Nitrifiers and their contribution to oxygen consumption

in Lake Erie

A dissertation submitted to

Kent State University in partial

fulfillment of the requirements for the

Degree of Doctor of Philosophy

By

Curtis Clevinger

November 2013

Dissertation written by

Curtis C. Clevinger

B.A., Hiram College, 1993

M.S., University of Texas at Austin, 1999

Ph.D, Kent State University, 2013

Approved by:

Darren L. Bade Darren L. Bade. Chair Doctoral Dissertation Committee

Members Doctoral Dissertation Committee

Laura G. Leff Laura G. Leff

Helen Piontkivska Helen Piontkivska

Joseph Ortiz Joseph Ortiz

Mietek Jaroniec Mietek Jaroniec

Accepted by:

Laura G. Leff Chair, Department of Biological Sciences

Janis H. Crother Dean, College of Arts and Sciences

ii

Table of Contents

LIST OF FIGURES------v

LIST OF TABLES------vii

DEDICATION------x

ACKNOWLEDGEMENTS------x

CHAPTER 1: General introduction------1-31

Nitrification------1

Hypoxia ------7

Study System ------9

Lake Erie History: Hypoxia and the link to phosphorus -- 11

Post GLWQA------13

Hypothesis------15

Research Question------15

Works Cited------17

CHAPTER 2: Ammonia oxidizing bacteria and archaea abundance and distribution in Lake Erie------32-68

Abstract------33

Introduction------35

iii

Materials and Methods------38

Results------43

Discussion------47

Works Cited------53

CHAPTER 3: Nitrification and oxygen use due to nitrification in the water column and sediments of Lake Erie------69-122

Abstract------70

Introduction------72

Materials and Methods------74

Results------82

Discussion------89

Works Cited------100

CHAPTER 4: Conclusions------123-134

iv

LIST OF FIGURES

CHAPTER 1: General introduction

Figure 1: Bathymetry of Lake Erie and Lake St. Claire-- 30

Figure 2: Lake Erie Stratification------31

CHAPTER 2: Ammonia oxidizing bacteria and archaea abundance and distribution in Lake Erie

Figure 3: Lake Erie study sample site------64

Figure 4: Total nitrifiers and AOA to AOB ratio in the

water column of Lake Erie------65

Figure 5: Total nitrifiers and AOA to AOB ratio in the

sediments of Lake Erie------66

Figure 6: Total nitrifiers in the epilimnion and

hypolimnion sites that had repeated temporal sampling-- 67

Figure 7: Relationship between total nitrifiers in the

epilimnion and hypolimnion and oxygen used due to

nitrification ------68

v

CHAPTER 3: Nitrification and oxygen use due to nitrification in the water column and sediments of Lake Erie

Figure 8: Oxygen consumption rate and oxygen

consumed due to nitrification in the hypolimnion of a

longitudinal transect------116

Figure 9: Respiration rate and percentage of total

oxygen use due to nitrification in the hypolimnion------117

Figure 10: Oxygen consumption rate and oxygen

consumed due to nitrification in the epilimnion of a

longitudinal transect------118

Figure 11: Respiration rate and percentage of total

oxygen use due to nitrification in the epilimnion------119

Figure 12. Total oxygen use by Nitrosomonas europaea

cells in artificial lake water------120

Figure 13: Oxygen use by Nitrobacter winogradskyi

cells in artificial lake water------121

Figure 14: The effect of additional nitrifiers on

epilimnion nitrification rates------122

vi

LIST OF TABLES

CHAPTER 1: General introduction

Table 1: Reactions involved in the oxidation of

ammonia to nitrate------28

Table 2: GPS locations of study sample site------29

CHAPTER 2: Ammonia oxidizing bacteria and archaea abundance and distribution in Lake Erie

Table 3. Sampling regime in Lake Erie 2008-2010. ----- 61

Table 4: Pearson correlation coefficients between total

nitrifiers, environmental variables and nitrification rates

in the epilimnion and hypolimnion------62

Table 5: Totals nitrifiers in the sediments with repeated

sampling at selected sites in Lake Erie------63

CHAPTER 3: Nitrification and oxygen use due to nitrification in the water column and sediments of Lake Erie

Table 6: Rate of oxygen consumption, SD, and % of

oxygen use due to nitrification in hypolimnion samples

from Lake Erie 2009------107

vii

Table 7: Rate of oxygen consumption, SD, and % of oxygen use due to nitrification in epilimnion samples from Lake Erie 2009------108

Table 8: Correlations between measured environmental variables, total oxygen consumption, nitrification rate, and % of oxygen use due to nitrification in the hypolimnion------109

Table 9: Correlations between measured environmental variables, total oxygen consumption, nitrification rate, and % of oxygen use due to nitrification in the epilimnion------110

Table 10: Correlations between measured environmental variables, total oxygen consumption, nitrification rate, and % of oxygen use due to nitrification in the water column------111

Table 11: Rate of oxygen consumption, SD, and % of oxygen use due to nitrification in sediment slurries from

Lake Erie 2009------112

Table 12: Rate of oxygen consumption, SD, %of oxygen use due to nitrification in intact sediments from

viii

Lake Erie 2009. ------113

Table 13: Oxygen consumption due to ammonia oxidation and nitrite oxidation in sediment slurry samples from Lake Erie------114

Table 14: Oxygen consumption due to ammonia oxidation and nitrite oxidation in water column samples from Lake Erie. ------115

ix

Dedication: To family and friends who believed in me.

Acknowledgements:

I wish to acknowledge my funding sources: NSF, Ohio Sea Grant R/ER082 and

Kent State Graduate Student Senate. My committee members, Darren Bade, Robert

T.Heath, Laura Leff, Helen Piontkivska, and Joseph Ortiz have been invaluable resources in this great journey. I also thank Heather Kirkpatrick, Josh Smith, Jennifer Clevinger,

Moumita Moitra, numerous undergraduate assistants, the captains and crews of RV Lake

Guardian, RV Erie Monitor, and CCG Limnos for their laboratory and field assistance.

In addition I thank many of my fellow graduate students from the Bade lab, L.Leff lab,

Mou lab, and Blackwood lab for their moral and technical support.

x

CHAPTER 1

Hypothesis, objectives and general introduction

Nitrification

Nitrification is the oxidization of ammonium to nitrite and nitrate in a process that consumes oxygen and generates a small amount of energy that organisms can use to fix inorganic carbon. Nitrification yields a small amount of energy, produces nitrate, and consumes oxygen (2 moles of oxygen per mole of ammonium). This is the basis of my measurements of nitrification rates later in this paper by measuring the consumption of oxygen. Nitrification is a two-step process. First ammonia is oxidized to nitrite by ammonia oxidizing bacteria (AOB) or by ammonia oxidizing archaea (AOA):

- + NH3 +3/2O2  NO2 + H + H2O

And then to nitrate by nitrite oxidizing bacteria (NOB):

- - NO2 +1/2 O2 NO3

The classification of nitrifiers differs depending on whether a traditional view or a more modern molecular viewpoint is used. Traditionally, nitrifying bacteria have been lumped together into one group, the family Nitrobacteriaceae. Further divisions were based on the ability to oxidize ammonia or nitrite, and morphological features such as cell size, shape and arrangements of membranes (Watson et al. 1989). This arrangement is contradictory to the more recent molecular phylogenetics based primarily on 16s rRNA and the differences in the key enzyme systems involved (Purkhold et al. 2000).

1 2

Nitrifiers, with the exception of Nitrospina and Nitrospira, which are distantly related to methane oxidizing bacteria, are related to photoautotrophs. There were several independent originations of nitrifiers by conversion from phototrophs to chemolithotrophs with the retention of the general structural features such as intracytoplasmic membrane system (Teske et al. 1994, Koops and Moller 1992).

Currently there are two monophyletic groups of the ammonia oxidizers based upon 16s rRNA and amoA sequencing. One group is within the Gamma division of the

Proteobacteria, and is related to methane oxidizing bacteria. The other group is within the Beta division of the Proteobacteria and is related to iron oxidizers (Bock and Wagner

2006). Nitrite oxidizers are in the Gamma (Nitrococcus), Epilson (Nitrospina), and

Alpha (Nitrospira) subclasses of Proteobacteria. The Nitrospira is in its own bacterial phylum (Brock and Wagner 2006). Archaeal representatives of nitrite oxidizers have not been identified, but the search for homologs of genes involved in nitrite oxidation/reduction in Archaea is ongoing (for example see Bartossek et al. 2010).

Ammonia oxidizers are lithoautrophic organisms that fix carbon dioxide using energy obtained from the oxidation of ammonia to nitrite. Ammonia, not ammonium, is the substrate for oxidation. Ammonia is first oxidized to hydroxylamine by membrane bound enzyme ammonia monooxygenase (AMO). This enzyme is also capable of oxidizing other non-growth supporting apolar substances such as methane, carbon monoxide, and some hydrocarbons. The initial oxidation of ammonia is an endergonic reaction (Table 1: rxn 1) with the oxygen source coming from dissolved oxygen. The

3 coupling of this reaction with the reduction of oxygen (Table 1: rxn 2) gives the required energy for the total reaction (Table 1: rxn 3). Ammonia monooxygenase is encoded by the genes amoA (presumed to contain the active site), amoB, and amoC and are co- transcribed. In some ammonia oxidizers, such as Nitrosomonas europaea, these genes can be duplicated and are either identical or very similar. Evidence suggests that AMO is a copper containing monooxygenase. The proteins in a typical Nitrosomonas europaea cell contains approximately 6% AMOA and AMOB. More AMOA and AMOB are found under higher ammonia concentrations than under lower ammonia concentrations, but the amount of AMO does not correlate with ammonia oxidizing activity.

Hydroxylamine is then oxidized to nitrite by hydroxylamine oxidoreductase, HAO,

(Table 1: rxn 4) with the oxygen coming from water. Hydroxylamine oxidoreductase is a multiple heme enzyme composed of three subunits located in the periplasmic space.

Each subunit is composed of 8 heme groups. Again there is duplication of the genes encoding this enzyme. All copies of these genes are either identical or very similar, suggesting a recent duplication event and not a lateral gene transfer. With the coupling of the oxidation of hydroxylamine to the reduction of oxygen (Table 1: rxn 5), there is a total electron yield of four electrons (Table 1: rxn 6), but two are consumed (Table 1: rxn

2) and two are fed into the respiratory chain (Table 1: rxn 5) to generate proton motive force and a ΔG= -235kj mol-1 (Table 1: rxn 7 Bock and Wagner 2006).

Nitrite oxidation has a much lower energy yield, ΔG =-54 kj mol-1, than ammonia oxidation. Although nitrite oxidation is an energy poor mechanism, the accumulation of nitrite is rare in aerobic systems testifying to the ubiquity of nitrite oxidizers in a wide

4 range of environmental conditions (Ward et al. 2011). Nitrite oxidation is initiated by

the enzyme nitrite-oxidoreductase (NO2-OR). This is a membrane-associated protein that is arranged in a crystalline structure and is made of two subunits. The sequences of NO2-

OR in nitrite oxidizers show similarities to nitrate reductases of organotrophic bacteria.

The actual oxidation of nitrite is endergonic (Table 1: rxn 8) with the oxygen source from water, but when coupled with the reduction of oxygen (Table 1: rxn 9) becomes exergonic (Table 1: rxn 10 Bock and Wagner 2006).

Nitrification has been shown to have a significant effect on oxygen consumption in several systems. A study by Polak (2004) in the Wloclawek Dam Reservoir (Poland) determined that oxygen demand due to nitrification, or N-BOD, accounted for 27-59% of

BOD. In the case of the Pearl River in China (Dai et al. 2006) and Providence River estuary in Rhode Island (Berounsky et al. 1985), nitrification could account for almost all of the oxygen demand. Nitrification (as measured by the disappearance of ammonium and the appearance of nitrate) coincides with an oxygen deficit in the lower Seine River in France (Garnier et al. 2007).

If nitrification rates from other studies are converted to oxygen consumption rates

using the assumption that nitrification consumes two moles of O2 for every mole of ammonium consumed, then it is possible to assess the impact of nitrification on the consumption of oxygen. The Schelde Estuary had a rate of up to 80 μmole N L-1 day-1,

-1 -1 which translates to an oxygen depletion rate of 160 μmole O2 L day (de Bie et al.

2002). Other studies cite nitrification rates from 0 to 500 μmoles N L-1 day-1 , which

-1 -1 corresponds to oxygen consumption rates of 0 to 1000 μmoles O2 L day (Pauer and

5

Auer 2000, Dai et al. 2008, Caffrey et al. 2003, Bianchi et al. 1994, Bianch et al 1999,

Berounsky and Nixon 1990, Miranda et al. 2007). Considering that air saturated water

-1 normally has <320 μmole O2 L , even low nitrification rates could use up all available oxygen in a few weeks, especially in thermally stratified waters such as the shallow hypolimnion (Fig. 1 and 2) of the Central Basin of Lake Erie that receive little oxygen input for several months during the summer.

For most research into nitrification, it was assumed that by inhibiting ammonia oxidation, that nitrite oxidation was also inhibited due to lack of substrate (Caffrey and

Miller 1995, Berounsky and Nixon 1990, Ginestet et al. 1998). The difficulty of culturing

NOB’s hampers further understanding of their eco-physiology. Much that is known about NOB biochemistry and metabolism comes from the “golden era” of experimentation 20+ years ago using a limited number of cultures, mainly Nictrobacter

(Ward et al. 2011). More recently, advances in culture-independent techniques have led to an increased understanding of NOBs. The enforcement and development of new discharge limits for ammonium and nitrite in wastewater treatment plants has spurred research into NOBs, especially in enumeration of NOBs and the conditions required for

NOBs to work in mixed bioreactors of wastewater treatment plants. Other culture independent research has been in the enumeration (Cebron and Garnier 2005) and discovery of NOBs in a wide variety of environments from low pH environments to acidic environments (Ward et al. 2011).

Much of the interest in nitrite oxidizers seems to arise in co-culture with ammonia oxidizing bacteria (AOB), especially in the context of wastewater treatment plants.

6

Nitrite can affect AOBs by interfering with the efficient oxidation of hydroxylamine.

NOBs can help to mitigate this interference by oxidizing nitrite, however the exact nature of the relationship between AOBs and NOB’s is unclear (Ward et al. 2011). Most literature assumes that ammonia oxidation (Caffrey and Miller. 1995, Berounsky and

Nixon 1990, Ginestet et al. 1998) is the rate-limiting step, and that by stopping or inhibiting ammonia oxidation, NOBs will become limited by lack of nitrite. This might not be entirely true, as it was shown in rice patty soils with nitrogen amendments; the potential nitrite oxidizing activity is higher than potential ammonia oxidizing activity (Ke and Conrad 2013).

If large amounts of ammonium are present in the system, nitrification can consume large amounts of oxygen, causing low oxygen conditions to occur. However,

Lake Erie ammonium levels are low (personal data, US EPA), but this is just a measurement of substrate pool size. The small pool size could be caused by either low regeneration, or rapid uptake (or a combination). Even if the amount of ammonium in the system is low, a significant amount of oxygen can be consumed if the regeneration of that pool is rapid. Miranda et al. (2007) demonstrated that nitrification rates were more likely regulated by renewal rates than the pool size of ammonium. This could come about by a having a small but steady input of ammonium over a longer period of time due to processes like ammonium flux from the sediments, DNRA from anoxic regions, and mineralization (perhaps from mussels). Thermal stratification with limited oxygen exchange with the atmosphere can exist for 3+ months in Lake Erie during the summer season. So even a small but steady rate of oxygen consumption due to nitrification can

7 lead to the depletion of large amounts of oxygen over time. Couple this with the limited volume and shallow depth of the hypolimnion of the Central Basin (Fig. 1 and 2), and hypoxia could be caused or accelerated by processes such as nitrification.

Hypoxia

Hypoxia in aquatic systems is defined as conditions where the oxygen concentration falls to the point where it is detrimental to aerobic aquatic life (Diaz 2001).

Typically an oxygen concentration below 2-4mg L-1 or about 20-40% saturation is detrimental or fatal to aerobic life. However, this threshold varies across species and life stages with many species surviving at or below oxygen concentrations of 2mg L-1 (Kalff

2002, Diaz 2001). Hypoxia occurs when the oxygen demand exceeds the flux of oxygen from photosynthesis or transfer from source areas, such as the atmosphere, via advective mixing or turbulent diffusion. Oxygen demand can be broken down into chemical oxygen demand (COD), due to the oxidation of reduced materials that are not biologically mediated and biological oxygen demand (BOD). The BOD can be further divided into carbonaceous biological oxygen demand, C-BOD, and biological oxygen demand due to the oxidation of ammonia, N-BOD (Smith 2008, Polak 2004). All of these processes occur in both the water column and in the sediments. Hypoxia generally occurs in the sediments and the hypolimnion where oxygen consumption is high and sources of oxygen are low. Lake morphology will affect the formation of regions of hypoxia. A shallow hypolimnion with a large sediment surface area to volume ratio, such as in the Central Basin of Lake Erie (Fig. 1 and 2), is more likely to become hypoxic as

8 there is a smaller reservoir of oxygen to begin with than the deeper Eastern Basin

(Hawley 2006, Rosa and Burns 1987).

Biota that require oxygen, for example fish, are affected by hypoxia. Hypoxia can be a natural part of an ecosystem, but humans often have a part in causing or contributing to hypoxia. The occurrence of hypoxia can act as another stressor to an already stressed system. Mortality of aerobic individuals is one of the most obvious signs of hypoxia.

Hypoxia can also lead to the collapse or decline of commercial fisheries (Diaz 2001).

Landings of commercial fish declined during periods of hypoxia in Lake Erie and improved when hypoxia decreased (Ludsin et. al 2001, Ryan 2003). There are also more subtle negative chronic effects on reproduction and growth rates. Food conversion efficiency can decline under conditions of hypoxia (Kalff 2002). Evans (2007) examined lake trout movement and reproduction in Ontario, Canada and determined that both of these measurements declined under low oxygen conditions. Some organisms

(especially macroinverterbrates) can survive hypoxia by entering a period of dormancy.

These organisms utilize stored carbon anaerobically at the cost of the incomplete carbon utilization and release of substances such as lactate and ethanol (Kalff 2002). Hypoxia leads to behavioral changes in organisms that migrate deep into the water column during the day to avoid visual predators and limits foraging areas for others. Thus distributions of organisms and their interactions can change under conditions of hypoxia (Keister et al.

2000). The impacts of hypoxia may not appear quickly. In fact, the production rates of some fish can increase for a period of time as prey fish are driven out of areas of refuge and enhance the growth of predator fish (Costanti et al. 2008). In addition, hypoxic areas

9 are no longer available for egg-laying/reproduction and can cause the death of eggs already there. These changes can lead to losses of entire or partial cohorts of individuals.

The loss of a cohort can change benthic and pelagic food webs over periods of time much longer than the duration of the low oxygen event.

Hypoxia has an affect on the biogeochemical cycling within a system. The reduction of oxygen within a system can lead to changes in redox potential that can result in reduction of oxidized material present within the sediments as alternative electron donors are utilized for respiration. In particular, the reduction of iron containing phosphorus compounds can cause the release of phosphorus from the sediments leading to considerable increases in internal loading of phosphorus (Kalff 2002, Burns and Ross

1972).

Introduction to Study System

Lake Erie is the shallowest (average depth of 19 meters) and smallest by volume

(419 cubic km) of the Laurentian Great Lakes and is the most heavily utilized and impacted of these lakes. The Lake Erie watershed has the highest human population, the most agricultural lands and the most urban centers compared to the other Great Lakes’ watersheds (Lucente 2007, Great Lakes Atlas 1995). Seventy-five percent of the Lake

Erie watershed is in agricultural use. The lake is an important transportation link with over 1 billion USD in shipping revenue (NRCS 2005) and a water source for 11 million people (Myers et al. 2003). Many people use Lake Erie for recreation with estimated tourism revenue of over 7 billion USD (NRCS 2005). Lake Erie is home to large

10 commercial and recreational fisheries (estimated value of 100+ million USD annually) that land more fish than all of the other Great Lakes combined with millions of kilograms of fish landed annually (Ryan et al. 2003, NRCS 2005). Due to the heavy use of Lake

Erie, there is much interest in maintaining a healthy system that will sustain current human activities. Changes in the system, such as the fairly recent return of hypoxia, have the potential to affect the utility of the lake and could have large economic impacts.

Billions of USD have been spent in the past to improve conditions on Lake Erie through the implementation of the Great Lakes Water Quality Agreement (GLWQA).

The current study (Table 2 and Figure 1 in Chapter 2) focused on the Central

Basin of Lake Erie where hypoxia is a seasonal occurrence (Burns et al. 2005) although there was some sampling in the Eastern Basin. The Central Basin stretches from the

Pelee-Loraine Ridge in the west to the Long Point-Erie Ridge in the east (Figure 1). It is relatively shallow, with a maximum depth of about 25m, which is deep enough for thermal stratification to occur. The hypolimnion is thin and the reservoir of oxygen available is fairly small compared to the hypolimnion in the deeper (70m) oxic, Eastern

Basin (Figure 2). This sets up the potential for possible hypoxia after stratification becomes established. The presence of hypoxia in the Central Basin has been well documented. The factors that contribute to the formation of hypoxia in the Central Basin are not well defined.

11

Some Lake Erie history: Hypoxia and the link to phosphorus.

Eutrophication often has been cited as the cause of increased frequency of hypoxia in aquatic systems. Often this eutrophication was attributed to anthropogenic inputs that caused the overproduction of unwanted phytoplankton (Bierman et al. 1984) that in turn caused low dissolved oxygen concentration in the hypolimnion from decomposition of the extra organic matter. Productivity in an ecosystem can be controlled by the resource(s) that is (are) most limiting to growth of the primary producers. Phosphorus is often considered the limiting nutrient in most freshwater systems (Nicholls and Dillon 1978, North et al. 2007, Schindler 1977, Schindler et al.

2008, but also see Elser and Frees 1995). Control of hypoxia is often linked to reductions in phosphorus loadings. Management schemes have been designed around this assumption, in particular the Great Lakes Water Quality Agreement (GLWQA).

Research has shown that phosphorus concentrations, phytoplankton, eutrophication and hypoxia have a complex relationship. Phosphorus concentrations have been used as a predicator of phytoplankton biomass (Dillon and Rigler 1974, Jones-Lee and Lee 1986, Lee and Lee-Jones 2001, Schindler et al. 1978, Vollenweider 1969) even though this relationship can vary greatly among lakes (see Nicholls and Dillon 1978 and references within). With increases in P-concentrations or loadings, the phytoplankton community responds with increased production and changes in species composition causing changes in food web structure (Chandler 1940, 1942, 1944, Tilman 1982). The presence of co-variation between species composition and trophic status, perhaps overly

12 simplistic, (Reynolds 1998, Reynolds 2000 a, b, Reynolds at al 2000) has a potential to affect the utility of a lake. The relationship between phytoplankton and phosphorus was carried further in efforts to relate P-loadings to chlorophyll content (and trophic status) by

Vollenweider (1968, 1969, 1975, 1976). As cited by Lee and Jones-Lee (2001) and Rast et al. (1983), these relationships have been used to evaluate the impact of adding or removing phosphorus to the overall productivity of a lake.

The increases in P-loadings led to more phytoplankton, increased frequency of undesirable algal blooms, and caused a reoccurring problem of hypoxia in Lake Erie in the 1960’s and 70’s (Burns and Ross 1972, El-Shaarawi 1987). The adverse effects of cultural eutrophication in the Great Lakes led to the signing of the Great Lakes Water

Quality agreement (GLWQA), 1972 renewed in 1978, amended in 1987, in an effort to mitigate and reverse adverse human effects (in part) by reducing P-loadings to 11,000 tons a year. The reduction goals where largely determined by using the relationships of phosphorus concentrations and loading to phytoplankton production.

The implication of the GLWQA led to great changes in Lake Erie. P- concentrations declined about 50% and loadings declined to the target level (Mastisoff and Ciborowski 2005), although there was yearly variation above and below that target.

Large areas of hypoxia disappeared in the hypolimnion from 1970 until 1989 (Burns et al. 2005). Chlorophyll concentrations and biomass dropped 52-89% (Makarewicz 1993,

Makarewicz et al. 1999). However, the chlorophyll concentrations were lower than those predicted based upon phosphorus concentrations, perhaps due to the introduction of dreissenid mussels (Nicholls et al. 1999, 2001). The phytoplankton community

13 composition has changed to a community more consistent with a mesotrophic environment (Makarewicz 1993). The application of this agreement led to a great improvement of conditions in Lake Erie including the disappearance of hypoxia.

Post GLWQA in Lake Erie: Hypoxia returns

There has been a recent recurrence of the symptoms of eutrophication (Matisoff and Ciborowski 2005), especially hypoxia (Burns et al. 2005, IFYLE 2005, and personal data). Loadings have remained below the desired level, but TP (Total Phosphorus) concentrations in the lake have risen (Rockwell et al. 2005). Phytoplankton shows only small amounts of P-limitation (Guildford et al. 2005, Bade et al. unpublished, Clevinger and Heath unpublished). Algal bloom frequency has increased. However, for not completely understood reasons, chlorophyll concentrations are lower than what are predicted by TP relationships (Matisoff and Ciborowski 2005). This lack of predicted

TP and chlorophyll relationship may be due to zebra mussel filtering (Nicholls et al.

1999, 2001), Others (North et al. 2007) have proposed that nitrogen and phosphorus are co-limiting and have also suggested iron as a limiting nutrient. Now researchers are hypothesizing that eutrophication/hypoxia control is probably more complex than just regulating the limiting nutrient, which is assumed to be phosphorus. There are many other factors that need to be considered.

Current research has not come up with a definitive explanation for the reoccurrence of hypoxia in Lake Erie. Perhaps it is the interactions of many different factors. Global climate change could be a factor. There has been a trend to slightly

14 warmer water temperatures (Burns et al. 2005). There has been an increase in consecutive days above 4° Celsius in Lake Erie (Burns et al. 2005) causing the lake to stratify earlier and longer with a warmer less oxygen-rich hypolimnion. The introduction of invasive dreissenid mussels (i.e. zebra and quagga mussels) could also be affecting the cycling of nutrients within the system. Dreissenids may stimulate phytoplankton standing stocks and productivity through remineralization (Conroy et al. 2005 a & b, Heath et al. 1995).

The ratio of N:P excreted may also favor certain phytoplankton species that lead to increased growth and/or decreased consumption (grazing) (Conroy et al. 2005 a & b).

The selective rejection of certain phytoplankton taxa by dreissenids (Vanderploeg et al.

2001) may also explain some of the blooms of algae that have been occurring. The

“near-shore shunt” hypothesis of Hecky et al. (2004) has attributed some of the recent increases in benthic algae to the reengineering of nutrient flow from the pelagic areas to the near-shore benthos by dreissenids. However, the effects of dreissenids have not been uniform (Conroy et al. 2005) and some studies (Barbiero et al. 2006, Conroy and Culver

2005) have shown conflicting results in different areas due to dreissenid invasion. The

Lake Erie of 20 years ago has changed much, and perhaps the past efforts to control hypoxia are no longer applicable or need to be modified. Phosphorus control is still a necessary part of the mitigation of hypoxia, but there are other factors that need to be considered that may contribute to hypoxia (Schlinder et al. 2008). Further studies are necessary to give direction to efforts that will lead (hopefully) to mitigation efforts to reverse these human-induced changes. The contribution of nitrification to the appearance

15 of hypoxia has not been studied in Lake Erie, and has received little but growing attention in other systems.

Hypothesis

I propose that nitrification is contributing substantially to oxygen consumption and the subsequent development of hypoxia in the Central Basin of Lake Erie. This study begins a scientific exploration to access the impacts of nitrification on oxygen consumption in Lake Erie. Renewed concern about hypoxia in the shallow hypolimnion of the Central Basin provides impetus for examining whether nitrification has a significant impact on oxygen dynamics. I believe that the prior cause of hypoxia, eutrophication due to phosphorus, is not the only contributing element to the development of hypoxia in Lake Erie.

Research questions and outline of dissertation

Chapter 2: In this chapter, I did a survey for one of the critical genes, amoA, involved in the production of the enzyme AMO used for ammonia oxidation. My questions were:

1) What are the population densities of ammonia oxidizers present in the study system?

2) Are they correlated with any of the measured environmental variables?

Chapter 2 was written as a manuscript that was submitted (July 2013) for publication in

Inland Waters and is placed here in its entirety with the only changes being formatting to

16 fit the Arts and Sciences Style guidelines for dissertations (i.e. margins, numbering of figures, etc.). It is intended to stand on its own with no further information from this dissertation. The other authors on this paper contributed monies, technical expertise, editorial assistance, ideas, and assistance in performing experiments. Comments from reviewers from Inland Waters were considered in the revision of this chapter.

Chapter 3: In this chapter I employed more traditional, non-molecular methods (i.e. bottle type experiments) to determine oxygen consumption rates in field collected samples. I was asking 4 questions:

1) What is the rate of total oxygen consumption?

2) How much of the total oxygen use is due to nitrification in the epilimnion, hypolimnion and sediments?

3) Are these rates correlated with environmental variables?

4) What is the contribution of nitrite oxidizing bacteria to oxygen consumption?

A portion of this, the hypolimnion and sediment data, was submitted for publication to

JGLR (revised copy accepted September 2013). The other authors on this paper contributed monies, technical expertise, editorial assistance, and manpower for performing experiments.

Chapter 4: Conclusion and Summary. Here I present a summary of my findings and some potential implications of this research. I place my research into the bigger ecological picture and discuss future avenues of research.

17

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28

Table 1: Reactions involved in the oxidation of ammonia to nitrate. Table modified from

Bock and Wagner 2006.

REACTION

1 NH3 + 0.5O2 + 17kj/molNH2OH

+ 2 0.5O2 +2H 2e H20 + 137 kj/mol

+ 3 NH3 +O2 + 2H + 2e NH2OH + H20 + 120kj.mol

+ 4 NH2OH + H2O +23kj/mol HNO2+ 4H + 4e

+ 5 0.5O2 + 2H +2eH2O + 137 kj/mol

- + 6 NH2OH + 1.5O2HNO2 + 2e +2H + 114kj/mol

7 NH3 + 1.5O2HNO2 + H2O + 235 kj/mol

- - + 8 NO2 + H20 +83kj/molNO3 +2e +2H

+ 9 0.5 O2 + 2H +2e H2O + 137kj/mol

- - 10 NO2 + 0.5 O2NO3 + 54kj/mol

29

Table 2: GPS locations of study sample sites on Lake Erie 2008-2010. Letters (ER, EM,

L) at beginning of site name designate platform samples were taken from; ER =RV Lake

Guardian, EM =RV Erie Monitor, L=CCG Limnos.

Site GPS Location

ER 30 42.431N, 81.205W

ER 43 41.788N, 81.945W

ER 73 41.928N, 81.757W

ER 78m 42.116N, 81.251W

ER 15m 42.516N, 79.893W

EM EB 41.483N, 82.752W

EM BM 41.489N, 82.696W

EM Soff 41.598N, 82.494W

EM CB 41.582N, 82.496W

L 016 42.5249N, 79.697W

L 51 41.1835N, 80.7645W

L 52 42.4661N, 80.895 W

L 56 42.3225N, 81.0746 W

L 59 42.1296 N, 81.2365W

L 154 42.5069 N, 79.9000 W

L 155 41.9160N, 81.6422W

L 46 42.3012N, 80.6239W

L 79 41.8520N, 82.1314W

30

Figure 1: Bathymetry of Lake Erie and Lake St. Clair (From NOAA)

31

Figure 2: Lake Erie stratification (Modified from Charlton 2004)

Chapter 2

Abundance and distribution of ammonia oxidizing bacteria and archaea in Lake Erie

Curtis C. Clevinger1*, Robert T. Heath1, Darren L. Bade1.

Submitted to Inland Waters July 2013

Running Title: AOA and AOB in Lake Erie 1. Kent State University, Department of Biological Sciences. *Corresponding author: Curtis Clevinger: [email protected] The other authors on this paper contributed monies, technical expertise, editorial assistance, ideas, and assistance in performing experiments.

32 33

Abstract The abundance and distribution of potential nitrifiers in Lake Erie was characterized in water column and sediment samples during the summers of 2008-2010. Ammonia oxidizing bacteria (AOB) and archaea (AOA), were quantified using qPCR of the portion of the ammonia monooxygenase (amoA) gene. Contributions of AOA and AOB to the total prokaryote community were assessed by examining 16S rDNA from the archaeal and bacterial assemblages. Environmental variables and nitrification rates were examined for correlations with AOA or AOB to understand factors that may control their distribution. AOA and AOB were present in all samples, with a distribution that was variable over time and space. The AOA/AOB ratio in the epilimnion, hypolimnion, and sediments was 1.02, 1.08, and 5.25, respectively. AOA comprised 48% of the archaeal

16S rDNA community, while AOB was less than 1% of the bacterial 16S rDNA community. Archaeal 16S rDNA comprised from 1-4% of the total 16S rDNA copies present in samples, with the highest percentage in the epilimnion. No significant correlations between nitrifiers (either AOA, AOB or total) and ammonium or oxygen was observed. AOA correlated weakly but significantly (p<0.05) with nitrate (r= -0.262,

N=53), TN (r= -0.395, N= 53) and nitrification rate (r=-0.313, N=50). AOB correlated weakly but significantly with nitrate (r=-0.351, N= 53) and total nitrogen (r=-0.433,

N=53). Ammonia oxidizers, in particular AOA, should be considered important in lakes and need to be considered in management plans and ecosystem modeling.

34

Keywords: archaeal 16S rDNA, bacterial 16S rDNA, amoA, ammonia monooxygenase, nitrification,

35

Introduction

Nitrification is the prokaryote-mediated oxidation of ammonium to nitrate

(Prosser 1986, Ward et al. 2011). The first step in nitrification, ammonia oxidation, was originally thought to be only performed by two groups of bacteria, beta and gamma proteobacteria, but subsequent research has discovered putative ammonia oxidizers in the phylum Crenarchaea of the domain archaea (Venter et al. 2004, Treusch et al. 2005).

However in freshwater lakes, the role of ammonia oxidizing archaea has not been explored extensively (but see Auguet et al. 2011). In some ecosystems, ammonia oxidizing archaea are the most numerous nitrifiers (Lam et al. 2007, Wutcher et al.

2006,Leninger et al. 2006, Francis et al. 2008), while in other systems bacteria dominate

(Boyle-Yarwood, 2008, Jia and Conrad 2009, Santoro et al. 2008, Wessen 2010). Thus, any further considerations of ammonia oxidizer abundance and distribution must include ammonia oxidizing archaea (AOA) and bacteria (AOB). The process of nitrification has clear implications in the nitrogen cycle of ecosystems via the transformation of ammonia to nitrate, but also has implications in oxygen and pH dynamics due to the oxygen consumptive nature of nitrification and the production of H+ as a byproduct.

Factors that control the distribution, abundance and activity of nitrifiers are uncertain and not well understood, with much of what is known confined to marine, terrestrial, and riverine systems. In freshwater oligotrophic alpine lakes, seasonal changes in AOA abundance were explained by temporal changes in ammonium and nitrite concentrations. Copy numbers of archaeal 16S rDNA and archaeal amoA were well correlated, suggesting the ability to carry out ammonia oxidation (Auguet et al.

36

2011). Whether these same factors determine the abundance, distribution and activity of nitrifiers in large lake systems like Lake Erie is unknown. In the oceans, there are higher abundances of AOA and AOB at mid depths than shallow or deep depths and their abundance can vary by an order of magnitude corresponding to environmental conditions

(Mincer et al 2007, Santoro et al. 2010, Church et al 2009). The relative contributions of archaea versus bacteria can vary by greater than an order of magnitude over less than

50m in sediment samples (Park et al. 2008, Li et al 2011) or within a salinity gradient in a subterranean estuary (Santoro et al 2008). Seasonality can affect gene copy numbers with higher AOA and AOB counts during the winter and spring than during the summer and fall in near-shore ocean and river environments (Herfort et al. 2009, Ando et al.

2009) and higher AOA counts during midsummer in oligotrophic lakes (Auguet et al.

2011). Environmental conditions such as ammonium concentration (Jia and Conrad

2009, Ando et al. 2009, Sims et al. 2012a), nitrate concentration (Ando et al. 2009), oxygen concentration (Abel et al. 2011, Santoro et al. 2008), and salinity (Santoro et al.

2008) have been correlated with nitrifier abundances in estuaries and oceans. Resource availability may differentially influence the distribution of AOA and AOB, as they appear to have different affinities for ammonia or other substrates (Martens-Habbena et al. 2009, Di et al. 2010). In some cases, nitrifier abundance has been correlated with nitrification rate (Caffey et al. 2007, Guby-Rangin et al 2010, Di et al. 2010), but this does not seem to be universal (Santoro et al. 2010).

In Lake Erie, the shallowest, smallest by volume, and most heavily used of the

Laurentian Great Lakes (Lucente 2007), there has been a recent recurrence of hypoxia

37

(Hawley et al. 2006, Burns et al. 2005) with no conclusive determination of its cause

(Lake Erie LaMP 2011). Nitrification could be a potential contributor to the development of hypoxia. A prior modeling study suggested that nitrification was important for nitrogen transformations in Lake Erie, but had a limited effect on oxygen consumption

(DiToro and Connolly 1980). However, this work contained no empirical evidence directly linked to nitrification, and recent evidence suggests that nitrification in Lake Erie can significantly influence oxygen consumption (Clevinger et al. accepted 2013). There is some indication into the impact of nitrification on Lake Erie, but the factors that control the distribution and abundance of nitrifiers are unknown. Given the heterogeneous nature of this large lake, ranging from deep, oligotrophic regions in the east to shallow eutrophic conditions in the west, we hypothesized that significant differences in abundance and distribution of AOA or AOB would be observed.

We examined the abundance and distribution of nitrifiers, both AOA and AOB in the water column and sediments in the Central and Eastern Basins of Lake Erie.

Quantitative PCR was used to enumerate the amoA gene, which encodes part of the enzyme ammonia monooxygenase, used to catalyze the first step in nitrification in ammonia oxidizing archaea and bacteria. We examined the spatial and seasonal variation in potential nitrifiers, and attempted to explain their distribution and abundance using environmental variables such as oxygen, ammonium, and nitrate concentrations. Further, we explored whether the abundance of putative nitrifiers was related to rates of nitrification to quantitatively link these organism to their ecosystem function.

38

Materials and Methods

Samples were collected in the Central and Eastern basins of Lake Erie during the summers of 2008-1010, with 36 sampling events over 12 sampling days at 15 stations

(Fig. 3 and Table 3). Epilimnion water samples, as determined by thermal profiles, were taken by Van Dorn bottle or rosette sampler approximately 1 m from the surface and, hypolimnion water was collected approximately 1 m from the bottom. Sediment grabs and cores were obtained via Ekman dredge or box corer when possible. Approximately

50 ml of sediment was taken from the top 1 cm of the core/grab and frozen at -20°C for later analysis.

One to 5L of water was filtered through a 0.22µm filter (Sterivix). The exact amount of water filtered was recorded in 2009 and 2010, but was not recorded in 2008.

Thus, only the relative contributions and not the absolute concentrations of AOA and

AOB, and archaeal 16S and bacterial 16S rDNA are available for 2008 samples.

MoBio’s Power Soil DNA Extraction Kit was used to extract DNA from the 0.22um

Sterivix filters and 0.5 grams wet weight of sediment following manufacture’s directions.

In addition 0.5 grams wet weight of sediment was dried at 70o C for 24 hours to standardize samples containing differing amounts of water. For 5 sediment samples, 3 independent samples per site were extracted to estimate variation.

Cultures and an environmental clone were used to construct standard curves of known copy numbers over 5 orders of magnitude for bacterial and archaeal amoA and

39

16s. Nitrosomonas europaea (ATCC 19718) was cultured using standard methods and media recipes from ATCC (2013) and used to construct standard curves for bacterial amoA and 16S rDNA. The standard curve for archaeal amoA was constructed by using an environmental clone obtained from an environmental DNA extract that was amplified using primers arch-amoaR and arch-amoaF (Francis et al. 2005). The products of this

PCR reaction where purified using Wizard PCR Preps (Promega # A7170) and used as a template for cloning in Promega’s pGem T-Easy Vector system (Cat # A1360) and E. coli competent cells (Cat #296338). Clones where blue/white screened on ampicillin LB medium plates with positive clones being picked and grown up in LB liquid media overnight. Positive clones where confirmed via PCR screening. Halobacterium salinarium, Presque Isle Culture #208, was cultured using standard methods and media

(Presque Isle 2013). Estimates of the gene copy numbers were obtained by comparison of the critical threshold of florescence (Ct) where florescence of products exceeds a given value, of unknowns with the Cts obtained from the standard curves with efficiencies from

95%-105%. The standard curve was constructed over four orders of magnitude of DNA template, and all data was used in the construction of an exponential standard curve for comparison to unknowns. To calculate the number of AOB, it was assumed that there were 2 copies of amoA per cell as is present in Nitrosomonas europaea and some other

AOB (Norton et al. 2002) and 1 copy of amoA for AOA (Hallam et al. 2006). It was assumed that there was 1 copy of 16S rDNA per cell in the construction of 16S rDNA standard curves, which would lead to conservative (low) estimates of bacterial and

40 archaeal nitrifiers in the total bacterial and archaeal community. The use of 3.6 copies of

16S rDNA per cell would lead to larger estimates (Dionisi 2002).

PCR fragments were generated using primers amoa-1f and amoa-2r (Leninger et al. 2006) for bacterial amoA, primers arch-amoaR and arch-amoaF (Francis et al. 2005) for archaeal amoA, primers B341 and 518R (Muyzer et al. 1996) for bacterial 16S rDNA, and primers Ar109F and AR 915R (Einen et al. 2008) for archaeal 16S rDNA. DNA extracts (1-3µl) were amplified using a MX3000P qPCR machine from Stratagene in optically clear tubes and caps from Agilent Technologies (Cat # 401425 and 401428) using QuantiTect qPCR mix (Cat # 204143) from Qiagen following manufacturer’s directions with a primer concentration of 0.6uM. The PCR program had the following parameters: 15 min at 95 oC, 1 min at 95 oC, 1 min at 55 oC, 1 min at 72oC followed by a plate read, repeated 40 times. There was a final cycle to produce a DNA dissociation curve: 1 min at 95oC, 1min at 55oC, an increase in temperature back up to 95oC with a plate read every 1 degree. All samples (sediment and water column) were analyzed in triplicate within a single qPCR run with PCR efficiencies between 95 and 105%. For a total of 20 water and sediment samples, triplicate Ct values were compared between independent qPCR runs to access variation between runs. At five sites, three independent, replicate sediment grabs were collected to determine within site variability.

DNA from each of these samples was extracted and analyzed in triplicate within a single qPCR run. Mean coefficients of variation (CV) were calculated for each set of these analyses to determine whether the precision of the methodology could adequately capture variation within a site.

41

Nitrification rates were calculated by the difference in oxygen consumption between replicate BOD bottles that had the nitrification inhibitors N-serve or allylthiourea added: 50 µM, final conc. (Caffrey and Miller 1995, Berounsky and Nixon

1990, Ginestet et al. 1998) and non-inhibited BOD bottles as described in Clevinger et al.

(accepted August 2013). The removal of the 2008 samples due to recent evidence

(Santoro et al. 2010) that demonstrated the inability of allylthiourea to completely inhibit archaeal nitrification does not substantially affect the overall results. Replicate (6) BOD bottles, 3 inhibited and 3 uninhibited, were filled with water column samples from the epilimnion and hypolimnion water samples. Samples were incubated at room temperature (22 ± 1ºC) for 1 to 5 days dependent upon the oxygen consumption rate.

Oxygen demand in the sediments was carried out in a similar fashion to water column samples in BOD bottles that were spiked with 30 ml of sediment. Chemical oxygen demand was met by adding 100 ml of hypolimnion water and allowing 24 hours to elapse

(similar to Strauss and Lamberti 2000). After 24 hours, the bottles where filled with water, sealed, and respiration and nitrification were allowed to occur for 3-8 hours at room temperature (22 ± 1ºC). Sediment rates were standardized to the weight of sediments after drying at 700C for 24 hours. Initial and final oxygen concentrations were determined with an oxygen probe (Nexsens WQ-DO Smart USB sensor) inserted into the

BOD bottle (2008 water samples and all sediment slurries) or with Winkler titrations

(2009 and 2010 water samples) (Franson 1975). The oxygen probe was allowed to warm up at least 30 minutes before initial use and calibrated with a water saturated air sample.

The oxygen probe was placed in the sample bottle while being stirred for approximately 1

42 minute before the reading was taken. The potential nitrification rate was calculated from the difference in oxygen consumption between the uninhibited and inhibited bottles.

Possible control(s) of putative nitrifier distribution by environmental variables, the concentrations of soluble reactive phosphorus (SRP), ammonium, nitrate, total nitrogen, and oxygen were examined for each site. Nitrate and SRP concentrations where determined using standard colorimetric methods (AWWA 1992) on a Lachat QuickChem

FIA+ 8000 series autoanalyzer. Ammonium concentrations were determined by the fluorometric method of Holmes (1999). Total nitrogen (TN) was determined by combustion and analysis in a Shimadzu DOC/TN analyzer Model TOC0VCPN/TNM-1. In lake oxygen concentrations were measured when possible with the shipboard CTD instrumentation of the RV Lake Guardian or CCG Limnos on the sampling rosette (not functional during part of 2009) or with an YSI 6-series sonde.

Statistical analysis was performed using IBM SPSS (v. 21). The data was graphed and analyzed in four major subsets: epilimnion, hypolimnion, water column (epilimnion plus hypolimnion) and sediment data. Calculations of Pearson correlations between all measured and calculated variables were calculated using the bivariate correlation (2 tailed) option. Means of epilimnion and hypolimnion samples were compared using

ANOVA and T-tests.

43

Results

The sediments, hypolimnion, and epilimnion of Lake Erie contained different proportions of archaeal and bacterial nitrifiers (Fig. 4 and 5). The nitrifier community in the sediments was enriched in AOA, as compared to the water column, with a mean

AOA/AOB ratio of 5.3 (range 0.4 to 21.6). The nitrifier community in epilimnion and hypolimnion had an AOA/AOB ratio of close to 1. The mean AOA/AOB ratio in the epilimnion was 1.0 (range 0.1 to 6.7). The mean AOA/AOB ratio in the hypolimnion was 1.1 (range 0.1 to 6.6). AOA was positively correlated with AOB (r=0.791, p<0.001) in the water column, but not in the sediments (r=0.097, p=0.617). The AOA/AOB ratio in the hypolimnion and epilimnion was generally higher in more eastern sites than more western sites (Fig. 4). The AOA/AOB ratio in the sediments did not show any trend with respect to geography (Fig. 5).

AOA and AOB, as detected by qPCR of amoA copies, were found at every site sampled. The mean concentration of all nitrifiers (cells L-1) was 3.88 ± 3.17 x 105 (SD) in the epilimnion and 5.18 ± 4.19 x 105 in the hypolimnion across all sampled sites and times. The abundance of nitrifiers in the sediments was 1.44 ± 1.24 x 108 nitrifiers gram-1.

There was considerable variation in the data within sampling events and within sites over time. Total nitrifiers varied significantly by up to an order of magnitude, both within a single sampling event and temporally within a single site (Fig. 4-5). The epilimnion and hypolimnion at a particular site and time in 2010 had similar numbers of total nitrifiers

44 present (solid points Fig. 4). Higher nitrifier abundances and variability were found in western sites compared to eastern sites in 2009 (Fig. 4-5).

Seasonal changes in total nitrifier abundance were not uniform among sites. In the epilimnion (Fig 6a), all temporally repeated sites had similar concentrations of putative nitrifiers at the beginning of the season, differing by only a factor of about three.

Midseason (July) nitrifier numbers in the epilimnion differed by over an order of magnitude, with 3 sites (ER30, ER43, and ER15m) decreasing in nitrifier numbers and 2 sites (ER73 and ER78M) increasing in nitrifier numbers. During August, nitrifier numbers in the epilimnion of ER43 and ER 78M increased. In September nitrifier numbers in the epilimnion sites converged to very similar numbers, differing by only a difference of approximately 2. The hypolimnion had a very different pattern (Fig. 6b).

Initially, there was a much larger spread of values among all sites, over an order of magnitude. ER78m, ER30, and ER43 started out almost identical but diverged greatly by the end of the season. Midseason nitrifier numbers in the hypolimnion of ER78m, ER73 and ER30 increased while at ER15m and ER43 nitrifier numbers decreased. Sites ER73,

ER30 and ER15M had similar nitrifier numbers at the end of the season as the beginning, while sites ER43 and ER 78M had greatly increased numbers of nitrifiers. In the sediments, nitrifiers generally increased as the season progressed, with most sites (except

ER73 and ER30 in June) varying by less than on order of magnitude at a particular time.

When considered separately, the abundance and distribution of AOA and AOB varied significantly between sites, dates, and sampling depths with no discernable

45 geographic or temporal patterns. Mean AOB numbers L-1 in the epilimnion and hypolimnion were similar, averaging 3.17 ± 3.00 105, and 3.44 ±3.10 105. Mean AOA numbers L-1in the epilimnion and hypolimnion were similar, averaging 1.15 ± 1.02 105, and 1.56 ± 1.30 105. In the sediments there was 3.10 ± 1.05 108 AOB gram -1 and 6.83 ±

1.30 107) AOA gram -1.

Using 16S rDNA as in indicator of bacterial and archaeal numbers, bacterial nitrifiers were a small contribution to the total bacterial community, while the contribution of archaea with amoA to the archaeal community was much higher.

Bacterial nitrifiers contributed less than 0.1% to the bacterial community and archaeal nitrifiers contributed roughly 20-90% to the archaeal community. Examining the different habitats, sediments had the highest concentration of amoA containing organisms in both the bacterial and archaeal communities compared to the epilimnion or hypolimnion. The sediments had 9.62 ± 0.02 10-3 AOB per copy of bacterial 16S rDNA and 9.71 ± 0.67 10-

1 AOA per archaeal 16S rDNA. The epilimnion had 4.11 ± .085 10-3 AOB per bacterial

16S rDNA and 2.29 ± 3.14 10-1 AOA per archaeal 16S rDNA and the hypolimnion had

2.23 ± 2.73 10-3 AOB per bacterial 16S and 2.49 ± 2.51 10-1 AOA per archaeal 16s rDNA. There were no geographic trends in the AOA to A16S rDNA ratio or AOB to

B16S rDNA ratio. The epilimnion was enriched in archaea, as evident by an archaeal to bacterial 16S rDNA ratio of 0.041± 0.095, then the hypolimnion and sediments with bacterial to archaeal ratios of 0.019 ± 0.044 and 0.012 ± 0.025 respectively.

46

Environmental factors were not related to the abundance or distribution of AOA,

AOB, or their combined numbers in this data set. Few significant correlations existed between nitrifiers and environmental variables when considering just water column samples from both the epilimnion and the hypolimnion (Table 4). Based upon laboratory experiments, a strong correlation between total nitrifiers, or AOA and AOB, individually, and nitrification rate was expected (y=1.29x-0.563, r2=0.973, p<0.001 Clevinger et al. accepted 2013), but this was not observed in environmental samples (Fig 7). A significant negative correlation that existed was between AOA and nitrification rate.

Oxygen concentrations (range 2-10mg/l) obtained from in vivo water column measurements or ammonium concentrations were not correlated with total nitrifier number, AOB or AOA. Nitrate was negatively correlated with AOB and AOA, but not total nitrifier number. Total dissolved nitrogen was negatively correlated with AOA, but not total nitrifiers or AOB. In the sediments, there was no significant correlation between nitrification rates and abundances of total nitrifiers (r=0.043, p=0.835), AOA (r=0.148, p=0.472), or AOB (r=0.079, p=0.702). Concentrations of nitrogen species and O2 were not measured in the sediments.

We assessed the precision of the qPCR enumeration of amoA by triplicate replication of all sample measurements within a qPCR run (all samples, n =57), across qPCR runs (n=20) and within independent replicate samples at the sample site (n=5).

The CV of Ct values for the triplicates of all samples averaged 2% with an efficiency ranging from 90-110%. For the comparison between independent qPCR runs the mean

CV of Ct values was 5%, and for the triplicate sediment grabs the average CV was 3%.

47

Repeated sampling of sediments (triplicates) at the same site and time showed a consistency of values obtained with a standard error an order of magnitude less than the average value of the replicates for AOA and AOB (Table 5).

Discussion

While AOA and AOB were found in all samples, the abundance and geographic distribution of putative nitrifiers in Lake Erie did not show distinctive patterns either individually or as a combined total. However, comparing the sediment environment to either the epilimnion or the hypolimnion, the ratios of AOA to AOB were more enriched in the sediments. These results are similar to what was found by Park et al. (2008) in marine sediments. Sediments at many sites had AOA as the dominant nitrifier, while in the water column there was more parity between AOB and AOA abundances. The carbon rich, low oxygen sediments of Lake Erie (Smith 2008) may therefore favor AOA.

In managed farmlands, AOA abundance increased with the addition of labile organic carbon while AOB community size varied little, supporting the idea that AOA could employ alternative growth strategies (Wessen et al. 2010). AOA are also less affected by low dissolved oxygen than are AOB (Abell 2011). The dominance of AOA could also be explained by the ammonia oxidation kinetics of AOA and AOB. Martens-Habbena et al.

(2009) and Di et al. (2010) demonstrated that certain AOA are adapted to very low ammonia levels in the oligotrophic oceans, suggesting a greater role of AOA under these conditions. However, substrate levels in sediments were not measured in our study.

48

Other than the differences observed in ratios of AOA and AOB between sediment and water column, their abundances, either individually or combined as a total, exhibited large variation with respect to site or date. Temporal or spatial trends in AOA and AOB were not consistent or generalizable over the entire lake. Ando et al. (2009), in the sands of Tanoura Bay (Japan), demonstrated seasonal changes in total nitrifiers, AOA and AOB of over an order of magnitude similar to our results.

It has been acknowledged that archaea can contribute substantially to the ecosystem function of ammonia oxidation, especially in marine environments and soils, but information regarding AOA in freshwater lotic habitats is still sparse (but see Auguet et al. 2011). In Lake Erie, the archaeal nitrifiers comprised a larger portion of the archaeal community than did the bacterial nitrifiers to the bacterial community. Archaeal nitrifiers comprised approximately 20-90% of the archaeal community with the highest contribution in the sediments, while bacterial nitrifiers comprised less than 0.1% of the bacterial community. Again, comparing the ratios of AOA/AOB, we saw parity in the water column but 3-5 times more AOA than AOB in the sediment. There are few examples of the contribution of AOA to archaeal communities in pelagic environments.

Auguet et al. (2011) showed that AOA may contribute more than 50% to the archaeal community in oligotrophic alpine lakes. The AOB portion in wetlands ranged from less than 1% to about 10% of the bacterial community (Sims et al 2012a,b). The lack of correlations between AOA and environmental variables may be attributable to the fact that actual numbers of archaea capable of ammonia oxidation are likely to be lower, as nitrifying activity has not been demonstrated in all amoA containing archaea

49

(Hatzenpichler 2012). Given the much lower affinity for ammonium by certain AOA, they may occupy a distinct niche from AOB (Martens-Habbena et al. 2009), and help explain the ubiquitous activity of nitrifiers in Lake Erie despite the potential for resource competition with heterotrophs or autotrophs.

Archaea comprised from 1 to 4% of the total number of individuals in the prokaryote community in Lake Erie, with the highest percentage in the epilimnion. Other studies of 16S rRNA hybridization of picoplankton in the Great Lakes indicated that archaea comprise from 0.7 to 10% of the total picoplankton (Likens 2010). In coastal ocean waters archaea comprise 1-17% of the total number of individuals in the prokaryote community (Schwarz 2010), while in more open waters they can make up to

50% of the prokaryote community (Herndl et al. 2005, Hatzenpichler 2012). Sediments and soils studies yield a similar range, from 1-38% (Soule 2009, Hansel et al. 2008,

Schwarz 2007). Our estimate of the archaeal contribution to the prokaryote community are likely a conservative one as we assumed that each bacterial cell only had 1 copy of

16S rDNA per cell, and is probably higher as many bacterial cells have multiple copies of

16S rDNA. The data suggests that archaea could have a substantial effect on ecosystem functions in Lake Erie.

There was a lack of strong correlations between nitrifiers, nitrification rate, or environmental variables. The lack of correlations is in contrast to our more controlled laboratory experiment showing a correlation between nitrifier number and nitrification rate (Clevinger et al. 2013). Similar lack of correlation between nitrifier number and

50 nitrification rate has been reported in the ocean (Santoro et al. 2010), but not in all instances (Caffey et al. 2007). Inactivity of the nitrifiers present in environmental samples could account for the lack of correlation between nitrifier number and nitrification rate. A correlation between AOA and nitrification rate, but not AOB (Guby-

Rangin et al. 2010) was observed in agricultural soils, while others have demonstrated just the opposite (Di et al. 2010). Jia and Conrad (2009) documented the difference between gene abundance and activity by demonstrating that even though archaea dominated amoA gene copy numbers, the bacteria dominated the functional response of nitrification. Other environmental factors such as pH (Nicol et al. 2008, Wankel et al

2011, Wessen et al 2010), ammonium (Jia and Conrad 2009, Ando et al. 2009, Sims et al.

2012), TN (Wessen et al. 2010), nitrate (Ando et al. 2009) and predation (Xiao et al.

2010) have been cited as affecting nitrifiers, either AOA and/or AOB. Our results support some of these assertions of environmental effects on nitrifiers, at least for nitrate and TN. However, correlations were weak and often opposite of what would be expected. Our measurements of environmental variables represent static values that do not account for the turnover of these substances. For example small pool sizes of ammonium could be attributed to high demand by nitrifiers, but could also occur when nitrifier activity is low, and inputs of ammonium are also low. Nitrification may be tightly coupled to ammonification rates.

The assessment of precision of qPCR enumeration between triplicate subsamples, independent qPCR runs and independent collected environmental samples demonstrated the repeatability of our results, with variation of the Ct ranging from 2-5%. Variability

51 among replicate samples was similar to the error inherent in the methodology. The variability in measurements is less than environmental variability suggesting that the variability is not random error, but natural variation arising from a natural source.

Therefore we feel confidant that the variability observed and the lack of generalizable patterns are not methodological artifacts, but that the understanding about controls on both bacterial and archaeal nitrifier abundances and activities requires significant further investigation. Developing methods (e.g., RTqPCR and other mRNA methods) that can distinguish between active and inactive organisms can further elucidate these controls

(e.g. Church et al. 2009).

Both archaeal and bacterial nitrifiers existed ubiquitously in the sediments and water column of Lake Erie. Their distribution and abundance was not predicted from routine environmental measurements, nor did they follow any consistent spatial or temporal pattern. Despite our inability to determine any predictive factors, the function of nitrifiers is clearly integral in nitrogen cycling. Especially in marine environments, the critical role of AOA in nitrification is being recognized, while little is known in freshwater environments. Our results, showing their prevalence in the archaeal community, highlight this. From an ecosystem perspective, nitrification has additional ramifications for oxygen and pH dynamics, and greenhouse gas production. The absence of nitrification in anoxic waters often leads to an increase of ammonium, essentially a local disruption of the nitrogen cycle. The uncertainty in the distribution and abundance of nitrifiers is a weakness in our understanding of the roles of these organisms in

52 freshwater communities and ecosystems, and further prevents us from knowing how they will respond to environmental change such as nitrogen pollution or climate change.

Acknowledgements

This work was supported by Ohio Sea Grant R/ER082 and Kent State Graduate Student

Senate.

We also thank Heather Kirkpatrick, Josh Smith, Jennifer Clevinger, Moumita Moitra, numerous undergraduate assistants, the captains and crews of RV Lake Guardian, RV

Erie Monitor, and CCG Limnos for their assistance.

53

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Xueqing G, Heath RT. 2005. Relationship Between Labile Dissolved Organic Carbon

(LDOC), Bacterioplankton Cell Phosphorus Quota, and Bacterial Phosphate

Uptake Rate in Lakes. J Great Lakes Res, 31(2):125-137.

61

Table 3. Sampling regime in Lake Erie 2008-2010. The nomenclature and locations of sites preceded by “ER” follows the USA EPA sampling regime (US EPA 2010) while sites preceded by “L” follows the Environment Canada sampling regime (Environment

Canada 2013). The nomenclature and locations of sites EB, Soff and CB follow Gao and

Heath (2005).

Sample Date Sample Sites June 5, 2008 Soff, CB June 19, 2008 CB July 12, 2008 ER30, ER78M August 15, 2008 ER30, ER78M August 17, 2008 Soff, EB October 23, 2008 Soff, EB June 5, 2009 ER43, ER78M June 12, 2009 ER73, ER43, ER78M, ER30, ER15M July 20, 2009 ER73, ER43, ER78M, ER30, ER15M August 20, 2009 ER78M September 13, 2009 ER73, ER43, ER78M, ER30, ER15M July 30, 2010 L056, L154, L052, L051, L056, L155, L079

62

Table 4: Pearson correlation coefficients between nitrifier abundances, environmental variables and nitrification rates for samples from both the epilimnion and hypolimnion. Correlations that are significant (p<0.05) are marked with a “*”.

Environmental Variable Total nitrifiers AOA AOB

Ammonia (N=51) -0.164 0.106 -0.146

Nitrate (N=53) -0.219 -0.262* -0.351*

Total dissolved nitrogen -0.433 * -0.399* -0.165 (N=53)

Oxygen (N=37) -0.028 -0.002 -0.029

Nitrification rate (N=50) -0.178 -0.313* -0.078

AOA (N=57) 0.791*

63

Table 5: AOB (assuming 2 copies of amoA/cell) and AOA (assuming 1 copy of amoA/cell) 107 per gram dry weight in repeated sampling of sediments at 5 sites in Lake Erie.

Mean Mean Site SE SE AOB AOA 16 1.8 0.6 5.4 1.1 56 0.8 0.1 6.9 0.6 59 0.5 0.1 4.0 0.2 154 1.2 0.2 5.3 0.4 155 0.8 0.1 4.5 0.9

64

Figure 3. Approximate locations of study sample sites in Lake Erie 2008-2010. Open circles designate water column samples only.

65

Figure 4: A: Total nitrifiers in water column samples in Lake Erie. B: AOA to AOB ratio (log scale on Y axis) in the water column of Lake Erie 2008-2010. Hypolimnion samples offset by 0.05 degrees.

66

Figure 5: A: Total nitrifiers in the sediments per gram dry weight of sediment in Lake Erie 2008-2010. B: AOA to AOB ratio (log scale on Y axis) in the sediments of Lake Erie 2008-2010.

67

140 A ER78M 120 ER73 -1 100 ER43 ) L 4 ER15M 80 ER30 60

40 Nitrifiers (x 10 Nitrifiers 20

0 5/27/09 6/16/09 7/6/09 7/26/09 8/15/09 9/4/09 9/24/09 160 Day of year B 140

-1 120 ) L 4 100 80 60

Nitrifiers (x 10 Nitrifiers 40 20 0 5/27/09 6/16/09 7/6/09 7/26/09 8/15/09 9/4/09 9/24/09 Day of year Figure 6A: Total nitrifiers in the epilimnion at 5 sites that had repeated temporal sampling. B. Total nitrifiers in the hypolimnion at 5 sites that had repeated temporal sampling

68

6

Hypolimnion

5 Epilimnion ) -1 Day

-1 4

3

2 Nitrification Rate (µmole L (µmole Rate Nitrification

1

0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 Nitrifiers (x104) L-1 Figure 7: Relationship between total nitrifiers in the epilimnion (solid square) and hypolimnion (open diamond) and nitrification rate in Lake Erie samples.

Chapter 3

Nitrification and oxygen use in the water column and sediments of Lake Erie.

Excerpt of chapter with sediment and hypolimnion data accepted for publication in

Journal of Great Lakes Research as:

Oxygen use by nitrification in the hypolimnion and sediments of Lake Erie.

Curtis C. Clevinger1*, Robert T. Heath1, Darren L. Bade1.

Accepted: To be published December 2013

1. Kent State University, Department of Biological Sciences. *Corresponding author: Curtis Clevinger: [email protected] The other authors on this paper contributed monies, technical expertise, editorial assistance, ideas, and assistance in performing experiments.

69 70

Abstract

Nitrification is an oxygen consumptive process that traditionally has been only viewed as a nutrient transformation process. To evaluate the contribution of nitrification to oxygen demand, hypolimnion, epilimnion and sediment samples were collected during the summers of 2008-2010 in Lake Erie. Oxygen consumption by nitrification in the

-1 -1 hypolimnion was 3.7± 2.9 (mean ± 1 SD) μmole O2 L day with nitrification accounting for 32.6 ± 22.2% of the total oxygen consumption. Nitrification in the hypolimnion contributed more to oxygen consumption in the eastern sites than western sites and was lowest in September. The nitrification rate in the epilimnion was 3.1 ± 3.2 (mean ± 1 SD)

-1 -1 μmole N L day with nitrification accounting for 28.2 ± 23.1% of the total oxygen consumption. Nitrification in the epilimnion contributed more to oxygen consumption in the western sites than eastern sites. In the epilimnion and hypolimnion, respiration and the percentage of oxygen used due to nitrification were negatively correlated. The nitrification rate did not correlate with environmental factors such as oxygen, nitrate or ammonium, or nitrifier numbers. Oxygen consumption by nitrification in sediment

-1 -1 slurries was 7.1 ± 5.8 μmole O2 gram day with nitrification accounting for 27.0 ±

19.2% of the total oxygen consumption with the lowest rates in July and the lowest percentages in June. Oxygen consumption by nitrification in intact sediment cores was

-2 -1 682 ± 61.1 μmole O2 m day with nitrification accounting for 30.4 ± 10.7% of the total oxygen consumption. Nitrification rates in intact cores were generally highest in

71

September. In limited sampling, nitrite oxidation consumed less oxygen than did ammonia oxidation with a mean oxygen use due to nitrite oxidation of 1.9 ± 1.3 μmole

-1 -1 -1 -1 -1 -1 O2 l day , 1.2 ± 0.6 μmole O2 l day , 1.0 ± 0.3μmole O2 l day and a mean oxygen use

-1 -1 -1 -1 due to ammonia oxidation of 5.4 ± 1.3 μmole O2 l day , 2.6 ± 2.6 μmole O2 l day , 2.2

-1 -1 ± 0.3 μmole O2 l day in the sediments, epilimnion, and hypolimnion respectively. The addition of nitrifiers did not cause a significant increase in nitrification rate. The proportion of oxygen consumed by nitrification corresponds closely with what would be predicted from complete oxidation of a Redfield molecule (23%). While nitrification is unlikely to be the dominant oxygen consumptive process, the rates observed in Lake Erie were sufficient to theoretically deplete a large portion of the hypolimnetic oxygen pool during the stratified period.

.

72

Introduction

Nitrification is the oxidization of ammonium to nitrite and nitrate in a process that consumes oxygen and generates a small amount of energy that organisms can use to fix inorganic carbon. Nitrification consumes 2 moles of oxygen per mole of ammonia oxidized. This consumption of oxygen can have a substantial affect on oxygen consumption in an ecosystem and lead to hypoxia or anoxia, especially in areas with limited oxygen exchange such as the hypolimnion in the Central Basin of Lake Erie.

Nitrification also produces nitrate. This is the substrate for denitrification and the subsequent export of nitrogen from an ecosystem via denitrification. The dynamics of uptake of nitrate as a source of nitrogen also differs from that of ammonium, favoring some organisms over others and potentially leading to changes in species assemblages

(Domingues et al. 2011).

Large-scale aquatic ecosystems increasingly are affected by regions of hypoxia in their profundal waters (Diaz and Rosenberg 2008). The causes and consequences of this increasing occurrence of hypoxia are not well understood, although cultural eutrophication is generally viewed as a major factor in promoting these occurrences

(Howarth et al. 2011). In the 1960s Lake Erie had large regions of hypoxia and anoxia in the central basin, reaching a maximum in the early 1970s (Burns and Ross 1972), that was attributed to excessive inputs of phosphorus compounds through cultural eutrophication (El Shaawari 1987). With the advent of the Great Lakes Water Quality

Agreement (IJC 1978), which mandated total phosphorus (TP) loading of 11,000 tonnes y-1 or less, cultural eutrophication of Lake Erie subsided and the central basin generally

73

-1 remained oxygenated (O2 > 1.0 mg L ) throughout the year until the mid-1990s. Since

1997, large regions of the central basin have become hypoxic during July until thermal destratification (Burns, et al. 2005), despite TP loadings that were generally far below the levels mandated by GLWQA (Dolan and McGunagle 2005), except during exceptionally rainy years (1997 and 1998).

The cause(s) of the annual reappearance of large hypoxic regions in the central basin remains unclear. There are several plausible hypotheses that have been proposed as contributors to current hypoxia. Increased cultural eutrophication may not be a major factor and most likely is not the only causative factor because the regions of hypoxia increased from 1997-2002 despite a decrease in water column chlorophyll concentrations

(Rockwell et al. 2005). Total phosphorus loadings have remained near the desired levels, but there has been a change in the quality of the phosphorus loading (Richards 2006,

Richards et al. 2009). Global climate change has caused warmer water temperatures leading to an increase in consecutive days above 4° C in Lake Erie and the development of stratification sooner and longer with a less oxygen-rich hypolimnion (Burns et al.

2005). The introduction of dreissenid mussels has also changed and redirected the nutrient and energy flow with the ecosystem (Hecky et al. 2004).

Nitrification is an oxygen-consumptive process that may be a candidate as a contributor to hypoxia in freshwater systems and as a potential factor in changing species assemblages. Nitrification is the microbially-mediated chemoautotrophic process whereby ammonium is oxidized to nitrite and then to nitrate, consuming two moles of oxygen per mole of ammonium oxidized to nitrate. The energy from these reactions is

74 used to fix inorganic carbon into organic compounds. The purpose of this study was to determine the extent to which nitrification contributed to the overall oxygen consumption rates in the hypolimnion, surficial sediment slurries, and intact sediment cores and the contribution of nitrification as a nutrient transformation process in the epilimnion of Lake

Erie during the summers of 2008-2010. As with prior research found in the literature, the concentration is on ammonia oxidizing archaea (AOA) and ammonia oxidizing bacteria (AOB) with only a few experiments on nitrite oxidizing bacteria (NOB).

Materials and Methods

Cruises on the RV Lake Guardian, CCG Limnos, RV Erie Monitor and private boats were used to access sampling sites during the summers of 2008-2010 in the Central and Eastern Basins of Lake Erie (Fig. 3 and Table 2 and 3). There where 5 sampling events at sites in the central/western portions of the Central Basin, including the

Sandusky Sub-basin in 2008: June1 and August 31 (ER43 and ER78M), June 5 (Soff, and EB), June 19 (Soff and CB), and August 17 (Soff and EB). Sampling was done on

June 5 (ER43) and August 20/3, 2009 (EB and ER43M). Additionally during 2009, on

June 12, July 20, and September 13 the sites ER73, ER43, ER78m, ER30, ER15m

(omitted in September) were sampled. The 2009 sites had a broader geographic basis than

2008 and included samples from the Eastern and Central Basins. On July 30, 2010 sites

L056, L154, L52, L51, L56, L155, and L79 were sampled over approximately 48 hours, which included samples from the Eastern and Central Basins. Epilimnion water samples were collected approximately 1 m from the surface and hypolimnion water samples were

75 collected approximately 1 m from the bottom; either by Van Dorn bottle or rosette sampler. Sediment grabs and cores were obtained via Ekman dredge or box corer when possible.

To determine possible control(s) of oxygen consumption by nitrification, putative ammonia oxidizing bacteria and archaea numbers, and the concentrations of soluble reactive phosphorus (SRP), ammonium, nitrate, dissolved organic carbon, total nitrogen, and oxygen was determined for each site. Total gene copies of amoA or nitrifiers

(assuming 2 copies of amoA per AOB and 1 per AOA), were enumerated by qPCR of total community DNA retained on a 0.2μm filter using primers and methods from Francis et al. (2005), and Leninger et al. (2006). We calibrated the qPCR for AOB using cultures of Nitrosomonas europaea, ATCC 19718, cultured using standard methods and media recipes from ATCC, which is known to have two gene copies of the amoA (Bock and

Wagner 2006). An environmental clone generated from primers of Francis et al. (2005) was used for calibration for AOA. Nitrate and SRP concentrations where determined using standard colorimetric methods on a Lachat QuickChem FIA+ 8000 series autoanalyzer. Ammonium concentrations were determined by the fluorometric method of

Holmes (1985). DOC and TN were determined by combustion and analysis in a

Shimadzu DOC/TN analyzer Model TOC0VCPN/TNM-1. Oxygen concentrations were measured with the shipboard CTD on the sampling rosette or with an YSI 6-series sonde.

76

Oxygen consumption by nitrification

For water column samples, water was placed into replicate BOD bottles (6 during

2008 or 9 during 2009 and 2010). Three of the bottles had the nitrification inhibitors N- serve (2009 and 2010; 50 µM, final concentration), or allylthiourea (2008; 50 µM final concentration), which have been shown to inhibit ammonium oxidation (Caffrey and

Miller 1995, Berounsky and Nixon 1990, Ginestet et al. 1998). Three bottles had no inhibitor added. The last 3 bottles (2009 and 2010) were used for initial oxygen determinations with Winkler titrations with azide modification. The bottles were sealed and incubated at room temperature (22 ± 1º C) for 1-5 days. Initial and final oxygen concentrations were determined either with an oxygen probe (Nexsens WQ-DO Smart

USB sensor) inserted into the BOD bottle (2008) or with Winkler titrations (2009 and

2010). The oxygen probe was allowed to warm up at least 30 minutes before initial use and calibrated with a water saturated air sample. The oxygen probe was placed in the sample bottle while being stirred for approximately 1 minute before the reading was taken. The potential nitrification rate was calculated from the difference in oxygen consumption between the uninhibited and inhibited bottles. It was assumed that by inhibiting ammonia oxidation, that nitrite oxidation was also inhibited due to lack of substrate.

Oxygen demand in the sediments was calculated 2 ways: a slurry type experiment

(2008- 2010) and an aerial measurement from intact sub-cores (2009). The slurry measurements were carried out in a manner very similar to the water column, but the sample BOD bottles (6) were amended with approximately 30 ml of homogenized

77 sediment from the top 1cm of the box core or Ekman grab. First, 30 ml of sediment and approximately 100ml of hypolimnetic water were added to a BOD bottle. The bottles were left uncapped for 24 hours to allow for the chemical oxygen demand to be satisfied and to allow for biota to adjust to their changed environment (Strauss and Lamberti

2000). After 24 hours, the bottles where filled with hypolimnetic water and the nitrification inhibitors were added as above. Bottles were sealed and incubated for 3-8 hours at room temperature (22 ± 1ºC). Oxygen consumption rates of uninhibited and inhibited bottles were determined as above with an oxygen probe and used to calculate potential nitrification rates. Rates were standardized to the average dry weight of 3 replicates of 30ml of homogenized slurry that were dried at 70°C for at least 24 hours.

For the aerial measurement of the nitrification (2009), 6 sub-cores were taken from a larger box core. The sub-cores were constructed from clear acrylic plastic tubes (3cm inside diameter and approx. 40cm long) with plastic BOD bottles (Environmental

Express ®), with bottoms removed, attached to the top (similar to Smith 2008). The sub- cores were inserted into the box core up to the junction of the tube and BOD bottle. The bottom of the tube was capped and the sub-core apparatus was removed with a minimal surface sediment disturbance. Additional hypolimnion water was added to fill up the sub-core apparatus (approx. 250 ml). The nitrification inhibitor N-serve (approx. 50uM) was added to 3 tubes per site, with the remaining tubes receiving no additions. Initial oxygen measurements were taken as above using an oxygen probe, then the BOD bottle was sealed. Final oxygen measurements were taken 4-8 hours later. The oxygen use due to nitrification was calculated as the difference between initial and final oxygen

78 measurements in inhibited and uninhibited bottles. It was assumed that by inhibiting ammonia oxidation, that nitrite oxidation was also inhibited due to lack of substrate.

To demonstrate the relationship between oxygen use and AOB, a culture of

Nitrosomonas europaea (ATCC 19718) was utilized. This AOB culture was prepared using standard methods and media recipes from ATCC, serially diluted with artificial lake water (from 1:20 to 1:60), and placed into replicate (6) BOD bottles. Three bottles received N-serve as described above. The BOD bottles were sealed and nitrification was allowed to occur for 24 hours. The initial and final oxygen concentrations were determined via an oxygen probe (Nexsens WQ-DO Smart USB sensor) as described above.

Nitrite Oxidation

Day cruises on August 20 and 23, 2009 utilized Ohio State University’s Stone laboratory research boat Erie Monitor and a private boat to sample the Sandusky Bay

(EB) and the Central Basin site ER43 (epilimnion and sediment only, due to weather conditions) respectively. A September 13, 2009 cruise of opportunity on the RV Lake

Guardian was used to sample 4 sites, ER78m, ER30, ER 43, and ER73 in the Central

Basin (Figure 3 in Chapter 2). Water samples were taken from approximately 1 m from the surface (to avoid photo-inhibition effects) and in stratified sites; a hypolimnion sample was obtained approximately 1 m from the bottom. Sediment grabs were obtained via Ekman dredge at all sites when possible to use for nitrification experiments. For

“slurry” experiments only the top 1 cm of the sediment was used.

79

Laboratory experiments to observe oxygen consumption of NOB’s were performed with the culture Nitrobacter winogradskyi (ATCC # 25391). Nitrobacter winogradskyi was cultured following standard culture methods from ATCC. Cell density in the cultures as determined by DAPI counting was 2.41x106 cells/ml. Cultures where diluted (range 1:2 to 1:32) with artificial lake water that had nitrite added to the same concentration as the culture media and placed into 3 BOD bottles per cell concentration.

Sodium chlorate (50 mmole L-1 final concentration) was added to 3 additional bottles that had the highest cell density (the 1:2 dilution or 1x106 cells ml-1) to observe the inhabitation of oxygen consumption by NOBs. Initial DO readings where taken using a

DO probe (Nexsens WQ-DO smart USB DO sensor). After sealing the BOD bottles, nitrite oxidation was allowed to occur for 3 days, then a final DO reading was taken.

Oxygen consumed due to nitrite oxidation was calculated as the difference between the initial and final oxygen readings.

Nitrification (nitrite oxidation) via oxygen demand: water column

Nitrification assays were performed in a similar way to prior nitrification assays as above. For water column samples, water was placed into replicate (9) BOD bottles.

Three of the bottles had the nitrification inhibitor N-serve (50 µmole L-1, final conc.) added to inhibit ammonium oxidation (Caffrey and Miller. 1995, Berounsky and Nixon

1990, Ginestet et al. 1998). Three bottles had chlorate added (final conc. 50mmole L-1) to inhibit nitrite oxidation (Belser and Mays 1980). In the three remaining bottles, no inhibitor was added to allow for complete nitrification (ammonia and nitrite oxidation)

80 and respiration to occur. The bottles were sealed and incubated at room temperature (22

± 1º C) for 1-5 days. Initial and final oxygen concentrations were determined with

Winkler titrations with azide modification to help prevent nitrite interference. Oxygen consumed due to nitrification was calculated from the difference between uninhibited bottles and the N-serve inhibited bottles. The oxygen consumed due to ammonia oxidation was calculated from the difference in oxygen consumption between the uninhibited and chlorate-inhibited bottles. Oxygen consumed due to nitrite oxidation was calculated as the difference in oxygen consumption between N-serve inhibited bottles and chlorate-inhibited bottles.

Nitrification (nitrite oxidation) via oxygen demand: sediments

Sediment slurry measurements were carried out in a manner very similar to the water column, but the sample BOD bottles (9) were amended with approximately 30 ml of homogenized sediment from the top 1cm of the box core or Ekman grab and 100ml of hypolimnion water. Twenty-four hours were allowed to elapse to allow for any chemical oxygen demand to be satisfied. After 24 hours, the bottles where filled up with hypolimnion water and one set of three bottles had a nitrification inhibitor N-serve added

(50 µmole L-1, final conc.) and another set of three bottles had chlorate (final conc. 50 mmole L-1) added, with the final three bottles having no additions (similar to sediment samples in Chapter 3). Bottles were incubated for 3-8 hours at room temperature (22 ±

1ºC. Initial and final oxygen concentrations were determined with an oxygen probe

(Nexsens WQ-DO Smart USB sensor) inserted into the BOD bottle. The oxygen probe

81 was allowed to warm up at least 30 minutes before initial use and calibrated with water- saturated air. The oxygen probe was placed in the sample bottle while being stirred for approximately 1 minute before the reading was taken. The oxygen consumed due to ammonia oxidation was calculated from the difference in oxygen consumption between the uninhibited and chlorate-inhibited bottles. Oxygen consumed due to nitrite oxidation was calculated as the difference in oxygen consumption between N-serve inhibited bottles and chlorate-inhibited bottles.

The effect of additional nitrifiers on nitrification rate

Epilimnion water from near-shore waters in the Central Basin (Gordan Park,

Cleveland, Ohio) was amended with ammonia oxidizing bacteria and ammonia to access the effects of additional nitrifiers and substrate. The initial hypothesis was that additional nitrifiers would increase the nitrification rate, based upon laboratory experiments with cultured organisms. Nitrosomonas europaea (ATCC 19718) was cultured using methods and media recipes from ATCC. This was the same culture used as a standard for

Ammonia Oxidizing Bacteria (AOB) enumeration in Chapter 2. Cultures were allowed to grow for 5 days to reach their maximum density of 1.5 x 107 cells/ml and were consistent across multiple culture events and varied by about 10%. From qPCR data, there were about 2.7 x 105 total nitrifiers (AOA + AOB) per liter in epilimnion waters in the Central

Basin. Nitrosomonas europaea was added to approximately 2x, 4x, 8x, 16x, 32x, 64x, and 128x times the original concentration of nitrifiers to observe changes in nitrification

82 rate. Ammonium (as ammonium chloride) was added to a final concentration of 5mmole

L-1 to decrease the probability of substrate limitation.

Statistical analysis was performed using IBM SPSS (v. 21). The data was graphed and analyzed in four subsets: epilimnion, hypolimnion, water column (epilimnion plus hypolimnion) and sediment data. Calculations of Pearson correlations between all measured and calculated variables were calculated using the bivariate correlation (2 tailed) option. Means of epilimnion and hypolimnion samples were compared using

ANOVA and T-tests.

Results

Water Column

The average nitrification rate (± 1 SD) in the epilimnion (N=44) was 3.1±3.2

-1 -1 μmole O2 L day . The nitrification rate in the epilimnion in 2008 (N = 6), 2009 (N =

-1 -1 19), 2010 (N =9) was 2.4 ± 2.7, 4.5 ± 3.6, 1.0 ± 0.96 μmole O2 L day respectively.

Nitrification over all 3 seasons on average accounted for 28.0 ± 23.3% of the total oxygen consumption in the epilimnion, assuming no oxygen exchange or production.

Nitrification in the epilimnion in 2008, 2009, and 2010 on average accounted 14.5 ±

15.5%, 41.2 ± 23.4%, and 13.6 ± 11.9% of the total oxygen consumption. It is acknowledged that the nitrification rate in the epilimnion is more of a nutrient transformation process than an oxygen consumptive process contributing to the development of hypoxia, unless oxygen demand exceeds flux from atmosphere and oxygen production via photosynthesis. The overall range of nitrification rates in the

83 epilimnion and hypolimnion (Tables 6 and 7) were very similar and the means were not significantly different (F(2,64)=1.325, P=0.273). Generally, the epilimnion and hypolimnion nitrification rates from the same site and time were not significantly

-1 -1 different. Nitrification rates ranged from undetectable to 4.9 µmoles O2 L day and showed no trend with respect to geography (Fig. 10). Oxygen consumed due to heterotrophic respiration (total oxygen use minus oxygen use due to nitrification) was a greater proportion of oxygen use in more eastern sites than in more western sites (Fig.

10). The range of heterotrophic respiration rates (total O2 consumption – nitrification) was much greater than, and independent of, nitrification rates, leading to a greater

contribution of nitrification to total O2 consumption at lower respiration rates (Fig. 11).

The epilimnion sites did not all follow the same temporal patterns in nitrification rates at sites that had repeated temporal sampling in the hypolimnion. There was considerable variation in rates, with no site consistently having the highest rate (Table 7).

Mean oxygen use in all hypolimnion samples (N=36) due to nitrification was 3.7

-1 -1 ± 2.9 µmoles O2 L day (± 1 S.D.). Total oxygen consumption of all samples in the

-1 -1 hypolimnion averaged 12.2 ± 5.3 µmoles O2 L day . On average, nitrification accounted for 30.4 ± 21.9% of total oxygen consumption. The mean oxygen use due to nitrification in the water column of the hypolimnion in 2008 (N = 5), 2009 (N = 17), and

2010 (N = 9) was 2.4 ± 1.9, 5.0 ± 3.0, and 1.6 ± 1.4 µmoles O2/L/d, respectively.

Nitrification accounted for 25.2 ± 13.2%, 41.0 ± 22.2%, and 19.3 ± 17.5% of the total oxygen consumption in each of the years. Total oxygen consumption rates generally

increased from east to west from 1.9 to 24.0 µmoles O2/L/d. Nitrification rates ranged

84

from undetectable to 10 µmoles O2/L/d and showed no trend with respect to longitude.

During 2010 nitrification decreased in importance in total oxygen consumption from east to west (Figure 8). Therefore nitrification decreased in importance in total oxygen

consumption from east to west. The range of heterotrophic respiration rates (total O2 consumption – nitrification) was much greater than, and independent of, nitrification

rates, leading to a greater contribution of nitrification to total O2 consumption at lower respiration rates (Fig. 9). Considering data from 2009, which had the greatest temporal coverage, the oxygen used from nitrification was generally lower in September than in

June and July (Table 6).

Most bivariate correlations between the nitrification rate and measured variables in the hypolimnion were not significant. The nitrification rate was not strongly correlated with gene copies of ammonium oxidizing bacteria (AOB), ammonia oxidizing archaea

(AOA) or total nitrifiers (AOB + AOA) (Table 8 and Fig. 7, Chapter 2). That is, the rate of nitrification was not strongly correlated to the number of nitrifying prokaryotes (or gene copies of amoA) detected, although we could show strong correlation (y=1.29x-

0.563, r2=0.973, p<0.001, Fig. 12) between numbers of nitrifiers and oxygen consumption due to nitrification in laboratory cultures of Nitrosomonas europaea (ATCC

19718). No significant correlations existed between nitrification rate or percentage of

+ - oxygen used due to nitrification and other variables such as NH4 , O2, NO3 , SRP, or DOC concentrations (Table 8). Two significant positive correlations were found; between total oxygen consumed and oxygen consumed due to nitrification, and between total oxygen use and the percentage of oxygen use due to nitrification. Correlations between

85 respiration (total oxygen use minus oxygen use due to nitrification) and measured variables led to similar conclusions with two notable results. Higher respiration rates were significantly negatively correlated (Pearson correlation coefficient =-0.375, N=29, p=0.045) with lower percentage of oxygen used due to nitrification but not correlated with oxygen use due to nitrification, at least not in a linear fashion. However, since the oxygen use due to nitrification, total oxygen use, and the percentage of oxygen use due to nitrification are not truly independent of one another (in a mathematical sense the way these variables are calculated here they are not independent, but biologically speaking they could be independent) these correlations should be viewed with caution. A wide variety of total oxygen use, oxygen use due to nitrification and percentage of oxygen use due to nitrification were observed.

Few strong or significant bivariate correlations between rate or percentage of oxygen use due to nitrification and measured environmental factors existed in the epilimnion or total water column. In the epilimnion nitrification rate and percentage of oxygen use due to nitrification, and DOC and total oxygen consumption are correlated

(Table 9). Again the first correlation must be viewed with caution as stated above.

Looking at the entire water column (Table 10), hypolimnion and epilimnion, does not give a very different correlation matrix from that of the epilimnion or hypolimnion. Total oxygen consumption and nitrification rate, nitrification rate and percentage of oxygen use due to nitrification, total nitrogen and total oxygen consumption, DOC and total oxygen consumption rates, and AOA and percentage of oxygen use due to nitrification are significantly correlated in the water column.

86

Due to a lack of strong predictors of the variation in nitrification rate, we explored within sample variation, within site variation, and inter-site variation. We conducted replicate observations (triplicate measures) on all samples drawn from all sites during

2008 and 2009 to determine the methodological variance in measurement. Within site variance among three separate samples drawn at the same site at the same time was accessed in the 2010 cruise at 9 sites. The coefficient of variation (CV) for the oxygen use due to nitrification for triplicate measures of the same sample averaged 18% (n=22).

Triplicate samples drawn at the same site had an average CV of 34% (n=9), while the CV of all sites sampled in 2010 averaged 64% (n=9). Among all sites and dates the CV was

83% (n=31).

Sediments

Mean oxygen use due to nitrification in all sediment slurries (N=29) was 7.1 ± 5.8

µmoles g-1day-1 (± 1 S.D.) with nitrification accounting for 27.0 ± 19.2% of the total oxygen consumption. In sediment slurries, total oxygen consumption over all 3 seasons was 18.6 ± 9.8 µmoles g-1day-1. The mean oxygen use due to nitrification in 2008 (n=7),

2009 (n = 15), and 2010 (n = 5) was 7.7 ± 4.3, 7.8 ± 7.0, and 4.3 ± 2.9 µmoles g-1day-1 respectively. Total oxygen consumption in 2008, 2009, and 2010 was 18.6 ± 9.8, 17.8 ±

7.8, and and14.2 ± 4.84 µmoles g-1day-1. Nitrification accounted for 27.1% ± 11.1, 25.2 ±

20.8%, 32.5 ± 25.5% of the total oxygen consumption in 2008, 2009, 2010, respectively.

The addition of sediment caused about a 15-fold increase in oxygen consumption and nitrification rates compared to hypolimnion samples. No consistent trends with respect to geography or time could be discerned, but generally the oxygen use due to nitrification

87 was lowest in July, while the percentage of oxygen use due to nitrification was lowest in

June (Table 11). There was a significant correlation (Pearson correlation coefficient=

0.429, N= 29, p=0.032) between total oxygen consumption and oxygen use due to nitrification. No other significant correlations between nitrification rate, total oxygen use, respiration, and percentage of oxygen used due to nitrification and measured environmental variables existed. Unlike in the water column, higher respiration rates were not significantly negatively correlated (Pearson correlation coefficient = -0.262, p=0.20) with lower percentage of oxygen used due to nitrification.

We explored within sample variation, within site variation, and inter site variation in sediment slurry samples. We conducted replicate observations (triplicate measures) on all samples drawn from all sites during 2008 and 2009 to determine the methodological variance in measurement. Within-site variance among three separate samples drawn at the same site at the same time was accessed in the 2010 cruise at 5 sites. The coefficient of variation (CV) for the oxygen use due to nitrification for triplicate measures of the same sample averaged 55.0% (n=20). Triplicate samples drawn at the same site had an average CV of 41.5% (n=5), while the CV of all sites sampled in 2010 averaged 63.0%

(n=5). Among all sites and dates the CV was 92.7% (n=25).

The average total sediment oxygen demand (± 1 S.D.) by intact sediment cores was 2280 µmoles m-2 day-1, with nitrification accounting for 682 ± 61.2 µmoles m-2 day-1 of that oxygen usage, or 30.4 ±10.7% of total oxygen use. No consistent geographical or temporal trends could be discerned, but generally September estimates were higher than

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June and July estimates and there were almost no temporal differences in average percentage of oxygen used due to nitrification (Table 12).

Nitrite Oxidation

There was a linear relationship between total cells and oxygen consumption rate in Nitrobacter winogradskyi (Fig. 13). The lack of oxygen consumption in samples with chlorate demonstrated the effect of the inhibitor, at least in culture. The addition of chlorate caused an order of magnitude less oxygen consumption compared to uninhibited bottles. Nitrosomonas europaea (Fig. 12) also had a linear relationship between cells and oxygen consumption rate, but in N. winogradskyi oxygen consumption was about one order of magnitude less than that of N.europaea at similar cell densities. This implies that the maximum rates of oxygen consumption of these two organisms differ, at least in pure cultures.

In field collected samples, uninhibited samples used the most oxygen, N-Serve inhibited samples used the least while chlorate inhibited samples used an intermediate amount of oxygen. In the sediments (Table 13), the mean oxygen use due to ammonia

-1 -1 oxidation to nitrite was 5.4 ± 1.3 μmole O2 g day . In the sediments, the mean oxygen

-1 -1 use due to nitrite oxidation to nitrate was 1.9 ± 1.3 μmole O2 g day . In the epilimnion

(Table 14), the mean oxygen use due to ammonia oxidation to nitrite was 2.6 ± 2.6 μmole

-1 -1 O2 l day . In the epilimnion, the mean oxygen use due to nitrite oxidation to nitrate was

-1 -1 1.2 ± 0.6 μmole O2 l day . In the hypolimnion (Table 14), the mean oxygen use due to

-1 -1 ammonia oxidation to nitrite was 2.2 ± 0.3 μmole O2 l day . In the hypolimnion (Table

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-1 - 17), the mean oxygen use due to nitrite oxidation to nitrate was 1.0 ± 0.3μmole O2 l day

1.

The effect of additional nitrifiers on nitrification rate

There were no significant statistical differences (F (8,27) = 0.0266, p=0.969) in oxygen use due to nitrification between the ambient sample (no addition of nitrifiers), a sample with additional ammonium added, and samples with additional ammonia oxidizing bacteria, Nitrosomonas europaea, added (Figure 14). Some samples with additional nitrifiers had a non-significant increase in oxygen use due to nitrification compared to the ambient concentration of nitrifiers. However, some samples with additional nitrifiers had a non-significant decrease in oxygen use due to nitrification compared to the ambient concentration of nitrifiers. The addition of ammonium did cause a slight, but not significant, increase in rate as compared to the ambient concentration of ammonium.

Discussion

Nitrification is an oxygen consumptive process, yet little attention is paid to its potential contribution to hypoxia in aquatic ecosystems. In Lake Erie, we observed significant oxygen consumption due to nitrification, suggesting that it could be an overlooked aspect when considering the recurrence of hypoxia over the past decade

(Burns et al 2005). On average, about 32% of the total oxygen consumed in the water column of the hypolimnion is due to nitrification (Tables 6, 7, 11). The percentage of oxygen consumption due to nitrification in the sediments was also about 27 or 30% (on a

90 sediment mass or areal basis, respectively). Interestingly, this corresponds closely to what would be expected by the complete oxidation of a Redfield molecule (C:N = 106:16).

Respiration would consume 106 moles of oxygen and nitrification would consume 32

moles, resulting in the percentage due to nitrification of 32/(106+32) = 23%.

Overall, there was a large amount of unexplained variation in nitrification rates and oxygen use due to nitrification in all the habitats studied . Generally the nitrification rates were higher in the epilimnion, but this difference was not always significant.

Temporal or spatial patterns were not necessarily consistent between sample sites or times in the epilimnion, hypolimnion and sediments. Some of the overall patterns were similar, i.e. the lowest average nitrification rate in the epilimnion and hypolimnion was in the September samples, but there was a high degree of variability. At higher oxygen consumption rates, nitrification had a lower contribution to total oxygen use (i.e. respiration is more important) than at lower oxygen consumption rates. The addition of epilimnion samples yielded results that were very similar to what just hypolimnion sites yielded, hinting at similar processes that govern nitrification in the hypolimnion and epilimnion. A notable exception to this was that respiration in the epilimnion (total oxygen use minus oxygen use due to nitrification) was a greater proportion of oxygen use in more eastern sites than in more western sites. Perhaps this could have be attributed to the availability (or regeneration) of ammonium, either from fixation in the numerous algal blooms, remineralization from mussels, or diffusing from the hypoxic sediments and hypolimnion. What is significant is that all samples show a similar of percentage of oxygen use due to nitrification, approximately 30%.

91

Oxygen consumption by NOBs is rarely studied in environmental samples.

According to the stoichiometry of nitrification, nitrite oxidation uses 0.5 mole of oxygen per mole of nitrite oxidized, while ammonia oxidation uses 1.5 moles (or a ratio of 3:1).

Previously, culture experiments have closely confirmed these expected results, showing ratios of ranging from 2:1 to 3:1 (Hendrikus et al. 1994, Laanbroek et al. 1994, Li and

Wang 2012). In this study, samples that had nitrite oxidation inhibited used more oxygen than samples that have had ammonia oxidation (and consequently nitrite oxidation inhibited), but less than samples that had no inhibition of nitrification. In the sediments, the mean ratio of oxygen use due to ammonia oxidation to nitrite oxidation was 3.7:1 (range 1.1:1 to 5.2:1). In the epilimnion the mean ratio of oxygen use due to ammonia oxidation to nitrite oxidation was 2.1:1 (range 0.66:1 to 4.3:1) while in the hypolimnion this ratio was 3:1 (range 1.7:1 to 5.9:1).

The deviation from the expected ratio of oxygen consumption of 3:1 between ammonia oxidizers and nitrite oxidizers could have come from multiple sources. Results from individual sites vary greatly from the mean, with environmental variables affecting each site differently. Environmental factors that influence nitrification potentially affect ammonia and nitrite oxidizers differentially and thus disrupt the linkage between AOBs and/or AOAs and NOBs (Kaplan et al. 2000). The addition of chlorate only inhibits nitrite oxidation, but not ammonia oxidation. Nitrite is toxic to many organisms and potentially inhibits growth and respiration. Nitrite can affect some AOBs by interfering with the efficient oxidation of hydroxylamine (Ward et al. 2011). Thus nitrite could build up in the samples, but nitrite concentrations were not measured in experimental bottles.

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Photoinhibition could also be an issue as it has been demonstrated as affecting nitrifiers

(Kaplan et al. 2000), especially in the epilimnion. For example, site ER43 on August 23

(site with a 0.6:1 ratio) was collected at the end of the day, after 12+ hours of natural exposure to light while site EB on August 20 (4.3:1 ratio) was collected late morning.

Even though these experiments were stored in dark coolers, samples were exposed to some light during collection and processing. Recovery times of nitrification activity from photoinhibition are unknown. The consumption of nitrite via anammox is unknown, however since conditions were oxic (except perhaps in the sediment slurry bottles), it is unlikely in anammox would have consumed much (if any) nitrite in laboratory experiments. However oxic conditions do not exist at all locations in Lake Erie, thus the contribution of anammox to nitrite consumption in the lake as a whole is unknown.

Based on our rates, nitrification is theoretically capable of utilizing all of the available oxygen present in the hypolimnion over the time that Lake Erie is stratified.

Assuming a 2 meter thick hypolimnion, an oxygen concentration of 320 µmole O2/L in the hypolimnion of Lake Erie at the time of stratification, and our mean aerial

2 nitrification estimate of 682 µmoles O2/m /d in the sediments, nitrification in the sediments could use up the available oxygen reservoir in about 900 days. Assuming a deeper hypolimnion would diminish this impact. However, using the same assumptions as above, with the addition of mean oxygen used by nitrification in the water column of the hypolimnion of 3.7 µmole O2 L/d, nitrification would use up the available oxygen reservoir in the hypolimnion in 81 days. This is well within the time frame that Lake Erie is normally stratified (Bolsenga and Herdendorf 1993, Mortimer 1987). This simplified

93 calculation is only illustrative and does not consider the coupling of nitrification with organic matter mineralization, competition for oxygen by different process, re-aeration, or hypolimnetic photosynthesis.

Our nitrification rates and percentage of oxygen used due to nitrification are similar in magnitude to other published reports. Oxygen consumption used due to nitrification in the Wloclawek Dam Reservoir accounted for 27-59% of the total oxygen consumption on average throughout the season, but at times was up to 100% (Polak

2004). In mesotrophic Grasmore Lake, nitrification accounted for 15-20% of oxygen consumption in the water column and sediments (Hall and Jeffries 1984). Muller and

Kirchesch (1983) observed nitrification consuming 20-40% of the total oxygen consumption in the Danube River, and up to 100% on the polluted Mosel River. In the case of the Pearl River, nitrification could account for almost all of the oxygen demand

(Dai et al. 2006). Rates of nitrification in the literature range from 0 to 160 µmoles N L-

1day-1, with lower rates in more oligotrophic and open water systems (Bianchi et al. 1999

Bianchi et al. 1994, Berounsky and Nixon 1990) than in more eutrophic (Pauer and Auer

2000, Miranda et al. 2007) and estuarine systems (Caffrey et al. 2003). These nitrification rates equate to oxygen consumption rates of 0 to 320 µmoles L-1day

(assuming 2 moles of oxygen per mole of ammonia oxidized). DiToro and Connolly

(1980), in a modeling study to understand oxygen consumption in Lake Erie, include nitrification as a parameter in their model. The rate of nitrification in their model was based on ammonium concentrations in the water column. With their equation and the current concentrations of ammonium ranging from 0.25 to 2.0 μmole L-1, the percentage

94 oxygen use due to nitrification in Lake Erie is from 1% to 21%, relative to the published hypolimnetic volumetric oxygen demand in Lake Erie from Burns et al. (2005) of 2.25 to

4.0 mg L-1 month-1. DiToro and Connolly (1980) concluded that nitrification was an important process for nutrient transformation, but not a large contributor to oxygen consumption. Our data suggests that nitrification can consume all of the available oxygen present in the hypolimnion, but when other oxygen consumptive processes are large, the relative contribution of nitrification would be reduced.

A consistent finding was variability in the distribution of nitrification rates between sites or sampling times. Few strong geographic or temporal trends could be discerned. Prior research has demonstrated the variability in nitrification rates, spatially and temporally. Nitrification rates can vary by an order of magnitude or more across sites sampled within a short temporal period (Bianchi et al. 1999, Dai et al. 2006,

Miranda et al. 2008). Similar patterns of variability can be found temporally at the same site with nitrification rates differing by up to an order of magnitude over the sampling period (Hall and Jeffries 1984, J.M. de Bie et al. 2002, Polak 2006).

What controls or influences the nitrification rate is still a mostly unanswered question. We did not find any strong bivariate correlations between nitrification rates and any of the measured environmental variables regardless of what subset of data examined, epilimnion, hypolimnion, water column (epilimnion plus hypolimnion samples), or sediments. We did find evidence suggesting that nitrification contributes less to oxygen use at sites where respiration is higher, often in the more eutrophic sites of the western part of Lake Erie. Prior research has shown correlations between nitrification rate and

95 ammonium concentrations (Bianchi et al. 1994, 1999, Polak 2004), and the lack of correlation in in our study implies that ammonium concentration was not a limiting factor for nitrification in Lake Erie. In cultures, oxygen concentration does not affect nitrification rates except at concentrations below 2 mg/L (Laanbroek et al. 1994,

Stenstrom and Poduska 1980). We found no relationship between oxygen concentration and nitrification, although we re-oxygenated our samples upon incubation. In some studies, nitrifier abundance has been correlated with nitrification rate (Caffey et al. 2007,

Guby-Rangin et al. 2010, Di et al. 2010, Bianchi et al. 1999), but this was not always the case (Santoro et al. 2010). Gene abundance indicating the presence of a microbe may not accurately indicate gene expression and activity of that microbe. Not all nitrifiers may be active, so merely identifying the presence of nitrifying prokaryotes may not be a reliable means of estimating nitrification rates (Jia and Conrad 2009). Other environmental factors such as pH (Nicol et al. 2008, Strauss et al. 2002), C:N ratio

(Strauss et al. 2002, Strauss and Lambertii 2000) competition and predation (Xiao et al.

2010, Lavrentyev et al. 1997) could affect the nitrification rate and were not considered here. Also the measurements of substrate and product are static measurements of pool size. The pool of ammonium (or other nutrients) could be small either because of high demand (high turnover rate) or due to low supply (low regeneration rate). Miranda et al.

(2007) demonstrated that nitrification rate was more likely regulated by renewal rates than the pool size of ammonium. The congruence of our results with predictions made by

Redfield stoichiometry may be indicative of this coupling with mineralization rates. We did find a negative correlation between respiration rate and percentage of oxygen used by

96 nitrification suggesting that nitrification contributes less to oxygen use at more eutrophic sites. Prior research has shown correlations between nitrification rate and ammonium concentrations (Bianchi et al. 1994, 1999, Polak 2004), implying that ammonium was not a limiting factor for nitrification in Lake Erie. Often the addition of ammonium caused an increase in the nitrification rate and also increased the overall oxygen consumption rate. Thus, the net effect on percentage of oxygen use due to nitrification was negligible.

In cultures, oxygen concentration does not affect nitrification rates except at concentrations below 2 mg L-1 (Laanbroek et al. 1994, Stenstrom and Poduska 1980).

The addition of nitrifiers had little to no effect on the nitrification rate. The nitrifiers added were cultured organisms, selected to grow in a rich medium in a very simple ecosystem with no competition with other organisms or predation. The environment they were added to was not simple, i.e. it was a sample drawn from the natural environment with all of the complexities of compounds and species interactions. Perhaps the added organisms just were not adapted to the environment they were added to and did not nitrify at their optimal rate. Activity of nitrifiers could also influence rate, as there can be a difference between gene abundance and activity. Other environmental factors such as pH (Nicol et al. 2008, Strauss et al. 2002), C:N ratio (Strauss et al. 2002, Strauss and

Lambertii 2000) competition and predation (Xiao et al. 2010, Lavrentyev et al. 1997) could affect the nitrification rate and were not considered here. Also the measurements of substrate and product are static measurements of pool size. The pool of ammonium (or other nutrients) could be small either because of high demand (high turnover rate) or due to low supply (low regeneration rate). Miranda et al. (2007) demonstrated that

97 nitrification rate was more likely regulated by renewal rates than the pool size of ammonium.

Despite our inability to clearly establish factors that control nitrification rates in

Lake Erie, nitrification is a contributing factor to the formation of hypoxia in Lake Erie and other aquatic ecosystems. This is not a new or unaccounted for process, but one that is often not considered in a context independent from the total rate of oxygen consumption. On average, nitrification does not dominate oxygen consumption, yet there are some times when it appears to be more or less important than what would be expected from Redfield stoichiometry, perhaps uncoupled from mineralization of organic matter.

Taken alone in a hypothetical context, the rate of nitrification we observed has the capacity to significantly deplete the oxygen reservoir in the hypolimnion of Lake Erie over the stratified period. Although hypoxia is not a problem in Lake Superior, evidence shows the significant impact this process can have on other large lakes (Finlay et al.

2007, Small et al. 2013). If nitrification is tightly coupled to mineralization of organic matter and ammonification, then it is unlikely that nitrification would function to this hypothetical extent – heterotrophic respiration would dominate oxygen consumption.

However, nitrification could be coupled to other ammonium producing processes and function to a greater or lesser extent. External (non-) point sources of ammonium could be important (e.g. Onondaga Lake; Pauer and Auer, 2000), but unlikely in the hypolimnion of Lake Erie. Dissimilatory nitrate reduction to ammonia (DNRA) could provide a source of ammonium and would present a potential positive feedback, since nitrification could reciprocate in supplying nitrate. Nitrification and DNRA would likely

98 be spatially segregated in oxic and anoxic sites, and limited by the flux of ammonium or nitrate across these sites. Anammox, on the other hand, would remove ammonium from the system causing nitrification to be less important. Most of these linkages are poorly understood.

Reducing the extent of hypoxia in Lake Erie has been a major management focus mainly addressed through reducing TP loading (Charlton 1980, Burns et al 2005). Except in localized point-source cases of ammonium or organic N loading, it seems unlikely that reducing N loading would improve hypoxia to a significant extent through the control of nitrification. Although there is significant controversy about the role of N reduction for eutrophication abatement (e.g., Lewis and Wurtsbaugh 2008, Schindler 2012), the importance of N for aquatic ecosystems, beyond simply limiting algal growth, warrants continued and careful consideration. Beyond oxygen consumption, nitrification further impacts aquatic environments in several ways (e.g. ammonia or nitrate toxicity and greenhouse gas production) that may warrant management consideration and an increased basic understanding of this process.

99

Acknowledgements

This work was supported by Ohio Sea Grant R/ER082 and Kent State Graduate Student

Senate.

We would also like to thank Heather Kirkpatrick, Josh Smith, Jennifer Clevinger,

Moumita Moitra, Jerry Maucemer, numerous undergraduate assistants, the captains and crews of RV Lake Guardian, RV Erie Monitor, and CCG Limnos for their assistance.

100

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Table 6: Rate of oxygen consumption (μmole L-1 day-1), standard deviation and percentage of oxygen consumption due to nitrification in hypolimnion samples from Lake Erie 2009. NS=not sampled.

Site June July August September Average 43 6.1±0.8 0.5±0.2 5.9±0.3 5.9±0.3 4.6 49.3% 17.7% 33.3% 33.3% 33.4%

73 8.3±0.2 7.8±0.9 1.7±0.6 5.9 46.4% 41.3% NS 9.60% 32.4%

78 6.8±0.9 10.3±1.5 2.8±0.9 6.6 45.5% 87.9% NS 15.6% 49.7%

30 4.0±0.5 3.9±0.2 1.9±0.4 3.3 59.6% 29.6% NS 10.5% 32.2%

15 2.0±0.7 4.2±0.8 3.0 35.4% 71.9% NS NS 53.6%

Average 5.4 5.3 3.1 4.6 47.2% 49.7% 17.3% 38.1%

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Table 7: Nitrification rate (μmole N L-1 day-1), percentage of total oxygen use due to nitrification and standard deviation in epilimnion samples from Lake Erie 2009. NS=not sampled.

Site June July August September Average 43 0.9±0.8 4.4±2.3 NS 1.6±1.0 2.3 16.7% 73.1% 36.73% 42.2%

73 4.9±0.23 2.3±2.5 0.8±0.4 2.6 69.2% 37.9% NS 32.4% 46.5%

78 0.8±0.4 1.4±0.7 0.9±0.7 1.1 14.8% 9.1% NS 37.4% 20.58%

30 2.9±0.4 4.3±1.4 2.0±0.23 3.1 60.8% 75.0% NS 52.7% 62.8%

15 3.8±0.7 1.5±0.9 2.7 61.5% 34.9% NS NS 48.2%

Average 2.7 2.8 1.3 2.8 44.6% 46.0% 39.93% 44.1%

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Table 8: Correlations between measured environmental variables, total oxygen consumption rate, nitrification rate, and percentage of oxygen used due to nitrification in hypolimnion samples. * Significant at p = 0.05.

Total O2 Nitrification Nitrification consumed % O2 used Total O consumed (μmoles O L-1 d-1; 2 2 0.317 -0.058 n=32) -1 -1 Nitrification rate (μmoles O2 L d ; n=32) 0.317 0.670* SRP (μmoles P L-1; n=15) 0.195 0.048 0.008 + -1 NH4 (μmoles N L ; n=25) -0.031 -0.025 0.004 - -1 NO3 (μmoles N L ; n=27) -0.190 -0.195 -0.217 DOC (μmoles C L-1; n=29) 0.053 0.102 0.068 TN (μmoles N L-1; n=29) -0.460* 0.029 0.331 -1 O2 (μmoles O2 L ; n=24) 0.117 -0.280 -0.293 AOB (cells L-1; n=25) 0.235 0.161 -0.058 AOA (cells L-1; n=26) 0.246 -0.036 -0.260

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Table 9: Correlations between measured environmental variables and total oxygen consumption rate, nitrification rate, and percentage of oxygen used due to nitrification in epilimnion samples. * = Significant at p=0.05

Total Oxygen Nitrification Rate Percentage Consumption (μmole L-1 day-1), oxygen use Rate (μmole L-1 due to day-1) nitrification Total Oxygen Consumption Rate 0.249 -0.177 (n=32) (μmole L-1 day-1) Nitrification Rate (n=32) (μmole L-1 0.249 0.670* day-1) Soluble Reactive Phosphorus (SRP) 0.303 0.117 0.128 (n=32) (μmole L-1) Ammonium (n=27) (μmole L-1) 0.039 0.024 0.189 -1 Nitrate (n=32) (μmole L ) 0.151 -0.028 -0.015 Dissolved Organic Carbon (DOC) 0.707* -0.216 -0.021 (n=32) (mg L-1) Total Nitrogen (n=32) (mg L-1) -0.106 -0.122 -0.057 Oxygen (n=24) (μmole L-1) 0.389 0.049 0.292 Ammonia Oxidizing Bacteria (n=26) -0.059 0.171 -0.538 (cells L-1) Ammonia Oxidizing Archaea (n=26) -0.240 -0.397* -0.042 (cells L-1)

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Table 10: Correlations between measured environmental variables and total oxygen consumption rate, nitrification rate, and percentage of oxygen used due to nitrification in water column samples. * = Significant at p=0.05

Total Oxygen Nitrification Percentage Consumption Rate (μmole Oxygen Use Rate (μmole L-1 L-1 day-1) Due to day-1) Nitrification Total Oxygen Consumption Rate (n=60) 0.304* -0.059 (μmole L-1 day-1) Nitrification rate (n=60) (μmole L-1 day-1) 0.304* 0.882* Soluble Reactive Phosphorus (SRP) 0.286 0.081 0.074 (n=59) Ammonium (n=51) (μmole L-1) 0.021 0.035 0.123 Nitrate (n=59) (μmole L-1) 0.006 -0.121 -0.016 Dissolved Organic Carbon (DOC) (n=59) 0.565* -0.137 -0.047 (mg L-1) Total Nitrogen (n=59) (mg L-1) -0.268* -0.064 0.080 Oxygen (n=45) (μmole L) 0.270 0.083 0.045 Ammonia Oxidizing Bacteria (n=50) (cells 0.138 0.167 -0.104 L-1) Ammonia Oxidizing Archaea (n=51) (cells 0.101 -.0313* -0.289* L-1)

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Table 11: Rate of oxygen consumption (μmole g-1 day-1), standard deviation and percentage of oxygen consumption due to nitrification in sediment slurries from Lake Erie 2009. NS=not sampled.

Site June July September Average 43 1.8±0.3 0.9±0.3 5.5±0.4 2.7 6.70% 17.9% 18.3% 14.3%

73 3.9±0.2 8.1±0.1 2.2±0.2 4.7 4.10% 30.5% 61.7% 22.1%

78M 3.8±0.4 1.4±0.2 3.3±1.0 2.8 11.5% 50.6% 6.5% 22.8%

30 3.0±0.8 0.3±0.4 2.0±0.1 1.8 11.7% 5.20% 52.7% 23.2%

15 1.7±0.1 0.6±0.3 1.1 58.8% 21.4% NS 40.1%

Average 2.8 2.3 3.3 2.8 18.6% 25.1% 34.8% 26.2%

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Table 12: Rate of oxygen consumption, standard deviation (μmole m-2 day-1) and percentage of oxygen consumption due to nitrification in intact sediment cores from Lake Erie 2009.

June July September Average 43 575±151 324±50.0 1170±22.3 690 25.9% 20.7% 39.5% 28.7%

73 468±112 281±18.0 755±67.9 501 24.8% 56.3% 26.7% 35.9%

78M 481±250 685±119 789±129 652 29.7% 27.10% 29.2% 28.50%

30 775±43.0 1060±76.3 819±56.8 886 41.3% 15.7% 27.4% 28.2%

Average 767 588 884 746 30.4% 29.9% 30.7% 30.4%

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Table 13: Oxygen consumption due to ammonia oxidation and nitrite oxidation in sediment slurry samples from Lake Erie. NS=not sampled.

Oxygen used Oxygen used due to ammonia due to nitrite oxidation oxidation date site (μmole/g/d) (μmole/g/d) 8/23/09 ER43 4.29 0.81 8/20/09 EB 7.82 1.58 9/13/09 ER30 4.76 4.16 9/13/09 ER43 5.91 1.37 9/13/09 ER73 4.39 2.00 9/13/09 ER78M 5.12 1.37 Mean 5.38 1.85

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Table 14: Oxygen consumption due to ammonia oxidation and nitrite oxidation in water column samples from Lake Erie. NS=not sampled

Oxygen Oxygen used due to used due to ammonia nitrite Hypolimnion oxidation oxidation Date Site or Epilimnion (μmole/l/d) (μmole/l/d) 8/23/09 ER43 Epilimnion 0.32 0.48 9/18/09 ER30 Epilimnion 2.82 1.08 9/18/09 ER43 Epilimnion 1.80 1.44 9/18/09 ER73 Epilimnion 1.92 1.65 9/18/09 ER78M Epilimnion 1.34 0.54 8/20/09 EB Epilimnion 7.60 1.75 Mean 2.6 1.7

8/23/09 ER43 Hypolimnion NS NS 9/18/09 ER30 Hypolimnion 1.74 0.78 9/18/09 ER43 Hypolimnion 2.44 1.42 9/18/09 ER73 Hypolimnion 3.33 1.50 9/18/09 ER78M Hypolimnion 2.38 0.40 8/20/09 EB Hypolimnion NS NS Mean 2.2 1.0

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25.00

-1 20.00 d -1

L 15.00 2

10.00

μmoles O 5.00

0.00 82.50 82.00 81.50 81.00 80.50 80.00 79.50 Longtitude (degrees)

Figure 8: Oxygen consumption rate (open circles) in, and oxygen consumed due to nitrification (closed diamonds) in hypolimnion samples in a longitudinal transect in Lake Erie 2010. Error bars are the standard deviation.

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100 90 80 70 60 50 40 30 20 10 0 % oxygen use due to nitrification nitrification to use due % oxygen 0 5 10 15 20 25

Respiration rate µmole O2/L/d

Figure 9: Respiration rate (total oxygen use minus oxygen used due to nitrification) and percentage of total oxygen use due to nitrification in the hypolimnion of Lake Erie 2008- 2010.

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14 12 moles moles µ 10 8 -1

Day 6 -1

L 4 2 0

Oxygen consumption rtae ( rtae Oxygen consumption 82.5 82 81.5 81 80.5 80 79.5 Longtitude (degrees)

Figure 10: Oxygen consumption rate (open circles) in, and oxygen consumed due to nitrification (closed diamonds) in epilimnion samples in a longitudinal transect in Lake

Erie 2010. Error bars are the standard deviation.

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80 70 60 50 40 30

to nitrification 20 10 0 percentgage of oxygen use due percentgage 0.0 10.0 20.0 30.0 40.0 -1 -1 Respiration rate μmoles O2 L day

Figure 11. Respiration rate and percentage of oxygen used due to nitrification in epilimnion samples 2008-2010.

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70 -1 60 50 day 2 40 30 20 10 µmoles O µmoles 0 0.00 10.00 20.00 30.00 40.00 50.00 Gene copies (x107) in a culture of Nitrosomonas europaea cells

Figure 12. Total oxygen use by Nitrosomonas europaea cells in artificial lake water

(y=1.2979x- 0.5643, R2=0.97).

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20 18 16 -1

day 14 -1 12 10 8 6

umoles oxygen l oxygen umoles 4 2 0 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Total Nitrobacter cells (x107)

Figure 13: Total oxygen use by Nitrobacter winogradskyi (ATCC # 25391) cells in artificial lake water (y=4.5203x- 0.4313 R2=0.9753).

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)

-1 2.5

day 2 -1 1.5 1 0.5 0 Oxygen use Oxygen due to moles L moles ( μ nitrification

Nitrosomonas additions relative to starting amount

Figure 14: The effect of additional nitrifiers on oxygen use due to nitrification in Lake

Erie water, Ambient = original amount of nitrifiers in ambient water sample or approximately 1.7x105 nitrifiers L-1, 2x= twice the original amount of nitrifiers etc. Error bars are standard deviation. No significant difference between treatments (F(8,27) =

0.0266, p = 0.969).

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Chapter 4 General discussion and conclusions

Nitrification contributes to oxygen consumption and the development of hypoxia in Lake Erie. On average, 28% (epilimnion), 30% (hypolimnion), 27% (sediment slurry) and 30% (intact cores) of the total oxygen demand was due to nitrification. This was fairly consistent regardless of how the dataset was divided up, either temporally or spatially. Locally, nitrification consumed up to 80% of the total oxygen consumed.

For nitrification to take place, organisms such as Nitrosomonas and Nitrobacter that have the genes for nitrification must be present in the environment. The gene amoA is of particular importance since it codes for part of the enzyme ammonia monooxygenase (AMO) that catalyzes the first step in nitrification, the oxidation of ammonia to hydroxylamine. In Chapter 2, amoA containing bacteria and archaea were enumerated in Lake Erie via qPCR and were found in all samples in quantities similar to what has been found in other studies (see references in Chapter 2). Comparing the sediment environment to either the epilimnion or the hypolimnion, the ratios of AOA to

AOB were more enriched in the sediments. The sediments had AOA as the dominant nitrifier, while in the water column there was more parity between AOB and AOA abundances. The abundances of AOA and AOB, either individually or as a combined total, exhibited large variation with respect to site or date. Some possible trends, such as higher nitrifier numbers during the onset of hypoxia (mid to late season), or higher nitrifier numbers in more western site were observed. However these trends were not

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consistent or generalizable over the entire lake. The variation in nitrifier numbers, either

AOA or AOB, does not appear to be a product of methodological variation but actual environmental variation as the within sample variation is considerably less than variation among samples.

The ubiquitous presence of archaea has been confirmed in many non-extreme environments (Robinson et al. 2005), including Lake Erie. My data suggests that archaea and/or archaeal nitrifiers could have a substantial effect on ecosystem functions in Lake

Erie. Examining the entire prokaryote community in Lake Erie, archaea comprised from

1 to 4% of the total prokaryote community, with the highest percentage in the epilimnion.

This is fairly consistent with other literature values (Hatzenpichler 2012, Herndl et al.

2005, Likens 2010, Schwarz 2010). The estimate of the archaeal contribution to the prokaryote community is likely a conservative one as it was assumed that each cell only had 1 copy of 16s rDNA per cell. The actual value is probably higher. The use of 4.2 16S rDNA cell-1 as a mean in bacterial cells (Větrovský and Baldrian 2013) would lead to a lower estimate of bacterial cells and a higher archaeal presence (approx. 4-16%). In Lake

Erie, the archaeal nitrifiers comprised a larger portion (20-90%) of the archaeal community than did the bacterial nitrifiers (less than 0.1%) to the bacterial community, especially in the sediments. Actual numbers of archaea capable of ammonia oxidation are likely to be lower, as nitrifying activity has not been demonstrated in all amoA containing archaea (Hatzenpichler 2012).

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My data did not reveal a strong bivariate correlation between nitrifiers and nitrification. In some studies, nitrifier abundance has been more strongly correlated with nitrification rate than in this study (Caffey et al. 2007, Guby-Rangin et al. 2010, Di et al.

2010, Bianchi et al. 1999) but this is not always the case as the inactivity of the nitrifiers present in environmental samples could account for the lack of correlation between nitrifier number and nitrification rate (Santoro et al. 2010). The activity of putative nitrifiers identified via qPCR was unknown, so merely identifying the presence of nitrifying prokaryotes may not be a reliable means of estimating nitrification rates (Jia and Conrad 2009). Further confirmation of nitrifier activity would have required the identification and quantification of gene transcripts or proteins. In the laboratory studies performed with Nitrosomonas and Nitrobacter that demonstrated a strong relationship between nitrifier and nitrification rate, many of the cells were assumed to be actively nitrifying and due to similar genetic makeup of the strain, the cells were nitrifying at similar rates. The differences in nitrification rate in laboratory samples due to differences in numbers of nitrifiers over an order of magnitude led to differences in nitrification rate of about an order of magnitude. The environmental samples likely did not have a single species of nitrifier, there was probably many (at least 2 as AOA and AOB were enumerated). In environmental samples there was about an order of magnitude of difference in nitrification rates and nitrifier numbers, but there was a lack of linear relationship between the two. Differences in community composition and differences between rates of nitrification among different species in differing niches (Ke et al. 2013)

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could account for that lack of linear relationship. The addition of nitrifiers, at least a cultured one, had little to no effect on the nitrification rate (Fig. 14).

Environmental factors such as pH (Nicol et al. 2008, Wankel et al 2011, Wessen et al 2010,) ammonia (Jia and Conrad 2009, Ando et al. 2009, Sims et al. 2012), TN

(Wessen et al. 2010), nitrate (Ando et al. 2009), and predation (Xiao et al. 2010) have been cited as being correlated with nitrifiers. My results, as shown by the weak correlations between measured environmental factors and nitrifiers, do not strongly identify possible environmental factors correlated with nitrifier abundances and distribution. This leaves open what factors (or combination of factors) control nitrifier abundance for future studies and whether these correlations are actually causation.

The functional evaluation of nitrifier activity in the epilimnion, hypolimnion and sediments was undertaken by measuring and comparing the disappearance of the substrate oxygen in inhibited and uninhibited BOD bottles in Chapter 3. In Lake Erie there was significant oxygen consumption due to nitrification, on average about 30% of the total oxygen consumed in the water column and sediments was due to nitrification, not greatly differing (on average) from what would be expected from the Redfield ratio.

There was variability in the distribution of nitrification rates between sites or sampling times with few strong geographic or temporal trends. Generally the nitrification rates were slightly higher in the epilimnion, but this difference was not always significant. As the TDOC was not greatly different (or significantly different) between the hypolimnion and epilimnion samples, the total amount of substrate (ammonia) available for nitrification via decomposition, assuming the Redfield ratios of C:N, was not greatly

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different. There was probably little inhibition of nitrification due to lack of oxygen in samples, especially considering the re-oxygenation of samples, but resumption of full nitrifying activity in re-oxygenated hypolimnion samples could have been delayed in hypolimnion samples. Temporal or spatial patterns were not necessarily consistent between sample sites or times in the epilimnion, hypolimnion and sediments. At higher oxygen consumption rates, nitrification had a lower contribution to total oxygen use (i.e. respiration was more important) than at lower oxygen consumption rates. Nitrification alone could use up the available oxygen reservoir in the hypolimnion in 81 days, well within the time frame that Lake Erie is normally stratified, ignoring other oxygen consumptive processes.

Correlations with sampled environmental variables, nitrification rate, percentage of oxygen used due to nitrification, or numbers of nitrifiers (or gene copies) were weak regardless of what subset of data examined, epilimnion, hypolimnion, water column

(epilimnion plus hypolimnion samples), or sediments. Prior research has shown correlations between nitrification rate and ammonium concentrations (Bianchi et al. 1994,

1999, Polak 2004), thus implying that ammonium was not a limiting factor for nitrification in Lake Erie. The measurements of environmental factors were static measurements of pool size. The pool of ammonium (or other nutrients) could be small either because of high demand (high turnover rate) or due to low supply (low regeneration rate). Miranda et al. (2007) demonstrated that nitrification rate was more likely regulated by renewal rates than the pool size of ammonium.

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Breaking down nitrification into ammonia oxidation and nitrite oxidation leads to similar results as looking at nitrification as a whole, that is assuming that inhibiting ammonia oxidation also inhibits nitrite oxidation. Nitrite oxidation was variable and followed no obvious geographic patterns at least at the scale sampled. There could have been patterns at different scales than what was sampled that yet remain to be discovered.

From the limited sampling done on Lake Erie nitrite oxidation used less oxygen then did ammonia oxidation with nitrite oxidation consuming close to the expected ratio of 2 or

3:1 less oxygen than ammonia oxidation on average (Laanbroek et al. 1994, Li and Wang

2012). Nitrite oxidation should use 0.5 mole of oxygen per mole of nitrite oxidized, while ammonia oxidation should use 1.5 moles (or a ratio of 3:1) for a total of 2 moles of oxygen per oxidized ammonia. In the sediments, this ratio was 3.6:1. In the epilimnion the ratio was 2.1:1 while in the hypolimnion, the ratio was 3.1:1. The buildup of nitrite in chlorate inhibited samples and methodology could have affected the results, especially in the water column samples.

One consistent theme was that there was a large variation in nitrification rates, percentage of oxygen use due to nitrification, and nitrifier numbers between sites, depths and temporally. Variation among sampling sites was larger than variation within replicates from the site, especially shown by the RV Limnos sampling regime were the variation between samples was 2x the variation due to methodological variation. Nitrification rates have been shown to vary by an order of magnitude or more across sites sampled within a short temporal period (Bianchi et al. 1999, Dai et al. 2006,

Miranda et al. 2008). Similar patterns of variability can be found temporally at the same

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site with nitrification rates differing by up to an order of magnitude over the sampling period in numerous habitat types (Hall and Jeffries 1984, De Bie et al. 2002, Polak 2006).

Further questions and avenues of research arose from the current research.

Nitrification is more than just a nutrient transformation process in Lake Erie. Oxygen consumption due to nitrification can be a major consumer of oxygen. There were gene related to nitrification detected, but the identification of the nitrifying organisms remains an open question. Based on gene numbers, there was a large potential role of AOA, but whether those AOA are actively nitrifying is unknown. Understanding the control of nitrifying activity and the distribution of AOA and AOB would be of significant importance in understanding nitrogen and oxygen cycling in lakes.

The reason(s) for the development of hypoxia in the Central Basin of Lake Erie are complex. Nitrification is not only important in nutrient transformations, it is important in oxygen dynamics in Lake Erie. Controlling hypoxia may require methods beyond just controlling total phosphorus loadings. Nitrification, nutrient loadings (both quantity and type), global climate change, introductions of exotic species, and changes in human activities need to be considered in our management and modeling regimes. The

Lake Erie ecosystem is heavily impacted by human actions and the consequences of these actions have not been completely addressed. In addition to the effects of nutrient transformation and oxygen consumption of oxygen by nitrification, nitrification contributes to conditions that foster denitrification leading to the export of nitrogen from the system and the release of phosphorus from the sediments further highlighting the

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importance of including the impacts of nitrification in nutrient and water quality management plans.

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