The Distribution and Abundance of Rafting Algae and Its Associated Fauna Now and in a Future Ocean

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2017

Cut adrift: the distribution and abundance of rafting algae and its associated fauna now and in a future ocean

Lauren Jean Cole University of Wollongong

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Recommended Citation Cole, Lauren Jean, Cut adrift: the distribution and abundance of rafting algae and its associated fauna now and in a future ocean, Doctor of Philosophy thesis, School of Biological Sciences, University of Wollongong, 2017. https://ro.uow.edu.au/theses1/121

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Cut adrift: the distribution and abundance of rafting algae and its associated fauna now and in a future ocean

A thesis submitted in fulfilment of the requirements for the award of the degree

DOCTOR OF PHILOSOPHY

From

UNIVERSITY OF WOLLONGONG

Lauren Jean Cole, Bachelor of Science

CENTRE FOR SUSTAINABLE ECOSYSTEM SOLUTIONS

SCHOOL OF BIOLOGICAL SCIENCES

2017

CERTIFICATION

I, Lauren Jean Cole, declare that this thesis, submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy, in the Centre for Sustainable Ecosystem

Solutions, School of Biological Sciences, University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution. All work conducted for this dissertation was conducted under the NSW DPI Research Permit F95/269-8.0.

Lauren Cole

6th July 2017.

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TABLE OF CONTENTS

TABLE OF CONTENTS……………………………………………………………………V

LIST OF FIGURES……………………………………………………………………………………………...… IX

LIST OF TABLES……………………………………………………………………………………...……...... XIII

ABSTRACT………………………………………………………………………………………………………….... XV

ACKNOWLEDGEMENTS………………………………………………………………………...………… XVII

CHAPTER 1 – GENERAL INTRODUCTION………………………………………………….……….. 1

1.1. IMPORTANCE OF DISPERSAL IN MARINE ENVIRONMENTS………………………………………. 2

1.1.1. Rafting as a Mode of Dispersal……………...…………………………………...………………. 2

1.1.2. The Dispersal Capability of Rafts…………………………………………..……………………. 4

1.2. RAFTS AND RAFTERS……………………………………………………………………………………. 5

1.2.1. The Origin of Rafts………………………………………………………………………………. 5

1.2.2. The Life of a Rafter………………………………………………………………………………. 7

1.3. KEY THEMES OF RESEARCH ON ALGAL RAFTING COMMUNITIES…………………….…..……. 9

1.4. RAFTING IN A FUTURE OCEAN…………………………………………..…………………………… 12

1.5. AIMS OF THE STUDY ...………………………………………..………………………………………... 13

CHAPTER 2- TRENDS IN RAFT ABUNDANCE, BIOMASS AND DISTRIBUTION

ALONG THE SOUTHERN NEW SOUTH WALES COASTLINE………………….... 16

2.1. INTRODUCTION………………………………………………………………………………………….. 17

2.2. METHODS…………………………………………………………………………………………………. 20

2.2.1. Study Locations…………………………………………………………...…………………….. 20

2.2.2. Sampling Design…………………………………………………………...………………….... 22

2.2.3. Analysis of data…………………………………………………………...…………………….. 24

2.3. RESULTS…………………………………………………………...…………………………………….... 25

2.3.1. Spatial and Temporal Trends in Raft Abundance and Biomass………………………………... 25

2.3.2. Comparing Invertebrate Communities………………………………………………………….. 28

2.4. DISCUSSION…………………………………………………………...…………………………………. 31

2.4.1. Spatial and Temporal Trends in Raft Abundance and Biomass ……………………………….. 32

2.4.2. Comparing Invertebrate Communities………………………………………………………….. 35

2.4.3. Implications and outlook………………………………………………………………….…….. 37

CHAPTER 3- THE DISTRIBUTION OF FLOATING AND BEACH-CAST ALGAL

RAFTS ALONG THE NSW COASTLINE …………...……………………………….... 38

3.1. INTRODUCTION………………………………………………………………….………………………. 39

3.2. METHODS………………………………………………………………….…………………………….... 42

3.2.1. Beach and Aerial Surveys………………………………………………………………………. 42

3.2.2. Survey design………………………………………………………………….………………... 44

3.2.3. Analysis of data………………………………………………………………….…………….... 45

3.3. RESULTS………………………………………………………………….……………………………….. 46

3.3.1. Beach Surveys………………………………………………………………….……………….. 46

3.3.2. Aerial Surveys………………………………………………………………….……………….. 47

3.3.3. The relationship between rafts and Phyllospora reefs………………………………………….. 48

3.4. DISCUSSION………………………………………………………………….…………………………... 50

CHAPTER 4 –TRENDS IN ABUNDANCE AND DIVERSITY OF RAFT-

ASSOCIATED INVERTEBRATES……………………………………………………… 54

4.1. INTRODUCTION ………………………………………………………………….…………………….... 55

4.2. METHODS………………………………………………………………….……………………………… 58

4.2.1. Laboratory methods……………………………………...……………………….…………….. 58

4.2.2. Analysis of data………………………………………………………………….…………….... 59

4.3. RESULTS………………………………………………………………….……………………………….. 60

4.3.1. The rafting community: Spatial and Temporal Trends…………………………………………. 60

4.3.2. The growth and development of Portunus spp. on rafts………………………………………... 65

4.4. DISCUSSION………………………………………………………………….…………………………... 66

4.4.1. The rafting community: Spatial and Temporal Trends………………………..………….…….. 66

4.4.2. The growth and development of Portunus spp. on rafts………………………………………... 69

4.4.3. Conclusions……………………………………………………………………………….…….. 71

CHAPTER 5 – FLOATING RAFTS: ISOLATED ISLANDS OR ACTIVE

ARCHIPELAGO?...... 72

5.1. INTRODUCTION………………………………………………………………….………………………. 73

5.2. METHODS………………………………………………………………….……………………………… 76

5.2.1. Sampling Design………………………………………………………………….…………...... 76

5.2.2. Analysis of data………………………………………………………………….…………….... 77

5.3. RESULTS ………………………………………………………………….………………………………. 78

5.4. DISCUSSION………………………………………………………………….…………………………... 81

CHAPTER 6 – RAFTS IN A FUTURE OCEAN………………………………………... 86

6.1. INTRODUCTION…………………………………………………………...……………………….…….. 87

6.2. METHODS………………………………………………………………….…………………………….... 90

6.2.1. Study location and design………………………………………………………………….….... 90

6.2.2. Measures of rafts fitness………………………………………………………………….…….. 92

6.2.3. Analysis of Data………………………………………………………………….……………... 93

6.3. RESULTS………………………………………………………………….……………………………….. 93

6.4. DISCUSSION………………………………………………………………….…………………………... 98

6.4.1. Conclusions…………………………………………………………………...…...…………... 101

CHAPTER 7- MODELLING THE IMPACTS OF A FUTURE OCEAN ON A KEY

HABITAT-FORMING MACROALGA: A BAYESIAN NETWORK APPROACH.. 103

7.1. INTRODUCTION………………………………………………………………….……..………………. 104

7.2. METHODS………………………………………………………………….…………………...………....107

7.2.1. Description of the model………………………………………………………………….….... 107

7.2.2. Description and parameterisation of the variables ……………………...…………….………. 108

7.2.2.1. Decision Nodes…………………………………………...………………….…….. 108

7.2.2.2 Intermediate Nodes………………………………………………………………..... 110

7.2.2.3. Output Nodes………………………………………………………………….….... 114

7.2.3. Sensitivity analysis………………………………………………………………….…………. 116

7.3. RESULTS………………………………………………………………….…………………………….... 116

VII

7.3.1. Model outcomes and predictions…………………………………………………………….... 116

7.3.2. Sensitivity analysis………………………………………………………………….…………. 118

7.4. DISCUSSION………………………………………………………………….……………………...….. 120

5.4.1. Sensitivity analysis………………………………………………………………….…………. 122

7.4.2. Conclusion ……………………..……………………………………………………….…….. 122

CHAPTER 8 – GENERAL DISCUSSION…………………………..…………………. 125

8.1. GENERAL FINDINGS AND CONSISTENCY WITH PREVIOUS RESEARCH………………..…….. 126

8.2 FUTURE DIRECTIONS………………………………………………………………….……………….. 128

8.3. POTENTIAL IMPLICATIONS OF FINDINGS…………………………………………………………. 130

REFERENCES………………………………………………………………………….... 132

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LIST OF FIGURES

Figure 1.1. Relative proportion of taxa reported or inferred as utilizing floating rafts during previous surveys. Data from Thiel & Gutow (2005b) ………...…………………………. 8

Figure 1.2. Relative abundance of regions where previous research has been conducted on the use of rafts by epifauna. Data from by Thiel et al. (2005b) ………...………………. 10

Figure 2.1. New South Wales, Australia, with inset of study sites Port Kembla and Jervis Bay along the coastline south of Sydney. The locations of rocky reefs indicated along shorelines in grey. Scales for each location identified in bottom right corner. …………. 22

Figure 2.2. Path of Port Kembla survey on April 28, 2013. Example of the path taken during a Port Kembla survey. ………...………………………….………...……………...……. 23

Figure 2.3. Concentration and composition of rafts floating throughout Jervis Bay (A) and Port Kembla (B) pooled across 9 days at each location. Gradient shading indicates average density of floating rafts (rafts/km2) and circles indicate the species composition of algal raft within that area. The location of rocky reef is indicated in black. ………...………. 26

Figure 2.4. Average density (rafts km-2±SD; top) and average biomass of rafts (kg±SD; bottom) of floating kelp Phyllospora comosa (black) and Sargassum spp. (grey) collected during multiple seasons in Jervis Bay (left) and Port Kembla (right). ………...………. 28

Figure 2.5. Multidimensional scaling ordination of untransformed (A) and Presence/absence transformed (B) invertebrate community assemblages for rafts of Phyllospora (black) and Sargassum (grey). ………...………………………….………...……………………… 30

Figure 2.6. Number of individuals (±SD; A) and species (±SD; B) per kg of rafting algae of Phyllospora comosa (black) or Sargassum spp. (grey) collected during spring in Jervis Bay. ………...…………………………………………….……………………………. 31

Figure 3.1. Aerial view of beaches surveyed for beached wrack. Beaches A (Noraville) and B (Macmasters) are north of the Sydney region, C (Mona Vale), D (Curl Curl) and E (Maroubra) are within Sydney and F (Garie), G (Stanwell Park) and H (Port Kembla) are to the south of Sydney. ………...………………………...…...…………………………. 43

Figure 3.2. Locations of beach and aerial surveys. Beaches surveyed are identified by large dots and letters A-H. Area covered by aerial survey is between southern and northern end markers. Sectors 25km in length of coastline indicated by dashed lines. Coastline where Phyllospora comosa is no longer found identified by Sydney Region. ………...………. 45

Figure 3.3. Biomass (kg) of beach-cast Phyllospora wrack washed ashore km-2 in a 24-hour period at each surveyed location. Beaches are listed from furthest north to furthest south. Error bars represent ± 1 standard error. Grey block represents locations where Phyllospora does not currently grow along the adjacent coastline. ………...………………………… 47

Figure 3.4B Map of coastline surveyed, partitioned into eight 25km sectors. Locations where rafts were found during aerial survey are indicated by black dots. Coastline where attached Phyllospora comosa is no longer found identified by “Sydney Region” .………………. 48

Figure 3.5. (A) Mass of beached wrack and (B) biomass of floating rafts in relation to the average percent cover of Phyllospora in each sector. Percent cover data from Coleman et. al. 2008. ………...……….………...………………………….…………………………. 49

Figure 3.6. Relative abundance of Phyllospora between locations. On the primary axis, the average biomass (kg) of Phyllospora wrack per km2 observed via beach (n=3) and aerial survey (n=4). On the secondary axis, the percent cover of attached Phyllospora (n= 20, see Coleman et al. 2008). Shaded area denotes sectors in Sydney. Error bars represent ± 1 standard error. Asterisk indicates no percent cover survey in sector. ………..…………. 50

Figure 4.1. The average number of individuals (A) and average number of species (B), found during each season at both locations (±SE). ………...………………..…………………. 61

Figure 4.2. The relative abundance of arthropods (grey) and gastropods (black) during each season and both locations surveyed. ………...………………………..…………………. 62

Figure 4.3. Multidimensional scaling ordination of the abundance and presence/absence transformed invertebrate community compositions for both locations and all seasons surveyed. ………...………………………….………...……....…………………………. 63

Figure 4.4. Number of megalopae per kg (A), juveniles per kg (B) and width of megalopae carapace in mm (C) each month. Box plots show median values (solid horizonal line), 50th percentile vales (box outline), 90th percentile values (whiskers), and outlier values (open circles). Months in figure C where no value is shown indicates no individuals were located. X denotes a month where no samples were collected. ………...………………. 66

Figure 5.1. Diagram of buoy used to track rafts that have been re-released after treatment. A) Hollow pool noodle 1 meter in length, each marked with a unique identification number. B) Fishing weights (1kg) fastened inside the bottom of the noodle causing all but the very bottom of the noodle to stick vertically out of the water. C) Synthetic rope 2 metres in length used to attach the buoy to the raft. D) Zip-tie used to attach the rope to a sturdy part of the stipe of the raft. ………...………………………….………...……………………. 77

Figure 5.2. Raft attached to identification buoy. ………...………………………………… 77

Figure 5.3. Number of individuals (A) and species (B) found per kilogram of floating algae for solo, group and reference rafts. Box plots show median values (horizontal line), 50th percentile (box outline), 90th percentile (whiskers), and outlier values (circles). ……… 79

Figure 5.4. Multidimensional scaling plot for the diversity of invertebrates on isolated rafts (square), rafts in a group (black) and reference rafts (grey) per kg. ………...…………. 81

Figure 6.1. Map of Phyllospora comosa’s range, from Port Macquarie, NSW in the north, to south of Hobart, TAS. Inset of Windang Island, NSW, site of wrack collection. Area or raft collected indicated with black line ………...…………………..……………………. 90

Figure 6.2. Experimental set-up for both the winter and wummer run. Winter temperatures are displayed on top of the diagram, summer temperatures are below. ………………….91

Figure 6.3. Relationship between temperature and three fitness indicators: A) Days of PSII. R²=0.88 for summer (n=16) and R²=0.74 for winter (n=12). B) Days raft remained buoyant. R²= 0.76 for summer (n=16) and R²= 0.79 for winter (n=12). C) Percent daily biomass change: R²= 0.56 for summer (n=16) and R²= 0.55 for winter (n=16).………...………………….………………….………...………………………….95

Figure 6.4. Baseline fluorescence yield (Fv/Fm) of rafts at time of collection during summer (n=16) and winter (n=16). Six measurements were taken per raft. Error bars represent ± 1 standard error .…………...………………………….………...…………………………. 95

Figure 6.5. Mean fluorescence yield (A) and percent of initial weight (B) of raft for each temperature treatment (n=4 per treatment, per season). Winter values appears in grey and summer in black. The 10°C treatment was only used during winter and the 31°C treatment was only used in summer. Florescent yield data was collected daily and weight measurements were collected every 3 days. Error bars represent ± 1 standard error. When a curve does not reach day 31, all algae in that temperature treatment had sunk or disintegrated and therefore no further measurements were taken. ………...……………. 97

Figure 7.1. A graphical representation of the Bayesian belief network. Squares: decision variables; ellipses: random variables. Black nodes represent locations or years. The lightest grey nodes represent environmental conditions, mid-grey nodes represent policy decisions and the dark grey nodes represent biological effects. The white nodes represent the potential outcomes of the model. ………...………………………….………...... …. 108

Figure 7.2. Coastline where Phyllospora comosa can be found along reefs in south-eastern Australia. The coastline of the most northern (New South Wales) and southern (Tasmania) states are outlines in grey and represent the area included in the model. ………....…… 108

Figure 7.3. Predicted radioactive forcing levels under three representative concentration pathways utilized in the model. Adapted from Van Vuuren et al. (2007). ………...…... 110

Figure 7.4. Predicting the influence of Representative Concentration Pathway on Attached Cover and Raft Abundance over time. Trends for New South Wales on the left and Tasmania on the right. The black line is RCP 2.6, grey is 4.5 and light grey is 8.5. .…. 117

Figure 7.5. The relationship between environmental protection and the change in abundance of rafts for the year 2115. Values represent changes in raft abundance in relation to the average predicted by the model. Black bars represent a scenario where none of the coastline is protected, grey bars represent restricted fishing and white bars represent a scenario where 100% of the coastline was within marine protected areas with very limited fishing, if any. ………...………………………….………...…………………………... 118

Figure 7.6. Sensitivity analysis, which determines the percent mutual information shared between each factor and the abundance of rafts predicted by the model. Factors with dark grey background are those in the first hierarchical level, mid-grey factors are in the 2nd hierarchical level and light grey bars are in the 3rd. Black bars are values for the state of New South Wales and white bars are for Tasmania. ………...………………………. 119

Figure 7.7. Sensitivity analysis of the three decision nodes and their relative influence on the abundance of rafts predicted by the model. Black bars are values for the state of New South Wales and white bars are for Tasmania. ………...……………………………. 119

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LIST OF TABLES

Table 2.1. Analysis of variance comparing the density (rafts km-2) and average raft biomass (kg) of Phyllospora comosa between season and location. (df) degrees of freedom, (MS) mean squares, (p) significance………...………………………….………...…………… 27

Table 2.2. The number of species and percent of total individuals from each taxon found within Phyllospora comosa and Sargassum spp. ………...……………………………... 29

Table 2.3. PERMANOVA of epifaunal invertebrate communities present on Phyllospora and Sargassum rafts during spring. (df) degrees of freedom, (MS) mean squares, (p) significance ………...……………………………………………………………………. 30

Table 2.4. SIMPER table of dissimilarity between Phyllospora and Sargassum. Table includes the average abundance of the top 6 contributing invertebrates to the dissimilarity per kg of raft. …………...………………………….………...…………………………. 31

Table 3.1. Analysis of variance comparing the biomass of Phyllospora comosa wrack found on surveyed beaches. (df) degrees of freedom, (MS) mean squares, (p) permutation significance…….………...………………………….………...…………………………. 47

Table 3.2. Analysis of variance comparing the biomass of Phyllospora comosa rafts found during aerial survey. (df) degrees of freedom, (MS) mean squares, (p) permutation significance……………....………………………….………...…………………………. 48

Table 3.3. Tukey’s Honest Significant Difference table with sectors that had a significantly different biomass of rafts………...………………………….………...…………………. 48

Table 4.1. The number of species and percent of total individuals from each taxon found on rafts. ………...………………………….………...……….………...…………………………. 60

Table 4.2. Analysis of variance for the relationship between the number of individuals per kilogram and species across seasons and locations. (df) degrees of freedom, (MS) mean squares, (p) permutation significance. ………...………………………….………...….... 61

Table 4.3. Abundance and Presence/absence PERMANOVA results for the effects of location and season on the species diversity found on floating macroalga Phyllospora comosa. ...……………….………...………………………….……….…………………. 63

Table 4.4. SIMPER table of dissimilarity between Jervis Bay and Port Kembla. Table includes the average abundance kg-1 of the top 13 contributing invertebrates to the dissimilarity. ………...…………………………………………….……………………. 64

Table 4.5. SIMPER table of average dissimilarity between seasons accompanied by species that contributed the most to the differences. Table includes the average abundance of the top 11 contributing invertebrates to the dissimilarity. ………...……………………...…. 65

Table 5.1. ANOVA and Tukey’s Honest Significance for the effect of treatment on the abundance and species diversity found per kilogram of floating macroalga Phyllospora comosa. ………...……….…………………………. ………...…………………………. 79

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Table 5.2. PERMANOVA for the effects of raft isolation on the species diversity (untransformed) found on floating macroalga species, Phyllospora comosa. ………...... 80

Table 5.3. Individuals per kilogram (±SD) of raft for each of the three treatments: solo, group or reference. ...……………….………...………………………….………...…………………………. 80

Table 5.4. SIMPER of the average dissimilarity between raft treatment accompanied by species that contributed the most to the differences. Table includes the average number of individuals per kg for the top 8 contributing invertebrate species………...…………….. 81

Table 6.1. Yearly average minimum and maximum temperatures within Phyllospora comosa’s range. Source: Australian Bureau of Meterology. ………...…………………. 92

Table 6.2: ANCOVA for three indicators of raft health: A) Days of PSII yield above 400 Fv/Fm; B) Number of days raft remained buoyant; C) Percent of original biomass after one week; for both summer and winter with covariate temperature. ………...…………...…. 94

Table 7.1. Table of variables included in the Bayesian Belief Network. The first column, Node, names the variable as well as its parent nodes. Node Type identifies the role of each node (decision, intermediate or outcome) and the type of information contained (biological, policy or environmental). The Categories node lists the way that the data included was categorized or discretised. Justification explains the rationale for how categories or discretization was done. The Quantification/Data Collection column identifies the sources of information or data included to populate that node. …………. 115

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ABSTRACT:

Floating algal rafts provide key habitat in the pelagic environment by providing a substratum for attachment, a food source and a potential mode of dispersal. However, along the eastern

Australian coastline urbanization and climate change are beginning to threaten the availability of rafts. To date, little is known about rafting invertebrate communities along this coastline and how they may be impacted by a changing future ocean.

In this study, I used a combination of lab, field and modelling studies to determine the role of algal rafts in the pelagic environment as well as how climate change will impact the availability of this key habitat. I sought to address five key unknowns about this habitat along the New South Wales coastline. First, determine the key raft-forming species of algae along the New South Wales coastline, survey if the distribution of these rafts is homogeneous even in the Sydney region, identify the species found on rafts and explore the potential impacts of future warmer sea surface temperatures on this habitat. Finally, I use a Bayesian Belief

Network (BBN) to model the factors which influence raft abundance to determine how climate change will influence its abundance in a future ocean.

I found that Phyllospora comosa (Labillardière) was the predominant species of algal raft within the surveyed locations along the New South Wales coastline. However, its distribution was not homogeneous though the Sydney region, with vast areas of urban coastline completely devoid of floating rafts. In the laboratory, I established a significant negative relationship with sea surface temperature and the health of algal rafts. Future rising temperatures are expected to reduce the resilience, structural integrity and longevity of floating algal rafts. My Bayesian Network determined that the concentration of greenhouse gasses (which drive increases in sea surface temperatures) will have the largest impact on the future availability of algal rafts along the Australian coastline. Phyllospora was found to host more than 60 epifaunal invertebrate taxa which have the potential to be impacted by its

decline in abundance within the Sydney region as well as further temperature-driven declines in coming decades.

This study demonstrates that algal rafts are an important pelagic habitat which provides vital resources for a diverse epifaunal assemblage. This pelagic habitat has already declined considerably in the Sydney region; a warming ocean threatens to widen this gap and cause future loss especially in the lowest latitudes within its range. The modelling used in this study highlights the importance of making sensible environmental decisions now, or risk a decline in raft abundance and potential negative consequences for associated epifaunal species.

XVI

ACKNOWLEDGEMENTS

Foremost, I would like to express my deepest gratitude to my supervisor, Andy Davis. Thank you for taking a chance on an international exchange student and providing me the opportunity to be a part of your lab as an undergraduate, an experience that changed the course of my academic career. Your continued patience, encouragement, and guidance have been key motivations throughout my PhD.

Further thanks to the staff at the University of Wollongong who provided advice and resources for the project. Especially Corrine De Mestre, for going above and beyond whenever I needed a hand with anything and for all the hours you put in to improve my boating skills. Thank you also to Marijka Batterham from the UOW Statistical Consulting

Service for your advice. Fieldworkers Dave, Sam and Miles for keeping me company during countless long drives to my furthest north field sites. I greatly appreciated your enthusiasm for field work and your continued interest in the outcomes of my research.

To Trent Penman for introducing to me to the world of Bayesian Networks. Thank you for taking me under your wing and assisting me with getting involved in the Australian Bayesian

Network Modelling society.

And finally, to my family. My parents for being my biggest supporters and my sanity through all these years. Even though you’ve been on the other side of the Pacific, knowing you were only a phone call away for advice and perspective has meant so much to me. To my husband

Cameron, who has ever only known me as a PhD candidate. Your overzealous enthusiasm for my research kept me moving forward even when my thesis was getting the better of me.

Thank you for keeping me company in the field and making every seaweed collection an adventure

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CHAPTER 1 – GENERAL INTRODUCTION

“There were repeated encounters with flotsam […] picked up by the currents and carried off into the open sea. With a careful examination of these apparently unremarkable objects, it turned out that almost every one of them represented a kind of little floating island with a community of organisms living on and under it.” -L. N. Besednov, 1960

1.1. IMPORTANCE OF DISPERSAL IN MARINE ENVIRONMENTS

Dispersal capability is an important component in the life history of most organisms. The scale and pattern of a species’ dispersal determines its capacity to maintain populations over a large geographic range (Helmuth et al. 1994), relocate from unfavourable conditions and colonize new locations (Johannesson 1988). In order to better understand important ecological processes such as spatial and temporal distribution, the genetic structure of populations, range expansion and invasive species, it is important to look at the role dispersal is playing (Kinlan and Gaines 2003, Hawes 2008).

One of the most challenging processes in the marine environment to examine is the dispersal of marine taxa (Hawes 2008, Muhlin et al. 2008, Leese et al. 2010, Fraser et al. 2011). This is due largely to the fact that dispersal is an extremely difficult variable to measure directly in the field. Often marine taxa are too small or abundant to feasibly quantify, directly observe or track over any meaningful distance (but see Davis and Butler 1989, Jokiel 1989, Hobday

2000a). Molecular studies have proven useful in providing insights into the outcomes of successful dispersal but offer comparatively little information about the process itself

(Donald et al. 2005, Waters 2008, Leese et al. 2010).

One of many possible mechanism for natural marine dispersal is the use of macroalgae or debris for rafting (Bushing 1994, Ingólfsson 1995, Hobday 2000c, a, Thiel and Haye 2006,

Waters 2008). This method is widely proposed to account for much of the present-day distribution pattern of marine organisms (Jokiel 1984, Highsmith 1985, Edgar 1987, Fraser et al. 2011). This chapter focuses on the viability and benefits of dispersal via algal rafting.

1.1.1. Rafting as a mode of dispersal

Algal rafting is thought to be one of the most important dispersal mechanisms, especially because it can be found in all major oceans (Thiel and Gutow 2005a, Hinojosa et al. 2010).

Over the past four decades, many studies have emphasised the important role algal rafting plays in the transport, population connectivity and colonization of marine invertebrates and fish (Jokiel 1984, Highsmith 1985, Johannesson 1988, Jokiel 1989, Helmuth et al. 1994,

Worcester 1994, Waters and Roy 2004, Donald et al. 2005, Thiel and Haye 2006, Hinojosa et al. 2010). Species that rely on this method often experience higher dispersal capability over a shorter time frame than other dispersal mechanisms (Highsmith 1985). The distances travelled by rafting have been found to be up to two orders of magnitude greater than those travelled by swimming larvae and provides organisms with the benefit of remaining in the water column longer (Worcester 1994). In addition to a means of dispersal, rafts also provide a substratum for attachment, protection and a food source (Thiel and Gutow 2005b,

Vandendriessche et al. 2007a, Vandendriessche et al. 2007b).

Early studies that looked at population biology and biogeography focused on larval fitness as a central component in determining dispersal (Sammarco and Andrews 1988, Jokiel 1989). It was assumed that highly mobile species or those with a long-lived planktonic larval phase would disperse over longer distances and be more genetically homogeneous while species which brood young, are sessile or do not have a free-swimming planktonic larval stage would have a more restricted geographic range (Ó Foighil 1989, Vermeij et al. 1990). However, the outcomes of a growing number of studies on population connectivity in the marine environment have indicated that dispersal distances are not always positively related to the duration of a species planktonic stages (Kinlan and Gaines 2003, Winston 2012). Long- distance larval dispersal does not explain many of the inconsistencies in the distribution of numerous marine species (Jokiel 1987, Jokiel 1989, Miranda and Thiel 2008).

Rafting is believed to be the most likely alternate method of long distance dispersal for many species with limited autonomous dispersal (Dell 1972, Highsmith 1985, Jackson 1986, Martel and Chia 1991). Some invertebrates encompass a wide geographic range despite their lack of

distinct dispersal phase (Highsmith 1985, Jackson 1986, Helmuth et al. 1994). For example,

Johannesson (1988) reported that the brooding species Littorina saxatilis (which lacks a dispersive larval phase), had a wider distribution than the closely-related L. littorea (which has a pelagic larval phase). The frequent use of rafting by less motile taxa can increase the occurrence of long distance dispersal, favouring connectivity and gene flow between populations (Martel and Chia 1991, Thiel and Haye 2006).

1.1.2. The Dispersal Capability of Rafts

Algal rafting is an important means by which both vertebrate and invertebrate species maintain genetic diversity even in remote or unstable environments (Parker and Tunnicliffe

1994, Gillespie et al. 2012). If an alga breaks from shore, any epifaunal species that remain attached can be passively transported to new habitats, thereby contributing to population connectivity of both the floating algae and its associated rafters (Miranda and Thiel 2008,

Hinojosa et al. 2010). Populations in remote or inaccessible regions may experience limited genetic exchange with other populaces, and their persistence may be directly dependant on the ability of fauna to survive long-distance dispersal (Helmuth et al. 1994). Remote islands connected only by ocean currents may rely upon propagules to provide faunal exchange over large divides (Leese et al. 2010).

Dispersal by rafting is a potential long-distance dispersal mechanism for many marine species, but how far rafts can travel and carry their rafters is still largely unknown. Finding ways to reliably measure distance estimates for effective dispersal has received particular attention as it should considered important for the design of marine protected areas (Miranda and Thiel 2008). The transport of rafts may be influenced by local oceanic conditions such as winds, currents and waves (Ohno 1984, Bushing 1994). Epifaunal species have the potential to be transported many kilometres depending on how long they associate with a raft and how long the raft is able to maintain its structural integrity (Helmuth et al. 1994, Hobday 2000c).

Oceanic conditions and algal survival times suggest that dispersal up to many thousands of kilometres may be possible (Jokiel 1984, Edgar 1987, Helmuth et al. 1994). For instance,

Durvillaea antarctica, a brown alga native to New Zealand and Chile has been located thousands of kilometres from those shores (Smith 2002).

The existence of corals along isolated volcanic islands also provides convincing evidence that long-range dispersal does take place (Jokiel 1989). Rafting offers a possible mechanism by which some species may have bridged the "East Pacific Barrier" between the tropical west

American shelf and Polynesia, Hawaii and the Central Pacific islands. These islands rose from the bottom of the ocean, thus the seaweeds growing there must have come from elsewhere. This suggests the potential for floating objects to transverse between locations as far as 20,000 to 40,000 kilometres apart (Jokiel 1984).

1.2. RAFTS AND RAFTERS

Algal rafts are created when a piece of macroalgae attached to a substratum is broken off and begins to drift at sea (Thiel and Gutow 2005a). This raft will take with it the initial population present when it was attached and with time, this composition will change. Species will leave or be driven off the raft because of conditions, competition and predators while other species will join the raft in search of food, shelter and rest (Kingsford 1993, Druce and Kingsford

1995, Thiel 2003, Gutow et al. 2009). After drifting, the raft will eventually dissolve, sink or find its way back to shore. If it returns to shore the species aboard may have the opportunity to colonize this area.

1.2.1. The Origin of Rafts

Leaves and fronds of macroalgae senesce and detach as a result of damage by grazers and wave action during storms (Seymour et al. 1988, Rothäusler et al. 2009). Species of alga with specialized gas-filled bladders (pneumatocysts) which aid in floatation (Thiel and Gutow

2005a) and allow detached pieces to float along the ocean’s surface act as rafts when

dislodged from their substratum. Most species lacking pneumatocysts sink to the ocean floor when detached, meaning that only a small proportion of all algal species contribute to this important floating pelagic habitat.

The rate of detachment of rafts from kelp beds varies between species of alga as well as the seasonality of storms (Seymour et al. 1988), population densities of grazing organisms

(Rothäusler et al. 2009), wind and current direction (Hawes 2008). Peaks in abundance for the formation of rafts by some algae are predictable at certain times of year according to local demography (Kingsford 1993, Druce and Kingsford 1995). Floating seaweeds can exist as surface patches, combining to form drift lines (Davenport and Rees 1993), large rafts or mats

(Shaffer et al. 1995) while at other times appearing as small discrete clumps (Ingólfsson

1995, Ingólfsson 1998). Raft aggregations are spatially and temporally stochastic (Davenport and Rees 1993, Ingólfsson 1998) and therefore their abundance is often patchy in distribution. For example, during one survey, ten rafts were observed within a span of 35 kilometres, but were then followed by a complete absence of rafts for the next 45 kilometres

(Helmuth et al. 1994).

Algae that detach from the substratum may drift throughout the ocean for quite some time before beaching or sinking (Bushing 1994, Hobday 2000c, b). Some species of seaweed remain buoyant for weeks or months after detachment from shore Rothäusler et al. 2012,

Graiff et al. 2013), especially in regions of the globe with colder sea surface temperatures which allows them to persist and drift longer. As a result, many species have been reported floating far from locations where they are known to inhabit (Hobday 2000c, a, Thiel and

Gutow 2005b). Several studies indicate that detached giant kelp Macrocystis spp. continues growing and may remain afloat for more than 100 days (Hobday 2000b). However, in the case of rafts in a bay, movement is almost certainly restricted and a majority of rafts likely beach nearby soon after detachment (Harrold and Lisin 1989).

Like icebergs, floating algal rafts are only partially exposed to the wind while more than 90% of their biomass is below the sea surface (Hinojosa et al. 2010). Some studies have shown that floating rafts move with surface winds while others believe that they follow the prevailing current (Harrold and Lisin 1989, Parker and Tunnicliffe 1994, Hernández-

Carmona et al. 2006, Rothäusler et al. 2012). Hinojosa et al. (2010) observed that floating kelps in southern Chile are influenced by surface currents when winds are mild but follow the direction of the wind when it is strong. Together, the complex interactions between winds and oceanographic features (surface currents, fronts and eddies) determine directional net transport and spatial distribution of floating algae (Hinojosa et al. 2010, Rothäusler et al.

2012).

1.2.2. The Life of a Rafter

Floating seaweeds have been noted to harbour an especially diverse fauna as compared to the pelagic environment (Kingsford 1993, Shaffer et al. 1995, Ingólfsson 1998, Thiel and Gutow

2005a, b, Vandendriessche et al. 2006a). Numerous studies have catalogued species composition on algal rafts. Thiel & Gutow (2005b) compiled these findings in their review, listing over 50 species of rafting alga and more than 1,200 species associated with rafting.

The diversity of species found on rafts varied depending on where and when surveys were performed (Stoner and Greening 1984) but the most common taxa were arthropods (including some threatened and commercially fished species), molluscs, cnidarians, bryozoans and annelids (Figure 1.1; Highsmith 1985, Worcester 1994, Thiel and Gutow 2005b).

Arthropoda Mollusca Cnidaria Bryozoan Annelida Other

Figure 1.1. Relative proportion of taxa reported or inferred as utilizing floating rafts during previous surveys. Data from Thiel & Gutow (2005b). As they drift, rafts are inhabited by an ever-changing community of species in different stages of their life history (Kingsford and Choat 1985, Thiel 2003). Many species with pelagic larval stages settle on attached alga (Marzinelli et al. 2016). If a raft breaks from shore, it takes the epifaunal community with it and some mobile individuals which have the ability to leave the raft may do so immediately (Hobday 2000b, Gutow et al. 2009). Once afloat on the ocean’s surface, an increasing number of mobile species present in the pelagic environment as larvae, juveniles or adults; quickly colonize from the surrounding water column (Ingólfsson 1995, Hobday 2000c, Vandendriessche et al. 2006a). Therefore, the community found on rafts most often comprise a combination of species inhabiting the raft when it was attached in the intertidal and those attracted to the raft after it has detached from shore (Ingólfsson 1995, Ingólfsson 1998). Some species possess characteristics that make them more successful long-term rafters than others (such as the ability to reproduce and recruit to the raft, Thiel 2003) and it was found that rafts did tend to slowly lose certain taxa with time (Ingólfsson 1998).

Every species of algae may have certain characteristics that appeal to different rafting species

(Thiel and Gutow 2005b). Each species likely exhibits a different level of suitability as habitat and therefore it can be expected that many seaweed-associated fauna would show a preference for certain algal species (Vandendriessche et al. 2006a, Vandendriessche et al.

2006b). It has been suggested that invertebrates utilize in some structural component of the raft such as habitat complexity, shade or other organisms associated with the drifting object on which to feed (Kingsford 1993, Druce and Kingsford 1995). Hauser (2006) found that high complexity artificial algal habitats were colonised by significantly higher numbers of individuals and species than those with lower complexity. Therefore, the availability of rafts influences the distribution patterns of some invertebrates in the pelagic environment by increasing habitat complexity in localized areas (Druce and Kingsford 1995, Kingsford

1995).

As a raft drifts, predation, competition for food and space (Hobday 2000c) as well as the longevity of the raft influence the abundance of epifaunal species (Gutow et al. 2015). Rafts can float from weeks to months and over this time the composition of rafters may change.

Less abundant species will encounter the raft or predators find the raft and begin feed on invertebrates (Kingsford and Choat 1985, Bushing 1994, Druce and Kingsford 1995). Rafters may persist by filter-feeding, predation on other rafters, and grazing directly on the raft

(Bushing 1994, Worcester 1994). However, species that directly consume their host raft will expedite its demise (Vandendriessche et al. 2007b) and therefore abundance of some herbivorous rafters may have negative impact on host raft longevity.

1.3. KEY THEMES OF RESEARCH ON ALGAL RAFTING COMMUNITIES

The role of rafts as habitat in the pelagic environment has been extensively explored in some regions of the world, while it is not as well understood in others. A selection of 160 articles on the topic revealed that more than 50% of studies have been conducted in the waters adjacent to North America and Europe. Surveys around Australia and New Zealand made up less than 7% (Fig. 1.2). Globally, many publications have focused on the associated fish assemblages (i.e. Hunter and Mitchell 1968, Lenanton et al. 1982, Kingsford 1992, Kingsford

1993, Druce and Kingsford 1995, Castro and Santiago 2002, Dempster and Kingsford 2004,

Ohta and Tachihara 2004, Vandendriessche et al. 2007a) while others focused more on specific epifaunal species (i.e. Helmuth et al. 1994, Clarkin et al. 2012b). Evaluation of entire invertebrate assemblages associated with drift are rather sparse in comparison (i.e. Highsmith

1985, Norkko et al. 2000, Clarkin et al. 2012a, Wichmann et al. 2012b), especially in

Australian waters (Figure 1.2.). Additionally, very few compare the invertebrate communities between locations or species of host alga (Stoner and Greening 1984). However, it should be noted that an extremely comprehensive three-part literature review on the topic of algal rafting was composed by Thiel, Gutow and Haye just over ten years ago (Thiel and Gutow

2005a, b, Thiel and Haye 2006). This series of reviews has assembled many of the important findings and trends in rafting literature from the rafts themselves, to their epifauna and the impact of this system on the marine environment.

North America South America Europe Asia Australia & New Zealand Other

Figure 1.2. Relative abundance of regions where previous research has been conducted on the use of rafts by epifauna. Data from by Thiel et al. (2005b). The epifaunal invertebrate community associated with floating seaweed rafts is known to be highly variable and influenced by many spatial and temporal factors (Fine 1970, Stoner and

Greening 1984, Kingsford and Choat 1985, Ingólfsson 1995, Vandendriessche et al. 2006a,

Vandendriessche et al. 2006b). As a result, findings of previous studies often reveal contradictory outcomes or fail to draw many clear conclusions. The most commonly explored variables in determining the invertebrate rafting community are raft size (Vandendriessche et

al. 2007b, Clarkin et al. 2012a) distance from source and time afloat (Howard 1985, Hobday

2000b, Ingólfsson 2000, Urban-Malinga and Burska 2009, Clarkin et al. 2012b).

A large number of authors have found a positive correlation between the abundance of associated fauna and raft size (Fine 1970, Stoner and Greening 1984, Kingsford and Choat

1985, Kingsford 1992, Druce and Kingsford 1995, Ingólfsson 1995, Ingólfsson 1998,

Vandendriessche et al. 2006a). Small rafts are expected to be able to provide shelter to fewer species and individuals than larger ones (Ingólfsson 1995) which have an increased capacity to provide food, protection, attachment space (Ingólfsson 1995, Vandendriessche et al.

2006a, Vandendriessche et al. 2006b). Larger rafts would also be expected to have a higher encounter rate by individuals in the surrounding environment. However, there are some studies which have not found a relationship between raft size and the number of individuals or species (Highsmith 1985), not necessarily because they are not present, but because they may be masked by other factors (Vandendriessche et al. 2007b, Clarkin et al. 2012a).

Determining the relationship between the abundance of species on floating algal clumps and distance from shore has also been complex and hard to generalize (Ingólfsson 1998, Hobday

2000a, Salovius et al. 2005). Hobday (2000a) hypothesized that classical island biogeography would result in more remote rafts having fewer species than rafts located in close proximity to the shoreline. However, in his study there was no relationship between species richness and distance from shore or days afloat despite some rafts being afloat for as many as 109 days. In contrast, other researchers report that rafts further from shore had fewer individuals and species per raft. Ingólfsson (1995) reported that the diversity of some animals eventually drops with distance from shore. He suggests that a large part of the colonizers arrive very soon after the clumps are adrift, as indicated by the general lack of positive correlations between number of individuals and distance from shore. Salovius et al. (2005) also suggest

that the colonisation process is dependent on distance to the shore and abundance of the most dominant species decreased with distance.

1.4. RAFTING IN A FUTURE OCEAN

Temperature is one of the most influential variables on the health and longevity of many marine species (Drinkwater et al. 2010). In the future, sea surface temperatures are projected to continue rising above their already elevated levels (CSIRO 2015) posing a serious risk to the marine environment. The near coastal sea surface temperature rise around Australia is expected to be between 0.4-1.0°C by 2030 and around 2-4°C by 2090 (CSIRO 2015). The warming of the western boundary currents off the east of Australia and Tasmania have been 2 to 3 times faster than the global mean (Wu et al. 2012, CSIRO 2015). Oceanic temperature has been linked with negative impacts on macroalgae including reductions in growth, photosynthetic efficiency and diminished reproduction (Davison 1987, Hobday 2000b,

Vandendriessche et al. 2007b, Connell et al. 2008, Rothäusler et al. 2009, Wernberg et al.

2010, Rothäusler et al. 2011b, Ridgway and Hill 2012, Rothäusler et al. 2012, Wiencke and

Bischof 2012, Flukes et al. 2015).

The negative impacts of temperature on attached macroalgal forests are likely to affect associated floating rafts in a similar manner. The response of these rafts to climate change will be an important aspect of predicting its ecological role in a future ocean (Macreadie et al.

2011). The ability of macroalgae to successfully adapt and endure through long-term increases in water temperature will be essential to their survival as well as that of other algal- reliant species (Davison 1987, Kuebler et al. 1991, Lee and Chang 1999). The longevity and durability of floating rafts determines their capacity to serve as habitat and a vector for dispersal (Vandendriessche et al. 2007b). Any decline in the abundance or quality of rafts may have serious impacts on connectivity, ecological function and the biodiversity in these

areas due to the multiple key roles it plays in the pelagic environment (Graham 2004, Ling

2008).

1.5. AIMS OF THE STUDY

Previous studies have shown that a wide variety of fauna can be found upon algal rafts in many locations around the globe and that they often provide key habitat, a food source and a mode of dispersal (Kingsford and Choat 1985, Edgar 1987, Ingólfsson 1995, Ingólfsson

1998, Hobday 2000c, Thiel 2003, Vandendriessche et al. 2006a, Gutow et al. 2009, Fraser et al. 2011). However, only a portion of this research has accounted for spatial or temporal patterns in the abundance and diversity of raft-forming alga and their associated rafting community, particularly in Australian waters. My research will aim to study both rafts and rafting species between multiple locations and across multiple seasons to determine the role rafting plays along the coastline of temperate south-eastern Australia. I am also interested in exploring how this important habitat will be impacted by future ocean conditions which are expected to warm dramatically in coming decades.

To build upon previous research and better understand the components of the rafting system, the main goals of the present study were to:

1) Determine the species composition of raft-forming algae in two locations along the south coast of New South Wales

2) Describe seasonal variability in abundance and biomass of these species of algae when adrift

3) Identify the epifaunal invertebrate community found on each species of floating algae

4) Explore the relationships between epifaunal invertebrate abundance and diversity over space and time

5) Determine the progression of pelagic colonization and the impact of aggregations of algal rafts to this process

6) Establish if algal rafts seasonally acclimatize to warmer sea surface temperatures

7) Create a probabilistic Bayesian Network model to explore the survival of rafts and raft- creating species in a future ocean

The first four aims are addressed in Chapters 2, 3 and 4, where spatial and temporal patterns in the abundance and biomass of key habitat-forming algae along the New South Wales coast were explored. Trends in the abundance and diversity of epifaunal invertebrates were also investigated in relation to the species of raft, location, and season. These chapters set the foundation for substantiating the role and importance of rafting habitat in the pelagic environment for an extensive assortment of invertebrate species.

To investigate the process of raft colonization in the pelagic environment, a manipulative experiment was conducted. In Chapter 5, defaunated rafts were released back to the pelagic environment near other rafts as well as at distance from them. I sought to determine which species are first to colonize rafts and establish what role proximity to other rafts plays in the rate of arrival and diversity of the first colonizers

The ecological role of rafts in a future ocean may be in jeopardy if rafting algae are unable to persist despite the particularly rapid onset of climate change in this part of the globe. In

Chapter 6, I seek to determine the impacts of climate change on the longevity and abundance of rafts. A manipulative lab experiment addresses aim 6, exploring the impact of sea surface temperature on raft fitness and investigating the possibility of physiological plasticity to withstand a rise in temperature.

Finally. Chapter 7 combines the findings of all the previous chapters into a probabilistic

Bayesian Network (BN) model which explores the survival of rafts and raft-creating species in a future ocean (aim 7). In combination with other peer-reviewed research, this BN seeks to build a picture encompassing many of the possible conditions of a future ocean and explore mitigation options that best ensure the survivorship of this key habitat.

I conclude with a synthesis of my findings and interpret developments in algal raft ecology over the past 10 years. I also consider directions for future research.

CHAPTER 2- TRENDS IN RAFT ABUNDANCE,

BIOMASS AND DISTRIBUTION ALONG THE

SOUTHERN NEW SOUTH WALES COASTLINE

2.1. INTRODUCTION

Macroalgae are an important component of rocky reefs as they provide habitat, shelter and food to a wide variety of temperate marine species (Dayton 1985, Graham 2004, Marzinelli et al. 2016). Storm events, large waves, stipe damage or herbivory can cause algae to break from shore and become a free-floating raft that is then free to drift through open water (Thiel and Gutow 2005a). The abundance and distribution of floating macroalgae has been found to vary both spatially and temporally (Dempster and Kingsford 2004, Rothäusler et al. 2015).

As many of the factors that cause detachment are intermittent, the supply of rafts is often inconsistent and fluctuates seasonally (Kingsford 1992, Thiel and Gutow 2005a). The distribution of rafts once detached often coincides with oceanic currents and occasionally strong winds (Thiel and Gutow 2005a, Thiel et al. 2011, Rothäusler et al. 2015). Rafts often accumulate in patches or drift lines with their spatial abundance and distribution proving difficult to predict both at a regional scale as well as within relatively small areas (Kingsford

1992, Ingólfsson 1998, Thiel and Gutow 2005a).

Rafts continue to play a vital role once adrift. Floating algae, especially when in large clumps, increases the complexity of the pelagic environment considerably (Kingsford 1995,

Thiel and Gutow 2005a, Duggins et al. 2016). Rafts not only provide food, a substratum, and protection from predators to a wide range of species (Edgar 1987, Davenport and Rees 1993,

Ingólfsson 1995, Minchinton 2006), but may also lessen the energy expenditure during dispersal (Rulifson 1983). Algal rafting is particularly important for some species that are unable to disperse over long distances by providing a mean to cover distances they could not achieve independently (Fell 1962, Highsmith 1985, Vermeij et al. 1990, Helmuth et al. 1994,

Worcester 1994, Kinlan and Gaines 2003, Minchinton 2006, Thiel and Haye 2006).

Some marine species achieve great dispersal distances and range expansions with the assistance of floating propagules such as rafts, which provide habitat for the duration of their time afloat (Edgar 1987, Jokiel 1990, Helmuth et al. 1994, Thiel and Gutow 2005a). The distance that propagules disperse may control the demographics of marine populations, as well as govern the rate of colonization, expansion, and exchange of individuals (Kinlan and

Gaines 2003, Donald et al. 2005). Biologists also speculate that passive rafting plays a key role in colonising isolated environments such as islands (Van den Hoek 1987, Leese et al.

2010, Fraser et al. 2011), with many species incapable of reaching these locations independently (Jokiel 1990, Kinlan and Gaines 2003, Thiel and Haye 2006). Beached wrack is often abundant on the shores of atolls (Jokiel 1990), supporting the notion that rafting algae and its inhabitants are capable of long-distance dispersal. Knowledge of both dispersal mechanisms and species utilizing dispersal propagules is vital to understanding biogeography and evolution (Jokiel 1990).

Along the coastline of New South Wales, Australia there are approximately 800 species of macroalgae (Millar and Kraft 1994, Millar 2009). However, only a few of these species have specialized gas-filled bladders, pneumatocysts, which aid in floatation (Thiel and Gutow

2005a). This allows these species to float along the surface acting as rafts while other species sink to the ocean floor when dislodged from rocky shores. Consequently, only a small proportion of macroalgae contribute to this important motile pelagic habitat. Previous surveys conducted along the coastline of the Sydney region have found that Sargassum spp.

(Dempster and Kingsford 2004) and Phyllospora comosa (Druce and Kingsford 1995) are the two most common species of floating algae in this region. The variability of algal raft composition and distribution suggests that it may be heavily influenced by the local structure of macroalgal reefs as well as physical processes (Kingsford 1992, Dempster and Kingsford

2004). While the stipe on Phyllospora comosa is quite durable and solid (circumference over

3cm). The stipe on Sargassum spp. is comparably thin and fragile (circumference often less than 1.5cm). This could make Sargassum more vulnerable to fragmentation and degeneration

(personal observation).

The distribution of mobile epifauna between rafts may be determined by species preference or could be completely random if species are unsystematic in their selection of propagule.

Surveys of epifaunal invertebrates in New Zealand (Taylor 1998) and the Northern Wadden

Sea (Gutow et al. 2015) established differences in assemblage between species of benthic macroalgae. However, studies of floating algal rafts have found no evidence for consistent patterns in the occurrence of macroinvertebrates between different species of algal rafts

(Clarkin et al. 2012a). A survey comparing benthic algae with seagrasses also found a 75% similarity of mobile epifauna between all substrata (Virnstein and Howard 1987). While the mobile fauna may be uniform and indiscriminate between species of rafting algae, less motile species such as bivalves may experience habitat selectivity when they are settling both on the reef as well as rafts in the pelagic environment.

Local physical processes influence the spatial and temporal abundance and composition of raft-forming species. Storm events are known to increase the size and abundance of algal rafts along the coastline of central New South Wales (Schiel 1994, Dempster and Kingsford

2004). Jervis Bay and Port Kembla are two locations where Phyllospora comosa and

Sargassum spp. are known to be found as rafts, yet would be categorized as very different

NSW coastlines. For example, Jervis Bay has a mainly sheltered coastline lined by reflective beaches while Port Kembla has a dissipative and exposed coastline. It is expected that Port

Kembla would have a lower abundance of attached algae than Jervis Bay of the more fragile

Sargassum spp. due to the more exposed choppy seas resulting in fragmentation of the stipe and subsequent degeneration. Phyllospora comosa, which is comparably more durable, is

expected to be equally abundant at both locations as Phyllospora reefs are plentiful in both locations (personal observation).

Numerous previous studies have found pelagic invertebrates to be indiscriminate in their selection of floating algal rafts (Clarkin et al. 2012a, Clarkin et al. 2012b, Gutow et al. 2015) which would mean that there is the potential for redundancy of algal species as habitat for associated invertebrates. Therefore, it is expected that both fucoid species, Phyllospora and

Sargassum, will harbour a similar community of mobile invertebrates despite possible differences in structural complexity, surface area and biomass. In the same coastal waters of

Australia, Druce and Kingsford (1995) concluded that the main factor attracting ﬁsh to drifting objects seemed to be their availability in the pelagic environment, not any particular quality.

In this chapter, I examine a key pelagic habitat along the southeast Australian coast that has been extensively studied elsewhere in the world. The goal of my survey is to compare the species composition of raft-forming algae in two New South Wales locations with different local processes, Jervis Bay and Port Kembla, to add to the generality of my work. I also examine seasonal variability in the abundance and individual raft biomass of Phyllospora comosa and Sargassum spp. Finally, I determine if there is a difference between the epifaunal invertebrate community found on each species of floating algae.

2.2. METHODS

2.2.1. Study Locations

Offshore sampling of macroalgal rafts took place in two locations: Jervis Bay (35.03°S,

150.74°E,) and Port Kembla (34.47°S, 150.93°E,), New South Wales. These two locations were chosen because they fit within a general dynamic classification characterizing much of the coastline along New South Wales (Bryant 1981). At one end of the classification is Jervis

Bay, which has a coastline lined by reflective beaches devoid of inshore topography which are mainly sheltered and temporarily stable. At the other end lies Port Kembla with dissipative and exposed coastline which is characterised by a barred surf zone and susceptibility to a rapid change in currents.

Port Kembla (Figure 2.1A) is located 71 km south of Sydney, just offshore an artificial harbour and includes the Five Islands Nature Reserve. The islands are surrounded by sponge gardens and rocky gullies with macroalgae to a maximum depth of approximately 30m. The sea surface temperature along Port Kembla fluctuates between 16.7°C in August and 25.5°C in March. Port Kembla is along a stretch of dissipative coastline which is exposed to a wide range of wave directions, creating spilling waves that break at an angle to shore and induce longshore currents. Wave motion causes water to pile up at shore so that rip currents form in order to return water (Bryant 1981). The coastline surrounding the harbour receives regular cargo traffic and the harbour historically experienced elevated levels of anthropogenic inputs but pollution reduction programs implemented in the 1970s have seen noticeable improvement in the quality of the marine environment of the harbour (He 2001).

Jervis Bay is a relatively pristine temperate marine embayment on the coast of New South

Wales (Figure 2.1B) partially included within a marine park (Holloway et al. 1992, Langtry and Jacoby 1996, Wang and Symonds 1999). Average sea surface temperatures range from

16.2°C in August to 24.9°C in March. Jervis Bay has an average depth of 15m (maximum depth of approximately 30m) and a surface area of 102km2 (N-S axis=15km, E-W axis=8km). The south-eastern end of the Bay opens onto the continental shelf via a 3.5 km entrance that is 30m deep. Vertical rocky cliffs near the entrance give way to sandy beaches which are bounded by shallow rocky reefs dominated by macroalgae. Beyond the rocky reefs

(depths >10m), much of the bottom of the Bay is open sand, but biogenic (seagrass) dominate in certain areas (Ward and Jacoby 1992). Along the coastline in Jervis Bay, waves do not

break until they reach the shoreline so there is only a narrow surf zone with no longshore currents, rips or bars (Bryant 1981). The bay has a dominant and persistent mean water circulation pattern driven by the inflow of the East Australian Current from the north near the surface on the southern side entrance creating a horizontal density-driven current along the seabed on the northern side of the entrance and out onto the shelf (Langtry and Jacoby 1996).

Within the Bay, currents generally show very little coherence with the wind (Holloway et al.

1992). Anthropogenic influences are minimal and there is no industry located on the shores or in its catchment (Ward and Jacoby 1992).

Floating rafts were surveyed from a vessel during seasonal opportunistic collections at each of the two sites: Jervis Bay and Port Kembla between 2011-13 (no surveys took place in Port

Kembla in the Spring of 2011 or in Jervis Bay in Autumn of 2013). At both locations, the waters immediately adjacent (0-50m) to the coastline were surveyed as well as several transects across open water (50m+ from shore; Figure 2.2). In low swell conditions, a survey

radius of about 20m was observable in any direction from the boat, effectively creating a 40m wide survey transect. Due to the gradually diminishing probability to see small rafts farther away from the boat, only rafts larger than 100g were collected as they had a higher probability of being detected. No searches took place during adverse weather conditions

(winds >25knots or waves above 2m) because the probably of detecting rafts within the belt transect would have been compromised. The density of rafts was calculated using GPS waypoints to determine the length of the survey path travelled multiplied by the width of the survey transect.

Figure 2.2. Path of Port Kembla survey on April 28, 2013. Example of the path taken during a Port Kembla survey. The path has an approximate width of 40m of transect shown by triple line in grey. The survey encircles the islands and mainland where rocky reefs are found as well as open water (further from shore) across the site.

Rafts were collected using onboard observers to identify floating seaweed. When rafts were spotted, the boat was manoeuvred gently towards the clumps. Rafts were carefully collected with a single swoop of a dip net (80 × 80 cm, mesh size 0.5 cm). The location of collection was recorded so that distance from nearest possible source (either exposed rocky intertidal shores or kelp beds) and nearest neighbour raft could be calculated. Each patch of floating algae was immediately transferred into a plastic bag. Any mobile organisms that fell off the

algal patch were collected and added into the bag. After collection in the field, the algal samples were immediately transported to the laboratory.

The algae and all contents of the bag were thoroughly washed using a series of three freshwater rinses (Ingólfsson 2000) in large tubs to remove all mobile associated taxa and scrubbed to remove as many sessile invertebrates as possible. A pilot study using 3 freshwater rinses followed by microscopic examination confirmed that the more than 95% of invertebrates were successfully removed from the raft by this method. The water was drained through a 500 µm sieve and the contents in the sieve were preserved in 70% ethanol. Once rinsed, algal rafts were classified to species, measured for length and weighed with a spring balance (kg wet weight).

Rafts collected from Jervis Bay during spring were analysed for invertebrate species composition (a subset of data used in Chapter 4). The contents collected from these rafts were placed in a sorting tray filled with freshwater. Invertebrates were counted and identified to lowest possible taxonomic level, and in some cases life stage, under a dissecting microscope.

As the focus of the study was on the allocation of motile individuals to rafts, some sessile and colonial species (where it is difficult to assign individuals or complete removal from rafts was likely imperfect) were not recorded. The total number of taxa and individuals were standardized by the wet-weight of each individual alga.

2.2.3. Analysis of data

I compared the density (number of rafts km-2) and average raft biomass (kilograms wet weight) with location (random) and season (fixed, pooled across years), using a 2-way

ANOVA in R Studio v.3.2.0. Before these analyses, I tested for normality using a Shapiro-

Wilk test and heterogeneity of variances with Levene's Test. Data were log transformed if variances were heterogeneous at p=0.05. When variances remained heterogeneous after

transformation I proceeded with the analysis of the log transformed data. A post-hoc HSD

(honest significant difference) test was used if there were significant differences between locations or seasons.

Linear regression was used to determine if there as a significant relationship between the mass of rafts and either the number of associated individuals or species. Multivariate analyses of community structure of the associated assemblage between species of alga was tested using PRIMER 7. Only samples collected during the spring season in Jervis Bay were used for analysis to eliminate the influence of season and location on the invertebrate community composition (see Chapter 4). To determine if there was a significant difference between invertebrate assemblages on each algal species, a PERMANOVA was performed using both abundance and presence absence data (allowing me to assess both the abundance and diversity of the community respectively). SIMPER analysis identified which taxa made the largest contribution to the dissimilarity between invertebrate assemblages. Untransformed and presence/absence data were visualized using a non-metric Multi-Dimensional Scaling

(MDS) plot and categorized by species of raft.

2.3. RESULTS

2.3.1. Spatial and Temporal Trends in Raft Abundance and Biomass

A total of 173 rafts were collected during this survey, 103 from Jervis Bay and 69 from Port

Kembla. Floating algae was present in both locations during all seasons, with location influencing the abundance of rafts while raft biomass was driven by seasonal trends.

Phyllospora comosa (C.Agardh, 1839) was the most abundant species of floating algae in both locations, often making up 100% of the rafts collected during a survey. In Port Kembla,

95% of the rafts collected were Phyllospora, with Sargassum spp. only encountered during two surveys (Figure 2.3). Sargassum was relatively more common in Jervis Bay, constituting

more than 45% of the rafts encountered. In particular, Sargassum made up a majority (75%) of the rafts collected in the north-eastern portion of the Bay. In all other areas of the Bay,

Sargassum was far less common, averaging around 20% of the rafts encountered.

The distribution of floating algae was patchy in nature with positional data showing hotspots of raft accumulation present within each location. The areas of high raft concentration are most often found along the shores of both locations, frequently surrounding rocky reef habitat. This was particularly true in Jervis Bay, where 77% of rafts surveyed were found within a half kilometre of shore (average distance from shore 389±38m). In Port Kembla, rafts dispersed further from shore, with only 31% being within 500m of shore or an island

(average distance from shore 695±43m). Despite rafts in Port Kembla averaging a further distance from possible sources, rafts in this location were more likely to collect into particular locations, potentially due to convergent fronts (personal observation). More than 60% of rafts along Port Kembla were part of a larger “clump” (multiple rafts all within 50m of each other) whereas in Jervis Bay only 25% of rafts were found as part of clumps.

Figure 2.3. Concentration and composition of rafts floating throughout Jervis Bay (A) and Port Kembla (B) pooled across 9 days at each location. Gradient shading indicates relative density of floating rafts (rafts/km2) and circles indicate the species composition of algal raft within that area. The location of rocky reef is indicated in black.

The density of floating Phyllospora was significantly different between locations and seasons. Phyllospora was more abundant throughout Port Kembla than in Jervis Bay (F1,11 =

52.033, p = <0.001; Table 2.1, Figure 2.4). This was particularly true in winter, where rafts of

Phyllospora were 9 times more common along Port Kembla (4.71±0.78 km2) than in Jervis

Bay (0.51±0.94 km2). The density of Phyllospora rafts was also found to vary between seasons (F1,3 = 7.001, p = 0.0067). This was driven by the high density of Phyllospora during autumn. A post hoc Tukey test confirmed that autumn had a significantly higher abundance than spring (p = 0.011), summer (p=0.020) and winter (p=0.011). Sargassum was only observed along Port Kembla during two surveys (and therefore could not be analysed via

ANOVA) but was encountered during five out of 9 surveys in Jervis Bay, particularly during winter and spring.

Table 2.1. Analysis of variance comparing the density (rafts km-2) and average individual raft biomass (kg) of Phyllospora comosa between season and location. (df) degrees of freedom, (MS) mean squares, (p) significance

ANOVA table of results df MS F p Density of rafts (per km²) Season 3 4.72 7.001 0.0067 Location 1 35.08 52.033 <0.001 Season x Location 3 0.98 1.457 0.2797 Residual 11 0.67

Average biomass of raft (kg) Season 3 2.211 4.095 0.008 Location 1 0.767 1.421 0.235 Location x Season 3 0.709 1.314 0.724 Residual 141 0.540

The average biomass of individual rafts varied significantly between seasons but not locations. Phyllospora rafts were at their largest in autumn, exceeding 1.8kg in wet mass per raft, while rafts were often smaller in spring and summer, rarely achieving more than 1.2kg

(F3,141=4.095, p<0.05). The biomass of individual Sargassum rafts (푥̅=0.626 ± 0.066kg) were on average significantly smaller than Phyllospora (푥̅=1.412 ± 0.081kg) during all seasons and locations where present (t=7.473, df=166, p<0.05).

Figure 2.4. Average density (rafts km-2±SD; top) and average biomass of individual rafts (kg±SD; bottom) of floating kelp Phyllospora comosa (black) and Sargassum spp. (grey) collected during multiple seasons in Jervis Bay (left) and Port Kembla (right).

2.3.2. Comparing Invertebrate Communities

Phyllospora and Sargassum both harboured diverse and abundant epifaunal assemblages overall, with 13,406 epifaunal individuals found in 44 algal individuals sampled, belonging to

41 taxa spanning 3 different phyla (Table 2.2). A total of 31 taxa were found on Phyllospora, and 34 on Sargassum. Of these, 19% were uniquely present on Phyllospora and 29% on

Sargassum.

Table 2.2. The number of species and percent of total individuals from each taxon found Phyllospora comosa and Sargassum spp.

Phyllospora comosa Sargassum spp. Number Percent of Number Percent of Taxon of species individuals of species individuals Arthropoda Cirripedia 1 0.23 0 0 Decapoda (Brachyuran Juvenile) 3 0.45 4 0.09 Decapoda (Brachyuran Megalopae) 6 3.45 3 0.32 Euphausiacea 1 2.72 1 11.20 Mollusca Bivalvia 5 84.38 7 36.94 Cephalopoda 1 1.30 1 0.08 Gastropoda (Heterobranchia) 0 0 1 0.40 Gastropoda (Littorinimorpha) 4 1.92 5 6.38 Gastropoda (Neogastropoda) 2 0.45 2 0.46 Gastropoda (Ptenoglossa) 1 0.57 2 3.93 Gastropoda (Sorbeoconcha) 1 3.45 2 39.94 Gastropoda (Vetigastropoda) 6 1.08 4 0.19 Gastropoda (Unknown) 0 1 0.02

Echinodermata Ophiuridae 0 0 1 0.07

Total number of species 31 34

The invertebrate communities on Phyllospora and Sargassum were significantly different

(F1,43=5.2867, p=0.001, Table 2.3). When just the presence or absence of species were considered, the difference in assemblages remained significant (F1,43=3.6615, p<0.003), which confirms that the difference is driven by species composition as well as abundance.

Likewise, multidimensional scaling of untransformed abundance data revealed relatively low overlap between the two species of raft (Stress=0.16; Fig. 2.5), corroborating that each is inhabited by a highly specific community of invertebrates. Using MDS presence/absence transformed data, the difference in species composition is less distinguishable (Stress=0.2).

This suggests that the relative abundances of taxa are part of the key to distinguishing the assemblages.

Table 2.3. PERMANOVA of epifaunal invertebrate communities present on Phyllospora and Sargassum rafts during spring (per kg). (df) degrees of freedom, (MS) mean squares, (p) significance

PERMANOVA table of results Abundance (presence/absence Abundance (untransformed) transformed) Source df MS Pseudo-F p MS Pseudo-F p Species 1 18954 5.2867 0.001 8449.9 3.6615 0.003 Residual 42 3585.3 2307.8 Total 43

Figure 2.5. Multidimensional scaling ordination of untransformed (A) and Presence/absence transformed (B) invertebrate community assemblages for rafts of Phyllospora (black) and Sargassum (grey).

Sargassum provided habitat for a significantly higher abundance of malacostracan crustaceans, bivalves and gastropods (T(-2.8674), df= 17.558, p<0.05, Figure 2.6); the three most common classes of invertebrates on rafts. Bivalves were the most common class on

Phyllospora rafts, while gastropods and the malacostraca were relatively low in abundance.

Sargassum had the highest abundance of gastropods, followed closely by bivalves. Species richness was also higher on Sargassum (T(32.177)=-4.0878, p<0.05) with the average number of species almost double that of Phyllospora. The only class where Sargassum did not outnumber Phyllospora was malacostracan crustaceans, where Phyllospora appears to have slightly higher average species richness, but not significantly (T(41.785)=0.6357, p=0.5284). Phyllospora had relatively even species richness between the three classes, averaging between 1-2 species per kilogram of algae. Sargassum averaged almost 3 bivalve

and 4 gastropod species per kilogram. Six invertebrates together contributed more than 90% of dissimilarity between the two species of raft (Table 2.4) and Sargassum had the higher abundance for all of them, some by more than an order of magnitude. In the case of the gastropod Alaba opiniosa, Sargassum had an average abundance more than 100-fold that of

Phyllospora.

Figure 2.6. Number of individuals (mean±SD; A) and species (±SD; B) per kg of rafting algae of Phyllospora comosa (black) or Sargassum spp. (grey) collected during spring in Jervis Bay.

Table 2.4. SIMPER table of dissimilarity between Phyllospora and Sargassum. Table includes the average abundance of the top 6 contributing invertebrates to the dissimilarity per kg of raft.

Phyllospora Sargassum Average Contributing Cumulative Species Average Average Diss/SD Dissimilarity % % Abundance Abundance

Electroma georgiana 55.2±25.8 205.6±94.0 28.7 1.11 31.85 31.85 Euphausiidae 1.9±0.9 72.4±30.0 23.65 0.7 26.25 58.1 Alaba opiniosa 2.4±0.1 257.8±140.1 20.56 0.86 22.82 80.92 Mytilus spp. 1.9±0.7 20.6±8.6 3.44 0.65 3.82 84.74 Janthina 0.4±0.2 25.3±12.4 2.65 0.6 2.95 87.68 Littorinidae spp. 0 26.1±17.1 2.22 0.39 2.47 90.15

2.4. DISCUSSION

In this chapterf I set out with three aims, to determine the algal species that comprise rafts off the coast of southern New South Wales, identify spatial and temporal trends in their abundance and biomass, and determine if each was inhabited by a unique epifaunal

invertebrate community. I determined that Phyllospora comosa was overwhelmingly the dominant species of raft in both locations while Sargassum was often comparatively sparse or completely absent. The abundance and biomass of floating algae was highly variable, on some days and locations I encountered large quantities of rafts and others, rafts were almost completely absent. Dempster et al. (2004) reported similar highly variable outcomes along the same coastline. Both species of alga also hosted a unique community of invertebrates, suggesting each plays a distinct role as marine habitat.

2.4.1. Spatial and Temporal Trends in Raft Abundance and Biomass

This survey confirmed that floating algal rafts are a common pelagic feature along the coastline of southern New South Wales. I observed a density of 1-5 rafts per km (equivalent to between 1.23-6.15kg km-2), which is comparable to surveyed densities of Sargassum off the New South Wales coast (1.1 clumps per 5000m2; Dempster and Kingsford 2004) and

Ascophyllum nodosum off western Iceland (1-10 kg per km2; Ingólfsson 1998). However, other locations have shown that the density of rafts can far exceed what I encountered.

Detached seaweed densities have been recorded from 60 rafts km-2 in in the Archipelago Sea

(Rothäusler et al. 2015) up to 1750 km-2 in the North Sea & German Bight (Thiel et al.

2011). Kingsford (1992) estimated the density of clumps near the coast of New Zealand in excess of 100 kg km-2 and in the Sargasso Sea, seaweed has been observed in the order of

1000 kg km-2 (Parr 1939).

The highest abundance of ﬂoating kelps is found during the spring and summer with a lower abundance in winter, indicating a predictable seasonal pattern for a number of algal species around the globe (Dayton 1985, Kingsford 1992, Hirata et al. 2001, Dempster and Kingsford

2004, Buschmann et al. 2006, Hinojosa et al. 2010, Thiel et al. 2011, Rothäusler et al. 2015).

The peak in spring and summer is often linked to the reproductive cycle of the benthic form

of many species (Komatsu et al. 2008, Hinojosa et al. 2010, Thiel et al. 2011, Rothäusler et al. 2015) which can result in increased densities, biomass and recruitment success

(Buschmann et al. 2006).

Surprisingly, Sargassum spp. was absent during autumn in both locations and was most abundant during the winter and spring in Jervis Bay. Floating rafts of Sargassum are known to usually exhibit strong seasonal patterns (Kingsford 1992, Hirata et al. 2001) due to increased fragility during their reproductive season (Norton 1976, Ohno 1984). The high fragility of this species may account for the disparity in its abundance between locations because of the differences in local seasonal processes. Strong currents or wave events (which would be more common in Port Kembla) have been cited as a reason for both producing strong seasonal trends as well as obscuring them (Kingsford 1992, Hobday 2000a, Thiel and

Gutow 2005a, Hinojosa et al. 2010).

Phyllospora comosa did not appear to experience seasonal trends in abundance and was common in both locations year-round. This is at odds with another survey conducted in New

South Wales which reported that Phyllospora comosa rafts were absent in the winter and infrequently observed in spring, summer and autumn (Dempster and Kingsford 2004). This contradiction may be rationalised by the survey of Coleman et al. (2008) along the same coastline. These authors report that Phyllospora has disappeared from 70 kilometres of the urbanized coastline of Sydney but was still abundant outside this region. As a result, it is not surprising that the Dempster et al. (2004) survey of rafts immediately adjacent to the Sydney coastline found Sargassum spp. was by far the most abundant floating alga, comprising >90% of all clumps. My study, which was conducted in areas where Phyllospora remains abundant on reefs stands in stark contrast. Phyllospora comosa was the overwhelmingly dominant species raft-forming algae nearly year-round in both locations surveyed. Druce and Kingsford

(1995) also conducted an investigation of algal rafts in both Broken Bay and Botany Bay where they reported that with the exception of one small piece of Sargassum spp., all of the floating algae sampled was Phyllospora comosa. However, Broken Bay is just north of the region where attached Phyllospora has disappeared from reefs and attached plants were actually harvested from this Bay during Druce and Kingsford’s (1995) experiment.

Therefore, although they state that most of the rafts found were Phyllospora (implying this was uniform in both locations), I contend that the relative abundance of this species would have been significantly greater in Broken Bay than in Botany Bay, but this was not specified in their findings.

The biomass of Phyllospora rafts collected in this survey were similar to those collected previously in the same area (Druce and Kingsford 1995) while Sargassum rafts were on average larger than those previously surveyed along the New South Wales coast (Dempster and Kingsford 2004). Interestingly, rafts of both species collected during my survey were larger than those collected from benthic populations by Marzinelli et al. (2016). Phyllospora rafts were 1.7 times the biomass of attached benthic individuals and Sargassum rafts were almost 10 times as large. Given that both surveys were performed during spring (Marzinelli et al. (2016) also sampled in summer), season is unlikely to be a contributing factor in the discrepancy between the average weight of rafts and attached algae. Nor does it seem likely that algal rafts are growing at a rate that could explain significantly larger rafts than attached individuals.

When compared to other species of rafting algae around the world, the biomass of

Phyllospora and Sargassum rafts fall in the middle of the range. For example, individual fragments of Durvillaea antarctica off the coast of Chile range from 0.2-0.6kg (Hinojosa et al. 2010) while giant kelp Macrocystis pyrifera off the poleward coasts of the Americas

forms rafts greater than 1.4kg (Hobday 2000a, c). However, both of these species are known to form larger patches comprised of multiple entangled rafts which range from 15 kg (in the case of Durvillaea antarctica) up to 800kg patches of Macrocystis pyrifera (Hinojosa et al.

2010). Neither Phyllospora nor Sargassum where observed entangling and forming larger clumps, even when multiple rafts were nearby.

2.4.2. Comparing Invertebrate Communities

The relationship between habitat complexity and species diversity has often been attributed to the associated greater surface area which can support a larger number of species (Conner and

McCoy 1979, Gunnill 1982, Attrill et al. 2000). However, while Sargassum has a more multifaceted and complex thallus than Phyllospora (Marzinelli et al. 2016), it has on average a comparatively smaller biomass and surface area per individual raft. In my survey,

Sargassum was found to host a higher number of individuals per kilogram suggesting that structural complexity is a more influential factor than raft biomass or surface area in determining the abundance of associated invertebrates. Similarly, high complexity holdfast mimics have been shown to be colonised by more individuals than less complex habitats, to a degree that cannot be explained simply by the complexity and surface area relationship

(Hauser et al. 2006).

The age and growth rate of floating algal rafts was thought to also influence the relative abundance of associated fauna, with greater abundances potentially being found on older, slow-growing species (Seed and O'Connor 1981, Fletcher and Day 1983). Phyllospora would be available for colonization for longer periods of time because it is a perennial species where

Sargassum has an annual cycle (Womersley 1987). However, given that is has been shown many invertebrate species are quite rapid colonizers to a variety of habitats (Virnstein and

Curran 1986, Ingólfsson 1998, Thiel 2003), it would be unlikely that the age or growth rate of an algal species significantly affects the abundance of motile invertebrates.

Environmental variables at the point of raft collection, along with location data, are often associated with variation in the species composition of rafts (Clarkin et al. 2012a). Storms, winds and currents before and after detachment can have dramatic effects on species numbers, turnover rates, and direction of drift paths (Ingólfsson 1998, Hobday 2000c) resulting in rafts losing species and being colonized by new ones. Ingólfsson (1998) noted that frequently “even a slight breeze would set a ﬂoating clump of algae in motion,” often resulting in the turnover of species while it drifts along. Internal waves also can carry rafts back onshore (Kingsford and Choat 1986), relocating species from the pelagic environment.

Numerous other studies from Australian Waters have highlighted the role of algal rafts as attractants for fish (Druce and Kingsford 1995, Dempster and Kingsford 2004). The presence of fish around rafts also likely has a strong influence on the dynamics of the invertebrates on rafts.

Although supporting a less diverse and densely populated assemblage, Phyllospora is responsible for providing much of the buoyant pelagic algal habitat along the greater New

South Wales coastline due to its greater abundance and biomass. A lack of abundance or species richness does not equate to a lack of ecological or economic importance. Phyllospora had fewer species overall, but played host to many unique species and therefore is not redundant as habitat. At both study locations, floating rafts may often be in sufficient quantities to be of importance in affecting the distribution of invertebrates nearshore and in the pelagic environment (Kingsford and Choat 1985).

2.4.3. Implications and outlook

The aggregation of invertebrates on drift algae is important to our understanding of events during the early life of many of these species (Kingsford and Choat 1985). As key habitat in the pelagic environment, knowledge of their spatial and temporal distribution is fundamental to establishing its ecological role for larval and juvenile invertebrates (Dempster and

Kingsford 2004). The size and growth rates of these species can also be used to estimate the length of time it has been associated with the raft, and even provide an alternative for aging the raft (Hobday 1998).

Anthropogenic disturbance in Sydney has shifted the species composition of raft-forming algae and may have an accompanying impact on the associated invertebrate communities. I explore this question further in the next chapter. Although Phyllospora and Sargassum often co-exist, each hosts a distinctive invertebrate community with several mutually exclusive species. If Phyllospora populations decline, as already seen in Sydney, it is unclear if

Sargassum can serve as surrogate habitat for displaced invertebrate species. The availability of Sargassum rafts in my study locations have been shown to be highly variable and there would likely be certain seasons and locations where it would not be able to compensate for the disappearance of Phyllospora. This may create spatial and temporal gaps in the availability of this key habitat and dispersal mechanism for many invertebrates, particularly larval stages, that may rely upon it.

CHAPTER 3- THE DISTRIBUTION OF

FLOATING AND BEACH-CAST ALGAL

RAFTS ALONG THE NSW COASTLINE

3.1. INTRODUCTION

Macroalgae are an important part of the marine environment along temperate coastlines around the globe. Some species become buoyant after they are torn from reefs and are able to act as floating rafts that have the potential to act as a dispersal vector, carrying associated species farther than they would be capable of moving independently (Helmuth et al. 1994,

Hobday 2000c, Thiel 2003, Thiel and Gutow 2005b, Rothäusler et al. 2009). While our understanding of dispersal and the inﬂuence of large-scale oceanographic processes is relatively well developed for ﬁsh and invertebrates (e.g. Connolly and Roughgarden 1998,

Botsford 2001, Broitman et al. 2005, Wilson et al. 2008, White et al. 2010) comparatively little is known about the dispersal of marine macrophytes despite their ecological importance

(Coleman et al. 2011b). As a habitat and food source in the pelagic environment (Thiel and

Gutow 2005b), these rafts play a key role in maintaining the diversity, dispersal and abundance of many associated invertebrate species (Kingsford and Choat 1985, Ingólfsson

1995, Hobday 2000c). In addition to the role they play afloat at sea, rafts that have beached are known to be an important factor structuring local assemblages of invertebrates on sandy shores (Marsden 1991, Eereveld et al. 2013).

The highest occurrences of floating rafts have been recorded between 20° and 50° in both hemispheres (Thiel and Gutow 2005a). However, within these regions there is still a large degree of variability in the biomass of raft-forming alga found. Both natural processes

(predation, storms, and disease) and anthropogenic (climate change, eutrophication, and urbanization) greatly influence the fitness and resilience of these macroalga populations

(Dayton et al. 1998, Steneck et al. 2003, Thibaut et al. 2005, Airoldi and Beck 2007).

Surveys have varied from less than 100kg/km2 (Hobday 2000a, Hinojosa et al. 2010) up to more than 1500kg/km2 (Kingsford 1992, Hinojosa et al. 2011) along the coasts of California

and Chile and densities of up to 1750 occurrences of seaweed km-2 in the German Bight

(Thiel et al. 2011).

Along the south eastern coast of Australia, one of the most common species of macroalga is

Phyllospora comosa (Chapter 2; Edgar 1984, Underwood et al. 1991, Coleman 2002).

Historically, this species often dominated large portions of the shallow rocky intertidal zone from Port Macquarie in the North to Tasmania in the south, with rafts being found as far away as Lord Howe (Womersley 1987, Millar and Kraft 1994) and Norfolk Islands (Millar

1999). Phyllospora comosa (hereafter referred to as Phyllospora) and its associated rafts have been shown to provide key habitat for many commercially important local species such as spiny lobster, urchins, abalone (Marzinelli et al. 2013) and blue swimmer crab (Chapter 4).

Surveys conducted by Coleman et al. (2008) discovered a gap in Phyllospora’s distribution about 70 kilometres in length along the Sydney coastline. During the field and literature surveys they conducted, no Phyllospora was found along reefs in this gap despite being common in the past (pre-1980s) and large populations still existing outside this area. They speculated that Phyllospora’s historical decline in Sydney was a result of ocean outfalls which for a time, released large amounts of stormwater, urban runoff and treated as well as untreated sewage onto nearby reefs.

The recent re-planting of Phyllospora forests within the Sydney region are showing early signs of success but acknowledge that highly localized dispersal and recruitment may pose a barrier to its recovery (Campbell et al. 2014). Propagules of some fucoids have been known to have limited dispersal and therefore may not settle successfully very far from the reefs where they originated (Kendrick and Walker 1995). However, other studies have found that floating algal rafts are capable of travelling hundreds or thousands of kilometres (Hobday

2000c) and Phyllospora’s presence as far away as Lord Howe island suggest it is capable of

long-distance dispersal. The East Australian Current and other oceanographic features such as eddies and counter-currents have been presumed to facilitate its long-distance dispersal along the southeast Australian coastline (Nilsson and Cresswell 1981, Mata et al. 2007, Coleman and Kelaher 2009) due to its appearance on beaches hundreds of kilometres from a potential source (Millar 1999, Coleman and Kelaher 2009, Coleman et al. 2011a). With this in mind, it seems possible that Phyllospora would drift across the 70km gap in Sydney with regularity

(Coleman and Kelaher 2009, Marzinelli et al. 2013).

While it is known that some species of algal rafts commonly travel long-distances, it is uncertain whether this rafting is sufficiently frequent for Phyllospora along the New South

Wales coastline. I predict that Phyllospora will be homogeneously distributed along the NSW coast despite its disappearance as attached plants from reefs in the Sydney region. A previous study on the connectivity in coastal marine organisms in the same region found that

Australia’s strongest boundary current, the East Australian Current (EAC), allowed for large- scale dispersal of benthic macroalga Ecklonia radiata (Coleman et al. 2011b). Given the similarity of Phyllospora's current distribution, it seems possible that this species is also regularly traversing significant distances along the coastline with the assistance of the EAC.

My aim was to survey the distribution of Phyllospora rafts both within and surrounding the

Sydney region to determine whether its abundance is depressed within the Sydney region where reef populations have disappeared. I tested this prediction in two ways. First, by surveying portions of the coastline for beach cast wrack and second, through aerial coastline surveys.

3.2. METHODS

3.2.1. Beach and Aerial Surveys

The eight beaches surveyed for beach cast wrack were between Noraville, 75 kilometres north of Sydney and Port Kembla, 80 kilometres south of Sydney. Of the beaches, five were adjacent to existing Phyllospora populations and three were within the Sydney region (where

Phyllospora is absent). Beaches were chosen based upon a variety of factors including distance to nearest rocky reef, beach orientation, and accessibility. All beaches were east to south-east facing (Figure 3.2). Beaches with minimal human impact were preferred but this was not always possible given proximity to the city. A check with local governments confirmed that none of these beaches were cleaned below the high-tide line and therefore beach cleaning would not interfere with wrack wash-up and collection.

The aerial survey encompassed 200km of New South Wales coastline between Lake Illawarra in the south and Budgewoi beach to the north (Figure 3.1). The coastline covered in this survey was partitioned into 8 sectors, each 25 kilometres in length. Sydney, Sydney metro and Botany heads are within Sydney and Phyllospora is absent from reefs within these sectors (Coleman et al. 2008). Phyllospora is commonly encountered on reefs in the remaining five sectors of coastline. No coastal survey could be conducted between Ben

Buckler and Cape Solander due to the controlled airspace regulations surrounding Sydney

International Airport. The flight path between these two points bypassed the interior of

Botany Bay.

3.2.2. Survey design

No beach or aerial surveys were conducted within a week of significant storm events (winds of more than 50 km/hr or a 5m swell). Beach collections took place over a one year period, averaging once every 4 months (three times in total). During a low tide of 0.3 metres or less, a 35m transect parallel to the low-tide line was designated at random and all wrack was removed between the low and high tide lines (average area of 700m2). Approximately 24 hours later during the low tide, each transect was re-cleared and any wrack that washed ashore was identified and weighed wet in kilograms.

Aerial survey flights were conducted on 2 occasions, October 19, 2014 and February 16,

2015. Both days had low wind and cloudless skies. A Cessna 172 Skyhawk flew round-trip from the Illawarra Regional Airport north to Budgewoi and back. The flight followed the designated “coastal flying” path which allows pilots to fly close to the beach and following the contours of the coastline. The plane flew at an average altitude of 150 meters and 250 meters from the coast for the duration of the journey. Two 200km transects were surveyed by human observers simultaneously during each flight. One transect covered the 100m immediately adjacent to the shore while the other 100m transect was approximately 400-

500m offshore.

The transects were subdivided into 8 sectors, each 25km in length, with an approximate survey area of 2.5km2. Two of these sectors were north of Sydney, three within Sydney and three below (Figure 3.2). Estimates of mean raft biomass were based on n=4 for each of the sectors (two surveys per sector during each flight).

Figure 3.2. Locations of beach and aerial surveys. Beaches surveyed are identified by large dots and letters A- H. Area covered by aerial survey is between southern and northern end markers. Sectors 25km in length of coastline indicated by dashed lines. Coastline where Phyllospora comosa is no longer found identified by Sydney Region.

Phyllospora rafts are on average more than twice the mass of Sargassum rafts (the only other significant contributor to pelagic rafts in the area, Chapter 2), and have much broader fronds and stipes, making them much easier to spot from a higher altitude. Positively identified

Phyllospora rafts that were located had their waypoint recorded. Phyllospora rafts were assumed to average 1.41±0.08kg wet weight and 1.03±0.002m in length (based on data from

Chapter 2), easily visible from a height of 150 meters. Other common species of algae in this region are either not buoyant or significantly smaller in average size and thus were unlikely to be mistaken for Phyllospora.

3.2.3. Analysis of data

Aerial survey data was mapped using ArcGIS software. Data were analysed using R Studio v.3.2.0. for all statistical tests. Before these analyses, I tested for normality using a Shapiro-

Wilk test and heterogeneity of variances with Levene's Test. A series of 2-factor ANOVAs

(sector X day) was conducted to identify any differences in the biomass between sectors.

Data were square root transformed if variances were heterogeneous at p=0.05. When variances remained heterogeneous after transformation I proceeded with the analysis of the square root transformed data. Post-hoc Tukey's HSD (honest significant difference) tests were used if significant differences were detected. The absence of Phyllospora in some sectors meant that not all sectors could be included in the analysis. My focus shifted to comparing sectors in which wrack was located.

3.3. RESULTS

3.3.1. Beach Surveys

Beach cast wrack was found washed ashore on half of the 8 beaches surveyed (Figure 3.3).

The beaches to the south of Sydney and the beach furthest north all regularly accumulated

Phyllospora wrack. However, no wrack was found within the city or at the beach in the sector just to the north. On beaches where wrack was found, there was no difference in the mass that accumulated (F3,6=0.091, p=0.975, table 3.1). The amount of wrack that accumulated on each beach was also not found to differ significantly between survey days (F2,6=0.069, p=0.979).

Along beaches where Phyllospora was found, the average mass of algae that washed in a 24- hour period was 3.28±0.27 kg/km2.

Table 3.1. Analysis of variance comparing the biomass of Phyllospora comosa wrack found on surveyed beaches. (df) degrees of freedom, (MS) mean squares, (p) permutation significance

ANOVA Table of Results Source Df Mean Sq F value p Day 2 580982 0.021 0.979 Sector 3 1917353 0.069 0.975 Residuals 6 27858471

3.3.2. Aerial Surveys

Aerial surveys located floating Phyllospora comosa rafts in 6 out of 8 sectors (Figure 3.4A).

No rafts were located within two of the Sydney sectors, forming a 55-kilometre gap between

Bate Bay and Narrabeen (Figure 3.4B). Isolated rafts (0.084kg/km2) were found floating along the coast of North Sydney despite being within the region where Phyllospora reefs have disappeared (Coleman et al. 2008). The sector with the highest average biomass of rafts was the Central Coast North with an average of 9.97kg km-2. Sector significantly influenced the biomass of rafts (F5,17=3.765, p=0.018; Table 3.2) with the furthest north sector having the highest density of rafts. The Sutherland sector, south of Sydney, also had significantly more rafts than the two locations with rafts to its north (p<0.027; Table 3.3). Biomass was

found to be highly variable between days of survey (F1,17=10.68, p<0.005), particularly in sectors north of the city which saw more than a 20-fold difference in biomass between the two days. Rafts were not found within the sector where replanting has been taking place (2 locations within Botany heads, see Campbell et al. 2014) with the nearest proximity raft more than 7 kilometres away.

Figure 3.4A. Biomass of rafts sighted during aerial surveys per km2 in each sector of coastline. Sectors are listed from furthest north to furthest south. Error bars represent ± 1 standard error. Grey bar represents sectors in Sydney. Figure 3.4B Map of coastline surveyed, partitioned into eight 25km sectors. Locations where rafts were found during aerial survey are indicated by black dots. Coastline where attached Phyllospora comosa is no longer found identified by “Sydney Region”.

Table 3.2. Analysis of variance comparing the biomass of Phyllospora comosa rafts found during aerial survey. (df) degrees of freedom, (MS) mean squares, (p) permutation significance Table 3.3. Tukey’s Honest Significant Difference table with sectors that had a significantly different biomass of rafts

ANOVA Table of Results Tukey's Honest Significant Difference Source Df MS F-value p Sector Sector p Day 1 3.233 10.68 0.005 Central Coast North - North Sydney 0.022 Sector 5 1.14 3.765 0.018 Central Coast North - National Park 0.025 Residuals 17 0.303

3.3.3. The relationship between rafts and Phyllospora reefs

There was a strong relationship between percent cover of attached algae and the mass of beached wrack (F(1,6)=7.466, p=0.034, R2=0.5544, Figure 3.5A). In sectors lacking

Phyllospora forests, no wrack washed ashore along nearby beaches. Beaches adjacent to

Phyllospora forests regularly had large amounts of wrack wash ashore. The there was no direct relationship between percent attached cover and biomass of rafts (F(1,6)=1.941, p= p=0.213, R2=0.2445, Fig. 3.5B). However, few rafts were found offshore coastline where

Phyllospora is absent whereas rafts were more common in sectors where Phyllospora is currently found on reefs.

Figure 3.5. (A) Mass of beached wrack and (B) biomass of floating rafts in relation to the average percent cover of Phyllospora in each sector. Percent cover data from Coleman et. al. 2008.

When the amount of wrack surveyed by each method is compared, it further highlights the strong relationship between reefs where Phyllospora is present and the availability of wrack

(Figure 3.6). The Sydney region is almost entirely devoid of wrack except for the occasional raft floating in from the edges. Outside the city, Phyllospora was common during nearly all surveys.

3.4. DISCUSSION

My initial prediction of a homogeneous distribution of rafts along the entire coastline was not supported. This study reveals that the dissemination of Phyllospora comosa rafts, both afloat at sea and washed ashore, closely mirrors the distribution of current day attached populations

(Coleman et al. 2008). No rafts were located within the Sydney region, except for small quantities in the northernmost region observed during aerial surveys. However, outside of

Sydney, to the north and south, rafts were abundant at sea and along beaches.

Phyllospora populations to the north and south of Sydney experience high genetic structure which indicates limited exchange between reefs (Coleman et al. 2011a) despite its dispersal- assisting physiology. Campbell et al. (2014) acknowledge that their reef re-establishment project within the Sydney region may have been inhibited by recruitment limitation as they only found recruits within or at the margins of the adult canopy. Similarly, off the California coast it was found that the probability of an algal raft successfully floating away from a reef

and then returning to shore more than 100km away occurred in less than 5% of cases

(Hobday 2000a). The total quantity of floating seaweeds seems to diminish rapidly with distance from their source, probably owing largely to their loss of buoyancy as their float bladders deteriorate. There are other explanations why populations separated by great distances are still genetically similar that are not reliant on the regular dispersal of rafts (see

Coleman and Kelaher 2009) or it may be possible that a small quantity of rafts are sufficient to prevent genetic drift.

The frequency of Phyllospora crossing the 70-kilometre gap may not be as common as currents would suggest is possible for propagules along this coastline (Coleman et al. 2011b).

Along the New South Wales coast, nearshore circulation patterns can be particularly difficult to predict (White et al. 2010). While most of dispersal via the EAC is pole-ward, equatorward dispersal is also common, particularly at higher latitudes. Eddies are also common in the austral summer and autumn (Mata et al. 2007), which can result in the non-linear transport of propagules (Coleman et al. 2011b, Rothäusler et al. 2015). Additionally, differences in the availability of rocky reef or kelp forest habitat between sectors (Alberto et al. 2010), the continuity of coastlines or local oceanographic features and seascapes (Rothäusler et al.

2015) may inﬂuence dispersal and connectivity.

Although boundary currents drive connectivity across large-scales, small-scale processes are important considerations and have the potential to deliver propagules away from their predicted paths (Gaylord et al. 2006). The dispersal of floating algae is known to be altered by impacts on raft supply, such as storms and changes in water circulation which tear attached macroalgae from reefs (Seymour et al. 1988). In the days to weeks following such events, the elevated supply of rafts often results in an increased abundance and altered distribution along the coastline. Although avoiding storm-driven disruptions to abundance

and dispersal were taken into consideration when selecting survey dates, aerial survey data suggest a high level of variability in raft biomass. The maximum density of floating rafts was

9.97kg km-2. However, 37.8% of the time rafts were sparse or absent (36.4%) in areas where

Phyllospora rafts are known to be common. Surveys of floating algal biomass in other regions have found densities anywhere between 0-3000kg/km2 (Kingsford 1992, Hobday

2000a, Hinojosa et al. 2010, Hinojosa et al. 2011) with great variability between sampling days.

The unreliability or absence (in the case of the Sydney metropolitan area) of rafts in many of these sectors potentially has serious consequences for epifaunal invertebrates. Many of the species found commonly on Phyllospora rafts are not capable of independent long-distance dispersal and I anticipate will experience recruitment difficulties in areas where rafts are sparse or absent. With limited gene flow, fragmented populations may suffer from inbreeding depression and become morphologically, physiologically or ecologically dissimilar (e.g.

Soule 1980, Lande 1993, Frankham 1998, Tanaka 2000, Keller and Waller 2002). Future studies could explore if species found commonly on Phyllospora rafts have experienced any change in abundance or distributional shifts in the decades subsequent to its disappearance.

Additionally, the longevity of rafts may be negatively impacted by the predicted rise in sea surface temperatures (see Chapter 6), making long-distance dispersal in this region even more difficult in the future.

With conservation strategies moving towards a focus on habitat rather than individual species, identifying the spatial and temporal dynamics of key habitat-forming macroalgae is increasingly important for the decision-making process (Coleman et al. 2011b). The results of this study have important implications for the conservation and management of Phyllospora forests, which provide ecological value as habitat along the New South Wales coastline.

Understanding the oceanographic processes that impact on dispersal may be key to assisting

its recovery in urbanized areas. The predicted strengthening of the EAC (Cai et al. 2005,

Suthers et al. 2011), will impact upon the distribution of species along the New South Wales coastline. For the rehabilitation of forests (Marzinelli et al. 2016) to be successful into the future it will be necessary to continue updating our understanding of local processes, especially given the rise in anthropogenic stressors predicted to impact upon macroalgal habitats world-wide (e.g. Dayton et al. 1998, Steneck et al. 2003, Airoldi and Beck 2007,

Coleman et al. 2008, Connell et al. 2008). Continued monitoring of oceanographic processes in this region will be critical to ensuring the survival of key habitat, such as Phyllospora forests, into the future.

CHAPTER 4 –TRENDS IN ABUNDANCE AND

DIVERSITY OF RAFT-ASSOCIATED

INVERTEBRATES

4.1. INTRODUCTION

Macroalgal forests and their free-floating rafts harbour a diverse assemblage of marine fauna

(Dayton 1985, Steneck et al. 2003, Graham 2004, Fraser et al. 2011) while also providing food, a substratum, and protection from predators (Thiel and Gutow 2005b, Minchinton 2006,

Urban-Malinga and Burska 2009). Algal rafting may be particularly important for species or life stages that are not independently capable of dispersing outside the local area (Highsmith

1985, Jackson 1986, Kinlan and Gaines 2003, Minchinton 2006), by lessening the energy expenditure usually required for a pelagic journey (Rulifson 1983). Some marine species have achieved great dispersal distances and range expansions with the assistance of floating propagules such as rafts (Edgar 1987, Jokiel 1990, Helmuth et al. 1994, Thiel and Gutow

2005a, Thiel and Haye 2006).

Floating seaweeds have been found to harbour a diverse epifaunal community (Highsmith

1985, Edgar 1987, Davenport and Rees 1993, Ingólfsson 1995, Minchinton 2006, Fraser et al. 2011, Clarkin et al. 2012a, Gutow et al. 2015). These species may have been originally living on the seaweed in situ or have colonized after it became a floating clump (Druce and

Kingsford 1995, Ingólfsson 1995, Ingólfsson 1998, 2000). Thiel & Gutow’s review (2005b) reported more than 1200 taxa associated with rafting around the globe. A variety of animals, such as crabs, isopods, gastropods, anemones, and bivalves were common passengers on detached macroalgae (Highsmith 1985, Worcester 1994). Despite this, algal rafting is still seldom deemed an essential stage in the life history of many species, despite the fact that some are found regularly in abundance on rafts (Thiel and Gutow 2005b). The abundance and diversity of the rafting community may be heavily influenced by spatial and temporal factors

(Fine 1970, Stoner and Greening 1984, Kingsford and Choat 1985, Ingólfsson 1995, Thiel

2003, Vandendriessche et al. 2006a, Hinojosa et al. 2010) as well as the size, age and quality of the raft (Thiel and Gutow 2005b).

While the successional processes occurring after algal detachment is well documented (Thiel

2003, Thiel and Gutow 2005b, Clarkin et al. 2012b), less is known about how the composition of invertebrates changes seasonally. Most previous studies on epifauna inhabiting seaweeds found seasonal trends in abundance patterns for at least some taxa, with abundance peaks generally occurring in spring or summer (Taylor 1998). The rafting community may also be dependent on the motility of the invertebrates themselves, changing over time. Some invertebrates are sessile obligate rafters while others may be highly mobile allowing them to come and go as the raft floats along (Friedrich 1969, Thiel and Gutow

2005b, Gutow et al. 2015).

One of many noteworthy species found as megalopae and juveniles on rafts along the coastline of South Eastern Australia is Portunus spp. (personal observation). This species holds great commercial value throughout its distribution in the Indo-west Pacific (Potter et al.

1983, Kailola et al. 1993, Svane and Cheshire 2005, Ikhwanuddin et al. 2012, Ikhwanuddin et al. 2013) with total world landings >172,000 tons in 2007 (FAO 2007, Ikhwanuddin et al.

2012). This species has been well studied in laboratories (Josileen and Menin 2005,

Ikhwanuddin et al. 2013, Azra and Ikhwanuddin 2015) and near shore environments (Potter et al. 1983, Ingles and Braum 1989, Bryars and Havenhand 2004, Ikhwanuddin et al. 2012) but less is known about its early planktonic stages in the pelagic environment. These early life stages may take refuge on rafts until they are large enough to settle back in the intertidal

(Wehrtmann and Dittel 1990, Hinojosa et al. 2007). Identifying when and to what extent

Portunus spp. utilizes rafts, of which little is known, may be a useful stock monitoring tool for these earliest life stages.

The association of epifaunal invertebrates with algal rafts has garnered much attention globally (Thiel and Gutow 2005b), yet gaps still remain in our understanding of the

community composition and the importance of rafting in the life history of many species along the coastline of South East Australia (but see Kingsford and Choat 1985, Langtry and

Jacoby 1996, Dempster and Kingsford 2004). Local physical processes likely influence the spatial and temporal abundance and composition of raft-occupying invertebrates (Clarkin et al. 2012a). The two locations used in this study, Jervis Bay and Port Kembla, are both known to have relatively abundant Phyllospora comosa rafts yet would be categorized as very different coastlines. Jervis Bay has a mainly sheltered coastline lined by reflective beaches while Port Kembla has a dissipative and exposed coastline. Studies of floating algae along the same coastline have provided insight into the processes affecting the recruitment of fish and crustacean species as larvae and juveniles (Kingsford 1995, Langtry and Jacoby 1996) but have not compared rafting communities between locations.

The aim of this chapter was to identify and quantify the invertebrate community found on

Phyllospora comosa pelagic rafts in two locations, Port Kembla and Jervis Bay. I explored the relationships between invertebrate abundance and diversity at both locations as well as across seasons. The community composition on rafts is expected to differ between locations as well as experience seasonal shifts; reflecting local patterns, species distributions, spawning events and growth cycles. I also monitored the abundance of Portunus spp., as other

Portunidae species are known to be common on rafts (Wehrtmann and Dittel 1990). Monthly measurements of abundance and carapace width are used to follow the progression of this species from larvae to adults throughout the year. Recognising the role rafts play in the life history (particularly the early stages) of this species as well as many others may have important implications for ecological management and commercial stock assessment.

4.2. METHODS

The invertebrate communities analysed in this chapter were collected from the rafts used to compare algal species abundance and biomass in Chapter 2. Invertebrates collected on

Phyllospora rafts during spring were used in analysis for Chapter 2 and form a subset of the data for this chapter. Sargassum spp. rafts analysed for their species community in Chapter 2 are not included in the dataset for this chapter. This chapter focuses on trends spatial and temporal trends of the associated invertebrate communities on Phyllospora only and is not a comparison between different species of macroalgae as seen in Chapter 2.

For more information on the collection methods of rafts, see Chapter 2.

4.2.1. Laboratory methods

The algae and all contents of the bag were thoroughly washed using a series of three freshwater rinses (Ingólfsson 2000) in large tubs to remove all mobile associates and scrubbed to remove as many sessile invertebrates as possible. The water was drained through a 500 µm sieve and the contents in the sieve were preserved in 70% ethanol. The contents collected from the rafts during the rinses were placed in a sorting tray filled with freshwater.

Invertebrates were counted and identified to lowest possible taxonomic level and in some cases, life stage under a dissecting microscope. For many species, identification keys of early life stages are inconclusive so it is difficult to determine if we have found the same species at two different life stages. Therefore, until better taxonomy is available, the different life stages will be treated as separate operational taxonomic units (distinguished using an alphanumeric naming system). As the focus of the study was on the allocation of motile individuals to rafts, some sessile and colonial species (where it is difficult to assign individuals or complete removal from rafts was likely imperfect) were not recorded.

In this region, both Portunus pelagicus and Portunus sanguinolentus are present (FAO 2016) and are difficult to identify at their youngest stages as they have not developed their distinguishing markings and have uniform growth rates (Sukumaran and Neelakantann 1997).

Therefore, for this survey they will be numerated together and identified as Portunus spp.

Any Portunus spp. identified were measured to the nearest 0.1cm using Vernier callipers.

Carapace width was measured as the distance between the 9th anterolateral spines of the carapace (Ikhwanuddin et al. 2012).

4.2.2. Analysis of data

Abundance and diversity of algal rafting communities were compared between locations

(random) and seasons (fixed), using a 2-factor ANOVA in R Studio v.3.2.0. The abundance and species richness of invertebrates was standardized per 1kg of raft. Before analysis, I tested for normality using a Kolmogorov-Smirnov test and homogeneity of variances with

Levene's Test. Invertebrate abundance and diversity were square root transformed. Post-hoc

Tukey's HSD (honest significant difference) test was used if significant differences were found between treatments.

Differences in invertebrate communities found between locations and seasons were evaluated using PRIMER7. SIMPER analysis on both untransformed and presence/absence data, was used to determine which taxa most contributed to this difference. To determine if this led to a significant difference in assemblage composition, a PERMANOVA was performed using both abundance (untransformed) and presence/absence (transformed) data. Results for both untransformed and presence/absence data were visualized using a non-metric Multi-

Dimensional Scaling (MDS) plot and categorized by location and season.

4.3. RESULTS

4.3.1. The rafting community: Spatial and Temporal Trends

Phyllospora was found to harbour a diverse and abundant epifaunal assemblage with 13,622 individuals from 132 algal rafts sampled, belonging to 64 taxa spanning 3 different phyla

(Table 4.1). There were 31 species of arthropods, 32 molluscs and one species of cnidarian.

The most common taxa of arthropods were decapods of which three different life stages were identified: zoea, megalopae and juveniles. Amphipods were also common in samples but are likely underestimated as they often bore into holdfasts which were not dissected to extract individuals. The most common molluscs were gastropods, from at least 5 different orders, all of which were juveniles.

Table 4.1. The number of species and percent of total individuals from each taxon found on rafts of Phyllospora.

The two locations had a significantly different in the number of individuals (F1,122=8.75, p=0.004), with Port Kembla having a higher average abundance per kilogram than in Jervis

Bay (except during spring). The number of individuals was also significantly influenced by season (F3,122=9.115, p<0.001; Table 4.2; Figure 4.5) with summer having a higher

abundance of invertebrates than autumn and spring (p<0.001) in both locations. During summer, the number of individuals kg-1 of raft was often above 200 in both locations. During autumn, when abundances were lowest, rafts in Jervis Bay often had fewer than 15

-1 invertebrates kg . The number of species was not influenced by season (F3,122=0.187, p=0.187) or location (F1,122)=2.008, p=0.159), averaging just under 6 species during all surveys. There was no significant interaction between location and season (F3,122=2.329, p=0.078).

Figure 4.1. The average number of individuals (A) and average number of species (B), found during each season at both locations (±SE).

The substantial differences in invertebrate abundance is driven by changes in the community composition of invertebrates during different seasons and between locations (Figure 4.2). In

Jervis Bay, arthropods are the dominant species during the summer, averaging 190 individuals kg-1 raft. In subsequent seasons, this drops to an average of 8 with the number of gastropods increasing over the same period from 6 in summer to 117 individuals kg-1 in the spring. Port Kembla is dominated by arthropods all year, with highest average abundances in

the summer of 250 and lowest in spring of 60 individuals kg-1. The number of gastropods remains constant all year, averaging just below 2 individuals kg-1.

Figure 4.2. The relative abundance of arthropods (grey) and gastropods (black) during each season and both locations surveyed.

Although diversity was comparable between all surveys, there was a significant difference in community composition between locations (F1,122=12.112, p<0.001, Table 4.3) and seasons

(F3,122=6.3915, p<0.001), but also a significant interaction between the two (F3,122=4.5606, p<0.001). Presence/absence transformed data which allowed me to assess species compositions between the algae taxa gave the same significant results for both factors and the interaction term (p=0.001). Although the two factors cannot be examined in isolation, multidimensional scaling for both abundance and P/A transformed data indicate different species comprise the raft assemblage in each instance (Stress=2.2; Figure 4.3). Location MDS for both abundance data and P/A illustrate relatively little overlap between samples from Jervis

Bay and Port Kembla, signifying a unique composition of invertebrates at each location. The pattern is less discernible in the season MDS but is best seen in the distinct clumping of samples from summer and autumn.

Table 4.3. Abundance and Presence/absence PERMANOVA results for the effects of location and season on the species diversity found on floating macroalga Phyllospora comosa.

Figure 4.3. Multidimensional scaling ordination of the abundance and presence/absence transformed invertebrate community compositions for both locations and all seasons surveyed.

A SIMPER analysis of species contribution to community composition reveals an average species dissimilarity between locations of 92.58 (Table 4.4). Nyctiphanes, a pelagic crustacean, contributes the largest amount (23.36%) to the dissimilarity between locations and is more prevalent in Port Kembla. Electroma georgiana, a bivalve, was the second largest contributor. It was often found in extremely high densities on rafts in Jervis Bay

(averaging 56.45 individuals kg-1) but was never found in Port Kembla. On average, there were higher abundances of molluscs in Jervis Bay such as Alaba opiniosa, while most arthropods were more prevalent in Port Kembla.

Table 4.4. SIMPER table of dissimilarity between Jervis Bay and Port Kembla. Table includes the average abundance kg-1 of the top 13 contributing invertebrates to the dissimilarity.

Port Jervis Bay Kembla Average Contributing Cumulative Average Diss/SD Average Dissimilarity % % Abundance Species Abundance Nyctiphanes australis 29.4±10.1 31.4±7.3 0.94 21.63 23.36 23.36 Electroma georgiana 56.5±24.5 0±0 0.53 13.55 14.63 37.99 Portunus spp. (megalopae) 3.6±1.3 31.1±8.4 0.67 13.45 14.53 52.52 Brachyuran (megalopae - N1) 0.6±0.2 21.9±8.9 0.55 11.34 12.25 64.77 Idotea spp. 1.2±0.5 10.7±4.3 0.44 6.76 7.31 72.08 Brachyuran (megalopae - B4) 0.3±0.1 9.8±4.2 0.43 4.25 4.59 76.67 Portunus spp. (juvenile) 1.1±0.4 2.9±0.7 0.45 3.7 3.99 80.66 Brachyuran (juvenile - B10) 17.6±8.2 0.1±0.1 0.31 3.46 3.73 84.4 Brachyuran (megalopae - N5) 0.7±0.3 1.1±0.6 0.27 1.75 1.89 86.29 Ostracoda 0.5±0.2 1.3±0.3 0.46 1.45 1.57 87.85 Alaba opiniosa 1.9±0.6 0.03±0.02 0.35 1.45 1.56 89.41 Brachyuran (megalopae - N3) 0.1±0.1 0.7±0.3 0.3 1.06 1.14 90.55

Nyctiphanes australias contributed heavily to to the dissimilarity between many seasons

(Table 4.5). Five species of megalopae also showed high levels of seasonal fluctuation, often peaking in abundance summer and infrequent the rest of the year. The two most seasonal mollucs, Electroma georgiana and Alaba opiniosa were most abundant in spring samples.

Table 4.5. SIMPER table of average dissimilarity between seasons accompanied by species that contributed the most to the difference. Table includes the average abundance of the top 11 contributing invertebrates to the dissimilarity.

Summer Summer Spring Autumn Autumn Autumn Seasons Spring Winter Winter Summer Spring Winter Average Dissimilarity 91.33 88.49 86.85 85.92 84.59 83.21 Species Nyctiphanes australis 25.83 19.5 13.67 22.94 17.96 15.13 Portunus spp. (megalopae) 25.35 25.22 2.45 29.92 9.11 5.6 Brachyuran (megalopae - N1) 1.43 18.98 30.02 3.41 8.66 31.97 Electroma georgiana 8.98 4.78 12.82 1.73 8.77 4.56 Brachyuran (megalopae - B4) 9.12 8.3 4.49 11.7 0.93 4.93 Idotea spp. 4.85 7.43 1.32 11.46 1.75 Brachyuran (juvenile - B10) 7.1 4.47 4.18 Portunus spp. (juvenile) 3.06 7.8 4.48 Brachyuran (megalopae - N5) 4.49 2.02 5.38 Brachyuran (megalopae - N3) 1.98 1.78 Alaba opiniosa 1.12 1.31

4.3.2. The growth and development of Portunus spp. on rafts

The Portunus spp. megalopae experienced their highest abundances in January with an average of 273.4 (±49.2) individuals kg-1 (Figure 4.4). Numbers sharply decline in the following months and by May the average has dropped to 2 individuals kg-1. No megalopae were found in June were less than one kg-1 were found between August and October. The month of November begins the summer peak in abundance.

Juvenile P. pelagicus reach their highest abundance in autumn, with 12.7 (±3.47) individuals kg-1 in May. Very few individuals were located between June and October, with the occasional raft beginning to carry juveniles in November. Their abundance begins to increase early in the summer with an average of 2-3 individuals kg-1. Juveniles on rafts also experienced seasonal trends in carapace width. The average annual carapace width for a juvenile P. pelagicus was 4.52mm (±0.21). However, in March the average carapace width increased to 11.1mm (±1.12) with the largest individual measuring 33.6mm.

4.4. DISCUSSION

The abundance and diversity of invertebrates identified on rafts during this survey highlights its importance as a pelagic habitat. Species with a variety of life histories share these small islands for at least a brief time during their development or journey. There were identifiable spatial and temporal patterns in species abundances and diversity suggesting that rafts play an assortment of ecological roles (habitat, food source, dispersal propagule) depending on the algal species, location and season. Some species common on rafts hold commercial value, including Portunus spp. This brachyuran was found in multiple life stages suggesting that rafts provide important habitat to this species during its earliest developmental stages.

4.4.1. The rafting community: Spatial and Temporal Trends

Pelagic invertebrates often congregate in higher densities on rafts than in the pelagic environment and the community on these rafts is also unique when compared to that of attached algae (Kingsford and Choat 1985). My survey demonstrates that the rafting community is likely influenced by season and location as well as the life histories of the rafters.

The abundance and diversity of invertebrates differed between locations. Rafts from Port

Kembla were dominated by arthropods, especially crab megalopae and pelagic shrimp

Nyctiphanes australis throughout the year. High abundances of juvenile and prevuvenile shrimps and crabs are known to be common rafters around the globe (Kingsford and Choat

1985, Wehrtmann and Dittel 1990). Jervis Bay often had higher abundances of molluscs, another common rafting phyla (Wichmann et al. 2012a), at times making up almost 95% of the community. The abundance of arthropods and molluscs on rafts indicates that the identified taxa can persist on ﬂoating algae after detachment, as many have been noted to also be common in Phyllospora forests (Marzinelli et al. 2016).

The level of epifaunal diversity surveyed on Phyllospora rafts parallels that found on other species. For example, surveyed pelagic Sargassum in the Sargasso Sea was inhabited by 67 species (Fine 1970). A notable exception would be peracards which were lower that may have been expected in both locations (Clarkin et al. 2012b, Wichmann et al. 2012a). This may be due to their nature of boring into the holdfasts of Phyllospora (personal observation) which often were separated from the raft when it was torn from shore. The 64 species or taxa enumerated from rafts is similar to that identified off the California coast on Macrocystis pyrifera (72 species or taxa, Hobday 2000c) and densities that were on average lower than that surveyed in the Patagonian Fjords (223-771 individuals per kilogram of alga, Wichmann et al. 2012a).

This dissimilarity in rafting invertebrate populations between locations may indicate variation in environmental factors or the local abundance and diversity of fauna which alters rafting community composition such as temperature, nutrient availability and distance from shore

(Ingólfsson 1995, Clarkin et al. 2012a), all of which alter its favourability as habitat to invertebrates looking for refuge (Highsmith 1985). For example, Clarkin et al. (2012a) found that relatively small geographic separations could make quite a difference to influential

environmental variables such as temperature (less than 1.5°C difference between locations led to significant differences in community composition) which could be true in this study as well. However, as there are correlations among many of the environmental and spatial variables within a location, it is difficult to evaluate the relative importance of key drivers of species composition (Clarkin et al. 2012a). Competitive interactions may also be key drivers of community composition. Interspecific and interference competition have been known to drive species compositions in seagrass meadows (Coen et al. 1981) and subtidal habitats

(Keough 1984). These interactions may be equally important in determining community composition on floating rafts.

Previous studies on subtidal brown seaweeds report some algal species showing strong seasonal variation in the total number of epifaunal individuals while others had no predictable seasonal pattern (Taylor 1998). In Iceland, maximum invertebrate densities on benthic algae were recorded during summer and animals were virtually absent during the middle of the winter (Ingólfsson 2000). However, the more temperate climate along the New South Wales coast allows for the overall abundance of rafting invertebrates to remain relatively stable throughout the year, although the occurrence of many individual species was found to be highly seasonal. While the species composition in Port Kembla remained relatively constant all year, in Jervis Bay the composition of invertebrates varied with season. Early in the year

(summer & autumn) rafts in Jervis Bay were dominated by arthropods, while later in the year many the rafters were molluscs (gastropods and bivalves). Peaks in the abundance of molluscs on rafts often coincided with times of the year where there are likely higher abundances of young pelagic life stages looking to settle on freshly detached rafts that serve as a refuge in the pelagic (Ingólfsson 2000). It has also been suggested that these seasonal patterns in epifaunal abundance are dictated by the availability of the desired food sources of each species (Vandendriessche et al. 2006a).

4.4.2. The growth and development of Portunus spp. on rafts

Little is known about the journey of Portunus spp. between when egg-incubating females release their larvae and when they are large enough to settle (Potter et al. 1983). Meagher

(1971) suggests that early-stage zoea move offshore during development, and later-stage larvae and juveniles return inshore to settle. P. pelagicus megalopae may be planktonic or benthic (Yatsuzuka 1962, Meagher 1971, Ingles and Braum 1989) and there is some evidence that early juvenile crab stages can also be planktonic (Meagher 1971, Svane and Cheshire

2005). It is thought that the younger stages of this species have a preference for shallower waters but very few small individuals were found in estuaries (Potter et al. 1983) which suggests that they may have to find refuge elsewhere (such as on rafts) during the early stages of their development. The survival of early stage estuarine crabs has been found to be highly dependent on an appropriate combination of temperature and salinity (Jones 1981), and rafts may provide necessary refuge for survival though vulnerable environmental conditions.

However, no reference to P. pelagicus or P. sanguinolentus utilizing rafts could be found in the literature despite their prevalence in my study (but see Wehrtmann and Dittel 1990).

The surveyed abundance of megalopae and juvenile Portunus spp. supports what is known about its reproduction cycle and that of other estuarine crabs. This species usually spawns from October to December, occasionally through January, with berried females rare from

April to September (Shields and Wood 1993, Svane and Cheshire 2005). This validates my findings of megalopae beginning to appear in early summer, given it takes from two to seven weeks to progress from planktonic larvae to the megalopa (Meagher 1971, Campbell 1984,

Bryars 1997, Svane and Cheshire 2005). In a study of the reproductive cycles of three decapod crustaceans off the South-west coast of India (including Portunus spp.) it was reported that they all have a non-continuous breeding periods that extend over several months

(Krishna Pillay and Nair 1971). Metapenaeus affinis and Uca annulipes, like Portunus spp.

were also found to have their highest gonad index in December but also experienced peaks in

February and September, respectively. This timing in more equatorial locations has been attributed to synchronization with the wet season (Anger 1995). It is likely that the reproductive cycle of local Portunus spp. is also influenced by regional environmental factors.

Based on lab-rearing of this species, I can estimate the average age of individuals found on rafts. The larvae of P. pelagicus have four zoea and one megalopa stage before metamorphosing into the first juvenile crab stage (Yatsuzuka 1962). Megalopae average between 1-4mm in size and the first juvenile crab stage has an average carapace width of

2.5mm (Yatsuzuka and Sakai. 1980, Svane and Cheshire 2005). The average juvenile crab found in this study was 4.52mm wide, suggesting it was in the 2nd crab stage. The largest individual was 33mm across, making it 54-55 days old and in the 9th crab stage of development (Josileen and Menin 2005). This age range suggests that earliest planktonic stages may be utilizing rafts as a refuge while growing until they are large enough to settle

(Wehrtmann and Dittel 1990).

It is interesting that the carapace length of juvenile crabs was largest early in March (late summer), the time when individuals transition from megalopae to juvenile. Blue crab

Callinectes sapidus in the Gulf of Mexico was also found to have spring megalopae with larger carapaces, longer rostral spines and antennae than other times of the year (Ogburn et al. 2011). There is also the potential for individuals which reach the juvenile stage earliest to benefit from reduced competition with conspecifics which is also known to affect their growth rate (Ikhwanuddin et al. 2013). When the onslaught of juveniles appears in late autumn, the water temperatures are cooler and I anticipate that there is an elevated level of competition for all resources available to individuals on rafts. It is also possible that other

seasonally variable factors such as prey availability also drive changes in morphology (Stuck et al. 2009).

4.4.3. Conclusions

The life history of many species has been tailored to utilize rafts as a valuable resource for dispersal and survival (Bushing 1994, Fraser et al. 2011). While it remains unknown what percentage of individuals that have the capacity to raft do so, it does seem likely that individuals which utilize rafts would experience at least a slightly greater probability of survival. The study of floating algae and its associated assemblages provides an insight into the processes affecting the recruitment of these species as larvae and juveniles (Kingsford

1995). The more is known about the composition and dynamics about species that utilize rafts, the more we can assess the importance of rafts as both a habitat and as a mode of dispersal for many key species. Additionally, monitoring the rafting community improves our understanding of invertebrate assemblage dynamics in the pelagic environment than other methods that may not be so easily able to account for the heterogeneous distribution of species in the pelagic environment. Long-term data enumerating rafting communities over space and time could be used as a tool to monitor the dispersal of the early life stages of many species that are hard to quantify in the pelagic environment. This may assist in stock management for key species such as Portunus spp.

CHAPTER 5 – FLOATING RAFTS: ISOLATED

ISLAND OR ACTIVE ARCHIPELAGO?

5.1. INTRODUCTION

Floating macroalgal rafts are often inhabited by numerous animal species, providing them with habitat, a food source and a mode of dispersal (Highsmith 1985, Helmuth et al. 1994,

Thiel and Gutow 2005b, Fraser et al. 2011, Wichmann et al. 2012b). Previous studies on detached macroalgae have shown that there are changes to the assemblage which can be subdivided into multiple phases which are dependent on the dominant processes (Thiel 2003).

Initially, the composition of this floating community will consist of individuals that have been marooned when the alga detaches (Clarkin et al. 2012b), some of which may disappear due to active emigration or predation, leaving just the most persistent species (Kingsford and

Choat 1985, Edgar 1987, Thiel 2003, Gutow et al. 2009). Shortly after, new organisms will also begin to colonize (Gutow et al. 2015). New colonizers to pelagic rafts are a combination of sessile species that arrive in their larval stage and mobile species (Vandendriessche et al.

2006a, Gutow et al. 2015) that arrive actively or by chance while swimming through the water column (Hobday 2000c) or as the result of transferring from other nearby floating propagules (Druce and Kingsford 1995, Ingólfsson 1995, Kingsford 1995, Ingólfsson 1998,

Clarkin et al. 2012b). Species that have successfully colonized rafts may in time begin to reproduce and have their offspring recruit within the raft (Thiel 2003) or other nearby refuges.

For some colonizing species, these rafts are a necessity (Ingólfsson and Olafsson 1997), while for many others the use of floating seaweeds may just be based on convenience and availability. Arrival at a particular habitat may be an accidental consequence of the innate behaviour to seek attached vegetation (Locke and Corey 1989, Ingólfsson 2000), a deliberate attempt to avoid predators or competitors, or to search for food or mates (Robertson and

Howard 1978, Virnstein and Curran 1986). Bell & Westoby (1986) suggest that some species

may settle into the first available habitat, regardless of quality then if possible, redistribute to more desirable sections. However, they are unlikely to leave regardless of habitat quality if there is vulnerability to predation associated with doing so (Coen et al. 1981, Heck and

Thoman 1981, Sogard 1989). As a result, in areas where seaweed rafts are scarce, species may unselectively attach to any available raft (Gutow et al. 2015) often resulting in a great number of individuals being concentrated into small patches of available habitat (Sogard

1989).

The distribution of algae is patchy in nature (Chapters 2 & 3) with hotspots of raft accumulation common in protected areas and along fronts. This results in areas with few to no rafts and others with a high density. Ocean hydrodynamics are constantly moving rafts around, dispersing them to create small isolated habitats and bringing them together to from larger and more complex habitats. Island biogeography theory theorizes that size is one of the most powerful variables in determining the number of species occupying an isolated area

(Triantis and Azorean 2011). Previous studies exploring the habitat value of different size isolated patches have found a significant association with larger, more complex patches of substratum harbouring greater species abundance and diversity (Keough 1984, Hovel and

Lipcius 2001). However, whether a species prefers multiple smaller habitats or one larger habitat may be species specific (McNeill and Fairweather 1993) and dependent on their level of mobility and ability to move between habitats.

Distance from other populations is also an important factor in determining the rate and probability of colonization by species. There are two theories on the relationship between proximity to other similar habitat and the rate at which new rafts are colonized. Both agree that the proximity to other similar habitat plays a substantial role in shaping the colonizing

community (Sogard 1989), but this can manifest in different ways. First, there is the “island biogeography” theory which predicts that the distribution of species reflects a gradient where habitats closer to existing populations are colonized more rapidly by settlers (Gaines and

Roughgarden 1985). As existing populations may have mobile species with high capacity to colonize new nearby locations, the rate at which this occurs can be rather rapid. Counter to this idea, is the “nearest refuge” hypothesis. Previous research has found elevated concentrations of organisms with an increase in distance from existing populations of artificial seagrass (Virnstein and Curran 1986). In this case, the most remotely located habitat

(no nearby refuge) in a hostile environment is colonized with a greater frequency because it is the only available shelter for nearby individuals. The conditions under which one of these processes dominates would be highly situational with key determinates being specific to certain species, seasons or habitat availabilities.

In this chapter, I examine the influence of isolation on the abundance and diversity of early invertebrate colonizers on algal rafts using a defaunation experiment. Floating algal rafts void of any epifauna were re-released into the pelagic environment in one of two treatments. I released rafts within high-density areas of rafts as well as at a great distance from any other floating propagules. The two aims of this experiment are: (1) to determine which species are capable of pelagic colonization, and (2) if proximity to other rafts plays a role in shaping the abundance and diversity of initial colonizers. It is predicted that the “island biogeography” will correctly predict the abundance and distribution of species found on rafts. While highly motile species will likely be relatively evenly distributed regardless of degree of isolation, isolated rafts will see less diversity and abundance of less motile species within the short time frame of this experiment.

5.2. METHODS

5.2.1. Sampling Design

Floating rafts of Phyllospora comosa were collected off the coast of Port Kembla (Figure 2.1) from a vessel over three days during spring 2014. Rafts were collected using onboard observers to identify floating seaweed. When rafts were spotted, the boat was manoeuvred gently towards the clumps. Rafts were carefully collected a single swoop of a dip net (80 ×

80 cm, mesh size 0.5 cm). Rafts larger than 100g were defaunated in the vessel using a series of 3 freshwater rinses. Once defaunated, rafts were then re-released at random in one of two treatments. The first was a release more than 100m from any other floating propagule (hereon known as the “solo” treatment, n=7). The other half of the rafts were re-deployed in areas where rafts had naturally collected into a high density (more than 5 rafts/10m2, hereafter known as the “group” treatment, n=7). All defaunated rafts were fitted with identification buoys (Figures 5.1 & 5.2) so they could be readily located and identified after 4 hours afloat.

All rafts were monitored every half hour (from approximately 10m away as to not disturb the movement and settlement of pelagic fauna) to ensure that they maintained appropriate distances from other rafts during this time.

After four hours had elapsed, rafts were re-collected using the dip net. Each raft was immediately transferred into a plastic bag. All mobile organisms that fell off the algal patch were collected and added into the bag. Additional rafts were also collected at random to be used as a reference for the abundance and diversity of the invertebrate communities during this time of year (hereafter known as the “reference” treatment, n=7). After collection in the field, the algal samples were immediately transported to the laboratory.

The algae and all contents of the bag were thoroughly washed using a series of three freshwater rinses in large tubs to remove all mobile associates. The water was drained

through a 500 µm sieve and the contents in the sieve were preserved in 70% ethanol. Rinsed algal rafts were weighed with a spring balance (kg wet weight). Invertebrates were counted and identified to lowest possible taxonomic level and in some cases, life stage under a dissecting microscope. As the focus of the study was on the allocation of motile individuals to rafts, some colonial species (where it is difficult to assign individuals or complete removal from rafts was likely imperfect) were not recorded.

5.2.2. Analysis of data

Abundance and species richness of algal rafting communities were compared between treatments (fixed) using an ANOVA in R Studio v.3.2.0. The abundance and species richness of invertebrates was standardized per 1kg of raft. Before analysis, I tested for normality using a Kolmogorov-Smirnov test and heterogeneity of variances with Levene's Test. Invertebrate abundance was square-root transformed. Post-hoc Tukey's HSD (honest significant difference) test was used when significant differences were found between treatments.

Differences in invertebrate communities between treatments were evaluated using PRIMER7.

SIMPER analysis on untransformed data was used to determine which taxa most contributed to differences. To determine if this led to a significant difference in assemblage composition, a PERMANOVA was performed. Results for untransformed abundance data were visualized using a non-metric Multi-Dimensional Scaling (MDS) plot and categorized by treatment.

5.3. RESULTS

Treatment was found to have a significant influence on both the number of individuals

(F2,18=14.37, p<0.001; Table 5.1, Fig. 5.3) and the number of species (F2,18=11.23, p<0.001) on Phyllospora rafts. Rafts collected at the same time as the defaunation experiment

(“reference” treatment) had on average 20.5±6.8 invertebrates kg-1. These “reference” rafts had significantly more individuals than both the “group” (p=0.017) and “solo” (p=<0.001) rafts. After four hours, “group” rafts had accumulated an average of 6.2±1.5 colonizers per raft (30.2% of the abundance found on “reference” rafts) while “solo” rafts only acquired

1.2±0.4 (5.8% of the abundance of “reference” rafts). However, the difference in invertebrate abundance between the “group” and “solo” treatments were not found to be significant

(p=0.086).

Unlike abundance, the species diversity that had accrued on defaunated rafts was significantly influenced by its proximity to other floating propagules. Within four hours,

“group” rafts had acquired an average of 2.7±0.3 species, which is 63% of the diversity found on “reference” rafts, a significantly close species richness (p=0.071). “Solo” rafts had an average of 1.1±0.3 species which was significantly fewer than “reference” rafts (p=0.001) but not “group” rafts (p=0.071).

Table 5.1. ANOVA and Tukey’s Honest Significance for the effect of treatment on the abundance and species diversity found per kilogram of floating macroalga Phyllospora comosa.

The composition of the rafting community was found to be dependent on treatment

(F2,18=1.7438, p=0.026; Table 5.2). Highly mobile pelagic species dominated “solo” rafts; with isopoda, brachyuran megalopae and euphausiacea Nyctiphanes australis being the most common species on these isolated habitats. These same taxa were even more abundant on

“group” rafts but were joined by additional less motile species such as juvenile brachyurans and vetigastropoda (Table 5.3). Sedentary taxa, Lepas spp., was only found on reference rafts as they would take a significant amount of time to settle and establish.

Table 5.2. PERMANOVA for the effects of raft isolation on the species diversity per kg (untransformed) found on floating macroalga species, Phyllospora comosa.

PERMANOVA table of results Number of Individuals df MS F p Treatment 2 5462.4 1.7438 0.026 Residuals 18 3132.5

Table 5.3. Individuals per kilogram (±SD) of raft for each of the three treatments: solo, group or reference.

Order Treatment Solo Group Reference Brachyuran megalopae (B19) 0.2±0.1 0.9±0.5 1.1±0.3

Brachyuran megalopae (B2) 0±0 0±0 0.67±0.6 kilogram per individuals of Number Brachyuran megalopae (B20) 0±0 1.1±0.9 1.2±1.1 Brachyuran megalopae (B4) 0.1±0.1 0.2±0.3 5.0±3.4 Decapoda Brachyuran megalopae (N2) 0.1±0.1 0.2±0.2 1.3±0.8 Leptomithrax spp. 0±0 0±0 0.1±0.1 Portunus spp. 0±0 0.1±0.1 0±0 Jasus edwardsii 0±0 0±0 0.1±0.1 Euphausiacea Nyctiphanes australis 0.1±0.1 1.1±0.6 5.0±2.7 Isopoda Idotea spp. (C1) 0.7±0.3 1.9±0.4 4.9±1.4 Idotea spp. (C5) 0±0 0±0 0.2±0.2 Pedunculata Lepas spp. 0±0 0±0 1.0±0.6

Phasianotrochus eximius 0±0 0.2±0.2 0±0 Vetigastropoda Tugali spp. 0±0 0±0 0.1±0.1

The abundance of isopods and brachyuran megalopae contributed more than 95% of the dissimilarity between treatments (Table 5.4). The dissimilarity between the reference and isolated rafts was 90.64, highlighting that a very small proportion of the expected diversity had reached the isolated rafts within four hours. Rafts released near other rafts accumulated enough diverity to be equally dissimilar to both other treatments. Multidimensional scaling

(stress=0.17; Figure 5.4,) confirmed the intermediate nature of the “group” rafts as they appear scattered in the region between “reference” and “solo” rafts.

Reference Group Group Treatment Solo Solo Reference Average Dissimilarity 90.64 77.39 76.08 Species Idotea spp. (C1) 28 25.46 20.07 Idotea spp. (C5) 21.79 10.92 16.07 Brachyuran megalopae (B4) 13.58 8.25 12.34 Brachyuran megalopae (B19) 7.08 13.09 5.87 Brachyuran megalopae (N2) 6.95 8.57 8.44 Brachyuran megalopae (B2) 4.95 4.44 Phasianotrochus eximius 5.35 Lepas spp. 3.8

Figure 5.4. Multidimensional scaling plot for the diversity of invertebrates on isolated rafts (square), rafts in a group (black) and reference rafts (grey) per kg.

5.4. DISCUSSION

The ability for invertebrates to colonize rafts at sea has been well established (Ingólfsson

2000, Gutow et al. 2009, Urban-Malinga and Burska 2009, Clarkin et al. 2012b) but it can be quite difficult to determine which species have colonized from the pelagic environment and which marooned when the raft was torn from the reef. This study aimed to determine which species are capable of pelagic colonization and whether proximity to other rafts plays a role in the rate of this process. Defaunated algal rafts provide a convenient, easily manipulated unit to explore this process in a natural setting.

In this study, new rafts in close vicinity to an existing source population of potential colonizers were more rapidly colonized than those which were isolated. This suggests that most invertebrates setting onto newly available rafts are coming from other nearby rafts as opposed to the pelagic environment. Numerous other studies have similarly found that colonization of ﬂoating substrata via contact with other substrata or “raft hopping” appears to be a key process (Ingólfsson 1998, Gutow and Franke 2003) in determining the abundance and community composition on rafts. The high species turnover of mobile associates moving between nearby rafts has been found to result in a faster succession of compositional changes and homogenization in the rafting assemblages (Vandendriessche et al. 2006a, Clarkin et al.

2012b, Gutow et al. 2015) than would likely be seen on isolated rafts. This supports my result that over the same amount of time, fewer individuals encountered and colonized isolated rafts, which are entirely reliant on individuals being recruited from the pelagic environment.

If this field study had allowed for rafts to remain adrift longer, it is likely that there would have been more complete homogenization between assemblages found on neighbouring rafts while isolated rafts may have maintained a comparatively unique community composition.

The other possible theory which was suggested to account for the distribution of motile species amongst habitats, the “nearest refuge” hypothesis, would have seen an increasing abundance of organisms on more isolated patches as it is their only available habitat

(Virnstein and Curran 1986). However, this theory was not validated under the circumstances of my study because most species recruiting to new rafts were doing so from existing nearby habitat. The isolated rafts were successfully colonized by some taxa that were likely dispersed in open water and were able to quickly concentrate around the rafts introduced to the system (Kingsford and Choat 1985). However, rafts in groups had the benefit of not only attracting those species, but also may acquire additional species via “raft hopping” (Hobday

2000c, Gutow et al. 2015).

It is possible that the 100meter distance minimum between rafts was not remote enough to create a scenario where the abundance of pelagic individuals seeking refuge is greater than the number of individuals simply moving between neighbouring rafts. Future studies may consider investigating multiple degrees of isolation between rafts to discern if the “nearest refuge” theory is accurate in explaining raft communities at greater degrees of isolation. The rate and community composition of early raft colonizers also likely varies over space and time (Sogard 1989, Ingólfsson 2000) which would make it interesting for future studies to add location or season as a factor when exploring rates of colonization. It would also be worth considering the impact that time of day would have on the movement of pelagic raft colonizing species.

Unsurprisingly, my results indicate that most the first and frequent colonizers of defaunated algal rafts are species that are capable of independently swimming the short distance between neighbouring rafts. The taxa that were most common on the defaunated rafts, regardless of proximity to other rafts, were crustaceans with swimming capabilities (Sogard 1989,

Ingólfsson 1998, Clarkin et al. 2012b). Crab megalopae, isopods and euphausiids, were the three most common taxa found on all rafts. Planktonic crustaceans in particular are known to be very prolific colonisers (Virnstein and Curran 1986), capable of independently joining, leaving and transferring to rafts from the water column (Ingólfsson and Olafsson 1997,

Ingólfsson 2000, Gutow and Franke 2003, Clarkin et al. 2012b). Isopods in particular have been the focus of many rafting studies as they are both planktonic as well as having a strong known association with algal rafts (Locke and Corey 1989, Davenport and Rees 1993,

Ingólfsson 1995, Ingólfsson 2000, Gutow and Franke 2003, Clarkin et al. 2012b, Gutow et al.

2015). Therefore, it is not surprising that they were commonly encountered on rafts during this survey.

Although molluscs were far less common on defaunated rafts, this does not mean that they are incapable of colonizing rafts at sea. While juvenile molluscs are past their planktonic dispersal phase, some are still able to join rafts because of contact between propagules as well as directly from the water column. Ingólfsson (1998) found that non-swimming species,

Littorina obtusata, could colonize rafts at sea from the surrounding water column after detaching from its intertidal habitat (Gutow et al. 2009). This independent floating by some gastropods which eventually drift into rafts (Frid and James 1988) may be just as likely a source of their presence on rafts as being marooned on rafts that have detached. Four hours was likely not enough time to see this process take place but it cannot be ruled out that some species of mollusc are capable of colonizing.

In previous studies which focused on seagrass, both clumped and isolated patches provide habitat for species in the pelagic although the source of their inhabitants and process of colonization is likely very different (Hovel and Lipcius 2001). While species are able to

“hop” between neighbouring habitats to access resources, those isolated for long periods of time may experience serious consequences in the form of altered community composition

(Gustafsson and Salo 2012) and may not be able to provide sufficient resources or opportunities for recruitment. This highlights the importance of algal drift rows and fronts

(Ingólfsson 1995, Hinojosa et al. 2011), which create opportunities not only for the exchange of fauna (Gutow et al. 2015) but also the provision of resources necessary for their survival in the pelagic environment. The frequency and extent of areas which collect rafts into larger clumps may have a significant role in structuring rafting communities by merging and isolating different populations for different durations of time (Clarkin et al. 2012a). If the abundance of rafts in the pelagic environment were to decrease, there would be an associated decline in the regularity with which they come together to form aggregations. This may

negatively impact species that rely on these larger, more complex structures for habitat and dispersal.

CHAPTER 6 – RAFTS IN A FUTURE OCEAN

6.1. INTRODUCTION

Phyllospora comosa is one of the largest and most common seaweeds along the south-eastern coast of Australia (Chapter 2; Edgar 1984, Underwood et al. 1991, Coleman 2002).

Widespread across wave-exposed coasts, Phyllospora often dominates the shallow subtidal zone, down to as deep as 18m (Edgar 1984). Floating individuals are found frequently in coastal waters throughout most of its distribution between Port Macquarie in the North to

Tasmania in the south (Womersley 1987, Millar and Kraft 1994). Rafts of Phyllospora comosa commonly provide habitat to a wide range of invertebrate species (see chapter 4) and may be key in their dispersal and the connectivity of populations along the coastline.

The longevity and durability of floating rafts determines their capacity to provide essential habitat and ensure dispersal potential. At present, relatively little is known about the processes related to persistence of rafts after detachment (but see Helmuth et al. 1994,

Hobday 2000c, Thiel and Gutow 2005a, Rothäusler et al. 2009, Rothäusler et al. 2012). The length of time a raft remains buoyant is highly variable (Smith 2002, Thiel and Gutow 2005a,

Vandendriessche et al. 2007b, Graiff et al. 2013) and likely related to the physiology of each species as well as local environmental conditions.

Temperature is argued to be one of the most influential variables on the health and longevity of many marine species (Drinkwater et al. 2010). In the future, sea surface temperatures are projected to continue rising above their already elevated levels (CSIRO 2015), posing a serious risk to the marine environment. More than 70% of the world’s coastlines have experienced warming as well as an earlier onset of the warm season (Lima and Wethey 2012,

CSIRO 2015). The rates of ocean warming have not been heterogeneous; with many areas experiencing extreme temperatures which can be more lethal to its inhabitants than a gradual change in mean temperature. Temperature increases in the ocean have been linked to habitat

loss as well as changes to recruitment, reproduction and growth of biota (Ridgway and Hill

2012).

Between winter and summer, it is not uncommon for the sea surface temperature to fluctuate by more than 8° C in temperate Australia. In other regions of the world that experience similar seasonal fluctuations in temperature, some species have evolved efficient protective mechanisms to acclimate and withstand higher temperatures (Parker 1960, Schofield et al.

1998, Ferreira et al. 2014). For example, some marine algae are capable of modifying their physiological performance in response to temperature stress by undergoing photosynthetic and structural changes (Parker 1960, Davison 1987, 1991). However, this physiological stress may be exacerbated for floating rafts as surface waters experience more extreme temperature fluctuations than is experienced a few meters below by attached alga (Macaya et al. 2005a).

Previous studies have found that alga exposed to temperatures exceeding their thermal tolerance experienced a reduction in growth, photosynthetic efficiency and diminished reproduction (Davison 1987, Hobday 2000b, Vandendriessche et al. 2007b, Rothäusler et al.

2009, Rothäusler et al. 2011b, Flukes et al. 2015). Higher seasonal water temperatures have been correlated with significant biomass losses, metabolic deficiencies and rapid destruction of the tissues in floating kelps (Graiff et al. 2013). For Phyllospora rafts, it remains unclear if their ability to compensate for high seasonal temperatures will translate to survival in a warmer future ocean.

At present, little information is available on the biology and survival of P. comosa after detachment, although it is known that the potential to persist at the sea surface is a key factor in long-distance dispersal (Coleman and Kelaher 2009). As ocean conditions continue to change, the future of Phyllospora forests and its floating rafts may be threatened. Any decline in the abundance or quality of Phyllospora on reefs or as rafts may have serious

consequences for connectivity, ecological function and biodiversity due to the key role it plays in providing habitat (Marzinelli et al. 2013) and as a vector for dispersal. A rise in sea temperatures therefore could result in a decline or further fragmentation of existing populations, especially near the northernmost end of its range and around urban centres

(Connell et al. 2008, Wernberg et al. 2010). The ability of macroalgae to successfully adapt to long-term increases in water temperature is essential to their survival as well as that of dependant epifaunal species (Davison 1987, Kuebler et al. 1991, Lee and Chang 1999). The capacity to optimize their metabolism and growth in response to seasonal changes (Staehr and Wernberg 2009, Wernberg et al. 2010) will be essential to survival in a future ocean.

I sought to determine if algal rafts seasonally acclimated to warmer ambient temperatures would better withstand further temperature stress than those acclimated to colder waters. I performed a laboratory experiment in which Phyllospora comosa rafts were exposed to temperatures spanning their current range as well as extremes predicted in the future. This experiment was conducted once during winter and once during summer to determine if there is any seasonal difference in how algal rafts respond to temperature stress. This experiment had two aims. First, to assess the relationship between temperature and raft longevity.

Second, to establish if Phyllospora physiology acclimates seasonally to remain healthy during cold winter and hot summer temperatures. I examine how Phyllospora comosa responds to different temperature treatments by monitoring three important correlates of raft health which, if compromised, may negatively impact its ability to perform its ecological role. The three variables indicative of stress examined were: PSII yield, biomass change and loss of buoyancy (time to sinking).

Determining if rafts can seasonally optimize their physiology may tell us about their potential to survive under future ocean conditions. I predict that the summer temperature-acclimatized

rafts will be more resilient against further temperature increases, thereby remaining healthy longer. When compared to rafts acclimated to winter temperatures, summer acclimated algal rafts are expected to experience less or a delayed onset of PSII stress, a slower rate of biomass loss and remain buoyant longer.

6.2. METHODS

6.2.1. Study location and design

This indoor-tank experiment was run twice, commencing on July 1 and February 1, each time lasting 31 days. I examined the effects of temperature on Phyllospora comosa longevity during both the height of summer and the coldest part of winter. Sea surface temperatures in this region are in their peak in February (23.7°C) and nearing their lowest in July (18.8°C).

Rafts of P. comosa were collected from a shallow subtidal reef (<2 m deep) along Windang

Island near the entrance to Lake Illawarra (34.54S, 150.87E; Figure 6.1), south eastern

Australia. Samples were collected after large storm events during which many freshly detached clumps of algae were stranded on shore.

This experiment was conducted in a seawater lab on the campus of University of Wollongong

(19km from collection site). Sixteen rafts with similar biomass (1.08kg ± 0.092kg) were randomly assigned to one of four temperature treatments (4 replicates per temperature, replications limited by lab capacity). Each raft was placed into an aeriated 60L transparent plastic container, receiving circulated unfiltered natural seawater. These containers were placed in one of four trays which were 50% submerged in fresh water. Temperature in each tray was maintained using a heater or chiller for temperature control and to circulate the water. Temperature loggers (iButtons) recorded temperature in each container every 4 hours for the duration of the experiment. All individuals were exposed to a light regimen of 14 hours light, 10 hours dark, provided by 36W white fluorescent tubes.

Figure 6.2. Experimental set-up for both the winter and wummer run. Winter temperatures are displayed on top of the diagram, summer temperatures are below.

The rafts were continuously exposed to one of four water temperatures (Figure 6.2). Three of the temperature treatments represent those experienced at the northernmost, middle and southernmost points in P. comosa’s current distribution (Table 6.1). A fourth temperature was used to represent an exceptionally warm event that may be experienced at the northern limit of Phyllospora’s range in in the future. For the winter experiment; 10, 16, 22 and 28°C and for the summer run, these temperatures were shifted up by 6°C to mirror the seasonal increase (31°C was the highest achievable temperature with available resources).

6.2.2. Measures of rafts health

An underwater pulse amplified flourometer (diving PAM) was used to measure in vivo chlorophyll A fluorescence of PSII every day. This is an efficient non-damaging way to monitor the kinetics of the photosynthetic process as well as changes in algal physiology

(Pang and Shan 2008). Six blades from each raft were selected at random and incubated for

20 minutes in darkness then measured for maximal quantum yield of fluorescence (Fv/Fm) which is an indicator of quantum efficiency (Rothäusler et al. 2011b). A pilot study of four rafts determined that the daily removal of six small frond segments had negligible impact on the total biomass (0.36±0.04% of total biomass removed compared to an average growth rate of 0.65±0.25% in the same time) and had no detectable impact on health. Mean values of the

6 Fv/Fm measurements were used as the average response for each raft. A decline in response is an indicator of physiological stress or damage (Machalek et al. 1996, Maxwell and Johnson

2000) and PSII Fv/Fm measurements below 400 indicate that the alga has suffered significant

PSII damage and is no longer functioning efficiently.

Total wet-weight biomass (g) was recorded every third day using a spring scale. I also monitored the number of days each raft remained positively buoyant. Individuals were considered buoyant if they were floating on the water’s surface, even if part of the raft had

lost buoyancy. Measurement of all 3 variables were collected for 31 days on all rafts that remained buoyant.

6.2.3. Analysis of Data

An ANCOVA model was used to establish if each of the three health variables are affected by season (factor) and temperature (covariate). Rafts that were still in good health after the duration of the experiment were not able to be included in certain portions of the analysis (i.e. if a raft never reached a Fv/Fm ratio below 400 during the experiment, it was excluded). A student’s T-test was employed to determine if there was a difference between initial photosynthetic efficiency between summer and winter acclimated rafts. Before these analyses, I tested for normality using a Kolmogorov-Smirnov test and heterogeneity of variances with Levene's Test. Models with the nested structure of temperature within season were used to create lines of best fit and calculate the slopes and y-intercepts for each season.

All statistics were completed using R Studio running platform version 3.2.0.

6.3. RESULTS

The rafts experienced clear measurable and observable signs of stress as water temperatures increased. However, in only one out of three variables tested did summer rafts significantly outperform their winter counterparts.

Temperature was found to have a significant influence on two out of three health variables.

An increase in temperature significantly decreased the number of days PSII functioned above a Fv/Fm ratio of 400 (F1,22=94.895, p<0.001; Table 6.2) at a rate of 1.23 days per degree.

During winter, all 10°C rafts maintained a Fv/Fm ratio above 400 as did one 16°C winter raft and two 16°C summer rafts. Therefore, these 7 rafts were not included in PSII yield analysis.

The number of days rafts were positively buoyant declined by 0.8 days per degree increase in

temperature (F1,23=76.796, p<0.001). All four of the 10°C winter rafts remained buoyant thought the duration of the experiment as did two 16°C summer rafts and they were therefore not included in buoyancy analysis.

Raft biomass was also influenced by temperature although not quite enough to be significant

(F1,29=4.000, p=0.068). On average, rafts decreased in biomass more quickly at elevated temperatures. However, at the highest temperature treatments, when plants died quickly, dead cells often swell with water causing them to gain biomass in the immediate term before they began to disintegrate (Figure 6.5). The lack of a significant interaction term (p>0.15; Figure

6.3) for all three models indicates that the relationship between temperature and each variable was the same during both seasons.

ANCOVA Days of PSII yield above 400 Days Wrack remained buoyant Percent of original biomass Source of variation Df F p Df F p Df F p Season 1 1.022 0.324 1 9.252 0.050 1 3.335 0.099 Temperature 1 94.895 <0.001 1 76.796 <0.001 1 4.000 0.068 Error 22 23 29

Season was found to have a significant influence on only the number of days rafts remained buoyant (F1,23=9.252, p=050). During the summer, rafts remained buoyant significantly longer than during the winter. There was no significant difference between seasons in the number of days PSII functioned efficiency (F1,25=1.022, p=0.324) or the daily change in biomass (F1,29=3.335, p=0.099).

PSII fluorescence yield measurements taken immediately after individuals were collected showed a significant difference between seasons in mean PSII yield (T(30)=2.296, p=0.029;

Figure 6.4). Winter rafts collected when the sea surface temperature was 16.7°C had a significantly higher PSII yield than their summer counterparts which were collected when the average temperature was 25.5°C.

Figure 6.4. Baseline fluorescence yield (Fv/Fm) of rafts at time of collection during summer (n=16) and winter (n=16). Six measurements were taken per raft. Error bars represent ± 1 standard error.

Daily measurements of PSII yield show a difference in performance for each season (Figure

6.5). Rafts in the lowest temperature treatment of 10°C (only used in winter), experienced a rise in PSII efficiency above that which they expressed in the field. At no point during the experiment did these rafts show any sign of physiological stress. Summer rafts at 16 and

22°C displayed higher levels of PSII functionality and survived longer than their winter counterparts. The summer acclimated 16°C rafts appeared relatively unstressed for almost three weeks whereas winter rafts began to experience a decline in PSII yield within two weeks. Summer rafts at 22°C did not show signs of PSII stress for two weeks while winter rafts experienced their decline almost a week earlier. At the highest temperatures, 28°C and

31°C, all rafts began an immediate and swift drop in PSII yield, showing signs of necrosis and blade loss nearly immediately. Winter rafts at 10°C showed an initial increase in biomass followed by a slow decline. As temperature increased, summer rafts lost biomass at a slower rate than their winter counterparts. At high temperatures (28 and 31°C treatments) rafts experienced a brief period of biomass increase then a rapid decline and loss of buoyancy.

6.4. DISCUSSION

Phyllospora comosa responds strongly to changes in temperature, with warmer waters proving to be detrimental to health and longevity. At low temperatures, rafts showed little to no sign of stress or damage thorough out the experiment. However, at elevated temperatures a decline in condition was apparent within 24 hours with rafts at the highest temperatures sinking in just a few days. Physiological processes in Phyllospora acclimated to summer temperatures functioned at experimental temperatures below normal environmental conditions while widespread mortality at high temperatures made it difficult to determine whether the converse applied for individuals from winter (Flukes et al. 2015).

The only variable that did not have a significantly negative correlation with a rise in temperature was change in biomass. Percent of original biomass after 1 week was not found to be significantly influenced by temperature. However, this is because rafts exposed to the two highest temperature treatments were observed to quickly experience necrosis, during which cells swell with water. This caused them to not accurately portray the poor condition of the raft which resulted in a significant shedding of fronds and pneumatocysts. Within days of this initial swelling, the dead cells quickly decomposed and only small portions of the raft remained intact. Overall, rafts at the lowest temperatures maintained or increased their biomass and as temperature increased, so did the rate of biomass loss in the form of shed fronds and the onset of necrosis. Previous studies have found that the decomposition rate of floating seaweed rafts is temperature-dependent (Hobday 2000b, Salovius and Bonsdorff

2004, Vandendriessche et al. 2007b). Additionally, the rate of weight loss (but not period of buoyancy) has also been found to be determined by the initial size of the seaweed fragment

(Vandendriessche et al. 2007b).

The combined measurement of variables often associated with stress in algal species provided a valuable insight into how Phyllospora comosa’s response to stress changes at different temperatures and between seasons. Flukes et al. (2015) found that Phyllospora thalli grew at temperatures 3-4°C below the normal winter minima, indicating considerable physiological plasticity. Algal rafts appeared visibly healthy when PSII yield was above 600 Fv/Fm. Rafts able to maintain this yield usually remained buoyant the duration of the experiment and some even increased in biomass. The only rafts that maintained a PSII yield above 600 Fv/Fm for the duration of the trail were those in the 10°C treatment as well as two rafts in the summer trial at 16°C. It is interesting that summer rafts (acclimated to 23.7°C) appeared to fair better than did their July counterparts (acclimated to an 18.8°C) in the 16°C treatment. This suggests that Phyllospora can quickly and positively respond to dramatic declines in temperature, a possible phenotype that may be favoured during the warm summer months in the middle and top of its range. In colder waters at the southerly end of their range,

Phyllospora rafts likely experience little temperature-induced stress seasonally and could survive on the sea surface for months at a time.

Although Phyllospora rafts appear to have significant longevity in cold water, this quickly declines with a rise in temperature. Rafts in the 16°C and 22°C treatments were exposed to the temperatures commonly experienced locally. However, only one raft in the 16°C treatment maintained a PSII yield above 400 Fv/Fm for the duration of the experiment.

Previous studies have found growth in fucoid species (including Phyllospora) in the temperature range of 12-17°C (Steen and Rueness 2004, Flukes et al. 2015). However, during this experiment most rafts at the upper end of that temperature range began to see their PSII yield drop into the 400-600 Fv/Fm range in the second week, showing signs of stress in the form of released spores and patches of necrosis. Summer plants did appear to endure slightly better than their winter counterparts at these temperatures but the difference was not

significant. Most plants at 22°C began to decompose and sink within 2 weeks while 16°C rafts took about a week longer to meet the same end. This suggests that rafts locally are only buoyant and providing pelagic habitat for 2-3 weeks before they sink or disintegrate.

Similarly, Flukes et al. (2015) found that at 22°C, net growth was negative as tissue necrosis significantly outweighed meristematic growth. Macrocystis spp. were also found to experience a dramatic reduction in survival above 20°C (Rothäusler et al. 2009).

At the top of their current biogeographic range, Phyllospora would seasonally be exposed to temperatures up to 28.4°C. However, rafts from the middle of the range that would not normally be subject to these temperatures seasonally, did not fare well. High temperatures are known to result in metabolic deficiencies and destroyed tissue in other species of floating alga (Graiff et al. 2013). In both the 28°C and 31°C treatments, rafts experienced a rapid decline in their PSII yield to below 400 within 24 hours. Below 400 Fv/Fm, rafts quickly show significant amounts of necrosis, major shedding of blades and pneumatocysts, yellow water discolouration and loss of buoyancy. Therefore, at the top of their range, rafts of Phyllospora may only survive for a few days before decomposing. Some rafts, particularly those at higher temperatures remained buoyant after PSII yield reached 0Fv/Fm and showed significant structural damage. This response on the part of Phyllospora is reinforced by previous studies which have found that stressful conditions impair the photosynthetic apparatus of floating seaweeds and that stressed algae invest energy to adjust and maintain photosynthetic activity

(Schofield et al. 1998, Hobday 2000b, Vandendriessche et al. 2007b, Rothäusler et al. 2009,

2011a, Rothäusler et al. 2011c), often at the cost significant necrosis to other regions.

Rothäusler et al. (2011a) reported that Macrocystis spp. had the capacity to physiologically acclimate to changing abiotic conditions. However, when exposed elevated temperatures these acclimation processes operated at the expense of growth and reproductive success, in addition to diminished biomass gains and blade elongation rates. Future studies into the

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faunal composition of highly necrotic rafts as compared to healthy rafts would provide an interesting insight into the value of these rafts as habitat.

Interestingly, it was found that how long rafts remained buoyant was influenced by season.

Rafts from summer remained buoyant significantly longer than their winter counterparts at the same temperature. This suggests that the way that rafts react to increased temperatures may be seasonally dependant. This may be due to their physiology or other external environmental factors that vary seasonally.

6.4.1. Conclusions

Species that cover large latitudinal ranges would be expected to have the capability to adjust to a wide temperature range. However, previous studies on Phyllospora found that there may be latitudinal variation in its tolerance to thermal stress (Flukes et al. 2015). As is the case with many other species (Helmuth et al. 2002, Thiel and Gutow 2005a, Williams et al. 2008,

Rothäusler et al. 2009, Somero 2010), it seems likely that the northern-most edge of

Phyllospora’s range is set by temperature and populations at this end are already near their thermal maxima. The acclimation mechanisms of floating rafts probably only operate around a similar temperature range to that of its attached benthic population. Sea surface temperatures are usually a few degrees above those common in the benthic intertidal zone, thus pushing floating rafts even closer to this thermal maxima (Macaya et al. 2005a). If temperatures continue to rise, the northern extent of its distribution will likely shift south as it surpasses the temperature threshold at which it can survive (Machalek et al. 1996). However, the range of Phyllospora comosa already extends to the southernmost end of Tasmania and has nowhere further south to extend. Therefore any poleward shift will result in a net loss of habitat (Wernberg et al. 2010).

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As temperatures rise there is likely to a more rapid onset of necrosis, increasing the rate of raft decomposition and sinking, resulting in fewer and poorer quality rafts. Therefore, warming waters could act as a dispersal barrier for rafts as the reduced buoyancy period makes travel over great distances almost impossible (Helmuth et al. 1994, Hobday 2000b,

Rothäusler et al. 2009). It is unclear what impact the physical condition of a raft may have on its desirability and functionality as habitat to epifaunal species. Additionally, suboptimal water temperatures can also affect the reproductive activity of floating algae (Macaya et al.

2005b, Rothäusler et al. 2009) in the form of reduced or absent reproductive tissue

(McKenzie and Bellgrove 2008) which could have dire consequences for the survival of this species, particularly at the northern end of its range.

Successful conservation and management of marine habitats will depend critically on how well we understand the response of key species to the likely synergistic effects of increased temperatures with other coexisting stressors (Harley et al. 2006, Wernberg et al. 2010). In areas of high thermal stress, even if Phyllospora kelp and raft habitat remain intact, they may exist in an altered state or diminished abundance which may make them especially susceptible to additional stressors. If oceans warm as predicted, the availability of algal rafts in the pelagic as key habitats may be seriously diminished. If rafts become less available or cannot float as long, there could be serious implications for species reliant on this habitat.

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CHAPTER 7- MODELLING THE IMPACTS OF A

FUTURE OCEAN ON A KEY HABITAT-

FORMING MACROALGA: A BAYESIAN

NETWORK APPROACH

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7.1. INTRODUCTION

Floating algal rafts play an important role as habitat, a food source and mode of dispersal for a wide variety of species (Chapter 4; Macaya et al. 2005a, Thiel and Gutow 2005b,

Vandendriessche et al. 2007a). The practice of rafting has been suggested to be an important marine habitat and dispersal mechanism, especially because algal rafts can be found in all major temperate regions of the ocean (Thiel and Gutow 2005b, Hinojosa et al. 2010).

Phyllospora comosa is the most common raft-forming alga along the New South Wales coastline (Chapter 3). In previous decades, there was a dramatic decline in the extent of P. comosa forests along the Sydney coastline, thought to be caused by the species’ sensitivity to chemical toxins (Coleman and Kelaher 2009). Although these conditions have improved, global warming still proves to be a threat. There is great potential for climate change to amplify physical and ecological factors that negatively influence macroalgal dynamics

(Chapter 6, Hobday 2000b, Thiel and Gutow 2005a). If this species experiences declines as the result of future ocean conditions, there may be a weakening or further fragmentation of existing populations, (Connell et al. 2008, Wernberg et al. 2010). Macreadie et al. (2011) predicted that climate change will lead to increasingly smaller and short-lived rafts, with increasingly rapid degradation times that will be only be capable of dispersal over short distances.

Determining the drivers of macroalgal abundance is complex. Researchers are only beginning to understand the intricacy of the relationships between physical and ecological factors in these environments. Questions of how and to what degree macroalgal communities will change remains largely unanswered (Menge et al. 2009, Macreadie et al. 2011). The importance of bottom–up processes, such as nutrients and temperature (Metaxas and

Scheibling 1996) as well as top–down mechanisms, such as grazing (Sala 2006, Ling et al.

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2009a) are difficult to quantify simultaneously (Menge 2000, Renken and Mumby 2009,

Jochum et al. 2012).

It is essential to understand the response and impact of future ocean conditions to mitigate the negative impacts of climate change. Policy makers and researchers alike have stressed the importance of successfully utilizing emission reduction strategies in combination with environmental management in order to mitigate climate effects (IPCC 2007, Richards et al.

2013, Edenhofer et al. 2014). The ability to assess the sensitivity of the system to these variables would assist in a more accurate prediction of future conditions. However, surveying the relationship between environmental drivers and macroalgal cover and drifting rafts in the field is difficult (Thiel and Gutow 2005b). As a result, most publications are only able to assess small portions of the system or only explore the interaction of a single variable.

Since there is little available data and only a general understanding of the effects of climate change on Phyllospora comosa, I sought to develop a conceptual model of these complex interactions. Here I use a Bayesian Network (BN) to provide valuable information on the synergistic impacts of multiple factors on this key habitat. BNs are graphical models that allow for the assessment of different options or decisions in determining outcomes, which can assist with management decisions under environmental conditions which often have high levels of uncertainty (Helle et al. 2011). They are an effective and user-friendly tool which have been used to model complex ecological scenarios, and are an efficient way to integrate scientific knowledge into an effective management tool (Hamilton et al. 2007, Aguilera et al.

2011, Lecklin et al. 2011, Richards et al. 2013).

One of the major strengths of the probabilistic framework generated by Bayesian Network models are their ability to incorporate interactions between numerous variables on different scales (Hamilton et al. 2007). This allows the best possible data and information (and helps

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avoid data scarcity or small datasets) from a variety of sources to be compiled into one easily updated model of a potentially complex system (Hamilton et al. 2007, Düspohl et al. 2012).

The use of conditional probabilities incorporates the inherent uncertainty of environmental systems and interactions into the model which flows through to the results and determines the probability of an outcome (Hamilton et al. 2007, Helle et al. 2011).

In the last two decades the number or publications using Bayesian belief networks has more than quadrupled (Aguilera et al. 2011) with a growing proportion of these focusing on ecological systems. For example, Sanchirico and Wilen (2001) used a Bayesian model to investigate the effects of marine reserve creation. Their model simulated the effects of reserve creation under various ecological structures to show harvest increase after an area of the fishery is set aside and protected from exploitation. The ability to model complex ecological systems in this user-friendly manner makes Bayesian Networks one of the best ways to provide accessible and understandable decision-making tools to a wider audience.

The purpose of my network was to compile all information that is known about factors that affect Phyllospora and its associated rafts and create a model of this system. This allows the user to explore the impacts of future climate scenarios on Phyllospora comosa and its associated drifting rafts. By simultaneously comparing the changes in multiple drivers, it is possible to identify their relative importance and relationships. The aim of this chapter was to build a probabilistic Bayesian Network model that combines the results of my studies on biological and ecological factors, future emission scenarios and possible mitigation options which may serve as a foundation for assessing future ecological scenarios as well as the effectiveness of different potential policy decisions. My network will also allow me to predict future abundance changes based upon different climate change scenarios.

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This chapter will describe the development of the model and assess its potential to predict repercussions based upon our current understanding of the system. This model improves our ability to quantify relationships and account for the complicated interactions between environmental variables. Users will be able to explore future scenarios and assess the relative sensitivity of this habitat to different circumstances. The data generated by this model can be used to identify the most pressing threats to this habitat and evaluate conservation options.

7.2. METHODS

This model was developed using the BBN software Netica, available from http://www.norsys.com. The inference algorithms used by Netica are described by

Spiegelhalter (1993). Bayesian Networks have been described in more detail elsewhere.(e.g.

Hamilton et al. 2007, Aguilera et al. 2011, Düspohl et al. 2012).

7.2.1. Description of the model

The model was designed using both new empirical data and available literature. It includes three scenario-creating options and several environmental, policy and biological variables, which combine to describe the overall uncertainty related to the abundance of Phyllospora comosa and its associated rafts in a future ocean (Figure 7.1). The model allows users to manipulate the location, year and emissions scheme; all which influence the outcome. Since the abundance of this species is highly dependent on local conditions such as temperature, urbanization etc., this model is best used to describe and compare two general locations,

Tasmania and New South Wales (Figure 7.2), which have different levels of sensitivity to each factor included in the model. The final outcomes of the model are the probability distributions describing the cover of Phyllospora comosa on reefs as well as its abundance as rafts.

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Figure 7.1. A graphical representation of the Bayesian belief network. Squares: decision variables; ellipses: random variables. Black nodes represent locations or years. The lightest grey nodes represent environmental conditions, mid-grey nodes represent policy decisions and dark grey nodes represent biological effects. The white nodes represent the potential outcomes of the model.

7.2.2. Description and parameterisation of the variables

The structure of the model and the prior distributions and conditional probabilities between the variables were defined using literature and experiments (Table 7.1). The model has 12 nodes of which 3 are decision nodes, 6 are intermediate nodes, and 2 are predicted outcomes.

Here I provide a description of the relationship between nodes and the methods used to quantify their conditional probabilities.

7.2.2.1. Decision Nodes

Year includes 4 states: Current (2015), 2030, 2090 and 2110. The state Current represents the system as it appears at present. The three other states were chosen based upon the years which the Intergovernmental Panel on Climate Change (IPCC) 2014 Assessment Report has made projections for the levels of atmospheric greenhouse gas. Nodes that are expected to change in response to its state are: distance from urbanization and sea surface temperature.

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Location includes two states within Phyllospora’s range: New South Wales and Tasmania.

These are the most northern (28-37°S) and most southern (41-43°S) locations where it occurs

(Figure 7.2). The use of multiple locations allows for the user to compare how factors can impact populations differently dependant on more local conditions. Nodes that are expected to change in response to its state are: environmental protection, distance from urbanization, sea surface temperature and change in raft longevity.

Representative Concentration Pathways are scenarios that describe plausible trajectories of different aspects of the future which can be used to investigate the potential consequences of anthropogenic climate change. The scenarios include many of the major driving forces and processes that can be used to inform climate change policy (Nakicenovic and Swart 2000,

IPCC 2007, Rhein et al. 2013, Edenhofer et al. 2014). The three pathways included in this model are RCP 8.5, RCP 4.5 and RCP 2.6 (Figure 7.3). The RCP 2.6 emission pathway represents a future scenario where greenhouse gas emissions peak mid-century and then radiative forcing levels decline to 2.6 W/m2 by 2100 (Van Vuuren et al. 2007). RCP 4.5 is a scenario which results in total radiative forcing stabilizing before 2100 by “employment of a range of technologies and strategies for reducing greenhouse gas emissions” (Clarke et al. 109

2007). The RCP 8.5 scenario predicts increasing greenhouse gas emissions over time (Riahi et al. 2007). The goal of using these scenarios is not to precisely predict the future climate but to better recognise the high level of uncertainty and also the numerous alternative possibilities, in order to consider how influential different decisions may be in the future

(IPCC 2007, Rhein et al. 2013, Edenhofer et al. 2014). Representative Concentration

Pathway is expected to impact the Sea Surface Temperature node.

Figure 7.3. Predicted radioactive forcing levels under three representative concentration pathways utilized in the model. Adapted from Van Vuuren et al. (2007).

7.2.2.2 Intermediate Nodes

Season contains 4 states: Summer, Autumn, Winter and Spring. Season influences expected

Sea Surface Temperature.

Environmental Protection (can also be utilized as a decision node for future scenarios) is a key policy decision that influences the abundance and distribution of many species subject to fishing pressures. Designated no-fishing zones are critical in keeping this food web in balance, protecting both predators and prey. Currently, 7.9% of Tasmania’s State coastal waters are reserved, however only 1.1% of Tasmania’s immediate coastal waters are fully protected in no-take areas (Parks & Wildlife Service Tasmania 2014). In New South Wales,

34% of the coastline is reserved but only 6% is within a sanctuary zone (EPA 2012). This

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node is set in the model to show no change in protection policy before 2115. By changing the percent of coastline which falls into each category of protection, this factor can be operated like a decision node. This node is expected to impact on the grazing sea urchin,

Centrostephanus rodgersii’s density.

Distance from urbanization and anthropogenic inputs have proven to be an important factor in determining the density of Phyllospora forests (Coleman et al. 2008). This once dominant species may experience further population declines because of the expansion of urbanized coastlines. Therefore, proximity to densely urbanized areas may continue to be a deciding factor in determining the survival of Phyllospora forests. Population and urbanization growth rates have been calculated using data provided by the Australian Bureau of Statistics

(Statistics" 2014). Discretization divides the coastline into 35km distances from urban centres.

Sea Surface Temperature (SST) is one of the most important factors that will be impacted by climate change in the marine environment (Wernberg et al. 2010, Rothäusler et al. 2011b,

Smale and Wernberg 2013). Tolerances to high temperatures (summer maxima) define the biogeographical boundaries of many macroalgal species (Harley and Paine 2009, Staehr and

Wernberg 2009, Smale and Wernberg 2013, Ferreira et al. 2014). Projected increases in temperature have been tied to a decrease algal health in the form of diminished PSII yield, rapid biomass loss and loss of buoyancy (Chapter 6). These changes may reduce population resilience in Phyllospora and increase the possibility of a sudden range shift in synergy with other stressors such as disease (Wernberg et al. 2010). In this model, temperature influences the presence of urchins (Grazing Pressure), NO3 availability and Raft Longevity. Data included in the Sea Surface Temperature node was provided by publicly available data from

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the Bureau of Meteorology (BOM), Department of Climate Change and Energy Efficiency and CSIRO (Nakicenovic and Swart 2000, IPCC 2007, BOM 2013).

Nitrate is key to macroalgal growth (Gerard 1997) and is severely limited within the mixed surface waters of the entire south eastern Australian shelf region (Staehr and Wernberg

2009). There is a strong inverse relationship between temperature and nitrate, resulting in negligible nitrate at high sea temperatures (Shepherd and Edgar 2013, Carnell and Keough

2014). Valentine & Johnson (2004a) speculate that the relationship between nitrate levels and algal canopy abundance may have been responsible for a massive die-off of Phyllospora in

Tasmanian waters, seeing as the event coincided with a particularly warm season. However,

Flukes (2015) found no link between nitrate availability and Phyllospora fitness to concentrations above 0.5 µmol. The parameterization of the Nitrate node in this network is based upon the seasonal inverse relationship between sea temperature and nitrate concentration equations presented by Silió-Calzada et al. (2008). The node for nitrate concentration was divided into two categories: insufficient and sufficient. Insufficient nitrate represents a scenario where less than 0.05 µmol (10% the concentration known to suffice for this species) nitrate is present. Sufficient represents nitrate concentrations above 0.05µmol/L, which principally means that enough nitrate may be present allowing for the population to survive.

Grazing pressure caused by urchins has been documented around the globe as a leading culprit driving phase shifts from macro-algal dominated habitats to barrens devoid of seaweeds (Andrew and O'Neill 2000, Byrnes et al. 2011). It is extremely difficult to recover these algal habitats once widespread barrens have formed (Sanderson et al. 2013). Along the eastern Australian coast sea urchin Centrostephanus rodgersii has played the largest role in determining the state of shallow reef communities (Andrew and Underwood 1989, 1993,

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Johnson et al. 2005, Ling et al. 2009a). Centrostephanus rodgersii was until recently restricted to the eastern coast of mainland Australia, but has expanded its geographical range to Tasmania starting in the late 1960s (Ling 2008), following the warming East Australian current towards higher latitudes (Ling et al. 2009b, Sanderson et al. 2013). Larvae of this species are limited by an approximate temperature range for successful development between

12-26°C (Pecorino et al. 2013a, Pecorino et al. 2013b). Given predictions of continued warming along this coastline, the prospect of further range expansion of Centrostephanus rodgersii could be substantial (Ling et al. 2009a). In a future scenario where this upper limit is reached for C. rodgersii, it is expected that other more temperature-tolerant species will increase in abundance to fill this grazing role (Schiel et al. 2004). In addition to a range extension associated with warming coastal waters, this species has also experienced a decline in predation. Many of their predators have been over-fished and are therefore unable to keep the populations in check, resulting in rapid declines in productive kelp beds (Ling et al.

2009a). Lobsters (Jasus edwardsii in particular) account for 92% of predation events observed on tethered Centrostephanus rodgersii and only very large individuals were successful predators (Ling et al. 2009a). Experiments conducted inside and outside Marine

Protected Areas have shown that the removal of these large predatory lobsters reduced the resilience of kelp beds against urchins and the creation of widespread barrens (Ling et al.

2009a). Data for this CPT comes from publications that surveyed C. rodgersii densities throughout their range (Andrew et al. 1998, Johnson et al. 2005, Barrett et al. 2007, Ling

2008). Discretization categorizes the urchin density into increments increasing by 2 individuals per square meter.

Change in Raft Longevity has been found to be heavily influenced by sea surface temperature

(Chapter 6). Increases in temperature are highly correlated with the rate at which floating rafts sink and are lost from the system (Hobday 2000b, Salovius and Bonsdorff 2004,

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Vandendriessche et al. 2007b). This node was designed to represent the likelihood of rafts deviating in longevity from the current average number of weeks afloat.

7.2.2.3. Output Nodes

Attached Phyllospora comosa Cover estimates the average abundance of this species along rocky reefs. In this model, percent cover is calculated based upon the synergistic effects of

Distance from Urbanization, Nitrate Levels, and C. rodgersii density. Discretization divides percent cover into 25% increments.

Raft availability estimates the relative abundance of rafts in relation to the local attached

Phyllospora population and the potential for raft longevity. The number of rafts available is highly correlated with the distance to the nearest reef (Chapter 3). Abundance is also influenced by raft longevity, with more rafts being present when individuals remain buoyant longer (Vandendriessche et al. 2007b). Together these two factors determine the outcome of the model.

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Node Node Type Categories Justification Quantification/Data Collection Current 2030 Based upon years defined within the Year Decision Node N/A 2090 IPCC Fifth Assessment Report (2013) 2115 New South Wales Location Decision Node Discrete Data N/A Tasmania (RCPs) are defined by their total Representative Decision Node 2.6 radiative forcing (cumulative measure RCP scenarios were designated by the Concentration 4.5 of human emissions of GHGs from all Intergovernmental Panel on Climate Change Pathways Policy Decision 8.5 sources) and represent a broad range (IPCC) Fifth Assessment Report (2013). of climate outcomes Spring Summer Season Decision Node Discrete Data N/A Autumn Winter Environmental Intermediate Node Full Take Derived from published data by the NSW and TAS Protection Restricted Take Discrete Data marine parks authorities (See NSW State of the Input: Policy Decision No Take Environment (2012) and Parks Tasmania (2014)) 2) Location Distance from Below 35km Derived from population density data as presented Urbanization Intermediate Node Continuous data discretised into equal 35-70km by the Australian Bureau of Statistics (2014) as Input: (35km) distances from coastal areas 70-105km well as NSW population and household projections 1) Year Policy Decision with high population densities Above105km (2014) 2) Location Below 11°C Temperature 11-14°C Intermediate Node Continuous data discretised into equal Input: 15-17°C width to optimise congruence with the Probabilities derived from data provided by the 1) Year 18-20°C Environmental temperature ranges experienced by P. Australian Bureau of Meteorology 2) Emissions 21-23°C Condition comosa 3) Location 24-26°C 26°C up Intermediate Node Sufficient (> Continuous data discretised into two Probabilities based on the seasonal relationship NO3 Availability 0.1µmol/L) categories, one with and one without between temperature and dissolved nitrogen as Input: Environmental Insufficient the minimum amount of dissolved outlined in equations within (Silió-Calzada et al. 1)Temperature Condition (<0.1µmol/L) nitrogen necessary for macroalga 2008). See main text for a description of method. C. rodgersii Density No urchins Continuous data discretised to equal Probabilities based on density data for (Grazing pressure) Intermediate Node 0-2/m2 width (2 individuals/m2). Represents Centrostephanus rodgersii as cited in (Andrew et Input: 2-4/m2 a sufﬁciently ﬁne discretization of al. 1998, Johnson et al. 2005, Barrett et al. 2007, 1) Protection Biological effect 4-6/m2 density data of Centrostephanus Ling 2008) 2) Temperature More than 6/m2 rodgersii from available publications -3 Change in Raft -2 Continuous data representing Longevity Intermediate Node -1 Probability based on the relationship between variation from the current number of Input: 0 temperature and number of days afloat (see chapter days afloat, discretised into weeks 1) Temperature Biological effect 1 5) above and below the average. 2) Location 2 3 Probabilities based on the relationship between percent cover and urchin density (Andrew et al. Attached Cover None 1998, Johnson et al. 2005, Barrett et al. 2007, Ling Input: Intermediate Node 0-25% 2008), distance from urbanization (Dalton and 1) Urchin Density Continuous data discretised to equal 25-50% Australia , Andrew and Underwood 1993, Andrew 2) Distance from width (25%). Biological effect 50-75% et al. 1998, Barrett et al. 1998, Barrett et al. 2001, Urbanization 75-100% Johnson et al. 2004, Valentine and Johnson 2004b, 3) NO3 Levels Coleman et al. 2008, Barrett et al. 2009) and NO3 (Silió-Calzada et al. 2008). Raft Availability None Predicted Input: 0-25% Probability based on the relationship between Outcome of BBN Continuous data discretised to equal 1) Attached Cover 25-50% percent cover with raft availably (Chapter 3) and width (25%). 2) Change in 50-75% sea surface temperature (Chapter 5). Biological Effect Buoyancy 75-100%

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7.2.3. Sensitivity analysis

Sensitivity analysis was undertaken on the network to identify the relative influence of different nodes and pathways through the network (Richards et al. 2013) on the output of the model. The sensitivity to findings for each location was done in respect to the availability of raft node (outcome of model). The output provides information on the relative amount of mutual information and variance of beliefs between the node in question and the outcome of the model.

7.3. RESULTS

7.3.1. Model outcomes and predictions

The model shows that the severity of change is highly correlated with both location and

Representative Pathway (Figure 7.4). In many scenarios, the model predicts a decline in attached Phyllospora with a much larger associated decline in rafts. Looking ahead to the year 2115, an RCP 2.6 scenario would see a 0.82% decline in percent cover in NSW and a

1.16% decline in TAS. This would also see a drop in raft abundance of 4.66% in NSW and

4.96% in TAS. This pathway results in an initial drop in Phyllospora both on reefs and on rafts in the mid-2000s but as greenhouse gasses begin to decline towards the end of the century, Phyllospora begins to return to its initial abundance. However, at the opposite end of the spectrum, the RCP 8.5 scenario results in a 4.66% loss in percent cover in NSW and a

4.96% loss in TAS. Most drastically, the decline in raft abundance under this scenario is

21.95% in NSW and 35.70% in TAS. The average (RCP 4.5, stabilization of gas emissions) predicted decline in attached Phyllospora is 1.03% in NSW and 4.46% in TAS by the end of the century. Comparatively, rafts are predicted to decline 10.86% in NSW and 19.83% in

TAS during the same time.

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The model also allows us to assess the impact that levels of coastal environmental protection have on the abundance of rafts (Figure 7.5). In NSW, 40% of the coastline is currently protected by reserves whereas only 9% of Tasmania’s immediate coastal waters are protected. Knowing that the abundance of rafts is expected to decline significanly by 2115, a change in policy influencing the percent of protected coastline will either improve or exacerbate the situation. If all marine parks were de-sanctioned, there would be an expected further average decline in rafts by 1% in NSW and 0.25% in TAS. However, if a situation where 100% of the coastline had regulated fishing within reserves, the abundance of rafts would increase by about 2% in both states. If fishing was banned all together, raft abundance could increase by as much as 5% in NSW, 4% in TAS.

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7.3.2. Sensitivity analysis

At the first hierarchical level, the most sensitive response variable (percent mutual information) to raft abundance in New South Wales was percent cover of attached

Phyllospora while in Tasmania it was raft longevity (Figure 7.6). At the second hierarchical level, NSW is most influenced by distance from urbanisation whereas TAS is affected by

SST and C. rodgersii density. Season had a larger influence on TAS than NSW in the 3rd level indicating higher seasonal variability in SST.

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Of the three decision nodes, Year, RCP and Environmental Protection, (location not included as it is being used as a distinguishing factor of influence), year has the most mutual information with the abundance of rafts (Figure 7.). The representative concentration pathway (RCP) has the second greatest influence, especially in Tasmania. As shown in

Figure 7.5, environmental protection does share information with the abundance of rafts, but not enough to have a strong influence on the outcome of the model.

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7.4. DISCUSSION

Given what is known about the biology of Phyllospora comosa, the scenarios presented by the model confirm the importance of environmental conditions such as sea surface temperature, as well as the biological effects of grazing and attached cover on the availability of rafts along the coastline. Using a BN model to manipulate the environmental scenarios allows different combinations of variables to be analysed using the most recent knowledge from multiple scientific disciplines.

The model shows that the number of rafts declines at a much faster rate than that of attached

Phyllospora for all Representative Concentration Pathway (RCP) scenarios. While the RCP scenarios both directly and indirectly influence the percent cover of this species, it has an amplified effect on rafts because it influences the outcome through multiple pathways. These results indicate that even a few degrees change in temperature are likely to dramatically influence the longevity of rafts (Chapter 6). If the future follows a RCP 4.5 or 8.5 scenario, the availability of Phyllospora as habitat is likely to decline and mitigation options will need to be explored if we wish to offset the temperature-induced decline.

The RCP 2.6 scenario results in a reduction in greenhouse gases by the end of the century, resulting in a decline in ocean temperature (when compared to mid-century temperatures).

The model predicts that the number of rafts in Tasmania will begin to bounce back accordingly. This trend is more opaque in New South Wales because the model shows an initial recovery around the end of the century but then it begins to decline again by 2115. This decline is due to growing urbanized coastlines taking over as the most important factor influencing both attached and raft abundance. If SST does in fact stabilize by the end of the century as predicted by RCP 2.6, the success of Phyllospora habitat will switch from being

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primarily driven by environmental and biological conditions to a direct correlation with the levels of habitat destruction.

The Environmental Protection node (when used as a decision node) provides insight into one of many possible environmental mitigation options. Given that a minority of the coastline in both states is currently protected, it is not surprising that removing the existing marine parks does not have an overwhelming influence on the abundance of rafts. However, it could be an important component of creating a successful plan to counteract climate change.

A reduction in rafts may also have an associated negative impact on invertebrates that rely upon rafts for habitat and dispersal. If there is a decline in raft abundance, there is likely also a decline in habitat complexity that is created by the clumping of rafts (Chapter 5).

Additionally, it is expected that there will be a reduction in the quality of rafts as warming temperatures can lead to an elevated rate of decomposition and less resilience to physical breakup (Macreadie et al. 2011). The abundance and diversity of rafting organisms may decline because of a decrease in raft size, density and complexity.

There are some variables that have been intentionally excluded from the model despite the important role they undoubtedly will play in future ocean dynamics. At this time, there is insufficient data to model some relationships to the degree necessary for inclusion. While studies relating to UV radiation, salinity, pH, turbidity, disease, etc. in a future ocean are numerous, the direct impact that they are expected to have on Phyllospora specifically remains uncertain. By excluding them from the model for the time being, the network theoretically represents a “best-case” scenario for the future of this species. As more relevant data becomes available these variables can be easily included, improving the accuracy of future versions of this model. Uncertainty is also unavoidably introduced through the discretization of variables in the model which results in the information about some minor

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changes being lost. Yet, despite this slight reduction in prediction power, the model still reveals important information regarding relationships and details about future oceanic conditions (Helle et al. 2011).

5.4.1. Sensitivity analysis

Sensitivity analysis explains differences in the driving factors between nodes and reinforces many of the trends seen in the outcome of the model. It is important to remember that nodes closest to a node of interest (in this case, rafts) typically have the biggest effect because more distant nodes introduce more uncertainty through levels of separation from the variable in question (Hamilton et al. 2007). Due to this, it is difficult to compare the importance of decision nodes to intermediate nodes even when assessed separately but they can provide important information on what is driving the model.

In New South Wales, percent cover of attached Phyllospora and distance from urbanization proved to be two of the most influential factors. This indicates that direct habitat destruction is largely dictating raft abundance along this coastline. In Tasmania, raft longevity, SST and urchin density are relatively more important, indicating that change in temperature and temperature-driven factors are driving abundance in this state. Essentially, the urbanization of coastline is happening at a faster rate in NSW than in TAS, but TAS is predicted to experience a faster rise in SST. Therefore, although we see raft declines in both states, they are as a result of different drivers.

7.4.2. Conclusion

The use of Bayesian Networks to model ecological dynamics is largely unexploited (Aguilera et al. 2011) but will likely continue to increase in use in coming decades. Existing models with similar objectives have been used to explore the major factors influencing initiation of

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algal blooms (Hamilton et al. 2007) and predict the growth of coral reef macroalgae (Renken and Mumby 2009). In these studies, they demonstrated the efficacy of the BBN to predict ecosystem dynamics with a higher accuracy than is often possible through other models.

These models have additional value in that they have been used to identify knowledge gaps and therefore to direct additional research and model development. For example, Bayesian

Networks developed to predict the potential for oils spills (Aps et al. 2009) were then used to model scenarios for their long-term impact (Lecklin et al. 2011) and the efficiency of different methods to combat them (Helle et al. 2011). Early results of my BN helped solidify the design of my field and lab experiments. The success of BN in identification of sustainable management strategies (Düspohl et al. 2012) will likely guide my future research. Looking forward, I seek to expand future renditions of my model to include data and scenarios that allow it to be used as an ecosystem management tool.

The BN model presented introduces an approach to combine available data on an environmental system into a user-friendly predictive tool. This Bayesian Network has highlighted the importance of reducing greenhouse gas emission to limit temperature increase as well as the vulnerability of Phyllospora to direct habitat damage. Even minor reductions in already small populations of Phyllospora along reefs may have severe consequences (Helle et al. 2011). Isolated or small populations are vulnerable to extinction due to the stochastic variations in genetic, demographic and environmental factors (Lande 1998, Fingas 2004).

The fact that it has already disappeared from the Sydney metropolitan area as well as areas of

NSW and TAS coastline emphasizes the importance of continuing to improve modelling, monitoring and protection. The structure of this model is relatively universal to intertidal macroalga species, and thus adaptable to other coastal sea areas experiencing climate change.

Bayesian networks of environmental systems offer a promising tool to inform further studies and policy on the ecological impacts of emissions schemes and other management decisions.

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As part of a strategic management tool, this model can assist in visualizing environmental relationships that are key to the recovery of macroalgal forests (Helle et al. 2011). While at this point there is still a possibility of each of the RCP scenarios becoming a reality, the ability to visualize the impacts of each will hopefully steer policy decisions towards an RCP

2.6 outcome which would see Phyllospora reefs and rafts recover and remain abundant into the future.

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CHAPTER 8 – GENERAL DISCUSSION

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8.1. General findings and consistency with previous research

This study used a combination of lab, field and modelling studies to determine the role of floating algal rafts in the pelagic environment along the New South Wales coastline. I assessed spatial and temporal trends in the abundance and diversity of raft-forming alga and their associated rafting community. I also explored how this important habitat may be impacted by future ocean conditions which are expected to warm in coming decades.

Phyllospora comosa was the dominant species of floating alga along the New South Wales coastline but its abundance was greatly reduced in the Sydney region. The distribution of floating Phyllospora comosa rafts in the region was found to closely relate to the density of

Phyllospora reefs growing along nearby coastline. As attached habitat, Phyllospora has been observed to support much greater numbers of abalone and urchins than any other habitat

(Marzinelli et al. 2013). Similarly, I found that as a raft, Phyllospora continues to host a highly specific invertebrate community including commercially important species. Therefore, given its abundance both along the coastline and in the pelagic environment, all my results agree with Marzinelli et al.’s (2013) assessment that Phyllospora plays “multiple functionally unique roles, and is not a redundant species.”

The proximity of defaunated rafts to existing habitat had a sizable impact on the degree to which they were colonized. Acting as source populations, defaunated rafts had a higher number of species in the first few hours than did rafts released in isolation. Overwhelmingly, highly mobile pelagic species (such as isopods, crab megalopae and euphausiids) were the first and most abundant species found on rafts (Sogard 1989, Ingólfsson 1998, Clarkin et al.

2012b). These results are consistent with other investigations which have found that the

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distribution of species may reflect a gradient where habitats closer to existing populations of invertebrates are colonized more rapidly by settlers (Gaines and Roughgarden 1985).

Two health indicators I tested were found to be negatively impacted by elevated temperature.

However, rafts acclimated to summer temperatures remained buoyant slightly longer despite widespread necrosis and appeared to experience a slower initial decline in PSII yield and biomass than their winter counterparts. A study by Flukes et al. (2015) evaluated individuals collected from the top and bottom of its latitudinal range and reported that warm-adapted individuals were able to maintain greater photosynthetic functionality at high temperatures, supporting my contention that Phyllospora rafts have the capacity to survive and grow under a range of environmental conditions.

I developed a conceptual model of key relationships in the form of a Bayesian Belief

Network. This model compiles the important information and relationships I observed in my research and allows me to determine likely future change. The outcome of this model supports the notion that Phyllospora habitat may be significantly impacted by future ocean conditions. Increases in sea surface temperatures and habitat destruction are predicted to have an even greater impact on Phyllospora as floating rafts than would be experienced by attached Phyllospora along reefs. Therefore, monitoring only the density of macroalga attached to reefs (which are expected to feel the effects of climate change more slowly), may result in the more rapid decline of pelagic algal raft habitat going un-noticed until it is nearly non-existent; which has been the case in the Sydney region. Looking to the future, rafting seaweeds as key habitat and a dispersal mechanism in the marine environment needs to be taken into account when drafting effective conservation measures (Thiel and Haye 2006).

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8.2. Future Directions

There is still much to be understood about the rafting process along the New South Wales coastline regarding the movement of rafts, the distances they travel and the impact they have on the dispersal potential of marine species. The role floating rafts play in the life history of many species as well as maintaining the distribution of these species may be greater than currently considered. For these reasons, it is clear why interest in this area of study has risen within recent decades.

Future research into algal rafting in the Sydney region, especially regarding the lack of

Phyllospora, may want to consider the impacts that this damaged system has on invertebrate species that rely on rafts for dispersal and gene flow (such as Portunus spp.). Coleman and

Kelaher (2009) found that this gap did not affect the genetics of the Phyllospora itself as it broadcast spawns propagules which has the potential to allow for dispersal over long distances (Coleman et al. 2011a) but does not answer the question of what impacts the discontinuous population may have on invertebrate species that rely upon it for transport.

Since previous research has shown that species composition can change in respect to distance from shore (Salovius et al. 2005) and over time (Helmuth et al. 1994, Hobday 2000c) there may be some species that experience hindered dispersal due to the decreased availability of rafts. A comparative study assessing the invertebrate community of known rafting species between areas still serviced by rafts (outside Sydney) and those that are not (the 70km gap in

Sydney) could be used to determine if there is any change in their diversity or abundance between these areas.

It would also be interesting to explore the impact of the loss of rafting habitat by comparing the epifaunal community between locations within the Sydney region to those at varying

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distances outside this region as well as in regions where this habitat has been restored

(Marzinelli et al. 2016). Given that my research has shown that rafts within the Sydney region are relatively rare, it would be interesting to see if this has had any impact on the abundance and diversity of epifaunal species. A similar defaunation experiment could compare the colonization of isolated rafts both within and outside the Sydney region. I predict that within the Sydney region rafts may be colonized more rapidly and be more densely populated because of limited availability of this pelagic habitat. In my experiment outside the Sydney region, I found that isolated habitats were colonized more slowly, but perhaps this is not the case in areas where rafts are particularly uncommon. Additionally, rafts within the Sydney region may harbour a less diverse fauna.

Future work on a Bayesian Network of this system would benefit from new information about the relationships explored by these questions as well as integration of other research in this area. Improved coastal surveying methods such as by remote drones also has the potential to improve our monitoring of the coast as well as offshore at a relatively low cost

(Casella et al. 2015) which would allow future models to use more fine-scale discretization of locations than is currently available. The further discretization of locations would allow a more critical analysis of latitudinal differences in response to stressors. The addition of more variables and potential stressors to the model will also improve its capacity to accurately predict future scenarios.

8.3. Potential Implications of Findings

Algal rafts off the coastline of New South Wales are a key pelagic habitat yet they often go without mention when describing life in the pelagic environment. Many articles describe the relationship between pelagic species with the sea bed but overlook the fact that some algal

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species become a pelagic feature themselves (Edgar 2001). The role algal rafts play as habitat and as a means of dispersal for many invertebrate species should not be undervalued: if this habitat were to be compromised in the future, it may have far-reaching ecological impacts.

Phyllospora comosa provides much of the pelagic floating habitat along the New South

Wales coastline and higher densities of rafts host a wider diversity of species. Given the abundance and diversity of species found on rafts, if the availability of rafts in the pelagic environment were to decrease, this may have negative impacts on species that rely upon them for habitat in the pelagic environment.

The response of algal rafts to climate change is an important aspect of predicting their ecological role in a future ocean (Macreadie et al. 2011). The future range and distribution of rafts of P. comosa may very well depend on the rate and severity of ocean warming. Long distance dispersal via buoyant algal rafts is only possible in colder waters where estimates of the survival periods of floating algae range widely from a few weeks up to an entire year

(Harrold and Lisin 1989, Helmuth et al. 1994, Ingólfsson 1998, Hobday 2000c,

Vandendriessche et al. 2007b, Hinojosa and Thiel 2009, Rothäusler et al. 2009). Sea surface temperatures are projected to continue to increase and the magnitude of these increases will depend on how the concentration of greenhouse gasses changes in coming decades. The near coastal sea surface temperature rise around Australia is expected to be between 0.4-1.0°C by

2030 and around 2-4°C by 2090 (CSIRO 2015). The western boundary currents off the east of Australia and Tasmania have been warming 2 to 3 times faster than the global mean (Wu et al. 2012, CSIRO 2015). As a result, along the east coast of Tasmania very large changes are expected, with median changes as large as 4°C by 2090, and up to 6°C in the next century

(CSIRO 2015). These severe warming projections suggest that marine biodiversity will be

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negatively impacted by habitat loss as well as the southward shifts in some species and local extinctions of others (Wernberg et al. 2011, CSIRO 2015).

We are already experiencing a decline in the frequency of rafting opportunities for epifaunal invertebrates in the Sydney region as a consequence of human activities which have drastically changed the spatial and temporal distribution of this key pelagic habitat (Thiel and

Haye 2006). In regions like Sydney where this species was likely once present in abundant quantities, its disappearance has the potential to influence population connectivity and the distribution of invertebrates both along reefs (Marzinelli et al. 2013) and in the pelagic environment (Kingsford and Choat 1985). Many temperate species with limited autonomous dispersal capacity have evolved to rely upon rafting on macroalgae (Edgar 1987, Helmuth et al. 1994, Ingólfsson 1998, O Foighil et al. 1999, Hobday 2000b, Thiel 2003, Rothäusler et al.

2009). Further change in the abundance and distribution of Phyllospora along reefs and as rafts may have significant economic impacts as many commercially and recreationally valuable species that show preference for Phyllospora habitat.

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