REGULATION OF BENTHIC ALGAL STRUCTURE AND FUNCTION IN NORTHERN
BOREAL WETLANDS
By
Allison Renee Rober

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Zoology
Ecology, Evolutionary Biology, and Behavior
2012

ABSTRACT
REGULATION OF BENTHIC ALGAL STRUCTURE AND FUNCTION IN NORTHERN
BOREAL WETLANDS
By
Allison Renee Rober
Algae are important to many of the processes that characterize wetland ecosystems.
Despite their importance, we know relatively little about the factors that regulate algal
communities in wetlands. This is particularly true for northern boreal regions where wetlands are
abundant and are considered to be extremely vulnerable to disturbances associated with climate
change. My dissertation research investigates how nutrients, grazing, light, and hydrology
regulate algal primary production and taxonomic structure in high latitude wetlands.
I documented spatial and temporal variability in algal structure and function in six
northern boreal wetlands in interior Alaska to determine the contribution of algal primary
production to wetland primary production and evaluate the relationships between environmental
parameters characteristic of different wetland types and algal productivity, abundance, and
taxonomic composition. There were significant spatial and seasonal differences in algal biomass
and taxonomic composition both within and between wetlands. Measures of algal productivity
were equivalent, and sometimes higher, than macrophyte production, contributing up to 50% of
wetland primary production. Water depth and nutrients were significant predictors of algal
taxonomic composition.
In Chapter 3 I evaluated the potential for grazers to regulate benthic algal communities in
boreal wetlands with future increases in nutrient concentrations using an in situ mesocosm
experiment in an Alaskan marsh. I tested the hypothesis that nutrient enrichment stimulates algal
accumulation and grazers regulate algal responses to nutrients by suppressing algal accumulation

but increasing productivity through nutrient recycling. My results support my hypothesis and
provide some of the first evidence that nutrients and grazing are important factors regulating
benthic algal biomass and community composition in a northern boreal wetland. My data also
suggest the potential importance of consumer-driven nutrient recycling to algal productivity and
wetland biogeochemistry.
In Chapter 4 I investigated how changes in light availability, in the presence and absence
of grazing, limit the ability for algae to respond to nutrient inputs using an in situ mesocosm
experiment. I hypothesized that light limitation and herbivory are both responsible for regulating
the algal response to nutrient enrichment. My analyses indicate that grazers are responsible for
maintaining low algal biomass even with increased nutrient availability, not light.
In the final chapter, I evaluated how changes in hydrology predicted with climate change
might influence algal community structure in boreal peatlands. I monitored shifts in algal
taxonomic composition in response to an ecosystem-scale water table manipulation, including
both drought and flooding conditions in a rich fen in interior Alaska. The observed changes in
algal taxonomic composition in response to fluctuations in water table suggests that increased
frequency of drought and flooding events expected with climate change may significantly alter
algal structure and function in boreal wetlands. Furthermore, my results suggest the potential
importance of nitrogen-fixation by cyanobacteria to wetland biogeochemistry.
The results of this dissertation improve our understanding of the abiotic and biotic factors
that regulate benthic algal productivity and taxonomic composition in northern boreal wetlands.
My results indicate that algae are an ecologically important component of wetland ecosystems.
These results have important implications for energy flow in boreal wetlands and indicate that
the current wetland structure and function may be altered by climate change.

ACKNOWLEDGEMENTS

I would like to thank my advisor Jan Stevenson for exposing me to the world of algae as an
undergraduate and giving me the opportunity to begin my scientific discovery in his lab. I also
want to thank Jan for seeing my potential and taking me on as a graduate student, this
dissertation research would not have been possible if it was not for Jan’s support. I would like to
thank my lab mates and committee members Drs. Elena Litchman, Richard Merritt, and Scott
Peacor for helpful feedback during all stages of planning and conducting this research and during
manuscript preparation. I would like to thank the EEBB program, the Graduate School,
Department of Zoology, and College of Natural Science at MSU as well as the Society for
Freshwater Science, the Phycological Society, and The Wetland Foundation for providing
funding that was necessary to conduct this dissertation research. I would like to thank Steven
Pierce at the Center for Statistical Consulting (CSTAT) at MSU for assistance with statistical
analysis. I would also like to thank the Bonanza Creek LTER and the University of Alaska
Fairbanks for use of their facilities, Dr. Merritt Turetsky for providing logistical support while
conducting research in Alaska, and Dr. Jeremy Jones at UAF for allowing me to analyze water
chemistry samples in his lab.
Most of all I would like to thank my best friend, lifetime collaborator, and husband
Kevin, for all his support. Kevin showed me see how hard I needed to work to reach my goals
and helped me get there. I would also like to thank my family for their support and Bonnie for
her companionship.

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TABLE OF CONTENTS

LIST OF TABLES............................................................................................................. vii
LIST OF FIGURES ........................................................................................................... viii
CHAPTER 1
INTRODUCTION .............................................................................................................. 1
1.1 Benthic algal ecology in freshwater wetlands................................................... 1
1.2 Environmental regulation of benthic algae in wetlands .................................... 1
1.3 Investigating environmental controls on wetland algal structure and function. 4
CHAPTER 2
SPATIAL AND TEMPORAL VARIABILITY OF ALGAL COMMUNITY DYNAMICS AND
PRODUCTIVITY IN LATERAL FLOODPLAIN WETLANDS ALONG THE TANANA
RIVER, ALASKA ............................................................................................................ 12
2.1 Introduction ..................................................................................................... 12
2.2 Methods ........................................................................................................... 15
2.3 Results ............................................................................................................. 21
2.4 Discussion ....................................................................................................... 25
CHAPTER 3
REGULATION OF ALGAL STRUCTURE AND FUNCTION BY NUTRIENTS AND
GRAZING IN A BOREAL WETLAND.......................................................................... 44
3.1 Introduction ..................................................................................................... 44
3.2 Methods ........................................................................................................... 47
3.3 Results ............................................................................................................. 51
3.4 Discussion........................................................................................................ 53
CHAPTER 4
THE ROLE OF LIGHT LIMITATION AND HERBIVORY ON ALGAL RESPONSE TO
NUTRIENT INPUTS IN A BOREAL MARSH, ALASKA ............................................ 70
4.1 Introduction ..................................................................................................... 70
4.2 Methods ........................................................................................................... 72
4.3 Results ............................................................................................................. 76
4.4 Discussion ...................................................................................................... 79
CHAPTER 5
ALGAL COMMUNITY RESPONSE TO EXPERIMENTAL AND INTERANNUAL
VARIATION IN HYDROLOGY IN AN ALASKAN BOREAL FEN ........................... 95
5.1 Introduction ..................................................................................................... 95
5.2 Methods ........................................................................................................... 97
5.3 Results ............................................................................................................. 102
5.4 Discussion ....................................................................................................... 104

v

CHAPTER 6
CONCLUSION................................................................................................................. 120
6.0 Summary ......................................................................................................... 120
6.1 Environmental controls on benthic algal structure and function..................... 120
6.2 The contribution of algal productivity to total wetland primary production... 123
6.3 Role of algal taxonomic composition in wetland ecosystem function............ 124
6.4 Implications of climate change on benthic algal structure and function......... 126

vi

LIST OF TABLES

Table 2.1 Mean (ranges) of surface water parameters in six wetlands (2 peatlands, 4 marshes)
over 12 weeks during the 2009 summer growing season ..............................................................31
Table 2.2 Mean relative abundance of algal taxa in six wetlands (2 peatlands, 4 marshes) over 12
weeks during the 2009 summer growing season. Table includes only taxa with > 5% relative
abundance in at least one of the wetland sites ...............................................................................32
Table 4.1 Analysis of variance table showing the responses of benthic algal biomass measured as
ash-free dry mass (AFDM), algal cell density, and total algal biovolume to manipulations of
light, nutrients, and grazing ...........................................................................................................83

vii

LIST OF FIGURES

Figure 1.1 Conceptual model describing the potential influences of climate change on wetland
ecosystem processes due to the relationship between environmental factors and algal structure
and function ...................................................................................................................................6
Figure 2.1 Aerial photograph outlining the location of the six wetland study sites .....................33
Figure 2.2 Images of the six wetland sites used in this study. F1 is a rich fen. F2 is a poor fen.
M1 is a densely vegetated marsh with tussock grasses creating saturated hallows. M2 is a large
marsh complex with large open water areas covered with floating macrophytes. M3 is a shallow
riverine marsh dominated by Equisetum fluviatile. M4 is a shallow riverine marsh with a
diversity of floating and emergent macrophytes...........................................................................34
Figure 2.3 Mean ± SE algal chlorophyll a concentration (A), ash-free dry mass (B), productivity
(C), and cell density (D) in six Alaskan boreal wetlands during the 2009 summer growing
season. Bars with the same letter are not significantly different among sites ..............................35
Figure 2.4 Aboveground macrophyte and algal contribution to wetland primary production in six
wetlands during early (first bar in each pair) and late (second bar in each pair) growing season
2009...............................................................................................................................................36
Figure 2.5 NMS between relative algal abundances and surface-water chemical variables and
time from six wetlands in the Tanana River floodplain, Alaska (final stress = 7.36 for 2dimensional solution and 55 iterations). All symbols are labeled with the wetland site. Different
symbols indicate week sampled during the growing season. Axis 1 and 2 accounted for 77% and
16% of the variability in the ordination respectively, for a cumulative 93% or variance explained
by the ordination ...........................................................................................................................37
Figure 3.1 Schematic diagram of enclosure design. Enclosures were constructed of welded wire
mesh (40 cm in diameter × 85 cm tall) and held ~60 L of water. The top 75 cm of each cylinder
was wrapped with 0.1-mm clear window vinyl and embedded 10 cm into sediments with an open
top extending 15 cm above the water column. We suspended all substrates attached to frames
that maintained a consistent depth of 5 cm below the water surface. We nested caged and
uncaged substrates together inside enclosures (grazer-exclusion and grazed treatments) and
added natural abundances of snails. All snails were removed from grazer-absent treatment
enclosures......................................................................................................................................59
Figure 3.2 Dissolved nutrient concentrations of NO3 (A), PO4 (B), and Si (C) in nutrient
enriched, control, and open wetland enclosures with (+) and without (–) grazers .......................60
Figure 3.3 Mean (±1 SE; n = 4) ash-free dry mass (AFDM) (A) and cell density (B) in the open
wetland, control, and nutrient-enriched enclosures with and without grazers. Bars with the same
letter are not significantly different among treatments .................................................................61

viii

Figure 3.4 Taxonomic composition and total biovolume of algae with >5% relative abundance in
the open wetland (A), control (B), and nutrient-enriched (C) enclosures with and without grazers
.......................................................................................................................................................62
Figure 4.1 Algal biomass measured as ash-free dry mass versus above ground macrophyte
biomass over a five week period during the summer growing season. Underwater PAR during
the first week of sampling when macrophyte biomass was lowest and algal biomass was highest
2
was 920.3 µmol quanta/m /s. Underwater PAR during the last week of sampling when
2

macrophyte biomass was highest and algal biomass was lowest was 206.6 µmol quanta/m /s
which was approximately 67% of available light .........................................................................84
Figure 4.2 Graphic of enclosure design. Enclosures were constructed of welded wire mesh (40
cm in diameter and 85 cm tall), and held approximately 60 L of water. The top 75 cm of each
cylinder was wrapped with 0.1 mm clear window vinyl and embedded 10 cm into sediments with
an open top extending 15cm above the water column. I suspended all substrates attached to wire
baskets and maintained a consistent depth of 5 cm below the water surface. I nested caged and
un-caged substrates inside enclosures and added natural abundances of snails. Un-shaded
treatments received full sunlight and 75% of light was blocked in shaded treatments ................85
Figure 4.3 Dissolved nutrient concentrations of NO3 and PO4 in shaded and un-shaded nutrient
enriched and control enclosures....................................................................................................86
Figure 4.4 Benthic algal biomass measured as ash-free dry mass (AFDM) and cell density in
control and nutrient enriched enclosures with and without grazers in shaded and un-shaded
treatments. Bars represent the mean of four replicates ± SE ........................................................87
Figure 4.5 Grazed and un-grazed algal taxonomic composition and total algal biovolume in
shaded and un-shaded nutrient enriched and control enclosures based on taxa comprising > 5%
relative abundance ........................................................................................................................88
Figure 5.1 Long term seasonal trends in water table heights across the control, lowered, and
raised water table treatments in interior Alaska (from Kane et al. 2010). Negative values indicate
water table position below the surface of the peat. Outlined values indicate water table
measurements made during this study. Inserted figure shows standard deviation in mean
monthly water table position across the five years of study (total of 1938 individual water table
measurements) ............................................................................................................................109
Figure 5.2 Mean (±1 SE; n = 8) (A) Soluble reactive phosphorus (SRP) and (B) dissolved
inorganic nitrogen (DIN) concentrations in control, lowered, and raised water table treatments on
each sampling date in the APEX fen during the summer growing season in 2009 (from Wyatt et
al. 2012) ......................................................................................................................................110
Figure 5.3 Mean (±1 SE; n = 8) algal cell density (A) and total biovolume (B) in the control,
lowered, and raised water table treatments on each sampling date in the APEX fen during the
summer growing season in 2009.................................................................................................111

ix

Figure 5.4 Percent of total cells (A-C) and total biovolume (D-F) in functional groups in the
control (A, D), lowered (B, E), and raised (C, F) water table treatments on each sampling date in
the APEX fen during the summer growing season in 2009........................................................112
Figure 5.5 Algal taxonomic composition as relative abundance (A-C) and percent of total
biovolume (D-F) of dominant algal genera in the control (A, D), lowered (B, E), and raised (C,
F) water table treatments on each sampling date in the APEX fen during the summer growing
season in 2009.............................................................................................................................113

x

CHAPTER 1

INTRODUCTION

1.1 Benthic algal ecology in freshwater wetlands

Algae are important to many of the processes that characterize wetland ecosystems. They
can exert considerable control over dissolved oxygen concentrations (Browder et al. 1994,
McCormick et al. 1997, Richardson 2010), sediment formation (Gleason and Spackman 1974,
McCormick et al. 1998), nutrient uptake and retention (Wetzel 1996, Gaiser et al. 2004, Wyatt et
al. 2012), and can account for a significant amount of total primary production (Robinson et al.
2000, Richardson 2010, Wyatt et al. 2010). Despite their importance, we know relatively little
about the factors that regulate algal communities in wetlands. This is particularly true for
northern boreal regions where wetlands are abundant and are considered to be extremely
vulnerable to disturbances associated with climate change. Understanding the regulation of algal
dynamics in wetlands is essential to predicting and understanding the implications of
environmental variation, anthropogenic effects, and changes in climate, all of which can alter the
current wetland ecosystem infrastructure.

1.2 Environmental regulation of benthic algae in wetlands

The factors that influence benthic algal structure and function in wetlands are not clearly
understood. Conceptual models attribute environmental factors such as climate, geology,

1

hydrology, flood disturbance frequency, substrata type and size, water chemistry, canopy cover
and light availability, and grazer density as strong influences on benthic algal productivity and
community structure (Figure 1.1) (Goldsborough and Robinson 1996). Much of our current
understanding about these regulatory processes has been adapted from hypotheses generated in
other aquatic ecosystems (Batzer et al. 2006). However, given the unique physical, chemical,
and biological properties of wetland environments, there is a need to investigate these processes
to evaluate the magnitude and characteristics of effects in wetlands and how they vary among
different types of wetlands.
Water-level fluctuations are common and frequent in wetlands, and are one of the
dominant controls on wetland plant and animal communities as well as on primary productivity
and decomposition (Gottlieb et al. 2005, Jackson 2006). Changing hydrological processes are
responsible for the movement and delivery of limiting nutrients into and out of wetland
ecosystems (Jonasson and Shaver 1999), and are therefore extremely important in regulating
algal distribution and abundance (Browder et al. 1994, Robinson et al. 2000). Even small
changes in depth of only a few millimeters can expose algal communities to variations in nutrient
concentrations and dissolved gases which can induce significant changes in community
metabolism (Kahn and Wetzel 1999). Flooding reduces macrophyte abundance and releases
nutrients from dead vegetation, litter, and sediments that may subsequently stimulate algal
production (Murkin 1989, Robinson et al. 2000). Drought and exposure of sediments reoxygenate anaerobic soils, facilitating the release of nutrients upon re-inundation (Schoenberg
and Oliver 1988, Goldsborough and Robinson 1996, Thomas et al. 2006).
Benthic algae are sensitive to changes in water quality, and nutrients are among the most
important factors regulating algal assemblages in aquatic ecosystems (Borchardt 1996). The

2

addition of nutrients can result in significant increases in biomass (Francoeur 2001) and shifts in
species composition (Fairchild et al. 1985, Gaiser et al. 2006), both of which can alter important
ecosystem processes related to energy flow and nutrient cycling within aquatic ecosystems.
Research examining the effects of nutrient enrichment on wetland ecosystems has stemmed
largely from studies conducted in subtropical (McCormick and O'Dell 1996, McCormick et al.
2001, Gaiser et al. 2005) and temperate regions (Gabor et al. 1994, Murkin et al. 1994,
McDougal et al. 1997), which are subject to nutrient contamination from increasing urban and
agricultural land use (i.e., Sklar et al. 2005). The effects of nutrient enrichment on wetland algal
communities at northern latitudes have been less studied, perhaps because it has been less
directly impacted by human development. However, boreal regions are experiencing rapid
changes in climate, which have led to a longer growing season with higher temperatures (Chapin
et al. 2006). Changes in thermal regime are expected to increase the extent of seasonal ice thaw,
which will potentially promote nitrogen and phosphorus mineralization in the expanded active
soil layer (Bridgham et al. 1995). While regional variability of nutrient inputs may be
significant, these changes are expected to have widespread impacts on nutrient concentrations of
aquatic systems throughout the boreal forest (Rouse et al. 1997).
In the absence of nutrient limitation, grazing strongly influences the quantity and quality
of algal biomass as well as the taxonomic composition and growth form of the algal assemblage
(McCormick and Stevenson 1991, Feminella and Hawkins 1995, Steinman 1996). Grazing
generally causes a reduction in algal biomass and can maintain low biomass accumulation even
in conditions of increased resource availability (e.g., nutrients and light) (Feminella and Hawkins
1995, Hill et al. 1995, Rosemond et al. 2000). Despite reductions in biomass, grazing can also
lead to increased productivity of the algal assemblage through the utilization of excreted

3

nutrients (McCormick and Stevenson 1991, Hillebrand 2002). The extent to which these
regulatory processes operate in wetlands is largely unknown, as evidence of grazing in wetland
ecosystems has been largely circumstantial (Robinson et al. 2000).
Since light is required to carry out photosynthesis, it is commonly considered the most
important resource regulating algal communities (Hill 1996). Light conditions in wetlands are
extremely dynamic. Not only are wetlands exposed to seasonal changes in incident radiation but
light attenuation also varies with the degree of shading by overlying macrophytes (Robinson et
al. 2000). As opposed to stream ecosystems, where light limitation can be avoided by colonizing
a variety of substrates, macrophytes are the primary substrate available for benthic algal
colonization in wetlands. This poses an interesting problem for light limited algal primary
production, especially in northern boreal wetlands that receive over 20 hours of daylight during
the summer growing season, resulting in rapid macrophyte growth (Chapin et al. 2006). This is
further complicated by climate change processes which have led to a longer growing season
(Magnuson et al. 2000, Chapin et al. 2006), with a subsequent increase and duration of
macrophyte production.

1.3 Investigating environmental controls on wetland algal structure and function

In this dissertation, I examine the role of hydrology, grazing, nutrients, and light in
regulating algal productivity, abundance, and taxonomic composition in northern boreal
wetlands, along with the spatial and temporal trends in these biotic and abiotic factors. I chose
these factors in order to gain a better understanding of how algae will respond to environmental
factors that are predicted to be altered by climate change processes. Chapter 2 describes the

4

spatial and temporal variation in physical and chemical factors in six wetlands (4 marshes and 2
peatlands) in interior Alaska and examines the relationships between these environmental
parameters and algal productivity, abundance, and taxonomic composition. These data are
useful for understanding the natural distribution and abundance of algae in boreal wetlands,
which is necessary to predict how processes related to anthropogenic activity and climate change
will influence wetland primary production, biogeochemistry, and food-web structure. Chapter 3
describes the independent and interactive effects of grazing and nutrients on benthic algal
biomass and taxonomic composition in an in situ mesocosm experiment. Additionally, since
grazers can recycle significant amounts of nutrients into the water column, I evaluated the
influence of consumer-driven nutrient recycling on algal biomass. Chapter 4 describes the
independent and interactive effects of grazing, nutrients, and light on benthic algal biomass and
taxonomic composition in an in situ mesocosm experiment. Specifically, I investigated how
changes in light availability, in the presence and absence of grazing, limit the ability for algae to
respond to nutrient inputs. Chapter 5 describes algal community response to experimental and
interannual variation in hydrology in an Alaskan boreal fen. I monitored shifts in algal
taxonomic composition at sites exposed to a long-term water table manipulation, including
drought and flooding conditions in an Alaskan fen. While continuous algal colonization would
typically only occur in flooded conditions in previous years, a spring flood provided a unique
opportunity to examine algal community response to rewetting after long-term drought as well.
This allowed me to investigate how much ecosystem memory of the antecedent water table
manipulations regulated the ability of taxa to recolonize sites following prolonged drought
compared to sites that had been continuously flooded.

5

Climate Change

Environmental Factors
(hydrology, pH, alkalinity, nutrients,
temperature, light, grazing)

Algal Functions

Algal Structure

(photosynthesis, respiration,
nutrient uptake,
nitrogen fixation, DOC release)

(biomass, species composition)

Ecosystem Processes
(food web support, carbon sequestration,
sediment formation, biogeochemical cycling)

Figure 1.1 Conceptual model describing the potential influences of climate change on wetland
ecosystem processes due to the relationship between environmental factors and algal structure
and function.

6

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7

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Ecology and Management 18: 517–542.
Robinson, G. G. C., S. E. Gurney, and L. G. Goldsborough. 2000. Algae in prairie wetlands.
Pages 163–198 in H. R. Murkin, A. G. van der Valk, and W. R. Clark (editors). Prairie wetland
ecology: the contribution of the Marsh Ecology Research Program. Iowa State University Press,
Ames, Iowa.
Rosemond, A. D., P. J. Mulholland, and S. H. Brawley. 2000. Seasonally shifting limitation of
stream periphyton: response of algal populations and assemblage biomass and productivity to
variation in light, nutrients, and herbivores. Canadian Journal of Fisheries and Aquatic Sciences
57:66–75.
Rouse, W. R., M. S. V. Douglas, R. E. Hecky, A. E. Hershey, G. W. Kling, L. Lesack, P. Marsh,
M. McDonald, B. J. Nicholson, N. T. Roulet, and J. P. Smol. 1997. Effects of climate change on
the freshwaters of arctic and subarctic North America. Hydrological Processes 11: 873–902.
Schoenberg, S. A., and J. D. Oliver. 1988. Temporal dynamics and spatial variation of algae in
relation to hydrology and sediment characteristics in the Okefenokee Swamp, Georgia.
Hydrobiologia 162: 123–133.
Sklar, F. H., M. J. Chimney, S. Newman, P. V. McCormick, D. Gawlik, S. Miao, C. McVoy, W.
Said, J. Newman, C. Coronado, G. Crozier, M. Korvela, and K. Rutchey. 2005. The ecologicalsocietal underpinnings of Everglades restoration. Frontiers in Ecology and the Environment 3:

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161–169.
Steinman, A. D. 1996. Effects of grazers on freshwater benthic algae. Pages 341–373 in R. J.
Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: freshwater benthic
ecosystems. Academic Press, New York.
Thomas, S., E. E. Gaiser, M. Gantar, and L. J. Scinto. 2006. Quantifying the responses of
calcareous periphyton crusts to rehydration: A microcosm study (Florida Everglades). Aquatic
Botany 84: 317–323.
Wetzel, R. G. 1996. Benthic algae and nutrient cycling in lentic freshwater ecosystems. Pages
641–667 in R. J. Stevenson, M. L. Bothwell, and R. L. Lowe (editors). Algal ecology: freshwater
benthic ecosystems. Academic Press, New York.
Wyatt, K. H., R. J. Stevenson, and M. R. Turetsky. 2010. The importance of nutrient colimitation in regulating algal community composition, productivity, and algal-derived DOC in an
oligotrophic marsh in interior Alaska. Freshwater Biology 55: 1845–1860.
Wyatt, K.H., M.R. Turetsky, A.R. Rober, D. Giroldo, E.S. Kane, and R.J. Stevenson. 2012.
Contributions of algae to GPP and DOC production in an Alaskan fen: effects of historical water
table manipulations on ecosystem responses to a natural flood. Oecologia DOI 10.1007/s00442011-2233-4.

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CHAPTER 2

SPATIAL AND TEMPORAL VARIABILITY OF ALGAL COMMUNITY DYNAMICS AND
PRODUCTIVITY IN LATERAL FLOODPLAIN WETLANDS ALONG THE TANANA
RIVER, ALASKA

2.1 Introduction

Few studies have examined the structure and function of benthic algae in wetlands or
their relationships with the physical and chemical conditions characteristic of different wetland
types. Determining the spatial and temporal patterns of benthic algal communities is important
for understanding wetland ecosystem function because algae play a critical role in many
ecosystem processes. In shallow wetlands where sufficient light reaches the bottom, benthic
algae contribute significantly to wetland primary production (Robinson et al. 2000, Richardson
2010, Wyatt et al. 2010), biogeochemical cycling (Wetzel 1996, Gaiser et al. 2004, Wyatt et al.
2012), sediment formation (Gleason and Spackman 1974, McCormick et al. 1998), and oxygen
production (Browder et al. 1994, McCormick et al. 1997, Richardson 2010).
The factors that influence benthic algal structure and function in wetlands are not clearly
understood. Conceptual models attribute regional environmental factors such as climate,
geology, and hydrology, and local factors such as flood disturbance frequency, substrata type and
size, water chemistry, canopy cover and light availability, and grazer density as strong influences
on benthic algal productivity and community structure (Goldsborough and Robinson 1996).
Much of our current understanding about these regulatory processes has been adapted from
hypotheses generated in other aquatic ecosystems (Batzer et al. 2006). However, given the
unique physical, chemical, and biological properties of wetland environments, there is a need to

12

investigate these processes to evaluate the magnitude and characteristics of effects in wetlands
and how they vary among different types of wetlands.
Most direct measurements of algal structure and function in wetlands have come from
studies conducted in subtropical (Browder et al. 1994, Richardson 2008) and temperate regions
(Goldsborough and Robinson 1996, Robinson et al. 2000). The abundance and distribution of
algal communities have been less studied at northern latitudes where wetlands are the dominant
land cover type. In Alaska alone, wetlands cover over 43 percent of the total surface area (Hall
et al. 1994). Given the importance of boreal wetlands as major stores of carbon, considerable
effort has been made to quantify primary productivity in these ecosystems (cf. Thormann and
Bayley 1997, Weltzin et al. 2000, Bayley and Mewhort 2004, Chivers et al. 2009). However, the
majority of these studies have focused on macrophyte production (McCormick et al. 1998,
Wieder 2006) and has mostly ignored the potential role of algae contributing to wetland primary
production and ecosystem function.
Wetlands occurring in boreal regions can be classified as either peatlands or marshes.
Peatlands are defined as ecosystems that have accumulated at least 40 cm of peat (National
Wetlands Working Group 1997). They are the dominant wetland type in boreal regions (Vitt et
al. 2006), mainly because cold temperatures and slow rates of decomposition facilitate
accumulation of organic matter. Peatlands in boreal regions tend to have little standing water
since water level is highly dependent on changes in rates of precipitation and evapotranspiration.
Marshes often occur within floodplains of large river systems and are characterized by shallow
water with submerged, floating, and emergent macrophytes. Marshes vary considerably in
physical and chemical nature (Mitsch and Gosselink 2006), which likely influences algal
structure and function.

13

Understanding the natural distribution and abundance of algae in boreal wetlands is
necessary to predict how processes related to climate change will influence wetland primary
production, biogeochemistry, and food-web structure. Climate change processes are already
having significant effects on northern boreal regions. Increased evapotranspiration with longer,
drier growing seasons (Serreze et al. 2000, Euskirchen et al. 2006), drainage after permafrost
thaw (Hinzman et al. 2005, Riordan et al. 2006), and/or encroachment of wetland vegetation
(Roach et al. 2011) have reduced the surface area of extensive portions of open water bodies in
wetland-rich landscapes of interior Alaska. However, some wetland areas in Alaska are
expanding due to hydrologic upwelling and increased flooding from melt-water runoff from
surrounding uplands (Osterkamp et al. 2000). Increased frequency of drought and flooding
events associated with climate change will likely alter the physical and chemical conditions of
aquatic ecosystems in the boreal region, including the movement of limiting nutrients into and
out of wetlands (Rouse et al. 1997). Furthermore, changes in thermal regime are expected to
increase the extent of seasonal ice thaw, and could promote N and P mineralization in the
expanded active soil layer (Bridgham et al. 1995). These changes are expected to have
widespread effects on aquatic ecosystems throughout the boreal forest (Rouse et al. 1997).
In this study I documented the spatial and temporal variation in physical and chemical
factors in six wetlands (4 marshes and 2 peatlands) in interior Alaska. I then examined the
relationships between these environmental parameters and benthic algal productivity, abundance,
and taxonomic composition. I was specifically interested in determining the contribution of algal
primary production to wetland primary production, documenting algal community composition
in both peatlands and marshes, and determining which environmental variable(s) best predict the
distribution and abundance of the algal communities. These data have important implications for

14

wetlands in the boreal region, but also more broadly, for carbon cycling in the boreal forest.
Furthermore, these data allow us to expand our knowledge from lakes and streams to boreal
wetlands, where benthic habitats have rarely been explored.

2.2 Methods

Study Site
For twelve weeks during the summer of 2009, I conducted the field work to characterize
the spatial and temporal changes in water depth, surface water chemistry, macrophyte biomass,
light attenuation, and algal productivity and taxonomic composition in six wetlands within the
Tanana River Floodplain just outside the Bonanza Creek Experimental Forest (35 km southeast
of Fairbanks, Alaska) (Figures 2.1 and 2.2). My study sites were located in two peatlands and
four marshes. I chose these sites to capture a range of physical and chemical conditions present
in a diversity of peatland and marsh types. Three of the wetlands used in this study (F1, M1, M2)
were characterized by Kashichke et al. (2009).
The Tanana River valley is about 150 to 250 km south of the Arctic Circle, and is part of
the circumpolar band of boreal forest. The area is underlain by discontinuous permafrost and is a
mosaic of forest, grassland, shrubs, and wetlands. The area has large fluctuations in daylight and
experiences more than 21 h of light per day in June and less than 3 h per day in December. The
growing season is short (approximately 135 days), lasting from May to August. This region
within interior Alaska has large fluctuations in temperature, with a mean annual temperature of 2.9°C, and low levels of precipitation (269 mm/y), of which approximately 30 percent falls as
snow (Hinzman et al. 2006).

15

The first site (F1) is a moderately rich fen and is dominated by brown moss species,
Sphagnum, and emergent vascular plants, beaked sedge (Carex utriculata), common horsetail
(Equisetum sp.), and Potentilla palustris. F1 is minerotrophic receiving water from surface
water runoff and precipitation, and to some extent, groundwater. Peat thickness exceeds 1 m at
this site. This site is currently being used for the Alaska Peatland Experiment (APEX) and is
described in more detail in Turetsky et al. (2008).
The second site (F2) is a poor fen located approximately 50 m from the APEX site and is
dominated by emergent marsh vegetation including Equisetum, Carex, and Potentilla palustris
with the moss community composed of Sphagnum species.
The third site (M1) is approximately 50 m from sites F1 and F2, but did not have ≥ 40 cm
of peat, and is thus classified as a marsh. The dominant vegetation is short tussock grasses,
where inter-tussock spaces tend to be saturated with water. M1, F1, and F2 are surrounded by
lowland black spruce (Picea mariana) forest.
The forth site (M2) is a marsh and is dominated by emergent vegetation including Carex
and Equisetum species as well as the floating macrophyte Menyanthes trifoliate (Buck Bean).
This site has a very thin layer of organic soil on top of the mineral soil layer, and is characterized
by extreme annual hydrologic changes likely linked to river flow conditions. Several small open
water pools are present within the marsh complex.
The fifth site (M3) is a shallow riverine marsh and is a near monoculture of emergent
Equisetum fluviatile surrounded by alder (Alnus), aspen (Populus balsamifera), and white spruce
(Picea glauca) forest. This site, although in close proximity (~200m) to M4, has very low
concentrations of dissolved organic matter in the water column and high dissolved oxygen.

16

The sixth site (M4) is a shallow riverine marsh and is dominated by emergent vegetation
including swamp horsetail (Equisetum fluviatile), beaked sedge (Carex utriculata), and water
parsnip (Sium suave) and submerged vegetation including flat leaved bladderwort (Utricularia
intermedia) and yellow water-crowfoot (Ranunculus gmelinii). This site has been the location of
several in situ mesocosm experiments looking at the effects of nutrient enrichment (Wyatt et al.
2010), pH (Wyatt and Stevenson 2010), and grazing (Rober et al. 2011) on benthic algal
structure and function.

Sampling procedure
Starting in May 2009, I sampled surface water chemistry and algal parameters weekly,
and then every two weeks beginning in July until August, or until the water table fell below the
soil surface, to evaluate algal responses to changes in environmental parameters. On each
sampling date I measured water depth using a meter stick, and water temperature, dissolved
oxygen (DO), and pH using a calibrated model 556 YSI® Multi-Probe (YSI Incorporated,
Yellow Springs, OH, U.S.A.). I filtered water for dissolved nutrient analysis using a 0.45 μm
Millex®-HA syringe-driven filter unit (Millipore Corporation, Bedford, MA, U.S.A.) into 120
mL acid-rinsed polyethylene bottles. Samples were stored on ice until returning to the lab,
where a portion of each filtered sample was analyzed for dissolved organic carbon (DOC) using
a Shimadzu TOC-V carbon analyzer (Shimadzu Scientific Instruments, Columbia, MD, U.S.A.).
The remaining portion of each sample was frozen and stored until analysis. I analyzed water
samples for dissolved inorganic nitrogen (DIN) as NO3 + NO2 following the cadmium reduction
method using a Skalar® auto-analyzer (Skalar Analytical, Breda, Netherlands). Soluble reactive
phosphorus (SRP) was measured following the ascorbic acid colorimetric method using a

17

Genesys™ 2 UV-Vis spectrophotometer (Spectronic Analytical Instruments, Garforth, U.K.)
(APHA 1998). I determined total nitrogen (TN) and total phosphorus (TP) concentrations
following oxidation with persulfate digestion and second derivative UV spectroscopy and
ascorbic acid methods respectively (APHA 1998).
2

I quantified macrophyte height and density in replicate m plots as percent cover and
stem density of each plant type. I harvested above ground plant biomass biweekly in randomly
selected m2 plots for estimates of plant biomass. Plants were dried, weighed, and converted to g
2

C/m assuming 40 percent of dry mass is carbon (Robinson et al. 2000). Since the APEX site is
part of a long-term experimental study, I did not harvest plants at the F1 site. However I
compared algal productivity at the F1 site to estimates of macrophyte gross primary production
(GPP) reported by Chivers et al. (2009). I measured photosynthetically active radiation (PAR) at
the wetland surface and at subsequent intervals below the waters surface until the bottom was
reached using a LI-COR submersible quantum sensor and LI-250 light meter (LI-COR, Lincoln,
NE, U.S.A.). I made measurements without disturbing the canopy by attaching the underwater
sensor to the end of a pole that was lowered into the macrophyte stand.
I collected algae from six randomly selected locations in each wetland for estimates of
benthic algal biomass, productivity, and taxonomic composition. Each sample consisted of four
2

25 cm subsamples collected from peat surface (if present) and the submersed portions of four
stems of the dominant emergent macrophyte. I used a plastic syringe to remove algae from each
2

25 cm quadrat until there were no loosely attached algae or biofilms present. In cases where
algae were attached to erect plant stems, I scraped the submersed portion of four stems clean
with a plastic spoon, and adjusted the surface area in calculations. Each algal sample was

18

homogenized in 120 mL of water for analysis of chlorophyll a, ash-free dry mass (AFDM), and
2

2

benthic algal abundance (algal cells/cm ). Chlorophyll a (mg/m ) was measured from a
subsample collected on a Whatman GF/F glass fiber filter. Filters were frozen and chlorophyll a
was measured using a Turner model 700 fluorometer (Turner Designs, Sunnyvale, CA, U.S.A.)
after extraction with 90% ethanol and correction for phaeophytin (APHA 1998). I determined
2

AFDM (g/m ) by drying samples at 105 °C for 48-72 h and combusting them for 1 h at 500 °C
in preweighed aluminum pans to determine the difference between dry mass and ashed mass
respectively (APHA 1998). I preserved a subsample in a 2% formalin solution for algal
compositional analysis. I used standard protocols to characterize algal taxonomic composition
by counting and identifying at least 300 natural units per sample using a Palmer-Maloney
nanoplankton counting chamber and identified algae to genus at 400X magnification (Charles et
2

al. 2002). I quantified benthic algal abundance (cells/cm of substrate) using the formula
provided in Lowe and Laliberte (2006).
I split a final portion of each homogenized sample into two separate biological oxygen
2

demand (BOD) bottles to measure benthic algal productivity (mg C/m /h) following McCormick
et al. (1998). I filled each BOD bottle with filtered water from the wetland and recorded initial
DO using a Hach HQ 40d luminescent DO probe (Hach Company, Loveland, CO, U.S.A.). I
wrapped one bottle from each set with aluminum foil for incubation in the dark and determined
production by measuring oxygen changes produced by algal samples incubated in situ in light
and dark bottles. Light and dark bottles were used to measure net primary productivity (NPP)
and respiration, respectively. I calculated GPP following Wetzel and Likens (2000) and

19

converted GPP values into units carbon based on a C:O molar ratio of 0.375 and a photosynthetic
quotient of 1.2 (Wetzel and Likens 2000).

Data Analysis
The distributions of variables were log (x + 1) transformed if necessary to correct for
non-normal distribution and unequal variances among sites prior to analysis. I used repeated
measures analysis of variance models with an adjusted Bonferroni significance level (p < 0.016)
and Tukey’s test for post hoc comparison of means to determine if algal productivity and
biomass were different between sites. I used a bivariate Pearson Correlation test to determine if
any of the environmental variables were correlated. Several of the environmental variables were
correlated and therefore could not be included in any model together. Therefore, I include water
depth, TN, TP, PAR, and wetland site in a linear mixed model to predict changes in algal
productivity and biomass, with the assumption that correlated variables (pH, water temperature,
DO, DIN, SRP, and DOC) would respond similarly (Zar 2010). All statistical analyses were
performed using general linear models in SPSS 18 (SPSS inc., Chicago, IL, U.S.A.).
I plotted the relationship between environmental variables and algal taxonomic
composition among sites with Non-metric Multidimensional Scaling (NMS) using PC-ORD
(version 5, MjM Software, Gleneden Beach, OR, U.S.A). I analyzed similarities in algal
taxonomic composition among wetland sites and sampling dates with a 2-way analysis of
similarities (ANOSIM) test using PRIMER (version 5, PRIMER-E Ltd, Plymouth, UK). I
calculated all algal community data as a proportion of the total before analysis and only included
taxa present at > 5% relative abundance. I square root transformed data prior to ordination and
ANOSIM.

20

2.3 Results

Surface water chemistry and water level characteristics
Mean TP concentration was lower in M2 compared to all other wetlands (p < 0.05; Table
2.1). Mean TP was not different between peatlands F1 and F2 (p > 0.05). Mean TP was similar
among marshes M2, M3, and M4 (p > 0.05), which had higher concentrations compared to the
other wetlands (Table 2.1). Mean TN concentration was higher in M2 compared to all other
wetlands (p < 0.05). Mean TN concentrations in F2 and M1 were similar (p > 0.05) but were
greater than TN concentrations in F1, M3 and M4, which were similar to one another (Table
2.1). Mean SRP concentration was below 4 µg/L in all wetlands, and was slightly higher at M3
compared to the other wetlands (Table 2.1). Mean DIN was significantly greater at M1
compared to all other wetlands (p < 0.05). Mean DIN was lowest at M4 and was similar among
all other wetlands (Table 2.1).
Water depth was greatest immediately following the spring thaw in all wetlands and
decreased throughout the growing season (Table 2.1). Mean water depth was greater in the
marshes compared to the peatlands and was greatest in M4 (p < 0.05; Table 2.1). Mean pH was
similar between the peatlands (F1 and F2) (p > 0.05) and was more acidic than in the marshes
(Table 2.1). Mean pH was slightly alkaline at M3 and was greater than all other wetlands (p <
0.05). Mean pH in M1 and M2 was similar and just below neutral (Table 2.1). The pH in M4
was near neutral (Table 2.1). Mean water temperature was similar among all six wetlands
throughout the growing season. Mean DO concentration was highest in M3 but was similar to
F1, F2, and M4 (p > 0.05). DO was similar between marshes M1 and M2 (p > 0.05), which were
lower than all other sites (p < 0.05; Table 2.1). Mean DOC concentration was lowest in wetlands

21

located closest to the Tanana River (M3 and M4) (Table 2.1). Mean DOC concentration was
similar in F2 and M2 (p > 0.05), which were greater than all other wetlands (Table 2.1). F1 and
M1 had similar mean DOC concentrations that were slightly lower than F2 and M2 (Table 2.1).
Although a repeated measures multivariate analysis of variance and Tukey’s post-hoc
comparisons of means test indicated that environmental variables were significantly different
among wetlands, they were not significant predictors of algal biomass or productivity within
wetlands.

Algal biomass and primary production
Mean chlorophyll a concentration was significantly greater in M2 compared to all other
wetlands (p ≤ 0.028; Figure 2.3A), which were not significantly different from each other (p >
0.05). Mean AFDM was greater in F2 compared to F1, M1, M3, and M4 (p ≤ 0.009; Figure
2.3B). AFDM in M2 was similar to F2 (p = 0.983) and was greater than F1, M1, and M3, but
was not significantly different than M4 (p > 0.05; Figure 2.3B). Mean AFDM in wetlands F1,
M1, M3, and M4 were not significantly different from one another (p > 0.05). Mean algal
productivity was greater at F2 compared to F1, M1, M3, and M4 (p ≤ 0.014; Figure 2.3C). Mean
productivity at M2 was similar to F2 (p = 0.8) and was greater than F1, M1, and M4 (p ≤ 0.005)
but was not significantly different than M3 (p > 0.05; Figure 2.3C). Algal productivity in F1,
M1, M3, and M4 were not significantly different from one another (p > 0.05). Algal cell density
was significantly greater at M2 (p ≤ 0.0001; Figure 2.3D) compared to all other wetlands which
were not significantly different from one another (p > 0.05).
Mean algal productivity in the peatland F1 represented about 7% of the total ecosystem
GPP during the early part of the summer growing season (Figure 2.4). Mean algal productivity

22

in the peatland F2 represented nearly 50% of wetland primary production during the early part of
the summer growing season, and decreased to about 23% during late growing season (Figure
2.4). Mean algal productivity in the marsh M1 represented approximately 19% of wetland
primary production during the early part of the summer growing season, and decreased to about
3% during late growing season (Figure 2.4). Mean algal productivity in the marsh M2
represented approximately 64% of wetland primary production during the early part of the
summer growing season, and decreased to about 18% during late growing season (Figure 2.4).
Mean algal productivity in the marsh M3 represented about 22% of wetland primary production
during the early part of the summer growing season, and decreased to < 1% during late growing
season (Figure 2.4). Mean algal productivity in the marsh M4 represented about 16% of wetland
primary production during the early part of the summer growing season, and decreased to
approximately 9% during late growing season (Figure 2.4).

Algal taxonomic composition
Algal taxonomic composition was strongly influenced by both hydrology and time (NMS
final stress = 7.36 for 2-dimensional solution and 55 iterations; Figure 2.5). Algal community
composition was equally influenced in direction and magnitude by TN and TP (Figure 2.5). The
effect of environmental variables that co-varied with water depth (water temperature, DO, pH)
could not be separated from the influence of water depth, but likely influence that algal
community in similar direction and much lower magnitude. Similarly, DIN and SRP co-varied
with TN and TP, and would therefore likely have influence in similar direction and magnitude.
PAR co-varied with DOC, but since PAR did not strongly contribute to the ordination it is likely
that DOC may not be very important in influencing algal community composition. Axis 1 and 2

23

in NMS accounted for 77% and 16% of the variability in the ordination respectively, for a
cumulative 93% or variance explained by the ordination (Figure 2.5). Monte Carlo test indicates
that the axes selected are significantly different than could be selected by chance (p = 0.02).
Algal taxonomic composition was more similar within wetland sites than between wetland sites,
yielding an ANOSIM with significant differences between wetland sites (Global R = 0.155; p =
0.015). ANOSIM also suggests that time was an important factor determining algal taxonomic
composition within wetlands (Global R = 0.291; p = 0.001).
Averaged across all sampling dates, there were 22 algal genera that were present at >5%
relative abundance in any one wetland (Table 2.2). Dinobryon was the dominant Chrysophyte
and was present in greater abundances in both peatlands (F1 and F2), particularly the rich fen
(F1), compared to the marshes (Table 2.2). Filamentous green algae (Chlorophyta) such as
Microspora, Oedogonium, Spirogyra, and Ulothrix were abundant in both peatlands and marshes
(Table 2.2). Chain forming desmids, such as Bambusina and Desmidium were particularly
abundant in peatlands (Table 2.2). Cyanobacteria, particularly nitrogen-fixing taxa (i.e., Nostoc,
Anabeana, Haplosiphon), were present in large quantities in both peatlands and marshes (Table
2.2). These taxa become more abundant over the course of the growing season as nutrients
concentrations and water table declined in all wetlands (Figure 2.5). Diatoms did not contribute
greatly to algal abundance, however Tabellaria was the dominant diatom in peatlands,
particularly the rich fen (F1), while Nitszchia was more abundant in marsh sites M3 and M4
(Table 2.2).

2.4 Discussion

24

The six wetlands used in this study capture a range of physical and chemical conditions
that were important in regulating algal productivity, abundance, and taxonomic composition.
There were significant spatial differences in algal biomass and taxonomic composition between
wetlands and seasonal differences within wetlands. Algal biomass and productivity were
greatest in a poor fen (F2) and a large riverine marsh (M2), suggesting that algae are important
contributors to primary production and therefore ecosystem function in both peatlands and
marshes. Algal taxonomic composition was more similar within wetland sites than between
wetland sites, suggesting that the physical and chemical environment indicative of different
wetland types is important for structuring algal taxonomic composition.
2

Mean productivity values among all wetland sites are within the range (0-500 g C/m /y)
of values reported from in the literature of temperate freshwater marshes (see review in
Goldsborough and Robinson 1996). During peak productivity, estimates of algal productivity
fall within the lower range of productivity values reported for the subtropical Florida Everglades
2

(300-600 g C/m /y; McCormick et al. 1998, Ewe et al. 2006). Assuming that peak macrophyte
2

productivity among wetland sites (70-170 g C/m /y) is equivalent to annual net productivity (g
2

2

C/m /y), measured values of 30-230 g C/m /y for benthic algae (based on 135 day ice-free
period) are equivalent, and in some cases higher, than macrophyte production. The measures of
algal productivity in a poor fen (F2) are higher than many of the values reported for marshes and
show that algae can contribute up to 50% of wetland primary production in peatland ecosystems.
Hydrology was the most important environmental factor influencing algal taxonomic
composition during this study. Water level is extremely dynamic within these sites and frequent
water level fluctuations have been shown to influence many of the physical and chemical factors

25

characteristic of wetland habitats (e.g., nutrients, light, temperature, substrate availability), and
therefore algal communities (Goldsborough and Robinson 1996). Research examining how
algae respond to changes in hydrology has come mainly from the work conducted in the Florida
Everglades (i.e., McCormick et al. 1998, Gottlieb et al. 2005, 2006, Iwaniec et al. 2006), where
wetland hydrology has been significantly altered by human development (Sklar et al. 2005).
Changes in wetland hydrology in boreal regions are occurring, in part because temperature
regimes that have constrained water at or near the surface of permanently frozen soils in the
region are increasing rapidly and will continue to increase during this century (Serreze et al.
2000, Hinzman et al. 2005, McGuire et al. 2007). Peatlands may be particularly sensitive to
changes in hydrology because water level is highly dependent on changes in rates of
precipitation and evapotranspiration (Hinzman et al. 2006). Therefore, my results indicating that
algal communities are most affected by changes in water depth suggest that altered hydrology
associated with climate change will have significant impacts on algal community composition.
As water depth decreased throughout the growing season, macrophyte density increased.
The increase in macrophyte biomass, and subsequently lower PAR reaching the waters surface,
was predicted to have limited algal biomass and productivity at some of the sites, particularly the
sedge dominated marsh (M1). However, following ordination analysis, the significance of water
depth in determining algal taxonomic composition suggests that water depth was a more
important determinant of algal parameters than light availability. This pattern is consistent with
an in situ mesocosm experiment conducted within the shallow riverine marsh (M4), where light
was found not to have a significant effect on algal biomass or taxonomic composition
(unpublished data; Chapter 4). Given that high latitude ecosystems receive nearly 20 h per day
of saturating light for the duration of the growing season, algal communities in northern latitude

26

ecosystems may receive sufficient light despite large seasonal changes in macrophyte cover.
Even in the sedge dominated marsh (M1), which had the highest density of macrophyte cover,
2

2

PAR ranged from 1111 µmol quanta/m /s early in the growing season to 64.4 µmol quanta/m /s
during peak macrophyte production, which is a sufficient amount of light to saturate
photosynthesis (Hill 1996). The results of this study are consistent with findings from the
Florida Everglades where experimentally reducing light availability had no effect of on
periphyton primary production or community composition (Thomas et al. 2006). These results
suggest that although the summer growing season is lengthening due to climate change processes
(Magnuson et al. 2000, Chapin et al. 2006), the subsequent decrease in light attenuation due to an
increase in the duration of macrophyte production may have little influence on algal biomass or
taxonomic composition.
Nutrients were an important environmental factor influencing algal productivity and
taxonomic composition. Both N and P influenced algal taxonomic composition in the same
direction and magnitude indicating that both nutrients are co-limiting within these ecosystems.
Similar co-limitation was reported in previous studies conducted within the Tanana River
floodplain, where the addition of a combination of N and P produced the greatest increase in
algal productivity and altered taxonomic composition compared to the addition of either nutrient
alone (Wyatt et al. 2010). Furthermore, nutrients released from previously dried peatland soils
have been shown to facilitate a spike in algal productivity (Schoenberg and Oliver 1988, Wyatt
et al. 2012) and favor the growth of filamentous green algae (Rober et al. accepted). Increased
nutrient availability may explain the higher than expected algal biomass and productivity
observed in the poor fen (F2) where wetland soils were rewetted from a flood that occurred
during 2008-2009. These results suggest that an increase in N and P availability with increased

27

soil weathering and organic matter mineralization because of climate change processes
(Bridgham et al. 1995, Rouse et al. 1997) will probably increase benthic algal biomass in
northern boreal wetlands. Furthermore, my results suggest that although algal productivity is
typically low in peatlands, spikes in algal productivity could become more prevalent with
increased frequency of flooding and drying, especially when it influences nutrient mineralization
and availability in surface soils (Wyatt et al. 2012).
Individual genera within the major algal groups exhibited interesting patterns of
abundance and distribution that were related to variation in environmental parameters. Both
water depth and nutrient concentrations declined over time in all wetland sites. A previous study
conducted at the F1 site (rich fen) reported that when nutrient concentrations and water table
position were low, nitrogen (N)-fixing cyanobacteria increased in abundance (Rober et al.
accepted). The results from this study are similar where cyanobacteria (Nostoc, Anaebena,
Haplosiphon) increased in abundance as the growing season progressed and nutrient
concentrations and water table position decreased, which was particularly prevalent in the rich
fen (F1), large riverine marsh (M2), and Equisetum dominated marsh (M3). The ability for these
taxa to fix atmospheric N enables them to survive in low nutrient environments and has been
described as the most important source of N to many arctic and boreal regions, contributing as
much as 80% of total annual ecosystem N (Solheim et al. 2006). The abundance of N-fixing
cyanobacteria in these sites suggests that they are likely contributing to N inputs in both
peatlands and marshes within the Tanana River floodplain. This is consistent with previous
findings from a Swedish mire where N-fixing cyanobacteria (Nostoc, Anaebena, Haplosiphon)
were found in association with several moss species and accounted for a significant amount of N
input (Granhall and Selander 1973) and also in feather mosses within the boreal forest (Deluca et

28

al. 2002). This study is among the few to suggest the potential importance of N-fixing
cyanobacteria to wetland N inputs, which may particularly important in northern boreal regions
where large quantities of nutrients are currently rendered inaccessible by the slowly
decomposing organic matter. Furthermore, potential increases in moss and vascular plant
production facilitated by nutrients made available by N-fixing cyanobacteria could increase the
carbon storage potential within boreal wetlands.
Filamentous green algae have been described as the most important contributors to algal
biomass in North American bogs due to their ability to tolerate periods of desiccation,
fluctuations in temperatures and light, and high acidity (Yung et al. 1986, Graham et al. 1996).
Filamentous green algae, such as Microspora, Oedogonium, Spirogyra, and Ulothrix were
abundant in both peatlands and marshes and were often found tangled among plant stems and
mosses. Chain forming desmids, such as Bambusina and Desmidium were particularly abundant
in peatlands. The large surface to volume ratio of these taxa has been hypothesized to increase
their ability to photosynthesize under nutrient limited conditions (Yung et al. 1986). Large
growths of filamentous green algae commonly appeared as grayish white clouds likely due to
infestation by fungi which are important for the degradation of algal tissue (Yung et al. 1986). In
addition to supporting fungi, labile dissolved organic carbon released from these taxa is also
important for supporting bacterial production (Wyatt et al. 2012, Rober et al. accepted).
Increases in bacterial density in the presence of algal exudates could increase the ability of the
bacterial community to decompose more recalcitrant carbon substrates (i.e., Hamer and
Marschner 2005), and thus influence wetland carbon cycling (Wyatt et al. 2012).
This is the first study to quantify spatial and temporal differences in algal biomass,
productivity, and algal taxonomic composition in relation to environmental factors in peatlands

29

and marshes in Alaska. While this study is limited in scope, having only covered one summer
growing season within a single floodplain, these data are useful for understanding the natural
distribution and abundance of algae in boreal wetlands, which is necessary to predict how
processes related to anthropogenic activity and climate change will influence wetland primary
production, biogeochemistry, and food-web structure. This is particularly important in Alaska
given the dominance of wetlands in the Alaskan landscape and the ecosystem services they
provide (e.g., carbon storage). Furthermore, my relatively high estimates of the algal
contribution to wetland primary production in both peatlands and marshes provide further
support for the inclusion of algal primary production in estimates of total wetland primary
production.

30

Table 2.1 Mean (ranges) of surface water parameters in six wetlands (2 peatlands, 4 marshes) over 12 weeks during the 2009 summer
growing season.
Characteristic

2
PAR (µmol/cm /s)

20.5

29.5

25.2

(19.8-25.9)

(21.1-41.7)

(8.81-1464.7)

(13.3-43.7)

(13.3-49.5)

989.4

1155.4

1199.6

1403.8

682.4

744.5

(967.9-1229.8)

(1029.9-1560.3)

(1221.1-1679.7)

(342.0-924.9)

(657.3-862.8)

1.38

2.45

3.10

1.85

3.28

1.93

(0-5.24)

(0-6.4)

(0.7-4.0)

(2.5-4.3)

(0.12-3.13)

11.6

7.77

33.0

18.6

12.9

4.99

(0-23.6)

(1.17-114.8)

(4.9-48.1)

(0-40.6)

(0-13.4)

7.2

11.8

15.9

17.8

12.3

20.0

(39-0)

(42-0)

(29-4)

(25-0)

(45-0)

5.53

5.69

6.57

6.31

8.39

7.60

(5.84-5.48)

(6.5-6.6)

(6.18-6.72)

(8.28-8.61)

(7.4-7.8)

20.9

19.1

19.5

20.2

18.9

16.4

(15-25.1)

(18.5-20.1)

(18.2-20.9)

(18.0-19.25)

(14.7-18.2)

12.1
(10.3-16.7)

9.80
(11.6-7.6)

6.70
(5.7-9.8)

6.79
(6.3-8.4)

12.5
-

9.23
(8.7-9.2)

28.7

47.9

35.3

40.7

10.8

13.95

(37.7-67.6)

(31.7-40)

(38.2-50.1)

(8.6-15.2)

(11.6-17.5)

713.5

862.4

357.8

758.3

556.7

698.8

(1154-424)

DOC (mg/L)

29.4

(25.3-33.7)

DO (mg/L)

22.7

(15.4-25)

Water temperature (°C)

21.8

(6.5- 4.61)

pH

M4

(10-0)

Water depth (cm)

M3

(0.96-39.1)

DIN (µg/L)

M2

(0-4.12)

SRP (µg/L)

M1

(876.9-1098.1)

TN (µg/L)

F2

(6.4-33.3)

TP (µg/L)

F1

(1297-337)

(1114-66.4)

(1208-326.7)

(1433-117.7)

(1395-206.6)

Note: TP = total phosphorus, TN = total nitrogen, SRP = soluble reactive phosphorus, DIN = dissolved inorganic nitrogen, DO =
dissolved oxygen, DOC = dissolved organic carbon, PAR = photosynthetically active radiation.
31

Table 2.2 Mean relative abundance of algal taxa in six wetlands (2 peatlands, 4 marshes) over 12
weeks during the 2009 summer growing season. Table includes only taxa with >5% relative
abundance in at least one of the wetland sites.
Algal genera

F1

F2

M1

M2

M3

M4

Sum

21.3
21.3

9.22
9.22

4.92
4.92

5.91
5.91

4.03
4.03

1.45
1.45

Sum

6.34
6.17
7.51
3.31
5.73
–
8.77
5.34
2.11
3.34
48.6

9.52
1.28
9.19
15.9
5.42
0.22
0.41
2.59
5.09
2.51
52.1

4.81
1.68
8.73
2.76
4.21
3.28
3.02
2.92
0.60
5.37
37.4

1.37
3.03
5.95
0.39
2.31
–
–
1.41
0.39
3.73
18.6

0.10
–
9.10
1.99
3.85
6.87
1.69
1.07
1.03
4.33
30.0

1.05
0.33
5.28
0.86
4.66
9.05
1.18
1.96
5.88
28.6
58.9

3.64
17.5
–
6.51
6.91
6.34
6.09
12.9
1.33
61.2

7.28
5.15
6.47
3.94
6.32
7.71
2.78
13.0
–
52.7

2.86
14.9
6.28
6.17
9.11
0.50
12.0
21.8
–
73.6

36.1
4.67
6.99
2.90
3.93
17.2
5.23
6.96
10.2
94.2

–
2.66
15.4
3.02
9.96
–
–
22.2
–
53.2

6.72
–
–
5.24
4.80
–
–
12.5
–
29.3

0.82
7.83
8.65

0.22
2.46
2.68

0.83
2.84
3.67

2.02
2.00
4.02

7.00
–
7.00

5.68
–
5.68

Chyrosophytes
Dinobryon
Greens
Bambusina
Desmidium
Gloeocystis
Microspora
Oedogonium
Palmella
Radiofilium
Sphaerocystis
Spirogyra
Ulothrix
Cyanobacteria
Anabeana
Aphanocapsa
Calothrix
Chroococcus
Gloeocapsa
Haplosiphon
Merismopedia
Nostoc
Phormidium
Sum
Diatoms
Nitszchia
Tabellaria
Sum

32

F2

M3
M4

Figure 2.1 Aerial photograph outlining the location of the six wetland study sites.

33

F2

M3

M4

Figure 2.2 Images of the six wetland sites used in this study. F1 is a rich fen. F2 is a poor fen.
M1 is a densely vegetated marsh with tussock grasses creating saturated hallows. M2 is a large
marsh complex with large open water areas covered with floating macrophytes. M3 is a shallow
riverine marsh dominated by Equisetum fluviatile. M4 is a shallow riverine marsh with a
diversity of floating and emergent macrophytes.

34

2

Log Ash-free dry mass (g / m )

A

2

Log Chlorophyll a (mg / m )

100.0

b
10.0

a

a

a

a

a
1.0

100.0

0.1
F2

M1

M2

M3

b

bc
ac
a

a

a

1.0

M4

F1

F2

M1

M2

M3

M4

100

C

D

ac

a
10.0

80

bc

b

2

100.0

10 algal cells / cm

a

a

1.0

4

2

10.0

0.1
F1

Log Algal productivity (mg C / m / h)

B

60

b
40

a
20

a

a

a
a

0.1

0

F1

F2

M1

M2

M3

M4

F1

Site

F2

M1

M2

M3

M4

Site

Figure 2.3 Mean ± SE algal chlorophyll a concentration (A), ash-free dry mass (B), productivity
(C), and cell density (D) in six Alaskan boreal wetlands during the 2009 summer growing
season. Bars with the same letter are not significantly different among sites.

35

Percent of total ecosystem GPP

100
80
60
40
20

Macrophyte
Algae

0
F1

F2

M1 M2
Site

M3

M4

Figure 2.4 Aboveground macrophyte and algal contribution to wetland primary production in six
wetlands during early (first bar in each pair) and late (second bar in each pair) growing season
2009.

36

M1
4
3
2

week
1
2
3
4
6
8
12

Axis 2

F1

M1
4
3
2

depth
F2
M2
F2

F2

F1
F1
M1

F2
F1
M 1 F2
M3
M3
F1
M4
M1
M4
M3
M4

TN
TP

F1F2
M1
4
3

M2
M2

M2

M1
F2
F1
4
3
2

week

Axis 1
Figure 2.5 NMS between relative algal abundances and surface-water chemical variables and
time from six wetlands in the Tanana River floodplain, Alaska (final stress = 7.36 for 2dimensional solution and 55 iterations). All symbols are labeled with the wetland site. Different
symbols indicate week sampled during the growing season. Axis 1 and 2 accounted for 77% and
16% of the variability in the ordination respectively, for a cumulative 93% or variance explained
by the ordination.

37

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Solheim, B., M. Zielke, J. W. Bjerke, and J. Rozema. 2006. Effects of enhanced UV-B radiation
on nitrogen fixation in arctic ecosystems. Plant Ecology 182: 109–118.
Thomas, S., E. E. Gaiser, and F. A. Tobias. 2006. Effects of shading on calcareous benthic
periphyton in a short-hydroperiod oligotrophic wetland (Everglades, FL, USA). Hydrobiologia
569: 209–221.
Thormann, M. N., and S. E. Bayley. 1997. Above ground plant production and nutrient content
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Turetsky, M. R., C. C. Treat, M. P. Waldrop, J. M. Waddington, J. W. Harden, and A. D.
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New Jersey, USA.

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CHAPTER 3

REGULATION OF ALGAL STRUCTURE AND FUNCTION BY NUTRIENTS AND
GRAZING IN A BOREAL WETLAND

3.1 Introduction

Algae can be abundant in wetlands and are significant contributors to many of the
physical, chemical, and biological processes that characterize wetland ecosystems
(Goldsborough and Robinson 1996, Wetzel 2006). In shallow wetlands where sufficient light
reaches the bottom, benthic algae can exert considerable control over dissolved oxygen
concentrations (Browder et al. 1994, Richardson 2008), sediment formation (Gleason and
Spackman 1974, McCormick et al. 1998), and nutrient uptake and retention (Wetzel 1996,
Gaiser et al. 2004), and can account for a significant fraction of total primary production
(Robinson et al. 2000, Richardson 2010, Wyatt et al. 2010). Nevertheless, relatively little is
known about the factors that regulate algal communities in wetlands, particularly in boreal
regions, where wetlands are abundant and processes related to ongoing climate change are
expected to have widespread effects on aquatic ecosystems (Rouse et al. 1997, Schindler 1998).
Benthic algae are sensitive to changes in water quality, and nutrients are among the most
important factors regulating algal assemblages in aquatic ecosystems (Borchardt 1996). Addition
of nutrients can result in significant increases in biomass (Francoeur 2001) and shifts in species
composition (Fairchild et al. 1985, Gaiser et al. 2006), both of which can alter important
ecosystem processes related to energy flow and nutrient cycling in aquatic ecosystems. Research
examining the effects of nutrient enrichment on wetland ecosystems has stemmed largely from

44

studies conducted in subtropical (McCormick and O'Dell 1996, McCormick et al. 2001, Gaiser et
al. 2005) and temperate regions (Gabor et al. 1994, Murkin et al. 1994, McDougal et al. 1997),
which are subject to nutrient contamination from increasing urban and agricultural land use (i.e.,
Sklar et al. 2005). The effects of nutrient enrichment on wetland algal communities at northern
latitudes have been less studied, perhaps because these latitudes have been less directly affected
by human development. However, boreal regions are undergoing rapid climate changes, which
have led to longer growing seasons with higher temperatures (Chapin et al. 2006). Changes in
thermal regime are expected to increase the extent of seasonal ice thaw, and could promote N
and P mineralization in the expanded active soil layer (Bridgham et al. 1995). Regional
variability in nutrient inputs may be significant, but these changes are expected to have
widespread effects on nutrient concentrations in aquatic systems throughout the boreal forest
(Rouse et al. 1997).
Nutrient enrichment is expected to increase algal productivity (Rouse et al. 1997), but
some evidence indicates that northern aquatic ecosystems may not show the same positive
relationship between increasing nutrient concentrations and algal biomass as those occurring at
lower latitudes (Flanagan et al. 2003). In a meta-analysis of lakes across a wide latitudinal
gradient, Flanagan et al. (2003) found that above 60°N, algal biomass decreases with increasing
latitude independently of nutrient concentration. This trend indicates strong environmental
controls on the algal response to nutrients at high latitudes. This control could occur via
physiological constraints associated with extremes in temperature and day length or via topdown regulation of algal primary production, in which grazers are free to consume any increase
in algal biomass that may be stimulated by nutrient enrichment (Hansson 1992).
In the absence of nutrient limitation, grazing strongly influences the quantity and quality

45

of algal biomass as well as the taxonomic composition and growth form of the algal assemblage
(McCormick and Stevenson 1991, Feminella and Hawkins 1995, Steinman 1996). Grazing
generally causes a reduction in algal biomass and can maintain low biomass accumulation even
in conditions of increased resource availability (e.g., nutrients and light) (Feminella and Hawkins
1995, Hill et al. 1995, Rosemond et al. 2000). Despite reductions in biomass, grazing also can
lead to increased productivity of the algal assemblage through the use of excreted nutrients
(McCormick and Stevenson 1991, Hillebrand 2002). The extent to which these regulatory
processes operate in wetlands is largely unknown because evidence of grazing in wetland
ecosystems has been largely circumstantial (Robinson et al. 2000).
I investigated the independent and interactive effects of grazing by the snail Lymnaea and
nutrient enrichment on a benthic algal community in an Alaskan marsh to evaluate the potential
for grazers to regulate benthic algal biomass and community composition given projected future
increases in nutrient concentrations. Wyatt et al. (2010) reported the effects of nutrient
enrichment alone in a concurrent study. I report the effect of grazers on algal community
structure and biomass following enrichment with limiting nutrients. I also examined the role of
grazers in wetland biogeochemical cycling by evaluating the potential of consumer-driven
nutrient recycling to influence algal accumulation. I tested the hypotheses that nutrient
enrichment stimulates algal accumulation and grazers regulate algal responses to nutrients by
suppressing algal accumulation but increasing productivity via nutrient recycling.

3.2 Methods

Study site

46

I conducted this study in a freshwater marsh in the floodplain of the Tanana River near
the Bonanza Creek Experimental Forest, ~35 km southwest of Fairbanks, Alaska, USA (lat
64°42’N, long 148°18’W). This region has a relatively short growing season (≤135 d) with >21 h
of light/d in June. The floodplain lies within an intermontane plateau characterized by wide
alluvium-covered lowlands with poorly drained, shallow soils over discontinuous permafrost
(Begét et al. 2006). Oxbows and thaw ponds dominate the floodplain landscape, and fluvial
deposition and erosion are annual disturbances (Begét et al. 2006). The study site is characteristic
of other marsh habitats that occur in the floodplain and has dense stands of beaked sedge (Carex
utriculata) and swamp horsetail (Equisetum fluviatile) surrounding open-water pools with sparse
emergent vegetation. The wetland supports grazer fauna including wood frog tadpoles (Rana
sylvatica) in early spring and the common pond snail Lymnaea spp., which is the most abundant
2

grazer in the marsh (~30/m ) throughout the summer growing season. Background
concentrations of inorganic nutrients were generally low during the study and were within the
range of other wetlands and lakes in the region (reviewed in Wyatt et al. 2010). A detailed
description of background physical and chemical conditions for my study site was given by
Wyatt and Stevenson (2010).

Experimental design
I manipulated nutrient supply and grazers in situ from 29 June to 22 July 2007 in
mesocosms modified from the design described by Greenwood and Lowe (2006). I constructed a
raised boardwalk prior to the beginning of the study to prevent the disturbance of wetland
sediments during experimental set-up and regular sampling. I constructed 16 mesocosm
enclosures by rolling welded wire mesh into a cylinder (40 cm in diameter) and wrapping each

47

cylinder with a layer of 0.1-mm-thick clear window vinyl. Enclosures were evenly spaced
throughout an open-water area of the wetland with ~10% vegetation cover and a water depth of
44–49 cm. Enclosures were pushed into the sediments so that ~15 cm extended above the water
surface, which allowed water inside enclosures to be in contact with sediments and kept
2

vegetation intact to simulate natural wetland conditions. I placed 4 ceramic tiles (25 cm ) into
each enclosure as artificial substrates for algal colonization. I suspended all substrates
horizontally by attaching them to a wire frame that could be repositioned to maintain a consistent
depth of 5 cm below the water surface.
I used a factorial combination of nutrient enrichment (enriched or control) and grazing
(grazed, grazer exclusion, or grazer absent) with 4 replicates of each treatment combination
(Figure 3.1). I added nutrients from a stock solution every 4 d to achieve water-level
concentrations for N = 1000 µg/L NaNO3, P = 100 µg/L NaPO4, and Si = 10 mg/L Na2O3Si after
each addition. I assumed these nutrient levels would saturate algal growth rates because they
exceeded concentrations reported to be limiting for benthic algae in studies reviewed by
Borchardt (1996). I began enrichment after the late-spring thaw to simulate nutrient inputs from
groundwater or surface-water runoff (McDougal et al. 1997). I manipulated grazer access inside
nutrient enriched and control enclosures by removing grazers completely (grazer absent
treatment) or by nesting caged (grazer-exclusion treatment) and uncaged (grazed treatment)
substrates together inside enclosures with natural abundances of the snail Lymnaea (Figure 3.1).
Cages around substrata within mesocosm enclosures prohibited grazing but allowed exchange of
water between the grazed and grazer-exclusion treatments to give algae access to nutrients
excreted by grazers. Algae in grazer-absent treatments received nutrients only from amendments.
Cages were made of 1-mm clear polyethylene Nitex screen (Dynamic Aqua-Supply Ltd., Surrey,

48

British Columbia). I evaluated mesocosm enclosure effects by monitoring conditions at 4
designated sites within the wetland using caged and uncaged substrates without enclosures or
nutrient manipulation (open wetland treatment).

Sampling methods
I collected and filtered water for dissolved nutrient analysis immediately after each
nutrient addition (every 4 d) using a 0.45-μm Millex®-HA syringe-driven filter unit (Millipore
Corporation, Bedford, Massachusetts). I determined concentrations of dissolved inorganic N
(DIN) as NO3 + NO2-N (Cd reduction method; APHA 1998), and of silicate (SiO2) (molybdate
method; APHA 1998) with a Skalar® auto-analyzer (Skalar Analytical, Breda, The Netherlands),
and of soluble reactive P (SRP) (ascorbic acid method; APHA 1998) with a Genesys™ 2 UVVis spectrophotometer (Spectronic Analytical Instruments, Garforth, UK). I measured water
depth, temperature, pH, and conductivity inside and outside each enclosure every 4 d with a
meter stick and a calibrated model 556 YSI® Multi-Probe (Yellow Springs Instruments, Yellow
Springs, Ohio).
In each enclosure, I removed algae from tiles with a toothbrush after 24 d and split the
resulting homogenous algal slurry volumetrically for analysis of ash-free dry mass (AFDM) and
benthic algal abundance. I was unable to measure chlorophyll a because I could not preserve
samples in this remote field location. Thus, algal biomass was measured as AFDM, cell density,
2

and total biovolume. I determined AFDM (mg/cm ) by drying samples for 24 h at 105°C and
combusting them for 1 h at 500°C in preweighed aluminum pans to determine the difference
between dry mass and ashed mass, respectively (APHA 1998). I preserved a whole water sample
in a 2% formalin solution for algal community analysis. I used standard protocols to characterize

49

algal biomass and dominant taxonomic composition. I counted ≥300 algal cells or
colonies/sample in a Palmer–Maloney nanoplankton counting chamber and identified the algae
to genus at 400× magnification (Charles et al. 2002). I quantified benthic algal abundance
2

(cells/cm of substrate) with the formula provided by Lowe and Laliberte (2006). I calculated
3

2

biovolume (µm /cm of substrate) by multiplying algal cell density by the estimated cell volume
using geometric formulae from Hillebrand et al. (1999).
I evaluated the potential for grazers to recycle N and P by estimating the daily rate of
nutrients excretion by the snails. I collected 24 snails from the open wetland and placed each
snail in a centrifuge tube filled with 40 mL of filtered water. After a 24 h incubation period, I
measured DIN and SRP concentrations with the methods described previously.

Statistical analyses
I log(x + 1)-transformed all data for statistical analyses if necessary to correct for
nonnormal distribution and unequal variances among treatments prior to analysis. I used an
unbalanced partly nested analysis of variance (ANOVA) (Quinn and Keough 2002) to determine
the effects of nutrient enrichment and grazers on benthic algal biomass as AFDM, cell density,
and total biovolume. I examined differences in biovolume of common genera (occurring at ≥5%
relative abundance) among treatments with 1-way ANOVA. I used Bonferroni corrections for
the algal assemblage analyses to preserve the experiment-wise Type I error rate of p = 0.05. I
used repeated-measures ANOVAs to determine effects of treatments on dissolved nutrients,
water depth, water temperature, pH, and conductivity measured throughout the experiment. In
instances when ANOVA indicated significant differences among treatments, I used Tukey post
hoc comparison of means tests to discriminate between different factor levels. I performed all

50

statistical analyses with SYSTAT (version 11; SYSTAT Software Inc., Point Richmond,
California).

3.3 Results

Water chemistry
Background levels of inorganic nutrients were low (mean ± SE: DIN = 8.02 ± 1.28 µg/L,
SRP = 8.69 ± 1.28 μg/L, SiO2 = 12.09 ± 0.49 mg/L) and remained nearly constant over the 24-d
experiment (Figure 3.2A–C). Nutrient levels in the open wetland and control enclosures with and
without snails did not differ significantly from each other (p > 0.05). Nutrient enrichment
increased water-column concentrations of DIN (1124.3 ± 705.6 µg/L), SRP (49.6 ± 47.6 μg/L)
and Si (35.7 ± 14.2 mg/L) to levels significantly greater than in the open wetland and control
enclosures (p < 0.05; Figure 3.2A–C). Water-column dissolved nutrient concentrations inside
nutrient-enriched enclosures did not differ between treatments with or without snails (p > 0.05).
Water depth (45.1 ± 0.5 cm), temperature (16 ± 0.05°C), pH (7.5 ± 0.3), and conductivity (0.37 ±
0.006 µS/cm) varied during the experiment but did not differ significantly among treatments (p >
0.05; data not shown).

Algal biomass
Significant effects of grazing were observed only after enrichment. Benthic algal biomass
was similar between the open wetland and control enclosures across all grazing treatments (p >
0.05; Figs 3.3A, B, 3.4A, B). AFDM (F2,13 = 81.91, p < 0.0001; Figure 3.3A), cell density
(F2,13 = 122.6, p < 0.0001; Figure 3.3B), and total biovolume (F2,13 = 14.86, p = 0.004; Figure

51

3.4C) were significantly greater in nutrient-enriched than in control enclosures. In nutrientenriched enclosures, AFDM (F2,11 = 7.88, p = 0.01; Figure 3.3A), cell density (F2,11 = 7.26, p =
0.01; Figure 3.3B), and total biovolume (F2,11 = 7.92, p = 0.01; Figure 3.4C) were significantly
lower in grazed than in grazer-exclusion treatments. In nutrient-enriched enclosures, algal
AFDM, cell density, and total biovolume was significantly greater in the grazer-exclusion
treatment than in grazed and grazer-absent treatments (p < 0.05) but did not differ significantly
between the grazed and grazer-absent treatments (p > 0.05). The nutrient × grazer interaction
term was significant for AFDM (F3,11 = 5.37, p = 0.02) and total biovolume (F3,11 = 4.64, p =
0.02).

Taxonomic composition
The algal community in the open wetland consisted of primarily Mougeotia and
Gloeocystis (Chlorophyta), Trachelomonas and Euglena (Euglenophyta), and Chroococcus
(Cyanobacteria), which made up ~90% of the total biovolume (Figure 3.4A). All taxa
represented a similar proportion of total biovolume in the control treatment compared to in the
open wetland except the proportion of Euglena (F7,29 = 17.2, p < 0.001) was significantly
greater in the control treatment than the open wetland (Figure 3.4B). Nutrient enrichment
increased the proportion of Mougeotia, Gloeocystis (F7,29 = 14.8, p < 0.001), and Chroococcus
(F7, 29 = 44.7, p < 0.001) compared to the control (Figure 3.4C). Grazing had little effect on the
algal community under low-nutrient conditions. However, in nutrient-enriched enclosures, the
proportion of Mougeotia was significantly lower (F7,24 = 2.5, p = 0.04; Figure 3.4C) and the

52

proportions of Chroococcus (F7,24 = 29.6, p < 0.001) and Gloeocystis (F7,24 = 12.3, p < 0.001)
were significantly higher in grazed than in grazer-exclusion treatments. Grazer-absent treatments
in nutrient-enriched enclosures were dominated by Gloeocystis and Chroococcus and lacked
Mougeotia. A combination of Limnothrix, Aphanocapsa, Ophiocytium, Ulothrix, and Nitzschia
made up <10% of the total biovolume in any 1 treatment.

Nutrient recycling by grazers
Excretion rates of DIN and SRP were 0.0004 mg snail

–1 –1

d

–1 –1

and 0.045 mg snail

d ,

respectively. I multiplied the excretion rates of DIN and SRP by the estimated number of snails
2

in the wetland (30 snails/m ), and calculated that snails could regenerate N at a rate of 7.5 mg/d
and P at 844.8 mg/d. When I estimated concentration changes by accounting for the approximate
volume of water in the wetland, I calculated that snails could regenerate N at a rate of 0.0002 mg
–1 –1

L

d

–1 –1

and P at 0.019 mg L

d .

3.4 Discussion

As predicted, addition of nutrients resulted in a significant increase in benthic algal
biomass and a shift in taxonomic composition in this northern boreal wetland. An increase in N
and P availability with increased soil weathering and organic matter mineralization is expected
for the region because of climate-change processes (Bridgham et al. 1995, Rouse et al. 1997).
My results suggest that this increase probably will increase benthic algal biomass in northern
boreal wetlands. The increase in algal biomass in response to a combination of N and P in this

53

study was similar to increases reported in other wetland studies conducted within the Tanana
River Floodplain (Wyatt et al. 2010) and to those in temperate regions (Wu and Mitsch 1998,
Robinson et al. 2000, Scott et al. 2005). My findings differ from results from the subtropical
Everglades where nutrient enrichment, especially P, causes an overall decrease in algal biomass
because of the loss of the native cyanobacterial mat (reviewed by McCormick and Stevenson
1998, Gaiser et al. 2006, Richardson 2010).
The shift in algal taxonomic composition from a diverse assemblage in ambient
conditions to one dominated by green algae and cyanobacteria after nutrient enrichment also has
been documented in temperate and subtropical wetlands receiving nutrient enrichment from
urban or agricultural runoff (Murkin et al. 1991, McCormick et al. 2001). The ability of some
filamentous green algae to exploit high nutrient concentrations and to outcompete other taxa for
light and space (i.e., Graham et al. 1996) may explain the increase in Mougeotia following
nutrient enrichment in this shallow boreal wetland. My findings are consistent with those
reported from the Florida Everglades where direct nutrient amendments (McCormick and O'Dell
1996) and from Delta Marsh, Manitoba, where nutrient-release from reflooded sediments
(Robinson et al. 1997) resulted in an overall increase in taxa from the family Zygemataceae
(Mougeotia, Spirogyra, Zygnema).
Grazing decreased algal biomass with and without nutrient enrichment, but results varied
in magnitude between treatments. In the absence of nutrient limitation, grazing strongly
influenced the quantity of algal biomass as well as the taxonomic composition and growth form
of the algal assemblage. This effect is consistent with trophic theory (Hairston et al. 1960,
Persson et al. 1988) where, in the absence of a higher predator, grazers are free to consume any
increase in algal biomass that may be stimulated by nutrient enrichment. This finding indicates

54

that, much like in lake and stream ecosystems (Hansson 1992, Feminella and Hawkins 1995,
Steinman 1996, Hillebrand 2002), benthic grazers can maintain low algal biomass accumulation
in northern boreal wetlands even in conditions of increased resource availability.
The decrease in Mougeotia on grazed substrates is consistent with results of other studies,
in which taxa that extended above the substratum were removed at a higher rate than those with a
more-prostrate or low-profile growth form (Cuker 1983, Steinman 1996, Hillebrand et al. 2002).
The lower abundance of Mougeotia in the grazer-absent treatment may have been the result of
different proportions of nutrients made available by snails within the periphyton matrix (see
discussion below). The removal of a large overstory species like Mougeotia promotes the
growth of smaller, faster growing understory species and leads to an increase in overall algal
productivity because of increased resource availability (McCormick and Stevenson 1991). This
process may explain the increased proportion of Chroococcus and Gloeocystis in grazed and
grazer-absent treatments and suggests that these taxa were able to take advantage of nutrient
inputs but were unable to compete for other resources, such as light, in treatments where
filamentous taxa dominated the algal community.
The significant interaction between nutrients and grazers suggests that the algal
community is under dual control from the bottom-up (nutrient limitation) and from the top-down
(consumption by herbivores). These interacting and opposing influences of nutrients and grazing
are consistent with results reported in the literature from lakes and streams (Rosemond et al.
1993, Hillebrand 2002), reflecting a similar importance of their regulatory effects on benthic
algal biomass and taxonomic composition in boreal wetlands. However, my results suggest that
the relative strengths of top-down vs bottom-up control were not equivalent. My experimental
design allowed me to examine both independent and interactive effects of nutrients and grazing,

55

so I was able to see that nutrients had a consistently greater effect on algal biomass and
taxonomic composition than did grazing, a result indicating that nutrient limitation was the
stronger regulatory factor in my study site. This finding differs from results reported by
Hillebrand (2002), who determined through meta-analysis that grazers are the stronger regulatory
factor influencing algal assemblages more often than nutrients in lakes, streams, and coastal
environments.
Despite the small direct effects of grazers under low-nutrient conditions, my results
suggest that they may influence algal biomass indirectly by recycling the low concentrations of
nutrients that are present. I expected that algal biomass would be similar between the grazerexclusion and grazer-absent treatments because neither treatment was grazed and that algal
biomass in both would be greater than in grazed treatments. Instead, algal biomass was similar in
grazer-absent and grazed treatments. Moreover, algal biomass increased 2× in grazer-exclusion
treatments. Snails are large and highly mobile consumers that are capable of recycling nutrients
at large spatial scales, which facilitates the resuspension and movement of nutrients for algal
uptake and use (Frost et al. 2002, Vanni 2002, Abbott and Bergey 2007). Snails in my study site
excreted a small but potentially important amount of nutrients, especially P, in their waste. Algae
in the grazed treatment may have been able to use recycled nutrients to regenerate biomass after
consumptive losses. The absence of consumer-driven nutrient recycling in grazer-absent
enclosures may have limited biomass accumulation to the point that it was more similar to
biomass in the grazed treatment than in the grazer-exclusion treatment. Algal biomass excluded
with a cage was inaccessible to grazers and exposed to excreted nutrients, which may explain the
greater biomass in grazer-exclusion than in grazed and grazer-absent treatments in enriched
enclosures.

56

Evidence exists for the positive effects of consumer-driven nutrient recycling on algal
growth rates in lakes (Elser et al. 2000, Vanni et al. 2002, Liess and Haglund 2007) and streams
(McCormick and Stevenson 1991, Evans-White and Lamberti 2006), but my results suggest that
consumer-driven nutrient recycling may strongly affect algal growth in shallow boreal wetlands.
In many wetland habitats, primary production depends on the rate of nutrient mineralization.
Therefore, the slower nutrients are released by decomposition, the less available nutrients are to
the ecosystem (de Mazancourt et al. 1998). Consumer-driven nutrient recycling may be an
important source of N and P to autotrophs in the water column and benthos in boreal wetlands,
where large quantities of nutrients are locked away in permanently frozen soils (Carpenter et al.
1992, Duff et al. 1999, Hinzman et al. 2005), than in regions with faster rates of nutrient
remineralization (Frost et al. 2002).
The available literature on benthic algal assemblages and the factors that regulate their
structure and function is much less for freshwater wetlands than for lakes and streams (Robinson
et al. 2000). This lack of information is particularly acute for northern boreal regions where
wetlands are abundant and extremely vulnerable to disturbances associated with climate change.
My data provide evidence that nutrients and grazing are important factors regulating benthic
algal biomass and community composition in a northern boreal wetland. They suggest that
nutrients are the stronger regulatory factor, but grazing quickly became important after nutrient
addition. Therefore, grazing may play an increasingly important role in the future if nutrient
inputs increase as expected with climate change (i.e., increased permafrost collapse and soil
weathering). My results support the hypothesis that nutrient enrichment stimulates algal
accumulation and demonstrate that the strong positive relationship observed between nutrient
addition and algal biomass at lower latitudes persists in high latitudes aquatic ecosystems. The

57

ability of grazers to suppress algal accumulation following enrichment supports my hypothesis
and may provide insight to the dampened response of algae to nutrients previously observed in
high-latitude regions (i.e., Flanagan et al. 2003). Furthermore, my results suggest the potential
importance of consumer-driven nutrient recycling to algal productivity and wetland
biogeochemistry, which may be particularly significant for northern boreal regions where large
quantities of nutrients are rendered inaccessible by the slowly decomposing organic matter.

58

Grazed and Excluded Grazed and Excluded Grazer absent
Control enclosures
Nutrient enriched Control enclosures
enclosures

Lymnaea

Uncaged substrate

Grazer absent
Nutrient enriched
enclosures

Caged substrate

Grazed and Excluded
Open wetland

Nutrients

Figure 3.1 Schematic diagram of enclosure design. Enclosures were constructed of welded
wire mesh (40 cm in diameter × 85 cm tall) and held ~60 L of water. The top 75 cm of each
cylinder was wrapped with 0.1-mm clear window vinyl and embedded 10 cm into sediments
with an open top extending 15 cm above the water column. I suspended all substrates
attached to frames that maintained a consistent depth of 5 cm below the water surface. I
nested caged and uncaged substrates together inside enclosures (grazer-exclusion and grazed
treatments) and added natural abundances of snails. All snails were removed from grazerabsent treatment enclosures.

59

3000

NO3 (µg/L)

A

2000

1000

0
200

150

4

(µg )

PO4 (µg/L)

B

100

50

0
80
70

Si (mg/L)
Si (mg/L)

60
50

NPSi + Grazers
NPSi - Grazers
Control + Grazers
Control - Grazers
Open wetland

C

40
30
20
10
0
0

4

8

12

16

20

Days since substrate deployment

Figure 3.2 Dissolved nutrient concentrations of NO3 (A), PO4 (B), and Si (C) in nutrient
enriched, control, and open wetland enclosures with (+) and without (–) grazers.
60

4

Grazed
Excluded
Absent

A

c

AFDM (mg/cm2)

3
b

b

2
aa

1

aaa

0

15

106 cells/cm2

B

10

c

5
b
a

0

b

a

Open
wetland

aa a
Control Nutrient
enriched

Figure 3.3 Mean (±1 SE; n = 4) ash-free dry mass (AFDM) (A) and cell density (B) in the open
wetland, control, and nutrient-enriched enclosures with and without grazers. Bars with the same
letter are not significantly different among treatments.

61

Figure 3.4 Taxonomic composition and total biovolume of algae with >5% relative
abundance in the open wetland (A), control (B), and nutrient-enriched (C) enclosures
with and without grazers.
62

LITERATURE CITED

63

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Wyatt, K. H., and R. J. Stevenson. 2010. Effects of acidification and alkalinization on a
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CHAPTER 4
THE ROLE OF LIGHT LIMITATION AND HERBIVORY ON ALGAL RESPONSE TO
NUTRIENT INPUTS IN A BOREAL MARSH, ALASKA

4. 1 Introduction

Algae can be abundant in wetlands and are significant contributors to many of the
physical, chemical, and biological processes that characterize wetland ecosystems
(Goldsborough and Robinson 1996, Wetzel 2006). In shallow wetlands where sufficient light
reaches the bottom, benthic algae can influence dissolved oxygen concentrations (Browder et al.
1994, Richardson 2008), sediment formation (Gleason and Spackman 1974, McCormick et al.
1998), nutrient uptake and retention (Wetzel 1996, Gaiser et al. 2004), and can account for a
significant amount of total primary production (Robinson et al. 1997, Richardson 2009, Wyatt et
al. 2010). Despite their importance, we know relatively little about the factors that regulate algal
communities in wetlands. This is particularly true for boreal regions, where wetlands are
abundant and processes related to ongoing climate change are expected to have widespread
impacts on aquatic ecosystems (Rouse et al. 1997, Schindler 1998).
Algal primary production is generally controlled by factors regulating from the bottomup (light and nutrients) and from the top-down (herbivory). Even though these structuring forces
are widely accepted to be interactive in both terrestrial (Hawkes and Sullivan 2001) and aquatic
(Brett and Goldman 1997, Leibold et al. 1997, Hillebrand 2002) ecosystems, the degree to which
each process influences producer biomass varies. Determining the hierarchy of regulatory
factors on primary producers and the strength of their interaction is a fundamental goal for

70

ecologists (Hansson 1992, Rosemond et al. 2000), and the extent to which these regulatory
processes operate in wetlands is largely unknown.
Light is required to carry out photosynthesis, therefore it is commonly considered the
most important resource regulating algal communities (Hill 1996). Light conditions in wetlands
are extremely dynamic. Not only are wetlands exposed to seasonal changes in incident radiation
but light attenuation also varies with the degree of shading by overlying macrophytes (Robinson
et al. 2000) because macrophytes are the primary substrate available for benthic algal
colonization in wetlands. This poses an interesting problem for light limited algal primary
production, especially in northern boreal wetlands that receive over 20 h of daylight during the
summer growing season, resulting in rapid macrophyte growth (Chapin et al. 2006) and therefore
decreased light availability to benthic algae. Furthermore, climate change processes which have
led to a longer growing season (Magnuson et al. 2000, Chapin et al. 2006), with a subsequent
increase and duration of macrophyte production.
In lakes and streams, insufficient light reduces the ability of algae to acquire and utilize
essential nutrients (Hill et al. 1995, Hillebrand 2005, Liess et al. 2009). Therefore changes in
light attenuation may affect the way benthic algae respond to nutrients (Grimshaw et al. 1997,
Rosemond et al. 2000). This issue is particularly acute in boreal wetlands where changes in
thermal regime are expected to increase the extent of seasonal ice thaw, which will probably
promote nitrogen and phosphorus mineralization in the expanded active soil layer (Bridgham et
al. 1995). An increase in nutrients is expected to increase algal primary production (Rouse et al.
1997). Understanding how changes in light attenuation will affect the ability of benthic algae to
utilize nutrients is further complicated by food web interactions where grazers are free to

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consume any increase in algal biomass, overwhelming the algal response to either changes in
light, nutrients or both (Feminella and Hawkins 1995, Hill et al. 1995, Rosemond et al. 2000).
The aim of this study was to investigate in situ how differences in the relative availability
of solar radiation in the presence or absence of grazing, alter the ability of benthic algae to
respond to nutrient enrichment in a northern boreal wetland. I tested the following hypotheses:
1) nutrient enrichment stimulates algal accumulation, 2) grazers regulate algal responses to
nutrients by suppressing algal accumulation, and 3) shading by macrophytes reduces the ability
of algae to respond to nutrient enrichment. The results of this study add insight into the balance
between resource availability and consumption, which ultimately determines the biomass and
taxonomic composition of primary producers.

4.2 Methods

Study Site
I conducted this study in a freshwater marsh located on the floodplain of the Tanana
River near the Bonanza Creek Experimental Forest, situated approximately 35 km southwest of
Fairbanks, Alaska, U.S.A. (latitude 64.42° N, longitude 148.18° W) for three weeks from June
22 to July 8, 2008. The area has large fluctuations in daylight with more than 21 h on June 21
and less than 3 h on December 21. The low sun angle in both summer and winter limit the solar
radiation that reaches the water surface. In Fairbanks (65°N) the maximum solar angle is 48.5°
2

at the summer solstice, resulting in daily solar radiation of 22,375 KJ/m /d in June (Hinzman et
al. 2006). The study site is characteristic of other marsh habitats that occur in oxbows along the
flood plain, which are shallow with dense stands of beaked sedge (Carex utriculata) and swamp

72

horsetail (Equisetum fluviatile) surrounding open water pools with sparse emergent vegetation.
The wetland supports grazer fauna including wood frog tadpoles (Rana sylvatica) in early spring
and the common pond snail Lymnaea sp., which is the most abundant grazer in the marsh
2

(~30/m ) throughout the summer growing season. Background concentrations of inorganic
nutrients were generally low during the study and within the range of other wetlands and lakes in
the region (see review in Wyatt et al. 2010). Mean ± SE dissolved organic carbon (DOC)
concentration, measured biweekly from May to July, was 13.95 ± 2.4 mg/L and reduced
photosynthetically active radiation (PAR) by approximately 20% at the surface.

Experimental design
I manipulated light, grazing, and nutrient concentrations in situ using 32 open-ended
cylinder enclosures modified from the design described by Greenwood and Lowe (2006). I
constructed enclosures by rolling welded wire mesh into a cylinder (40 cm in diameter) and lined
the inside of each cylinder with a layer of 0.1 mm clear polyvinylidene film, which transmits
90% of PAR and 80-90% UV (Bothwell et al. 1993). I embedded each enclosure 10 cm into the
sediment with the open top extending above the water column and placed them in areas with
2

similar depth and open canopy. I placed four ceramic tiles (25 cm ) into each enclosure as
artificial substrates for algal colonization. I suspended all substrates attached to a wire frame that
could be repositioned to maintain a consistent depth of 5 cm below the water surface.
I measured algal and macrophyte biomass over a five week period during the previous
summer growing season to measure changes in algal biomass with deceasing light due to
increasing macrophyte growth (Figure 4.1). The shaded treatment (75% blocked) simulated the
low light levels measured at peak macrophyte biomass (Figure 4.1). The un-shaded treatment

73

(0% blocked) simulated the early growing season when macrophyte biomass is low (Figure 4.1).
I used a factorial combination of nutrient enrichment (enriched or control), grazing (grazed or
un-grazed), and light (shaded or un-shaded) with four replicates each (Figure 4.2). Un-shaded
treatments received full sunlight. Shading was achieved using charcoal solar screening (New
York Wire, Mt. Wolf, PA, U.S.A.) that blocked 75% of light. I adhered shade screen to 40 cm
diameter rings made of pipe insulation, allowing all light treatments to float on the waters surface
within each enclosure. This allowed the screen to move freely up and down with water level
fluctuation, and also kept the screen suspended above the water so as not to disturb the
substrates.
In a concurrent study, Wyatt et al. (2010) identified nitrogen (N) and phosphorous (P) as
the nutrients most limiting to algal productivity at this study site. Therefore, I added a preweighed combination of N as NaNO3 and P as Na2HPO4 evenly onto the waters surface in
nutrient enriched enclosures every four days, for 16 days. I assumed these nutrient levels would
saturate algal growth rates because they exceeded concentrations reported to be limiting for
benthic algae in studies reviewed by Borchardt (1996). I began enrichment after the late spring
thaw to simulate nutrient inputs from groundwater or surface water runoff (McDougal et al.
1997). I manipulated grazer access to periphyton on tiles inside nutrient enriched and control
enclosures by nesting both caged (un-grazed treatment) and un-caged (grazed treatment)
substrates together inside enclosures with natural abundances of the snail Lymnaea (Figure 4.2).
Cages around substrata within mesocosm enclosures prohibited grazing but allowed algae access
to nutrients. Cages were made of 1 mm clear polyethylene Nitex screen (Dynamic Aqua-Supply
Ltd., Surrey, BC, Canada), which blocks approximately 5% PAR.

74

Sampling procedure
I measured average light during 15 second intervals every four days in each enclosure
using a LI-COR submersible quantum sensor and LI-250 light meter (LI-COR, Lincoln, NE,
U.S.A.) at peak sunlight. I collected and filtered water for dissolved nutrient analysis every four
days using a 0.45 μm Millex®-HA syringe-driven filter unit (Millipore Corporation, Bedford,
MA, USA). I determined concentrations of dissolved inorganic nitrogen (DIN) as nitrate +
nitrite-N (cadmium reduction method, APHA 1998) using a Skalar® auto-analyzer (Skalar
Analytical, Breda, Netherlands), and of soluble reactive phosphorous (SRP) (ascorbic acid
method, APHA 1998) using a Genesys™ 2 UV-Vis spectrophotometer (Spectronic Analytical
Instruments, Garforth, UK). I measured water depth, water temperature, pH, and conductivity in
each enclosure every four days using a calibrated 650 YSI meter (YSI incorporated, Yellow
Springs, OH, U.S.A.).
Following completion of the study, I removed algal biomass on tiles from each enclosure
with a toothbrush and split the resulting homogenous algal slurry volumetrically for analysis of
ash-free dry mass (AFDM) and cell counts. I was not able to measure chlorophyll a because I
could not preserve samples in this remote field location. Thus, algal biomass was measured as
2

2

3

2

mg/cm AFDM, cell density/cm , and total algal biovolume μm /cm . I determined AFDM after
drying samples for 24 h at 105ºC and ashing for 1 h at 500ºC in pre-weighed aluminum pans to
determine the difference between dry mass and ashed mass, respectively (APHA 1998). I
preserved a whole water sample with a 2% formalin solution for algal community analysis. I
used standard protocols to characterize algal biomass and dominant taxonomic composition by
counting and identifying at least 300 algal cells or colonies per sample using a Palmer-Maloney
nanoplankton counting chamber and identified algae to genus at 400x magnification (Charles et

75

2

al. 2002). I quantified benthic algal abundance (cells/cm of substrate) using the formula
3

2

provided in Lowe and Laliberte (2006). I calculated biovolume (µm /cm of substrate) by
multiplying algal cell density by the estimated cell volume using geometric formulae from
Hillebrand et al. (1999).

Statistical Analyses
All data for statistical analyses were log + 1 transformed if necessary to correct for nonnormal distribution and unequal variances among treatments prior to analysis. I used a 3-way
analysis of variance (ANOVA) with light and nutrients as between subjects factors and grazing
as a within subject factor to determine the effects of light manipulation, nutrient enrichment, and
grazing on benthic algal biomass as AFDM, cell density, and total biovolume. I examined
differences in biovolume of common genera (occurring at ≥ 5% relative abundance) among
treatments with a 1-way ANOVA. I used repeated measures ANOVAs to determine effects of
treatments on dissolved nutrients, water depth, water temperature, pH, and conductivity
measured throughout the experiment. I used Tukey post-hoc comparison of means tests to
discriminate between different factor levels. I performed all statistical analyses with SYSTAT
(version 11, SYSTAT software inc. Point Richmond, CA, USA).

4.3 Results

Water chemistry
Mean ± SE inorganic N and P concentrations in the control enclosures were DIN = 2.63 ±
6.39 µg/L; SRP = 17.3 ± 8.60 μg/L and remained nearly constant over the 16 day experiment

76

(Figure 4.3). N and P concentrations in nutrient enriched enclosures (DIN = 2194 ± 1184 µg/L;
SRP = 239 ± 306 μg/L) were significantly greater than the control enclosures (p < 0.05).
Nutrient concentrations remained slightly higher in shaded treatments compared to un-shaded
treatments, but differences were not statistically significant (p > 0.05). Depth (17.6 ± 0.57 cm),
water temperature (17.8 ± 0.15 °C), pH (7.03 ± 0.03), and conductivity (0.29 ± 0.01 µS) varied
during the experiment but did not differ among treatments (p > 0.05; data not shown). Mean
2

2

PAR was 568 ± 85.0 µmol quanta/m /s in un-shaded treatments, 63.0 ± 12.0 µmol quanta/m /s
2

in shaded treatments, and 638.7 ± 75.4 µmol quanta/m /s in the open wetland.

Algal biomass
Grazing significantly decreased AFDM (F1,11 = 40.5, p < 0.0001; Figure 4.4; Table 4.1),
cell density (F1,11 = 39.4, p < 0.0001; Figure 4.4; Table 4.1), and total biovolume (F1,11 = 18.6,
p = 0.001; Figure 4.5; Table 4.1) compared to un-grazed treatments in control and nutrient
enriched enclosures, under all light conditions. Grazers decreased algal biomass in nutrient
enriched enclosures to levels that were not significantly different from grazed biomass in control
enclosures (p > 0.05) under all light conditions. Algal biomass was greater in un-grazed nutrient
enriched enclosures compared to control enclosures under all light conditions but differences
were not significant (p > 0.05; Table 4.1). There was a significant effect of light on AFDM
(F1,11 = 9.21, p = 0.01; Table 4.1), but not on cell density or total biovolume (p > 0.05).
There was a significant two way interaction between nutrients and grazing for AFDM
(F1,11 = 4.77, p = 0.05; Table 4.1), cell density (F1,11 = 11.04, p = 0.007; Table 4.1), and total

77

biovolume (F1,11 = 4.07, p = 0.069; Table 4.1). The significant interaction between nutrients
and grazers suggests that the algal community is under dual control from the bottom-up (nutrient
limitation) and from the top-down (consumption by herbivores) where nutrient enrichment
increases algal biomass and grazing reduces the effect of nutrients. The interaction between light
and nutrients was not significant for any of the biomass parameters (p > 0.05). The interaction
between light and grazing was not significant for any of the biomass parameters (p > 0.05). The
three way interaction between light, nutrients, and grazing was not significant for any of the
biomass parameters (p > 0.05; Table 4.1).

Community composition
Shading did not affect algal community composition, but grazing and nutrient enrichment
did. Of the ten taxa that were present in greater than 5% relative abundance, none of the taxa
responded to changes in light (Figure 4.5). Green algae, especially Gloeocystis, comprised 5468% of the of the total cell density in all treatments. Diatoms, especially Nitzschia, were more
abundant in nutrient enriched enclosures compared to the control. Grazing decreased Nitzschia
(F7,22 = 2.204, p = 0.074) compared to un-grazed treatments in both nutrient enriched and
control enclosures regardless of light manipulation. Nutrient enriched enclosures had a greater
abundance of the filamentous green algae Ulothrix compared to control enclosures. Grazing
significantly decreased Ulothrix (p = 0.05) compared to un-grazed treatments in both nutrient
enriched and control enclosures regardless of light manipulation. The basal cells of
Stigeoclonium were more abundant on grazed than un-grazed substrates in nutrient enriched
enclosures. Un-shaded nutrient enriched enclosures had a significantly lower abundance of
Gloeocapsa (cyanobacteria) (F7,22 = 5.575, p = 0.001) and Stigeoclonium (chlorophyta) (F7,22 =
78

4.118, p = 0.005) independent of grazing, compared to any of the other nutrient or light
treatments. Taxa from Euglenophyceae (Trachelomonas), Chrysophyceae (Ophiocytium), and
Cyanophyceae (Aphanocapsa and Chroococcus) were unaffected by either light, nutrient or
grazer manipulations.

4.4 Discussion

Grazing and nutrients were more important regulatory factors determining algal biomass
and community composition than light. The addition of nutrients increased benthic algal
biomass and grazers suppressed algal accumulation, supporting my first two hypotheses. These
interacting and opposing influences of nutrients and grazing are consistent with the literature
from lakes and streams (Rosemond et al. 1993, Hillebrand 2002), reflecting a similar importance
of their regulatory effects on benthic algal biomass and taxonomic composition in boreal
wetlands. The significant interaction between nutrients and grazers suggests that the algal
community is under dual control from the bottom-up (nutrient limitation) and from the top-down
(consumption by herbivores), where the positive effect of nutrients is decreased in the presence
of grazers. However, my results indicate that the relative strengths of top-down versus bottomup control were not equivalent. Since my experimental design allowed me to examine both the
independent and interactive effects of nutrients and grazing, I was able to determine that grazers
had a consistently greater effect on both algal biomass and taxonomic composition, indicating
that grazing was the stronger regulatory factor during this study. The significant interaction
between nutrients and grazers is consistent with results from a concurrent study (Rober et al.
2011). However, the shift in the primary regulatory factor from nutrients in the 2007 study to

79

grazers in this 2008 study suggests that the degree to which either factor regulates algal biomass
and community composition may be influenced by interannual variability.
In the Florida Everglades increased nutrient inputs caused an increase in macrophyte
abundance, which in turn reduced periphyton abundance due to light limitation (Grimshaw et al.
1997, McCormick et al. 1998). While the results of my survey of macrophyte growth in the
Tanana River floodplain showed a similar trend of decreasing algal biomass with increasing
macrophyte density (see Figure 4.1), experimentally manipulating light availability did not
produce this same effect. While these results largely do not support the hypothesis that shading
by macrophytes reduces the ability of algae to respond to nutrient enrichment, there was some
evidence to support this. Water column nutrient concentrations remained slightly higher in
shaded treatments compared to un-shaded treatments, suggesting that the algal community was
not able to utilize nutrients in the shaded treatment as well as in the un-shaded treatment.
Furthermore, algal biomass measured as AFDM was slightly lower in all shaded treatments
compared to un-shaded treatments, which complements the greater uptake of nutrients in the unshaded treatment.
The lack of a response by the algal community to light manipulation suggests that light
was not as limiting as expected. High latitude ecosystems receive light nearly 20 h per day
during the growing season, therefore algal communities in northern latitude ecosystems may
receive sufficient light despite large seasonal changes in macrophyte cover. Active net
2

photosynthesis is common at less than 10 µmol/m /s (Carlton and Wetzel 1987; 1988, Wetzel
2

2006). My study site received on average 638.7 µmol quanta/m /s during peak daylight hours
2

just below the water surface and an average of 384.8 µmol quanta/m /s penetrated to the

80

sediments in un-shaded areas. This is a sufficient amount of light to saturate photosynthesis (Hill
1996). Furthermore, previous research suggests that algal growth may be less sensitive to
reductions in light than photosynthesis (Rier et al. 2006). Therefore a 75% reduction in PAR
2

which resulted in an average of 63 µmol quanta/m /s in shaded treatments had little effect on
algal biomass. These results are consistent with those reported by Thomas et al. (2006) which
found no effect of experimentally reducing light availability on periphyton primary production or
community composition in the Everglades, and attributed this to the ability of algal communities
to maintain efficient photosynthetic rates within their acclimated irradiance regime.
Algal taxonomic composition was largely the same in nutrient and light treatments.
These results suggest that the algal community was controlled more by the presence or absence
of grazers than by changes in resources. The observed changes in algal taxonomic composition
suggest that there are trade-offs between herbivore resistant and resource competitive species.
This is consistent with literature from lakes (Marks and Lowe 1989), streams (McCormick and
Stevenson 1991, Steinman 1996, Rosemond et al. 1993, 2000), and coastal environments
(Lubchenco 1978) where grazer resistant species are overgrown by faster growing species when
herbivores are removed. Thus, algal taxa with high growth potential, such as the dominant
diatom taxa (Nitzschia) observed in un-grazed treatments in this study, could respond to
increases in resources, but only when grazers were excluded. Basal filaments of Stigeoclonium
were more abundant in grazed treatments, likely because their low profile growth form is
considered resistant to grazing and they are commonly abundant under grazed conditions (Marks
and Lowe 1989, McCormick and Stevenson 1991, Steinman 1996). Although small in size,
Gloeocystis comprised approximately 50% or more of the total algal biovolume in all treatments.
The abundance of this green alga may be due to its ability to exploit available nutrients and

81

outcompete other taxa for light and space (Graham et al. 1996). Furthermore, their small size and
gelatinous sheath may protect them to from consumption or passage through the gut (Cuker
1983, Peterson et al. 2002).
The relative availability of light compared with nutrients in aquatic environments has
been identified as a key factor regulating primary producers and their interactions with other
trophic levels (Sterner et al. 1997, Berman-Frank and Dubinsky 1999). In this study, I found
stronger effects of grazers and nutrients compared to light on benthic algae in a northern boreal
wetland. My findings suggest that an increase in N and P availability with increased soil
weathering and organic matter mineralization expected for the region with climate change
processes (Bridgham et al. 1995, Rouse et al. 1997) will probably increase benthic algal biomass
in northern boreal wetlands. The ability of grazers to suppress algal accumulation following
enrichment suggests that, much like lake and stream ecosystems (Hansson 1992, Feminella and
Hawkins 1995, Steinman 1996, Hillebrand 2002), benthic grazers can constrain benthic algal
biomass to low accumulation in northern boreal wetlands even in conditions of elevated resource
availability. Therefore grazing may play an increasingly important role in regulating benthic
algal communities in northern boreal wetlands as nutrient inputs increase with climate change.
Furthermore, the results from this study suggest that although the summer growing season is
lengthening due to climate change processes (Magnuson et al. 2000, Chapin et al. 2006), the
subsequent decrease in light attenuation due to an increase in the duration of macrophyte
production may have little influence on algal biomass or taxonomic composition.

82

Table 4.1 Analysis of variance table showing the responses of benthic algal biomass measured
as ash-free dry mass (AFDM), algal cell density, and total algal biovolume to manipulations of
light, nutrients, and grazing.
Effect
df
SS
F
P
AFDM
Light
Nutrient
Grazer
Light x Nutrient
Light x Grazer
Nutrient x Grazer
Light x Nutrient x Grazer
Cell Density
Light
Nutrient
Grazer
Light x Nutrient
Light x Grazer
Nutrient x Grazer
Light x Nutrient x Grazer
Biovolume
Light
Nutrient
Grazer
Light x Nutrient
Light x Grazer
Nutrient x Grazer
Light x Nutrient x Grazer

1
1
1
1
1
1
1

0.017
0.003
0.180
0.002
0.003
0.021
0.002

9.212
1.824
40.51
0.901
0.009
4.770
0.385

0.011
0.204
<0.0001
0.363
0.927
0.052
0.548

1
1
1
1
1
1
1

0.001
0.023
1.129
0.026
0.029
0.316
0.024

0.078
1.309
39.40
1.492
1.006
11.042
0.847

0.785
0.277
<0.0001
0.247
0.337
0.007
0.337

1
1
1
1
1
1
1

0.116
0.013
0.777
0.098
0.044
0.170
0.073

1.341
0.147
18.58
1.135
1.044
4.073
1.744

0.271
0.709
0.001
0.309
0.329
0.069
0.213

83

4.50

Algal biomass
Macrophyte biomass

400

2

Algal biomass (g /m )

300

3.00

250
2.50
200
2.00
150
1.50

100

1.00

50

0.50

2

350

3.50

Macrophyte biomass (g /m )

4.00

450

0

0.00
6/3/2009

920.3 µmol
920.3 µmol
-2 -1
quanta m-2 s-1)
quanta (m s

6/18/2009

7/3/2009
Time

7/18/2009

-50
8/2/2009

206.6 µmol
206.6 µmol
-2 -1
quanta m-2 ss-1)
quanta (m

Figure 4.1 Algal biomass measured as ash-free dry mass versus above ground macrophyte
biomass over a five week period during the summer growing season. Underwater PAR during
the first week of sampling when macrophyte biomass was lowest and algal biomass was highest
2
was 920.3 µmol quanta/m /s. Underwater PAR during the last week of sampling when
2

macrophyte biomass was highest and algal biomass was lowest was 206.6 µmol quanta/m /s
which was approximately 67% of available light.

84

Figure 4.2 Graphic of enclosure design. Enclosures were constructed of welded wire mesh
(40 cm in diameter and 85 cm tall), and held approximately 60 L of water. The top 75 cm of
each cylinder was wrapped with 0.1 mm clear window vinyl and embedded 10 cm into
sediments with an open top extending 15cm above the water column. I suspended all
substrates attached to wire baskets and maintained a consistent depth of 5 cm below the water
surface. I nested caged and un-caged substrates inside enclosures and added natural
abundances of snails. Un-shaded treatments received full sunlight and 75% of light was
blocked in shaded treatments.

85

4000

Un-shaded control
Shaded control
Un-shaded N+P
Shaded N+P

NO3 (µg L- 1 )

3000

2000

1000

0
0

4

8

12

16

700
600

PO4 (µg L- 1 )

500
400
300
200
100
0
0
4
8
12
16
Days since substrate deployment
Figure 4.3 Dissolved nutrient concentrations of NO3 and PO4 in shaded and un-shaded nutrient
enriched and control enclosures.

86

Figure 4.4 Benthic algal biomass measured as ash-free dry mass (AFDM) and cell density in
control and nutrient enriched enclosures with and without grazers in shaded and un-shaded
treatments. Bars represent the mean of four replicates ± SE.

87

Figure 4.5 Grazed and un-grazed algal taxonomic composition and total algal
biovolume in shaded and un-shaded nutrient enriched and control enclosures based on
taxa comprising > 5% relative abundance.

88

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94

CHAPTER 5

ALGAL COMMUNITY RESPONSE TO EXPERIMENTAL AND INTERANNUAL
VARIATION IN HYDROLOGY IN AN ALASKAN BOREAL FEN

5.1 Introduction

Algae can be abundant in wetlands and contribute significantly to many of the physical,
chemical, and biological processes that characterize wetland ecosystems (Goldsborough and
Robinson 1996, Wetzel 2006). Many of the processes carried out by algae in wetlands (e.g.,
nitrogen-fixation, soil formation) are related to taxonomic composition (Goldsborough and
Robinson 1996, Inglett et al. 2004). Despite literature describing the importance of algae for
wetland ecosystem processes (Vymazal 1995, Robinson et al. 2000, Richardson 2010), and
known differences in algal functions related to taxonomic composition (Graham et al. 2009),
relatively little is known about the factors that regulate algal communities in wetlands. This
issue is particularly significant in boreal regions, where wetlands are abundant and processes
related to ongoing climate change are expected to have widespread effects on aquatic ecosystems
(Rouse et al. 1997, Schindler 1998).
Hydrology is perhaps the single most important factor regulating the establishment and
maintenance of wetland ecosystems (Mitsch and Gosselink 2006). Frequent water level
fluctuations influence many of the physical and chemical factors characteristic of wetland
habitats (e.g., nutrients, light, temperature, substrate availability), and therefore algal
communities (Goldsborough and Robinson 1996). Research examining how algae respond to
changes in hydrology has come mainly from the work conducted in the Florida Everglades (i.e.,

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McCormick et al. 1998, Gottlieb et al. 2005, 2006, Iwaniec et al. 2006), where wetland
hydrology has been significantly altered by human development (Sklar et al. 2005). The effects
of hydrology on wetland algal communities at northern latitudes have been less studied.
Changes in wetland hydrology in boreal regions are particularly significant, in part because
temperatures that have constrained water at or near the surface of permanently frozen soils in the
region are increasing rapidly. Furthermore, climate models predict that temperatures in the
region will continue to increase during this century (Serreze et al. 2000, Hinzman et al. 2005,
McGuire et al. 2007).
Peatlands may be particularly sensitive to global change because water level is highly
dependent on changes in rates of precipitation and evapotranspiration (Hinzman et al. 2006,
Sulman et al. 2010). Peatlands cover extensive portions of interior Alaska where the surface
areas of open water bodies in wetland-rich landscapes are already declining, likely due to
increased evapotranspiration with longer, drier growing seasons (Serreze et al. 2000, Euskirchen
et al. 2006), drainage after permafrost thaw (Hinzman et al. 2005, Riordan et al. 2006), and/or
encroachment of wetland vegetation (Roach et al. 2011). However, some wetland areas in
Alaska are expanding due to hydrologic upwelling and increased flooding from melt-water
runoff from surrounding uplands (Osterkamp et al. 2000).
Increased frequency of drought and flooding events associated with climate change will
likely alter the physical and chemical conditions of aquatic ecosystems in the boreal region,
including the movement of limiting nutrients into and out of wetlands (Rouse et al. 1997).
Seasonal drought and exposure of sediments will likely oxygenate anaerobic soils and stimulate
microbial decomposition facilitating nutrient remineralization, while flooding of previously dried
soils may release available nutrients into the overlying water column (Boon 2006, Thomas et al.

96

2006). Algae in shallow wetlands are sensitive to changes in hydrology as well as water
chemistry, and thus, even small changes in water depth can result in desiccation (Thomas et al.
2006) or expose algal communities to environmental conditions that may induce significant
changes in community structure.
In this study, I monitored changes in algal community composition in response to an
ecosystem-scale water table manipulation that included both drought (lowered water table
treatment) and flooding (raised water table treatment) conditions in a rich fen in interior Alaska.
Although surface water conditions would only typically allow for continuous algal colonization
in the raised water table treatment, a significant flooding event provided a unique opportunity to
examine algal community response at sites previously exposed to long-term drought as well. I
investigated how much ecosystem memory of the antecedent water table manipulations regulated
the ability of taxa to recolonize sites following prolonged drought compared to sites that had
been continuously flooded. In a concurrent study, we reported on surface water chemistry and
algal community metabolism following rewetting (Wyatt et al. 2012). Here, I evaluate the
effects of rewetting on algal community structure.

5.2 Methods

Study site and experimental design
The APEX (Alaska Peatland Experiment) site is located within the Tanana River
floodplain just outside the Bonanza Creek Experimental Forest, approximately 35 km southeast
of Fairbanks, Alaska (64°82′N, 147°87′W). This region within interior Alaska has large
fluctuations in temperature, with a mean annual temperature of -2.9°C, and low levels of

97

precipitation (269 mm/y) (Hinzman et al. 2006). The growing season is relatively short (135
days or less) and experiences more than 21 h of light per day in June. The APEX site utilized in
this study is a rich fen which receives water from surface water runoff and precipitation, and to a
small extent, groundwater. The APEX site is dominated by brown moss, Sphagnum, and
emergent vascular flora, including Equisetum, Carex, and Potentilla.
Within the rich fen, three treatment plots were established in 2005 including a control,
lowered, and raised water table treatment (Conlin 2008, Turetsky et al. 2008). Treatment plots
2

are 120 m in area and are located approximately 25 m apart. Each treatment plot is surrounded
by a permanent, raised boardwalk. Prior to the initiation of the APEX water table manipulation
in 2005, early growing season water table position and plant species composition were not
significantly different between treatments (Turetsky et al. 2008). Water table is manipulated
through a series of drainage canals (40 cm wide, 1 m deep) that divert water away from the
lowered water table treatment. Surface water from a nearby well is pumped into the raised water
table treatment at a rate of approximately 10 cm/d using solar powered bilge pumps. The
chemistry of water additions to the raised water table treatment is similar to ambient pore water,
with no significant differences in pH, electrical conductivity, and concentrations of anionscations or organic acids (Turetsky et al. 2008). A datalogger communication system maintains
natural fluctuations in water table levels in the experimental treatments based on fluctuations in
the control treatment associated with precipitation and seasonal drying trends.
Throughout all four years of manipulation, the lowered water table treatment had a
consistently lower mean water table height relative to the surface of the peat than the control
treatment, and the raised water table treatment was consistently wetter (Figure 5.1; Kane et al.
2010). The mean (± SE) monthly water table position across all four years of manipulation

98

during the growing season for the control and lowered treatments was 7.2 ± 3.2 and 10.0 ± 3.8
cm beneath the surface of the peat, respectively, whereas the raised treatment had water 0.1 ± 2.2
cm above the peat surface on average. The water table position in the lowered treatment was
also generally more variable than in the control, whereas experimentally raising the water table
height in the raised treatment reduced fluctuations in water table height within the months of
June, July and August (Figure 5.1; Kane et al. 2010).
However, from May-July 2009, water table height in treatment plots was not well
regulated by experimental manipulation, but instead by a flood which occurred at the end of the
summer in 2008. Between the months of May and October 2008, over 275 mm of precipitation
fell in interior Alaska (National Atmospheric Deposition Program, station AK01). Therefore, all
three treatments were flooded in August-September 2008 and remained flooded during the spring
thaw in 2009 (Figure 5.1). Water table height above the peat surface decreased with time across
all water table treatments following the spring snowmelt, but it was not significantly different
between plots (p > 0.05; Figure 5.1). Following the spring flood, water column nutrient
concentrations peaked in early June in each water table treatment and then decreased sharply
(Figure 5.2A,B). Averaged across all sampling dates (mean ± SE), dissolved inorganic nitrogen
(DIN) and soluble reactive phosphorus (SRP) were consistently greater in the lowered water
table treatment (SRP = 2.86 ± 0.24 µg/L; DIN = 17.12 ± 2.05 µg/L) compared to raised (SRP =
1.07 ± 0.09 µg/L; DIN = 12.9 ± 0.84 µg/L) or control (SRP = 1.38 ± 0.16 µg/L; DIN = 12.4 ±
1.54 µg/L) water table treatments (p < 0.0001; Figure 5.2A,B; Wyatt et al. 2012).
Benthic algal biomass measured as chlorophyll a and ash-free dry mass (AFDM) peaked
following the maxima in nutrient concentrations (Wyatt et al. 2012). Averaged across all
sampling dates (mean ± SE), chlorophyll a concentration and AFDM were higher in the lowered

99

2

2

treatment (chl a = 23.3 ± 3.69 mg/m ; AFDM = 2.889 ± 0.30 g/m ) than in the control (chl a =
2

2

2

2.46 ± 0.44 mg/m ; AFDM = 0.84 ± 0.09 g/m ) or raised (chl a = 2.42 ± 0.43 mg/m ; AFDM =
2

0.78 ± 0.06 g/m ) water table treatments (p < 0.0001).

Sampling methods
In May 2009, I began monitoring algal parameters within each of the water table
treatments weekly, and then every two weeks beginning in July until August to evaluate algal
responses to altered water table position. I sampled algae at eight randomly selected locations in
each of the water table treatments for estimates of algal density, biovolume, and taxonomic
composition. Because the APEX site is part of a long-term study, I used non-destructive
2

methods of removing algae from submersed surfaces. Each sample consisted of four 25 cm
subsamples collected from peat surface and the submersed portions of four stems of the

2

dominant emergent macrophyte. I used a plastic syringe to remove algae from each 25 cm

quadrat until there were no loosely attached algae or biofilms present on the peat surface. In
cases where algae were attached to erect plant stems, I scraped the submersed portion of four
stems clean with a plastic spoon, and adjusted the surface area in calculations. Each composite
sample, which included algal material from stems and from the peat surface, was diluted to a
measured volume with filtered water and gently inverted several times before separating for
subsequent analyses. Each algal sample was preserved with 2% formalin for algal taxonomic
analysis. I used standard protocols to characterize algal taxonomic composition by counting and
identifying at least 300 natural units or colonies per sample using a Palmer-Maloney
nanoplankton counting chamber and identified algae to genus at 400X magnification (Charles et

100

al. 2002). For diatom compositional analysis, I acid cleaned an aliquot of each sample and
mounted cleaned diatoms to a microslide using NAPHRAX® mounting medium. I identified and
enumerated diatom valves at 1000X magnification. I quantified benthic algal abundance
2

(cells/cm of substrate) using the formula provided in Lowe and Laliberte (2006) and calculated
3

2

biovolume (µm /cm of substrate) by multiplying algal cell density by the estimated cell volume
using geometric formulae from Hillebrand et al. (1999).

Data analysis
I log (x + 1) transformed data if necessary for statistical analyses to correct for nonnormal
distribution and unequal variances among treatments prior to analysis. I used repeated measures
ANOVAs with an adjusted Bonferroni significance level and Tukey’s test for post hoc
comparison of means to test the null hypothesis that water table treatment had no effect on algal
cell density, biovolume, and taxonomic composition. I identified a total of 78 genera that were
included in statistical analyses for cell density within phyla but individual taxa were only
included in analyses when present at > 5% relative abundance. Biovolume was only calculated
for taxa present at > 5% relative abundance. Water temperature (21.1 ± 0.3 °C), DO (9.52 ± 0.2
mg/L), and pH (6.51 ± 0.03) varied among treatments during the experiment but were not
significant predictors of algal biomass or taxonomic composition within treatments (p > 0.05;
data not shown). A detailed description of the physical and chemical variables in the APEX site
during this study is reported in Wyatt et al. (2012). Statistical analyses were performed using
general linear models in SPSS 18 (SPSS inc., Chicago, Illinois).

5.3 Results

101

Algal taxonomic composition
4

2

Mean algal cell density (10 cells/cm ) peaked immediately following the maxima in
nutrient concentrations, and was nearly 3-fold higher in the lowered water table treatment (21.14
± 2.9) compared to control (6.76 ± 1.31) or raised (8.39 ± 1.02) water table treatments (F2,15 =
8.88, p = 0.003; Figure 5.3A). The absolute abundance of almost all taxa was greater in the
lowered water table treatment due to greater overall biomass, however the relative abundance of
taxa differed between treatments (F22,180 = 5.95, p < 0.0001; Figure 5.4A-C).
Chrysophytes were significantly more abundant in the control water table treatment
compared to lowered or raised water table treatments (F2,75 = 36.525, p < 0.0001; Figure 5.4A).
Dinobryon was the dominant chrysophyte in the control treatment (F2,180 = 68.18, p < 0.0001;
Figure 5.5A). Cyanobacteria comprised a greater proportion of total cell density in the raised
(22–62%) and control (22–53%) water table treatments compared to the lowered (10–48%) water
table treatment (F2,75 = 11.21, p < 0.0001; Figure 5.4). Nostoc was the dominant cyanobacteria
in all water table treatments and increased in abundance as nutrient concentration and water table
position declined (Figure 5.5A-C, 5.5D-F). Diatom relative abundance peaked in the middle of
the growing season in all treatments, but was consistently greater in the raised water table
treatment (9–28%) compared to lowered (7–10%) or control (1–19%) treatments (F2,75 = 13.75,
p < 0.0001; Figure 5.4). The increase in diatom relative abundance in all treatments was driven
by an increase in the abundance of Tabellaria, which was greater in the raised water table
treatment compared to lowered or control treatments (F2,180 = 25.13, p < 0.0001; Figure 5.5C).

102

The green algae (Chlorophyta) were more abundant in the lowered treatment compared to raised
or control water table treatments (F2,75 = 54.42, p < 0.0001; Figure 5.5B). The lowered water
table treatment was dominated by large filamentous green algae Oedogonium (F2,180 = 6.62, p =
0.002; Figure 5.5B), Spirogyra (F2,180 = 9.37, p < 0.0001; Figure 5.5B), and Microspora (F2,180
= 5.54, p = 0.005; Figure 5.5B). Small coccoid taxa comprised the greatest proportion of green
algae in raised and control water table treatments, many of which were present at < 5% relative
abundance (Figure 5.5A,C). The green algae Gloeocystis, Bambusina, Ulothrix, and Zygnema
did not differ significantly between treatments at anytime during the study (Figure 5.5A-C). Of
the 78 genera identified, 76% were present in all three water table treatments.

Algal biovolume
Total algal biovolume was significantly greater in the lowered water table treatment
compared to raised or control water table treatments (F2,15 = 25.89, p < 0.0001; Figure 5.3B).
Greater biovolume in the lowered water table treatment was driven by Oedogonium (F2,180 =
12.9, p < 0.0001; Figure 5.5E), Spirogyra (F2,180 = 9.9, p < 0.0001; Figure 5.5E), and
Microspora (F2,180 = 4.6, p = 0.011; Figure 5.5E). Although filamentous green algae did not
constitute a large proportion of the relative abundance of the algal community in raised or
control water table treatments (Figure 5.5A,C), they had larger cell sizes compared to many of
the diatoms, chrysophytes, and cyanobacteria that were present in greater relative abundance.
Therefore, despite the low abundance of Oedogonium, Spirogyra, and Bambusina in raised and
control water table treatments (Figure 5.5A,C), they comprised a significant portion of total algal

103

biovolume (p < 0.05; Figure 5.5D,F). These results are limited to the high biovolume taxa (i.e.,
filaments), because they comprised a portion of the cell density in all treatments (Figure 5.4D-F)
and have much greater cell sizes compared to many of the smaller taxa.

5.4 Discussion
Algal community structure was significantly different among water table treatments, even
when all treatments were flooded. Differences in community composition were manifested
mostly by changes in relative abundance rather than the presence/absence of individual taxa.
The presence of most taxa in all three treatments suggests that the long-term natural variation in
water table position that occurs within both the control and experimental plots with spring
flooding, precipitation events, and seasonal drawdown as well as similar regional environmental
conditions, regulates species membership of the algal community (sensu Pickett et al. 1989,
Stevenson 1997). However, altered nutrient dynamics associated with rewetting of previously
dried soils likely regulates the density and relative abundance of taxa that were available to
colonize substrates. Thus, antecedent conditions are likely acting on the algal community in two
ways, first by limiting the taxa that are available in the seed bank to colonize substrates and then
by increasing nutrient concentrations after rewetting, which shapes the relative abundance of
taxa present on the peat surface.
The abundance of green algae across all water table treatments is consistent with the
literature from a survey of North American peatlands (Yung et al. 1986). Many species of green
algae have an affinity for low pH conditions (Graham et al. 1996, Greenwood and Lowe 2006,
Wyatt and Stevenson 2010), making them well adapted to acidic conditions in peatland
ecosystems. The presence of filamentous green algae in Alaskan wetlands has also been

104

attributed to their ability to tolerate the extreme fluctuations in temperature that occur at this
latitude (Prescott 1963). The increase in filamentous taxa in the lowered water table treatment
was likely the response to increased nutrient availability following the spring thaw, since some
green algae are capable of exploiting available nutrients and outcompeting other taxa for light
and space (Graham et al. 1996). These results are consistent with those reported in previous
studies conducted within the Tanana River floodplain, where filamentous green algae increased
in biomass following nutrient enrichment (Wyatt et al. 2010, Rober et al. 2011) and from Delta
Marsh, Manitoba where filamentous green algae contributed approximately 87% of the total
algal biomass after a wetland was re-flooded following an experimental drawdown (Robinson et
al. 1997).
The increase in the abundance of Nostoc in all water table treatments as nutrient
concentrations declined, suggests that it is able to survive in low nutrient environments. Nostoc
is commonly found living endosymbiotically within moss tissues (Granhall and Selander 1973,
DeLuca et al. 2002) and as epiphyton attached to moist moss surfaces in peatlands (Basilier
1980). Nostoc is capable of fixing atmospheric nitrogen (N) for moss and vascular plant growth
and for microbial decomposition (DeLuca et al. 2002). N-fixation by cyanobacteria has been
described as the most important source of N to many arctic and boreal regions, contributing as
much as 80% of total annual ecosystem N (Solheim et al. 2006). While a considerable amount
of research has been conducted within arctic and boreal regions to determine the importance of
N-fixation in boreal forests (Uliassi and Ruess 2002, DeLuca et al. 2002, Hobara et al. 2006), to
my knowledge none have quantified the N-fixation potential of peatland cyanobacteria under
different water table regimes. My results suggest that changes in water table position will
influence the abundance of N-fixing cyanobacteria and therefore likely the amount of N being

105

fixed under differing hydrologic conditions. This may be particularly significant under
hydrologic conditions similar to those in the raised water table treatment, where continuously
saturated soils reduce nutrient availability in the water column.
Diatoms are sensitive to desiccation stress, and the lower abundance of diatoms in the
lowered water table treatment compared to the control and raised treatments is consistent with
literature from the Everglades, where diatom abundance decreased in areas experiencing more
frequent drought (Browder et al. 1981, Gottlieb et al. 2006). This may also explain the greater
abundance of diatoms in the raised water table treatment, which had been flooded during the
previous four growing seasons and consistently had less variability in water table position
compared to the other treatments (Kane et al. 2010). Overall, diatoms did not contribute greatly
to total cell abundance or biovolume in this study. This group of algae, which use silica (Si) to
build their cell walls, may have been limited by Si concentrations which were below detection
through much of the summer growing season (Wyatt et al. 2012). This is consistent with other
studies which have shown that Si is an important limiting nutrient for algae in peatland
ecosystems (Struyf and Conley 2009).
Chrysophytes are widely distributed and are commonly found in oligotrophic habitats,
especially at northern latitudes (Wehr and Sheath 2003). The degree to which I observed
chrysophytes in this study, particularly Dinobryon, is consistent with a previous study in Alaska
(Hilliard 1968). This alga is mixotrophic, allowing it to switch between autotrophic and
heterotrophic metabolism (Wehr and Sheath 2003). Therefore, it may be able to maintain
metabolic activity in low light conditions or under ice (Wiedner and Nixdorf 1998), which may
explain its abundance early in the growing season following the spring thaw. However, the
lower abundance of Dinobryon in the raised and lowered water table treatments relative to the

106

control suggests that chrysophytes may be particularly sensitive to changes in hydrology and
could decline in boreal peatlands as fluctuations in water table position become more frequent
with climate change.
Since algal function within an ecosystem can be related to the overall abundance of a
particular taxonomic group, I used estimates of algal abundance as an indication of their
functional importance. In this study, filamentous green algae (Oedogonium, Spirogyra,
Microspora) comprised a substantial proportion of the algal cell density in the lowered water
table treatment and were dominant as measured by biovolume. Therefore, it is likely that
filamentous green algae will play an increasingly important role in wetland ecosystem function
with increasing frequency of drying and rewetting events. This may particularly true in shallow
wetlands which we would expect to experience more frequent fluctuations in water table. This
shift in community composition will likely have ecosystem level consequences given the
significant amount of labile dissolved organic carbon that was released from filamentous green
algae in the lowered water table treatment and its’ utilization by bacterial communities (Wyatt et
al. 2012).
Cell volume and abundance data were not consistent in raised and control water table
treatments where cyanobacteria comprised a significant proportion of the algal community.
These taxa (Nostoc, Chroococcus, and Gloeocapsa) are small coccoid cells, which have much
smaller cell volumes compared to the filamentous green taxa present. Therefore, the dominance
of filamentous green algae in measures of biovolume in raised and control water table treatments
is disproportionate relative to their absolute abundance. This could mislead conclusions
regarding the function of the algal community within these sites, where cyanobacteria, like
Nostoc, may be important for ecosystem function.

107

Compared to the extensive literature on benthic algae in lakes and streams, there is little
published information examining the benthic algal assemblages of freshwater wetlands or the
factors that regulate their structure and function (Robinson et al. 2000). This discrepancy is
particularly acute for northern boreal regions where wetlands are abundant and extremely
vulnerable to disturbances associated with climate change. My results provide evidence that
hydrology is an important factor regulating benthic algal community structure in a northern
boreal peatland and adds to a growing literature on the role of algae in wetland ecosystems. The
observed differences in algal taxonomic composition in response to fluctuations in water table
suggests that increased frequency of drought and flooding events expected with climate change
may significantly alter algal community structure and function in boreal wetlands from the
expected natural peatland algal community (i.e., control treatment). My results suggest that this
may be particularly important when hydrologic conditions influence nutrient mineralization and
availability in surface soils. Furthermore, the similarity between taxa found in this study and
those of other floristic studies in peatlands (i.e., Yung et al. 1986, Mataloni 1999, Greenwood
and Lowe 2006), indicate that the effect of altered hydrology on algal community structure could
be widely applicable to peatland ecosystems beyond those in Alaska.

108

20

Control
Lowered
Raised

0
-20

-100
2005

2006

2007

1

Month

2008

Sep

4
Aug

-80

7

Jul

-60

10

Jun

-40

May

Mean standard
deviation (2005-2009)

Water table height above surface moss (cm)..

40

2009

Year of study (depicted is May - Oct.)
Figure 5.1 Long term seasonal trends in water table heights across the control, lowered, and
raised water table treatments in interior Alaska (from Kane et al. 2010). Negative values
indicate water table position below the surface of the peat. Outlined values indicate water table
measurements made during this study. Inserted figure shows standard deviation in mean
monthly water table position across the five years of study (total of 1938 individual water table
measurements).

109

7
6

A

Control
Lowered
Raised

SRP (µg / L)

5
4
3
2
1
0
-1

60

B

DIN (µg / L)

50
40
30
20
10
0
5/25 6/2 6/10 6/19 7/2 7/16 7/27
Sampling date
Figure 5.2 Mean (±1 SE; n = 8) (A) Soluble reactive phosphorus (SRP) and (B) dissolved
inorganic nitrogen (DIN) concentrations in control, lowered, and raised water table treatments on
each sampling date in the APEX fen during the summer growing season in 2009 (from Wyatt et
al. 2012).

110

50

Control
Lowered
Raised

A

104 Algal cells / cm2

40
30
20
10
0
2000
Total biovolume (106 µm3 / cm2 )

B

1500

1000

500

0
5/25 6/2 6/10 6/19 7/2 7/16
Sampling date

Figure 5.3 Mean (±1 SE; n = 8) algal cell density (A) and total biovolume (B) in the control,
lowered, and raised water table treatments on each sampling date in the APEX fen during the
summer growing season in 2009.

111

Percent of biovolume

Percent of cells

Sampling date

Sampling date

Figure 5.4 Percent of total cells (A-C) and total biovolume (D-F) in functional groups in the
control (A, D), lowered (B, E), and raised (C, F) water table treatments on each sampling date
in the APEX fen during the summer growing season in 2009.

112

Percent of biovolume

Percent of cells

Sampling date

Sampling date

Figure 5.5 Algal taxonomic composition as relative abundance (A-C) and percent of total
biovolume (D-F) of dominant algal genera in the control (A, D), lowered (B, E), and raised
(C, F) water table treatments on each sampling date in the APEX fen during the summer
growing season in 2009.

113

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CHAPTER 6

CONCLUSION

6.0 Summary
This dissertation research adds to a growing literature on the prevalence of algae in
wetland ecosystems. The results of this dissertation improve our understanding of the abiotic
and biotic factors that regulate benthic algal productivity and taxonomic composition in northern
boreal wetlands and how this may be altered by processes related to ongoing climate change. My
results indicate that algae are an ecologically important component of wetland ecosystems,
aiding in wetland biogeochemical cycling and providing a labile food source for consumers.
These results have important implications for energy flow in boreal wetlands and indicate that
the current wetland structure and function may be altered by climate change.

6.1 Environmental controls on benthic algal structure and function
The work of Wyatt et al. (2010), Wyatt and Stevenson (2010), Rober et al. (2011), Wyatt
et al. (2012), and Rober et al. (accepted) have contributed significantly to our understanding of
the environmental controls on benthic algal structure and function in high latitude wetlands.
Though little work had previously examined algal dynamics in northern boreal wetlands in
interior Alaska, these studies have experimentally examined the role of nutrients, pH, grazers,
light, and hydrology in regulating algal structure and function. Furthermore, my detailed
documentation of spatial and temporal variation in algal abundance, productivity, and
community composition is useful for understanding the natural distribution and abundance of

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algae in boreal wetlands, which is necessary to predict how processes related to climate change
will influence wetland primary production, biogeochemistry, and food-web structure.
Multiple lines of evidence indicate that nutrients are the most important environmental
factor influencing algal abundance and taxonomic composition in these wetland ecosystems.
Survey results showed that both N and P were strong predictors of algal taxonomic composition,
influencing the community in the same direction and magnitude, indicating that both nutrients
are co-limiting in these ecosystems. Results from in situ experimental nutrient enrichment
showed the addition of a combination of N and P produced the greatest increase in algal
productivity and altered taxonomic composition compared to the addition of either nutrient alone
(Wyatt et al. 2010). Following long-term water table manipulation, rewetting of previously dried
peatland soils released a pulse of nutrients into the water column which facilitated a spike in
algal productivity (Wyatt et al. 2012) and altered taxonomic composition (Rober et al. accepted).
Furthermore, nutrients excreted by snails were used by algae to regenerate biomass after
consumptive losses (Rober et al. 2011). The mechanism by which nutrients enter these wetlands
will likely differ, however the results from this work suggest that increased nutrient inputs will
increase algal biomass and productivity and shift taxonomic composition.
In the absence of nutrient limitation, grazing strongly influenced the quantity of algal
biomass as well as the taxonomic composition and growth form of the algal assemblage (Rober
et al. 2011). This finding indicates that, much like in lake and stream ecosystems (Hansson
1992, Feminella and Hawkins 1995, Steinman 1996, Hillebrand 2002), benthic grazers can
maintain low algal biomass accumulation in northern boreal wetlands even in conditions of
increased resource availability.

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Hydrology was perhaps as important in regulating algal structure and function as
nutrients. There is considerable seasonal variation in water depth within the wetlands of the
Tanana River floodplain. During the course of this study water depth was consistently greater
early in the growing season following snow melt, but prior to seasonal ice thaw in the soil, than
late in the growing season. Algal abundance was also greatest during the early growing season
with higher diversity of taxa compared to late season. In my survey of six wetlands within the
floodplain I determined that hydrology was a significant factor influencing algal taxonomic
composition. Furthermore, algal communities were directly affected by decreased water table
position in the APEX water table manipulation, where only taxa that could tolerate periods of
drought (e.g., Nostoc) were present at the end of the growing season when the water table had
dropped below the peat surface (Rober et al. accepted).
Fluctuations in hydrology indirectly influence algal communities by influencing many of
the physical and chemical factors within wetland habitats (e.g., nutrients, light, temperature,
substrate availability) (Goldsborough and Robinson 1996). In several of our studies, hydrology
indirectly influenced both algal biomass and taxonomic composition by influencing the
movement and delivery of nutrients into the water column. Nutrient amendments added to
mesocosms simulated nutrient inputs from groundwater or surface-water runoff following spring
thaw and significantly increased algal biomass and influenced algal taxonomic composition
(Wyatt et al. 2010, Rober et al. 2011). Furthermore, nutrients released from rewetted soils
facilitated a significant increase in algal abundance and productivity (Wyatt et al. 2012), and
favored the growth of filamentous green algae (Rober et al. accepted). Therefore, while nutrients
have been shown to be the most important regulatory factor influencing algal communities, the
mechanism by which nutrients enter the wetland is often determined by hydrologic processes.

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Although I hypothesized that shading by macrophytes would limit light available for
algal growth, the lack of a response by the algal community to light limitation in either the
survey or light manipulation experiment, suggests that light was not as limiting as expected.
High latitude ecosystems receive nearly 20 h per day of saturating light for the duration of the
growing season, therefore algal communities in northern latitude ecosystems may receive
sufficient light despite large seasonal changes in macrophyte cover. This may be especially true
2

in wetlands where active net photosynthesis is common at less than 10 µmol/m /s (Carlton and
Wetzel 1987, 1988, Wetzel 2006). My results are consistent with those from the Everglades
where experimentally reducing light availability had no effect of on periphyton primary
production or community composition, and was attributed to the ability of algal communities to
maintain efficient photosynthetic rates within their acclimated irradiance regime (Thomas et al.
2006).

6.2 The contribution of algal productivity to total wetland primary production
Most estimates of wetland algal productivity have come from studies conducted in
subtropical (Browder et al. 1994, Richardson 2008) and temperate regions (Goldsborough and
Robinson 1996, Robinson et al. 2000). Given the importance of boreal wetlands as major stores
of carbon, considerable effort has been made to quantify primary productivity in these
ecosystems (cf. Thormann and Bayley 1997, Weltzin et al. 2000, Chivers et al. 2009). However,
the majority of these studies have focused on macrophyte production (Wieder 2006) and have
mostly ignored the potential role of algae in contributing to wetland primary production.
Mean productivity values among all wetland sites from my survey are within the range
2

(0-500 g C/m /y) of values reported from in the literature of temperate freshwater marshes (see

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review in Goldsborough and Robinson 1996). During peak productivity, my estimates of algal
productivity fall within the lower range of productivity values reported for the subtropical
2

Florida Everglades (300-600 g C/m /y; McCormick et al. 1998, Ewe et al. 2006). Assuming that
2

peak macrophyte productivity among wetland sites (70-170 g C/m ) is equivalent to annual net
2

2

productivity (g C/m /y), my measured values of 30-230 g C/m /y for benthic algae (based on
135 day ice-free period) are equivalent, and in some cases higher, than macrophyte production.
My measurements of algal productivity in peatlands are among the few to be reported.
My measures of algal productivity in a peatland are higher than many of the values reported for
marshes and show that algae can contribute up to 50% of wetland primary production in peatland
ecosystems. These results provide further support for the inclusion of algal primary production
in estimates of total wetland gross primary production.

6.3 Role of algal taxonomic composition in wetland ecosystem function
Since algal function within an ecosystem can be related to the overall abundance of a
particular taxonomic group, I used estimates of algal abundance as an indication of their
functional importance. I found multiple lines of evidence for the functional importance of
filamentous green algae in boreal wetland ecosystems. Filamentous green algae dominated the
algal community following nutrient inputs in marshes and peatlands (Wyatt et al. 2010, Rober et
al. 2011, Rober et al. accepted). The increase in filamentous green algae following enrichment
likely has ecosystem level consequences given the significant amount of labile dissolved organic
carbon that is released from filamentous green algae and its’ utilization by bacterial communities
(Wyatt et al. 2012). Increases in bacterial density in the presence of algal exudates could

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increase the ability of the bacterial community to decompose more recalcitrant carbon substrates
(i.e., Hamer and Marschner 2005), and thus influence wetland carbon cycling.
I found that grazers significantly reduced the filamentous green algae Mougeotia and
Ulothrix, providing evidence for the importance of green algae to the wetland food web.
Furthermore, the role of filamentous green algae in supporting fungal (Chapter 2) and bacterial
communities (Wyatt et al. 2012) provides further support for utilization of algae in the microbial
loop. Traditionally wetland food webs have been considered to be detritus based (Murkin 1989,
Batzer and Wissinger 1996, Mitsch and Gosselink 2006), however detritus is a poor quality food
source, and the extent to which detrital material is transferred from the microbial loop to higher
trophic levels is unknown (Batzer et al. 2006). The concept that shredders of vascular plant
matter dominate food web processes in streams may not apply to many non-wooded wetland
types where shredders are relatively rare and microbial processes are primarily responsible for
the breakdown of plant matter (Wissinger 1999, Hart and Lovvorn 2003). Additionally, stable
isotope analyses indicate that invertebrates consume algae rather than macrophyte tissue (Neill
and Cornwell 1992), and that assimilated detritus is also of algal origin rather than that of
macrophytes (Hart and Lovvorn 2003). Although algae typically have lower standing stocks of
biomass compared to wetland macrophytes, algal turnover rates are measured in days rather than
years, and the edibility and nutritive value of algae makes them considerably more important to
secondary production than living or non-living plant material (Campeau et al. 1994,
Goldsborough and Robinson 1996, Robinson et al. 2000).
In both the survey of peatlands and marshes and in my study of algal community
response to experimental water table manipulation I found significant quantities of N-fixing
cyanobacteria, particularly Nostoc. Nostoc is commonly found living endosymbiotically within

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moss tissues (Granhall and Selander 1973, DeLuca et al. 2002) and as epiphyton attached to
moist moss surfaces in peatlands (Basilier 1980). Nostoc is capable of fixing atmospheric N for
moss and vascular plant growth and for microbial decomposition (DeLuca et al. 2002). Nfixation by cyanobacteria has been described as the most important source of N to many arctic
and boreal regions (Solheim et al. 2006). While a considerable amount of research has been
conducted within arctic and boreal regions to determine the importance of N-fixation in boreal
forests (Uliassi and Ruess 2002, DeLuca et al. 2002, Hobara et al. 2006), to my knowledge none
have quantified the N-fixation potential of wetland cyanobacteria under different water table
regimes. My results suggest that changes in water table position will influence the abundance of
N-fixing cyanobacteria and therefore likely the amount of N being fixed under differing
hydrologic conditions. Furthermore, potential increases in moss and macrophyte production
facilitated by nutrients made available by N-fixing cyanobacteria could increase the carbon
storage potential within boreal wetlands.

6.4 Implications of climate change on benthic algal structure and function
Climate models project that North American boreal regions will experience more
warming than any other biome, with the greatest warming occurring in the continental interiors
(National Research Council 2001). Interior Alaska is already experiencing large changes in
climate including increases in surface annual temperatures (Hinzman et al. 2005, Houghton et al.
2001, McGuire et al. 2002; 2007, Serreze et al. 2000), increases in annual precipitation
(Hinzman et al. 2005), longer growing seasons (Euskirchen et al. 2006, Goetz et al. 2005,
Serreze et al. 2000), and altered snowpack dynamics (Dye 2002, Serreze et al. 2000). My results
suggest that although the summer growing season is lengthening due to climate change processes

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(Magnuson et al. 2000, Chapin et al. 2006), the subsequent decrease in light attenuation due to an
increase in the duration of macrophyte production may have little influence on algal biomass or
taxonomic composition.
In response to recent climatic change, the surface area of open water bodies within some
wetland-rich landscapes in Alaska is declining, likely due to increased summer moisture deficits
and permafrost degradation (Hinzman et al. 2005, Oechel et al. 2000, Riordan et al. 2006,
Yoshikawa and Hinzman 2003). However, expansion of open water is occurring in wetlands in
the Tanana Flats region of interior Alaska (Osterkamp et al. 2000), an area experiencing ongoing
permafrost thaw and hydrologic upwelling as increased melt-water from the Alaska Range drains
through the Tanana Flats. The differences in algal taxonomic composition I observed in
response to fluctuations in water table suggests that increased frequency of drought and flooding
events expected with climate change may significantly alter algal community structure and
function in boreal wetlands. My results suggest that this may be particularly important when
hydrologic conditions influence nutrient mineralization and availability in surface soils.
An increase in the extent of seasonal ice thaw is predicted to increase microbial
decomposition and will probably promote N and P mineralization in the expanded active soil
layer (Bridgham et al. 1995), as well as chemical weathering of parent rock material (Rouse et al.
1997). While regional variability of nutrient inputs may be significant, these changes are
expected to have widespread impacts on nutrient concentrations of aquatic systems throughout
the boreal forest (Rouse et al. 1997). My results suggest that this increase probably will increase
benthic algal biomass in northern boreal wetlands. Furthermore, my results demonstrating the
ability of grazers to suppress algal accumulation following enrichment, suggest that grazing may

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play an increasingly important role in the regulation of algal abundance and taxonomic
composition if nutrient inputs increase as expected with climate change.

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