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The effect of water velocity on carbon isotope fractionation of aquatic macrophytes
By
Lisa Harris
A Thesis
Presented to
The University of Guelph
In partial fulfillment of requirements
For the degree of
Master of Science
In
Integrative Biology
Guelph, Ontario, Canada
© Lisa Harris, January, 2016 !
ABSTRACT ! THE EFFECT OF WATER VELOCITY ON THE CARBON ISOTOPE
FRACTIONATION OF AQUATIC MACROPHYTES
Lisa Harris Advisor: Dr. J.D. Ackerman
University of Guelph, 2016
Smith and Walker (1980) proposed that the diffusive limitation of the boundary layer surrounding aquatic plants would limit carbon availability and result in less discrimination against 13C. I investigated this mechanism in a laboratory experiment with Vallisneria
- - americana, a HCO3 user, and Sagittaria subulata, not known to use HCO3 , and a field study with V. americana in the Maitland River, Goderich, ON. The δ13C signatures of V. americana in the laboratory and field became significantly more negative with increasing velocity whereas those of S. subulata became more positive. The results for V. americana support Smith and
Walker’s (1980) mechanism, however those for S. subulata were opposite, which is likely due to differences in carbon uptake mechanisms between the two species. When analyzing δ13C signatures of aquatic macrophytes, it is important to consider the fluid velocity, the photosynthetic mechanism and the type of carbon available.
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ACKNOWLEDGEMENTS
I have been incredibly fortunate during the course of my Masters to have encountered so many wonderful people. First, I would like to thank my advisor, Dr. Josef Ackerman, for giving me this opportunity to explore the world of aquatic plants and further my knowledge on conducting scientific research. I would also like to thank my committee members, Dr. Hafiz Maherali and
Dr. Jonathan Newman, for their guidance and critical analysis throughout my Masters.
My fellow Ackerman Lab members were incredibly supportive during my research and I greatly appreciate all of the advice that they gave me. Thank you to Rakesh Mistry, Shaylah
Tuttle-Raycraft, Dori Gao, Dr. Michael Nishizaki and Dr. Colette Mesher for inspiring me and for your continued friendship. I would also like to thank Dr. Colette Ward, who taught me how to sample isotopes and provided guidance throughout my Masters, as well as Dr. Kate Stuttaford, who provided guidance and laboratory supplies to assist with my water chemistry analysis.
Thanks to all of my amazing research and field assistants: Raytha De Assis Murillo, Arieanna
Balbar, James Akselsen, Michael Pfundt, Jodie Ball, Megan Davies, Benjamin Crema, Madeline
Lang and Mark Philpott; without you my research would not have been possible.
I would like to thank Matt Cornish and Mike Davies from the Hagen Aqualab for their support and guidance. I was also very fortunate to have worked with Steve Wilson and Ian
Moore from the Physics Workshop, and I greatly appreciate their advice and problem solving creativity. For their support and guidance during my growth chamber experiments, I would also like to thank Tannis Slimmon, Sue Couling and Michael Mucci from the Phytotron.
My friends and family have been incredibly supportive and inspiring during the course of my Masters and I certainly could not have completed my research without their help. Thank you
! ! iv! to my parents and my amazing siblings, for your love and encouragement. Finally, I would like to thank my partner, Mark for his continued support and for inspiring me every step of the way throughout my Masters.
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TABLE OF CONTENTS
ABSTRACT!...... !III! ACKNOWLEDGEMENTS!...... !III! TABLE OF CONTENTS!...... !V! LIST OF TABLES!...... !VII! LIST OF FIGURES!...... !X! LIST OF APPENDICIES!...... !XV! INTRODUCTION!...... !1! LITERATURE REVIEW!...... !2! BOUNDARY LAYER THEORY!...... !2! Concentration Boundary Layer!...... !4! CARBON ISOTOPE FRACTIONATION!...... !6! Definitions and Calculations!...... !6! Photosynthesis and Carbon Fractionation!...... !7! INORGANIC CARBON IN THE AQUATIC ENVIRONMENT!...... !9! The Aquatic Environment!...... !9! The Effect of Velocity on Photosynthesis and Growth!...... !11! Carbon Speciation in Freshwater!...... !12! Carbon Uptake Mechanisms!...... !14! Temporal and Spatial Variation in δ13C signatures!...... !16! A Mechanism to Explain Lower Discrimination Against 13C in Aquatic Producers!...... !18! STUDY ORGANISMS!...... !19! Vallisneria americana!...... !19! Biomass and Carbon Acquisition of V. americana!...... !20! Sagittaria subulata!...... !21! THESIS RATIONALE!...... !21! RESEARCH QUESTION!...... !24! RESEARCH OBJECTIVES!...... !25! HYPOTHESES AND PREDICTIONS!...... !25! MATERIALS AND METHODS!...... !26! LABORATORY EXPERIMENTS WITH V. AMERICANA AND S. SUBULATA!...... !26! Laboratory Plant Cultivation and Care!...... !26! FLOW CHAMBER SYSTEMS!...... !27! Momentum Boundary Layer Thickness Calculations!...... !31! GROWTH CHAMBER!...... !32! PLANT PLACEMENT!...... !33! WATER CHEMISTRY!...... !35! GROWTH ANALYSIS!...... !39! SAMPLE PREPARATION AND CARBON ISOTOPE ANALYSIS!...... !40! Laboratory!...... !40! STATISTICAL ANALYSIS!...... !42! FIELD STUDY!...... !43! SAMPLE PREPARATION!...... !53!
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STATISTICAL ANALYSIS!...... !54! RESULTS!...... !55! 13 EFFECT OF VELOCITY ON THE Δ C SIGNATURES OF MACROPHYTES IN LABORATORY EXPERIMENTS!.!55! EFFECT OF VELOCITY ON GROWTH!...... !58! FIELD RESULTS!...... !60! 13 EFFECT OF MOMENTUM BOUNDARY LAYER THICKNESS ON Δ C SIGNATURE!...... !64! DISCUSSION!...... !69! 13 EFFECT OF VELOCITY ON Δ C SIGNATURE IN LABORATORY EXPERIMENTS!...... !69! CONTROLLED EXPERIMENTS!...... !69! - HCO3 UPTAKE!...... !72! PROPOSED MECHANISM FOR EFFECT OF VELOCITY ON S. SUBULATA!...... !73! 13 EFFECT OF VELOCITY ON Δ C SIGNATURES OF V. AMERICANA IN THE MAITLAND RIVER!...... !76! 13 EFFECT OF MBL THICKNESS ON Δ C SIGNATURE IN BOTH FIELD AND LABORATORY CONDITIONS!.....!78! MACROPHYTE GROWTH!...... !81! IMPLICATIONS!...... !81! CONCLUSIONS!...... !83! REFERENCES!...... !84! APPENDIX 1: SEACHEM FLOURISH INGREDIENTS!...... !95! APPENDIX 2: INTEGRATED VELOCITY MEASUREMENT USING PLASTER OF PARIS HEMISPHERES!...... !96! RESULTS OF PLASTER OF PARIS HEMISPHERES!...... !98!
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LIST OF TABLES ! Table 1: The average pH measured at 9 am in the flow chambers for the two experiments
involving V. americana and S. subulata. Note the different length of the experiments for
the two plant species, resulting in different n values. …………………………………...36
Table 2: Nutrient concentration measured in the flow chambers over the course of both
laboratory plant experiments. Note the different length of the experiments for the two
plant species, resulting in different n values……………………………………………..37
Table 3: The concentration of bicarbonate present in the various water sources measured via
titrations (mean ± standard deviation, n = 3). The predicted values of the S. subulata
experiments were based on DI water with 0.15 g/L of sodium bicarbonate. Vallisneria
americana values were based on water sampled from the flow chambers at the end of the
experiment. It is evident that alkalinity increased over the course of the experiment with
V. americana. ……………………………………………………………………………38
13 Table 4: The average δ CDIC signature for the water used in the laboratory experiments and the
δ13C signature for the sodium bicarbonate. ……………………………………………...39
Table 5: Parameters measured in each quadrat. Legend: V = V. americana, P = Potagemon, R/S
= rocky and sandy and S/S = soft and silty; Dense = quadrat full of macrophytes and river
bottom not visible, Patch = one or more patches of macrophytes and river bottom visible
between patches. All values are averages ± standard deviation with number of
measurements (n) included in quadrat column. Plants were sampled from all red
quadrats…………………………………………………………………………………..48
Table 6: Nutrient concentration at the field site measured in 2014 and 2015 compared to values
measured in the Maitland River in 2002 (Belore et al. 2002). …………………………..51
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Table 7: The pH and temperature at the Maitland River field site in both field seasons. Theses
parameters were only sampled once in 2014 and five time in 2015..……………………51
Table 8: River conditions corresponding to field visits in 2015 (Environment Canada Water
Office 2015)……………………………………………………………………………...52
Table 9: Results of the Tukey’s HSD test where significant p-values are in
bold………………58
Table 10: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined…………………………………………………………………….57
Table 11: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined…………………………………………………………………….62
Table 12: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined. …………………………………………………………………...63
Table 13: Results of the Tukey’s HSD test for laboratory V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to
MBL thickness at each velocity. ………………………………………………………...66
Table 14: Results of the Tukey’s HSD test for field 2014 V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to
MBL thickness at each velocity………………………………………………………….67
Table 15: Results of the Tukey’s HSD test for field 2015 V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to
MBL thickness at each velocity………………………………………………………….67
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Table 16: Results of the Tukey’s HSD test for laboratory S. subulata where significant p-values
are in bold and marginal results are underlined. Note treatments correspond to MBL
thickness at each velocity………………………………………………………………..68
Table 1.A1: The guaranteed analysis of Seachem Flourish, which was used as the plant nutrients
throughout all laboratory experiments. The components were derived from: Potassium
Chloride, Calcium Chloride, Copper Sulfate, Magnesium Chloride, Ferrous Gluconate,
Cobalt Sulfate, Magnesium Sulfate, Manganese Sulfate, Boric Acid, Sodium Molybdate,
Zinc Sulfate, Protein Hydrolysates………………………………………………………95
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LIST OF FIGURES
Figure 1: Components of a boundary layer and how it develops along a flat plate (from Douglas
et al. 2005)………………………………………..…………………………………..…...4
Figure 2: The concentration and momentum boundary layers and their relative velocity and
concentration gradients that form when fluid in motion intersects with a flat plate and the
surface acts as a source of the scalar (from Nishihara and Ackerman (2008)……...... 6
Figure 3: A comparison of the ranges of δ13C signatures of terrestrial and aquatic plants. Aquatic
plants exhibit the widest range of δ13C signatures that are not necessarily representative
of the photosynthetic pathway, as seen with terrestrial plants. Data from (1) Benedict
(1978), (2) Smith and Walker (1980), (3) O’Leary (1981) (4) Osmond et al. 1981; Keeley
and Sandquist (1992), and (5) Hemminga and Mateo (1996)……………...... 9
Figure 4: The relationship between DIC and pH in freshwater, which depicts the relative
amounts of carbon species at different pH levels (from Wetzel and Likens 2000). Note
- that above a pH of ~8, the CO2 levels are negligible and plants would need to use HCO3
(Keeley 1998)………………………………………….……………………………...….14
Figure 5: A proposed single cell C4 photosynthetic pathway for aquatic macrophytes (from
Bowes 2011)…………………………………………………...…………………..…….15
Figure 6: The morphology of (A) V. americana and (B) S. subulata (Images from IFAS 1990
and Tropica 2015 respectively)……………………………………………………….….24
Figure 7: Side view of the flow chambers used in this experiment and the arrows indicate the
direction of flow……………………………………………………………………….....27
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Figure 8: Top view of the flow chambers, which were comprised of four channels each. The
arrow indicates the direction of flow…………………...... 28
Figure 9: Modeled boundary layer thicknesses (using Eqn (1) – (3)) at (A) different downstream
distances for the three velocity treatments used in the laboratory and (B) 2 cm
downstream from the leading edge at a velocity of 0.5, 2.3 and 5.5 cm/s compared to the
thickness of the MBL and DSL measured in situ at 0.5 and 6.6 cm/s by Nishihara and
Ackerman (2009)………………………..…………………………………………….…31
Figure 10: The placement of flow chambers in the growth chamber for the (A) V. americana
experiment and (B) the S. subulata experiment………………………………………….33
Figure 11: Photograph of (A) S. subulata and (B) V. americana in channels within the flow
chamber systems (arrows indicate the direction of flow)……………….……………….35
Figure 12: Diel change in pH measured in the flow chambers containing S. subulata. The lights
in the growth chamber were turned on at 9 am, which corresponds to the sudden climb in
pH about 15 minutes later from 8.54 to 8.61. The bar across the top of the plot indicates
whether it was night (black section) or day (yellow section) in the growth chamber...... 36
Figure 13: The field site in the Maitland River indicated by the red circle (from Ferreyra and
Beard 2007)………………………………………………………...………………….....44
Figure 14: Upstream view of the Maitland River at the field site on August 13, 2015…………45
Figure 15: Drawing of the field site with the location of quadrats indicated. See Table 5 for
information on each quadrat. The blue arrow indicates the direction of flow…………...46
Figure 16: Water level (green line) and discharge (orange line) during the summer of (A) 2014
and (B) 2015 at the Maitland River near Benmiller Line, Goderich (Water Office 2015).
The monitoring station was ~500 meters downstream from the macrophyte bed. The red
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circles indicate sampling dates.…………………………………………………………..50
Figure 17: Water velocity measured within quadrats at different water levels (see Table 7) in the
field site in 2015. ……………………………………………………………………...…51
Figure 18: Boxplot of the δ13C signature of V. americana plants grown under different
velocities. Different letters indicate significant differences between groups as determined
by Tukey’s HSD…...…………………………………………………………………….56
Figure 19: Boxplot of the δ13C signature of S. subulata plants grown at different velocities.
Different letters indicate significant differences between groups as determined by
Tukey’s HSD.……………………………….…………………………………………...57
Figure 20: The relationship between velocity and δ13C signature compared between V.
americana and S. subulata………………………………………………….……………58
Figure 21: The relationship between velocity and change in LA compared between V. americana
and S. subulata………………………………………...………………………………....60
Figure 22: Boxplot of the difference in δ13C signature of V. americana plants grown in the
Maitland River during the summer of 2014. Different letters indicate significant
differences between groups as determined by Tukey’s HSD….………………………...62
Figure 23: Boxplot of the difference in δ13C signature of V. americana plants grown in the
Maitland River during the summer of 2015……………………………...……………....63
Figure 24: The relationship between velocity and δ13C signature of V. americana plants sampled
from the Maitland River in the summer of 2014 and 2015. Note that the velocity
measurements for 2014 were based on a single measurement, whereas the velocity
measurements for 2015 were based on the average of five measurements throughout the
field season…………………………………………………...…………………………..64
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Figure 25: The effect of MBL thickness on the δ13C signatures for V. americana plants grown in
the laboratory and sampled in the field in 2014 and 2015…………………………….....66
Figure 26: The effect of MBL thickness on the δ13C signatures for S. subulata plants grown in
the laboratory. …………………………………………………………………………...68
Figure 27: The effect of (A) velocity and (B) Reynolds number (Re) on δ13C signature of both
macrophyte species in this thesis compared to the trends from Ellawala et al. (2012) and
Trudeau and Rasmussen (2003). Re was based on length scales of: (1) the diameter of
the stalk-like section of a C. fibrosa plant for Ellawala et al. (2012); (2) the width of a
glass microscope slide for Trudeau and Rasmussen (2003); and (3) the width of a blade
for V. americana or S. subulata from the laboratory experiments………………….……71
Figure 28: The results of Ellawala et al. (2012) compared to the results of this thesis for S.
subulata in terms of both (A) velocity and (B) Reynolds number. The length scale for
Reynolds number calculations was the diameter of the stalk-like segment of C. fibrosa
and the width of a blade of S. subulata. The red lines indicate the trend if the zero value
for Ellawala et al. (2012) was removed………………………………………………….76
Figure 29: The effect of MBL thickness on the δ13C signatures of V. americana and S. subulata
in the laboratory and field studies in this thesis and the effect of MBL thickness on the
δ13C signatures of C. fibrosa (Ellawala et al. 2012; note the zero value was not included)
and various species of periphyton (Trudeau and Rasmussen 2003).…………………….80
Figure 1.A2: The relationship between velocity and gypsum flux for plaster of Paris
hemispheres calibrated at 20 °C……………………………………………...…………..97
Figure 2.A2: Photograph of the plaster of paris hemispheres that were deployed into the
river………………………………………………………………………………………98
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Figure 3.A2: The proportion of the plaster of Paris hemispheres remaining after being deployed
in the Maitland River for 8 days in 2015. The average velocities were: C1 = 1.2 cm/s, C2
= 2.2 cm/s and C3 = 5.6 cm/s……………………………………………………………99
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LIST OF APPENDICIES
Appendix 1: Seachem Flourish Ingredients
Appendix 2: Integrated Velocity Measurement Using Plaster of Paris Hemispheres
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INTRODUCTION ! Stable isotopes can be used to trace the origin of a sample and the trophic position of an organism within an ecosystem (Fogel and Cifunentes 1993). This ability has advanced our understanding of aquatic food web structure and productivity patterns (Hollander and McKenzie
1991; Keough et al 1996; Madigan et al. 2012). Stable isotopes of carbon (13C) and sulfur (34S) are typically used to provide source information whereas nitrogen (15N) provides information on the trophic position (Michener and Kaufman 2007). Once fixed by a primary producer, the carbon isotope signature can be diagnostic and is the most commonly reported isotope signature
(Fogel and Cifunentes 1993). Unfortunately, physical factors such as water movement can affect the stable isotope composition of an organism as was demonstrated by Chouvelon et al. (2012) who found that carbon isotope signatures differed between inshore and offshore zones as well as between benthic and pelagic zones in the Bay of Biscay. Moreover, large ranges of carbon isotope signatures for primary producers in aquatic systems have been reported (Hecky and
Hesslein 1995), and one plausible explanation for this is the relationship between the delivery
(i.e., water velocity) and the uptake of carbon in primary producers.
Given that water velocity is one of the most influential abiotic factors affecting aquatic macrophyte populations (Bornette and Puijalon 2011), it is likely that mass transport of solutes like carbon may be responsible for differences in carbon isotope fractionation. This concept was introduced by Smith and Walker (1980) who proposed that the diffusional limitation in the boundary layer around aquatic primary producers would affect their discrimination against 13C.
My thesis will address this theoretical model through a set of laboratory experiments and measurements in the field using Vallisneria americana Michx. Vallisneria americana, which has
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- ribbon-shaped leaves and is a known bicarbonate (HCO3 ) user and which will be compared in the laboratory to Sagittaria subulata (L.) Buch., which has similar growth form but is not known
- to use HCO3 .
LITERATURE REVIEW
The following review will examine the isotope fractionation theory and boundary layer theory that will be used in this thesis. It will also explore photosynthesis in aquatic macrophytes and examine how inorganic carbon behaves in the freshwater environment.
Boundary Layer Theory ! Flowing fluids can be characterized by a Reynolds number (Re = Ul /v, where l is the length scale, U is the velocity, and v is the viscosity of the fluid), which is the ratio of inertial to viscous forces in a fluid (Nishihara and Ackerman 2008). Re provides an indication of the flow regime; creeping, laminar, or turbulent (Schlichting and Gersten 2000). Creeping flow occurs at microscopic scales and velocities characterized by conditions experienced by microbes. Laminar flow occurs at low velocities and small spatial scales and is characterized by streamlines (lamina) that slide past each other (Spellman 2008). As the velocity and/or spatial scale increases, the flow transitions to turbulence. Turbulent flow can be characterized by “chaotic” water motion comprised of eddies (Spellman 2008).
When fluid in motion comes in contact with an object (e.g., leaf), shear stress (t) due to the no-slip condition at the surface acts upon the fluid and a velocity gradient forms. As the fluid continues downstream, the gradient grows leading to a region of reduced velocity, referred to as
! 2! ! the boundary layer. The boundary layer is the region from the surface of the leaf to where the U is 99% of free-stream velocity (U0) (Gordon et al. 2004; Nishihara and Ackerman 2008). There are three possible hydrodynamic conditions that can exist in the momentum or velocity boundary layer (MBL): laminar, transitional, and turbulent (Nishihara and Ackerman 2008). These conditions are determined by the local Reynolds number:
Rex = Ux /v (1) where x is the distance downstream from the leading edge, with the transition occurring when
5 Rex = 3-5 × 10 (Nishihara and Ackerman 2008). The thickness (denoted as δBL) of the laminar boundary layer is given by:
1/2 δMBL = 5x /Rex (2)
(Nishihara and Ackerman 2008). Once the boundary layer becomes turbulent, its thickness is given by the 1/7 power law:
1/7 δMBL = 0.16x /Rex (3) and it can be separated vertically into three components: (1) the viscous sublayer which also contains the thin diffusional sublayer (DSL) adjacent to the boundary; (2) the logarithmic layer in which inertial forces dominate; and (3) the outer layer as the fluid approaches U0 (Figure 1)
(Nishihara and Ackerman 2008).
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FM5_C11.fm Page 369 Wednesday, September 21, 2005 9:48 AM
! 11.1 Qualitative description of the boundary layer 369
FIGURE 11.1 Development of the boundary layer along a flat plate, illustrating variations in layer thickness and wall shear stress
Figure 1: Components of a boundary layer and how it develops along a flat plate (from Douglas
et al. 2005).
Concentration Boundary Layer ! When a source or sink of dissolved or particulate matter occurs at a surface, a concentration
boundary layer (CBL) can form if the material is not replenished or removed, respectively. The
thickness of the CBL extends from the surface to 99 % of the bulk concentration (Nishihara and
Ackerman 2008). A CBL can form under both laminar and turbulent conditions and its thickness
(δ) as given by:
1/2 1/3 δCBL = 5x / Rex Sc Laminar (4) so that more and more of the fluid is retarded and the thickness of the fluid layer δ = 0.16x / Re 1/7 Sc1/3 Turbulent (5) affected increases, as shown inCBL Fig. 11.1. Returningx to the Reynolds number concept, ifwhere the Reynolds Sc is the Schmdit number number, locally which is based is the on ratio the of distance v (diffusion from of momentum)the leading to edge D of the plate, then it will be appreciated that, initially, the value is low, so that the fluid flow close(molecular to the diffusion wall may of thebe nutrientcategorized in question). as laminar. The CBL However, contains as a diffusivethe distance boundary from layer the
leading(DBL), edgewhich increases is defined so by doesthe region Reynolds in which number, turbulent until diffusivity a point ( KmustD) is lessbe reached than the where the flow regime becomes turbulent. molecularFor smooth, diffusivity polished (D) of the plates nutrient the in question. transition The mayDBL extends be delayed away from until the Re surface equals 500 000. However, for rough plates or for turbulent approach flows, transition may until KD = D (Nishihara and Ackerman, 2008). occur at much lower values. Again, the transition does not occur in practice at one well-defined point but, rather, a transition zone is established between the two flow ! 4! regimes, as shown in Fig. 11.1. The random particle motion characterizing turbulent flow results in a far more rapid growth of the boundary layer in the turbulent region, so that the velocity gradient at the wall increases, as does the corresponding shear force opposing motion. Figure 11.1 also depicts the distribution of shear stress along the plate in the flow direction. At the leading edge, the velocity gradient is large, resulting in a high shear stress. However, as the laminar region progresses, so the velocity gradient and shear stress decrease with thickening of the boundary layer. Following transition the velocity gradient again increases, and the shear stress rises. Theoretically, for an infinite plate, the boundary layer goes on thickening indefinitely. However, in practice, the growth is curtailed by other surfaces in the vicinity. This is particularly the case for boundary layers within ducts, as will be !
Heterogeneous and homogeneous reactions can occur in the CBL. Heterogeneous reactions occur only in the diffusive boundary layer and influence the flux into and out of the
CBL (Nishihara and Ackerman 2008). Photosynthetic processes are an example of heterogeneous reactions. Homogeneous reactions occur throughout the CBL and include
- chemical reactions, such as the conversion of HCO3 to carbon dioxide (CO2) (Nishihara and
Ackerman 2008). By definition, the surface concentration at the leading edge of the CBL is equal to the bulk concentration. If the CBL thickens downstream, then the surface concentration becomes less than the bulk concentration (in the case of the surface acting as a sink).
A boundary layer occurs because of the interaction of water and a surface, such as a flat plate oriented into the oncoming flow, which can be used to model a leaf surface (Figure 2). In this case, both the momentum (of the fluid) and the concentration (of the scalar) boundary layers must be considered when discussing diffusive process occurring across a boundary layer
(Nishihara and Ackerman 2008). This thesis deals directly with the thickness of the MBL, which as demonstrated by Nishihara and Ackerman (2009), increases in thickness with decreasing velocity. The results of Nishihara and Ackerman (2009) show that the CBL behaved in a similar manner to the MBL but at a smaller scale, as the MBL thickness was greater than the CBL by a factor of 10 on average.
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Mass Transport in Aquatic Environments 303
advection, and boundary layer reactions, which are influenced by the properties and flow characteristics of the water, the biological and physical characteristics of the organism, the concentration and diffusional characteristics of the scalar quantity, and the kinetics and mechanism of the boundary layer reactions (Chambré and Acrivos, 1956; Acrivos and Chambré, 1957; Chambré and Young, 1958; Libby and Liu, 1966; Dang, 1983; Nishihara and Ackerman, 2006, 2007a).
11.3.1 Momentum and concentration boundary layers
Water flowing over a surface forms a momentum boundary layer (MBL) that can have lam- inar, transitional, or turbulent characteristics, depending on spatial and velocity scales that can be determined through the local Reynolds number (Re xU/ν, where x is the down- stream distance). The MBL forms as a result of the tendency= of water to adhere to surfaces (i.e., the no-slip condition; U 0), which produce tangential forces (i.e., shear stresses; τ) that are greatest at the water-surface= interface (i.e., wall shear stress; Ackerman and Hoover, 2001). The laminar MBL in two-dimensions can be described by solving the continuity equation and the equation of motion and their exact and approximate solutions are well known (Schlichting and Gersten, 2000). More importantly, the solutions provide a measure of the MBL thickness (δMBL), and in the case where the organisms can be approximated as a flat plate (Fig. 11.2), the δMBL at a given distance downstream (x) from the leading edge is
5 x ! δMBL 1/2 (11.1) ≈ Rex
Approaching velocity (u) & Concentration (C) Velocity Concentration gradient gradient gradient
Momentum boundary layer
Concentration boundary layer z
Leaf x
No-slip Perfect sink condition condition (u ϭ 0) (C ϭ 0) Figure 11.2. The momentum boundary layer and concentration boundary layer over a model leaf. The velocity Figure 2: The gradientconcentration is a result of and the no-slip momentum condition at boundary the water-surface layers interface and and their the concentration relative velocity gradient occurs, and given that the leaf surface acts as a sink and consumes all of the scalar arriving to the surface (C 0). = concentration gradients that form when fluid in motion intersects with a flat plate and the surface The turbulent MBL has vertical structure with three regions extending from the surface: (i) the viscous sublayer (VSL) where forces are largely viscous in nature; (ii) the logarithmic acts as a source of the scalar (from Nishihara and Ackerman (2008)).
Carbon Isotope Fractionation
Definitions and Calculations ! The carbon-12 isotope (12C) is abundant (~98.9%) in the atmosphere relative to carbon-13 (13C)
(O’Leary et al. 1992) and isotope fractionation occurs when physical or chemical processes discriminate against certain isotopes (i.e., 13C), thereby changing the isotopic ratio and in the case of photosynthesis enriching the plant tissue with the preferred isotope (12C) (O’Leary et al.
1992). Molecules containing 13C are discriminated against because they are less reactive than molecules containing 12C (Smith and Walker 1980; Keeley 1991). The isotopic composition of an organism, including aquatic macrophytes, can be represented as R-values, which are equal to the abundance ratio of 13C/12 C. The R-values are commonly transformed to δ13C values (Fogel
! 6! ! and Cifunentes 1993; Jardine et al. 2003), which are expressed in parts per thousand (‰) and represent the change in 13C relative to 12C:
13 δ C (‰) = [Rsample ⁄ Rstandard – 1] × 1000 (6)
13 12 where Rsample is the abundance ratio of C/ C in a sample and Rstandard is the abundance ratio of
13C/12 C in a standard, which is commonly PDB (Chicago) Belemnite (Smith and Walker 1980;
Farquhar et al. 1982). The kinetic fractionation factor (∝) is commonly reported and is calculated by:
∝ = [dXh,p / Xh,s] / [dXl,p/Xl,s] (7)
13 where Xh is the heavier isotope (in this case C), Xl is the lighter isotope, s is the substrate and p is the product (Fogel and Cifunentes 1993). Negative fractionation factors mean that the heavier isotope is more depleted than the product (Fogel and Cifunentes 1993). In terms of 13C, the equilibrium reaction of CO2(g) and CO2(aq) has a kinetic fractionation factor of 0.9991 and the
- + equilibrium reaction of CO2(g) and H2O to HCO3 and H has a kinetic fractionation factor of
0.9921 (Mook et al. 1974; Fogel and Cifunentes 1993). These different equilibrium fractionation factors illustrate that the δ13C signature of an aquatic macrophyte is affected by the type of
- carbon (CO2 or HCO3 ) it uses.
Photosynthesis and Carbon Fractionation ! The different photosynthetic pathways and their respective enzymes fractionate carbon and therefore the δ13C signature of what a plant utilizes will be different than the δ13C of the plant tissue (Fogel and Cifunentes 1993). The extent to which 13C is discriminated against depends on whether the plant’s photosynthetic pathways are C3, C4 or crassulacean acid metabolism (CAM), and whether the plant is terrestrial or aquatic (Figure 3) (Vogel 1980). Terrestrial plants have
! 7! ! access to almost infinite amount of carbon (Hecky and Hesslein 1995) and the uptake of carbon is primarily limited by the stomatal openings at the leaf’s surface; therefore terrestrial plants have carbon isotope ratios that are directly related to the photosynthetic pathway and the associated enzyme (Smith and Walker 1980; Keeley 1991). During photosynthesis, C3 plants utilize the enzyme Ribulose biphosphate carboxylase (RUBISCO), which discriminates strongly against
13 C. The level of discrimination is different relative to C4 plants that utilize the enzyme PEP carboxylase, which discriminates less strongly against 13C, resulting in more positive δ13C signatures (Smith and Walker 1980). A study by Benedict (1978) illustrated this difference, as
13 13 the δ C signatures of C3 plants ranged from -22 ‰ to -34 ‰, whereas the δ C signatures of C4
13 plants ranged from -8 ‰ to -20 ‰. Plants exhibiting CAM photosynthetic pathways have δ C signatures that encompass values obtained from both C3 and C4 plants (Smith and Walker 1980).
The differences of isotope ratios between photosynthetic pathways have been quantified thus enabling researchers to identify the photosynthetic process used by a plant by sampling its stable isotope signature. In aquatic environments, however, there is no consistent relationship between photosynthetic enzymes and the observed level of isotope fractionation (Smith and Walker 1980;
Keeley and Sandquist 1992). There are other factors influencing the isotopic fractionation of plants in aquatic systems (Figure 3).
! 8! !
CAM Photosynthetic Pathway(2) C4 Photosynthetic Pathway(1) C3 Photosynthetic Pathway(1) Terrestrial Vascular Plants(1,2) PEP(3) RUBISCO(3) Aquatic Plants(3,4) Marine/Freshwater Algae(2) Seagrasses(2,5) Sagittaria subulata(6) Vallisneria americana(4,6)
Dissolved Carbon Dioxide(2,5) Dissolved Bicarbonate(2,5)
0 -10 -20 -30 -40 -50 -60
δ13C signature (permil)
Figure 3: A comparison of the ranges of δ13C signatures of terrestrial and aquatic plants. Aquatic plants exhibit the widest range of δ13C signatures that are not necessarily representative of the photosynthetic pathway, as seen with terrestrial plants. Data from (1) Benedict (1978), (2) Smith and Walker (1980), (3) O’Leary (1981) (4) Osmond et al. 1981; Keeley and Sandquist (1992),
(5) Hemminga and Mateo (1996) and (6) lab and field experiments from this thesis.
Inorganic Carbon in the Aquatic Environment
The Aquatic Environment ! Aquatic macrophytes are a functional group and are the most diverse group of plants, resulting from their many different evolutionary pathways (Sculthorpe 1967). As depicted in Figure 3, the aquatic environment in which these aquatic macrophytes live places certain constraints on photosynthesis that differ from terrestrial systems. Foremost is the fact that the density and viscosity of water are greater than that of air and therefore boundary layers play a more
! 9! ! important role in the aquatic environment (Vogel 1980). The molecular diffusion of dissolved inorganic carbon (DIC) in water is substantially slower than in air (D is ~ 10,000 times smaller in water), which means that the diffusion of DIC at the plant-fluid interface will influence the photosynthetic rate of a plant (O’Leary 1981; Lucas and Berry 1985; Keeley and Sandquist
1992: Denny 1993). It is relevant to note that the uptake of DIC in submerged aquatic macrophytes occurs at the plant-fluid interface (epidermis) and is not controlled by stomatal openings, as is the case with terrestrial plants (Kuo and den Hartog 2007). Completely submerged macrophytes must rely solely on DIC for photosynthesis (Titus and Stone 1982). The different isotopes present in an aquatic system, for example 12C and 13C, would have different diffusion coefficients, however it is commonly assumed that the effects of isotopes on the diffusion of DIC in water are minimal and need not be considered (Farquhar et al. 1982). The diffusion of DIC at the plant-fluid interface is affected by a variety of factors, including fluid velocity and rate of photosynthesis (Keeley and Sandquist 1992; Nishihara and Ackerman 2006).
- The type of photosynthetic pathway a plant uses and whether it has the ability to use HCO3 also further complicates this (Badger et al. 1980; Farquahar et al. 1982).
As indicated above, velocity affects the thickness of the diffusive boundary layers as does the roughness on the leaf surface, including hairs and the presence of epiphytes (Koch 1994).
Carbon must travel across the boundary layer to reach the plant and be utilized in photosynthesis.
In the seagrasses Thalassia testudinum and Cymodocea nodosa, once the carbon has crossed the boundary layer, it also must cross the cuticle (usually reduced in aquatic plants), cell wall, plasmalemma and the chloroplast envelope before it is used in photosynthesis (Koch 1994). In the aquatic environment, diffusion through the boundary layer is typically slower than the diffusion through the plant tissue itself (Larkum et al. 1989; Koch 1994). Even though DIC is
! 10! ! typically limiting in aquatic systems, it seems the boundary layer limits the plants access to DIC even further (Koch 1994). The presence of a boundary layer in aquatic systems is traditionally thought to play an important role in how plants access nutrients such as carbon and therefore determine the rate of photosynthesis. However, as demonstrated by Nishihara and Ackerman
(2006), photosynthesis is driven by the flux of carbon (i.e., product of velocity and concentration) not the velocity alone. Moreover, DIC flux (i.e., delivery) may not be the limiting factor for photosynthesis, rather homogeneous reactions in the CBL (i.e., the uncatalyzed
- conversion of HCO3 to CO2) may be the dominant process controlling photosynthesis (Nishihara and Ackerman 2009).
The Effect of Velocity on Photosynthesis and Growth ! Velocity affects photosynthesis in a variety of ways, the most common being an increase in photosynthetic rate with increasing velocity up to a maximum saturating level beyond which rates may decline (Nishihara and Ackerman 2006). Madsen and Sondergaard (1983) reported that the rate of photosynthesis decreased in Callitriche stagnalis Scop. at velocities greater than
12 cm/s, and this was related to plant density, which partially mitigated the effect of velocity.
They proposed that at high velocities, the “mechanical perturbation” of the blades reduced the ability of the plants to photosynthesize. Madsen et al. (1993) found that plants with an increased surface area:volume ratio were less affected by the inhibitory effects of velocity. Doyle (2001) found the V. americana plants exposed to high wave generated shear stress had a slower growth rate than those plants in a more sheltered environment. Nishihara and Ackerman (2006) found that photosynthetic rate of V. americana increased with increasing velocity from 0 cm/s to 6.6 cm/s. Velocity had a greater effect on photosynthetic rate at low nutrient levels than high nutrient
! 11! ! levels which supported the importance of flux rather than velocity alone (Nishihara and
Ackerman 2006). Based on this body of evidence, both flow conditions and biological conditions play a role in a plant’s photosynthetic response to velocity.
Carbon Speciation in Freshwater
13 Aquatic freshwater plants exhibit a wider range of δ C signatures than terrestrial plants (-11 ‰ to -50 ‰), which is due to a variety of factors affecting isotope fractionation (Figure 3) (Keeley and Sandquist 1992). The type of carbon available to plants is variable in aquatic systems and this source carbon influences the carbon isotope fractionation (Keeley and Sandquist 1992). For
- example, if a plant uses bicarbonate (HCO3 ) instead of dissolved carbon dioxide (CO2) then the resultant δ13C signature will be approximately 7 ‰ to 11 ‰ less negative (Mook et al. 1974;
Keeley and Sandquist 1992). 12C is used preferentially and therefore the equilibrium reactions of
- -2 carbon species (CO2, HCO3 and CO3 ) that fractionate carbon also vary, which results in different carbon species having different isotopic signatures (Hecky and Hesslein 1995). Sharkey
13 and Berry (1985) found that algal cells grown at high CO2 concentration had δ C signatures that were more negative than algal cells grown in a CO2 limiting environment, as these cells relied on
- HCO3 . The pH of an aquatic system plays an important role in determining what type of carbon will be available to the aquatic macrophytes.
The pH of the water affects the photosynthetic capacity of aquatic macrophytes (Titus and Stone 1982). Since the pH of many freshwater systems is basic, the most abundant carbon
- species available for plants to use in photosynthesis is typically HCO3 (Figure 4) (Sharkey and
Berry 1985; Thomaz et al. 2008). However, aquatic plants prefer to use carbon dioxide (CO2)
- because less energy is required to use it relative to HCO3 (Sharkey and Berry 1985; Thomaz et
! 12! !
13 al. 2008). If CO2 was in excess, aquatic plants could have a similar δ C signature to terrestrial plants, however this is rarely the case (Sharkey and Berry 1985; Hecky and Hesslein 1995). In many freshwater aquatic systems, there is not enough CO2 to support a plant’s photosynthetic requirements. About half of the aquatic macrophytes that have been examined have evolved
- - mechanisms to use HCO3 (Thomaz et al. 2008). HCO3 use in plants can be shown indirectly by placing them in a basic solution and determining if they continue to increase the pH and at what
- - rate (Smith 1968). This is because when a plant takes up HCO3 it releases hydroxide (OH ), thereby raising the pH (Smith 1968). This body of evidence illustrates how important the chemical conditions of the aquatic environment are in determining what type of carbon is available, and therefore determining their δ13C signatures.
- An increase in pH above ~8.3 results in HCO3 being the only source of carbon available
-2 - to aquatic plants since CO3 is not used by plants (Maberly and Spence 1983). HCO3 use varies greatly between species and some species are more efficient at uptake than others (Invers et al.
1997). Invers et al. (1997) found that as pH increased, the photosynthetic rates of the seagrasses
Posidonia oceanica and Cymodocea nodosa decreased, however the response of Zostera noltii was not as strong, which demonstrates that not all aquatic macrophytes respond to environmental conditions the same way. It is possible that Zostera noltii might use different carbon sources and photosynthetic pathways, which would explain this difference.
! 13! !
Figure 4: The relationship between DIC and pH in freshwater, which depicts the relative amounts of carbon species at different pH levels (from Wetzel and Likens 2000). Note that above
- a pH of ~8.3, the CO2 levels are negligible and plants would need to use HCO3 (Keeley 1998).
Carbon Uptake Mechanisms ! Carbonic anhydrase influences the rate at which aquatic plants uptake carbon, since it plays an
- important role in the conversion of CO2 from other forms of DIC, such as HCO3 (Lucas and
Berry 1985; Sultemeyer 1998). If the plant is in a low-pH, CO2-saturated environment and the uptake of carbon is rapid, then carbonic anhydrase is one of the enzymes that would limit the rate of photosynthesis (Lucas and Berry 1985). The presence of carbonic anhydrase can be diagnostic in determining what carbon uptake mechanisms and photosynthetic pathways a plant is using.
CAM photosynthesis concentrates CO2 and is beneficial when carbon is limiting (Keeley
1998). Plants with CAM metabolism uptake carbon at night and fix it into malate for storage and future use in photosynthesis (Keeley 1998). C4 metabolisms use both PEP and RUBISCO, in the cytosol and chloroplasts respectively (Bowes 2011). In aquatic macrophytes, the photosynthetic pathways are often more complex than those of terrestrial plants, as demonstrated by Holaday
! 14! !
and Bowes (1980). They found that photosynthetic pathways of Hydrilla verticaillata, while
similar to CAM in many ways, were lacking anatomical characteristics typically associated with
this pathway. More recently, Bowes (2011) noted that certain aquatic plants were capable of
single cell C4 5 Aquatic Single-Cell C4 Photosynthesis
&IG ! PROPOSED SCHEME OF HOW THE SINGLE CELL # SYSTEM OPERATES IN A (YDRILLA LEAF CELL MODIFIED AND UPDATED FROM "OWES ET AL Figure 5: A proposed single cell C4 photosynthetic pathway for aquatic macrophytes (from
Bowes 2011). IN BOTH # AND # LEAVES AND #/ ENTRY IS BY DIF RECYCLES PYRUVATE TO 0%0 WHICH RETURNS TO THE FUSION THIS PROCESS IS NOT THE AGENT RESPONSIBLE CYTOSOL AS SUBSTRATE FOR THE 0%0# REACTION
FOR THE ##- OF THE # LEAF )NSTEAD IT APPEARS TO -UCH OF THE RECENT WORK WITH # (YDRILLA HAS ENHANCE ACCESS TO AND DIFFUSION OF #/ VIA THE FOCUSED ON KEY REGULATORY ENZYMES IN THE PROC Ȫ DISSOLVED (#/photosynthesis THAT TENDS TO BE THE MORE ABUN that lacked the Krantz anatomy (i.e.,ESS $URING INDUCTION OF THE # dual cell compartments) of terrestrial STATE THE ACTIVITY C4 DANT FORM OF INORGANIC CARBON IN MOST WATER BOD OF WHAT BECOMES THE INITIAL CARBOXYLASE 0%0#
IES plants /THER (Figure SUBMERSED 5). This SPECIES illustrates THAT DO the NOT inherent SHOW complexityINCREASES UP TO FOLD /THER # of aquatic photosynthesis and CYCLE ENZYMES this is a EVIDENCE OF A ##- OPERATE A SIMILAR ACIDIFICATION ALSO INCREASE IN ACTIVITY BUT 0%0# IS THE FIRST MECHANISM "OWES AND 3ALVUCCI field that requires further investigation %LZENGA . TO BE UP REGULATED 3ALVUCCI AND "OWES AND 0RINS A B !SCENCIO AND "OWES -AGNIN - * !FTER ENTRY INTO THE LEAF A CYTOSOLIC CARBONIC There are two main mechanisms that describeET AL how an aquatic #ONSEQUENTLY THE DECLINE IN plant utilizes HCO . IN THE ANHYDRASE PRESUMED TO BE (6#! CATALYZES THE FIRST DAY OR TWO IS PROBABLY THE RESULT OF PHOTORES3 EQUILIBRATION OF #/ WITH (#/ Ȫ AND THE LATTER IS PIRATORY #/ RECAPTURE PRIOR TO THE ##- BECOM Generally, HCO - is either taken up by active transport across the cell wall or converted into CO USED BY 0%0# (60%0# TO CARBOXYLATE PHOS3 ING FULLY OPERATIONAL %XPOSURE OF FULLY FUNCTIONAL 2
PHOENOLPYRUVATE TO OXALOACETATE ! CYTOSOLIC # (YDRILLA LEAVES TO DIETHYLOXALACETATE A 0%0# AMINOTRANSFERASE in the boundary AND layer A and MALATE then DEHYDROGENASE taken up by the plantINHIBITOR (Bowes 2011). REDUCES Walker THEIR PHOTOSYNTHESIS et al. (1980) RATE AND
CATALYZE THE PRODUCTION OF ASPARTATE AND MALATE - INCREASES THE / INHIBITION OF PHOTOSYNTHESIS RESPECTIVELY )T IS POSTULATED THAT /!! OR !SP ARE proposed a model of HCO3 use in which aquatic plantsBY MORE create THAN an TWOFOLD acidified -AGNIN layer around ET AL them to "Y
THE MAJOR # ACIDS TRANSPORTED INTO THE CHLORO CONTRAST THE INHIBITOR HAS NO EFFECT ON # LEAF PLAST RATHER THAN MALATE 4HE /!! IS CONVERTED PHOTOSYNTHESIS AND ITS / INHIBITION 4HESE TO MALATE BY A CHLOROPLASTIC -$( AND .!$0( RESULTS ARE TO BE EXPECTED IF THE INHIBITOR CURTAILS IS OXIDIZED TO .!$0 ! CHLOROPLASTIC .!$0 CARBON FIXATION THROUGH THE # LEAF 0%0# 3IMI ! 15! MALIC ENZYME (6-% CATALYZES THE OXIDATIVE LAR FINDINGS HAVE BEEN REPORTED IN TERRESTRIAL # DECARBOXYLATION OF MALATE TO PYRUVATE THEREBY SPECIES WITH ANOTHER 0%0# INHIBITOR DICHLORO
ELEVATING THE ;#/= AT THE RUBISCO FIXATION SITE DIHYDROXYPHOSPHINOYLMETHYL PROPENOATE G AND OVERCOMING THE COMPETITIVE EFFECTS OF / *ENKINS 4HE # VALUES REPORTED FOR 4HUS IT IS IN THE CHLOROPLAST NOT THE WHOLE CELL LAKE GROWN PLANTS ARE ALSO CONSISTENT WITH A CHANGE
WHERE #/ IS CONCENTRATING ! SPECIFIC PARTIALLY FROM RUBISCO TO 0%0# AS THE INITIAL CARBOXYLASE CHARACTERIZED CHLOROPLASTIC PYRUVATE ORTHOPHOS 4ABLE 3PENCER ET AL (YDRILLA PLANTS PHATE DIKINASE ISOFORM BELIEVED TO BE (600$+ AT THE EDGE OF A DENSE MAT OF VEGETATION HAVE !
- - convert HCO3 to CO2 prior to it entering the plant. In this model, HCO3 is not transported though the plant membranes, rather it is converted in the external environment. They tested this model with Chara, a macroalga, and found that it was possible to explain carbon assimilation rates with this model (Walker et al. 1980). Lucas (1983) discussed the various ways in which
- - plants are proposed to use HCO3 : (1) electrogenic and polarized transport whereby HCO3 is moved into the plant and utilized by an electrical potential gradient; (2) the antiport hypothesis in
- which HCO3 is actively moved into the plant by a ‘transporter’ and no electrical gradients are generated; and (3) the proton or H+ pump, which involves moving H+ ions outside the plant to
- create a acidified layer. It would not be incorrect to conclude that mechanisms of HCO3 uptake in aquatic macrophytes are complex and to suggest that this could affect isotope fractionation.
Temporal and Spatial Variation in δ13C signatures ! The δ13C signatures of DIC and aquatic organisms can vary on temporal scales. For example,
Hollander and McKenzie (1991) found that the δ13C signature of DIC varied seasonally due to changes in species diversity. This seasonal variation is important to consider when analyzing
δ13C signatures because isotopic composition provide an integrated signal over the life of an organism (Fogel and Cifunentes 1993). Moreover, there are data from large-spatial scales spanning many ecosystems as well as small-spatial scales involving controlled laboratory environments, which demonstrate spatial variation in δ13C signatures.
Differences in δ13C signatures among taxa and environments have also been noted. For example, seagrasses have a relatively low carbon isotope ratio (13C/12C) (Farquhar et al. 1982) and a less negative δ13 C signature compared to other aquatic macrophytes (Hemminga and
Mateo 1996). A review by France (1995) revealed a difference in benthic algae from lakes compared to rivers (using 876 13 C values). They also noted that pelagic algae discriminated
! 16! ! more against 13 C and proposed that higher turbulence leading to thinner boundary layers was the reason for this pattern. France (1995) also observed δ13C signatures that differed by at least 10 ‰ between planktonic and benthic algae as well as differences between algae collected from pools and riffles (Finlay et al. 2002 and Finlay et al. 1999 respectively). δ13 C signatures from pools were less negative compared to riffles and they believed was due to the thicker boundary layer in low velocity environments (Finlay et al. 2002). Similar observations were made from the macroalgae Cladophora, which was less negative in pools (-23.2 ‰) compared to riffles (-28.1
‰) (Hicks 1997).
France and Holmquist (1997) found less negative δ13 C signatures in macroalgae sampled from inside a seagrass bed compared to the edge of the bed. They hypothesized this finding was due to the variability in water movement between the two environments. However, they also sampled macroalgae from a mangrove ecosystem and found the opposite trend, which they hypothesized was due to the CO2 enrichment in the middle of the mangroves due to falling detritus. This illustrates the complex relationship between the aquatic environment and δ13 C signatures and demonstrates the importance of controlling for carbon availability to assess the effect of fluid movement on isotope fractionation.
Controlled experiments have been conducted to investigate the relationship between carbon isotope fractionation and water velocity. Trudeau and Rasmussen (2003) found that the
δ13 C signatures of periphyton (diatoms and filamentous green algae) were more negative in the faster moving sections of the artificial streams. Ellawala et al. (2012) examined the effect of isotropic turbulence directly on 13C and 15N fractionation in the macroalgae, Chara fibrosa using an oscillating grid apparatus. They found that, on average, increased turbulence led to more isotopic discrimination against 13C and 15N. This trend was not consistent as the δ13 C signatures
! 17! ! of C. fibrosa appear to decline from -27 ‰ to -30 ‰; however, if the 0 cm/s values are not included, then the δ13 C signatures of C. fibrosa appear to increase from -30 ‰ to -29 ‰. There appears to be a relationship between water velocity and carbon isotope fractionation in aquatic primary producers.
A Mechanism to Explain Lower Discrimination Against 13C in Aquatic Producers ! Smith and Walker (1980) proposed that carbon isotope fractionation in aquatic plants was reduced by the diffusion of carbon through the thick boundary layer (the “unstirred layer”) that occurs under low velocities. In this case, the diffusional limitation of carbon by the boundary layer will counteract the effect of the chemical fractionation of the enzymes involved in carbon fixation and lead to the uptake of the 13C isotope (Smith and Walker 1980; Vogel 1980; Trudeau and Rasmussen 2003; Keeley and Sandquist 1992). In aquatic environments with low velocities, the reduced discrimination is a result of the limited carbon supply available to a plant with a thick boundary layer, because the carbon isotopes diffuse more slowly across this greater distance (Smith and Walker 1980; Keeley and Sandquist 1992). A plant with a limited carbon supply will need to use DIC molecules containing 13C when the amount of available 12C molecules is low (Smith and Walker 1980; Keeley 1991; Keeley and Sandquist 1992). The use of
DIC molecules containing 13C leads to a less negative δ13C signature.
The diffusional resistance around an aquatic plant under high velocities is reduced due to a thinner boundary layer (Keeley and Sandquist 1992). In this case, the level of carbon isotopic fractionation is related more closely to the level of fractionation produced by photosynthetic enzymes, such as RUBISCO. Osmond et al. (1981) demonstrated that an aquatic bryophyte
(Fontinalis antipyretica) had a δ13C signature of approximately -33.4 ‰ under fast flowing
! 18! ! conditions, which is consistent with isotopic fractionations expected of RUBISCO (Benedict
1978). This model seems robust because it has been used to explain differences in isotope signatures observed under different flow regimes. Unfortunately, the model has yet to be examined in a rigorous manner (i.e., one that controls for physical and chemical variables such as carbon type and uptake mechanisms) in a laboratory setting.
Study Organisms
Vallisneria americana ! Vallisneria americana Michx. (American eelgrass or water celery), which is an aquatic macrophyte in the Hydrocharitaceae family, has tapered, linear blade-like leaves growing from a shoot attached to runners. It is a temperate plant and can thrive in a wide range of temperatures
(10oC to 26.6oC) (Sculthorpe 1969). It can be found throughout North America, but is especially prolific along the eastern side of the continent (De Wit 1964; Catling et al. 1994). This plant has a short stem from which long ribbon-like leaves extend (Titus and Stephens 1983). The growing season is from late May until late August, which is relatively short compared to other aquatic macrophytes (Titus and Adams 1979). It has been classified as a dioecious perennial plant, however at the end of the growing season (late August to early September) the blades die off and the plant converts into a winter bud during the winter months (Titus and Stephens 1983). Winter buds are buried approximately 3 to 15 cm deep in the sediment (Titus and Hoover 1991). They have a fibrous root system and produce stolons from the axil of the leaf from which new rosettes grow (Titus and Hoover 1991). The plants can also reproduce sexually and typically flower in mid July (Titus and Hoover 1991). Titus and Stephens (1983) found that by the end of the growing season, a V. americana plant was comprised of 7.1 rosettes on average. It is cultivated
! 19! ! widely and also provides a food source for a variety of wildlife, including ducks and moose
(Knapton and Petrie 1999; Les et al. 2008), therefore it is both an ecologically important plant and has anthropogenic uses (e.g., aquarium plant).
Biomass and Carbon Acquisition of V. americana ! Titus and Stephens (1983) found that the majority of the biomass of V. americana in Chenango
Lake, New York was in the leaves between June and August. The width of the blades ranged from about 3 to 10 mm and the length of the leaves was variable and depended greatly on velocity and water depth (Lovett Doust and Laporte 1991). Madsen (1991) noted that aquatic plants can be plastic in their responses to their environmental conditions (e.g., velocity) in terms of resource allocation. The total nonstructural carbon (TNC) of V. americana populations in
Wisconsin fluctuated from 5 to 15 % of the plants total dry weight, but could vary from 4 to 13
% interannually (Titus and Adams 1979). TNC includes free sugars, sucrose, glucose, fructose and starch (Rosas et al. 2013). Since V. americana is a perennial, the resource allocation at the plant level changes throughout the year (Madsen 1991). The leaves have been reported to have
13 o an average δ C signature of -18.2 ± 1.6 /oo, from samples taken in Lake Memphremagog,
Quebec (LaZerte and Szalados 1982; Keeley and Sandquist 1992).
Madsen (1991) observed that V. americana plants used carbon from the sediment, however it only accounted for about 1.4 % of their total carbon uptake. Titus and Stone (1982)
- found that V. americana could use HCO3 in photosynthesis, even though its photosynthetic rate declined with increasing pH from 7 to 9 (holding DIC concentration constant), the plant was still able to photosynthesize even when free CO2 was diminished. Barrett (2007) concluded that V.
- americana can uptake HCO3 and that it uses CAM photosynthesis, although this pathway is
! 20! ! more complicated than previously thought. Vallisneria americana seems to be able to use both
- HCO3 and CO2 at the same time in a single blade (Barrett 2007). Barrett (2007) determined that
- HCO3 use was greatest in the tips of the blades and reduced or non existent in the base of the blades, which is thought to be due to light limiting photosynthesis instead of carbon.
Sagittaria subulata ! Sagittaria subulata (L.) Buch. is a perennial submerged macrophyte species native to North and
South America (Cook 1985). It belongs to the family Alismataceae and is known to have a highly plastic morphology, often making this plant difficult to identify (Adams and Godfrey
1961; De Wit 1964). While similar in morphology to V. americana but different in terms of venation (De Wit 1964), S. subulata also reproduces both sexually and asexually via rhizomes and runners (De Wit 1964). A Sagittaria shoot is comprised of a rosette of blades, with the youngest blades in the center of the rosette (Lieu 1978). The blades are ribbon-like and taper into a sharp point. The length of the blades varies from 5 to 50 cm, depending on abiotic factors such as depth and light availability (De Wit 1964). Sagittaria subulata, once believed to be a CAM plant lacking in Krantz anatomy (Keeley 1998) has since been thought to undergo single cell C4 photosynthesis (Figure 5) (Bowes 2011).
Thesis Rationale ! Aquatic plants have δ13 C signatures that span a wider range than those of terrestrial systems
(Keeley and Sandquist 1992). The presence of boundary layers in aquatic environments and the role they play in the diffusional limitation of nutrient uptake at the leaf surface have been proposed as a mechanism to explain this wider range (Smith and Walker 1980). There have been
! 21! ! a variety of field and laboratory studies that have demonstrated a significant relationship between
δ13 C signature of aquatic macrophytes and velocity. However, these studies have not examined boundary layers per se and in term of laboratory studies have used micro and macroalgae (e.g.,
Chara fibrosa) to analyze the effect of velocity on the δ13 C signature (Trudeau and Rassmussen
2003; Ellawala et al. 2012). The use of macroalga like Chara is complicated by a complex morphology (many branches extending from a central stem), which makes it difficult to measure the boundary layer at the plant-fluid interface and may have contributed to the inconsistent trend between isotopic fractionation and fluid movement (Ellawala et al. 2012).
There are also potentially compounding factors related to the effect of pH on DIC and the
- ability of macrophytes to use HCO3 as a carbon source. Nishihara and Ackerman (2006) demonstrated experimentally that mass transport of aquatic macrophytes is not solely dependent on the thickness of the boundary layer, but that flux of DIC (i.e., product of velocity and DIC concentration) is also a contributing factor. Nishihara and Ackerman (2009) also demonstrated that diffusive boundary layers were not limiting photosynthesis via diffusive limitation (i.e., transport) in V. americana under moderate flows and saturating light levels, rather
- photosynthesis was limited by the uncatalyzed conversion of HCO3 to CO2 in the boundary layer
(i.e., homogeneous reactions). The length of the experiment was relatively short (1 hour) and it would be interesting to examine the response of V. americana under controlled DIC conditions over a longer period of time.
The purpose of this thesis is, therefore, to: (1) examine the effect of velocity on the δ13 C signature on linear-bladed aquatic angiosperms; (2) compare the responses of two macrophytes
- of similar morphology but differing ability to use HCO3 (Vallisneria americana and Sagittaria subulata) (Figure 6); and (3) control the type of carbon available to the plants through the pH of
! 22! ! the experimental system. A flat-blade morphology enables an application of the flat-plate analogy of the boundary layer to a model system developed for V. americana (Nishihara and
Ackerman 2006, 2007, 2009). S. subulata has not been studied as extensively as V. americana, which makes it an interesting subject for comparison and relatively little is known about the plant. Importantly, V. americana and S. subulata reproduce asexually through runners
(Sculthorpe 1969), which provides an opportunity to minimize the effects of genetic variation through the use of genetically identical individuals (ramets) from a single clone (genet). This is relevant as genetics can play a role in determining the baseline 13C/12C ratio of plants (Tieszen
1991).
It is relevant to note that the experimental design used does not allow for the isolation of
- the effect of HCO3 users from non-users, as only one plant from each group was used. It does, however, inform whether the type of carbon a plant uses could have an effect on the carbon isotope fractionation and hence the model presented in Smith and Walker (1980).
! 23! !
A!
B!
Figure 6: The morphology of (A) V. americana and (B) S. subulata (Images from IFAS 1990 and Tropica 2015 respectively).
Research Question ! Is there support for Smith and Walkers’s (1980) mechanism for the effect of velocity on the carbon fractionation of aquatic macrophytes?
! 24! !
Research Objectives ! The research objectives are: (1) to examine the effects of velocity on carbon fractionation of
- - aquatic macrophytes V. americana (a known HCO3 user) and S. subulata (not a known HCO3 user) in laboratory experiments where the type of DIC is controlled; (2) to examine the relationship between velocity and carbon fractionation of V. americana in the field; and (3) to compare the results of the field experiment to that of the laboratory experiments.
Hypotheses and Predictions
H: The diffusional limitation of the boundary layer around aquatic macrophytes and their photosynthetic pathway will affect the fractionation of 13C, and therefore their δ13 C signature as proposed by Smith and Walker (1980).
Prediction 1: I predict that V. americana grown under low velocities with thicker boundary layers will have less discrimination against 13C compared to V. americana plants grown at fasters velocities with thinner boundary layers.
Prediction 2: I predict that S. subulata will differ from the response of V. americana because it is
- not known to utilize HCO3 in photosynthesis.
13 H0: There will be no difference in the δ C signature of aquatic macrophytes grown under different velocities with different resulting boundary layer thicknesses, regardless of their photosynthetic pathway.
! 25! !
MATERIALS AND METHODS
Laboratory Experiments with V. americana and S. subulata
Laboratory Plant Cultivation and Care ! Vallisneria americana and S. subulata were grown in the Hagen Aqualab, University of Guelph, in a 2:1 soil to sand mixture based on the methods of Nishihara and Ackerman (2006). Plants were purchased from Boreal Laboratories and were sourced from laboratory populations in
Florida. The tanks were aerated with an air stone, which drew air from the Hagen Aqualab’s
HVAC system, which is flushed with external air every couple of hours. A single clone of each macrophyte species was cultivated to ensure that all plants (ramets) used in laboratory experiments were from the same genet. No sexual reproduction occurred in the laboratory plant populations. Macrophytes were grown in a 1:50 000 mixture of deionized water to Flourish aquarium plant nutrients (Appendix 1; Seachem Laboratories Inc., Madison, GA), which was added on a biweekly basis. Nutrients levels and water chemistry were examined every 8 weeks over the 8 month growth period. The following nutrient levels were measured using a HACH kit
- (model DR800): total Fe = 0.0157 ± 0.029 (mean ± standard deviation, n = 4) mg/L, NO3 = 0.27
- 3- ± 0.19 mg/L, NO2 = 0.0047 ± 0.0027 mg/L, NH3 = 0.039 ± 0.020 mg/L and PO4 = 0.37 ± 0.13 mg/L. These nutrient levels resulted in adequate growth of both V. americana and S. subulata populations. pH (8.36 ± 0.40) and water temperature (18.5 ± 0.67 °C ) were measured at the same time with a multiparameter water quality meter (YSI Professional Series).
The plants were grown under a light:dark cycle of 12 h:12 h supplied by IP67 fluorescent lights (Fluorescent High Bay V, Visoneering). Photosynthetically active radiation (PAR) measured with a 4π sensor (QSL2101, Biospherical Instruments) was 176 µmol photons m-2 s-1
! 26! ! at the water surface. The light levels were determined using the methodology of Nishihara and
Ackerman (2009) who achieved saturating rates of photosynthesis in V. americana with 156
µmol photons m-2 s-1. One liter of DI water was added to the tanks once weekly to ensure that the water depth remained consistent and to avoid the concentration of nutrients. Algal growth in the tanks was monitored daily and algae were removed from the walls of the tanks with a sponge if necessary.
Flow Chamber Systems
Figure 7: Side view of the flow chambers used in this experiment and the arrows indicate the direction of flow.
! 27! !
Figure 8: Top view of the flow chambers, which were comprised of four channels each. The arrow indicates the direction of flow.
Laboratory experiments were conducted in a set of three recirculating flow chamber systems, each of which contained four channels (85 cm long × 10 cm wide × 10 cm deep) located above a 189 L reservoir lined with heavy-duty polyethylene Duchesne vapor barrier and containing 108 L of water. Water was pumped (Hailea, HX-4500) from the reservoir into the individual channels, which were equipped with ball or gate valves for flow control (Figures 7 and 8). Each channel had an upstream gate (10 cm downstream of inlet) to condition the flow, a
7 cm diameter × 11 cm deep reservoir in the bottom in mid channel at 24.5 cm downstream, and an adjustable gate at 84.5 cm downstream to maintain a constant water depth (5 cm depth in all channels). The dimensions of the channels were designed to ensure that the boundary layer on the plant could develop and flow conditions and speed were verified using sodium fluoroscein dye. The channels were also designed to ensure that the plants had ample room to grow over the course of the experiment using the work of Rybicki and Carter (2002) to estimate the growth rate for V. americana, the larger of the two species.
! 28! !
The water in the reservoir was treated with 2 mL of Flourish [1:50 000] prior to the start of each experiment and it was aerated continuously to ensure that CO2 and O2 were at saturating concentrations for photosynthesis. Maintaining a 5 cm water depth in the channels ensured that the wetted area of each channel was equal across treatments and that light availability would not be affected by water depth. The latter is relevant as Cooper and DeNiro (1989) demonstrated that plant depth could significantly affect carbon fractionation.
Each channel contained one of four velocity treatments, comparable in part to the experiment conditions used in Nishihara and Ackerman (2006): V1 = 0.5 ± 0.06 cm/s, V2 = 2.3 ±
0.1 cm/s, V3 = 5.5 ± 0.7 cm/s and C = control or no flow. Water velocities were measured by timing the volume discharged from each channel. The thickness of the boundary layers generated
(Eqn (1), (2) and (3)) on the leaf at a location 10 cm downstream increased with decreasing velocity by a factor of ~ 2 (Figure 9). The water (4.25 L) in the no flow control channel was exchanged with water from the reservoir once every two days to ensure the water source was the same across all treatments. The high-speed channels (V2 and V3) were equipped with a gate valve and the others (V1 and C) were equipped with a ball valve. Treatment position was blocked, and each treatment was located on an inside channel at least once (Figure 10). This was designed to reduce the amount of variation caused by differences in light availability and differences in potential channel interaction.
Removable plant containers made of 4-inch sections of 2-inch wide schedule 40 PVC pipe were inserted into the reservoir of each channel. Three 8 x 5 cm windows were cut evenly around the circumference of the PVC pipe and were spaced about 1 cm from the bottom of the pipe segment. Each container was lined with 1 x 1 mm mesh to facilitate the movement of water and nutrients into and out of the sediment. A 2:1 soil to sand mixture, the same as that used for
! 29! ! plant cultivation, was used to fill the containers. Pea gravel was used around the removable plant containers to keep them from moving and to minimize the entrainment of the soil-sand mixture into the water.
0.025!
0.02!
0.015!
0.01!
0.005! Boundary!Layer!Thickness!(m)!
0! 0.01! 0.02! 0.03! 0.04! 0.05! 0.06! 0.07! 0.08! 0.09! 0.1! 0.11! Distance!Downstream!from!the!Leading!Edge!(m)!! A! 0.5!cm/s! 2.3!cm/s! 5.5!cm/s!
! 30! !
1.4! 1.2! 1! 0.8! 0.6! 0.4! Thickness!(cm)! 0.2! 0! 0! 1! 2! 3! 4! 5! 6! 7! Velocity!(cm/s)!
measured!MBL!Nishihara!and!Ackerman!2009!
B! measured!DSL!Nishihara!and!Ackerman!2009! predicted!MBL!
Figure 9: Modeled boundary layer thicknesses (using Eqn (1) – (3)) at (A) different downstream distances along a flat plate for the three velocity treatments used in the laboratory and (B) 2 cm downstream from the leading edge at a velocity of 0.5, 2.3 and 5.5 cm/s compared to the thickness of the MBL and DSL measured in situ at 0.5 and 6.6 cm/s by Nishihara and Ackerman
(2009).
Momentum Boundary Layer Thickness Calculations ! The thickness of the momentum boundary layer (δMBL) was calculated using Eqn (1) through (3).
The δMBL at 2 cm downstream from the leading edge was used for the laboratory experiments as this corresponded to the segment of the blade that was sampled (see below). The δMBL 12 cm downstream from the leading edge was calculated using the velocities measured in the field.
These δMBL were compared to those measured by Nishihara and Ackerman (2009) and the measured values were slightly higher than the predicted values by about 3 mm on average
! 31! !
(Figure 9). Therefore, the predicted values are a good representation of the actual momentum boundary layer thicknesses, which is in agreement with the findings of Nishihara and Ackerman
(2009).
Growth Chamber ! The flow chamber systems were placed in a 3.3 m2 PGV36 walk-in growth chamber (Conviron) outfitted with a Conviron controller (CMP5000) located in the Phytotron in the Science
Complex, University of Guelph. The chamber was ventilated from bottom to top and temperature, relative humidity, atmospheric CO2 concentration and PAR were monitored and logged at 30-minute intervals. The plants were exposed to a 16:8 light:dark cycle to mimic natural conditions in late summer in Southern Ontario. PAR was gradually increased throughout the day until it reached a maximum level of 140 µmol photons m-2 s-1 at the water surface. This lighting design was created to be comparable to the field conditions and to maximize growth
(Rybicki and Carter 2002). T5 fluorescent lights were the primary light source and were finely controlled with an Apogee quantum light sensor (Model 100/200) and dimming ballast. The relative humidity of the growth chamber was maintained at 79.9 ± 0.2% RH to reduce the rate of evaporation. The temperature was 23 ± 0.3 °C: 21 ± 0.1 °C during the light:dark cycle. These temperatures were increased or decreased at a rate of 1° C/h. The atmospheric CO2 concentration was set at an ambient 400 ppm, which was ambient for the year 2015. Time spent in the growth chamber was limited to reduce variation in the CO2 concentration. However, due to the need to take daily measurements, the CO2 concentration did deviate from the desired level, resulting in
410 ± 53 ppm over the course of the 5-month long experiment. The position of the flow chambers was selected randomly with a random number generator and was changed between
! 32! !
experiments to control for any environmental gradients within the growth chamber (Figure 10).
A! Door!
B!
Door!
Figure 10: The placement of flow chambers in the growth chamber for the (A) V. americana
experiment and (B) the S. subulata experiment.
Plant placement ! Twelve V. americana shoots and 12 S. subulata shoots were selected from the Hagen Aqualab
population if the blades were green and in good physical condition (i.e., no rips or tears of the
! 33! ! leaf tissue). These plants were photographed against a 1 cm × 1 cm grid and the length and width at the tip, base and middle of each blade was measured to ± 0.01cm using calipers (Mitutoyo,
505-633-50). A wet weight of each plant was taken and an overall qualitative assessment was made of the plant’s physical condition. The plants were transplanted into their respective plant container and allowed to acclimatize for four days in the growth chamber in a cooler filled with deionized water and Flourish [1:50 000] and aerated. The plants were then placed at random into a channel in the flow chamber systems. The valves on the channels were all fully open for the first 24 hours to allow for the homogenization of the bulk water. Ideally, the plants would have been positioned perpendicular to the oncoming flow to allow for the application of flat plate boundary layer theory. The plants were initially secured perpendicular to the oncoming flow with a polymer monofilament (Red Wolf 4.5 kg fishing line), however due to blade senescence the fishing wire was removed and the two species of plants were positioned differently to the oncoming flow due to differences in blade flexibility (Figure 11). The 12 V. americana plants remained in the flow chambers for 7 weeks, however, the period was extended to 12 weeks for S. subulata plants due to the lower growth of the plants.
! 34! !
=!2cm! =!2cm! !
Figure 11: Photograph of(A) S. subulata and (B) V. americana in channels within the flow chamber systems (arrows indicate the direction of flow).
Water Chemistry ! The reservoir was originally filled with 108 L of deionized water and 16.2 g of NaHCO3 (Fisher
- Scientific) to increase the pH above the 8.3 threshold where HCO3 is the only form of DIC.
During the first week of the experiment, pH was monitored daily to determine that it remained consistently above 8.3 (Table 1). After the first week, temperature, conductivity, dissolved oxygen and pH were measured on a weekly basis using the water quality probe. pH was measured in the reservoir and once in each of the channels of all flow chamber systems (i.e., 15 pH measurements per day). pH was always measured when the lights in the growth chamber came on, or “morning”, because this is when the pH would be at its lowest (Figure 12). The pH fluctuates throughout the day, with the highest value occurring mid to late afternoon reflecting high photosynthesis.
! 35! !
8.68!
8.66! 8.64! 8.62!
8.6!
pH! 8.58!
8.56! 8.54!
8.52! 8.5! 7:12!AM! 12:00!PM! 4:48!PM! 9:36!PM! 2:24!AM! 7:12!AM! Time!of!day!
Figure 12: Diel change in pH measured in the flow chambers containing S. subulata. The lights in the growth chamber were turned on at 9 am, which corresponds to the sudden climb in pH about 15 minutes later from 8.54 to 8.61. The bar across the top of the plot indicates whether it was night (black section) or day (yellow section) in the growth chamber.
Table 1: The average pH measured at 9 am in the flow chambers for the two experiments involving V. americana and S. subulata. Note the different length of the experiments for the two plant species, resulting in different n values.
Plant species pH
V. americana 8.9 ± 0.2 (n = 13) S. subulata 8.2 ± 0.2 (n =18)
Two mL of Flourish were added to each system every week to ensure the plants had adequate nutrients necessary for growth. Twenty L of DI water treated with 2.98 g of NaHCO3 and 0.37
! 36! ! mL of Flourish was exchanged weekly in each system to: (1) account for evaporative water loss
- and nutrient buildup; and (2) ensure that the HCO3 concentration available to the plants remained relatively consistent. Water chemistry, including nitrate, nitrite, total iron, ammonia and reactive phosphorus, was measured with a HACH kit (Model DR800) (Table 2). These nutrients were selected based on those measured by the Provincial Water Quality Network
(2013) and the suggestions of Bornette and Puijalon (2011) and Wetzel and Likens (2000).
Table 2: Nutrient concentration measured in the flow chambers over the course of both laboratory plant experiments. Note the different length of the experiments for the two plant species, resulting in different n values.
Experiment Nitrate Nitrite Ammonia Total Reactive (mg/L) (mg/L) (mg/L) Iron Phosphorus (mg/L) (mg/L) V. americana 1.1 ± 0.0048 ± 0.010 ± 0.098 ± 0.19 ± 0.2 (n=2) 0.4 0.006 0.006 0.04 S. subulata 1.1 ± 0.0069± 0.015 ± 0.23 ± 0.62 ± 0.8 (n=6) 0.8 0.004 0.02 0.4
Based on dilution, the plants were exposed to approximately 0.15 g/L of NaHCO3 over course of each experiment. Bromocresol green and phenolphthalein blue titrations (with 0.00502
M HCl standardized with Na2CO3) were performed to determine the alkalinity and estimated the
- - HCO3 concentration ([HCO3 ]) of the water in each system (Table 3). This concentration of titrant was chosen because many of the water samples had relatively low alkalinities and a stronger acid would have lacked the precision necessary to read the end point. Three subsamples of each water source were titrated. The calculations were adapted from Standard Methods for the
Examination of Water and Wastewater (1999) and Stumm and Morgan (1996), and by definition
! 37! !
- all titrated water samples only possessed HCO3 alkalinity; therefore the alkalinity was expressed
- as [HCO3 ]:
Alkalinity (mg/L CaCO3) = (A C × 100 g/mol)/ (S) (8) where A is the volume of acid used (L), C is the concentration of the acid (M) and S is the volume of sample used (L).
Table 3: The concentration of bicarbonate present in the various water sources measured via titrations (mean ± standard deviation, n = 3). The predicted values of the S. subulata experiments were based on DI water with 0.15 g/L of sodium bicarbonate. Vallisneria americana values were based on water sampled from the flow chambers at the end of the experiment. It is evident that alkalinity increased over the course of the experiment with V. americana.
- 3 Water Source [HCO3 ] mol/m Tap water 5.70 ± 0.2 Well Water 5.32 ± 0.09 DI water with Flourish nutrients 0.0180 ± 0.003 S. subulata experiment (predicted) 1.79 ± 0.03 V. americana experiment (measured) 3.21 ± 0.01
Two one-liter plastic containers (containing 1 L DI, 0.019 mL Flourish and 0.15 g NaHCO3 to match the chemical composition of the water used in the experiments outlined above) were placed in the growth chamber to equilibrate with the atmospheric carbon dioxide levels for 48 hours. One water sample from each container (2 replicates) was collected in 40 mL clear glass screw top vials (LL-VV10004, Lilium Laboratories) and sealed with 22*3 mm PTFE/Silicon
Septa (LL-VS10001, Lilium Laboratories) as per the methodology of the Stable Isotope
Laboratory at University of California Santa Cruz (Stable Isotope Laboratory) and IT2 Isotope
Tracer Technologies (pers. comm. August 2015 with Dr. Orfan Shouakar-Stash). Vials were
! 38! !
13 filled completely, ensuring no headspace, and were kept refrigerated until analyzed for δ CDIC signature. This signature included the NaHCO3, flourish, DI water and the dissolved carbon
13 dioxide gas. The δ CDIC signature was also determined for a sample of the NaHCO3 used in the laboratory experiments (Table 4).
13 Table 4: The average δ CDIC signature for the water used in the laboratory experiments and the
δ13C signature for the sodium bicarbonate.
13 13 δ CDIC Laboratory Bulk Water δ C Sodium Bicarbonate (n = 2) (n = 2) - 5.85 ± 0.2 - 6.05
Growth Analysis ! Images of the plants were taken daily using a DSLR (Sony Alpha) in order to assess their growth over the course of the experiments. Qualitative observations of plant growth and physical condition were recorded on a biweekly basis. These observations included but were not limited to: algal growth on the walls of the chamber or the plant; whether the plant was displaying green pigmentation or another colour; number of blades; and the number of senescent blades.
Two methods were used to quantify plant growth. The first involved determining leaf area (LA) based on the sum of the area of each blade on a shoot. LA was calculated by multiplying the length from the base to the tip of each blade by the width at the middle of the blade; due to the shape of the blades this technique overestimates the area but still provide a representative measure of area. Dead tissue (i.e., yellow or clear in appearance) was not included in the measurement of blade length. Image J (US NIH) was used to measure the length of blades in each image; however sometimes the plants were not laying flat or were not clearly represented
! 39! ! in each image. To ensure measurements were accurate, a combination of the following measurements was used to determine total blade length: 1) the initial blade lengths and widths of plants recorded prior to transplanting; 2) the images taken during the course of the experiment; and 3) the biweekly qualitative observations. Growth was also determined from the number of blades on a shoot, which was measured by counting the number of blades at the start and conclusion of the experiment. The difference between these two values was the number of blades grown during the course of the experiment, which was a conservative estimate because some of the original blades could have died and fallen off the shoot.
Sample Preparation and Carbon Isotope Analysis
Laboratory ! At the conclusion of the experiments plant tissue was sampled to determine its δ13C signature.
All tissue that was sampled met the following criteria: (1) was exposed to the oncoming flow of water; and (2) was new tissue grown during the experiment. Prior to sampling, a photograph was taken against a 1 cm × 1 cm grid and a diagram was drawn of the position of each main shoot and its secondary shoots and runners relative to the oncoming flow. Vallisneria americana and S. subulata grow in a rosette formation, with the youngest blades at the center of that rosette. An image was drawn of each blade’s position in the rosette in order to document the age of each blade sampled. The youngest 3 to 5 blades were sampled from each shoot depending on the length of each blade; if a blade was less than 2 cm long then an extra blade was sampled. If the main shoot did not exhibit enough growth during the course of the experiment to be sampled, then its secondary shoots were sampled in the same manner. This sampling methodology was
! 40! ! developed to ensure that there was enough tissue to be handled and processed effectively as well as enough dry tissue mass (at least 0.3 mg) to determine the δ13C signature.
The blades were thoroughly rinsed with DI water to remove macroscopic algae. The blades were photographed against a 1 cm × 1 cm grid and the length and the width at the base, tip and middle of each blade were measured. Age of tissue was controlled for by selecting the youngest blades and by sampling a 2 cm segment from the base towards the tip (Cooper and DeNiro
1989). The 2 cm segments were cut into fine segments with scissors and placed in tin containers for drying. All surfaces, including the scissors, were cleaned between sample processing with DI water and 95% ethanol. Plant tissue was oven dried at 65 ° C for 24 hours.
Once the plant tissue was dry, the samples were crushed to homogenize the sample. Cut pieces of tissue were placed into a sleeve of weighing paper and rolled until the sample was finely ground. Samples were stored in 1.5 mL centrifuge tubes (Fisher) until they were weighed.
Between handling each sampled, all surfaces were cleaned with DI water and 95% ethanol.
Tissue samples were weighed to 0.30 ± 0.04 mg and after every 10 samples an internal adjustment was performed on the scale (XP 26, Mettler Toledo) to ensure that it remained accurate. The tissue was packaged in 6 by 4 mm pressed tin capsules (Isomass Scientific), which were folded into small cubes and placed into a microwell plate (Thermo Scientific) for shipping.
A total of 17 samples were weighed per plant species, with one homogenized sample per channel
(N = 12) and five duplicates. Duplicates were taken at the fastest velocity and the control, with one extra sample run at each of the fastest velocities and two extra samples run for one control channel. This design was aimed at comparing the variation in δ13C signature between the fastest and lowest velocities, examining the accuracy of the δ13C analysis and assessing the effect of sample homogeneity.
! 41! !
Samples were analyzed for δ13C signature at IT2 Isotope Tracer Technologies in Waterloo,
Ontario. A DeltaPlus XL Isotope Ratio Mass Spectrometer (FinniganMat, Germany) and an
Elemental Analyzer (EA-1110 CHN, CE Instruments, Italy) were used to determine what the
δ13C signature was for each plant sample. Standards used were IAEA-CH6, IT2-13 and IT2 –
Beet with a typical standard deviation of ± 0.1‰.
Statistical Analysis ! Each of the four velocity (3 + control) levels were replicated three times (i.e., n = 12; a flow chamber with four channels represented a replicate). Velocity was the primary predictor variable and δ13C signature was the response variable for the analyses. To ensure the data fit a linear model, the R2 and residual plots were analyzed and compared to those of a quadratic and cubic model. While a quadratic model fit the V. americana data marginally better than the linear and cubic models, in light of the relatively low number of data points and lack of a biological mechanism to explain this pattern, a linear model was used.
The normality of the data was determined by Shapiro-Wilk normality tests (Shapiro and Wilk
1965). Change in LA for both S. subulata and V. americana was transformed logarimithically to ensure normality. No outliers were identified; the definition of an outlier being a value that was greater than 1.5 times the difference between the 1st and 3rd quartile (Crawley 2007). A Bartlett test was used to determine homogeneity of variance among treatments (Bartlett 1937).
A general linear model (GLM) for each species with all fixed effects (velocity, change in
LA, number of blades sampled, whether a secondary shoot was sampled, system number and their interactions) was run and a backwards selection technique was used to identify significant effects (Miller 2002), due to the small sample size of the study. A one-way ANOVA was used to
! 42! ! analyze the effect of velocity on δ13C signature and a Tukey’s Honest Significant Difference test was used to determine which pairs of treatments were significantly different (Tukey 1953). The effect of MBL thickness on δ13C signatures was analyzed using one-way ANOVAs. Linear regressions were used to compare the direction of the response of the δ13C signature to velocity or MBL thickness and ANCOVAs were used to compare the slopes of the regression lines between species.
One-way ANOVAs were used to analyze the effect of velocity on the two growth parameters, number of blades grown and change in LA. When data could not be transformed a non-parametric Kruskal-Wallis rank sum test (Kruskal and Wallis 1952) was used to analyze the effect of velocity on growth parameters. Linear regressions were used to compare the direction of the response of the growth parameters to velocity and ANCOVAs were used to compare the slopes of the regression lines between species.
All statistical analyses were done in R version 3.0.2 and were undertaken using a Type 1 error rate (∝) of 0.05. Marginally significant effects (defined as those with a p-value between
0.05 and 0.1) were included to demonstrate potential biological differences that were not significant at ∝ = 0.05 due to the small sample size of the study.
Field Study ! Vallisneria americana was examined in the Maitland River at Benmiller Line (43.718686, -
81.623341), Ontario during the summer months (June to early September) in 2014 and 2015
(Figures 13 and 14). The site was a mixed macrophyte bed comprised primarily of V. americana and secondarily Potagemon species, including P. pusillus. This site had a wide range of velocities, which was measured with a propeller current meter (Swoffer Model 2100). Discharge and water level data measured 500 m downstream from the macrophyte bed were accessed from
! 43! Evaluation of Collaborative and Integrated Water Management 275 actually range from simple consultation up to active involvement in designing and implementing evaluation protocols (Ewing et al., 2000; Parkes & Panelli, 2001).
Background Study Area1 The Maitland River watershed is located in the Southwestern portion of Ontario, Canada’s most populous and economically diversified province (Figure 1). Almost 80% of the 2540 km2 drained by this watershed is devoted to agricultural production (B. M. Ross & Associates, 1995). As in the rest of rural Ontario, the Maitland River watershed is embedded in processes of agricultural and rural change (Troughton, 1997; Smithers & Joseph, 1999). Production intensification, livestock specialization !and corporate farming represent the main sectoral trends in the region (Caldwell, 2001; Keddie & Wandel, 2001). At the same time as the agricultural sector is evolving towards fewer but larger and more specialized intensive operations, the region is Environment Canada (Water Office 2015). Nitrate, nitrite, ammonia, total iron and reactive becoming an attractive tourist and retirement destination (Cummings et al., 1998). phosphorusOther key were demographic measured andusing economic a HACH kit trends (DR 890) are decreasingonce during farmeach field population season (Belore and et increasing rural non-farm developments (Caldwell, 2003; Smithers et al., 2004). As a al.result 2002) of (Table these processes,6). A multiparameter there is a water potential quality for probe conflict (YSI between profession competing series) was visions used to and perceptions of ‘rurality’ in the watershed, as cottagers and small family farms are measureconfronted pH, withdissolved the oxygen, realities conductivity of agricultural and temperature industrialization (Table (Smithers7) during each & Joseph,visit. 1999; Caldwell, 2001; Ferreyra et al., under review). This potential for conflict is especially visible in current debates and controversies regarding the legitimacy, and
Figure 1. Map of the Maitland River watershed, Ontario, Canada. Figure 13: The field site in the Maitland River indicated by the red circle (from Ferreyra and
Beard 2007).
! 44! !
Figure 14: Upstream view of the Maitland River at the field site on August 13, 2015.
! 45! !
Figure 15: Drawing of the field site with the location of quadrats indicated. See Table 5 for information on each quadrat. The blue arrow indicates the direction of flow.
! 46! !
Table 5: Parameters measured in each quadrat. Legend: V = V. americana, P = Potagemon, R/S
= rocky and sandy and S/S = soft and silty; Dense = quadrat full of macrophytes and river bottom not visible, Patch = one or more patches of macrophytes and river bottom visible between patches. All values are averages ± standard deviation with number of measurements (n) included in quadrat column. Plants were sampled from all red quadrats.
! 47! !
Quadrat Water Depth (cm) Canopy Height (cm) Velocity (cm/s) Plant Species Substrate Density A1 (n=5) 65 ± 5.9 23 ± 8.0 27.5 ± 5.3 V/P R/S patch A2 (n=3) 46 ± 4.0 22 ± 3.2 20.5 ± 9.2 V/P S/S + R/S patch A3 (n=3) 49 ± 7.9 31 ± 13 20.5 ± 2.1 V/P S/S dense A4 (n=3) 65 ± 5.6 25 ± 5.5 26.0 ± 8.5 P R/S dense A5 (n=3) 58 ± 13 37 ± 11 19.5 ± 0.7 V/P R/S dense A6 (n=3) 56 ± 1.4 35 ± 0 20.5 ± 9.2 V S/S patch A7 (n=5) 60 ± 13 28 ± 8.0 24.5 ± 3.0 V/P R/S dense B1 (n=3) 81 ± 7.9 56 ± 18 11.0 ± 1.4 V/P R/S dense B2 (n=3) 79 ± 5.5 64 ± 14 6.00 ± 2.8 V/P R/S dense B3 (n=3) 74 ± 13 58 ± 18 9.00 ± 4.2 V/P R/S dense B4 (n=3) 70 ± 17 40 ± 22 17.5 ± 3.5 V/P R/S dense B5 (n=3) 72 ± 8.5 50 ± 9.5 11.5 ± 3.5 V/P R/S dense B6 (n=3) 72 ± 10 47 ± 15 22.0 ± 7.1 V/P R/S patch B7 (n=4) 70 ± 3.6 41 ± 14 17.0 ± 3.0 V S/S dense B8 (n=3) 78 ± 8.2 55 ± 30 12.0 ± 8.5 V R/S dense B9 (n=3) 74 ± 4.7 65 ± 10 8.5 ± 11 V R/S dense B10 (n=3) 72 ± 7.8 49 ± 20 10.5 ± 7.8 V/P R/S dense B11 (n=3) 76 ± 9.3 57 ± 18 11.0 ± 9.9 V/P R/S dense B12 (n=3) 89 ± 6.7 68 ± 27 5.50 ± 3.5 V R/S dense B13 (n=3) 85 ± 9.3 61 ± 23 10.0 ± 5.7 V R/S dense B14 (n=3) 81 ± 5.3 66 ± 17 8.50 ± 5.0 V R/S dense B15 (n=3) 77 ± 8.9 55 ± 18 11.0 ± 7.1 V R/S dense B16 (n=3) 79 ± 8.1 55 ± 14 13.5 ± 12 V R/S dense B17 (n=5) 75 ± 4.6 50 ± 7.8 16.8 ± 3.0 V R/S patch C1 (n=5) 72 ± 6.2 56 ± 16 1.50 ± 1.5 V R/S patch C2 (n=5) 74 ± 9.1 56 ± 15 2.00 ± 1.8 V R/S patch C3 (n=5) 80 ± 16 57 ± 25 4.25 ± 4.3 V R/S patch ! 48! !
A"
! 49! !
!
B"
Figure 16: Water level (green line) and discharge (orange line) during the summer of (A) 2014 and (B) 2015 at the Maitland River near Benmiller Line, Goderich (Water Office 2015). The monitoring station was ~500 meters downstream from the macrophyte bed.
The red circles indicate sampling dates. ! 50! Table 6: Nutrient concentration at the field site measured in 2014 and 2015 compared to values
measured in the Maitland River in 2002 (Belore et al. 2002).
Nutrient 2014 (n = 1) 2015 (n = 1) Belore et al. (2002) Nitrate (mg/L) 1.95 4.80 N/A Nitrite (mg/L) 0.021 0.058 N/A Total Iron (mg/L) N/A 0.12 N/A Ammonia (mg/L) 0.06 0.00 0.04 Reactive Phosphorus 0.11 0.16 0.028 (mg/L)
Table 7: The pH and temperature at the Maitland River field site in both field seasons. Theses
parameters were only sampled once in 2014 and five time in 2015.
2014 (n = 1) 2015 (n = 5) pH 9.02 8.80 ± 0.2 Temperature (° C) 20.9 23.1 ± 1.0
35!
30!
25! Average!Velocity! 27.5cm/s! 20! 16.8cm/s! 15! 4.3cm/s!
10! 2cm/s! Water&Velocity&(cm/s)& 5! 1.5cm/s!
0! 1.92! 1.96! 1.975! 2.03! 2.05! &Water&Level&(m)&
Figure 17: Water velocity measured within quadrats at different water levels (see Table 8) in the
Maitland River in 2015.
! ! 51! Table 8: River conditions corresponding to field visits in 2015 (Environment Canada Water
Office 2015).
22-Jul-15 13-Aug-15 20-Aug-15 09-Sep-15 18-Sep-15 Discharge (m3/s) 12.5 5.00 7.70 19.0 6.40 Water Depth (m) 2.030 1.920 1.975 2.040 1.960
Velocity was measured during each visit and the plants were sampled once at the end of the
growing season in 2014. More water velocity measurements were taken in 2015. In 2015, the
macrophyte bed was divided into 2 m by 2 m quadrats, which were sampled for macrophyte
species, sediment type, water depth, canopy height and velocity (Figure 15 and Table 5).
Velocity, water depth and canopy height were measured at the center of each 2 m by 2 m
quadrats. The propeller of the Swoffer current meter was positioned at 40 percent of the water
depth from the bottom to avoid any interference by the boundary layer of the river. Velocity
measurements were taken either at the edge of a patch (at 40% water depth) or above the canopy
of the plants in dense quadrats (at approximately 10 cm above the top of the canopy, see Table 5
for canopy heights in each quadrat). Quadrats were resampled if they possessed four
characteristics: (1) the quadrat had patches of plants; (2) the quadrat was in close proximity to
those sampled in 2014; (3) there was relatively low temporal variation in velocity; and (4)
quadrats encompassing a range of velocities suitable for the study (Figure 17). Velocity was
measured on five days in 2015 that represented a range of water levels and discharge and
velocity was measured on one day in 2014 (Figure 16A and B and Table 8). Plaster of Paris
hemispheres were used to gain a better understanding of fluid movement throughout the
macrophyte bed, however the hemispheres remained in the river for too long and could only be
used for qualitative assessments of flow (see Appendix 2).
Plants were sampled at the end of the growing season in 2014 and 2015, by removing 3
! ! 52! shoots from each of 5 quadrats in both 2014 and 2015 (i.e., a total of 15 shoots per growing
season). Shoots were sampled at the upstream edge of each patch directly downstream of where
the velocity reading was taken. Shoots were sampled at 10 cm intervals (Lovett Doust and
LaPorte 1991). The entire shoot was sampled and kept refrigerated until processed for isotope
analysis.
Sample Preparation ! The plants collected in 2014 were sampled in a different manner than the laboratory plants.
Shoots were cleaned with DI water and visible epiphytes were removed. Prior to sampling a
photograph was taken of each shoot against a 1 cm × 1 cm grid. A blade greater than 30 cm in
length was sampled from each shoot and oven dried at 65 ° C for 24 hours. These blades were
ground with a mortar and pestle and homogenized into a fine powder. Unfortunately, neither the
total length of the blade sampled nor its position on the shoot were noted or recorded. There were
a total of three blades sampled from five quadrats (N = 15).
In 2015 the plants were sampled in a manner similar to the laboratory experiment. Shoots
were cleaned with DI water and visible epiphytes were removed. Prior to sampling a photograph
was taken of each shoot against a 1 cm × 1 cm grid. The total number of blades on each shoot
was recorded as well as the length of all blades sampled. The three youngest blades greater than
12 cm in length (from the center of the rosette) were sampled. A 2 cm segment of the blades was
taken 10 cm from the base of the blade, which was where the tissue was green and had been
protruding from the sediment in the river. These 2 cm segments were cut into fine sections with
scissors and placed in tin containers for drying. All surfaces were cleaned between sample
processing with DI water and 95% ethanol. Plant tissue was oven dried at 65 ° C for 24 hours.
! ! 53! Three shoots were sampled from each of five quadrats and one sample was sent from each of
those plants (N = 15), with two extra samples run at the quadrats with the fastest and slowest
velocities. To compare the sampling technique of 2014 to the new method used in 2015, 3 shoots
from quadrat C3 were resampled (N = 3) and a single blade longer than 30 cm was processed.
The total length of the blade was recorded and it was oven dried at 65 ° C for 24 hours. These
blades were ground with a mortar and pestle and homogenized into a fine powder. These tissue
samples were stored, weighed and analyzed in the same manner as the laboratory plants.
Statistical Analysis ! Velocity was the primary predictor variable and δ13C signature was the response variable for the
analyses. All data were examined for normal distributions using Shapiro-Wilk normality tests
(Shapiro and Wilk 1965) and Bartlett’s test was used to examine homoscedasticity (Bartlett
1937). A GLM for the 2015 field season with all fixed effects (velocity, total blade number of
each shoot, quadrat water depth and their interactions) was run and a backwards selection
technique was used to identify significant effects (Miller 2002), due to the small sample size of
the study. One-way ANOVAs were used to analyze the effect of velocity on δ13C signature in the
2014 and 2015 field seasons. The effect of MBL thickness on δ13C signatures was analyzed
using one-way ANOVAs. Post hoc Tukey Honest Significant Difference tests were used to
determine which quadrats were significantly different (Tukey 1953). Linear regressions were
used to compare the direction of the response of δ13C signature to velocity and MBL thickness
between the two field seasons and ANCOVAs were used to compare the slopes of the regression
lines. All statistical analyses were done in R version 3.0.2 and were undertaken using a type 1
error rate (∝) of 0.05.
! ! 54! RESULTS Effect of Velocity on the δ13C signatures of Macrophytes in Laboratory Experiments ! The 13C values decreased in value with increasing velocity of the treatment for V. americana
13 (Figure 18). Velocity had a significant effect on the δ C signature of V. americana (F3,8 = 16.05,
p < 0.001). It is important to note that the GLM analysis for each species demonstrated that the
only significant effect was velocity; therefore all other effects were omitted from any further
analyses. Tukey’s HSD revealed that the no-flow control (0 cm/s) had significantly higher 13C
values than 2.3 cm/s and 5.5 cm/s, and the 0.5 cm/s treatments had significantly higher 13C
values than 2.3 cm/s and 5.5 cm/s (Table 9). Conversely, the 13C values increased in value with
increasing velocity of the treatment for S. subulata (Figure 19). Velocity had a significant effect
13 on the δ C signature of S. subulata (F3,8 = 12.12, p = 0.0024; Figure 19; all other predictors and
their interactions in an original GLM were not significant and so measures of growth rate,
sampling technique and system number were omitted from any further analyses). Tukey’s HSD
revealed that the 5.5 cm/s treatment had significantly higher 13C values than the control and 0.5
cm/s, and marginal differences were found between 2.3 cm/s and 0.5 cm/s, and between 5.5 cm/s
and 2.3 cm/s (Table 10).
As indicated above, V. americana’s δ13C signatures became more negative with
increasing velocity while S. subulata’s δ13C signatures became less negative with increasing
velocity. This would indicate that V. americana blades grown under the faster velocities
13 2 discriminate more against C that those grown at slower velocities (F1,10 = 19.68, R = 0.66, p =
0.0013). The opposite trend was true for S. subulata where discrimination was lower at higher
2 velocities (F1,10 = 33.42, R = 0.77, p < 0.001) (Figure 20). ANCOVA confirmed that the
! ! 55! discrimination of 13C differed significantly between V. americana and S. subulata grown at the
same velocities (F1,20 = 59.13, p < 0.001) (Figure 22).
The effect of velocity on δ13C signature of Vallisneria americana
-14
-16 a! a! b!
C signature (permil) C signature -18 13 δ b!
-20
0 0.5 2.3 5.5
Velocity (cm/s)
Figure 18: Boxplot of the δ13C signature of V. americana plants grown under different
velocities. Different letters indicate significant differences between groups as determined by
Tukey’s HSD.
Table 9: Results of the Tukey’s HSD test where significant p-values are in bold.
Treatment p-value Comparisons (cm/s) 0.5 vs. 0 0.30 2.3 vs. 0 0.0030 5.5 vs. 0 0.0010 2.3 vs. 0.5 0.035 5.5 vs. 0.5 0.015 5.5 vs. 2.3 0.93
! ! 56!
The effect of velocity on δ13C signature of Sagittaria subulata
-21
-22 a!
-23 b! b!
C signature (permil) C signature ab! 13 -24 δ
-25
0 0.5 2.3 5.5
Velocity (cm/s)
Figure 19: Boxplot of the δ13C signature of S. subulata plants grown at different velocities.
Different letters indicate significant differences between groups as determined by Tukey’s HSD.
Table 10: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined.
Treatment p-value Comparisons (cm/s) 0.5 vs. 0 0.78 2.3 vs. 0 0.32 5.5 vs. 0 0.0070 2.3 vs. 0.5 0.087 5.5 vs. 0.5 0.0020 5.5 vs. 2.3 0.091
! ! 57! >10!
>12!
>14! y&=&50.896x&5&15.24& >16! R²&=&0.66,&p&=&0.0013! >18!
>20!
C&signature&(‰&)& >22! 13 δ >24! y&=&0.56x&5&24.32& >26! R²&=&0.77,&p&<&0.001!
>28! 0! 1! 2! 3! 4! 5! 6! Velocity&(cm/s)&
V.!americana! S.!subulata!
Figure 20: The relationship between velocity and δ13C signature compared between V.
americana and S. subulata.
Effect of Velocity on Growth ! The two estimates of growth, change in leaf area (LA) and number of blades, increased slightly
with the velocity of the treatment for V. americana although the effects of velocity were not
significant in either case (change in LA: F3,8 = 1.51, p = 0.28; number of blades grown: H3 =
3.611, p = 0.31 respectively). Importantly, there was no effect of replicate (i.e., flow chamber
system number) on either growth measure (change in LA: F2,9 = 0.225, p = 0.80; number of
blades grown: H2 = 1.805, p = 0.41). There was no change in growth estimates with increasing
velocity for S. subulata plants (change in LA: F3,8 = 0.781, p = 0.54; number of blades grown: F3,8
= 0.598, p = 0.63), nor was there an effect of replicate on the change in LA or number of blades
! ! 58! grown (F2,9 = 0.405, p = 0.68 and F2,9 = 0.13, p = 0.88 respectively). An ANCOVA
demonstrated that the effect of velocity on the change in LA was not significantly different
between V. americana and S. subulata (F1,20 = 0.028, p = 0.72) (Figure 21). Unfortunately, the
relationship between number of blades grown and velocity could not be compared between
macrophyte species because this growth estimate was not normally distributed and could not be
transformed for V. americana.
Qualitative growth measurements were made throughout the course of both experiments as
were observations regarding pigmentation of V. americana. At the conclusion of the V.
americana laboratory experiment, 11 out of 12 plants exhibited some degree of dark red
pigmentation instead of the typical green. The sole green plant was in the 0.5 cm/s velocity
treatment. Blades that were shaded by another or at the base of the blade retained a rich green
pigmentation was observed. Based on this observation it seems that light availability was an
important factor in the plants exhibiting the unusual red pigmentation. Future experiments with
V. americana should use lower light levels if red pigmentation is to be avoided.
! ! 59! 1! )&
2 0.5!
0!
>0.5!
>1!
>1.5!
Log&Change&in&leaf&area&(cm >2!
>2.5! 0! 1! 2! 3! 4! 5! 6! Velocity&(cm/s)&
V.!americana! S.!subulata!
Figure 21: The relationship between velocity and change in LA compared between V. americana
and S. subulata (refer to Effect of velocity on growth for statistical analysis).
Field Results ! The GLM analysis for the 2015 field season demonstrated that the only significant effect was
velocity; therefore all other effects were omitted from any further analyses. and were therefore
omitted from any further analyses. The δ13C signatures of the plants decreased with increasing
velocity in both 2014 and 2015, although the range of velocities examined were different (Figure
22 and 23). Velocity had a significant effect on the δ13C signatures of the plants sampled in 2014
13 (F4,10 = 5.715, p = 0.010) where the δ C signatures at the 0 cm/s quadrat were significantly
higher than the 20 cm/s and 40 cm/s quadrats (Figure 22) (Table 11). Similar results were
13 obtained in 2015 (F4,10 = 3.532, p = 0.048) (Figure 23) where the δ C signatures were
! ! 60! marginally significantly higher in the 2 cm/s vs. the 16.8 cm/s quadrat (Table 12). The linear
regressions demonstrated that during both field seasons the δ13C signature of V. americana
2 became more negative as velocity increased (2015: F1,13 = 11.74, R = 0.47, p = 0.0045; 2014:
2 F1,13 = 18.85, R = 0.59, p < 0.001). Although slightly different in pattern, the effect of velocity
on the discrimination against 13C was not significantly different between V. americana sampled
in 2014 and 2015 (ANCOVA F1,26 = 1.12, p = 0.22) (Figure 24). The comparison of the two
different sampling techniques (see Field Methods) between the two field seasons demonstrated
that there was no significant difference in the δ13C signatures obtained from the two techniques
(paired t-test: t2 = 1.47, p = 0.28).
! ! 61! The effect of velocity on δ13C signature of Vallisneria americana in the Maitland River
-21.5
-22.0 a! b! -22.5
ab! -23.0 ab! b!
C signature (permil) C signature -23.5 13 δ
-24.0
-24.5
0 5 10 20 40
Velocity (cm/s)
Figure 22: Boxplot of the difference in δ13C signature of V. americana plants grown in the
Maitland River during the summer of 2014. Different letters indicate significant differences
between groups as determined by Tukey’s HSD.
Table 11: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined.
Treatment p-value Comparisons (cm/s) 5-0 0.77 10-0 0.90 20-0 0.043 40-0 0.019 10-5 0.99 20-5 0.25 40-5 0.12 20-10 0.17 40-10 0.08 40-20 0.98
! ! 62! The effect of velocity on δ13C signature of Vallisneria americana in the Maitland River -18 -19 -20 C signature (permil) C signature -21 13 δ -22
1.5 2 4.3 16.8 27.5
Average velocity (cm/s)
Figure 23: Boxplot of the difference in δ13C signature of V. americana plants grown in the
Maitland River during the summer of 2015.
Table 12: Results of the Tukey’s HSD test where significant p-values are in bold and marginal
results are underlined.
Treatment p-value Comparisons (cm/s) 2-1.5 0.99 4.3-1.5 0.99 16.8-1.5 0.19 27.5-1.5 0.30 4.3-2 0.98 16.8-2 0.093 27.5-2 0.15 16.8-4.3 0.20 27.5-4.3 0.32 27.5-16.8 0.99
! ! 63! >18.0!
>19.0! )&
oo >20.0! y&=&50.08593x&5&19.69& / o R²&=&0.47,&p&=&0.0045& >21.0!
>22.0! y&=&50.0530x&5&21.88& C&signature&(
13 >23.0! R²&=&0.59,&p&<&0.001& δ
>24.0!
>25.0! >5! 0! 5! 10! 15! 20! 25! 30! 35! 40! 45! Velocity&(cm/s)&
2015! 2014!
Figure 24: The relationship between velocity and δ13C signature of V. americana plants sampled
from the Maitland River in the summer of 2014 and 2015. Note that the velocity measurements
for 2014 were based on a single measurement, whereas the velocity measurements for 2015 were
based on the average of five measurements throughout the field season.
Effect of Momentum Boundary Layer Thickness on δ13C Signature ! In order to address the hypothesis regarding Smith and Walker’s (1980) proposed mechanism of
boundary layer limitation to explain the higher 13C use (less discrimination) by aquatic
macrophytes at low velocities, it was necessary to use the measurements of velocity and
downstream distances to determine the thickness of the momentum boundary layers (δMBL; see
Figure 9A). The results indicate that the δ13C signatures of V. americana increased (became less
negative) with increasing δMBL for plants grown in the laboratory and sampled in the field
! ! 64! (Figure 25). MBL thickness had a significant or marginally significant effect on the δ13C
signatures of V. americana in the laboratory experiments and both field seasons (Laboratory: F2,6
= 15.23, p = 0.0050; Field 2014: F3,8 = 3.915, p = 0.054; Field 2015: F4,10 = 3.532, p = 0.048).
Tukey’s HSD revealed that the δ13C signatures in the laboratory differed significantly between a
δMBL of 0.988 cm and both a δMBL of 0.295 cm and 0.456 cm (Table 13). The 2014 field season
13 had marginally significantly different δ C signatures between the δMBL of 0.542 cm and δMBL of
0.271 cm (Table 14). The 2015 field season had marginally significantly different δ13C
signatures between the δMBL of 1.18 cm and 0.408 cm (Table 15). It is relative to note that all
data for velocities equal to 0 was omitted from the δMBL analyses. The responses of V. americana
in the laboratory and in the field were significantly different (ANCOVA F2,30 = 11.17, p <
13 0.001); however the direction of their responses was the same as with increasing δMBL, the δ C
signatures became more positive (Figure 25).
! ! 65! >15!
>17!
>19!
>21! C&signature&(‰)&& 13
δ >23!
>25!
>27! 0.1! 1! 10! Log&boundary&layer&thickness&(cm)&
V.!americana!Lab! V.!americana!Field!2014! V.!americana!Field!2015!
Figure 25: The effect of MBL thickness on the δ13C signatures for V. americana plants grown in
the laboratory and sampled in the field in 2014 and 2015 (refer to Effect of momentum boundary
layer thickness on δ13C signatures for statistical analysis).
Table 13: Results of the Tukey’s HSD test for laboratory V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to MBL
thickness at each velocity.
Treatment Comparisons p -value (cm) 0.456-0.295 0.74 0.988-0.295 0.0050 0.988-0.456 0.010
! ! 66!
Table 14: Results of the Tukey’s HSD test for field 2014 V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to MBL
thickness at each velocity
Treatment Comparisons p -value (cm) 0.383-0.271 0.96 0.542-0.271 0.094 0.767-0.271 0.13 0.542-0.383 0.18 0.767-0.383 0.25 0.767-0.542 0.99
Table 15: Results of the Tukey’s HSD test for field 2015 V. americana where significant p-
values are in bold and marginal results are underlined. Note treatments correspond to MBL
thickness at each velocity
Treatment Comparisons p -value (cm) 0.408-0.319 0.99 0.807-0.319 0.32 1.18-0.319 0.15 4.32-0.319 0.30 0.807-0.408 0.20 1.18-0.408 0.093 4.32-0.408 0.19 1.18-0.807 0.98 4.32-0.807 0.99 4.32-1.18 0.99
Conversely, the response of S. subulata was opposite to that of V. americana in that the
13 δ C signatures decreased (became more negative) with increasing δMBL (Figure 26). MBL
13 thickness had a significant effect on the δ C signatures of S. subulata (F2,6 = 12.04, p = 0.0070).
13 Tukey’s HSD revealed that the δ C signatures were significantly different between the δMBL of
! ! 67! 0.988 cm and the δMBL of 0.295 cm and that they were marginally different between the δMBL of
0.456 cm and both 0.295 cm and 0.988 cm δMBL (Table 16).
>15!
>17!
>19!
>21!
>23! C&signature&(‰)&& 13 δ >25!
>27! 0.1! 1! 10! Log&boundary&layer&thickness&(cm)&
Figure 26: The effect of MBL thickness on the δ13C signatures for S. subulata plants grown in
the laboratory (refer to Effect of momentum boundary layer thickness on δ13C signatures for
statistical analysis).
Table 16: Results of the Tukey’s HSD test for laboratory S. subulata where significant p-values
are in bold and marginal results are underlined. Note treatments correspond to MBL thickness at
each velocity
Treatment Comparisons Difference p -value (cm) 0.456-0.295 -1.623333 0.10 0.988-0.295 -3.266667 0.0055 0.988-0.456 -1.643333 0.096
! ! 68! DISCUSSION Effect of Velocity on δ13C signature in Laboratory Experiments ! The results from this thesis support Smith and Walker’s (1980) mechanism for carbon isotope
fractionation in aquatic plants, but also demonstrates it depends on the physiological abilities of
the macrophyte species. Specifically, the model is appropriate V. americana but not for S.
subulata. One possible explanation for the difference in response between the two species that is
- - for Smith and Walkers mechanism is true for HCO3 users (V. americana) but not for non-HCO3
- users (S. subulata) when HCO3 is the primary source of DIC as is the case for many lakes and
rivers (i.e., the pH of the water is in excess of 8.3). The null hypothesis that δ13C signature would
be the same across velocities can be rejected, even though the direction of the response differed
between V. americana and S. subulata (Figure 20). Vallisneria americana plants had a more
negative δ13C signature with increasing velocity, which is in agreement with the majority of the
laboratory and field data collected on primary producers to date (see Literature Review Section).
The opposite relationship in S. subulata indicates that there was more 13C discrimination at low
- velocity, which could be a result of the uncatalyzed conversion of HCO3 to CO2 in the boundary
layer being sufficient to supply CO2 to the plant at low velocity but this effect diminishing at
higher velocities as the boundary layer became thinner.
Controlled Experiments ! Ellawala et al. (2012), who studied the effect of isotropic turbulence on 13 C isotopes in Chara
fibrosa using an oscillating grid apparatus, and Trudeau and Rasmussen (2003), who examined
the effect of velocity on stream periphyton in the laboratory, both found more negative δ13C
signatures with increasing velocity (Figure 27 A). The same relationships hold using the
Reynolds number based on the length scale of the alga (cell diameter and width of microscope
! ! 69! slide, respectively), which accounts for different spatial and velocity scales and thus different
hydrodynamic conditions (Figure 27). The same relationships also hold using MBL thickness,
which is also a function of velocity (Figure 29). Regardless of the analysis, these results
demonstrate an increase in velocity and decrease in MBL thickness (or Reynolds number)
corresponds to a more negative δ13C signature, which is the same trend that was found with the
V. americana plants in this thesis.
The results for S. subulata demonstrate that an increase in velocity results in a more positive
δ13C signature. This result is similar to that of France and Holmquist (1997), who found that δ13C
signatures of seagrasses were more positive at the edge of a seagrass bed sampled in a mangrove
ecosystem. Their proposed mechanism for this difference was that in the mangrove ecosystem,
the plants were supplied with excess CO2 due to the mangrove detritus. France and Cattaneo
(1998) also observed a positive relationship between velocity and δ13C signature of filamentous
benthic algae. They proposed that terrestrial organic matter was being decomposed by microbes
which was changing its δ13C signature and that the plants were then using this as a carbon source
in slow flowing regions. This would interfere with the expected negative relationship between
δ13C signature and velocity. However, these mechanisms do not explain the trend observed in the
laboratory experiments for S. subulata, as the amount of carbon available to the plants was
- controlled and was primarily in the form of HCO3 . A more plausible mechanism to explain the
- response in S. subulata is the manner in which it uptakes HCO3 .
! ! 70! >10!
>15!
>20!
>25! C&signature&(‰&)& 13 δ >30!
>35! 0! 10! 20! 30! 40! 50! 60! Velocity&(cm/s)& A!
Trudeau!and!Rasmussen!2003! Ellawala!et!al.!2012! V.americana! S.subulata!
0!
>5!
>10!
>15!
>20! C&signature&(‰&)&
13 >25! δ >30!
>35! 0.0001! 0.01! 1! 100! 10000! Reynolds&Number&
B! Trudeau!and!Rasmussen!2003! Ellawala!et!al.!2013! V.!americana! S.!subulata!
Figure 27: The effect of (A) velocity and (B) Reynolds number (Re) on δ13C signature of both
macrophyte species in this thesis compared to the trends from Ellawala et al. (2012) and Trudeau
and Rasmussen (2003). Re was based on length scales of: (1) the diameter of the stalk-like
! ! 71! section of a C. fibrosa plant for Ellawala et al. (2012); (2) the width of a glass microscope slide
for Trudeau and Rasmussen (2003); and (3) the width of a blade for V. americana or S. subulata
from the laboratory experiments.
- HCO3 Uptake ! - HCO3 use has been found to vary with velocity in aquatic macrophytes. Nishihara and
Ackerman (2006) found that water velocity had a greater effect on the photosynthetic rate of V.
americana when nutrient concentrations were low. The nutrient concentrations ([DIC]) in this
thesis were in the mid range of those examined by Nishihara and Ackerman (2006). They
determined that the proportion of O2 flux (their measure of photosynthetic rate) that was due to
- - HCO3 uptake decreased with increasing velocity. Extrapolating from their data, HCO3
availability in the laboratory experiments with V. americana is predicted to decrease linearly
from ~ 98% to ~ 93% (5%) with an increase in velocity from 0.5 cm/s to 5.5 cm/s (Nishihara and
- Ackerman 2006). LaZerte and Szalados (1982) noted that a plant that uptakes HCO3 would have
13 a more positive δ C signature than a plant that uses CO2. One could conclude that at higher
- 13 velocities, the reduction in HCO3 use would result in a more negative δ C signature simply
13 - because of the difference in δ C signatures between HCO3 and CO2. However, at the relatively
low [DIC] concentrations and the limited CO2 availability in this experiment, it is unlikely that
the change δ13C signature observed over the range of velocities examined in this thesis could be
explained solely by this mechanism. It also does not explain the increase in δ13C signature with
increasing velocity that was observed for S. subulata.
Nishihara and Ackerman (2009) investigated DIC uptake by V. americana and measured O2
flux along the length of a single blade. They found that O2 flux was not the same along the
! ! 72! length of the leaf and reached its maximum value at 2 cm downstream from the leading edge and
then declined (Nishihara and Ackerman 2009). Assuming that these conditions were the same
for V. americana grown for this thesis, the tissue that was sampled was 2 cm downstream from
the leading edge represented tissue with high photosynthetic rate. Nishihara and Ackerman
(2009) proposed that the supply of DIC decreased downstream leading to a decline in the O2 flux
- and that this was likely caused by the lack of conversion of HCO3 to CO2 in the MBL. Based on
the aforementioned evidence and the work of Titus and Stone (1982), it is clear that V.
- - americana uses HCO3 for photosynthesis, however the specific mechanism of HCO3 uptake has
not been directly studied. Based on the results of this thesis, V. americana seems to be able to
- directly uptake HCO3 because a thinner boundary layer resulted in more discrimination against
13 - C as the carbon pool was less limiting. If V. americana was only converting HCO3 into CO2 in
an acidified layer at the surface of the blade, one would expect that the boundary layer thickness
would have the opposite effect on the δ13C signature. While this mechanism may not hold true
for V. americana, it may explain the trend observed for S. subulata as described below and
above.
Proposed Mechanism for Effect of Velocity on S. subulata ! - Aquatic macrophytes employ a variety of techniques to utilize HCO3 in photosynthesis, as
- discussed above. They can be generalized into two different approaches: (1) direct use HCO3 ; or
- (2) converting HCO3 to CO2 in an acidified layer on the surface of the plant and then uptaking
the CO2 (Lucas and Berry 1985; Bowes 2011). A possible mechanism to explain the trend in
δ13C signature observed in S. subulata plants is that S. subulata plants are not able to directly
- uptake HCO3 . Bowes (2011) noted that S. subulata showed evidence of a plant with single cell
! ! 73! - C4 photosynthesis (see Figure 5). This is typically associated with an inability to use HCO3
directly from the water column and an acidified layer around the blade could be used to convert
- HCO3 to CO2 (Walker et al. 1980). Carr and Axelsson (2008) found that the seagrass Zostera
- marina used these acidic regions to use HCO3 as a carbon source. The reactions that could occur
within the boundary layer are important to consider, which in this case is the conversion of
- HCO3 to CO2 (Gutknecht and Tosreson 1973; Walker et al. 1980). At higher velocities and a
thinner boundary layer, the turbulence and eddies along the blade could interfere with the
accumulation of H+ ions along the outer edge of the blade. At higher velocities, the plant would
have less access to a carbon source compared to slower velocities with a thicker boundary layer
that facilitates the accumulation of H+ ions. Therefore, plants grown at higher velocities would
discriminate less against 13C and have a less negative δ13C signature.
Nitella and Chara, which are both macroalgae, have both been shown to create an acidic
- layer at their internodal cells to facilitate the conversion of HCO3 to CO2 (Lucas 1975; Lucas
1983). As discussed previously, Ellawala et al. (2012) used Chara fibrosa in their experiments.
They found that δ13C signature decreased with increasing velocity, however this trend was not
consistent (Figure 28). They found a decrease in δ13C signature from 0 cm/s to 0.5 cm/s, but then
the δ13C signature gradually increased from 0.5 cm/s to 2 cm/s. Perhaps if C. fibrosa was studied
at higher velocities an overall positive relationship might occur between δ13C signature and
velocity. As previously discussed, there are differences in the morphology between C. fibrosa
and S. subulta that could affect the boundary layer formation, as well as a difference in the
generation of the velocity between the two experiments, as Ellawala et al. (2012) used isotropic
turbulence. While these discrepancies between this thesis and the work of Ellawala et al. (2012)
might have contributed to the different plant responses, perhaps the most compelling difference
! ! 74! is that the pH of Ellawala et al. (2012) was 7.3 ± 0.1 for their laboratory experiments; i.e., it was
not held above 8.3 to limit availability of CO2 as in this thesis. This would indicate that C.
- fibrosa would not have had to rely solely on the conversion of HCO3 to CO2 in the boundary
layer for use in photosynthesis. This would explain why the response of C. fibrosa differed from
the response of S. subulata, even though the two species are proposed to share similar
photosynthetic pathways.
>15! >17! >19! >21! >23! >25! C&signature&(‰)&&
13 >27! δ >29! >31! 0! 1! 2! 3! 4! 5! 6! Velocity&(cm/s)&
A& S.!subulata! Ellawala!et!al.!2012!
! ! 75! >19!
>21!
>23!
>25!
>27! C&signature&(‰)&& 13
δ >29!
>31! 0! 20! 40! 60! 80! 100! 120! 140! 160! Reynolds&Number& B& S.!subulata! Ellawala!et!al.!2012!
Figure 28: The results of Ellawala et al. (2012) for C. fibrosa compared to the results of this
thesis for S. subulata in terms of both (A) velocity and (B) Reynolds number. The length scale
for Reynolds number calculations was the diameter of the stalk-like segment of C. fibrosa and
the width of a blade of S. subulata. The red lines indicate the trend if the zero values for Ellawala
et al. (2012) was removed.
Effect of Velocity on δ13C signatures of V. americana in the Maitland River ! During both field seasons (2014 and 2015), velocity had a statistically significant effect on the
δ13C signature of V. americana. The effect of velocity was better at explaining the variation in
the δ13C signatures for the 2014 field season than the 2015 field season in terms of R2, however
the data from the 2015 field season included a better representation of the velocity regime in the
macrophyte bed. If the velocity was measured 5 times throughout the 2014 field season, based on
comparisons of the discharge and water level data between the two years, one could predict that
! ! 76! the range of velocities would decrease and be more similar to the average values found in 2015
(Figure 26). Regardless, the field results are consistent with the results of France and Holmquist
(1997) for the seagrass bed not in a mangrove forest. They found a more negative δ13C signature
for macroalgae sampled at the edge of the seagrass bed where there was increased fluid
movement compared to macroalgae sampled from within the seagrass bed (France and
Holmquist 1997).
Importantly, the results of the field study are consistent with the findings for V.
americana in the laboratory experiments. Both show a more negative δ13C signature at faster
velocities, however there was a larger range of δ13C signatures in the laboratory experiments,
which is interesting as the velocity range was also smaller than the field. This discrepancy may
relate to the increased variation in velocity and sources of DIC in the field, which could
minimize the differences in δ13C signatures found compared to the controlled laboratory setting.
The difference in the response of δ13C signature to velocity between field seasons may be
due to the different environmental conditions the plants experienced from year to year. The water
levels and discharge in the Maitland during the summer of 2014 and 2015 were different (see
Figure 16 A and B). In 2014, the water levels fluctuated throughout the course of the summer,
whereas in 2015 the water levels were very high in June (peaking at 2.9 m) and then remained
relatively consistent throughout the rest of the summer. Both seasons had a similar baseline
water level of about 1.90 – 1.95 m, however the highest water level occurred in 2015 in June
since the highest water level in 2014 only reached about 2.55 m. The difference in flow regime
the plants would have experienced could have affected their δ13C signature. Based on field
observations, the macrophyte bed experienced a dramatic decline in the abundance of plants in
the summer of 2015 compared to 2014, which is thought to be a result of an ice scour during the
! ! 77! extremely cold winter months of 2014-15. This may have also affected the δ13C signature if the
remaining plants represented another genet, for example.
Effect of MBL Thickness on δ13C signature in both Field and Laboratory Conditions ! As indicated previously, Smith and Walker’s mechanism is contingent on boundary layer
thickness (dMBL), which is predicted in part by velocity (Eqn (1) - (3)). MBL thickness has a
significant or marginally significant effect on the change in δ13C signatures in both laboratory
experiments and both field seasons, however the direction of this response differed depending on
the species of aquatic plant in the former. It is relevant to note that velocities equal to 0 cm/s
could not be included in the δ MBL comparison, which is one of the reasons the statistical analyses
for MBL thickness yielded slightly different results than the statistical analyses using velocity.
Nishihara and Ackerman (2009) demonstrated that the concentration boundary layer (CBL) and
the diffusional boundary layer (DBL) within it were not constant but decreased in thickness with
increasing velocity; however the CBL was 1/25 the height of the MBL. While the magnitude of
the CBL is smaller than the MBL, the impact of velocity is similar and one would expect the
same trend in δ13C signatures if plotted against CBL thickness.
13 The relationship of the δ C signatures with the δ MBL is revealed in a comparison of the
results from this thesis with those of Ellawala et al (2012) and Trudeau and Rasmussen (2003)
(Figure 29). The δ13C signatures of V. americana sampled in both laboratory and the field and
the periphyton from Trudeau and Rasmussen (2003) all increased with increasing MBL
thickness. Conversely, the δ13C signatures of S. subulata from the laboratory experiments and the
C. fibrosa from Ellawala et al. (2012) decreased with increasing MBL thickness (Note that the
zero values were omitted from Ellawala et al. (2012) for this MBL analysis). While these values
! ! 78! are estimates of the MBL conditions experienced by the plants in these two experiments, they
provide a reasonable value with which to compare the results of this study. It is clear that MBL
thickness affects the δ13C signatures of aquatic plants and that this effect is not consistent across
all primary producers. Smith and Walker’s (1980) mechanism would predict that the δ13C
signatures would increase with increasing MBL thickness; however, as previously discussed, the
type of DIC available to the plants and their respective photosynthetic pathways also play an
important role in the carbon fractionation of aquatic macrophytes.
! ! 79! >15! >17! >19! >21! >23! >25! C&signature&(‰)&& 13
δ >27! >29! >31! 0.1! 1! 10! Log&boundary&layer&thickness&(cm)&
V.!americana!Lab! V.!americana!Field!2014! V.!americana!Field!2015!
S.!subulata!Lab! Ellawala!et!al.!2012! Trudeau!and!Rasmussen!2003!
Figure 29: The effect of MBL thickness on the δ13C signatures of V. americana and S. subulata
in the laboratory and field studies in this thesis and the effect of MBL thickness on the δ13C
signatures of C. fibrosa (Ellawala et al. 2012; note the zero value was not included) and various
species of periphyton (Trudeau and Rasmussen 2003).
! ! 80! Macrophyte Growth ! Generally speaking, velocity should have a positive influence on plant growth, because the
thinner boundary layer at higher velocities would make it easier for nutrients to diffuse into the
plant (Madsen et al. 1993). However, Doyle (2001) found that V. americana plants that were
exposed to higher turbulence due to waves accumulated significantly less mass than plants in low
turbulence areas. They examined a larger range of velocities, with the maximum shear velocity
equal to 1.4 m/s. Madsen et al. (1993) found that increasing velocities from 1 cm/s to 8.6 cm/s
resulted in a decrease in photosynthesis for eight species of freshwater macrophytes but their
growth was not measured (Madsen et al. 1993). Based on the growth measures used in this study,
velocities ranging from 0 cm/s to 5.5 cm/s at a pH > 8.3 did not have an effect on the growth of
V. americana and S. subulata. An effect of velocity on growth may have been discovered if other
measures of growth were analyzed, such as dry weight, however the nature of this study did not
allow for this type of assessment.
Implications ! This research contributes to the understanding of food web dynamics by informing how
environmental conditions can affect the carbon isotope concentration of aquatic plants and how
this varies according to the DIC use of the taxon. Such information would help in reducing the
variation in baseline isotope levels used for an ecosystem study as for example was revealed in
the review by France (1995) who found that the differences in δ13C signatures between pelagic
and benthic producers was also present in the respective consumers. Finlay et al. (1999) also
found that a lower δ13C signature with increasing velocity for algae growing on cobbles was
evident in their invertebrate consumers. The information regarding the δ13C signature of
! ! 81! producers in an aquatic system can be beneficial to understanding the spatial scales of organism
interactions and perhaps even the mobility of predators between different rivers (Finlay et al.
1999). Unfortunately, the results from this thesis indicate that it is not sufficient to simply
incorporate spatial variation in sampling location to adequately incorporate the variation in δ13C
signatures, because the δ13C signature of the producer may vary positively or negatively with
velocity depending on their carbon uptake mechanism. To ensure effective isotope analysis
during food web mapping, the influence of abiotic factors on the isotopic composition of
producer species should be considered, as well as the photosynthetic mechanisms and type of
available carbon. An increased understanding of the mechanisms of carbon uptake by plants is
also important since carbon output by anthropogenic sources is increasing and the need for
reducing its detrimental effects grows.
Based on the results of this thesis, velocity and MBL thickness have a significant effect
on the isotope fractionation and therefore the δ13C signature of aquatic macrophytes. Velocity
explained between 47 % to 77% of the variation in δ13C signatures, based on the R2 values from
the linear regressions conducted for both laboratory and field studies. This effect may also be
dependent on the mechanisms used by the plant to photosynthesize, such as direct uptake of
- - HCO3 or an acidified layer to convert HCO3 to CO2. This thesis also demonstrated that the same
species of plant can have a different δ13C signature depending on the environmental conditions in
which it was grown (i.e., laboratory versus field). For example, the ranges of δ13C signatures that
were found in the laboratory were approximately -15 ‰ to -20 ‰ for V. americana. The range of
δ13C signatures found in the field across both field seasons was -18 ‰ to -24.5 ‰. The δ13C
signatures changed by approximately 5 ‰ when velocity increased from 0 to 5.5 cm/s and they
! ! 82! changed by approximately 2 ‰ when the velocity increased from 0 to 40 cm/s (2014) or 1.5 to
27.5 cm/s (2015).
Conclusions ! This research advanced our understanding of how boundary layer thickness affects carbon
isotope fractionation and the carbon isotope signatures in aquatic systems. The mechanism
proposed by Smith and Walker (1980) was supported by results from V. americana but not from
S. subulata. The different response of S. subulata could be due to a different photosynthetic
- uptake mechanism for HCO3 than V. americana. Based on the results of this thesis, in a
controlled laboratory setting, a change in velocity by about 5 cm/s will result in a change in δ13C
signatures of about 5 ‰. In a more variable field setting, a change in velocity of about 38 cm/s
will result in a change in δ13C signature of about 2 ‰ in a particular year, and 6.5 ‰ over the
two years. Future research should consider both velocity and type of nutrient uptake mechanisms
when analyzing the fractionations of stable isotopes, whether it is at a small/controlled scale
(laboratory) or the larger ecosystem scale.
Research on this subject should not assume that diffusion through the boundary layer is
driving the difference observed in isotope concentrations. This thesis suggests that there are other
possible factors involved that influence the carbon fractionation of aquatic plants, such as
photosynthetic mechanisms and type of DIC available. Both of these factors should be taken into
- account for future studies, which could focus on determining experimentally whether HCO3
uptake mechanisms are responsible for the differences found in the carbon fractionation of V.
americana and S. subualta with respect to velocity. To achieve this, the effect of velocity on
- - carbon fractionation in more aquatic macrophyte species, both HCO3 users and non-HCO3
users, should be examined, while controlling for the type of DIC available to the plants.
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!
! ! 94! Appendix 1: Seachem Flourish Ingredients ! Table 1.A1: The guaranteed analysis of Seachem Flourish, which was used as the plant nutrients
throughout all laboratory experiments. The components were derived from: Potassium Chloride,
Calcium Chloride, Copper Sulfate, Magnesium Chloride, Ferrous Gluconate, Cobalt Sulfate,
Magnesium Sulfate, Manganese Sulfate, Boric Acid, Sodium Molybdate, Zinc Sulfate, Protein
Hydrolysates.
Nutrients Percent
Available Phosphate ( P2O5) 0.01%
Soluble Potash 0.37%
Calcium (Ca) 0.14%
Magnesium (Mg) 0.11%
Sulfur (S) 0.2773%
Boron (B) 0.009%
Chlorine (Cl) 1.15%
Cobalt (Co) 0.0004%
Copper (Cu) 0.0001%
Iron (Fe) 0.32%
Manganese (Mn) 0.0118%
Molybdenum (Mo) 0.0009%
Sodium (Na) 0.13%
Zinc (Zn) 0.0007%
Total Nitrogen 0.07%
! ! 95! Appendix 2: Integrated Velocity Measurement using Plaster of Paris Hemispheres ! Plaster of Paris hemispheres were used to provide a longer-term integrative estimate of velocity.
Commercial grade plaster of paris (DAP, 60-100% plaster of paris, 10-30% limestone, 0.5-1.5%
silica) and DI water were mixed in a 2:1 (volume:volume) ratio (Porter et al. 2000). The
compound was well mixed and poured into a plastic hemisphere mold and tapped on the counter
to remove air bubbles (Jokiel and Morrissey 1993). The mixture was allowed to dry in the mold
for at least 48 hours at room temperature (Jokiel and Morrissey 1993). The hemispheres were
removed from the mold and oven dried for 48 hours at 40 °C (Petticrew and Kalff 1991). Once
dried, any rough edges on the hemispheres were sanded off to ensure a smooth surface.
Hemispheres were weighed to the nearest 0.0001 g and their height and width were measured to
0.1 cm.
Hemispheres were calibrated in a laboratory flow channel (100 cm × 11 cm × 10 cm)
connected to the faucet of the laboratory water tap using a length of polyethylene tubing. An
upstream gate was used to condition the flow and a downstream gate was used to maintain a 7-
cm water depth. The flow conditions in the channel were assessed using sodium fluorescein dye.
One hemisphere was placed in the channel at a time 50 cm downstream of the upstream gate and
was calibrated according to Petticrew and Klaff (1991). Each of three hemispheres were
calibrated for 24 hours at 0 cm/s, 1.26 cm/s, and 2.9 cm/s. The velocities were based on the
average of ten discharge measurements into a 10 L container. Temperature and pH were
monitored with a multiparameter water quality probe (YSI Professional series) and were
maintained at 20 °C, and 8, respectively to maintain a consistent dissolution rate (Petticrew and
Klaff 1991; Jokiel and Morrissey 1993). After 24 hours, the hemispheres were removed from the
! ! 96! flume and dried in the oven for 48 hours at 40 °C. Hemispheres were weighed and their height
and width were measured to 0.1 cm. The gypsum flux (g/(hr cm2)) was calculated for each
hemisphere by the following formula:
Gypsum flux = x/[(2πrh)(t)] (9)
where r is the radius of the hemisphere, h is the height of the hemisphere, t is the time in the
flume and x is the change in weight from the beginning to the end of the calibration. The
relationship between gypsum flux and velocity was analyzed with a linear regression (Figure
1.A2).
0.006!
0.005! &)& 2 cm • 0.004! y&=&0.001x&+&0.0023& R²&=&0.99& 0.003!
0.002! Gypsum&Wlux&(g/h 0.001!
0! 0! 0.5! 1! 1.5! 2! 2.5! 3! 3.5! Velocity&(cm/s)&
Figure 1.A2: The relationship between velocity and gypsum flux for plaster of Paris
hemispheres calibrated at 20 °C.
The hemispheres were attached to plastic cards with waterproof epoxy (LePage; Doty 1971;
Jokiel and Morrissey 1993). The weight of the hemisphere plus the plastic card was recorded
! ! 97! prior to deployment into the field, which occurred at seven quadrats on September 9, 2015. Three
plastic cards were tied to a brick (Figure 2.A2) and one brick was placed at the upstream side of
each macrophyte patch (Quadrats: A1, A7, B7, B17, C1, C2, C3). Ideally, the bricks would have
been left in the river for 24 hours. However, due to high water levels which were unsafe, the
bricks remained in the river for 8 days and therefore the majority had completely dissolved and
could not be used for the analysis. Quadrats C1, C2 and C3 still contained a small amount of
plaster of paris and were used for a purely qualitative assessment.
Figure 2.A2: Photograph of the plaster of paris hemispheres that were deployed into the river.
Results of Plaster of Paris Hemispheres ! The hemispheres collected from quadrats C1, C2 and C3 revealed a difference of velocity
among the sites, with C3 experiencing the fastest velocity and C1 experiencing the slowest
velocity. As illustrated in Figure 3.A2, the hemispheres completely dissolved at quadrats C3 and
dissolved the least at quadrats C1. These values are in agreement with the measured velocities as
the most plaster of Paris remained in the quadrat with the lowest measured velocity and the
plaster of Paris was completely gone in the quadrat with a higher measured velocity. The results
! ! 98! should be considered as primarily qualitative as the plaster of Paris hemispheres were left in the
river for too long. Specifically, Jokiel and Morrissey (1993) state that the clod card, or in this
case plaster of Paris hemispehres, cannot dissolve to less than 30 % of its original weight
because the response is no longer linear. These values correspond to the measured velocities and
the average velocities are as follows: C1 = 1.2 cm/s, C2 = 2.2 cm/s and C3 = 5.6 cm/s.
0.35!
0.3!
0.25!
0.2!
0.15!
0.1!
0.05! Proportion&of&hemisphere&remaining&(%)& 0! C1! C2! C3! Quadrat&
Figure 3.A2: The proportion of the plaster of Paris hemispheres remaining after being deployed
in the Maitland River for 8 days in 2015. The average velocities were: C1 = 1.2 cm/s, C2 = 2.2
cm/s and C3 = 5.6 cm/s.
!
! ! 99!