Jacquetta Udy a Thesis Submitted for the Degree of Master of Science at the University of Otago Dunedin, New Zealand Submitted

DRIVERS OF TEMPERATE REEF FISH COMMUNITY STRUCTURE AND

FOOD WEB ARCHITECTURE

Jacquetta Udy

A thesis submitted for the degree of Master of Science

At the University of Otago Dunedin, New Zealand

Submitted June 2018

2 Abstract ______

An understanding of the drivers that influence community structure and functioning is essential to predict and manage the impacts of human induced stressors on the marine environment. The current thesis aimed to resolve the relative importance of natural, and anthropogenic induced, variation in kelp abundance versus fishing pressure in driving temperate reef fish community and food web structure. Reef communities were compared in an orthogonal design between marine reserves and fished areas and barren and kelp bed habitat, within the Marlborough Sounds and Fiordland.

Underwater visual surveys of the reef fish community, revealed that reef fish density varied with fishing pressure and the presence of kelp beds, with interactions between the two factors. Blue cod (Parapercis colias) displayed the biggest variation in density between reserves and fished areas, with a larger fishing effect in barren habitats. Further, the density of non-exploited fish species, Evechinus chloroticus, and macroalgae also varied with fishing pressure. The results suggest that fishing pressure is heavier in the Marlborough Sounds, compared to Fiordland. Benthic surveys of kelp abundance, as well as regional variability in the response of fish to the factor KELP, imply there is a difference in the kelp community between the two regions. Fish community structure is likely driven by an interaction between habitat quality and fishing pressure at both the local and regional scale.

Comparison of 8 reef fish species common to both regions found up to 40 % less organic matter from macroalgae supporting omnivorous species in the Marlborough Sounds, compared to Fiordland. Combining trophic position data with stratified surveys of abundance and species biomass, revealed regional differences in the contribution of macroalgae to whole fish communities in terms of density of biomass. In Fiordland over 77% of the biomass of exploited reef fishes was supported by macroalgae, compared to 31% in the Marlborough Sounds. Regional differences in trophodynamics may be explained by a lack of kelp input to the food web in the Marlborough Sounds, as supported by surveys of kelp density.

The contribution of macroalgae to cumulative fish biomass decreased with trophic level in Marlborough, while the high trophic level fish species in Fiordland were supported by an equal mix of phytoplankton and macroalgae, providing further support for the hypothesis of lower kelp input in the Marlborough Sounds. Here we find that regional differences in fish community and food web structure result in the Fiordland fish community using 2.91 times more organic matter per unit area than the community in Marlborough.

The results suggest there is likely an important interaction between differences in kelp bed habitat and changes in reef fish community structure wrought by fishing, for controlling reef fish communities. This thesis corroborates the importance of kelps as foundation species on temperate reefs and highlights the need to recognise spatial variability, and multiple environmental stressors, when designing management approaches to protect the integrity of temperate reef ecosystems.

Backyards

ii Acknowledgments ______

Firstly, thank you to my supervisor, Steve Wing for his ideas, advice, enthusiasm and encouragement throughout the whole project. You were a huge help keeping this thesis on track, and we would be missing some crucial samples without your exceptional aim with the pole spear. Thanks for listening patiently while I blabbled on about whatever new problem I’d encountered, and for all the editing even when I only got things in a bit last minute.

To all the people who came diving, counted fish and tried their best at spearfishing; Sorrell O’Connell Milne, Stina Kolodzey, Rebecca McMullin, Jack Hall, Leo Durante, Lana Young, Clara Schlieman, Lottie Borra, Alex Connelly and Sara Niksic, you guys were amazing. From the warm summer days in Marlborough to sitting in wet wetsuits cuddling hot water bottles and cups of tea in Fiordland, there were never any complaints no matter how many dives I tried to squeeze into a day.

Thanks to Bill and Evan for their constant good humour as the Polaris crawled along, and to Sean Heseltine for sitting patiently on the Typhoon while we had all the fun underwater. Thank you to all the staff at the Portobello Marine Lab, and sorry to the Portobello Fire Department for some false alarms when furnacing fish got a bit out of hand. Huge thankyou to the team at the Chemistry Department for processing all my stable isotope samples. Thank you to all the people who were involved in the Fiordland project before me, who’s data and experience helped enormously; Lucy Wing, Olga Shatova, Nicola Beer, Jean Davis and Susan Lusseau.

This research wouldn’t have been possible without funding from the National Science Challenge: Sustainable Seas (4.1.1 Ecosystem Connectivity) the Royal Society of New Zealand Marsden Fund (UOO1008) and from the University of Otago’s Research Committee.

To the beach flat, with the best backyard in the world, and everyone who lived there, thanks for making the last 2 years so full of shenanigans and waves that I’m still not sure how a thesis got written in amongst it all. Brooke, Cas, Sam, Burt, Sez, Max and Em, you guys were the most supportive and distracting flatmates I could ask for. Cheers to New St for adopting me while I was finishing this thing.

To my amazing parents, for showing me all the wonderful creatures in the ocean, and your meticulous proof reading, your support has always been amazing. I can’t wait to go exploring the Pacific with you guys, imagine all the fish we can count! Huge thankyou to my sister, Danielle, for all her GIS expertise.

iii Table of Contents ______

Abstract ...... i

Acknowledgments ...... iii

Table of Contents ...... iv

List of Tables ...... vi

List of Figures ...... vii

Chapter 1: General introduction ...... 1 1.1 Temperate reefs ...... 3 1.2 Threats to temperate reefs ...... 3 1.3 Marine reserves ...... 4 1.4 Trophic structure of temperate reef communities ...... 5 1.5 Study Sites ...... 7 1.6 Objectives ...... 8

CHAPTER 2: Effect of fishing on temperate reef community structure in the context of habitat variability ...... 13 2.1 Introduction ...... 14 2.1.1 Research Questions ...... 16 2.2 Methods ...... 17 2.2.1 Study Sites ...... 17 2.2.2 Surveys of Reef Fish, Invertebrate and Kelp Density ...... 19 2.2.3. Statistical analysis ...... 21 2.3 Results ...... 23 2.3.1 Effect of FISHING and KELP on fish density ...... 24 2.3.2 Differences in Community Composition and Structure ...... 31 2.3.3 Effect of FISHING on Evechinus chloroticus and kelp density ...... 34 2.4 Discussion ...... 34 2.4.1 Effect of FISHING ...... 36 2.4.2 Effect of KELP ...... 37 2.4.3 Interaction of FISHING effect with KELP ...... 38 2.4.4 Regional differences ...... 39 2.4.5 Reserve effect on Evechinus chloroticus and kelp density ...... 40 2.4.6 Caveats ...... 40

iv 2.4.7 Conclusions ...... 41

Chapter 3: Organic matter derived from kelp supports a large proportion of biomass in temperate rocky reef fish communities: implications for ecosystem based management ...... 44 3.1 Introduction ...... 45 3.2 Methods ...... 48 3.2.1 Surveys of fish and macroalgae abundance ...... 48 3.2.2 Stable isotope analysis ...... 50 3.2.3 Trophic positions ...... 54 3.2.4 Proportion of fish biomass supported by macroalgae ...... 55 3.2.5 Statistical analysis ...... 56 3.3 Results ...... 57 3.3.1 Macroalgae community ...... 57 3.3.2 Stable isotope analysis ...... 57 3.3.3 Trophic positions ...... 62 3.3.4 Herbivore macroalgae use ...... 65 3.3.5 Proportion of fish biomass supported by macroalgae ...... 66 4.0 Discussion ...... 67

Chapter 4: Regional differences in the energetics of two temperate reef fish communities: implications for the loss of kelp forests ...... 73 4.1 Introduction ...... 74 4.2 Methods ...... 77 4.2.1 Surveys of reef fish density ...... 77 4.2.2 Trophic position of reef fish ...... 78 4.2.3 Biomass distribution across trophic positions ...... 79 4.2.4 Organic matter required to support reef fish community ...... 80 4.3 Results ...... 81 4.4 Discussion ...... 88

Chapter 5: Synthesis ...... 93

REFERENCES ...... 99

v List of Tables ______

Table 2.1. Frequency of occurrence of species on transects in Fiordland and the Marlborough Sounds...... 24

Table 2.2. Results from GAMLSS models run on individual species for the Marlborough Sounds for the a) Mu parameter (Mean of the non-zeros) and b) Nu parameter (probability of zero)...... 29

Table 2.3. Results from GAMLSS models run on individual species from Fiordland for the a) Mu parameter (Mean of the non-zeros) and b) Nu parameter (probability of zero)...... 29

Table 2.4. Results of PERMANOVA analysis on Bray Curtis for relative abundance (RA) and presence absence (PA), for the non-exploited and exploited fish community in Marlborough Sounds and Fiordland ...... 32

Table 2.5. Results of PERMANOVA analysis on Bray Curtis for relative abundance (RA) and presence absence (PA), for the non-exploited and exploited fish community with Marlborough Sounds and Fiordland analyzed separately ...... 32

Table 3.1. Isotopic signatures (!13C and !15N) and trophic position of each reef fish species observed on transect in Fiordland ...... 51

Table 3.2. Isotopic signatures (!13C and !15N) and trophic position of each reef fish species observed on transect in the Marlborough Sounds ...... 52

Table 3.3. Summary of general linear model results for holdfast density (2m-2) of the most common macroalgae species ...... 58

Table 3.4. Average density and biomass per transect of each reef fish species observed in the Fiordland, New Zealand...... 61

Table 3.5. Average density and biomass per transect of each reef fish species observed in the Marlborough Sounds, New Zealand...... 61

Table 4.1. Results from GLMs on the regional difference in organic matter required to support the fish communities, as calculated using a range of values for trophic efficiency...... 87

vi List of Figures ______

Figure 2.1. Map showing the location of survey sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand...... 18

Figure 2.2. Frequency of site averages for kelp holdfast density (2m-2)...... 20

Figure 2.3. Effect size of FISHING on a) mean density when the species is present (Mu parameter) and b) the probability of the species not being present on a transect (Nu parameter) ...... 25

Figure 2.4. Effect size of KELP on a) mean density when species are present (Mu parameter) and b) the probability of the species not being present on a transect (Nu parameter) ...... 26

Figure 2.5. Overall mean blue cod density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat...... 27

Figure 2.6. Overall mean non-exploited fish density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat...... 30

Figure 2.7. Overall mean exploited fish density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat...... 30

Figure 2.8. PCO analysis of site averages based on resemblance matrices constructed using Bray Curtis similarity index on relative abundance data ...... 33

Figure 2.9. a) Mean density of Evechinus chloroticus for the quadrats where E. chloroticus are present ±"1"SE and b) the proportion of quadrats where E. chloroticus are absent, for fished (grey bars) and reserve (black bars) areas...... 35

Figure 2.10. a) Mean density of holdfasts for the quadrats where kelp is present ±"1"SE and b) the proportion of barren quadrats, for fished (grey bars) and reserve (black bars) areas...... 35

Figure 3.1. Map showing the location of study sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand...... 49

Figure 3.2. Holdfast density per 2 m2 of Ecklonia radiata, Carpophyllum machalocarpum, Macrocystis pyrifera and Undaria pinnatifida ...... 58

Figure 3.3. Stable isotope signatures of reef fish species present in each region ...... 59

Figure 3.4. Trophic position of reef fish present in each region ...... 60

vii Figure 3.5. Proportion of organic matter from macroalgae supporting (a) exploited reef fish and (b) non- exploited reef fish from Fiordland (grey bars) and Marlborough Sounds (black bars)...... 63

Figure 4.1. Map showing the location of study sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand...... 78

Figure 4.2. Cumulative average fish biomass (250 m-2) (black circles) and cumulative average fish biomass supported by macroalgae (250 m-2) (open circles) versus trophic level for temperate reef fish observed on transect in (a) Marlborough Sounds and (b) Fiordland...... 82

Figure 4.3. a) average fish biomass 250 m-2 (grey bars) and amount of fish biomass supported by macroalgae (black bars) and b) the proportion of fish biomass supported by macroalgae...... 83

Figure 4.4. Proportion of cumulative fish biomass supported by macroalgae versus trophic level for Fiordland (black circles) and the Marlborough Sounds (open circles)...... 84

Figure 4.5. Cumulative organic matter (black circles) and organic matter from kelp (open circles) required to support the reef fish assemblage (250m-2) versus trophic level for the a) Marlborough and b) Fiordland fish communities...... 85

Figure 4.6. a) Average total organic matter 250 m-2 (grey bars) and organic matter derived from macroalgae (black bars) required to support the fish community and b) the proportion of organic matter derived from macroalgae ...... 86

Figure 4.7. Estimates of organic matter required to support the fish community in Fiordland (black circles) and the Marlborough Sounds (open circles), obtained using varying values for trophic transfer efficiency...... 87

viii

Chapter 1:

General introduction

Inquisitive blue cod in the Marlborough Sounds

1 1.0 General introduction Understanding the interactions that influence the distribution and abundance of species, and hence determine community structure is one of the main aims of ecological science (Krebs 2009). Human activities are threatening the integrity of the world’s ecosystems, and hence an understanding of the factors that drive the spatial distribution of species is essential to predict and manage the impacts of human induced stressors (Simberloff 2004). In this context, when analysing the effect of anthropogenic changes, the need to consider whole ecosystems has been increasingly realised in recent decades (Minns et al. 2011). Accordingly, it is now understood that the effects of human induced change need to be considered in terms of how they affect the functioning of whole ecosystems (Halpern et al. 2010).

Historically fisheries management rarely considered ecosystem approaches to management, and hence in general, fisheries have not been managed sustainably (Botsford et al. 1997). There are various definitions of ecosystem based management, although the main principle is that it is an integrated approach to management that considers the entire ecosystem, including humans, and acknowledges the cumulative impacts of different stressors (Long et al. 2015). Ecosystem based management differs from most current marine management approaches that generally focus on single species and impacts (Kraak et al. 2014, Long et al. 2015). The goal of ecosystem based management therefore is to maintain ecological integrity, allowing for both conservation objectives and the sustainable provision of resources and services to be met (Halpern et al. 2010, Cowan et al. 2012). Achievement of these management goals requires a sound understanding of the factors that regulate ecosystem structure and functioning, as well as an evaluation of the cumulative impacts various anthropogenic stressors may have on aspects of ecosystem functioning (Garcia & Cochrane 2005).

The current thesis aimed to resolve the relative importance of natural, and anthropogenic induced, variation in kelp abundance versus fishing pressure in driving temperate reef fish community and food web structure. The objective was to establish how anthropogenic stressors may have affected two of New Zealand’s temperate reef fish communities, in order to aid in the development of effective ecosystem-based management strategies.

2 1.1 Temperate reefs Temperate rocky reefs support a diverse and productive community, with many species of commercial, recreational and customary importance (Dayton 1985, Shepherd & Edgar 2013a). Temperate reefs are found in cool waters between the tropics and the poles, and healthy reefs are generally dominated by kelp forests. Kelps are highly productive and structurally complex (Mann 1973, Dayton 1985, Duggins et al. 1989). As a result, kelps are considered marine foundation species on temperate reefs (Miller et al. 2015), with an abundance of literature describing their importance as habitat formers (e.g. Choat & Ayling 1987, Carr 1991, Taylor & Cole 1994, Anderson & Millar 2004, Pérez-Matus & Shima 2010) and a source of organic matter (e.g. Mann 1973, Bustamante & Branch 1996, Norderhaug et al. 2003, Yorke et al. 2013, Koenigs et al. 2015). Numerous invertebrate (Taylor 1998, Wing et al. 2008, Miller et al. 2015) and fish species (Jones 1984, Holbrook et al. 1990a, Pérez- Matus & Shima 2010) are positively correlated with the presence of kelp, with large alterations to community structure when kelp is absent (Graham 2004, Wernberg et al. 2016). Fish are also an integral part of the temperate reef ecosystem, occupying an array of ecological roles as predators, prey and herbivores (Russell 1983, Babcock et al. 1999, Shepherd and Edgar 2013b). As a consequence, differences in the diversity and relative abundance of fish species can affect ecosystem functioning (Babcock et al. 1999, Tegner 2000, Salomon et al. 2008, Newcombe & Taylor 2010).

1.2 Threats to temperate reefs Temperate reefs are currently threatened by numerous anthropogenic stressors, with fishing, habitat degradation and invasion by exotic organisms among the main threats (Shepherd and Edgar 2013a, Smale et al. 2013). The density, distribution and diversity of kelp forests is declining globally, with loss of kelp forests the biggest form of habitat degradation on temperate reefs (Steneck et al. 2003). There is a high degree of natural variability in kelp density and diversity, influenced by many biological processes (e.g. grazing pressure, disease, competition) and physical factors (e.g. wave exposure, freshwater input, light and nutrient availability, water temperature) (Kingsford & Battershill 1998). However the abundance of kelps is also controlled by many anthropogenic impacts that affect these biological processes and physical factors (Steneck et al. 2003). Impacts include high levels of sediment and nutrient runoff (Eriksson et al. 2002), overfishing of sea urchin predators (Shears & Babcock 2002) and increasing sea surface temperatures as a result of

3 global climate change (Shears & Babcock 2002, Steneck et al. 2003, Johnson et al. 2011). The ecological consequences of decline in kelp forests will depend on their relative importance as an ecosystem engineer or food resource (Miller et al. 2015).

Many marine systems, particularly those along developed coastlines, are simultaneously exposed to anthropogenic impacts that affect the bottom up (e.g. habitat degradation) and top down (e.g. fishing mortality) control of the community (Williams et al. 2008, Wilson et al. 2008). For temperate communities, the loss of kelp forests is likely to affect the bottom up control of communities (Graham 2004, Wernberg et al. 2016) while removal of high trophic level species, by fishing, simultaneously affects the top down control (Babcock et al. 1999, Willis & Anderson 2003, Salomon et al. 2008). Fishing reduces the abundance of target species, and by altering predator-prey and competitive interactions, can also have indirect effects on the abundance of non-exploited species (Pinnegar et al. 2000, Willis & Anderson 2003, Gascuel 2005). As a result, fishing has the potential to alter community structure, and consequently ecosystem functioning (Crowe et al. 2013). The degree to which fishing affects the fish community is likely dependent on habitat quality (Wilson et al. 2008), with variations in habitat quality, such as density of kelp, either ameliorating or exacerbating the top down effects of fishing (Menge & Sutherland 1987, Shurin et al. 2002).

1.3 Marine reserves Marine reserves are increasingly being adopted as tools for fisheries management and ocean conservation worldwide (Pauly et al. 2002, Lubchenco et al. 2003, Halpern et al. 2010). No-take marine reserves protect whole communities within a defined area. This allows them to protect ecosystem processes (Boaden & Kingsford 2015), and also makes them a useful tool for investigating the impacts of fishing on marine ecosystems (Tegner 2000, Sala et al. 2012). Although not a perfect baseline, in the absence of data on marine community structure prior to the commencement of fishing, marine reserves have proven to be a beneficial tool for understanding direct extractive impacts on communities (Edgar et al. 2009, Sala et al. 2012). Marine reserves also provide an effective reference for understanding the interactions of fishing with other anthropogenic stressors (Edgar 2008).

4 In developed countries where destructive fishing practices are generally prohibited in all areas, fishing does not have the same community wide effects as reported in countries where bulk harvestings and destructive fishing methods are common (Emslie et al. 2015). Despite only a few species being directly targeted, fishing can affect the structure of the whole community by altering predator-prey and competitive interactions (Pinnegar et al. 2000, Gascuel 2005, Langlois & Ballantine 2005, Myers et al. 2007). Comparison of fish communities between marine reserves and fished areas, provides an opportunity to quantify the effect of fishing on reef fish community structure (Boaden & Kingsford 2015).

There are currently 44 marine reserves in New Zealand’s territorial sea (Molloy 2015), with rocky reefs the most commonly protected ecosystem (Thrush et al. 2011). Increases in the abundance and size of otherwise exploited fish species have been reported within New Zealand’s marine reserves, relative to adjacent fished areas (Denny 2003, Willis & Anderson 2003, Pande & Gardner 2012, Costello 2014). However, differences in the rate and magnitude of recovery of exploited populations between habitats and bioregions, when fishing is removed, highlights the need to consider the effects of fishing in the context of habitat variability (Langlois & Ballantine 2005). In addition, there is also variation in the degree to which recovery of exploited fish populations affects the non-exploited fish, invertebrate and macroalgae communities between New Zealand’s marine reserves (Babcock et al. 1999, Denny 2003, Willis & Anderson 2003, Pande & Gardner 2012, Schiel 2013).

1.4 Trophic structure of temperate reef communities Successful management of exploited fish species requires effective management of their prey resources, as fisheries production is constrained by the amount of available food resources (Minns et al. 2011, Friedland et al. 2012b). Consequently, an understanding of the trophic structure and energy flow through temperate reef communities is vital for effective management (Watson et al. 2013, Persson et al. 2014). Trophic structure refers to the feeding relationships within a community, and implies the transfer of energy from base organic matter sources to herbivores and subsequently carnivores (Krebs 2009). Each animal within the community occupies a trophic position. For this study, trophic position refers to a combination of trophic level, the average number of trophic exchanges in the food web leading up to a consumer, and the proportion of that food web supported by alternative organic matter sources.

5 Temperate rocky reef food webs are supported by organic matter derived from phytoplankton (Ware & Thomson 2005, Truong et al. 2017), benthic macroalgae (Mann 1973, Duggins et al. 1989, Koenigs et al. 2015) and in some cases detritus from terrestrial inputs (Jack et al. 2009, McLeod et al. 2010b). Macroalgae can be extremely productive (Mann 1973). It provides organic matter directly to grazing invertebrates and fish (Norderhaug et al. 2005), produces suspended particulates that are consumed by suspension feeders (Wing & Jack 2012) and produces detritus that is exported to the benthic community (Duggins et al. 1989, Krumhansl & Scheibling 2012). Although seasonally variable in its availability (Murphy et al. 2001), phytoplankton is also an important source of organic matter to temperate reefs (Abrantes et al. 2015, Truong et al. 2017).

Temperate reef food webs are energetically open (Trebilco et al. 2016), with autochthonous phytoplankton and macroalgae production (Miller et al. 2011) as well as allochthonous inputs. Allochthonous organic matter may enter the reef food web either as detritus or suspended particulate matter, by migration of consumers onto the reef, or by reef associated species foraging in adjacent habitats (Barrett 1995, Shepherd and Edgar 2013b, Hyndes et al. 2014). As a consequence, marine food webs generally encompass multiple habitats (Hyndes et al. 2014).

Identifying the sources and fate of organic matter in the temperate reef fish community, is an important step towards understanding ecosystem function. Although the sources and fate of organic matter use within temperate food webs have been investigated, there is a high degree of variability in the literature about the relative importance of the various sources to the fish community (Fredriksen 2003, Koenigs et al. 2015, Markel & Shurin 2015, von Biela et al. 2016, Truong et al. 2017). Differences may be due to the relative availability of the alternate sources (Cowen 1986, Hamilton et al. 2011, Jack & Wing 2011), or a result of a difference in the feeding strategies of the fish species present in the community (Ramírez et al. 2013, Truong et al. 2017). In order to determine how the loss of kelp forests may affect both ecosystem function and variability in fisheries production within coastal systems, it is important to ascertain the degree to which kelp is utilised as an organic matter source by the reef fish community and how this may vary with kelp abundance.

6 1.5 Study Sites New Zealand’s rocky reef communities are typical of those on other temperate coasts, with large brown algae a dominant occupier of space (Schiel & Foster 1986, Schiel 1990). This study was based in two regions on the South Island, New Zealand; Marlborough Sounds and Southern Fiordland. Both regions are characterised by extensive wave-sheltered rocky reef habitats at the entrances of the waterways, harbouring kelp forests and similar reef fish and benthic invertebrate communities (Shears & Babcock 2007, Wing & Jack 2014). The topography of Fiordland and Marlborough Sounds results in strong gradients in environmental conditions, mainly light, wave exposure and salinity, which affects the level of primary production (Miller et al. 2006, Davidson 2014). In Fiordland, the main gradient is due to the large freshwater inputs limiting light availability (Wing et al. 2007), whereas in the Marlborough Sounds the amount of bottom stress from current and wave action determines where sediment can settle, and hence there is greater settlement of fine sediments in the inner Sounds (Handley 2015, Urlich 2015). As a result the biomass of macroalgae, particularly Laminarian kelps, is an order of magnitude higher on the outer coast than in the inner fiords/sounds (Shears & Babcock 2007, Wing & Jack 2014). The environmental gradients present in these coastal waterways, presents a rare opportunity where there is sufficient replication to investigate the relative importance of consumer driven top-down versus habitat driven bottom-up controls on fish community structure. Comparison between the two regions allows for analysis of how regional differences in composition and density of kelp forests may affect reef fish food web structure.

1.5.1 Marlborough Sounds The Marlborough Sounds are located on the north-eastern coast of the South Island, New Zealand. The Marlborough Sounds are a large network of drowned river valleys, submerged by sea level rise after the last ice age 14,000 years ago (Nicol 2011). The Sounds have long been inhabited by the Māori people, and European settlers arrived in the mid to late 19th Century (Handley 2016). With the arrival of settlers, large areas of the Sounds’ catchment were cleared for timber extraction and pastoral farming. Today large areas of this land have been planted with exotic forest (mainly Pinus radiata), although some areas have been left to revert to native bush. These land use changes are thought to have impacted the coastal marine environment by increasing the sediment load to these ecosystems (Handley 2015).

7 It is estimated that the Marlborough Sounds has lost approximately 90% of its kelp forests during the past 50 years, with anecdotal accounts from long term residents all reporting a significant decline in the extent of kelp surface canopy in the Sounds during their lifetimes (Handley 2016). There is also a long history of exploitation of marine species in the Sounds, with species ranging from urchins and pilchards to sharks and whales targeted since European settlement (Handley 2016). The Kokomohua Marine Reserve was established in 1993, affording full protection to the area surrounding Long Island. In addition to the marine reserve, since 2016 commercial fishing is banned annually in the Sounds between 1st September and 20th December.

1.5.2 Fiordland The Fiordland region is located on the southwestern coast of the South Island, New Zealand, and consists of a series of deep, glacially carved fjords (Suggate 1990). Fiordland is part of the Te Wahipounamu UNESCO World Heritage Area, and has been a national park since 1904. As a consequence, the fiords have undisturbed native forests covering their catchments and the multilayered kelp forests are relatively intact (Miller et al. 2006, Wing et al. 2007, Wing & Jack 2014). Sections of the marine environment of Fiordland are protected with a network of marine reserves nested within commercial exclusion zones. In 2005 the Fiordland Marine Management Act established eight new no-take marine reserves, in addition to two reserves established in 1993, and closed the inner regions of 11 fjords to commercial fishing (Wing & Jack 2014).

1.6 Objectives The principal aims of the current thesis were to establish how reef fish community structure and food web architecture varied with the presence and density of kelp beds, and with variation in fishing pressure between the Fiordland and Marlborough Sounds regions. The objective was to establish how loss of kelp forests and exploitation of target fish species may have affected the functioning of temperate reef ecosystems, and to establish if there was any interaction between the two stressors. We investigated how reef fish community structure varied with fishing pressure and presence of kelp beds, on the local and regional scale. The importance of macroalgae as an organic matter source to the temperate reef fish community was evaluated, and the trophic structure of the fish community was compared between regions to establish if this was affected by the composition of the kelp community.

8 Further, we estimated how differences in trophic structure may have affected the stability and energetic requirements of the reef fish food web.

The data chapters, outlined below, have been written as stand-alone papers, and thus there was some double up in topics covered, particularly in the Introductions and Methods sections. Chapter 3 has already been submitted to the Journal of Aquatic Conservation and is presented here as the submitted manuscript. Chapter 4 is intended to be a follow up paper, to investigate the implications of the results presented in Chapter 3, and will be submitted to Marine Ecology Progress Series.

Chapter 2: Effect of fishing on temperate reef fish community structure in the context of habitat variability

Aim: To resolve the relative importance of the presence of kelp beds versus fishing pressure in influencing patterns in reef fish community composition and structure, and to quantify potential interactions between fish populations and kelp communities. This chapter investigated these relationships within each region and compared whether the same relationships were observed between Fiordland and the Marlborough Sounds.

Questions: 1.! What species of fish comprise the reef-associated fish community in Fiordland and the Marlborough Sounds?

2.! Which species of fish vary in abundance most strongly with fishing pressure or the presence of kelp beds? Does the presence of kelp influence the response of individual species to fishing?

3.! How does the overall density and community structure of the non-exploited and exploited fish community vary with fishing pressure and the presence of kelp beds? Are the effects of fishing consistent between the kelp and barren habitats? Does the response of the reef fish assemblage differ between regions?

9 4.! Do marine reserves have lower densities of sea urchins? How does density of sea urchins covary with density of kelp holdfasts on rocky reefs in Fiordland compared with the Marlborough Sounds?

Chapter 3: Organic matter derived from kelp supports a large proportion of biomass in temperate rocky reef fish communities: implications for ecosystem based management

Aim: To determine the trophic position of temperate rocky reef fish between Fiordland and the Marlborough Sounds. Here trophic position refers to a combination of trophic level, the average number of trophic exchanges in the food web leading up to a consumer, and the relative contribution of organic matter derived from macroalgae and phytoplankton to that food web. The objective of this chapter was to establish if the kelp community and/ or the trophic position of reef fish species varied between Fiordland and the Marlborough Sounds. Further, this chapter investigated whether the invasive kelp, Undaria pinnatifida was utilised as an organic matter source by herbivorous reef fish.

Questions: 1.! Does the composition and density of subtidal kelp beds vary between Fiordland and Marlborough?

2.! Does the trophic position of the common coastal fish species present vary between Fiordland and the Marlborough Sounds?

3.! Which macroalgae groups do herbivorous fish feed on? Do herbivorous fish utilise the invasive kelp, U. pinnatifida as an organic matter source?

4.! Does the relative contribution of organic matter derived from macroalgae on a biomass per unit area basis, in both the non-exploited and exploited reef fish communities, differ between Fiordland and the Marlborough Sounds?

10 Chapter 4: Regional differences in the energetics of two temperate reef fish communities – implications for the loss of kelp forests

Aim: To investigate how the observed differences in relative abundance (Chapter 2) and trophic structure between Fiordland and the Marlborough Sounds (Chapter 3), translates to differences in the energetic requirements of the food webs supporting reef fish communities in the two regions.

Questions: 1.! How is biomass distributed across trophic levels in the Fiordland and Marlborough fish communities?

2.! Does the proportion of cumulative fish biomass supported by macroalgae vary with trophic level? Is there a regional difference in the slope of this relationship?

3.! Is there a difference in the amount of organic matter required to support the reef fish communities between Fiordland and the Marlborough Sounds? How does the relative contribution from macroalgae and phytoplankton vary with region?

4.! How do estimates of basal organic matter used by the reef fish community fluctuate with various trophic transfer efficiencies?

CHAPTER 2:

Effect of fishing on temperate reef community structure in the context of habitat

variability

Butterfly perch surround a marblefish in Fiordland

13 2.1 Introduction Growing evidence demonstrates that fishing, as well as decreasing target species biomass, can alter the structure of entire marine ecosystems (Pinnegar et al. 2000, Gascuel 2005, Myers et al. 2007). Removal of target species by fishing can affect the relative abundance of associated species in the community by altering predator-prey and competitive interactions (Willis & Anderson 2003, Langlois & Ballantine 2005). Consequently the structure of communities is intrinsically linked with the dynamics and functioning of that community (Crowe et al. 2013), so understanding the effects of fishing on marine community composition and structure is vital for implementing effective ecosystem based management (Grigg et al. 1984, Garcia & Cochrane 2005, Pérez-Matus et al. 2017). The magnitude of a population or community’s response to fishing may be dependent on bottom-up effects such as the system’s productivity or habitat complexity (Menge & Sutherland 1987, Pace et al. 1999, Aburto-Oropeza et al. 2011). Therefore, it is imperative that habitat quality and heterogeneity be considered when analyzing the effects of fishing on community structure.

No-take marine reserves protect whole communities within a defined area, making them a useful tool for investigating the impacts of fishing on marine ecosystems (Tegner 2000). In New Zealand, the majority of marine reserves have focused on protecting coastal reef communities (Thrush et al. 2011, Schiel 2013). As many reef-associated fishes have limited home ranges, they typically respond well to spatial management (Barrett 1995), as evidenced by wide spread increases in abundance and size of otherwise exploited species within New Zealand’s marine reserves (Willis & Anderson 2003, Pande & Gardner 2012, Costello 2014). Nevertheless, the recovery of exploited species has not been consistent across all reserves. Comparisons among reserves demonstrate that the magnitude and rate of the recovery, when fishing is removed, differs among habitats and bioregions (Langlois & Ballantine 2005).

Previous studies have investigated the effects of fishing on community structure in temperate regions, generally focusing on the interactions between exploited predatory fish, invertebrate and macroalgae abundance (Babcock et al. 1999, Shears & Babcock 2002, Salomon et al. 2008). However, there have been relatively few studies focussing on how protection from fishing may affect the non-exploited fish community on temperate reefs by altering predatory and competitive interactions. On coral reefs, depletion of predatory fish in

14 areas open to fishing has been associated with higher densities of prey and herbivorous fish (Boaden & Kingsford 2015). It is likely that similar effects may be occurring on temperate reefs. For example, analysis of fish abundances in the Fiordland marine reserve network indicated that ‘forage fish’, a guild of lower trophic level planktivorous fishes, increased in abundance as the large predators declined in fished regions (Wing & Jack 2013). Cryptic reef fish abundance is also positively affected by a decline in predatory fish abundance (Willis & Anderson 2003).

Temperate reef fish assemblages, like most communities, are influenced by the habitats that support them (Holbrook et al. 1990, Carr 1991, De Troch et al. 1996). On temperate reefs, the presence of kelp has a dominant influence on the composition of reef fish assemblages, with distinct fish communities associated with kelp beds versus barren rocky reef habitats (Choat & Ayling 1987, Jones 1988, Anderson & Millar 2004, Pérez-Matus & Shima 2010). Association of reef fish with kelp beds is thought to be related to a combination of the increased availability of food and the refuge from potential predators that the complex structure provides (Steneck et al. 2003, Graham et al. 2007).

The trophic interactions between temperate reef species have been observed to vary along environmental gradients (Shears et al. 2008, Perez-Matus et al. 2017). Therefore it is imperative that the effects of fishing on community structure be considered across the natural variability in habitat types found along environmental gradients. Variation in the complexity of multi-layered kelp beds can influence predator-prey interactions by offering refuge to prey (Crowder & Cooper 1982, Heck 1991, Rangeley & Kramer 1998) or camouflage to predators (Hobson & Chess 2001). Hence, changes in the reef fish community structure associated with removal of predators may vary depending on the structure and complexity of kelp bed habitat. Habitat variability may also affect the degree to which exploited populations are impacted by fishing or their rate and amount of recovery when fishing pressure is removed or reduced (Aburto-Oropeza et al. 2011, Perez-Matus et al. 2017). Clearly the effects of fishing must be considered in the context of natural variability in order to resolve ecosystem level effects of fishing (Shears et al. 2008, Jack & Wing 2013, Wing & Jack 2014). Nevertheless, only a few studies have included resolution of important environmental variation when comparing fished and non-fished marine communities associated with spatial management (Chapman & Kramer 1999, McClanahan & Arthur 2001, Stewart-Oaten & Bence 2001).

15 In addition to the presence of kelp beds influencing fish assemblages, changes in the fish community may simultaneously modify the kelp community. Marine reserves can have positive effects on kelp forest communities through trophic cascades whereby larger and more abundant top predators consume herbivorous sea urchins regulating population density and leading to positive effects on kelp growth (Babcock et al. 1999, Murray et al. 1999, Halpern & Warner 2002, Shears & Babcock 2002, Lubchenco et al. 2003, Shears & Babcock 2003, Lester et al. 2009, Leleu et al. 2012). In this case a positive feedback may occur where abundant kelp growth and habitat provision can enhance recruitment into fish populations (Choat 1982, Jones 1988). The potential for such strong interactions in kelp forest communities is context dependent (Shears et al. 2012). For example, trophic cascades may not be as prevalent in southern New Zealand where sea urchins are generally less abundant, relative to northern New Zealand where they can dominate space in many rocky reef communities (Fowler-Walker & Connell 2002, Shears & Babcock 2007, Schiel 2013).

The present study focussed on resolving the relative importance of natural patterns in composition of habitats versus fishing pressure in influencing patterns in reef fish community composition and structure, as well as quantifying potential interactions between fish populations and kelp communities. These relationships were investigated in two coastal waterway systems on the South Island, New Zealand: Marlborough Sounds and Southern Fiordland. Both regions are characterised by extensive wave-sheltered rocky reef habitats at the entrances of the sounds, harbouring kelp forests with similar reef fish and benthic invertebrate communities (Shears & Babcock 2007, Wing & Jack 2014).

2.1.1 Research Questions

1.! What species of fish comprise the reef-associated fish community in Fiordland and the Marlborough Sounds?

2.! Which species of fish vary in abundance most strongly with fishing pressure or the presence of kelp beds? Does the presence of kelp influence the response of individual species to fishing?

4.! Do marine reserves have lower densities of sea urchins? How does density of sea urchins covary with density of kelp holdfasts on rocky reefs in Fiordland compared with the Marlborough Sounds?

2.2 Methods

2.2.1 Study sites In order to compare the effects of fishing and presence of kelp forest habitat, our study sites were stratified in a factorial design among exposed (generally higher kelp density) and sheltered sites (generally lower kelp density) and within fished and non-fished (marine reserve) areas within each region (Figure 2.1).

Diving surveys in the Marlborough Sounds were conducted during January 2017 (8 sites) and February 2018 (4 sites) from the RV Polaris II. In the Sounds, our twelve sites were distributed around the Kokomohua Marine Reserve, established in 1993. Sites were chosen using data and charts from reports on macroalgae assemblages (Shears & Babcock 2007) to guide our orthogonal distribution of sampling. The control ‘fished’ sites used in this study were also partially managed to reduce fishing effort, with the Sounds being closed to commercial fishing from 1st September till 20th December each year, and reduced recreational take limits for blue cod within the Marlborough Sounds (MPI 2018a).

Figure 2.1. Map showing the location of survey sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand. Symbols within each region represent sites in marine reserves (triangles) and fished areas (circles). Shading in each figure represent kelp bed sites (black) or barren areas (grey).

Diving surveys in Fiordland were conducted during November 2015 (11 sites) and May 2017 (7 sites) from the RV Polaris II and RV Typhoon. In order to sample exposed and sheltered sites within both fished and unfished areas, study sites in Fiordland were spread throughout the network of reserves in the southern Fiordland Marine Area. Site selection in Fiordland was based on kelp density data from previous monitoring reports (Wing & Jack

18 2014), and information on habitat types (Wing et al. 2007b). The Fiordland network of marine reserves was established in 2005, though the Te Awaatu Channel reserve in Doubtful Sound has been established since 1993. The inner waters of Fiordland were closed to commercial fishing in 2005, and further recreational restrictions are in place for some target species in particular fjords (MPI 2018a). Here we group sites as ‘fished’ or ‘reserve’ based on whether they are located within a no-take marine reserve or elsewhere, as fishing effects are still observed between commercial exclusion zones and no take marine reserves (Wing & Jack 2013).

2.2.2 Surveys of reef fish, invertebrate and kelp density Non-cryptic reef fish species were enumerated at each site by divers using SCUBA along multiple belt transects (50 m long by 5 m wide by 2.5 m high). Transects were kept short (50m) to increase replication and consequently increase power and precision (Samoilys & Carlos 2000). Transects were centered at 5 and 15 m depths. In cases where the bottom of the reef was shallower than 15 m the deep transect was centred just above the bottom of the reef. Four independent replicate transects were surveyed at each depth for each site. At some sites only three replicate transects were completed if the dive team had exhausted their air supply. The composition of diver teams identifying and counting fishes was kept constant between sites and regions for the duration of the study.

At each site, before each dive survey, concentration of phytoplankton and water column structure were measured using a SeaBird SBE 25 conductivity, temperature and depth profiler (CTD) with an attached Wetstar fluorometer used to estimate concentration of Chl a (mg/m3). In order to characterise the density and species composition of the kelp and invertebrate community at each site 2 m2 quadrats were randomly placed along the belt transects described above, to achieve 5-10 quadrats per depth stratum (<5 m, 10-15 m). The density of errant invertebrate species and the number of holdfasts of each kelp species was recorded. The kelp species observed during the surveys were, Lessonia variegata, Ecklonia radiata, Cystophora spp., Carpophyllum maschalocarpum, Carpophyllum flexuosum, Marginariella urvilliana, Sargassum sinclairii, Undaria pinnatifida and Macrocystis pyrifera.

Figure 2.2. Frequency of site averages for kelp holdfast density (2m-2).

As the presence or absence of large stipitate or canopy forming kelp, rather than the species identity, is correlated most strongly with temperate reef fish assemblage structure (Pérez-Matus & Shima 2010), we grouped kelp species together for our analysis of the coincidence of kelp beds with fish density. Further, because the distribution of the average number of holdfasts was too varied to use as a continuous variable in the models we classed sites as ‘kelp bed’ or ‘barren’ habitats. If the average kelp density for a site was greater than 1 holdfast per 2m2, the site was classed as a ‘kelp bed’. This threshold fit well with the distribution of holdfast densities (Figure 2.2). Although some sites classed as ‘barren’ had a few scattered holdfasts, we concluded that an average kelp density below 1 holdfast per 2m2 is likely to have negligible effects on fish responses compared to a site with no kelp holdfasts (Holbrook et al. 1990a).

20 2.2.3. Statistical analysis Drivers of reef fish abundance Like many data sets comprising discrete counts from ecological studies, our survey data on fish density per transect were zero inflated and the distribution of counts differed between the different explanatory variables. Hence the assumptions of normality of data distributions for generalised linear models were not met. To overcome this, we used generalised linear style models run in the Generalised Additive Models for Location, Scale and Shape (GAMLSS) package in R to test for potential drivers of species density. GAMLSS is based on regression type models, and allows for the simultaneous modelling of all distribution parameters (Stasinopoulos & Rigby 2007). Models are still fitted using maximum likelihood, but GAMLSS allows for distributions that are not in the exponential family. Models for all species were run using the zero-adjusted inverse Gaussian distribution family.

A key feature of the GAMLSS models is the separation of fish counts into the mean of the non-zeros (Mu), the scale parameter (Sigma) and the probability of zero (Nu) (Hernandez et al. 2009). This overcomes the issue of zero-inflation, and allows the factors associated with each component of fish density to be identified. The Mu co-efficient enabled us to calculate the ratio effect of each factor (e.g. mean of non-zeros (fished)/ mean of non- zeros (reserve)), and the Nu co-efficient enabled calculation of the odds ratio of the covariability of each factor with presence or absence of each species.

We used GAMLSS models to test how a series of environmental factors within the two different regions covaried with density for the most commonly observed fish species, blue cod (Parapercis colias), tarakihi (Nemadactylus macropterus), blue moki (Latridopsis ciliaris), spotty (Notolabrus celidotus), banded wrasse (Notolabrus fucicola), scarlett wrasse (Pseudolabrus miles) and butterfly perch (Caesioperca lepidoptera). To determine which factors best statistically explained the mean densities of fish, we compared different models using the generalised Akaike information criterion (GAIC). The initial models included SITE

(random), REGION (2 levels, fixed), FISHING (2 levels, fixed), KELP (2 levels, fixed), average 3 Chl a (mg/m ) concentration (continuous) and average INVERTEBRATE density (continuous).

The region interaction with KELP and FISHING was significant for most species, and thus in order to investigate the effect of FISHING and KELP within each region, we separated data for the two regions and ran models for each independently.

21 Within each region removing SITE improved GAIC, indicating that the variation among sites was small relative to that explained by other factors. The average Chl a (mg/m3) concentration and INVERTEBRATE density at each site did not significantly covary with the density of any fish species, and thus these factors were also removed from the models. The final models used to test for explanatory factors for species density included FISHING (2 levels, fixed), KELP (2 levels, fixed) and their interaction. Further GAIC testing was used to determine whether FISHING, KELP or both factors best statistically explained the Mu (mean of non-zeros) and nu (probability of zero) distributions of each species. These tests were done on each species independently and hence the effect of FISHING and KELP on the Nu parameter, probability of zero, was only calculated for species were each factor had an effect on the proportion of zeros observed. Residuals were plotted for each model to check that the assumptions of each model were valid. Where the interaction between FISHING and KELP was significant we calculated overall means for each group to interpret the interaction. In this case the co-efficients from the GAMLSS models were used to calculate predicted mean densities for each group. Predicted means are the GAMLSS equivalent of least squares means, and combine the different parameters (Mu, Sigma and Nu) into an overall mean. In order to obtain 95 % confidence intervals for the overall means of each group we used bootstrapping.

To summarise the individual species responses, we summed the abundance of all species observed on each transect to calculate total non-exploited and exploited density. Butterfish (Odax pullus), sea perch (Helicolenus percoides), red cod (Pseudophycis bachus), trumpeter (Latris lineata), tarakihi, red moki (Cheilodactylus spectabilis), copper moki (Latridopsis forsteri), kahawai (Arripis trutta), blue cod, blue moki and leatherjacket (Parika scaber) were the only exploited species observed on the transects in both regions. All other species observed were classed as non-exploited (Table 2.1). We then used GAMLSS models as described above to test for effects of the factors FISHING, KELP and REGION on the non- exploited and exploited density. Predict means were calculated for each group of factors using GAMLSS model parameters and 95 % confidence intervals for the overall means of each group were calculated using bootstrapping. Here significant differences between groups are inferred from the 95 % confidence intervals.

22 Effect of FISHING and KELP on fish community assemblages To test for differences in community composition and structure (non-exploited and exploited) between regions, habitat types and fishing zones we used the fish count data to construct resemblance matrices using the Bray Curtis similarity index. We constructed resemblance matrices based on both relative abundance data, indicating differences in community structure, and presence absence data indicating differences in community composition, to be able to distinguish whether observed assemblage differences were associated with species loss or from changes in relative abundance (Jack & Wing 2013).

Differences in community structure and composition were tested among the factors REGION,

FISHING and KELP using permutational multivariate analysis of variance (PERMANOVA, Primer-e version 6). PERMANOVA tests are robust to deviations from a normal distribution of data by being permutation based to recreate the underlying distribution in the sample data.

We initially tested for differences in community structure and composition using all data with main factors: REGION, FISHING and KELP and all interactions. Due to significant

REGION interactions with FISHING and KELP (Table 2.4), we also separated the regions and ran independent tests with FISHING and KELP and their interaction to be able to investigate the importance of these factors within each region. We used principle coordinates analysis (PERMANOVA+, Primer-e version 6) to visually compare the differences between each site average within each region.

Effect of FISHING on Evechinus chloroticus and kelp density

Here we use GAMLSS models, run in R, to test for effects of FISHING (2 levels, fixed) and SITE (random, Fiordland: 18 levels, Marlborough: 12 levels) on Evechinus chloroticus and kelp holdfast density in Fiordland and the Marlborough Sounds. E. chloroticus was the only sea urchin species encountered in our study.

2.3 Results Fiordland had higher fish species richness than the Marlborough Sounds, with 20 fish species observed in Fiordland compared to 13 in the Marlborough Sounds (Table 2.1). The most common species were present in both regions, however regional differences occurred in the presence of some of the less common species, as well as the frequency at which species occurred (Table 2.1).

23 2.3.1 Effect of FISHING and KELP on fish density

Density of individual species covaried with both FISHING and KELP, with large variation among species in the magnitude and direction of their response to each factor. In

contrast, the direction of the effect of FISHING and KELP was generally the same within a species between the two different regions, with interspecific regional differences in the effect sizes observed (Figure 2.3, 2.4).

Table 2.1. Frequency of occurrence of species on transects in Fiordland and the Marlborough Sounds. Exploited species indicated by e. Species ordered by frequency of observation across both regions.

Common Name Scientific Name Fiordland Marlborough Sounds

Spotty Notolabrus celidotus 71.9 % 97.4 %

Blue Cod e Parapercis colias 64.9 % 80.5 %

Scarlett Wrasse Pseudolabrus miles 75.4 % 24.7 %

Butterfly perch Caesioperca lepidoptera 72.8 % 11.7 %

Banded Wrasse Notolabrus fucicola 44.7 % 46.8 %

Tarakihi e Nemadactylus macropterus 28.1 % 16.9 %

Marblefish Aplodactylus arctidens 26.3 % 3.9 %

Blue Moki e Latridopsis ciliaris 7.0 % 29.9 %

Girdled Wrasse Notolabrus cinctus 27.2 %

Sea Perch e Helicolenus percoides 21.9 %

Leatherjacket e Parika scaber 15.8 % 5.2 %

Telescope Fish Mendosoma lineatum 12.2 %

Red Banded Perch Hypoplectrodes huntii 11.4 %

Butterfish e Odax pullus 5.3 % 11.7 %

Splendid Perch Callanthias allporti 5.3 %

Red Lined Perch Lepidoperca tasmanica 4.4 %

Trumpeter Latris lineata 4.4 %

Cm Roughy Paratrachichthys trailli 3.5 %

Yellow eyed mullet Aldrichetta forsteri 2.5 %

Red Cod e Lotella rhacinus 2.6 %

Red Moki e Cheilodactylus spectabilis 5.2 %

Copper Moki e Latridopsis forsteri 1.7 %

Kahawai e Arripis trutta 2.6 % !

Figure 2.3. Effect size of FISHING on a) mean density when the species is present (Mu parameter) and b) the probability of the species not being present on a transect (Nu parameter), for the most common reef fish species in Marlborough Sounds (black circles) and Fiordland (open circles). The two regional effects for each species are connected by a line. Effect sizes are calculated from GAMLSS models run separately for each species. Error bars are 95% confidence intervals for the effect, if bars do not intersect 1 than effect is significant.

Figure 2.4. Effect size of KELP on a) mean density when species are present (Mu parameter) and b) the probability of the species not being present on a transect (Nu parameter), for the most common reef fish species in Marlborough Sounds (black circles) and Fiordland (open circles). The two regional effects for each species are connected by a line. Effect sizes calculated from GAMLSS models run separately for each species. Error bars are 95% confidence intervals for the effect, if bars do not intersect 1 than effect is significant.

26 Blue cod was the only exploited species that consistently benefited from reserve protection, with a higher probability of being present within reserves in both regions (Marlborough Sounds, p = 0.048: Fiordland, p = 0.007). In addition, when present, blue cod occurred at 2.02 times greater density within reserves than in fished areas in the Marlborough Sounds (p = 0.019) (Figure 2.3, Table 2.2, 2.3). Therefore, there was a dramatically larger total effect size of FISHING on blue cod occurrence and density in the Marlborough Sounds than in Fiordland (Figure 2.3, Figure 2.5). In addition, for blue cod density when present, there was a significant interaction between FISHING and KELP for the Marlborough Sounds (p = 0.02) (Table 2.2a), with the largest fishing effect observed in barren habitats (Figure 2.5). Blue cod were most commonly observed at barren sites in the Marlborough Sounds (p <

0.001) (Table 2.2b), though there was no effect of the factor KELP in Fiordland (Table 2.3).

Fiordland Marlborough Sounds

20 ) 2 −

m Fishing FISHED RESERVE Density (250

0 Barren Kelp bed Barren Kelp bed

Figure 2.5. Overall mean blue cod density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat. Predict means are calculated from GAMLSS models, and 95% confidence intervals are from bootstrapping to combine effect parameters.

27 Tarakihi were found at higher densities in marine reserves in Fiordland, with a higher chance of being present in reserves (p = 0.016), and a higher mean abundance when present in reserves (p < 0.001) (Table 2.3). In the Marlborough Sounds however, when present, tarakihi occurred in greater abundances in fished areas (p < 0.001), and there was no effect of

FISHING on probability of being present (Figure 2.3, Table 2.2). There was greater variance among observed tarakihi densities in the Marlborough Sounds than Fiordland (Figure 2.3 a, 2.4 a). Blue moki had greater abundances when present in kelp beds in Fiordland (p = 0.022) (Figure 2.4). Blue moki showed a negative response to reserve protection in Fiordland, when present they were in greater abundance in fished areas (p = 0.046) (Figure 2.3, Table 2.3a).

In Fiordland spotties were present most often in reserves (p < 0.001), and when present had higher abundances in reserves (p < 0.001) (Figure 2.3, Table 2.3). Spotties were most abundant in barren habitat in both regions. In Fiordland, the difference was due to a higher chance of being present in barren habitat (p = 0.006), whereas in Marlborough they were present in greater densities in the barren habitat (p = 0.006) (Figure 2.4, Table 2.2a,

2.3b). In Fiordland, there was a significant interaction between FISHING and KELP (p = 0.003) for explaining the proportion of transects on which spotties were observed (Table 2.3 b).

There was no effect of FISHING on density of spotties in the Marlborough Sounds.

The factor KELP explained a larger amount of variation in banded wrasse density than the factor FISHING (Figure 2.3, Figure 2.4). Banded wrasse, when present, had a higher abundance in kelp beds (p = 0.022) and a higher probability of being present in kelp beds (p = 0.002) in Fiordland (Table 2.3). In the Marlborough Sounds, there was a trend towards banded wrasse being present most frequently in kelp beds (p = 0.077) (Figure 2.4, Table 2.2b). In Fiordland, banded wrasse were observed most frequently in fished areas (p = 0.033) (Table 2.3a). In the Marlborough Sounds scarlett wrasse tended to be present most frequently in fished areas (p = 0.053) (Table 2.2a). Butterfly perch were the only non-exploited species that showed a negative response to reserve protection in both regions. The proportion of transects on which butterfly perch were observed was highest in fished areas in both regions (Marlborough, p = 0.041: Fiordland, p = 0.037), and in the Marlborough Sounds where they were present they occurred in higher abundance in fished areas (p = 0.002) (Table 2.2, 2.3a). Butterfly perch were observed most frequently in kelp beds in the Marlborough Sounds (p = 0.041) (Figure 2.4, Table 2.2b).

28 Table 2.2. Results from GAMLSS models run on individual species for the Marlborough Sounds for the a) Mu parameter (Mean of the non-zeros) and b) Nu parameter (probability of zero). Degrees of freedom are the degrees of freedom required for the model fit and the residual degrees of freedom. Asterisks indicate significance of factors (p < 0.001 ***, p < 0.01 **, p < 0.05 *, p < 0.1 . ) a)! Mu parameter FISHING KELP F x K df t p t p t p Blue Cod 12,65 2.4 0.019 * 1.86 0.068 . 2.36 0.022 * Tarakihi 8,69 -4.03 <0.001 *** -5.54 <0.001 *** 3.79 <0.001 *** Blue Moki 8,69 0.20 0.844 1.52 0.133 -0.33 0.745 Spotty 8,69 0.41 0.686 2.83 0.006 ** -0.17 0.867 Banded Wrasse 8,69 -0.03 0.978 -1.38 0.173 0.26 0.793 Scarlett Wrasse 10,67 0.39 0.699 0.20 0.840 0.00 0.999 Butterfly Perch 10,67 -3.27 0.002 ** -0.09 0.929 0.00 0.999

b)! Nu parameter FISHING KELP F x K df t p t p t p Blue Cod 12,65 -2.01 0.048 * -2.01 0.048 * -0.09 0.929 Tarakihi 8,69 1.53 0.129 Blue Moki 8,69 1.79 0.077 . Spotty 8,69 -0.09 0.93 Banded Wrasse 8,69 4.03 <0.001 *** Scarlett Wrasse 10,67 1.96 0.053 . 1.63 0.107 0.16 0.929 Butterfly Perch 10,67 2.08 0.041 * 2.08 0.041 * 0.08 0.937 ! !

Table 2.3. Results from GAMLSS models run on individual species from Fiordland for the a) Mu parameter (Mean of the non-zeros) and b) Nu parameter (probability of zero). Degrees of freedom are the degrees of freedom required for the model fit and the residual degrees of freedom. Asterisks indicate significance of factors (p < 0.001 ***, p < 0.01 **, p < 0.05 *, p < 0.1 .) a)! Mu parameter FISHING KELP F x K df t p t p t p

Blue Cod 12,102 -0.65 0.519 -1.33 0.185 1.85 0.067 . Tarakihi 10,104 4.30 <0.001 *** 0.87 0.384 -2.25 0.026 * Blue Moki 8,106 -2.01 0.046 * -2.31 0.022 * 0.00 0.990 Spotty 10,104 3.51 <0.001 *** 1.20 0.233 -0.64 0.521 Banded Wrasse 10,104 -1.57 0.120 -2.04 0.044 * 0.06 0.956 Scarlett Wrasse 10,104 -0.92 0.360 -0.45 0.652 -1.95 0.054 . Butterfly Perch 10,104 0.68 0.496 -0.03 0.977 -1.23 0.221

b)! Nu parameter FISHING KELP F x K df t p t p t p Blue Cod 12,102 -2.89 0.007 ** -0.39 0.701 1.34 0.183 Tarakihi 10,104 -2.44 0.016 * -0.69 0.491 2.36 0.019 * Blue Moki 8,106 1.37 0.175 Spotty 10,104 -3.67 <0.001 *** -2.80 0.006 * 3.03 0.003 * Banded Wrasse 10,104 2.16 0.033 * 3.15 0.002 * 0.86 0.392 Scarlett Wrasse 10,104 0.09 0.925 0.10 0.921 -0.08 0.937 Butterfly Perch 10,104 2.11 0.037 * 0.00 1.000 1.73 0.087 .

29 Fiordland Marlborough Sounds

200

150 ) 2

m Fishing FISHED 100 RESERVE

Density (250

Barren Kelp bed Barren Kelp bed

Figure 2.6. Overall mean non-exploited fish density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat. Predict means are calculated from GAMLSS models, and 95% confidence intervals are from bootstrapping to combine effect parameters.

Fiordland Marlborough Sounds 60

) 2 − m Fishing FISHED RESERVE

Density (250

Barren Kelp bed Barren Kelp bed

Figure 2.7. Overall mean exploited fish density in Fiordland and Marlborough for the fished (red) and reserve (blue) transects within kelp bed and barren habitat. Predict means are calculated from GAMLSS models, and 95% confidence intervals are from bootstrapping to combine effect parameters

30 The response of the total density of the non-exploited fish species, was mainly explained by the factor KELP, though the direction of the response differed between regions (Figure 2.6). In Fiordland, the highest densities of non-exploited species were observed in kelp beds, whereas in Marlborough the highest densities were found in barren areas. Fiordland had much higher density of non-exploited species, compared to the densities observed in the Marlborough Sounds, particularly in kelp bed habitat. We observed no significant effect of the factor FISHING on non-exploited fish density (Figure 2.6).

In barren areas, there was significantly lower exploited reef fish density in fished areas for both regions, with the magnitude of the FISHING effect greater in the Marlborough

Sounds (Figure 2.7). On reefs with kelp beds FISHING did not significantly explain differences in exploited density in either region (Figure 2.7).

2.3.2 Differences in community composition and structure PERMANOVA analysis revealed that the influence of fishing pressure and habitat type on the exploited and non-exploited fish communities likely differed between regions, as evidenced by significant REGION interactions with both KELP (Exploited, p = 0.003: Non-

Exploited, p < 0.001) and FISHING (Exploited, p = 0.029: Non-Exploited, p = 0.011) (Table

2.4). Although there were regional differences in the effect of FISHING in terms of relative abundance, or community structure, FISHING affected the exploited and non-exploited community in terms of community composition comparably between regions (Table 2.4).

There were significant effects of FISHING on the community composition of non- exploited and exploited fish assemblages within each region (Table 2.5). We observed differences in the composition of the non-exploited community between kelp bed and barren habitats in both regions, however habitat type was only associated with differences in the exploited community in the Marlborough Sounds (Table 2.5). In Fiordland, there was a significant interaction between the factors KELP and FISHING for the non-exploited and exploited communities, mainly attributable to differences in community composition (Table

2.5). However, in the Marlborough Sounds, the only interaction between KELP and FISHING was for the relative abundance of exploited species, or community structure (Table 2.5).

31 Table 2.4. Results of PERMANOVA analysis on Bray Curtis for relative abundance (RA) and presence absence (PA), for the non-exploited and exploited fish community in Marlborough Sounds and Fiordland. F statistics reported are pseudo-F generated by permutation. Significant (p < 0.05) p values are in bold.

REGION KELP FISHING RE x KE RE x FI KE x FI RE x KE x FI

F 1,183 p F 1,183 p F 1,183 p F 1,183 p F 1,183 p F 1,183 p F 1,183 p Non- RA 60.7 <0.001 16.81 <0.001 14.69 <0.001 8.24 <0.001 3.82 0.011 0.82 0.499 3.97 0.007 Exploited PA 68.33 <0.001 33.96 <0.001 20.28 <0.001 negative - 2.13 0.114 0.18 0.851 4.78 0.010

Exploited RA 11.54 <0.001 5.05 0.001 7.37 <0.001 4.11 0.003 2.67 0.029 3.92 0.005 2.09 0.071 PA 10.07 <0.001 4.72 0.004 6.51 <0.001 2.97 0.031 0.42 0.763 1.88 0.122 1.29 0.267

KELP FISHING FISHING x KELP Pseudo – F p Pseudo – F p Pseudo – F p Non Marlborough RA F1,73 = 12.55 <0.001 F1,73 = 3.85 0.007 F1,73 = 0.78 0.557 Exploited Sounds PA F1,73 = 12.82 <0.001 F1,73 = 6.22 0.002 F1,73 = 1.71 0.169

Fiordland RA F1,110 = 14.60 <0.001 F1,110 = 15.21 <0.001 F1,110 = 4.11 0.003

PA F1,110 = 21.29 <0.001 F1,110 = 17.39 <0.001 F1,110 = 3.49 0.025

Exploited Marlborough RA F1,73 = 7.94 <0.001 F1,73 = 8.29 <0.001 F1,73 = 3.50 0.007 Sounds PA F1,73 = 6.37 0.001 F1,73 = 4.68 0.005 F1,73 = 0.13 0.916

Fiordland RA F1,110 = 2.13 0.071 F1,110 = 2.71 0.033 F1,110 = 2.96 0.027

PA F1,110 = 2.15 0.087 F1,110 = 2.88 0.040 F1,110 = 3.11 0.029

32 A) B)

C) D)

Figure 2.8. PCO analysis of site averages based on resemblance matrices constructed using Bray Curtis similarity index on relative abundance data for the A) non-exploited fish community in Fiordland, B) non-exploited fish community in Marlborough, C) exploited fish community in Fiordland and D) exploited fish community in Marlborough. For fished (open shape, grey lines) and reserve (black shape, black lines) communities at kelp bed sites (triangles, solid lines) and barren sites (circles, dashed lines).

33 PCO analysis suggests that non-exploited communities group together primarily based on presence of kelp (Figure 2.8 a,b). In the Marlborough Sounds, the exploited community appears to group together based on whether it is fished or not, whereas in Fiordland there is no strong grouping, likely a result of the significant interaction between the factors KELP and

FISHING (Figure 2.8 c,d).

2.3.3 Effect of FISHING on Evechinus chloroticus and kelp density E. chloroticus density, when present, was significantly higher in fished areas in Fiordland (t = -3.951, p < 0.001) and the Marlborough Sounds (t = -2.168, p = 0.032) (Figure 2.9). In Fiordland, there was also a trend towards a lower probability of E. chloroticus being absent in fished areas (t = 1.935, p = 0.054) (Figure 2.9).

In Fiordland, there was no effect of the factor FISHING on density of kelp holdfasts, when kelp was present. However, in the Marlborough Sounds, when kelp is present, the mean holdfast density is higher in reserves than fished areas (t = 9.132, p < 0.001) (Figure 2.10).

There was no effect of the factor FISHING on the proportion of barren quadrats in either region (Figure 2.10).

2.4 Discussion The results from the present observational study suggest that temperate reef fish communities are shaped by a combination of natural habitat variability and by human exploitation of targeted fish species. Accordingly, FISHING was found to significantly decrease the density of exploited fish species in both regions. As FISHING significantly impacted the density of some non-exploited fish species and the structure of the non- exploited fish assemblage, it is likely that removal of large bodied predatory species such as blue cod in the exploited species group altered patterns of predation and competition within the temperate reef ecosystem. Variation in individual species density and in the exploited and non-exploited fish assemblages was predominantly explained by the factor KELP, with the effect of the factor FISHING in some cases influenced by the presence or absence of kelp.

The factor FISHING helped statistically explain variation in E. chloroticus density in both regions, and variation in kelp density in the Marlborough Sounds. The results found here are consistent with a strong interaction between kelp and sea urchin density at the site level.

34 Figure 2.9. a) Mean density of Evechinus chloroticus for the quadrats where E. chloroticus are present ±"1"$% and b) the proportion of quadrats where E. chloroticus are absent, for fished (grey bars) and reserve (black bars) areas. Significance (p < 0.05) is indicated by asterisks as determined from GAMLSS model.

Figure 2.10. a) Mean density of holdfasts for the quadrats where kelp is present ±"1"$% and b) the proportion of barren quadrats, for fished (grey bars) and reserve (black bars) areas. Significance (p < 0.05) is indicated by asterisks as determined from GAMLSS model.

35 2.4.1 Effect of FISHING The density of exploited fish was highest within marine reserves, although not all exploited species were found at higher densities in marine reserves. We observed higher blue cod density inside reserves in both regions, consistent with observations of their response at other reserves in New Zealand (Willis & Anderson 2003, Pande & Gardner 2012). Blue cod are the primary target species of recreational fishers in southern New Zealand and are also part of a large commercial fishery (MPI 2018b). This finding corroborates the findings of similar studies that concluded the most heavily exploited species are the most likely to respond rapidly to a reduction in fishing pressure (Nardi et al. 2004, Edgar & Barrett 2012). Alternatively, the strong response of blue cod to reserve protection may be associated with their life history. Tagging experiments indicate that blue cod move very little and have high site fidelity (Cole et al. 2000, Mace & Johnston 2010). The limited home range of blue cod makes them vulnerable to exploitation but also means their population density responds particularly well to spatial management (Dugan & Davis 1993).

It is likely that fishing does decrease the density of blue moki and tarakihi populations, although the scale of our study was not appropriate to quantify the regional effect (West et al. 2009). Tarakihi were found to be present in higher densities within reserves in Fiordland, yet in Marlborough they occurred in higher densities in fished areas. Tarakihi often form large schools of young fish (Francis 2001, Davidson 2014), and thus a few sightings of large schools would skew the mean density, potentially explaining the varied response to fishing observed between regions. We observed several of these large schools in the Marlborough Sounds, whereas most of the tarakihi encountered in Fiordland were solitary or small groups of larger individuals as evidenced by the greater variance in tarakihi density in Marlborough. Blue moki and tarakihi are only part time reef dwellers, often occurring over sand or mud and undertaking annual migrations up to 500km (Francis 2001). These ranges are greater than the spatial area protected by no-take marine reserves, potentially influencing the weak response of their populations to reserve protection relative to obligate reef dwellers with small home ranges (Dugan & Davis 1993).

In association with the higher abundance of blue cod inside reserves, we find significantly lower densities of some non-exploited species within reserves. Decreased non- exploited density is often associated with increased predation pressure inside reserves, though these observations come mainly from coral reef communities (Boaden & Kingsford 2015).

36 On temperate reefs, predator prey interactions may affect juveniles of larger non-exploited species, smaller ‘forage fish’ such as butterfly perch (Wing & Jack 2013) as well as the cryptic fish community (Willis & Anderson 2003). However, on temperate reefs, many non- target species, such as banded wrasse and scarlett wrasse, occupy similar trophic levels to the exploited species (Denny & Schiel 2001, Russell 2010). As these species were more frequently observed in fished areas, it is likely that fishing may also be affecting interspecific competition for food and space (Denny 2003). In Fiordland, spotties occurred at higher densities inside reserves, indicating that reserve protection may also positively affect some non-target species.

Reserves have been shown to have positive effects on the density of exploited species (Mosqueira et al. 2000, Cote et al. 2001, Willis & Anderson 2003), however, their effects on the non-exploited community are more variable (Jennings & Polunin 1997, Micheli et al. 2004, Boaden & Kingsford 2015). Even within New Zealand, the non-exploited community displays intraspecific differences in their response to reserve protection among different reserves (Denny 2003, Willis & Anderson 2003, Pande & Gardner 2012). These differences highlight the need for further investigation into how fishing may be affecting the structure of the reef fish community and the implications for this in terms of ecosystem function. The results presented here stress the importance of considering species specific responses. Although we found individual species and the structure of the non-exploited assemblage to be affected by the factor FISHING, the overall density of non-exploited fish was not significantly affected by FISHING. Grouping the fish community into predefined units may hide responses of individual species (Jennings et al. 1995, Jennings & Polunin 1997), and thus mask small differences in interspecific interactions caused by fishing that may affect aspects of ecosystem function.

2.4.2 Effect of KELP In agreement with other studies (e.g. Choat & Ayling 1987, Holbrook et al. 1990a, Levin & Hay 1996), we found that the assemblage of non-exploited and exploited fish communities is affected by the presence of kelp on the reef. The non-exploited species: banded wrasse, scarlett wrasse and butterfly perch, were more frequently observed in kelp bed habitat. We also found a higher species richness of fish present within kelp bed habitat. Kelp provides refuge from predators and is often associated with increased food availability

37 (Steneck et al. 2003, Graham et al. 2007, Pérez-Matus & Shima 2010), hence macroalgae dominated reefs often support higher numbers of small fishes (Choat & Ayling 1987). We observe this pattern in Fiordland, where the non-exploited density is highest at sites within kelp beds.

Spotties however were most abundant and present most often in barren areas. Although spotties utilise kelp bed habitat for predator protection as juveniles (Jones 1984), the adults are most often found in areas without kelp (Pérez-Matus & Shima 2010, Davis & Wing 2012). This is likely driven by the distribution of their food (Jones 1984, Anderson & Millar 2004) and may be the result of niche partitioning with other wrasses (Davis & Wing 2012). Blue cod were also observed most frequently at barren sites, in the Marlborough Sounds. Based on studies from northern New Zealand, this has been hypothesised to be associated with the higher density of urchins and therefore food in barren habitat (Choat & Ayling 1987, Anderson & Millar 2004).

2.4.3 Interaction of FISHING effect with KELP

We found significant interactions between the effect of FISHING and KELP for the assemblage of the exploited community for both regions, indicating that the presence of kelp influences the observed effects of fishing. For blue cod, the most abundant exploited species, the effect of fishing was dependent on habitat, with a larger difference between the density at reserve and fished sites in barren areas. As barren areas are the preferred habitat of blue cod (Choat & Ayling 1987, Anderson & Millar 2004) this may be a result of these habitats being targeted by fishers. Alternatively, the larger effect of fishing in barren areas may be related to the lower productivity of these areas reducing the resilience and productivity of fished populations (Aburto-Oropeza et al. 2011).

In Fiordland, the explanatory power of the factor FISHING on the non-exploited community assemblage was also dependent on the presence of kelp, with spotties, butterfly perch and scarlett wrasse all displaying some interaction between the factors FISHING and

KELP. If non-exploited communities are controlled by the density of exploited predators, then this may be a consequence of the KELP * FISHING interaction in the exploited community. Alternatively, this interaction is consistent with the idea that the structural

38 complexity provided by kelp alters predator prey interactions between exploited and non- exploited fish species (Crowder & Cooper 1982, Heck 1991, Hobson & Chess 2001).

2.4.4 Regional differences Despite similar species composition, we found large differences in the temperate reef community structure between Fiordland and Marlborough. The Fiordland community is characterised by low invertebrate and exploited fish density and high non-exploited fish density, while in the Marlborough Sounds there is high invertebrate and exploited fish density and low non-exploited fish density. The overall communities in each region match the communities generally associated with kelp bed (Fiordland) and barren habitats (Marlborough) (Choat and Ayling 1987). This may imply regional differences in the kelp habitat available to the fish community, or in the prey base utilised by exploited fish (Graham et al. 2017). The significant interaction between KELP and REGION for determining both exploited and non-exploited fish assemblages, as well as the intraspecific regional variability in response to KELP, indicate that kelp may not influence distributions of the reef fish assemblages in the same way within the two regions. Differences in species composition, density or height of kelp may affect fish aggregation and habitat preference (Holbrook et al. 1990a, Carr 1991, Levin & Hay 1996). Hence the regional variation in fish response to kelp may indicate that there are regional differences in the kelp community.

We found a significant interaction between REGION and FISHING for explaining community similarities for the exploited and non-exploited fish assemblages. The interaction is significant for similarity of community structure in terms of relative abundance of different species but not for presence absence of the species assemblages. This suggests that FISHING affected the same species in each region but there were regional differences in the magnitude of the FISHING effect, as supported by the observed intraspecific regional differences. Differences in fishing pressure between the regions is thus a likely explanation for the observed patterns (Cote et al. 2001). Due to easier access and proximity to larger human populations the Marlborough Sounds are likely subject to higher recreational fishing pressure than the Fiordland region. As we have demonstrated that fishing effects are to some extent determined by the kelp habitat, regional differences in the response of the community to fishing may also be due to underlying regional scale differences in the kelp community.

39 2.4.5 Reserve effect on Evechinus chloroticus and kelp density In correlation with higher density of the benthic predator blue cod within marine reserves, benthic surveys reveal E. chloroticus density, when present, is lower inside reserves than in fished areas for both regions. These results are consistent with the idea that removal of predatory fish species by human exploitation, can lead to increases in the abundance of herbivorous sea urchins usually preyed upon by the fish (Sala & Zabala 1996, Shears & Babcock 2002). In the Marlborough Sounds we observe higher kelp densities inside the marine reserve, similar to positive reserve effects on kelp abundance observed in northern New Zealand (Babcock et al. 1999, Shears & Babcock 2002). As there was lower E. chloroticus abundance inside reserves, top down processes are likely involved in regulating the kelp community in Marlborough (Shears et al. 2008, Salomon et al. 2010). Although other factors, such as sea surface temperature and localised sediment runoff, may simultaneously influence the benthic community (Hay 1990, Schiel 2013, Handley 2015).

Although E. chloroticus density varied with the factor FISHING in both regions, variation in kelp holdfast density is only explained by FISHING in the Marlborough Sounds. E. chloroticus density is much lower in the Fiordland region than the Marlborough Sounds, with sea urchins absent from over 80% of quadrats. Experimental removal of E. chloroticus in Fiordland has been shown to increase macroalgae density (Villouta et al. 2001). However, our results suggest that as the average sea urchin abundance is low in Fiordland (compared to northern New Zealand) top down processes are not likely to be important in shaping the subtidal benthic communities (Fowler-Walker & Connell 2002, Shears & Babcock 2003).

Alternatively, the greater variation in kelp abundance with the factor FISHING in the Marlborough Sounds, in contrast to Fiordland, may be attributable to the observed heavier fishing pressure on blue cod within the Sounds.

2.4.6 Caveats By comparing between no-take reserves and areas open to fishing, our results are a proxy for how well exploited populations have recovered within reserves. Although the reserves used in this study have been established long enough that we should see evidence of a fishing effect on exploited species, they may not have had time for longer term ecological changes, that may alter our interpretation of the effects of fishing on the non-exploited fish community, to fully develop (Edgar et al. 2009, Babcock et al. 2010). Reserve protection

40 also favours species with small home ranges, and often does not protect transient species that may still be important for ecosystem functioning (Dugan & Davis 1993). Thus, using no-take marine reserves as a proxy for unfished population structure may not give an accurate interpretation of all of the effects of fishing on community structure.

As many of the significant FISHING affects we observed, particularly for the non- exploited species, are on the frequency of occurrence of that species rather than abundance when present, it is possible that these differences are actually driven by underlying habitat differences not quantified in this study (Chapman & Kramer 1999, Edgar & Barrett 2012). Although we attempted to control for the main habitat feature affecting reef fish assemblages, there are many other aspects of habitat not quantified here that may affect the reef fish assemblage such as, geological complexity (Holbrook et al. 1990a, Carr 1991, Trebilco et al. 2015, Darling et al. 2017), and the height and species assemblage of the algal community present (Holbrook et al. 1990b, Carr 1991, Levin & Hay 1996). Including analyses of the effects of KELP and FISHING on the different ontogenetic stages of each fish species may also help to untangle the processes that shape the community (Jones 1984, Trebilco et al. 2015).

In the present study, we used visual census techniques to measure the density of fish populations. While visual census is appropriate for comparing between different communities, it may not give an accurate representation of the whole community due to the different responses of individual species to divers (Willis et al. 2000). For example, although snapper is present in the Marlborough Sounds we did not observe them on any of our transects (Davidson 2014). We also only surveyed a snapshot of the fish assemblage, making no measure of temporal variation. While previous surveys have found the reef fish assemblage in New Zealand to be comparable over time (Anderson & Millar 2004), there may be unresolved temporal variation that could affect our analysis of community structure (Reed et al. 2016).

2.4.7 Conclusions In developed countries where only a few species are targeted by fishing, and destructive fishing practices are prohibited, fishing does not have the same community wide effects as reported in countries where bulk harvesting and destructive fishing methods are common (Emslie et al. 2015). However, despite only a few species being directly impacted

41 by fishing we find evidence of community wide differences between protected and fished sites consistent with the idea that some non-exploited fish and invertebrate species may be indirectly affected by fishing. We found that fishing can reduce targeted species density and alter the non-exploited fish assemblage suggesting that fishing is likely to influence the functioning of temperate reef ecosystems (Crowe et al. 2013). We conclude that in Southern New Zealand the presence of kelp is a vital factor in shaping the composition of fish communities, although variation in fish communities may also affect the density of kelp. The results of this study highlight the importance of evaluating fishing effects in the context of community composition, interactions and habitat variability.

Chapter 3:

Organic matter derived from kelp supports a large proportion of biomass in temperate rocky reef fish communities: implications for ecosystem based management

Blue cod cruising through a kelp bed in Marlborough

44 3.1 Introduction Understanding trophic structure of marine communities is an important source of information needed to inform the development of effective ecosystem-based management (Persson et al. 2014). For example, both intra- and inter-specific differences in feeding ecology can have direct consequences for the growth rates and reproductive success of geographically distinct populations (Wainright et al. 1996, Wing et al. 2012, Beer & Wing 2013). Further, differences in the complexity and connectivity of food webs can be directly linked to community dynamics and resilience under stress (e.g. Wing & Jack 2013). As a corollary, understanding the sources and fate of organic matter within coastal food webs is a vital step towards understanding both ecosystem function and variability in fisheries production within coastal systems (Ware & Thomson 2005, Friedland et al. 2012).

Trophic structure and the underlying trophodynamics may vary spatially, even among fish communities with very similar composition (Bergstad et al. 2012, Wing et al. 2012). Differences in trophodynamics among similar fish communities can be strongly influenced by the relative availability of alternate organic matter sources and their effect on the composition of the prey base (Rodgers & Wing 2008, Jack & Wing 2011). As a consequence, individual specialisation in feeding as a response to a changing prey field can alter the pattern of connections within food webs resulting in changes in niche breadth (Bolnick et al. 2003). By this mechanism, geographically distinct populations may have naturally different trophic structure (Marshall et al. 2014).

In temperate rocky reef ecosystems, food webs are supported by organic matter derived from phytoplankton (Gregson & Booth 2005, Ware & Thomson 2005), macroalgae (Mann 1973, Duggins et al. 1989) and in some cases detritus from terrestrial inputs (Jack et al. 2009, McLeod et al. 2010b). Due to their high trophic level, fish act as integrators of the flux of organic matter through coastal food webs (Thomas & Cahoon 1993, Vander Zanden & Vadeboncoeur 2002, McLeod et al. 2010a). Hence, the trophic position of temperate reef fish provides a measure of the relative contributions from alternative organic matter sources to underlying food webs (Norderhaug et al. 2005, Koenigs et al. 2015, Truong et al. 2017).

Stable isotope analysis provides a repeatable method of defining an organism’s trophic position, where trophic position is a combination of trophic level and the proportion

45 of organic matter originating from alternate sources. The isotopic signature of an animal’s tissues reflects that of its diet (DeNiro & Epstein 1978, 1981), and therefore the natural abundance of stable isotope ratios of carbon (13C:12C) and nitrogen (15N: 14N), reported as deviations from a standard as !13C and !15N, can provide tracers of organic matter through food webs (Fry 2006). Phytoplankton and macroalgae each have characteristic !13C values that change relatively little at each trophic step. Thus, the !13C of a consumer can be used to determine the relative contribution of organic matter derived from alternative sources to the underlying food web supporting a consumer (Fry 2006). In contrast, there is a large predictable increase in !15N with each trophic exchange. Therefore, the !15N of a consumer’s tissues can be used to determine its integrated trophic level (McCutchan et al. 2003). Accordingly, stable isotope analysis provides a powerful method for detecting differences in trophic position among consumers (Davenport & Bax 2002, Fredriksen 2003, Melville & Connolly 2003).

Macroalgae can be extremely productive on temperate rocky coasts (Mann 1973). For example, kelp beds provide organic matter directly to grazing invertebrates (Norderhaug et al. 2005), produce suspended particulates that are consumed by suspension feeders (Wing & Jack 2012) and detritus that is exported to the benthic community (Duggins et al. 1989, Krumhansl & Scheibling 2012). The contribution of macroalgae as an organic matter source supporting temperate reef fishes ranges widely between different studies from 20 – 90 % (Fredriksen 2003, Koenigs et al. 2015, Markel & Shurin 2015, von Biela et al. 2016). Nevertheless, few studies have combined information on individual fish species to quantify the trophic pathways that support whole fish communities in terms of biomass (Truong et al. 2017), or investigated how these pathways may change between geographically distinct populations.

Kelp forests are currently under threat globally due to a variety of anthropogenic activities (Dayton et al. 1998, Steneck et al. 2002, Connell et al. 2008). Impacts include the effects of coastal sedimentation and eutrophication on light availability and water quality (Erikson et al. 2002), range contraction due to coastal warming (Johnson et al. 2011), direct harvesting of kelp and overharvesting of sea urchin predators (Shears & Babcock 2002, Steneck et al. 2004, Foster & Schiel 2010). The current threats to kelp forests highlight the need to quantify their importance as an organic matter source, and to determine how

46 differences in macroalgae communities can impact the trophic structure of temperate reef fish communities.

New Zealand subtidal reef communities are similar to those found on many kelp- dominated coasts (Schiel 1990). Large brown algae are a dominant occupier of space, providing both habitat structure and an important source of organic matter to coastal communities (Dayton 1985, Schiel & Foster 1986). The present study considers subtidal communities from two coastal waterway systems on the South Island, New Zealand: the Marlborough Sounds and Fiordland. Both regions are characterised by extensive wave- sheltered rocky reef habitats at the entrances of the sounds, harbouring kelp forests and similar reef fish and benthic invertebrate communities (Shears & Babcock 2007, Wing & Jack 2014), though there is some regional variability in macroalgal assemblages (Shears & Babcock 2007). The two regions provide an important scientific opportunity to answer the question: How do regional differences in the composition and abundance of kelp beds influence composition of organic matter sources supporting reef fish communities?

Stable isotope analysis was used to make direct comparisons of the trophic position of individual fish species between the two regions. By combining data on macroalgal density and species composition in the two regions with stable isotope data, differences in the distribution of kelp beds were linked with the trophic structure of reef fish communities at the regional scale. Further, applying stable isotopic analysis to the herbivorous fish species, Odax pullus and Aplodactylus arctidens, enabled the contribution of the three main macroalgal groups (native kelps (Phaeophytes), rhodophytes and Undaria pinnatifida) to their diet to be quantified. U. pinnatifida is an invasive kelp that has established itself on many of New Zealand’s rocky reefs, including those in the Marlborough Sounds (Russell et. al. 2008), however at the time of this study it had not invaded our study sites in Fiordland.

The contribution of organic matter derived from macroalgae to whole fish communities in terms of biomass per unit area was quantified by combining information on density, per-capita biomass and trophic position of the most common reef fish species in each region. Here the fish community is split into exploited and non-exploited species. In New Zealand, the exploited species are generally high trophic level generalist predators (Francis 2001), and thus are more likely to exhibit dietary shifts based on resource availability (Beer & Wing 2013, Cowen 1986, Hamilton et al. 2011, Jack & Wing 2011). Splitting the

47 community in this way also enables a better understanding of the trophic pathways supporting commercially important species.

The objectives of this study were to determine the relative contribution of organic matter derived from macroalgae and phytoplankton to food webs supporting temperate rocky reef fish communities in the Marlborough Sounds and Fiordland. Specifically, this study aimed to (1) determine the composition and density of kelp beds over a range of subtidal study sites in Fiordland and Marlborough, (2) quantify the density, per capita biomass and trophic position of the common coastal fish species present in each region, (3) determine which macroalgae groups herbivorous fish feed on, and to investigate whether the invasive U. pinnatifida is utilised as an organic matter source in the Marlborough Sounds, and (4) to contrast the relative contribution of organic matter derived from macroalgae on a biomass per unit area basis in both non-exploited and exploited reef fish communities in the Marlborough Sounds and Fiordland. These data and analyses provide a unique example of linkages between regional differences in the supply of organic matter from kelp beds and the trophic structure of coastal reef fish.

3.2 Methods

3.2.1 Surveys of fish and macroalgae abundance In order to sample a representative range of habitats and conditions within each region, study sites were stratified in a factorial design among exposed (generally more macroalgae) and sheltered sites (generally fewer macroalgae) and within fished and non- fished (marine reserve) areas (Figure 3.1). Including sites inside marine reserves removed fishing pressure as a confounding factor that may be driving regional differences in trophic structure.

Figure 3.1. Map showing the location of study sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand. Symbols within each region represent sites in marine reserves (triangles) and fished areas (circles).

49 Diving surveys in the Marlborough Sounds were conducted during January 2017 (8 sites) and February 2018 (4 sites) from the RV Polaris II. In the Sounds, our twelve sites were distributed around the Kokomohua Marine Reserve. Sites were chosen using data and charts from reports on macroalgae assemblages (Shears & Babcock 2007) to guide our orthogonal distribution of sampling.

Diving surveys in Fiordland were conducted during November 2015 (11 sites) and May 2017 (7 sites) from the RV Polaris II. In order to sample exposed and sheltered sites within both fished and unfished areas, study sites in Fiordland were spread throughout the network of reserves in the southern Fiordland Marine Area. Fiordland site selection was based on kelp density data from previous monitoring reports (Wing & Jack 2014), and information on habitat types reported by Wing et al. (2007).

Non-cryptic reef fish species were enumerated at each site by divers using SCUBA along multiple belt transects (50 m long by 5 m wide by 2.5 m high) centred at 5 and 15 m depths. In cases where the bottom of the reef was shallower than 15 m, the deep transect was centred just above the bottom of the reef. Four independent replicate transects were surveyed at each depth for each site. At some sites only three replicate transects were completed if the dive team had exhausted their air supply. The composition of diver teams identifying and counting fishes was kept constant between sites and regions for the duration of the study. To characterise the density and species composition of the macroalgal community at each site 2 m2 quadrats were randomly placed along the belt transects described above, to achieve 5-10 quadrats per depth stratum (5 m, 10-15 m), with the number of holdfasts of each stipitate macroalgae species recorded.

3.2.2 Stable isotope analysis A random sample of individuals from each fish species observed on the belt transects was collected from each region, using a combination of hook and line and pole spears. Sampling was carried out under permit from New Zealand Ministry of Primary Industries and under ethical approval from the University of Otago animal ethics committee (ET 21/11). As sample sizes for each species varied with abundance there were uneven sample sizes among species, resulting in the most common species represented with the largest sample sizes (Tables 3.1 and 3.2). Collection with pole spear enabled us to sample a similar size range for

50 Table 3.1. Isotopic signatures (!13C and !15N) and trophic position, as determined by mass balance mixing models, of each reef fish species observed on transect in Fiordland, New Zealand. Ordered by average biomass per transect.

Species Common name !"#$ ±&'( !")* ±&'( Proportion Trophic Level ±&'( N macroalgae ±&'( Caesioperca lepidoptera butterfly perch -17.86±0.12 13.05±0.16 0.437±0.022 3.26±0.07 62 Mendosoma lineatum telescope fish -17.85±0.44 12.43±0.61 0.470±0.083 3.00±0.26 5 Pseudolabrus miles scarlett wrasse -17.74±0.13 14.53±0.18 0.397±0.024 3.869±0.07 51 Notolabrus celidotus spotty -17.79±0.08 12.47±0.11 0.480±0.015 3.025±0.05 213 Parapercis colias blue cod -17.07±0.10 13.27±0.13 0.608±0.018 3.38±0.06 119 Notolabrus fucicola banded wrasse -17.98±0.16 13.72±0.22 0.376±0.031 3.53±0.09 29 Aplodactylus arctidens marblefish -21.09±0.39 10.62±0.55 1.000±0.069 1.06±0.22 6 Nemadactylus macropterus tarakihi -16.44±0.25 13.75±0.35 0.706±0.048 3.59±0.15 18 Notolabrus cinctus girdled wrasse -17.72±0.31 13.48±0.43 0.449±0.059 3.44±0.18 11 Parika scaber leatherjacket -17.99±0.39 12.99±0.55 0.410±0.075 3.23±0.23 3 Helicolenus percoides sea perch -17.55±0.17 13.48±0.43 0.490±0.033 3.42±0.10 139 Latridopsis ciliaris blue moki -16.46±0.39 13.63±0.55 0.739±0.075 3.55±0.23 8 Odax pullus greenbone -16.29±0.44 9.14±0.61 1.000±0.076 1.08±0.24 6 Latris lineata trumpeter -17.62±0.62 12.93±0.87 0.499±0.118 3.22±0.36 2 Latridopsis forsteri copper moki -19.00±0.62 13.31±0.87 0.155±0.118 3.22±0.36 2 Hypoplectrodes huntii red-banded perch -17.22±0.88 14.88±1.23 0.499±0.167 4.02±0.51 1 Lotella rhacinus red cod -15.77±0.44 13.25±0.61 0.858±0.084 3.41±0.26 4 Callanthias allporti splendid perch -17.77±0.88 14.09±1.23 0.406±0.167 3.69±0.51 1 Paratrachichthys trailli common roughy -17.83±0.88 14.05±1.23 0.394±0.167 3.67±0.51 1

51 Table 3.2. Isotopic signatures (!13C and !15N) and trophic position, as determined by mass balance mixing models, of each reef fish species observed on transect in the Marlborough Sounds, New Zealand. Ordered by average biomass per transect.

Species Common name !"#$ ±&'( !")* ±&'( Proportion macroalgae Trophic Level ±&'( N ±&'( Parapercis colias blue cod -17.88±0.19 14.52±0.18 0.255 ± 0.027 3.24±0.07 20 Notolabrus celidotus spotty -17.48±0.23 14.31±0.22 0.328±0.033 3.15±0.09 13 Notolabrus fucicola banded wrasse -16.43±0.34 13.85±0.33 0.518±0.049 2.94±0.13 6 Caesioperca lepidoptera butterfly perch -19.52±0.37 13.29±0.36 0.026±0.054 2.75±0.15 5 Pseudolabrus miles scarlett wrasse -17.62±0.83 13.13±&0.81 0.347±0.121 2.65±0.33 6 Latridopsis ciliaris blue moki -17.02±0.28 13.27±0.27 0.441±0.040 2.71±0.11 9 Aplodactylus arctidens marblefish -19.71±0.48 12.73±0.47 1.000 ±0.070 1.33±0.19 5 Cheilodactylus spectabilis red moki -17.11±0.59 14.56±0.57 0.381±0.086 3.25±0.23 2 Nemadactylus macropterus tarakihi -16.88±0.59 14.78±0.57 0.413±0.086 3.34±0.23 6 Arripis trutta kahawai -18.82±0.41 14.67±0.41 0.095±0.061 3.32±0.16 4 Parika scaber leatherjacket -18.57±0.83 13.00±0.81 0.194±0.121 2.62±0.33 10 Aldrichetta forsteri yellow-eyed mullet -17.83±0.31 12.96±0.31 0.317±0.046 2.59±0.12 5 Odax pullus greenbone -15.97±0.59 9.96±0.57 1.000±0.086 0.71±0.23 3

52 each species for each region. There was only one species observed on transect for which we did not obtain samples, the red lined perch (Lepidoperca tasmanica) in Fiordland. L. tasmanica accounted for less than 0.01 % of the estimated biomass observed at two of the sites in Fiordland.

Fish were frozen and transported back to the Portobello Marine Laboratory where dorsal muscle tissue samples were dried at 60 °C for 48 h, ground to a fine powder using mortar and pestle and 1mg subsamples were sealed into tin capsules for measurement of !13C and !15N. Lipids were not extracted from muscle tissue before isotopic analysis as the C:N ratio was between 3.5 and 4 for all species. These values are borderline when determining whether lipid extraction is required, however as the same species were being compared between regions is was not deemed necessary (Post et al., 2007, Skinner, Martin, & Moore, 2016).

For each macroalgal species present at a study site samples of blade tissue were collected from multiple individuals (n = 5) stratified by depth. Macroalgae detritus was not sampled. As the process of decomposition does not affect the !13C (Fenton & Ritz 1988, Stephenson et al. 1986), we assumed that our !13C value for macroalgae would also encompass detritus. The macroalgae samples are representative of growth conditions in the summertime period when a majority of organic matter from macroalgae communities is produced. Samples were dried at 60 °C for 48 h and ground into a fine powder using mortar and pestle. Powder from SPOM and macroalgae samples were weighed to 3 mg and sealed into tin capsules for measurement of !13C and !15N.

Analysis of !15N and !13C of fish, SPOM and macroalgae was carried out on a Europa 20-20 update stable isotope mass spectrometer (Europa Scientific, Crewe, UK) interfaced to a Carlo Erba elemental analyser (NA1500; Carlo Erba, Milan, Italy) in continuous flow mode (precision: 0.2 ‰ for !13C, 0.3 ‰ for !15N) at Iso-trace Research in the Department of

53 Chemistry, University of Otago. Raw results were calibrated to international scales using USG40 and USG41 reference materials. An in-house laboratory standard (EDTA, Elemental Microanalysis, Cheshire, UK) was measured in duplicate after every twelve samples for drift correction. Drift corrected data are reported with respect to the appropriate international reference standard; atmospheric air for !15N and Vienna Pee Dee Belemnite for !13C. The isotope ratio is expressed in standard delta notation (Fry 2006). Variability in sample replicates within trays was estimated by calculating the average variance and standard deviation for !15N and !13C. As the standard deviation was less than 2 % of the mean for all samples replicated within trays, we concluded that instrument drift within a run was low and very unlikely to mask true differences in isotopic signatures among groups.

3.2.3 Trophic positions The relative abundance of each macroalgal species, as determined from density data from each site, was used to calculate an aggregate macroalgal signature for !15N and !13C with variance stratified among species (after Wing et al. 2012). Average values of !15N and !13C for SPOM and macroalgae were then calculated for each region, with variance among sites. For all fish except the herbivores, a two-step iterative procedure was used to determine the basal organic matter used and the trophic level of each individual (Jack & Wing 2011). Firstly an individual-based two-source mass balance model after Phillips & Gregg (2001) was used to calculate the relative contribution of macroalgae and SPOM using !13C. In this step, an approximation of trophic level was used to estimate trophic discrimination of !13C. 15 The results of this model were used to estimate the corresponding ! N of the mixture of 15 organic matter sources supporting each individual (! Nbase). The trophic level was then 15 15 15 calculated for each individual from ! Nbase, defined as: (! Nconsumer - ! N base/∆n), where ∆n is the trophic discrimination factor, after Post (2002). The resulting estimate of the trophic level was then iterated back into the mass balance model until a stable solution was obtained for both the mixture of organic matter sources and trophic level. We used the average trophic discrimination factors of +0.5 ‰ (SE 0.17) for !13C, and +2.3 ‰ (SE 0.28) for !15N, after McCutchan et al. (2003), for each enrichment step. Trophic discrimination factors can vary between taxa and systems (Newsome et al. 2010). However, as the same species were being compared between regions any errors introduced by the use of an average discrimination factor should not have affected the detection of regional differences in trophic position.

54 For the two strictly herbivorous species greenbone (Odax pullus) and marblefish (Aplodactylus arctidens) we used estimates of the trophic level and mass balance estimates as above, but considered alternative sources of organic matter from within the macroalgal community. Examination of stomach contents from O. pullus and A. arctidens confirmed their strictly herbivorous diet. As primary consumers can have a more variable trophic discrimination factor !15N than the average value among trophic transfers found in higher trophic level consumers (Vander Zanden & Rasmussen 2001), an average of the !15N reported for three herbivorous fish species by Mill et al. (2007) was used for the herbivorous fish mixing models. Here, using the !13C of the herbivorous fish and a two-step mixing model, we were able to isotopically discriminate between organic matter from native kelps (Phaeophytes) as a group and organic matter from the invasive kelp Undaria pinnatifida and Ulva spp. As a group and rhodophytes as a group. Macroalgae species were grouped based on similarities in !13C values.

3.2.4 Proportion of fish biomass supported by macroalgae Average wet weight (g) was calculated for each fish species collected for isotopic analysis within each region. To determine the per-capita ash-free dry weight (g) for each species, a subset of the fish collected were dried at 60 °C for 48 h and then weighed, ashed in a muffle furnace at 500 °C for 24 h and reweighed. The ash-free dry weight (g) for each species was used to develop an equation for ash-free dry weight, or biomass, from wet weight (biomass (g) = 0.2206 x wet weight (g), r2=0.96). This conversion factor was then used to convert the average wet weight of each fish species for each region into an average per-capita biomass per species.

As fishing can strongly influence the size structure of fished populations (Hamilton et al. 2007), abundance of the most commonly exploited species was recorded into size classes, blue cod (Parapercis colias) (<15 cm, 15-33 cm, >33 cm) and blue moki (Latridopsis ciliaris) (<40 cm, >40 cm). Fish samples of these species were divided into the size classes, and an average per-capita weight for each size class was calculated. The conversion factor was then used to derive the per-capita biomass (g) for each size class.

For each transect the abundance of each species was multiplied by the average per- capita biomass for that species. This data was then summed among species as an estimate of

55 the total biomass per transect. Species biomass on each transect was multiplied by the average proportion of biomass that was supported by macroalgae for that species (based on stable isotope calculations above). Values were summed across species to estimate the total biomass per transect supported by macroalgae (g 250 m-2). Dividing the amount of biomass supported by macroalgae by the total amount of biomass gave the proportion of biomass supported by macroalgae on each transect.

We grouped the observed species as either exploited or non-exploited, depending on whether they were targeted by fisheries. O. pullus, sea perch (Helicolenus percoides), red cod (Pseudophycis bachus), trumpeter (Latris lineata), tarakihi (Nemadactylus macropterus), red moki (Cheilodactylus spectabilis), copper moki (Latridopsis forsteri), kahawai (Arripis trutta), P. colias, L. ciliaris and leatherjacket (Parika scaber) were the only exploited species observed on the transects in both regions. All other species observed were classed as non- exploited, which was confirmed after Francis (2001). The proportion of exploited and non- exploited biomass supported by macroalgae for each transect was calculated using the method described above.

3.2.5 Statistical analysis Our regional comparison of macroalgae densities was restricted to the three most commonly occurring species (Ecklonia radiata, Macrocystis pyrifera, Carpophyllum machalocarpum) and the invasive Undaria pinnatifida. To test for regional differences in holdfast density, we used a general linear model (JMP 11.0 SAS) with factors DEPTH (2 levels, fixed) and REGION[DEPTH] (2 levels, fixed) for each species. The holdfast densities were log transformed to achieve a more normal distribution.

General linear models (JMP 11.0 SAS) were used to test whether there were differences in (1) the contribution of macroalgae to underlying food webs, and (2) the trophic levels of exploited and non-exploited reef fish species between the two regions with factors

REGION (2 levels, fixed), SPECIES (5 levels, fixed). Further, we tested for differences in (3) the contribution of three groups of macroalgae: native phaeophytes, rhodophytes and Ulva spp. – U. pinnatifida as a group to the diet of the two strictly herbivorous species O. pullus, and A. arctidens using a general linear model on REGION (two levels, fixed). These analyses resolved intraspecific differences in trophic positions between the two regions. A general

56 linear model was used to test for differences in (4) the contribution of macroalgae to whole communities of exploited and non-exploited reef fish in terms of biomass density between the two regions: REGION (two levels, fixed), EXPLOITATION [REGION] (two levels, fixed). These tests provide a direct comparison of the proportion of biomass supported by macroalgae among regions and species groups

3.3 Results

3.3.1 Macroalgae community Analysis of holdfast density of the most abundant macroalgae species revealed regional differences in the benthic communities. Ecklonia radiata density was significantly higher in Fiordland than Marlborough, though Carpophyllum machalocarpum and Undaria pinnatifida were both most abundant in the Marlborough Sounds (Figure 3.2, Table 3.3). There was no regional effect on the density of M. pyrifera. Depth had no interaction with E. radiata, while all other macroalgae species were present in significantly higher densities in the shallow quadrats (Figure 3.2, Table 3.3).

3.3.2 Stable isotope analysis The two alternate groups of organic matter sources (macroalgae and SPOM) were well discriminated by !13C. With trophic discrimination !13C and !15N after McCutchan et al. (2003) applied to multiple trophic levels all fish species !13C values fell between the two sources, suggesting there is no input from terrestrial sources (Figure 3.3). The Fiordland and Marlborough fish communities are characterised by a similar group of species, but with differing relative abundance and species diversity between regions (Tables 3.4 and 3.5). We observed 20 different fish species in Fiordland in contrast to only 13 in the Marlborough Sounds. Telescopefish (Mendosoma lineatum) was the only species present in Fiordland and not Marlborough that made a substantial contribution to the total fish biomass. Despite similar species composition the averages of !13C and !15N for exploited and non-exploited reef fish species demonstrate distinctly different patterns for trophic structure in Fiordland versus the Marlborough Sounds (Figure 3.3, Tables 3.1 and 3.2).

57 Table 3.3. Summary of general linear model results for holdfast density (2m-2) of the most common macroalgae species.

Species Main Test Region (Depth) Depth 2 F3,467 p r F p F p

Ecklonia radiata 7.23 < 0.0001*** 0.04 10.79 < 0.0001*** 1.69 0.19

Carpophyllum machalocarpum 13.22 < 0.0001*** 0.08 7.45 0.0007*** 19.99 < 0.0001***

Macrocystis pyrifera 4.41 0.0045** 0.03 0.77 0.77 10.95 0.0010** Undaria pinnatifida 11.18 < 0.0001 0.07 12.88 < 0.0001*** 6.91 0.0089**

Figure 3.2. Holdfast density per 2 m2 of Ecklonia radiata, Carpophyllum machalocarpum, Macrocystis pyrifera and Undaria pinnatifida at a) 5 m depth and b) 10-15 m depth in Fiordland (grey bars) and Marlborough Sounds (black bars). Pairs marked with an asterisk are significantly different based on a Tukey’s post-hoc test. Error bars indicate + 1 SE.

Figure 3.3. Stable isotope signatures (!13C and !15N) of basal organic matter sources (macroalgae and suspended particulate organic matter (SPOM)) with trophic discrimination "13C and "15N after McCutchen et al. (2003) applied to multiple trophic levels. Averages for exploited reef fish species (filled circles) and non-exploited fish species (open circles) are shown for (a) Fiordland and (b) Marlborough Sounds. Error bars indicate + 1 SE.

Figure 3.4. Trophic position of reef fish from trophic level and proportion of organic matter from macroalgae supporting each exploited reef fish species (filled circles) and non-exploited fish species (open circles) are shown for (a) Fiordland and (b) Marlborough Sounds. Where primary producers are trophic level 0. Error bars represent + 1 SE among individuals for each species.

60 Table 3.4. Average density and biomass per transect of each reef fish species observed in the Fiordland, New Zealand. Ordered by highest average biomass per transect.

Species Common name Density ±"#$ Biomass (g) ±"#$ Caesioperca lepidoptera butterfly perch 65.28 ±"8.49 1459.32"±189.69 Mendosoma lineatum telescope fish 21.49 ±"7.09 622.01 ±"205.11 Pseudolabrus miles scarlett wrasse 12.18 ± 1.44 551.40 ±"65.14 Notolabrus celidotus spotty 18.56 ±"3.28 422.65 ±"74.57 Parapercis colias blue cod 2.11 ±"0.27 237.02 ±"32.17 Notolabrus fucicola banded wrasse 2.39 ±"0.39 216.32 ±"35.18 Aplodactylus arctidens marblefish 0.67 ±"0.14 141.12 ±"29.68 Nemadactylus macropterus tarakihi 0.99 ±"0.31 88.32 ±"27.32 Notolabrus cinctus girdled wrasse 0.93 ±0.24 64.17 ±"16.47 Parika scaber leatherjacket 0.57 ±0.16 58.46 ±"16.75 Helicolenus percoides sea perch 0.54 ±"0.15 30.50 ±"8.29 Latridopsis ciliaris blue moki 0.13 ±"0.05 16.77 ±"6.14 Odax pullus greenbone 0.11 ±"0.05 14.04 ±"6.93 Latris lineata trumpeter 0.04 ±"0.02 13.27 ±"5.83 Latridopsis forsteri copper moki 0.03 ±"0.02 7.96 ±"5.92 Hypoplectrodes huntii red-banded perch 0.21 ±"0.07 4.79 ±"1.66 Lotella rhacinus red cod 0.04 ±"0.02 4.29 ±"2.61 Lepidoperca tasmanica red lined perch 0.17 ±"0.08 3.79 ±"1.81 Callanthias allporti splendid perch 0.23 ±"0.11 2.71 ±"1.30 Paratrachichthys trailli common roughy 0.62 ±"0.38 2.89 ±"1.76

Table 3.5. Average density and biomass per transect of each reef fish species observed in the Marlborough Sounds, New Zealand. Ordered by highest average biomass per transect.

Species Common name Density ±"#$ Biomass (g) ±"#$ Parapercis colias blue cod 9.08"±"1.96 1038.72 ±"204.52 Notolabrus celidotus spotty 29.56"±"5.27 560.90 ±"101.74 Notolabrus fucicola banded wrasse 1.24"±"0.36 176.78 ±"50.71 Caesioperca lepidoptera butterfly perch 1.31"±"1.00 81.27 ±"62.48 Pseudolabrus miles scarlett wrasse 0.40"±"0.15 52.08 ±"20.02 Latridopsis ciliaris blue moki 0.24"±"0.09 31.59 ±"12.02 Aplodactylus arctidens marblefish 0.09"±"0.06 13.84 ±9.67 Cheilodactylus spectabilis red moki 0.09"±"0.05 13.59 ±"8.17 Nemadactylus macropterus tarakihi 0.22"±"0.14 13.38 ±"8.53 Arripis trutta kahawai 0.04"±"0.04 11.71 ±"11.71 Parika scaber leatherjacket 0.09"±"0.05 7.81 ±"4.69 Aldrichetta forsteri yellow-eyed mullet 0.07"±"0.05 4.87 ±"3.60 Odax pullus greenbone 0.02"±"0.02 2.78 ±"2.78

61 3.3.3 Trophic positions Analysis of trophic levels and the proportion of organic matter from macroalgae supporting exploited and non-exploited reef fish species common to both regions, clearly shows structural differences in reef fish communities from Fiordland and the Marlborough Sounds (Figure 3.4, Tables 3.1 and 3.2)

A general linear model (1) revealed significant regional differences in the proportion of organic matter from macroalgae supporting individual reef fish species (Figure 3.5): (Main 2 Test (exploited species): F9,151 = 14.84, p < 0.0001, r = 0.46, REGION: F = 24.85, p <0.0001: 2 Main Test (non-exploited species): F9,294 = 16.77, p < 0.0001, r = 0.34, REGION: F = 25.34, p < 0.0001). Here a Tukey’s post-hoc test resolved differences within species between regions (Figure 3.5). Butterfly perch (Caesioperca lepidoptera), exhibited the largest shift in organic matter use between regions, ranging from 43 % of their biomass being supported by macroalgae in Fiordland to being almost exclusively planktivorous in Marlborough Sounds (2 % of biomass from macroalgae). After C. lepidoptera the omnivorous exploited species, blue cod (Parapercis colias), blue moki (Latridopsis ciliaris) and tarakihi (Nemadactylus macropterus) had the next largest intraspecific change in organic matter use between regions, with all three species having significantly less macroalgal contribution to their diets in the Marlborough Sounds (Figure 3.5).

Tukey post-hoc tests on the general linear models of trophic level (2) (Main Test 2 (exploited species): F9,151 = 33.74, p < 0.0001, r = 0.67, REGION: F = 15.02, p = 0.0002: 2 Main Test (non-exploited species): F9,286 = 24.41, p < 0.0001, r = 0.43, REGION: F = 7.69, p = 0.0059) revealed significantly lower trophic level of four individual reef fish species in the Marlborough Sounds compared to Fiordland; blue moki (L. ciliaris), tarakihi (N. macropterus), scarlett wrasse (Pseudolabrus miles) and banded wrasse (Notolabrus fucicola) (Figure 3.6). For all other species there was no difference in trophic level between the regions (Figure 3.6).

Figure 3.5. Proportion of organic matter from macroalgae supporting (a) exploited reef fish and (b) non-exploited reef fish from Fiordland (grey bars) and Marlborough Sounds (black bars). Pairs marked with an asterisk are significantly different based on a Tukey’s post-hoc test. Error bars indicate + 1 SE. Herbivorous species are indicated with (H).

Figure 3.6. Trophic levels of (a) exploited reef fish and (b) non-exploited reef fish from Fiordland (grey bars) and Marlborough Sounds (black bars), where primary producers are trophic level 0. Pairs marked with an asterisk are significantly different based on a Tukey’s post-hoc test. Error bars indicate + 1 SE. Herbivorous species are indicated with (H).

64 3.3.4 Herbivore macroalgae use The herbivorous species greenbone (Odax pullus) and marblefish (Aplodactylus arctidens) had differences in mixtures of organic matter from native kelps versus other macroalgal species among regions (Figure 3.7). Here a general linear model (3) detected significant differences in the mix of macroalgal groups between regions in the diet of O. 2 pullus (Main test: F5,18 = 54.65, p < 0.0001, r = 0.94) and A. arctidens (Main test: F5,27 = 5.72, p = 0.0010, r2 = 0.51). A Tukey’s post-hoc test revealed that both species had a high prevalence of organic matter from the Ulva spp. – Undaria pinnatifida group in the Marlborough Sounds (Figure 3.7). U. pinnatifida replaces the contribution of native kelps in the herbivores diet but does not affect the proportion of diet comprised of rhodophytes.

Figure 3.7. Proportion of organic matter from Laminarian kelps (dark grey), rhodophytes (light grey) and a combination of Ulva sp. and Undaria pinnatifida (white) in greenbone (Odax pullus) and marblefish (Aplodactylus arctidens) by region. GLMs for each species were followed by a Tukey’s post-hoc test. Levels not connected by the same letter are significantly different, italics indicate separate test for each species. Error bars indicate + 1 SE.

65 3.3.5 Proportion of fish biomass supported by macroalgae Analysis of the proportion of organic matter from macroalgae supporting whole exploited reef fish communities and non-exploited reef fish communities on the basis of biomass per unit area revealed significant differences between Fiordland and the 2 Marlborough Sounds (4) (Main Test: F3,338 = 455.39, p <0.0001, r = 0.80, REGION: F = 1222.67, p < 0.0001, EXPLOITED [REGION]: F = 106.41, p < 0.0001). The proportional contribution of macroalgae to both exploited and non-exploited biomass was significantly lower in the Marlborough Sounds than Fiordland (Figure 8). There was a larger regional effect on the proportional contribution of macroalgae to exploited biomass. In Fiordland, the proportional contribution of macroalgae to exploited biomass (77 %) was greater than the contribution to non-exploited biomass (59 %) (t = 14.03, p < 0.0001). Though in the Marlborough Sounds the proportional contribution of macroalgae towards non-exploited biomass (37 %) was greater than for exploited biomass (31 %) (t = -4.00, p < 0.0001) (Figure 3.8).

Figure 3.8. Proportion of organic matter from macroalgae supporting exploited reef fish communities (grey bars) and non-exploited reef fish communities (black bars) from Fiordland and the Marlborough Sounds. Levels not connected by the same letter are significantly different based on a Tukey’s post-hoc test. Error bars indicate + 1 SE.

66 3.4! Discussion The data and results presented here demonstrate dramatic differences in the trophic structure of the coastal reef fish communities between Fiordland and the Marlborough Sounds, despite similar species composition. We show that rocky reef fish communities in southern New Zealand are supported by both pelagic productivity and macroalgae, though the relative importance of the two sources differs regionally. We found that macroalgae supported a lower proportion of reef fish biomass in the Marlborough Sounds, relative to Fiordland, for both the exploited and non-exploited community. This pattern was also observed in the intraspecific regional differences in organic matter source use in foodwebs supporting individual species. Here the majority of species exhibited lower macroalgae use in the Marlborough Sounds. As fish integrate organic matter fluxes from pelagic and benthic sources (Thomas & Cahoon 1993, Vander Zanden & Vadeboncoeur 2002), these observations are likely a result of a regional difference in the relative availability of organic matter derived from macroalgae with kelp forests in the Marlborough Sounds contributing less organic matter to their ecosystem (Hamilton et al. 2011, Wing et al. 2012).

Our benthic surveys indicated significantly lower Ecklonia radiata density in the Marlborough Sounds, relative to that found on reefs in Fiordland. Our surveys revealed the existence of high-density kelp beds predominately made up of E. radiata and distributed down to 15 or 20 m in the more wave-exposed sites in Fiordland, compared to the low density of E. radiata confined to the upper 5 m in wave-washed sites in the Marlborough Sounds. In contrast, C. machalocarpum and U. pinnatifida, which made up a majority of kelps in the Marlborough Sounds were confined to the shallow depth strata. As a Laminarian, E. radiata is a highly productive species that likely produces more detritus per unit area than C. machalocarpum (Kirkman 1984). A large portion of macroalgae that is assimilated into the food web comes from detritus (Duggins et al. 1989, Krumhansl & Scheibling 2012). Hence the higher density of E. radiata in Fiordland likely underpins a greater regional production of organic matter from macroalgae and larger inputs of kelp- derived organic matter into the food web. Nevertheless, because of the ephemeral nature of phytoplankton production we cannot conclusively determine whether the observed differences in the composition of organic matter supporting the two fish communities were driven by changes to macroalgae or phytoplankton availability. Limited observations of Chl a concentrations, a proxy for phytoplankton biomass, indicate that pelagic production may be

67 higher in Fiordland (Goebel et al. 2005) than Marlborough (Oglivea et al. 2000) during bloom events. Therefore, we conclude that regional trophodynamic differences are likely driven by differences in macroalgae availability.

If the observed regional differences in organic matter use by the reef fish community are caused by disparities in the availability of macroalgae, then trophodynamic differences may be a result of anthropogenic impacts as there have been significant declines in macroalgae in the Sounds over the last fifty years (Hay 1990, Handley 2016). In support of this hypothesis, comparison of !13C of collagen in fish bones from the present and from the first years of human habitation of the Sounds indicate a shift away from macroalgal uptake in food webs supporting coastal fish species (A Connolly, L Wing unpublished data). Suggested mechanisms for the decline in macroalgae in the Sounds include warming of the ambient sea surface temperature (Hay 1990), increases in the amount of fine sediment released into the Sounds as a result of land clearing (Handley 2016), and overharvesting of sea urchin predators such as rock lobster and blue cod (Davidson et al. 2014). While there is direct evidence of a decline in Macrocystis pyrifera cover (Hay 1990), there is no direct evidence for changes in subtidal stipitate species such as E. radiata. Nevertheless, E. radiata would be sensitive to the same stressors such as changes in water quality and temperature that led to the observed declines in M. pyrifera. Responses of macroalgae to fine sediment in other locations (Erikson et al. 2002, Shepherd et al. 2009) suggest that the changes in water quality and increases in anthropogenic sources of sediment delivered to the Sounds could explain the lower densities of macroalgae, particularly E. radiata, observed in deeper waters.

In contrast, Fiordland is a relatively pristine region with intact native forest catchments (Miller et al. 2006; Wing & Jack 2014). Hence there is a much lower likelihood that macroalgae biomass has been influenced by catchment runoff. Our observations are insufficient to confirm if changes in catchment runoff in the Sounds since European settlement is a causal factor for the observed regional trophodynamic differences in reef fish communities. However, we have demonstrated that there is a significant regional difference in the organic base of the food web, with a smaller proportion of organic matter derived from macroalgae supporting fish biomass in the Marlborough Sounds. These observations are consistent with a lower density of the common kelp, E. radiata, and less extensive kelp beds

68 in the Marlborough Sounds. This difference could have been influenced by land-based inputs and decline from a more pristine state, or natural variability among regions.

Contrary to the majority of species, a greater proportion of banded wrasse (Notolabrus fucicola) diet was supported by macroalgae in the Marlborough Sounds. Additionally, we found no regional difference in organic matter use for scarlett wrasse (Pseudolabrus miles) and leatherjackets (Parika scaber). N. fucicola and P. miles selectively forage for invertebrates around algal holdfasts (Russell 1983), and N. fucicola are more closely associated with macroalgae than other species (Davidson et al. 2014; Perez Matus & Shima 2010). Accordingly, their feeding is less likely to reflect the relative regional availability of carbon sources at the base of the food chain. N. fucicola and P. miles as well as blue moki (Latridopsis ciliaris) and tarakihi (Nemadactylus macropterus) occupied a significantly lower average trophic level in Marlborough relative to Fiordland. This likely indicates a difference in the prey items consumed as well as a regional difference in the structure of the invertebrate food web. L. ciliaris and N. macropterus often feed by filtering invertebrates out of the mud or sand (Russell 1983). The higher !15N values observed for these species in Fiordland may also be a result of greater detrital inputs to benthic invertebrate communities, as microbial breakdown of detritus can decrease !15N (Guest et al. 2008).

Our estimates of trophic positions of individual species generally corroborated previous studies and life history accounts (e.g. Lusseau & Wing 2006, Wing & Jack 2013). However, we found some interesting deviations. Specifically, in Fiordland the butterfly perch (Caesioperca lepidoptera) was estimated to obtain 43 % of its biomass from macroalgae despite being generally considered to be exclusively a zooplankton feeder (Francis 2001, Russell 1983). In the present study, C. lepidoptera were observed aggregating around E. radiata holdfasts in Fiordland and consequently are likely to feed on mesograzers of macroalgae present on fronds and in the surrounding water column. The observed result demonstrates the multiple channels by which macroalgae may enter the food web, and the potential dangers of assuming diets based solely on gut content analysis, or behavioural observations.

69 In our analysis of the herbivorous species, greenbone (Odax pullus) and marblefish (Aplodactylus arctidens), we found a significantly larger prevalence of organic matter from Undaria pinnatifida and Ulva spp. In the Marlborough Sounds for both species, where U. pinnatifida has extensively invaded subtidal reefs (Russell et al. 2008). As we were unable to distinguish between Ulva spp. And U. pinnatifida isotopically, this result could indicate an increase in the consumption of either of these species in the Marlborough Sounds. However, since we observed Ulva spp. In both regions, it is likely that in the Marlborough Sounds herbivorous fish were grazing on the large and highly palatable U. pinnatifida (South et al. 2017). Since herbivorous fish, as well as invertebrate grazers (Jimenez et al. 2015) likely feed on U. pinnatifida on invaded reefs, the species has the potential to augment natural fluxes of organic matter. U. pinnatifida can increase net primary production on invaded reefs, particularly in habitats from which native kelp has been lost (Valentine & Johnson 2005, James & Shears 2016). However due to its unique life history, with sporophyte growth primarily in winter, the prevalence of U. pinnatifida could alter the availability of macroalgal derived food at the regional scale (Jimenez et al. 2015, South et al. 2017). Its presence may affect the grazing community if there is insufficient biomass of native kelp to rely on when the biomass of U. pinnatifida declines in spring.

Variation in !13C and !15N among basal organic matter sources and reef fishes provided sufficient resolution to make conclusions on the relative importance of pelagic versus benthic sources of organic matter in supporting the fish community (Phillips & Gregg 2001), yet we were unable to resolve which macroalgae species were the most important among the higher trophic level fish species. In our analysis of fish trophic positions, we used a combined isotopic signature for macroalgae in the mixing models, based on the relative abundance of different macroalgae species at our study sites. Yet differences in production rates, palatability (Wessels et al. 2006) or carbohydrate content (Lamare & Wing 2001) may indicate that the density of different macroalgae species does not provide a good proxy for biomass of organic matter it contributes to the food web. If one species of macroalgae was contributing the majority of the biomass not in proportion to its abundance, then this would affect our estimates of the proportion of biomass supported by macroalgae.

In the present study, we present regional scale analysis of fish community trophodynamics. While there may also be considerable small-scale variability in organic

70 matter use within a region (Hamilton et al. 2011), it is likely to affect only relatively sedentary species (Wing et al. 2012). Macroalgae is assimilated into the food web predominantly through the detrital food web (Duggins et al. 1989, Krumhansl & Scheibling 2012). Hence, it provides a potential organic matter source for fish communities both within and adjacent to kelp forest habitats (e.g. Harrold et al. 1998). The large spatial extent of inputs of organic matter from macroalgae to coastal food webs indicates that a regional scale approach is most suitable when investigating the effect of macroalgae availability on fluxes of organic matter to widely distributed coastal reef fish communities.

The results of the present study demonstrate how the trophic structure, in particular, the relative importance of organic matter derived from macroalgae in supporting food webs underlying reef fish communities, can vary significantly between regions. The most likely explanation for the observed differences in reef fish trophodynamics is that the lower abundance of kelp beds in the Marlborough Sounds has resulted in simplified food webs with limited inputs from macroalgae. These patterns likely affect the trophic structure of the coastal ecosystem and contribute to relatively low fisheries productivity (Ware & Thomson 2005, Friedland et al. 2012). Our study demonstrates that input of benthic and pelagic sources of organic matter to food webs supporting reef fish communities can be highly variable over regional spatial scales. These observations have important implications for the spatial application of ecosystem based approaches to management of coastal resources, and highlight the important link between land based stressors and coastal productivity.

Chapter 4: Regional differences in the energetics of two temperate reef fish communities: implications for the loss of kelp forests

Kelp forest at the entrance to Doubtful Sound, Fiordland

73 4.1 Introduction Fisheries production is constrained by the amount of primary production available at the base of the food web (Downing & Plante 1993, Ware & Thomson 2005, Friedland et al. 2012, Watson et al. 2013). Additionally, differences in the trophic structure of the community affect how energy is transferred up the food web as well as the energy requirements of the community (Pauly & Christensen 1995). Anthropogenic impacts such as nutrient loading, increased sedimentation and climate change are altering the quantities of primary production in the world oceans (Johnson et al. 2011, Koenigstein et al. 2016, Krumhansl et al. 2016). As a consequence, elucidating the trophic structure of marine communities, and the sources of organic matter required to support them, is a vital part of the development of effective ecosystem based models for fisheries management and for predicting how changes to primary production may affect the functioning of marine ecosystems (Watson et al. 2013, Persson et al. 2014).

The two main sources of organic matter for temperate reef communities are phytoplankton and macroalgae (Duggins et al. 1989, Fredriksen 2003, Koenigs et al. 2015, Markel & Shurin 2015, von Biela et al. 2016). Macroalgae are extremely productive and provide an important autochthonous food resource (Mann 1973, Duggins et al. 1989, Koenigs et al. 2015). Macroalgae is consumed directly by some reef fish, and also by many invertebrates that then provide prey for reef fish (Graham 2004, Norderhaug et al. 2006, Davenport & Anderson 2007, Pérez-Matus & Shima 2010). Allochthonous phytoplankton production is more seasonally variable, yet is still an important source of carbon for many reef fish communities (Koenigs et al. 2015, Truong et al. 2017). Phytoplankton production is mainly utilised by reef fish through feeding on zooplankton, migrating pelagic fishes (Trebilco et al. 2016, Truong et al. 2017), or filter feeding invertebrates (Miller & Page 2012).

Lower-order consumers tend to derive the bulk of their organic matter from either phytoplankton or macroalgae (Rooney et al. 2006, Hamilton et al. 2014). As trophic level increases, consumers are supported by a mix of the available organic matter sources as the variety of prey types increases (McMeans et al. 2013, Koenigs et al. 2015). This coupling of different energy channels by top predators confers stability to the food web (Rooney et al. 2006). Theoretically, if higher trophic level consumers are better able to integrate prey, then

74 the food web should have a ‘hump shaped’ structure when graphed on axes of percent contribution of alternate organic matter sources versus trophic level (McMeans et al. 2013). Rooney et al., (2006) showed that this relationship is present across a diverse variety of ecosystems. If both sources of organic matter (macroalgae and phytoplankton) are sufficiently available top level consumers should be supported by an approximately equal mix of the two sources (Rooney et al. 2006).

As a result of their high trophic level, reef fish act as integrators of the flux of organic matter from macroalgae and phytoplankton (Thomas & Cahoon 1993, Vander Zanden & Vadeboncoeur 2002b, Hamilton et al. 2011). As most temperate reef fish employ generalist feeding strategies, their diets reflect the relative availability of their prey, and hence the relative availability of the organic matter sources that support the prey (Cowen 1986, McLeod et al. 2010a, Hamilton et al. 2011, Jack & Wing 2011). If one source is limited then you would expect the top predators to aquire the majority of their carbon from the most abundant source (McCann & Rooney 2009).

As energy is transferred up the food web, approximately 90% of energy is lost with each trophic transfer (Pauly & Christensen 1995, Ware 2000). As a consequence, the amount of base organic matter required to support a fish at trophic level 4 is an order of magnitude higher than the organic matter required to support a fish of equal biomass at trophic level 3. As higher trophic level fish require more energy to sustain them, if supply of one organic matter source is limited then as trophic level increases the proportion of carbon acquired from the most abundant source will increase (McCann & Rooney 2009). For temperate reef fish, if the local supply of organic matter is limited than high trophic level fish may utilize subsidies from external sources to meet their high energy demands (Trebilco et al. 2016).

Kelp forests are currently under threat from a variety of anthropogenic activities with evidence for widespread losses of kelp habitat along coastlines worldwide (Dayton et al. 1998, Steneck et al. 2002, Connell et al. 2008). As kelp can be an important organic matter source for many reef fish communities (Koenigs et al. 2015, von Biela et al. 2016) a reduction in kelp supply may affect the structure, stability and productivity of the reef food web (McMeans et al. 2013, Markel & Shurin 2015).

75 This study considered the temperate reef fish community of two coastal waterway systems on the South Island, New Zealand: the Marlborough Sounds and Fiordland. Although the Marlborough Sounds and Fiordland are characterised by similar fish species (Jack & Wing 2013, Davidson 2014) there are discrepancies in the trophic structure of the two reef fish communities, with intraspecific regional differences in trophic position (Chapter 3). Reef fish in the Marlborough Sounds use significantly less organic matter derived from macroalgae than in Fiordland, and some species occupy a significantly lower trophic level in Marlborough Sounds compared to Fiordland. Based on surveys of kelp density, we suggested that differences in trophic structure may be a result of a lack of macroalgae input to the food web in the Marlborough Sounds (Chapter 3). The observed lower kelp densities in the Marlborough Sounds, relative to Fiordland, are likely a result of anthropogenic induced stressors such as warming of the ambient sea surface temperature and increased fine sediment runoff (Hay 1990, Handley 2015). Hence, comparison of the energetics of the two reef fish communities provides insight into the implications of the loss of kelp forests.

The present study aimed to investigate how the observed differences in organic matter use and trophic level of temperate reef fish species between the two regions (Chapter 3), translates to differences in the stability and energetic requirements of the reef fish food web. In particular we asked whether the proportion of fish biomass supported by macroalgae versus phytoplankton is constant across trophic levels or if one source becomes more predominantly used by higher trophic levels, as a measure of the availability of the alternate sources. As a consequence of the loss of energy with trophic transfer, two fish communities of equivalent biomass may have different energy requirements if there are differences in the trophic structure of the two fish communities (Pauly & Christensen 1995). Further, this study aimed to investigate how the observed differences in relative abundance (Chapter 2) and trophic structure (Chapter 3) between the Marlborough Sounds and Fiordland affects the amount of organic matter required to support the alternate reef fish communities.

Stable isotope analysis provides a repeatable method for estimating an animal’s trophic position, as the isotopic signature of an animal’s tissues reflects that of its diet (Deniro & Epstein 1978, 1981). Phytoplankton and macroalgae each have characteristic $13C values, and thus the $ 13C of a consumer can be used to determine the relative contribution of organic matter derived from the alternate sources (Fry 2006). As there is a large predictable

76 increase in $ 15N with each trophic exchange, the $ 15N of a consumer’s tissues can be used to determine its integrated trophic level (McCutchan et al. 2003).

In the present study, we used stable isotope analysis to determine the trophic position of the most common species in the temperate reef fish communities of Fiordland and the Marlborough Sounds. We then combine information on density, per-capita biomass and trophic position of the reef fish species in each region to investigate how biomass is distributed across trophic levels in the reef fish community, and how much of the biomass at each trophic level is supported by macroalgae. A regional comparison of this relationship allowed us to address how limited local productivity, may affect energy flow through the food web. Information on the trophic level and relative biomass of each species was then used to estimate the amount of basal organic matter required to support the temperate fish communities on a per unit area basis. Here we are able to compare how regional differences in trophic structure relate to differences in the energy requirements of the two communities.

4.2 Methods

4.2.1 Surveys of reef fish density The density of reef fish in each region was estimated using underwater visual census. Divers using SCUBA recorded the abundance of all fish observed along belt transects (50 m long by 5 m wide by 2.5 m high) centred at 5 and 15 m depths. Four independent replicate transects were surveyed at each depth for each site. At some sites only three replicate transects were completed if the dive team had exhausted their air supply. The composition of diver teams identifying and counting fishes was kept constant between sites and regions for the duration of the study.

Diving surveys in the Marlborough Sounds were conducted during January 2017 (8 sites) and February 2018 (4 sites), and surveys in Fiordland were conducted during November 2015 (11 sites) and May 2017 (7 sites). Study sites in each region were stratified in a factorial design among exposed (generally more macroalgae) and sheltered sites (generally fewer macroalgae) and within fished and non-fished (marine reserve) areas, in order to sample a representative range of habitats (Figure 4.1)

Figure 4.1. Map showing the location of study sites in the Marlborough Sounds and Fiordland Marine Area, New Zealand. Symbols within each region represent sites in marine reserves (triangles) and fished areas (circles).

4.2.2 Trophic position of reef fish For each fish species observed on the belt transects a random sample of individuals was collected from each region, using a combination of hook and line and pole spears. Sampling was carried out under permit from the New Zealand Ministry of Primary Industries and under ethical approval from the University of Otago animal ethics committee (ET 21/11). Collection with pole spear enabled us to sample a similar size range for each species for each region. Fish were frozen and transported back to the Portobello Marine Laboratory where

78 dorsal muscle tissue samples were dried at 60 °C for 48 h, ground to a fine powder using mortar and pestle and 1mg subsamples were sealed into tin capsules for measurement of !13C and !15N.

Suspended particulate organic matter (SPOM) was collected from each site using a 20!"# plankton net vertically cast through the water column from 15 m to the surface. SPOM samples were passed through a 250!"# filter to remove zooplankton. For each macroalgal species present at a study site samples of blade tissue were collected from multiple individuals (n=5) stratified by depth. Samples of SPOM and macroalgae were dried at 60 °C for 48 h and ground into a fine powder using mortar and pestle. Powder from SPOM and macroalgae samples were weighed to 3 mg and sealed into tin capsules for measurement of !13C and !15N. See Chapter 3.2.2 for details of isotopic analysis.

Using the average !15N and !13C values for macroalgae and SPOM from each region, a mass balance mixing model was used to determine the contribution of different basal organic matter sources and the trophic level of each individual fish after (Jack & Wing 2011), see Chapter 3.2.3 for details.

4.2.3 Biomass distribution across trophic positions Average carbon biomass values for each fish species in each region, were calculated as outlined in Chapter 3.2.4. For each transect the abundance of each species was multiplied by the average per-capita biomass for that species. Species biomass on each transect was multiplied by the average proportion of biomass that was supported by macroalgae for that species (based on stable isotope calculations above). From these data the average biomass of each species, and the average biomass supported by macroalgae of each species was calculated for each region. Plots of cumulative fish biomass and cumulative fish biomass supported by macroalgae by trophic level, for both Fiordland and Marlborough, allowed visualisation of how the proportion of fish biomass supported by macroalgae changed with trophic level and of how the distribution of biomass across trophic levels differed between regions.

For each transect the total biomass, and the biomass supported by macroalgae was summed across species to give a total biomass (250m-2) and biomass supported by

79 macroalgae (250m-2). Dividing the amount of biomass supported by macroalgae by the total amount of biomass gave the proportion of biomass supported by macroalgae on each transect.

General linear models (JMP 11.0 SAS) with factors REGION (2 levels, fixed) and SITE

[REGION] (random) were used to test for regional differences in a) total fish biomass, b) fish biomass supported by macroalgae, c) fish biomass supported by SPOM and d) proportion of fish biomass supported by macroalgae.

The proportion of total cumulative fish biomass supported by macroalgae at each trophic level was calculated, and a general linear model with factors REGION (fixed, 2 levels) and TROPHIC LEVEL [REGION] (continuous), was used to test whether there was a relationship between the proportion of cumulative fish biomass supported by macroalgae and trophic level and whether the slope of the relationship differed between regions. Herbivores (Odax pullus and Aplodactylus arctidens) were excluded from this analysis.

4.2.4 Organic matter required to support reef fish community For each transect we calculated the amount of organic matter required to support the biomass of each species observed using the following formula, where TE is the transfer efficiency.

3*1ℎ!/*0#(11!(') %&'()*+!,(--.&!/*0#(11! ' = ! 78!9:;<=>?!@ABAC

Trophic level is calculated for each species assuming primary producers are at trophic level 0. Here we use the average transfer efficiency 0.1 for the transfer of energy between all trophic levels (Pauly & Christensen 1995, Ware 2000). The amount of organic matter biomass required to support each species was multiplied by the proportion of that species biomass supported by macroalgae, to give the amount of macroalgae biomass required to support each species. For each transect the biomass of organic matter, and the biomass of organic matter supplied by macroalgae was summed across species to give total organic matter biomass (250m-2) and organic matter biomass supplied by macroalgae (250m-2). Dividing the amount of organic matter supplied by macroalgae by the total amount of organic matter required gave the proportion of organic matter derived from macroalgae on each transect. The amount of organic matter derived from SPOM was calculated as the difference between total organic matter and organic matter supplied by macroalgae. General linear models (JMP 11.0 SAS)

80 with factors REGION (2 levels, fixed) and SITE [REGION] (random) were used to test for regional differences in a) total organic matter, b) organic matter derived from macroalgae, c) organic matter derived from SPOM and d) proportion organic matter derived from macroalgae.

As trophic efficiencies can vary between taxa and systems (Ware 2000, Barnes et al. 2010), we tested the sensitivity of our estimates of organic matter required to support the fish community to variability in transfer efficiency. We calculated organic matter required as above, but using transfer efficiency values ranging from 0.05 to 0.2 for the calculation of the organic matter biomass required to support each species (Barnes et al. 2010). General linear models (JMP 11.0 SAS) with factors REGION (2 levels, fixed) and SITE [REGION] (random) were used to test for regional differences in the total amount of organic matter required to support the fish community, as calculated using the range of reported transfer efficiencies.

4.3 Results The shape of the distribution of reef fish biomass across trophic levels varied between regions (Figure 4.2). The distribution of fish biomass extended to higher trophic levels in Fiordland than the Marlborough Sounds (Figure 4.2). In Fiordland, the highest average trophic level was 4.02 ± 0.51 (Hypoplectrodes huntii), while in Marlborough Nemadactylus macropterus occupied the highest average trophic level at 3.336 0.2316.

82 Total fish biomass (250 m-2) was significantly higher in Fiordland than the 2 Marlborough Sounds (F1, 189 = = 5.1618, p = 0.0308, R = 0.3711) (Figure 4.2, Figure 4.3 a). Along with the greater fish biomass, there was a greater amount of fish biomass 2 supported by macroalgae in Fiordland (F1, 186 = 12.96, p = 0.0012, R = 0.422), however there was no regional difference in the amount of fish biomass supported by SPOM (F1, 186 = 1.3624, p = 0.2527, R2=0.3313) (Figure 4.3 a). Consequently, macroalgae supported a greater proportion of total reef fish biomass in Fiordland (49.32 % ±!1.08!%) than in

Marlborough (33.57 % ±!0.62!%) (F1, 186 = 182.59, p < 0.0001) (Figure 4.3 b).

Figure 4.3. a) average fish biomass 250 m-2 (grey bars) and amount of fish biomass supported by macroalgae (black bars) and b) the proportion of fish biomass supported by macroalgae. Error bars indicate ±!1 SE, and asterisks indicate significant regional differences (p < 0.05).

Figure 4.4. Proportion of cumulative fish biomass supported by macroalgae versus trophic level for Fiordland (black circles) and the Marlborough Sounds (open circles).

There was a significant regional difference in the slope of the relationship between trophic level and the proportion of cumulative fish biomass supported by macroalgae (Main

Test: F3, 26 = 25.26, p < 0.0001; TROPHIC LEVEL [REGION]: F = 37.88, p < 0.0001; REGION: F = 30.16, p < 0.0001). In Marlborough, the proportion of cumulative fish biomass supported by macroalgae declined with increasing trophic level (t = -8.61, p < 0.0001), however in Fiordland there was no relationship between trophic level and proportion of cumulative fish biomass supported by macroalgae (t = -1.30, p = 0.2054) (Figure 4.4).

Using an average transfer efficiency of 10%, the Fiordland reef fish community required a greater biomass of base organic matter to support them than the Marlborough reef 2 fish community (F1, 189 = 11.257, p = 0.0022, R = 0.5816). The Fiordland fish community 2 incorporate more organic matter from macroalgae (F1, 189 = 17.5579, p = 0.0002, R = 0.6126) 2 and SPOM (F1, 186 = 7.3939, p = 0.0110, R = 0.5423) into biomass, on a per unit

85 area (250 m-2) basis (Figure 4.6 a). The fish communities in both regions derived over 50% of their organic matter from phytoplankton, although the proportion of organic matter derived from macroalgae was greater in Fiordland (46.41 % ±!0.75!%) than the Marlborough Sounds 2 (31.37 % ±!0.56!%) (F1, 189 = 75.3495, p < 0.0001, R = 0.8135). While the total fish biomass was only 1.72 times higher in Fiordland than the Marlborough Sounds, the Fiordland fish community consumed and integrated 2.91 times more organic matter. Further, the Fiordland fish community made use of 4.44 times more macroalgae and 2.29 times more SPOM than the Marlborough fish community.

86 Table 4.1. Results from GLMs on the regional difference in organic matter required to support the fish communities, as calculated using a range of values for trophic efficiency.

Transfer efficiency Effect size F1,189 p 0.05 3.73 12.96 0.001 0.075 3.21 12.02 0.002 0.1 2.91 11.26 0.002 0.125 2.71 10.61 0.003 0.15 2.57 10.06 0.004 0.175 2.46 9.59 0.004 0.2 2.37 9.18 0.005 !

The use of different transfer efficiencies for the calculation of organic matter needed to support the fish community altered the magnitude of the regional difference in organic matter required, due to regional differences in the distribution of biomass by trophic level (Table 4.1, Figure 4.7). However, the regional difference in organic matter required to support the fish community remained significant for transfer efficiencies ranging from 0.05 to 0.2 (Table 4.1).

87 4.4 Discussion The data and results presented here demonstrate that the observed differences in trophic structure between the Marlborough Sounds and Fiordland (Chapter 3), result in regional differences in the energetics of the temperate reef fish community. The relationship between macroalgae use and trophic level, distribution of biomass across trophic levels, and the amount of organic matter required to support the fish community differed significantly between the two regions.

A lower proportion of total fish biomass was supported by macroalgae in the Marlborough Sounds, relative to Fiordland. As the proportion of cumulative fish biomass supported by macroalgae declined with increasing trophic level in the Marlborough Sounds it suggests that the macroalgae production available to the fish community is limited. In Marlborough, the higher trophic level species increasingly rely on pelagic subsidies rather than autochthonous macroalgae to support them. As many high trophic level temperate reef fish, exhibit dietary shifts based on resource availability (Cowen 1986, Hamilton et al. 2011, Jack & Wing 2011a, Beer & Wing 2013b), the increased reliance of higher trophic levels on phytoplankton derived energy indicates that this is the most available resource based on the mobile consumer adaptive response hypothesis (McCann & Rooney 2009). By contrast, in Fiordland, the proportion of cumulative fish biomass supported by macroalgae does not change with trophic level, indicating there is sufficient macroalgae production available to the fish community to support the energy requirements of higher trophic level species. The Fiordland community matches theoretical predictions of coupling of different energy channels when both sources are equally available (Rooney et al. 2006).

Alternatively, the decreasing contribution of macroalgae to fish biomass as trophic level increases in the Marlborough Sounds may be due to a lack of transfer of macroalgae derived carbon to high trophic level species, rather than a lack of macroalgae production. Due to larger body sizes, herbivorous and omnivorous fish have lower predation rates than many zooplanktivorous fish (Russell 1983, Stevenson et al. 2007, Young et al. 2010, Truong et al. 2017), which could reduce the transfer of macroalgae derived carbon to higher trophic levels. However, fish on temperate reefs have been observed to feed mainly on invertebrates rather than fish (Page et al. 2013), with the high trophic level fish species in this study being generalist carnivores or omnivores rather than exclusive piscivores (Russell 1983, Jones

88 1988). As many reef invertebrates are supported by macroalgal derived organic matter (Hobson & Chess 2001, Koenigs et al. 2015), macroalgal derived organic matter would still be available to reef fish even in the absence of predation on herbivorous fish.

Allochthonous primary production from phytoplankton is a large organic matter source that may be adequate to support the fish community in the absence of macroalgae input (Cresson et al. 2014, Champion et al. 2015). Despite the input of macroalgae to the Fiordland system, phytoplankton still supports around half (50.68 %) of the fish biomass. This is consistent with other studies that report both phytoplankton and macroalgae production to be important sources of carbon for temperate reef fish communities (McMeans et al. 2013, Koenigs et al. 2015, Truong et al. 2017). If there is sufficient supply of phytoplankton, the increased reliance on pelagic subsidies in the Marlborough community may not affect the amount of fisheries production (Downing et al. 1990, Ware & Thomson 2005), though it is likely to reduce the stability of the food web (Rooney et al. 2006). Here fish community production, particularly production of high trophic level species is likely to be more variable than if the community was supported by a more equal mix of sources as it is more vulnerable to perturbations in pelagic productivity (Doak et al. 1998). As the species occupying the highest trophic levels in Marlborough are all exploited species; tarakihi (N. macropterus), kahawai (Arripis trutta), red moki (Cheilodactylus spectabilis) and blue cod (Parapercis colias), this may have implications for the stability of fisheries production.

The Fiordland fish community supported higher average fish biomass and more fish biomass at higher trophic levels, relative to Marlborough, and as a consequence required more organic matter to support the fish community. The total fish biomass was 1.72 times higher in Fiordland than the Marlborough Sounds, yet in Fiordland the fish community required 2.91 times more organic matter to support fish biomass. As 90% of energy is lost with trophic transfer (Pauly & Christensen 1995), the small regional differences in distribution of biomass across trophic levels translated to larger differences in the amount of organic matter required to support the fish community. The occurrence of greater biomass at higher trophic levels in Fiordland, relative to Marlborough, suggests there is greater base productivity in Fiordland, as food chain length is thought to be determined by base productivity (Oksanen et al. 1981, Persson et al. 1992, Vander Zanden et al. 1999). Consistent with the greater energy requirements of the Fiordland fish community, there was more organic matter supplied by both macroalgae and phytoplankton in Fiordland. Further,

89 there was a greater regional difference in organic matter supplied by macroalgae (4.44 times more in Fiordland) than phytoplankton (2.29 times more in Fiordland). The biomass of reef fish per unit area supported by organic matter derived from phytoplankton was equivalent between regions. Consequently, the difference in observed magnitude of reef fish biomass per unit area between the regions, is comprised of biomass supported by macroalgae. This result highlights the greater input of macroalgal derived carbon to the reef fish community in Fiordland, relative to Marlborough.

Community biomass is often thought to be a function of habitat productivity (Randall & Minns 2000), indicating that Fiordland is a more productive marine environment than the Marlborough Sounds. However, fish biomass may not be an appropriate measure of habitat productivity if one community is subject to higher levels of exploitation (Minns et al. 2011). Hence, the lower fish biomass in the Marlborough Sounds, relative to Fiordland, may alternatively be attributable to heavier fishing pressure as opposed to a reflection of the organic matter available. If this is the case, differences in the fish community between regions results in dramatic differences in how organic matter in both regions is converted into fish biomass.

Regardless of the trophic efficiency used to calculate the organic matter required to sustain the reef fish community, the energetic requirements of the Fiordland fish community were consistently higher than those of the Marlborough fish community. The magnitude of the regional difference however was affected by trophic efficiency, indicating we may have over or under estimated the amount of organic matter required by using the average 10% value for majority of calculations (Pauly & Christensen 1995). Further, as transfer efficiency may decrease with increasing trophic level (Ware 2000, Barnes et al. 2010), we may have underestimated the regional difference in organic matter use, as there is more biomass at higher trophic levels in Fiordland.

The present study only quantified fish biomass as opposed to quantifying fish production (i.e. the rate of creation of biomass). As fish biomass and fish production are correlated (Downing & Plante 1993, Randall et al. 1995), fish production is likely higher in Fiordland than the Marlborough Sounds. However, there are other variables that may affect the production-biomass ratio (Randall et al. 1995, Minns et al. 2011), and hence our estimates of total fish biomass may not directly reflect regional differences in fish production. There is

90 evidence that the growth rate of some temperate reef species increases with increased kelp use (Beer & Wing 2013, Markel & Shurin 2015), and hence the magnitude of the regional difference in fish production, may be larger than the regional difference in total fish biomass, as the Fiordland community utilizes more macroalgae derived carbon. The assumption that higher fish biomass relates to greater fish production is also dependent on the two communities having comparable average fish size (Randall et al. 1995). Inclusion of growth rates in further research would aid in establishing differences in the productive capacity of the fish community between Marlborough Sounds and Fiordland (Minns et al. 2011).

The estimates of biomass distribution amongst trophic positions in this study use regional averages for each species trophic position. Though our estimates include variation at the transect and site level based off different relative abundances of the reef fish species, the estimates do not include regional variation in trophic position. Although there may be considerable small-scale interspecies variation in trophic position within a region (Hamilton et al. 2011), due to the large spatial extent of inputs of organic matter from macroalgae to coastal food webs (Duggins et al. 1989b, Krumhansl & Scheibling 2012b), a regional scale approach to estimating organic matter fluxes is most suitable.

The results presented here demonstrate that there are differences in the energetics of the reef fish community between the Marlborough Sounds and Fiordland. The results provide further support for the hypothesis that the supply of macroalgae derived organic matter to the reef fish community is limited in the Marlborough Sounds, relative to Fiordland. Here there is likely an important interaction between differences in production in organic matter source pools, in this case low inputs from of kelp forests in the Marlborough Sounds region, and changes in reef fish community structure from fishing induced mortality. The result is a large difference in the volume of organic matter that is transferred into fish production between the two regions. If the lower input of macroalgae derived organic matter to the Marlborough community is a result of anthropogenic induced changes to macroalgae abundance, then the results highlight the implications of loss of kelp forests for food web stability and productivity. Regardless of the drivers of the observed energetic differences, the results emphasise the importance of considering regional variability in basal organic matter source pools when applying ecosystem based approaches to coastal resources.

Chapter 5: Synthesis

Sunset view from Polaris II, steaming back towards Dunedin

93 This thesis has utilised data from underwater visual census, combined with stable isotope analysis to investigate how reef fish community structure and food web architecture vary with fishing pressure and kelp abundance. Drivers of reef fish community structure were examined within and between the Fiordland and Marlborough Sounds regions, and regional differences in trophic structure and energetics of the fish community were evaluated.

The factor FISHING explained much of the observed variance in density of exploited fish species, with blue cod (Parapercis colias) displaying the biggest variation in density between reserves and fished areas. The results also indicate that fishing indirectly affects the non-exploited fish community as some non-exploited species and the structure of the non- exploited fish assemblage varied with FISHING within each region. Yet variation in the total density of non-exploited fish species was mainly explained by the factor KELP. Densities of the herbivorous sea urchin, Evechinus chloroticus, vary with FISHING, and consequently kelp holdfast density may also be influenced by fishing pressure. Significant interactions between the factors FISHING and KELP for explaining individual fish species density, and the non- exploited and exploited community assemblage, indicate that the presence of kelp bed habitat influences the observed effects of fishing. For blue cod, the most abundant exploited species, the difference in density between reserve and fished areas was greatest in barren habitats.

Significant KELP * FISHING interactions for the density of some of the non-exploited species, are consistent with the idea that the structural complexity provided by kelp alters interactions between exploited and non-exploited species.

Surveys of the benthic community revealed that Fiordland is characterised by high- density Ecklonia radiata beds extending down to the deep stratum (10-15 m), with some Carpophyllum machalocarpum and Macrocystis pyrifera in the shallow depth strata (< 5 m). In contrast, in the Marlborough Sounds there are high-density mixed kelp beds comprised of E. radiata, C. maschalocarpum and Undaria pinnatifida present in the shallow stratum, with only sparse holdfasts in the deeper quadrats. Differences in species composition, density or height of the kelp community may affect fish aggregation and habitat preference (Holbrook et al. 1990a, Carr 1991, Levin & Hay 1996). Hence the significant interaction between the factors KELP and REGION for explaining exploited and non-exploited fish community similarities, as well as the intraspecific regional variability in fish response to KELP, further support the idea that the kelp community varies between Fiordland and the Marlborough Sounds. In addition, the overall reef communities in each region match the communities

94 generally associated with kelp bed (Fiordland) and barren habitats (Marlborough) (Choat & Ayling 1987). On the regional scale the Fiordland reef community is characterised by low invertebrate and exploited fish density and high non-exploited fish density, while the Marlborough Sounds reef community has high invertebrate and exploited fish density and low non-exploited fish density. The observed patterns in invertebrate and fish abundance, as well as kelp holdfast density, suggest greater availability of suitable kelp bed habitat in the Fiordland region.

The effect of FISHING on density of individual fish species and overall fish community structure varied between Fiordland and the Marlborough Sounds. The REGION *

FISHING interaction was only significant for explaining differences in fish community structure, and not fish community composition, indicating that FISHING affected the same species within each region but there were regional differences in the magnitude of the

FISHING effect. The larger effect of FISHING on blue cod density in the Marlborough Sounds supports this assumption, indicating that the Marlborough Sounds are subject to higher fishing pressure than Fiordland. Additionally, regional scale differences in the quality and availability of kelp forest habitat may contribute to observed differences in the FISHING effect. The observed variation in reef fish density between regions, fishing zones and habitats suggest there is an interaction between habitat quality and fishing pressure for driving differences in fish community structure at both the local and regional scale.

In addition to regional variation in reef community structure, we find significantly different food web structure between Fiordland and the Marlborough Sounds. A comparison of the trophic position of 8 reef fish species common to both regions found that a majority of species were supported by a lower proportion of organic matter derived from macroalgae in the Marlborough Sounds relative to that observed in Fiordland. The banded wrasse (Notolabrus fucicola) was the only species that was linked to food webs supported by a higher proportion of organic matter derived from macroalgae in the Marlborough Sounds. Combining stable isotope data for all fish species present in each region, with species density and biomass information, revealed that a lower proportion of exploited and non-exploited fish biomass was supported by macroalgae in the Marlborough Sounds on a per unit area basis. As the diet of reef fish generally reflects resource availability (Cowen 1986, Hamilton et al. 2011, Jack & Wing 2011), we presented the hypothesis that there is lower macroalgae input to the food webs in the Marlborough Sounds relative to those in Fiordland.

95 The observed decline in organic matter derived from macroalgae with increasing trophic level in the Marlborough Sounds, provided further evidence of a lack of macroalgae input to the Marlborough fish community based on the mobile consumer adaptive response hypothesis (McCann & Rooney 2009). By contrast, the high trophic level fish in Fiordland utilised a relatively equal mix of organic matter derived from macroalgae and phytoplankton, suggesting that both sources are equally available. As a result of being supported by a combination of macroalgae and phytoplankton, reef fish production in Fiordland is likely linked to a less variable supply of organic matter, a property that leads to increases in food web stability (Doak et al. 1998, Rooney et al. 2006).

The regional variability in kelp abundance may be due to natural variation between the two regions, however evidence suggests that there has been substantial loss of kelp forests in the Marlborough region in recent years (Hay 1990, Handley 2016). If there has been a reduction in the input of organic matter derived from kelp to the food webs supporting the Marlborough Sounds fish community, this may have important implications for the productivity of the region. The observed higher trophic level of individual species, longer overall food chain length, and higher total fish biomass in the Fiordland region, indicate that Fiordland is a more productive environment than the Marlborough Sounds (Oksanen et al. 1981, Randall & Minns 2000). Here the biomass of reef fish per unit area supported by organic matter derived from phytoplankton is equivalent between regions. Therefore, the difference in observed magnitude of reef fish biomass per unit area between the regions, is comprised of biomass supported by macroalgae. Hence, we propose that regional differences in fish biomass may be a result of lower macroalgae production. This conclusion is supported by survey data of macroalgae density and species composition in each region.

However, as there were regional differences in the effect of fishing between the two regions, the variability in fish biomass may also be a result of fisheries induced mortality. Contrary to the results from the present study, anecdotal evidence, based on catch per unit effort measurements from fishers, indicates that in the early 1900’s there was greater fish abundance in the Marlborough Sounds than in Fiordland (Handley 2016). The decline in fish abundance is likely largely attributable to top down fishing induced changes. However, differences in the available organic matter sources, may have also driven bottom up control of the quantity of fish biomass. The result of these two processes acting together is that the

96 current fish community in the Marlborough Sounds has likely been shaped by a combination of fisheries mortality and habitat degradation.

Regardless of the drivers of regional differences in community and food web structure, the result is a large difference in the amount of organic matter that is transferred into fish production between the two regions. The total fish biomass per unit area was 1.72 times greater in Fiordland than the Marlborough Sounds, yet the Fiordland fish community utilised 2.91 times more organic matter, indicating a larger amount of biomass at higher trophic levels. The majority of this difference was contributed by macroalgae, with the Fiordland fish community utilising 4.44 times more macroalgal derived organic matter, and 2.29 time more phytoplankton derived organic matter than the Marlborough Sounds community. The present study cannot conclusively determine whether the observed differences in composition of organic matter supporting the two fish communities were driven by changes to macroalgae or phytoplankton availability. However, as phytoplankton supported the majority of fish biomass in both regions it is clearly an important organic matter source to the temperate reef fish community regardless of the availability of macroalgae. We suggest that there is likely an important interaction between differences in production in organic matter source pools, in this case low inputs from kelp forests in the Marlborough Sounds region, and changes in reef fish community structure wrought by fishing mortality, for controlling the biomass of reef fish populations.

The results of the present study corroborate the importance of kelps as foundation species on temperate reefs. Kelps influence reef fish community structure and provide an important source of organic matter to the food webs supporting the reef fish community. Accordingly, the maintenance of healthy kelp forests is essential for sustaining natural ecosystem integrity in rocky reef communities. The findings presented highlight the importance of including management of fish habitat in the management of fisheries (Minns et al. 2011). We find that marine reserves may afford some protection to the kelp community in southern New Zealand, as evidenced by higher kelp holdfast abundance within the Kokomohua marine reserve in Marlborough Sounds. However, in southern New Zealand, a model involving multiple effects, including environmental and climatic influences, catchment-derived sedimentation and reef fish and invertebrate species demographics would be more appropriate for predicting variation in kelp communities, than a simple trophic effects model (Schiel 2013). As such, management of the large range of stressors on kelp

97 forest communities is imperative to maintain ecosystem integrity on New Zealand’s rocky reefs.

The findings presented in this thesis indicate that marine reserve protection, increases the abundance of some exploited fish species, but may not be as effective for exploited migratory species. Further, comparison of the fish communities in reserve and fished areas, reveals that removal of a few target species is coincident with variation in densities of other fish species and herbivorous sea urchins. The current study supports the growing idea that marine reserves are a beneficial tool for achieving some of the goals of ecosystem based management (Cowan et al. 2012). Although when used as a single tool, reserves may not be effective in achieving successful ecosystem based management due to the multiple environmental stressors on marine communities (Halpern et al. 2010). The current thesis provides a new context for understanding how fishing and habitat degradation may synergistically affect reef fish communities in New Zealand, with implications for managing multiple stressors in the marine environment.

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