional group diversity as hypothesized, N2O flux was significantly higher within the
obligate annuals. The fact that differences in denitrification function existed between the
monoculture functional groups, despite indications of similar bacterial diversity,
suggested that there were differences in denitrifier communities and/or the presence of
different macrophytes created different microenvironments.
When the relationship between total TRFs and a number of measured parameters were
analyzed independent of functional group or functional group diversity only three
parameters were significant. TRF numbers were negatively correlated to in situ N2 flux and to in situ N2O flux (after added nitrate) and positively correlated to sediment C:N
ratios. The fact that as TRF numbers increased, in situ denitrification flux decreased,
may be explained by limiting nitrate concentrations within all of the mesocosms. A
< 87% increase in in situ denitrification occurred in all treatments after nitrate addition.
However, there was no relationship between TRF numbers and denitrification potential.
- Since this assay occurred under non-limiting NO3 conditions, but without glucose 123 addition, bioavailable C may have become the limiting factor. It was also conducted on
sediment samples void of plants, therefore the direct effect of plants on the denitrifiers
including oxic/anoxic zones within the root matrix was also removed. The decrease in
N2O flux with increasing TRF numbers may be attributable to more active nitrous oxide
reductase (Ye et al. 1994), or the different denitrifier communities (Cavigelli and
Robertson 2001). Although, there was no correlation between increasing TRF numbers
(bacterial diversity) and increasing denitrifier diversity as predicted. The positive
relationship between bacterial diversity and sediment C:N was not unexpected given that
C is a major factor influencing bacterial populations. However, what was unexpected
was the lack in significant correlations between TRF numbers and labile C, interstitial
water DOC, macrophyte C:N and macrophyte biomass.
The prevalence of higher microbial diversity within surface sediments as opposed to
deeper levels is attributed to a greater variety and content of organic compounds at the
surface (Tiedje et al. 2001). Plants exert a strong influence on the composition of
microbial communities in soil through rhizodeposition and the decay of litter and roots
(Nannipieri et al. 2003). And, plant litter plays a critical role in determining soil
properties and substrate supply for microorganisms (Bardgett and Shine 1999).
It would therefore, be expected that the C indices measured would be reflective of the
various macrophytes present, and in turn, the diversity of bacteria capable of being supported. The fact that no relationships were detected between TRFs with the above mentioned C parameters indicates that bacterial diversity was high regardless of plant presence and/or any subtle differences, which may have existed, were not detected. Also, far lower concentrations of C than was present within our systems have been determined 124 as optimum for denitrification (LAlisse-Grundmann et al. 1988). Concentrations of 500
µg C g-1dry sediment were sufficient for optimum denitrification in the presence of
- optimum NO3 concentrations, both in laboratory assays, and in the field.
3.5.3 Bacterial community composition and denitrification
The results of the various statistical analyses performed all point to the presence of similar bacterial community composition within all 8 treatments. Examination of the similarities between the replicates for each treatment indicated no differences between the functional group types or functional group diversity treatments. The fact that the
Pearson’s correlation analysis (Figure 3.3) showed no clear clustering of treatment replicates for any of the treatments demonstrates that overall, there was just as much similarity in community composition between treatments as there was within. This is not unexpected given that the differences between replicates on a microscale have the potential to be quite large just by the very nature of the plasticity of environmental conditions and microbial composition within microbial niches (Findlay et al. 1997).
However, it was expected that some macrophyte functional group treatment effects would be manifested at least on bacterial community composition, particularly since there were significant differences between the monoculture functional groups for denitrification fluxes. Rhizosphere microbial populations associated with particular plants in undisturbed field soils were significantly different from one another (Westover et al.
1997) and, microbial communities did not differ between different soils, but they did differ between plant species (Grayston et al. 1998).
125 Although we were attempting to link bacterial diversity with the function denitrification, we chose not to use primers that targeted denitrifiers specifically as previous studies have done (Smith and Tiedge 1992, Ye et al. 1993, Scala and Kerkhof
1998, Braker et al. 2000, Gruntzig et al. 2001). Current research on denitrifiers has identified two types of nitrite reductase enzymes, one containing copper and one containing cytochrome cd. These enzymes are encoded by the genes nirK and nirS, respectively, and represent two structurally different, but functionally equivalent enzymes from very different genetic lineages (Betlach 1982, Braker et al. 2000). The genes are typically targeted with specific primers since they are believed to be present within a large number of denitrifiers. But, the percentage of denitrifiers that may be overlooked by these targeted primers is not known. As well, nosZ sequences (nitrous oxide reductase gene) enzymes are also targeted with primers, but isolated sequences are at most 63% related to known denitrifiers which indicates a substantial in situ diversity not reflected in the cultivable portion of the population (Scala and Kerkhof 1998). Furthermore, the isolation of denitrifiers carrying the nosZ sequences would eliminate a number of
denitrifiers known to exist that do not possess the complete pathway for denitrification
(Betlach 1982, Beauchamp et al. 1989, Ye et al. 1994, Zumft 1997).
Because of cross reactions and false-positive results, along with too narrow a
specificity of probes, the techniques targeting functional genes or enzymes are believed
to be of very limited use for analyzing the community of denitrifiers including those
unculturable in soil (Conrad 1996). Our selection of universal PCR primers was
intended to include the greatest majority of bacteria present by targeting a region
considered to be highly conserved within all prokaryotes. By analyzing the bacterial 126 community as a whole, and not just the denitrifiers, we attempted to obtain a better indication of the total bacterial community diversity within the treatments, and also functional differences linked to these communities. What is known to date regarding prokaryotes, is that they have diverse yet highly specific metabolic and environmental requirements. As well, they survive by forming associations with other prokaryotes and other organisms (Paerl and Pinckney 1996). These associations may facilitate mutualistic nutrient, gas, and metabolic exchange where growth, reproduction, and biogeochemical cycling is conducted more effectively and efficiently than on the individual population level (Paerl and Pinckney 1996).
For this particular study, similar numbers in genera known to contain denitrifiers was evident in all 8 treatments. However, despite having eleven genera known to contain denitrifiers in common, there were total community differences between treatments. The tussocks showed the highest totals with Alcaligenes, Paracoccus and
Rhodopseudomonas unique to this monoculture. All other identified genera with denitrifiers were present within 2 or more treatments. This was also the case for the functional group diversity treatments with two exceptions, Aquifex was unique to the 2
FG diversity treatment, and Flavobacterium was unique to the 3 FG diversity treatment.
The database currently available for bacterial identification in automated identification systems is heavily dominated by clinical strains. Serious deficiencies for many of the microbial groups exist because of the lack of knowledge regarding environmental species
(Tiedje 1995). Despite these problems, the identifiable portion of OTUs that we obtained provides some valuable insight. The data indicate that plant/microbial interactions were taking place to influence bacterial communities which in turn affected function, at least 127 within the monoculture treatments. These effects may be attributable to physical changes
within the microenvironment because of differences in above- and belowground plant
morphologies and physiology. These changes may in turn influence oxic/anoxic zones
- within the root matrix, competition for NO3 , or pH (Reddy et al. 1989, Cavigelli and
Robertson 2000, Frenzel 2000).
It is to be expected that complex interactions occurring between the entire microbial
consortia would also affect denitrification function (Groffman 1991, Wrage et al. 2001),
as well as the presence and diversity of microbial grazers. Ingham et al. (1985)
determined that nematode excretion increased N mineralization rates of bacteria and N-
+ NH4 concentration. Blair et al. (1990) measured differences in N fluxes between mixed-
species litterbags and single-species litterbags. These results were attributed to
differences in the decomposer community since lower microbial and microarthropod
densities and higher nematode densities occurred when litter of varied resource quality was mixed together.
Denitrifiers are known to be highly diverse with different substrate specificities while
sharing only the use of oxidized N species as electron acceptors in a facultative anaerobic
metabolism (Heywood and Watson 1995). Denitrifying bacteria under aerobic conditions
are able to utilize a larger variety of organic acids, carbohydrates, and other organic
compounds such as carbon and energy sources. However, under anoxic conditions some
denitrifiers become more limited in the substrates they are capable of utilizing. For
example, under aerobic conditions the denitrifying bacteria Pseudomonas stutzeri
metabolized cysteine, isoleucine, leucine and valine but under anaerobic conditions, the
same amino acids were not used as carbon sources (Heywood and Watson 1995). 128 Symbiotic relationships between denitrifiers are also known to exist. By isolating two
organisms capable of denitrifying methanol, it was determined that Vibrio extorquens
excreted approximately half of the methanol consumed as soluble metabolites, mostly
citrate and isocitrate, which was then utilized by the denitrifier Pseudomonus stutzeri
(Beauchamp et al. 1989). Denitrifers are also known to possess different abilities to
produce the complimentary suite of enzymes required to reduce nitrate through to
dinitrogen. For example, Aquaspirillum spp. and Pseudomonas spp. were capable of
reducing nitrate to nitrous oxide only, while Vibrio spp. reduce nitrous oxide to
dinitrogen (Robertson and Kuenen 1991). Collectively, these studies hint that denitrifier
community composition plays an important role in regulating function.
An interesting outcome of our study was the occurrence of similar denitrifier
communities within the obligate annuals and the 4 FG diversity treatments. These two
treatments also exhibited the highest in situ nitrous oxide fluxes, after nitrate addition,
although only the obligate annuals were significantly higher. Whether this was
coincidental, or the denitrifier community composition played a role has yet to be
resolved. Monocultures of obligate annuals may be producing more N2O by altering
- the balance between NO3 concentration and available carbon, or by lowering C availability causing slower nitrous oxide reductase enzyme synthesis (Beauchamp et al.
1989, Hutchinson and Davidson 1993, Swerts et al. 1996). The presence of obligate annuals may be affecting key abiotic factors such as oxic/anoxic zones, and pH in such a way that alters the denitrifier community (Cavigelli and Robertson 2000, Frenzel 2000).
Since overall denitrification function was not altered by macrophyte functional group diversity, but nitrous oxide flux was influenced by the presence of a particular functional 129 group, community composition rather than diversity per se appears to play the more important role in influencing this particular function.
3.5.4 Diversity and stability
One common theory tested within biodiversity studies is ecosystem stability (McGrady
–Steed et al. 1997, Naeem and Li 1997, Wardle et al. 2001a). It is hypothesized that the stability of measured functions in ecosystems should increase as diversity increases, because more diverse communities have higher similarity on average in the range of species traits present (Tilman 1999). The examination of biodiversity effects on stability within aquatic microbial communities determined ecosystem respiration to become more predictable with increasing biodiversity (McGrady –Steed et al. 1997) and replicate communities to be more consistent in biomass and density measures indicating more ecosystem reliability with increased biodiversity (Naeem and Li 1997).
For our study, the effect of macrophyte functional group diversity on denitrification flux stability was examined using Tilman’s (1999) µ / σ calculation where the true mean divided by the true standard deviation provides an indication of the spatial stability of randomly assembled communities differing in diversity. The results did not indicate that denitrification flux became more stable as macrophyte functional group diversity increased (Figure 3.6). Stability values, in fact, were no higher within the higher diversity treatments than they were within the monoculture functional groups.
This result is not too surprising given the nature of denitrification, which is well known to exhibit extremely high variability over short distances. Measurement of in situ denitrification flux exhibits large coefficients of variation due to localized denitrification 130 “hot spots” (Christensen et al. 1990, Murray et al. 1995, Groffman 1991, Groffman et al.
2000). Furthermore, these coefficients frequently exceed 100% even with intensive
sampling of small field plots. This occurrence is largely due to the heterogeneous
- distribution of factors controlling denitrification such as NO3 and C supply (Groffman
1991).
In a study measuring microbial community dynamics within a methanogenic reactor
over a 604 day period, functional stability did not imply community stability (Fernandez
et al. 1999). Although similar methane fluxes were measured, high temporal variability
within OTUs was observed. We also analyzed the relationship between TRF numbers
and macrophyte functional group diversity using the same µ / σ calculation (Figure 3.7).
But, unlike Fernandez et al. (1999), we observed no trend for an increase in bacterial
diversity stability with increasing macrophyte diversity. In fact, the facultative annuals
and obligate annuals showed the highest µ/σ values and were more than double those of the 2 FG, 3 FG and 4 FG macrophyte diversity treatments.
131
7 in s itu N2
6 In s itu N2 (N+) in s itu N2O(N+) 5 denit. potent.
σ 4 /
µ 3
2
1 0
01234
Functional group diversity treatments
Figure 3.6: Variance in denitrification flux relative to macrophyte functional group
diversity. The higher the value the lower the variance in flux within the diversity
treatment representing increased stability (after Tilman 1999). Values are obtained by
dividing the mean (µ) gas flux for each treatment by the standard deviation (σ). Gas
fluxes analyzed are in situ N2 (in situ N2), in situ N2 with nitrate added (in situ N2 N+), in situ N2O with nitrate added (in situ N2O N+) and denitrification potential (denit. potent.)
132
12 facultative annual 10 obligate annual 8
σ
/ 6 µ reed
4 2 tussock 0 01234 Functional group diversity treatments
Figure 3.7: Variance in TRFs relative to functional group diversity. The higher the value the lower the variance in flux within the diversity treatment which represents increased stability (after Tilman 1999). Values are obtained by dividing the mean (µ) totals of
TRFs for each treatment by the standard deviation (σ). The individual functional groups
for the 1 FG diversity treatment are labeled.
133 In summary, in order to derive meaningful information pertaining to the relationship
between biodiversity and function in soils, the links between genetic diversity and
community structure and between community structure and function must first be
understood (O’Donnell et al. 2001). Using a combination of molecular 16S rRNA based
(TRFLP) and metabolic (denitrification flux measurements) approaches, we investigated
the links between macrophyte functional group diversity, bacterial diversity, and
denitrification function within wetland sediments. No significant differences in TRF
numbers for the monoculture macrophyte functional groups or the macrophyte functional
group diversity treatments were evident. Furthermore, differences in denitrification function between the diversity treatments or differences in in situ nitrous oxide flux after nitrate addition were not observed. However, significant differences did occur between the monoculture macrophyte functional groups for denitrification flux and for in situ
nitrous oxide under higher nitrate concentrations with the obligate annuals showing a
significantly higher flux. Our results suggest that macrophyte functional group diversity
does not impact bacterial diversity, bacterial community composition, or denitrification
function. However, since N2O flux was significantly higher within one macrophyte
functional group, trace gas flux overall may be dampened within wetlands exhibiting
higher macrophyte diversity. This finding has important implications for wetland
mitigation practices which, to date, commonly result in wetlands exhibiting low
macrophyte diversity and is also relevant to issues related to global climate change.
134
CHAPTER 4
CONCLUSIONS
This research provides evidence that increasing macrophyte functional group diversity
does not result in increased C pool quantity and/or quality, bacterial biomass, bacterial diversity, or denitrification function in wetland sediments. In the first study which included clonal dominants, significantly higher plant biomass was evident due to the superior competitive abilities of this particular functional group. This increased biomass appeared to contribute to the significantly higher labile C pools and significantly higher denitrification potential in the highest diversity treatment indicating the presence of a sampling effect. However, the more plausible explanation, since only two sampling points were driving this average upward, is due to the inherent nature of denitrification itself in which denitrifying ‘hot spots’ are frequently found and high variability between
replicates is common (Murray 1995, Groffman 1991, Groffman et al. 2000). This explanation is further supported by the lack of significant differences between the individual macrophyte functional groups for denitrification potential as well as the fact
that bacterial biomass was not significantly higher, within the diversity treatments, or
between the functional groups. In situ denitrification did not increase across the
macrophyte functional group diversity gradient in either of the two studies. We also
determined that there were no detectable differences in bacterial diversity either between
the diversity treatments or between the individual macrophyte functional groups. The
135 results indicate that rather than a niche-differentiation mechanism, due to increased
macrophyte functional group diversity, there was an averaging effect taking place.
Significant differences were observed between the macrophyte functional groups for
denitrification function, C pools and denitrifier bacterial community composition. The tussocks and reeds showed consistently higher in situ denitrification and denitrification potential while the obligate annuals showed significantly higher in situ N2O fluxes when nitrate became available. Although there were no significant differences between the treatments in the number of denitrifier genera present, there were differences in denitrifier community composition. Differences in competition between the heterotrophic microbial communities and the macrophyte functional groups for the limited resource, nitrate were apparent. As were complex feed back mechanisms with regard to mineralization rates on the part of the microbes, and C inputs and abiotic influences on the part of the plants that served to confound the elucidation of consistent patterns. These complex relationships have been reported in comparable terrestrial studies (Wardle and Nicholson 1996, Zak et al. 2003).
Further research is required to investigate the relationship between macrophyte functional group diversity, bacterial diversity, bacterial community composition, and denitrification function after perturbations which are commonly experienced in naturally occurring wetlands. Research is also required to investigate the N2O:N2 ratio emitted from entire systems including the macrophytes within diverse and monoculture communities. Further investigations are also required to understand the direct link between C substrates via macrophyte root exudation and maintenance of bacterial
136 diversity, and the effects on denitrification function due to reduced microbial diversity
and diversity across different trophic levels.
Currently, federal laws requiring compensatory mitigation for impacts on or destruction
to natural wetlands have been ineffectual. A recent report by the National Research
Council investigating the efficacy of these wetland policies determined that the majority
of the mitigated wetlands developed into systems promoting low diversity of wetland
associated species (Zedler et al. 2001a). One of the principal findings were that the goal
of no net loss of wetlands was not being met for function even though this is clearly
stated in Section 404 of the Clean Water Act. Mitigation permits are granted through the
U.S. Army Corps of Engineers and require the recipient to restore or replace the affected wetland and have clearly stated performance goals with regard to a number of factors including hydrology, water quality, and desired plant and animal communities. As well, monitoring for mitigation permit compliance is legislated to take place once annually for
5 years; however this has not been strictly enforced.
The results of our study indicate that low plant diversity wetlands would not impact denitrification function. Further, treatment wetlands designed for nitrate removal are highly effective with plant monocultures (Kadlec and Knight 1996). However, our results along with those of other studies, also indicate that the maintenance of diverse wetland systems is important for other highly valued functions. For instance, increased macrophyte diversity may reduce trace gas flux indirectly by ensuring that wetlands with monocultures of particular macrophytes, such as obligate annuals, that promote N2O flux, do not exist. Furthermore, evidence suggests that methanogenesis is lower within high macrophyte diversity systems (Reed et al., in prep.), and wildlife habitat, for a number of 137 wetland dependent species, is greatly influenced (Kent 1994, Whitman et al. 1995, Kusler and Kentula 1998, Denny 1994, National Wetlands Working Group 2000, Zedler et al.
2001b).
In order for policy relevant to wetland mitigation and protection to be effective, it is critical that all functions affected by plant diversity be taken into account, and also that policy makers are cognizant of the fact that there is still a great deal yet to be learned.
Clearly improvements to mitigation permitting are needed to ensure more effective wetland designs, more stringent and increased mitigated wetland monitoring, and most importantly, improved protection for already existing high quality, natural wetlands.
138
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APPENDIX A DATA OBTAINED FOR MESOCOSM STUDY #1 AND STUDY #2
161 September 2001
denitrification flux: N-N2O+N2 N-N2O+N2 mesocosm mg/m2/day ug/m2/day mg/L ppm ug C/g soil % % ratio treatments samples DEA total in situ N-NO3 DOC Labile C sediment N sediment C sediment C:N controls A2 4.34 86.76 0.15 286.63 0.17 4.23 25.58 A6 2.77 43.38 0.10 198 302.33 0.16 4.14 25.17 A10 6.13 0.00 0.10 160 248.45 0.14 4.30 30.33 C8 5.45 0.00 0.10 322.53 0.17 4.37 26.36 D9 3.39 43.38 0.10 204 411.36 0.15 4.06 27.87 clonal B2 6.94 86.76 0.11 84 296.14 0.17 4.16 24.44 dominants C3 2.32 0.00 0.07 84 343.83 0.18 4.31 24.64 C4 3.19 455.51 0.10 112 339.30 0.18 4.37 24.61 C10 3.82 43.38 0.04 35 353.56 0.19 4.33 23.37 D7 4.56 86.76 0.07 90 364.69 0.16 4.07 25.16 tussock A4 3.17 0.00 0.11 307.90 0.14 4.53 31.96 B6 4.28 0.00 0.05 314.55 0.16 4.17 25.56 B8 6.93 0.00 0.10 321.61 0.19 4.57 24.19 C5 6.19 21.69 0.10 306.68 0.17 3.93 23.26 E7 4.10 21.69 0.09 340.88 0.16 4.29 26.14 reed D3 4.05 0.00 0.09 245 300.85 0.18 4.43 24.81 D5 4.90 0.00 0.09 294 273.71 0.18 4.35 24.65 D6 7.47 0.00 0.06 77 248.45 0.16 4.16 25.47 E10 3.63 21.69 0.06 114 283.68 0.16 4.14 25.16 F4 2.73 0.00 0.06 122 332.41 0.15 3.95 26.03 facultative A3 3.58 0.00 0.12 239 311.28 0.15 4.26 28.03 annuals E3 3.11 0.00 0.10 257 288.33 0.16 4.07 26.07 E6 5.49 0.00 0.06 167 283.62 0.16 4.30 27.40 F3 3.17 563.96 0.06 174 299.09 0.17 3.94 23.12 F9 2.25 0.00 0.10 300 359.58 0.16 4.23 25.80 obligate A9 3.38 1409.91 0.09 350.33 0.16 4.12 25.95 annuals C7 4.35 21.69 0.06 293.04 0.16 4.15 25.72 D8 5.73 151.84 0.05 73 342.39 0.14 4.14 28.65 E1 4.59 21.69 0.06 101 309.21 0.16 4.22 26.74 F6 5.74 130.15 0.10 148 341.57 0.15 4.10 26.50 1FG avg 4.39 121.47 0.08 150.89 316.27 0.16 4.21 25.74 st dev 1.46 303.03 0.02 82.32 29.80 0.01 0.17 1.88 st error 0.29 60.61 0.00 16.46 5.96 0.00 0.03 0.38 2FGB94.27325.360.04 253.900.164.4627.45 B10 7.44 0.00 0.04 61 348.98 0.17 4.29 24.96 C1 4.76 0.00 0.07 80 366.32 0.19 4.40 23.73 C2 3.38 455.51 0.10 102 361.75 0.17 4.45 26.30 E5 6.27 65.07 0.08 292 348.09 0.19 4.45 23.28 E9 5.64 65.07 0.10 122 308.01 0.16 3.89 24.00 3FG A1 7.12 0.00 0.07 43 384.99 0.18 4.42 24.68 A8 3.97 629.04 0.05 307.60 0.16 4.23 26.37 B5 5.43 173.53 0.05 366.32 0.15 4.25 27.84 E8 2.25 151.84 0.09 70 356.31 0.17 3.85 22.70 F5 5.68 65.07 0.06 107 320.49 0.17 4.13 24.86 F8 5.26 520.58 0.05 58 334.20 0.17 4.07 23.33 4FG A5 4.53 1648.51 0.05 229.69 0.15 4.18 27.07 C6 5.17 1388.22 0.05 336.30 0.18 4.17 23.37 D4 6.73 1344.84 0.09 106 324.18 0.16 4.11 26.32 E4 2.38 1366.53 0.04 118 347.80 0.17 4.14 24.28 F2 6.97 86.76 0.05 73 364.14 0.16 4.64 29.32 F7 8.46 1258.07 0.07 72 317.68 0.16 4.12 26.02 5FGA74.33173.530.11 388.040.154.4930.64 B1 6.51 86.76 0.08 338.99 0.16 4.49 28.07 B3 3.34 0.00 0.11 59 382.49 0.17 4.30 25.51 B4 16.17 0.00 0.06 72 372.17 0.17 4.38 25.51 B7 7.59 65.07 0.05 406.80 0.15 4.10 26.94 D2 563.96 0.05 64 328.48 E2 12.21 0.00 0.05 325.70 0.20 4.73 23.52 continued
Table 1. Macrophyte functional group and functional group diversity data: Study #1 162 Table 1 continued
Denitrification flux: April 2002 N-N2O+N2 N-N2O+N2 mg/m2/day ug/m2/day mg/L PPM ug C/g soil % % ratio treatments samples DEA total in situ NO3/NH3 DOC Labile C sediment N sediment C sediment C:N controls A2 2170.54 1.45 34.24 309.01 0.16 3.61 23.22 A6 54.26 2.22 47.89 269.27 0.17 2.97 17.69 A10 1.13 45.79 6.80 80.69 345.42 0.18 4.06 22.19 C8 1.26 662.84 0.92 14.10 293.99 0.15 3.86 26.27 D9 2.86 972.39 3.07 40.36 265.15 0.18 3.70 20.09 clonal B2 5.45 27.70 0.28 45.38 475.28 0.20 4.61 23.30 dominants C3 4.61 38.01 0.00 39.31 474.25 0.16 2.75 16.77 C4 4.41 27.48 0.15 10.59 276.98 0.16 2.69 16.69 C10 4.52 0.11 30.12 454.81 0.22 4.81 21.91 D7 7.56 3.89 0.02 45.21 361.15 0.19 3.85 20.60 tussock A4 2.89 194.16 0.29 44.62 294.16 0.19 4.07 20.97 B6 2.66 1119.39 0.76 32.20 317.99 0.18 3.51 19.26 B8 2.05 1136.79 0.25 17.31 285.60 0.21 4.02 19.45 C5 4.37 938.74 0.83 31.36 276.70 0.18 3.01 16.64 E7 5.18 758.54 1.20 84.01 234.86 0.17 4.00 23.12 reed D3 4.02 55.41 0.02 44.47 311.64 0.18 3.81 21.19 D5 7.38 0.01 18.01 268.42 0.18 3.82 21.59 D6 3.98 0.68 39.23 347.75 0.20 3.89 19.60 E10 2.80 992.08 0.08 30.48 362.14 0.16 3.69 22.43 F4 2.79 18.77 0.03 19.07 263.83 0.16 3.82 24.66 facultative A3 4.23 593.69 0.98 28.11 351.35 0.19 3.54 19.05 annual E3 1.65 605.14 3.02 46.56 267.08 0.17 4.06 23.41 E6 0.05 49.32 238.44 0.19 3.82 19.90 F3 1.44 301.08 4.12 63.84 287.16 0.12 3.73 29.86 F9 2.76 973.31 7.58 100.50 364.72 0.15 3.62 24.16 obligate A9 2.96 7.10 0.37 26.12 271.72 0.17 4.09 24.53 annual C7 2.52 32.05 0.05 25.90 252.22 0.20 4.42 22.58 D8 4.97 47.62 0.11 53.68 274.29 0.20 4.03 20.46 E1 3.04 24.96 0.39 57.81 329.26 0.18 3.83 21.76 F6 1.21 7.78 0.64 72.92 243.51 0.17 3.73 22.55 1FG avg 3.73 376.37 0.88 42.25 315.41 0.18 3.81 21.46 st dev 1.66 436.82 1.70 21.42 69.81 0.02 0.48 2.90 st error 0.36 94.96 0.34 4.28 13.96 0.00 0.10 0.58 2FG B9 2.63 56.55 0.19 49.01 303.40 0.19 3.86 20.30 B10 8.21 36.40 0.00 55.95 283.57 0.16 2.91 18.13 C1 6.08 38.47 0.05 17.51 511.76 0.16 3.16 19.13 C2 3.38 35.95 0.04 11.34 330.28 0.16 2.81 17.40 E5 1.43 168.06 0.01 13.59 278.29 0.17 3.93 23.39 E9 0.54 8.93 1.50 40.36 279.07 0.19 3.95 20.97 3FG A1 3.44 16.94 0.19 60.15 281.44 0.20 3.74 18.57 A8 7.10 29.31 0.94 42.17 350.59 0.19 3.69 19.93 B5 10.80 0.04 28.29 361.08 0.20 3.87 19.71 E8 16.03 0.05 70.02 366.83 0.19 3.70 19.35 F5 2.60 328.56 0.14 16.21 256.33 0.10 3.17 30.60 F8 1.08 302.00 0.00 48.64 531.37 0.18 4.30 23.27 4FG A5 4.18 0.00 35.26 369.13 0.19 3.71 19.55 C6 4.01 42.36 0.04 13.43 386.98 0.17 3.81 21.89 D4 6.19 28.39 0.05 57.56 431.07 0.17 3.98 23.57 E4 3.53 584.76 0.60 31.91 280.84 0.19 4.28 22.31 F2 7.00 696.27 0.15 33.44 472.41 0.14 3.89 27.80 F7 10.04 16.49 0.46 35.81 560.26 0.17 3.21 18.47 5FG A7 5.43 33.89 0.02 83.23 373.17 0.22 3.94 17.70 B1 5.16 17.86 0.02 398.68 0.20 4.31 22.02 B3 5.38 72.12 0.52 52.17 340.86 0.20 4.26 21.34 B4 6.61 43.04 0.02 32.32 438.56 0.20 4.63 22.73 B7 4.24 15.80 0.01 63.56 329.86 0.22 4.24 19.53 D2 3.66 0.14 53.81 509.98 E2 8.52 430.90 0.50 36.98 258.31 0.18 4.52 25.59 163 August 2002
Denitrification flux: N-N2O+N2 N-N2 ug CO2-C/ mg/m2/day mg/m2/day mg /L ppm ug C/g soil g soil % % ratio treatments samples DEA total insitu NO3+NO2 DOC Labile C SIR sediment N sediment C sediment C:N controls B7 11.42 0.63 0.00 78.78 91.78 39.90 0.13 2.36 18.77 D3 6.67 3.40 0.00 94.53 170.40 29.83 0.11 2.33 20.33 D7 13.86 5.34 0.22 88.68 280.44 17.93 0.12 2.42 20.03 D8 14.12 1.69 138.8 243.30 17.58 0.12 2.41 20.52 F2 14.56 7.08 0.00 74.53 215.65 30.36 0.12 2.61 21.18 F7 13.84 3.21 0.00 77.44 214.47 49.23 0.10 1.92 19.58 tussock A1 21.75 0.17 0.00 62.38 163.56 45.89 0.10 2.27 21.82 B2 2.21 0.18 0.02 70.85 205.21 17.35 0.13 2.85 21.40 C6 11.55 14.33 0.00 38.78 129.35 8.25 0.12 2.42 19.61 E3 10.95 2.10 0.00 128.2 261.95 32.11 0.10 2.26 22.35 E5 12.41 4.43 1.20 29.53 353.93 21.58 0.12 2.36 20.53 reed B3 15.50 4.26 0.01 70.85 235.34 42.34 0.14 2.64 19.40 B4 11.42 3.79 0.48 75.62 97.57 15.47 0.12 2.35 19.27 C3 13.31 3.16 0.18 83.22 209.04 23.29 0.13 2.46 19.71 D5 3.01 0.00 63.58 260.87 25.66 0.13 2.71 21.57 E2 2.64 6.35 0.00 81.98 234.94 27.21 0.11 2.32 21.74 F8 14.81 1.18 134.46 21.64 0.12 2.60 22.36 facultative A3 16.84 0.45 0.15 151.8 181.07 37.92 0.14 2.90 21.17 annual A8 10.25 1.28 0.00 67.17 101.79 14.35 0.10 2.46 24.06 B1 21.46 1.64 0.01 91.58 0.00 15.20 0.11 2.30 20.36 B6 13.01 0.29 0.00 148.6 199.77 26.68 0.12 2.43 19.68 C1 15.66 0.00 0.00 44.99 200.14 39.79 0.12 2.51 20.43 D2 16.56 3.66 0.00 92.12 119.77 21.44 0.10 2.14 22.26 obligate C5 0.11 0.00 90.04 189.02 30.13 0.14 2.83 20.37 annual D4 15.51 0.44 0.00 52.41 95.39 23.93 0.13 2.61 19.66 E1 3.13 2.86 0.00 50.06 177.58 20.71 0.11 2.68 25.15 E7 26.44 8.29 0.00 52.98 203.36 39.55 0.13 2.88 21.94 F3 2.79 0.07 0.00 132.5 168.88 19.64 0.11 2.44 22.42 F6 15.54 0.14 0.00 59.96 276.65 31.14 0.14 2.66 19.37 1FG avg 13.04 2.70 0.09 79.05 182.59 26.14 0.12 2.53 21.16 st dev 6.43 3.37 0.27 34.16 74.72 9.89 0.01 0.22 1.55 st error 1.34 0.70 0.06 7.12 15.57 2.06 0.00 0.05 0.32 2 FG A7 15.42 7.37 0.00 77.67 256.44 9.06 0.12 2.72 23.15 C7 16.26 1.67 0.00 80.73 226.48 21.94 0.12 2.32 19.26 D1 21.10 3.80 0.00 38.09 216.28 18.90 0.12 2.60 22.57 D6 16.97 10.15 0.00 73.22 245.37 8.38 0.12 2.68 21.96 F1 16.16 2.29 0.00 80.5 192.08 26.63 0.11 2.13 19.49 F5 29.03 0.44 1.87 17.75 202.64 27.09 0.14 2.67 19.28 3 FG A4 13.48 2.70 0.02 68.05 203.29 35.41 0.11 2.21 20.61 A5 13.57 0.07 0.66 48.84 175.66 9.95 0.11 2.26 19.84 C2 3.04 0.00 53.22 195.42 26.15 0.14 3.18 22.27 C4 12.97 1.85 0.00 90.79 199.62 20.87 0.12 2.35 20.37 E4 15.76 1.10 3.07 30.72 129.09 12.32 0.15 3.50 23.35 E6 15.29 1.20 0.00 87.3 231.05 20.19 0.12 2.31 19.03 4 FG A2 13.40 6.47 0.00 65.69 0.00 26.27 0.10 2.43 23.59 A6 15.92 5.54 0.00 53.3 185.83 24.40 0.12 2.52 21.78 B5 16.57 9.32 0.00 53.52 168.58 27.41 0.13 2.29 17.99 B8 14.68 5.25 0.00 74.62 76.24 21.76 0.12 2.72 23.60 C8 15.64 3.43 0.00 46.59 173.81 14.55 0.10 2.23 22.58 E8 21.01 3.38 0.77 33.16 257.19 30.36 0.13 2.64 20.51 continued
Table 2. Macrophyte functional group and functional group diversity data: Study #2
164
Table 2 continued
September 2003 Denitrification flux: nitrate added: N-N2O+N2 N-N2 N-N2O N-N2 N-(N2O+N2) ug C/ ug CO2-C/ mg/m2/day mg/m2/day ug/m2/day ug/m2/day mg/m2/day ratio mg/L ppm g sediment g sediment % % ratio treatments samples DEA total insitu in situ N2O in situ N2 total insitu N2:N2O NO3+NO2 DOC Labile C SIR sediment N sediment C sediment C:N controls B7 29.45 1.90 1040.13 26493.94 27.53 25.47 0.00 113.50 111.00 58.20 0.12 2.37 19.75 D3 22.78 1.53 1099.01 24276.30 25.38 22.09 0.00 111.40 130.68 57.07 0.11 2.11 19.76 D7 22.45 0.94 1452.26 45392.96 46.85 31.26 0.00 146.80 167.51 60.54 0.16 3.13 19.73 D8 34.88 0.27 3964.28 56167.16 60.13 14.17 0.00 94.78 109.99 50.68 0.13 2.62 19.61 F2 20.29 1.44 2806.40 27416.32 30.22 9.77 0.00 72.91 107.55 63.29 0.11 2.14 19.22 F7 32.76 0.87 6515.55 38995.16 45.51 5.98 0.00 46.57 97.56 48.92 0.11 2.54 22.61 Tussock A1 38.62 2.38 738.89 37530.14 38.27 50.79 0.25 13.89 130.58 67.14 0.14 2.45 17.33 B2 50.95 1.95 569.13 30615.22 31.18 53.79 0.00 16.12 107.78 45.96 0.13 2.42 18.65 C6 40.76 2.70 1373.76 32754.36 34.13 23.84 0.00 16.38 87.09 53.25 0.12 2.35 19.73 E3 42.26 2.86 902.76 52477.63 53.38 58.13 191.58 47.43 0.11 2.79 25.02 E5 55.10 0.85 1766.26 46590.09 48.36 26.38 0.26 13.42 166.49 58.48 0.13 2.59 19.94 Reed B3 64.28 1.79 412.13 26219.19 26.63 63.62 0.23 27.13 137.73 53.27 0.14 2.64 18.66 B4 51.23 2.18 1099.01 25002.43 26.10 22.75 0.00 42.02 103.03 31.63 0.13 2.51 19.88 C3 79.73 2.95 372.88 32636.61 33.01 87.53 22.49 101.62 25.68 0.13 2.53 19.77 D5 27.12 2.15 1059.76 30948.85 32.01 29.20 0.04 36.45 81.19 40.84 0.12 2.74 23.26 E2 57.31 1.63 765.38 23746.42 24.51 31.03 0.00 34.58 122.33 41.66 0.12 2.35 19.09 F8 61.71 1.88 883.13 46727.47 47.61 52.91 0.13 19.64 139.50 28.92 0.13 2.39 19.01 Facultative A3 25.51 0.16 451.38 24178.18 24.63 53.57 0.00 136.00 119.42 71.25 0.14 2.76 19.53 annual A8 13.01 0.69 726.13 23550.17 24.28 32.43 0.00 119.50 111.41 39.32 0.11 2.32 22.05 B1 34.10 0.92 1746.64 42272.56 44.02 24.20 0.00 57.59 119.07 39.92 0.11 1.97 18.30 B6 19.49 -0.09 1118.63 29496.59 30.62 26.37 234.30 142.07 51.36 0.14 2.70 18.76 C1 0.87 1785.89 19350.39 21.14 10.84 0.00 56.09 101.43 81.46 0.14 2.93 21.43 D2 16.25 0.05 471.00 43626.69 44.10 92.63 0.00 79.62 92.58 49.11 0.10 2.18 21.45 Obligate C5 38.84 2.98 7732.31 18486.88 26.22 2.39 0.00 115.90 149.79 45.02 0.14 2.70 19.34 annual D4 37.98 -0.18 2256.89 91963.42 94.22 40.75 0.00 104.80 140.69 69.01 0.14 3.11 21.48 E1 52.68 0.27 2001.76 96143.57 98.15 48.03 0.00 24.94 101.19 38.99 0.12 2.66 21.90 E7 49.42 1.79 10813.45 18800.89 29.61 1.74 0.00 17.57 114.46 48.35 0.13 2.75 21.79 F3 40.99 -0.14 1766.26 87665.51 89.43 49.63 0.04 19.16 92.25 38.42 0.11 2.48 22.67 F6 40.70 -0.16 4396.03 54459.77 58.86 12.39 0.00 116.24 38.92 0.13 2.86 21.38 1FG avg 42.64 1.32 1965.63 40662.74 42.63 38.91 0.01 57.50 120.41 48.06 0.13 2.57 20.45 st dev 16.40 1.11 2509.45 22880.80 22.73 23.96 0.01 56.38 26.63 13.94 0.01 0.26 1.85 st error 3.42 0.23 522.80 4766.83 4.74 4.99 0.00 11.75 5.55 2.90 0.00 0.05 0.39 2 FG A7 50.69 0.05 1746.64 25296.81 27.04 14.48 83.00 112.65 38.51 0.12 2.92 24.67 C7 51.20 1.42 3061.52 32597.36 35.66 10.65 0.00 129.20 143.17 42.51 0.11 2.32 20.50 D1 42.38 0.78 196.25 12187.21 12.38 62.10 0.00 7.50 93.32 55.94 0.11 2.27 20.94 D6 47.60 0.41 981.26 47021.84 48.00 47.92 0.00 46.11 113.82 60.46 0.13 2.51 18.76 F1 32.79 1.60 3434.40 23942.67 27.38 6.97 0.00 51.66 149.81 47.64 0.12 2.46 20.22 F5 0.00 0.07 529.88 37287.77 37.82 70.37 0.00 4.05 146.50 47.44 0.13 2.75 20.91 3 FG A4 28.97 0.32 490.63 17917.76 18.41 36.52 0.00 40.98 76.83 0.11 2.44 21.38 A5 32.11 -0.07 647.63 70984.14 71.63 109.61 0.03 43.73 109.12 64.88 0.11 2.27 20.05 C2 55.03 2.38 1746.64 39191.41 40.94 22.44 0.51 11.19 110.18 38.61 0.13 2.72 20.41 C4 45.53 0.05 2806.40 69414.13 72.22 24.73 0.00 56.70 155.83 56.21 0.11 2.18 20.11 E4 60.51 0.37 353.25 18035.51 18.39 51.06 1.23 12.49 69.97 20.19 0.13 2.29 17.91 E6 33.74 0.41 0.00 0.00 0.00 29.62 79.08 46.53 0.13 2.39 17.77 4 FG A2 26.58 1.03 608.38 40702.55 41.31 66.90 0.00 26.85 126.51 61.81 0.15 3.06 20.54 A6 38.19 1.74 5553.92 66077.86 71.63 11.90 0.00 14.14 91.84 23.26 0.15 3.49 22.80 B5 30.15 1.40 5632.42 40408.17 46.04 7.17 0.00 53.96 42.39 42.37 0.12 2.30 18.67 B8 33.64 -0.07 5750.17 31105.85 36.86 5.41 0.00 53.96 116.98 39.03 0.13 2.52 20.10 C8 36.86 0.96 4454.91 66332.98 70.79 14.89 0.00 25.62 32.47 0.11 2.17 20.22 E8 61.56 -0.23 1393.39 31694.61 33.09 22.75 0.08 9.13 126.98 25.16 0.15 3.36 22.41 continued
165
Table 2 continued
April 2003 Denitrification flux: nitrate added: N-N2O+N2 N-N2 N-N2O N-N2 N-(N2O+N2) ug C/ ug CO2-C/ mg/m2/day mg/m2/day ug/m2/day ug/m2/day mg/m2/day ratio mg/L ppm g sediment g sediment % % ratio treatments samples DEA total insitu in situ N2O in situ N2 total insitu N2:N2O NO3+NO2 DOC Labile C SIR sediment N sediment C ediment C:N controls B7 6.71 2.51 371.37 13210.08 13.58 35.57 0.119 74.23 106.48 90.60 0.13 1.99 14.89 D3 2.85 6.11 220.72 12762.00 12.98 57.82 0.121 95.63 119.27 99.52 0.15 2.16 14.46 D7 4.42 0.31 453.34 30792.83 31.25 67.92 0.101 54.85 95.09 142.79 0.14 2.24 15.82 D8 4.45 3.30 379.39 27726.37 28.11 73.08 0.248 35.03 92.57 124.20 0.14 2.14 15.09 F2 3.40 0.60 354.20 18859.89 19.21 53.25 0.304 40.29 104.68 117.57 0.14 2.32 16.07 F7 3.41 0.94 1901.51 14406.16 16.31 7.58 0.382 48.12 112.42 96.80 0.15 2.17 14.81 tussock A1 10.91 2.43 355.80 20553.74 20.91 57.77 0.392 16.81 138.67 106.99 0.15 3.03 20.28 B2 5.87 2.28 2291.89 8210.51 10.50 3.58 0.265 15.12 112.98 84.46 0.13 2.31 17.43 E3 8.11 2.22 625.06 16509.16 17.13 26.41 0.897 16.73 130.29 87.45 0.11 2.08 18.76 E5 23.67 2.18 235.37 13367.37 13.60 56.79 0.151 26.14 95.31 75.91 0.15 2.51 16.81 reed B3 8.37 0.17 851.50 6313.11 7.16 7.41 0.472 14.32 106.66 64.96 0.14 2.64 19.27 B4 8.30 2.40 381.22 24917.72 25.30 65.36 0.451 20.39 86.98 55.59 0.11 2.41 21.55 C3 12.94 4.48 2501.85 7498.90 10.00 3.00 0.173 14.5 97.67 39.21 0.14 2.27 16.42 D5 8.99 3.03 724.66 11629.79 12.35 16.05 0.342 12.87 96.59 70.06 0.15 2.61 17.65 E2 5.23 4.40 3381.05 14533.46 17.91 4.30 0.097 36.17 97.28 125.22 0.13 2.38 18.88 F8 14.25 4.10 240.87 29430.29 29.67 122.19 0.358 12.67 114.87 44.94 0.17 2.55 14.66 facultative A3 4.62 3.29 704.51 7970.10 8.67 11.31 0.081 80.61 108.22 129.39 0.15 2.37 15.80 annual A8 3.20 5.11 97.77 7166.45 7.26 73.30 0.118 99.68 119.96 132.29 0.14 2.16 15.67 B6 4.17 0.14 253.00 10495.98 10.75 41.49 0.125 119.4 88.29 111.90 0.16 3.64 23.17 C1 3.34 3.08 758.09 21540.33 22.30 28.41 0.512 42.05 107.23 104.43 0.14 2.47 18.01 D2 2.37 0.25 1078.17 5638.83 6.72 5.23 0.062 71.88 97.81 107.09 0.11 2.17 19.84 obligate C5 3.67 2.49 1504.27 34269.36 35.77 22.78 0.070 88.93 94.17 108.85 0.13 2.02 15.16 annual D4 4.74 0.25 4819.15 7663.52 12.48 1.59 0.085 70.14 108.69 122.06 0.16 3.21 19.88 E1 6.47 7.81 876.00 38452.23 39.33 43.90 0.150 63.5 89.37 91.37 0.13 2.39 18.10 E7 4.84 6.34 1074.28 21030.89 22.11 19.58 0.156 56.43 102.16 143.99 0.13 2.41 18.09 F3 4.21 0.21 234.68 32388.22 32.62 138.01 0.324 34.99 101.04 101.85 0.16 3.36 21.49 F6 5.24 0.12 865.24 30307.66 31.17 35.03 0.081 41.13 142.59 79.81 0.14 2.54 18.56 1FG avg 7.31 2.70 1135.93 17613.70 18.75 37.31 0.255 45.45 106.52 94.66 0.14 2.55 18.36 st dev 4.94 2.15 1191.47 10483.29 10.20 37.91 0.208 32.52 15.61 29.15 0.02 0.42 2.22 st error 1.03 0.45 248.22 2184.02 2.13 7.90 0.045 6.77 3.25 6.07 0.00 0.09 0.46 2 FG A7 6.74 6.96 1113.66 8923.72 10.04 8.01 0.097 62.23 113.81 77.38 0.13 2.32 17.96 C7 7.82 7.70 1584.40 16725.30 18.31 10.56 0.067 60.33 97.22 86.54 0.14 2.34 17.15 D1 5.45 1.57 2454.68 8579.82 11.03 3.50 0.125 51.17 127.83 102.26 0.13 2.18 17.09 D6 5.99 2.72 1777.42 8440.38 10.22 4.75 0.084 77.39 81.49 89.57 0.14 2.09 14.94 F1 7.89 6.44 754.65 11252.47 12.01 14.91 0.248 31.57 97.16 69.72 0.14 2.47 18.03 F5 11.46 5.53 172.86 31619.60 31.79 182.92 0.485 11.87 120.93 91.82 0.16 2.74 16.76 3 FG A4 4.73 9.97 215.45 15227.21 15.44 70.68 0.157 43.4 105.33 139.65 0.13 2.49 18.64 A5 4.98 6.06 1082.06 5881.07 6.96 5.44 0.258 33.49 82.07 119.41 0.13 2.15 16.13 C2 11.25 3.54 1149.61 9066.82 10.22 7.89 0.826 13.59 103.68 77.62 0.12 2.22 18.20 C4 5.25 4.17 465.70 15560.12 16.03 33.41 0.074 77.18 99.17 88.70 0.13 2.01 16.05 E4 7.40 3.91 1089.39 14821.27 15.91 13.61 0.744 22.7 112.62 80.09 0.15 2.67 17.39 E6 5.76 6.32 2263.04 22082.51 24.35 9.76 0.133 34.59 124.09 68.97 0.12 2.01 16.30 4 FG A2 4.03 8.75 278.19 12043.07 12.32 43.29 0.109 49.24 138.69 132.68 0.15 2.26 15.19 A6 7.53 9.76 544.70 29984.83 30.53 55.05 0.074 42.55 86.47 111.78 0.13 2.00 15.75 B5 4.40 3.46 1722.24 16712.25 18.43 9.70 0.242 25.95 166.50 101.76 0.14 2.48 18.13 C8 3.00 6.20 3547.05 16317.52 19.86 4.60 0.062 53.89 120.58 101.22 0.13 2.43 18.08 E8 13.95 5.00 1414.51 22097.62 23.51 15.62 0.141 20.8 85.33 86.80 0.14 2.73 18.98
166
APPENDIX B TRFLP DATA
167 All identified bacteria for 0 FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism Name B7 D7 F2 ACETOBACTER spp. * ACETONEMA LONGUM STR. APO-1 DSM 6540 (T). ** ACHOLEPLASMA OCULI ISM 1499. ** ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). * ACIDOVORAX spp. ** AFIPIA FELIS. *** AGROMYCES MEDIOLANUS strains ** ALCALIGENES FAECALIS SUBSP. FAECALIS ATCC 8750 (T). * ALICYCLOBACILLUS SP. strains * ALLOIOCOCCUS OTITIS NCFB 2890 (T). * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. *** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). ** ANAEROPLASMA spp. * AQUASPIRILLUM spp. ** ARTHROBACTER SP. STR. RC100. * ARTHROBACTER SP. STR. RC100. ** BACILLUS spp. *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA023). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA067). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). *** BACTEROIDES UREOLYTICUS ATCC 33387 (T). ** BDELLOVIBRIO STOLPII STR. UKI2 ATCC 27052 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). ** BETA-PROTEOBACTERIUM 16S RIBOSOMAL RNA. * BIFIDOBACTERIUM spp. ** BORDETELLA AVIUM ATCC 35086 (T). * BREVIBACILLUS spp. *** BREVUNDIMONAS spp. * BURKHOLDERIA spp. *** CALDOTOGA FONTANA STR. B4. *** CAMPYLOBACTER spp. ** CARYOPHANON LATUM strains * CAULOBACTER spp. * CELLULOMONAS spp. *** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). *** CHLAMYDIA spp. ** CHLOROBIUM LIMICOLA strains ** CITROBACTER spp. ** CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. ** CLONE 1_60. * CLONE 113. * CLONE 141. * CLONE 167. * CLONE 22. * CLONE 282. * CLONE 330. * CLONE 348. * CLONE 368. * CLONE A12. * CLONE ADRIATIC76. *** CLONE ADRIATIC91. * CLONE ADRIATICR16. * CLONE ASB009. **
168 OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 CLONE ASB016. ** CLONE ASB017. * CLONE ASB029. * CLONE ASB031. * CLONE BH017. * CLONE BPC043. *** CLONE BPC060. *** CLONE BPC090. ** CLONE BPC094. *** CLONE BPC102. * CLONE C028. * CLONE CLONE DA115. *** CLONE CN1. ** CLONE CN3. ** CLONE DA011. *** CLONE DA015. *** CLONE DA023. ** CLONE DA026. *** CLONE DA032. *** CLONE DA036. *** CLONE DA066. ** CLONE DA067. * CLONE DA114. ** CLONE DA134. *** CLONE DA154. *** CLONE ENV.OPS 8. * CLONE FB14. ** CLONE FB15. *** CLONE FB16. *** CLONE H1.2.F. * CLONE H1.43.F. *** CLONE JW29. *** CLONE JW6. ** CLONE LBS10. * CLONE LBS25. ** CLONE LBS3. ** CLONE LBS9. * CLONE LRE13. ** CLONE LRE17. * CLONE LRE18. *** CLONE LRE25. ** CLONE LRE9. *** CLONE LRS15. * CLONE LRS4. * CLONE OCS14. ** CLONE OCS146. ** CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE ODPB-B7. * CLONE OM180. ** CLONE OM93. * CLONE RIZ1015. *** CLONE RIZ103. *** CLONE RIZ1074. * CLONE RIZ1078. *** CLONE RIZ1083. *** CLONE RIZ6I. * CLONE S023. * CLONE S027. * CLONE S125. ** 169 OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 CLONE SAR 406. ** CLONE SAR248. * CLONE SAR324. * CLONE SJA-102. * CLONE SJA-121. *** CLONE SJA-168. * CLONE SJA-171. * CLONE SJA-176. *** CLONE SJA-181. *** CLONE SJA-182. * CLONE SJA-186. ** CLONE SJA-47. ** CLONE SJA-62. ** CLONE SJA-68. * CLONE SJA-87. *** CLONE SJA-9. ** CLONE SVA0010A. * CLONE SVA0071. *** CLONE SVA0113. * CLONE SVA0318. * CLONE SVA0631. * CLONE SVA0679. ** CLONE SVA0853. * CLONE SVA0864. *** CLONE SVA1037. * CLONE SY1-44. * CLONE T10. * CLONE T19. * CLONE T20. ** CLONE T22. ** CLONE T25. * CLONE T3. ** CLONE T33. ** CLONE T35. * CLONE T41. * CLONE T43. * CLONE T65. ** CLONE T67. ** CLONE T70. * CLONE T73. * CLONE T79. * CLONE T90. *** CLONE T96. * CLONE T98. *** CLONE TBS13. * CLONE TBS29. * CLONE TBS3. * CLONE THRIPS6.12. ** CLONE TRE13. ** CLONE TRE19. ** CLONE TRE3. ** CLONE TRS11. ** CLONE TRS2. * CLONE TRS24. * CLONE TRS28. * CLONE TRS7. ** CLONE UC25. * CLONE UC32F. * CLONE UC37F. * CLONE UC44. * 170
OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 CLONE UC47. * CLONE UC52. * CLONE VC2.1 BAC31. * CLONE VC2.1 BAC4. * CLONE WR105. ** CLONE WR108. ** CLONE WR109. * CLONE WR1105. ** CLONE WR1111. * CLONE WR1112. ** CLONE WR1115. * CLONE WR1117. * CLONE WR1119. * CLONE WR1123. *** CLONE WR1124. * CLONE WR1132. ** CLONE WR1134. * CLONE WR114. ** CLONE WR1140. *** CLONE WR1141. ** CLONE WR1145. * CLONE WR119. * CLONE WR128. ** CLONE WR134. ** CLONE WR137. ** CLONE WR144. ** CLONE WR148. ** CLONE WR151. *** CLONE WR153. *** CLONE WR156. * CLONE WR161. * CLONE WR168. * CLONE WR170. ** CLONE WR171. ** CLONE WR177. *** CLONE WR182. * CLONE WR184. ** CLONE WR191. ** CLONE WR193. ** CLONE WR197. * CLONE WR198. ** CLONE WR199. * CLONE WS53. ** CLONE WS53. * CLONE WS54. * CLOSTRIDIUM spp. *** COMAMONAS spp. ** CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). *** CYTOPHAGA SP. strains *** DERMABACTER HOMINIS NCFB 2769 (T). ** DESULFOBACTERIUM spp. ** DESULFOBULBUS BG25 STR. BG25. * DESULFOVIBRIO spp. ** DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). ** DICHELOBACTER NODOSUS STR. 198A ATCC 27521. * EHRLICHIA BOVIS. *** ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. ** ENTEROBACTER spp. ** ERWINIA spp. ** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). **
171 OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 ESCHERICHIA COLI strains *** ESCHERICHIA HERMANNII. ** EUBACTERIUM spp. ** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FIBROBACTER spp. * FLEXIBACTER TRACTUOSUS STR. LEWIS BA-3 ATCC 23168 (T). * FRANKIA SP. strains * FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" ** GARDNERELLA VAGINALIS ATCC 14018 (T). ** GLUCONACETOBACTER spp. * GRAM NEG" *** HAEMOPHILUS INFLUENZAE strains *** HAFNIA ALVEI ATCC 13337 (T). ** HERBASPIRILLUM G8A1 STR. G8A1. * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). ** HYDROGENOPHAGA spp. ** IFO 15614. ** IFO 15706. ** IFO 15777. * KINEOSPORIA spp. * KITASATOSPORA spp. ** KITASATOSPORIA spp. *** KURTHIA ZOPFII STR. F64/100; K5 ATCC 33403 (T). * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). ** LEPTOTHRIX spp. *** LEUCOBACTER KOMAGATAE. ** LISTONELLA ANGUILLARUM strains ** MAGNETOBACTERIUM BAVARICUM. ** MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" ** MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACILLUS FLAGELLATUM STR. KT1. *** METHYLOBACTERIUM spp. *** METHYLOCYSTIS spp. ** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. *** MICROBACTERIUM spp. *** MICROBISPORA BISPORA PARTIAL RIBOSOMAL RNA OPERON A,B,C,D INCLUDING 16S *** MICROCOCCUS spp. *** MICROCYSTIS spp. ** MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOORELLA THERMOACETICA ATCC 39073. ** MOUNT COOT-THA REGION (BRISBANE" *** MYCOBACTERIUM spp. *** MYCOPLASMA spp. ** MYXOCOCCUS CORALLOIDES STR. M2 ATCC 25202 (T). * NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS strains *** NOSTOC MUSCORUM PCC 7120. * OERSKOVIA XANTHINEOLYTICA NCIMB 11025. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). *** PAENIBACILLUS spp. *** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. ** PARACRAUROCOCCUS RUBER strains * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). ** PHOTOBACTERIUM spp. ** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. *
172 OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 PIRELLULA UNCULTURED PIRELLULA CLONE 6N14. * PLANOCOCCUS spp. ** PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST ** PREVOTELLA BUCCALIS ATCC 35310 (T). * PROTEUS VULGARIS IFAM 1731. ** PSEUDOMONAS spp. *** PSYCHROSERPENS BURTONENSIS ACAM strains * QUINELLA OVALIS. * RALSTONIA spp. ** RHODOBACTER spp. *** RHODOCOCCUS COPROPHILUS JCM 3200 (T). * RHODOCYCLUS PURPUREUS STR. 6770 DSM 168 (T). * RHODOFERAX ANTARCTICUS STR. ANT.BR. ** RHODOPILA GLOBIFORMIS DNA FOR 16S RRNA. * ROSEOBACTER MED6 STR. MED6. *** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). ** SALMONELLA spp. *** SEQUENCE 1 FROM PATENT US 5508193. ** SHEWANELLA spp. ** SHIGELLA spp. ** SPHAEROTILUS IF4, IF5 STR. IF4,IF5. *** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). * SPHINGOMONAS spp. * SPIRILLUM VOLUTANS ATCC 19554 (T). *** STAPHYLOCOCCUS spp. ** STENOTROPHOMONAS spp. ** STR. 400M ATT. * STR. ACE. * STR. AS2965. *** STR. AS2985. *** STR. AS2987. ** STR. AS2989. * STR. AS3080. *** STR. AS3088. *** STR. AS3090. *** STR. AS3142. *** STR. AS3380. *** STR. AS3641. *** STR. B1. ** STR. B100. * STR. B-3060. * STR. BD1-1. *** STR. BD1-33. * STR. BD2-3. ** STR. BD3-7. ** STR. BD4-10. ** STR. BD4-12. ** STR. BD5-11. ** STR. BD5-12. ** STR. DHA-71. * STR. ES-1. *** STR. FROM LAKE GOSSENKOELLESEE. *** STR. HNSM13. ** STR. HNSS13. ** STR. HW1. ** STR. IC025. ** STR. J 195. ** STR. JL 134. ** STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. ** 173 OFG forward primer continued: mesocosm # Organism Name B7 D7 F2 STR. JTB131. * STR. JTB146. * STR. JTB148. * STR. JTB36. ** STR. KN4. ** STR. LSV21. ** STR. N4-7. ** STR. NKB11. * STR. NKB13. * STR. NKB14. ** STR. NKB15. ** STR. NKB16. ** STR. NKB18. * STR. NRRLB-14851. * STR. NRRLB-14911. ** STR. P211. * STR. PCE-FF ATCC 35879. *** STR. PENDANT. * STR. RA1. ** STR. SR 119. ** STR. SUR ATT. * STR. T25. * STR. T3. ** STR. T41. * STR. UNIDENTIFIED BACTERIUM D. * STR. UW 103/A31. * STR. WSA. * STREPTOMYCES spp. *** SULFOBACILLUS spp. ** SULFUROSPIRILLUM BARNESII strains ** SUTTONELLA INDOLOGENES ATCC 25869 (T). * SYMBIONT OF ALVINELLA POMPEJANA. ** SYMBIONT OF CRITHIDIA SP. *** SYMBIONT OF INTRACELLULAR ILEAL SYMBIONT OF MESOCRICETUS AURATUS. * SYMBIONT OF SUS SCROFA. * SYNECHOCOCCUS SP. PCC 6301. *** SYNTROPHOBACTER WOLINII. ** TELLURIA CHITINOLYTICA STR. 20M ACM 3522 (T). * THERMOACTINOMYCES CANDIDUS. * THERMOBACILLUS XYLANOLYTICUS STR. XE. * THERMOBISPORA BISPORA strains *** THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. ** THERMOMICROBIUM ROSEUM ATCC 27502 (T). * THERMUS spp. * TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). ** UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S023 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" ** UNCULTURED EUBACTERIUM H1.2.F 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. *** UNIDENTIFIED BACTERIUM 16S RRNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM CLONE SAR248 16S RIB RNA GENE" * UNIDENTIFIED EUBACTERIUM CLONE SAR324 16S RIB RNA GENE" * UNNAMED ORGANISM. *** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. ** VIBRIO spp. ** XANTHOMONAS spp. * XYLELLA FASTIDIOSA strains *** XYLOPHILUS AMPELINUS ATCC 33914 (T). ** ZOOGLOEA SP. 16S RIBOSOMAL RNA GENE" ** 174 All identified bacteria for 0 FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism Name B7 D7 F2 ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). * * BACILLUS spp. *** BLASTOBACTER SP. STR. PC30.44. * BOSEA THIOOXIDANS STR. RPPL5-VS. ** BURKHOLDERIA EN-B3. *** CLONE 2951. ** CLONE BPC110. * CLONE EKHO-1. * CLONE ENV.OPS 12. ** CLONE GCA112. ** CLONE H1.43.F. ** CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE K20-75. ** CLONE KTK 14. * CLONE OPB11. ** CLONE OPB12. ** CLONE OPB34. ** CLONE OPB65. ** CLONE OPB9. ** CLONE RB29. * CLONE S027. * CLONE SCALE-6. * CLONE SJA-101. ** CLONE SJA-108. ** CLONE SJA-131. ** CLONE SJA-15. *** CLONE SJA-168. * CLONE SJA-170. * CLONE SJA-21. ** CLONE SJA-58. ** CLONE SJA-61. * CLONE T17. ** CLONE T78. ** CLONE TM6. * CLONE UC43F. *** CLONE UC51F. *** CLONE VADINCA02. ** CLONE WB004. ** CLONE WCHB1-05. * CLONE WCHB1-31. * CLONE WCHB1-57. ** CLONE WCHB1-62. ** CLONE WCHB1-64. * CLONE WCHB1-80. ** CYNOMORIUM COCCINEUM CHLOROPLAST 16S RIBOSOMAL RNA GENE" * DESULFORHOPALUS LSV20 STR. LSV20. * ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** EPERYTHROZOON SUIS strains * FERVIDOBACTERIUM spp. * HALOANAEROBACTER spp. * HALOANAEROBIUM PRAEVALENS ATCC 33744 (T). * HALOBACTEROIDES spp. * HILDENBRANDIA OCCIDENTALIS. * IFO 15702. * 175 All identified bacteria for tussock FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism name A1 C6 E5 ACETOBACTER spp. * ACETONEMA LONGUM STR. APO-1 DSM 6540 (T). * ACHOLEPLASMA OCULI ISM 1499. * ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). * ACIDOVORAX spp. *** AFIPIA FELIS. ** AGROMYCES MEDIOLANUS strains ** ALCALIGENES FAECALIS SUBSP. FAECALIS ATCC 8750 (T). * ALICYCLOBACILLUS SP. Strains * ALLOIOCOCCUS OTITIS NCFB 2890 (T). * AMARICOCCUS KAPLICENSIS strains * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. ** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). * ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). * ANGIOCOCCUS DISCIFORMIS ATCC 33172 (T). * AQUASPIRILLUM spp. *** ARCHANGIUM GEPHYRA ATCC 25201 (T). * ARTHROBACTER SP. STR. RC100. ** BACILLUS spp. ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA023). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA067). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA113). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). ** BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BDELLOVIBRIO STOLPII STR. UKI2 ATCC 27052 (T). * BETA-PROTEOBACTERIUM 16S RIBOSOMAL RNA. * BIFIDOBACTERIUM spp. * BREVIBACILLUS spp. ** BREVUNDIMONAS spp. * BURKHOLDERIA spp. ** CALDOTOGA FONTANA STR. B4. * CAMPYLOBACTER spp. * CARYOPHANON LATUM strains * CAULOBACTER spp. * CELLULOMONAS spp. ** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). ** CHLOROBIUM LIMICOLA strains * CITROBACTER spp. *** CLONE 1_60. * CLONE 113. * CLONE 141. * CLONE 22. * CLONE 282. * CLONE 330. * CLONE 348. * CLONE 368. * CLONE ADRIATIC76. ** CLONE ADRIATIC91. * CLONE ADRIATICR16. * CLONE ASB009. ** CLONE ASB016. ** 176 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 CLONE ASB029. * CLONE ASB031. * CLONE BH017. * CLONE BPC043. ** CLONE BPC060. ** CLONE BPC090. ** CLONE BPC094. ** CLONE BPC102. * CLONE C028. * CLONE CLONE DA115. ** CLONE CN1. *** CLONE CN3. *** CLONE DA011. ** CLONE DA015. ** CLONE DA023. ** CLONE DA026. ** CLONE DA032. ** CLONE DA036. ** CLONE DA038. * CLONE DA040. * CLONE DA057. * CLONE DA066. * CLONE DA067. * CLONE DA113. * CLONE DA116. * CLONE DA134. ** CLONE DA154. ** CLONE FB14. * CLONE FB15. *** CLONE FB16. *** CLONE H1.2.F. * CLONE H1.43.F. ** CLONE JW29. * CLONE JW6. * CLONE LBS10. * CLONE LBS25. * CLONE LBS3. * CLONE LBS6. * CLONE LBS9. * CLONE LRE13. ** CLONE LRE18. ** CLONE LRE22. * CLONE LRE25. * CLONE LRE9. *** CLONE LRS4. * CLONE OCS146. * CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE OM180. ** CLONE OM21. ** CLONE OM93. ** CLONE RIZ1015. ** CLONE RIZ103. ** CLONE RIZ1074. * CLONE RIZ1078. ** CLONE RIZ1079. * CLONE RIZ1081. * 177 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 CLONE RIZ1083. ** CLONE RIZ6I. * CLONE S125. ** CLONE SAR 406. * CLONE SJA-102. * CLONE SJA-121. ** CLONE SJA-162. * CLONE SJA-168. * CLONE SJA-176. ** CLONE SJA-181. ** CLONE SJA-186. ** CLONE SJA-47. * CLONE SJA-51. * CLONE SJA-62. *** CLONE SJA-87. ** CLONE SJA-9. ** CLONE SVA0010A. * CLONE SVA0071. *** CLONE SVA0113. * CLONE SVA0318. *** CLONE SVA0631. * CLONE SVA0679. ** CLONE SVA0864. *** CLONE SY1-44. * CLONE T19. * CLONE T20. *** CLONE T22. * CLONE T25. * CLONE T3. ** CLONE T33. *** CLONE T35. * CLONE T41. * CLONE T43. * CLONE T65. *** CLONE T67. ** CLONE T70. * CLONE T73. ** CLONE T79. ** CLONE T90. ** CLONE T96. * CLONE T98. *** CLONE TBS13. * CLONE TBS3. * CLONE THRIPS6.12. ** CLONE TRE13. ** CLONE TRE19. *** CLONE TRE3. * CLONE TRS11. ** CLONE TRS2. * CLONE TRS7. * CLONE UC43F. * CLONE UC52. ** CLONE WR105. * CLONE WR108. * CLONE WR1105. * CLONE WR1111. * CLONE WR1112. * 178 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 CLONE WR1119. * CLONE WR1123. *** CLONE WR1132. * CLONE WR114. * CLONE WR1140. *** CLONE WR1141. * CLONE WR119. * CLONE WR122. * CLONE WR128. * CLONE WR134. * CLONE WR137. * CLONE WR144. * CLONE WR148. * CLONE WR151. *** CLONE WR153. *** CLONE WR156. * CLONE WR159. * CLONE WR161. * CLONE WR170. * CLONE WR171. * CLONE WR173. * CLONE WR177. ** CLONE WR184. * CLONE WR191. * CLONE WR193. * CLONE WR197. * CLONE WR198. * CLONE WR199. * CLONE WS53. * CLOSTRIDIUM spp. ** COMAMONAS spp. *** CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). ** CYSTOBACTER spp. * CYTOPHAGA SP. strains * DELFTIA ACIDOVORANS STR. STANIER 14 ACM 489 (T). * DESULFOBACTERIUM spp. * DESULFOBULBUS spp. * DESULFOVIBRIO spp. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * EHRLICHIA BOVIS. ** ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. * ENTEROBACTER spp. *** ERWINIA spp. *** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). ** ESCHERICHIA COLI strains *** ESCHERICHIA HERMANNII. ** EUBACTERIUM LENTUM JCM 9979. * EUBACTERIUM XYLANOPHILUM ATCC 35991 (T). * EXIGUOBACTERIUM ACETYLICUM NCIMB 9889 (T). * FIBROBACTER spp. * FLECTOBACILLUS MAJOR ATCC 29496 (T). * FLEXIBACTER spp. * FRANKIA SP. Strains * FUSOBACTERIUM spp. ** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" ** GARDNERELLA VAGINALIS ATCC 14018 (T). ** GELIDIBACTER spp. * 179 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 GLUCONACETOBACTER spp. * GLUCONOBACTER spp. * GRAM NEG" ** HAEMOPHILUS INFLUENZAE strains *** HAFNIA ALVEI ATCC 13337 (T). *** HERBASPIRILLUM G8A1 STR. G8A1. * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). * HYDROGENOPHAGA spp. *** IFO 15614. * IFO 15706. * IFO 15777. * KINEOSPORIA spp. ** KITASATOSPORA spp. * KITASATOSPORIA spp. * KURTHIA ZOPFII strains * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). ** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). *** LEUCOBACTER spp. * LISTONELLA ANGUILLARUM strains *** MATSUEBACTER CHITOSANOTABIDUS. ** MELITTANGIUM spp. * METHYLOBACILLUS FLAGELLATUM STR. KT1. *** METHYLOBACTERIUM spp. ** METHYLOCYSTIS spp. ** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. ** MICROBACTERIUM spp. ** MICROBISPORA BISPORA strains ** MICROCOCCUS spp. ** MICROCYSTIS spp. *** MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOORELLA THERMOACETICA ATCC 39073. ** MOUNT COOT-THA REGION (BRISBANE" *** MYCOBACTERIUM spp. ** MYCOPLASMA spp. ** MYXOCOCCUS spp. * NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS strains *** OCHROSPHAERA SP. STR. 181 (HAPTOPHYTE) -- CHLOROPLAST. * OERSKOVIA XANTHINEOLYTICA NCIMB 11025. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). ** PAENIBACILLUS spp. ** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. ** PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PEPTOSTREPTOCOCCUS spp. * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PHOTOBACTERIUM spp. *** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. ** PLANOCOCCUS spp. * PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST ** PROTEUS VULGARIS IFAM 1731. *** PSEUDOMONAS spp. *** PSYCHROSERPENS BURTONENSIS ACAM strains * RALSTONIA spp. * RHODOBACTER spp. ** RHODOCYCLUS PURPUREUS STR. 6770 DSM 168 (T). * RHODOFERAX ANTARCTICUS STR. ANT.BR. ** 180 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 RHODOPSEUDOMONAS SP. strains * RHODOTHALASSIUM SALEXIGENS ATCC 35888 (T). * ROSEOBACTER spp. ** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). * S.TYPHI GENE FOR 16S RIBOSOMAL RNA. * S.TYPHIMURIUM GENE FOR 16S RIBOSOMAL RNA. * SACCHAROCOCCUS THERMOPHILUS STR. 657 ATCC 43125 (T). * SALMONELLA spp. *** SEQUENCE 1 FROM PATENT US 5508193. ** SHEWANELLA SP. STR. 16.K. * SHIGELLA spp. *** SPHAEROTILUS IF4,IF5 STR. IF4,IF5. *** SPHINGOMONAS spp. * SPIRILLUM spp. *** SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). * STAPHYLOCOCCUS spp. ** STENOTROPHOMONAS spp. ** STIGMATELLA AURANTIACA ATCC 25190 (T). * STR. 400M ATT. * STR. ACE. ** STR. ALV. * STR. AS2965. ** STR. AS2985. ** STR. AS2987. * STR. AS2988. * STR. AS2989. * STR. AS3080. ** STR. AS3088. ** STR. AS3090. ** STR. AS3142. ** STR. AS3187. * STR. AS3380. ** STR. AS3641. ** STR. B1. ** STR. B100. ** STR. B-3060. * STR. B5-6. * STR. BD1-1. ** STR. BD2-3. * STR. BD3-7. * STR. BD4-10. * STR. BD5-11. *** STR. BD5-12. * STR. ES-1. ** STR. FROM LAKE GOSSENKOELLESEE. *** STR. HNSM13. * STR. HNSS13. * STR. HRV10. * STR. HW1. ** STR. J 195. * STR. JL 134. * STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. * STR. JTB146. * STR. JTB148. *** STR. JTB36. * STR. KN4. *** 181 Tussock forward primer continued: mesocosm # organism name A1 C6 E5 STR. LSV21. * STR. N4-7. ** STR. NKB11. * STR. NKB13. * STR. NKB14. * STR. NKB15. * STR. NKB16. * STR. NRRLB-14911. ** STR. P211. * STR. PCE-FF ATCC 35879. *** STR. PENDANT. ** STR. RA1. *** STR. RJ. * STR. SCB42. * STR. SUR ATT. * STR. T25. * STR. T3. ** STR. T41. * STR. UNIDENTIFIED BACTERIUM D. * STR. UW 103/A31. ** STREPTOMYCES spp. ** SULFOBACILLUS spp. *** SULFUROSPIRILLUM BARNESII strains * SYMBIONT OF ALVINELLA POMPEJANA. * SYMBIONT OF CRITHIDIA SP. *** SYMBIONT OF INTRACELLULAR ILEAL SYMBIONT OF MESOCRICETUS AURATUS. * SYMBIONT OF SUS SCROFA. * SYNECHOCOCCUS SP. PCC 6301. *** SYNTROPHOBACTER WOLINII. * TELLURIA CHITINOLYTICA STR. 20M ACM 3522 (T). * THERMOACTINOMYCES CANDIDUS. * THERMOBACILLUS XYLANOLYTICUS STR. XE. * THERMOBISPORA spp. ** THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. ** TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). *** UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" ** UNCULTURED EUBACTERIUM H1.2.F 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED ALPHA PROTEOBACTERIUM 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. *** UNNAMED ORGANISM. ** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. *** VIBRIO spp. *** VOGESELLA INDIGOFERA ATCC 19706 (T). * XANTHOMONAS spp. ** XYLELLA FASTIDIOSA strains *** XYLOPHILUS AMPELINUS ATCC 33914 (T). *** ZOOGLOEA strains ** 182 All identified bacteria for tussock FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # organism name A1 C6 E5 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" ** ACETOHALOBIUM spp. *** BACILLUS spp. *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). * BLASTOBACTER SP. STR. PC30.44. * BOSEA THIOOXIDANS STR. RPPL5-VS. * BOTHROMESOSTOMA SP. * BURKHOLDERIA EN-B3. *** CHLOROBIUM spp. * CLONE 1404-40. * CLONE 2951. ** CLONE 4953. * CLONE 52. * CLONE BPC110. * CLONE CLONE DA115. * CLONE ENV.OPS 12. *** CLONE GCA112. ** CLONE H1.43.F. *** CLONE HSTPL11. * CLONE HSTPL20. * CLONE HSTPL53. * CLONE HSTPL65. * CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE K20-75. ** CLONE M37. * CLONE MUG6. ** CLONE OPB11. *** CLONE OPB12. *** CLONE OPB34. *** CLONE OPB65. *** CLONE OPB9. *** CLONE RB29. * CLONE RB33. * CLONE S027. * CLONE SCALE-6. * CLONE SJA-101. ** CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. * CLONE SJA-21. ** CLONE SJA-58. *** CLONE SJA-68. * CLONE T17. * CLONE T78. *** CLONE TM6. * CLONE UC43F. ** CLONE UC51F. ** CLONE VADINCA02. *** CLONE WB004. * CLONE WCHB1-57. *** CLONE WCHB1-62. *** CLONE WCHB1-80. *** CYMATOSIRA BELGICA (CENTRIC DIATOM). * 183 Tussock reverse primer continued: mesocosm # organism name A1 C6 E5 DESULFORHOPALUS LSV20 STR. LSV20. * ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** EXIGUOBACTERIUM SP. * FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). ** G.OBSCURIGLOBUS 16S RRNA GENE. * GEMMATA OBSCURIGLOBUS strains * GEOBACTER ""HYDROGENOPHILUS""."" * HALOANAEROBACTER spp. ** HALOBACTEROIDES spp. ** HILDENBRANDIA OCCIDENTALIS. * HYPHOMICROBIUM M3 STR. M3 ATCC 202122. * KOCKOVAELLA THAILANDICA. * LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LENTZEA KOREENSIS STR. LM 121T (=IMSNU 50711T). * LEPTONEMA ILLINI STR. 3055. *** MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). ** MOUNT COOT-THA REGION (BRISBANE" * MYCOPLASMA spp. * NITROSOSPIRA SP. STR. F3. * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. ** PARACOCCUS SP. STR. B8B2. * PLANCTOMYCES spp. * RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** SARGASSO SEA" ** SMITTIUM DIPTERORUM. * SPHINGOMONAS UG30 STR. UG30. * SPIROCHAETA spp. * SPIROPLASMA spp. * SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 13-2. * STR. 292. * STR. 394. ** STR. 63.G. * STR. BD3-16. *** STR. BD3-7. *** STR. ML-126. * STR. NKB17. * STR. RM1. * STR. RM17. * STR. SP5-17. * STR. SUR ATT. * SUTTERELLA spp. *** SYNTROPHOBACTER SP. STR. TSUA1. * SYNTROPHUS SP. * TREPONEMA UNCULTURED TREPONEMA CLONE RFS64. * UNCLASSIFIED ORGANISM (ACIDOBACTERIUM CAPSULATUM PHYLUM) 16S RRNA * UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM RB33 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED GREEN NON-SULFUR BACTERIUM strains *** UNNAMED ORGANISM. *** VIBRIO 2P44 strains **
184 All identified bacteria for reed FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) me socosm # Organism Name C3 E2 ACETOBACTER ACETI NCIMB 8621 (T). * ACHOLEPLASMA OCULI ISM 1499. * ACIDOVORAX spp. * AFIPIA spp. ** AGROMYCES MEDIOLANUS JCM 1376. * ALICYCLOBACILLUS SP. strains ** ALLOIOCOCCUS OTITIS NCFB 2890 (T). * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. ** ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). * AQUASPIRILLUM spp. * ARTHROBACTER SP. STR. RC100. * BACILLUS spp. ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA067). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA113). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). * BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). ** BETA-PROTEOBACTERIUM 16S RIBOSOMAL RNA. ** BIFIDOBACTERIUM THERMOPHILUM ATCC 25525 (T). * BREVIBACILLUS spp. ** BREVUNDIMONAS DIMINUTA ATCC 11568 (T). * BURKHOLDERIA spp. ** CAMPYLOBACTER spp. * CARYOPHANON spp. * CAULOBACTER spp. * CELLULOMONAS FLAVIGENA STR. GG. * CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). ** CHLAMYDIA spp. * CHLOROBIUM LIMICOLA strains * CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. * CLONE A21. * CLONE ADRIATIC76. ** CLONE ADRIATIC91. * CLONE ASB009. * CLONE ASB016. * CLONE ASB029. ** CLONE ASB031. ** CLONE BH017. * CLONE BPC043. * CLONE BPC060. * CLONE BPC090. * CLONE BPC094. * CLONE CLONE DA115. * CLONE DA011. ** CLONE DA015. ** CLONE DA026. * CLONE DA032. ** CLONE DA036. ** CLONE DA038. * CLONE DA040. * CLONE DA057. **
185 Reed forward primer continued: mesocosm # Organism Name C3 E2 CLONE DA066. * CLONE DA067. ** CLONE DA113. * CLONE DA114. ** CLONE DA116. * CLONE DA134. ** CLONE DA154. ** CLONE ENV.OPS 12. * CLONE FB14. * CLONE FB15. * CLONE FB16. * CLONE H1.43.F. ** CLONE JW23. * CLONE JW29. ** CLONE JW6. ** CLONE LBS10. * CLONE LBS25. * CLONE LBS3. * CLONE LBS9. * CLONE LRE13. * CLONE LRE18. * CLONE LRE25. * CLONE LRE9. * CLONE OCS146. * CLONE OM180. * CLONE RIZ1015. ** CLONE RIZ103. ** CLONE RIZ1078. ** CLONE RIZ1081. * CLONE RIZ1083. ** CLONE S023. * CLONE S027. * CLONE SAR248. * CLONE SAR324. * CLONE SJA-102. * CLONE SJA-121. * CLONE SJA-171. * CLONE SJA-181. ** CLONE SJA-186. ** CLONE SJA-47. ** CLONE SJA-62. * CLONE SJA-68. * CLONE SJA-87. ** CLONE SJA-9. * CLONE SVA0071. * CLONE SVA0318. * CLONE SVA0679. * CLONE SVA0864. * CLONE T10. * CLONE T19. ** CLONE T20. * CLONE T22. * CLONE T25. ** CLONE T3. * CLONE T33. * CLONE T35. ** CLONE T41. **
186 Reed forward primer continued: mesocosm # Organism Name C3 E2 CLONE T47. * CLONE T65. * CLONE T67. * CLONE T70. ** CLONE T73. * CLONE T79. * CLONE T90. ** CLONE T96. ** CLONE T98. ** CLONE TBS1. * CLONE TBS29. * CLONE TBS3. * CLONE TRE19. * CLONE TRE3. ** CLONE TRS2. * CLONE TRS28. * CLONE TRS7. ** CLONE UC25. * CLONE UC32F. * CLONE UC37F. * CLONE UC44. * CLONE UC47. * CLONE UC52. * CLONE WR105. ** CLONE WR108. ** CLONE WR1105. ** CLONE WR1112. ** CLONE WR1119. * CLONE WR1123. ** CLONE WR1124. * CLONE WR1132. ** CLONE WR1134. * CLONE WR114. ** CLONE WR1140. ** CLONE WR1141. ** CLONE WR128. ** CLONE WR134. ** CLONE WR137. ** CLONE WR144. ** CLONE WR148. ** CLONE WR151. ** CLONE WR153. ** CLONE WR159. * CLONE WR168. * CLONE WR170. ** CLONE WR171. ** CLONE WR173. * CLONE WR177. ** CLONE WR184. ** CLONE WR191. ** CLONE WR193. ** CLONE WR198. ** CLOSTRIDIUM spp. ** COMAMONAS spp. * CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). ** CYTOPHAGA SP. strains * DELFTIA ACIDOVORANS STR. STANIER 14 ACM 489 (T). * 187 Reed forward primer continued: mesocosm # Organism Name C3 E2 DESULFOBACTERIUM spp. * DESULFOVIBRIO spp. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * DICHELOBACTER NODOSUS STR. 198A ATCC 27521. * EHRLICHIA BOVIS. * ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. ** ERWINIA spp. * ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). * ESCHERICHIA COLI strains * EUBACTERIUM LENTUM JCM 9979. * FIBROBACTER spp. ** FRANKIA SP. strains * FUSOBACTERIUM spp. * GARDNERELLA VAGINALIS ATCC 14018 (T). * GLUCONACETOBACTER DIAZOTROPHICUS ATCC 49037 (T). * GLUCONOBACTER spp. * GRAM NEG" * HAEMOPHILUS INFLUENZAE strains * HALOTHECE 'MPI 96P605' STR. MPI 96P605. * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). ** HYDROGENOPHAGA spp. * KINEOSPORIA spp. ** KITASATOSPORA spp. * KITASATOSPORIA spp. * KURTHIA ZOPFII STR. F64/100; K5 ATCC 33403 (T). * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). ** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). ** LISTONELLA ANGUILLARUM HI 11446. * MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. ** METHYLOBACILLUS FLAGELLATUM STR. KT1. * METHYLOBACTERIUM spp. * METHYLOCYSTIS spp. ** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). ** METHYLOSINUS spp. ** MICROBACTERIUM spp. ** MICROBISPORA BISPORA PARTIAL RIBOSOMAL RNA OPERON A,B,C,D INCLUDING 16S * MICROCOCCUS spp. ** MICROCYSTIS spp. ** MOORELLA spp. ** MOUNT COOT-THA REGION (BRISBANE" ** MYCOBACTERIUM LEPRAE STR. ARMADILLO GROWN. * MYCOPLASMA spp. ** MYXOCOCCUS CORALLOIDES STR. M2 ATCC 25202 (T). * NITROSOMONAS EUROPAEA STR. M103. ** NITROSOSPIRA MULTIFORMIS. Strains ** NODULARIA BCNOD9427 STR. BCNOD9427. * NOSTOC MUSCORUM PCC 7120. * OERSKOVIA XANTHINEOLYTICA NCIMB 11025. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). ** PAENIBACILLUS spp. ** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PLANOCOCCUS spp. ** PSEUDOMONAS spp. * QUINELLA OVALIS. *
188 Reed forward primer continued: mesocosm # Organism Name C3 E2 RALSTONIA spp. ** RHODOBACTER spp. ** RHODOFERAX ANTARCTICUS STR. ANT.BR. * ROSEOBACTER MED6 STR. MED6. * RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). ** SACCHAROCOCCUS THERMOPHILUS STR. 657 ATCC 43125 (T). * SALMONELLA MATOPENI SM1 16S RIBOSOMAL RNA GENE" * SPHAEROTILUS IF4,IF5 STR. IF4, IF5. * SPIRILLUM VOLUTANS ATCC 19554 (T). ** STAPHYLOCOCCUS spp. * STENOTROPHOMONAS MALTOPHILIA ATCC 13637 (T). * STR. 400M ATT. * STR. ACE. * STR. ALV. * STR. AS2965. * STR. AS2985. * STR. AS2987. ** STR. AS2988. ** STR. AS2989. * STR. AS3080. * STR. AS3088. * STR. AS3090. * STR. AS3142. * STR. AS3187. ** STR. AS3380. * STR. AS3641. * STR. B1. * STR. BD1-1. * STR. BD2-3. * STR. BD3-7. * STR. BD4-10. * STR. BD5-11. * STR. BD5-12. * STR. ES-1. * STR. FROM LAKE GOSSENKOELLESEE. * STR. HNSM13. ** STR. HNSS13. ** STR. HW1. * STR. IC025. * STR. J 195. * STR. JL 134. * STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. * STR. JTB131. * STR. JTB148. * STR. JTB36. * STR. LSV21. * STR. NKB14. * STR. NKB15. * STR. NKB16. * STR. NRRLB-14851. * STR. NRRLB-14911. * STR. P211. ** STR. PCE-FF ATCC 35879. * STR. PENDANT. * STR. RA1. * STR. SUR ATT. * 189 Reed forward primer continued: mesocosm # Organism Name C3 E2 STR. T25. ** STR. T3. * STR. T41. ** STR. UNIDENTIFIED BACTERIUM D. * STR. WSA. * STREPTOMYCES spp. ** SULFOBACILLUS THERMOSULFIDOOXIDANS strains ** SULFUROSPIRILLUM BARNESII strains * SUTTONELLA INDOLOGENES ATCC 25869 (T). * SYMBIONT OF ALVINELLA POMPEJANA. * SYMBIONT OF CRITHIDIA SP. ** SYMBIONT OF INTRACELLULAR ILEAL SYMBIONT OF MESOCRICETUS AURATUS. * SYMBIONT OF SUS SCROFA. * SYNECHOCOCCUS SP. PCC 6301. * SYNTROPHOBACTER WOLINII. * THERMOBACILLUS XYLANOLYTICUS STR. XE. * THERMOBISPORA BISPORA STR. R51 ATCC 19993 (T) [GENE=RRNA]. * THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. * THERMOMICROBIUM ROSEUM ATCC 27502 (T). * THERMUS spp. ** TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). * UNCULTIVATED SOIL BACTERIUM CLONE S023 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED BACTERIUM 16S RRNA GENE" ** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. ** UNIDENTIFIED EUBACTERIUM CLONE SAR248 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM CLONE SAR324 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUKARYOTE OM164 16S RIBOSOMAL RNA GENE" * UNNAMED ORGANISM. ** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. * VIBRIO spp. * VOGESELLA INDIGOFERA ATCC 19706 (T). * XYLELLA FASTIDIOSA strains * XYLOPHILUS AMPELINUS ATCC 33914 (T). *
190 All identified bacteria for reed FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism Name C3 E2 ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). ** BACILLUS VORTEX. ** BLASTOBACTER SP. STR. PC30.44. ** BOSEA THIOOXIDANS STR. RPPL5-VS. ** BURKHOLDERIA EN-B3. ** CLONE 1404-40. ** CLONE 52. ** CLONE H1.43.F. ** CLONE HSTPL69. ** CLONE K20-75. ** CLONE M37. ** CLONE OPB11. ** CLONE OPB12. ** CLONE SCALE-6. ** CLONE SJA-131. ** CLONE T78. ** CLONE UC43F. ** CLONE UC51F. ** CLONE VADINCA02. ** CLONE WCHB1-57. ** ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). ** GEMMATA OBSCURIGLOBUS strains ** LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). ** LEPTONEMA ILLINI STR. 3055. ** MOUNT COOT-THA REGION (BRISBANE" ** MYCOPLASMA spp. ** PLANCTOMYCES spp. ** RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). ** SARGASSO SEA" ** SPIROPLASMA spp. ** SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). ** STR. 292. ** STR. BD3-7. ** STR. RM1. ** STR. RM17. ** SUTTERELLA WADSWORTHENSIS strains ** UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. ** UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED GREEN NON-SULFUR BACTERIUM OPB12 16S RIBOSOMAL RNA **
191 All identified bacteria for facultative annual FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Me socosm # Organism Name A3 B1 C1 ACETITOMACULUM RUMINIS STR. 139B ATCC 43876 (T). * ACETOBACTER spp. *** ACHOLEPLASMA OCULI ISM 1499. *** ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). * ACIDOVORAX spp. ** AFIPIA spp. *** AGROMYCES MEDIOLANUS spp. *** ALICYCLOBACILLUS SP. strains * ALLOIOCOCCUS OTITIS NCFB 2890 (T). ** AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. *** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). *** ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). * AQUASPIRILLUM spp. ** ARTHROBACTER SP. STR. RC100. *** BACILLUS spp. *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA067). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA113). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). ** BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). ** BETA-PROTEOBACTERIUM 16S RIBOSOMAL RNA. ** BIFIDOBACTERIUM spp. *** BREVIBACILLUS spp. *** BREVUNDIMONAS spp. *** BURKHOLDERIA spp.. *** C.LIMICOLA 16S RRNA GENE" * CALDOTOGA FONTANA STR. B4. * CAMPYLOBACTER spp. * CARYOPHANON LATUM subspp. * CAULOBACTER spp. *** CELLULOMONAS spp. *** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). *** CHLAMYDIA spp. * CHLOROBIUM LIMICOLA DSM 245 (T). * CITROBACTER spp. ** CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. *** CLONE 1_60. * CLONE 113. * CLONE 141. * CLONE 167. * CLONE 22. * CLONE 282. * CLONE 2C83. * CLONE 330. * CLONE 348. * CLONE 368. * CLONE A54. * CLONE ADRIATIC76. *** CLONE ADRIATIC91. * CLONE ADRIATICR16. * CLONE ASB009. ** 192 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 CLONE ASB016. ** CLONE ASB029. *** CLONE ASB031. *** CLONE BH017. * CLONE BPC043. ** CLONE BPC060. ** CLONE BPC090. ** CLONE BPC094. ** CLONE BPC102. *** CLONE CLONE DA115. *** CLONE CN1. *** CLONE CN3. *** CLONE DA011. *** CLONE DA015. *** CLONE DA026. ** CLONE DA032. *** CLONE DA036. *** CLONE DA038. * CLONE DA040. * CLONE DA057. ** CLONE DA066. ** CLONE DA067. *** CLONE DA113. * CLONE DA114. *** CLONE DA116. * CLONE DA134. *** CLONE DA154. *** CLONE FB14. ** CLONE FB15. ** CLONE FB16. ** CLONE H1.43.F. *** CLONE JW23. ** CLONE JW25. * CLONE JW28. * CLONE JW29. ** CLONE JW6. ** CLONE LBS25. * CLONE LBS3. ** CLONE LRE13. * CLONE LRE18. ** CLONE LRE25. *** CLONE LRE9. *** CLONE LRS4. * CLONE OCS14. * CLONE OCS146. ** CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE OM180. * CLONE OM21. ** CLONE OM93. ** CLONE RIZ1015. *** CLONE RIZ103. *** CLONE RIZ1074. ** CLONE RIZ1078. *** CLONE RIZ1081. ** CLONE RIZ1083. *** CLONE RIZ6I. *
193 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 CLONE SAR 406. ** CLONE SAR248. * CLONE SAR324. * CLONE SJA-102. ** CLONE SJA-111. * CLONE SJA-121. *** CLONE SJA-168. *** CLONE SJA-176. ** CLONE SJA-181. *** CLONE SJA-186. ** CLONE SJA-47. *** CLONE SJA-62. ** CLONE SJA-63. * CLONE SJA-68. ** CLONE SJA-87. *** CLONE SJA-9. *** CLONE SVA0010A. * CLONE SVA0071. *** CLONE SVA0091. * CLONE SVA0113. * CLONE SVA0631. * CLONE SVA0679. * CLONE SVA0725. * CLONE SVA0853. * CLONE SVA0864. *** CLONE SVA1037. * CLONE SY1-44. ** CLONE T10. *** CLONE T19. ** CLONE T20. ** CLONE T22. * CLONE T25. ** CLONE T3. * CLONE T33. ** CLONE T35. ** CLONE T41. ** CLONE T43. * CLONE T47. * CLONE T65. ** CLONE T67. * CLONE T70. ** CLONE T73. * CLONE T79. * CLONE T90. ** CLONE T96. ** CLONE T98. *** CLONE TBS1. *** CLONE TBS13. * CLONE TBS29. * CLONE TBS3. ** CLONE THRIPS6.12. *** CLONE TRE13. *** CLONE TRE19. ** CLONE TRE3. *** CLONE TRS11. *** CLONE TRS2. * CLONE TRS7. *** 194 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 CLONE TRS9. * CLONE UC32F. * CLONE WR105. *** CLONE WR108. *** CLONE WR109. * CLONE WR1105. *** CLONE WR1112. *** CLONE WR1117. * CLONE WR1119. *** CLONE WR1123. *** CLONE WR1124. ** CLONE WR1132. *** CLONE WR1134. ** CLONE WR114. *** CLONE WR1140. *** CLONE WR1141. *** CLONE WR122. ** CLONE WR128. *** CLONE WR134. *** CLONE WR137. *** CLONE WR143. * CLONE WR144. *** CLONE WR148. *** CLONE WR151. *** CLONE WR153. *** CLONE WR159. ** CLONE WR161. ** CLONE WR170. *** CLONE WR171. *** CLONE WR173. * CLONE WR177. *** CLONE WR182. * CLONE WR184. *** CLONE WR191. *** CLONE WR193. *** CLONE WR198. *** CLONE WS53. ** CLONE WS54. * CLOSTRIDIUM spp. *** COMAMONAS spp. ** CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). *** CYTOPHAGA SP. strains *** DERMABACTER HOMINIS NCFB 2769 (T). ** DESULFOBULBUS BG25 STR. BG25. * DESULFOVIBRIO spp. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * DICHELOBACTER NODOSUS STR. 198A ATCC 27521. *** DICTYOGLOMUS THERMOPHILUM STR. RT46B.1. * EHRLICHIA BOVIS. * ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. *** ENTEROBACTERspp. *** ERWINIA spp. *** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). ** ESCHERICHIA COLI strains *** ESCHERICHIA HERMANNII. *** EUBACTERIUM spp. *** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * 195 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 FIBROBACTER spp. ** FLEXIBACTER TRACTUOSUS STR. LEWIS BA-3 ATCC 23168 (T). * FRANKIA spp. *** FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" ** GARDNERELLA VAGINALIS ATCC 14018 (T). * GLUCONACETOBACTER spp. *** GLUCONOBACTER spp. *** GRAM NEG" ** HAEMOPHILUS INFLUENZAE strains. *** HAFNIA ALVEI ATCC 13337 (T). ** HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). * HYDROGENOPHAGA spp. ** IFO spp. *** KINEOSPORIA spp. ** KITASATOSPORA spp. * KITASATOSPORIA spp. * KURTHIA ZOPFII STR. F64/100; K5 NCIMB 9878 (T). * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). *** LEPTOTHRIX spp. *** LEUCOBACTER KOMAGATAE. ** LISTONELLA ANGUILLARUM strains *** MAGNETOBACTERIUM BAVARICUM. * MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACILLUS FLAGELLATUM STR. KT1. *** METHYLOBACTERIUM spp. *** METHYLOCYSTIS spp. *** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. *** MICROBACTERIUM spp. ** MICROBISPORA BISPORA PARTIAL RIBOSOMAL RNA OPERON A,B,C,D INCLUDING 16S *** MICROCOCCUS spp. *** MICROCYSTIS spp. *** MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOORELLA THERMOACETICA ATCC 39073. *** MOUNT COOT-THA REGION (BRISBANE" *** MYCOBACTERIUM spp. *** MYCOPLASMA spp. *** NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS strains *** NODULARIA BCNOD9427 STR. BCNOD9427. ** NOSTOC MUSCORUM PCC 7120. ** OERSKOVIA XANTHINEOLYTICA NCIMB 11025. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). *** PAENIBACILLUS spp. *** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. *** PARACRAUROCOCCUS RUBER strains * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PHOTOBACTERIUM DAMSELA SUBSP. DAMSELA NCIMB 2184. ** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. * PLANOCOCCUS spp. ** PREVOTELLA BUCCALIS ATCC 35310 (T). * PROTEUS VULGARIS IFAM 1731. ** PSEUDOMONAS spp. *** PSYCHROSERPENS BURTONENSIS strains * 196 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 RALSTONIA spp. ** RHODOBACTER spp. *** RHODOFERAX ANTARCTICUS STR. ANT.BR. * ROSEOBACTER MED6 STR. MED6. *** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). *** RUMINOCOCCUS HANSENII ATCC 27752 (T). * SACCHAROCOCCUS THERMOPHILUS STR. 657 ATCC 43125 (T). ** SALMONELLA spp. *** SEQUENCE 1 FROM PATENT US 5508193. ** SHEWANELLA SP. strains ** SHIGELLA spp. ** SPHAEROTILUS IF4 STR. IF4, IF5. ** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). * SPIRILLUM VOLUTANS ATCC 19554 (T). *** STAPHYLOCOCCUS spp. ** STENOTROPHOMONAS SP. STR. P-9-8. * STR. 400M ATT. ** STR. ABRAXAS. * STR. ACE. *** STR. ALV. ** STR. AS2965. *** STR. AS2985. *** STR. AS2987. *** STR. AS2989. *** STR. AS3080. *** STR. AS3088. *** STR. AS3090. *** STR. AS3142. *** STR. AS3380. *** STR. AS3641. *** STR. B1. *** STR. B100. * STR. B-3060. *** STR. BD1-1. ** STR. BD2-3. ** STR. BD3-7. * STR. BD4-10. * STR. BD4-12. ** STR. BD5-11. ** STR. BD5-12. * STR. ES-1. *** STR. FROM LAKE GOSSENKOELLESEE. ** STR. HNSM13. *** STR. HNSS13. *** STR. HW1. * STR. IC025. * STR. J 195. * STR. JL 134. * STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. * STR. JTB146. * STR. JTB36. * STR. KN4. ** STR. N4-7. ** STR. NKB11. * STR. NKB13. * STR. NKB18. * 197 Facultative annual forward primer continued: Mesocosm # Organism Name A3 B1 C1 STR. NRRLB-14911. * STR. P211. *** STR. PCE-FF ATCC 35879. *** STR. PENDANT. *** STR. RA1. ** STR. SR 119. ** STR. SUR ATT. *** STR. T25. ** STR. T3. * STR. T41. **
STR. UNIDENTIFIED BACTERIUM D. * STR. UW 103/A31. ** STREPTOMYCES spp. *** SULFOBACILLUS spp. *** SULFUROSPIRILLUM BARNESII 16S RIBOSOMAL RNA GENE" * SUTTONELLA INDOLOGENES ATCC 25869 (T). *** SYMBIONT OF ALVINELLA POMPEJANA. * SYMBIONT OF CRITHIDIA SP. *** SYNECHOCOCCUS SP. PCC 6301. *** THERMOACTINOMYCES CANDIDUS. ** THERMOBACILLUS XYLANOLYTICUS STR. XE. ** THERMOBISPORA BISPORA strains *** THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. ** THERMOMICROBIUM ROSEUM ATCC 27502 (T). ** THERMOMONOSPORA CHROMOGENA ATCC 43196 (T). * THERMUS spp. * TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). ** UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. *** UNIDENTIFIED BACTERIUM 16S RRNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. ***
UNIDENTIFIED EUBACTERIUM CLONE SAR248 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM CLONE SAR324 16S RIBOSOMAL RNA GENE" * UNNAMED ORGANISM. *** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. ** VIBRIO spp. ** XANTHOMONAS spp. * XYLELLA FASTIDIOSA strains *** XYLOPHILUS AMPELINUS ATCC 33914 (T). ** ZOOGLOEA SP. 16S RIBOSOMAL RNA GENE" ***
198
All identified bacteria for facultative annual FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism Name A3 B1 C1 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" ** ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). *** BACILLUS spp. *** BOSEA THIOOXIDANS STR. RPPL5-VS. * BURKHOLDERIA EN-B3. *** CLONE 1404-40. ** CLONE 2951. *** CLONE 52. * CLONE ACE-19. * CLONE ENV.OPS 12. *** CLONE GCA112. *** CLONE H1.43.F. *** CLONE HSTPL11. * CLONE HSTPL20. * CLONE HSTPL53. * CLONE HSTPL65. * CLONE HSTPL69. *** CLONE HSTPL8. * CLONE HSTPL86. *** CLONE K20-75. * CLONE M37. ** CLONE MUG6. * CLONE OPB11. *** CLONE OPB12. *** CLONE OPB34. *** CLONE OPB65. *** CLONE OPB9. *** CLONE RB29. * CLONE S027. * CLONE SCALE-6. ** CLONE SJA-101. * CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. *** CLONE SJA-58. *** CLONE SJA-68. ** CLONE T17. * CLONE T78. *** CLONE UC43F. *** CLONE UC51F. *** CLONE VADINCA02. *** CLONE WCHB1-05. * CLONE WCHB1-57. *** CLONE WCHB1-62. *** CLONE WCHB1-64. * CLONE WCHB1-80. *** CYNOMORIUM COCCINEUM CHLOROPLAST 16S RIBOSOMAL RNA GENE" * DEBARYOMYCES spp. * DESULFORHOPALUS LSV20 STR. LSV20. * ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FRANCISELLA spp. * GEMMATA OBSCURIGLOBUS strains ** GEOBACTER ""HYDROGENOPHILUS""."" ** 199 Facultative annual reverse primer continued: mesocosm # organism name A3 B1 C1 HALOANAEROBACTER spp. * HALOANAEROBIUM PRAEVALENS ATCC 33744 (T). * HALOBACTEROIDES spp. * HILDENBRANDIA OCCIDENTALIS. * LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LEPTONEMA ILLINI STR. 3055. *** MARINE SNOW ASSOCIATED CLONE AGG8. * MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). ** MOUNT COOT-THA REGION (BRISBANE" ** MYCOPLASMA BOVIRHINIS STR. PG43 (T). * ORENIA MARISMORTUI STR. DY-1 DSM 5156 (T). * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. *** PIRELLULA UNCULTURED PIRELLULA CLONEs * PLANCTOMYCES spp. * RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** RHODOCOCCUS YT-2 STR. YT-2. * SARGASSO SEA" *** SPIROCHAETA spp. * SPIROCHETE SP. 16S RIBOSOMAL RNA (RRNA) GENE. * SPIROPLASMA spp. ** SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 2-1498. * STR. 292. ** STR. 394. ** STR. BD3-16. *** STR. RM1. * STR. RM17. * STR. SP40-12. * STR. SP5-18. * STREPTOCOCCUS HYOINTESTINALIS DSM 20770 (T). ** SUTTERELLA WADSWORTHENSIS strains *** SYNTROPHOBACTER SP. STR. TSUA1. * TREPONEMA spp. * UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED EUBACTERIUM RB29 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED GREEN NON-SULFUR BACTERIUM OP strains *** UNNAMED ORGANISM. ** VIBRIO 2P44 16S RRNA GENE SEQUENCE. * WOLBACHIA PERSICA ATCC VR-331 (T). *
200 All identified bacteria for obligate annual FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Me socosms # Organism Name C5 E1 F3 ACETOBACTER spp. * ACETONEMA LONGUM STR. APO-1 DSM 6540 (T). *** ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). ** ACIDOVORAX spp. ** AFIPIA spp. *** AGROMYCES MEDIOLANUS strains *** ALICYCLOBACILLUS SP. Strains * ALLOIOCOCCUS OTITIS NCFB 2890 (T). *** ALPHA-PROTEOBACTERIUM SPECIES 16S RRNA GENE (ISOLATE TM28). * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. *** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). ** ANAEROPLASMA spp. ** AQUASPIRILLUM spp. ** ARTHROBACTER SP. STR. RC100. *** BACILLUS spp. *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA023). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA113). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). *** BACTEROIDES UREOLYTICUS ATCC 33387 (T). ** BDELLOVIBRIO STOLPII STR. UKI2 ATCC 27052 (T). ** BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). *** BLASTOMONAS NATATORIA DSM 3183 (T). ** BREVIBACILLUS spp. *** BREVUNDIMONAS spp. ** BURKHOLDERIA spp. *** CALDOTOGA FONTANA STR. B4. * CAMPYLOBACTER spp. ** CARYOPHANON LATUM strains *** CAULOBACTER spp. ** CELLULOMONAS spp. *** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). *** CHLAMYDIA spp. * CHLOROBIUM LIMICOLA strains ** CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. *** CLONE 1_60. ** CLONE 113. ** CLONE 141. ** CLONE 167. * CLONE 22. ** CLONE 282. ** CLONE 330. ** CLONE 348. ** CLONE 368. ** CLONE ADRIATIC76. *** CLONE ADRIATIC91. * CLONE ADRIATICR16. ** CLONE ASB009. ** CLONE ASB016. * CLONE ASB029. * CLONE ASB031. * CLONE BH017. ***
201 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 CLONE BPC043. *** CLONE BPC060. *** CLONE BPC090. ** CLONE BPC094. *** CLONE C028. *** CLONE CLONE DA115. *** CLONE CN1. ** CLONE CN3. ** CLONE DA011. ** CLONE DA015. ** CLONE DA023. ** CLONE DA026. *** CLONE DA032. ** CLONE DA036. ** CLONE DA038. * CLONE DA040. * CLONE DA057. * CLONE DA066. *** CLONE DA111. * CLONE DA113. * CLONE DA114. *** CLONE DA116. * CLONE DA134. ** CLONE DA154. ** CLONE ENV.OPS 12. ** CLONE FB14. * CLONE FB15. *** CLONE FB16. *** CLONE GCA018. * CLONE GCA025. * CLONE H1.2.F. * CLONE H1.43.F. *** CLONE JW23. * CLONE JW29. ** CLONE JW6. *** CLONE LBS1. ** CLONE LBS10. ** CLONE LBS25. ** CLONE LBS6. * CLONE LBS9. ** CLONE LRE13. * CLONE LRE17. ** CLONE LRE18. ** CLONE LRE22. ** CLONE LRE9. ** CLONE LRS11. * CLONE LRS4. ** CLONE OCS146. *** CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE ODPB-B4. * CLONE OM180. * CLONE OM59. * CLONE OM93. * CLONE RIZ1015. *** CLONE RIZ103. *** CLONE RIZ1078. ** 202 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 CLONE RIZ1083. *** CLONE S023. ** CLONE S027. ** CLONE S125. *** CLONE SAR 406. *** CLONE SJA-102. * CLONE SJA-121. *** CLONE SJA-168. ** CLONE SJA-176. *** CLONE SJA-181. *** CLONE SJA-186. *** CLONE SJA-47. *** CLONE SJA-62. * CLONE SJA-63. * CLONE SJA-68. ** CLONE SJA-87. *** CLONE SJA-9. *** CLONE SVA0071. ** CLONE SVA0113. ** CLONE SVA0318. ** CLONE SVA0631. * CLONE SVA0679. ** CLONE SVA0853. ** CLONE SVA0864. * CLONE SVA0996. * CLONE SVA1037. * CLONE SY1-44. ** CLONE T10. * CLONE T20. ** CLONE T22. * CLONE T28. * CLONE T3. * CLONE T33. ** CLONE T43. * CLONE T59. * CLONE T65. ** CLONE T67. * CLONE T73. *** CLONE T79. *** CLONE T90. *** CLONE T98. *** CLONE TBS1. * CLONE TBS13. * CLONE TBS3. *** CLONE TBS7. ** CLONE THRIPS6.12. ** CLONE TRE13. ** CLONE TRE19. ** CLONE TRE3. *** CLONE TRS1. ** CLONE TRS11. ** CLONE TRS2. * CLONE TRS28. ** CLONE TRS7. ** CLONE UC25. ** CLONE UC32F. * CLONE UC37F. ** 203 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 CLONE UC44. ** CLONE UC47. ** CLONE UC52. ** CLONE VC2.1 BAC16. * CLONE WR105. *** CLONE WR108. *** CLONE WR1105. *** CLONE WR1109. * CLONE WR1112. *** CLONE WR1117. * CLONE WR1120. * CLONE WR1123. *** CLONE WR1124. ** CLONE WR1126. ** CLONE WR1132. *** CLONE WR1134. ** CLONE WR1138. ** CLONE WR114. *** CLONE WR1140. *** CLONE WR1141. *** CLONE WR1143. * CLONE WR117. ** CLONE WR118. ** CLONE WR128. *** CLONE WR134. *** CLONE WR137. *** CLONE WR143. * CLONE WR144. *** CLONE WR147. * CLONE WR148. *** CLONE WR150. ** CLONE WR151. *** CLONE WR153. *** CLONE WR156. ** CLONE WR157. * CLONE WR168. * CLONE WR170. *** CLONE WR171. *** CLONE WR173. ** CLONE WR177. *** CLONE WR184. *** CLONE WR190. * CLONE WR191. *** CLONE WR193. *** CLONE WR198. *** CLONE WS53. ** CLOSTRIDIUM spp. *** COMAMONAS spp. ** CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). *** CYTOPHAGA SP. strains *** DELFTIA ACIDOVORANS STR. STANIER 14 ACM 489 (T). * DESULFOBULBUS spp. ** DESULFOVIBRIO spp. ** DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). ** EHRLICHIA BOVIS. * ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. * ENTEROBACTER CLOACAE ATCC 13047. * 204 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 ENTEROBACTER spp. ** ERWINIA spp. ** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). *** ERYTHROBACTER spp. ** ERYTHROMONAS URSINCOLA STR. KR-99 DSM 9006 (T). ** ESCHERICHIA COLI strains ** ESCHERICHIA HERMANNII. ** EUBACTERIUM XYLANOPHILUM ATCC 35991 (T). ** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FIBROBACTER spp. ** FLECTOBACILLUS MAJOR ATCC 29496 (T). * FLEXIBACTER spp. ** FRANKIA SP. strains * FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" ** GARDNERELLA VAGINALIS ATCC 14018 (T). ** GLUCONACETOBACTER spp. * GLUCONOBACTER spp. * GRAM NEG" *** HAEMOPHILUS INFLUENZAE strains ** HALOANAEROBIUM ACETOETHYLICUM strains * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). *** HYDROGENOPHAGA spp. ** IAM 12620. ** IFO 15614. *** IFO 15706. ** IFO 15777. *** KINEOSPORIA spp. ** KITASATOSPORA spp. ** KITASATOSPORIA spp. ** KURTHIA ZOPFII strains *** LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). *** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). *** LEUCOBACTER KOMAGATAE. ** LISTONELLA ANGUILLARUM strains * MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACTERIUM spp. *** METHYLOCYSTIS spp. *** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. *** MICROBACTERIUM spp. *** MICROCOCCUS spp. *** MICROCYSTIS spp. * MICROSCILLA spp. ** MOORELLA THERMOACETICA ATCC 39073. ** MOUNT COOT-THA REGION (BRISBANE" *** MYCOBACTERIUM spp. *** MYCOPLASMA HOMINIS strains * MYXOCOCCUS CORALLOIDES STR. M2 ATCC 25202 (T). ** NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS strains *** NODULARIA BCNOD9427 STR. BCNOD9427. * NOSTOC MUSCORUM PCC 7120. *** OERSKOVIA XANTHINEOLYTICA NCIMB 11025. ** OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). *** PAENIBACILLUS spp. ***
205 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. ** PARACRAUROCOCCUS RUBER strains * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). ** PHAEOSPIRILLUM FULVUM STR. 1360 ATCC 15798. * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PHOTOBACTERIUM spp. ** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. * PLANOCOCCUS spp. *** PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST * PORPHYROBACTER spp. ** PREVOTELLA BUCCALIS ATCC 35310 (T). ** PROTEUS VULGARIS IFAM 1731. * PSEUDOMONAS spp. ** PSYCHROSERPENS BURTONENSIS ACAM strains * RALSTONIA spp. *** RHIZOMONAS SUBERIFACIENS IFO 15211 (T). ** RHODOBACTER spp. *** RHODOCYCLUS PURPUREUS STR. 6770 DSM 168 (T). ** RHODOFERAX ANTARCTICUS STR. ANT.BR. * RHODOVIBRIO SALINARUM ATCC 35394 (T). * ROSEOBACTER MED6 STR. MED6. *** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). *** SALMONELLA spp. *** SHIGELLA DYSENTERIAE. * SPHAEROTILUS IF4,IF5 STR. IF4,IF5. *** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). ** SPHINGOMONAS spp. ** SPIRILLUM VOLUTANS ATCC 19554 (T). *** SPIROSOMA LINGUALE STR. MC1 ATCC 23276. ** STAPHYLOCOCCUS spp. *** STENOTROPHOMONAS spp. ** STR. 400M ATT. ** STR. ABRAXAS. * STR. ACE. ** STR. AS2965. *** STR. AS2985. *** STR. AS2987. *** STR. AS2988. * STR. AS2989. ** STR. AS3080. *** STR. AS3088. *** STR. AS3090. *** STR. AS3142. *** STR. AS3187. * STR. AS3380. *** STR. AS3641. *** STR. B1. *** STR. B100. * STR. B-3060. * STR. BD1-1. ** STR. BD2-3. * STR. BD3-7. ** STR. BD4-10. ** STR. BD5-11. ** STR. BD5-12. ** STR. BD5-9. ** STR. CD. ** 206 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 STR. ES-1. ** STR. FROM LAKE GOSSENKOELLESEE. *** STR. GR-06. * STR. HNSM13. *** STR. HNSS13. *** STR. HW1. * STR. IC025. * STR. J 195. ** STR. JL 134. ** STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. ** STR. JTB131. * STR. JTB146. * STR. JTB148. ** STR. JTB36. ** STR. KN4. ** STR. N4-7. ** STR. NKB11. * STR. NKB13. ** STR. NRRLB-14911. * STR. P211. * STR. PCE-FF ATCC 35879. * STR. PENDANT. ** STR. RA1. ** STR. RJ. * STR. SUR ATT. ** STR. T3. * STR. TM28. * STR. UNIDENTIFIED BACTERIUM D. *** STR. UW 103/A31. ** STR. WSA. * STREPTOMYCES spp. *** SULFOBACILLUS DISULFIDOOXIDANS STR. SD-11. ** SULFUROSPIRILLUM BARNESII strains ** SUTTONELLA INDOLOGENES ATCC 25869 (T). * SYMBIONT OF ALVINELLA POMPEJANA. ** SYMBIONT OF CRITHIDIA SP. *** SYMBIONT OF INTRACELLULAR ILEAL SYMBIONT OF MESOCRICETUS AURATUS. ** SYMBIONT OF SUS SCROFA. ** SYNECHOCOCCUS SP. PCC 6301. ** SYNTROPHOBACTER WOLINII. * TELLURIA CHITINOLYTICA STR. 20M ACM 3522 (T). * THERMOBACILLUS XYLANOLYTICUS STR. XE. * THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. *** THERMOMICROBIUM ROSEUM ATCC 27502 (T). * THERMUS THERMOPHILUS strains * THERMUS UNCULTURED EUBACTERIUM H21.73.F. * TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). ** UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" *** UNCULTIVATED SOIL BACTERIUM CLONE S023 16S RIBOSOMAL RNA GENE" ** UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" ** UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" *** UNCULTURED EUBACTERIUM H1.2.F 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. ** UNIDENTIFIED BACTERIUM 16S RRNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** 207 Obligate annual forward primer continued: Mesocosms # Organism Name C5 E1 F3 UNIDENTIFIED BACTERIUM 16S RRNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM 16S RRNA GENE" * UNNAMED ORGANISM. *** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. ** VIBRIO spp. * VOGESELLA INDIGOFERA ATCC 19706 (T). * XANTHOMONAS spp. * XYLELLA FASTIDIOSA strains * XYLOPHILUS AMPELINUS ATCC 33914 (T). ** ZOOGLOEA SP. 16S RIBOSOMAL RNA GENE" **
All identified bacteria for obligate annual FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism Name C5 E1 F3 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" * ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). *** BACILLUS spp. *** BLASTOBACTER SP. STR. PC30.44. * BOSEA THIOOXIDANS STR. RPPL5-VS. * BURKHOLDERIA EN-B3. *** CANDIDA VERSATILIS. * CHLOROBIUM LIMICOLA DSM 245 (T). * CLONE 2951. * CLONE ACE-19. * CLONE BPC110. * CLONE ENV.OPS 12. *** CLONE GCA112. *** CLONE H1.43.F. *** CLONE HSTPL64. * CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE K20-75. ** CLONE KTK 14. * CLONE KTK 27. * CLONE KTK 32. * CLONE KTK 41. * CLONE MUG6. * CLONE OPB11. *** CLONE OPB12. *** CLONE OPB34. *** CLONE OPB65. *** CLONE OPB9. *** CLONE RB29. ** CLONE SCALE-6. *** CLONE SJA-101. ** CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. *** CLONE SJA-21. ***
208 Obligate annual reverse primer continued: Mesocosms # Organism Name C5 E1 F3 CLONE SJA-58. *** CLONE SJA-61. ** CLONE T78. *** CLONE UC43F. ** CLONE UC51F. ** CLONE VADINCA02. *** CLONE WB004. * CLONE WCHB1-31. ** CLONE WCHB1-57. ***
CLONE WCHB1-62. *** CLONE WCHB1-80. *** DEBARYOMYCES CASTELLII. * DEBARYOMYCES UDENII. * DESULFORHOPALUS LSV20 STR. LSV20. ** ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** EPERYTHROZOON SUIS strains * EURYPYGA HELIAS 12S MITOCHONDRIAL RIBOSOMAL RNA" * FERVIDOBACTERIUM GONDWANENSE STR. AB39 ACM 5017 (T). * HALOANAEROBACTER spp. ** HALOBACTEROIDES spp. ** HILDENBRANDIA OCCIDENTALIS. ** LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LEPTONEMA ILLINI STR. 3055. ** MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PLANCTOMYCES spp. * RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** RHODOCOCCUS YT-2 STR. YT-2. * SARGASSO SEA" ** SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 394. * STR. BD3-16. *** STR. BD3-7. *** STR. NKB17. ** STR. RM1. * STR. RM17. * STR. SP40-12. * SUTTERELLA WADSWORTHENSIS strains *** THAUERA MZ1T STR. MZ1T. * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM RB29 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED GREEN NON-SULFUR BACTERIUM strains *** UNNAMED ORGANISM. ** VIBRIO 2P44 strains **
209 All identified bacteria for 2FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism Name A7 D1 F1 ACETOBACTER spp. ** ACHOLEPLASMA OCULI ISM 1499. * ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). * ACIDOVORAX spp. *** AFIPIA spp. *** AGROMYCES MEDIOLANUS strains ** ALCALIGENES FAECALIS SUBSP. FAECALIS ATCC 8750 (T). * ALICYCLOBACILLUS SP. strains * ALLOIOCOCCUS OTITIS NCFB 2890 (T). * AMARICOCCUS KAPLICENSIS strains * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. ** ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). ** AQUASPIRILLUM spp. *** AQUIFEX PYROPHILUS STR. KOL5A. * ARTHROBACTER SP. STR. RC100. ** BACILLUS spp. ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA023). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA052). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA113). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). ** BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). * BIFIDOBACTERIUM spp. * BORDETELLA AVIUM ATCC 35086 (T). * BREVIBACILLUS spp. * BREVUNDIMONAS spp. ** BURKHOLDERIA spp. *** CALDOTOGA FONTANA STR. B4. * CAMPYLOBACTER spp. * CAULOBACTER spp. *** CELLULOMONAS spp. ** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). ** CHLOROBIUM LIMICOLA strains * CITROBACTER spp. ** CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. * CLONE 1_60. * CLONE 113. * CLONE 141. * CLONE 22. * CLONE 282. * CLONE 330. * CLONE 348. * CLONE 368. * CLONE ACK-L5. * CLONE ADRIATIC76. ** CLONE ADRIATICR16. * CLONE ASB009. ** CLONE ASB016. ** CLONE ASB017. * CLONE ASB029. * CLONE ASB031. * 210 2FG forward primer continued: Mesocosms # Organism Name A7 D1 F1 CLONE BH017. *** CLONE BPC043. ** CLONE BPC060. ** CLONE BPC090. * CLONE BPC094. ** CLONE C028. * CLONE CLONE DA115. ** CLONE CN1. *** CLONE CN3. *** CLONE DA011. ** CLONE DA015. ** CLONE DA023. * CLONE DA026. ** CLONE DA032. ** CLONE DA036. ** CLONE DA038. * CLONE DA040. * CLONE DA052. * CLONE DA057. * CLONE DA066. * CLONE DA113. * CLONE DA114. * CLONE DA116. * CLONE DA134. ** CLONE DA154. ** CLONE ENV.OPS 8. * CLONE FB14. * CLONE FB15. ** CLONE FB16. ** CLONE H1.43.F. *** CLONE JW13. * CLONE JW29. ** CLONE JW6. ** CLONE LBS12. * CLONE LBS25. * CLONE LBS3. * CLONE LRE13. *** CLONE LRE17. * CLONE LRE18. *** CLONE LRE25. * CLONE LRE9. *** CLONE LRS11. * CLONE LRS15. * CLONE LRS4. * CLONE OCS14. ** CLONE OCS146. ** CLONE ODPB-B4. * CLONE OM180. ** CLONE OM21. ** CLONE OM93. ** CLONE RIZ1015. ** CLONE RIZ103. ** CLONE RIZ1078. ** CLONE RIZ1079. * CLONE RIZ1081. * CLONE RIZ1083. ** CLONE SAR 406. * 211 2FG forward primer continued: Mesocosms # Organism Name A7 D1 F1 CLONE SAR248. * CLONE SAR324. * CLONE SJA-10. * CLONE SJA-102. * CLONE SJA-111. * CLONE SJA-121. ** CLONE SJA-162. * CLONE SJA-171. * CLONE SJA-176. *** CLONE SJA-181. * CLONE SJA-181. * CLONE SJA-182. * CLONE SJA-186. * CLONE SJA-22. * CLONE SJA-47. * CLONE SJA-51. * CLONE SJA-62. *** CLONE SJA-68. * CLONE SJA-87. *** CLONE SJA-9. ** CLONE SVA0071. *** CLONE SVA0113. * CLONE SVA0318. * CLONE SVA0679. ** CLONE SVA0864. ** CLONE SVA1064. * CLONE SY1-44. ** CLONE T10. * CLONE T20. *** CLONE T22. * CLONE T3. *** CLONE T33. *** CLONE T37. * CLONE T65. ** CLONE T67. *** CLONE T73. *** CLONE T79. * CLONE T90. * CLONE T98. *** CLONE TBS13. * CLONE TBS3. * CLONE THRIPS6.12. *** CLONE TRE13. *** CLONE TRE19. *** CLONE TRE3. * CLONE TRS11. *** CLONE TRS2. * CLONE TRS24. * CLONE TRS7. * CLONE TRS9. * CLONE UC25. * CLONE UC32F. * CLONE UC37F. * CLONE UC44. * CLONE UC47. * CLONE UC52. * CLONE VC2.1 BAC16. * 212 2FG forward primer continued: Mesocosms # Organism Name A7 D1 F1 CLONE WR105. * CLONE WR108. * CLONE WR109. * CLONE WR1105. * CLONE WR1109. * CLONE WR1111. * CLONE WR1112. * CLONE WR1115. * CLONE WR1120. * CLONE WR1123. *** CLONE WR1124. * CLONE WR1132. * CLONE WR1134. * CLONE WR114. * CLONE WR1140. *** CLONE WR1141. * CLONE WR119. * CLONE WR128. * CLONE WR134. * CLONE WR137. * CLONE WR144. * CLONE WR148. * CLONE WR151. *** CLONE WR153. *** CLONE WR156. * CLONE WR161. * CLONE WR168. * CLONE WR170. * CLONE WR171. * CLONE WR173. * CLONE WR177. *** CLONE WR184. * CLONE WR191. * CLONE WR193. * CLONE WR197. * CLONE WR198. * CLONE WR199. * CLONE WS53. * CLONE WS54. * CLOSTRIDIUM spp. *** COMAMONAS spp. *** CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). ** CYTOPHAGA SP. strains *** DECHLORISOMA spp. * DERMABACTER HOMINIS NCFB 2769 (T). ** DESULFOBACTERIUM spp. * DESULFOBULBUS BG25 STR. BG25. * DESULFOVIBRIO spp. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * DICHELOBACTER NODOSUS STR. 198A ATCC 27521. ** EHRLICHIA BOVIS. ** ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. ** ENTEROBACTER spp. *** ERWINIA spp. *** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). ** ESCHERICHIA COLI strains *** ESCHERICHIA HERMANNII. ** 213 2FG forward primer continued: Mesocosms # Organism Name A7 D1 F1 EUBACTERIUM spp. ** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FIBROBACTER SUCCINOGENES STR. GC5. * FLEXIBACTER TRACTUOSUS STR. LEWIS BA-3 ATCC 23168 (T). * FUSIBACTER PAUCIVORANS SEBR 4211. * FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" * GARDNERELLA VAGINALIS ATCC 14018 (T). ** GLUCONACETOBACTER spp. ** GLUCONOBACTER spp. ** HAEMOPHILUS INFLUENZAE strains ** HAFNIA ALVEI ATCC 13337 (T). ** HALOBACILLUS spp. * HERBASPIRILLUM G8A1 STR. G8A1. * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). ** HYDROGENOPHAGA spp. *** IFO 15706. * KINEOSPORIA spp. * KINGELLA ORALIS STR. UB-38 CCUG 30450 (T). * KITASATOSPORA spp. * KITASATOSPORIA spp. * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). ** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). *** LEUCOBACTER KOMAGATAE. ** LISTONELLA ANGUILLARUM strains *** MAGNETOBACTERIUM BAVARICUM. * MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACILLUS spp. ** METHYLOBACTERIUM spp. ** METHYLOCYSTIS spp. *** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. ** MICROBACTERIUM spp. *** MICROBISPORA BISPORA PARTIAL RIBOSOMAL RNA OPERON B INCLUDING 16S * MICROCOCCUS spp. ** MICROCYSTIS ELABENS. * MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOUNT COOT-THA REGION (BRISBANE" ** MYCOBACTERIUM spp. *** MYCOPLASMA HOMINIS STR. 7488. * NEISSERIA spp. * NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS strains *** NOSTOC MUSCORUM PCC 7120. * OCHROSPHAERA SP. STR. 181 (HAPTOPHYTE) -- CHLOROPLAST. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). ** PAENIBACILLUS spp. ** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PEPTOSTREPTOCOCCUS SP. STR. C. * PHOTOBACTERIUM spp. *** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. * PLANOCOCCUS spp. * PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST ** PROTEUS VULGARIS IFAM 1731. *** PSEUDOMONAS spp. *** 214 2FG forward primer continued: Mesocosms # Organism Name A7 D1 F1 PSYCHROSERPENS BURTONENSIS ACAM strains * RALSTONIA spp. ** RHODOBACTER spp. *** RHODOCOCCUS COPROPHILUS JCM 3200 (T). * RHODOFERAX ANTARCTICUS STR. ANT.BR. ** RHODOPSEUDOMONAS SP. strains * RHODOTHALASSIUM SALEXIGENS ATCC 35888 (T). * ROSEOBACTER DENITRIFICANS STR. OCH 114 (T). * ROSEOBACTER spp. *** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). * SACCHAROCOCCUS THERMOPHILUS STR. 657 ATCC 43125 (T). * SALMONELLA spp. *** SEQUENCE 1 FROM PATENT US 5508193. ** SHEWANELLA GELIDIMARINA strains ** SHIGELLA spp. **
SPHAEROTILUS IF4,IF5 STR. IF4,IF5. *** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). * SPHINGOMONAS spp. * SPIRILLUM VOLUTANS ATCC 19554 (T). *** SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). * SPOROSARCINA UREAE. *
All identified bacteria for 2FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) mesocosm # Organism Name A7 D1 F1 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" * ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). *** BACILLUS spp. *** BOSEA THIOOXIDANS STR. RPPL5-VS. * BURKHOLDERIA EN-B3. *** CERAMIUM RUBRUM (RED ALGA). * CHLOROBIUM LIMICOLA DSM 245 (T). * CLONE 1404-40. * CLONE 2951. ** CLONE 52. * CLONE BPC110. * CLONE EKHO-1. * CLONE ENV.OPS 12. *** CLONE GCA112. *** CLONE H1.43.F. *** CLONE HSTPL11. * CLONE HSTPL20. * CLONE HSTPL53. * CLONE HSTPL65. * CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE K20-75. ** CLONE M37. * CLONE MUG6. **
215 2FG reverse primer continued: Me socosm s # Organism Name A7 D1 F1 CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. * CLONE SJA-21. ** CLONE SJA-58. *** CLONE SJA-61. * CLONE SJA-68. * CLONE T17. * CLONE T78. *** CLONE UC43F. *** CLONE UC51F. *** CLONE VADINCA02. *** CLONE WB004. ** CLONE WCHB1-05. * CLONE WCHB1-31. * CLONE WCHB1-57. *** CLONE WCHB1-62. *** CLONE WCHB1-64. * CLONE WCHB1-80. *** DEBARYOMYCES spp. * DESULFORHOPALUS LSV20 STR. LSV20. * ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). ** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * GEMMATA OBSCURIGLOBUS strains * GEOBACTER ""HYDROGENOPHILUS""."" * HALOANAEROBACTER spp. ** HALOBACTEROIDES spp. ** LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LEPTONEMA ILLINI STR. 3055. *** MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). ** MOUNT COOT-THA REGION (BRISBANE" * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PLANCTOMYCES spp. ** PYURA MIRABILIS. * RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** SARGASSO SEA" *** SPIROCHAETA SP. STR. TM3. * SPIROCHAETA spp. * SPIROPLASMA spp. * SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 292. * STR. 394. ** STR. BD3-16. *** STR. BD3-7. *** STR. JTB36. * STR. NKB17. ** STR. RM1. * STR. RM17. * SUTTERELLA WADSWORTHENSIS strains *** TREPONEMA spp. * TRIOZA EUGENIAE (EUGENIA PSYLLID). * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM RB29 16S RIBOSOMAL RNA GENE" **
216 All identified bacteria for 3FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism Name A4 C2 E4 ACETOBACTER spp. ** ACETONEMA LONGUM STR. APO-1 DSM 6540 (T). ** ACHOLEPLASMA OCULI ISM 1499. ** ACIDOVORAX spp. ** AFIPIA spp. *** AGROMYCES MEDIOLANUS strains *** ALLOIOCOCCUS OTITIS NCFB 2890 (T). ** AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. *** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). *** ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). ** ANEURINIBACILLUS spp. * AQUASPIRILLUM spp. ** ARTHROBACTER SP. STR. RC100. *** BACILLUS spp. *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA011). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA015). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA023). * BACTERIAL SPECIES 16S RRNA GENE (CLONE DA026). ** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA032). *** BACTERIAL SPECIES 16S RRNA GENE (CLONE DA115). *** BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). *** BIFIDOBACTERIUM spp. ** BLASTOMONAS NATATORIA DSM 3183 (T). * BREVIBACILLUS spp. *** BREVUNDIMONAS spp. ** BURKHOLDERIA spp. *** BUTYRIVIBRIO FIBRISOLVENS STR. OB189. * CALDOTOGA FONTANA STR. B4. ** CAMPYLOBACTER spp. * CARYOPHANON LATUM strains ** CAULOBACTER spp. ** CELLULOMONAS spp. *** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). *** CHLAMYDIA spp. * CHLORARACHNION REPTANS CCMP 238 (AMOEBOFLAGELLATE) -- CHLOROPLAST. * CHLOROBIUM LIMICOLA strains * CITROBACTER spp. ** CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. *** CLONE 1_60. * CLONE 141. * CLONE 167. * CLONE 22. * CLONE ACK-L5. * CLONE ADRIATIC76. *** CLONE ADRIATICR16. * CLONE ASB009. ** CLONE ASB013. * CLONE ASB016. ** CLONE ASB028. * CLONE ASB029. ** CLONE ASB031. ** CLONE ASB033. * CLONE BH017. **
217 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 CLONE BPC043. ** CLONE BPC060. ** CLONE BPC090. *** CLONE BPC094. ** CLONE BPC102. ** CLONE C028. ** CLONE CLONE DA115. *** CLONE CN1. ** CLONE CN3. ** CLONE DA011. *** CLONE DA015. *** CLONE DA023. * CLONE DA026. ** CLONE DA032. *** CLONE DA036. *** CLONE DA066. ** CLONE DA114. *** CLONE DA134. *** CLONE DA154. *** CLONE ENV.OPS 12. * CLONE FB14. * CLONE FB15. ** CLONE FB16. ** CLONE H1.2.F. * CLONE H1.43.F. *** CLONE JW23. ** CLONE JW29. * CLONE JW6. *** CLONE LBS1. * CLONE LBS12. * CLONE LBS25. * CLONE LBS28. * CLONE LBS3. ** CLONE LBS6. * CLONE LRE13. ** CLONE LRE17. * CLONE LRE18. ** CLONE LRE22. * CLONE LRE25. ** CLONE LRE28. * CLONE LRE9. *** CLONE LRS15. * CLONE LRS4. * CLONE OCS14. * CLONE OCS146. ** CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE ODPB-B9. * CLONE OM180. ** CLONE OM21. * CLONE OM93. ** CLONE RIZ1015. *** CLONE RIZ103. *** CLONE RIZ1074. ** CLONE RIZ1078. *** CLONE RIZ1081. * 218 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 CLONE RIZ1083. *** CLONE S125. * CLONE SAR 406. ** CLONE SJA-10. * CLONE SJA-102. *** CLONE SJA-108. * CLONE SJA-121. *** CLONE SJA-176. *** CLONE SJA-181. ** CLONE SJA-186. *** CLONE SJA-21. * CLONE SJA-22. * CLONE SJA-47. ** CLONE SJA-52. * CLONE SJA-62. ** CLONE SJA-63. * CLONE SJA-68. * CLONE SJA-87. ** CLONE SJA-9. ** CLONE SVA0071. *** CLONE SVA0113. * CLONE SVA0318. * CLONE SVA0679. ** CLONE SVA0864. *** CLONE SVA1037. * CLONE SY1-44. ** CLONE T10. ** CLONE T20. ** CLONE T22. * CLONE T3. ** CLONE T33. ** CLONE T65. ** CLONE T67. ** CLONE T73. * CLONE T79. * CLONE T90. ** CLONE T98. ** CLONE TBS1. * CLONE TBS13. * CLONE TBS3. ** CLONE TBS7. * CLONE THRIPS6.12. ** CLONE TRE13. ** CLONE TRE19. ** CLONE TRE3. *** CLONE TRS1. * CLONE TRS11. ** CLONE TRS2. ** CLONE TRS7. *** CLONE UC32F. ** CLONE UC52. * CLONE VC2.1 BAC16. * CLONE VC2.1 BAC32. ** CLONE WR105. *** CLONE WR108. *** CLONE WR1105. *** 219 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 CLONE WR1112. *** CLONE WR1117. * CLONE WR1119. ** CLONE WR1123. ** CLONE WR1124. ** CLONE WR1126. * CLONE WR1132. *** CLONE WR1134. ** CLONE WR1138. * CLONE WR114. *** CLONE WR1140. ** CLONE WR1141. *** CLONE WR117. * CLONE WR118. * CLONE WR128. *** CLONE WR134. *** CLONE WR137. *** CLONE WR144. *** CLONE WR148. *** CLONE WR150. * CLONE WR151. ** CLONE WR153. ** CLONE WR156. * CLONE WR161. ** CLONE WR168. ** CLONE WR170. *** CLONE WR171. *** CLONE WR177. * CLONE WR177. * CLONE WR184. *** CLONE WR190. * CLONE WR191. *** CLONE WR193. *** CLONE WR198. *** CLONE WS54. * CLOSTRIDIUM spp. *** COMAMONAS spp. * CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). *** CYTOPHAGA spp. *** DECHLORIMONAS CL STR. CL. * DECHLORISOMA SUILLA STR. PS. * DELFTIA ACIDOVORANS STR. STANIER 14 ACM 489 (T). * DERMABACTER HOMINIS NCFB 2769 (T). * DESULFOBULBUS BG25 STR. BG25. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * DICHELOBACTER NODOSUS STR. 198A ATCC 27521. ** DICTYOGLOMUS THERMOPHILUM STR. RT46B.1. * EHRLICHIA BOVIS. ** ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. *** ENTEROBACTER spp. ** ERWINIA spp. *** ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). ** ERYTHROBACTER spp. * ERYTHROMONAS URSINCOLA STR. KR-99 DSM 9006 (T). * ESCHERICHIA COLI strains *** ESCHERICHIA HERMANNII. ** 220 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 EUBACTERIUM spp. ** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FIBROBACTER spp. *** FLAVOBACTERIUM MIZUTAII STR. KM 1203 ATCC 33299 (T). * FLEXIBACTER spp. * FRANKIA spp. ** FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" ** GARDNERELLA VAGINALIS ATCC 14018 (T). ** GLUCONACETOBACTER spp. ** GLUCONOBACTER spp. ** GRAM NEG" ** HAEMOPHILUS INFLUENZAE strains *** HAFNIA ALVEI ATCC 13337 (T). ** HALOANAEROBIUM spp. * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). ** HYDROGENOPHAGA spp. ** IAM 12620. * IFO 15614. *** IFO 15706. *** IFO 15777. ** IODOBACTER FLUVIATILE ATCC 33051 (T). * KINEOSPORIA spp. *** KINGELLA ORALIS STR. UB-38 CCUG 30450 (T). * KITASATOSPORA spp. * KITASATOSPORIA spp. * KURTHIA ZOPFII STR. F64/100; K5 ATCC 33403 (T). ** LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). *** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). *** LEUCOBACTER KOMAGATAE. ** LISTONELLA ANGUILLARUM strains *** MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACILLUS FLAGELLATUM STR. KT1. *** METHYLOBACTERIUM spp. *** ME THYLOC YSTIS spp. *** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). *** METHYLOSINUS spp. *** MICROBACTERIUM spp. *** MICROBISPORA BISPORA RIBOSOMAL RNA OPERON A,C INCLUDING 16S RIBOSOMAL *** MICROCOCCUS spp. *** MICROCYSTIS spp. *** MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOORELLA THERMOACETICA ATCC 39073. ** MOUNT COOT-THA REGION (BRISBANE" *** MYCOBACTERIUM spp. *** MYCOPLASMA spp. *** NEISSERIA spp. * NITROSOMONAS EUROPAEA STR. M103. *** NITROSOSPIRA MULTIFORMIS *** NODULARIA BCNOD9427 STR. BCNOD9427. *** NOSTOC MUSCORUM PCC 7120. ** OCHROSPHAERA SP. STR. 181 (HAPTOPHYTE) -- CHLOROPLAST. * OERSKOVIA XANTHINEOLYTICA NCIMB 11025. * OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). *** PAENIBACILLUS spp. ***
221 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PARACRAUROCOCCUS RUBER STR. NS102. * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PHOTOBACTERIUM DAMSELA SUBSP. DAMSELA NCIMB 2184. ** PHYTOPLASMA GPH SUBSP. GERBERA PHYLLODY PHYTOPLASMA STR. GPH. *** PLANOCOCCUS spp. *** PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST [GENE=RRNA GENE]. * PORPHYROBACTER spp. * PREVOTELLA BUCCALIS ATCC 35310 (T). * PROTEUS VULGARIS IFAM 1731. ** PSEUDOMONAS spp. *** PSYCHROSERPENS BURTONENSIS ACAM 167. * QUINELLA OVALIS. * RALSTONIA spp. *** RATHAYIBACTER TOXICUS STR. CS14 JCM 9669 (T). * RHIZOMONAS SUBERIFACIENS IFO 15211 (T). * RHODOBACTER spp. *** RHODOCYCLUS PURPUREUS STR. 6770 DSM 168 (T). * RHODOFERAX ANTARCTICUS STR. ANT.BR. ** ROSEOBACTER MED6 STR. MED6. *** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). *** SALMONELLA spp. *** SEQUENCE 1 FROM PATENT US 5508193. ** SHEWANELLA spp. * SHIGELLA spp. ** SPHAEROTILUS IF4,IF5 STR. IF4,IF5. ** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). * SPHINGOMONAS spp. * SPIRILLUM VOLUTANS ATCC 19554 (T). *** SPIROSOMA LINGUALE STR. MC1 ATCC 23276. * STAPHYLOCOCCUS spp. ** STENOTROPHOMONAS spp. *** STR. 400M ATT. ** STR. ACE. ** STR. AS2965. *** STR. AS2985. *** STR. AS2987. ** STR. AS2988. ** STR. AS2989. ** STR. AS3080. ** STR. AS3088. ** STR. AS3090. *** STR. AS3142. *** STR. AS3187. ** STR. AS3380. *** STR. AS3641. *** STR. B1. ** STR. B100. * STR. B-3060. * STR. BD1-1. ** STR. BD2-3. ** STR. BD3-7. * STR. BD4-10. * STR. BD4-12. * STR. BD5-11. **
222 3FG forward primer continued: Me socosm s # Organism Name A4 C2 E4 STR. BD5-12. * STR. BD5-9. * STR. CD. * STR. ES-1. *** STR. FROM LAKE GOSSENKOELLESEE. *** STR. HNSM13. *** STR. HNSS13. *** STR. HW1. ** STR. IC025. * STR. J 195. * STR. JL 134. * STR. JL 206 DSM 41755. * STR. JL 415 DSM 41754. * STR. JTB131. ** STR. JTB146. * STR. JTB148. * STR. JTB36. * STR. KN4. ** STR. N4-7. ** STR. NKB11. * STR. NKB13. * STR. NKB18. * STR. NRRLB-14911. * STR. P211. ** STR. PCE-FF ATCC 35879. *** STR. PENDANT. ** STR. RA1. ** STR. RJ. * STR. SR 119. * STR. SUR ATT. ** STR. T3. ** STR. UNIDENTIFIED BACTERIUM D. ** STR. UW 103/A31. *** STR. WSA. ** STREPTOMYCES spp. *** SULFOBACILLUS spp. *** SULFUROSPIRILLUM BARNESII 16S RIBOSOMAL RNA GENE" * SUTTONELLA INDOLOGENES ATCC 25869 (T). ** SYMBIONT OF ALVINELLA POMPEJANA. * SYMBIONT OF CRITHIDIA SP. *** SYNECHOCOCCUS SP. PCC 6301. *** TELLURIA CHITINOLYTICA STR. 20M ACM 3522 (T). * THERMOACTINOMYCES CANDIDUS. ** THERMOBISPORA BISPORA strains *** THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. *** THERMOMICROBIUM ROSEUM ATCC 27502 (T). ** THERMUS spp. * TREPONEMA SACCHAROPHILUM STR. PB ATCC 43261 (T). * TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). ** UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" ** UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" * UNCULTURED ARCHAEON 2C30 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.2.F 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. *** UNIDENTIFIED BACTERIUM 16S RRNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED BETA PROTEOBACTERIUM CLONE ACK-L5 16S RIBOSOMAL RNA * UNIDENTIFIED EUKARYOTE OM164 16S RIBOSOMAL RNA GENE" ** UNNAMED ORGANISM. *** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. ** VIBRIO spp. ** VITREOSCILLA STERCORARIA ATCC 15218 (T). * VOGESELLA INDIGOFERA ATCC 19706 (T). * XANTHOMONAS spp. ** XYLELLA FASTIDIOSA strains *** XYLOPHILUS AMPELINUS ATCC 33914 (T). ** ZOOGLOEA spp. ** 223 All identified bacteria for 3FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism Name A4 C2 E4 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" * ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). *** BACILLUS spp. *** BLASTOBACTER SP. STR. PC30.44. *** BOSEA THIOOXIDANS STR. RPPL5-VS. *** BURKHOLDERIA EN-B3. *** CLONE 2951. ** CLONE 4953. * CLONE BPC110. * CLONE ENV.OPS 12. *** CLONE GCA112. *** CLONE H1.43.F. *** CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE K20-75. *** CLONE KTK 14. * CLONE MUG6. * CLONE OPB11. *** CLONE OPB12. *** CLONE OPB34. *** CLONE OPB65. *** CLONE OPB9. *** CLONE S027. * CLONE SCALE-6. *** CLONE SJA-101. * CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. * CLONE SJA-21. ** CLONE SJA-58. *** CLONE SJA-61. ** CLONE T17. * CLONE T78. *** CLONE UC43F. *** CLONE UC51F. *** CLONE VADINCA02. *** CLONE WB004. * CLONE WCHB1-05. * CLONE WCHB1-31. ** CLONE WCHB1-43. * CLONE WCHB1-57. *** CLONE WCHB1-62. *** CLONE WCHB1-80. *** CYNOMORIUM COCCINEUM CHLOROPLAST 16S RIBOSOMAL RNA GENE" * ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** FERVIDOBACTERIUM GONDWANENSE STR. AB39 ACM 5017 (T). * HALOANAEROBACTER spp. * HALOBACTEROIDES spp. * HILDENBRANDIA OCCIDENTALIS. * HYPHOMICROBIUM M3 STR. M3 ATCC 202122. * LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LEPTONEMA ILLINI STR. 3055. *** MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). **
224 3FG reverse primer continued: Me socosms # Organism Name A4 C2 E4 MYCOPLASMA spp. *** ORENIA MARISMORTUI STR. DY-1 DSM 5156 (T). * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. *** RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** SARGASSO SEA" *** SPHINGOMONAS UG30 STR. UG30. * SPIROCHAETA spp. * SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 394. ** STR. BD3-16. *** STR. BD3-7. *** STR. NKB17. * STR. RM1. *** STR. RM17. *** STR. SP40-12. * STR. SP40-2. * STREPTOCOCCUS HYOINTESTINALIS DSM 20770 (T). * SUTTERELLA WADSWORTHENSIS strains *** THAUERA MZ1T STR. MZ1T. * UNCULTIVATED SOIL BACTERIUM CLONE S027 16S RIBOSOMAL RNA GENE" * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED GREEN NON-SULFUR BACTERIUM strains *** UNNAMED ORGANISM. *** USTILAGO HORDEI (COVERED SMUT OF BARLEY AND OATS BASIDIOMYCETE * USTILAGO MAYDIS MUCL 30488 (COVERED SMUT OF MAIZE BASIDIOMYCETE *
225 All identified bacteria for 4FG treatment replicates: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism name A2 B5 C8 ACETOBACTER spp. * ACETONEMA LONGUM STR. APO-1 DSM 6540 (T). * ACHOLEPLASMA OCULI ISM 1499. ** ACIDOMONAS METHANOLICA STR. MB 58 IMET 10945 (T). * ACIDOVORAX spp. * AFIPIA spp. ** AGROMYCES MEDIOLANUS strains ** ALICYCLOBACILLUS SP. Strains ** ALLOIOCOCCUS OTITIS NCFB 2890 (T). * AMYCOLATOPSIS ORIENTALIS SUBSP. LURIDA DSM 43187. ** ANAEROBRANCA HORIKOSHII STR. JW/YL-138 DSM 9786 (T). ** ANAEROPLASMA ABACTOCLASTICUM STR. 6-1 ATCC 27879 (T). * AQUASPIRILLUM SINUOSUM LMG 4393 (T). * ARTHROBACTER SP. STR. RC100. ** AZOARCUS INDIGENS 16S RIBOSOMAL RNA GENE" * BACILLUS spp. ** BACTERIAL SPECIES 16S RRNA GENE clones *** BACTEROIDES UREOLYTICUS ATCC 33387 (T). * BEIJERINCKIA INDICA SUBSP. INDICA ATCC 9039 (T). * BETA-PROTEOBACTERIUM 16S RIBOSOMAL RNA. * BIFIDOBACTERIUM spp. ** BORDETELLA AVIUM ATCC 35086 (T). * BREVIBACILLUS spp. ** BREVUNDIMONAS spp. ** BURKHOLDERIA spp. *** CALDOTOGA FONTANA STR. B4. ** CAMPYLOBACTER spp. * CARYOPHANON LATUM NCDO 2034. * CAULOBACTER spp. ** CELLULOMONAS spp. ** CETOBACTERIUM CETI STR. M-3333 NCFB 3026 (T). ** CHLAMYDIA spp. * CHLOROBIUM LIMICOLA strains * CITROBACTER spp. * CLAVIBACTER XYLI SUBSP. CYNODONTIS STR. CXC. ** CLONE 1_60. * CLONE 113. * CLONE 12-126. * CLONE 141. * CLONE 22. * CLONE 282. * CLONE 330. * CLONE 348. * CLONE 368. * CLONE ADRIATIC76. ** CLONE ADRIATICR16. * CLONE ASB029. * CLONE ASB031. ** CLONE BH017. ** CLONE BPC043. * CLONE BPC060. * CLONE BPC090. *** CLONE BPC094. * CLONE BPC102. * 226 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 CLONE C028. * CLONE CLONE DA115. ** CLONE CN1. ** CLONE CN3. ** CLONE DA011. ** CLONE DA015. ** CLONE DA023. * CLONE DA026. * CLONE DA032. ** CLONE DA036. ** CLONE DA066. * CLONE DA067. * CLONE DA114. * CLONE DA134. ** CLONE DA154. ** CLONE ENV.OPS 12. * CLONE ENV.OPS 8. * CLONE FB15. *** CLONE FB16. *** CLONE H1.43.F. *** CLONE JW13. * CLONE JW15. * CLONE JW23. * CLONE JW28. * CLONE JW29. ** CLONE JW6. * CLONE LBS12. * CLONE LBS25. * CLONE LBS3. ** CLONE LBS6. * CLONE LRE18. *** CLONE LRE22. * CLONE LRE25. ** CLONE LRE9. *** CLONE LRS11. * CLONE LRS13. * CLONE LRS4. * CLONE OCS146. ** CLONE ODPB-B3. * CLONE ODPB-B4. * CLONE OM156. * CLONE OM93. * CLONE RIZ1015. ** CLONE RIZ103. ** CLONE RIZ1078. ** CLONE RIZ1081. * CLONE RIZ1083. ** CLONE S125. * CLONE SAR 406. ** CLONE SAR248. * CLONE SAR324. * CLONE SJA-111. * CLONE SJA-121. ** CLONE SJA-168. * CLONE SJA-171. * CLONE SJA-176. *** 227 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 CLONE SJA-181. ** CLONE SJA-186. ** CLONE SJA-22. * CLONE SJA-47. ** CLONE SJA-87. *** CLONE SJA-9. * CLONE SVA0071. *** CLONE SVA0113. * CLONE SVA0679. ** CLONE SVA0864. *** CLONE SVA1037. * CLONE SVA1064. * CLONE SY1-44. * CLONE T19. * CLONE T20. * CLONE T25. * CLONE T33. * CLONE T35. * CLONE T37. * CLONE T41. * CLONE T65. * CLONE T70. * CLONE T73. * CLONE T79. * CLONE T90. ** CLONE T96. * CLONE T98. ** CLONE TBS13. * CLONE TBS3. *** CLONE THRIPS6.12. * CLONE TRE13. * CLONE TRE19. * CLONE TRE3. ** CLONE TRS11. * CLONE TRS2. * CLONE TRS7. ** CLONE TRS9. ** CLONE UC32F. ** CLONE WR105. ** CLONE WR108. ** CLONE WR109. ** CLONE WR1105. ** CLONE WR1109. * CLONE WR1112. ** CLONE WR1119. ** CLONE WR1120. * CLONE WR1123. ** CLONE WR1124. * CLONE WR1132. ** CLONE WR1134. * CLONE WR114. ** CLONE WR1140. ** CLONE WR1141. ** CLONE WR122. * CLONE WR128. ** CLONE WR134. ** 228 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 CLONE WR114. ** CLONE WR1140. ** CLONE WR1141. ** CLONE WR122. * CLONE WR128. ** CLONE WR134. ** CLONE WR137. ** CLONE WR144. ** CLONE WR148. ** CLONE WR151. ** CLONE WR153. ** CLONE WR159. * CLONE WR161. *** CLONE WR170. ** CLONE WR171. ** CLONE WR173. * CLONE WR177. *** CLONE WR184. ** CLONE WR191. ** CLONE WR193. ** CLONE WR198. ** CLONE WS54. * CLOSTRIDIUM spp. *** COMAMONAS ACIDOVORANS IAM 12409. * CORYNEBACTERIUM VITARUMEN NCTC 20294 (T). ** CYTOPHAGA SP. Strains ** DERMABACTER HOMINIS NCFB 2769 (T). ** DESULFOBACTERIUM spp. * DESULFOVIBRIO spp. * DESULFUROMUSA BAKII STR. GYPROP DSM 7345 (T). * EHRLICHIA BOVIS. *** ENDOSYMBIONT OF HELIOTHIS VIRESCENS TESTIS. ** ENTEROBACTER spp. * ERWINIA spp. * ERYSIPELOTHRIX RHUSIOPATHIAE STR. ALPHA-P15 ATCC 19414 (T). ** ESCHERICHIA COLI strains ** ESCHERICHIA HERMANNII. * EUBACTERIUM spp. *** FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * FIBROBACTER spp. ** FLEXIBACTER TRACTUOSUS STR. LEWIS BA-3 ATCC 23168 (T). * FRANKIA SP. Strains ** FUSIBACTER PAUCIVORANS SEBR 4211. * FUSOBACTERIUM spp. *** GAMMA PROTEOBACTERIUM N4-7 16S RIBOSOMAL RNA GENE" *** GARDNERELLA VAGINALIS ATCC 14018 (T). * GLUCONACETOBACTER spp. * GLUCONOBACTER spp. * GRAM NEG" ** HAEMOPHILUS INFLUENZAE strains *** HAFNIA ALVEI ATCC 13337 (T). * HOLOPHAGA FOETIDA STR. TMBS4 DSM 6591 (T). * HYDROGENOPHAGA spp. * IFO 15614. ** IFO 15706. ** IFO 15777. ** 229 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 KINEOSPORIA spp. * LACTOBACILLUS CATENAFORMIS STR. 1871 ATCC 25536 (T). *** LEPTOTHRIX DISCOPHORA STR. SS-1 ATCC 43182 (T). *** LEUCOBACTER KOMAGATAE. *** LISTONELLA ANGUILLARUM strains * MAGNETOBACTERIUM BAVARICUM. * MARINE PSYCHROPHILE IC025 16S RIBOSOMAL RNA GENE" * MATSUEBACTER CHITOSANOTABIDUS. *** METHYLOBACILLUS spp. *** METHYLOBACTERIUM spp. ** METHYLOC YSTIS spp. ** METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). ** METHYLOSINUS spp. * MICROBACTERIUM spp. *** MICROBISPORA BISPORA RIBOSOMAL RNA ** MICROCOCCUS spp. ** MICROCYSTIS spp. ** MICROSCILLA SERICEA STR. SIO-7 ATCC 23182. * MOORELLA THERMOACETICA ATCC 39073. * MOUNT COOT-THA REGION (BRISBANE" ** MYCOBACTERIUM ELEPHANTIS. *** MYCOPLASMA spp. *** NITROSOMONAS EUROPAEA strains *** NITROSOSPIRA spp. ** OXALOPHAGUS OXALICUS STR. ALT OX1 DSM 5503 (T). ** PAENIBACILLUS spp. ** PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. * PELOBACTER ACIDIGALLICI STR. MAGA12 DSM 2377 (T). * PHLOMOBACTER FRAGARIAE 16S RRNA GENE" * PHOTOBACTERIUM DAMSELA SUBSP. DAMSELA NCIMB 2184. * PLANOCOCCUS spp. * PREVOTELLA BUCCALIS ATCC 35310 (T). * PROTEUS VULGARIS IFAM 1731. * PSEUDOMONAS spp. *** PSYCHROSERPENS BURTONENSIS ACAM strains * RALSTONIA spp. ** RATHAYIBACTER TOXICUS STR. CS14 JCM 9669 (T). * RHODOBACTER spp. ** ROSEOBACTER MED6 STR. MED6. ** RUBRIVIVAX GELATINOSUS STR. ATH 2.2.1 ATCC 17011 (T). ** SALMONELLA spp. ** SEQUENCE 1 FROM PATENT US 5508193. * SHIGELLA spp. * SPHAEROTILUS IF4, IF5 STR. IF4, IF5. *** SPHINGOBACTERIUM SPIRITIVORUM ATCC 33861 (T). * SPIRILLUM VOLUTANS ATCC 19554 (T). *** STAPHYLOCOCCUS spp. ** STENOTROPHOMONAS spp. ** STR. 48.H. * STR. ACE. ** STR. ALV. * STR. AS2965. ** STR. AS2985. ** STR. AS2987. ** STR. AS3080. ** STR. AS3088. ** 230 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 STR. AS3090. ** STR. AS3142. ** STR. AS3380. ** STR. AS3641. ** STR. B1. * STR. B100. * STR. B-3060. * STR. BD1-1. *** STR. BD2-3. ** STR. BD2-4. * STR. BD3-7. * STR. BD4-10. * STR. BD4-12. * STR. BD5-11. * STR. ES-1. *** STR. FROM LAKE GOSSENKOELLESEE. ** STR. HNSM13. * STR. HNSS13. * STR. IC025. * STR. JTB146. * STR. JTB36. * STR. KN4. * STR. LSV21. * STR. N4-7. *** STR. NKB11. * STR. NKB13. * STR. NKB14. * STR. NKB15. * STR. NKB16. * STR. NRRLB-14851. * STR. NRRLB-14911. * STR. P211. * STR. PCE-FF ATCC 35879. *** STR. PENDANT. ** STR. RA1. * STR. SR 119. * STR. T25. * STR. T41. * STR. UW 103/A31. * STREPTOMYCES spp. ** SULFOBACILLUS THERMOSULFIDOOXIDANS. ** SULFUROSPIRILLUM BARNESII 16S RIBOSOMAL RNA GENE" * SYMBIONT OF ALVINELLA POMPEJANA. * SYMBIONT OF CRITHIDIA SP. *** SYNECHOCOCCUS SP. PCC 6301. ** SYNTROPHOBACTER WOLINII. * THERMOACTINOMYCES CANDIDUS. ** THERMOBISPORA BISPORA strains ** THERMODESULFOVIBRIO TGE-P1 STR. TGE-P1. * THERMOMICROBIUM ROSEUM ATCC 27502 (T). ** THERMOMONOSPORA CHROMOGENA ATCC 43196 (T). * THERMUS spp. ** TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). * UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" * UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" * UNCULTURED ARCHAEON 2C30 16S RIBOSOMAL RNA GENE" * 231 4FG forward primer continued: Me socosms # Organism name A2 B5 C8 UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM 16S RIBOSOMAL RNA. ** UNIDENTIFIED BACTERIUM 16S RRNA GENE" ** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM CLONE SAR248 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM CLONE SAR324 16S RIBOSOMAL RNA GENE" * UNNAMED ORGANISM. *** VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. * VIBRIO spp. * XANTHOMONAS spp. ** XYLELLA FASTIDIOSA strains *** XYLOPHILUS AMPELINUS ATCC 33914 (T). * ZOOGLOEA SP. 16S RIBOSOMAL RNA GENE" **
All identified bacteria for 4FG treatment replicates: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Mesocosm # Organism Name A2 B5 C8 ACCIPITER SUPERCILIOSUS 12S MITOCHONDRIAL RIBOSOMAL RNA" * ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). *** AONIDIELLA AURANTII (CALIFORNIA CITRUS SCALE INSECT; CAL. RED * BACILLUS spp. *** BLASTOBACTER SP. STR. PC30.44. * BOSEA THIOOXIDANS STR. RPPL5-VS. * BOTHROMESOSTOMA SP. * BURKHOLDERIA EN-B3. *** CLONE 1404-40. * CLONE 2951. ** CLONE 52. * CLONE ACE-19. * CLONE ENV.OPS 12. *** CLONE GCA112. ** CLONE H1.43.F. *** CLONE HSTPL11. * CLONE HSTPL20. * CLONE HSTPL53. * CLONE HSTPL65. * CLONE HSTPL69. *** CLONE HSTPL86. *** CLONE M37. * CLONE MUG6. ** CLONE OPB11. *** CLONE OPB12. *** CLONE OPB34. *** CLONE OPB65. *** CLONE OPB9. *** CLONE RB29. ** CLONE SCALE-6. *** CLONE SJA-101. ** CLONE SJA-108. *** CLONE SJA-131. *** CLONE SJA-15. *** CLONE SJA-170. *** CLONE SJA-21. ** CLONE SJA-58. *** CLONE SJA-61. * CLONE SJA-68. * CLONE T17. * CLONE T78. *** CLONE TM6. * CLONE UC43F. *** CLONE UC51F. *** CLONE VADINCA02. *** CLONE WB004. * 232 4FG reverse primer continued: Me socosm s # Organism name A2 B5 C8 CLONE WCHB1-05. * CLONE WCHB1-31. * CLONE WCHB1-57. *** CLONE WCHB1-62. *** CLONE WCHB1-80. *** CYNOMORIUM COCCINEUM CHLOROPLAST 16S RIBOSOMAL RNA GENE" * DESULFORHOPALUS LSV20 STR. LSV20. ** ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). *** ENVIRONMENTAL CLONE OCS162 SMALL SUBUNIT RIBOSOMAL RNA GENE" * FERVIDOBACTERIUM NODOSUM STR. RT 17-B1 ATCC 35602 (T). * GEMMATA OBSCURIGLOBUS strains * GEOBACTER ""HYDROGENOPHILUS""."" * HALOANAEROBACTER spp. ** HALOANAEROBIUM PRAEVALENS ATCC 33744 (T). * HALOBACTEROIDES spp. ** HILDENBRANDIA OCCIDENTALIS. * KOCKOVAELLA THAILANDICA. * LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). *** LEPTONEMA ILLINI STR. 3055. *** MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). ** MOLGULA spp. * MOUNT COOT-THA REGION (BRISBANE" * MYCOPLASMA spp. * NAEGLERIA spp. * OEDOGONIUM CARDIACUM. * ORENIA MARISMORTUI STR. DY-1 DSM 5156 (T). * PALMARIA PALMATA (EDIBLE? RED ALGA) -- CHLOROPLAST. *** PIRELLULA spp. * PLANCTOMYCES spp. * PYURA MIRABILIS. * RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). *** RHODOCOCCUS YT-2 STR. YT-2. ** SARGASSO SEA" *** SPHINGOMONAS UG30 STR. UG30. * SPIROCHAETA spp. * SPIRODACTYLON AUREUM 18S RIBOSOMAL RNA GENE" * SPIROPLASMA spp. * SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). *** STR. 292. * STR. 394. ** STR. 608. * STR. BD3-16. *** STR. BD3-7. *** STR. NKB17. * STR. RM1. * STR. RM17. * STR. SP40-12. * STR. SP5-18. ** STREPTOCOCCUS HYOINTESTINALIS DSM 20770 (T). ** SUTTERELLA WADSWORTHENSIS strains *** SYNTROPHOBACTER SP. STR. TSUA1. * TREPONEMA spp. * UNCLASSIFIED ORGANISM (ACIDOBACTERIUM CAPSULATUM PHYLUM) 16S RRNA * UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" *** UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. *** UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" * UNIDENTIFIED EUBACTERIUM RB29 16S RIBOSOMAL RNA GENE" ** UNIDENTIFIED GREEN NON-SULFUR BACTERIUM strains *** UNNAMED ORGANISM. ** VIBRIO 2P44 ** 233 All identified bacteria for original sediment: forward primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Organism Name LISTONELLA ANGUILLARUM HI 11446. MATSUEBACTER CHITOSANOTABIDUS. METHYLOBACILLUS FLAGELLATUM STR. KT1. METHYLOCYSTIS ECHINOIDES STR. 2. METHYLOPHILUS METHYLOTROPHUS STR. AS1 ATCC 53528 (T). MICROBACTERIUM spp. MOBILUNCUS MULIERIS STR. SV 17J ATCC 35243 (T). MOUNT COOT-THA REGION (BRISBANE" MYCOBACTERIUM spp. NITROSOMONAS EUROPAEA STR. M103. NITROSOSPIRA MULTIFORMIS strains PAENIBACILLUS ALVEI strains PARACRAUROCOCCUS RUBER strains PHLOMOBACTER FRAGARIAE 16S RRNA GENE" PHOTOBACTERIUM PROFUNDUM STR. DSJ4. PORPHYRA PURPUREA (ALGA) -- CHLOROPLAST PROTEUS VULGARIS IFAM 1731. PSEUDOMONAS spp. RALSTONIA spp. RHODOBACTER spp. RHODOFERAX ANTARCTICUS STR. ANT.BR. ROSEOBACTER MED6 STR. MED6. SALMONELLA spp. SEQUENCE 1 FROM PATENT US 5508193. SHEWANELLA GELIDIMARINA strains SHIGELLA spp. SPIRILLUM VOLUTANS ATCC 19554 (T). STAPHYLOCOCCUS KLOOSII strains STENOTROPHOMONAS spp. STR. 400M ATT. STR. ACE. STR. B100. STR. BD1-1. STR. BD5-11. STR. BD5-12. STR. ES-1. STR. HW1. STR. NKB18. STR. PCE-FF ATCC 35879. STR. PENDANT. STR. RA1. STR. SUR ATT. STR. T3. STR. UW 103/A31. STR. WSA. SUTTONELLA INDOLOGENES ATCC 25869 (T). SYMBIONT OF CRITHIDIA SP. SYNECHOCOCCUS SP. PCC 6301. THIOBACILLUS BAREGENSIS. Strains TYPE 0803 FILAMENTOUS BACTERIUM 16S RRNA GENE (STRAIN BEN04B). UNCULTIVATED SOIL BACTERIUM CLONE C028 16S RIBOSOMAL RNA GENE" UNCULTIVATED SOIL BACTERIUM CLONE S125 16S RIBOSOMAL RNA GENE" UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNNAMED ORGANISM. UNNAMED ORGANISM. UNNAMED ORGANISM. UNNAMED ORGANISM. VARIOVORAX UNCULTURED PROTEOBACTERIUM OCS98. VIBRIO spp. XANTHOMONAS spp. XYLELLA FASTIDIOSA strains XYLOPHILUS AMPELINUS ATCC 33914 (T). ZOOGLOEA SP. strains
234 All identified bacteria for original sediment: reverse primer * represents bacteria present in mesocosm Genera known to contain denitrifiers from Zumft (1997) Organism Name ACETOHALOBIUM ARABATICUM STR. Z-7288 DSM 5501 (T). BACILLUS TIPCHIRALIS. BLASTOBACTER SP. STR. PC30.44. BOSEA THIOOXIDANS STR. RPPL5-VS. BURKHOLDERIA EN-B3. CLONE 1404-40. CLONE 52. CLONE BPC110. CLONE ENV.OPS 12. CLONE H1.43.F. CLONE HSTPL11. CLONE HSTPL20. CLONE HSTPL53. CLONE HSTPL65. CLONE HSTPL69. CLONE HSTPL86. CLONE M37. CLONE OPB11. CLONE OPB12. CLONE OPB34. CLONE OPB65. CLONE OPB9. CLONE SJA-101. CLONE SJA-108. CLONE SJA-131. CLONE SJA-15. CLONE SJA-58. CLONE SJA-68. CLONE T78. CLONE VADINCA02. CLONE WCHB1-05. CLONE WCHB1-57. CLONE WCHB1-62. CLONE WCHB1-80. CYNOMORIUM COCCINEUM CHLOROPLAST 16S RIBOSOMAL RNA GENE" DESULFORHOPALUS LSV20 STR. LSV20. ENDOSYMBIONT OF MEALYBUG (DYSMICOCCUS NEOBRIVIPES). G.OBSCURIGLOBUS 16S RRNA GENE. GEMMATA OBSCURIGLOBUS strains GEOBACTER ""HYDROGENOPHILUS""."" LAWSONIA INTRACELLULARIS STR. 1482/89 NCTC 12656 (T). LEPTONEMA ILLINI STR. 3055. MICROBACTERIUM HALOPHILUM STR. N 76 IFO 16062 (T). MOUNT COOT-THA REGION (BRISBANE" MYCOPLASMA spp. RHODOBACTER CAPSULATUS STR. ATH 2.3.1 ATCC 11166 (T). RHODOCOCCUS YT-2 STR. YT-2. SPHINGOMONAS UG30 STR. UG30. SPIROCHAETA spp. SPIROPLASMA spp. SPOROHALOBACTER LORTETII STR. MD-2 ATCC 35059 (T). STR. 292. STR. BD3-16. STR. BD3-7. STR. RM1. STR. RM17. STR. SP5-17. SUTTERELLA WADSWORTHENSIS strains TREPONEMA UNCULTURED TREPONEMA CLONE RFS64. UNCULTURED EUBACTERIUM H1.43.F 16S RIBOSOMAL RNA GENE" UNIDENTIFIED BACTERIUM DNA FOR 16S RIBOSOMAL RNA. UNIDENTIFIED EUBACTERIUM FROM THE AMAZON 16S RIBOSOMAL RNA GENE" UNIDENTIFIED GREEN NON-SULFUR BACTERIUM OPB strains UNNAMED ORGANISM. UNNAMED ORGANISM. UNNAMED ORGANISM. VIBRIO 2P44 strains 235
Number of TRF peaks per treatment: Enzyme Enzyme Enzyme TreatmentMesocosm Hha1 Total Msp 1 Total Rsa 1 Total # forward reverse forward reverse forward reverse All Total Controls B7 152 97 249 137 100 237 166 75 241 727 D7 94 65 159 100 52 152 37 72 109 420 F2 69 46 115 119 34 153 131 74 205 473 avg 105.00 69.33 174.33 118.67 62.00 180.67 111.33 73.67 185.00 540.00 st dev 42.58 25.77 68.30 18.50 34.12 48.79 66.71 1.53 68.23 164.10 st error 25.05 15.16 40.18 10.88 20.07 28.70 39.24 0.90 40.14 96.53 Tussock A1 141 108 249 16 69 85 150 52 202 536 C6 120 90 210 97 49 146 128 39 167 523 E5 70 57 127 138 59 197 145 55 200 524 avg 110.33 85.00 195.33 83.67 59.00 142.67 141.00 48.67 189.67 527.67 st dev 36.47 25.87 62.31 62.08 10.00 56.07 11.53 8.50 19.66 7.23 st error 21.46 15.21 36.65 36.52 5.88 32.98 6.78 5.00 11.56 4.26 Reed C3 135 73 208 108 51 159 130 48 178 545 E2 89 56 145 91 66 157 40 56 96 398 avg 112 64.5 176.5 99.5 58.5 158 85 52 137 471.5 st dev 23 8.5 31.5 8.5 7.5 1 45 4 41 73.5 st error 16.43 6.07 22.50 6.07 5.36 0.71 32.14 2.86 29.29 52.50 Fac ann A3 129 93 222 99 57 156 130 51 181 559 B1 96 64 160 101 62 163 114 45 159 482 C1 155 80 235 107 56 163 129 43 172 570 avg 126.67 79.00 205.67 102.33 58.33 160.67 124.33 46.33 170.67 537.00 st dev 29.57 14.53 40.08 4.16 3.21 4.04 8.96 4.16 11.06 47.95 st error 17.39 8.54 23.58 2.45 1.89 2.38 5.27 2.45 6.51 28.20 Ob ann C5 84 66 150 107 51 158 134 60 194 502 E1 134 46 180 127 56 183 160 58 218 581 F3 74 31 105 122 67 189 151 72 223 517 avg 97.33 47.67 145.00 118.67 58.00 176.67 148.33 63.33 211.67 533.33 st dev 32.15 17.56 37.75 10.41 8.19 16.44 13.20 7.57 15.50 41.96 st error 18.91 10.33 22.21 6.12 4.81 9.67 7.77 4.45 9.12 24.68 2FG A7 180 119 299 127 73 200 149 78 227 726 D1 154 103 257 149 79 228 119 50 169 654 F1 66 54 120 108 58 166 141 81 222 508 avg 133.33 92.00 225.33 128.00 70.00 198.00 136.33 69.67 206.00 629.33 st dev 59.74 33.87 93.61 20.52 10.82 31.05 15.53 17.10 32.14 111.07 st error 35.14 19.92 55.06 12.07 6.36 18.26 9.14 10.06 18.91 65.34 3FG A4 122 89 211 115 64 179 129 60 189 579 C2 89 78 167 125 53 178 119 63 182 527 E4 127 71 198 120 50 170 168 66 234 602 avg 112.67 79.33 192.00 120.00 55.67 175.67 138.67 63.00 201.67 569.33 st dev 20.65 9.07 22.61 5.00 7.37 4.93 25.89 3.00 28.22 38.42 st error 12.15 5.34 13.30 2.94 4.34 2.90 15.23 1.76 16.60 22.60 4FG A2 135 91 226 152 76 228 13 93 106 560 B5 110 84 194 85 53 138 26 51 77 409 C8 96 73 169 116 46 162 153 64 217 548 avg 113.67 82.67 196.33 117.67 58.33 176.00 64.00 69.33 133.33 505.67 st dev 19.76 9.07 28.57 33.53 15.70 46.60 77.35 21.50 73.89 83.93 st error 11.62 5.34 16.81 19.72 9.23 27.41 45.50 12.65 43.47 49.37 original sediment 109.00 61.00 170.00 138.00 90.00 228.00 71.00 53.00 124.00 522
236 Electropherograms for original sediment and one control replicate, Hha1 enzyme, forward primer. All peaks are not labelled.
Original Sediment
Control intensity Flourescence
237 Electropherograms for one replicate per macrophyte functional group, Hha1 enzyme, forward primer. All peaks are not labelled.
Tussock k
Reed
intensity
Facultative
Flourescence annual
Obligate annual
238 Electropherograms for one replicate per macrophyte functional group diversity treatment, Hha1 enzyme, forward primer. All peaks are not labelled.
2FG
3FG intensity Flourescence
4FG
239 Detailed TRFLP Information
Sediment samples for bacterial molecular analysis were collected in September 2002 at macrophyte peak biomass from four randomly selected areas within each mesocosm. Soil cores were collected to a depth of 10 cm, bulked in airtight plastic bags and immediately stored at 4oC. Within 48 hrs of collection, ~40 g of subsample was placed into plastic scintillation vials and frozen using liquid N to prevent bacterial cell wall lysing. The vials were then stored at –20oC until DNA extraction. Cross contamination of bacteria between samples was minimized by washing and sterilizing the sediment sampler between sample extractions. Genomic DNA (gDNA) was extracted from the samples using the MoBio Soil DNA isolation kit (MoBio Laboratories, Solana Beach, CA) following the stated protocol with slight modifications for DNA extraction optimization. Modifications included: Step #1 adding between 0.5-1.0g of sediment into the bead solution tubes along with 0.3g of 0.1mm zirconia/silicon beads; Step#7 increasing centrifuge time to 1.0 minute; Step #11 increasing centrifuge time to 1.5 minutes; Step #17 increasing centrifuge time to 2.0 minutes; Step #20 increasing centrifuge time to 1.0 minute; and Step #19, increasing the volume of Solution S5 added to the filter to 56ul and then letting this sit for 1.0 minute. After extraction, the samples were immediately stored at –20oC. The bacterial gDNA was then quantified using 100ul Pico Green, 98ul TE buffer and 2ul gDNA per sample and read on a fluorometer (Bioassay Reader). Samples were adjusted to 2ng/ul using LSTE buffer. These samples were then polymerase chain reaction (PCR) amplified using 11F forward and 907R reverse tagged primers with the sequences: 11F : 5’- GTTTGATCMTG GCTCAG-3’; 907R: 5’-CCGTCAATTCMTTTRAGTTT-3’ (M=A or C R=A or G). Each 200ul PCR reaction contained 1mM MgCl2, 1X PCR reaction buffer, 0.2mM PCR nucleotide mix, 0.45ul bovine serum albumin, 3% DMSO, 0.5uM DNA primers, 0.025 U HotStarTaq polymerase (Qiagen), and 0.95ng DNA template. Initial denaturation on the reaction mixtures took place at 95oC for 15 minutes and amplification reactions were performed with 30 cycles of denaturation (45sec, 94oC), primer annealing (1 min., 52.5oC), and primer extention (2 min., 72oC) with a final extension step (10 min., 72oC). The PCR took place in a PTC-100 Programmable Thermal Controller thermocycler (MJ Research Inc.). Amplified DNA was verified using gel electrophoresis with 2ul DNA sample in 1% agarose in 1X TAE buffer. The amplified gDNA were then cleaned using Millipore Microcon PCR filter units with slight modifications. For each sample, all of the cleaned PCR product was pipetted into a filter unit and nuclease free (NF) water was added to a total volume of 500ul. These filter units were then centrifuged at 1000 rpm for 10 minutes. With the filter still wet, another 400 ul of NF water was added and then centrifuged at the same speed for 17minutes. The filter unit was then placed into a new microcentrifuge tube and 56ul of LSTE (1mM Tris, 0.1 mM EDTA, pH 8) was added and the product instructions were then followed. The cleaned PCR product was then quantified using the same Pico Green method mentioned above for gDNA quantification. Digestion solutions were then set up for the cleaned PCR samples with three enzymes Hha1, Msp 1 and Rsa 1. Each sample was adjusted to a final concentration of 300 ng/20 ul digest along with 5:1 enzyme solution mix and addition of other substances (neb #1, 2, or 4; BSA, water) according to the manufacture’s directions. 240 Digestion of samples took place in the same thermocylcer described above with the program: 37oC (3 hrs), 75oC (20 minutes) and 4oC (infinity). These samples were then stored at –20oC and transported to the Ohio State Plant Genomics Laboratory where they were analyzed for terminal restriction lengths using an ABI 3700 DNA Analyzer. Optimal base pair detection procedure was achieved using a positive control Xanthomonas campestris pv. Vesicatoria strain #110c with known basepair lengths of 212 bp (Hha1,11F), 495 bp (Msp1, 11F), 478 bp (Rsa1, 11F), 547,549 bp (Hha1, 907R), 243,245 bp (Msp1, 907R) and 34,35 (Rsa1, 907R). Best results were obtained using a double injection of 0.5ul sample at 2000 volts for 100 seconds. The internal lane size standard GeneScan -500 LIZ (Applied Biosystems) was used with labeled fragments of 35, 50, 75, 100, 139, 150, 160, 200, 250, 300, 340, 350, 400, 450, 490, and 500 bases. Peak area and base pair data and electropherograms were obtained using the computer software Genotyper 3.7 (ABI Prism). All peaks with base pairs identical to the standards were removed in order to reduce standard inclusion in sample analysis. All peaks were adjusted to a fluorescent intensity height of 100 to remove background noise and named peaks occurred within the range of the standard between 35 and 500 base pairs.
241
APPENDIX C MESOCOSM DESIGN FOR STUDY #1 AND STUDY #2
242
Mesocosm Experimental Design, Study #1 A B C D E F Macrophyte Functional Groups: 1,2 1 All 1,3 5 5 5 5 1 = Matrix- Clonal Dominant (perennials) 2 = Interstitial- Tussock (perennials) 2 C 1 1,4 All All 1,3 3 = Interstitial- Reed (perennials) 4,5 4 = Ruderals- Faculative Annual 5 = Ruderals- Obligate Annual 4 All 1 3 4 4 3 all = 1,2,3,4,5 c = controls 4 3 2 All 1 1,2 2,3 3,4 4,5
1,2 2,4 2,3 5 2 3 2,3 4,5 5 4 N
6 c 2 1,3 3 4 5 4,5
1,2 7 All All 5 1 2 3,5
8 2,3 2 C 5 1,3 2,3 5 5 5
9 5 2,5 5 C 2,5 4
10 c 1,2 1 1 3 1
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Mesocosm Experimental Design, Study #2
A B C D E F Macrophyte Functional Groups: 1 2 1,2 4 4 1 3,4 1 = Ruderals- Obligate Annual (Bidens cernua, Eleocharis obtusa) 2 = Interstitial- Tussock (perennials) (Iris versicolor, Acorus calamus) 2,3 3 = Interstitial- Reed (perennials) (Juncus canadensis, Juncus effusus) all 2 4 3 C 2 4 4 = Ruderals- Faculative Annual (Mimulus ringens, Lycopus americanus) all = 1,2,3,4 3 4 3 3 C 2 1 c = controls
1,2 1,2 2 3 1,3 1 4 4 4 3 N
5 1,3 all 1 3 2 1,2 4
all 4 2 1,4 1,3 1 6 4
7 1,3 C 1,3 C 1 C
all 8 4 all all C 3
244