A Case Study of Salford Quays

Controls on Phytoplankton Community Change in a Redeveloped Freshwater Dock: A Case Study of Salford Quays

A thesis submitted to the University of Manchester for the degree of Ph. D.

in the Faculty of Life Sciences

2014

Robert Philip Mansfield

Contents

Contents ...... 2

Tables ...... 6

Figures ...... 7

Abbreviations ...... 12

Abstract ...... 13

Lay Abstract...... 14

Declaration ...... 15

Acknowledgements ...... 19

1.0 General Introduction ...... 20

1.1 Bottom-up control ...... 22

1.2 Top-down control ...... 26

1.3 ‘Sideways’ control ...... 30

1.4 Management and prediction in freshwater ecosystems ...... 31

1.4.1 Monitoring species invasions ...... 35

1.5 Salford Quays: a highly successful water restoration project...... 37

1.6 Aims...... 44

1.7 Details of each paper ...... 45

1.7.1 Paper 1: Drivers of change in a redeveloped urban dockland: long term trends in a

highly simplified lake system ...... 45

1.7.2 Paper 2: Generalised Additive Models reveal non-linear patterns and novel

associations in a long term lake dataset ...... 45

1.7.3 Paper 3: Multiplex panels of Microsatellite Loci for the Invasive Bivalve Dreissena

polymorpha allow determination of habitat connectivity at multiple spatial scales ...... 46

1.7.4 Paper 4: The spread and effects of the invasive bivalve Dreissena polymorpha in a

restored urban waterway ...... 47

1.7.5 Paper 5: Annual and inter-annual water quality variation in an enclosed dockland

and its relationship to the filter-feeding bivalve Dreissena polymorpha: implications for

future management ...... 48

2.0 Drivers of change in a redeveloped urban dockland: long term trends in a highly simplified lake system ...... 49

2.1 Abstract ...... 49

2.2 Introduction ...... 50

2.3 Methods ...... 54

2.4 Results ...... 58

2.5 Discussion ...... 73

2.6 Acknowledgements ...... 79

3.0 Generalised Additive Models reveal non-linear patterns and novel associations in a long term lake dataset ...... 80

3.1 Abstract ...... 80

3.2 Introduction ...... 80

3.3 Methods ...... 85

3.3.1 Study site & dataset ...... 85

3.3.2 Climatic Variables ...... 85

3.3.3 Analysis ...... 86

3.4 Results ...... 86

3.4.1 Changes in phytoplankton abundance ...... 86

3.4.2 Zooplankton ...... 88

3.4.3 Comparison to other models ...... 90

3.5 Discussion ...... 90

3.6 Acknowledgements ...... 94

3.7 Supplementary data: residual patterns for each GAM model ...... 95

3.7.1 Equation 1 ...... 95

3.7.2 Equation 2 ...... 96

3.7.3 Equation 3 ...... 97

3.7.4 Equation 4 ...... 98

4.0 Multiplex panels of Microsatellite Loci for the Invasive Bivalve Dreissena polymorpha allow determination of habitat connectivity at multiple spatial scales ...... 99

4.1 Abstract ...... 99

4.2 Introduction ...... 100

4.3 Methods ...... 103

4.4 Results ...... 104

4.5 Discussion ...... 109

4.6 Acknowledgements ...... 110

4.7 Supplementary Maps ...... 111

5.0 The spread and effects of the invasive bivalve Dreissena polymorpha in a restored urban waterway ...... 113

5.1 Abstract ...... 113

5.2 Introduction ...... 114

5.3 Methods ...... 118

5.4 Results ...... 121

5.5 Discussion ...... 127

5.6 Acknowledgements ...... 131

6.0 Annual and inter-annual water quality variation in an enclosed dockland and its relationship to the filter-feeding bivalve Dreissena polymorpha: implications for future management ...... 132

6.1 Abstract ...... 132

6.2 Introduction ...... 133

6.3 Methods ...... 138

6.4 Results ...... 141

6.5 Discussion ...... 148

6.6 Acknowledgements ...... 152

6.7 Supplementary data: Tukey HSD tests for significantly different chlorophyll patterns . 153

7.0 General discussion ...... 155

8.0 Further Work ...... 166

Bibliography ...... 169

Word Count: 46407

Tables

Table 1. Phytoplankton functional groupings from Reynolds et al. 2002 ...... 33

Table 2. Dimensions and average surface levels of various water quality variables in each basin of

Salford Quays between 1984 and 1986 (APEM Ltd, pers. comm.). See Figure 11 for basin nomenclature...... 38

Table 3. Major functional groupings identified in SQ as described in Reynolds et al. (2002)...... 56

Table 4. M. aeruginosa abundance in SQ since 2004 organised by colony diameter. Closure occurs when counts exceed World Health Organisation guidelines of over forty 90-200 μm colonies or more than three >200 μm colonies. Dashes indicate no data collected...... 67

Table 5. Best fit given by GAM models with one to four variables and their linear (Lin.) equivalents. GAM fits are given as s(variable), other variables have been fitted linearly. chl=chlorophyll a. Plots of residual patterns are given in 3.7...... 87

Table 6. Loci and primers used in panels with original characteristics given. MP – Multiplex identifier, Rep – repeat motif, H0/He – observed and expected hetereozygsity, Ref – reference. 1:

Feldheim et al. (2011), 2: Naish & Boulding (2001; Corr. 2011), 3: Thomas, Hammouti & Seitz

(2011)...... 105

Table 7. Selected significant changes and their magnitude in meta-analysis of zebra mussel infected sites, * indicates insufficient data, a value insignificant at P=0.052 owing to wide variation in data (Higgins and Vander Zanden 2010) ...... 135

Table 8. Functional groups seen in SQ over this study and their descriptors (Reynolds et al. 2002)

...... 140

Figures

Figure 1. Idealised annual succession in temperate lakes of different trophic state, after De

Senerpont Domis et al., (2012) and Sommer et al., (2011) ...... 21

Figure 2. Community changes over a seasonal cycle in a 'standard' meso/eutrophic deep temperate lake system (Sommer et al. 1986) ...... 22

Figure 3. Seasonal stratification in a temperate lake that freezes in winter, known as dimictic stratification (Hutchinson 1957). Layers are: light blue: fully mixed, blue: epilimnion, purple: metalimnion, dark blue: hypolimnion...... 25

Figure 4. pH-CO2-CaO relationship in natural waters, from Reynolds (2006). Changes in the concentration of any one compound will affect the equilibrium...... 26

Figure 5. Decision tree of phytoplankton species development from the end of winter (red). Green circles indicate constant picoplankton dominance and letters indicate overall survival strategy. C:

Competitive; R: Ruderal; S: stress resistant. Adapted from plots in Reynolds (2006)...... 27

Figure 6. Effect of Dreissena spp. on energy flow within a freshwater ecosystem. Green lines indicate increases in abundance following establishment while red indicate decreases. After

Higgins & Vander Zanden (2010) ...... 30

Figure 7. Alternate stable states in lotic systems adapted from Scheffer et al. (1993)...... 31

Figure 8. The Manchester Docks in 1970 and 2009 with key areas of interest labelled. Note the surface contamination in both turning basin and docks in 1970...... 39

Figure 9. Location of sloped walls in the smaller basins of SQ and internal structure of affected basins, other walls are vertical. Maximum water depth is 8m and width (east to west) varies with basin, proceeding left to right maximum width is 66 m, 56 m and 102 m while maximum height

(north to south) is 67 m for all basins...... 39

Figure 10. Representation of a Helixor mixing system, based on Williams et al. (2010) ...... 40

Figure 11. Map of the old Manchester docks and the modern SQ in, respectively 1970 and 2009

(Source: Edina Digimap) ...... 41

Figure 12. Timeline of key changes in SQ over the past 25 years ...... 42

Figure 13. Manchester Ship Canal and Salford Quays, showing the location of sample sites (white circles). The site of D. polymorpha introduction is marked by x. Adapted from Williams et al.

(2010)...... 52

Figure 14. Structure of triangles used in Reynolds habitat template. Each point relates to both a growth strategy (vis. Figure 5) and a point in yearly succession...... 58

Figure 15. Trends for each variable in SQ. Points indicate a reading and line LOESS line of best fit with standard error shown as grey shaded area...... 63

Figure 16. Important variables for the Manchester Ship Canal immediately adjacent to SQ. Points indicate a reading and line LOESS line of best fit with standard error shown as grey shaded area.64

Figure 17. Proportional area plot of contribution of each functional group to total phytoplankton biomass in SQ with cluster boundaries (as found in Figure 19) indicated (vertical lines)...... 65

Figure 18. Proportional area plot of contribution of each family to total zooplankton abundance in

SQ with cluster boundaries (as found in Figure 19) indicated (vertical lines)...... 66

Figure 19. NMDS plot of the algal communities in SQ. Shading indicates temporal position from

1992 to 2010 (see scale, right) and symbols denote cluster number. Ellipses denoting standard deviation of each cluster are overlaid and labelled as A: pre-2001 (amalgamation of 3 Planktothrix dominated clusters), B: 2001-2005 and C: 2005-2010...... 68

Figure 20. Vectors describing the measured variables in SQ fitted over the NMDS cluster ellipses given in Figure 19 (note amalgamation of first 3). Zooplankton vectors (daphnia, bosmina, calanoids, cyclopoids and total zooplankton; * denotes cladoceran, absence copepod groups) were fitted separately to reduce the influence of the sampling gap on the other variables and, with the exception of total zooplankton were treated as proportion of total community to reduce the effect of overall abundance change...... 69

Figure 21. Vectors describing the functional groups in SQ fitted over the NMDS cluster ellipses given in Figure 19...... 70

Figure 22. Habitat template for phytoplankton species assemblages in SQ (after Reynolds 2006

(Table 3) but using groupings found in this study). Triangles are obtained by joining the

8 representative taxa of that period. Broken line indicates initial grouping, solid line intermediate and triple line recent period. Y group purposely absent, as in original plot...... 71

Figure 23. Representation of GAM fit method. GLM regressions representing straight lines (red) are connected by non-linear GLMs (blue) to allow matching to any underlying trend (black).

Dashed lines indicate 95% confidence intervals...... 84

Figure 24 GAM relationships within the dataset with 95% confidence intervals (dotted lines).

Linear terms are given by: Intercept -1.16, PAR coefficient: 1x10-3 and TN coefficient: 0.519 ...... 87

Figure 25. Seasonal pattern in PAR for these data. No significant annual trend exists (see 2.0). .... 88

Figure 26. Predictions of chlorophyll a for 2003 using model 4 with 95% CI given and compared to both real values and predictions of different lake models (note only able to predict maximum production over growing period). Lake model regression equations taken from: A – (Vollenweider

1976), B – (Dillon and Rigler 1974), C – (Phillips et al. 2008), D – (Prairie et al. 1989) ...... 89

Figure 27. Locations of sample sites (yellow) and sites of initial invasion in the UK (red)...... 101

Figure 28. Graph of sample sites within SQ (red pins), identified by letter (A-F). Sample sizes: A: n=31, B: n=30, C: n=32, D: n=43, E: n=16, F:n= 23...... 102

Figure 29. PCR conditions for microsatellite amplification in this study...... 103

Figure 30. Cumulative frequencies of allele sizes for each viable locus studied. Shading indicates alternate alleles...... 106

Figure 31. DAPC plot of D. polymorpha with sites indicated, 95% ellipses plotted and eigenvalues given...... 107

Figure 32. DAPC plot of populations within SQ grouped by sample site. Ellipses give inertia and overlap indicates similarity ...... 108

Figure 33. DAPC plot of populations within SQ, clustering of individuals determined without priors.

Ellipses give inertia and overlap indicates similarity...... 108

Figure 34. Smaller scale map of differentiation between sites 1 and 2 with direction of likely gene flow indicated ...... 111

Figure 35. Smaller scale map of differentiation between sites 3 and 4 with direction of likely gene flow indicated ...... 112

Figure 36. Diagrammatic representation of SQ showing basin names and volumes and transect locations for the 2010 survey (dark blue dots). The spot of initial D. polymorpha introduction is marked by X...... 117

Figure 37. Box and whisker plot of D. polymorpha size distribution in each basin of SQ from the

2010 dive survey. Box indicates median and interquartile range, whiskers are given by the most extreme data point within one inter quartile range, notch overlap indicates similarity (Chambers et al. 1983)...... 121

Figure 38. Mussel density with depth for each dive transect of the 2010 survey ...... 122

Figure 39. Mussel size distribution in 2000 and 2010 ...... 123

Figure 40. Filtration rates and standard deviation for mussels at 15 mm (squares) and 22 mm

(diamonds) for different algal groups. Data from Bellamy (1997) are denoted by triangles. Low density Chlamydomonas and Planktothrix filtration rates (starred) were significantly different from one another but within these pairs mussel sizes were not significantly different ...... 124

Figure 41. Mussel spat settlement over time in Ontario basin in 2010 ...... 125

Figure 42. Filtration rates obtained at various temperatures and LOESS line of best fit with 95% confidence interval shown ...... 126

Figure 43. Chlorophyll a and proportion of water column filtered by zebra mussels day-1 of each basin in SQ over 2010. Note the chlorophyll sampling frequency is monthly and temperature measurements weekly. Chlorophyll data provided by APEM Ltd...... 126

Figure 44. Diagrammatic representation of the Basins within SQ with minimum turnover time due to D. polymorpha filtration (see Chapter 5.0). Site names and locations are also shown...... 138

Figure 45. Chlorophyll concentrations (points) and LOESS smoothed trends for the three dock

Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown 141

Figure 46. Zooplankton filtration (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown ...... 142

Figure 47. SRP (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown. Line indicates approximate level of limitation at 5μg l-1 (Reynolds 2006) ...... 143

Figure 48. Si (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown ...... 144

Figure 49. D. polymorpha filtration (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown ...... 145

Figure 50. Changes in phytoplankton functional groups in the three dock basins over a full annual cycle in 2010 and 2011. Normalised trend in chlorophyll is overlaid as a loess smoothing (from

Figure 45). White line indicates M. aeruginosa bloom detection...... 146

Figure 51. Changes in zooplankton functional groups in the three dock Basins over a full annual cycle in 2010 and 2011. Normalised trend in overall zooplankton filtration is overlaid as a LOESS smoothing (from Figure 46). White line indicates M. aeruginosa bloom detection...... 147

Figure 52. Montezuma’s Well, Arizona, USA. The lake is fed by a number of underground springs that prevent stratification (Boucher et al. 1984) ...... 157

Abbreviations

ABI – Applied Biosystems NMDS – Nonmetric Multidimensional Scaling

AIC – Akaike Information Criterion OECD – Organization for Economic

Cooperation and Development ATU – allylthiourea

PAR – Photosynthetically Active Radiation APEM – Recursive acronym

PCR – Polymerase Chain Reaction BOD – Biological Oxygen Demand

SNP – Single Nucleotide Polymorphism CASE – Collaborative Awards in Science and

Engineering SQ – Salford Quays

DIN – Dissolved Inorganic Nitrogen SRP – Soluble Reactive Phosphorus

DNA – Deoxyribonucleic Acid SS – Suspended Solids

EA – Environment Agency TN – Total Nitrogen

EU – European Union TP – Total Phosphorus

FAM, VIC, NED, PET – Florescent primer UK – United Kingdom labels for molecular analysis US – United States

GAM – Generalised Additive Model VIF – Variance Inflation Factor

GLM – Generalised Linear Model WFD – Water Framework Directive

MSC – Manchester Ship Canal YSI – Yellow Stone Instruments

NERC – Natural Environmental Research

Council

Robert Philip Mansfield, University of Manchester, 2013: Controls on Phytoplankton Community Change in a Redeveloped Freshwater Dock: A Case Study of Salford Quays. For the degree of PhD.

Abstract Salford Quays were created from the highly polluted Manchester docks after their closure in 1984. In order to make use of the potential for an attractive waterside location in the centre of Greater Manchester, it was decided to redevelop the area for commercial, recreational and residential use. This involved isolating and artificially mixing the docks and instigating a series of management interventions, including the introduction of fish, macrophytes and the invasive filter- feeding bivalve Dreissena polymorpha. The positive results of these interventions are clearly visible in modern day Salford Quays (SQ) which now provides a home to several thousand people, office and retail space, a site for water sports activities and the location of the new BBC Media City. Despite this success the precise drivers of environmental improvements and the extent to which each intervention has contributed to restoration has proven elusive. Therefore further investigation is warranted, not only to inform future water quality management but also to determine the ecosystem processes involved and to increase our understanding of how lentic ecosystems function.

Restoration of SQ has been accompanied by intensive monitoring of water quality and ecology from 1984 to the present day. The resulting dataset has been analysed to examine the relationships between the physiochemical environment, management and phytoplankton community structure using a combination of non-linear regression and ordination techniques. This has explained the patterns behind the change from Planktothrix agardhii dominated eutrophy to the clear waters of the present day and indicated the importance of nutrient control and D. polymorpha filtration on past and present ecosystem function. This study has demonstrated how useful non-linear approaches are to the study of ecology and a strong case has been made for their incorporation into future analysis.

To quantify the effects of the introduced D. polymorpha population, further data were collected on their spread and effects on the SQs ecosystem. Using the limited past data available, plus a full scuba dive survey in 2010 and ex situ lab experiments on filtration rate it has been possible to quantify their effect on the phytoplankton communities and show that mussels are likely a significant controlling factor in all basins except the larger, Huron basin where populations remain inexplicably low. In parallel a new molecular method has been developed to chart the spread of D. polymorpha both around SQ and in new areas via a 9 loci microsatellite multiplex to assess both historic effects and the potential for future dispersal.

Finally, a high resolution, multi-parameter dataset was collected over 2010/2011 to determine the current seasonal patterns in biological and physiochemical environment in SQ. It has shown the overwhelming influence of D. polymorpha to the annual and inter-annual variation in water quality and plankton ecology and, when combined with molecular analysis, shows the possible implications of their use in water management.

This thesis will serve to broaden our understanding of freshwater ecology and will prove especially useful in future management projects, especially in relation to other artificial waterways and lake systems.

Lay Abstract

Manchester docks were responsible for much of the areas early success by allowing oceangoing ships direct access to the city’s many industries. Today the docks have been renamed Salford

Quays and are home to the Lowry, BBC Media City and a large number of flats and houses. This change has taken a great deal of time and money as when the docks were closed in 1984 they were one of the most polluted areas of water in the country. They have had to be isolated, continuously mixed and many new plants and animals have had to be added to create the crystal clear waters that we see today. Unfortunately we were not sure exactly how each change had affected the environment within the Quays and how we could repeat this success elsewhere.

To solve this problem we have looked at how the area has changed using the thirty years’ worth of data collected during this transformation. This has been used to explain how changes in plant nutrients and grazers first of all caused large problems to water managers but now help to keep the water clear and attractive.

We have also studied how an invasive species, the zebra mussel, has changed how the modern

Salford Quays work and if they have been important in past improvements. In doing so we have shown how they are currently working as a very effective filter to keep the quays clear and also how they may have started to spread to other areas in the northwest.

This work will help to guide future management of the Manchester Ship Canal, as well as other polluted lakes and slow flowing rivers across the UK. It will improve the value and attractiveness of other inner city waters and show people how invasive species like zebra mussels can alter how a lake works.

Declaration

No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

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To future generations

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I hope this helps

Those who have knowledge, don't predict. Those who predict, don't have knowledge.

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Acknowledgements

Many people have served as either a mentor or an inspiration during my time at Manchester. Chief among them is my supervisor, Keith White who early on forgave me for my lack of interest in football and taught me how to be an academic, both professionally and personally. My Advisory team have been equally vital to completion of this project and as such I would like to thank Keith Hendy and Adrian Williams for their honest advice, assistance and opportunity to be part of the fast moving world of environmental management, at least when I had time! My academic advisor Richard Preziosi has also been a great help to my project, despite my near constant pestering!

I wish to thank Amanda Bamford, Roland Ennos and Cathy McCrohan who, despite not being members of my supervisory team, have been a constant support and valued friends during my PhD. The other PIs at Manchester who have been part of my journey are almost too numerous to name and I worry if I start I may accidentally miss someone, suffice to say you know who you are and you have my respect, gratitude and pipetting arm should you ever need it.

I would never have made it through my first few months without the help and support of Katie Woodburn and Andrew Dean. You were then and remain now an exemplar of the kind of scientist I want to be and I will miss you greatly in the future. I also want to thank Nate Truelove and the rest of the molecular biology crew who showed me how cool their work is and how chance meetings can have exciting, and productive, outcomes. Finally thanks to the others that have been part of my past (and I hope future) journey: Dave Armson who kept me sane and helped me think, Adam van Casteren who went closed source despite my sincerest efforts, Ellen Forty who pulled me out of my shell, the biomechanics group for always making me smile and plant sciences for welcoming me, despite my ignorance of pretty much every technique they use!

I do not think my academic education would have been complete without the many students that have crossed my bench over the course of my studies. The optimism, determination and scientific skill were inspirational and I hope I managed to share with you at least a little of how fun (and tedious!) this profession can be. It is true that if one wishes to fully understand a subject they must teach it and I hope I didn’t blind you with too much stats. I would also like to list our two newest lab mates: Cecilia Medupin and Ismael Alkhamaisie. You have certainly made the last 12 months interesting and I continue to be impressed by your intelligence, determination and amazing progress. I wish you all the best for the rest of your PhDs.

I would like to thank my family for their application of proper support when needed and willingness to let me learn for myself when I had to. I hope it wasn’t too rough on you! My mum, Celia for everything she did to get me to Manchester. My dad, Steve who may have beaten me to a PhD by 6 months but at least it was in social science. I am indebted to him for letting me break his computer every weekend for 13 years and for reminding me there are better other ways to look at a problem than those I’m used to.

Finally, thanks to my wife who has shared many of the ups and downs of this journey with me. Thanks for giving me a reason to carry on when times were tough and for having patience when I had none. Even 46438 words do not seem like enough.

19 Chapter 1: General Introduction

1.0 General Introduction

Freshwaters are host to a third of all vertebrate species and 10% of total animal diversity, despite accounting for only 1% of Earth’s surface area and 0.0091% of total water volume (Strayer and

Dudgeon 2010). Standing (lotic) waters form a key part of the freshwater hydrosphere and provide habitats for both terrestrial and aquatic species. Lakes also have substantial anthropogenic use, not only as a source of potable water but for recreation, agriculture, transport, coolant and waste disposal. Such a wide range of uses provides ample opportunity for damaging effects to occur and pollution problems are not uncommon (Moss 2010). Owing to the vulnerability and value of freshwater ecosystem services it is vital that effective methods of management and restoration be established; but to accomplish this requires a better understanding of lake ecosystem processes.

Excluding terrestrial carbon inputs and lakes where macrophytes dominate (see 1.3), the primary producers in lake environments are the phytoplankton (Scheffer et al. 1993). Owing to their small size and fast reproduction rates they respond rapidly to changes in external conditions – both bottom-up (e.g. nutrients, light or stratification) or top-down (grazing by organisms such as zooplankton; Reynolds, 2006). The action of top-down control through invertebrate grazers forms the basis for a large part of the aquatic food web, resulting in a number of ecosystem level effects and feedback mechanisms (Perrow et al. 1999). The relative importance of both controls is thought to be the cause of the seasonal succession seen in many systems (Sommer et al. 1986) although the exact mechanisms involved are poorly understood (Zhao et al. 2008). Figure 1 summarises the key patterns in lake phyto- and zooplankton populations over a yearly cycle and at different trophic states.

In mesotrophic temperate systems that are sufficiently deep to allow thermal stratification, annual phytoplankton production is separated into several phases (Sommer et al. 1986; Figure 1 and Figure 2): initially environmental limitation (light and temperature) creates a winter period of

20 Chapter 1: General Introduction low production; this is followed by a spring bloom governed by available nutrients and increasing light and temperature; a clear water phase is then instigated by grazing pressure and summer stratification; a second autumnal bloom is caused by starvation of grazers and water column overturn in the autumn; and finally a return to the winter phase results from falling temperatures and light intensity and duration.

Figure 1. Idealised annual succession in temperate lakes of different trophic state, after De Senerpont Domis et al., (2012) and Sommer et al., (2011)

Each period is typified by a certain community structure dictated by trophic state, lake type and local geography. The commonly held successional pattern for temperate, deep, mesotrophic water bodies is given in Figure 2. Changes are primarily due to variations in stratification, grazing and nutrient limitation over the yearly cycle. There also are various effects of changes in nutrient regime; a highly eutrophicated system for example will have a greatly reduced clear water phase and larger cyanobacteria or cryptophyte population while an oligotrophic system will have low

21 Chapter 1: General Introduction chlorophyll production throughout and abundance of picoplankters, chrysophytes and other species adapted to survive low resource availability (Reynolds et al. 2002). Therefore by monitoring bulk abundance and species composition it is possible to make inferences about the nutritional state of an ecosystem, its mixing regime and levels of grazing by zooplankton or bivalve molluscs (Reynolds 2006).

Figure 2. Community changes over a seasonal cycle in a 'standard' meso/eutrophic deep temperate lake system (Sommer et al. 1986)

1.1 Bottom-up control

While able to refer to any environmental limitation, bottom-up control is usually used to explain limitations in nutrient availability, a factor that varies with the species present (Reynolds et al.

2002). Of particular importance is the ability of many cyanobacteria to produce heterocysts that fix atmospheric N, and the demand for Si in diatoms (Reynolds 2006); indeed it is often the requirement for soluble Si in the form of silica that is the cause of the collapse of the spring diatom bloom (Sommer et al. 1986). In addition, species that are adapted to low nutrient environments may be able to actively promote nutrient uptake, utilise unusual sources or engage in ‘luxury uptake’ during nutrient excess that may then be able to sustain a number of subsequent generations (Reynolds 2006). The principal limiting nutrients in the majority of freshwater systems are nitrogen and phosphorus which are required in a stoichiometric ratio of approximately 106:16:1 (C:N:P; Redfield, 1934) for optimum survival and reproduction. Limitation

22 Chapter 1: General Introduction of algal density through other elements such as iron or molybdenum has also occasionally been recorded but this appears to be the exception in freshwater environments (Reynolds 2006). When these nutrients are in excess, limitation will usually be created by the availability of light due to self-shading or oxygen due to respiration (Reynolds 2006).

Increases in the availability of nitrogen and phosphorus are the principal causes of water quality decline in human impacted systems (Jørgensen et al. 2004). Sources are generally agricultural fertilisers, sewage and industrial wastes, all of which are also frequently associated with other potentially harmful compounds such as pesticides, hormones and particulate matter (Schindler

1977; Jørgensen et al. 2004). Sustained increases in levels of N and P will likely lead to cyanobacterial blooms, as will increases in P alone due to the ability of cyanobacteria to fix atmospheric nitrogen (Fogg et al. 1973). Such a change is frequently seen in enriched systems and was a frequent occurrence in the Norfolk Broads before restoration work was undertaken

(Madgwick 1999). As there is no equivalent source of phosphorus to the freshwater environment, increase in N alone will not usually lead to algal problems but in older lakes or those that have a history of high phosphorus inputs, there will be substantial P stores in the sediments (Hutchinson

1969). These are gradually released at a rate determined by temperature, composition and redox potential (Sondergaard et al. 2003) with negative values increasing the release of phosphate and metals as soluble ions are produced (Gambrell et al. 1991; Sondergaard et al. 2003). In some situations the growth of anaerobic algae and gas production may combine to cause large ‘rafts’ of sediments to float to the surface while decomposing (Williams et al. 2010). Such conditions are a serious problem in lakes and depositional rivers worldwide (Smith et al. 1999) and frequently promote dense growths of often toxic cyanobacteria (Cooke and Kennedy 2001).

There are a number of remedial approaches to nutrient enrichment problems. Removal of the sediments is possible but both are often difficult and expensive. It also presents the environmental problem of disposal of material that may be contaminated with other waste products such as trace metals (Jørgensen et al. 2004). Alternatively, oxygen levels can be

23 Chapter 1: General Introduction maintained through artificial mixing to reduce the release of phosphorus. It is also possible to treat the effects of increased nutrient load through manipulation of the ecosystem itself; principally through effects upon the phytoplankton (see 1.3).

Local climate has a marked effect on phytoplankton community dynamics (Reynolds 2006), most notably by the combined effect of sunlight duration and intensity (hence temperature and energy availability) and low wind causing the water column to stratify, an event that usually happens biannually in temperate lakes (Hutchinson, 1957; Figure 3). During stratification, the hypolimnion will be entirely isolated from the atmosphere and thus able to deoxygenate, a process that is greatly enhanced if a large amount of dissolved or particulate organic matter such as leaf litter or sewage is present to undergo decomposition. The epilimnion by comparison will be highly oxygenated but have no access to the nutrient stores present in the sediments and thus may exhibit a reduced ability to sustain algal production (Hutchinson 1957). Such a situation promotes species such as cyanobacteria and flagellates which are better able to regulate their buoyancy and thus take advantage of both the high nutrients of the hypolimnion and the high light, high oxygen environment found at the surface (Reynolds et al. 2002). The collapse of this stratification will have the effect of promoting less buoyant species such as diatoms and supply high nutrient water to the otherwise limited surface waters. The sudden increase in nutrients is the primary cause of the spring and autumn blooms seen in temperate systems, although the former also requires an increase in light intensity and temperature (Sommer et al. 1986).

Ambient temperature will, as with all ectothermic organisms, determine the rate of chemical reactions and thus growth, movement and grazing rates (Davenport 1991). Local climate will determine the amount of light available for photosynthesis (measured as Photosynthetically

Active Radiation; PAR) and thus maximum attainable primary productivity (Edmondson 1956). The availability of sunlight to the water column is linked not only to the seasonal and longitudinal position of the lake but also to the amount of matter in suspension (Liboriussen and Jeppesen

2003). Large amounts of algae, soil, sewage or other particulates can limit light availability at

24 Chapter 1: General Introduction depth and absorption of radiation at the surface will cause heating, altering growth rates and overall production.

Carbon availability in water is strongly associated with ambient pH (Figure 4; Moss, 1998).

Dissolved CO2 is easily obtained and metabolised but its removal will cause an increase in pH and

- a preponderance of HCO3 which only a few species are able to utilise. At excessively high pH,

2- carbon is mainly present as CO3 which is unavailable for use. This presents an interesting feedback mechanism in that, at high alkalinities, C becomes increasingly difficult to obtain while as phytoplankton utilise C, local pH levels increase. The magnitude of this effect is also related to the local geology; lakes in limestone areas for example are buffered from achieving highly acidic pH values, while lakes around bogs and coniferous woodland may have an increased acidity caused by inputs of humic substances (Battarbee and Howells 1990). Decreases in pH may also result from anthropogenic variables such as acid rain (Battarbee and Howells 1990).

25 Chapter 1: General Introduction

Figure 4. pH-CO2-CaO relationship in natural waters, from Reynolds (2006). Changes in the concentration of any one compound will affect the equilibrium.

Oxygen limitation may have a marked effect on phytoplankton dynamics. During times of high algal biomass, the requirements of cells for oxygen during nocturnal respiration may outstrip supply, leading to anoxic conditions and mass mortality of many aerobic organisms in the lake

(Baldwin and Whipple 1906). Such effects can also be seen during the day as a result of stratification or if phytoplankton, usually buoyant cyanobacteria, are able to reach sufficient densities to self-shade. In such situations, decomposition of algae killed by light limitation and UV radiation leads to an increased oxygen demand, anaerobic decomposition and production of noxious gases such as methane and hydrogen sulphide (Fogg et al. 1973).

1.2 Top-down control

The efficacy and mode of feeding displayed by primary consumers can have marked effects on the composition, cell size and density of the phytoplankton community (Reynolds 2006). Pressure by some filter feeders such as Daphnia spp. may select for larger or filamentous algae that are less easily grazed but this may in turn create a selective pressure for raptorial copepods or rotifers

26 Chapter 1: General Introduction able to handle such species (Reynolds 2006). In addition, high densities of zooplankton may increase the effect of bottom-up limitation through sequestering nutrients (Loladze et al. 2000).

Figure 5. Decision tree of phytoplankton species development from the end of winter (red). Green circles indicate constant picoplankton dominance and letters indicate overall survival strategy. C: Competitive; R: Ruderal; S: stress resistant. Adapted from plots in Reynolds (2006)

Like phytoplankton, zooplankton form part of a yearly cycle, exhibiting a lagged relationship to phytoplankton biomass similar to the classic Lotka-Volterra relationship (Figure 1); see also

Sommer et al., 1986). Indeed, the clear water phase is usually created and maintained by the large numbers of zooplankton that are produced during the spring bloom with a similar, less pronounced pattern occurring in the autumn. The correlation between the annual cycle of zooplankton and phytoplankton respectively is a strong regulator of overall species composition

(Figure 5; see also Reynolds, 2006).

27 Chapter 1: General Introduction

Meroplanktonic species such as fish are also often important to succession by both competing with and predating on zooplankton species. The latter of these controls is especially important towards the autumn when fish fry mature to the point where their size and zooplanktivorous diet may cause a substantial reduction in zooplankton abundance (Sommer et al. 1986). Intensive predation will remove the larger, more energetically favourable zooplankton leaving smaller, less efficient species that would otherwise be outcompeted (Brooks and Dodson 1965). Many species of fish will retain a zooplanktivorous diet for their whole lives and if not controlled by piscivores exert a constant pressure that will lead to large population fluctuations across both trophic levels

(Shapiro and Wright 1984). This relationship can be used as a method of water management through manipulation of the fish community (Shapiro and Wright 1984). For example, if increased numbers of piscivores are added to an ecosystem then zooplantkivore abundance will decrease, causing a concurrent increase in zooplankton grazing and a reduction in phytoplankton abundance. While temporary, such biomanipulation can create an increase in amenity and ecological value or create a more permanent shift in stable state (see 1.3) to occur (Shapiro and

Wright 1984).

Grazers upon the phytoplankton (and the smaller zooplankton) are not limited to other planktonic species. Filter feeders such as bivalve molluscs also exploit the algal community and compete with zooplankton for resources (Kryger and Riisgård 1988). While many species of bivalve filter-feed and hence will impact on the plankton community, one of the most infamous is the zebra mussel,

Dreissena polymorpha which is listed as one of the 100 most damaging invaders on the planet

(Lowe et al. 2000). Owing to their planktonic dispersal (unusual in freshwater molluscs) and ability to colonise any available hard surface, they are able to reach sufficient densities to exert a significant effect upon the aquatic environment (Nalepa and Schloesser 1993) via grazing.

Although impacts are focused primarily upon the phytoplankton on which they subsist there are significant effects upon the whole aquatic food web (Figure 6; Higgins & Vander Zanden, 2010).

The basic principle upon which this operates is the transfer of both energy and nutrients from the

28 Chapter 1: General Introduction water column to the sediments, causing a reduction in pelagic and an increase in benthic productivity (Nalepa and Schloesser 1993).

Such is the effect of D. polymorpha that many invaded systems have gone through a process of oligotrophication, despite continued nutrient inputs (Cha et al. 2013). This ability led to interest in using D. polymorpha as a remedial intervention for poor water quality in the 1980s (Reeders and

Bij de Vaate 1990), an idea gradually abandoned as the dangers of biological control became evident. It was found that non-target effects such as cyanobacterial blooms could develop and that increases in propagule pressure could cause colonisation (or more rapid recruitment) in nearby ecosystems (Higgins and Vander Zanden 2010). This was especially evident in the Great

Lakes of North America, for example, in Lake Michigan a dramatic decline in phytoplankton production led to a reduction in Diporeia spp. by two orders of magnitude. Diporeia was a previously abundant grazer that formed the basis for a large proportion of the food web. An increase in the proportional abundance of grazing resistant cyanophytes was also noted (Evans et al. 2011). Despite this, the use of the zebra mussels in biocontrol has recently been the subject of renewed debate (Mclaughlan and Aldridge 2013), especially as concerns regarding their ability to promote toxic species has proved largely unfounded, provided nutrient levels remain elevated

(Sarnelle et al. 2012). However known effects on phytoplankton species distribution include a general trend of reduction in all communities with the possible exception of cyanophytes, a shift to smaller, fast reproducing flagellates and a selection against larger, energetically favourable eukaryotic species such as Cryptomonas and Pediastrum that produce polyunsaturated Fatty

Acids (PUFAs), a valuable food resource for higher trophic levels (Wacker and Von Elert 2003;

Higgins and Vander Zanden 2010).

29 Chapter 1: General Introduction

Figure 6. Effect of Dreissena spp. on energy flow within a freshwater ecosystem. Green lines indicate increases in abundance following establishment while red indicate decreases. After Higgins & Vander Zanden (2010)

1.3 ‘Sideways’ control

Phytoplankton may not be the only primary producers of an aquatic ecosystem. Macrophytes may also occur in shallow systems where sufficient light will reach the substrate (Scheffer et al. 1993).

This creates competition for energy and soluble nutrients that frequently means only one group dominates, owing to a number of stabilising mechanisms (Figure 7). In order to force a change in stable state to one dominated by phytoplankton, a large degree of anthropogenic disturbance

30 Chapter 1: General Introduction must take place or a high-intensity natural event (Scheffer et al., 1993). To change the system back to macrophyte dominance invariably requires management interventions such as the addition of reed beds (promote grazers and compete with phytoplankton) or barley straw

(produce of natural algaecide) (Garbett 2005), or manipulation of fish communities (see 1.2).

Figure 7. Alternate stable states in lotic systems adapted from Scheffer et al. (1993).

1.4 Management and prediction in freshwater ecosystems

Decreases in the quality of freshwater ecosystems over the 20th century have led to a number of laws concerning their use and management. The Law on Prevention and Control of Water

Pollution in China, Australia’s National Water Quality Management Strategy and the EU Water

Framework Directive (WFD) are all examples of this shift in environmental attitudes in recent years. In order to achieve these goals however, a proper understanding of the target ecosystem is required so as to understand not only its current and ‘natural’ state but also to properly direct management efforts, a process that can be decidedly complex (e.g. Devlin et al. 2007).

31 Chapter 1: General Introduction

The WFD is most relevant to this UK-based study and specifies that ecosystems must be returned to a state before they were impacted by man by 2015. This requires the establishment of indicator species and physiochemical assessment processes to measure impacts. Among these indicators, phytoplankton have found a role owing to their diversity and rapid adaptation to changing environmental conditions (Hutchinson 1961; Reynolds et al. 2002). Indeed it is usually relatively simple to detect the presence of elevated nutrient levels through the increased incidence of algal blooms and cyanobacterial species. Such changes also result in a serious loss of amenity and environmental value through, for example, anoxia and toxin production (Fogg et al.

1973). As such their monitoring and modelling are essential to the management of both natural and artificial standing waters. Reynolds et al. (2002) provide an excellent example of such a scheme by giving each functional grouping a letter code relating to their environmental tolerances

(Table 1). This is an example of a number of useful categorisations Reynolds has produced (e.g.

Figure 5) and has thus been used throughout this project.

32 Chapter 1: General Introduction

Table 1. Phytoplankton functional groupings from Reynolds et al. 2002 ID Habitat Typical representatives Tolerances Sensitivities

Clear, well-mixed, base poor, Urosolenia, Cyclotella Nutrient A pH rise lakes comensis deficiency Vertically mixed, mesotrophic Aulacoseira subarctica, pH rise, low Si, B Light deficiency small-medium lakes Aulacoseira islandica stratification Mixed, eutrophic small- Asterionella formosa, Light, C Si exhaustion C medium lakes Aulacoseira ambigua deficiencies stratification D Shallow, enriched waters Synedra acus, Nitzschia Flushing Low nutrients Tabellaria, Cosmarium, Nutrient Stratification N Mesotrophic epilimnia Staurodesmus deficiency pH rise Fragilaria crotonensis, Mild light and C Stratification Si P Eutrophic epilimnia Aulacoseira granulata deficiency depletion Geminella, Mougeotia, Nutrient T Deep, well-mixed epilimnia Light deficiency Tribonema deficiency Highly light Planktothrix agardhii, Mixed Lakes S1 Turbid mixed layers deficient Flushing Limnothrix redekei conditions Spirulina, Arthrospira, Light deficient S2 Shallow, turbid mixed layers Flushing

Raphidiopsis conditions Synechococcus, Light deficiency Z Clear, mixed layers Low nutrient prokaryote picoplankton grazing Chrysococcus, eukaryote X3 Shallow, clear, mixed layers Low base status Mixing, grazing picoplankton Shallow, clear mixed layers in Plagioselmis, Mixing, filter X2 Stratification meso-eutrophic lakes Chrysochromulina feeding Nutrient Shallow mixed layers in Chlorella, Ankyra, X1 Stratification deficiency filter enriched conditions Monoraphidium feeding Y Usually, small, enriched lakes Cryptomonas Low light Phagotrophs! Small, oligotrophic, base poor Dinobryon, Mallomonas Low nutrients E CO2 deficiency lakes or heterotrophic ponds (Synura) (mixotrophy) Low nutrients, F Clear epilimnia Colonial Chlorophytes CO2 deficiency high turbidity Short, nutrient-rich water Nutrient G Eudorina, Volvox High light columns deficiency Shallow, enriched lakes Pediastrum, Coelastrum, Settling into J - ponds and rivers Scenedesmus low light Aphanothece, K Short, nutrient-rich columns - Deep mixing Aphanocapsa Dinitrogen-fixing Anabaena flos-aquae, Low nitrogen low Mixing, poor H1 Nostocaleans Aphanizomenon carbon, light, low P

Summer epilimnia in Stratified Lakes U Uroglena Low nutrients CO2 deficiency mesotrophic lakes Mixing, poor LM Dielly mixed layers of small Ceratium, Microcystis Very low C, stratification light Metalimnia of mesotrophic Microcystis, Flushing, low M High insolation lakes Sphaerocavum total light P. rubescens, P. Low light, strong R Metalimnia of mesotrophic Instability mougeotii segregation V.low light, strong V Metalimnia of eutrophic Chromatium, Chlorobium Instability segregation Shallow mesotrophic lakes bottom-dwelling W2 ? ? small humic lakes Trachelomonas Q Small humic lakes Gonyostomum High colour ?

33 Chapter 1: General Introduction

Setting restoration targets can be greatly assisted by the ability to predict how a system may respond to a given nutrient regime. Early attempts utilised linear models to relate phytoplankton to nutrient or predator load (Vollenweider 1968, 1976; Dillon and Rigler 1974) and a review of such models and their applicability is provided in Phillips et al. (2008). There are limitations to such an approach however; chief among them is the variable nature of aquatic ecosystems

(Phillips et al. 2008). This can make precise predictions extremely difficult and requires that one only applies models that were validated upon similar lake environments (Phillips et al. 2008). The classic example of this is the limitations inherent in the original Vollenweider (1976) equations which were formulated on data collected in North America and thus of limited utility in European ecosystems. Further to this (and often ignored in the literature) is the limitations of linear regression itself (Zuur et al. 2007). Errors include a lack of appreciation for spatial and temporal autocorrelation, no analysis of residual error and the use of log-log relationships (e.g. Seip et al.

2000; Havens & Nürnberg 2004; Phillips et al. 2008) which can increase error, inflate p-values and create incorrect associations (Zuur et al. 2007). This is aside from the limitation introduced by forcing an environmental pattern to a linear relationship which, especially for seasonal data, may be a large oversimplification. This problem is exemplified by the issues associated with interpreting long term temperature patterns where there may be a powerful seasonal component as well as a decadal trend (Wood 2006).

The development of more general models of phytoplankton productivity, able to describe ecosystem processes rather than relationships is a more recent development (Jørgensen 2010). Of particular note owing to its success is the PROTECH model (Reynolds, Irish, & Elliott, 2001). This assumes phytoplankton productivity defaults to the maximum attainable in laboratory culture but is then adjusted for species sinking rates, volumes and nutrient utilisation. It can also use simple stratification equations to create a well validated model of up to 10 individual phytoplankton species (Reynolds et al. 2001). This model has been extensively used (C.300 papers as of Aug

2013; Google Scholar) but despite its development by a public body, it is not available to most

34 Chapter 1: General Introduction researchers or water managers on account of both cost and intellectual property rights, which has limited its usefulness to studies such as those undertaken here. Environmental models can subsequently be linked to physical ones that describe processes such as mixing, as is the case for

CAEDYM/DRYSEM (Bruce et al. 2006), although this development has recently also become closed source.

1.4.1 Monitoring species invasions

With a problem as pervasive as invasive species there are insufficient resources to monitor all vectors at all times. Indeed, there is a substantial difficulty even in the early detection of invaders in many ecosystems owing the level of sampling effort required to detect a small population

(Estoup and Guillemaud 2010). Unfortunately, once an organism is established it can often be difficult to determine the source population, especially when long distance anthropogenic vectors are suspected (Estoup and Guillemaud 2010).

There has thus been much interest in posteriori methods for vector determination and also in determining if any allopatric processes are underway within known populations (Estoup and

Guillemaud 2010). The advent of modern molecular methods has provided an ideal tool for such studies and a number of techniques are now available of varying resolution, cost and reliability

(Selkoe and Toonen 2006; Gardner et al. 2011). Most rely on the measurement of random genetic drift between two or more populations using non-coding regions of DNA known as neutral markers (Pearse and Crandall 2004). Coding regions are substantially less effective as they are subject to selection which may alter mutation frequencies between sites for reasons other than geographic isolation. These may also correct random mutations that have a negative effect on fitness and thus disguise population isolation (Frankham et al. 2010; Gardner et al. 2011).

Microsatellites are highly popular in this regard as their use is relatively cheap once they have been identified, they are abundant in most eukaryotic genomes, have high resolution and can also be used to determine relatedness between individuals or even historic population size (Selkoe and Toonen 2006). Microsatellites comprise short chains of nucleotide patterns 1-6 bases

35 Chapter 1: General Introduction repeated between 5 and 40 times (Li et al. 2002) and are thus extremely susceptible to slippage during replication resulting in a highly variable yet inheritable length that can be detected by sequence weight rather than base composition (Goldstein and Schlotterer 1999). By using a number of such markers it can be possible to determine not only habitat connectivity between multiple areas but also direction of gene flow within as few as 10 generations (Schlötterer 2000).

Such work is not without its limitations however, for example, mutations in flanking regions can prevent amplification. This makes many microsatellites highly species specific (Selkoe and Toonen

2006)and in the case of some taxa finding reliable markers that amplify for all individuals within a species can be highly problematic, a problem that is especially prevalent in some marine invertebrates (Cruz et al. 2005), lepidopterans (Meglecz et al. 2004) and birds (Primmer et al.

1997). Such mutations can prevent amplification in an individual or an allele, a problem known as null-alleles (Paetkau and Strobeck 1995).

Microsatellite analysis also presents the possibility that two differing mutations will yield alleles of a similar length, hiding the true population structure in an event known as homoplasy (Selkoe and

Toonen 2006). Interference can also be introduced by the location of an individual microsatellite marker on a chromosome which may create an increased (or decreased if near important coding regions) possibility of exchange through crossover or of mutation. Individually this is of little concern as variability in mutation rates is to be expected, however, if the mutation rates of two or more loci are not independent (i.e. they come from similar areas of the same chromosome) then so called linkage disequilibrium may have taken place which will bias any conclusions (Selkoe and

Toonen 2006). Such an occurrence can make an individual appear homozygous, an excess of which in a population suggests emigration, immigration or other population level processes that can confound analysis; a violation of Hardy-Weinberg equilibrium (Frankham et al. 2010).

Many of these problems are shared by other molecular markers (Sunnucks 2000; Avise 2004;

Selkoe and Toonen 2006) and the ubiquity of molecular methods in modern biology means there are a number of tools for determination of the errors outlined above (Selkoe and Toonen 2006).

36 Chapter 1: General Introduction

Despite these drawbacks their utility and ease of use make microsatellites an excellent choice for determination of population processes, especially when resources are limited. The other main choice for studies on invasion vectors is usually Single Nucleotide Polymorphisms (SNPs) which utilise single base substitutions in non-coding regions of DNA, they do, however require the use of next-generation sequencing technology which can be prohibitively expensive (Frankham et al.

2010).

1.5 Salford Quays: a highly successful water restoration project

Many cities in the UK and elsewhere possess canals, wharfs and docklands constructed to facilitate the transport goods during the industrial revolution. Most were built between 1760 and

1830 by private investors (Holland and Andrews 1998) and were only large enough for inland barges. Others, constructed later, had sufficient depth to accommodate ocean going vessels, perhaps best exemplified by the Suez and Panama Canals. The Manchester Ship Canal (MSC) is one such construction and was built in the 1890s to connect Greater Manchester to the Mersey

Estuary and thus the open sea. This greatly decreased the cost and complexity of moving raw materials and manufactured goods between the city’s burgeoning industries and the world market and greatly aided Manchester’s continued economic success (Gray 1999). Despite early problems with profitability, the MSC became the third largest port in the UK by the mid-1950s

(Williams et al. 2010) but their success was paralleled by numerous water quality problems. The

MSC and its tributaries were subject to sewage inputs from the cities of Manchester and Salford, waste from the cities’ many industries including from the extraction of metals (e.g. chromium and iron), various hydrocarbons, soaps and dyes (Gray 1999). Discussion with previous dockworkers by the author has revealed anecdotal reports of foaming, bright colour changes and a petrol spillage in the 1970s that led to the water surface catching fire. Despite high nutrient inputs algal blooms were not a major feature of the system owing to the large amount of suspended solids in the water column. Unfortunately the high biological component of these inputs did lead to near

37 Chapter 1: General Introduction continuous anoxia which was only worsened by permanent stratification caused by steep, mostly vertical walls, flat bottom and sheltered location of the dock basins (Table 2).

Table 2. Dimensions and average surface levels of various water quality variables in each basin of Salford Quays between 1984 and 1986 (APEM Ltd, pers. comm.). See Figure 11 for basin nomenclature.

Perim. Vol. O Nitrate Ammonia BOD + ATU Phosphate 2 pH (m) (m3) (%) (µg/L) (µg/L) (mg/L) (µg/L) St Louis 251.7 14197 59.3 10.0 897.5 1540.0 2.0 207.3 Ontario 687.3 133868 64.7 7.9 2221.0 4212.8 2.7 892.0 Huron 1329.7 310997 42.3 7.2 2244.0 4976.7 3.0 971.0

In the latter third of the 20th Century the size of shipping increased and the UK began to trade preferentially with Continental Europe. This, plus various other socio-economic factors, caused the docks to cease being profitable and they were eventually closed in 1984 (Gray 1999). This closure led to a large area of derelict industrial land that was quickly earmarked for regeneration.

Although initial proposals included the suggestion that the docks should be filled in it was decided that redevelopment should take advantage of the area’s waterside location. This provided an attractive inner-city environment and the possibility for high value housing and commerce, an excellent solution to the large problems of unemployment and economic decline in the Greater

Manchester area during the 1970s and 1980s (Bellinger et al. 1993). In order to maximise this potential, the docks (renamed Salford Quays in 1986) had to be managed to improve the poor water quality. Salford Quays (hereafter SQ) were therefore isolated from the polluted waters of the MSC (Figure 8) and all storm drains diverted to prevent further inputs of nutrients or organic matter. One dock was also divided into three to maximise potential real estate, creating a number of sloped walls Figure 9. Stratification was prevented by the inclusion of several Helixor mixing systems (Figure 10 and Figure 11) which allowed the water to naturally circulate and thus oxygenate via entrainment of oxygen from the atmosphere (Williams et al. 2010). In order to allow access by boat traffic a small double lock system was installed (width 7.5m), and the enclosed docks were linked by small (width 10m) canals (Figure 8).

38 Chapter 1: General Introduction

Figure 8. The Manchester Docks in 1970 and 2009 with key areas of interest labelled. Note the surface contamination in both turning basin and docks in 1970.

39 Chapter 1: General Introduction

Figure 10. Representation of a Helixor mixing system, based on Williams et al. (2010)

40 Chapter 1: General Introduction

Map of the old Manchester docks and the modern SQ in, respectively 1970 and 2009 (Source: Edina Digimap) 2009 and 1970 Edina (Source: respectively SQ in, modern the Manchester and old the Mapof docks

. .

Figure Figure

41 Chapter 1: General Introduction

Several environmental management projects were undertaken following isolation and artificial mixing (Figure 12). A number of fish introductions were carried out to enhance biodiversity and remedy the unsightly stickleback (Gasterosteus aculeatus) die offs caused by lack of top-down control. The introductions proved highly successful and a self-sustaining fish population now exists in SQ (White et al. 1993; Williams et al. 2010). A continual programme of habitat diversification has also been undertaken involving the addition of macrophytes to not only increase biodiversity and aesthetics but also to attempt to force a change in stable state. It is also worth noting that macrophytes have also naturally colonised SQ (Figure 11) such that in several basins numbers now require annual control (Williams et al. 2010).

Figure 12. Timeline of key changes in SQ over the past 25 years

D. polymorpha were introduced into the quays in the early 1990s in a controlled experiment to remediate the Planktothrix agardhii blooms that became a feature of the system (see Figure 12).

The limited available evidence suggest that they had not been able to establish a large population in SQ until after 2000 and were absent from all but a few areas. More recently, anecdotal reports and regular invertebrate samples have suggested a population explosion but the reasons for this remain uncertain (APEM pers. com). With the increasingly low nutrient levels present in the system, zebra mussel may be contributing to Microcystis aeruginosa blooms now prevalent in the autumn (Figure 12) and the extremely clear waters now present in the area during the remainder of the year. It is unclear as to the reasons and timing of the mussel’s delayed population increase and if the delay is due to poor founder effects and inbreeding (since remedied by a second accidental introduction event) or to the shallower adjoining canals preventing rapid colonisation

42 Chapter 1: General Introduction of adjacent basins. Determination of current densities is also required in order to ascertain if D. polymorpha’s filtration capacity is sufficient to affect current biological and physiochemical parameters, as predicted by Higgins (2010; Figure 6).. Answering this question will also inform the future water management uses of this organism in highly polluted waterways (Mclaughlan and

Aldridge 2013).

Today SQ is a notable commercial success and is home to a theatre, shopping centre, numerous office and flat complexes and the new BBC Media City. This success is an excellent example of the value for urban waterside regeneration in any system and is an exemplar for other artificial and natural urban systems.

Over the course of restoration, SQ has been subject to a near continuous monitoring program, managed principally by the environmental consultancy company APEM Ltd who are also responsible for the water quality and ecological management of the area. Data have been collected from the isolated and open basins plus the MSC on an almost monthly basis since 1986.

This has created a unique dataset covering almost 25 years and presents an exceptional opportunity to document and interpret the changes that have taken place in an artificial and heavily managed ecosystem. This study will analyse past, present and future trends in water quality in a restored industrial dockland with a specific emphasis on the shifting patterns of phytoplankton community and abundance.

The final outputs of this study will therefore have wider relevance to other canal systems, including the MSC which continues to be improved and managed (Williams et al. 2010). The results will also provide more than just a study of SQ; the system represents an idealised macrocosm with a cuboid shape and constant mixing regime. As such, the amount of variation in parameter relationships is minimised and the effect of different changes should be easier to infer while also elucidating the patterns of seasonality and biotic/abiotic interactions in such a system.

43 Chapter 1: General Introduction

1.6 Aims

There are a number of aims to the papers in this thesis but all are related to the understanding of past, present and potential future environmental trends in SQ. The specific aims are therefore:

1. Examine the process of restoration within the quays and how shifts in species assemblages can be linked both to changes in the external environment and new management practices. 2. Determine which physical, chemical and biological variables have been most instrumental in the reduction of overall chlorophyll abundance over the past 25 years. 3. Evaluate the effectiveness of current linear models in predicting chlorophyll levels in SQ and if necessary suggest improvements. a. It is hypothesised that the area’s differing hydrology to natural systems will require a different modelling approach b. Lessons learned will nonetheless be of great value to understanding other lake systems. They will point to patterns that are indicative of features such as stratification and littoral processes and their relationship to ecosystem structure and dynamics. 4. Determine the effect of the introduced D. polymorpha population on the past and present water quality and ecology in SQ. a. In addition I will examine if D. polymorpha have diverged from their site of introduction in 1992 and what their current population density and effects are. b. I will also seek to determine basin connectivity and whether there is any evidence of immigration/emigration of D. polymorpha to and/or from other populations. It is hypothesised that a single population of D. polymorpha exists in SQ and that it has remained isolated from other populations due to impoundment. 5. Describe the current seasonal succession of both the physical environment and plankton community in SQ and suggest future directions for habitat management, both locally and in the adjacent Manchester Ship Canal. This will provide a model ecosystem for the restoration of other highly artificial waterways and suggest how such ecological improvements can be achieved in the future with the most efficient use of time and resources.

44 Chapter 1: General Introduction

1.7 Details of each paper

While there are five separate aims to this thesis, they clearly separate into three separate strands:

1) Analysis of past data (1984-2010) provided by APEM Ltd, 2) Collection and analysis of weekly field data from SQ (2010-2012), 3) enumeration, genotyping and assessment of the resident D. polymorpha population. This has resulted in five papers which are presented here under the alternative submission format.

1.7.1 Paper 1: Drivers of change in a redeveloped urban dockland: long term trends

in a highly simplified lake system

This paper is an analysis of phytoplankton community change over the course of the restoration in

Salford Quays. This paper utilises the wealth of physical and biological data on the quays to identify the main phases of restoration using a combination of NMDS and cluster analysis of phytoplankton functional groupings correlated to linear vectors of major top-down and bottom- up controls. It serves more of a case study of restoration in a highly artificial freshwater environment than a direct attempt to answer ecological hypothesis, however, this is an essential first step in the determination of the processes of restoration in SQ. In addition there is a clear benefit to understanding how phytoplankton communities behave in such a highly simplified system when important controlling factors such as stratification and littoral areas are absent. It is also the first stage in evaluating the scale of D. polymorpha effects upon the environment in SQ, with the acceptance that only inferential data are available for much of this period.

This paper is currently unpublished but submitted to Fundamental and Applied Limnology and I am the sole contributor to all work described in this paper although I gratefully acknowledge the contributions of a number of proof readers and my advisory team.

1.7.2 Paper 2: Generalised Additive Models reveal non-linear patterns and novel

associations in a long term lake dataset

The wealth of data available for SQ necessitated learning various new data analysis methods.

Attempts to relate the system to the relationships published by previous authors (e.g. Dillon &

45 Chapter 1: General Introduction

Rigler 1974) were only useful in certain systems, situations and seasons. This was largely due to the relatively simple approaches used that have largely been outdated by modern methods yet little work has been done to see how new approaches may alter our understanding. I have attempted to remedy this here by relating chlorophyll production to 4 separate variables using a combination of non-linear modelling techniques, post-hoc tests and residual analysis to describe the patterns seen in SQ. The specific hypotheses to be tested were that the changes in SQ were only related to reductions in nutrient availability and that the artificial nature of SQ would confound standard analysis and modelling techniques. In answering these I also sought to provide an example of ‘best-practice’ in modern analysis of ecological data and show the utility of non- linear approaches to environmental data.

This paper is currently unpublished but under review with The Journal of Ecology and I am the sole contributor to all work described in this paper although I gratefully acknowledge the contributions of a number of proof readers and my advisory team.

1.7.3 Paper 3: Multiplex panels of Microsatellite Loci for the Invasive Bivalve

Dreissena polymorpha allow determination of habitat connectivity at multiple

spatial scales

As previous work had made it apparent that there was a correlation between the modern environment in SQ and the increase in D. polymorpha population density it was decided that a deeper analysis of their population dynamics was needed. As such a multi-loci microsatellite panel was produced to discover what the habitat connectivity between basins was like and if the small adjoining canals were a barrier to population spread. Should this be the case then it would explain why there were low densities of zebra mussels in the Huron Basin as opposed to the alternative hypothesis that there were differences in environmental parameters that had not been detected or measured. In order to show the utility and validity of these panels, D. polymorpha were obtained from a separate site along the Bridgewater Canal in Warrington, UK and also from a collaborator in Catalan, Spain who provided samples from three sites, two clearly connected by a

46 Chapter 1: General Introduction single river and a third in a separate drainage basin. The hypothesis for this work was that each basin within SQ was largely isolated from colonisation by planktonic larvae with only the occasional introduction. Further to this it was hypothesised that the Salford and Warrington populations were also broadly isolated owing the separation of Salford Quays from the main Ship

Canal and that the UK and Spanish populations had no gene flow. Within Spain there was expected to be high connectivity between the close sites owing to their connection by a main river and that the third site was isolated from that to a greater extent than the Warrington and

Salford populations.

This paper is currently unpublished but under review with the Journal of Molluscan Studies and I am the sole contributor to all work described in this paper although I gratefully acknowledge the contributions of a number of proof readers and my advisory team and N Truelove for methodological assistance.

1.7.4 Paper 4: The spread and effects of the invasive bivalve Dreissena polymorpha in

a restored urban waterway

As the population in Salford Quays was shown to be a single entity and ubiquitous in all but Huron basin a more in depth investigation into their densities and seasonal effects was undertaken. Dive survey data collected in 2010 were combined with ex situ filtration rate experiments and estimation of re-filtration rates to determine the overall filtration capacity in each basin under different temperature regimes. This would allow the establishment of when low temperature suppression of filtration ceased and if high temperature suppression was present. These data could then be correlated to monthly measures of chlorophyll abundance collected by APEM Ltd to assess if there was a relationship between filtration and phytoplankton abundance. The main hypothesis to test was that algal biomass was severely limited by D. polymorpha abundance in all but the Huron Basin and that in highly colonised areas they were approaching carrying capacity.

As with papers 1 and 2 this also provided an opportunity to see the effects of this variable on the

47 Chapter 1: General Introduction highly simplified system of SQ and thus infer the main controlling variables in the absence of stratification or large littoral areas.

This paper is currently unpublished and I am the sole contributor to all work described in this paper although I gratefully acknowledge the contributions of a number of proof readers and my advisory team as well as E Hammond who assisted in practical work.

1.7.5 Paper 5: Annual and inter-annual water quality variation in an enclosed

dockland and its relationship to the filter-feeding bivalve Dreissena

polymorpha: implications for future management

By combining data on D. polymorpha filtration with new, weekly field data on the physical and biological situation in SQ it was possible to test the hypothesis that both annual and seasonal variation in the environment in SQ was due to variations in filtration capacity and population density. This analysis could then be compared between the basins to assess the effect of the various differences between each. That is the smaller surface area to volume ratio in St Louis, the largely homogeneous environment of Ontario, or the Huron Basin which was largely devoid of zebra mussels. It was hypothesised that both Ontario and St Louis would be broadly similar but the magnitude of D. polymorpha effects would be affected by the differing availability of colonisable substrate and sediment loading between the two. It was also hypothesised that Huron would have a more ‘normal’ temperate seasonal cycle, reminiscent of a mesotrophic water body and that between year the infested basins would alter their susceptibility to mussel filtration as the relationship between overall abundance and carrying capacity changed.

48 Chapter 2: Long term trends in SQ

2.0 Drivers of change in a redeveloped urban dockland: long term

trends in a highly simplified lake system

R. Mansfielda*, A. Williamsb, K. Hendryb, K. Whitea a: University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. b: APEM Ltd, Riverview, A17 Embankment Business Park, Stockport, SK4 3GN.

* University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. [email protected], Tel: 00447811363408

2.1 Abstract

Shallow urban lakes are inherently variable due to their unpredictable mixing regime and so present a number of challenges to water managers seeking to improve water quality. Salford

Quays (8.14 ha, depth=6.6m), Greater Manchester, UK is an example of a managed artificial moderately deep urban water body that provides a number of ecosystem services, including increased property prices, attractive commerce location and increased aesthetic and recreational value. In the past the condition of the area was very different and the area was designated one of the most polluted areas of water in the UK. Here we examine the long-term dataset (1985-2010) associated with restoration and document changes of several orders of magnitude in both phosphorus and chlorophyll a. Three distinct phases of phytoplankton community succession were identified over the restoration period: cyanobacterial dominance, an abundance of larger chlorophytes and finally a preponderance of r-selected taxa such as nanoplankters and cryptomonads. We show that these phases relate to changes in limitation from photolimitation to a likely increase in zooplankton grazing and, finally, the combined effects of low nutrients and filter feeding by the invasive bivalve Dreissena polymorpha. Owing to water column mixing and the lack of a littoral zone Salford Quays will be relatively unaffected by confounding variables such as stratification and therefore offer an insight into the processes of community change in similar

49 Chapter 2: Long term trends in SQ artificial and heavily modified natural systems elsewhere. In addition the Quays offer an excellent case study of urban water management and serve as an example both of best practice and a target ecosystem to direct the restoration of other urban waterways.

2.2 Introduction

Changes in nutrient composition are a major influence on lake phytoplankton community structure (e.g. Phillips et al. 2008). Anthropogenic activities usually lead to increases in nutrient concentration and can pose a threat to natural biodiversity (Hutchinson 1969). For this reason there are a number of both national and international moves to control further ecosystem damage and, in many cases, to restore degraded ecosystems in the face of continued exploitation

(e.g. Australia’s National Water Quality Management Strategy, China’s Law on Prevention and

Control of Water Pollution and the EU Water Framework Directive). Unfortunately, reductions in nutrient inputs alone may not produce the desired effects as local climate and hydrology will have a marked effect on species composition (Reynolds 2006) and thus a deeper understanding of community processes is required. The phytoplankton is also influenced by the wider community; for example macrophyte colonisation will increase both competition for light and grazing

(Scheffer et al. 1993), filter feeding bivalves can reduce total algal biomass and selectively promote some phytoplankton (Higgins and Vander Zanden 2010) and fish may alter grazer abundance and increase nutrient mobility (Williams and Moss 2003). In light of these issues, and to conform to the demands of new legislation there is a need for a greater understanding on how these processes interact.

Over the course of their natural evolution, standing waters are typically subject to a gradual increase in nutrients with a concurrent increase in productivity (Hutchinson 1969). While this may take hundreds to millions of years to complete, anthropogenic changes may be wrought over much shorter timescales. Anthropogenic nutrient addition, principally of nitrogen and phosphorus through organic pollution and agriculture, may lead to marked changes in primary production and thus the whole ecosystem (Hutchinson 1969). In addition, measures of the ratio between these

50 Chapter 2: Long term trends in SQ two elements can provide further insight into the controls acting on primary production (Downing and McCauley 1992). Added pressures of invasive species, fish management and removal of littoral vegetation can further degrade an ecosystem leading to loss of biodiversity and amenity value (Jørgensen et al. 2004).

The presence of many interacting variables can make identification of underlying lake processes, and hence management, difficult (Gulati et al. 2008). Shallow lakes are particularly variable owing to their polymictic nature and lower thermal capacities (Reynolds 2006) and are therefore difficult to manage and conserve. Valuable microcosm (McKee et al. 2003) and mesocosm (Moss et al.

2004) work has been undertaken but their ability to aid restoration is limited due to the atypical size/shape and the relatively short duration of most studies. The restoration of Salford Quays (SQ;

Salford, UK; Figure 13) provides a unique opportunity to study the consequences of lake restoration on a macro scale yet with the absence of variables such as polymixis and littoral processes that are difficult to quantify. In this study we identify key drivers of phytoplankton community change in SQ with the aim of better understanding controls on phytoplankton biomass in temperate standing waters.

51 Chapter 2: Long term trends in SQ

Figure 13. Manchester Ship Canal and Salford Quays, showing the location of sample sites (white circles). The site of D. polymorpha introduction is marked by x. Adapted from Williams et al. (2010).

Salford Quays (SQ) were originally constructed as part of the Manchester Ship Canal (MSC), an ambitious project to allow ocean-going ships direct access to the Greater Manchester area from the Irish Sea (Gray 1999). Although originally open to the canal, the docks (renamed Salford Quays in 1989), are now a small (total area of 8.14 ha), moderately deep (6.6m) artificial lake system which has been totally isolated from both the MSC, only receiving inputs from precipitation and the rare operation of a double lock system (Williams et al. 2010). There have been a number of milestones over the course of restoration (Figure 12). Isolation of the all but one dock (which is not considered in this study) occurred between 1986 and 1988 and involved the construction of large bunds at the entrance to each. This was accompanied by the division of one dock into three smaller basins, resulting in new internal walls being sloped (Figure 9) and the construction of shallow (Zave=2m) adjoining canals which allow movement of both water and biota. Shortly after isolation Helixor mixing systems were installed to artificially circulate the water through submerged air jets. The purpose of which was to prevent stratification and hence anoxia (Williams et al. 2010), and to promote an oxidised surface layer on the sediments to reduce release of

52 Chapter 2: Long term trends in SQ phosphorus and heavy metals (Bellinger et al. 1993; Sondergaard et al. 2003; Williams et al.

2010).In the 1980s the biodiversity of the MSC and SQ was extremely low. There was a limited plankton community and pollution tolerant benthic fauna. Only two fish species were present:

Gasterosteus aculeatus (three-spined stickleback) and Rutilus rutilus (Roach); and these were subject to large fluctuation in numbers due to the absence of predation (Bellinger et al. 1993). In order to increase biodiversity, additional 12,000 l fish consisting of Roach (Rutilus rutilus), Rudd

(Scardinius elmaliensis), Bream (Ballerus ballerus), Carp (Cyprinus carpio), Chub (Squalius cephalus), Dace (Leuiscus sp.) and Perch (Perca flavescens) were introduced to the isolated basins in 1988 and 1989 with smaller introductions of the same species over subsequent years. Although there was little subsequent monitoring, data that are available show they subsequently displayed some of the fastest growth rates in the UK and displayed low levels of metal build up due to reduced mobilisation from the now oxic sediments (Williams et al. 2010). Macrophytes (rush

Scirpus albescens and water lily Nymphaea alba) were introduced to the smaller basins and several floating islands provided habitats for waterfowl and refuges for fish fry and invertebrates, including zooplankton. By 2003 other macrophytes such as Elodea nuttallii (western waterweed),

Nitella mucronata (stonewort) and Ceratophyllum demersum (hornwort) had colonised naturally

(Williams et al. 2010) and subsequent prolific growth has necessitated the periodic removal of macrophyte stands so that water-based leisure activities can continue. A number of small cages of

Dreissena polymorpha (zebra mussels) were introduced into the Quays in 1994 (location shown in

Figure 13) as a pilot trial to assess their ability to control the burgeoning Planktothrix agardhii population. These cages consisted of fifteen 75x25 cm Maritime Mussel Mesh (MA40) bags containing a total of 750 individuals between 20-25 mm in length within one of the small connecting canals (W M Bellamy Unpubl.)

Although there has been substantial decreases in phytoplankton biomass, autumnal blooms of the toxic cyanophyte Microcystis aeruginosa occurred between 2004 and 2010 (Williams et al.

53 Chapter 2: Long term trends in SQ

2010), with densities often sufficient to force the temporary closure of the water sports centre established in 2001.

The creation and subsequent restoration of SQ offers a unique insight into controls on phytoplankton community in a previously nutrient-rich and organically polluted urban standing water. Owing to their largely vertical sides, uniform habitat and managed mixing regime, the quays allows us to examine community succession in a relatively homogeneous environment at the macroscale using a long-term data set. In this study we identify key drivers of phytoplankton community change in SQ with the aim of better understanding controls on phytoplankton biomass in temperate standing waters. The specific aims are to evaluate the role of changing nutrient availability and the mixing regime in controlling phytoplankton community structure, and to evaluate if D. polymorpha may be affecting the current phytoplankton community. In addressing these aims we will identify key drivers of the changing community structure and hence provide insights into the reasons for the current favourable water quality and ecology in SQ. We anticipate that our findings will add to our understanding of temperate standing waters and inform water quality and ecological management of both artificial and natural systems elsewhere.

2.3 Methods

Data have been collected by APEM Ltd since 1991 from the sites indicated in Figure 13. Some earlier periods have been marked by reduction in sampling frequency to quarterly observations but all sites from 2002 have been sampled on a monthly basis (n=231) based on a 28 day sampling schedule (n=231). Although some scant records exist before 1991 these have not been used in this study owing to their non-continuous nature and unusual environmental conditions caused by the volume of concrete used during isolation. The data analysed include measurements of phytoplankton and zooplankton densities as well as temperature, oxygen, total phosphorus (TP), total nitrogen (TN), Helixor operation, chlorophyll a, pH, Secchi depth and invertebrate counts from the three sites shown in Figure 13. As these variables are co-linear between basins and all sampling sites were of identical habitat (edge of basin against a wall with depth 7-8m) they have

54 Chapter 2: Long term trends in SQ been averaged to remove the danger of pseudoreplication (Hurlbert 1984) and also to provide an overview of habitat changes with the minimum of confounding variables.

Nutrient analyses were conducted on samples of both surface and bottom (within 1 m of sediment layer) waters. TP and TN were digested and analysed colorimetrically using standard methodology (EA 1981, 1992). Temperature and oxygen profiles at metre intervals were obtained using either a Hydrolabs Multiparameter Sonde or an YSI ProPlus field meter.

Phytoplankton were enumerated using the Utermöhl settlement method. Fourteen millilitres of surface water was collected, fixed with Lugol’s iodine and allowed to settle in a chamber before enumerating on an inverted microscope, thus allowing inclusion of picoplanktonic species (EA

1990). Data were transformed to biovolume estimates based on average sizes and shape approximations of Reynolds and Bellinger (1992), Stephen (1997) and A Dean (pers. comm.) and were assigned functional groups based on Reynolds, Huszar, & Kruk (2002; Table 1). This metric allowed the classification of species by size and environmental preferences (Table 3; Figure 22). In some cases where identification to species were not possible, the range of possible groupings were used; for example Cyclotella spp. Could have referred to a number of diatom type groupings so were simply labelled as such (A-C). This approach also helped to control for between observer variation by amalgamating questionable species classifications and records where an estimate of size could not be made.

55 Chapter 2: Long term trends in SQ

Table 3. Major functional groupings identified in SQ as described in Reynolds et al. (2002).

ID Environmental preference Representative taxa A Spring Diatoms of increasing (A to C) trophic state, generally found in B Cyclotella, Stephanodiscus well mixed lakes. Increasing tolerance of light deficiency A to C C Diatoms and desmids found in low levels of available CO2 and higher P Staurastrum nutrients (thus more resistant to low light), sensitive to stratification X1 Picoplanktonic species of decreasing (X1 to X3) trophic state, generally X2 sensitive to filter feeding and mixing. Plagioselmis X3 Cryptomonads, broad range of conditions but sensitive to phagotrophs Y Cryptomonas and other grazers. Tolerant of low light. Mixotrophs generally found in oligotrophic to mesotrophic F Oocystis environments with higher light levels Larger chlorophytes found in more eutrophic shallow lakes, sensitive to J Pediastrum settling into low light, therefore also to stratification Nitrogen fixing cyanobacteria that dominate in high phosphate, low H nitrate environments. Adapted to survive both stratification and low Anabaena light

Three metre zooplankton vertical net trawls were counted under a dissecting microscope.

Combined numbers of cladocerans, copepods and total zooplankton were also used in these analysis but rotifers were not routinely monitored and are thus excluded.

Zebra mussel abundance has not been routinely quantified, however, an inference of population density is possible by utilising the presence of spat in benthic invertebrate coloniser units (designs following Czerniawska-Kusza 2004). These were sampled monthly for benthic invertebrates but were useful in that they allowed a settlement surface for young mussels. They were thus included in invertebrate counts and provided an excellent inference of propagule pressure and thus population density.

Dive survey data were obtained by APEM Ltd in 2000 and 2010. The former survey was conducted

2 using a 4608 cm quadrat placed at depths of 1, 2, 3 and 4 m at 10 m intervals across all dock walls except those in Huron Basin (Figure 13), this gave a total replicate number of 35 transects, each of

4 quadrats, totalling 140. Zebra mussel counts were conducted by touch owing to low visibility.

The 2010 survey utilised the same dive company as 2000 and was conducted using a 1 m2 quadrat

56 Chapter 2: Long term trends in SQ

at depths of 1, 3, 5, 7 m (or at Zmax if sediment build up prevented a 7m quadrat) givng a total replicate number of 28 (Figure 36). Counts were conducted by visual counting of photographs owing to increased water clarity.

Data analyses were conducted on R (v2.13.1) utilising three dimensional Nonmetric

Multidimensional Scaling (NMDS) on square root transformed species abundance data using the

Vegan package (v2.0-5) and Bray Curtis distances. Data from spring to autumn were used and winter was excluded owing to the overwhelming influence of light and temperature limitation and low overall diversity skewed relationships for other periods and prevented model convergence as well as increasing NMDS stress. All three axes were examined but as no significant pattern or relevant information was present in the third it has not been presented to ease interpretation.

Plotting of all significant environmental variables upon NMDS utilised P values below 0.1 and were selected using backwards selection (Zuur et al. 2007). Functional group, zooplankton abundance and environmental variable significant vectors were selected separately. Cluster analysis was conducted using Ward’s metric (Ward 1963) on phytoplankton functional group abundance data.

This method is an agglomerative solution to clustering that relies on sums of squares to determine groupings rather than distance analysis, in a similar method to ANOVA (Ward 1963). Finally we will construct a community template utilising the work done by Reynolds (2006; pg. 349) (Figure

14) that places each functional grouping on a scale according to tolerances to nutrient and energy scarcity. By adding the three primary functional groupings to such a template to form a triangle, the rough classification of the systems limitations throughout the year can be made and compared to other studies.

57 Chapter 2: Long term trends in SQ

Figure 14. Structure of triangles used in Reynolds habitat template. Each point relates to both a growth strategy (vis. Figure 5) and a point in yearly succession.

The entirety of the data were presented as yearly mean, maximum and minimum. When trends were considered they were tested using a Generalised Additive Model (GAM; Wood 2006) with the parameter as the dependent and a smoothed term for date as explanatory variable, where a significant seasonal trend existed this was removed from the annual trend prior to analysis.

2.4 Results

Chlorophyll a displays a highly significant nonlinear decline from a maximum of 243 μg l-1 in 1992 to a low of 1 μg l-1 in 2007 (P<0.001; Figure 15B) as well as a strong seasonal pattern (P<0.001).

The initial rise is related to increases in water clarity due to suspended solid deposition following isolation and changes in pH due to construction works (see below and Williams et al. 2010). The subsequent stabilisation post-1995 coincided with a reduction in Helixor operation (Figure 15a) from 24 hours a day to periods where they may only be operated for an hour a day.

TP (Figure 15C) substantially decreased from a maximum of 1125 μg l-1 in 1986 to <5 μg l-1 in 2007

(P<0.001) in parallel with chlorophyll a. The overall trend interacted strongly with season (P<0.05) preventing separation of seasonal and annual trends. From 2007-2009 the average TP was at the

58 Chapter 2: Long term trends in SQ limit of detection of 5-35 μg l-1, classifying SQ as at least mesotrophic under OECD guidelines

(OECD 1982). TN (Figure 15D) also initially decreased with chlorophyll from 6134 μg l-1 in 1995 to only 93 μg l-1 in 2007 but with a two year lag. Recent years have seen an increase in the levels of

TN up to 4126 μg l-1 in 2008 but no seasonal pattern is evident (P>0.05). The TN:TP ratio by mass

(Figure 15E) markedly changed over the study period (P<0.001) but in a non-linear fashion as amounts of TN and TP varied independently. At several points the ratio was indicative of nitrogen limitation but for the majority of the dataset the value suggests phosphorus limitation or co- limitation. Unfortunately limits of detection (5-30 μg l-1) prevented proper analysis of Soluble

Reactive Phosphate levels; however, the reduced levels of TP would suggest that they remain very low. Dissolved Inorganic Nitrogen (Figure 15F) does not show a significant annual trend (P>0.05) but elevated levels exceeding 2 mg l-1 are notable during the start and end of the dataset. There is a significant seasonal pattern (P<0.01) that suggests minimum levels occur in the summer and recover over autumn to spring.

The number of D. polymorpha found in invertebrate coloniser baskets markedly increased in recent years from zero pre-2002 to 192in 2009 (Figure 15F). This is a clear indication of increased population recruitment. Limited abundance data also exists for D. polymorpha that colonised SQ, specifically the year of introduction (1992), and dive survey counts in 2000 (x individuals m-2, inter-quartile range=8) and densities in 2010 (x 1003 individuals m-2, inter-quartile range=4313). pH (Figure 15H) has remained largely stable over the course of the dataset ( . 6). There have been reduced alkalinity in 2005-2006 with a minimum of 7.80 in 2009. The highly significant seasonal trend (P<0.01) suggests a peak in spring.

Suspended solids (Figure 15I) can be seen to initially decrease from a high of 111 mg l-1 in 1987 after impoundment, only to increase again during 1990-5 as algal particle abundance increased.

Following this second peak there is a further decrease to a <0.01 mg l-1 in July 2008 that appears now to of stabilised. In tandem with suspended solids, Secchi depth (Figure 15J) also increased over the course of the dataset and also shows a notable reduction during the chlorophyll maxima,

59 Chapter 2: Long term trends in SQ with a minimum of 0.2m in May of 1992. Unlike SS there has been a continued decrease to a maximum of 6.8 m in December of 2009, likely linked to the lower accuracy of SS measurements at low weights and a reduction in smaller, dissolved substances. DO (Figure 15K) markedly improved following Helixor installation, with values as low as 30.1% (May 1985) before 1990 and a mean of 101.0% since, although this is diurnal maxima, no records exist of nocturnal minima.

There is a clear change in zooplankton abundance (Figure 15L) from 135.33 individuals m-3 before sampling ceased in April 1995 to 32,830 m-3 shortly after regular sampling resumed in March

2003. A short period of sampling in 1997-8 indicated densities of up to 25,000 individuals m-3 but there is a lack of data between this and 2003. During the chlorophyll peak in 1992 (c.f. Figure 15A) there was reduced zooplankton abundance but it is suggested that numbers likely increased over the gap in sampling. Post 2003 there was an overall decline in zooplankton numbers. No regular seasonal trend is evident (P<0.05).

Data from the Manchester Ship Canal have also been supplied for comparison (Figure 16). It can be seen that Chlorophyll levels (Figure 16A) have been comparatively low ( .20 μg l-1) with a minimum of 0.22 μg l-1 in December of 1998. TP (Figure 16B) has declined from a maxima of 4000

μg l-1 in 1991 to an annual mean of 353.5 μg l-1 in 2009. TN (Figure 16C) increased initially and shows a number of elevated values in 2009 reaching highs of 27.5 mg l-1 but between these periods mean levels were 6.7 mg l-1. Owing to these patterns in N and P the TN:TP ratio (Figure

16D) has shown a gradual increase overall. There was then a period of stability between 2001 and

2008 as well as a recent increase as TN levels have increased. Secchi depth (Figure 16F) was below

1 m for much of the dataset with a minimum of 0.1 in both 1993 and 1997. Since 2000 transparency has been increasing with a maximum Secchi depth of 2.6 m in January 2002. There are also a number of high values of Secchi depth occasionally observed throughout the dataset, with the increased transparency likely a result of unusual rainfall and discharge patterns.

Suspended Solids (Figure 16E) have also been relatively stable over the period of the dataset with

60 Chapter 2: Long term trends in SQ a number of higher values in recent years, despite the simultaneous increase in Secchi depth. The most recent high reading being 115.63 mg l-1 in December 2009.

Climatic averages were also analysed. Between 1992 and 2005 there was no change in hours of sunlight (P>0.1, 114.0 month-1) or rainfall (P>0.1, 106.2 mm month-1) once seasonal variation has been removed. Although there is unlikely to be a significant effect over the course of this dataset, water surface temperature did increase significantly in a linear fashion (P<0.001) by

0.09°C year-1 despite increases in both water clarity (as a result of chlorophyll decline) and algal standing crop decreasing energy retention at the surface in addition to the mixing action of the

Helixors (Hutchinson 1957). Regional air temperature data from the UK Meteorological Office showed a similar, albeit smaller increase of 0.07°C year-1 (P<0.005).Overall, phytoplankton community composition has clearly shifted significantly over the course of the dataset (Figure 17) with a change from low diversity S1 dominated community to a more diverse and variable system occurring around 2002. Zooplankton also displayed a community shift from a dominance of cyclopoids and bosminids to a community of largely consisting of daphnia and calanoid copepods, with occasional occurrences of representatives of the Sididae (Figure 18). The timing of this community shift is hidden by the notable gap in zooplankton abundance data, however, it is clear that it occurred between 1997 and 2003, overlapping the period of phytoplankton community change.

61 Chapter 2: Long term trends in SQ

62 Chapter 2: Long term trends in SQ

Figure 15. Trends for each variable in SQ. Points indicate a reading and line LOESS line of best fit with standard error shown as grey shaded area.

63 Chapter 2: Long term trends in SQ

Figure 16. Important variables for the Manchester Ship Canal immediately adjacent to SQ. Points indicate a reading and line LOESS line of best fit with standard error shown as grey shaded area.

64 Chapter 2: Long term trends in SQ

Figure 17. Proportional area plot of contribution of each functional group to total phytoplankton biomass in SQ with cluster boundaries (as found in Figure 19) indicated (vertical lines).

65 Chapter 2: Long term trends in SQ

Figure 18. Proportional area plot of contribution of each family to total zooplankton abundance in SQ with cluster boundaries (as found in Figure 19) indicated (vertical lines).

66 Chapter 2: Long term trends in SQ

Microcystis aeruginosa (Table 4) was not frequently noted during routine phytoplankton counts but was monitored for adherence to bathing water regulations. These data show the first appearance of this cyanobacterium in the autumn of 2004 and subsequent but less severe occurrences every autumn until 2009. There is an evident increase in 2010 and also a general pattern of increased abundance in Ontario compared to other basins with the exception of 2008 when a M. aeruginosa bloom also occurred in St. Francis. 2006 is notable for the large abundances seen in both Ontario and Huron.

Ontario Ontario Huron Huron St Francis St Francis 90-200 μm >200 μm 90-200 μm >200 μm 90-200 μm >200 μm 2004 10900 - - - - - 2005 444 160 8 1 1 2006 32666 7333 8000 4000 9 2 2007 51 52 2 0 0 0 2008 32 6 0 83 13.5 2009 2 4 3 0 1 5 2010 213 710 38 17 49 49

67 Chapter 2: Long term trends in SQ

Figure 19. NMDS plot of the algal communities in SQ. Shading indicates temporal position from 1992 to 2010 (see scale, right) and symbols denote cluster number. Ellipses denoting standard deviation of each cluster are overlaid and labelled as A: pre-2001 (amalgamation of 3 Planktothrix dominated clusters), B: 2001-2005 and C: 2005-2010.

There is a clear differentiation of the algal community into 5 main periods based on the cluster analysis. The first three of these all represent differing sub-communities of P. agardhii dominance so have been combined into a single grouping in further analysis. By plotting these with time onto

NMDS results (Figure 19), three clear groupings can be seen: an initial grouping pre-2001 which encompasses the first three clusters, an interim assemblage (fourth cluster, 2001-2005) and a recent community (fifth cluster 2005-2010). The three smaller clusters of the pre-2001 period each consist of >90% Planktothrix agardhii, but with an additional unique sub-community (Figure

16). Due to the preponderance of the S1 species P. agardhii the three small clusters have been combined in further analysis.

68 Chapter 2: Long term trends in SQ

By using the vectors associated with each environmental parameter against the NMDS values

(arrows in Figure 20 and Figure 21) it can be seen that the initial pre 2001 grouping is correlated with increased levels of TP and TN (Figure 20) and also with higher algal abundance, denoted by chlorophyll a. The vectors (arrows) show the intermediate grouping is highly correlated with increased zooplankton abundance although this can only be stated with certainty for the second half of the cluster owing to missing data. Zooplankton communities (Figure 18) have clearly shifted to a higher proportion of cladoceran grazers during the interim and recent periods with the current period being correlated with daphnids and reduced copepod numbers. The interim period was the only one that can be related to increased bosmina but again there exists only limited data for this period. This was also linked with decreasing, yet still high, TP and reduced TN.

69 Chapter 2: Long term trends in SQ

The recent period is not associated with any of these formerly controlling variables but is linked to reduced concentrations of TP and chlorophyll a and increased numbers of D. polymorpha caught in the invertebrate samplers (Figure 20).

Figure 21. Vectors describing the functional groups in SQ fitted over the NMDS cluster ellipses given in Figure 19.

Figure 21 is constructed as Figure 20 but utilises biomass estimates for each phytoplankton functional grouping against each time period. The initial group largely consists of S1 type species, in this case exclusively P. agardhii. There is also a correlation with diatoms of the genus

Stephanodiscus representing group B or C. The intermediate period is characterised by the species groupings P (Closterium sp. and Staurastrum sp.), J (principally Pediastrum sp.) and X1

(Chlamydomonas sp.). The recent period is chiefly described by an abundance of X2 Plagioselmis nannoplanctica and Y group Cryptomonas sp. This period is also differentiated by increased

70 Chapter 2: Long term trends in SQ numbers of centric diatoms; some are Cyclotella while others are unidentified but of reduced size and therefore given the classification A-B. In addition various members of the F group are present, in particular Coenochloris fottii, Oocystis spp. and Sphaerocystis spp.

Figure 22. Habitat template for phytoplankton species assemblages in SQ (after Reynolds 2006 (Table 3) but using groupings found in this study). Triangles are obtained by joining the representative taxa of that period. Broken line indicates initial grouping, solid line intermediate and triple line recent period. Y group purposely absent, as in original plot.

Plotting the main functional groupings on the habitat template from Reynolds (2006; Figure 22) is not simple owing to the controlled mixing regime and between year variation that is especially

71 Chapter 2: Long term trends in SQ evident toward the more recent period. It can be seen that the community has shifted from one of light to nutrient limitation. It can also be seen that the changes between the intermediate and interim communities are mainly due to a reduction in light limitation as the effect of self-shading decreases. The recent period is sufficiently unusual not to adhere to the use of a successional triangle, instead requiring an inverse arrangement that does not describe seasonal succession in the standard way. It does suggest a wider range of functional groupings, an increase in nutrient limitation and also the reduced influence of energy limitation.

72 Chapter 2: Long term trends in SQ

2.5 Discussion

Due to isolation from the MSC and water column there have been large changes in the physical- chemical environment at SQ and hence the phytoplankton community since 1992. The most marked change in the former is the decline in nutrients, in particular phosphorus which is associated with the decline in chlorophyll. Phosphorus may not be the only limiting nutrient in SQ as TN:TP ratios have occasionally reached values where nitrogen may either interact with phosphorus or be limiting (Downing and McCauley 1992). Downing & McCauley found that nitrogen limitation can occur at TN:TP ratios greater than 20 during periods of phosphorus excess.

However the absence of H group dominance suggests that this was not a decisive factor (Reynolds et al. 2002). The large increase in TN:TP from 2003 is largely due to the dramatic rise in TN that seems to be independent of the change in algal abundance. The change in the TN:TP ratio may result from increased macrophyte biomass which can release nitrogen obtained from the sediments during winter senescence (Donk et al. 1993), a conclusion supported by the seasonal trend in DIN levels.

Salford Quays has characteristics indicative of a deep water body. Mainly a low macrophyte biomass (outside of the few shallow areas and adjoining canals) resulting from the low ratio of profundal to littoral area which can limit niche space, especially for zooplankton (Scheffer et al.

1993). However, the lack of stratification since Helixor installation in 1985-90 and high algal biomass while eutrophicated are more characteristic of a shallow lake (Stauffer 1991). Many of the algal species in SQ are also typical of a shallow lake system. For example, complete dominance of S1 group taxa has been noted in many shallow hyper-eutrophic lakes. S1 species are encouraged by frequent mixing which allows species such as P. agardhii to take full advantage of their highly efficient light harvesting mechanisms in an environment where light is the only limiting factor (Reynolds 2006). Such conditions favour groups such as B, C and Y (Reynolds 2006) which are also seen frequently in SQ. The prevention of stratification in SQ makes classification by mixing regime inappropriate as it is atypical of the dimictic and monomictic water bodies typically

73 Chapter 2: Long term trends in SQ found in temperate latitudes (Lewis 1983). For this reason we suggest classification of SQ as anthropomictic - a water body with an entirely artificial mixing regime.

The difference between the initial (pre-2001) and more recent (2005-10) phytoplankton community is almost entirely contained in axis one of the NMDS (Figure 20). This axis represents a reduction in TP, chlorophyll-a and Helixor operation and an increase in D. polymorpha grazing and

Secchi depth. The interim period (2001-5) is separated from the other two by axis 2 representing increased grazing and decreased levels of oxygen, TN and pH. The SQ phytoplankton community has also changed from S1 (P. agardhii) in the initial group to the current clear water state dominated by smaller flagellates, of which phosphorus is likely the key variable, in agreement with Williams et al. (2010). Vector analysis reveals an extremely strong correlation between total chlorophyll and S1 species in axis 1 which is in turn correlated to nutrient (TN and TP) concentrations. The sudden switch in species composition in 2000 is a possible indication that a change in stable state has occurred, supported by the increases in Secchi depth and establishment of macrophytes (Scheffer et al. 1993). We suggest that this change resulted from the continuing reduction in nutrients which can cause rapid decreases in cyanobacterial abundance and corresponding macrophyte increases, owing to reduced shading (Watson, McCauley, & Downing

1997). Eutrophic diatoms (B-C and D) also decline in SQ over this period as light penetration increases and nutrient concentrations decrease (Reynolds et al. 2002).

The start of the interim period is characterised by an increase in the number of algal groups, most notably P group diatoms and desmids, group J large chlorophytes and eutrophic picoplankton of group X1; both groups are typical of shallow (i.e. well-mixed), enriched systems which follows from the strong positive correlation with TP. There is a trend of decreasing levels of TN at SQ; however, the lack of H group taxa suggests that nitrogen limitation is not important. P and J groups have before been shown to occur in succession (e.g. Reynolds 1979) and has been linked to the changing availability of Si which was not measured in SQ so we are unable to conclude if this is the driving factor. This lack of Si data does limit the conclusions that can be drawn from

74 Chapter 2: Long term trends in SQ studying changing diatom assemblages. As such the changing dominance between, for example, X groups and A-C groups cannot be attributed to this variable; however, the importance of Si availability to seasonal succession and the control of diatom abundance has been firmly established elsewhere (e.g. Sommer et al. 1986; Reynolds et al. 2002; Reynolds 2006).

The interim period is the only time when there is a strong correlation to grazer abundance although pressure was apparently insufficient to create a system dominated by P. agardhii or other poorly grazed cyanophytes (McCauley, Murdoch, & Watson, 1988). It should also be noted that data on grazer abundance is sparse during this period so there remains the possibility that the underlying pattern could be attributed to other factors. From the data available it would appear that zooplankters were likely limited by the increased fish foraging efficiency resulting from improvements in water clarity, and aided by the introduction of macrophyte and macroalgal refuges in 2003 (Williams and Moss 2003). While increased grazing has been linked to the occurrence of the grazing resistant M. aeruginosa (Reynolds et al. 1982), peaks in production of this alga in 2006 occurred after a reduction in overall grazing intensity. As such it may be that another variable has been responsible for the presence of this species in sufficient quantities to close the water sports centre. It is possible that the combined effects of D. polymorpha and changes in trophic state (Sarnelle et al. 2012) or a paucity of water column nitrogen and sediment excess (Ferber et al. 2004) contributed to the bloom but this cannot be conclusively stated with the available data. This species may also be promoted in some circumstances by D. polymorpha

(Higgins and Vander Zanden 2010)

Changes in the dominant form of zooplankton grazers support a distinct change between the initial and present phytoplankton groupings. The earlier period is exemplified by a dominance of copepod species which are better able to persist in periods of large cyanophyte dominance owing to their ability to select prey items, manipulate larger algae, and also consume other prey, such as rotifers (Reynolds 2006). A period of Bosmina dominance during the interim period is to be expected as, while they are principally filter feeders, they are known to intercept and manipulate

75 Chapter 2: Long term trends in SQ prey items when required (DeMott 1982). Their replacement by daphnids will be the result of the now almost complete dominance in the quays of smaller algal species that can be filtered effectively. As daphnids are still able to persist this is a clear indication that total algal production has not dropped to such oligotrophic conditions that only the less energetically demanding copepods can survive (Reynolds 2006).

The recent phytoplankton group is notable as being highly correlated with reduced Total

Phosphorus; with concentrations reaching <35 μg l-1 for the period and possibly approaching oligotrophy. The availability of this nutrient is likely a major contributory factor to the continuing decline in overall algal abundance at the Quays and also the switch to species indicative of mesotrophic conditions such as X2 and A/B assemblages. The former of these, along with the Y group, are both highly susceptible to zooplankton grazing but possess growth strategies to facilitate high production and sustain heavy losses (Reynolds 2006). Both of these are advantageous to algae persisting in shallow lake environments while their small surface area to volume ratio would aid nutrient uptake (Reynolds 2006). These species’ enhanced light harvesting ability may also be important in obtaining nutrients at depth adjacent to the sediments while concurrently being able to obtain sufficient light to propagate (Reynolds 2006). The shift to the recent period has also been marked by an increase in diatoms, chlorophytes and cryptophytes.

This change in the phytoplankton community occurred over comparatively small nutrient changes compared to the transition between the initial and intermediate periods and is characteristic of the gradient seen in a shift to a mesotrophic system (Watson et al. 1997). This change is supported by increased water clarity, establishment of macrophytes and lower, stable P levels.

There would also appear to be a correlation between onset of mesotrophy and an increase in D. polymorpha abundance. It is difficult to separate cause and effect in such a situation but the limitation of algal biomass by filtration and the ‘shunting’ of nutrients to the sediments through pseudofaeces production may indicate that this species has aided the switch from a diverse, eutrophic species assemblage to the communities seen today. While it is impossible to ascertain

76 Chapter 2: Long term trends in SQ exactly when exponential growth occurred, the frequency of D. polymorpha occurrence in invertebrate colonisers increased markedly during 2004-5 from 0 to a maximum of 146 (although the overall maximum in 2009 was 192 individuals), corresponding to the shift from the intermediate to the recent community and the establishment of natural macrophytes in the shallow adjoining canals and sloped banks of the smaller basins. Although grazing by D. polymorpha limits the growth of most species of phytoplankton, an increase in filtration could promote groups such as cryptophytes (Y assemblage) which have not been significantly negatively correlated to mussel presence (Higgins and Vander Zanden 2010) and so would account for the increased proportion of this group. An increase in the level of filtration will also reduce the zooplankton population as the zebra mussel is a direct competitor for food resources (Higgins and

Vander Zanden 2010).

The increasing trend in surface temperature over the study period is extremely interesting. The duplication of this in the air temperature data for the region suggests it is not limited to SQ and therefore does not reflect changes in hydrology or riparian morphology. It has been shown that higher warmer temperatures can have a negative effect on water quality, including possible effects on sediment phosphorus release (Sondergaard et al. 2003) and denitrification (Cavari and

Phelps 1977) as microbial metabolism increases. Climate-induced changes in standing waters have been reported in a number of lakes in North America (e.g. Arhonditsis & Brett, 2004) and

Europe (e.g. Dokulil et al., 2006). A smaller temperature change than recorded in Salford Quays led to a gradual decoupling of the spring diatom bloom and Daphnia reproductive cycles in Lake

Windermere and thus zooplankton recruitment failure (George and Harris 1985). Further effects of warming on the plankton community include an increase in cyanobacterial populations

(Jeppesen et al. 2009) and shifts in diatom species dominance, although not necessarily on overall chlorophyll abundance (Elliott and Defew 2012). As climate has been shown to have a major impact on lake characteristics (Jeppesen et al. 2009), a continuing trend of elevating temperature could affect the environment of both SQ and the adjacent MSC.

77 Chapter 2: Long term trends in SQ

Fitting phytoplankton assemblages to Reynolds’ habitat template shows that the early post- isolation environment in SQ was characterised by increased levels of nutrients and limited light availability as a result of self-shading. These characteristics are shared with hyper-eutrophic, yet frequently mixed systems such as eutrophic pools (Reynolds 2006). The interim period communities can be likened to that of the highly stable Montezuma’s Well, Arizona in 1981

(Boucher et al. 1984), probably the closest natural corollary to SQ at this stage in its evolution.

Montezuma’s Well displays limited anoxia as it is constantly mixed by the inflow of water from artesian springs and also shows a propensity for small r-selected phytoplankton (Boucher et al.

1984). In the recent period in SQ nutrient limitation became significant while energy availability increased due to enhanced water clarity. Although the continued presence of X group species is generally indicative of elevated nutrients they may be encouraged by the constant mixing regime, low surface area to volume ratio and high filtration rates. The deviation from the standard succession observed in natural lakes is likely a result of the controlled mixing regime effectively removing the stresses associated with stratification in addition to the further reductions in nutrient levels. As such it is difficult to find a natural system that is an adequate corollary. The similarities to natural systems earlier in restoration do, however, show the value of ecosystem studies such as SQ in understanding freshwater environments.

As a macroscale experiment, SQ has shown how a switch to clear water state can occur in a fresh standing water during restoration with changes limited to isolation from polluting sources, water column mixing and possibly late stage filter feeder addition. This has been achieved without the additional need for teleost biomanipulation, without a large area available for macrophytes to establish and before oligotrophic phosphorus conditions (<8 µg l-1) could be reached, all of which should be taken into account in future studies of lake restoration. Today, the high quality waters of SQ are regularly used for water sports and in 2002 played host to the Commonwealth Games triathlon (Williams et al. 2010). Improvements such as these enhance biodiversity and increase the recreational and commercial potential of artificial urban water bodies with dramatic increases

78 Chapter 2: Long term trends in SQ in ecosystem service value. It is hoped that the lessons learned at SQ can help assist restoration projects elsewhere and provide a valuable target ecosystem for future water managers in similar systems. Future work will now seek to identify any further trends both overall and between basins using more detailed analysis (chapters 4 and 5).

2.6 Acknowledgements

The authors would like to thank E Bellinger and D Sigee for their comments on an earlier draft of this work. Our thanks are extended to NERC for a studentship to RM and our CASE Partner, APEM

Ltd for additional funding and support. Staff at APEM Ltd are also to be congratulated on the organisation and collection of the excellent dataset used here and the highly successful work done at Salford Quays.

79 Chapter 3: Non-linear patterns in SQ

3.0 Generalised Additive Models reveal non-linear patterns and

novel associations in a long term lake dataset

R. Mansfielda*, A. Williamsb, K. Hendryb, R. Preziosia, K. Whitea a: University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. b: APEM Ltd, Riverview, A17 Embankment Business Park, Stockport, SK4 3GN.

* University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. [email protected], Tel: 00447811363408

3.1 Abstract

Conservation of freshwater ecosystems is of vital importance to biodiversity, economic development and ecosystem services provision. Despite this, models used to investigate the relationship between phytoplankton biomass and environmental variables are generally either simplistic linear relationships or complicated stoichiometric interactions that are difficult to parameterise. Here we examine the use of Generalised Additive Models (GAMs) as a predictor of chlorophyll concentrations in an artificial lake. We produce a four variable model that incorporates nutrients, light and mixing regime. Our model is both a better predictor of phytoplankton biomass than existing models and applicable over the entire yearly cycle in our study system (R2=0.77). The use of the GAM approach and the incorporation of residual analysis provides an excellent example of a technique that is still underused in ecology. Our model provides an argument for a greater adoption of this technique to environmental science by providing new insights into lake ecosystem processes.

3.2 Introduction

While only accounting for 1% of planetary surface area, freshwater ecosystems account for 10% of animal diversity and a third of total vertebrate abundance (Strayer and Dudgeon 2010). The centrality of water resources to current and future economic development is also increasing

Chapter 3: Non-linear patterns in SQ

(Suweis et al. 2013) but despite this importance, freshwater systems are often highly polluted.

Legislation such as China’s Law on Prevention and Control of Water Pollution, Australia’s National

Water Quality Management Strategy and the European Union Water Framework Directive (EU

WFD) aims to ensure the proper restoration and maintenance of important water bodies.

Unfortunately, determining current and past ecological status is not always straightforward (e.g.

Devlin et al. 2007) and the emergence of novel ecosystems and environmental states derived through anthropogenic pressure can hinder management efforts. Because of this, the increasing number of highly managed artificial systems deserve detailed exploration both to meet legislative requirements and to improve the status of these critical ecosystems.

Phytoplankton production is one of the main indicators of quality in aquatic systems (e.g. Galvez-

Cloutier & Sanchez 2007) and is one of the main metrics used to assess the status of standing water under the EU WFD (UK Technical Advisory Group 2008). Excessive algal growth – often measured as bulk chlorophyll a (Environment Agency 1980) – can lead to toxic chemical production, unsightly surface scums and nocturnal anoxia (Fogg et al. 1973). Reducing phosphorus, the most frequently limiting nutrient for algal growth, is considered to be of paramount importance in the restoration of standing freshwaters (Schindler 1977). Methods such as food web manipulation or chemical controls such as algicides provide only temporary improvements if nutrient inputs are not also controlled (Søndergaard et al. 2007).

Despite its relative scarcity, a reduction in phosphorus alone does not always produce the desired affects (Søndergaard et al. 2007) as sediment nutrient loading, stratification and the self- reinforcing nature of an algal dominated stable state will also influence phytoplankton biomass

(Jørgensen et al. 2004). In addition the ratio between phosphorus and nitrogen – the second most frequently limiting nutrient – can create an added pressure on phytoplankton production owing to species tolerances and the ability of some cyanobacteria to fix nitrogen (Zhu et al. 2010). On top of this is the added complexity of grazers, either in the form of zooplankton or filter feeding macroinvertebrates such as bivalves (Reynolds 2006). This ‘top-down’ control on the

Chapter 3: Non-linear patterns in SQ phytoplankton may be quite marked and lead to increased deposition rates of nutrients to the sediments as well as direct competition for suspended nutrient supplies. The strength of this effect will of course be highly dependent on the species, in particular their filtration efficiency, niche and life span. For example a planktonic daphnia will cycle any acquired nutrients in the water column more readily than a filter feeding bivalve which will have a larger filtration capacity and a tendency to transfer nutrients to the sediments through the production of comparatively large faecal and pseudo faecal pellets (Higgins and Vander Zanden 2010).Simple predictive models have been developed many times to explain the relationship between chlorophyll a and phosphorus and nitrogen (Phillips et al. 2008). Unfortunately there is little consistency in the model coefficients produced by different authors for different system types. Because of this, prediction of changing chlorophyll patterns in a lake environment requires us to use a model that was derived from a similar environment (Phillips et al. 2008). To account for variation among systems modern models include variables such as hydrodynamics or phytoplankton functional groupings that allow for changing algal production (Jørgensen 2010). Using such an approach does, however, always risks over-parameterisation and the use of variables that are not easy to obtain in the field.

Mathematically, many studies have assumed that a linear regression model can be built without consideration of the limitations of such an approach (e.g. Dillon & Rigler 1974; Seip et al. 2000 but see Havens & Nürnberg 2004). Chief amongst these limitations is the assumption of a linear trend over the entire range of the dataset. However, the effects of changes in nutrient regime may be more or less pronounced depending on the current trophic status (Watson et al. 1997), phyto- and zooplankton interactions and physiochemical environment (Williams and Moss 2003). For example, at very high nutrient concentrations, excessive algal production at the water’s surface causes light limitation and the effect of further increases in nitrogen or phosphorus is greatly reduced. This would not be an insurmountable problem if conditions and sites were chosen to reduce this confounding effect through confining the modelled parameters to linear trends or

Chapter 3: Non-linear patterns in SQ transforming the data. A more satisfactory solution may be to assume a different underlying distribution as in General Linear Models (GLMs); however this again may confine model parameters in a way that can bias results (Guisan et al. 2002). The utilisation of Generalised

Additive Models (GAMs; Hastie & Tibshirani 1986) provides an improved method for fitting trends to ecological data (Guisan et al. 2002) as it removes the need to assume a specific distribution when constructing a model. This is accomplished by breaking the data up into subsets

(splines) that can be described using standard GLM approaches and linked together (Figure 23).

Selection of the optimal fit is usually accomplished through information criteria such as Akaike

Information Criterion (AIC). GAMs can greatly increase model fit and/or quality (traditionally measured with AIC) without the need for new variables, but at the cost of requiring larger data sets because of the additional degrees of freedom required. Extensions of this method have been applied to various datasets in fields as diverse as brain imaging and climate change (Wood 2006) and have found a use in improved ordination vectors (Oksanen 2008) but have only seen limited application to lake ecosystems. Here we report the first application of a GAM approach to lake phytoplankton modelling. We also incorporate examination of residual error, a stage of data analysis that is often lacking in such studies (Seip et al. 2000; Havens and Nürnberg 2004; Phillips et al. 2008) and is known to cause problems in both model fit and significance through missing important underlying patterns (Zuur et al. 2007).

Chapter 3: Non-linear patterns in SQ

Figure 23. Representation of GAM fit method. GLM regressions representing straight lines (red) are connected by non-linear GLMs (blue) to allow matching to any underlying trend (black). Dashed lines indicate 95% confidence intervals.

We used a data set describing the period of phytoplankton decline in a redeveloped dockland now known as Salford Quays (SQ; Salford, UK, 53.470N, 2.287W, total area 8.14 ha, depth 6.6m).

This system consists of three separate but interconnected artificial lakes (Williams et al. 2010).

We will show that utilisation of this modelling technique and the proper residual pattern analysis can produce a more appropriate model than would otherwise be possible using linear techniques.

This will allow us to propose appropriate controls on algal biomass without relying on the approximations of more traditional regression analysis. In this way we can test the hypothesis that phytoplankton control in Salford Quays is mainly due to phosphorus reduction. Finally, we will supply a study of a re-engineered urban system, an environment that is very abundant, yet for which natural lake models may be largely inadequate (Bellinger et al. 1993). Our results inform future water quality and ecosystem management and may also address the problem of differences among freshwater models by suggesting which variables may be responsible for this variation.

Chapter 3: Non-linear patterns in SQ

3.3 Methods

3.3.1 Study site & dataset

A full review of the environment within SQ has been provided by Williams et al. (2010). In summary, the quays are an isolated, entirely artificial lake system with extremely low habitat heterogeneity. They are artificially mixed by Helixor Systems (Process Engineering S.R.L, Romania) to prevent stratification and thus bottom water anoxia. In addition the basins are constantly monitored for changes in both physical and chemical characteristics (Williams et al. 2010). This combination of hydrological simplicity and a long-term data provides an ideal environment to study changes in a lake environment with a minimum of confounding variables.

Extensive data have been collected from three sites by APEM Ltd over 1986-2012, including 20 physiochemical variables of which eleven (hours of sunlight, rainfall, Helixor operation, water surface temperature, water oxygen saturation, pH, Total Nitrogen – TN, Total Phosphorus – TP,

Dissolved Inorganic Nitrogen – DIN, N:P ratio and photosynthetically active radiation - PAR) have been selected for study based on ecological relevance and possibilities of co-linearity. Data were collected on an at least quarterly basis from 1986 to 2001 with monthly sampling beginning in

2002. Although the dataset spans 1986-2012 the period of phytoplankton decline to stability

(1992-2005) has been selected for investigation of chlorophyll relationships. Prior to 1992 the limiting factor for phytoplankton growth was considered to be photic depth, initially due to the high levels of suspended solids but later by phytoplankton self-shading themselves, after 2005 a clear change in ecosystem stable state occurred and the limiting variable changed from light to other physiochemical parameters (Williams et al. 2010).

3.3.2 Climatic Variables

Levels of Photosynthetically Active Radiation (PAR) were obtained using satellite measurements from NOAA-CIRES Climate Diagnostics Centre’s NCEP-DOE Reanalysis 2 project as in (Williams et al. 2005).

Chapter 3: Non-linear patterns in SQ

3.3.3 Analysis

Statistical analyses were conducted on R version 2.13.1, utilising the MGCV package (Wood 2006).

Averages for each of the three sampling sites in SQ were used because of non-independence and data were log transformed prior to analysis to reduce the effect of outliers.

For model construction chlorophyll a was chosen as the dependant variable and all possible unique permutations up to 5 variables were placed into GAMs. Interaction terms were tested up to three variable models as more complicated interactions caused unacceptable increases in degrees of freedom. These were compared via Akaike's Information Criterion (AIC) and analysis of residual error. Collinear variables were removed using both current scientific knowledge and

Variance Inflation Factors (VIFs), preferring values ≤5 (Heiberger and Holland 2004).

3.4 Results

3.4.1 Changes in phytoplankton abundance

A GAM model that utilises only TP against chlorophyll a produces an R2 of 0.57 and hence explains a large amount of the variation in SQ chlorophyll levels (equation 1, Table 5). The model can be improved by utilising more variables (equation 2 to equation 4, Table 5) with a model incorporating more variables removing most of the residual pattern (see 3.7). The final model incorporates management (Helixors), seasonal (PAR) and nutritional (TN and TP) parameters to account for the variation seen within SQ. All except equation 1 exceed an R2 of 0.65 required for model prediction (Prairie et al. 1989) and in every case the non-linear model is superior to its linear equivalent (Table 5). It can be seen in Figure 24 that there is a strong positive correlation between chlorophyll and log TP but, by reference to overall residual pattern (see 3.7), the need for a non-linear fit is also apparent. The Helixors (Figure 24) are only important in controlling chlorophyll production when operating for short (0-6 hrs day-1) and extended periods (20-24 hrs day-1) but the former of these displays wide confidence intervals owing to a paucity of observations between 0 and 6 hours/day operation. Nevertheless Helixor operation offers a substantial improvement in model fit once it is incorporated in equation two. The inclusion of TN 86

Chapter 3: Non-linear patterns in SQ in equation 3 mainly serves to remove the observed residual pattern and PAR in equation 4 accounts for the seasonal pattern seen in chlorophyll data as light intensity varies from winter to summer. This is clearly indicated by its underlying distribution (Figure 25).

AIC Lin. AIC R2 Residual pattern Eq. 1 Chl = s(TP) 213.98 223.37 0.57 Strong Eq. 2 Chl = s(TP)+s(Helixor Operation) 175.78 206.64 0.74 Autocorrelation Eq. 3 Chl= s(TP)+s(TN)+s(Helixor Operation) 166.10 195.69 0.74 Uneven within seasons Eq. 4 Chl = s(TP)+TN+s(Helixor Operation)+PAR 157.41 191.59 0.77 Uneven between years

Figure 24 GAM relationships within the dataset with 95% confidence intervals (dotted lines). Linear terms are given by: Intercept -1.16, PAR coefficient: 1x10-3 and TN coefficient: 0.519

Chapter 3: Non-linear patterns in SQ

1200

800

600

400 200

2 4 6 8 10 12 Month

Figure 25. Seasonal pattern in PAR for these data. No significant annual trend exists (see 2.0).

3.4.2 Zooplankton

As zooplankton data for the period of interest are limited, inclusion into any of the above models was not possible. To determine if grazing was important in restoration, counts of cyclopoids, calanoids, daphnids, bosminids, total copepods, total cladocerans and total zooplankton were used to explain the residual pattern in equation 4 for the periods January 1992 to March 1997 and

April 2003 to December 2006. These were treated separately as there is a clear change in the dynamics of the zooplankton population between these periods (Figure 18) suggesting a change in relationship may have occurred. Zooplankton data were not collinear with other variables in equation 4 over either period so their effect can be assumed to be independent. Adjusted R2 values were only above <0.001 in the case of bosminid frequency prior to 1995 (R2=0.08); however this was not significant (P=0.127). Thus grazing pressure is not a main driver for chlorophyll in SQ.

Chapter 3: Non-linear patterns in SQ

Equation 4 Equation

Actual

Month

2003

0 5 10 15 20 25 30

Chlorophyll a Chlorophyll g l 1

Chapter 3: Non-linear patterns in SQ

3.4.3 Comparison to other models

To assess the goodness of fit for our model against previous linear approaches the maximum winter/spring TN and TP values were obtained for 2003 (the most recent period for which a full year’s worth of observations are available). This was considered analogous to maximum TN/TP at overturn which is what is stipulated for these models ((Phillips et al. 2008)). It is clear that our

GAM modelling approach provides a superior prediction of chlorophyll compared to other commonly used models (Phillips et al. 2008;Figure 24). The most marked difference is the temporal resolution of the two approaches, with previous models only being able to provide average levels of chlorophyll for any particular year when given the average spring nutrient regime. By utilising a non-linear approach we have been able to include predictions across the annual cycle (Figure 24) and also greatly increase the accuracy of estimates within SQ. The models under comparison are of course constructed from natural systems and not lakes such as SQ. As such a degree of difference is to be expected a fact that highlights the importance of considering similar systems when utilising these models (Phillips et al. 2008).

3.5 Discussion

We have demonstrated that the application of a non-linear modelling technique such as GAM can be used to great effect in the analysis of long term limnological data. Our approach provides an increased level of accuracy and hence predictive power, and reduces the amount of residual error in the resultant models. Equation 2 would have been suitable for prediction using the criteria of

Prairie (1996) and as further variables do not markedly improve R2 it would have been logical to assume this relationship represented the most appropriate fit to the data. However, analysis of residual pattern shows that more appropriate models are available which greatly improve AIC.

There does remain some residual pattern over the study period suggesting that in some instances the relationship is still imperfect but not correctable without over parameterisation. Nevertheless the incorporation of residual analysis proved extremely important to SQ and we wish to highlight its usefulness to those undertaking similar studies.

Chapter 3: Non-linear patterns in SQ

The overall relationship given by equation 4 adds two new variables to the nutrients that have been used in freshwater models since Smith (1982) – PAR and Helixor operation. The relationship reaffirms the importance of nutrient control to freshwater restoration and emphasises that while phosphorus removal is important, it is not the only tool required for water quality management

(Jørgensen et al. 2004). Incorporating the effect of environmental variables such as PAR may also prove useful in the face of climatic variation over the coming decades as restoration works alongside shifting weather patterns.

The Helixor component is analogous to introducing a variable for wind-induced mixing in a natural lake. Artificial mixing is essential to the maintenance of oxygen levels at SQ, especially in warmer months. Periods of inactivity quickly lead to bottom water anoxia (Gray 1999) and the inevitable release of nutrients from the sediments (Sas 1989; Sondergaard et al. 2003). The inclusion of

Helixor operation in all but the simplest model suggests that mixing in SQ is more important than levels of nitrogen or PAR. Mixing is, however, known to be able to disturb sediments and allow diffusion of high nutrient pore water into the environment (Yousef et al. 1980). In addition it has been postulated that mixing allows for a larger population of the shade tolerant cyanobacterium

Planktothrix agardhii at SQ as mixing prevents exclusion from the photic zone for a sufficient period to prevent growth (Williams et al. 2010). Nonetheless it has helped to extend the model over a larger proportion of the year than the ‘onset of overturn’ stipulated by others, (e.g. Dillon

& Rigler 1974). The relationships between chlorophyll and nutrients does vary with the onset of stratification (Mazumder 1994) so introducing a variable that accounts for this will increase accuracy in much the same way that introducing a variable for PAR will help to make the model valid in all seasons. Similarly as long term stratification is never present, this model may be limited in its comparison to stratifying water bodies.

PAR varies with the seasonal cycle, peaking at the summer solstice and reaching a minimum during the winter solstice. While PAR adds little to the overall AIC of the model, it provides a vital function in that it accounts for seasonal variation in a manner which is not usually attempted in

Chapter 3: Non-linear patterns in SQ limnological regression modelling (Phillips et al. 2008). The requirement of this variable to create an even seasonal spread in the residuals shows the importance of incorporating such effects in a model if it is to be relevant over the whole annual cycle. If this correction had not been introduced the relationship would be less accurate at certain points in the year and thus less valuable in terms of both environmental insight and management applications. PAR may of course be serving as a proxy of other seasonal variables such as prevailing weather conditions, base metabolic rate, or availability of energy. The inclusion of this parameter suggests that the amount of energy available for photosynthesis may limit phytoplankton abundance when nutrients are in excess (Talling 1957) and that low temperatures may compound the effects of nutrient limitation

(Rhee and Gotham 1981). The advantage of incorporating satellite derived PAR is that values collected in an identical way can be obtained for any location and it is an excellent variable to explain shifts in abundance related to the seasonal cycle.

Despite zooplankton being unavailable for inclusion in the model due to limited data, the high degree of accuracy afforded by the measured variables and reduced residual pattern suggests a strong bottom-up control on the phytoplankton in SQ. This is in partial agreement with the history of the system as it has been shown that, while zooplankton may have been important for determining community structure, levels of grazing have not been sufficient to cause a shift to resistant cyanobacterial species (Williams et al. 2010; 2.0)). Thus our resultant model may not be valid in systems where zooplankton grazing is likely to be a significant contributor to algal abundance. Nonetheless, our modelling approach can easily be extended to other systems.

A possible limitation to the relationship seen in equation 4 is the error in accuracy created by using logged inputs and outputs that must then be transformed back to usable data allowing for small errors to be amplified (Reynolds 1980). However, our comparison to real data in 2003 indicates that no significant deviation has occurred and predicted values still fall within the bounds of other systems.

Chapter 3: Non-linear patterns in SQ

It is important to consider systems with similar hydrologies when applying a lake model, and not unusual for a bespoke model to offer superior fit to a general relationship (Phillips et al. 2008).

Nonetheless, the inclusion of new variables into our final model broadens the relevance of equation 4 and makes clear the importance of a variety of factors, not just nutrient abundance, in influencing community structure in freshwater environments. As the majority of chlorophyll production equations utilise only TP and TN, comparison with the SQ model is not simplistic but it can clearly be seen that our model provides both a better fit and an improved relevance over a yearly cycle compared to previous approaches. This dramatic improvement in the model supports not only the case for using similar variables in future work but also the application of non-linear approaches and analysis of residual pattern in ecological modelling and we anticipate that such approaches will become more generally utilised by the ecological community. It is our hope that this model can now be validated on other long-term datasets and applied to other canals, docklands and heavily modified systems such as the nearby Manchester Ship Canal or Liverpool

Docks. In such systems the parameters provided here may prove more appropriate than those produced from natural lakes while this modelling approach provides a more relevant relationship for both natural and artificial systems. This provides the added advantage that systems such as SQ provide a resource for large scale mesocosm experiments.

In summary, the new variables not only help to validate the model but also provide new insight into environmental relationships in a simplified aquatic ecosystem. This allows us to identify the key variables determining algal biomass in a restored dock system and provided a tool that can be used in future restoration projects. The use of GAM has provided a better fit than previous regressions which invariably approximate to linear or other predefined patterns. This non-linear approach holds much promise in the interpretation of relationships that may confound other methods of regression. We therefore recommend and encourage its use and refer interested readers to texts by Zuur (2007, 2011) for general applications and Wood (2006) for a more detailed discussion.

Chapter 3: Non-linear patterns in SQ

3.6 Acknowledgements

R. Mansfield is in receipt of an NERC CASE studentship with APEM Ltd and we would like to express our thanks to both organisations for financial support. We would like to thank the staff of

APEM for collection of the high quality dataset we used for analysis. The authors would also wish to thank T Gilmore and C Knight for their helpful comments on an early draft.

Chapter 3: Non-linear patterns in SQ

3.7 Supplementary data: residual patterns for each GAM model

Plots below provide detail of residual pattern for each equation. From top left clockwise plots are:

Autocorrelation of the residuals obtained from correlating each value with subsequent values.

Results above the dashed line indicate a significant relationship at P=0.05; residual dispersal for each year, unequal spread between years indicates differing efficiency of fit; as before with seasons; overall residual pattern, ideally should be entirely random; residual spread for months.

3.7.1 Equation 1

Chapter 3: Non-linear patterns in SQ

3.7.2 Equation 2

Chapter 3: Non-linear patterns in SQ

3.7.3 Equation 3

Chapter 3: Non-linear patterns in SQ

3.7.4 Equation 4

Chapter 4: D. poly microsatellite panels

4.0 Multiplex panels of Microsatellite Loci for the Invasive Bivalve

Dreissena polymorpha allow determination of habitat

connectivity at multiple spatial scales

R. Mansfielda*, N. Truelovea, R. Preziosia, K. Whitea a: University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK.

* University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. [email protected], Tel: 00447811363408

4.1 Abstract

Nine microsatellite loci for the invasive bivalve Dreissena polymorpha have been successfully co- amplified via a two panel multiplex polymerase chain reaction (PCR). This method has successfully been applied to 288 individuals from around the Northwest UK and Catalan, Spain allowing population statistics to be determined. Here we describe those statistics, the successful and problematic sequences encountered and use these data in determining both national and international relatedness. In this way we are able to determine that local dispersal is occurring between populations in two of the Northwest UK sites: Salford Quays and Warrington. It is also apparent that there may be cryptic populations within the isolated docklands of Salford Quays.

The implications for their future management and the protection of uninvaded ecosystems are discussed.

Chapter 4: D. poly microsatellite panels

4.2 Introduction

The zebra mussel Dreissena polymorpha Pallas is a highly invasive Ponto-Caspian species that is ranked as one of the world’s ‘100 worst’ invasive species (Lowe et al. 2000). It is a quintessential r-selected coloniser with generation times of 1-2 years and females that are able to produce over

1 million planktonic eggs during a single spawning event. Mature veligers settle on any hard surface and in extreme cases average densities can reach >10,000 individuals m-2 (Higgins and

Vander Zanden 2010).

Once established, D. polymorpha can have a significant effect on the environments they inhabit.

Filtration of particulate matter from the water column and the production of pseudofaeces create a net flow of energy and resources to the benthos (Higgins and Vander Zanden 2010). This can inhibit pelagic production while increasing productivity in the sediments. Damaging effects are not merely environmental, with mussels frequently fouling submerged pipes and water-borne machinery. It is estimated that in the United States alone such costs exceed US$267 million

(Connelly et al. 2007).

A number of vectors have been responsible for this species’ now near ubiquitous existence. Canal construction, ballast water transport and recreational water users have all contributed to the expansion of their range around Europe and America (Higgins and Vander Zanden 2010). In the

UK, initial establishment is believed to have occurred in Surrey docks circa 1824 where D. polymorpha were reportedly used as fishing bait. Populations were subsequently detected in nearby Goole Docks and Glasgow’s Clyde and Forth Canal before spreading throughout the country (Aldridge et al. 2004; Figure 24).

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Figure 27. Locations of sample sites (yellow) and sites of initial invasion in the UK (red).

This ability to disperse means that it is important to be able to document the spread and identify possible vectors responsible for the transport of D. polymorpha and to this end we have created a two panel multiplex that has been applied to populations in Spain and NW England (Figure 27). 1)

Salford Quays (hereafter SQ) (n=175, from the six sites shown in Figure 28), an isolated, interconnected artificial lake system in Greater Manchester, UK where D. polymorpha have been present since 1994 (Williams et al. 2010) (53.47086N, 2.28778W); 2) a section of the Bridgewater

Canal in Warrington (53.36189N, 2.602131W), roughly 25km from the Quays by Euclidean

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Chapter 4: D. poly microsatellite panels distance and presenting the possibility of gene flow by either natural or anthropogenic spread

(n=17); 3) Miranda de Ebro (42.67900N,2.93524W) (n=32) and 4) Ircio in Catalonia (n=32), Spain

(42.654500N, 2.89697W) both separated by only 4 km and connected by the Ebro River thus allowing direct spread; 5) Pantà de la Baells (42.65500N, 1.88333E), a reservoir along the

Llobregat river, Spain separated from sites 3 and 4 by 400km and in a different drainage basin therefore with a reduced probability of gene flow (n=32).

Figure 28. Graph of sample sites within SQ (red pins), identified by letter (A-F). Sample sizes: A: n=31, B: n=30, C: n=32, D: n=43, E: n=16, F:n= 23.

The aims of this study were 1) development of a microsatellite suite for D. polymorpha and 2) use of this suite to determine the presence or absence of gene flow between a number of populations. In this way we aim to aid in the determination of population isolation for invasive species management. It is hypothesised that this microsatellite suite would be capable of detecting similarities between sites 3 and 4, allow differentiation between these and site 5; and a larger separation between Spain and UK populations, provided no new introduction events had occurred since. In addition it would be possible to determine whether the hydrological isolation of 102

Chapter 4: D. poly microsatellite panels

Salford Quays has prevented gene flow or if populations have been able to immigrate or emigrate from the enclosed basins. In addition, D. polymorpha were collected from each of the four interconnected lakes in the Salford Quays system to ascertain if this is a single population or a number of connected colonies.

4.3 Methods

D. polymorpha (n=288) were collected from each of the five sites. Their DNA was then extracted from adductor muscle tissue using a Promega Wizard SV 96 Genomic DNA purification system.

Thirteen microsatellite loci were taken from the literature and combined into appropriate multiplexes with 5’ fluorescent labelled primers (dyes: FAM, VIC, NED and PET). PCRs of each multiplex were run on a Veriti Thermal Cycler (Applied Biosystems; ABI) using a Type-it

Microsatellite PCR kit (PCR conditions given in Figure 29). Total reaction volume was 5 µl with an approximate DNA concentration of 40 ng ml-1. The PCR product was run on a 3730 DNA Analyser

(ABI) against GeneScal500LIZ size standard (ABI). Subsequent computer analysis was performed on Genemapper (v 3.7) (ABI) for peak calling, Micro-checker (Van Oosterhout et al. 2004) for detection of null alleles and the R (v 2.15.2; R Core Team 2012) packages Adegenet (v 1.3-5;

Jombart 2008) and MsatAllele (v 1.03; Alberto 2009) for later analysis, including use of

Discriminant Analysis of Principal Components (DAPC) (Jombart et al. 2010).

Figure 29. PCR conditions for microsatellite amplification in this study.

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4.4 Results

In total, 4 loci failed to amplify correctly and there appeared to be interference for PET labels in multiplex A which prevented identification of sequence length amongst ‘false-peaks’. It was decided to select new loci rather than redesign published primers for failed amplifications so we do not discourage their future use. There were few problems in peak detection but in sequences such as Dpo171 and Dpo221 the close proximity in fragment sizes made the determination of homozygosity and true allele length problematic. The authors would also wish to highlight the

2011 corrigendum of Naish & Boulding (2001) when choosing appropriate primers as this corrects a sequence error present in the earlier paper.

Table 6 and Figure 30 summarise the selected microsatellite loci. The former of these describes the used markers and lengths obtained, as well as literary sources while the latter identifies the distribution of lengths and how they were separated out into individual alleles. Allele frequency suggests an excess of homozygotes for at least one locus (Table 6) at each site but across all sites only two loci consistently showed evidence of a paucity of heterozygotes, suggesting the presence of null alleles for DpolB6 and Dpo171.

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Table 6. Loci and primers used in panels with original characteristics given. MP – Multiplex identifier, Rep – repeat motif, H0/He – observed and expected hetereozygsity, Ref – reference. 1: Feldheim et al. (2011), 2: Naish & Boulding (2001; Corr. 2011), 3: Thomas, Hammouti & Seitz (2011).

Primers Alleles Length Ho/He

MP Loci Rep. 5’-3’ Dye (this (this study) *:excess Ref. study) Min Max

F:GACTTTATTTGTAA Dpo 34 66 195 TGA TGAGGATGTTGG 6FAM 133/109 1 221 R:TGGGTTGGTGTCA (10) (152) (185) ATGTTTC F:CGTTGTTCAAGCA Dpol 16 256 352 AAT ATAAGAAAGAC 6FAM 81/30* 2 B6 R:CGTGTGCTCATGT (28) (258) (361) A TTCCTCC F:TTGTTGGATTCGG Dpo 35 112 292 TAGA TGGAATA NED 64/38 1 260 R:CCATAGATCCGTT (35) (121) (325) TGCGAGT F:TGGTTGATGCAGT Dpol 8 218 249 TAAA GACCCTA VIC 45/36 3 9 R:TGTCGCTTGATCC (18) (200) (242) ATGTTTT F:TAATCGCATTCCG Dpo 41 125 271 AC GCGTAG 6FAM 128/82* 1 171 R:GAAATGGATTGA (16) (138) (220) AACGAAAGAAA F:TGTTTCACCCCATT Dpol 6 479 509 AAT AATGACAG 6FAM 77/48 3 6 R:GTCCATTGTTGAT (9) (461) (491) GCCACATTA F:TGATCAGATATTTT Dpol 10 195 402 B AAT CACAAACTGC PET 54/33 1 B9 R:GCGTGTGTTTTTG (20) (198) (400) AAACGTG F:GCACTGTCAACGT Dpol 11 187 247 AAT CACACTTTTG VIC 46/36 2 C5 R:CCTTGCTAACAGC (10) (199) (230) TCGGTTGTATC F:GCATTCCATCAAA Dpol 11 293 418 ATG AACACAGAT VIC 59/27 3 19 R:GATCAACACCAAA (21) (277) (416) GTTCGTTTC F:AAGCCGGTCTGTT Dpo TG GAGTAGG PET - - - - 1 281 R:AGCTTGACGATTA GCCAGGA F:TCATACCGCCATT Dpol AAT GATATGC PET - - - - 3 7 R:TGCGCTCGAATAA ATGACAA F:AGACTGTGCTTCA Dpo TGA GGGATCG PET - - - - 1 Not amplified 101 R:GATGCATACCTCG ACCTCGT F:TTTTTCTTCTGGTC Dpol AAT TCGACG NED - - - - 2 B8 R:AATTTGAACATTA AACATTTGTC

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Figure 30. Cumulative frequencies of allele sizes for each viable locus studied. Shading indicates alternate alleles.

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2 DAPC

DAPC1

Figure 31. DAPC plot of D. polymorpha with sites indicated, 95% ellipses plotted and eigenvalues given.

Ellipse overlap in Figure 31 shows genetic links between the Salford and Warrington population indicating that, despite isolation, migration either out of or into the Quays has occurred. This is not to say that the two populations are directly connected, there exists the very high possibility that there are other extant populations in the area and migration between that and both our source populations may be occurring. It should also be noted that different loci showed heterozygote deficiency between these two basins and thus it is likely they established separately and later gene flow occurred. The Spanish populations, which are distinct from the UK mussels, are well connected between sites 3 and 4 and distinct from site 5 although DA eigenvalues (Figure

31) suggest this separation is not as strong as between these and the UK populations. The majority of variation is captured by axis one and separates the UK and Spanish populations.

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2 DAPC

DAPC1

Figure 32. DAPC plot of populations within SQ grouped by sample site. Ellipses give inertia and overlap indicates

similarity

2 DAPC

DAPC1

Figure 33. DAPC plot of populations within SQ, clustering of individuals determined without priors. Ellipses give inertia and overlap indicates similarity.

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Closer analysis of the separate sampling points within SQ (Figure 32) shows there to be little differentiation between sites. The excess of homozygotes in SQ may however be evidence of a recent migrant or sub-population not taken into account during hypothesis generation or sampling, termed the Wahlund effect, an analysis of genetic similarity on all SQ mussels was undertaken without any prior groupings. The resulting cluster analysis followed by DAPC (Figure

32) shows two of unique genetic groupings within the quays identified as groups 2 and 6.

4.5 Discussion

It would seem that migration between the Quays and Warrington population may have occurred.

The fact that the same heterozygote excess was not present in the latter suggests that these two were likely established separately and later immigration or emigration may have taken place, an event that has been recorded in other invaded areas such as North America (Müller et al. 2002).

The differentiation between these and the Spanish populations supports the initial hypothesis regarding site differentiation, as does the connectivity (or lack thereof) between the three

Spanish sites. That overlap that does occur between the two Spanish catchments is likely a result of the relatively recent separation of these populations which must of occurred since invasion from France in 2001 (Rajagopal et al. 2009).

The possibility of genetically distinct populations within the quays that are not part of the geographical patterns sampled are likely the result of an unaccounted for temporal or spatial gradient creating barriers to interbreeding. This effect has been seen in a number of sedentary marine molluscs, despite also possessing planktonic dispersal strategies (Johnson and Black 1984).

Johnson and Black found that in limpets of the genus Siphonaria isolated populations occurred over relatively small geographic distances, creating effects similar to those seen here. In the quays this effect may have been caused by the recent addition of a new population of zebra mussels into the quays which have spread throughout the area through planktonic dispersal, yet have not fully interbred with local mussels. This would temporarily create a result similar to that described

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Chapter 4: D. poly microsatellite panels by Johnson and Black, a difference that could only be confirmed with future sampling and analysis.

While there are a number of null alleles in these data, it is not uncommon for invertebrate species

(Hedgecock and Li 2004). It may also be encouraged by recent changes in the UK D. polymorpha populations, such as the die-back in the early 2000s disrupting the Hardy-Weinberg equilibrium

(Aldridge et al. 2004). The large number of homozygotes in SQ is likely a result of recent rapid changes in population size caused by restoration activities (see 2.0) and a testament to the small number of mussels in the original introduction (Bellamy 1997). Homozygote excess in the other sites studied is either the result of a contained, local mutation in the primer site; evidence of violation in Hardy-Weinberg; or the Wahlund Effect (Frankham et al. 2010).

It is clear that isolation between UK and Spanish populations as well as between Spanish catchments has occurred and that migration within catchments in the UK and Spain are occurring.

Similar international results were found by (Rajagopal et al. 2009) in a study between D. polymorpha from London and Spain’s east coast, further supporting these conclusions. Moreover these methods have proved sufficiently powerful for use in invasion studies and will prove invaluable to future work on D. polymorpha invasions. Any attempts to expand or enhance these methods are welcomed.

4.6 Acknowledgements

Our thanks are extended to NERC for a studentship to RM and our CASE Partner, APEM Ltd for additional funding and support. Additional funding was provided through the Research Grants

Scheme of the Malacological Society of London. We would also like to thank A Moolna and S

Griffiths for their help and advice during the laboratory work.

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4.7 Supplementary Maps

Figure 34. Smaller scale map of differentiation between sites 1 and 2 with direction of likely gene flow indicated

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Figure 35. Smaller scale map of differentiation between sites 3 and 4 with direction of likely gene flow indicated

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Chapter 5: Spread and effects of D. poly in SQ

5.0 The spread and effects of the invasive bivalve Dreissena

polymorpha in a restored urban waterway

R. Mansfielda*, E. Hammonda, A. Williamsb, K. Hendryb, K. Whitea a: University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. b: APEM Ltd, Riverview, A17 Embankment Business Park, Stockport, SK4 3GN.

* University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. [email protected], Tel: 00447811363408

5.1 Abstract

While often described as highly damaging invaders, there has been a recent interest in the use of the zebra mussel, Dreissena polymorpha as a water management tool in eutrophic freshwaters.

The intentional introduction of this species into the redeveloped docklands known as Salford

Quays (Greater Manchester, UK) in 1994 provides an ideal system in which to assess the effects of such an intervention in an artificial freshwater system having low habitat heterogeneity. This paper examines the current status of the mussel population, their filtration capacity, seasonality and ecosystem effects. We show that D. polymorpha are able to exert a significant controlling force on pelagic production due to their capacity to filter large volumes of suspended matter, with consequent changes in water quality and phytoplankton abundance, similar to that seen in both natural lakes and mesocosm experiments. Analysis suggests the mussel population approaches and may occasionally exceed carrying capacity with consequent effects on larval recruitment and high levels of inter-generational completion. This led to a cycle of recruitment over a number of years which, when combined with a possible relationship between D. polymorpha and the toxic cyanophyte Microcystis aeruginosa, suggests that the population is not an entirely positive influence. As such we conclude that the use of this species in water quality management may yet have unwanted non-target effects.

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5.2 Introduction

Invasive species are an extremely damaging result of globalisation. The establishment of an alien organism and its development into an environmental hazard is a relatively rare event, comprising

<1% of total relocations (Firn et al. 2011); yet thanks to the scale of global transport, in the US alone economic damage from invasives is estimated at ≈$120 billion year-1 (Pimentel et al. 2005).

Some species have only a limited effect on their new environment such as the common goldfish

Carassius auratus (Colautti and MacIsaac 2004) while others, such as the European rabbit

Oryctolagus cuniculus may actually create new niche space and provide valuable ecosystem services in its introduced range (Lees and Bell 2008). Unfortunately a large number of invasives are also responsible for out competing local organisms and re-engineering whole ecosystems

(Pimentel et al. 2000). A prime example of such an organism is the Zebra Mussel, Dreissena polymorpha (Nalepa and Schloesser 1993) which, being both highly fecund and extremely adaptable, has been listed as one of the ‘100 worst’ invaders worldwide (Lowe et al. 2000). Once established, populations can reach 10,000-100,000 individuals m-2 with one study reporting densities of 750,000 individuals m-2 (Ludyanskiy, Mcdonald & Macneill 1993; Effler & Siegfried

1994). Colonisation is often rapid owing to their unique (among freshwater bivalves) planktonic dispersal phase and ability of each female to produce a million veligers within 1-2 years of settlement (Ludyanskiy et al. 1993). Such is the success of the zebra mussel that population density is able to overshoot the carrying capacity of the lake, causing food limitation for pelagic organisms, including maturing veliger. This process can lead to large population fluctuations in some areas and corresponding changes in local ecology that can severely affect biodiversity and complicate water management (Strayer and Malcom 2006).

Estimated costs arising from blocking of US water inlets and machinery are in excess of US$267 million (Connelly et al. 2007). In the UK, populations exist across the country and a great number of these ecosystems show evidence of damage (Oreska and Aldridge 2010).

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Once established, D. polymorpha will alter an ecosystem by taking nutrients and energy out of the water column and transferring them via senescence and pseudofaeces onto the sediment (Higgins and Vander Zanden 2010). Such transfer has the effect of promoting the benthic fauna while causing a substantial drop in the pelagic biomass (Higgins and Vander Zanden 2010). The additional effect of this pressure can be large shifts in phytoplankton community composition, with mussel-infested areas favouring smaller, fast reproducing species such as small chlorophytes and cryptophytes (Higgins and Vander Zanden 2010). Promotion of cyanobacterial species has been reported in the literature (Vanderploeg et al. 2001) but there is clear variation in the strength of this relationship between systems (Higgins and Vander Zanden 2010). Recent studies suggest other factors such as trophic state work in tandem to promote algal blooms (Sarnelle et al. 2012).

Despite the possibility of algal blooms from the presence of zebra mussels, eutrophic lakes and reservoirs have often been reported to be rendered oligotrophic by large infestations (Reeders and Bij de Vaate 1990). This ability was noted by Richter (1986) who suggested that D. polymorpha could be utilised as an algal control agent. A subsequent trial use in the

Volkerakmeer, The Netherlands removed 69% of all suspended matter entering the lake from a feeder stream (Nalepa and Schloesser 1993). Interest in this form of control subsequently waned as concerns about the efficacy and safety of biological control systems became apparent but there has been some modern interest in reviving the use of this species in control efforts

(Mclaughlan and Aldridge 2013).

The establishment of a population in Salford Quays, Greater Manchester, UK in 1994 (hereafter

SQ), was therefore considered to be an appropriate solution to the dense blooms of the cyanobacterium Planktothrix agardhii which were present in the system. Post-introduction monitoring has shown that zebra mussels did not contribute to the decline in algal blooms but may have been responsible for a subsequent shift in phytoplankton community and overall abundance. It has also been suggested that D. polymorpha in SQ have been responsible for the

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Chapter 5: Spread and effects of D. poly in SQ promotion of the occasional autumnal bloom of Microcystis aeruginosa since 2004 (see Chapter

2.0).

Salford Quays were created from Manchester Docks as part of a large urban regeneration project in the 1980s (Bellinger et al. 1993). Prior to this they were connected to the Manchester Ship

Canal (MSC), a large, highly polluted navigation connecting Greater Manchester to the Mersey

Estuary (Gray 1999). Their industrial past meant that the area suffered from high inputs of sewage and pollutants, many of which were deposited to the sediments. In addition, low flow rate and vertical sides in the MSC led to near permanent stratification and bottom water anoxia. Both have been eliminated through the isolation and artificial mixing of the dock basins by installation of

Helixor mixing systems, accompanied by a number of habitat diversification projects. In addition, a number of organism introduction events have sought to correct low biodiversity and algal blooms, including fish diversification in 1992 and the authorised introduction of D. polymorpha as a biocontrol agent in 1994. The site of the zebra mussel introduction is given in Figure 36 and consisted of 15 mesh bags containing an average of 50 mussels measuring 20-25mm (W M

Bellamy Unpubl.)

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Since impoundment there has been a precipitous decline in TP and TN levels (although a recent increase in N has been noted; see 2.0) and a concurrent decrease in algal densities. This has been accomplished by a corresponding change in community composition from the cyanobacterium

Planktothrix agardhii dominance in 1990 to 2001, to large chlorophytes in 2001 to 2005 and finally small flagellates and diatoms since 2005 (see Chapter 2.0). It was suggested that this final assemblage was associated with an apparent increase in D. polymorpha densities after what appears to be limited population growth following introduction.

With a species from such a large geographic area as D. polymorpha it is important to understand environmental tolerances as authors have reported varying environmental optima for the species from different areas (e.g. Walz 1978; Lei, Payne & Wang 1996). It has also been suggested that the effect of small introductions and low initial genetic diversity may have an effect on local tolerances (Crooks and Soulé 1999). Indeed, this has been attributed to the die back of D.

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Chapter 5: Spread and effects of D. poly in SQ polymorpha in NW Britain around the year 2000 (Aldridge et al. 2004). For this reason the seasonal variation in filtration ability, especially during winter and summer is of interest as this will determine the seasonal effect on the aquatic environment and where the maxima occur.

This paper examines the current status of the mussel population in SQ and their overall filtration capacity. Its goal is to determine the current effect of D. polymorpha on the biotic and abiotic environment in SQ and confirm or deny the relationship between the zebra mussel and phytoplankton community structure indicated in Chapter 2.0. This will serve not only as a contribution to the recent renewed debate about utilising D. polymorpha as a management tool

(Mclaughlan and Aldridge 2013) with a focus on redeveloped docklands but also of the way in which zebra mussels can affect an infested ecosystem. We will seek further evidence for the mechanisms behind the relationship between D. polymorpha and M. aeruginosa including the influence of water temperature on filtration capacity. An understanding of the effect of temperature is of vital importance to those planning water remediation operations, or seeking to understand the effects of this species on the natural biota of the NW UK as it will determine the size of spring and autumnal blooms and may even affect the intensity of the clear water phase.

Finally we will determine if there is an effect of D. polymorpha on the physiochemical environment within the quays and what current population demographics are, including an assessment of limitations to further expansion.

5.3 Methods

Dive survey data have been obtained by APEM Ltd in 2000 and 2010. The 2000 survey was

2 conducted using a 4608 cm quadrat placed at depths of 1, 2, 3 and 4m at 10 m intervals across the dock walls in all basins except Huron (Figure 36), this gave a total replicate number of 35 sets of 4 quadrats, totalling 140 counts. Zebra mussel counts were conducted by touch and samples were obtained from 5 sites for later analysis of length and thus an inference of age class.

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The 2010 survey utilised the same dive company and was conducted using a 1 m2 quadrat at depths of 1, 3, 5, 7 m (or simply maximum depth if sediment build up or detritus prevented a 7m quadrat) at the locations indicated in Figure 36 giving a total sample number of 28. Counts were conducted by visual counting of photographs owing to increased water clarity compared to 2000.

As before a representative sample was requested for determination of mussel length and between 17 and 252 mussels were collected from each basin with instructions that a representative sample be collected from each quadrat.

Ex situ filtration rate estimates were obtained using SQ mussels and the methods of Kraak et al.

(1994) modified as in Bellamy (1997). A number of species of planktonic algae were used to assess if there was any variation in filtration ability as the community changed. Five mussels of either 15 mm (the average in SQ) or 22 mm (the original size introduced and upper level of modern SQ mussels) were placed into a tank (N=5 per treatment) containing 3 litres of aerated standard snail water (Thomas et al. 1975). Algae were then added to reach appropriate concentrations (see below) and the change in numbers over 60 minutes was recorded by counting on a Sedgwick rafter. Species tested were Chlamydomonas reinhardtii 30,000 cells ml-1 (comparable to previous work e.g. Walz 1978; Lei, Payne & Wang 1996), C. reinhardtii 1,000 cells ml-1 (equivalent for the modern SQ and Planktothrix agardhii 500 cells ml-1 (to assess effect of earlier SQ species dominance). A) mixed community of 20% Cryptomonas ovata, 60% Cyclotella sp. and 20% C. reinhardtii 500 cells ml-1 similar to modern SQ with a number of representative species was also examined to determine if substitution with a similar biovolume of Chlamydomonas would be appropriate in future analysis (an assumption often implicit in past work e.g. Kraak et al. 1994).

Further to this an inoculation of C. reinhardtii 1,000 cells ml-1 was added at 2, 4, 7, 12, 17 and

20°C to determine the temperature-induced seasonal pattern of filtration in SQ. Mussels were randomised at each water change and left for 1 week to acclimatise for each temperature measurement. Temperatures were attempted in sequence so it is not possible to discount the possibility of time dependent variation linked to their captivity, however, with the requirement

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Chapter 5: Spread and effects of D. poly in SQ for manual counting there was insufficient time and resources to control for this variable. It was, however, assumed that the two week acclimatisation period after collection allowed any changes relating to captivity to occur before experimentation began.

Changes in cell density were converted to an estimated filtration rate per hour using the equation given by Coughlan (1969):

Where m = filtration rate (ml hr-1), M = Volume of tank (ml), n = animals in tank (individuals), t it duration of experiment (hours), D and C indicate the density of cells in the experimental and control tanks at time 0 and at time t, indicated by subscript.

Filtration rate at temperature was then fitted to a LOESS so an estimation of filtration could be determined for any temperature over a yearly cycle (Cleveland 1979). Filtration rates for SQ could then be calculated using:

∑

Where R is total proportion filtered for a basin per day at temperature t, r is filtration rate per mussel (mm day-1) at temperature t, N is number of mussels per m2 at depth d, W is colonisable wall perimeter at depth d (m2) and V is the volume of the basin in question (ml).

To monitor mussel settlement rates and thus interspecific competition with adults, a number of colonisation plates were introduced to SQ. These consisted of 30x15 cm slate panels mounted on untreated wooden boards and were attached together to achieve a final depth distribution of 0m,

3m and 6m. One of these was placed at the western and one at the eastern end of Ontario basin.

These were placed at the start of the year and checked regularly when boat based surveying was undertaken in SQ (n=8). A single plate was also placed at 1.5m in Welland Lock connecting SQ to

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Chapter 5: Spread and effects of D. poly in SQ the MSC to determine if larval dispersal via this route was possible, as ingress has been suggested

(Williams et al. 2010).

5.4 Results

Size distribution of mussels from the 2010 survey show that populations from the smaller basins have a larger inter-quartile range than the larger areas, while St Louis and St Francis also have a similarly larger average size than other basins. No determination of size in the Huron basins was possible owing to low sample size.

Figure 37. Box and whisker plot of D. polymorpha size distribution in each basin of SQ from the 2010 dive survey. Box indicates median and interquartile range, whiskers are given by the most extreme data point within one inter quartile range, notch overlap indicates similarity (Chambers et al. 1983).

The 2000 survey only found D. polymorpha in Ontario basin where average density was 21 mussels m-2 and all individuals were found between 2m and 3m depth. By 2010 there had been an increase in densities of several orders of magnitude and mussels had colonised all the other basins. ery few ( = 8.8 ind. m-2, σ 16. ) D. polymorpha were however seen in Huron basin. The

2010 survey also found that mussels had encrusted any available hard surface including concrete

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Chapter 5: Spread and effects of D. poly in SQ and scrap metal. Discarded plastic bags on the sediments of all basins were also colonised and a build-up of shell debris was observed throughout all but Huron basin.

Huron A Huron B Ontario A Ontario B St Francis St Louis St Peter

4 Depth (m) Depth

0 2 4 6 0 2 4 6 0 2 4 6 0 2 4 6 0 2 4 6 0 2 4 6 0 2 4 6 Density 1000s m 2

Figure 38. Mussel density with depth for each dive transect of the 2010 survey

Dive transects (Figure 38) clearly showed very few mussels near the surface and maximal densities at around 3 m in St Louis and Ontario, after which a gradual reduction is evident. In St

Francis and St Peters increase in mussel density do not occur until below 3m with the latter peaking at 7 m and the former at 5 m.

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10.0

7.5

2000 5.0

2.5

0.0 Freq. 60

2010 40

0 10 20 30 Length (mm)

Figure 39. Mussel size distribution in 2000 and 2010

There were large size differences in the populations between the two time periods. Mussels collected in 2000 are not only on average 10mm larger than their 2010 counterparts but there would appear to be a change in population structure. The earlier survey found a bimodal distribution and two distinct age classes while the later survey noted a single clear population peak and a positively skewed distribution (Figure 39).

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Chapter 5: Spread and effects of D. poly in SQ

600

) 500

1 -

400

300

200

FiltrationRate (ml hr 100

Figure 40. Filtration rates and standard deviation for mussels at 15 mm (squares) and 22 mm (diamonds) for different algal groups. Data from Bellamy (1997) are denoted by triangles. Low density Chlamydomonas and Planktothrix filtration rates (starred) were significantly different from one another but within these pairs mussel sizes were not significantly different

Filtration rate differences between phytoplankton species assemblages (Figure 40) were analysed using type II unweighted two-way ANOVA (interaction term not significant; P>0.5). While cell density differences are likely to be important, the adjustment of cell counts to filtration rate allows a direct comparison. This shows that filtration rates are significantly different between species (P<0.05) but, perhaps surprisingly, mussel size is not a factor (P>0.1). This level of significance is caused by the difference between high concentration C. reinhardtii ( = 275 ml hr-1

σ 12 ) and P. agardhii ( = 122 ml hr-1 σ 66) suggesting reduced capacity when feeding on the latter. The similarity between C. reinhardtii in both high and low ( = 202 ml hr-1 σ ) concentrations and community filtration rate ( = 237 ml hr-1 σ 32) confirms that they are a reasonable surrogate for the natural biota of SQ and therefore suitable organisms to use in experimental conditions in this instance. The community assemblage also showed no significant

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Chapter 5: Spread and effects of D. poly in SQ change in species composition due to filtration (chi sq. P>0.05).

12.0

10.0

- m

8.0 spat

6.0 0m 3m

4.0 6m D. D. polymorpha

2.0

0.0 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

Month

Figure 41. Mussel spat settlement over time in Ontario basin in 2010

Assessment of spat settlement suggests that spawning rates are relatively constant throughout spring and autumn with cessation occurring in the winter months and reduced rates in the summer (Figure 41). Larval settlement is greatest at 6 m. Growth of the macroalgae Cladophora sp. probably prevented settlement of a large number of larvae on slates close to the surface.

Overall colonisation is very low and no individuals were present on the slate placed in Welland

Lock, linking SQ to the Manchester Ship Canal.

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Chapter 5: Spread and effects of D. poly in SQ

Figure 42. Filtration rates obtained at various temperatures and LOESS line of best fit with 95% confidence interval shown

Francis Louis Ontario

100

15 75

10 50

0 0 day Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec

Peters

15 Proportion

Chlorophyll a Chl a 10

d$prop Prop.

5 0 Mar Jun Sep Dec d$date

Filtration capacity shows a rapid increase from 2 to 12°C and a more gradual decline with further increases to 20°C (Figure 42). When these data are used to calculate percentage of each basin filtered by mussels day-1 using filtration rate per mussel multiplied by approximate total density then divided by volume of the basin (Figure 43) a relationship can be seen between the

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Chapter 5: Spread and effects of D. poly in SQ commencement of grazing in the spring and the cessation of the spring algal bloom. While this also occurs in Huron basin, subsequent production suggests it to be part of a normal clear water phase (Sommer et al. 1986). In the other basins post-spring bloom algal production is low, with the exception of St Peters which does show some growth; likely a result of the lower overall filtration capacity compared to the other infested basins.

5.5 Discussion

While in some areas of SQ the majority of the colonisable surface area has been covered, distribution both vertically and horizontally is not uniform. Populations area generally low at the surface where competition with macroalgae for space limited settling (Molloy et al. 1997). Indeed, in shallow areas such as below horizontal underwater pipes, large numbers of encrusting mussels were frequently found (pers. obs.). The presence of larger specimens in St Louis and St Francis is unlikely to be due to population age as no mussels were found in these basins during the 2000 survey. Neither is it likely a result of differing populations as all mussels in SQ are genetically very similar (see Chapter 4.0). The principal difference is that the smaller basins possess reduced wall space available for colonisation owing to a slope in the east and west facing walls (Bellinger et al.

1993). This differing morphology effectively halves the available substrate for D. polymorpha and thus increases the available resources to those still present, therefore allowing increased production on the remaining surfaces. A more in depth dive survey would be required for confirmation but bankside observations suggest this is the case. While no D. polymorpha were found in the soft sediments, all hard surfaces were heavily colonised. Berkman, Haltuch & Tichich

(1998) found that in Lake Erie shell debris could ultimately make soft sediments colonisable. Such a diversification may constrain growth rates and fecundity of D. polymorpha as resources become more limited and cause a further reduction in phytoplankton production and increases in benthic invertebrate diversity, as was seen in Lake Erie (Bially and Macisaac 2000).

The reduction in average length of mussels between 2000 and 2010 indicates density dependence, which could occur at lower concentrations of mussels provided food supplies (in this

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Chapter 5: Spread and effects of D. poly in SQ case suspended matter such as phytoplankton) were low, as seems to be the case here.. There remains the possibility that the dive team may have introduced bias through improper sampling

(i.e. only collecting larger, easily accessible mussels) however clear instructions were given to avoid such a bias. While densities are lower than those reported in other studies, the lower nutrient levels in SQ likely provide a reduced level of overall algal production and thus a lower energy resource for mussel growth. As mussel population expansion likely took place around 2005 it is unlikely to be the result of recent rapid population growth, unless some large population crash occurred. Unusual size distributions were also noted in the Huron Estuary by Strayer &

Malcom (2006) and were explained by dominance of well recruited cohorts competing with larvae for space and resources. This creates a situation where average size and population density vary as the dominant cohort matures and then a new one establishes, leading to an excess of small, young mussels and eventually, exceptionally high filtration rates as carrying capacity is overshot by the filtration abilities of maturing veliger. Older populations are typified by lower densities of large mussels with a more defined generational gap with lower overall filtration rates which creates a 3-5 year cyclic recruitment pattern (Strayer and Malcom 2006). This may also explain the yearly differences in phytoplankton community composition noted by APEM Ltd with years of greater filtration leading to cryptophyte dominance and lower filtration allowing diatoms and chlorophytes to occur in larger numbers (Higgins and Vander Zanden 2010). Categorical determination of density dependence would require determination of the rate of natural increase in the phytoplankton against all other controlling variables for which insufficient data are available. However, a spring turnover rate of near 100% in Ontario basin combined with mesotrophic chlorophyll levels is unlikely to satisfy energy requirements, especially as most phytoplankton seen in SQ possess low levels of polyunsaturated fatty acids (PUFAs), an essential nutrient for D. polymorpha reproduction (Wacker and Von Elert 2003).

The dive survey data for D. polymorpha in SQ suggests that the population was eliminated from around the site of introduction between 1992 and 2000. A population crash was also observed

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Chapter 5: Spread and effects of D. poly in SQ elsewhere in the UK during the 1990s, and was especially noted in the Manchester area (Aldridge et al. 2004). However some individuals were able to survive in SQ while populations in Preston,

Mersey and their original introduction site in Goole, northeast UK show complete natural eradication (Aldridge et al. 2004), the latter now being a habitat for Anodonta sp. (pers. obs.), a species usually out competed by D. polymorpha (Aldridge et al. 2004). Aldridge et al. postulated that if the majority of D. polymorpha in the UK stem from a single 19th Century introduction then an inherent susceptibility to changing climate or water quality patterns may have reduced population abundance. The result of this die back will be that no cyanobacterial control was present at the cessation of algal blooms in 2001, despite that being the overriding goal of their introduction (Bellamy 1997). Initial poor recruitment seen in SQ may also have been encouraged by P. agardhii dominance this species has extremely low PUFA content (Wacker and

Von Elert 2003). Population expansion may therefore be a direct result of the shift from permanent P. agardhii dominance to that of more energetically favourable chlorophytes.

Preferential grazing of such high value species by D. polymorpha would explain their subsequent removal from all basins in 2004/5 (Figure 17)

Our recorded filtration rates using C. reinhardtii fall within the range given by other authors (e.g.

Walz 1978; Lei, Payne & Wang 1996) increasing the confidence in our observations. Filtration of the ‘average’ community was high and while there was no noticeable change in species composition, it is possible that the less nutritionally beneficial species would be rejected as pseudofaeces and not re-suspended (Vanderploeg et al. 1996). Most notable from these results is the reduced capacities shown in the presence of P. agardhii, likely a result of toxin production or handling difficulty (Higgins and Vander Zanden 2010).

Schulte & Spezia (1975) suggested that the filtration capacity in the marine mussel Mytilus edulis followed a rough n-shaped quadratic distribution with filtration commencing at 5-10°C and ceasing between 20-30°C. Similar patterns have also been recorded in D. polymorpha by Lei,

Payne & Wang (1996) who found cessation began >25°C and Walz (1978) who found suppression

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Chapter 5: Spread and effects of D. poly in SQ began at >15°C. This is similar to the trend here and likely related to the latter mussel population being of European descent and the former being collected from the Great Lakes and thus subject to differing founder effects and selective pressures. We did not exceed 20°C in our laboratory experiments as it was not ecologically significant for SQ where the maximum surface temperature in the last five years has never exceeded 21°C (pers. obs.). Despite this, a slight inhibition above

15°C that may offer a degree of summer release for the phytoplankton population.

By combining rate and density estimates it can be seen that all basins bar Huron and Peters have a turnover time sufficient to have a significant effect on the aquatic community. In all basins there would appear to be a relationship between the onset of filtration and the cessation of the spring bloom. D. polymorpha are, therefore, likely to be having a significant effect on the whole pelagic ecosystem by, for example promoting certain genera of phytoplankton and competing with zooplankton (Higgins and Vander Zanden 2010). Species such as M. aeruginosa are more likely be related to D. polymorpha under oligotrophic conditions (Sarnelle et al. 2012), a trophic state which SQ may be approaching (see Chapter 2.0). Thus the continuing water quality changes may promote M. aeruginosa populations, especially as blooms appear to have begun in 2004, the same year that D. polymorpha expansion occurred.

Spawning activity of D. polymorpha would appear to be seasonal, with peaks in the spring and autumn to coincide with periods when algal production will be at its greatest and thus a way to maximise offspring survival Wacker & Von Elert (2003). Settlement rates also suggest that several years would be required to achieve total coverage of a submerged surface and significantly lower than the 209-2503 ind. m-2 found by (Nalepa and Schloesser 1993) although this may only be a result of current density dependence.

It is interesting to note that a colonisation slate positioned in Welland Lock did not show D. polymorpha settlement indicating that this route is unlikely to be an important invasion vector into the Manchester Ship Canal. Containment could therefore be affected by education of the local water users and limitation on traffic (Yankovich and Haffner 1993). Unfortunately the 130

Chapter 5: Spread and effects of D. poly in SQ detection of populations in areas along the Bridgewater Canal (see Chapter 4.0) suggest that the species may already of spread sufficiently to render such confined control measures ineffective or alternatively that vectors into both environments from elsewhere are present.

We conclude that the D. polymorpha population in SQ is exhibiting a strong effect on phytoplankton production and is present at a sufficiently high density to approach the limits of its carrying capacity. While isolated from other water bodies, molecular studies have suggested gene flow further down the canal (see Chapter 4.0) and therefore recreational anglers (the likely vector in such relocations Griffiths et al. 1991) should be educated to prevent anthropogenic dispersal. It is also worth noting that studies on the public perception of a D. polymorpha infestation may not be negative. Indeed in systems where clear water is a boon a population may serve to increase tourism and property prices (Limburg et al. 2010). This does of course ignore the ecological consequences of such an introduction but does underline the complex interplay of ecosystems and society. We therefore largely in favour the promotion of D. polymorpha in areas where they have already established, especially in similar, artificial and heavily polluted waterways. It does appear however that the increased propagule pressure may present problems to containment and their effectiveness is highly dependent on the current nutrient regime.

5.6 Acknowledgements

R. Mansfield is in receipt of an NERC CASE studentship with APEM Ltd and we would like to express our thanks to both organisations for financial support. In addition we would like to thank the dive team involved in this work and A Dean for his assistance in cell culture.

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Chapter 6: Current effects of D. poly in SQ

6.0 Annual and inter-annual water quality variation in an

enclosed dockland and its relationship to the filter-feeding

bivalve Dreissena polymorpha: implications for future

management

* University of Manchester FLS, Michael Smith Building, Oxford Rd, Manchester, M13 9PL, UK. [email protected], Tel: 00447811363408

6.1 Abstract

There have been a number of recent studies on the use of the invasive zebra mussel, Dreissena polymorpha in water quality management, despite its highly invasive nature. In this paper we use two years of intensive water quality monitoring data to examine the effects of high densities of this organism in a redeveloped freshwater dockland, Salford Quays (Greater Manchester, UK).

Through comparison of infested and control sites it is concluded that densities are sufficient to limit phytoplankton production to oligotrophy, despite a clear excess of nutrients. In addition we show that community composition under grazing pressure is changed markedly, being limited to small, R-selected diatoms, chlorophytes and cryptophytes while unaffected areas display larger colonial chlorophyte species. Finally we show that the association between D. polymorpha and

Microcystis aeruginosa in Salford Quays may be a result of inhibition of grazing in summer temperatures leading to a zooplankton resurgence and a dominance of inedible algae. As such we suggest caution in their future use as a management tool.

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Chapter 6: Current effects of D. poly in SQ

6.2 Introduction

With a realisation of the value of lakes to biodiversity (Strayer and Dudgeon 2010) and their importance of water security (Suweis et al. 2013), there have been a number of both national and international legislative moves to improve the quality of lotic ecosystems . The most important in the UK is the EU Water Framework Directive and Water Resources Act 1991 and others exist in

America (Clean Water Act 1972), China (Water Law 2002) and Australia (Water Act 2007). One of the most pervasive problems in the aquatic environment is that of cultural or anthropogenic eutrophication (Jørgensen et al. 2004) caused by excessive anthropogenic inputs; primarily of N and P, the most frequently limiting nutrients in freshwater environments (Reynolds 2006). This lessens the amount of nutrient mediated or bottom-up control and, in the absence of high levels of particulate matter or the competitive effects of macrophytes, eutrophication will usually result in excess primary production and often a switch to larger, inedible and often toxic species of phytoplankton (Fogg et al. 1973). Densities of these organisms can become high enough to cause mass mortality through intraspecific competition, resulting in decomposition products, anoxia and biodiversity loss across all trophic levels (Fogg et al. 1973). The prevalence of inedible algae will decrease the efficiency of the top-down controllers, the zooplankton, and thus limit the availability of energy to other organisms and may lead to dramatic changes in ecosystem function as exemplified in changes in phytoplankton standing crop and zooplankton biomass (see Figure 1,

Chapter 1). Such changes are usually to the detriment both of natural biodiversity and ecosystem service value and have been reported in numerous ecosystems since the middle of the last century (Hutchinson 1969).

There are a number of potential solutions to anthropogenic eutrophication. Although reductions in pollutant inputs are the most obvious this may be difficult to achieve as many modern sources are agricultural fertilisers, promoted by cheap availability and government subsidies. This creates a large number of diffuse sources and/or social, economic and political barriers to change.

Alternative, albeit temporary, solutions are to force a change in the food web through the

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Chapter 6: Current effects of D. poly in SQ addition of macrophyte competitors or manipulation of the fish community to reduce algal biomass. In saline and, to an extent, brackish environments substrate for filter feeding organisms can be added to increase the speed at which nutrients and phytoplankton are sequestered in the sediments, as was done in the highly successful restoration of Liverpool docks, UK (Hawkins et al.

1992). Unfortunately in freshwater environments there are few species capable of similar effects and instead chemical controls such as barley straw that releases algicides’(Jørgensen et al. 2004) are used.

In 1990, the use of the invasive Ponto-Caspian species, Dreissena polymorpha (Reeders and Bij de

Vaate 1990) was trialled as a means to control anthropogenic eutrophication. Despite positive results in experiments by Reeders & Bij de Vaate the concept has not been widely adopted owing to concerns about the effects of invasive species in new environments. This is especially relevant in the case of D. polymorpha as they have been listed as one of the hundred most damaging invaders in the world (Lowe et al. 2000) owing to their highly fecund nature (a mature female may produce >1 million larvae year-1), planktonic dispersal and ability to reach densities in excess of

10,000 individuals m-2 or more on any available hard surface (Higgins and Vander Zanden 2010).

Once established, D. polymorpha are highly effective in shunting nutrients and energy from the pelagic to the sediments due to their ability to filter large volumes of water (2-287 ml mussel-1 h-1;

Kryger & Riisgård 1988). They are thus able to remove phytoplankton and other particulates down to one micron (Jørgensen et al. 1984) while depositing in the sediments as pseudofaeces those that are inedible or present in excess .Filtration by zebra mussels will frequently lead to an increase in water clarity, even in systems where nutrient inputs remain high (Reeders and Bij de

Vaate 1990). This may appear advantageous (Limburg et al. 2010) but the ecological consequences can be catastrophic. An invasion into the great lakes of North America has led to large decreases in biodiversity and phytoplankton standing crop which are now serious conservation concerns (Vanderploeg et al. 2002). A summary of the main effects of zebra mussels in different aquatic environments is given in Table 7. Of particular note is the non-significant

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Chapter 6: Current effects of D. poly in SQ effect in most systems on soluble phosphates, despite a reduction in overall phosphorus levels. In rivers results were borderline significant, the result of large variation within the data, but were generally elevated. In areas where phosphate levels were increased, this was linked to sediment nutrient regeneration being more rapid than the ability of the phytoplankton community to reproduce. Other nutrients were unaffected in most cases but decreases in phytoplankton and zooplankton production were nearly universal.

In parallel with these changes, variations in phytoplankton community structure were also detected. Increases in the abundance of toxic cyanobacteria or less nutritionally favourable species are common. Most notable of these is the promotion of the toxic cyanobacterium

Microcystis aeruginosa which is often associated with zebra mussel infestation. Interestingly, recent studies have found that the intensity of M. aeruginosa promotion is inversely proportional to the levels of eutrophication seen within an ecosystem (Sarnelle et al. 2012), although no causal mechanism has been established. Toxin production may not only present a hazard to human health but also affect grazers and accumulate in higher trophic levels, impairing overall ecosystem function (Xie et al. 2005).

Lakes Pelagic– Rivers Enclosures Overall Littoral profundal Secchi depth 38.5% 30.7% 50.5% 71.4% * SS -39.7% -72.2% -46% -38.6% -58.8% DIN * SRP 429%a 393.8% TP -19.5% -20.8% -17.9% SiO2 * * Water column ﬂora/fauna Chl a -47.3% -37.8% -58.1% -78.3% -79.6% Zooplankton -51.3% -56.1% -76.5% * Benthic ﬂora/fauna Periphyton * * 170.5% * * Zoobenthos (excl. D. poly) 211.7% * Zoobenthos (incl. D. poly) 749% 1976% * *

Despite these potential problems and risks, there has recently been renewed interest in using D. polymorpha in water management, with the stipulation that such practices are only attempted in

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Chapter 6: Current effects of D. poly in SQ areas where they are already ubiquitous (Mclaughlan and Aldridge 2013). As such, a study of the short and long term effects of this species in ecosystems where water management is undertaken would be of enormous value. We have therefore collected a high resolution dataset of biological and physiochemical parameters from a well-studied invaded ecosystem known as Salford Quays

(Figure 44; hereafter SQ), a restored area of docklands in Greater Manchester, UK (area: 8.14 ha; depth 6.6m). The quays are an entirely artificial lake system developed from the old Manchester

Docks in the 1980s. Although initially a highly eutrophic system and subject to large algal blooms, the environment has since improved markedly and now approaches mesotrophy (see Chapter

2.0). Previous work on the Quays has taken advantage of the fact that the area represents an idealised macrocosm being basically interconnected cuboid tanks (depth 7m) with a constant mixing regime provided by the installed Helixor system (Williams et al. 2010). It is also interesting to note that since 2004 (the approximate date of D. polymorpha population expansion; see 2.0) there have existed brief autumnal blooms of M. aeruginosa throughout the quays which may be related to the resident mussel population. Detailed descriptions of management and ecology can be found in (Bellinger et al. 1993; Williams et al. 2010).

Previous work on the D. polymorpha population has already suggested that there is an effect on chlorophyll levels in Salford Quays and that, since the population expansion in 2002, turnover rates can approach 100% day-1 in the spring and autumn (Figure 43). In addition it has been suggested (Chapter 4.0) that the D. polymorpha populations within SQ may be subject to cyclic population fluctuations over the course of several years with differing levels of filtration and thus density dependence, an occurrence also seen in the Hudson River (Strayer and Malcom 2006).

Previous work (see Chapter 2.0) has related population growth to the presence of more energetically favourable species but the collection of high resolution data over two years, combined with knowledge of seasonal filtration patterns (see Chapter 5.0) will enable an examination of the controls acting on the environment.

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Chapter 6: Current effects of D. poly in SQ

This study therefore has a number of aims. It seeks to determine what the effect of using D. polymorpha for managing algal blooms in SQ has been and thus what the current patterns of seasonal planktonic and physiochemical succession are compared to other water bodies. It also seeks to determine to what extent these differences can be attributed to D. polymorpha filtration and how those differences relate to the effects seen by Higgins et al (Table 7). We also attempt to determine if density dependent processes are affecting D. polymorpha filtration and if so if this varies between years, using inter-annual and inter-basin patterns in plankton and nutrients. The results of this study will have wider relevance as SQ can be considered a lake macrocosm experiment with little littoral area, a controlled mixing regime and isolation from the rest of the catchment. Finally, this study also provides an opportunity to investigate the possible mechanisms linking M. aeruginosa blooms in SQ with the presence of D. polymorpha. With recent renewed interest in the use of D. polymorpha in management projects (Mclaughlan and Aldridge 2013) these data will provide vital information to managers interested in this species. It will help to determine if the risks of increased propagule pressure and non-target effects are acceptable and hence whether it is worth promoting greater mussel settlement for pollution and algal bloom management in existing infested systems.

It is hypothesised that all sites at Salford Quays except Huron Basin where mussel turnover can be below 0.2% day-1 (Figure 43) will display a degree of oligotrophication owing to infestation, with associated changes in suspended matter and phytoplankton community composition. The highly managed mixing regime may also amplify the effect of D. polymorpha as at no point is there a separation of the water column from the grazer community through stratification. The majority of variation in filtration pressure on the phytoplankton community will therefore likely be attributable to the density of mussels on the dock walls.

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Chapter 6: Current effects of D. poly in SQ

Figure 44. Diagrammatic representation of the Basins within SQ with minimum turnover time due to D. polymorpha filtration (see Chapter 5.0). Site names and locations are also shown.

6.3 Methods

Samples were collected from three sites to encompass the range of environments available in SQ

(Figure 44). St Louis has a much reduced surface area to volume ratio, sloped sides, littoral area and floating vegetated islands, Ontario has none of these but contains the largest densities of D. polymorpha and Huron has the largest Surface area to volume ratio, no littoral area or islands and only a limited D. polymorpha population. Sampling was carried out on a biweekly basis for two years although with occasional omissions owing to adverse weather or equipment failure. Water samples for nutrient analysis were collected from the sites indicated from both surface and bottom (within 1m of maximum depth) waters. As no significant difference was found owing to the constant mixing regime (P>0.05) these numbers were averaged to prevent pseudoreplication.

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Chapter 6: Current effects of D. poly in SQ

Nutrient analyses were conducted using a continuous flow analyser (Skalar Analytical B.V., The

Netherlands). Dissolved nutrients were separated off using a 0.45 μm membrane (Millipore).

Soluble Reactive Phosphate (SRP) was determined via the molybdate blue method, as was silicates, with the inhibition of phosphate reaction using oxalic acid (EA 1992). Dissolved Inorganic

Nitrogen was determined using reduction by cadmium and reacting with α- napthyethlenediaminedihydrochloride in the presence of sulphanilamide (EA 1981).

Surface samples were used for enumeration of phytoplankton via the Utermöhl settlement method (EA 1990). Fourteen millilitres of surface water were taken, fixed with Lugol’s Iodine, placed in a settlement chamber and then enumerated on an inverted microscope. Biovolume conversions were conducted using the values of Reynolds & Belllinger (1992), Stephen (1997) and

Dean (2004) and were assigned functional groups based on Reynolds, Huszar, & Kruk (2002). If identification of a species did not allow assignment to a specific grouping a range was used, for example Cyclotella spp. could belong to any of groups A-C so was simply labelled as ‘A-C’. A list of phytoplankton groups relevant to this study is provided in Table 8.

A 3 m vertical zooplankton trawl was taken and enumerated completely using a dissecting microscope. Counts of zooplankton were converted to filtration capacity using the equations of

Haney (1971) and Holtby (1986) and measurements of length obtained under a compound microscope for a subsample of individuals using a stage micrometer.

D. polymorpha density data have been presented before in Chapter 5.0 (Figure 38). Current densities were determined via a dive survey that utilised vertical transects with 1 m2 quadrats placed at 1, 3, 5, 7 m and at maximum depth in each Basin. A sample was taken to determine median length of the mussel population and these data were then converted to a filtration rate for any given temperature seen in SQ over the past 5 years using ex situ filtration rate experiments based on the methods of Kraak et al. (1994) at 2, 4, 7, 12, 17 and 20°C. Re-filtration rate (Yu and Culver 1999) was calculated but found to be ≈1 in all Basins. By combining these two set of observations an estimate of seasonal filtration rates was determined (Figure 43). 139

Chapter 6: Current effects of D. poly in SQ

Statistical analysis and graphing were conducted using R v2.15.3 (R Core Team 2012) and the packages MGCV (Wood 2006) and ggplot2 (Wickham 2009).

Table 8. Functional groups seen in SQ over this study and their descriptors (Reynolds et al. 2002)

ID Habitat Typical representative taxa Tolerances Sensitivities Clear, often well-mixed, Urosolenia, Cyclotella Nutrient A pH rise base poor, lakes comensis deficiency Vertically mixed, pH rise, Si Aulacoseira subarctica, Light B mesotrophic small- depletion Aulacoseira islandica deficiency medium lakes stratification Asterionella formosa, Mixed, eutrophic small- Light, C Si exhaustion C Aulacoseira ambigua, medium lakes deficiencies stratification Stephanodiscus rotula Shallow, enriched turbid Synedra acus, Nitzschia spp., Nutrient D Flushing waters, including rivers Stephanodiscus hantzschii depletion Tabellaria, Cosmarium, Nutrient Stratification pH N Mesotrophic epilimnia Staurodesmus deficiency rise Synechococcus, prokaryote Light deficiency Z Clear, mixed layers low nutrient picoplankton grazing Shallow, clear, mixed Koliella, Chrysococcus, low base X3 Mixing, grazing layers eukaryote picoplankton status Shallow, clear mixed Plagioselmis, Mixing, filter X2 layers in meso-eutrophic stratification Chrysochromulina feeding lakes Nutrient Shallow mixed layers in Chlorella, Ankyra, stratification deficiency filter enriched conditions Monoraphidium X1 feeding Usually, small, enriched Cryptomonas low light Phagotrophs Y lakes Shallow, enriched lakes Pediastrum, Coelastrum, Settling into low J - ponds and rivers Scenedesmus, Golenkinia light

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6.4 Results

Figure 45. Chlorophyll concentrations (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown

Chlorophyll trends (Figure 45) show clear differences between Huron and the other basins after the initial spring phytoplankton bloom (between weeks 9 and 20). Huron shows a continued cycle of phytoplankton production compared to very limited algal biomass elsewhere for the remainder of the year. The exception to this is a brief but notable spike in phytoplankton abundance in

Ontario Basin in the autumn of 2010. The absence of a second peak in the spring bloom of 2011 in both Ontario and St Louis Basins is also worth note. Statistically, comparison of trends is complicated by the brief nature of several peaks in algal biomass. Nevertheless, significant differences were found between autumn production (weeks 25-40) in 2010 (ANOVA, P<0.01) between Louis and Huron basins and in 2011 between both Louis/Huron and Ontario/Huron no difference was discernable for between year autumnal production (ANOVA, P<0.01). No

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Chapter 6: Current effects of D. poly in SQ significant difference was found between basins for spring production (weeks 1-20) in either 2010 or 2011 (ANOVA, P>0.05). Between year spring production was significantly different (ANOVA,

P<0.01). See 6.7 for post hoc tests.

Figure 46. Zooplankton filtration (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown

Zooplankton abundance (Figure 46) is clearly strongly affected by chlorophyll (Figure 45) with peaks in grazing following shortly after increases in algal production. The autumnal peak in St

Louis Basin is notable for its comparative size compared to phytoplankton production, and the much reduced production in Ontario Basin in 2011 is also worth noting.

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Phosphate levels (Figure 47) are generally low in all Basins and occasionally approach or fall below limits of detection (5 μg l-1 by these methods). The most interesting trends in 2010 are seen in St

Louis and Ontario Basins where levels gradually increase after the spring diatom bloom with a reduction in Ontario around the time of the brief autumnal spike in chlorophyll (see Figure 45). In

2011 SRP levels also increase after the spring bloom but levels are generally higher and there are a number of differences later on in the year. Phosphate levels in Louis are much reduced after week 38 while in Ontario there is a dramatic reduction between weeks 30 and 35 and after week

40, neither of these changes correlate to increases in phytoplankton biomass but in Louis there is a concurrent decrease in silicate levels (see below) which may indicate a brief diatom bloom that has quickly been consumed or settled out. No similar change in Si is seen in Ontario but a similar process with non-siliceous algae cannot be discounted. In both years in Huron Basin phosphate

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Chapter 6: Current effects of D. poly in SQ concentrations generally remain low until cessation of phytoplankton production in the late autumn.

Figure 48. Si (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown

Silicon levels (as SiO2; Figure 48) are high at the start of 2010 but drop quickly as diatoms utilise supplies which are deposited onto the sediments upon death owing to the high density of the frustule. After this point there is a general, if slight, increase in silicon in all basins that is likely affected by periods of diatom growth (below). In Louis and Huron Basins there is only limited release of Si into the water column over the winter of 2010 but mid-year increases are present. In

Ontario Basin, silicate increases in the winter but is rapidly sequestered and remains low for the duration of the year.

At no point over the two years did nitrate levels exceed limits of detection (≈400 μg l-1). Parallel monthly surveys by APEM Ltd also recorded levels below their limits of detection ≈100 μg l-1 in the

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Chapter 6: Current effects of D. poly in SQ winter of 2010. This could suggest periods of nitrate limitation; however, measures of Kjeldahl

Nitrogen conducted by APEM (pers. comm.) give mean levels of 1.14 mg l-1 (σ 0.73) suggesting ample N supply.

2010 2011

0.9

Huron

1 0.6

y a d 0.3

0.0

0.9

Louis 0.6

0.3 proportion of basinfiltred of proportion

a 0.0

r o

0.9

y l Ontario

o 0.6

. D 0.3

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0 10 20 30 40 50 0 10 20 30 40 50 Week Number

Figure 49. D. polymorpha filtration (points) and LOESS smoothed trends for the three dock Basins over a full annual cycle in 2010 and 2011 with 95% confidence interval (shading) shown

D. polymorpha filtration (Figure 49) is almost absent in Huron Basin. This is in contrast to St Louis and Ontario Basins where overall daily filtration approaches 50% and 100% of the total Basin volume respectively in spring and autumn. A marked reduction in overall filtration capacity occurs in the summer as a result of thermal inhibition of filtration (below).

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Chapter 6: Current effects of D. poly in SQ

Figure 50. Changes in phytoplankton functional groups in the three dock basins over a full annual cycle in 2010 and 2011. Normalised trend in chlorophyll is overlaid as a loess smoothing (from Figure 45). White line indicates M. aeruginosa bloom detection.

The phytoplankton community in SQ (Figure 50) is principally dominated by only a few functional groups. Centric diatoms of groups A-C such as Cyclotella sp. occur at the start of the spring blooms and generally increase towards the onset of the winter period. Y group flagellates such as

Cryptomonas and picoplankters such as Chlamydomonas minuta (group X) dominate during the middle of the year, although this dominance is skewed towards group X in St Louis and Ontario

Basins in 2010, as in Huron but with an increased prevalence of Y group compared to the other basins.. In 2011 in St Louis and Ontario, the summer production is typified by Y group phytoplankton, this is similar to Huron at week 28 but in this basin the Y group is replaced by the growth of J group chlorophytes such as Pediastrum duplex.

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In contrast to phytoplankton, zooplankton (Figure 51) show the same two phase distribution in every basin and year. Early grazing peaks shortly after the spring phytoplankton bloom and is dominated largely by calanoid copepods with occasional increases in cyclopoids. Zooplankton filtration rate falls in the summer and the community shifts to small filter feeding daphnids in the autumn. In Huron Basin there is a noticeable autumn bloom in both years but this is smaller in other basins with the exception of Ontario in 2010. These peaks coincide with an increase in phytoplankton production, a decrease in Dreissena filtration and the occurrence of M. aeruginosa.

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6.5 Discussion

Plankton dynamics in Ontario and St Louis Basins are similar to the oligotrophic PEG model (Figure

1) in that a spring diatom bloom develops as temperatures increase and continues until silicate is exhausted. As silicon limitation of diatoms occurs prior to the onset of intense grazing a second bloom of flagellates and nanoplankters occurs which uses much of the remaining phosphate. By this time (weeks 17-20) grazing by both zooplankters and D. polymorpha increases creating substantial top-down limitation and hence reduction in chlorophyll. At no point does zooplankton filtration rate alone seem to be sufficient to create full top down limitation ( estimated to be generally 30% at ~13°C Sommer, Gliwicz, Lampert, & Duncan (1986), let alone the dramatic control of phytoplankton seen in our study. This signifies the importance of D. polymorpha filtration and also supports the conclusion of Higgins et al. (2010) that zebra mussels are able to limit both zooplankton and phytoplankton abundance.

After the spring bloom has ceased there is a gradual increase in available phosphate in Louis and

Ontario Basins which continues until the following spring. The exception to this increase is a reduction in phosphorus in Ontario Basin in the autumn of 2010 which is linked to a brief algal bloom (see below). This gradual increase in nutrients suggests that phytoplankton are not bottom-up limited during the second half of a yearly cycle, yet chlorophyll remains generally low, as do zooplankton. The remaining possibility of trace element limitation is highly unlikely in an urban environment owing to deposition of both particulate and soluble pollutants (Azimi et al.

2003) and such a strong continuous effect due to pathogens would be unprecedented (Reynolds

2006). The remaining potential control in the quays, D. polymorpha, has been linked to large increases in SRP in river and enclosure environments (Higgins and Vander Zanden 2010). The proposed mechanism for such an increase is that grazing intensity greatly reduces phytoplankton standing stock to the extent that rapid growth is not possible and so allows nutrient release from the sediments to build up in the water column. This would explain a number of inter-annual and inter-Basin trends at Salford Quays such as low levels of SRP in Huron Basin throughout the

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Chapter 6: Current effects of D. poly in SQ growing season. The smaller increase in SRP seen in St Louis Basin can be attributed to the smaller area of available sediment for nutrient release, owing to the reconstruction works carried out in the 1980s which created a sloped gradient in each of the small basins and also involved the removal of the existing contaminated sediments (Bellinger et al. 1993). St Louis also contains a large biomass of macrophytes and macroalgae which compete with pelagic species for dissolved nutrients (Dodds and Gudder 1992).

In Ontario Basin a period of intense algal production occurred in the autumn of 2010 which sequesters much of the available phosphate. This is mirrored by an intense zooplankton peak and the presence of the grazing resistant M. aeruginosa which in 2010 resulted in the closure of water sports facilities. The instigator for such a change is unclear, however SRP does not appear to be responsible as levels were elevated for the majority of the autumn period and substantially higher in 2011 when no bloom occurred in either basin. Little evidence of similar peaks in zooplankton preceding M. aeruginosa blooms is evident in previous data (APEM Ltd, pers. comm.) although the short duration (2-3 weeks) would reduce the likelihood of detecting such a change over a monthly sampling regimen. Sarnelle et al. (2012) found that in low phosphorus environments there was a correlation between D. polymorpha and M. aeruginosa and postulated that the cause was the increased importance of D. polymorpha nutrient excretion to algal supply, a resource that

M. aeruginosa had access to if rejected in pseudofaeces. Given the timing seen here, we suggest the causal factor to be the effect of temperature inhibition on D. polymorpha reducing the intensity of grazing and thus allowing phytoplankton proliferation owing to the ample stores of soluble nutrients. The corresponding increase in zooplankton which follows then provides a niche for a grazing resistant species such as M. aeruginosa which may be further promoted by the higher temperatures at this time of year (Robarts and Zohary 1987). The possibility of nutrient access being a contributing factor is further undermined by the lack of a similar algal bloom in the autumn of 2011, despite higher levels of phytoplankton limitation. The absence of a 2011 bloom would make sense if it were a result of the higher filtration capacity of D. polymorpha as the

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Chapter 6: Current effects of D. poly in SQ maturing cohort approaches (or even temporally exceeds) carrying capacity (Strayer and Malcom

2006). The presence of a chlorophyll increase in just a single Basin and M. aeruginosa in all basins

(although highest in Ontario; APEM pers. comm.) adds another layer of complexity that we are unable to fully explain; but the spread of M. aeruginosa to other areas is likely owing to natural diffusion, propagule pressure and their highly competitive nature once established (Reynolds

2006).

The chlorophyll dynamics in Huron Basin are somewhat different to those in the other two basins.

While a spring bloom is evident and follows an identical pattern to elsewhere, the subsequent clear water phase is brief and followed by a further period of phytoplankton and zooplankton production. The increase in both these variables and lack of SRP accumulation would suggest that the absence of D. polymorpha is creating an ecosystem that is principally controlled by phosphate and creating a chlorophyll and zooplankton succession very similar to that seen in a mesotrophic

PEG model (Figure 1, Chapter 1). Interestingly, the autumnal bloom in Huron consists of J group chlorophytes such as Pediastrum and Scenedesmus which are favoured by the mixing regime in the quays. These species are usually found in higher nutrient environments than the species seen in Ontario and St Louis Basins (Reynolds et al. 2002) and, especially in the case of Scenedesmus, are a high quality food resource containing large amounts of energy in Polyunsaturated Fatty

Acids (PUFAs). Species containing such substances are preferentially taken up by D. polymorpha populations as they are vital nutrients for reproduction (Vanderploeg et al. 1996). Such an effect supports the hypothesis that zebra mussels are responsible for the limitation of diversity and size of the phytoplankton in SQ. Indeed the communities of Huron Basin are indicative of the phytoplankton communities recorded in all basins after the collapse of cyanobacterial production in 2001 and prior to the establishment of a large D. polymorpha population in 2004 (Figure 17) with continued presence of larger species such as Pediastrum sp. in Huron (Figure 50). Similar changes were noted by Higgins & Vander Zanden (2010) who showed that all groups except cryptophytes and chrysophytes were selected against and by Wacker & von Elert (2002 & 2003)

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Chapter 6: Current effects of D. poly in SQ who noted the importance of high PUFA species to D. polymorpha development. Interestingly this selectivity was not observed by Naddafi et al. (2007) who instead reported an avoidance of chlorophytes by zebra mussels but also observed that, in general, smaller nanoplankters were rejected as pseudofaeces. Selective feeding by the zebra mussel may therefore account for the relative abundance of smaller chlorophytes in infested areas of SQ. This would not require that the larger phytoplankters be more energetically beneficial, simply easier to ingest.

There are clear inter-basin and inter-annual differences in the phytoplankton and nutrient dynamics of Salford Quays, principally between Huron Basin and the other two sites. This is unlikely to be due to the measured physical variables as trends in solar radiation, mixing and precipitation are comparable between years. As there are still remnants of pre-Dreissena population increase phytoplankton in the Huron basin there is likely an effect on phytoplankton community change but without further evidence on the cause of this low density it is impossible to fully separate cause an effect with these data. By comparing the time at which the most dramatic changes in these variables occurred it would seem that D. polymorpha grazing is having a strong effect on the environment in SQ. It would therefore also follow that the increase in grazing caused by a maturing cohort of D. polymorpha could exacerbate these effects.

While most physiochemical variables indicate the quays are mesotrophic, the overall pattern of chlorophyll succession indicates oligotrophy. The exception is Huron Basin which shows a clear mesotrophic pattern. The apparent decrease in trophic state of the other basins in 2011 indicates further oligotrophication that we suggest is related to the D. polymorpha population (Higgins and

Vander Zanden 2010). Interestingly, the management of the mixing regime in SQ so as to prevent stratification has also created a number of interesting effects such as nutrient build up. Higgins &

Vander Zanden only saw such effects in river and enclosure experiments but it would appear that the assertion that the quays are a large scale macrocosm is indeed true. All other significant relationships in lake environments postulated by Higgins & Vander Zanden appear to have held and comparison of Ontario and Huron supports the majority of the claims of their meta-analysis.

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While D. polymorpha can result in an increase in ecosystem services in some freshwater environments (Limburg et al. 2010), their presence may result in a decrease in ecosystem service value in SQ, compared to the already clear waters that were present prior to population expansion in 2004. This is due to an increase in the incidence of algal blooms and anecdotal reports of a reduction in pelagic productivity at all trophic levels by local fishermen (pers. obs.), an observation that is likely to be accurate for the pelagic (Higgins and Vander Zanden 2010).

Comparative analysis of the three basins is complicated to a degree by their connectivity and the presence of at least some D. polymorpha in Huron Basin. Nevertheless, mussels are having a clear effect on water quality and are likely to be responsible not only for the oligotrophication of infested basins but also for the selective filtration of more energetically valuable species. Owing to their correlation with M. aeruginosa and the indeterminate processes involved, combined with their lack of efficacy during intense algal blooms before 2001 (see Chapter 2.0) we would advise caution in the future use of zebra mussels in water quality management. Gene flow between the

SQ population and another further west is also indicated (see Chapter 4.0) and increases in propagule pressure would significantly increase the probability of relocation (Mclaughlan and

Aldridge 2013), most notably to the nearby MSC.

6.6 Acknowledgements

R. Mansfield is in receipt of an NERC CASE studentship with APEM Ltd and we would like to express our thanks to both organisations for financial support. In addition we would like to thank

A Dean for his assistance throughout the practical element of this study, especially regarding the operation of the auto-analyser.

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6.7 Supplementary data: Tukey HSD tests for significantly different

chlorophyll patterns

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Chapter 7: General Discussion

7.0 General discussion

Salford Quays form a unique environment that has been formed from a highly degraded industrial docklands in Manchester. The work described in this thesis has charted this change and identified the likely causes of improvements (Chapter 2). I have also used these data to explore the use of non-linear models to predict changes in chlorophyll a concentrations over a yearly cycle, with clear improvements in accuracy over traditional models (Chapter 3). Chapter 4 examined the past and present distribution of D. polymorpha both within SQ and further afield with analysis of population connectivity in both Warrington and Spain. New data have been collected to determine the present conditions within SQ by quantifying the densities and capacities of D. polymorpha (Chapter 5) and comparing it to the annual trends in physical and chemical conditions

(Chapter 6). In doing so I have presented and described the seasonal progression of phytoplankton, zooplankton and essential nutrients in the quays and how it compares to the expected trends from the literature (Sommer et al. 1986), allowing a discussion about the use of this species in water quality management (Chapters 5 & 6).

Despite there being a number of management interventions in SQ (see below), it is clear from

Chapters 2 and 3 that the most effective have been isolation and mixing respectively. The former is to be expected as the removal of new pollutant inputs is the logical first step in any restoration project and allows ambient nutrient levels to fall (in SQ TP fell from a maximum 1125 μg l-1 in

1986 to <5 μg l-1 in 2007, and thus algal growth, to reduce (Jeppesen et al. 2007). This change was not immediate however and the initial response to isolation and mixing was a large increase in phytoplankton biomass (Chapter 2). This was a result of a rapid increase in photic depth without an accompanying drop in soluble nutrient concentrations until more than a decade later. Such disparity in limiting variables is an important lesson in taking a long-term perspective on restoration projects. While such a dramatic change in water clarity is difficult to achieve in most systems, a similar pattern was observed in Hoyer & Jones (1983) who conducted a meta-analysis of various lakes in 96 reservoirs across the mid-west of North America, they found that by adding 155

Chapter 7: General Discussion a term to explain inorganic suspended solid concentration could increase model R2 by 7%, and that this was a particularly important variable for many lake systems.

Gradual sequestration of nutrients into the sediments would not have been possible without the

Helixor systems which have proven to be highly effective in preventing water column stratification. As expected (Walker et al. 1993), they have been essential to the maintenance of an oxic surface layer and prevented the re-release of nutrients, especially the essential nutrient phosphorus which can now be limiting in the quays (although note the increased importance of D. polymorpha since 2005). Interestingly, the danger of increases in nutrient content through sediment mobilisation (Hamilton and Mitchell 1997) do not appear to have been realised, supposedly because the surface is sufficiently oxygenated that only aerobic particles are ever re- suspended. Artificial mixing to prevent stratification therefore holds great promise as it does not require the disposal of large amounts of contaminated sediments and also averts any other problems associated with stagnation. These include changes in REDOX that lead to toxic forms of ammonia and release of metal ions, as well as more noticeable issues such as the release of hydrogen sulphide, methane and floating fungal mats (Walker et al. 1993). It is, however, expensive and careful consideration of the costs and the benefits is necessary before installation, use in more rural settings for example would probably be difficult to justify owing to high economic costs and limited direct economic benefits. In Salford the high cost was apparent from the mid-1990s, ≈10 years after installation and the systems have since been micromanaged to obtain optimum efficiency as a response to fluctuating oxygen and chlorophyll levels. This management is accomplished through thrice weekly oxygen and temperature profiles to detect the presence of stratification, readings which are then used to set the timings of air compressor operation.

My work has shown that the Helixor systems are of greater importance than simple oxygen management (chapter 3). At exceedingly low and high periods of operation phytoplankton production is enhanced, a result of the length of time they are in the photic zone. By mixing

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Chapter 7: General Discussion effectively, phytoplankton are not at the surface for sufficient time to result in photo-inhibition

(Fogg et al. 1973) and not below compensation depth long enough to allow respiration to exceed photosynthesis (Reynolds 2006). It is difficult to find a corollary to this the literature, a close similarity exists between SQ and Montezuma’s Well, Arizona, USA (Boucher et al. 1984) (Figure

52). In this ecosystem, ingress of new water creates a regime of constant mixing as in the quays

but there are also very high CO2 levels and a band of macrophytes which limit the strength of comparison. Nonetheless it is clear that some similarities exist in phytoplankton community structure such as a preponderance of smaller chlorophytes and cryptophytes in both systems. In

Montezuma’s well, these communities exist in the absence of filter feeders but in the presence of equally constraining nutrient regimes.

Figure 52. Montezuma’s Well, Arizona, USA. The lake is fed by a number of underground springs that prevent stratification (Boucher et al. 1984)

There are decidedly few studies that directly refer to the efficacy of Helixor systems. A paper in

1 6 questioned their overall efficiency owing to the setting up of isolated ‘cells’ of overturn

(Ritchie 1969). This was attributed to the lack of any warm water to create density gradients and relatively shallow placement of the systems themselves, preventing whole water column overturn. A more recent study by Wilson & Beutel (2005) that reviews a number of Helixor installations notes the generally positive results when there is sufficient air output and correct placement to ensure overturn. They noted decreases in ammonia of up to 85% with no associated changes in SRP or nitrates while hypolimnetic oxygen concentrations could increase by up to four-

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Chapter 7: General Discussion fold during operation. Unfortunately ammonia could not be monitored during this study but

APEM data suggests an average of 102 μg l-1 (σ 136), excellent by UKTAG guidelines and suggesting levels have not been elevated by extended Helixor operation, although this decrease has taken more than a decade. It is clear that nutrient levels have drastically decreased in SQ and are likely aided by isolation. Despite these improvements, it is important to emphasise that pore water and organic matter content of SQ sediments remain at a level that would quickly lead to anoxia, nutrient release and a return to algal blooms should the system ever be inoperable for an extended period (Boult and Rebbeck 1999). The length of time required for this to take place is debateable and dependent on ambient weather but brief periods of Helixor inaction over the past

20 years suggest a number of weeks would be required before problems began (APEM pers. comm.). Other studies on the effects of different mixing systems in lakes invariably deal with environments that are still subject to pollutant inputs (Wilson and Beutel 2005). In such situations it has been shown that often the effects of increased organic matter decomposition and phosphate addition can interfere with the action of mixing systems but improvements in oxygen levels and ecological function are often present. It is also the case that some observers have noted increases in nutrients associated with mixing systems (Yousef et al. 1980) but this has not been detected here. I surmise that, if there is entrainment of sediment particles, this does not occur at a depth sufficient to access the more polluted sediment layer, nor deep enough to mobilise large quantities of anoxic material.

The study of Helixor operation within the quays has been of renewed value in 2013 as a comparable system has also been installed in the adjacent turning basin that still forms part of the main ship canal. From 1990 to 2012 water column anoxia was prevented through the presence of

-1 VITOX injectors which supersaturated the water with liquid O2 at a cost of £3m year (Williams et al. 2010). As the ship canal is still sub ect to large amounts of organic pollution ( D in 2010 was

3.0 mg l-1, σ 1. ) and may stratify during the summer (pers. obs.), it is unclear if this new

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Chapter 7: General Discussion system will be able to prevent stagnation problems in the future. This will likely be an issue in the summer when surface heating is at its highest while wind and rainfall is reduced.

Other management interventions will have had an effect on ecosystem function but it does not appear that they have been as instrumental as isolation and mixing. For example, the addition of

12,000 fish, including carp (Cyprinus carpio), roach (Rutilus rutilus), bream (Abramis brama) and perch (Perca flavescens) in 1990 will have stabilised the teleost population by introducing additional trophic levels to the exclusively zooplanktivourus species previously present (R. rutilus and Gasterosteus aculeatus). This removed the unsightly die offs associated with boom/bust in the fish population and resulted in a more uniform predation pressure on the zooplankton

(Williams et al. 2010). The introduced fish subsequently showed some of the highest growth rates ever recorded in the UK (Williams et al. 2010) and, aside from occasional small introductions, have become largely self-sustaining (White et al. 1993; Williams et al. 2010). Interestingly the continued improvements in water clarity may now be exerting a pressure on the local fish population through exhaustion of pelagic energy supplies, as has been seen in other Dreissena invaded systems (Heath and Fahnenstiel 1995). During routine fish measuring work I have also personally noted a high incidence of damage to many individuals that indicates attack by predatory birds, specifically cormorants. Nonetheless, fish diversification would have had an effect on zooplankton biomass and population structure since introduction, however with the data available it would be difficult to determine the relative strength of this compared to the changes in the physiochemical environment (Chapter 2). It is possible over this period there was also diverse rotifer community as these are species that are known to favour filamentous cyanobacteria as a food resource (Reynolds 2006); however there has been no sustained record of rotifer abundance during the restoration of SQ (APEM pers. com.). Finally, it is worth noting that the introduction of C. carpio has not led to a noticeable increase in eutrophication in SQ, despite their previous association with increased water column nutrients through sediment disturbance

(Matsuzaki et al. 2007). As with disturbance by mixing it would seem that oxygen levels are

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Chapter 7: General Discussion sufficient (and the oxic sediment layer thick enough) that little nutrient release occurs. It would also seem that resuspension by teleosts is not sufficent to have a noticeable effect on suspended solid levels, possibly simply due to lack of a sufficiently large population compared to basin size but this cannot be confirmed with current data.

The addition of floating islands and diversification of the aquatic habitat through the construction of gabions and reed beds does not appear to have changed phytoplankton dynamics in a significant way. This is supported by the fact that the small basins where these interventions took place did not show a significantly different biological or physiochemical pattern over the first two decades following isolation (data were statistically similar; Chapters 2 and 3). Indeed, chlorophyll was still largely comparable to Ontario basin (where no habitat diversification took place) in

2010/11 (Chapter 6). It is possible that the maturation of all these interventions resulted in a change in stable state in 2001, although it would seem from the NMDS analysis presented and discussed in 2.0 and the modelling component of 3.0 that the overwhelming influence for this period is nutrient abundance, a factor controlled primarily by isolation and stratification (Williams et al. 2010). The difference in current chlorophyll and nutrient dynamics between larger Huron basin and the other sites more recently (6.0) points to the only other intervention that appears to contribute significantly to the areas biotic and abiotic environment, the introduction of the invasive zebra mussel, D. polymorpha in 1994.

Chapter 2 utilised benthic invertebrate colonisers to indicate the density of zebra mussels over time in the quays. When combined with the 2000 and 2010 dive survey (Chapter 5) it was found that initial mussel recruitment was very poor with little population growth until ≈2005, despite their highly effective planktonic dispersal phase (Nalepa and Schloesser 1993). Indeed, it seems that the 750 individuals initially introduced had not survived and no mussels were present in the small basins. Therefore, and in common with the other biotic and abiotic variables discussed above, there is no significant correlation with changes in the density of the dominant phytoplankter P. agardhii in 2001. Indeed it is likely that the diversification in phytoplankton

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Chapter 7: General Discussion community increased mussel filtration capacity (Chapter 5). A switch to more nutritionally beneficial chlorophytes will also increase larval survival as large, filamentous cyanobacteria are difficult to graze (Vanderploeg et al. 1996) and do not produce the essential fatty acids needed for spat development (Wacker and Von Elert 2003). The increase in zebra mussel population from

2005 resulted in a further shift in phytoplankton community composition to low numbers of smaller, more highly fecund species such as Rhodomonas, Chlamydomonas and Cyclotella, as well as a parallel decrease in zooplankton abundance (Chapter 2). These changes mirror the effects of similar, large scale D. polymorpha infestation elsewhere (Higgins and Vander Zanden 2010) but differ somewhat in nutrient characteristics. While nitrate and silicate follow the expected trends in reduction, phosphate builds up in the water column during periods of intense grazing (Chapter

6). This is a pattern not usually seen in lakes but has been reported on numerous occasions in enclosures and river environments where grazing was sufficient to prevent phytoplankton population growth (Higgins and Vander Zanden 2010).

The expansion of D. polymorpha in 2005 into all basins bar Huron appears to have been a sudden event (Chapter 4). As there is a large population present within the canal connecting Huron basin to Ontario (where the highest densities of mussels are present) the absence of zebra mussels in the former basin is surprising, and currently inexplicable. In basins where large D. polymorpha populations exist, filtration capacity can exceed 50% of the water column day-1, sufficient to have a significant effect on phytoplankton production (Chapter 6), as has been seen in the Great Lakes of America (Fishman et al. 2010). There are a number of observations to make about the costs and benefits of zebra mussels to water quality at Salford Quays as there has been renewed interested in their use as an ecosystem service to maintain water clarity (e.g. Mclaughlan &

Aldridge, 2013). If we assume that the phytoplankton community in Huron basin is not affected by

D. polymorpha then it is clear that mussels are not essential to the maintenance of a clear water column. Indeed, if D. polymorpha are related to M. aeruginosa blooms then there may be an ecosystem cost as their presence as this limits the use of the area for water sports. Finally,

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Chapter 7: General Discussion engineers involved in servicing the Helixor systems have frequently noted the extra work involved in D. polymorpha fouling of equipment (APEM pers. comm.).

Molecular analysis of the D. polymorpha population in SQ revealed a number of interesting relationships (Chapter 4). Perhaps most significantly there is clear evidence of gene flow between the population in the quays and another in the Bridgewater Canal 25 km away (Euclidian distance) although it is not possible to discern the direction in which migration is taking place. This indicates either an intermediate population of unknown size and density or, more likely, relocation by fishermen or other water users. Owing to these observations it seems logical to conclude that the population in SQ is in no way isolated from others in the area, despite the isolation of the basins themselves from the rest of the catchment. As with many aquatic invasive species, vectors likely exist both from anglers and other water users such as rowers and sailors (Vander Zanden and

Olden 2008), as well as the transport of equipment such as pontoons into the quays for sporting events. A programme of education and control is therefore advised within the area to try to limit the further immigration and emigration of invasive species. Indeed a number of invasive macrophytes such as Elodea canadensis are also present in the quays, likely introduced from local fishermen or hobbyists. While they are not a major detriment to the ecosystem, they are best not introduced into other local water bodies.

As predicted, there are very few similarities between the D. polymorpha populations in Spain and the NW UK but population exchange in other areas of the country cannot be discounted. Likewise the presence of cryptic populations of zebra mussels in Salford Quays (Chapter 4) is of interest and a clear ecological explanation is not immediately obvious. I suggest that these are individuals that have transplanted from elsewhere in the country and have not yet been present for sufficient time to fully integrate into the resident population. The lack of any apparent geographic pattern to their presence can therefore easily be explained by one or two generations of planktonic dispersal. The benefits of this mode of reproduction are perhaps best exemplified by the

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Chapter 7: General Discussion population in the Hudson Estuary where between first detection in 1991 and subsequent counts in 1992 the population increased to an estimated 550 billion individuals (Strayer et al. 1996).

The current seasonal patterns in SQ are heavily influenced by the presence of D. polymorpha filtration. The basins where they are present have phytoplankton successional patterns reminiscent of an oligotrophic system yet nutrient levels exceed limitation through much of the year. This has been seen in other infested ecosystems such as Saginaw Bay in Lake Huron where phytoplankton communities rapidly shifted to those represented by an oligotrophic community post establishment (Fishman et al. 2010). In Huron Basin (SQ) chlorophyll levels are more mesotrophic and can be assumed to be the successional pattern of the quays without zebra mussels. Most interestingly this system has a similar ecosystem services value to the others, indeed, in most years M. aeruginosa levels have been lower in this basin (APEM pers. comm.), likely a result of the reduced levels of D. polymorpha and comparatively high trophic state

(Sarnelle et al. 2012).

The habitat diversification efforts in the smaller basins appear to have had little impact on the phytoplankton communities present. The addition of gabions and floating islands planted with macrophytes does increase aesthetic value but does not appear to be essential to the restoration of the ecosystem. This is a key observation as the addition of macrophytes or biomanipulation of the fish community is usually required to force a change in stable state (Scheffer et al. 1993). In the quays water quality appears to of improved largely unaided by plant addition or indeed D. polymorpha filtration, at least until population expansion in 2005, by which point clear water had already been achieved. Indeed, natural macrophytes did not colonise naturally until after water clarity increased in 2001. Fish stock manipulation did not provide any immediate benefits

(Chapter 2) but it is likely that improvements in food web functioning would have been required for the change in stable state to occur. It would seem that instead this has simply been due to large reductions in pollutant input and mixing. As such, in future management projects these should be focused upon, with other changes being used to increase ecosystem service value. This

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Chapter 7: General Discussion is in contrast to much of the advice given to traditional lake restoration projects where the importance of biomanipulation to force a change in stable state are often emphasised (Richter

1986).

Chapter 3 confirmed the relationship between nutrients, mixing and chlorophyll in SQ that was proposed in Chapter 2 and also addressed some of the issues facing those interested in ecological relationships both in artificial lake systems and in other lentic environments. While broadly useful, similar regression relationships published by others (e.g. Phillips et al., 2008; Reynolds, 1980) are in many ways limited and in some cases flawed by ignoring the basic assumptions of regression such as independence in x and the inherent variability within an ecological dataset. By incorporating a non-linear approach and combining it with appropriate post-hoc analysis I have shown how this process can be greatly improved. At the same time I have produced a relationship that has predictive power and hence may prove useful in the restoration of the nearby turning basin and the Manchester Ship Canal now Helixor systems are also installed, plus their potential utility in other both natural and artificial systems. I do accept that many of the previous models of maximum phytoplankton production are within acceptable limits for SQ and while my approach has a broader relevance, the coarser calculation provided by other workers is still quite acceptable, indeed, until further validation of my approach and larger datasets can be obtained they will maintain their central use in water management. The fact they are still relevant in SQ is encouraging as it shows that key ecosystem processes in natural systems are still active and relevant in such a highly simplified area.

My preference for open source does not prevent me accepting that a further improvement on the approach used here would be to utilise a more stochastic model such as PROTECH or DREYSIM.

Open source versions such as the General Lake Model are available but require the specialist – and very costly – software environment, MatLab to apply. Such an approach in SQ would allow a deeper understanding of the processes active in the area rather than the ‘black box’ approach provided by statistical regression. Unfortunately insufficient data on SQ were available for such a

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Chapter 7: General Discussion model and the extra variables such as variation in sediment nutrient and pore water characteristics were not collectable within time and budget constraints. Nevertheless, the extension of the current work into such stochastic modelling is possible, especially if appropriate open-source packages become available.

In conclusion it is clear that isolation and mixing are highly effective methods of improving a highly degraded freshwater environment. It also seems apparent that lakes can be modelled statistically with a high degree of accuracy, provided the correct techniques and analysis are employed. Finally, the addition of D. polymorpha into such an ecosystem as a management tool may be considered of limited use and possibly a detriment to ecosystem quality. While I cannot rule out their efficacy in areas where there are still continuing problems with nutrient input I would be highly concerned about possible non-target effects.

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Chapter 8: Further work

8.0 Further Work

There is much that could be done both with the existing dataset and the unique environment offered by SQ. For example, it would be exceptionally interesting to be able to isolate the basins and utilise them for habitat manipulation experiments. Changes such as temporarily deactivating the mixing systems, removing zebra mussels or even limiting fish abundance would allow a greater understanding of the magnitude of their effects in the quays, as opposed to the observational relationships discussed above. If a smaller basin were used for such an experiment it would allow a similar control system to be provided for easy comparison. In addition, such manipulation would inform future changes such as a financially advantageous reduction in Helixor operation or control of invasive species within the quays. Manipulation of the quays environment could also be of great use in informing the future management of the Manchester Ship Canal now the environment has improved and Helixor systems have been installed, especially with the risk of

D. polymorpha moving into the area. Such information would be vital if future problems in the canal are to be avoided, especially the possibility of dense algal blooms in the turning basin which may prove an embarrassment to both managers and the local authorities, owing to the presence of the new BBC Media City on its banks. Unfortunately such experiments would require the approval of Salford City Council who are unlikely to risk adverse effects on local aesthetics and commerce.

Further experimental work on the quays would also be required to fully parameterise a stochastic model of the ecosystem’s functioning. New data on sediment characteristics such as solid matter and pore water nutrient content would be required and information on release rates under the conditions provided in the quays would be required. To parameterise a model such as DREYSIM information on factors such as pore water content and sediment quality would also be required.

In the highly urbanised environment of SQ atmospheric deposition data would also be required to determine the only remaining vector of nutrient addition to the system.

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Chapter 8: Further work

It may also be a requirement that longer term data are required to properly understand the inter- annual variation in the quays. This is especially true with regards to the D. polymorpha population that is likely to vary over a 3-5 year period owing to density dependent interactions between generations (Strayer and Malcom 2006). Continued monitoring of zebra mussel genotypes may also yield important results regarding the presence and speed of dispersion of new introductions, while incorporating a more rigorous sampling approach may explain some of the observed genotypic variation. Finally, a study of the turning basin to ascertain if zebra mussels are present seems wise owing to the possibility of mixing between this population and others in the northwest. Such work would also allow us to examine the risks of relocation between two adjacent water bodies that are almost totally isolated.

The available past data on Salford Quays would benefit from further examination. For example, it would be interesting to determine what could be inferred from analysis of algal sub-community during P. agardhii dominance and if useful ecological information could be gleamed from such an examination. It may, for example, be able to indicate other environmental trends or give some forewarning of the stable state shift in 2001. There also exists a wealth of data over the same time period from the open basin and the ship canal which would provide interesting comparative systems to SQ in a future study. The open basin especially has not been isolated yet is still mixed by Helixor systems and is thus a further macrocosm experiment in mixing alone.

The modelling approach discussed in Chapter 3 is merely the initial stage in what could be developed as an extremely useful modelling approach. For this reason further validation both of the model produced for SQ and the methodology on other freshwater environments would be very worthwhile. It would be of particular value once more data are available on the functioning of the environment in the turning basin in order to pre-empt algal blooms. I am also of the view that such non-linear approaches are underused in the whole of ecology, and the advantages such increases in power they provide cannot be exaggerated. Therefore there is a definite need to

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Chapter 8: Further work apply this technique to new datasets and existing ecological questions to help us to fully understand the often variable nature of the natural environment.

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