The Size-Based Ecosystems of Warm and Cold-Core Eddies Off Eastern Australia

The size-based ecosystems of warm and cold-core eddies off eastern Australia

Peter Garside

A thesis in fulfilment of the requirements for the degree of Master of Philosophy at The University of New South Wales.

School of Biological, Earth, and Environmental Sciences

Faculty of Science

June 2020

Thesis/Dissertation Sheet

Surname/Family Name : GARSIDE Given Name/s : Peter Jeffrey Abbreviation for degree as give in the University calendar : MPHIL Faculty : SCIENCE School : Biological, Earth and Environmental Sciences Thesis Title : The size based ecosystems of warm and cold core eddies off eastern Australia

Abstract 350 words maximum: (PLEASE TYPE) Mesoscale ocean eddies are commonly formed ocean habitats in the western Tasman Sea off the east coast of Australia. Ocean eddies form distinct ecosystems with elevated, or depleted productivity compared to the surrounding waters in a region that supports several ocean fisheries that are currently managed in real time by fisheries permits based on sea surface temperature and other satellite derived features that have been related to fish populations, but more details on the variable food-web parameters of ocean eddies would greatly benefit ecosystem based dynamic management strategies. I investigated two contrasting ocean eddies in the western Tasman Sea during September 2017, a cyclonic and anti-cyclonic eddy, using a size-based approach and stable isotope analysis of 15N, to identify a normalised biomass size-spectra (NBSS) and significant linear relationships between trophic level and body-size from primary producers to mesopelagic fishes. After correcting for differences in ẟ15N of Particular Organic Matter (POM, at the base of the food web), I derived estimates of predator prey mass ratios (PPMR), food-chain lengths (FCL), and trophic transfer efficiencies (TE) for each of the eddy food webs. The biological community within a cyclonic eddy had a higher enrichment of ẟ15N resulting in increased trophic level with body-size when compared to an anti-cyclonic eddy. This resulted in a PPMR that was 7.5 times larger in the cyclonic eddy, and a TE that was approximately half as efficient than the contrasting anti-cyclonic warm-core eddy. Comparisons of two warmer water in the northern Tasman Sea eddies, with two similar eddies in the cooler waters to the south showed that the northern eddies influenced by tropical waters and the EAC had PPMRs 2.5-3 times larger than the eddies with the same rotational direction in the Tasman Sea. Furthermore, estimated trophic transfer efficiencies of both anti-cyclonic eddies were approximately double that of the cyclonic eddy in the same region of the Tasman Sea. Food chains were longer in both anti-cyclonic eddies than in the cyclonic eddies, with greater transfer efficiencies corresponding to a smaller PPMR brought on by higher levels of predation and carnivory. Identifying patterns between habitat type and food-web dynamics such as predator-prey relationships and transfer efficiencies of biological communities in the Tasman Sea would provide additional information to improve upon current dynamic ecosystem-based ocean models and benefit fisheries management into the future.

Declaration relating to disposition of project thesis/dissertation

I hereby grant to the University of New South Wales or its agents a non-exclusive licence to archive and to make available (including to members of the public) my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known. I acknowledge that I retain all intellectual property rights which subsist in my thesis or dissertation, such as copyright and patent rights, subject to applicable law. I also retain the right to use all or part of my thesis or dissertation in future works (such as articles or books).

…………………………………………………………… ……….……………………...…….… Signature Date The University recognises that there may be exceptional circumstances requiring restrictions on copying or conditions on use. Requests for restriction for a period of up to 2 years can be made when submitting the final copies of your thesis to the UNSW Library. Requests for a longer period of restriction may be considered in exceptional circumstances and require the approval of the Dean of Graduate Research.

INCLUSION OF PUBLICATIONS STATEMENT

UNSW is supportive of candidates publishing their research results during their candidature as detailed in the UNSW Thesis Examination Procedure.

Publications can be used in their thesis in lieu of a Chapter if: • The candidate contributed greater than 50% of the content in the publication and is the “primary author”, ie. the candidate was responsible primarily for the planning, execution and preparation of the work for publication • The candidate has approval to include the publication in their thesis in lieu of a Chapter from their supervisor and Postgraduate Coordinator. • The publication is not subject to any obligations or contractual agreements with a third party that would constrain its inclusion in the thesis

Please indicate whether this thesis contains published material or not:

This thesis contains no publications, either published or submitted for publication ☒ (if this box is checked, you may delete all the material on page 2)

Some of the work described in this thesis has been published and it has been documented in the relevant Chapters with acknowledgement ☐ (if this box is checked, you may delete all the material on page 2)

This thesis has publications (either published or submitted for publication) ☐ incorporated into it in lieu of a chapter and the details are presented below

CANDIDATE’S DECLARATION I declare that: • I have complied with the UNSW Thesis Examination Procedure • where I have used a publication in lieu of a Chapter, the listed publication(s) below meet(s) the requirements to be included in the thesis. Candidate’s Name Signature Date (dd/mm/yy) Peter Jeffrey Garside

‘I hereby grant the University of New South Wales or its agents a non-exclusive licence to archive and to make available (including to members of the public) my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known. I acknowledge that I retain all intellectual property rights which subsist in my thesis or dissertation, such as copyright and patent rights, subject to applicable law. I also retain the right to use all or part of my thesis or dissertation in future works (such as articles or books).’

‘For any substantial portions of copyright material used in this thesis, written permission for use has been obtained, or the copyright material is removed from the final public version of the thesis.’

Signed ……………………………………………......

Date ……………………………………………......

AUTHENTICITY STATEMENT ‘I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis.’

Signed ……………………………………………......

Date ……………………………………………......

ORIGINALITY STATEMENT

‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

Signed ……………………………………………......

Date ……………………………………………......

< PAGE INTENTIONALLY LEFT BLANK >

Acknowledgements

This research was supported by the Australian Institute of Nuclear Science and Engineering (AINSE) Honours Scholarship Program.

Thank you to my supervisor Iain Suthers for taking the chance and giving me this amazing opportunity. The patience, guidance and support will always be greatly appreciated. Also, I would like to acknowledge my other supervisors Debashish Mazumder and Jason Everett for the revisions, advice, and time they have put into this thesis with me. It was a longer journey than we expected but we made it in the end. Additionally, I want to acknowledge the huge help I received from Lian Kwong, Natasha Henschke, and Kieran Murphy who shared their wisdom, ideas, and findings from the eddies that we are investigating together. Also, Andrew Stewart, who helped guide my fish identification skills on board the Investigator, and Alan McLennan for making the introduction that started this whole journey.

I am greatly appreciative of the hard-working researchers of the FAMER Lab at UNSW who answered questions, helped with technical expertise, and created a welcoming friendly environment. A special thanks to all of my friends who volunteered to help me on my project, all the research staff, crew, and friends I made on the RV Investigator in 2017 who made this whole project possible, and all of the staff that assisted me at ANSTO during my work there.

Abstract

Mesoscale ocean eddies are commonly formed ocean habitats in the western Tasman Sea off the east coast of Australia. Ocean eddies form distinct ecosystems with elevated, or depleted productivity compared to the surrounding waters in a region that supports several ocean fisheries that are currently managed in real time by fisheries permits based on sea surface temperature and other satellite derived features that have been related to fish populations, but more details on the variable food-web parameters of ocean eddies would greatly benefit ecosystem based dynamic management strategies. I investigated two contrasting ocean eddies in the western Tasman Sea during September 2017, a cyclonic and anti-cyclonic eddy, using a size-based approach and stable isotope analysis of 15N, to identify a normalised biomass size-spectra (NBSS) and significant linear relationships between trophic level and body-size from primary producers to mesopelagic fishes. After correcting for differences in ẟ15N of Particular Organic Matter (POM, at the base of the food web), I derived estimates of predator prey mass ratios (PPMR), food-chain lengths (FCL), and trophic transfer efficiencies (TE) for each of the eddy food webs. The biological community within a cyclonic eddy had a higher enrichment of ẟ15N resulting in increased trophic level with body-size when compared to an anti-cyclonic eddy. This resulted in a PPMR that was 7.5 times larger in the cyclonic eddy, and a TE that was approximately half as efficient than the contrasting anti-cyclonic warm-core eddy.

Comparisons of two warmer water in the northern Tasman Sea eddies, with two similar eddies in the cooler waters to the south showed that the northern eddies influenced by tropical waters and the EAC had PPMRs 2.5-3 times larger than the eddies with the same rotational direction in the Tasman Sea. Furthermore, estimated trophic transfer efficiencies of both anti-cyclonic eddies were approximately double that of the cyclonic eddy in the same region of the Tasman Sea. Food chains were longer in both anti-cyclonic eddies than in the cyclonic eddies, with greater transfer efficiencies corresponding to a smaller PPMR brought on by higher levels of predation and carnivory. Identifying patterns between habitat type and food-web dynamics such as predator-prey relationships and transfer efficiencies of biological communities in the Tasman Sea would provide additional information to improve upon ii

current dynamic ecosystem-based ocean models and benefit fisheries management into the future.

iii

Table of Contents

Acknowledgements ...... i

Abstract ...... ii

List of Figures ...... vii

List of Tables ...... x

Chapter 1 – General Introduction ...... 1

Food webs of the mesopelagic ocean ...... 1 Stable isotopes in ecosystem studies ...... 3 Size-based food web analysis ...... 6 Pelagic Habitats of the western Tasman Sea ...... 8 Ocean fisheries of the Tasman Sea ...... 12 Thesis aims ...... 14 Chapter 2 – Food web structure of contrasting mesoscale eddies of the EAC ...... 15

Abstract ...... 15

Introduction ...... 16

Size-structured marine ecosystems ...... 16 Using Stable Isotopes to determine trophic structure ...... 17 Quantifying ecosystem processes ...... 18 Methods ...... 20

Study area ...... 20 In-situ Oceanographic Sampling ...... 20 Estimation of eddy biomass ...... 22 Stable isotope analysis of biological communities ...... 23 Trophic level calculations ...... 25 Calculation of food web metrics ...... 26 Statistical analysis ...... 27 Results ...... 29

Biomass and NBSS ...... 30 Stable Isotope Analysis ...... 31 Trophic level – body mass relationships ...... 36 Estimation of ecosystem metrics ...... 37 Discussion ...... 39

Ecosystem metrics of contrasting mesoscale eddies ...... 39 Body-Size based trophic ecology of mesoscale eddies...... 40 Comparisons with previous studies ...... 42 Conclusion and remarks ...... 43 Chapter 3 – Comparison of size-based eddy ecosystems: Warm-core eddies have longer food- chains and greater transfer efficiency than cold-core eddies ...... 45

Abstract ...... 45

Introduction ...... 46

Methods ...... 49

Study area...... 49 Community Sample Collection ...... 50 Normalised Biomass size spectra ...... 52 Stable Isotope Analysis ...... 52 Trophic level calculations ...... 54 Calculation of food-chain metrics ...... 54 Results ...... 55

Oceanographic characteristics ...... 55 Zooplankton and fish communities ...... 57 Normalised biomass size-spectra (NBSS) ...... 60 Stable Isotope Analysis ...... 61 Community Trophic Level – Body Size Analysis ...... 64 Estimates of ecosystem food chain metrics ...... 66 Discussion ...... 67

Potential areas of uncertainty ...... 70

Concluding remarks ...... 71 Chapter 4 – General Discussion ...... 73

Oceans of eddies ...... 73

Pelagic ecosystem structure...... 75

Broader findings of the four mesoscale eddies ...... 78

Thesis Limitations and Considerations ...... 79

Final Thoughts on the global impacts of this research ...... 81

References...... 83

Chapter 2 - Appendix ...... 99

Appendix 2A – Length Weight Relationships for fish species ...... 99 Appendix 2B – List of samples and results of stable isotope analysis...... 100 Appendix 2C – Trophic level comparisons (TLs vs TLc) ...... 117 Chapter 3 - Appendix ...... 119

Appendix 3A – Trophic level comparisons (TLs vs TLc)...... 119 Appendix 3B – List of samples and results of stable isotope analysis ...... 120

List of Figures

Figure 1.1: A simplified representation of a pelagic food web in the tropical Pacific Ocean from producers through to apex predators. Arrows point from the prey to the predator (from Belgrano et al., 2005; chapter 12)...... 2 Figure 1.2: Illustration summarising the diurnal and vertical trophodynamics of some major epipelagic predators off eastern Australia, showing the relative sizes (50 cm range) and fish-squid composition (% biomass). From Young et al. (2010)...... 3 Figure 1.3: Example of trophic enrichment of δ15N in two species of fish (Walleye and Yellow Perch) plotted against the mean δ15N of the baseline reference organism, in this case filter feeding mussels. From Cabana and Rasmussen (1996)...... 6 Figure 1.4: Dynamic ocean habitats of the Tasman Sea classified for each month of 1995(Hobday et al. 2011). The seven habitats are represented by a colour and a number in the colour bar, based on 5 oceanographic variables (Bathymetry, SST, temperature at 250m, chlorophyll and nitrite climatology)...... 9 Figure 1.5: Diagram of surface currents and circulations of the EAC region of the South Pacific. Solid red lines represent permanent currents; dashed lines represent transient currents; red and blue circles represent warm, and cold core eddy fields. From Oke et al. (2019)...... 12 Figure 2.1: Location of sampling sites within the western Tasman Sea during sample collection period 31 Aug - 18 Sept 2017 A) Satellite derived sea surface temperature (SST); B) MODIS Chlorophyll-a; and C) Sea Level Anomaly (SLA). Eddy centre marked for CCE (  ), and WCE (  )...... 21 Figure 2.2: Depth profiles for each eddy showing A) mean temperature (°C), and B) mean Salinity (PSU) in the top 1000 m of the CCE eddy (solid blue line) and WCE eddy (solid red line). C) mean temperature, and D) mean salinity in the top 300 m. Sample collection took place in the top 100 m of each eddy...... 29 Figure 2.3: Biomass (mg m-3) of (A) zooplankton sampled in the MOCNESS (n=1) and, (B) all fish collected in MIDOC trawls of the top 100 m of the two eddies. Biomass was corrected for volume filtered by the trawl nets...... 30

vii

Figure 2.4: Normalised Biomass Size Spectra (NBSS) of the two eddies. Biomass of the zooplankton and fish communities in each eddy were binned into size classes and normalised by dividing the biomass of each bin by the width of the bin. The dashed line represents separate NBSS for zooplankton (left side), and fish communities (right side) separately...... 31 Figure 2.5: Stable Isotope Analysis of fish, zooplankton, and Particulate Organic Matter (POM). A) Mean values (±SD) of δ15N (‰) vs. δ13C (‰) for each of the functional groups, B) Mean enrichment (±SD) in δ 15N and δ13C for each of the functional groups, and adjusted for the baseline POM values. Expressed as Δ15N (‰) and Δ13C (‰). .... 33 Figure 2.6: Relationship between body-size(g) and mean (+/- SD) stable isotope composition of A) δ15N; and B) δ13C for zooplankton (⚫) and fish (▲). Lines represent linear regression relationships in the CCE (blue) and WCE (red)...... 34 Figure 2.7. Comparison of the trophic levels of zooplankton and fish in the WCE and CCE. A) Mean trophic position of each major functional group, and B) mean trophic position of each size class. Values expressed are mean TL (±SD). The dashed reference line represents the midpoint where TL in both the CCE and WCE would be equal...... 36 Figure 2.8: Relationship between body size (g) and mean trophic level (±SD) of the mesopelagic communities sampled within both eddies. The maximum body size class represented is from the 8-16 g size class for both eddies. Trophic levels were calculated using the scaled fractionation approach. Dashed lines represent the relationships of the zooplankton and fish communities separately...... 38 Figure 3.1: Satellite based imagery of (A) mean Sea Surface temperature (SST), (B) Ocean colour (Chlorophyll-a), and (C) Sea surface anomaly (SSA) of four mesopelagic eddies sampled during the September 2017 RV Investigator voyage (31-Aug to 19- Sept 2017). Each eddy was sampled between dusk and dawn. ○ = NCC, ◊ = NWC, □ = SCC, Δ = SWC...... 51 Figure 3.2: Depth profiles for each eddy taken from CTD casts showing A) mean temperature(°C), and B) mean Salinity, and C) Mean Fluorescence in the top 1000 m; and D) mean temperature, E) mean salinity, and F) mean fluorescence in the

viii

top 300m of the NCC eddy (solid blue line), NWC eddy (solid red line), SCC eddy (dashed blue line), and SWC eddy (dashed red line). Biological samples were taken from the top 100m of each eddy at night...... 56 Figure 3.4: Comparison of (A) Total biomass of zooplankton captured in the EZ net (n = 1, mg m-3), and (B) mean biomass of fish (mg m-3 ±SD) captured using the pelagic trawl (see section 2.2 for sampling methods). All samples were captured in the top 100 m of water at night...... 58 Figure 3.5: NMDS ordination of family diversity similarity for pelagic trawls in each of the four eddies. Data was transformed using a 4th root transformation...... 59 Figure 3.6: Normalised Biomass Size Spectra (NBSS) of zooplankton and fish from four mesoscale eddies sampled in the western Tasman Sea. A) Cold-core eddies; and B) Warm-core eddies. Dashed line has been added as a reference...... 61 Figure 3.7: Mean (±SD) Stable Isotope values of δ15N (‰) vs. δ13C (‰) all fish and zooplankton size classes of all four eddies. A) NCC, B) NWC, C) SCC, D) SWC. Diagonal dashed line added for reference...... 63 Figure 3.8: Linear relationships between A) mean δ15N and body-mass and B) mean δ13C and body-mass, derived from stable isotope analysis of the zooplankton and fish sampled in the top 100 m of each eddy. Error bars represent one standard deviation from the mean...... 64 Figure 3.9: Linear regression relationships between mean trophic level (±SD) and body mass for the entire community of each of the two cold-core eddies (Top) and the two warm-core eddies (Bottom). Dashed lines show the separate relationships for zooplankton and fish communities...... 66 Figure 4.1: Global observations of the formation of eddies with a lifespan >16 weeks. Obersvations were made over a 16 year period from October 1992-December 2008. Each dot represents number of eddies formed within 1 x 1° regions of the global oceans. Dot colour represents number of eddies formed from 1 (blue) to 4 (red) eddies per region. From Chelton et al. (2011b)...... 74

List of Tables

Table 2.1: Number of samples in each taxonomic group and size-class processed for stable isotope analysis for the WCE and CCE...... 28 Table 2.2: Mean stable isotope values for each taxonomic group within the CCE and WCE (±SD), n-sample size, and range of isotopic values in permil (‰). Values in bold indicate significant difference between eddies (P <0.05). POM was assumed to be TL = 1 for the purposes of isotopic baseline...... 35 Table 2.3: Results of linear regression analysis of the relationship between trophic level and body-size class between the WCE and CCE. b = slope of linear relationship. NS = Non- significant, ...... 37 Table 2.4: Summary of the estimated food chain metrics of the two eddies derived from linear relationships between body size and trophic level for the entire community ...... 38 Table 3.1: Sampling methods for nekton, zooplankton and particulate organic matter (POM) used on board RV Investigator in September 2017 voyage...... 52 Table 3.2: Summary of average (SD) of temperature (°C), salinity and Fluorescence (mV) in the upper 100 m. The Mixed Layer Depth (MLD) calculated from the minimum depth to which T < T(10 m) − 0.4°C (Henschke et al. 2019, Condie and Dunn, 2006) ...... 56 Table 3.3: Percentage of each family of fish abundance in the total catch from the pelagic trawls of each eddy (i.e. collected at night in the top 100m of each eddy). Dominant taxa are in bold. Shannon’s diversity index (H) is calculated for the fish families in each eddy...... 59 Table 3.4: linear relationships for normalised biomass size spectra (NBSS) for each of the four eddies derived from linear regression relationships of zooplankton and micronekton biomass in logarithmic size bins...... 60 Table 3.5: Mean (± SD) isotopic value of δ15N and δ13C for all samples taken from each of the four eddies, with minimum and maximum isotopic value of all samples. Isotopic values expressed are in permil (‰). Significant difference between eddies is denoted by differing letters...... 62 Table 3.6: Mean trophic level (±SE) estimated from stable N isotope analysis for each log2 body-size class sampled in each eddy...... 65

Table 3.7: Ecosystem metrics derived from the linear relationship between trophic position and body-size for each of the four eddies...... 67

Chapter 1 – General Introduction

Food webs of the mesopelagic ocean

The global oceans cover more than 70% of the earth’s surface and support a massive biomass of small pelagic fish (or baitfish), including the lanternfish (myctophids) and bristlemouths (gonostomatids). It is suggested, based on comprehensive bioacoustics observations of global tropical and subtropical oceans, that the mesopelagic zone (200 – 1000 m deep) supports the largest biomass of fish on the planet (Irigoien et al., 2014). The bioacoustic data from these global observations indicated that the previously estimated biomass of mesopelagic fish based on catch-rates and large scale ecosystem models, could be underestimated by at least an order of magnitude (Irigoien et al., 2014). In the Tasman Sea alone, estimations of micronekton biomass vary greatly up to a factor of 58 based on the sampling method chosen, with up to 29 g m-2 of mesopelagic fish being estimated by bioacoustics compared to 0.5 – 3 g m-2 estimated from ecosystem models (Kloser et al., 2009). The discovery of these new biomass estimates has re-emphasised the importance of mesopelagic fish populations in ecosystem food chains as they are key in understanding the trophic connections from primary producers, to the predators of the ocean food webs.

The implications of this discovery are widespread, from a more thorough understanding of carbon sequestration in the abyssal deep (Kwong et al. 2020), to respiration by microbial food webs, and the understanding of food web dynamics (Jennings et al. 2015). Another key insight of the discovery by Irigoien et al., (2014) was that the estimated transfer efficiencies between predator and prey – i.e. between zooplankton, fish, and their predators, may be inaccurate based on the substantial underestimation of mesopelagic fish biomass. Irigoien et al. (2014) suggested that transfer efficiency may be greater in the blue ocean than on the more turbid and productive shelves. In order to better understand the role that the mesopelagic fish play in the oceans, we need to consider the energy flow of entire ecosystem food webs from producers to predators, and not just focus on the fish alone.

Food web analysis involves an understanding of the biological transfer rates of ecosystems based on the predator-prey interactions, where consumers are generally one or two steps

1 Chapter 1 – General Introduction

above their prey in the trophic structure (Anderson et al, 2009; Lindeman 1942). The trophic structure of an ecosystem describes the pathways of energy flow from producers to consumers, where each subsequent trophic level (TL) of the food web represents another step of energy assimilation from prey to consumers. Traditionally, predator-prey interactions have been identified through a dietary analysis of gut contents (e.g. Bernal et al., 2013; Pakhomov et al., 1996; Young et al., 2010), where the sampling and identification of prey species within the stomachs of consumers provides a snapshot consumer feeding, so substantial repetition of samples is required. However, sampling gut contents over a long time period is logistically expensive and difficult at large scales which makes capturing the temporal variations in the diets of consumers, and therefore the feeding ecology of entire marine habitats, expensive and time consuming. The development of novel techniques in assessing and predicting the dietary dynamics of fish in response to ontogeny, season, and abundance of predators and prey (also known as trophodynamics) will add to the existing research and will greatly benefit the current understanding of the impacts of dynamic marine habitats on the small mesopelagic fish assemblages which are the primary subject of my thesis, as well as the top marine predators that feed on them (Young et al. 2015).

2 Chapter 1 – General Introduction

Marine ecosystems are complex systems where predator-prey interactions determine the food web structure and efficiency of energy transfer (Belgrano et al., 2005; Everett et al., 2017) (Fig. 1.1). Classifying each species in a pelagic ecosystem into functional groups (e.g. carnivores, omnivores, or herbivores, planktivores, piscivores etc.) is also difficult since feeding strategies often change based on season, life history stage, body size and with availability of prey. For example, large, commercially targeted fish species may be considered apex predators as adults, but the same species can be planktivores or omnivores during a young stage (Hughes et al., 2013; Young et al. 2015). Understanding trophodynamics in marine food webs is particularly useful for examining short-term (diurnal) changes in foraging which is important to consider, as vertical migrations of both predators and prey, plays a significant role in the ecology of many pelagic species (Fig. 1.2, Young et al. 2010; Kwong et al., 2020;).

Stable isotopes in ecosystem studies

Stable isotope analysis (SIA) of the relative body composition of naturally occurring isotopes in consumer organisms is one key advance in recent decades to understanding the integration and assimilation of energy into food webs. SIA has many benefits compared to traditional gut content analysis including being able to trace the assimilation of energy from the diet (Cabana and Rasmussen 1996; Vander Zanden and Rasmussen, 2001).

Figure 1.2: Illustration summarising the diurnal and vertical trophodynamics of some major epipelagic predators off eastern Australia, showing the relative sizes (50 cm range) and fish-squid composition (% biomass). From Young et al. (2010).

3 Chapter 1 – General Introduction

SIA provides an alternate method for investigating trophic ecology at a large scale to quantify the structure of food webs (Peterson & Fry, 1987). SIA quantifies the relative concentration of heavier stable isotopes compared to lighter isotopes of an element, expressed in delta (δ) notation, and reported in parts per thousand (‰). Isotopes of different elements have different properties that make them useful for determining characteristics of ecological communities. For example, large differences between marine and terrestrial isotopic values of sulphur stable isotopes (δ34S), makes it useful to determining sewage and other terrestrial- based contaminants in marine environments (Gaston et al., 2004). In food web ecology, the relative isotope ratios of 13C:12C and 15N:14N (δ13C and δ15N) that naturally occur in plant and animal tissues provide indicators of trophic level and food web nutrient sources (Cabana and Rasmussen, 1996; Caut et al., 2009; Vander Zanden and Rasmussen, 2001). These isotope ratios provide an isotopic signature that can be traced in organisms to determine trophic levels of consumers and visualise food chain links which create the pathways of energy transfer through a food web from primary producers to consumers (Boecklen et al., 2011).

Nitrogen stable isotope ratios are used to indicate the trophic level (TL) of organisms as well as provide a representation of energy flow within an ecosystem. The concentration of δ15N within a fish increases due to biophysical and biochemical steps as the nutrient is assimilated after feeding. A higher concentration of δ15N represents a higher TL since consumers will become enriched in δ15N on average by 3-4‰ per trophic level relative to prey, this is known as trophic fractionation, or trophic enrichment (Minagawa and Wada, 1984; Peterson and Fry, 1987; Post, 2002). The ratio of carbon isotopes (δ13C) changes relatively little on average 0- 1‰ (DeNiro & Epstein, 1978) as prey is consumed by a predator. This makes it very useful for determining the diet sources of an ecosystem. In terrestrial ecosystems, δ13C is often used to differentiate between diets based on plants with different photosynthetic pathways (C3 (e.g. wheat, rice) or C4 (eg. corn); Post 2002; Minagawa and Wada, 1984), and can be used to detect anthropogenic impacts such as sewage discharge in marine ecosystems (Gaston et al. 2004; Piola et al. 2006).

4 Chapter 1 – General Introduction

The concentration of stable isotopes within a fish’s tissue is ultimately representative of its food source. Consumers will have an enriched concentration of δ15N (denoted as Δ15N) and δ13C (Δ13C) relative to their food source, which is represents a stepwise enrichment in isotopic signature, known as trophic fractionation (Post, 2002; Vander Zanden and Rasmussen, 2001). The level of enrichment for each ecosystem will vary based on many different factors, including primary producers, prey type and abundance, the prevalence of feeding strategies such as omnivory and many other factors. This variation gives each food web a different level of enrichment at each successive TL, known as the trophic enrichment factor (TEF) (Hussey et al., 2014; Peterson and Fry, 1987; Post, 2002; Vander Zanden and Rasmussen, 2001). The widely used TEF for aquatic food web studies is 3.4‰ for δ15N, and 1‰ for δ13C (Vanderklift and Ponsard 2003; Caut et al. 2009), meaning with each additional TL consumers will be enriched, relative to their food, by approximately 3.4‰ and 1‰ in Δ15N and Δ13C respectively (Vander Zanden and Rasmussen, 2001).

Figure 1.3: Example of trophic enrichment of δ15N in two species of fish (Walleye and Yellow Perch) plotted against the mean δ15N of the baseline reference organism, in this case filter feeding mussels. From Cabana and Rasmussen (1996).

5 Chapter 1 – General Introduction

In order to accurately estimate TL, the isotopic concentration of consumers must be compared with isotopic values from organisms with a known trophic level at the base of the food web. This baseline, or reference value could come from particulate organic matter (Iken et al .2009), herbivorous grazers, (Post, 2002), or filter feeding primary consumers (Cabana and Rasmussen 1996; Jennings et al., 2015; Fig. 1.3). These reference organisms are essential when comparing trophic levels between different ecosystems.

Whilst the constant TEF above (3.4‰ for δ15N, and 1‰ for δ13C) are widely accepted and used in aquatic stable isotope analysis, TEF values can vary greatly among taxa, food sources, and environments, and is influenced by the body-size of consumers (Caut et al., 2009; Henschke et al., 2015; Hussey et al 2014; Mazumder et al., 2016). The use of constant TEFs that are based on the global mean for aquatic ecosystems can result in the underestimation of TLs, particularly in marine environments where species feed opportunistically on a wide variety of prey types (Caut et al., 2009; Hussey et al., 2014). Hussey et al. (2014) developed a method for estimating TLs in marine ecosystems that uses a scaling TEF, which is designed to consider the varying TEFs and provide more reliable TL estimates from marine stable isotope analysis. Scaling the TEF for marine food webs becomes particularly important at higher TL and larger body sizes where consumers have more prey options.

Size-based food web analysis

Body-size is another potential method for determining the TL of an organism. It is the key factor in determining the organismal rates of respiration, metabolism, movement, and prey selection (Brown et al., 2004, Blanchard et al. 2017, Jennings et al 2001a; 2002), and is often considered the “master trait” of an ecosystem as it is a powerful way to examine the flux of energy pathways through ecosystems due to the natural size-structure of pelagic ecosystems (Andersen et al., 2016; Jennings et al., 2001a; Potapov et al 2019). By condensing the thousands of species-based interactions into size-classes, the number of controlling processes and predator-prey interactions within the food web are vastly reduced while the core influencing factors affecting the food web structure are maintained (Blanchard et al 2017; Jennings et al. 2001; 2002a). While this approach excludes species-specific information, it provides a simple and logistically tractable view of the complex ecological and physiological

6 Chapter 1 – General Introduction

structure of aquatic communities (Pauly et al., 1998; Polovina and Woodworth-Jefcoats, 2013).

The size-based ecosystem theory is based on Sheldon et al. (1972), who observed equal biomass and declining abundance of plankton in logarithmic body size bins (commonly called the size-spectra). Sheldon et al. (1972) recognised that this relationship would not only hold for plankton but would be accurate for organisms of all body sizes, from bacteria to whales (Everett et al. 2017; Blanchard et al. 2018). This distribution follows a reduction in total biomass as body-size increases, since predators usually consume smaller size prey (Barnes et al., 2010, Mehner et al., 2018).

Jennings et al. (2001; 2002a; 2002b; 2008) was the first to combine the size-based theory of Sheldon et al., (1972), with stable isotope analysis to determine the trophic level (TL) of organisms based on δ15N. In a bench-mark study, Jennings et al. (2001) captured up to 48 species of fish and elasmobranchs with a benthic trawl in heavily fished areas of the North Sea and Celtic Sea. They determined the δ 15N (TL) composition of each species and assigned them to 15 size classes from 1 g up to nearly 33 kg. This study established that body size provides a powerful tool for assessing trophic levels and predator prey interactions in marine ecosystems. Their innovation was how the high variability in the TL of species was transformed into a linear relationship between TL and body size class (Jennings et al. 2001).

The work on ecosystem size-structure by Jennings and colleagues has also proven to be useful for predicting ecosystem properties under continued stressors, such as climate change (Jennings et al., 2008) and commercial fishing (Jennings and Blanchard, 2004; Jennings and Collingridge, 2015). Jennings and Blanchard (2004) used size-based ecosystem data of the North Sea to derive ecosystem metrics of predator-prey body mass ratios (PPMRs), and transfer efficiency between trophic levels (trophic transfer efficiency (TE)). These metrics along with size-spectra data provided the ability to estimate fish abundance size spectra of an un-fished North Sea. This work estimated that the biomass of large fish (from 4 – 66 kg) in the North Sea at the time (2004), was up to 99 % lower than it would be in an unexploited condition, and that many studies that had previously underestimated this depletion. The extensive applications of the work of Jennings and colleagues coupled with SIA makes a size-

7 Chapter 1 – General Introduction

based approach to food web analysis extremely beneficial for understanding and managing marine ecosystems present, and future.

Pelagic Habitats of the western Tasman Sea

The Tasman Sea is dominated by a strong western boundary current, the East Australian Current (EAC), which transports warm, oligotrophic water from the Coral Sea down the eastern coast of Australia. Several distinct oceanographic habitats have historically been identified in the region based on remotely sensed patterns in temperature, salinity, and ocean bathymetry (Cresswell 1994, Hobday and Hartmann, 2006). These habitats have been used in the past to classify coastal blooms of gelatinous zooplankton (Henschke et al., 2011) and larval fish habitats (Mullaney et al. 2011). More recently, seven dynamic offshore habitats across the broader Tasman Sea have been identified and tracked remotely based on variation in five satellite derived oceanographic variables including SST, temperature at 250 m, chlorophyll-a and nitrite climatology (Hobday et al., 2011; Fig. 1.4). The identification and monitoring of these habitats in real time using satellite imagery have greatly improved the management regulation in the Tasman Sea (Hobday et al, 2011). This thesis examines two common ocean habitats of the western Tasman Sea - cyclonic and anti-cyclonic ocean eddies.

Eddies have been identified to form in all parts of the global oceans (Chelton et al., 2011b). Global studies of ocean eddies have associated both warm and cold-core eddies with steep gradients in zooplankton biomass between the eddy and the surrounding waters (Condie and Condie, 2016; Weibe et al., 1976; 1985). In the Tasman Sea the EAC produces a particularly large number of eddies, which distinguishes it from other western boundary currents around the world (Wilkin & Zhang 2008; Suthers et al. 2011; Oke et al 2019b). The EAC separates from the New South Wales coast between approximately 30 - 34°S and forms the Tasman Front (also known as the EAC Separation zone; Oke et al., 2019a; 2019b; Ridgeway and Dunn 2003), producing a high frequency of mesoscale eddies in the region known as “Eddy Avenue'' (Everett et al., 2012; Oke et al., 2019a; 2019b; Fig. 1.5). These eddies have been tracked as they flow into the EAC’s southern extension and towards Tasmania. This high degree of eddy activity supports the planktonic and fish communities of the region (Bakun 2006; Godø et al. 2012; Everett et al., 2012). From a biological perspective, eddies can enrich pelagic ecosystems

8 Chapter 1 – General Introduction

through a combination of upwelling, entrainment, and retention of nutrient rich waters from the continental shelf (Everett et al. 2015).

Figure 1.4: Dynamic ocean habitats of the Tasman Sea classified for each month of 1995(Hobday et al. 2011). The seven habitats are represented by a colour and a number in the colour bar, based on 5 oceanographic variables (Bathymetry, SST, temperature at 250m, chlorophyll and nitrite climatology).

Cyclonic eddies in the southern hemisphere are uplifting favourable and therefore tend to have cooler, denser surface waters, resulting in a depressed sea surface and sometimes referred to as cold-core eddies. Due to upwelling of nutrients and environments that promote primary production through Ekman pumping, cyclonic eddies are sometimes tinged with

9 Chapter 1 – General Introduction

green with phytoplankton which can be observed with satellite imagery. Anticyclonic eddies (warm core eddies) are downwelling favourable and therefore tend to have warm surface waters, with an elevated surface level (Everett et al., 2012; 2014; Gaube et al., 2014; Karstensen et al., 2017). Due to the downwelling, oligotrophic environments they often have reduced primary production and are sometimes suggested to be biological deserts (Suthers et al. 2011), but depending on coastal entrainment and surface capping with warm water, they can appear to be productive (Waite et al. 2007; 2019).

As the oceans change due to global trends of warming sea temperatures the habitats of the Tasman Sea are expected to shift. With predictions of a strengthening EAC extending southward (Suthers et al., 2011), and projected changes to Tasman Sea eddies under climate change projections we expect to find an increase in eddy lifespan and frequency (Oliver et al., 2015). Through the examination of gut contents analysis (Young et al., 2010; 2011), and biochemical trophic markers in predatory fish (Parrish et al., 2015; Pethybridge et al., 2015) and zooplankton (Henschke et al., 2015) in the Tasman Sea, a change in the water temperature and the expansion of oligotrophic habitats will have a noticeable impact on the species composition of lower trophic level organisms, leading to a shift towards more carnivory within ocean zooplankton food webs (Henschke et al., 2015; Laiolo et al., 2016), and subsequentially altering the diets of top predators such as tuna (Parrish et al., 2015; Pethybridge et al., 2015; Young et al., 2010).

In addition to tracking distinct oceanographic habitats in the Tasman Sea, Hobday et al., (2011) determined a relationship between the physical habitats with the biological communities. Combining satellite-based habitat prediction with existing stable isotope data of δ15N and δ13C for fish caught in the region, resulted in an improvement of up to 40% in identifying the presence of targeted fish species. Species within these distinct habitats share more similarities in isotopic composition than with individuals from other habitats (Hobday et al., 2011), this identifies that each unique habitat has different trophodynamics that form over time. This is also confirmed by a similar finding (Revill et al., 2009) that predatory fishes north and south of the Tasman Front have different muscle isotope values as a result of extended residence times in a particular habitat. If regular migration between habitats was occurring isotopic signatures would be “blurred” between regions (Revill et al., 2009).

10 Chapter 1 – General Introduction

Based on satellite tagging and stable isotope composition of large pelagic predators (Young et al. 2011, Hobday et al. 2011) the numerous pelagic habitats of the Tasman Sea have shown ecological significance for fisheries in eastern Australia, however a more detailed look into how the low to mid trophic level organisms affect the structure and efficiency of distinct food webs is warranted. Fisheries rely on these trophic levels to transport valuable nutrients up to the top predators, so quantifying ecosystem based differences in the trophodynamics of micronekton and microzooplankton and their effects on carbon transport, transfer efficiencies and other food web parameters will provide much needed information on why these habitats have different impacts on fisheries. With a clearer biological understanding of the dynamic habitats of the Tasman Sea, and a recent shift to ecosystem based fisheries management strategies, tracking the physical characteristics of dynamic marine habitats can be linked to the biological characteristics to provide near real time predictions of food web efficiency and productivity.

11 Chapter 1 – General Introduction

Figure 1.5: Diagram of surface currents and circulations of the EAC region of the South Pacific. Solid red lines represent permanent currents; dashed lines represent transient currents; red and blue circles represent warm, and cold core eddy fields. From Oke et al. (2019).

Ocean fisheries of the Tasman Sea

The open ocean regions of the Tasman Sea are important for supporting the considerable fishing industries within Australian waters, contributing to the nation’s $48 billion a year Blue Economy (NSMC, 2015). Determining its source and flow of energy and nutrients through fisheries food webs is important because it allows us to predict population responses to environmental and anthropogenic impacts on the targeted fish species and the lower trophic level fish on which they feed. This is the basis for ecosystem-based fisheries management (EBFM), as opposed to single-species fisheries management strategies that have traditionally been used to manage fishery stocks (Pikitch et al., 2004; Dunn et al., 2016; Hobday et al., 2014).

Over the past few decades, there have been significant advances, towards a more ecosystem focussed approach to fisheries management world-wide (Dunn et al., 2016; Lewison et al., 2015; Pikitch et al., 2004). In Australia, fisheries incorporate ocean conditions such as temperature, salinity, and chlorophyll to identify shifting ocean habitats, and to restrict fishing bycatch of the protected Southern Bluefin Tuna (Thunnus maccoyii) during migration through long line fishing zones (Hobday and Hartmann, 2006). Whilst the use of physical ocean variables are used to detect and track ocean habitats, and fish stocks are monitored through mortality modelling and catch per unit effort (CPUE) strategies, there is still a significant lack of knowledge on the overall ecosystems, and the food webs, that support these vast fisheries.

The many large predatory fish species that are targeted by national fisheries depend on the massive assemblages of zooplankton and small midwater fish which make up the food webs between primary producers and the apex predator fishes (Young et al. 2010, 2014). The midwater planktivorous fish that are estimated to have the largest biomass of all fish contribute to sustain large commercial fisheries by forming a vital link in the food chain (Irigoien et al., 2014; et al. 2014; Young et al. 2011; 2015). However, the efficiency of energy transfer through these pelagic food webs and the trophic structure of midwater fish

12 Chapter 1 – General Introduction

communities are largely unknown, since many of them have opportunistic feeding behaviours as both omnivores and carnivores (Jennings et al. 2008, Young et al., 2010a). Due to inadequate data, many fisheries models resort to allocating small-sized zooplankton to the same role as phytoplankton, and larger zooplankton to the grouping of small fish. This increases the potential for inaccuracies as it completely ignores the trophic interactions that are occurring between these taxa (Heneghan et al. 2016; Blanchard et al. 2017).

The Eastern Tuna and Billfish Fishery (ETBF) operates year-round in most regions of the Tasman Sea and Coral Seas generating around $38M pa (ABARES, 2019), 0.1% of the Blue Economy. The primary target species of the ETBF include several high trophic level predators such as Yellowfin Tuna (Thunnus albacares), Striped Marlin (Kajikia audax), and Albacore Tuna (Thunnus alalonga). These targeted fish are near apex predators of the pelagic ecosystems, feeding primarily on the pelagic fish and squid of the open ocean. Gut contents analysis of ten of the most abundant fish species caught by longline fisheries conducted by Young et al. (2010b) indicate that all the species fed on a diverse range of micronekton, fish, squid, and crustaceans. There was ontogenetic variation in diet from crustaceans or small fish to squid (Revill et al. 2009). The primary food for albacore was fish north of Tasman Front, with larger individuals feeding on a larger proportion of squid south of the Tasman Front (Revill et al. 2009). The main prey taxa of these pelagic predators were carangid and scombrid ﬁshes, and ommastrephidae squid species which are known to be predators of smaller species towards the lower trophic levels such as myctophids and zooplankton (Young et al., 2010a; 2010b).

For half of each year, the cooler waters in the southern regions of the ETBF are a known migratory habitat of Southern Bluefin Tuna which itself has a large economic value (approximately $36 Million) in the Australian Southern Bluefin Tuna Fishery (ABARES, 2019). The overlap in the two fisheries has resulted in the division of fisheries management zones and a restriction on fishing for the ETBF based on ocean temperatures (Hobday and Hartmann, 2006, Hobday et al., 2011; ABARES, 2019). Whilst this uses remote sensing data to determine fishery management strategies, it also highlights the benefits of dynamic ecosystem-based fisheries management (EBFM) strategies based on habitat preference of non-target or highly vulnerable species. Ultimately, the connections between ocean habitats and the ecosystem food webs contained within requires further investigation.

13 Chapter 1 – General Introduction

Since food web function and predator-prey relationships underpin many current ecosystem models further study (Pethybridge et al., 2015), fine scale analysis of trophic level relationships and food web structure is beneficial for large scale predictions and estimates of biomass and transfer efficiencies (Jennings et al., 2002b; Blanchard et al., 2017). The addition of food web characteristics, such as predator-prey mass ratios, to ecosystem management models has been used previously to predict global patterns in biomass, production, and trophic structure (Jennings et al., 2008), and calculate trophic transfer efficiency (Jennings et al., 2002b). in the Tasman Sea region, previous work on zooplankton size structure in the western Tasman Sea has demonstrated a relationship between the biophysical aspects (i.e: sea-surface temperature, chlorophyl concentrations, and surface level anomaly) and zooplankton community size spectra characteristics (White, unpublished thesis, 2018). Based on this previous work, examining the size-structured pelagic eddy ecosystems of the Tasman Sea and identifying habitat based variations in food web structure and function can be connected to the biophysical characteristics of the region in order to model and estimate the condition, location and biomass of fisheries stocks in a changing ocean environment.

Thesis aims

The overall goal of this research is to compare the ecosystem food-web structure and trophic transfer efficiencies of contrasting eddy habitats of the Tasman Sea. To accomplish this goal, my thesis will:

1. Use stable isotope analysis of nitrogen and carbon to estimate the trophic level-body size relationships and size-based ecosystem of a cyclonic and anticyclonic eddy off eastern Australia (Chapter 2). 2. Derive ecosystem estimates of predator-prey mass ratios (PPMR), Trophic Transfer Efficiencies (TE), and food-chain lengths (FCL), for each of the studied eddies (Chapter 2). 3. Provide a broader comparison of the mesopelagic fish community, and the derived ecosystem metrics between two eddies north of the Tasman Front, with two other eddies in the cooler waters of the western Tasman Sea (Chapter 3)

14 Chapter 2 - Food web structure of contrasting mesoscale eddies

Chapter 2 – Food web structure of contrasting mesoscale eddies of the EAC

Abstract

Mesoscale ocean eddies are commonly formed by the East Australian Current (EAC) in the western Tasman Sea. These eddies form distinct biological communities and have either elevated, or depleted productivity based on the eddy rotation. Using a size-based approach and a trophic level analysis based on the stable isotope composition, I identify significant relationships between trophic level and body-size for the zooplankton and mesopelagic fish communities of a cyclonic (cold-core) eddy and an anticyclonic (warm-core) eddy. These trophic level – body size relationships were used to calculate ecosystem estimates of predator prey mass ratio (PPMR), trophic transfer efficiency (TE), and food-chain length (FCL) for both eddies. The zooplankton and small fish community of the cold-core eddy had a higher concentration of ẟ15N resulting in a more rapid increase in trophic level with body-size compared to the warm-core eddy. This resulted in a PPMR that was 7.5 times larger than the warm-core eddy and a TE that was 1.8 times lower than the warm-core eddy, indicating less energy transfer passing from prey to predator over a smaller food chain length. The analysis of ocean habitats using this size-based method, rather than a species-based approach, quantifies complex ecosystems to enable ecosystem models used in fisheries management. Identifying how different habitats affect these metrics provides a means to relate an ecological perspective with satellite imagery in a warming ocean.

15 Chapter 2 - Food web structure of contrasting mesoscale eddies

Introduction

The biomass of the ocean’s large pelagic predators such as tuna and billfish depend on the vast amounts of energy from zooplankton and small pelagic fish lower in the food-chain. These smaller consumers act as a conduit for energy between the primary producers and the larger species at the top of the food chain (Young et al., 2010; 2014). Small pelagic fish are thought to have the largest biomass of all fish (Irigoien et al., 2014; Young et al. 2011; 2015) however the complexity of the food web and largely unknown efficiency of energy transfer that occur within pelagic food webs create uncertain biomass estimates for fisheries (Jennings et al. 2008). This food-web complexity arises due to the myriad of species and feeding strategies employed at lower trophic levels such as grazing omnivory and carnivory depending on the environment (Cherel et al., 2010; Choy et al., 2012; Henschke et al., 2015; Kozlov, 1995; Pakhomov et al., 1996; Parry, 2006).

Size-structured marine ecosystems

Using a size-based approach to describe food webs is one approach to remove the complexity associated with marine food webs. By condensing the thousands of species-based interactions into size-classes, the number of controlling processes and predator-prey interactions within the food web are vastly reduced while the core influencing factors affecting the food web structure are maintained (Blanchard et al 2017; Jennings et al. 2001; 2002a). Marine ecosystems are strongly size structured ecosystems, and body size is often described as the ‘master trait’, where body size determines key aspects of an organism's life history (Blanchard et al., 2017). Body size regulates an organism’s metabolism, mobility, development, and more importantly, what it can eat – the relative size of predator to prey (Andersen et al., 2015; Blanchard et al., 2017). By regulating an individual’s life-history, body size has an important community-wide effect on abundance (Andersen and Beyer 2006; Blanchard et al., 2009), biomass (Han and Straškraba, 1998; Jennings et al., 2002; Jennings and Collingridge, 2015, Sheldon, 1972), and trophic position (Jennings et al., 2001; Jennings and van der Molen, 2015; Ou et al., 2017; Potapov et al., 2019). A size-structured approach, simplifies many of the

16 Chapter 2 - Food web structure of contrasting mesoscale eddies

possible food web connections into a single linear food chain, creating an opportunity to estimate predator-prey interactions and energy transfer through the food-web.

When the biomass of an ecosystem is split into logarithmic body size classes, a linear relationship between biomass and body size is established (Blanchard et al., 2017; Edwards et al. 2017; Sheldon et al., 1972). The distribution of biomass with body size is referred to as the Normalised Biomass Size Spectrum (NBSS). The NBSS is characterised by a negative slope, describing the loss of energy from prey to predator through the food chain (Edwards et al. 2017; Han and Straškraba, 1998; Kerr and Dickie, 2001). This size-spectra approach is therefore a useful method to assess the trophic-structure of an ecosystem and detect natural and anthropogenic disturbances to population biomass such as fishing at the top of the food chain, (Blanchard et al., 2017; Jennings and Blanchard, 2004; Shin et al., 2005), or increased production at the bottom of a food chain (Basedow et al., 2014). The details of the community’s size-spectra can be combined with trophic level estimates of organisms in each size class to identify relationships and key metrics that describe the trophic structure and efficiency of an ecosystem.

Using Stable Isotopes to determine trophic structure

The stable isotope composition of nitrogen provides continuous empirical estimates of an animal’s trophic level (TL) and reflects their diet over a period of days to months (Hobson and Welch, 1992; Zanden and Rasmussen, 1999). An estimate of TL is possible due to metabolic effects that result in the retention of the heavier 15N isotope compared to 14N (expressed as δ15N), which increases in the consumer as trophic position increases (Peterson and Fry, 1987, Post, 2002). This process typically reveals a stepwise enrichment between 1‰ and 5‰ in δ15N concentration from prey to predator and is referred to as trophic fractionation, or the trophic enrichment factor (TEF; Minagawa and Wada, 1984, Post, 2002, Zanden and Rasmussen, 1999). The high variability in δ15N is due to diet quality (McMahon et al., 2015), environmental factors such as temperature (Barnes et al., 2007), and δ15N content of the primary food source (Owens, 1987).

A constant trophic enrichment factor of 3.4‰ has commonly been adopted by ecologists based on mean differences in δ15N values between prey and consumer tissue (Peterson and

17 Chapter 2 - Food web structure of contrasting mesoscale eddies

Fry, 1987, Post, 2002). However, recent literature indicated that trophic fractionation does not increase consistently with trophic level (Caut et al., 2009, Hussey et al., 2014). A new approach adopts a scaled fractionation relationship, to negate the inflated Δ15N predicted in constant fractionation relationships (Hussey et al., 2014). The scaled fractionation model features a diminishing trophic fractionation value, such that with each successive step in the food chain δ15N increases in progressively smaller increments.

Estimating trophic level from δ15N requires a known trophic level organism to act as a baseline to compare organisms to, in many previous studies this is usually a primary consumer such as a filter feeder, or grazing consumer that assimilate N from a variety of sources (Jennings and van der Molen, 2015), capturing variation in primary production at the base of the food chains. Pelagic ecosystems however are dominated by a single type of primary production in the form of phytoplankton, with additional nitrate sources such as upwelling, and detritus which is generally combined into the particulate organic matter (POM) sound in the oceans (Dorado et al., 2012; Wada and Hatori, 1976). Pelagic food web analysis commonly adopts particulate organic matter (POM) as a proxy for phytoplankton (Dorado et al. 2012; Lorrain et al., 2015). Similar metabolic principles driving δ15N fractionation also cause the concentration of the carbon isotope ratio (δ13C) to increase by a factor on average of 0.4 ‰ (DeNiro and Epstein, 1978, Fry and Sherr, 1989) in oceanic systems (France et al., 1998). The trophic fractionation value can be used to determine an individual’s primary diet source (Post, 2002) and provides useful information on feeding dynamics by supplementing TL estimates (Boecklen et al., 2011).

Quantifying ecosystem processes

The size-distribution of an ecosystem, and the trophic level of each size-class, provides a good understanding of energy flow and trophic structure of an ecosystem. From this understanding yields the predator-prey mass ratio (PPMR) which reveals the predator-prey interactions of an ecosystem that ultimately determine energy transfer from prey to a consumer (Jennings and Warr, 2003; Mehner et al., 2018; Trebilco et al., 2013). The PPMR then provides the trophic transfer efficiency (TE) that quantifies how much of prey production is transferred to the predators between successive trophic levels, and the food chain length (FCL) of the ecosystem

18 Chapter 2 - Food web structure of contrasting mesoscale eddies

that describes how many steps of inefficient energy assimilation there are from the bottom to the top of a food web (Barnes et al., 2010). Together, the PPMR, TE, FCL are key ecosystem metrics which can be used to inform models and improve fisheries stock assessments, enhance understanding of ecosystem stability, and influence decision making for fisheries management and environmental conservation (Barnes et al., 2010; Sheldon et al., 1972; Blanchard et al., 2009; Jennings and Blanchard, 2004; Jennings et al., 2015).

The size-distribution and energy flow of an ecosystem are strongly determined by the habitat and the influencing factors from the surrounding environment. Due to different inputs and predator prey interactions the flow of energy through an oligotrophic (low nutrient) environment will be very different to a eutrophic environment (high nutrient) (Belgrano et al., 2005; Gaube et al., 2014; Kemp et al., 2001). Since the Tasman Sea, and the global oceans (Chelton et al, 2011b), are dominated by eddies that supports often distinct biological communities, it is important to identify and understand how these formations impact the trophic ecology of the ecosystems. The influence eddy rotation has on the entire eddy community from primary producers to predatory fish is poorly understood, with the majority of research in the Tasman Sea region being focused on zooplankton and primary production (Everett et al., 2012; Henschke et al., 2019, 2015; Taylor et al, 2010), or on larger commercially targeted fish species (Brandt et al., 1982; Young et al., 2010; 2015). Here I investigate the size- based ecosystem of two contrasting eddies, linking the zooplankton and micronekton communities, to determine the trophic structure of two eddy environments. Comparisons of the ecosystem metrics that describe predator prey interactions and energy transfer will provide a greater understanding of the habitat efficiencies of the Tasman Sea. Specifically, I aim to:

1) Use the stable isotope analysis to estimate consumer trophic level and estimate ecosystem metrics of predator-prey mass ratio (PPMR), trophic transfer efficiency (TE) and food chain length (FCL) within two eddies. 2) Compare the body size and trophic level (TL) relationships of the biological communities within the eddies to model food web and energy pathways within both eddy ecosystems.

19 Chapter 2 - Food web structure of contrasting mesoscale eddies

Methods

Study area

Sample collection took place during a 19-day voyage on board Australia’s Marine National Facility (MNF) vessel the RV Investigator. Sampling was conducted from 2 - 10 September 2017 in an anti-cyclonic eddy (warm-core eddy, WCE), approximately 200 km offshore from Newcastle (33.2’S, 154.7’E), and a cyclonic eddy (cold-core eddy, CCE) located off the coast of Brisbane (27°6’S, 156° 3’E) in the western Tasman Sea (Fig. 2.1). The CCE formed approximately 5 months prior to sampling in early April 2017 and was beginning to decay, as noted by an increasing sea level anomaly during sampling (Kwong et al., 2020). The WCE was a younger eddy formed by the retroflection of the EAC as it flowed east at the Tasman Front (~33 °S).

In-situ Oceanographic Sampling

A Seabird 9 Conductivity-Temperature-Depth (CTD) probe equipped with a Chelsea Aqua- Tracker Mk3 fluorometer, mounted on a sampling-rosette, was deployed between the surface and 1000 m within each eddy to measure in-situ temperature, salinity, fluorescence, and oxygen. Mixed layer depth (MLD) for each eddy was calculated (Condie and Dunn, 2006), where MLD was the depth where the temperature was less than the surface temperature (10 m) minus 0.4 °C (MLD = TMLD < T10m – 0.4 °C, where T is temperature).

Particulate organic matter Particulate organic matter (POM) was collected from water samples collected in Niskin bottles attached to the CTD rosette. Water samples were collected from surface waters (5 m) and the chlorophyll-a maximum (~ 75 m). The CTD deployments were timed to coincide with EZ net and Danish Trawl deployments for fish and zooplankton (see below). Four litres of water were filtered using 47 mm diameter pre-combusted, and acidified glass fibre filters (GF/F) using a low-pressure vacuum pump. Filtered samples were then frozen at -20 °C until preparation for stable isotopes analysis.

20 Chapter 2 - Food web structure of contrasting mesoscale eddies

Figure 2.1: Location of sampling sites within the western Tasman Sea during sample collection period 31 Aug - 18 Sept 2017 A) Satellite derived sea surface temperature (SST); B) MODIS Chlorophyll-a; and C) Sea Level Anomaly (SLA). Eddy centre marked for CCE (  ), and WCE (  ).

Zooplankton Zooplankton was sampled at night in the top 100 m of water using a 1 m2 Multiple Opening- Closing Net and Environmental Sensing System (MOCNESS) with five remotely operated 500 µm mesh nets down to 500 m deep. For logistical reasons only one tow was made in each eddy. A digital General Oceanics (Florida, USA) flowmeter recorded the flow and volume filtered. The net was towed at approximately 3 knots, with the last net (the subject of this study) sampling from 100 m deep to the surface. A 20 cm diameter, 100 µm plankton net was mounted inside the MOCNESS. Each zooplankton sample was sorted into size groups by gently rinsing through a stacked column of sieves providing zooplankton biomass in 5 size classes: 125-250, 250-500, 500-1000, 1000-2000, and 2000-4000 µm. The two smallest size classes were derived from the 100 µm mesh net, and the 3 larger size classes were from the MOCNESS nets. Each size group was stored on pre-weighed petri dishes and were oven-dried at 60 °C for 48 hours. Each petri dish was weighed to the nearest 0.01 g before being frozen at -20 °C until preparation for stable isotope analysis.

21 Chapter 2 - Food web structure of contrasting mesoscale eddies

Fish and micronekton The fish and micronekton communities within each eddy were sampled at night using a 157.5 m2 mouth opening, Danish pelagic trawl net between 100 m and the surface (3 In the CCE and 2 In the WCE). Mesh size of the trawl reduced from 200 mm stretched mesh width at the mouth to 10 mm in the codend. At the codend was a MIDwater Open and Closing (MIDOC) net system with six cod-ends graduating from 10 mm mesh to 500 µm mesh. This study analysed the sixth, and final, cod-end which sampled from 100 m deep to the surface. Volume filtered was calculated for each codend by multiplying the net mouth area by speed and duration of trawl. All samples were collected at night in order to capture taxa that vertically migrate through the water column to epipelagic waters. Due to logistical constraints, sampling within each eddy took place across two consecutive nights.

Once retrieved the cod-ends samples were immediately placed on ice and sorted on board in accordance with an approved protocol (UNSW Animal Care and Ethics approval 17/91A). Each catch was sorted into broad morphotypes of fish, squid, crustaceans, and jelly. Those catches weighing more than 5 kg in total were subsampled prior to sorting. In this study, all individual fish in the catch (or subsample) were further identified to the lowest possible taxonomic level before being photographed for later reference, and then frozen on board at -20 °C.

Estimation of eddy biomass

Zooplankton biomass in each size class was determined from the dry weight of zooplankton catch from the MOCNESS. Dry weight was converted to wet weight using a conversion ratio of 0.171 for crustaceans which made up the majority of the catch (Young et al. 1996) and adjusted for volume filtered. For the smallest plankton net being nested within the MOCNESS, the volume filtered was calculated as a proportion of the 1 m2 mouth area of the MOCNESS.

Total fish community biomass for each size class was calculated by analysing photographs of the catch and estimating weight using length-weight relationships derived from linear regressions of standard-length vs weight. Relationships were derived for common species found within each trawl catch by weighing selected individuals that represent the range of standard lengths for the species within the trawl (Appendix 2A). Each individual fish was weighed to the nearest 0.01 g and standard length was measured to the nearest mm before

22 Chapter 2 - Food web structure of contrasting mesoscale eddies

being frozen for future analysis. Weights for fish that were not commonly found within the total catch were estimated using length-weight relationships from literature (Froese et al. 2014; www.fishbase.org). The total biomass of each size class was calculated by correcting for subsampling and the volume filtered through the trawl.

The binned biomass of both zooplankton and fish communities was used to calculate a normalised biomass size-spectrum (NBSS) of the community. The total biomass of each size class was normalised by dividing the biomass of each bin by the width of the bin (as mg m-3 mg-1). The NBSS of each eddy was derived by fitting a linear regression to the relationship between log2 normalised biomass and log2 body-size of each size-bin of zooplankton and fish from each eddy (Krupica et al. 2012; Suthers et al. 2006).

Stable isotope analysis of biological communities

SIA of carbon and nitrogen was conducted on the mesopelagic fish, zooplankton, and POM assemblages sampled from each eddy. Fish selected for SIA were weighed to the nearest 0.01 g (wet weight) and assigned to a log2 body mass class (0-0.5, 0.5-1, 1-2, 2-4, 4-8, 8-16 g). Four separate groups of mesopelagic fishes were selected for SIA based on family identities. The selected families represent a range of sizes, feeding preferences, and relative abundance collected in each eddy.

The four fish groups include the following three distinct fish families (Table 2.1): 1) Myctophidae (zooplanktivorous lanternfishes); 2) Sternoptychidae (zooplanktivorous hatchetfish); and, 3) Stomiidae (Piscivorous and zooplanktivorous viperfishes and dragonfishes) The fourth group (Others) contained a mix of other fish consisting of several families of mesopelagic fish that were not captured in sufficient number (or size ranges) to be included as their own group. This group was primarily made up of the families, Phosichthyidae (Lightfish), Gonostomatidae (bristlemouths). A complete list of samples analysed for stable isotopes is presented in Appendix 2B.

Dissection of each individual fish was undertaken to minimise contamination from gut contents and skin. For fish samples weighing 1 g or more, a small fillet of white dorsal musculature tissue was removed for analysis (Jennings et al., 2001). Fish that weighed less

23 Chapter 2 - Food web structure of contrasting mesoscale eddies

than 1 g were dissected to remove the head, organs, and skin, leaving bone and muscle tissue to ensure a large enough sample was collected. A single pooled sample of each size class of zooplankton was analysed as they represent the earlier consumer trophic levels of the food chains and link the primary producers with the pelagic fish and other nekton consumers.

All samples were dried at 60 °C for 48 hours and then separately ground into a homogenous powder using a mortar and pestle and 0.5 ± 0.1 mg of each of the powdered samples was packaged into tin foil capsules for analysis. POM was prepared by halving the filter paper and folding this to fit within the tin foil capsules. Ground samples were analysed on a continuous- flow stable isotope ratio mass spectrometer (CF-IRMS), model Delta V Plus (Thermo Scientific Corporation, U.S.A.), interfaced with an elemental analyser (Thermo Fisher Flash 2000 HT EA, Thermo Electron Corporation, U.S.A.) at the Australian Nuclear Science and Technology Organisation, Sydney. Data has been reported relative to International Atomic Energy Agency secondary standards calibrated against global standards of Vienna PeeDee Belemnite for carbon and air for nitrogen. Stable isotope values were reported in delta (δ) units, in parts per thousand (‰) relative to the international standard and determined as per equation 1:

푅푠푎푚푝푙푒 푋(‰) = ( − 1) ∙ 1000 (1) 푅푠푡푎푛푑푎푟푑

13 15 13 12 15 14 where X is δ C or δ N, Rsample is the C: C or N: N of the biological sample, and Rstandard represents the global standards for carbon and nitrogen as described above.

Samples were not treated to remove carbonates or lipids before stable isotope analysis due to low lipid content (~1%) of fish and zooplankton in the region (Davenport and Bax, 2002; Revill et al., 2009) and for consistency with other local studies (e.g. Henschke et al. 2015). Instead of removing lipids, the δ13C data was mathematically normalised for lipid content after analysis of the samples. For all samples where the carbon to nitrogen (C:N) ratio (by mass) was greater than 3.5, lipid corrections were applied using equation 2 (Post et al. 2007):

13 13 δ C푐표푟푟푒푐푡푒푑 = δ C푢푛푡푟푒푎푡푒푑 − 3.32 + 0.99 ∙ C ∶ N (2)

24 Chapter 2 - Food web structure of contrasting mesoscale eddies

Trophic level calculations

Trophic levels were calculated using two different approaches from the SIA results of δ15N within consumer organisms of each eddy. Particulate organic matter (POM), which is primarily made up of photosynthetic phytoplankton, was selected as the base for these food webs and was set as the reference trophic level of 1 (Dorado et al., 2012; Wada and Hattori, 1976). TL was estimated using two alternate models of trophic enrichment assumptions, which are used in literature. The first approach is more widely used and assumes a constant enrichment of

15 δ N with each TL. This constant enrichment approach (TLC) was calculated using equation 3 (Post, 2002):

15 15 훿 푁푠– 훿 푁푟푒푓 푇퐿 = ( ) + 푇퐿 (3) 퐶 푇퐸퐹 푟푒푓

15 15 15 Where δ Ns represents the δ N of the consumer sample, and δ Nref and TLref are baseline values of the δ15N from POM and the assumed trophic level of 1. Generally accepted TEF (trophic enrichment factor) 3.4 ‰ was used (Minagawa and Wada, 1984).

15 The second approach used is based on a scaled enrichment of the δ N isotope (TLS). This method follows a meta-analysis by Hussey et al. (2014) which assesses 59 experimental studies using SIA to estimate trophic level: Trophic level under the scaled approach was then calculated as follows (Equation 4):

15 15 15 15 log(훿 푁푙푖푚 – 훿 푁푟푒푓) − log(훿 푁푙푖푚 – 훿 푁푠) 푇퐿 = + 푇퐿 (4) 푆 푘 푟푒푓

The TLS equation uses the following parameters which are described in Hussey et al., (2014) meta-analysis:

15 훽표 − 훿 푁푙푖푚 푘 = −log ( 15 ) (5) −훿 푁푙푖푚

15 −훽표 훿 푁푙푖푚 = (6) 훽1 where β0 = 5.92 and β1= -0.27.

25 Chapter 2 - Food web structure of contrasting mesoscale eddies

Calculation of food web metrics

Food web parameters and ecosystem metrics were calculated using a linear relationship between TL and body size-class (as log2(BM)), using the middle of each body mass size class as the reference point. The relationships of each eddy were determined using a linear regression model as described in Jennings et al. (2001). The calculations were established from the TL estimates of the entire community (i.e. fish and zooplankton combined), as well as only the zooplankton and fish groups separately. The ecosystem metrics were Predator-Prey Mass Ratio (PPMR), Transfer Efficiency (TE), and Food-Chain Length (FCL).

The mean Predator-Prey Mass Ratios (PPMR) for each eddy were calculated for the total community using the slope of the TL-body mass relationships, as described in Jennings et al., (2002b):

푃푃푀푅 = 2훥푇퐿/ 푠푙표푝푒 (7)

The PPMR in each eddy is then used to calculate the mean trophic transfer efficiency (TE) as an estimate of prey production that is converted to predator production between each TL (Barnes et al., 2010):

푇퐸 = 푃푃푀푅푏+0.75 (8) where, b is the slope of the linear abundance size spectrum, for this study a value of -1.05 was used to represent the ‘typical slope’ of marine ecosystems (Barnes et al. 2010), and 0.75 is the assumed scaling function of consumption with body weight driven by metabolic rates (Barnes et al. 2010; Andersen et al., 2009; Trebilco et al., 2013).

Calculations of food chain length (FCL) were performed for the community using the equation as follows: (9) 퐹퐶퐿 = 푇퐿푚푎푥 – 푇퐿푚푖푛

26 Chapter 2 - Food web structure of contrasting mesoscale eddies

The maximum TL was taken from the 8-16 g size class, due to insufficient sample numbers in higher size classes.

All ecosystem metrics explained in above were calculated from the TL - log2(body mass) relationship. Only the findings calculated from TLS estimates are presented, as the results from this approach are regarded to reduce over and under estimation of trophic level at the lower and higher trophic levels of a food web (Hussey et al., 2015). The results calculated from TLC are supplied in Appendix 2C to ensure the findings can be directly compared with literature using the traditional constant approach.

Statistical analysis

One-way analysis of variance (ANOVA) was conducted to test for significant difference in δ15N and δ13C values between the eddies. Analysis was conducted separately for the whole community, as well as for each taxon (POM, Zooplankton, Fish, Myctophidae, and Sternoptychidae). Linear regression models were used to determine the relationship between body-mass (as log2(BM)) and trophic level in the WCE and CCE. An analysis of covariance (ANCOVA), using eddy type as an interaction (TL*eddy), was used to test for differences in the slope of the body mass-trophic level relationships of each eddy. Assumptions of normality and homogeneity of variance for each linear model were checked using residual plots and normal quantile plots and all models met the assumptions. All data analysis was conducted using R v. 3.6.1 (R Core Team, 2019).

27 Chapter 2 - Food web structure of contrasting mesoscale eddies

Table 2.1: Number of samples in each taxonomic group and size-class processed for stable isotope analysis for the WCE and CCE. Group Size Class n - CCE n - WCE

0 - 0.5 g 13 14 0.5 – 1 g 2 10 Myctophidae 1 – 2 g 7 8 (Lanternfish) 2 – 4 g 15 14 4 – 8 g 8 5 8 – 16 g 1 2

0 - 0.5 g 4 15 0.5 – 1 g 6 4 Sternoptychidae 1 – 2 g 7 4 (Marine Hatchetfish) 2 – 4 g 4 1 4 – 8 g 3 1 8 – 16 g 0 2

0-0.5 g 2 2 0.5-1 g 6 2 Stomiidae 1-2 g 3 0 (Dragonfish and 2-4 g 3 0 Viperfish) 4 – 8 g 1 2 8 – 16 g 1 2

0 - 0.5 g 9 7 0.5 – 1 g 4 5 1 – 2 g 0 1 ‘Other’ Fish 2 – 4 g 1 0 4 – 8 g 9 7 8 – 16 g 0 0

0.001 - 0.008 mg 1 1 0.008 - 0.065 mg 1 1 Zooplankton 0.065 - 0. 52452 mg 1 1 0.524 - 4.189 mg 1 1 4.189-33.51 mg 1 1

POM N/A 4 4 TOTAL - 110 118

28 Chapter 2 - Food web structure of contrasting mesoscale eddies

Results

The temperature and salinity of the WCE and CCE were similar within the top 100 m of the water column. The CCE had an average temperature of 19.66 °C (±0.456) compared to the WCE average of 19.96 °C (±0.105). The salinity was 35.73 (±0.049) and 35.77 (±0.005) in the CCE and WCE, respectively.

Figure 2.2: Depth profiles for each eddy showing A) mean temperature (°C), and B) mean Salinity (PSU) in the top 1000 m of the CCE eddy (solid blue line) and WCE eddy (solid red line). C) mean temperature, and D) mean salinity in the top 300 m. Sample collection took place in the top 100 m of each eddy.

29 Chapter 2 - Food web structure of contrasting mesoscale eddies

The mixed layer depth of the CCE was estimated at 86 m which was just shallower than the maximum depth of sampling. Mixed layer depth in the WCE was estimated to be at 226 m indicating that region sampled (top 100 m of the water column) was well mixed (Fig. 2.2). Chlorophyll-a was measured at 0.51 mg m-3 in the WCE (Kwong et al., 2020) and 0.45 mg m-3 in the CCE (Henschke et al., 2017).

Biomass and NBSS

Biomass of zooplankton in each EZ net trawl was 32% higher in the CCE (50.80 mg.m-3) compared to the WCE (38.39 mg.m-3) (Fig. 2.3). Due to logistical complications only a single zooplankton trawl was conducted in each eddy, therefore it is not possible to test the statistical significance of the difference.

Figure 2.3: Biomass (mg m-3) of (A) zooplankton sampled in the MOCNESS (n=1) and, (B) all fish collected in MIDOC trawls of the top 100 m of the two eddies. Biomass was corrected for volume filtered by the trawl nets.

From the pelagic MIDOC trawls there was no significant difference in the biomass of fish captured in the WCE compared to the CCE (F1,12 = 4.206, p =0.624). The mesopelagic fish community within the WCE was made up of 23 species from 11 families in WCE. The majority (75%) of the fish captured in the WCE were identified species belonging to the family

30 Chapter 2 - Food web structure of contrasting mesoscale eddies

Myctophidae. The CCE fish community was made up of 25 species from 15 families, with 46% of fish captured in the CCE being myctophids.

The NBSS was calculated for the community from zooplankton to fish. Both eddies had a significant linear relationship between body size and normalised biomass (p < 0.0001; CCE: r2 = 0.977; WCE: r2 = 0.972; Fig 2.4). There was no significant difference in the slopes of the size spectra of each eddy (p = 0.33).

The δ15N values for the entire community sampled within the CCE ranged from 2.6 ‰ to 12.8 ‰, and δ13C ranged from -21.094 ‰ to -18.60 ‰. The WCE ranged from 2.7‰ to 14.7‰ and from -21.78 ‰ to -17.7 ‰ in δ15N and δ13C respectively (Table 2.2).

The stable N isotope values of the entire sampled communities of the eddies reveal significant differences (ANOVA, F(1, 235) = 7.1, p = 0.008) between the two eddy communities (Table 2.3). Mean δ15N was higher in the CCE compared to the WCE. There was no significant difference

13 in the δ C values between the entire communities of the two eddies (F(1,235) = 2.08, p = 0.15).

31 Chapter 2 - Food web structure of contrasting mesoscale eddies

δ15N values for all fish taxa combined (i.e. excluding POM, and zooplankton) were significantly more enriched in the CCE (F(1, 205) = 28.96, p < 0.0001) compared to the WCE. The stable carbon values were also significantly different between the eddies, with the WCE having more

13 enriched δ C compared to the CCE (F(1, 205) = 10.99, p = 0.0011).

15 Mean δ N was significantly higher in the CCE for the myctophids (Myctophidae; F(1, 103) =

19.20, p < 0.001 ), and hatchetfish (Sternoptychidae; F(1, 49) = 56.72, p < 0.0001 ). In contrast, the Stomiids (Stomiidae) did not have a significant difference in mean δ15N in the CCE

13 compared to the WCE (F(1, 22) = 0.82, p = 0.38; Table 2.2). δ C values were significantly more enriched for the hatchetfish (F(1,22) = 0.407, p =0.0029) in the CCE compared to the WCE.

The lower trophic level taxa (i.e. the zooplankton) had no significant differences in either of the stable N and stable C isotope values between the two eddies. There was no difference in the δ15N (p = 0.74), or the δ13C (p = 0.1) values of the particulate organic matter (POM) between the two eddies at the base of the food chain. When adjusted to determine the isotopic enrichment Δ15N for and Δ13C, compared to the baseline POM values, the zooplankton and all fish groups in the CCE (Fig. 2.5B) had more enriched Δ 15N identifying that they are occupying higher trophic levels than those within the WCE. Mean values of POM δ15N within the WCE (4.2 ‰ ± 1.65) and the CCE (3.87 ‰ ±0.89), were used as the isotopic baseline to calculate TL (Fig. 2.5A; Table 2.2) for all taxa sampled.

When the stable isotope values of the biological communities of each eddy are examined based on body size, instead of taxonomic identity, there were significant positive relationships in enrichment of δ15N (Fig. 2.6A) and δ13C (Fig. 2.6B) as body size increases. When δ15N is converted to trophic levels in both eddies, the TL is higher in the CCE for all size classes (except 8-16 g size class, which had few replicates in both eddies, Fig. 2.7B). Mean TL was also higher in the CCE in each of the taxonomic groups (Table 2.2). Despite having no significant difference in the enrichment of POM at the base of the food chain, the TL of organisms within the CCE was higher than the TL of organisms of the same size class within the WCE.

Chapter 2 - Food web structure of contrasting mesoscale eddies

C (‰) C for (‰)

N (‰) N vs. (‰) δ

A) A) Mean values (±SD) of δ

C C for each of the functional groups, and adjusted for the baseline POM

N N and δ

(±SD) (±SD) in δ

enrichment

C (‰). C

N (‰) and Δ and (‰) N

functional functional groups, B) Mean

Stable Stable Isotope Analysis of fish, zooplankton, and Particulate Organic Matter (POM

: :

the

gure gure

Fi each of Δ as Expressed values.

Chapter 2 - Food web structure of contrasting mesoscale eddies

) and fish fish and )

⚫

for zooplankton ( for zooplankton

C C

)

red

(

N; and B) δ and N;

in the CCE (blue) and WCE and CCE (blue) the in

SD) stable isotope composition of A) δ A) of composition isotope SD) stable

size(g) and mean (+/ mean and size(g)

). Lines represent linear regression relationships relationships regression linear represent Lines ).

▲

(

between body between

Relationship

: :

2 Figure Figure

34 Chapter 2 - Food web structure of contrasting mesoscale eddies

Table 2.2: Mean stable isotope values for each taxonomic group within the CCE and WCE (±SD), n-sample size, and range of isotopic values in permil (‰). Values in bold indicate significant difference between eddies (P <0.05). POM was assumed to be TL = 1 for the purposes of isotopic baseline. δ15N δ13C TL Eddy Taxon Group n Mean δ15N Mean δ13C Mean TL Range Range Range All Fish 100 11.08 (±0.82) 8.5 – 12.8 -19.32 (±0.37) -20.3 – -18.6 2.6 (±0.23) 1.94 – 3.17 Myctophidae 46 11.16 (±0.76) 9.6 – 12.8 -19.43 (±0.39) -20.3 – -18.6 2.65 (±0.23) 2.21 – 3.17 Sternoptychidae 24 11.39 (±0.29) 10.7 – 11.94 -19.13 (±0.31) -20.3 – -18.8 2.71 (±0.09) 2.51 – 2.88 CCE Stomiidae 16 10.82 (±0.98) 8.8 – 12.4 -19.14 (±0.22) -19.5 – -18.8 2.56 (±0.28) 2.01 – 3.03 Other fish 14 10.64 (±1.05) 8.5 – 11.8 -19.5 (±0.29) -19.9 – -19.1 2.5 (±0.29) 1.94 – 2.84 Zooplankton 5 7.98 (±1.07) 6.8 – 9.2 -19.50 (±0.51) -20.3 – -18.8 1.83 (±0.24) 1.56 – 2.11 POM 4 3.875 (±0.90) 2.6 – 4.7 -20.79 (±0.29) -21.1 – -20.5 1 - All Fish 107 10.42 (±0.95) 8.0 – 14.7 -19.15 (±0.39) -20.4 – -17.7 2.43 (±0.26) 1.77 – 3.85 Myctophidae 59 10.36 (±1.04) 8.0 – 12.1 -19.31 (±0.38) -20.4 – -18.5 2.37 (±0.29) 1.77 – 2.87 Sternoptychidae 27 10.41 (±0.57) 9.5 – 12.2 -18.9 (±0.22) -19.3 – -18.5 2.37 (±0.16) 2.13 – 2.91 WCE Stomiidae 8 11.29 (±1.57) 9.9 – 14.7 -18.85 (±0.60) -19.6 – -17.7 2.66 (±0.53) 2.23 – 3.85 Other fish 13 10.23 (±0.22) 9.9 – 10.6 -19.09 (±0.17) -19.3 – -18.9 2.32 (±0.06) 2.23 – 2.42 Zooplankton 5 7.3 (±0.70) 5.9 – 7.8 -20.01 (±0.56) -20.7 – -19.1 1.58 (±0.15) 1.32 – 1.72 POM 4 4.2 (±1.65) 2.7 – 6.2 -21.31 (±0.45) -21.8 – -20.8 1 -

35 Chapter 2 - Food web structure of contrasting mesoscale eddies

Figure 2.7. Comparison of the trophic levels of zooplankton and fish in the WCE and CCE. A) Mean trophic position of each major functional group, and B) mean trophic position of each size class. Values expressed are mean TL (±SD). The dashed reference line represents the midpoint where TL in both the CCE and WCE would be equal. Trophic level – body mass relationships

The TL of organisms increased significantly with body mass in both eddies (Table 2.3). The

relationship between TL and body mass (BM) for the WCE was calculated as TLWCE = 2.39 +

2 0.0797 · log2BM (F1,115 = 149.1, r = 0.56, p < 0.001), and for the CCE was calculated as TLCCE =

2 2.61 + 0.0659 · log2BM (F1,107 = 91.76, r =0.45, p < 0.001).

The slope of the relationships between body size and trophic level (Fig. 2.8) of each eddy were

not significantly different between the two water masses (F(3,225)= 33.14, p = 0.12). However, regression intercepts were significantly different between the two eddies (p = <0.001).

36 Chapter 2 - Food web structure of contrasting mesoscale eddies

Table 2.3: Results of linear regression analysis of the relationship between trophic level and body-size class between the WCE and CCE. b = slope of linear relationship. NS = Non-significant,

Group Eddy n b SE r2 F p

Whole CCE 109 0.066 0.006 0.454 91.76 <0.001 Community WCE 117 0.080 0.006 0.590 164.70 < 0.001 CCE 104 0.059 0.013 0.169 21.95 <0.001 All Fish WCE 110 0.097 0.011 0.403 74.69 <0.001 CCE 5 0.028 0.024 0.066 1.35 NS Zooplankton WCE 5 0.032 0.008 0.799 16.93 0.0073 CCE 47 0.038 0.018 0.067 4.31 0.044 Myctophidae WCE 59 0.118 0.014 0.534 1.66 < 0.001 CCE 26 0.011 0.013 0.031 0.76 NS Sternoptychidae WCE 27 0.068 0.011 0.575 34.82 <0.001 CCE 16 0.12 0.37 0.44 11.01 0.0051 Stomiidae WCE 8 0.155 0.064 0.406 5.78 NS

Estimation of ecosystem metrics

The CCE had a PPMR of 37,105. This PPMR was more than six times larger than found in the WCE (PPMR = 5,989). Using the PPMR to calculate the TE of each eddy, the TE of the WCE (0.074, 7.4 %) was nearly double in the CCE (0.043, 4.3 %) (Table 2.5).

The smaller PPMR within the WCE results in more efficient conversion of production from prey to predator, as prey items are larger in body size, and therefore a higher TL. The food chain in the WCE (FCL = 2.85) was longer than the food chain within the CCE (FCL = 2.17), from baseline POM to the largest size-class that were sampled.

37 Chapter 2 - Food web structure of contrasting mesoscale eddies

Figure 2.8: Relationship between body size (g) and mean trophic level (±SD) of the mesopelagic communities sampled within both eddies. The maximum body size class represented is from the 8- 16 g size class for both eddies. Trophic levels were calculated using the scaled fractionation approach. Dashed lines represent the relationships of the zooplankton and fish communities separately.

Table 2.4: Summary of the estimated food chain metrics of the two eddies derived from linear relationships between body size and trophic level for the entire community Maximum Predator-Prey Food Chain Transfer Eddy Trophic Mass Ratio Length Efficiency Level

CCE 43,042 2.17 0.0407 3.17

WCE 5,698 2.85 0.0746 3.85

38 Chapter 2 - Food web structure of contrasting mesoscale eddies

Discussion

The calculation of ecosystem metrics from trophic level (TL) and body-size relationships within a pelagic ecosystem are useful for quantifying energy flow throughout the food web, which is an important step towards developing ecosystem models. This study quantified the trophic level-body mass relationship (TL-BM) between two common types of mesoscale eddies off the eastern coast of Australia. Despite the abiotic conditions and biomass within the two eddies being similar the two water masses created very different ecosystem metrics. In particular, the predator prey mass ratio (PPMR) within the cold core eddy (CCE) was approximately six- times greater than that of the warm core eddy (WCE) which has important implications for the transfer of energy through the food-web. The WCE had a longer food chain length with a more efficient transfer efficiency between each subsequent trophic level because of consumers feeding on prey items with a larger body size.

Ecosystem metrics of contrasting mesoscale eddies

Community wide predator prey mass ratio (PPMR) and trophic transfer efficiencies are traditionally estimated by gut content analysis of the common taxon that make up the community. Using SIA to derive TL-BM relationships of the entire community greatly reduces the difficulty in estimating these ecosystem metrics (Barnes et al., 2010; Blanchard et al., 2017; Hunt et al., 2015; Jennings et al., 2001; Smith et al., 2007; Trebilco et al., 2013) and is key for understanding ecosystem energy flow. The PPMR of the CCE (37,105:1) was 6.2 times greater than the PPMR of the WCE (5,989:1) revealing that the predators within the CCE food-web feed on prey much smaller than their body size when compared to similar size predators within the WCE.

Like the CCE, eutrophic environments that facilitate higher nutrients and phytoplankton biomass are often dominated by omnivores and herbivores (Henschke et al., 2015; Miller et al 2010) which have higher PPMRs. This has been related to lower stability within an ecosystem and it is expected that small PPMRs allow organisms to persist on a wider selection of prey (Heneghan et al 2016; Jennings and Warr, 2003). The TE in the WCE was almost double the CCE due to the smaller steps between trophic levels (lower PPMR). TEs for pelagic marine

39 Chapter 2 - Food web structure of contrasting mesoscale eddies

ecosystems are generally inefficient with reported values in previous studies typically ranging from 0.03-0.13 (3-13 %; Irigoien et al., 2014; Jennings et al., 2002; Mehner et al., 2018; Trebilco et al., 2013). The TEs calculated for the WCE (0.074) and the CCE (0.043) are within this range, with the WCE having a more efficient conversion of prey production to predator production.

The TE needs to be considered with the food chain length (FCL) as the higher efficiency in the food chain links of the WCE, combined with TE which will determine overall efficiency of the ecosystem. The FCL describes the number of trophic links between individuals at the base of the food web and the top (Jennings et al. 2001; Jennings and Warr 2003) for a community within a given size range. This study identified food chains of up to 3.9 TLs, from primary producers to secondary and tertiary consumers. The comparison of FCL between eddies showed the WCE had a longer FCL relative to the CCE. However, the slopes of the normalised biomass size spectra (NBSS) was statistically similar between the eddies which indicates both eddies have a similar biomass in all size classes from small (zooplankton) to larger (fish) size classes. This suggests that despite the different ecosystems, the resultant biomass was similar due to the competing effects of TE and FCL.

Body-Size based trophic ecology of mesoscale eddies.

Both δ15N and δ13C values increased significantly and consistently with body size in both eddies, indicating that size classes fed on prey items that were of a fairly consistent size, and for organisms in the size range sampled, such that feeding on relatively large prey items was rare.

The POM stable isotope signatures of δ15N and δ13C were not significantly different (Table 2.3) between the two eddies, indicating that POM was creating a similar food source at the base of the food chain despite being separated by almost 6 degrees of latitude. Significant differences in isotopic concentrations only began to occur in the fish groups which are the higher-level consumers in this study. This also suggests that that trophic enrichment of the isotopes is different between the two eddies (Davenport and Bax, 2002; Henschke et al., 2015; Post, 2002), which may be a result of increased predation or opportunistic feeding strategies.

In contrast, there were significant between eddy differences in TL between all consumer taxa groups. Mean TLs were significantly higher in the CCE for each taxonomic group, except for

40 Chapter 2 - Food web structure of contrasting mesoscale eddies

the stomiid fish group (viperfish, dragonfish) which showed no significant difference between eddies. SIA estimates of TL for stomiids and myctophids indicate that stomiids and myctophids within the eddies are occupying a similar TL compared to previous estimates (TL 2 – 3; Choy et al., 2012). Initial expectations were that stomiids would occupy higher trophic levels, compared to myctophids, based on a piscivorous feeding strategy and preference. However, global estimates in the trophic positions of stomiids and myctophids (Choy et al., 2012; Kozlov, 1995) indicate that sporadic feeding, and very low metabolic rates of stomiids, compared to myctophids, would contribute to different isotopic turnover rates and therefore different enrichment rates of δ15N.

The δ15N isotope is used in trophic ecology studies to estimate TL of marine organisms and therefore the creation of a TL-BM relationship within the size-structured communities. The two eddies had significantly different relationships between body-size and trophic level over the entire community. This indicates that the trophic levels of organisms in the WCE, as indicated by a steeper slope, are increasing in trophic level at a faster rate than an organism of the same size in the CCE. This is likely due to a predominance of predation or opportunistic omnivory over grazing that is occurring more within the WCE.

The analysis of the trophic level of taxon within the CCE and WCE was conducted using two methods of trophic level estimation based on a constant TEF (Minagawa and Wada, 1984), and a scaling TEF (Hussey et al., 2014). Comparisons of TL estimates of the two approaches (Appendix 2C) show that the scaled TL approach estimated lower trophic levels at all size classes compared to TLc. Therefore, intercepts of TL-BM relationships are decreased and estimates of PPMR, FCL, and TE are also different to the scaled TL estimates with PPMR being reduced, and TE and FCL being increased. The CCE PPMR, under the constant TEF of 3.4 ‰, was estimated at 12,558:1 (approximately one quarter of the scaled PPMR), and the WCE PPMR was 1911:1 (approximately one third of the scaled value). Whilst it was not an aim of this study to test or compare these two methods, species specific estimates from TLc also appear to align more closely to estimates from previous SIA studies as well as gut contents analysis (Cherel et al., 2010; Olivar et al., 2018; Sutton and Hopkins, 1996).

41 Chapter 2 - Food web structure of contrasting mesoscale eddies

Comparisons with previous studies

By using this size-based approach to understanding eddy food webs, the ecosystem metrics estimated from size-spectra data simplifies complex species-based interactions into numerical parameters that can be used by ecosystem models to estimate and predict fisheries production over a large spatial and temporal scale (Jennings et al., 2002b, 2008; Blanchard et al., 2009, 2017). Many previous studies that utilise this method have identified ecosystem parameters of pelagic fish ecosystems (eg: Bode et al., 2007; Jennings et al., 2002a, 2002b; Ohshimo et al., 2016) (Table 4.1).

Trophic level studies on benthic food webs of the North Sea has been conducted in the past by Jennings et al., (2002b) and Jennings and Warr (2003) and have identified a substantially lower PPMR of 80:1 and 424:1 respectively, the latter study also identifying a mean transfer efficiency of 16.3%. Comparing these parameters with the PPMR and transfer efficiencies estimated from the eddy ecosystem indicates a highly predatory environment driven by carnivory, and where many of the larger consumers are primarily piscivorous (Jennings et al., 2002b). When compared to the eddy ecosystems the PPMR is substantially lower, creating a This is in contrast to the pelagic eddy ecosystems where PPMRs were much larger due to many of the taxa feeding on the more abundant zooplankton communities.

A study in the south Pacific Ocean, near New Caledonia by Hunt et al., (2015) looked into the entire food web community across multiple taxonomic groups and size classes including zooplankton and fish. The study by Hunt et al., (2015) showed very similar ecosystem values compared to the two warm-core eddies examined in this thesis, with relatively similar PPMR and TE, and very similar food chain length estimates of 1.7-2.3, indicating a similarity between trophodynamics of the two habitats. Inclusion of the larger fish/nekton greatly increased the PPMR estimates by an order of magnitude, producing similar PPMRs to pelagic fish habitats along the Iberian Peninsula (Bode et al., 2007). These large PPMRs and low transfer efficiencies indicate that predation on smaller nekton and zooplankton is common in pelagic fish communities. It could be expected that the inclusion of larger consumers in the present study eddy would result in similar PPMR estimates as many of the common predatory species in the region feed on small fish/nekton (Young et al., 2005).

42 Chapter 2 - Food web structure of contrasting mesoscale eddies

Conclusion and remarks

This study applies a relatively new ecosystem approach by using a combined approach of size and stable isotope analysis to understand and map the food webs of common habitats within the western Tasman Sea. Using a combined approach yielded metrics that describe the food web in terms of the predator-prey mass ratio, trophic levels, food chain length, and transfer efficiencies which are within the expected ranges of similar pelagic ecosystems. This is significant for both understanding the trophic structure of Tasman Sea and for determining ecosystem metrics that can be applied to models for fisheries and environmental management. This work will help to further understand and address the ecological and fisheries significance of warm core and cold core eddies as we have little understanding how the trophic ecology of these two ubiquitous features of the global ocean compare at higher trophic levels (Jennings et al., 2008). Using stable isotope analysis of the ocean communities to calculate ecosystem food chain metrics could benefit ecosystem models that aim to predict habitat production and transfer efficiency throughout the region.

One aspect of the pelagic food webs that was not examined in this chapter, is the relative positions in the TL-BM relationships of additional taxa that was captured in the trawls. In particular, pelagic feeding squid have been found to make up a significant portion of top predatory fish diets (Young et al., 2010). Inclusion of the rest of the taxa from the ecosystems would also provide a more comprehensive analysis of the food chains, however these taxa were selected for other studies and were unavailable for this research. Furthermore, inclusion of the large fish predator species that are known to feed in these waters of the Tasman Sea (Young et al., 2010) and occupy higher trophic levels would also complete the food web analysis and allow for further biodiversity and trophic level comparisons between the eddies.

43 Chapter 2 - Food web structure of contrasting mesoscale eddies

(Jennings et al., 2008), and calculate trophic transfer efficiency (Jennings et al., 2002b). in the Tasman Sea region, previous work on zooplankton size structure in the western Tasman Sea has demonstrated a relationship between the biophysical aspects (i.e: sea-surface temperature, chlorophyl concentrations, and surface level anomaly) and zooplankton community size spectra characteristics (White, unpublished thesis, 2018). This study has shown that satellite data can be used to create accurate predictions of zooplankton community distributions and structure. Since the body size of an organism in these eddy food chains is related to their trophic level, size spectra predictions of the lower trophic levels can be used to predict trophic levels of the top predators, and therefore understand the food web characteristics and transfer efficiency of ecosystems on a large spatial scale. If we can understand how the predator prey relationship metrics differ between the habitats of the Tasman Sea we can expand on the previous research in this field and create ecosystems models, in real time, that relate ecosystem structure and energy transfer to the fishery productivity in the region.

The application of this research is highly relevant for the western Tasman Sea, particularly into the future where it is expected to experience ocean warming, resulting in a strengthening of the EAC within the next few decades (Everett et al., 2012; Oliver et al., 2015; Suthers et al., 2011). This is expected to result in an increase in strength, frequency, and lifespan of mesoscale eddies, which will increase the distance of pole-ward transport of eddy waters and their ecosystems (Oliver et al., 2015.) Understanding the biological impact of these intensified eddies will become more important when applying the appropriate management efforts within the warming Tasman Sea.

44 Chapter 3 – Comparison of size-based eddy ecosystems

Chapter 3 – Comparison of size-based eddy ecosystems: Warm-core eddies have longer food-chains and greater transfer efficiency than cold-core eddies Abstract

Mesoscale ocean eddies are a frequent occurrence in the Tasman Sea region creating distinct habitats that impact the biophysical characteristics within the waters. cyclonic eddies (cold- core, CCEs) are upwelling favourable and frequently reveal elevated chlorophyll a biomass, anticyclonic eddies (warm-core, WCEs) typically have lower chlorophyll-a. The food webs created within eddies are defined primarily by body size, however the differences in size- structure and predator-prey interactions based on eddy type have yet to be quantified. We compared the zooplankton and micronekton ecosystems in the upper mixed layer (<100 m depth) of cyclonic and anticyclonic eddies, in regions north and south of the Tasman Front off of eastern Australia. Compared to the WCE in each region, the CCEs had similar chlorophyll a concentration but nearly twice the biomass of zooplankton due to upwelling. Overall, the four eddies had a similar total biomass of mesopelagic fish, and similar Shannon diversity indices of fish families. The size-based ecosystems were characterised in terms of Predator Prey Mass Ratio (PPMR), Trophic Efficiency (TE) and Food Chain Length (FCL), by using the δ15N composition to calculate trophic level. Although all 4 eddies were distinctive and separated by up to 7° latitude, the CCE were characterised by PPMR 3 to 8 times greater than the corresponding WCE. Therefore, the CCE had lower TE and shorter FCL compared to the WCE. While this study was limited to four eddies, the results suggest that CCE ecosystems may result in similar fisheries productivity as more oligotrophic WCE, due to the competing effects of TE and FCL. CCE are characterised by a higher PPMR which indicates an increased proportion of herbivory, while WCE have a lower PPMR, indicating increased carnivory. The emerging use of dynamic ecosystem management models can utilise the relationships developed in this study to understand food-web dynamics at finer scales than currently available, and by linking them with existing models that currently use satellite based biophysical observations to manage fishery productivity and delimit fishing zones based on habitat preference of the target species.

45 Chapter 3 – Comparison of size-based eddy ecosystems

Introduction

Mesoscale eddies create patches of highly productive habitats within the open oceans (Chelton et al. 2011). Since the rotation of an eddy entrains waters from the surrounding areas, the difference between an eddy’s source water and the water bodies in its path has an important effect on the community composition (Waite et al. 2007; 2019; Matis et al., 2014). The location of an eddy during formation has been linked to variations in chlorophyll-a concentration (Everett et al. 2012; 2014; Gaube et al., 2014), zooplankton abundance and diversity (Taylor et al., 2010; Henschke et al., 2015; Laiolo et al., 2016; Cetina-Heredia et al., 2019), and the distribution and diversity of larval fish (Muhling et al. 2007; Matis et al., 2014). However, the broader ecosystem impact of mesoscale eddy fields on fisheries productivity in the region remains relatively unknown. Warm core eddies off eastern Australia generally generate down-welling favourable conditions and are less productive than cold core eddies that promote primary production with cooler nutrient rich waters raised up by their upwelling favourable rotation (Bakun, 2006; Everett et al., 2014, 2012; Roughan et al., 2017). In addition to rotational direction, the source waters of eddies, as well as the waters entrained along its path, also impact the overall productivity (Waite et al., 2007). For example, eddies that entrain highly productive shelf waters tend to promote elevated biomasses of plankton, and different larval fish communities (Everett et al., 2012, Mullaney and Suthers 2013; Matis et al., 2014). The differences in the biophysical characteristics of the mesoscale features tend to result in different community composition, abundance, and trophic structure, all within relatively small spatial scales.

These differences may result in different community structure within small spatial areas and large relative differences between eddies of the same type situated across broad spatial areas. For example, in a comprehensive summary of five eddies, Waite et al. (2019) solved a paradox of WCEs in the Leeuwin Current, which had a greater chlorophyll-a concentration than CCEs, and yet lower lipid indices in larval lobster. They determined that despite the greater flux of nitrate in the deeper mixing WCE (dominated by diatoms), the shallower mixed layer depth of cyclonic eddies enabled the more nutritious flagellates to grow. In summary, cyclonic and anticyclonic eddies tend to facilitate differing levels of production at the bottom of the food

46 Chapter 3 – Comparison of size-based eddy ecosystems

chain (Waite et al. 2019) through the mixed layer depth, and the entrainment or expelling of plankton to adjacent water masses (Waite et al. 2007; Everett et al. 2015; Malan et al. 2020).

Stable isotope analysis of carbon and nitrogen provides a method for quantifying food webs (Boecklen et al. 2011; Henschke et al. 2015). The heavier isotope of nitrogen (15N) indicates the trophic level as it accumulates in successive levels of predation, while 13C has much slower enrichment (Post, 2002), and varies with latitude (Logan et al. 2020) making it ideal for determining source nutrients. The relationship between size and trophic level based on 15N Jennings et al. (2002a) is a powerful ecosystem approach because it largely resolves the species complexity of the samples to compare with other habitats even if the species compositions are vastly different (Jennings et al., 2001).

These differences in production manifest through the food web by influencing consumer diets (Henschke et al., 2015, Waite et al., 2007) and ultimately their trophic level (Hunt et al., 2015), and the length of the food chain (Jennings and Warr, 2003; Young et al., 2015). In the Tasman Sea for example, the different eddy types created by the East Australian Current (EAC) form distinct habitats that promote or hinder primary production in the western Tasman Sea (Everett et al., 2012; Henschke et al., 2015). At the Tasman Front, the warm oligotrophic waters of the EAC give way to cooler nutrient rich waters of the southwestern Tasman Sea (Everett et al., 2012), however eddies formed in the EAC entrain and transport the warm waters and biological communities within southward forming semi-isolated habitats of warmer and cooler waters (Hobday et al. 2011).

This chapter is part of a series of multidisciplinary studies from a voyage in September 2017 investigating four eddies off eastern Australia, examining their physical oceanography (Malan et al. 2020; Archer et al. 2020) and their biological communities (Kwong et al. 2020; Henschke et al. 2020). In this chapter I compare the mesopelagic communities and ecosystems of a cyclonic and an anticyclonic eddy in the warmer EAC influenced waters north of the Tasman Front (Chapter 2), with two southern eddies that were sampled in the different waters to the south of the Tasman Front (unpublished honours thesis, Kas 2018). Similar to Chapter 2, Kas (2018) used trophic level–body-mass relationships to show that the cold-core eddy (upwelling favourable) had a larger predator-prey mass ratio, shorter food-chain length and lower trophic

47 Chapter 3 – Comparison of size-based eddy ecosystems

efficiency than the warm-core eddy (downwelling favourable). The larger predator-prey mass ratio (PPMR) resulted in a smaller trophic transfer efficiency between prey and predators. The PPMR represents an intermediate value in prey size that is neither too small to be consumed by a predator, nor too large to be caught or handled by a predator (Brose 2010). Such studies have been undertaken in in North Sea (Jennings and Warr, 2003; Jennings et al., 2002b) where they found that a smaller PPMR is associated with more stable environments and longer food chains. Jennings et al. (2002b) found the size-structured bathypelagic food-webs of the North Sea had a very small PPMR of 109:1 and a TE of 3.7 – 12.4%, whereas studies in the oligotrophic south Pacific Ocean near New Caledonia (Hunt et al., 2015) identified a much higher PPMR for microzooplankton and micronekton of 3683:1 with a TE of 8.5%, and a PPMR of 244000:1 with a TE of 2.4% for nekton. This illustrates how these values can vary from cool eutrophic conditions to warm oligotrophic conditions.

The region north of the Tasman Front has pelagic fisheries influenced by northern oligotrophic conditions of the Coral Sea, while those from the southern region are characterised by the comparatively chlorophyll rich waters of the western Tasman Sea (Revill et al. 2009). While the two regions have distinctively different patterns in the seasonal climatology of temperature and salinity (Baird et al. 2011), the eddies produced by the EAC eventually propagate into the southern region (Chapter 1). The regions north and south of the Tasman Front have been shown to have effectively separate ecosystems off eastern Australia, which has been shown in the diets and stable isotope composition of commercially landed fish (Revill et al. 2009), as well as the size-structured composition of zooplankton along the coast (Baird et al., 2008, White 2018) and dispersal of marine organisms and fisheries (Hobday and Hartmann, 2006; Everett et al., 2014).

This present study is the first to undertake a combined SIA and size-structured food-chain analysis of mesopelagic eddy ecosystems of Tasman Sea eddies, in both the northern and southern regions. Specifically, I aim to:

1. Compare the oceanographic context of four eddies to ascertain its impact on the biomass of phytoplankton, zooplankton and fish, and fish diversity

48 Chapter 3 – Comparison of size-based eddy ecosystems

2. Compare stable isotope composition of zooplankton and fish in δ13C and δ15N among eddies, and investigate relationships between isotopic value, trophic level, and body-size; and 3. Compare the trophic level body-size relationships using PPMR, TE, and FCL.

Methods

Study area

The biological communities of four separate, mesoscale eddies that formed in the western Tasman Sea were sampled in September 2017 on board the RV Investigator (Figure 3.1). A warm core and a cold core eddy were sampled in the warmer waters north of the Tasman Front (northern eddies), and a warm-core and cold-core eddy dipole (Malan et al., 2020) were sampled south of the Tasman Front (southern eddies, Kas, 2018). The northern cold core eddy (NCC, referred to as CCE in Chapter 2) was ∼150 km diameter eddy located off of Brisbane (approximately 27.5 °S), and the northern warm-core eddy (NWC, WCE in Chapter 2) was ∼200 km diameter off the city of Newcastle (approximately 33 °S), formed by the retroflection of the EAC (Fig. 3.1, Chapter 2). By inspection of satellite imagery (www.oceancurrent.com.au) the NCC was formed offshore many months earlier and was beginning to decay (Kwong et al., 2020). The NWC eddy was formed 1-2 months earlier from the “retroflection” of the EAC, as the current turned east to form the Tasman Front (or Tasman Convergence, Oke et al. 2019).

The southern cold-core eddy (SCC) was formed in between the NWC on the northern side, and a second warm-core eddy (SWC) to the south creating an eddy dipole (Malan et al., 2020), south of the Tasman Front. Both eddies were more than 3 months old based on inspection of satellite imagery. The EAC provided a strong tangential flow to the northern side of the SCC (>1.5 m s-1), creating a strongly upwelling eddy (Henschke et al., 2019). An eddy jet formed between the SCC and SWC dipole creating significant onshore currents, forcing offshore waters to diverge at the shelf break, to north and south. This eddy dipole and the north- westerly eddy jet were found to be characteristic features at this latitude (~33°S), generating more than 50% of the onshore flow estimated from the previous 20 years of altimetric

49 Chapter 3 – Comparison of size-based eddy ecosystems

observations (Malan et al. 2020). The eddy dipole affected the biological characteristics of each eddy warping the shape and forcing productive water ‘leaking’ out of the eddy current (Malan et al. 2020).

A Seabird-9 Conductivity-Temperature-Depth (CTD) probe was deployed in each eddy to record oceanographic conditions of temperature and salinity (Chapter 2, Section 2.2). A CTD rosette, fitted with 12 Niskin bottles and the CTD was deployed between the surface and 1000 m for temperature, salinity, fluorescence, and oxygen. Water samples collected at the surface (4 m) and the deep chlorophyll maximum (DCM) for the analysis of particulate organic matter (POM; details below). Satellite derived estimates of sea surface temperature (SST), sea level anomaly (SLA), and chlorophyll-a concentration was used to identify and characterise each eddy. SST and chlorophyll-a were obtained from the Daily Moderate Resolution Imaging Spectroradiometer level 3 (MODIS), from the Integrated Marine Observing System (IMOS) Data Portal (http://imos.aodn.org.au/imos/) at 1 km resolution. Satellite altimeter data, for SLA were obtained from NASA/CNES (Jason-1 and 2) and ESA (ENVISAT) and mapped in near- real time for the Australian region.

Community Sample Collection

Particulate Organic Matter (POM), zooplankton, and fish communities were collected using a range of sampling gear within each eddy (Table 3.1). Sampling generally took place across 2 consecutive nights, but the ship’s position was adjusted nightly to ensure sampling took place within the boundary of the same eddy. Water samples were taken near the surface (4 m) and the deep chlorophyll maximum (DCM) in each eddy for POM, which was obtained by filtering 4 L seawater onto 47 mm diameter pre-combusted, and acidified glass fibre filters (GF/F) using a low-pressure vacuum pump. Filter papers were then frozen at –20°C until preparation for stable isotopes analysis.

Sampling methods are the same as described in Chapter 2. Briefly, this involved sampling for zooplankton using a 1 m2 Multiple Opening-Closing Net and Environmental Sensing System (MOCNESS) with five remotely operated 500 µm mesh nets between 500 m and the surface with a net triggered every 20 m. A digital General Oceanics flowmeter recorded the flow and volume filtered. The final (5th) net was towed at approximately 3 knots, sampling from 100 m

50 Chapter 3 – Comparison of size-based eddy ecosystems

deep to the surface which was the focus of this study. Additionally, a 20 cm diameter, 100 µm plankton net was suspended inside each net of the MOCNESS. Each trawl was sorted into size groups by gently rinsing through a stacked column of sieves with decreasing mesh size providing zooplankton samples in 5 size classes (125-250, 250-500, 500-1000, 1000-2000, and 2000-4000 μm). Each size group was stored on pre-weighed petri dishes and were oven-dried at 60°C for 48 hours (Kwong et al. 2019). Each petri dish was weighed to the nearest 0.01 g before being frozen at -20°C until preparation for stable isotope analysis.

Figure 3.1: Satellite based imagery of (A) mean Sea Surface temperature (SST), (B) Ocean colour (Chlorophyll-a), and (C) Sea surface anomaly (SSA) of four mesopelagic eddies sampled during the September 2017 RV Investigator voyage (31-Aug to 19-Sept 2017). Each eddy was sampled between dusk and dawn. ○ = NCC, ◊ = NWC, □ = SCC, Δ = SWC.

The fish and micronekton communities within each eddy were sampled using a 157.5 m2 Danish pelagic trawl net between 100 m and the surface at 2-3 knots (~1.25 m s-1). Mesh size of the trawl reduced from 200 mm stretched mesh width at the mouth to 10 mm near the codend. At the codend was a MIDwater Open and Closing (MIDOC) net system with six cod- ends graduating from 10 mm mesh to 500 µm mesh. This study analysed the sixth, and final, cod-end which sampled from 100 m deep to the surface. All samples were collected at night from dusk until dawn. Due to logistical constraints, sampling within each eddy took place

51 Chapter 3 – Comparison of size-based eddy ecosystems

across 2 or 3 consecutive nights. In the SCC, only one MIDOC trawl was made for the fish biomass and diversity measures, as logistical and weather constraints prevented further sampling. However, at the SCC, another 6 tows were made with the Danish Trawl in the upper 100 m, without the MIDOC system but with a 10 mm mesh liner (for collecting larval lobster). These samples could not be used for calculating fish biomass and biodiversity, as this net is caused greater drag, with a smaller mouth area and requiring a slower tow speed (2 knots). However, these samples were used for stable isotope analyses in SCC.

Table 3.1: Sampling methods for nekton, zooplankton and particulate organic matter (POM) used on board RV Investigator in September 2017 voyage. Target Taxa Sampling Gear Depths Sampled Number of replicates

Danish pelagic trawl NCC – 3; NWC – 2; Fish and micronekton Surface to 100 m with MIDOC SCC – 1; SWC – 3 MOCNESS net Zooplankton Surface to 100 m 1 per eddy (“EZ Net”) Particulate Organic CTD Rosette with 20 L 4 m (surface) and 4 per eddy Matter Niskin bottles DCM (~75-100 m)

Normalised Biomass size spectra

The biomass of both zooplankton and fish communities were binned into logarithmic (Log10) size classes by wet weight to create a normalised biomass size-spectrum (NBSS) of the community. The total biomass of each size class was normalised by dividing the biomass of each size bin by the width of the bin (units m-3) and the relationship between body size and normalised biomass (on a log10 – log10 scale) was identified using a linear regression. The slope and intercept of the NBSS were derived from the linear least-squares relationship of each eddy (Krupica et al. 2012; Suthers et al. 2006). Significant between eddy differences in NBSS slope were tested using ANCOVA, with Tukey’s HSD post hoc analysis if a significant between slopes was found.

Stable Isotope Analysis

SIA of carbon and nitrogen was conducted on the fish, zooplankton, and POM assemblages sampled from each eddy. Fish selected for SIA were weighed to the nearest 0.01 g (wet weight) and assigned to a log2 body mass class (0-0.5, 0.5-1, 1-2, 2-4, 4-8, 8-16 g).

52 Chapter 3 – Comparison of size-based eddy ecosystems

Fish samples consisted of a small fillet of white dorsal muscle tissue. Fish that weighed less than 1 g were dissected to remove head, organs, and skin, leaving bone and muscle tissue to ensure a large enough sample was collected. We chose not to remove lipids before analysis to allow comparison with earlier research in the region (e.g. Davenport and Bax 2002; Revill et al. 2009; Henschke et al. 2015). These studies suggested that lipid removal was not necessarily due to the low lipid content (~1%) of Australian taxa. After stable isotope analysis, the δ13C data was instead mathematically adjusted to account for lipid content in samples where the carbon to nitrogen (C:N) ratio (by mass) was greater than 3.5, lipid corrections were applied. Samples with C:N greater than 3.5 (for aquatic organisms) have previously been identified to have lipid concentration that will create depleted δ13C in tissue samples (Post et al., 2007). Mathematical corrections to δ13C are calculated using the following equation from

13 13 Post et al. (2007): δ Ccorrected = δ Cuntreated - 3.32 + 0.99 ∙ C∶N.

All samples were processed for SIA at the Australian Nuclear Science and Technology Organisation (ANSTO), according to ANSTO protocol and sampling methodology. Ground samples were analysed on a continuous-flow stable isotope ratio mass spectrometer (CF- IRMS), model Delta V Plus (Thermo Scientific Corporation, U.S.A.), interfaced with an elemental analyser (Thermo Fisher Flash 2000 HT EA, Thermo Electron Corporation, U.S.A.) at the Australian Nuclear Science and Technology Organisation, Sydney. Data has been reported relative to International Atomic Energy Agency secondary standards calibrated against global standards of Vienna PeeDee Belemnite for carbon and air for nitrogen. Stable isotope values were reported in delta (δ) units, in parts per thousand (‰) relative to the international standard.

A one-way analysis of variance (ANOVA) was used to test for significant differences in δ13C or δ15N values in the entire eddy community. Tukey's HSD test was used post hoc to identify which eddies differed significantly if differences were identified in the ANOVA.

53 Chapter 3 – Comparison of size-based eddy ecosystems

Trophic level calculations

Trophic levels were calculated using two different approaches from the SIA results of δ15N within consumer organisms of each eddy. Particulate organic matter (POM), which is primarily made up of photosynthetic phytoplankton, was selected as the base for these food webs and was set as the baseline reference trophic level (TL) = 1 (Dorado et al., 2012; Henschke et al., 2015; Post 2002).

TL was estimated using two alternate models of trophic enrichment assumptions, which are used in literature. The first approach is more widely used and assumes a constant enrichment of δ15N with each TL. This constant enrichment approach (TLc) was calculated using the

훿15푁 –훿15푁 following equation (Post, 2002): 푇퐿 = ( 푠 푟푒푓) + 푇퐿 . Where δ15Ns represents the 푐 푇퐸퐹 푟푒푓 δ15N of the consumer sample, and δ15Nref and TLref are baseline values of the δ15N from POM and the assumed trophic level of 1. The TEF (trophic enrichment factor) applied was 3.4 ‰ (Minagawa and Wada, 1984).

The second approach used is based on a scaled enrichment of the δ15N isotope (TLs). This method follows a meta-analysis by Hussey et al. (2014) which assesses 59 experimental studies using SIA to estimate trophic level. It has been identified that the traditional TEF value of 3.4 ‰ may result in underestimation of trophic level in smaller size classes, and overestimate trophic level at larger size classes. The scaled approach therefore aims to reduce these inaccuracies by scaling the trophic enrichment as body size increases. This present study reports on the scaled trophic level estimations. However, in order to allow for direct comparisons of trophic levels with the constant TEF approach in existing literature, results using a TEF of 3.4‰ are included in Appendix 3A .

Calculation of food-chain metrics

Linear regression was conducted to identify significant linear relationships between body mass bins (log2) and trophic level estimated from SIA (BM-TL relationship). Significant BM-TL relationship slopes were compared between eddies using ANCOVA, with Tukey’s HSD test conducted if significantly different slopes were identified.

54 Chapter 3 – Comparison of size-based eddy ecosystems

Ecosystem food chain metrics were calculated from the BM-TL relationship. The mean Predator-Prey Mass Ratios (PPMR) for each eddy was calculated as described in Jennings et al., (2002b) where PPMR = 21/m, where m is the slope of the BM-TL relationship for the eddy.

Trophic transfer efficiency (TE) is calculated as TE = PPMRb+0.75, where b represents the typical slope of linear abundance size spectrum for marine ecosystems (Barnes et al., 2010) of -1.05.

Food chain length (FCL) is calculated by subtracting the trophic level of the primary producers (TL = 1.0) from the maximum trophic level estimated from stable isotope analysis of the community. All equations for ecosystem metrics are explained further in Chapter 2.

Results

Oceanographic characteristics

The cyclonic eddies had shallower mixed layer depth (MLD) of ~86 m and ~226 m for NCC and SCC respectively) compared to the anticyclonic eddies (~185 m and ~309 m for NWC and SWC respectively).

The vertical profiles in temperature and salinity were separate and began to converge ~1,000 m depth, suggesting that the eddy structure was over 1000 m deep (Fig. 3.2). Within the net sampling depth range (0-100 m), the mean temperature was 18.8°C in the NCC eddy, and 19.9°C in the NWC (Table 3.2), and the slightly lower salinity of the NCC (~0.1) was consistent with an upwelling favourable eddy. The temperatures in the southern eddies were cooler than the northern, and with greater differences between them. The SCC was 2.5°C cooler than the SWC (16.0 and 18.5°C in SCC and SWC respectively, Fig. 3.2A), and nearly 0.2 lower salinity (35.58 and 35.77 respectively, Fig. 3.2B, Table 3.2).

Comparison between the northern and southern eddies show that the northern eddies (NCC and NWC) were warmer than their southern counterparts (SCC and SWC). The NCC was 2.8 °C warmer than the SCC, and the NWC was 1.4 °C warmer than the SWC. The Fluorescence, which is a representation of the concentration of photosynthetic organisms within the water, was much higher in the SCC eddy compared to the NCC, which is expected based on the cooler southern waters where the SCC eddy was located.

55 Chapter 3 – Comparison of size-based eddy ecosystems

Table 3.2: Summary of average (SD) of temperature (°C), salinity and Fluorescence (mV) in the upper 100 m. The Mixed Layer Depth (MLD) calculated from the minimum depth to which T < T(10 m) − 0.4°C (Henschke et al. 2019, Condie and Dunn, 2006) Eddy Temperature Salinity Fluorescence MLD

NCC 18.8 (0.3) 35.64 (0.025) 20.7 (1.6) 91 (18) NWC 19.9 (0.1) 35.77 (0.006) 24.1 (2.2) 226 (72) SCC 16.0 (0.1) 35.58 (0.007) 33.2 (2.3) 185 (11) SWC 18.5 (0.1) 35.77 (0.004) 24.3 (2.5) 309 (31)

Figure 3.2: Depth profiles for each eddy taken from CTD casts showing A) mean temperature(°C), and B) mean Salinity, and C) Mean Fluorescence in the top 1000 m; and D) mean temperature, E) mean salinity, and F) mean fluorescence in the top 300m of the NCC eddy (solid blue line), NWC eddy (solid red line), SCC eddy (dashed blue line), and SWC eddy (dashed red line). Biological samples were taken from the top 100m of each eddy at night.

56 Chapter 3 – Comparison of size-based eddy ecosystems

Zooplankton and fish communities

Eddies from the northern region had less zooplankton and fish biomass than either of the southern eddies. NWC and NCC eddy had 50% less biomass of zooplankton than the corresponding southern eddy (Fig. 3.3). The NCC eddy (1.84 mg m-3) had less fish biomass than the NWC eddy (3.11 mg m-3). The SCC eddy (1.65 g m-3) had less fish biomass than the SWC eddy (8.6 mg m-3). In total 25 different families of fish were identified over all four eddies, with a similar Shannon’s diversity index (H) of fish in the NCC (H = 2.29), NWC (H = 2.06), and SWC (H = 2.13) (Table 3.3), the SCC eddy had a less diverse fish community compared to the other three eddies (H = 1.68) with 89.9% of fish in the family Myctophidae.

A total of 25 different fish taxa were identified in the SCC eddy, and 22 taxa were identified in the SWC eddy. A large proportion of the total catch in each eddy was made up of myctophids (Family: Myctophidae). The SCC myctophids primarily consisted of Scopelopsis multipunctatus, Ceratoscopelus warmingii and Hygophum hygomii (20%, 16% and 9% of myctophids respectively). The myctophid species in the SWC eddy was made up of Ceratoscopelus warmingii (33%), and Hygophum hygomii (13%), and Lampanyctus tenuiformis (10%). The remaining biomass for fish species was made up of 16 families in the NCC, and 6 families in the NWC eddy.

57 Chapter 3 – Comparison of size-based eddy ecosystems

Figure 3.3: Comparison of (A) Total biomass of zooplankton captured in the EZ net (n = 1, mg m-3), and (B) mean biomass of fish (mg m-3 ±SD) captured using the pelagic trawl (see section 2.2 for sampling methods). All samples were captured in the top 100 m of water at night.

The NWC was made up of 23 species from 15 families. Most of the fish captured in the NWC were from the family Myctophidae. The NCC eddy fish community was made up of 25 species from 12 identified Families. The family Myctophidae made up 46% of the total fish catch in the NCC eddy, and 75% of the total fish catch in the NWC eddy. Marine hatchetfish (Family: Sternoptychidae) were more abundant in the northern eddies than in the southern eddy pair. Hatchetfish made up 12% of the NCC eddy fish catch, and 5.9% of the NWC eddy catch. In the southern eddies hatchetfish made up 1.4% and 3.3% in the SCC and SWC eddy respectively.

There was a characteristic diversity of fish families in the NWC and SWC eddy (Fig. 3.4), and there was a trend for the northern-southern eddies to be separated along the (second) MDS2 axis. The trend for the cyclonic eddies was less clear. Two of the three NCC trawls and the only SCC trawl were separated from the anticyclonic eddies on the positive side of the MDS1 axis. One NCC trawl was on the negative side of the MDS1 axis, due to a small catch for uncertain reasons.

58 Chapter 3 – Comparison of size-based eddy ecosystems

Figure 3.4: NMDS ordination of family diversity similarity for pelagic trawls in each of the four eddies. Data was transformed using a 4th root transformation. Table 3.3: Percentage of each family of fish abundance in the total catch from the pelagic trawls of each eddy (i.e. collected at night in the top 100m of each eddy). Dominant taxa are in bold. Shannon’s diversity index (H) is calculated for the fish families in each eddy. Proportion of individuals in fish catch NCC NWC SCC SWC Family H = 2.29 H = 2.06 H = 1.68 H = 2.13 Bathylagidae 0.0 0.4 0.0 0.6 Ceratiidae 0.0 0.1 0.0 0.0 Diretmidae 0.0 0.0 0.0 0.3 Evermannellidae 0.3 0.0 0.0 0.0 Gempylidae 0.5 0.0 0.0 0.0 Gonostomatidae 2.6 7.8 0.7 19.3 Grammicolepididae 0.0 0.1 0.0 0.0 Howellidae 0.0 0.2 0.0 0.0 Linophrynidae 0.3 0.0 0.0 0.0 Macroramphosidae 0.3 1.1 0.0 0.0 Molidae 0.0 0.1 0.0 0.0 Myctophidae 46.0 75.3 89.9 64.1 Nemichthyidae 0.0 2.7 0.7 0.6 Notosudidae 0.0 0.1 0.0 1.9 Oneirodidae 0.0 0.0 0.0 0.3

59 Chapter 3 – Comparison of size-based eddy ecosystems

Paralepididae 0.0 1.0 1.4 1.1 Phosichthyidae 2.9 1.1 0.0 5.0 Pleuronectiformes 0.0 0.0 0.0 0.3 Serrivomeridae 0.3 0.0 0.0 0.3 Sternoptychidae 11.9 5.9 1.4 3.3 Stomiidae 1.3 0.8 2.2 1.1 Tetraodontidae 0.3 0.0 0.0 0.0 Trachipteridae 0.5 0.0 0.0 0.0 Trichiuridae 0.0 0.8 0.0 0.0 Unidentified Fish 32.8 2.6 3.6 1.9 TOTAL 100 100 100 100

Normalised biomass size-spectra (NBSS)

Relationships between biomass and body size class provided a strong relationship in each of the four eddies. Each eddy had a significant negative relationship between biomass and body size (p <0.0001; Fig. 3.5). The slopes and intercepts of all four eddies were all similar to each other (ANCOVA, F(3,36) = 0.87; p = 0.47) (Fig. 3.5). The NBSS relationship for each eddy is given in table 3.4.

Table 3.4: linear relationships for normalised biomass size spectra (NBSS) for each of the four eddies derived from linear regression relationships of zooplankton and micronekton biomass in logarithmic size bins. Eddy Relationship R2 p

NCC Log2(Normalised Biomass) = – 1.18·Log2BM+ 0.31 0.97 < 0.0001

NWC Log2(Normalised Biomass) = – 1.09·Log2BM+ 0.22 0.98 < 0.0001

SCC Log2(Normalised Biomass) = – 1.05·Log2BM+ 0.82 0.98 < 0.0001

SWC Log2(Normalised Biomass) = – 1.10·Log2BM+ 0.41 0.98 < 0.0001

60 Chapter 3 – Comparison of size-based eddy ecosystems

Figure 3.5: Normalised Biomass Size Spectra (NBSS) of zooplankton and fish from four mesoscale eddies sampled in the western Tasman Sea. A) Cold-core eddies; and B) Warm-core eddies. Dashed line has been added as a reference. Stable Isotope Analysis

Stable Isotope values of δ13C and δ15N within each eddy was determined from 473 samples, which included POM, zooplankton (< 0.5 g category), and fish up to 16 g category (Fig. 3.6). In general, the northern region had higher δ15N composition and lower δ13C composition than the southern region. The mean δ15N was significantly higher in the NCC eddy compared to

15 either of the southern eddies. (ANOVA, F(3,469)= 9.503, p <0.0001). The mean δ N within the SWC eddy was significantly lower than both northern eddies (Table 3.5).

The mean δ15N of the POM in the NCC was 3.88‰ (range 2.6 to 4.7‰) while the SCC POM had a mean δ15N of 3.6‰ (range 2.9 to 4.2‰). The POM in the NWC eddy had a mean δ15N of 4.2‰ (range 2.7 to 6.2‰) while the SWC was more depleted in δ15N compared to the other eddies with a mean of 1.4‰ (range 0.5 to 3.7‰). The cold-core eddies had a narrower range of δ15N for the entire sampled community compared to the warm-core eddies. (Table 3.3). There was a significant relationship (p < 0.0001) between δ15N and body size of organisms within all four eddies (Fig. 3.7).

61 Chapter 3 – Comparison of size-based eddy ecosystems

The NCC, NWC, and SWC eddies each had a significant relationship between body size and

13 δ C (p < 0.0001). The relationship was not significant in the SCC eddy (F(1,115) = 0.006, p = 0.94,

13 Fig. 3.7). The mean δ C was significantly different (F(3,469) = 27.89, p < 0.0001) between the northern and southern eddies (i.e. more negative in the southern), but did not significantly differ between the two northern eddies or the two southern eddies separately (Tukey’s p < 0.05; Table 3.5).

Table 3.5: Mean (± SD) isotopic value of δ15N and δ13C for all samples taken from each of the four eddies, with minimum and maximum isotopic value of all samples. Isotopic values expressed are in permil (‰). Significant difference between eddies is denoted by differing letters. WM N δ15N δ15N Range δ13C δ13C Range

NCC 118 10.52a (±1.88) 2.6 – 12.8 -19.40a (±0.46) -21.09 – -18.6

NWC 126 9.88ab (±1.82) 2.7 – 14.7 -19.30a (±0.62) -21.78 – -17.7

SCC 133 9.57bc (±1.75) 2.9 – 12.8 -19.82b (±0.45) -20.97 – -18.59

SWC 127 9.15c (±2.29) 0.5 – 13.7 -19.92b (±0.83) -25.3 – -18.48

62 Chapter 3 – Comparison of size-based eddy ecosystems

Figure 3.6: Mean (±SD) Stable Isotope values of δ15N (‰) vs. δ13C (‰) all fish and zooplankton size classes of all four eddies. A) NCC, B) NWC, C) SCC, D) SWC. Diagonal dashed line added for reference.

63 Chapter 3 – Comparison of size-based eddy ecosystems

Figure 3.7: Linear relationships between A) mean δ15N and body-mass and B) mean δ13C and body- mass, derived from stable isotope analysis of the zooplankton and fish sampled in the top 100 m of each eddy. Error bars represent one standard deviation from the mean.

Community Trophic Level – Body Size Analysis

All four eddies had a significant positive relationship between the body-size and the estimated trophic level of the organisms within each size bin (P < 0.001, Fig. 3.8). The slopes of the relationships between eddy types (i.e.: NCC vs SCC; and NWC vs SWC) indicate that there was

64 Chapter 3 – Comparison of size-based eddy ecosystems

no significant differences between the slopes of the cold-core eddies (p = 0.51) or the warm- core eddies (p = 0.26) separately. There was a significant difference in the slopes of the NCC eddy and the SWC eddy (p = 0.018), where the SWC eddy had a more rapid increase in TL with body size (Fig. 3.8).

The relationship between trophic level (TL) and body mass for the SCC eddy was TLSCC = 2.36

+ 0.072·Log2BM, and for the SWC eddy the relationship equation is TLSWC = 2.64 +

0.092·Log2BM (Fig. 3.8). The relationship equation for the NWC was identified as TLNWC = 2.39

+ 0.0797·log2BM, and the NCC was identified as TLNCC = 2.61 + 0.0659·log2BM.

Table 3.6: Mean trophic level (±SE) estimated from stable N isotope analysis for each log2 body-size class sampled in each eddy.

Log2 Body Mass class (g)

Eddy -17.5 -14.5 -11.5 -8.5 -5.5 -2.0 -0.5 0.5 1.5 2.5 3.5

1.56 1.65 2.06 2.11 1.76 2.32 2.63 2.72 2.70 2.75 2.60 NCC - - - - - (0.08) (0.04) (0.04) (0.03) (0.05) -

1.32 1.32 1.50 1.68 1.72 2.11 2.32 2.25 2.59 2.60 2.92 NWC - - - - - (0.05) (0.03) (0.04) (0.04) (0.03) (0.19)

1.25 1.29 1.47 1.50 1.47 2.25 2.29 2.48 2.42 2.49 3.15 SCC - - - - - (0.04) (0.05) (0.06) (0.07) (0.12) -

1.21 1.26 1.52 1.71 1.81 2.43 2.56 2.73 2.78 2.84 3.19 SWC - - - - - (0.05) (0.06) (0.15) (0.08) (0.06) (0.08)

The communities sampled within each eddy show an overlap of the TL estimates within the fish communities as well as in the zooplankton communities, suggesting that these size classes feed on food sources from similar trophic level. The mean TL of size classes in the zooplankton community of the NCC eddy ranges from TL 1.56 – 2.11 and the fish community TL ranged from 2.32 – 2.75 (Table 3.6). The maximum TL sampled from this community was 3.17. Comparing the mean TL of each size class in the NCC eddy with those of the SCC eddy show that the northern eddy has a higher mean TL at each size class (Table 3.6) with the exception of the largest size class (8-16 g), however the largest size class has only a single sample within

65 Chapter 3 – Comparison of size-based eddy ecosystems

the size-class and therefore may not indicate an accurate mean for the community. The maximum TL estimated for the SCC was 3.22.

Figure 3.8: Linear regression relationships between mean trophic level (±SD) and body mass for the entire community of each of the two cold-core eddies (Top) and the two warm-core eddies (Bottom). Dashed lines show the separate relationships for zooplankton and fish communities. Estimates of ecosystem food chain metrics

The Predator-Prey Mass Ratio (PPMR), derived from the slope of the body-size trophic level relationship found that the PPMR of the NCC eddy (PPMR = 43,042:1) was approximately three times that of the SCC eddy (15,994:1). Both these cyclonic eddy PPMR were nearly 10-fold greater than their regional anticyclonic counterparts, where the PPMR of the NWC eddy (5,698:1) was nearly three times greater than the SWC eddy (PPMR = 1,825:1).

Consequently, the Trophic Efficiency (TE) of the two northern eddies was nearly double that of their southern counterparts. The TE of the NCC (4.1%) was similar to that of SCC (5.5%), which were approximately half the TE of the NWC (7.5%) and the SWC (10.5%, Table 3.7).

66 Chapter 3 – Comparison of size-based eddy ecosystems

Food chain lengths (FCL) were similar among the eddy types, with a higher maximum trophic level within the warm-core eddies compared to the cold-core eddies. The food chain length of both cyclonic cold-core eddies was approximately 2.2 trophic levels and a food chain length of nearly 3 trophic levels in both the anti-cyclonic warm-core eddies (Table 3.7).

Table 3.7: Ecosystem metrics derived from the linear relationship between trophic position and body- size for each of the four eddies. Predator-Prey Mass Trophic Transfer Eddy Food Chain Length Max TL Ratio Efficiency NCC 43,042 2.17 0.041 3.17 NWC 5,698 2.85 0.075 3.85 SCC 15,994 2.22 0.055 3.22 SWC 1,825 2.91 0.105 3.91

Discussion

Warm-core eddies in the western Tasman Sea create ecosystems that promote opportunistic carnivory and omnivory in marine consumers which leads to longer food chains and more efficient transfer of energy from prey to predator. Conversely, cold-core eddies often create habitats with more abundant and varied sources of primary production (Waite et al., 2007: 2019), thus promoting herbivory at smaller size classes, resulting in a shorter food chains with a large size difference between predators and prey.

The trophic ecology and ecosystem metrics of these mesoscale eddies of the Tasman Sea were influenced by their location north or south of the Tasman Front. The two northern eddies were influenced by the oligotrophic waters of the East Australian Current, and transport of southern Coral Sea water into the study area, as revealed through stable isotope analysis, and the calculation of the ecosystem metrics of Predator-Prey Mass Ratio (PPMR), trophic transfer efficiency (TE) and food-chain length (FCL). Cold-core eddies had much greater PPMRs when compared to nearby warm-core eddies. This reflects the dominance of herbivorous and omnivorous feeding strategies of low TL zooplankton (e.g. copepods, krill, salps, larvaceans). As a result of this large PPMR cold-core eddies had comparatively small trophic transfer efficiency (TE) and reduced FCL, indicating that due to consumers feeding on much smaller

67 Chapter 3 – Comparison of size-based eddy ecosystems

sized prey, there was less efficient energy assimilation compared to a consumer of the same size in a warm-core eddy (Brose 2010).

Three of the four eddies had a similar rate of TL increase with body size (Figure 3.8) except for the SWC which had a more rapid increase in TL as body size increased. The PPMRs of the southern eddies were much lower than their northern counterparts (i.e. NCC vs SCC and NWC vs SWC) suggesting greater levels of carnivory within the warmer waters in the north. This difference however may also be created due to differences in the abundances of predator and their preferred prey size (Tsai et al., 2016). Since predator prey interactions, described by PPMR, determine the transfer of energy to the next trophic level, smaller PPMRs are often associated with a higher TE, due to predators feeding on more nutritious prey. It is also possible that under oligotrophic conditions there may be longer gut retention times, improving trophic efficiency. Previous studies have also related a smaller PPMR to higher ecosystem stability, and the environmental factors that favour smaller PPMR also promote longer food chains (Cousins, 1987; Jennings and Warr, 2003a, 2003b). Since the body-size, trophic level relationships are all created using the same size ranges (up to 18 g) this study shows that that warm core eddies investigated created a longer food chains with greater trophic transfer efficiency than a cold core eddy in the same region.

A similar size-based food chain analysis of pelagic ecosystems was conducted in the oligotrophic ecosystem of the tropical south Pacific Ocean (Hunt et al., 2015). This study estimated a PPMR of approximately 3600:1 for microzooplankton and micronekton (a similar size range as the communities sampled in the present study, 0.2 - 200 mm), resulting in a TE of 8.5% (0.085). The PPMR and TE of both cold core eddies in the present study were much larger than those estimated in the tropical South Pacific, indicating that there was more predation on smaller zooplankton species and much less carnivory in cold core eddies compared to this oligotrophic tropical ecosystem. In contrast, the NWC eddy had similar community wide PPMR and TE to the south Pacific ecosystem, indicating similar trophic structure between the two habitats. TE is mathematically derived from the PPMR, and biologically this may be interpreted from gut retention times and digestive efficiency. In eutrophic environments digestion may be incomplete when prey is abundant, compared to oligotrophic environments where prey is scarce. Comparisons of TE from 41 different aquatic

68 Chapter 3 – Comparison of size-based eddy ecosystems

environments identify an average global TE of 9.2 %, and 7.1% average for 5 pelagic marine environments (Christensen and Pauly, 1993). TE of both cold core eddies was almost half that of the global average TE, whereas the warm core eddies had TE much closer to 9.2% (See Appendix 3B for comparisons with additional previous studies).

The rate of enrichment of δ15N is known to increase with body size providing a significant and reliable estimate of trophic level (Davenport and Bax, 2002; Miller et al., 2010) with body size (Post 2002a, Jennings et al., 2002; Jennings and van der Molen, 2015). The size of phytoplankton communities within a pelagic ecosystem is important to determining the trophic interactions of the zooplankton communities (Rau et al., 1990; Waite et al. 2007; Henschke et al., 2015). A wider size range of phytoplankton prey within a food web creates additional trophic pathways for more herbivorous species (e.g. copepods, ciliates, euphausiids etc.), whereas a narrower range will promote opportunistic carnivory which will have an impact on the food chain length and trophic efficiency of the food web (Dickman et al., 2008; Young et al., 2015). A more enriched source(s) of food at the base of the food chains of the SCC, driven by a very strong upwelling, is indicated by the wider range of δ13C in the POM samples, and higher isotopic values of δ15N and δ13C for the smaller zooplankton size classes compared to the SWC (Fig. 3.6 and Fig. 3.7). The SWC had depleted mean values of δ15N and δ13C and lower chlorophyll-a values, suggesting that the POM was dominated by a narrower range of smaller phytoplankton species promoting predation in the zooplankton communities (Rau et al., 1990; Henschke et al 2015).

The warm-core eddies had more rapid enrichment of δ15N and δ13C with increasing body size (3.6a and 3.6b), suggesting a higher rate of carnivory within warm-core eddies compared to the cold-core eddies. This enrichment found at the base of the food chain is compounded as predator size increases creating a higher TL with body size in warm-core eddies (Fig. 3.8). This has previously been observed in zooplankton in the western Tasman Sea eddies (Henschke et al., 2015) where the oligotrophic conditions created by a warm-core eddy increased the trophic level of omnivorous zooplankton due to a lower abundance and diversity of prey, creating more predation and opportunistic feeding. Similar opportunistic feeding has also been observed in a wide variety of myctophids that make up the majority of the zooplankton predators in each. Analysis of myctophid gut contents indicate that myctophids feed primarily

69 Chapter 3 – Comparison of size-based eddy ecosystems

on the most available zooplankton prey taxa and show a high degree of dietary overlap between myctophid species (Pakhomov et al., 1996). Previous SIA studies also show that body size is the main structuring characteristic with larger species occupying higher trophic levels (Cherel et al., 2010).

Potential areas of uncertainty

This comparison of eddy ecosystems only examines two warm-core and two cold-core eddies surveyed within the same month. The effect of season on the ecosystem metrics is unknown, but PPMR should increase (with decreased TE) in the spring (more eutrophic) and decrease (with increased TE) in the autumn as prey becomes scarce (more oligotrophic) (Gaedke and Straile, 1994). Also, the effect of marine microbes and diazotrophy (nitrogen fixation) in the ‘microbial loop’ which could form an alternate source of nitrates and nutrients for the low trophic level grazers of these eddies is unknown (Azam et al., 1983; Blanchard et al., 2017; Laiolo et al., 2016). The ‘microbial loop’ would likely create an additional source of baseline production which can feed the lower trophic level consumers. The addition of this source of production could alter TL estimates and should be a consideration in future studies (Hunt et al., 2015, Landrum et al., 2011). Conducting a size-structure analysis of the phytoplankton and primary producer communities would help with identifying the variety of taxa that may influence the food-chains primary consumers and grazers (e.g. diatoms or flagellates; Waite et al. 2019).

This study also focused on specifically the zooplankton and mesopelagic fish taxa that migrate into the epipelagic waters of these eddies during the night. Additional organisms that are expected to share similar trophic levels, such as squid and larger pelagic zooplankton, were removed from this study to be looked at in other publications (Kwong et al., 2020, Murphy et al. 2020). Inclusion of the rest of the taxa from the ecosystems would also provide a more complete view of the food chains, particularly since the squid are a dominant prey group for the large fish predators of the Tasman sea (Young et al., 2010). Furthermore, inclusion of these large fish predator species that are known to feed in these waters of the Tasman Sea (Young et al., 2010), that occupy higher trophic levels would allow for further biodiversity and trophic level comparisons between the eddies. Global patterns in predator-prey relationships

70 Chapter 3 – Comparison of size-based eddy ecosystems

investigated by Barnes et al. (2010), indicate that PPMR increases with body size, and as a result decreases TE at the higher trophic levels. We would expect that including the higher trophic levels would increase the mean PPMR and decrease the mean TE for these ecosystems, but the magnitude of these changes is unknown at this time.

Ideally, I would like to create a model that uses satellite-based observations of sea surface temperature and altimetry and ecosystem metrics observed in these eddies to be able to remotely predict PPMR and TE using satellite data. In order to accomplish this, more eddies would need to be sampled over a wider temporal resolution, which would provide an understanding of how the ecosystem metrics vary with seasons. The logistical costs and expenses of this study on land and at sea were considerable, even when only targeting four eddies, and a number of logistical issues hampered us with such a robust sampling design. It may be possible to determine if these ecosystems metrics can be more easily obtained from only sampling the zooplankton communities and not deploying the pelagic trawl. It is possible that a coupled stable isotope size spectrum approach to zooplankton alone could provide an ecosystem perspective to dynamic ocean management but further analysis of zooplankton, and micronekton is necessary for a complete understanding of the eddy ecosystem (e.g. Fig. 3.6; Hunt et al. 2015).

Concluding remarks

The eddies of the western Tasman Sea sampled during this study show great similarities in terms of the physical and some biological characteristics such as biomass and family diversity. Despite their similarities the eddy communities had remarkably different PPMR and TE that was estimated from stable isotope values. The differences in PPMR represent the different feeding strategies of the zooplankton and micronekton, with the warm-core eddies representing a more carnivorous food chain where predators are eating prey closer to their own body size, resulting in higher community mean TE and longer food chains than in cold- core eddies. An understanding of the trophic structure of the fish and plankton communities within the common ocean habitats and producing ecosystem metrics that describe the predator-prey interactions and efficiencies within are vital for producing accurate fisheries

71 Chapter 3 – Comparison of size-based eddy ecosystems

models and sustaining the large predators that are targeted by Australia’s longline fisheries in the western Tasman Sea.

It is essential to understand the variations in the trophic structures in the dominant habitats in the open ocean. Mesoscale cyclonic and anti-cyclonic eddies are easily observed and tracked using satellite imagery, but there is a lack of connection between the satellite imagery of these habitats and their biological communities. Future directions for this research would be to relate the ecosystem metrics of these four eddies to the environmental conditions in which they are found. Identifying and modelling relationships between the ocean temperature and altimetry with the eddies and the size-structure of the biological communities could provide a means to model ecosystem metrics of PPMR and TE on a large spatial scale using only remotely sensed information. Creating this seascape could benefit fisheries and dynamic ocean management strategies throughout the region or even on a global scale.

72 Chapter 4 – General Discussion

Chapter 4 – General Discussion

In this thesis I examined the size-structured trophic relationships of four ocean eddies in the western Tasman Sea. In order to reasonably represent the zooplankton and fish communities of these eddies I sampled the epipelagic waters at night to include deep water species that migrate towards the surface at dusk, and before they descend before dawn. To summarise this complex system, I used community biomass size spectra and derived key ecosystem metrics of predator prey body mass ratios (PPMR), trophic transfer efficiency (TE) and food chain length (FCL). After acknowledging the north-south differences across the Tasman front, the two warm-core eddies had zooplankton and fish communities with much smaller PPMRs and longer food chains than their companion cold-core eddies. The warm-core eddies, because of smaller PPMRs, had more efficient transfer of energy from one trophic level to the next and longer food chains. Considering how different in age, size, and composition the four eddies were, this tentative observation from just one voyage was surprising and remarkable.

The western Tasman Sea has a dynamic patchwork of habitats that range from the oceanic equivalent of a rainforest, south of the Tasman Front to deserts in the southern Coral Sea (Wilkin and Zhang 2007). The dominant force of the Tasman Sea is the fast-flowing East Australian Current (EAC), which generates a persistent field of eddies that characterise the waters and biological communities off eastern Australia. Cyclonic (cold-core) eddies have significantly more chlorophyll-a concentrations than the surrounding Tasman Sea waters due to entrainment and upwelling of nutrient rich coastal waters, whereas anticyclonic (warm- core) eddies have significantly less chlorophyll-a than the surrounding waters (Baird et al. 2008; Everett et al., 2012).

Oceans of eddies

The biological implications of mesoscale eddies may have global importance. In a synthesis of 16 years of sea level anomaly (derived from altimetry), Chelton et al. (2011b) described the global distribution of eddy formation and movement and showed that cyclonic and anticyclonic eddies influence all parts of the world’s oceans, many with lifespans of months

73 Chapter 4 – General Discussion

and years (Fig. 4.1). By tracking the eddies, Chelton et al. (2011b) found that eddies travel many hundreds of kilometres across ocean basins. from west to east transporting two potentially different ecosystems. Since mesoscale eddies can be tracked using altimetry, it may be possible to use ecosystem metrics, such as those found in this thesis, to provide a first- order approximation of pelagic processes within eddies. This would allow for dynamic monitoring of the biological characteristics of ocean food webs from remotely sensed data.

Figure 4.1: Global observations of the formation of eddies with a lifespan >16 weeks. Observations were made over a 16-year period from October 1992-December 2008. Each dot represents number of eddies formed within 1 x 1° regions of the global oceans. Dot colour represents number of eddies formed from 1 (blue) to 4 (red) eddies per region. From Chelton et al. (2011b).

The eddies of the Tasman Sea are expected to increase in frequency and intensity as a result of changing climates and increasing global temperatures (Suthers et al., 2011; Oliver et al., 2015). Predictions based on Global Climate Models suggest that there will be an increase in eddy frequency due to strengthening EAC which will favour the creation of more warm-core eddies with longer lifespans in the Tasman Sea (Oliver et al., 2015). Observations and predictions of ecosystem metrics for eddies, and the comparisons between cold and warm- core eddies in the region made in this thesis will be valuable for Australia’s network of ocean observing infrastructure. The Integrated Marine Observing System (IMOS) collects real-time, or near real-time data that is openly accessible on almost all regions of Australia’s ocean region (Lara-Lopez et al., 2019; IMOS, www.imos.org.au). From ocean moorings, gliders, drifters, satellite, and ship-board observations, IMOS can provide high-resolution ocean data of physical oceanographic characteristics of waters off Australia. This network of ocean observing makes tracking eddies easier through physical characteristics of sea-level anomaly,

74 Chapter 4 – General Discussion

ocean colour, and sea-surface temperature. Until now it has been difficult to interpret these physical characteristics of the ocean and convert them into a biological perspective of ecosystem structure.

By relating the observations and ecosystem metrics identified in this thesis with the oceanographic characteristics of the four eddies, there is the potential to use this research to produce relatively simple ecosystem models to predict ecosystem food chain characteristics across the western Tasman Sea. Similar work has been conducted in the past on zooplankton size spectra in the western Tasman Sea (White, 2018) that found significant correlations between environmental variables, and the size-structure of zooplankton communities which were used to predict community size spectra based on satellite observations. More recent advances in the northeast Pacific Ocean used generalised additive models (GAMs) to define ocean isoscapes of δ15N and δ13C to predict isotope spatial distribution based on zooplankton community stable isotope analysis and relatively few model parameters such as sea surface temperature, sea-level anomaly, and chlorophyll-a concentrations (Espinasse et al., 2020). The use of widely available biophysical data from IMOS and relatively simple GAMs of size spectra and stable isotope values from zooplankton or micronekton communities could be used in a similar fashion to estimate ecosystem metrics over the Tasman Sea, creating near- real time estimates of PPMR, TE, and FCL for the dynamic ocean habitats of Australia.

Pelagic ecosystem structure.

Pelagic food webs are generally expected to consist of five to six trophic levels from primary producers to top level fish predators, with the mesopelagic zooplankton and fishes occupying the low to mid trophic levels (TL 2 - 4; Davenport and Bax, 2002; Choy et al., 2012; Bernal et al., 2013; Young et al., 2010). Top ocean predators, including large pelagic fish species (such as tuna, and billfish), seabirds, sharks, and marine mammals, all rely on the low to mid trophic level taxa through direct, or indirect predator prey interactions (Young et al., 2010; Young et al., 2015). The major top predators of the Tasman Sea have been recognised as belonging to three general predator groupings that target different feeding niches based on feeding depth and prey type (Young et al., 2010), with Ommastrephid squid and mesopelagic carangid and scombrid fishes being the dominant prey types. These large pelagic predatory fish as well as a

75 Chapter 4 – General Discussion

number of their dominant prey species feed on the abundant zooplankton and micronekton which were the focus of this thesis (Young et al., 2011).

Previous ecological research of habitats and water types in the western Tasman Sea have focused on a relatively small range of taxa such as Particulate Organic Matter (Baird et al. 2008), zooplankton such as copepods (Henschke et al., 2015), krill (Taylor et al., 2010), salps and pyrosomes (Henschke et al., 2011; 2019), or fish ranging from larvae (Griffiths and Wadley, 1986; Mullaney et al., 2011), and mesopelagic fish species to commercially targeted predators (Young et al., 2010; 2015). Few studies have attempted to combine the wide range of taxa into a single study of a complete ecosystem food web, instead focussing on nekton, or zooplankton as individual communities. By using the size-based approach that has been pioneered by Jennings and others (e.g. Jennings et al., 2001b, 2001a, 2002; Jennings and Collingridge, 2015; Jennings and Mackinson, 2003) this thesis simplifies species-based food webs and creates a model of these eddy food chains that allows for direct comparisons with any other size-based analysis conducted (Table 4.1).

Table 4.1: Comparison of predator – prey body mass ratios (PPMR) and trophic transfer efficiencies (TE) between the four Tasman Sea eddies from this present study, with literature values from other stable isotope studies. Food Web PPMR TE (%) Reference NCC Eddy (Pelagic) 43042 4.1 Present Study NWC Eddy (Pelagic) 5698 7.5 Present Study SCC Eddy (Pelagic) 15994 5.5 Present Study SWC Eddy (Pelagic) 1825 10.5 Present Study Southwest sub-tropical Pacific (Pelagic)a 3683 8.5 Hunt et al., 2015 Southwest sub-tropical Pacific (Pelagic)b 244000 2.4 Hunt et al., 2015 North Sea (Demersal)b 80 - Jennings et al., 2001 North Sea (Demersal)b 424 16.3 Jennings and Warr, 2003 East China Sea (Pelagic)b 3430 - Ohshimo et al., 2016 Atlantic Iberian Shelf (Pelagic)b 200000 - Bode et al., 2007 a Macrozooplankton/Micronekton b Nekton

Research into size-structured food chains of the pelagic subtropical South Pacific by Hunt et al. (2015) identified that the microzooplankton/mesozooplankton size classes, which were similar in size range to those examined within this thesis, are primarily responsible to determining the overall food-chain length of ecosystems as they are more sensitive to changes

76 Chapter 4 – General Discussion

in size structure of primary producers. The micronekton ecosystems within the subtropical Pacific studied by Hunt et al., (2015) show very similar ecosystem values to the two warm- core eddies examined in this thesis, with relatively similar PPMR and TE, and very similar food chain length estimates of 1.7-2.3, indicating a similarity between trophodynamics of the two habitats. When including the larger consumers in pelagic studies such as the nekton samples in the study by Hunt et al., (2015), and predator prey mass ratios estimated from the Iberian peninsula by Bode et al. (2007), PPMRs were significantly higher compared to the eddy ecosystems indicating high levels of predation on zooplankton or smaller nekton. It is highly likely that the inclusion of larger consumers in the eddy ecosystems would result in similar PPMR estimates as many of the common predatory species in the region feed on small sized fish and nekton (Young et al., 2005).

Trophic level studies on benthic food webs of the North Sea conducted by Jennings et al., (2001) and Jennings and Warr (2003) have identified a substantially lower PPMR of 80:1 and 424:1 respectively, the latter study also identifying a mean transfer efficiency of 16.3%. These PPMR estimates indicate a highly predatory environment driven by carnivory, and where many of the larger consumers are primarily piscivorous. This is in contrast to the pelagic eddy ecosystems where many of the taxa identified were planktivorous feeding on the more abundant zooplankton.

The predator-prey interactions of these eddy ecosystems are described, in a simplified way, by PPMR, a promising parameter for modelling food web structure and dynamics (Nakazawa et al., 2011; Blanchard et al., 2017). The combination of PPMR, FCL, and TE can be used to determine the relationship of ecosystem energy availability with body-size. In the North Sea, Jennings and Blanchard (2004) used these metrics and estimates of community size spectra to predict fish abundances in the presence, and absence, of anthropogenic fishing pressure. The results of these predictive models indicated that fishing had decreased the biomass of large fish by 38% compared to the absence of fishing. Jennings and Collingridge (2015), also used similar modelling strategies to estimate fish biomass on a global scale compared to traditional estimates, revealing that global consumer biomass and productivity predictions are hampered by large uncertainties in trophic transfer efficiencies and PPMR, and the use of these ecosystem metrics, even in simple models, increase the effectiveness and produce

77 Chapter 4 – General Discussion

equitable estimates compared to the more complex models that are currently in use. A deeper understanding of the efficiency and trophic structure of these pelagic food chains would be a great benefit to Australian fisheries using management strategies that rely on a dynamic understanding of Australia’s ocean habitats (Hobday et al., 2011; Smith et al., 2007).

Broader findings of the four mesoscale eddies

The overarching goal of my thesis was to create a greater understanding of the ubiquitous eddies created by the EAC. As part of the multi-disciplined approach to sampling these four eddies, different areas of the biological communities that were sampled within the four eddies are being studied by different researchers at different institutions. The research includes several other important features of these four eddies. The southern eddy dipole (SCC and SWC, Chapter 3) drove an onshore flow of water over 200 km from the Tasman Sea towards Newcastle, a region which receives more than 50% of the onshore flows for the NSW coast (Malan et al. 2020), and was colloquially described as the “larval super-highway” (Malan et al., 2020).

The biomass of gelatinous zooplankton grazers (pyrosomes), and their role in vertical carbon flux was identified in three of the four eddies from this thesis. The biologically driven carbon flux through the water column, was examined on a wider range of zooplankton and micronekton taxa by Kwong et al. (2020). This study identified that in eddies with deeper mixed layers (such as in warm-core eddies) micronekton are more important to vertical carbon flux than zooplankton, whilst in eddies with shallower mixed layers the zooplankton contributed more. The differences in carbon export were attributed to food availability, temperature, and time spent migrating (Kwong et al., 2020). Additionally, Henschke et al. (2019) observed increased chlorophyll-a and preferred food in the cold core eddy (SCC) lead to significantly greater biomass of the pyrosome Pyrosoma atlanticum. This increase in pyrosome biomass also created significant amounts of vertical carbon flux in the form of faecal pellets, sinking carcasses, and diel-vertical migration.

Several other studies are currently in development, or review, for publication, such as the trophic position of pelagic squid (Murphy et al., in review), and species diversity, growth, and

78 Chapter 4 – General Discussion

distributions of larval fish (Hinchcliff et al., in prep.). These separate studies create a complete picture of the pelagic ecosystems that support Australia’s national blue economy, and it is my ambition to combine the results of this thesis with the numerous other discoveries made from this voyage into a complete synthesis of eddy ecosystems off eastern Australian.

Thesis Limitations and Considerations

My thesis is based on the samples captured from a single research voyage that sampled four ocean eddies during spring (oceanographically the coldest time of the year), sometimes without replication such as only one MOCNESS tows for zooplankton, and only one MIDOC in the SCC eddy. With a lack of seasonal samples, it is very difficult to infer any general patterns from the results of my study, and therefore caution should be made when extrapolating these results. Nevertheless, the ecosystem metrics for the northern eddies were similar to estimates made for zooplankton and micronekton from around New Caledonia (Hunt et al. 2015) and align with metrics expected from eutrophic and oligotrophic systems (Ohshimo et al., 2016). To further generalise my findings, it is important to return to similar eddies with the same methods during late summer, and to sample each eddy at least twice (as we had originally intended). It would be particularly interesting to compare these ecosystem metrics during the daytime and capture the diel vertical migration at 500 m depth.

In order to capture a wide variety of taxa of each community, with limited replication, sampling was undertaken in the epipelagic waters during the night. This ensured that we sampled many of the mesopelagic taxa that undergo diel vertical migration (DVM), and we were unable to assess any variations in the trophic ecology of the eddies at depth, or during daytime. The process of DVM creates variation in daytime and night-time biomass within the epipelagic waters of the eddies (Sutton, 2013), and also creates an avenue of vertical carbon transport within ocean eddies. This has been shown to act as a significant carbon sink where differences in carbon export were dependent on food availability, temperature, time spent migrating, and mixed layer depth create different levels of vertical migration and carbon flux (Kwong et al., 2020).

The total biomass were made for each eddy using pelagic trawl catch biomass adjusted by the amount of water filtered by the net area, and net sampling of micronekton may underestimate

79 Chapter 4 – General Discussion

biomass by an order of magnitude due to active net avoidance (Kloser et al., 2009; Kaartvedt et al., 2012). Ideally, biomass estimates from these four eddies would be supported by bioacoustic data that can accurately identify vertical distributions of eddy communities, however due to logistical and calibration errors with the bioacoustics equipment on board, acoustic estimates of eddy biomasses could not be accurately measured and were not included in this study.

The taxa that were examined in this thesis were restricted to zooplankton, and the micronekton fish captured with pelagic trawls towed at 1 m s-1. Other taxa such as fast-moving squid, gelatinous zooplankton and larger crustaceans were either unsampled, in low abundance, or were directed to other studies (Henschke et al., 2019; Kwong et al., 2020; Murphy et al., 2020; Hinchcliff et al., in prep.). Squid were only obtained in sufficient abundance in the SCC due to more tows made without the MIDOC to sample the larval lobster Murphy et al., in review). As such the contribution of these taxa to energy transfer efficiency, and PPMR is largely overlooked. Since these taxa make up significant proportions of prey species for large predatory fish (Young et al., 2010; 2011), their inclusion into this research would provide information on a much wider range of energy pathways in eddy ecosystems. Additionally, the inclusion of TL data of the large marine predatory species that feed within this region (Revill et al., 2009), would also provide valuable insights into the total food chain size, and energy transfer efficiency all the way from producers to predators.

The use of bulk tissue stable isotope analysis of carbon and nitrogen in ecological studies is based on numerous studies that have refined methods and created a suitable alternative to gut-content analysis to estimate trophic level (Cabana and Rasmussen, 1996; Jennings and van der Molen, 2015; McCormack et al., 2019). The traditional methods involve a constant enrichment of δ15N with each successive trophic level (Post, 2002), providing that the isotopic values for baseline trophic levels are known, but uncertainties or variations (temporal, and spatial) in production sources at the base of marine food webs can lead to inaccurate estimations of trophic levels. In this study I calculated both TL based on the enrichment of δ15N as 3.4 ‰ per TL, as well as a scaled trophic enrichment factor (Chapter 2, 3), but there is uncertainty in the enrichment factor. Recent advances involve the use of compound-specific isotope analysis, such as “source” amino-acids (phenylalanine) which fractionate very little

80 Chapter 4 – General Discussion

with trophic level (Choy et al., 2012), compared to “trophic” amino acids (e.g. glutamic acid) which do fraction by ~7 ‰ per TL. Choy et al., (2012) compared bulk-tissue and compound specific SIA of two dominant mesopelagic fishes - lanternfish (Myctophidae) and dragonfish (Stomiidae) from five locations across the globe. Their results found that bulk-tissue analysis estimates were inconsistent and produced trophic level estimates that were not consistent with gut-contents analysis, due to regional variability in isotopic signatures of baseline organisms (i.e. POM). They found lanternfish had a TL of ~2.9, whilst dragonfish had a TL ~3.2 (which was nearly one TL lower than that estimated from previous stomach contents analysis). It was expected that dragonfish species have exceptionally low metabolic rates in the deep ocean, about tenfold lower than the more active, diel-vertically migrating lanternfishes, which leads to the lower than expected TL estimate from SIA. The TL estimates for these two fish families identified in this thesis were very similar to the estimates made by Choy et al., (2012). In Chapter 2, the mean TL for the Stomiidae family (2.6, and 2.7 in the CCE and WCE respectively) were much closer to the TL of myctophids than previous gut contents studies would suggest. The large overlap in TL ranges of these two families suggests that they share the same, or similar trophic niches at these size ranges. Choy et al., (2012) also notes that compound specific SIA also has inconsistencies when compared to gut-contents analysis, but have less issues compared to bulk tissue analysis. This relatively new stable isotope analysis technique merits consideration but at the time of this study was relatively expensive for such a large-scale project.

Final Thoughts on the global impacts of this research

Satellite data on sea-surface anomalies at a global scale identify that cyclonic, and anticyclonic eddies are formed in nearly every sub-tropical and temperate ocean of the world (Chelton et al., 2011b). Size spectra data has been used previously to estimate fish populations under a number of different scenarios, with significant work being conducted on creative predictive models to estimate consumer biomass under different fishing pressures (Jennings and Blanchard, 2004; Jennings et al., 2002b), however these studies are very localised since few parameters such as PPMR, TE, and size-spectra slope are consistent on global scales (Jennings

81 Chapter 4 – General Discussion

and Collingridge, 2015). The size spectra data and estimates of ecosystem metrics from this study will help to generate these predictive models of the Tasman Sea.

My study provides one of the first size-based studies of the epipelagic-ecosystem of zooplankton and fish combined. One of the more important parts of ocean food webs is the connection between top predators and the micronekton/zooplankton within their diets. As these connections change based on life history stages, regions, time of the year and the depth preferences of the fish, a more detailed view on the food webs of different regions and the habitats within is vital (La Borgne et al., 2011). Many ecosystem and fisheries modelling approaches generally represent small zooplankton as phytoplankton, and larger zooplankton as small fish, thereby misrepresenting, or ignoring completely, the trophic dynamics that occur in between these very different trophic communities (Heneghan et al., 2016). These models do not therefore capture accurately the trophic dynamics leading to estimates of fish productivity and ecosystem stability (Heneghan et al. 2016; Blanchard et al. 2017). Other models use chlorophyll-a concentrations as the primary determinant of fish production, also ignoring the transfer efficiencies and predator prey interactions that occur between the lower consumer trophic levels (Stock et al., 2017).

As the global oceans warm, habitats and food webs will undoubtably change. It has been shown that warming seas has an observable effect on the composition, and biomass of primary producers, zooplankton, and micronekton communities. Further research into the composition and food web characteristics of pelagic food webs is needed to predict and manage the changes that they will undergo (La Borgne et al. 2011). Eddies in particular have been predicted to change in frequency, size, and intensity under climate change predictions, meaning there will be more eddies in the future (Oliver et al. 2015).With a more detailed understanding of the size-based relationships in these food chains we provide simple yet informed ecosystem metrics that describe the food web size structures and predator prey relationships of the open ocean eddies of the Tasman Sea.

82 References

References

Andersen, K. h., Berge, T., Gonçalves, R. j., Hartvig, M., Heuschele, J., Hylander, S., Jacobsen, N. s., Lindemann, C., Martens, E. a., Neuheimer, A. b., Olsson, K., Palacz, A., Prowe, A. e. f., Sainmont, J., Traving, S. j., Visser, A. w., Wadhwa, N., Kiørboe, T., 2016. Characteristic Sizes of Life in the Oceans, from Bacteria to Whales. Annu. Rev. Mar. Sci. 8, 217–241. https://doi.org/10.1146/annurev-marine-122414-034144

Andersen, K.H., Beyer, J.E., DeAngelis, A.E. and E.D.L., 2006. Asymptotic Size Determines Species Abundance in the Marine Size Spectrum. The American Naturalist 168, 54–61. https://doi.org/10.1086/504849

Andersen, K.H., Beyer, J.E., Lundberg, P., 2009. Trophic and individual efficiencies of size-structured communities. Proc Biol Sci 276, 109–114. https://doi.org/10.1098/rspb.2008.0951

Australian Bureau Of Agricultural Resource Economics And Sciences (ABARES), 2019. Fishery status reports 2019. https://doi.org/10.25814/5D80431DE3FAE

Azam, F., Fenchel, T., Field, J.G., Gray, J.S., Meyer-Reil, L.A., Thingstad, F., 1983. The Ecological Role of Water-Column Microbes in the Sea. Marine Ecology Progress Series 10, 257–263.

Azis Ismail, M.F., Ribbe, J., Karstensen, J., Lemckert, C., Lee, S., Gustafson, J., 2017. The Fraser Gyre: A cyclonic eddy off the coast of eastern Australia. Estuarine, Coastal and Shelf Science 192, 72– 85. https://doi.org/10.1016/j.ecss.2017.04.031

Baird, M.E., Timko, P.G., Middleton, J.H., Mullaney, T.J., Cox, D.R., Suthers, I.M., 2008. Biological properties across the Tasman Front off southeast Australia. Deep Sea Research Part I: Oceanographic Research Papers 55, 1438–1455. https://doi.org/10.1016/j.dsr.2008.06.011

Bakun, A., 2006. Fronts and eddies as key structures in the habitat of marine fish larvae: opportunity, adaptive response and competitive advantage. Scientia Marina 70, 105–122. https://doi.org/10.3989/scimar.2006.70s2105

Barnes, C., Bethea, D.M., Brodeur, R.D., Spitz, J., Ridoux, V., Pusineri, C., Chase, B.C., Hunsicker, M.E., Juanes, F., Kellermann, A., Lancaster, J., Ménard, F., Bard, F.-X., Munk, P., Pinnegar, J.K., Scharf, F.S., Rountree, R.A., Stergiou, K.I., Sassa, C., Sabates, A., Jennings, S., 2008. Predator and Body Sizes in Marine Food Webs: Ecological Archives. Ecology 89, 881–881.

Barnes, C., Maxwell, D., Reuman, D.C., Jennings, S., 2010. Global patterns in predator—prey size relationships reveal size dependency of trophic transfer efficiency. Ecology 91, 222–232.

Barnes, C., Sweeting, C.J., Jennings, S., Barry, J.T., Polunin, N.V.C., 2007. Effect of temperature and ration size on carbon and nitrogen stable isotope trophic fractionation. Functional Ecology 21, 356–362. https://doi.org/10.1111/j.1365-2435.2006.01224.x

Belgrano, A., Scharler, Scharler, U.M., Dunne, J., Ulanowicz, R.E., 2005. Aquatic Food Webs: An Ecosystem Approach. OUP Oxford.

83 References

Bernal, A., Olivar, M., Fernández de Puelles, M., 2013. Feeding patterns of Lampanyctus pusillus (Pisces: Myctophidae) throughout its ontogenetic development. Marine Biology 160, 81–95. https://doi.org/10.1007/s00227-012-2064-9

Blanchard, J., Law, R., Castle, M., Jennings, S., 2011. Coupled energy pathways and the resilience of size-structured food webs. Theoretical Ecology 4, 289–300. https://doi.org/10.1007/s12080- 010-0078-9

Blanchard, J.L., Heneghan, R.F., Everett, J.D., Trebilco, R., Richardson, A.J., 2017. From Bacteria to Whales: Using Functional Size Spectra to Model Marine Ecosystems. Trends in Ecology & Evolution 32, 174–186. https://doi.org/10.1016/j.tree.2016.12.003

Blanchard, J.L., Jennings, S., Law, R., Castle, M.D., McCloghrie, P., Rochet, M.-J., Benoît, E., 2009. How Does Abundance Scale with Body Size in Coupled Size-Structured Food Webs? Journal of Animal Ecology 78, 270–280.

Bode, A., Alvarez-Ossorio, M.T., Cunha, M.E., Garrido, S., Peleteiro, J.B., Porteiro, C., Valdés, L., Varela, M., 2007. Stable nitrogen isotope studies of the pelagic food web on the Atlantic shelf of the Iberian Peninsula. Progress in Oceanography, Ecological Functioning of the Iberian Seas: A synthesis of GLOBEC Research in Spain and Portugal 74, 115–131. https://doi.org/10.1016/j.pocean.2007.04.005

Boecklen, W.J., Yarnes, C.T., Cook, B.A., James, A.C., 2011. On the Use of Stable Isotopes in Trophic Ecology. Annu. Rev. Ecol. Evol. Syst. 42, 411–440. https://doi.org/10.1146/annurev-ecolsys- 102209-144726

Brandt, S.B., 1983. Temporal and spatial patterns of lanternfish (family Myctophidae) communities associated with a warm-core eddy. Mar. Biol. 74, 231–244. https://doi.org/10.1007/BF00403447

Brandt, S.B., 1981. Effects of a Warm-Core Eddy on Fish Distributions in the Tasman Sea Off East Australia. Marine Ecology Progress Series 6, 19–33.

Brose, U., 2010. Body-Mass Constraints on Foraging Behaviour Determine Population and Food-Web Dynamics. Functional Ecology 24, 28–34.

Bryndum‐Buchholz, A., Tittensor, D.P., Blanchard, J.L., Cheung, W.W.L., Coll, M., Galbraith, E.D., Jennings, S., Maury, O., Lotze, H.K., 2019. Twenty-first-century climate change impacts on marine animal biomass and ecosystem structure across ocean basins. Global Change Biology 25, 459–472. https://doi.org/10.1111/gcb.14512

Cabana, G., Rasmussen, J.B., 1996. Comparison of Aquatic Food Chains Using Nitrogen Isotopes. Proceedings of the National Academy of Sciences of the United States of America 93, 10844– 10847.

Cai, W., Shi, G., Cowan, T., Bi, D., Ribbe, J., 2005. The response of the Southern Annular Mode, the East Australian Current, and the southern mid-latitude ocean circulation to global warming. Geophysical Research Letters 32. https://doi.org/10.1029/2005GL024701

84 References

Caut, S., Angulo, E., Courchamp, F., 2009. Variation in discrimination factors (Δ15N and Δ13C): the effect of diet isotopic values and applications for diet reconstruction. Journal of Applied Ecology 46, 443–453. https://doi.org/10.1111/j.1365-2664.2009.01620.x

Cetina-Heredia, P., Roughan, M., Liggins, G., Coleman, M.A., Jeffs, A., 2019. Mesoscale circulation determines broad spatio-temporal settlement patterns of lobster. PLOS ONE 14, e0211722. https://doi.org/10.1371/journal.pone.0211722

Cetina‐Heredia, P., Roughan, M., Sebille, E. van, Coleman, M.A., 2014. Long-term trends in the East Australian Current separation latitude and eddy driven transport. Journal of Geophysical Research: Oceans 119, 4351–4366. https://doi.org/10.1002/2014JC010071

Chelton, D.B., Gaube, P., Schlax, M.G., Early, J.J., Samelson, R.M., 2011a. The Influence of Nonlinear Mesoscale Eddies on Near-Surface Oceanic Chlorophyll. Science 334, 328–332.

Chelton, D.B., Schlax, M.G., Samelson, R.M., 2011b. Global observations of nonlinear mesoscale eddies. Progress in Oceanography 91, 167–216. https://doi.org/10.1016/j.pocean.2011.01.002

Cherel, Y., Ducatez, S., Fontaine, C., Richard, P., Guinet, C., 2008. Stable isotopes reveal the trophic position and mesopelagic fish diet of female southern elephant seals breeding on the Kerguelen Islands. Marine Ecology Progress Series 370, 239–247.

Cherel, Y., Fontaine, C., Richard, P., Labatc, J.-P., 2010. Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean. Limnol. Oceanogr. 55, 324–332. https://doi.org/10.4319/lo.2010.55.1.0324

Choy, C.A., Davison, P.C., Drazen, J.C., Flynn, A., Gier, E.J., Hoffman, J.C., McClain-Counts, J.P., Miller, T.W., Popp, B.N., Ross, S.W., Sutton, T.T., 2012. Global Trophic Position Comparison of Two Dominant Mesopelagic Fish Families (Myctophidae, Stomiidae) Using Amino Acid Nitrogen Isotopic Analyses. PLOS ONE 7, e50133. https://doi.org/10.1371/journal.pone.0050133

Christensen, V., Pauly, D., 1993. Flow characteristics of aquatic ecosystems, in: In Trophic Models of Aquatic Ecosystems.

Condie, S., Condie, R., 2016. Retention of plankton within ocean eddies. Global Ecology and Biogeography 25, 1264–1277. https://doi.org/10.1111/geb.12485

Coplen, T.B., 2011. Guidelines and recommended terms for expression of stable-isotope-ratio and gas- ratio measurement results. Rapid Commun. Mass Spectrom. 25, 2538–2560. https://doi.org/10.1002/rcm.5129

Cousins, S., 1987. The decline of the trophic level concept. Trends in Ecology & Evolution 2, 312–316. https://doi.org/10.1016/0169-5347(87)90086-3

Cresswell, G., 1994. Nutrient enrichment of the Sydney continental shelf. Mar. Freshwater Res. 45, 677–691. https://doi.org/10.1071/mf9940677

Cresswell, G.R., Legeckis, R., 1986. Eddies off southeastern Australia. Deep Sea Research Part A. Oceanographic Research Papers 33, 1527–1562. https://doi.org/10.1016/0198- 0149(86)90066-X

85 References

Davenport, S.R., Bax, N.J., 2002. A trophic study of a marine ecosystem off southeastern Australia using stable isotopes of carbon and nitrogen. Canadian Journal of Fisheries and Aquatic Sciences 59, 514–530.

Dickman, E.M., Newell, J.M., González, M.J., Vanni, M.J., 2008. Light, Nutrients, and Food-Chain Length Constrain Planktonic Energy Transfer Efficiency across Multiple Trophic Levels. Proceedings of the National Academy of Sciences of the United States of America 105, 18408–18412.

Dorado, S., Rooker, J.R., Wissel, B., Quigg, A., 2012. Isotope baseline shifts in pelagic food webs of the Gulf of Mexico. Marine Ecology Progress Series 464, 37–49.

Drazen, J.C., Sutton, T.T., 2017. Dining in the Deep: The Feeding Ecology of Deep-Sea Fishes. Annu. Rev. Mar. Sci. 9, 337–366. https://doi.org/10.1146/annurev-marine-010816-060543

Dunn, D.C., Maxwell, S.M., Boustany, A.M., Halpin, P.N., 2016. Dynamic ocean management increases the efficiency and efficacy of fisheries management. Proceedings of the National Academy of Sciences of the United States of America 113, 668–673.

Edwards, A.M., Robinson, J.P.W., Plank, M.J., Baum, J.K., Blanchard, J.L., 2017. Testing and recommending methods for fitting size spectra to data. Methods in Ecology and Evolution 8, 57–67. https://doi.org/10.1111/2041-210X.12641

Espinasse, B., Hunt, B.P.V., Batten, S.D., Pakhomov, E.A., 2020. Defining isoscapes in the Northeast Pacific as an index of ocean productivity. Global Ecology and Biogeography 29, 246–261. https://doi.org/10.1111/geb.13022

Everett, J.D., Baird M. E., Oke P. R., Suthers I. M., 2012. An avenue of eddies: Quantifying the biophysical properties of mesoscale eddies in the Tasman Sea. Geophysical Research Letters 39. https://doi.org/10.1029/2012GL053091

Everett, J.D., Baird, M.E., Buchanan, P., Bulman, C., Davies, C., Downie, R., Griffiths, C., Heneghan, R., Kloser, R.J., Laiolo, L., Lara-Lopez, A., Lozano-Montes, H., Matear, R.J., McEnnulty, F., Robson, B., Rochester, W., Skerratt, J., Smith, J.A., Strzelecki, J., Suthers, I.M., Swadling, K.M., van Ruth, P., Richardson, A.J., 2017. Modeling What We Sample and Sampling What We Model: Challenges for Zooplankton Model Assessment. Front. Mar. Sci. 4. https://doi.org/10.3389/fmars.2017.00077

Everett, J.D., Baird, M.E., Roughan, M., Suthers, I.M., Doblin, M.A., 2014. Relative impact of seasonal and oceanographic drivers on surface chlorophyll a along a Western Boundary Current. Progress in Oceanography 120, 340–351. https://doi.org/10.1016/j.pocean.2013.10.016

Everett, J.D., Macdonald, H., Baird, M.E., Humphries, J., Roughan, M., Suthers, I.M., 2015. Cyclonic entrainment of preconditioned shelf waters into a frontal eddy. Journal of Geophysical Research: Oceans 120, 677–691. https://doi.org/10.1002/2014JC010301

Falkowski, P.G., Ziemann, D., al, et, 1991. Role of Eddy Pumping in Enhancing Primary Production in the Ocean. Nature; London 352, 55. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1038/352055a0

Flynn, A. J., Pogonoski, J. J., 2012. Guide to mesopelagic fishes of the southern Tasman Sea. CSIRO Marine and Atmospheric Research, Hobart, Australia.

86 References

Flynn, A.J., Kloser, R.J., 2012. Cross-basin heterogeneity in lanternfish (family Myctophidae) assemblages and isotopic niches (δ13C and δ15N) in the southern Tasman Sea abyssal basin. Deep Sea Research Part I: Oceanographic Research Papers 69, 113–127. https://doi.org/10.1016/j.dsr.2012.07.007

France, R.L., Peters, R.H., 1997. Ecosystem differences in the trophic enrichment of 13C in aquatic food webs. Can. J. Fish. Aquat. Sci. 54, 1255–1258. https://doi.org/10.1139/f97-044

Fulton, E.A., Smith, A.D.M., Punt, A.E., 2005. Which ecological indicators can robustly detect effects of fishing? ICES J Mar Sci 62, 540–551. https://doi.org/10.1016/j.icesjms.2004.12.012

Gaedke, U., Straile, D., 1994. Seasonal changes of trophic transfer efficiencies in a plankton food web derived from biomass size distributions and network analysis. Ecological Modelling, State-of- the-Art in Ecological Modelling proceedings of ISEM’s 8th International Conference 75–76, 435–445. https://doi.org/10.1016/0304-3800(94)90038-8

Gaston, T.F., Kostoglidis, A., Suthers, I.M., 2004. The 13C, 15N and 34S signatures of a rocky reef planktivorous fish indicate different coastal discharges of sewage. Mar. Freshwater Res. 55, 689–699. https://doi.org/10.1071/MF03142

Gaube, P., McGillicuddy, D.J., Chelton, D.B., Behrenfeld, M.J., Strutton, P.G., 2014. Regional variations in the influence of mesoscale eddies on near-surface chlorophyll. Journal of Geophysical Research: Oceans 119, 8195–8220. https://doi.org/10.1002/2014JC010111

Godø, O.R., Samuelsen, A., Macaulay, G.J., Patel, R., Hjøllo, S.S., Horne, J., Kaartvedt, S., Johannessen, J.A., 2012. Mesoscale Eddies Are Oases for Higher Trophic Marine Life. PLOS ONE 7, e30161. https://doi.org/10.1371/journal.pone.0030161

Griffiths, F.B., Wadley, V.A., 1986. A synoptic comparison of fishes and crustaceans from a warm-core eddy, the East Australian Current, the Coral Sea and the Tasman Sea. Deep Sea Research Part A. Oceanographic Research Papers 33, 1907–1922. https://doi.org/10.1016/0198- 0149(86)90085-3

Han, B.-P., Straškraba, M., 1998. Size Dependence of Biomass Spectra and Population Density I. The Effects of Size Scales and Size Intervals. Journal of Theoretical Biology 191, 259–265. https://doi.org/10.1006/jtbi.1997.0574

Hare, J.A., Churchill, J.H., Cowen, R.K., Berger, T.J., Cornillon, P.C., Dragos, P., Glenn, S.M., Govoni, J.J., Lee, T.N., 2002. Routes and Rates of Larval Fish Transport from the Southeast to the Northeast United States Continental Shelf. Limnology and Oceanography 47, 1774–1789.

Heneghan, R.F., Everett, J.D., Blanchard, J.L., Richardson, A.J., 2016. Zooplankton Are Not Fish: Improving Zooplankton Realism in Size-Spectrum Models Mediates Energy Transfer in Food Webs. Front. Mar. Sci. 3. https://doi.org/10.3389/fmars.2016.00201

Henschke, N., Everett, J.D., Baird, M.E., Taylor, M.D., Suthers, I.M., 2011. Distribution of life-history stages of the salp Thalia democratica in shelf waters during a spring bloom. Marine Ecology Progress Series 430, 49–62.

Henschke, N., Everett, J.D., Suthers, I.M., Smith, J.A., Hunt, B.P.V., Doblin, M.A., Taylor, M.D., 2015. Zooplankton trophic niches respond to different water types of the western Tasman Sea: A

87 References

stable isotope analysis. Deep Sea Research Part I: Oceanographic Research Papers 104, 1–8. https://doi.org/10.1016/j.dsr.2015.06.010

Henschke, N., Pakhomov, E.A., Kwong, L.E., Everett, J.D., Laiolo, L., Coghlan, A.R., Suthers, I.M., 2019. Large Vertical Migrations of Pyrosoma atlanticum Play an Important Role in Active Carbon Transport. Journal of Geophysical Research: Biogeosciences 124, 1056–1070. https://doi.org/10.1029/2018JG004918

Herman, A.W., Harvey, M., 2006. Application of normalized biomass size spectra to laser optical plankton counter net intercomparisons of zooplankton distributions. Journal of Geophysical Research: Oceans 111. https://doi.org/10.1029/2005JC002948

Hertz, E., Robinson, J.P.W., Trudel, M., Mazumder, A., Baum, J.K., 2014. Estimation of predator-prey mass ratios using stable isotopes: sources of errors. Marine Ecology Progress Series 516, 1–6. https://doi.org/10.3354/meps11079

Herzka, S.Z., 2005. Assessing connectivity of estuarine fishes based on stable isotope ratio analysis. Estuarine, Coastal and Shelf Science, Connectivity in the life cycles of fishes and invertebrates that use estuaries 64, 58–69. https://doi.org/10.1016/j.ecss.2005.02.006

Ho, P., Chang, C., Hsieh, C.H., Shiah, F., Miki, T., 2013. Effects of increasing nutrient supply and omnivorous feeding on the size spectrum slope: a size-based nutrient-phytoplankton- zooplankton model. Population Ecology; Tokyo 55, 247–259. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1007/s10144-013-0368-3

Hobday, A.J., Hartmann, K., 2006. Near real-time spatial management based on habitat predictions for a longline bycatch species. Fisheries Management & Ecology 13, 365–380. https://doi.org/10.1111/j.1365-2400.2006.00515.x

Hobday, A.J., Hartog, J.R., 2014. Derived Ocean Features for Dynamic Ocean Management. Oceanography 27, 134–145.

Hobday, A.J., Lough, J.M., 2011. Projected climate change in Australian marine and freshwater environments. Mar. Freshwater Res. 62, 1000–1014. https://doi.org/10.1071/MF10302

Hobday, A.J., Maxwell, S.M., Forgie, J., McDonald, J., Darby, M., Seto, K., Bailey, H., Bograd, S.J., Briscoe, D.K., Costa, D.P., Crowder, L.B., Dunn, D.C., Fossette, S., Halpin, P.N., Hartog, J.R., Hazen, E.L., Lascelles, B.G., Lewison, R.L., Poulos, G., Powers, A., 2014. Dynamic Ocean Management: Integrating Scientific and Technological Capacity with Law, Policy, and Management. Stanford Environmental Law Journal 33, 125–165.

Hobday, A.J., Young, J.W., Moeseneder, C., Dambacher, J.M., 2011. Defining dynamic pelagic habitats in oceanic waters off eastern Australia. Deep Sea Research Part II: Topical Studies in Oceanography, The East Australian Current – Its Eddies and Impacts 58, 734–745. https://doi.org/10.1016/j.dsr2.2010.10.006

Hobson, K.A., Welch, H.E., 1992. Determination of trophic relationships within a high Arctic marine food web using δ 13 C and δ 15 N analysis. Marine Ecology Progress Series 84, 9–18.

88 References

Holbrook, N.J., Bindoff, N.L., 1999. Seasonal Temperature Variability in the Upper Southwest Pacific Ocean. J. Phys. Oceanogr. 29, 366–381. https://doi.org/10.1175/1520- 0485(1999)029<0366:STVITU>2.0.CO;2

Holbrook, N.J., Goodwin, I.D., McGregor, S., Molina, E., Power, S.B., 2011. ENSO to multi-decadal time scale changes in East Australian Current transports and Fort Denison sea level: Oceanic Rossby waves as the connecting mechanism. Deep Sea Research Part II: Topical Studies in Oceanography, The East Australian Current – Its Eddies and Impacts 58, 547–558. https://doi.org/10.1016/j.dsr2.2010.06.007

Hughes, J.M., Stewart, J., Lyle, J.M., McAllister, J., Stocks, J.R., Suthers, I.M., 2013. Latitudinal, ontogenetic, and historical shifts in the diet of a carnivorous teleost, Arripis trutta, in a coastal pelagic ecosystem altered by climate change. Can. J. Fish. Aquat. Sci. 70, 1209–1230. https://doi.org/10.1139/cjfas-2013-0083

Hunt, B.P.V., Allain, V., Menkes, C., Lorrain, A., Graham, B., Rodier, M., Pagano, M., Carlotti, F., 2015. A coupled stable isotope-size spectrum approach to understanding pelagic food-web dynamics: A case study from the southwest sub-tropical Pacific. Deep Sea Research Part II: Topical Studies in Oceanography, Impacts of climate on marine top predators 113, 208–224. https://doi.org/10.1016/j.dsr2.2014.10.023

Hussey, N.E., MacNeil, M.A., McMeans, B.C., Olin, J.A., Dudley, S.F.J., Cliff, G., Wintner, S.P., Fennessy, S.T., Fisk, A.T., 2014. Rescaling the trophic structure of marine food webs. Ecology Letters 17, 239–250. https://doi.org/10.1111/ele.12226

Iken, K., Bluhm, B., Dunton, K., 2010. Benthic food-web structure under differing water mass properties in the southern Chukchi Sea. Deep Sea Research Part II: Topical Studies in Oceanography, Observations and Exploration of the Arctic’s Canada Basin and the Chukchi Sea: the Hidden Ocean and RUSALCA Expeditions 57, 71–85. https://doi.org/10.1016/j.dsr2.2009.08.007

Irigoien, X., Klevjer, T.A., Røstad, A., Martinez, U., Boyra, G., Acuña, J.L., Bode, A., Echevarria, F., Gonzalez-Gordillo, J.I., Hernandez-Leon, S., Agusti, S., Aksnes, D.L., Duarte, C.M., Kaartvedt, S., 2014. Large mesopelagic fishes biomass and trophic efficiency in the open ocean. Nat Commun 5, 1–10. https://doi.org/10.1038/ncomms4271

Jennings, S., Blanchard, J.L., 2004. Fish Abundance with No Fishing: Predictions Based on Macroecological Theory. Journal of Animal Ecology 73, 632–642.

Jennings, S., Collingridge, K., 2015. Predicting Consumer Biomass, Size-Structure, Production, Catch Potential, Responses to Fishing and Associated Uncertainties in the World’s Marine Ecosystems: e0133794. PLoS ONE 10. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1371/journal.pone.0133794

Jennings, S., Mackinson, S., 2003. Abundance–body mass relationships in size-structured food webs. Ecology Letters 6, 971–974. https://doi.org/10.1046/j.1461-0248.2003.00529.x

Jennings, S., Mélin, F., Blanchard, J.L., Forster, R.M., Dulvy, N.K., Wilson, R.W., 2008. Global-scale predictions of community and ecosystem properties from simple ecological theory. Proceedings of the Royal Society of London B: Biological Sciences 275, 1375–1383. https://doi.org/10.1098/rspb.2008.0192

89 References

Jennings, S., Pinnegar, J., Polunin, N.V., Boon, T., 2001. Weak cross‐species relationships between body size and trophic level belie powerful size‐based trophic structuring in fish communities. Journal of Animal Ecology 70, 934–944. https://doi.org/10.1046/j.0021-8790.2001.00552.x

Jennings, S., Pinnegar, J.K., Polunin, N.V.C., Warr, K.J., 2002a. Linking size-based and trophic analyses of benthic community structure. Marine Ecology Progress Series 226, 77–85.

Jennings, S., van der Molen, J., 2015. Trophic levels of marine consumers from nitrogen stable isotope analysis: estimation and uncertainty. ICES J Mar Sci 72, 2289–2300. https://doi.org/10.1093/icesjms/fsv120

Jennings, S., Warr, K.J., 2003a. Environmental correlates of large-scale spatial variation in the delta super(15)N of marine animals. Marine Biology 142, 1131–1140. http://dx.doi.org/10.1007/s00227-003-1020-0

Jennings, S., Warr, K.J., 2003b. Smaller Predator-Prey Body Size Ratios in Longer Food Chains. Proceedings: Biological Sciences 270, 1413–1417.

Jennings, S., Warr, K.J., Mackinson, S., 2002b. Use of size-based production and stable isotope analyses to predict trophic transfer efficiencies and predator-prey body mass ratios in food webs. Marine Ecology Progress Series 240, 11–20.

Jonsson, T., Ebenman, B., 1998. Effects of Predator–prey Body Size Ratios on the Stability of Food Chains. Journal of Theoretical Biology 193, 407–417. https://doi.org/10.1006/jtbi.1998.0708

Kaartvedt, S., Staby, A., Aksnes, D.L., 2012. Efficient trawl avoidance by mesopelagic fishes causes large underestimation of their biomass. Marine Ecology Progress Series 456, 1–6.

Karstensen, J., Schütte, F., Pietri, A., Krahmann, G., Fiedler, B., Grundle, D., Hauss, H., Körtzinger, A., Löscher, C.R., Testor, P., Vieira, N., Visbeck, M., 2017. Upwelling and isolation in oxygen- depleted anticyclonic modewater eddies and implications for nitrate cycling. Biogeosciences 14, 2167–2181. https://doi.org/10.5194/bg-14-2167-2017

Kas, L., 2018. From production to predation in the western Tasman Sea: the trophic ecology of size structured pelagic ecosystems (Honours Thesis). University of New South Wales, Sydney, Australia.

Keppler, L., Cravatte, S., Chaigneau, A., Pegliasco, C., Gourdeau, L., Singh, A., 2018. Observed Characteristics and Vertical Structure of Mesoscale Eddies in the Southwest Tropical Pacific. Journal of Geophysical Research: Oceans 123, 2731–2756. https://doi.org/10.1002/2017JC013712

Kerr, S.R., 1974. Theory of Size Distribution in Ecological Communities. J. Fish. Res. Bd. Can. 31, 1859– 1862. https://doi.org/10.1139/f74-241

Kerr, S.R., Dickie, L.M., 2001. The Biomass Spectrum: A Predator-Prey Theory of Aquatic Production. Columbia University Press.

Kimura, S., Kasai, A., Nakata, H., Sugimoto, T., Simpson, J.H., Cheok, J.V.S., 1997. Biological productivity of meso-scale eddies caused by frontal disturbances in the Kuroshio. ICES J Mar Sci 54, 179– 192. https://doi.org/10.1006/jmsc.1996.0209

90 References

Kloser, R.J., Ryan, T.E., Young, J.W., Lewis, M.E., 2009. Acoustic observations of micronekton fish on the scale of an ocean basin: potential and challenges. ICES J Mar Sci 66, 998–1006. https://doi.org/10.1093/icesjms/fsp077

Kozlov, A.N., 1995. A review of the trophic role of mesopelagic fish of the family Myctophidae in the Southern Ocean ecosystem. CCAMLR Science 2, 71–77.

Kwong, L.E., Henschke, N., Pakhomov, E.A., Everett, J.D., Suthers, I.M., 2020. Mesozooplankton and Micronekton Active Carbon Transport in Contrasting Eddies. Front. Mar. Sci. 6, 825. https://doi.org/10.3389/fmars.2019.00825

Laiolo, L., McInnes, A.S., Matear, R., Doblin, M.A., 2016. Key Drivers of Seasonal Plankton Dynamics in Cyclonic and Anticyclonic Eddies off East Australia. Frontiers in Marine Science; Lausanne. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.3389/fmars.2016.00155

Landrum, J.P., Altabet, M.A., Montoya, J.P., 2011. Basin-scale distributions of stable nitrogen isotopes in the subtropical North Atlantic Ocean: Contribution of diazotroph nitrogen to particulate organic matter and mesozooplankton. Deep Sea Research Part I: Oceanographic Research Papers 58, 615–625. https://doi.org/10.1016/j.dsr.2011.01.012

Landry, M.R., 1977. A review of important concepts in the trophic organization of pelagic ecosystems. Helgolander Wiss. Meeresunters 30, 8–17. https://doi.org/10.1007/BF02207821

Lara-Lopez, A., Hodgson-Johnston, I., Cahill, M., Mancini, S., Blain, P., Moltmann, T., 2019. From research to end-users, tracing the path of ocean observations in Australia. Mar. Freshwater Res. 70, 925–935. https://doi.org/10.1071/MF18066

LEWISON, R., HOBDAY, A.J., MAXWELL, S., HAZEN, E., HARTOG, J.R., DUNN, D.C., BRISCOE, D., FOSSETTE, S., O’KEEFE, C.E., BARNES, M., ABECASSIS, M., BOGRAD, S., BETHONEY, N.D., BAILEY, H., WILEY, D., ANDREWS, S., HAZEN, L., CROWDER, L.B., 2015. Dynamic Ocean Management: Identifying the Critical Ingredients of Dynamic Approaches to Ocean Resource Management. BioScience 65, 486–498.

Lindeman, R.L., 1942. The Trophic-Dynamic Aspect of Ecology. Ecology 23, 399–417. https://doi.org/10.2307/1930126

Lorrain, A., Graham, B.S., Popp, B.N., Allain, V., Olson, R.J., Hunt, B.P.V., Potier, M., Fry, B., Galván- Magaña, F., Menkes, C.E.R., Kaehler, S., Ménard, F., 2015. Nitrogen isotopic baselines and implications for estimating foraging habitat and trophic position of yellowfin tuna in the Indian and Pacific Oceans. Deep Sea Research Part II: Topical Studies in Oceanography, Impacts of climate on marine top predators 113, 188–198. https://doi.org/10.1016/j.dsr2.2014.02.003

Macdonald, H.S., Roughan, M., Baird, M.E., Wilkin, J., 2016. The formation of a cold-core eddy in the East Australian Current. Continental Shelf Research 114, 72–84. https://doi.org/10.1016/j.csr.2016.01.002

Malan, N., Archer, M., Roughan, M., Cetina‐Heredia, P., Hemming, M., Rocha, C., Schaeffer, A., Suthers, I., Queiroz, E., 2020. Eddy-Driven Cross-Shelf Transport in the East Australian Current Separation Zone. Journal of Geophysical Research: Oceans 125, e2019JC015613. https://doi.org/10.1029/2019JC015613

91 References

Matis, P.A., Figueira, W.F., Suthers, I.M., Humphries, J., Miskiewicz, A., Coleman, R.A., Kelaher, B.P., Taylor, M.D., 2014. Cyclonic entrainment? The ichthyoplankton attributes of three major water mass types generated by the separation of the East Australian Current. ICES J Mar Sci 71, 1696–1705. https://doi.org/10.1093/icesjms/fsu062

Maxwell, S.M., Hazen, E.L., Lewison, R.L., Dunn, D.C., Bailey, H., Bograd, S.J., Briscoe, D.K., Fossette, S., Hobday, A.J., Bennett, M., Benson, S., Caldwell, M.R., Costa, D.P., Dewar, H., Eguchi, T., Hazen, L., Kohin, S., Sippel, T., Crowder, L.B., 2015. Dynamic ocean management: Defining and conceptualizing real-time management of the ocean. Marine Policy 58, 42–50. https://doi.org/10.1016/j.marpol.2015.03.014

Mazumder, D., Johansen, M.P., Fry, B., Davis, E., 2018. Muscle and carapace tissue–diet isotope discrimination factors for the freshwater crayfish Cherax destructor. Marine and Freshwater Research 69, 56. https://doi.org/10.1071/MF16360

Mazumder, D., Saintilan, N., Williams, R.J., Szymczak, R., 2011. Trophic importance of a temperate intertidal wetland to resident and itinerant taxa: evidence from multiple stable isotope analyses. Marine and Freshwater Research 62, 11. https://doi.org/10.1071/MF10076

Mazumder, D., Williams, R.J., Wen, L., Saintilan, N., Walsh, C.T., 2016. Impoundment constraint of fish niche diversity in a temperate Australian river. Hydrobiologia 771, 195–206. https://doi.org/10.1007/s10750-015-2630-5

Mazumder, D.D., n.d. Application of Stable Isotopic techniques to wetlands conservation 8.

McCormack, S.A., Trebilco, R., Melbourne-Thomas, J., Blanchard, J.L., Fulton, E.A., Constable, A., 2019. Using stable isotope data to advance marine food web modelling. Rev Fish Biol Fisheries 29, 277–296. https://doi.org/10.1007/s11160-019-09552-4

Mehner, T., Lischke, B., Scharnweber, K., Attermeyer, K., Brothers, S., Gaedke, U., Hilt, S., Brucet, S., 2018. Empirical correspondence between trophic transfer efficiency in freshwater food webs and the slope of their size spectra. Ecology 99, 1463–1472. https://doi.org/10.1002/ecy.2347

Miller, T.W., Brodeur, R.D., Rau, G., Omori, K., 2010. Prey dominance shapes trophic structure of the northern California Current pelagic food web:: evidence from stable isotopes and diet analysis. Marine Ecology Progress Series 420, 15–26.

Minagawa, M., Wada, E., 1984. Stepwise enrichment of 15N along food chains: Further evidence and the relation between δ 15N and animal age. Geochimica et Cosmochimica Acta 48, 1135–1140. https://doi.org/10.1016/0016-7037(84)90204-7

Moore, S.K., Suthers, I.M., 2006. Evaluation and correction of subresolved particles by the optical plankton counter in three Australian estuaries with pristine to highly modified catchments. Journal of Geophysical Research: Oceans 111. https://doi.org/10.1029/2005JC002920

Morris, T., Letnic, M., 2017. Removal of an apex predator initiates a trophic cascade that extends from herbivores to vegetation and the soil nutrient pool. Proc. R. Soc. B 284, 20170111. https://doi.org/10.1098/rspb.2017.0111

92 References

Mullaney, T.J., Gillanders, B.M., Heagney, E.C., Suthers, I.M., 2014. Entrainment and advection of larval sardine, Sardinops sagax, by the East Australian Current and retention in the western Tasman Front. Fisheries Oceanography 23, 554–567. https://doi.org/10.1111/fog.12089

Mullaney, T.J., Miskiewicz, A.G., Baird, M.E., Burns, P.T.P., Suthers, I.M., 2011. Entrainment of larval fish assemblages from the inner shelf into the East Australian Current and into the western Tasman Front. Fisheries Oceanography 20, 434–447. https://doi.org/10.1111/j.1365- 2419.2011.00594.x

Mullaney, T.J., Suthers, I.M., 2013. Entrainment and retention of the coastal larval fish assemblage by a short‐lived, submesoscale, frontal eddy of the East Australian Current. Limnology and Oceanography 58, 1546–1556. https://doi.org/10.4319/lo.2013.58.5.1546

Murphy, K.J., Pecl, G.T., Richards, S.A., Semmens, J.M., Revill, A.T., Suthers, I.M., Everett, J.D., Trebilco, R., Blanchard, J.L., 2020. Functional traits explain trophic allometries of cephalopods. Journal of Animal Ecology 89, 2692–2703. https://doi.org/10.1111/1365-2656.13333

Nakazawa, T., Ushio, M., Kondoh, M., 2011. Scale Dependence of Predator–Prey Mass Ratio: Determinants and Applications, in: Belgrano, A. (Ed.), Advances in Ecological Research, The Role of Body Size in Multispecies Systems. Academic Press, pp. 269–302. https://doi.org/10.1016/B978-0-12-386475-8.00007-1

Nilsson, C.S., Cresswell, G.R., 1980. The formation and evolution of East Australian current warm-core eddies. Progress in Oceanography 9, 133–183. https://doi.org/10.1016/0079-6611(80)90008- 7

NSMC, N.M.S.C., 2015. National Marine Science Plan 2015-2025: Driving the development of our blue economy. 16.

Ohlsson, K.E.A., Wallmark, P.H., 1999. Novel calibration with correction for drift and non-linear response for continuous flow isotope ratio mass spectrometry applied to the determination of δ15N, total nitrogen, δ13C and total carbon in biological material†. Analyst 124, 571–577. https://doi.org/10.1039/A900855A

Ohshimo, S., Tanaka, H., Nishiuchi, K., Yasuda, T., 2016. Trophic positions and predator–prey mass ratio of the pelagic food web in the East China Sea and Sea of Japan. Mar. Freshwater Res. 67, 1692– 1699. https://doi.org/10.1071/MF15115

Oke, P.R., Pilo, G.S., Ridgway, K., Kiss, A., Rykova, T., 2019a. A search for the Tasman Front. Journal of Marine Systems 199, 103217. https://doi.org/10.1016/j.jmarsys.2019.103217

Oke, P.R., Roughan, M., Cetina-Heredia, P., Pilo, G.S., Ridgway, K.R., Rykova, T., Archer, M.R., Coleman, R.C., Kerry, C.G., Rocha, C., Schaeffer, A., Vitarelli, E., 2019b. Revisiting the circulation of the East Australian Current: Its path, separation, and eddy field. Progress in Oceanography 176, 102139. https://doi.org/10.1016/j.pocean.2019.102139

Olbers, D., Eden, C., Willebrand, J., 2012. Ocean Dynamics. Springer, Berlin, Heidelberg, GERMANY.

Olivar, M.P., Bode, A., López-Pérez, C., Hulley, P.A., Hernández-León, S., 2018. Trophic position of lanternfishes (Pisces: Myctophidae) of the tropical and equatorial Atlantic estimated using stable isotopes. ICES J Mar Sci. https://doi.org/10.1093/icesjms/fsx243

93 References

Oliver, E.C.J., O’Kane, T.J., Holbrook, N.J., 2015. Projected changes to Tasman Sea eddies in a future climate. Journal of Geophysical Research: Oceans 120, 7150–7165. https://doi.org/10.1002/2015JC010993

Ou, C., Montaña, C.G., Winemiller, K.O., 2017. Body size–trophic position relationships among fishes of the lower Mekong basin. Royal Society Open Science 4, 160645. https://doi.org/10.1098/rsos.160645

Pakhomov, E.A., Perissinotto, R., McQuaid, C.D., 1996. Prey composition and daily rations of myctophid fishes in the Southern Ocean. Marine Ecology Progress Series 134, 1–14.

Parrish, C.C., Pethybridge, H., Young, J.W., Nichols, P.D., 2015. Spatial variation in fatty acid trophic markers in albacore tuna from the southwestern Pacific Ocean—A potential ‘tropicalization’ signal. Deep Sea Research Part II: Topical Studies in Oceanography, Impacts of climate on marine top predators 113, 199–207. https://doi.org/10.1016/j.dsr2.2013.12.003

Parry, M., 2006. Feeding behavior of two ommastrephid squids Ommastrephes bartramii and Sthenoteuthis oualaniensis off Hawaii. Marine Ecology Progress Series 318, 229–235.

Pauly, D., Christensen, V., 1995. Primary production required to sustain global fisheries. Nature; London 374, 255. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1038/374255a0

Pauly, D., Christensen, V., Dalsgaard, J., Froese, R., Torres, F., 1998. Fishing Down Marine Food Webs. Science 279, 860–863.

Peterson, B.J., Fry, B., 1987. Stable Isotopes in Ecosystem Studies. Annual Review of Ecology and Systematics 18, 293–320.

Pethybridge, H.R., Parrish, C.C., Morrongiello, J., Young, J.W., Farley, J.H., Gunasekera, R.M., Nichols, P.D., 2015. Spatial Patterns and Temperature Predictions of Tuna Fatty Acids: Tracing Essential Nutrients and Changes in Primary Producers. PLOS ONE 10, e0131598. https://doi.org/10.1371/journal.pone.0131598

Pikitch, E.K., Santora, C., Babcock, E.A., Bakun, A., Bonfil, R., Conover, D.O., Dayton, P., Doukakis, P., Fluharty, D., Heneman, B., Houde, E.D., Link, J., Livingston, P.A., Mangel, M., McAllister, M.K., Pope, J., Sainsbury, K.J., 2004. Ecosystem-Based Fishery Management. Science 305, 346–347.

Piola, R.F., Moore, S.K., Suthers, I.M., 2006. Carbon and nitrogen stable isotope analysis of three types of oyster tissue in an impacted estuary. Estuarine, Coastal and Shelf Science 66, 255–266. https://doi.org/10.1016/j.ecss.2005.08.013

Polovina, J.J., Woodworth-Jefcoats, P.A., 2013. Fishery-Induced Changes in the Subtropical Pacific Pelagic Ecosystem Size Structure: Observations and Theory. e62341. PLoS ONE 8. http://dx.doi.org/10.1371/journal.pone.0062341

Post, D.M., 2002a. Using Stable Isotopes to Estimate Trophic Position: Models, Methods, and Assumptions. Ecology 83, 703–718. https://doi.org/10.2307/3071875

Post, D.M., 2002b. The long and short of food-chain length. Trends in Ecology & Evolution 17, 269– 277. https://doi.org/10.1016/S0169-5347(02)02455-2

94 References

Post, D.M., Layman, C.A., Arrington, D.A., Takimoto, G., Quattrochi, J., Montaña, C.G., 2007. Getting to the fat of the matter: models, methods and assumptions for dealing with lipids in stable isotope analyses. Oecologia; Heidelberg 152, 179–89. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1007/s00442-006-0630-x

Potapov, A.M., Brose, U., Scheu, S., Tiunov, A.V., 2019. Trophic Position of Consumers and Size Structure of Food Webs across Aquatic and Terrestrial Ecosystems. The American Naturalist 194, 823–839. https://doi.org/10.1086/705811

R Core Team, 2019. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.

Raitsos, D.E., Pradhan, Y., Lavender, S.J., Hoteit, I., McQuatters‐Gollop, A., Reid, P.C., Richardson, A.J., 2014. From silk to satellite: half a century of ocean colour anomalies in the Northeast Atlantic. Global Change Biology 20, 2117–2123. https://doi.org/10.1111/gcb.12457

Rau, G.H., Teyssie, J.-L., Rassoulzadegan, F., Fowler, S.W., 1990. 13C/12C and 15N/14N variations among size-fractionated marine particles: implications for their origin and trophic relationships. Marine Ecology Progress Series 59, 33–38.

Reum, J.C.P., Jennings, S., Hunsicker, M.E., 2015. Implications of scaled δ15N fractionation for community predator–prey body mass ratio estimates in size-structured food webs. Journal of Animal Ecology 84, 1618–1627. https://doi.org/10.1111/1365-2656.12405

Revill, A.T., Young, J.W., Lansdell, M., 2009. Stable isotopic evidence for trophic groupings and bio- regionalization of predators and their prey in oceanic waters off eastern Australia. Marine Biology 156, 1241–1253. http://dx.doi.org.wwwproxy1.library.unsw.edu.au/10.1007/s00227- 009-1166-5

Richardson, A.J., Schoeman, D.S., 2004. Climate Impact on Plankton Ecosystems in the Northeast Atlantic. Science (Washington) 305, 1609.

Roughan, M., Keating, S.R., Schaeffer, A., Cetina Heredia, P., Rocha, C., Griffin, D., Robertson, R., Suthers, I.M., 2017. A tale of two eddies: The biophysical characteristics of two contrasting cyclonic eddies in the East Australian Current System: Cyclonic Eddies in the EAC. Journal of Geophysical Research: Oceans 122, 2494–2518. https://doi.org/10.1002/2016JC012241

Sheldon, R.W., Kerr, S.R., 1972. The Population Density of Monsters in Loch Ness1. Limnology and Oceanography 17, 796–798. https://doi.org/10.4319/lo.1972.17.5.0796

Sheldon, R.W., Prakash, A., Sutcliffe, W.H., 1972. The Size Distribution of Particles in the Ocean. Limnology and Oceanography 17, 327–340. https://doi.org/10.4319/lo.1972.17.3.0327

Sheldon, R.W., Sutcliffe Jr., W.H., Paranjape, M.A., 1977. Structure of Pelagic Food Chain and Relationship Between Plankton and Fish Production. J. Fish. Res. Bd. Can. 34, 2344–2353. https://doi.org/10.1139/f77-314

Shin, Y.-J., Cury, P., 2004. Using an individual-based model of fish assemblages to study the response of size spectra to changes in fishing. Can. J. Fish. Aquat. Sci. 61, 414–431. https://doi.org/10.1139/f03-154

95 References

Shin, Y.-J., Rochet, M.-J., Jennings, S., Field, J.G., Gislason, H., 2005. Using size-based indicators to evaluate the ecosystem effects of fishing. ICES J Mar Sci 62, 384–396. https://doi.org/10.1016/j.icesjms.2005.01.004

Smith, A.D.M., Fulton, E.J., Hobday, A.J., Smith, D.C., Shoulder, P., 2007. Scientific tools to support the practical implementation of ecosystem-based fisheries management. ICES J Mar Sci 64, 633– 639. https://doi.org/10.1093/icesjms/fsm041

Stock, C.A., John, J.G., Rykaczewski, R.R., Asch, R.G., Cheung, W.W.L., Dunne, J.P., Friedland, K.D., Lam, V.W.Y., Sarmiento, J.L., Watson, R.A., 2017. Reconciling fisheries catch and ocean productivity. Proceedings of the National Academy of Sciences of the United States of America 114, E1441– E1449. https://doi.org/10.2307/26479335

Suthers, I.M., Young, J.W., Baird, M.E., Roughan, M., Everett, J.D., Brassington, G.B., Byrne, M., Condie, S.A., Hartog, J.R., Hassler, C.S., Hobday, A.J., Holbrook, N.J., Malcolm, H.A., Oke, P.R., Thompson, P.A., Ridgway, K., 2011. The strengthening East Australian Current, its eddies and biological effects — an introduction and overview. Deep Sea Research Part II: Topical Studies in Oceanography, The East Australian Current – Its Eddies and Impacts 58, 538–546. https://doi.org/10.1016/j.dsr2.2010.09.029

Sutton, T.T., 2013. Vertical ecology of the pelagic ocean: classical patterns and new perspectives. Journal of Fish Biology 83, 1508–1527. https://doi.org/10.1111/jfb.12263

Sutton, T.T., Hopkins, T.L., 1996. Trophic ecology of the stomiid (Pisces: Stomiidae) fish assemblage of the eastern Gulf of Mexico: Strategies, selectivity and impact of a top mesopelagic predator group. Mar. Biol. 127, 179–192. https://doi.org/10.1007/BF00942102

Takahashi, M., Watanabe, Y., Kinoshita, T., Watanabe, C., 2001. Growth of larval and early juvenile Japanese anchovy, Engraulis japonicus, in the Kuroshio-Oyashio transition region. Fisheries Oceanography 10, 235–247. https://doi.org/10.1046/j.1365-2419.2001.00160.x

Taylor, M.D., Mullaney, T.J., Suthers, I.M., 2010. Mesoscale distribution of larval Euphausia similis in various water masses of the East Australian Current. Deep Sea Research Part I: Oceanographic Research Papers 57, 1295–1303. https://doi.org/10.1016/j.dsr.2010.06.010

Tranter, D.J., Leech, G.S., Vaudrey, D.J., 1982. Biological significance of surface flooding in warm-core ocean eddies. Nature 297, 572–574. https://doi.org/10.1038/297572a0

Tranter, D.J., Parker, R.R., Cresswell, G.R., 1980. Are warm-core eddies unproductive? Nature 284, 540–542. https://doi.org/10.1038/284540a0

Trebilco, R., Baum, J.K., Salomon, A.K., Dulvy, N.K., 2013. Ecosystem ecology: size-based constraints on the pyramids of life. Trends in Ecology & Evolution 28, 423–431. https://doi.org/10.1016/j.tree.2013.03.008

Tsai, C.-H., Hsieh, C., Nakazawa, T., 2016. Predator–prey mass ratio revisited: does preference of relative prey body size depend on individual predator size? Functional Ecology 30, 1979–1987. https://doi.org/10.1111/1365-2435.12680

Vander Zanden, M.J., Rasmussen, J.B., 2001. Variation in δ15N and δ13C Trophic Fractionation: Implications for Aquatic Food Web Studies. Limnology and Oceanography 46, 2061–2066.

96 References

Vanderklift, M.A., Ponsard, S., 2003. Sources of Variation in Consumer-Diet δ 15N Enrichment: A Meta- Analysis. Oecologia 136, 169–182.

Wada, E., Hattori, A., 1976. Natural abundance of 15N in particulate organic matter in the North Pacific Ocean. Geochimica et Cosmochimica Acta 40, 249–251. https://doi.org/10.1016/0016- 7037(76)90183-6

Waite, A.M., Muhling, B.A., Holl, C.M., Beckley, L.E., Montoya, J.P., Strzelecki, J., Thompson, P.A., Pesant, S., 2007. Food web structure in two counter-rotating eddies based on δ15N and δ13C isotopic analyses. Deep Sea Research Part II: Topical Studies in Oceanography, The Leeuwin Current and its Eddies 54, 1055–1075. https://doi.org/10.1016/j.dsr2.2006.12.010

Waite, A.M., Raes, E., Beckley, L.E., Thompson, P.A., Griffin, D., Saunders, M., Säwström, C., O’Rorke, R., Wang, M., Landrum, J.P., Jeffs, A., 2019. Production and ecosystem structure in cold‐core vs. warm‐core eddies: Implications for the zooplankton isoscape and rock lobster larvae. Limnol Oceanogr 64, 2405–2423. https://doi.org/10.1002/lno.11192

Waite, A.M., Stemmann, L., Guidi, L., Calil, P.H.R., Hogg, A.M.C., Feng, M., Thompson, P.A., Picheral, M., Gorsky, G., 2016. The wineglass effect shapes particle export to the deep ocean in mesoscale eddies. Geophysical Research Letters 43, 9791–9800. https://doi.org/10.1002/2015GL066463

Wallis, J.R., Swadling, K.M., Everett, J.D., Suthers, I.M., Jones, H.J., Buchanan, P.J., Crawford, C.M., James, L.C., Johnson, R., Meiners, K.M., Virtue, P., Westwood, K., Kawaguchi, S., 2016. Zooplankton abundance and biomass size spectra in the East Antarctic sea-ice zone during the winter–spring transition. Deep Sea Research Part II: Topical Studies in Oceanography, East Antarctic sea-ice physics and ecosystem processes 131, 170–181. https://doi.org/10.1016/j.dsr2.2015.10.002

Wiebe, P.H., E.M. Hurlbert, E.J. Carpenter, A.E. Jahn, G.P. Knapp, S.H. Boyd, P.B. Ortner, J.L. Cox. 1976, Gulf stream cold core rings: large-scale interaction sites for open ocean plankton communities, Deep Sea Research and Oceanographic Abstracts 23, 695–710. https://doi.org/10.1016/S0011-7471(76)80015-0

Wiebe, P.H., Flierl, G.R., Davis, C.S., Barber, V., Boyd, S.H., 1985. Macrozooplankton biomass in Gulf Stream warm-core rings: Spatial distribution and temporal changes. Journal of Geophysical Research: Oceans 90, 8885–8901. https://doi.org/10.1029/JC090iC05p08885

White, Z., 2018. Zooplankton size structure off southeastern Australia; quantifying the missing trophic link for fisheries (Masters of Philosophy Thesis). University of New South Wales, Sydney, Australia.

Wilkin, J.L., Zhang, W.G., 2007. Modes of mesoscale sea surface height and temperature variability in the East Australian Current. Journal of Geophysical Research: Oceans 112. https://doi.org/10.1029/2006JC003590

Williams, A., Koslow, J.A., 1997. Species composition, biomass and vertical distribution of micronekton over the mid-slope region off southern Tasmania, Australia. Marine Biology 130, 259–276. https://doi.org/10.1007/s002270050246

97 References

Young, J.W., Bradford, R., Lamb, T.D., Clementson, L.A., Kloser, R., Galea, H., 2001. Yellowfin tuna (Thunnus albacares) aggregations along the shelf break off south-eastern Australia: links between inshore and offshore processes. Mar. Freshwater Res. 52, 463–474. https://doi.org/10.1071/mf99168

Young, J.W., David McKinnon, A., Ceccarelli, D., Brinkman, R., Bustamante, R.H., Cappo, M., Dichmont, C., Doherty, P., Furnas, M., Gledhill, D., Griffiths, S., Hutton, T., Ridgway, K., Smith, D., Skewes, T., Williams, A., Richardson, A.J., 2012. Workshop on the ecosystem and fisheries of the Coral Sea: an Australian perspective on research and management. Rev Fish Biol Fisheries 22, 827– 834. https://doi.org/10.1007/s11160-011-9251-5

Young, J.W., Hobday, A.J., Campbell, R.A., Kloser, R.J., Bonham, P.I., Clementson, L.A., Lansdell, M.J., 2011. The biological oceanography of the East Australian Current and surrounding waters in relation to tuna and billfish catches off eastern Australia. Deep Sea Research Part II: Topical Studies in Oceanography, The East Australian Current – Its Eddies and Impacts 58, 720–733. https://doi.org/10.1016/j.dsr2.2010.10.005

Young, J.W., Hunt, B.P.V., Cook, T.R., Llopiz, J.K., Hazen, E.L., Pethybridge, H.R., Ceccarelli, D., Lorrain, A., Olson, R.J., Allain, V., Menkes, C., Patterson, T., Nicol, S., Lehodey, P., Kloser, R.J., Arrizabalaga, H., Anela Choy, C., 2015. The trophodynamics of marine top predators: Current knowledge, recent advances and challenges. Deep Sea Research Part II: Topical Studies in Oceanography, Impacts of climate on marine top predators 113, 170–187. https://doi.org/10.1016/j.dsr2.2014.05.015

Young, J.W., Lansdell, M., Campbell, R., Cooper, S., Juanes, F., Guest, M., 2010. Feeding ecology and niche segregation in oceanic top predators off eastern Australia. Marine Biology 157, 2347– 2368. https://doi.org/10.1007/s00227-010-1500-y

98 Chapter 2 - Food web structure of contrasting mesoscale eddies

Chapter 2 - Appendix

Appendix 2A – Length Weight Relationships for fish species

Appendix 2A Table 1: Length-Weight relationships for the common fish species identified in the pelagic trawls in the CCE and WCE. Relationships were derived through linear relationship between wet weight (g) and standard length (SL; mm). All relationships were statistically significant (p < 0.01). Species a b n r2 SL Range (mm) Argyropelecus aculeatus 2.75E-05 3.073072 28 0.983582 17 - 67 Argyropelecus hemigymnus 0.001017 1.751714 9 0.696665 11.5 - 24.5 Chauliodus sloani 3.19E-07 3.387744 8 0.993036 82 - 258 Cyclothone sp 7.70E-04 1.382902 6 0.732588 20 - 37 Diaphus perspicillatus 3.78E-05 2.762968 12 0.966691 25.5 - 77.5 Malacosteus sp 3.81E-07 3.514266 6 0.988192 76 - 245 Myctophid sp 3.49E-06 3.294131 11 0.943978 32 - 96.5 Nanobrachium sp 4.88E-06 3.064491 13 0.975129 45 - 171 Polyipnus ruggeri 7.64E-05 2.706958 11 0.97191 18.5 - 49.5 Scopelopsis multipunctatis 7.19E-06 3.126831 35 0.988718 19 - 65 Sternoptyx diaphana 1.24E-05 3.441352 6 0.893855 21 - 31 Vinciguerria poweriae 2.52E-06 3.339867 6 0.663684 33 - 38

99 Chapter 2 - Appendix

Appendix 2B – List of samples and results of stable isotope analysis.

Appendix 2B Table 1: List of samples and results for stable isotope analysis of δ15N (‰) and δ13C (‰) within the CCE and WCE. Trophic level (TL) was calculated using two methods based on δ15N using Particulate Organic Matter (POM) as the primary producer (TL = 1). TLs is calculated using scaled trophicAppendix enrichment 2B Table (Hussey1: Continued et al., 2014), whereas TLc is calculated using the traditional TEF of 3.4 ‰ per trophic level.

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

F7 CCE 0-0.5g Cyclothone sp. Other 10.60 9.90 37.50 -19.82 3.54 2.77 2.29

F8 CCE 0-0.5g Cyclothone sp. Other 11.20 10.00 38.70 -19.50 3.46 2.80 2.32

F9 CCE 0-0.5g Cyclothone sp. Other 12.10 10.40 41.50 -19.50 3.43 2.92 2.43

T30 CCE 0-0.5g Sigmops elongatus Other 9.00 10.90 32.40 -19.26 3.60 3.07 2.57

F4 CCE 0-0.5g Macroramphosus scolopax Other 10.80 9.40 39.80 -19.97 3.69 2.63 2.16

F5 CCE 0-0.5g Macroramphosus scolopax Other 11.20 9.40 41.30 -19.87 3.69 2.63 2.16

D37 CCE 01-2g Diaphus brachycephalus Myctophidae 13.00 11.30 42.80 -19.10 3.29 3.18 2.68

D38 CCE 01-2g Diaphus brachycephalus Myctophidae 13.80 11.80 45.00 -18.90 3.26 3.33 2.84

D39 CCE 04-8g Diaphus brachycephalus Myctophidae 14.10 12.50 45.70 -19.20 3.24 3.54 3.06

D40 CCE 0-0.5g Diaphus sp Myctophidae 12.10 10.00 40.90 -20.20 3.38 2.80 2.32

M50 CCE 04-8g Lampadena sp. Myctophidae 12.90 10.60 42.80 -18.60 3.32 2.98 2.48

M51 CCE 01-2g Lampanyctus sp Myctophidae 11.50 10.60 37.60 -19.20 3.27 2.98 2.48

100 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

M52 CCE 01-2g Diaphus brachycephalus Myctophidae 13.50 11.40 43.50 -18.80 3.22 3.21 2.71

M53 CCE 02-4g Diaphus brachycephalus Myctophidae 13.00 11.80 42.60 -18.80 3.28 3.33 2.84

M54 CCE 04-8g Diaphus hudsoni Myctophidae 12.90 11.20 46.10 -19.38 3.57 3.15 2.65

M55 CCE 0-0.5g Diaphus hudsoni Myctophidae 12.30 11.00 40.10 -19.30 3.26 3.10 2.60

M56 CCE 0-0.5g Diaphus danae Myctophidae 11.90 10.30 39.70 -19.80 3.34 2.89 2.40

M80 CCE 01-2g Diaphus perspicillatus Myctophidae 13.26 11.90 45.56 -19.58 3.44 3.36 2.87

M81 CCE 02-4g Diaphus perspicillatus Myctophidae 13.20 10.36 47.71 -18.93 3.61 2.91 2.42

M62 CCE 04-8g Myctophid sp. Myctophidae 14.35 10.95 49.12 -19.41 3.42 3.08 2.58

M63 CCE 04-8g Myctophid sp. Myctophidae 14.43 11.05 48.04 -19.18 3.33 3.11 2.61

M64 CCE 02-4g Myctophid sp. Myctophidae 13.22 10.94 46.19 -19.83 3.49 3.08 2.58

M85 CCE 0.5-1g Myctophid sp. Myctophidae 13.22 10.54 44.11 -19.29 3.34 2.96 2.47

M66 CCE 0.5-1g Myctophid sp. Myctophidae 12.72 10.86 43.31 -19.29 3.40 3.05 2.55

M67 CCE 04-8g Myctophid sp. Myctophidae 14.34 11.01 47.87 -19.09 3.34 3.10 2.60

M68 CCE 02-4g Myctophid sp. Myctophidae 13.10 11.64 47.11 -19.53 3.60 3.28 2.79

101 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

M69 CCE 0-0.5g Myctophid sp. Myctophidae 12.06 11.60 41.76 -19.33 3.46 3.27 2.78

M70 CCE 04-8g Myctophid sp. Myctophidae 13.30 12.23 43.76 -19.36 3.29 3.46 2.97

M71 CCE 04-8g Myctophid sp. Myctophidae 14.03 11.91 47.71 -19.14 3.40 3.36 2.87

N32 CCE 08-16g Nanobrachium atrum Myctophidae 12.00 11.00 38.70 -19.40 3.23 3.10 2.60

S04 CCE 02-4g Scopelopsis multipunctatus Myctophidae 13.80 10.50 45.80 -19.60 3.32 2.95 2.45

S05 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.70 9.70 40.20 -20.30 3.44 2.71 2.24

S05 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.50 9.60 42.30 -20.10 3.38 2.68 2.21

S06 CCE 02-4g Scopelopsis multipunctatus Myctophidae 14.20 11.30 45.60 -19.30 3.21 3.18 2.68

S07 CCE 02-4g Scopelopsis multipunctatus Myctophidae 14.10 11.50 46.10 -19.50 3.27 3.24 2.74

S08 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.10 12.30 43.10 -19.19 3.56 3.48 3.00

S09 CCE 02-4g Scopelopsis multipunctatus Myctophidae 11.80 11.40 40.00 -19.30 3.39 3.21 2.71

S10 CCE 02-4g Scopelopsis multipunctatus Myctophidae 12.30 10.90 40.20 -19.70 3.27 3.07 2.57

S17 CCE 02-4g Scopelopsis multipunctatus Myctophidae 13.30 12.70 44.90 -19.50 3.38 3.60 3.13

S18 CCE 02-4g Scopelopsis multipunctatus Myctophidae 13.60 11.40 45.70 -19.60 3.36 3.21 2.71

102 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

S32 CCE 01-2g Scopelopsis multipunctatus Myctophidae 13.70 11.30 44.70 -19.20 3.26 3.18 2.68

S34 CCE 02-4g Scopelopsis multipunctatus Myctophidae 14.10 11.40 47.20 -19.80 3.35 3.21 2.71

S35 CCE 02-4g Scopelopsis multipunctatus Myctophidae 13.70 11.70 46.10 -19.50 3.36 3.30 2.81

S37 CCE 02-4g Scopelopsis multipunctatus Myctophidae 13.50 10.90 45.60 -19.60 3.38 3.07 2.57

S38 CCE 02-4g Scopelopsis multipunctatus Myctophidae 15.80 11.00 52.60 -19.60 3.33 3.10 2.60

S39 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.90 10.50 41.40 -19.60 3.48 2.95 2.45

S40 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.90 10.60 41.60 -19.90 3.50 2.98 2.48

S42 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.40 10.60 40.70 -19.99 3.57 2.98 2.48

S43 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.50 10.20 40.00 -20.00 3.48 2.86 2.37

S44 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.40 10.20 40.10 -20.04 3.52 2.86 2.37

S45 CCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.20 12.30 38.90 -18.90 3.47 3.48 3.00

S46 CCE 01-2g Scopelopsis multipunctatus Myctophidae 10.80 12.80 42.60 -19.02 3.94 3.63 3.17

F6 CCE 0-0.5g Psenes sp Other 11.10 8.50 39.80 -19.87 3.59 2.36 1.94

F10 CCE 04-8g Stemonosudis sp. Other 13.90 11.51 45.92 -19.16 3.30 3.25 2.75

103 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

POM1 CCE NA Bulk Sample POM 0.00 4.70 0.00 -20.59 6.80 1.24 1.15

POM2 CCE NA Bulk Sample POM 0.00 4.00 0.00 -20.99 6.90 1.04 1.02

POM3 CCE NA Bulk Sample POM 0.00 2.60 0.00 -20.50 8.30 0.63 0.78

POM4 CCE NA Bulk Sample POM 0.00 4.20 0.00 -21.09 7.40 1.10 1.06

F3 CCE 0.5-1g Ichthyococcus australis Other 10.70 11.80 42.40 -19.10 3.96 3.33 2.84

V18 CCE 0-0.5g Vinciguerria poweriae Other 11.50 11.30 39.90 -19.40 3.47 3.18 2.68

V19 CCE 0.5-1g Vinciguerria poweriae Other 11.50 11.80 39.90 -19.20 3.47 3.33 2.84

V20 CCE 0-0.5g Vinciguerria poweriae Other 11.50 11.80 39.80 -19.30 3.46 3.33 2.84

V21 CCE 0.5-1g Vinciguerria poweriae Other 13.21 11.27 45.33 -19.48 3.43 3.17 2.67

V22 CCE 0.5-1g Vinciguerria poweriae Other 13.35 10.91 45.63 -19.52 3.42 3.07 2.57

A38 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.30 11.10 40.50 -19.10 3.29 3.13 2.62

A39 CCE 02-4g Argyropelecus aculeatus Sternoptychidae 12.20 11.40 40.60 -18.90 3.33 3.21 2.71

A40 CCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.50 11.30 38.90 -19.10 3.38 3.18 2.68

A41 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 12.90 11.20 43.60 -19.10 3.38 3.15 2.65

104 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

A42 CCE 02-4g Argyropelecus aculeatus Sternoptychidae 13.30 11.40 43.70 -18.90 3.29 3.21 2.71

A43 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 11.20 11.70 38.10 -19.00 3.40 3.30 2.81

A44 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 11.30 10.70 39.10 -20.30 3.46 3.01 2.51

A45 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 11.10 11.30 38.10 -19.70 3.43 3.18 2.68

A46 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.50 11.53 40.64 -18.96 3.25 3.25 2.75

A47 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 12.56 11.38 41.74 -19.16 3.32 3.21 2.71

A49 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 11.34 11.93 40.08 -18.78 3.53 3.37 2.88

A49 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.34 11.94 40.08 -18.95 3.25 3.37 2.88

A50 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 11.54 11.70 37.55 -19.06 3.25 3.30 2.81

A51 CCE 04-8g Argyropelecus aculeatus Sternoptychidae 12.30 11.60 39.40 -19.00 3.20 3.27 2.77

A52 CCE 04-8g Argyropelecus aculeatus Sternoptychidae 12.20 11.50 39.40 -19.00 3.23 3.24 2.74

A53 CCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.40 11.50 37.60 -19.10 3.30 3.24 2.74

A54 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 10.80 11.20 35.30 -19.10 3.27 3.15 2.65

A55 CCE 02-4g Argyropelecus aculeatus Sternoptychidae 12.40 11.60 40.20 -18.90 3.24 3.27 2.77

105 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

A56 CCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.10 11.50 39.10 -19.10 3.23 3.24 2.74

A57 CCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.90 11.40 39.60 -19.10 3.33 3.21 2.71

A58 CCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.10 10.90 37.70 -19.20 3.40 3.07 2.57

A7 CCE 04-8g Argyropelecus aculeatus Sternoptychidae 13.30 11.20 42.90 -19.10 3.23 3.15 2.65

A8 CCE 02-4g Argyropelecus aculeatus Sternoptychidae 12.90 11.20 41.50 -19.30 3.22 3.15 2.65

A9 CCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 12.00 11.10 39.10 -19.30 3.26 3.13 2.62

T07 CCE 01-2g Malacosteus australis Stomiidae 12.10 10.70 38.50 -19.00 3.18 3.01 2.51

T08 CCE 08-16g Chauliodus sloani Stomiidae 12.70 11.00 41.60 -19.10 3.28 3.10 2.60

T11 CCE 0.5-1g Chauliodus sloani Stomiidae 11.00 10.30 38.20 -19.40 3.47 2.89 2.40

T12 CCE 04-8g Malacosteus australis Stomiidae 11.00 12.40 37.10 -18.80 3.37 3.51 3.03

T14 CCE 02-4g Chauliodus sloani Stomiidae 11.50 11.70 39.30 -19.20 3.42 3.30 2.81

T15 CCE 0.5-1g Chauliodus sloani Stomiidae 11.50 10.60 39.30 -18.90 3.42 2.98 2.48

T16 CCE 0.5-1g Chauliodus sloani Stomiidae 11.40 10.50 39.70 -19.30 3.48 2.95 2.45

T17 CCE 0.5-1g Chauliodus sloani Stomiidae 11.20 12.30 39.50 -18.83 3.53 3.48 3.00

106 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

T19 CCE 02-4g Chauliodus sloani Stomiidae 11.60 11.70 40.30 -19.20 3.47 3.30 2.81

T27 CCE 0-0.5g Leptostomias sp. Stomiidae 8.70 8.80 31.70 -19.01 3.64 2.45 2.01

T27 CCE 0-0.5g Leptostomias sp. Stomiidae 9.10 8.90 31.10 -19.30 3.42 2.48 2.04

T28 CCE 01-2g Chauliodus sloani Stomiidae 10.40 11.00 36.80 -18.92 3.54 3.10 2.60

T29 CCE 0.5-1g Chauliodus sloani Stomiidae 10.90 10.70 37.60 -19.40 3.45 3.01 2.51

T31 CCE 01-2g Malacosteus australis Stomiidae 11.10 10.90 37.90 -19.10 3.41 3.07 2.57

T32 CCE 0.5-1g Chauliodus sloani Stomiidae 11.30 10.90 38.40 -19.30 3.40 3.07 2.57

T34 CCE 02-4g Chauliodus sloani Stomiidae 11.82 10.76 38.93 -19.48 3.29 3.02 2.53

Z01 CCE 0.000001-0.000008g Bulk Sample Zooplankton 5.40 6.80 25.10 -19.32 4.65 1.86 1.56

Z02 CCE 0.000008-0.000065g Bulk Sample Zooplankton 8.60 7.20 37.10 -20.25 4.31 1.98 1.65

Z03 CCE 0.000065-0.000524g Bulk Sample Zooplankton 1.90 9.00 11.10 -18.84 5.84 2.51 2.06

Z03 CCE 0.000065-0.000524g Bulk Sample Zooplankton 2.00 9.00 11.10 -19.13 5.55 2.51 2.06

Z04 CCE 0.000524-0.004189g Bulk Sample Zooplankton 5.20 9.20 27.20 -19.84 5.23 2.57 2.11

Z05 CCE 0.004189-0.03351g Bulk Sample Zooplankton 5.50 7.70 26.50 -19.65 4.82 2.13 1.76

107 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

T23 WCE 0-0.5g Sigmops elongatus Other 10.80 10.10 35.40 -19.20 3.28 2.74 2.29

T24 WCE 0-0.5g Sigmops elongatus Other 10.30 10.10 37.10 -18.85 3.60 2.74 2.29

T36 WCE 02-4g Sigmops elongatus Other 12.05 9.95 39.87 -18.92 3.31 2.69 2.25

M12 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.20 8.50 39.20 -20.36 3.50 2.26 1.88

M13 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.50 9.30 39.40 -19.60 3.43 2.50 2.08

M14 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.20 8.70 39.10 -19.70 3.49 2.32 1.93

M15 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.10 9.10 40.80 -20.20 3.37 2.44 2.03

M16 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.10 8.00 39.40 -19.90 3.26 2.12 1.77

M17 WCE 0.5-1g Ceratoscopelus warmingii Myctophidae 11.90 9.40 40.20 -19.50 3.38 2.53 2.10

M18 WCE 0.5-1g Ceratoscopelus warmingii Myctophidae 12.60 10.90 40.60 -18.50 3.22 2.97 2.51

M19 WCE 0.5-1g Ceratoscopelus warmingii Myctophidae 12.30 9.60 40.80 -19.10 3.32 2.59 2.15

M20 WCE 01-2g Ceratoscopelus warmingii Myctophidae 11.50 9.50 39.80 -19.60 3.46 2.56 2.13

M21 WCE 01-2g Ceratoscopelus warmingii Myctophidae 12.20 9.70 43.80 -19.27 3.59 2.62 2.18

M22 WCE 01-2g Ceratoscopelus warmingii Myctophidae 12.80 9.50 42.30 -19.30 3.30 2.56 2.13

108 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

M23 WCE 01-2g Ceratoscopelus warmingii Myctophidae 12.00 9.50 43.60 -19.52 3.63 2.56 2.13

M24 WCE 01-2g Ceratoscopelus warmingii Myctophidae 12.50 9.60 42.30 -19.30 3.38 2.59 2.15

M25 WCE 08-16g Myctophum phengodes Myctophidae 14.10 11.50 45.60 -18.60 3.23 3.15 2.69

M26 WCE 08-16g Myctophum phengodes Myctophidae 14.00 11.00 46.20 -19.20 3.30 3.00 2.54

M27 WCE 02-4g Hygophum hygomii Myctophidae 13.50 11.60 45.00 -18.90 3.33 3.18 2.72

M28 WCE 02-4g Hygophum hygomii Myctophidae 12.80 10.20 44.10 -19.20 3.45 2.76 2.31

M29 WCE 02-4g Hygophum hygomii Myctophidae 12.80 11.50 46.00 -18.86 3.59 3.15 2.69

M30 WCE 02-4g Hygophum hygomii Myctophidae 11.70 10.30 41.00 -19.25 3.50 2.79 2.34

M31 WCE 02-4g Hygophum hygomii Myctophidae 12.30 10.90 43.20 -19.04 3.51 2.97 2.51

M32 WCE 02-4g Hygophum hygomii Myctophidae 13.10 11.80 45.80 -19.20 3.50 3.24 2.78

M33 WCE 02-4g Hygophum hygomii Myctophidae 13.00 12.10 45.20 -19.10 3.48 3.32 2.87

M34 WCE 02-4g Hygophum hygomii Myctophidae 13.10 11.90 44.70 -19.10 3.41 3.26 2.81

M35 WCE 02-4g Hygophum hygomii Myctophidae 13.20 11.60 47.20 -18.88 3.58 3.18 2.72

M36 WCE 02-4g Hygophum hygomii Myctophidae 13.10 12.00 45.80 -19.20 3.50 3.29 2.84

109 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

M37 WCE 02-4g Hygophum hygomii Myctophidae 13.00 11.00 44.40 -18.70 3.42 3.00 2.54

M38 WCE 02-4g Hygophum hygomii Myctophidae 13.10 11.70 44.50 -19.00 3.40 3.21 2.75

M38 WCE 02-4g Hygophum hygomii Myctophidae 13.20 11.40 43.70 -18.90 3.31 3.12 2.66

M39 WCE 02-4g Hygophum hygomii Myctophidae 13.10 10.50 49.50 -19.28 3.78 2.85 2.40

M40 WCE 02-4g Hygophum hygomii Myctophidae 12.00 10.90 41.70 -19.40 3.48 2.97 2.51

M41 WCE 02-4g Hygophum hygomii Myctophidae 13.10 11.50 48.30 -19.17 3.69 3.15 2.69

M43 WCE 02-4g Diaphus perspicillatus Myctophidae 12.70 11.60 46.20 -19.12 3.64 3.18 2.72

M44 WCE 02-4g Diaphus perspicillatus Myctophidae 11.30 11.10 47.70 -19.94 4.22 3.03 2.57

M45 WCE 02-4g Diaphus perspicillatus Myctophidae 12.10 11.20 44.00 -19.62 3.64 3.06 2.60

M46 WCE 02-4g Diaphus perspicillatus Myctophidae 12.50 11.00 45.40 -18.92 3.63 3.00 2.54

M47 WCE 02-4g Ceratoscopelus warmingii Myctophidae 12.40 9.80 44.80 -19.34 3.61 2.65 2.21

M48 WCE 02-4g Notoscopelus sp Myctophidae 13.80 11.40 44.70 -18.90 3.24 3.12 2.66

M49 WCE 02-4g Notoscopelus sp Myctophidae 13.70 11.70 44.20 -18.80 3.23 3.21 2.75

M57 WCE 0-0.5g Diaphus perspicillatus Myctophidae 13.50 11.40 45.00 -19.20 3.33 3.12 2.66

110 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

M58 WCE 02-4g Hygophum hygomii Myctophidae 12.40 12.10 42.10 -19.30 3.40 3.32 2.87

M59 WCE 02-4g Lobianchia doefleni Myctophidae 11.80 10.10 40.40 -19.20 3.42 2.74 2.29

M60 WCE 01-2g Lobianchia doefleni Myctophidae 12.00 9.70 40.50 -19.30 3.38 2.62 2.18

M61 WCE 01-2g Lobianchia doefleni Myctophidae 12.30 9.80 41.20 -19.30 3.35 2.65 2.21

M82 WCE 01-2g Lobianchia doefleni Myctophidae 11.80 9.90 40.80 -19.30 3.46 2.68 2.23

M83 WCE 0.5-1g Hygophum hygomii Myctophidae 12.10 10.10 40.60 -19.20 3.36 2.74 2.29

M84 WCE 0.5-1g Lobianchia doefleni Myctophidae 12.40 9.70 41.60 -19.80 3.35 2.62 2.18

M65 WCE 0.5-1g Lobianchia doefleni Myctophidae 12.40 9.80 41.80 -19.20 3.37 2.65 2.21

M72 WCE 0.5-1g Myctophid sp. Myctophidae 12.87 10.11 45.29 -19.71 3.52 2.74 2.29

M73 WCE 0.5-1g Myctophid sp. Myctophidae 13.29 10.41 46.66 -19.12 3.51 2.83 2.37

M74 WCE 0.5-1g Myctophid sp. Myctophidae 13.12 9.89 44.98 -19.35 3.43 2.67 2.23

M75 WCE 0.5-1g Myctophid sp. Myctophidae 12.80 11.11 44.96 -19.01 3.51 3.03 2.57

S20 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.00 9.50 39.20 -19.50 3.27 2.56 2.13

S21 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.10 9.30 40.50 -19.60 3.35 2.50 2.08

111 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

S22 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.40 9.20 39.50 -19.50 3.46 2.47 2.05

S23 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.20 9.30 38.70 -19.70 3.46 2.50 2.08

S24 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.20 9.50 38.90 -19.60 3.47 2.56 2.13

S25 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.00 9.40 40.60 -19.40 3.38 2.53 2.10

S26 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 11.10 9.00 38.80 -20.30 3.50 2.41 2.00

S27 WCE 0-0.5g Scopelopsis multipunctatus Myctophidae 12.00 9.30 40.60 -19.40 3.38 2.50 2.08

POM5 WCE NA Bulk Sample POM 0.00 4.90 0.00 -21.09 7.10 1.21 1.13

POM6 WCE NA Bulk Sample POM 0.00 2.70 0.00 -20.80 7.80 0.56 0.74

POM7 WCE NA Bulk Sample POM 0.00 3.00 0.00 -21.60 7.80 0.65 0.79

POM8 WCE NA Bulk Sample POM 0.00 6.20 0.00 -21.78 6.40 1.59 1.38

V07 WCE 0.5-1g Vinciguerria poweriae Other 11.40 10.60 40.10 -19.04 3.52 2.88 2.42

V08 WCE 0.5-1g Vinciguerria poweriae Other 11.80 10.20 41.20 -19.20 3.49 2.76 2.31

V09 WCE 0.5-1g Vinciguerria poweriae Other 11.20 10.30 38.90 -19.30 3.47 2.79 2.34

V11 WCE 0-0.5g Vinciguerria poweriae Other 11.00 10.00 39.30 -19.28 3.57 2.71 2.26

112 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

V12 WCE 0.5-1g Vinciguerria poweriae Other 11.40 10.40 39.80 -19.30 3.49 2.82 2.37

V13 WCE 0-0.5g Vinciguerria poweriae Other 8.80 10.50 30.90 -18.94 3.51 2.85 2.40

V14 WCE 0-0.5g Vinciguerria poweriae Other 10.90 10.30 38.70 -19.01 3.55 2.79 2.34

V14 WCE 0-0.5g Vinciguerria poweriae Other 11.30 10.20 38.10 -19.20 3.37 2.76 2.31

V16 WCE 0-0.5g Vinciguerria poweriae Other 11.30 9.90 40.20 -19.10 3.56 2.68 2.23

V17 WCE 0.5-1g Vinciguerria poweriae Other 11.30 10.50 39.60 -18.85 3.50 2.85 2.40

A10 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.70 9.50 37.70 -18.90 3.22 2.56 2.13

A11 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.10 10.00 37.90 -19.10 3.41 2.71 2.26

A12 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.40 10.10 36.10 -19.30 3.47 2.74 2.29

A13 WCE 02-4g Argyropelecus aculeatus Sternoptychidae 12.80 10.70 41.40 -18.60 3.23 2.91 2.45

A14 WCE 08-16g Argyropelecus aculeatus Sternoptychidae 13.60 12.20 43.50 -18.80 3.20 3.35 2.91

A15 WCE 08-16g Argyropelecus aculeatus Sternoptychidae 13.60 11.40 43.70 -19.00 3.21 3.12 2.66

A17 WCE 04-8g Argyropelecus aculeatus Sternoptychidae 13.40 11.00 43.50 -18.50 3.25 3.00 2.54

A19 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.30 10.10 35.80 -19.00 3.48 2.74 2.29

113 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

A20 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.70 10.10 36.90 -19.00 3.45 2.74 2.29

A21 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.50 10.40 38.40 -18.80 3.34 2.82 2.37

A22 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.50 9.90 36.50 -19.20 3.48 2.68 2.23

A23 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 9.20 10.30 32.30 -18.94 3.51 2.79 2.34

A24 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.50 10.90 36.10 -19.20 3.44 2.97 2.51

A25 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.70 9.90 37.40 -19.10 3.50 2.68 2.23

A26 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.40 10.10 35.90 -19.00 3.45 2.74 2.29

A27 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 10.30 10.10 35.70 -19.00 3.47 2.74 2.29

A28 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 12.20 10.00 40.90 -19.00 3.35 2.71 2.26

A29 WCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 12.70 10.50 42.40 -18.70 3.34 2.85 2.40

A30 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 11.50 9.80 38.60 -19.20 3.36 2.65 2.21

A31 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 12.20 10.40 41.30 -18.90 3.39 2.82 2.37

A32 WCE 0-0.5g Argyropelecus aculeatus Sternoptychidae 12.10 9.90 40.90 -19.00 3.38 2.68 2.23

A33 WCE 0-0.5g Argyropelecus hemigymnus Sternoptychidae 12.30 11.20 41.60 -18.70 3.38 3.06 2.60

114 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

A34 WCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.20 10.60 40.40 -18.60 3.31 2.88 2.42

A34 WCE 01-2g Argyropelecus aculeatus Sternoptychidae 11.80 10.70 38.50 -18.60 3.26 2.91 2.45

A35 WCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.40 10.30 41.60 -18.90 3.35 2.79 2.34

A36 WCE 01-2g Argyropelecus aculeatus Sternoptychidae 12.00 10.60 40.30 -18.60 3.36 2.88 2.42

A37 WCE 0.5-1g Argyropelecus aculeatus Sternoptychidae 11.80 10.40 39.90 -18.70 3.38 2.82 2.37

T09 WCE 0-0.5g Chauliodus sloani Stomiidae 10.30 10.90 35.00 -19.00 3.40 2.97 2.51

T10 WCE 0.5-1g Eustomias sp. Stomiidae 10.50 9.90 35.70 -18.50 3.40 2.68 2.23

T10 WCE 0.5-1g Eustomias sp. Stomiidae 10.80 10.00 34.90 -18.50 3.23 2.71 2.26

T21 WCE 04-8g Chauliodus sloani Stomiidae 12.60 11.30 41.80 -19.10 3.32 3.09 2.63

T22 WCE 08-16g Melanostomiinae Stomiidae 11.70 12.10 41.00 -18.95 3.50 3.32 2.87

T25 WCE 04-8g Malacosteus australis Stomiidae 12.20 11.30 39.70 -19.60 3.25 3.09 2.63

T26 WCE 08-16g Idiacanthus atlanticus Stomiidae 10.50 14.70 36.50 -17.70 3.48 4.09 3.85

T35 WCE 0-0.5g Chauliodus sloani Stomiidae 10.95 10.15 37.53 -19.41 3.43 2.75 2.30

Z06 WCE 0.000001-0.000008g Bulk Sample Zooplankton 7.20 5.90 32.10 -20.21 4.46 1.50 1.32

115 Chapter 2 - Appendix

Appendix 2B Table 1: Continued

ID Eddy WC Species Group % N δ15N (‰) % C δ13C (‰) C:N TLc TLs

Z07 WCE 0.000008-0.000065g Bulk Sample Zooplankton 8.90 6.80 37.80 -20.72 4.25 1.76 1.50

Z08 WCE 0.000065-0.000524g Bulk Sample Zooplankton 8.60 7.60 33.60 -19.55 3.91 2.00 1.68

Z08 WCE 0.000065-0.000524g Bulk Sample Zooplankton 8.00 7.60 31.70 -19.10 3.96 2.00 1.68

Z09 WCE 0.000524-0.004189g Bulk Sample Zooplankton 5.20 7.60 22.80 -20.48 4.38 2.00 1.68

Z10 WCE 0.004189-0.03351g Bulk Sample Zooplankton 5.60 7.80 26.20 -19.79 4.68 2.06 1.72

Z10 WCE 0.004189-0.03351g Bulk Sample Zooplankton 5.60 7.80 22.50 -20.24 4.02 2.06 1.72

116 Chapter 2 - Appendix

Appendix 2C – Trophic level comparisons (TLs vs TLc)

Appendix 2C Figure 1: Trophic level – Body mass relationships for fish and zooplankton taxa in the WCE (Red) and the CCE (Blue). Mean trophic levels are estimated for each size class using the scaled TL approach (TLs; Filled circles, solid lines) and the constant TEF of 3.4 ‰ (TLc; Open circles, dashed lines). (a) Myctophidae, (b) Stomiidae, (c) ‘Other’, (d) Sternoptychidae, (e) Zooplankton.

Appendix 2C Table 1: Ecosystem metrics derived for the CCE and WCE using scaled (TLs) and constant TEF of 3.4 ‰ (TLc). Predator-Prey Food Chain Transfer Maximum Eddy Mass Ratio Length Efficiency Trophic Level

TLs TLc TLs TLc TLs TLc TLs TLc

CCE 43,042 10,319 2.17 2.63 0.04 0.06 3.17 3.63

WCE 5,698 1,977 2.85 3.09 0.07 0.10 3.85 4.09

117 Chapter 2 - Appendix

Appendix 2C Figure 2: Relationship between body size (g) and mean trophic level (±SD) of the mesopelagic communities sampled within the CCE and WCE. Trophic levels were calculated using both the scaled fractionation approach (Filled circles, solid line; Hussey et al., 2014), and a constant trophic enrichment factor (TEF) of 3.4‰ per trophic level (Empty circles, dashed line; Post, 2002).

118 Chapter 3 – Appendix

Chapter 3 - Appendix

Appendix 3A – Trophic level comparisons (TLs vs TLc)

Appendix 3A Table 1: Comparison of ecosystem metrics from the four eddies using both scaled enrichment method (TLs; Hussey et al., 2014) and a constant trophic enrichment factor (TEF) of 3.4 ‰ (TLc; Post, 2002). Predator-Prey Food Chain Transfer Maximum Eddy Mass Ratio Length Efficiency Trophic Level

TLs TLc TLs TLc TLs TLc TLs TLc

NCC 43,042 10,319 2.17 2.63 0.041 0.063 3.17 3.63

NWC 5,698 1,977 2.85 3.09 0.075 0.103 3.85 4.09

SCC 15,994 2,528 2.22 2.71 0.055 0.095 3.22 3.71

SWC 1,825 334 2.91 3.62 0.105 0.175 3.91 4.62

Appendix3A Figure 1: Relationship between body size (g) and mean trophic level (±SD) of the mesopelagic communities sampled within all four eddies. Trophic levels were calculated using both the scaled fractionation approach (Filled circles, solid line; Hussey et al., 2014), and a constant trophic enrichment factor (TEF) of 3.4‰ per trophic level (Empty circles, dashed line; Post, 2002).

119 Chapter 3 – Appendix

Appendix 3B – List of samples and results of stable isotope analysis

Appendix 3C Table 1: List of samples and results for stable isotope analysis of δ15N (‰) and δ13C (‰) within the four eddies (NCC, NWC, SCC, SWC). Trophic level (TL) was calculated using two methods based on δ15N using Particulate Organic Matter (POM) as the primary producer (TL = 1). TLs is calculated using scaled trophic enrichmentAppendix 3C (Hussey Table 1: et Continued al., 2014), whereas TLc is calculated using the traditional TEF of 3.4 ‰ per trophic level. ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs F7 NCC 0-0.5g 0.5 Gonostomatidae cyclothone sp. Other 10.6 9.9 37.5 -19.8 3.5 2.8 2.3 F8 NCC 0-0.5g 0.5 Gonostomatidae cyclothone sp. Other 11.2 10.0 38.7 -19.5 3.5 2.8 2.3 F9 NCC 0-0.5g 0.5 Gonostomatidae cyclothone sp. Other 12.1 10.4 41.5 -19.5 3.4 2.9 2.4 T30 NCC 0-0.5g 0.1 Gonostomatidae Sigmops elongatus Other 9.0 10.9 32.4 -19.3 3.6 3.1 2.6 F4 NCC 0-0.5g 0.5 Macroramphosidae Macroramphosus scolopax Other 10.8 9.4 39.8 -20.0 3.7 2.6 2.2 F5 NCC 0-0.5g 0.5 Macroramphosidae Macroramphosus scolopax Other 11.2 9.4 41.3 -19.9 3.7 2.6 2.2 D37 NCC 01-2g 1.247 Myctophidae Diaphus brachycephalus Myctophidae 13.0 11.3 42.8 -19.1 3.3 3.2 2.7 D38 NCC 01-2g 2 Myctophidae Diaphus brachycephalus Myctophidae 13.8 11.8 45.0 -18.9 3.3 3.3 2.8 D39 NCC 04-8g 8 Myctophidae Diaphus brachycephalus Myctophidae 14.1 12.5 45.7 -19.2 3.2 3.5 3.1 D40 NCC 0-0.5g 0.5 Myctophidae Diaphus sp Myctophidae 12.1 10.0 40.9 -20.2 3.4 2.8 2.3 M50 NCC 04-8g 7.65 Myctophidae Lampadena sp. Myctophidae 12.9 10.6 42.8 -18.6 3.3 3.0 2.5 M51 NCC 01-2g 1.36 Myctophidae Lampanyctus sp Myctophidae 11.5 10.6 37.6 -19.2 3.3 3.0 2.5 M52 NCC 01-2g 2 Myctophidae Diaphus brachycephalus Myctophidae 13.5 11.4 43.5 -18.8 3.2 3.2 2.7 M53 NCC 02-4g 4 Myctophidae Diaphus brachycephalus Myctophidae 13.0 11.8 42.6 -18.8 3.3 3.3 2.8 M54 NCC 04-8g 8 Myctophidae Diaphus hudsoni Myctophidae 12.9 11.2 46.1 -19.4 3.6 3.2 2.7 M55 NCC 0-0.5g 0.5 Myctophidae Diaphus hudsoni Myctophidae 12.3 11.0 40.1 -19.3 3.3 3.1 2.6 M56 NCC 0-0.5g 0.5 Myctophidae Diaphus danae Myctophidae 11.9 10.3 39.7 -19.8 3.3 2.9 2.4 M80 NCC 01-2g 2 Myctophidae Diaphus perspicillatus Myctophidae 13.3 11.9 45.6 -19.6 3.4 3.4 2.9 M81 NCC 02-4g 4 Myctophidae Diaphus perspicillatus Myctophidae 13.2 10.4 47.7 -18.9 3.6 2.9 2.4 M62 NCC 04-8g 8 Myctophidae Myctophid Myctophidae 14.3 10.9 49.1 -19.4 3.4 3.1 2.6 M63 NCC 04-8g 8 Myctophidae Myctophid Myctophidae 14.4 11.1 48.0 -19.2 3.3 3.1 2.6

120 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs M64 NCC 02-4g 4 Myctophidae Myctophid Myctophidae 13.2 10.9 46.2 -19.8 3.5 3.1 2.6 M85 NCC 0.5-1g 1 Myctophidae Myctophid Myctophidae 13.2 10.5 44.1 -19.3 3.3 3.0 2.5 M66 NCC 0.5-1g 1 Myctophidae Myctophid Myctophidae 12.7 10.9 43.3 -19.3 3.4 3.1 2.6 M67 NCC 04-8g 8 Myctophidae Myctophid Myctophidae 14.3 11.0 47.9 -19.1 3.3 3.1 2.6 M68 NCC 02-4g 4 Myctophidae Myctophid Myctophidae 13.1 11.6 47.1 -19.5 3.6 3.3 2.8 M69 NCC 0-0.5g 0.5 Myctophidae Myctophid Myctophidae 12.1 11.6 41.8 -19.3 3.5 3.3 2.8 M70 NCC 04-8g 8 Myctophidae Myctophid Myctophidae 13.3 12.2 43.8 -19.4 3.3 3.5 3.0 M71 NCC 04-8g 8 Myctophidae Myctophid Myctophidae 14.0 11.9 47.7 -19.1 3.4 3.4 2.9 N32 NCC 08-16g 11.42 Myctophidae Nanobrachium atrum Myctophidae 12.0 11.0 38.7 -19.4 3.2 3.1 2.6 S04 NCC 02-4g 2.37 Myctophidae Scopelopsis multipunctatus Myctophidae 13.8 10.5 45.8 -19.6 3.3 2.9 2.5 S05 NCC 0-0.5g 0.15 Myctophidae Scopelopsis multipunctatus Myctophidae 11.7 9.7 40.2 -20.3 3.4 2.7 2.2 S05 NCC 0-0.5g 0.15 Myctophidae Scopelopsis multipunctatus Myctophidae 12.5 9.6 42.3 -20.1 3.4 2.7 2.2 S06 NCC 02-4g 2.77 Myctophidae Scopelopsis multipunctatus Myctophidae 14.2 11.3 45.6 -19.3 3.2 3.2 2.7 S07 NCC 02-4g 2.83 Myctophidae Scopelopsis multipunctatus Myctophidae 14.1 11.5 46.1 -19.5 3.3 3.2 2.7 S08 NCC 0-0.5g 0.39 Myctophidae Scopelopsis multipunctatus Myctophidae 12.1 12.3 43.1 -19.2 3.6 3.5 3.0 S09 NCC 02-4g 2.98 Myctophidae Scopelopsis multipunctatus Myctophidae 11.8 11.4 40.0 -19.3 3.4 3.2 2.7 S10 NCC 02-4g 2.7 Myctophidae Scopelopsis multipunctatus Myctophidae 12.3 10.9 40.2 -19.7 3.3 3.1 2.6 S17 NCC 02-4g 3.1 Myctophidae Scopelopsis multipunctatus Myctophidae 13.3 12.7 44.9 -19.5 3.4 3.6 3.1 S18 NCC 02-4g 2.603 Myctophidae Scopelopsis multipunctatus Myctophidae 13.6 11.4 45.7 -19.6 3.4 3.2 2.7 S32 NCC 01-2g 2 Myctophidae Scopelopsis multipunctatus Myctophidae 13.7 11.3 44.7 -19.2 3.3 3.2 2.7 S34 NCC 02-4g 4 Myctophidae Scopelopsis multipunctatus Myctophidae 14.1 11.4 47.2 -19.8 3.3 3.2 2.7 S35 NCC 02-4g 4 Myctophidae Scopelopsis multipunctatus Myctophidae 13.7 11.7 46.1 -19.5 3.4 3.3 2.8 S37 NCC 02-4g 4 Myctophidae Scopelopsis multipunctatus Myctophidae 13.5 10.9 45.6 -19.6 3.4 3.1 2.6 S38 NCC 02-4g 4 Myctophidae Scopelopsis multipunctatus Myctophidae 15.8 11.0 52.6 -19.6 3.3 3.1 2.6 S39 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.9 10.5 41.4 -19.6 3.5 2.9 2.5 S40 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.9 10.6 41.6 -19.9 3.5 3.0 2.5

121 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs S42 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.4 10.6 40.7 -20.0 3.6 3.0 2.5 S43 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.5 10.2 40.0 -20.0 3.5 2.9 2.4 S44 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.4 10.2 40.1 -20.0 3.5 2.9 2.4 S45 NCC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.2 12.3 38.9 -18.9 3.5 3.5 3.0 S46 NCC 01-2g 2 Myctophidae Scopelopsis multipunctatus Myctophidae 10.8 12.8 42.6 -19.0 3.9 3.6 3.2 F6 NCC 0-0.5g 0.445 Nomeidae Psenes sp Other 11.1 8.5 39.8 -19.9 3.6 2.4 1.9 F10 NCC 04-8g 8 Paralepididae Stemonosudis sp. Other 13.9 11.5 45.9 -19.2 3.3 3.2 2.7 POM1 NCC NA NA Particulate Organic Matter Bulk Sample POM 0.0 4.7 0.0 -20.6 6.8 1.2 1.1 POM2 NCC NA NA Particulate Organic Matter Bulk Sample POM 0.0 4.0 0.0 -21.0 6.9 1.0 1.0 POM3 NCC NA NA Particulate Organic Matter Bulk Sample POM 0.0 2.6 0.0 -20.5 8.3 0.6 0.8 POM4 NCC NA NA Particulate Organic Matter Bulk Sample POM 0.0 4.2 0.0 -21.1 7.4 1.1 1.1 F3 NCC 0.5-1g 0.73 Phosichthyidae Ichthyococcus australis Other 10.7 11.8 42.4 -19.1 4.0 3.3 2.8 V18 NCC 0-0.5g 0.4 Phosichthyidae Vinciguerria poweriae Other 11.5 11.3 39.9 -19.4 3.5 3.2 2.7 V19 NCC 0.5-1g 0.53 Phosichthyidae Vinciguerria poweriae Other 11.5 11.8 39.9 -19.2 3.5 3.3 2.8 V20 NCC 0-0.5g 0.41 Phosichthyidae Vinciguerria poweriae Other 11.5 11.8 39.8 -19.3 3.5 3.3 2.8 V21 NCC 0.5-1g 1 Phosichthyidae Vinciguerria poweriae Other 13.2 11.3 45.3 -19.5 3.4 3.2 2.7 V22 NCC 0.5-1g 1 Phosichthyidae Vinciguerria poweriae Other 13.3 10.9 45.6 -19.5 3.4 3.1 2.6 A38 NCC 01-2g 1.27 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.3 11.1 40.5 -19.1 3.3 3.1 2.6 A39 NCC 02-4g 2.03 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.2 11.4 40.6 -18.9 3.3 3.2 2.7 A40 NCC 0-0.5g 0.4 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.5 11.3 38.9 -19.1 3.4 3.2 2.7 A41 NCC 0.5-1g 0.72 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.9 11.2 43.6 -19.1 3.4 3.2 2.7 A42 NCC 02-4g 3.74 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 13.3 11.4 43.7 -18.9 3.3 3.2 2.7 A43 NCC 01-2g 1.8 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.2 11.7 38.1 -19.0 3.4 3.3 2.8 A44 NCC 01-2g 1.2 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.3 10.7 39.1 -20.3 3.5 3.0 2.5 A45 NCC 0.5-1g 0.9 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.1 11.3 38.1 -19.7 3.4 3.2 2.7 A46 NCC 01-2g 1.4 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.5 11.5 40.6 -19.0 3.3 3.3 2.8

122 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs A47 NCC 0.5-1g 0.7 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.6 11.4 41.7 -19.2 3.3 3.2 2.7 A49 NCC 01-2g 1.7 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.3 11.9 40.1 -18.8 3.5 3.4 2.9 A49 NCC 01-2g 1.7 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.3 11.9 40.1 -19.0 3.2 3.4 2.9 A50 NCC 0.5-1g 0.9 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.5 11.7 37.5 -19.1 3.3 3.3 2.8 A51 NCC 04-8g 4.03 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.3 11.6 39.4 -19.0 3.2 3.3 2.8 A52 NCC 04-8g 4.2 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.2 11.5 39.4 -19.0 3.2 3.2 2.7 A53 NCC 0-0.5g 0.4 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.4 11.5 37.6 -19.1 3.3 3.2 2.7 A54 NCC 0.5-1g 0.73 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.8 11.2 35.3 -19.1 3.3 3.2 2.7 A55 NCC 02-4g 2.2 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.4 11.6 40.2 -18.9 3.2 3.3 2.8 A56 NCC 01-2g 1.2 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.1 11.5 39.1 -19.1 3.2 3.2 2.7 A57 NCC 0-0.5g 0.48 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.9 11.4 39.6 -19.1 3.3 3.2 2.7 A58 NCC 0-0.5g 0.47 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.1 10.9 37.7 -19.2 3.4 3.1 2.6 A7 NCC 04-8g 6.3 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 13.3 11.2 42.9 -19.1 3.2 3.2 2.7 A8 NCC 02-4g 2.63 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.9 11.2 41.5 -19.3 3.2 3.2 2.7 A9 NCC 0.5-1g 0.88 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.0 11.1 39.1 -19.3 3.3 3.1 2.6 T07 NCC 01-2g 1.11 Stomiidae Malacosteus australis Stomiidae 12.1 10.7 38.5 -19.0 3.2 3.0 2.5 T08 NCC 08-16g 9.55 Stomiidae Chauliodus sloani Stomiidae 12.7 11.0 41.6 -19.1 3.3 3.1 2.6 T11 NCC 0.5-1g 0.59 Stomiidae Chauliodus sloani Stomiidae 11.0 10.3 38.2 -19.4 3.5 2.9 2.4 T12 NCC 04-8g 7.98 Stomiidae Malacosteus australis Stomiidae 11.0 12.4 37.1 -18.8 3.4 3.5 3.0 T14 NCC 02-4g 3.51 Stomiidae Chauliodus sloani Stomiidae 11.5 11.7 39.3 -19.2 3.4 3.3 2.8 T15 NCC 0.5-1g 0.78 Stomiidae Chauliodus sloani Stomiidae 11.5 10.6 39.3 -18.9 3.4 3.0 2.5 T16 NCC 0.5-1g 0.59 Stomiidae Chauliodus sloani Stomiidae 11.4 10.5 39.7 -19.3 3.5 2.9 2.5 T17 NCC 0.5-1g 0.73 Stomiidae Chauliodus sloani Stomiidae 11.2 12.3 39.5 -18.8 3.5 3.5 3.0 T19 NCC 02-4g 2.23 Stomiidae Chauliodus sloani Stomiidae 11.6 11.7 40.3 -19.2 3.5 3.3 2.8 T27 NCC 0-0.5g 0.23 Stomiidae Leptostomias sp. Stomiidae 8.7 8.8 31.7 -19.0 3.6 2.4 2.0 T27 NCC 0-0.5g 0.23 Stomiidae Leptostomias sp. Stomiidae 9.1 8.9 31.1 -19.3 3.4 2.5 2.0

123 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs T28 NCC 01-2g 1.34 Stomiidae Chauliodus sloani Stomiidae 10.4 11.0 36.8 -18.9 3.5 3.1 2.6 T29 NCC 0.5-1g 0.6 Stomiidae Chauliodus sloani Stomiidae 10.9 10.7 37.6 -19.4 3.4 3.0 2.5 T31 NCC 01-2g 1.29 Stomiidae Malacosteus australis Stomiidae 11.1 10.9 37.9 -19.1 3.4 3.1 2.6 T32 NCC 0.5-1g 0.58 Stomiidae Chauliodus sloani Stomiidae 11.3 10.9 38.4 -19.3 3.4 3.1 2.6 T34 NCC 02-4g 4 Stomiidae Chauliodus sloani Stomiidae 11.8 10.8 38.9 -19.5 3.3 3.0 2.5 Z01 NCC 125 µm 8.18E-06 Zooplankton Bulk Sample Zooplankton 5.4 6.8 25.1 -19.3 4.6 1.9 1.6 Z02 NCC 250 µm 6.54E-05 Zooplankton Bulk Sample Zooplankton 8.6 7.2 37.1 -20.2 4.3 2.0 1.6 Z03 NCC 500 µm 5.24E-04 Zooplankton Bulk Sample Zooplankton 1.9 9.0 11.1 -18.8 5.8 2.5 2.1 Z03 NCC 500 µm 5.24E-04 Zooplankton Bulk Sample Zooplankton 2.0 9.0 11.1 -19.1 5.6 2.5 2.1 Z04 NCC 1000 µm 0.004189 Zooplankton Bulk Sample Zooplankton 5.2 9.2 27.2 -19.8 5.2 2.6 2.1 Z05 NCC 2000 µm 0.03351 Zooplankton Bulk Sample Zooplankton 5.5 7.7 26.5 -19.7 4.8 2.1 1.8 T23 NWC 0-0.5g 0.5 Gonostomatidae Sigmops elongatus Other 10.8 10.1 35.4 -19.2 3.3 2.7 2.3 T24 NWC 0-0.5g 0.5 Gonostomatidae Sigmops elongatus Other 10.3 10.1 37.1 -18.9 3.6 2.7 2.3 T36 NWC 02-4g 4 Gonostomatidae Sigmops elongatus Other 12.0 9.9 39.9 -18.9 3.3 2.7 2.2 M12 NWC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.2 8.5 39.2 -20.4 3.5 2.3 1.9 M13 NWC 0-0.5g 0.5 Myctophidae Scopelopsis multipunctatus Myctophidae 11.5 9.3 39.4 -19.6 3.4 2.5 2.1 M14 NWC 0-0.5g 0.07 Myctophidae Scopelopsis multipunctatus Myctophidae 11.2 8.7 39.1 -19.7 3.5 2.3 1.9 M15 NWC 0-0.5g 0.1172 Myctophidae Scopelopsis multipunctatus Myctophidae 12.1 9.1 40.8 -20.2 3.4 2.4 2.0 M16 NWC 0-0.5g 0.065 Myctophidae Scopelopsis multipunctatus Myctophidae 12.1 8.0 39.4 -19.9 3.3 2.1 1.8 M17 NWC 0.5-1g 0.56 Myctophidae Ceratoscopelus warmingii Myctophidae 11.9 9.4 40.2 -19.5 3.4 2.5 2.1 M18 NWC 0.5-1g 0.94 Myctophidae Ceratoscopelus warmingii Myctophidae 12.6 10.9 40.6 -18.5 3.2 3.0 2.5 M19 NWC 0.5-1g 0.833 Myctophidae Ceratoscopelus warmingii Myctophidae 12.3 9.6 40.8 -19.1 3.3 2.6 2.2 M20 NWC 01-2g 1.01 Myctophidae Ceratoscopelus warmingii Myctophidae 11.5 9.5 39.8 -19.6 3.5 2.6 2.1 M21 NWC 01-2g 1.35 Myctophidae Ceratoscopelus warmingii Myctophidae 12.2 9.7 43.8 -19.3 3.6 2.6 2.2 M22 NWC 01-2g 1.25 Myctophidae Ceratoscopelus warmingii Myctophidae 12.8 9.5 42.3 -19.3 3.3 2.6 2.1 M23 NWC 01-2g 1.45 Myctophidae Ceratoscopelus warmingii Myctophidae 12.0 9.5 43.6 -19.5 3.6 2.6 2.1

124 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs M24 NWC 01-2g 1.66 Myctophidae Ceratoscopelus warmingii Myctophidae 12.5 9.6 42.3 -19.3 3.4 2.6 2.2 M25 NWC 08-16g 10.67 Myctophidae Myctophum phengodes Myctophidae 14.1 11.5 45.6 -18.6 3.2 3.1 2.7 M26 NWC 08-16g 8.99 Myctophidae Myctophum phengodes Myctophidae 14.0 11.0 46.2 -19.2 3.3 3.0 2.5 M27 NWC 02-4g 2.78 Myctophidae Hygophum hygomii Myctophidae 13.5 11.6 45.0 -18.9 3.3 3.2 2.7 M28 NWC 02-4g 2.08 Myctophidae Hygophum hygomii Myctophidae 12.8 10.2 44.1 -19.2 3.4 2.8 2.3 M29 NWC 02-4g 2.94 Myctophidae Hygophum hygomii Myctophidae 12.8 11.5 46.0 -18.9 3.6 3.1 2.7 M30 NWC 02-4g 2.7 Myctophidae Hygophum hygomii Myctophidae 11.7 10.3 41.0 -19.3 3.5 2.8 2.3 M31 NWC 02-4g 2.28 Myctophidae Hygophum hygomii Myctophidae 12.3 10.9 43.2 -19.0 3.5 3.0 2.5 M32 NWC 02-4g 2.46 Myctophidae Hygophum hygomii Myctophidae 13.1 11.8 45.8 -19.2 3.5 3.2 2.8 M33 NWC 02-4g 2.97 Myctophidae Hygophum hygomii Myctophidae 13.0 12.1 45.2 -19.1 3.5 3.3 2.9 M34 NWC 02-4g 2.34 Myctophidae Hygophum hygomii Myctophidae 13.1 11.9 44.7 -19.1 3.4 3.3 2.8 M35 NWC 02-4g 2.9 Myctophidae Hygophum hygomii Myctophidae 13.2 11.6 47.2 -18.9 3.6 3.2 2.7 M36 NWC 02-4g 2.61 Myctophidae Hygophum hygomii Myctophidae 13.1 12.0 45.8 -19.2 3.5 3.3 2.8 M37 NWC 02-4g 3.78 Myctophidae Hygophum hygomii Myctophidae 13.0 11.0 44.4 -18.7 3.4 3.0 2.5 M38 NWC 02-4g 3.42 Myctophidae Hygophum hygomii Myctophidae 13.1 11.7 44.5 -19.0 3.4 3.2 2.7 M38 NWC 02-4g 3.42 Myctophidae Hygophum hygomii Myctophidae 13.2 11.4 43.7 -18.9 3.3 3.1 2.7 M39 NWC 02-4g 2.89 Myctophidae Hygophum hygomii Myctophidae 13.1 10.5 49.5 -19.3 3.8 2.9 2.4 M40 NWC 02-4g 2.81 Myctophidae Hygophum hygomii Myctophidae 12.0 10.9 41.7 -19.4 3.5 3.0 2.5 M41 NWC 02-4g 2.28 Myctophidae Hygophum hygomii Myctophidae 13.1 11.5 48.3 -19.2 3.7 3.1 2.7 M43 NWC 02-4g 3.15 Myctophidae Diaphus perspicillatus Myctophidae 12.7 11.6 46.2 -19.1 3.6 3.2 2.7 M44 NWC 02-4g 3.1 Myctophidae Diaphus perspicillatus Myctophidae 11.3 11.1 47.7 -19.9 4.2 3.0 2.6 M45 NWC 02-4g 2.69 Myctophidae Diaphus perspicillatus Myctophidae 12.1 11.2 44.0 -19.6 3.6 3.1 2.6 M46 NWC 02-4g 2.74 Myctophidae Diaphus perspicillatus Myctophidae 12.5 11.0 45.4 -18.9 3.6 3.0 2.5 M47 NWC 02-4g 3.66 Myctophidae Ceratoscopelus warmingii Myctophidae 12.4 9.8 44.8 -19.3 3.6 2.6 2.2 M48 NWC 02-4g 2.4 Myctophidae Notoscopelus sp Myctophidae 13.8 11.4 44.7 -18.9 3.2 3.1 2.7 M49 NWC 02-4g 2.35 Myctophidae Notoscopelus sp Myctophidae 13.7 11.7 44.2 -18.8 3.2 3.2 2.7

125 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs M57 NWC 0-0.5g 0.27 Myctophidae Diaphus perspicillatus Myctophidae 13.5 11.4 45.0 -19.2 3.3 3.1 2.7 M58 NWC 02-4g 2.81 Myctophidae Hygophum hygomii Myctophidae 12.4 12.1 42.1 -19.3 3.4 3.3 2.9 M59 NWC 02-4g 2.8 Myctophidae Lobianchia doefleni Myctophidae 11.8 10.1 40.4 -19.2 3.4 2.7 2.3 M60 NWC 01-2g 1.1 Myctophidae Lobianchia doefleni Myctophidae 12.0 9.7 40.5 -19.3 3.4 2.6 2.2 M61 NWC 01-2g 1.21 Myctophidae Lobianchia doefleni Myctophidae 12.3 9.8 41.2 -19.3 3.3 2.6 2.2 M82 NWC 01-2g 1.57 Myctophidae Lobianchia doefleni Myctophidae 11.8 9.9 40.8 -19.3 3.5 2.7 2.2 M83 NWC 0.5-1g 0.51 Myctophidae Hygophum hygomii Myctophidae 12.1 10.1 40.6 -19.2 3.4 2.7 2.3 M84 NWC 0.5-1g 0.6 Myctophidae Lobianchia doefleni Myctophidae 12.4 9.7 41.6 -19.8 3.4 2.6 2.2 M65 NWC 0.5-1g 0.91 Myctophidae Lobianchia doefleni Myctophidae 12.4 9.8 41.8 -19.2 3.4 2.6 2.2 M72 NWC 0.5-1g 1 Myctophidae Myctophid Myctophidae 12.9 10.1 45.3 -19.7 3.5 2.7 2.3 M73 NWC 0.5-1g 1 Myctophidae Myctophid Myctophidae 13.3 10.4 46.7 -19.1 3.5 2.8 2.4 M74 NWC 0.5-1g 1 Myctophidae Myctophid Myctophidae 13.1 9.9 45.0 -19.3 3.4 2.7 2.2 M75 NWC 0.5-1g 1 Myctophidae Myctophid Myctophidae 12.8 11.1 45.0 -19.0 3.5 3.0 2.6 S20 NWC 0-0.5g 0.1355 Myctophidae Scopelopsis multipunctatus Myctophidae 12.0 9.5 39.2 -19.5 3.3 2.6 2.1 S21 NWC 0-0.5g 0.133 Myctophidae Scopelopsis multipunctatus Myctophidae 12.1 9.3 40.5 -19.6 3.3 2.5 2.1 S22 NWC 0-0.5g 0.1269 Myctophidae Scopelopsis multipunctatus Myctophidae 11.4 9.2 39.5 -19.5 3.5 2.5 2.1 S23 NWC 0-0.5g 0.1518 Myctophidae Scopelopsis multipunctatus Myctophidae 11.2 9.3 38.7 -19.7 3.5 2.5 2.1 S24 NWC 0-0.5g 0.1684 Myctophidae Scopelopsis multipunctatus Myctophidae 11.2 9.5 38.9 -19.6 3.5 2.6 2.1 S25 NWC 0-0.5g 0.1795 Myctophidae Scopelopsis multipunctatus Myctophidae 12.0 9.4 40.6 -19.4 3.4 2.5 2.1 S26 NWC 0-0.5g 0.123 Myctophidae Scopelopsis multipunctatus Myctophidae 11.1 9.0 38.8 -20.3 3.5 2.4 2.0 S27 NWC 0-0.5g 0.1852 Myctophidae Scopelopsis multipunctatus Myctophidae 12.0 9.3 40.6 -19.4 3.4 2.5 2.1 POM5 NWC NA NA Particulate Organic Matter Bulk Sample POM 0.0 4.9 0.0 -21.1 7.1 1.2 1.1 POM6 NWC NA NA Particulate Organic Matter Bulk Sample POM 0.0 2.7 0.0 -20.8 7.8 0.6 0.7 POM7 NWC NA NA Particulate Organic Matter Bulk Sample POM 0.0 3.0 0.0 -21.6 7.8 0.6 0.8 POM8 NWC NA NA Particulate Organic Matter Bulk Sample POM 0.0 6.2 0.0 -21.8 6.4 1.6 1.4 V07 NWC 0.5-1g 0.64 Phosichthyidae Vinciguerria poweriae Other 11.4 10.6 40.1 -19.0 3.5 2.9 2.4

126 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs V08 NWC 0.5-1g 0.99 Phosichthyidae Vinciguerria poweriae Other 11.8 10.2 41.2 -19.2 3.5 2.8 2.3 V09 NWC 0.5-1g 0.91 Phosichthyidae Vinciguerria poweriae Other 11.2 10.3 38.9 -19.3 3.5 2.8 2.3 V11 NWC 0-0.5g 0.15 Phosichthyidae Vinciguerria poweriae Other 11.0 10.0 39.3 -19.3 3.6 2.7 2.3 V12 NWC 0.5-1g 0.68 Phosichthyidae Vinciguerria poweriae Other 11.4 10.4 39.8 -19.3 3.5 2.8 2.4 V13 NWC 0-0.5g 0.48 Phosichthyidae Vinciguerria poweriae Other 8.8 10.5 30.9 -18.9 3.5 2.9 2.4 V14 NWC 0-0.5g 0.29 Phosichthyidae Vinciguerria poweriae Other 10.9 10.3 38.7 -19.0 3.6 2.8 2.3 V14 NWC 0-0.5g 0.29 Phosichthyidae Vinciguerria poweriae Other 11.3 10.2 38.1 -19.2 3.4 2.8 2.3 V16 NWC 0-0.5g 0.13 Phosichthyidae Vinciguerria poweriae Other 11.3 9.9 40.2 -19.1 3.6 2.7 2.2 V17 NWC 0.5-1g 0.55 Phosichthyidae Vinciguerria poweriae Other 11.3 10.5 39.6 -18.9 3.5 2.9 2.4 A10 NWC 0-0.5g 0.16 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.7 9.5 37.7 -18.9 3.2 2.6 2.1 A11 NWC 0-0.5g 0.19 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.1 10.0 37.9 -19.1 3.4 2.7 2.3 A12 NWC 0-0.5g 0.14 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.4 10.1 36.1 -19.3 3.5 2.7 2.3 A13 NWC 02-4g 3.46 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.8 10.7 41.4 -18.6 3.2 2.9 2.5 A14 NWC 08-16g 11.1 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 13.6 12.2 43.5 -18.8 3.2 3.4 2.9 A15 NWC 08-16g 9.2 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 13.6 11.4 43.7 -19.0 3.2 3.1 2.7 A17 NWC 04-8g 4.62 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 13.4 11.0 43.5 -18.5 3.2 3.0 2.5 A19 NWC 0-0.5g 0.15 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.3 10.1 35.8 -19.0 3.5 2.7 2.3 A20 NWC 0-0.5g 0.375 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.7 10.1 36.9 -19.0 3.4 2.7 2.3 A21 NWC 0-0.5g 0.277 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.5 10.4 38.4 -18.8 3.3 2.8 2.4 A22 NWC 0-0.5g 0.176 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.5 9.9 36.5 -19.2 3.5 2.7 2.2 A23 NWC 0-0.5g 0.263 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 9.2 10.3 32.3 -18.9 3.5 2.8 2.3 A24 NWC 0-0.5g 0.146 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.5 10.9 36.1 -19.2 3.4 3.0 2.5 A25 NWC 0-0.5g 0.078 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.7 9.9 37.4 -19.1 3.5 2.7 2.2 A26 NWC 0-0.5g 0.175 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.4 10.1 35.9 -19.0 3.5 2.7 2.3 A27 NWC 0-0.5g 0.189 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 10.3 10.1 35.7 -19.0 3.5 2.7 2.3 A28 NWC 0-0.5g 1.01 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.2 10.0 40.9 -19.0 3.4 2.7 2.3

127 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs A29 NWC 0.5-1g 0.72 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.7 10.5 42.4 -18.7 3.3 2.9 2.4 A30 NWC 0-0.5g 0.23 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.5 9.8 38.6 -19.2 3.4 2.6 2.2 A31 NWC 0-0.5g 0.39 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.2 10.4 41.3 -18.9 3.4 2.8 2.4 A32 NWC 0-0.5g 0.21 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.1 9.9 40.9 -19.0 3.4 2.7 2.2 A33 NWC 0-0.5g 0.17 Sternoptychidae Argyropelecus hemigymnus Sternoptychidae 12.3 11.2 41.6 -18.7 3.4 3.1 2.6 A34 NWC 01-2g 1.39 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.2 10.6 40.4 -18.6 3.3 2.9 2.4 A34 NWC 01-2g 1.39 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.8 10.7 38.5 -18.6 3.3 2.9 2.5 A35 NWC 01-2g 1.65 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.4 10.3 41.6 -18.9 3.4 2.8 2.3 A36 NWC 01-2g 1.04 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 12.0 10.6 40.3 -18.6 3.4 2.9 2.4 A37 NWC 0.5-1g 1 Sternoptychidae Argyropelecus aculeatus Sternoptychidae 11.8 10.4 39.9 -18.7 3.4 2.8 2.4 T09 NWC 0-0.5g 0.393 Stomiidae Chauliodus sloani Stomiidae 10.3 10.9 35.0 -19.0 3.4 3.0 2.5 T10 NWC 0.5-1g 0.66 Stomiidae Eustomias sp. Stomiidae 10.5 9.9 35.7 -18.5 3.4 2.7 2.2 T10 NWC 0.5-1g 0.66 Stomiidae Eustomias sp. Stomiidae 10.8 10.0 34.9 -18.5 3.2 2.7 2.3 T21 NWC 04-8g 7.796 Stomiidae Chauliodus sloani Stomiidae 12.6 11.3 41.8 -19.1 3.3 3.1 2.6 T22 NWC 08-16g 10.267 Stomiidae Melanostomiinae Stomiidae 11.7 12.1 41.0 -19.0 3.5 3.3 2.9 T25 NWC 04-8g 8 Stomiidae Malacosteus australis Stomiidae 12.2 11.3 39.7 -19.6 3.3 3.1 2.6 T26 NWC 08-16g 13.48 Stomiidae Idiacanthus atlanticus Stomiidae 10.5 14.7 36.5 -17.7 3.5 4.1 3.9 T35 NWC 0-0.5g 0.5 Stomiidae Chauliodus sloani Stomiidae 11.0 10.1 37.5 -19.4 3.4 2.7 2.3 Z06 NWC 125 µm 8.18E-06 Zooplankton Bulk Sample Zooplankton 7.2 5.9 32.1 -20.2 4.5 1.5 1.3 Z07 NWC 250 µm 6.54E-05 Zooplankton Bulk Sample Zooplankton 8.9 6.8 37.8 -20.7 4.2 1.8 1.5 Z08 NWC 500 µm 5.24E-04 Zooplankton Bulk Sample Zooplankton 8.6 7.6 33.6 -19.6 3.9 2.0 1.7 Z08 NWC 500 µm 5.24E-04 Zooplankton Bulk Sample Zooplankton 8.0 7.6 31.7 -19.1 4.0 2.0 1.7 Z09 NWC 1000 µm 0.004189 Zooplankton Bulk Sample Zooplankton 5.2 7.6 22.8 -20.5 4.4 2.0 1.7 Z10 NWC 2000 µm 0.03351 Zooplankton Bulk Sample Zooplankton 5.6 7.8 26.2 -19.8 4.7 2.1 1.7 Z10 NWC 2000 µm 0.03351 Zooplankton Bulk Sample Zooplankton 5.6 7.8 22.5 -20.2 4.0 2.1 1.7 G140 SCC 01-2g 1.0176 Melanocetidae Melanocetus johnsonii Other 9.2 12.8 33.2 -19.2 3.6 3.7 3.2

128 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs C02 SCC 01-2g 1.9895 Myctophidae Ceratoscopelus warmingii Myctophidae 13.4 10.2 43.9 -20.2 3.3 2.9 2.4 C03 SCC 0-0.5g 0.4667 Myctophidae Ceratoscopelus warmingii Myctophidae 10.9 9.1 38.2 -20.1 3.5 2.6 2.1 C04 SCC 02-4g 3.8712 Myctophidae Ceratoscopelus warmingii Myctophidae 13.9 9.6 45.3 -20.1 3.3 2.8 2.3 C06 SCC 01-2g 1.9319 Myctophidae Ceratoscopelus warmingii Myctophidae 13.2 9.6 43.9 -20.4 3.3 2.8 2.3 C07 SCC 0.5-1g 0.8546 Myctophidae Ceratoscopelus warmingii Myctophidae 12.3 9.1 41.7 -20.5 3.4 2.6 2.1 C08 SCC 01-2g 1.2403 Myctophidae Ceratoscopelus warmingii Myctophidae 13.5 9.7 44.7 -20.5 3.3 2.8 2.3 C09 SCC 01-2g 1.0705 Myctophidae Ceratoscopelus warmingii Myctophidae 13.1 9.5 42.7 -20.3 3.2 2.7 2.2 C10 SCC 0.5-1g 0.6467 Myctophidae Ceratoscopelus warmingii Myctophidae 11.9 8.6 41.0 -20.1 3.5 2.5 2.0 C14 SCC 0.5-1g 0.9731 Myctophidae Ceratoscopelus warmingii Myctophidae 11.3 8.6 38.0 -20.4 3.4 2.5 2.0 C15 SCC 0.5-1g 0.7687 Myctophidae Ceratoscopelus warmingii Myctophidae 12.0 8.9 40.8 -20.3 3.4 2.6 2.1 C19 SCC 01-2g 1.2845 Myctophidae Ceratoscopelus warmingii Myctophidae 13.8 9.5 45.7 -20.2 3.3 2.7 2.2 C20 SCC 0.5-1g 0.8931 Myctophidae Ceratoscopelus warmingii Myctophidae 11.2 8.2 38.7 -20.1 3.5 2.4 1.9 C21 SCC 0-0.5g 0.2036 Myctophidae Ceratoscopelus warmingii Myctophidae 11.3 7.9 39.4 -20.0 3.5 2.3 1.8 C22 SCC 02-4g 2.3528 Myctophidae Ceratoscopelus warmingii Myctophidae 14.0 9.8 45.8 -20.0 3.3 2.8 2.3 C24 SCC 0.5-1g 0.9018 Myctophidae Ceratoscopelus warmingii Myctophidae 11.5 8.7 39.0 -20.2 3.4 2.5 2.0 C27 SCC 02-4g 3.2094 Myctophidae Ceratoscopelus warmingii Myctophidae 13.5 10.5 45.4 -20.2 3.3 3.0 2.5 C81 SCC 0.5-1g 0.7643 Myctophidae Ceratoscopelus warmingii Myctophidae 11.1 8.6 39.3 -20.1 3.6 2.5 2.0 C82 SCC 0-0.5g 0.3733 Myctophidae Ceratoscopelus warmingii Myctophidae 10.5 9.1 38.5 -20.2 3.7 2.6 2.1 C83 SCC 0.5-1g 0.5195 Myctophidae Ceratoscopelus warmingii Myctophidae 10.6 8.6 37.9 -20.4 3.6 2.5 2.0 C84 SCC 0-0.5g 0.4189 Myctophidae Ceratoscopelus warmingii Myctophidae 10.6 9.2 37.9 -20.2 3.6 2.6 2.2 C85 SCC 0-0.5g 0.4999 Myctophidae Ceratoscopelus warmingii Myctophidae 10.5 9.2 38.2 -20.4 3.6 2.6 2.2 C86 SCC 0-0.5g 0.4577 Myctophidae Ceratoscopelus warmingii Myctophidae 10.4 9.2 37.8 -20.2 3.6 2.6 2.2 C90 SCC 0-0.5g 0.2151 Myctophidae Ceratoscopelus warmingii Myctophidae 10.5 9.2 37.2 -20.3 3.5 2.6 2.2 G01 SCC 0-0.5g 0.1263 Myctophidae Lampanyctus sp. Myctophidae 12.7 9.9 41.7 -19.8 3.3 2.9 2.3 G02 SCC 0-0.5g 0.093 Myctophidae Lampanyctus sp. Myctophidae 10.8 8.7 37.1 -20.5 3.4 2.5 2.0 G05 SCC 01-2g 1.5481 Myctophidae Scopelopsis multipunctatus Myctophidae 12.8 11.8 40.8 -19.4 3.2 3.4 2.9

129 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs G06 SCC 01-2g 1.89 Myctophidae Scopelopsis multipunctatus Myctophidae 12.5 11.8 40.1 -19.4 3.2 3.4 2.9 G08 SCC 08-16g 9.5407 Myctophidae Lampandena luminosa Myctophidae 11.5 12.6 51.8 -19.5 4.5 3.6 3.1 G101 SCC 0-0.5g 0.2371 Myctophidae Lampanyctus sp. Myctophidae 10.0 9.0 38.4 -20.0 3.8 2.6 2.1 G104 SCC 0-0.5g 0.3866 Myctophidae Notoscopelus resplendens Myctophidae 10.6 8.7 36.8 -20.9 3.5 2.5 2.0 G106 SCC 0-0.5g 0.1335 Myctophidae Lampanyctus sp. Myctophidae 10.1 9.2 38.3 -20.3 3.8 2.6 2.2 G109 SCC 01-2g 1.8343 Myctophidae Scopelopsis multipunctatus Myctophidae 12.6 12.4 41.4 -19.5 3.3 3.6 3.1 G11 SCC 04-8g 4.0245 Myctophidae Sybolophorus barnardi Myctophidae 13.6 8.2 42.5 -20.4 3.1 2.4 1.9 G110 SCC 02-4g 2.113 Myctophidae Scopelopsis multipunctatus Myctophidae 13.3 11.5 41.3 -19.5 3.1 3.3 2.8 G111 SCC 01-2g 1.9358 Myctophidae Scopelopsis multipunctatus Myctophidae 12.8 11.2 41.4 -19.6 3.2 3.2 2.7 G112 SCC 01-2g 1.8588 Myctophidae Scopelopsis multipunctatus Myctophidae 12.8 11.2 41.8 -19.3 3.3 3.2 2.7 G113 SCC 02-4g 2.112 Myctophidae Scopelopsis multipunctatus Myctophidae 13.0 11.3 40.6 -19.4 3.1 3.3 2.7 G114 SCC 02-4g 2.6052 Myctophidae Scopelopsis multipunctatus Myctophidae 13.5 11.6 41.8 -19.3 3.1 3.4 2.8 G115 SCC 01-2g 1.1403 Myctophidae Sybolophorus barnardi Myctophidae 12.6 9.1 41.1 -20.4 3.3 2.6 2.1 G116 SCC 01-2g 1.591 Myctophidae Scopelopsis multipunctatus Myctophidae 13.2 11.2 42.4 -19.6 3.2 3.2 2.7 G118 SCC 02-4g 2.432 Myctophidae Scopelopsis multipunctatus Myctophidae 14.1 11.2 43.7 -19.5 3.1 3.2 2.7 G120 SCC 02-4g 3.9689 Myctophidae Sybolophorus barnardi Myctophidae 14.3 9.2 44.4 -20.4 3.1 2.6 2.2 G121 SCC 02-4g 4.1199 Myctophidae Sybolophorus barnardi Myctophidae 13.3 9.3 44.6 -20.5 3.3 2.7 2.2 G125 SCC 0.5-1g 0.5985 Myctophidae Notoscopelus resplendens Myctophidae 11.5 8.2 39.4 -20.8 3.4 2.4 1.9 G126 SCC 0.5-1g 0.5458 Myctophidae Lampanyctus sp. Myctophidae 11.1 10.3 43.9 -20.0 3.9 3.0 2.4 G127 SCC 0.5-1g 0.5694 Myctophidae Lampanyctus sp. Myctophidae 11.6 10.2 43.8 -19.8 3.8 2.9 2.4 G128 SCC 0.5-1g 0.5189 Myctophidae Lampanyctus sp. Myctophidae 11.9 10.3 42.1 -19.9 3.5 3.0 2.4 G129 SCC 0.5-1g 0.5133 Myctophidae Lampanyctus sp. Myctophidae 11.5 10.2 42.5 -19.9 3.7 2.9 2.4 G13 SCC 04-8g 4.4729 Myctophidae Sybolophorus barnardi Myctophidae 13.2 10.1 43.4 -19.7 3.3 2.9 2.4 G130 SCC 0.5-1g 0.506 Myctophidae Lampanyctus sp. Myctophidae 11.2 10.3 41.7 -20.3 3.7 3.0 2.4 G131 SCC 0.5-1g 0.5 Myctophidae Lampanyctus sp. Myctophidae 11.4 11.1 40.7 -19.7 3.6 3.2 2.7 G14 SCC 02-4g 2.0802 Myctophidae Sybolophorus barnardi Myctophidae 13.7 8.8 42.6 -20.4 3.1 2.5 2.1

130 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs G15 SCC 04-8g 5.3206 Myctophidae Sybolophorus barnardi Myctophidae 13.5 10.0 44.3 -20.4 3.3 2.9 2.4 G16 SCC 02-4g 3.3703 Myctophidae Sybolophorus barnardi Myctophidae 13.9 8.8 44.2 -20.1 3.2 2.5 2.1 G19 SCC 01-2g 1.13 Myctophidae Sybolophorus barnardi Myctophidae 12.5 9.0 40.8 -20.2 3.3 2.6 2.1 G21 SCC 04-8g 7.0982 Myctophidae Nannobrachium Myctophidae 12.0 11.2 42.9 -20.3 3.6 3.2 2.7 G31 SCC 04-8g 6.7199 Myctophidae Diaphus Myctophidae 12.2 12.5 39.8 -19.1 3.3 3.6 3.1 G34 SCC 04-8g 4.2434 Myctophidae Sybolophorus barnardi Myctophidae 12.3 12.3 42.3 -19.8 3.4 3.6 3.0 G37 SCC 04-8g 4.6387 Myctophidae Sybolophorus barnardi Myctophidae 12.3 10.5 47.7 -19.9 3.9 3.0 2.5 G85 SCC 0-0.5g 0.1991 Myctophidae Lampanyctus 2 Myctophidae 9.8 9.1 36.4 -20.1 3.7 2.6 2.1 G87 SCC 04-8g 5.3817 Myctophidae Sybolophorus barnardi Myctophidae 11.0 9.5 39.3 -19.7 3.6 2.7 2.2 G88 SCC 0-0.5g 0.289 Myctophidae Lampanyctus 1 Myctophidae 10.2 9.3 38.7 -19.9 3.8 2.7 2.2 G93 SCC 0-0.5g 0.4338 Myctophidae Lampanyctus 2 Myctophidae 10.0 8.8 37.6 -20.0 3.7 2.5 2.1 H01 SCC 0.5-1g 0.8725 Myctophidae Hygophum hygomii Myctophidae 12.9 9.5 44.1 -19.9 3.4 2.7 2.2 H02 SCC 01-2g 1.1035 Myctophidae Hygophum hygomii Myctophidae 13.4 9.6 46.0 -19.7 3.4 2.8 2.3 H03 SCC 01-2g 1.2272 Myctophidae Hygophum hygomii Myctophidae 13.0 9.5 43.4 -19.8 3.4 2.7 2.2 H04 SCC 01-2g 1.5168 Myctophidae Hygophum hygomii Myctophidae 12.8 10.1 43.5 -19.7 3.4 2.9 2.4 H05 SCC 0.5-1g 0.7674 Myctophidae Hygophum hygomii Myctophidae 12.3 9.5 43.5 -19.5 3.5 2.7 2.2 H08 SCC 0-0.5g 0.4805 Myctophidae Hygophum hygomii Myctophidae 11.5 9.6 39.8 -19.7 3.5 2.8 2.3 H09 SCC 01-2g 1.4035 Myctophidae Hygophum hygomii Myctophidae 12.7 10.0 43.4 -19.9 3.4 2.9 2.4 H10 SCC 02-4g 3.6127 Myctophidae Hygophum hygomii Myctophidae 12.5 10.5 45.2 -19.9 3.6 3.0 2.5 H11 SCC 01-2g 1.9838 Myctophidae Hygophum hygomii Myctophidae 12.8 10.0 49.0 -19.8 3.8 2.9 2.4 H12 SCC 01-2g 1.7794 Myctophidae Hygophum hygomii Myctophidae 13.3 10.1 46.1 -19.9 3.5 2.9 2.4 H14 SCC 04-8g 4.0906 Myctophidae Hygophum hygomii Myctophidae 13.7 11.1 45.7 -19.5 3.3 3.2 2.7 H17 SCC 02-4g 2.5581 Myctophidae Hygophum hygomii Myctophidae 12.3 10.5 47.7 -19.9 3.9 3.0 2.5 H19 SCC 02-4g 3.0943 Myctophidae Hygophum hygomii Myctophidae 12.6 9.9 43.1 -19.8 3.4 2.9 2.3 H22 SCC 0.5-1g 0.7837 Myctophidae Hygophum hygomii Myctophidae 12.8 9.2 44.9 -19.7 3.5 2.6 2.2 H25 SCC 0.5-1g 0.964 Myctophidae Hygophum hygomii Myctophidae 16.3 9.4 57.4 -19.5 3.5 2.7 2.2

131 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs H71 SCC 04-8g 5.2971 Myctophidae Hygophum hygomii Myctophidae 12.9 10.3 43.3 -19.9 3.3 3.0 2.4 H72 SCC 01-2g 1.2344 Myctophidae Hygophum hygomii Myctophidae 11.6 9.2 41.2 -19.8 3.5 2.6 2.2 H73 SCC 01-2g 1.59782 Myctophidae Hygophum hygomii Myctophidae 12.1 9.8 42.2 -19.7 3.5 2.8 2.3 H74 SCC 02-4g 2.578 Myctophidae Hygophum hygomii Myctophidae 12.8 10.1 43.8 -19.7 3.4 2.9 2.4 H75 SCC 0.5-1g 0.925 Myctophidae Hygophum hygomii Myctophidae 12.2 10.0 43.2 -19.9 3.5 2.9 2.4 H76 SCC 0.5-1g 0.7615 Myctophidae Hygophum hygomii Myctophidae 12.2 9.7 42.7 -19.9 3.5 2.8 2.3 H77 SCC 0-0.5g 0.3831 Myctophidae Hygophum hygomii Myctophidae 11.3 9.4 39.6 -19.9 3.5 2.7 2.2 H79 SCC 0-0.5g 0.2506 Myctophidae Hygophum hygomii Myctophidae 10.6 10.1 40.1 -19.5 3.8 2.9 2.4 H80 SCC 0-0.5g 0.3394 Myctophidae Hygophum hygomii Myctophidae 11.3 9.0 40.4 -19.5 3.6 2.6 2.1 H81 SCC 0-0.5g 0.3466 Myctophidae Hygophum hygomii Myctophidae 11.1 9.3 39.3 -19.4 3.5 2.7 2.2 H83 SCC 0-0.5g 0.3187 Myctophidae Hygophum hygomii Myctophidae 10.9 9.6 38.7 -20.0 3.5 2.8 2.3 H84 SCC 0-0.5g 0.3898 Myctophidae Hygophum hygomii Myctophidae 11.6 9.9 40.3 -19.0 3.5 2.9 2.3 H85 SCC 0-0.5g 0.3282 Myctophidae Hygophum hygomii Myctophidae 10.9 9.6 36.0 -19.7 3.3 2.8 2.3 POM1 SCC NA NA Particulate Organic Matter Bulk Sample POM NA 2.9 NA -21.0 4.5 0.8 0.9 POM2 SCC NA NA Particulate Organic Matter Bulk Sample POM NA 3.5 NA -18.8 6.3 1.0 1.0 POM3 SCC NA NA Particulate Organic Matter Bulk Sample POM NA 3.8 NA -18.6 7.0 1.1 1.0 POM4 SCC NA NA Particulate Organic Matter Bulk Sample POM NA 4.2 NA -18.9 7.5 1.2 1.1 T01 SCC 0-0.5g 0.4264 Stomiidae Idiacanthus atlanticus Stomiidae 9.0 11.2 31.2 -19.4 3.5 3.2 2.7 T05 SCC 0.5-1g 0.832 Stomiidae Idiacanthus atlanticus Stomiidae 9.3 11.3 31.7 -19.7 3.4 3.3 2.7 T07 SCC 0.5-1g 0.7803 Stomiidae Idiacanthus atlanticus Stomiidae 9.5 12.2 32.3 -19.3 3.4 3.5 3.0 T10 SCC 0-0.5g 0.4075 Stomiidae Idiacanthus atlanticus Stomiidae 9.9 11.8 34.4 -19.6 3.5 3.4 2.9 T12 SCC 0-0.5g 0.1134 Stomiidae Idiacanthus atlanticus Stomiidae 10.2 9.3 35.6 -19.8 3.5 2.7 2.2 T13 SCC 0-0.5g 0.2759 Stomiidae Idiacanthus atlanticus Stomiidae 8.3 10.5 28.3 -19.8 3.4 3.0 2.5 T14 SCC 0.5-1g 0.6083 Stomiidae Idiacanthus atlanticus Stomiidae 9.0 11.2 30.9 -19.4 3.4 3.2 2.7 T27 SCC 0.5-1g 0.7774 Stomiidae Idiacanthus atlanticus Stomiidae 8.3 11.1 27.6 -18.6 3.3 3.2 2.7 T28 SCC 0.5-1g 0.6775 Stomiidae Idiacanthus atlanticus Stomiidae 10.3 7.4 33.0 -19.4 3.2 2.1 1.7

132 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs T29 SCC 0.5-1g 0.7008 Stomiidae Chauliodus sloani Stomiidae 10.6 9.8 36.2 -20.1 3.4 2.8 2.3 T31 SCC 01-2g 1.1976 Stomiidae Eustomias Stomiidae 11.6 10.5 38.8 -19.7 3.4 3.0 2.5 T33 SCC 01-2g 1.9495 Stomiidae Chauliodus sloani Stomiidae 10.4 10.8 37.9 -19.5 3.6 3.1 2.6 T34 SCC 01-2g 1.8292 Stomiidae Chauliodus sloani Stomiidae 10.9 10.5 37.7 -19.6 3.5 3.0 2.5 T36 SCC 04-8g 6.9185 Stomiidae Chauliodus sloani Stomiidae 14.2 8.4 63.4 -19.9 4.5 2.4 2.0 T47 SCC 0.5-1g 0.5855 Stomiidae Chauliodus sloani Stomiidae 10.9 9.9 37.4 -19.2 3.4 2.9 2.3 T52 SCC 0-0.5g 0.115 Stomiidae Idiacanthus atlanticus Stomiidae 9.7 9.5 35.4 -19.8 3.7 2.7 2.2 T54 SCC 0.5-1g 0.7466 Stomiidae Idiacanthus atlanticus Stomiidae 8.8 10.7 30.4 -19.2 3.5 3.1 2.6 T55 SCC 0-0.5g 0.4613 Stomiidae Idiacanthus atlanticus Stomiidae 8.8 10.4 31.6 -19.6 3.6 3.0 2.5 T62 SCC 0-0.5g 0.4324 Stomiidae Idiacanthus atlanticus Stomiidae 8.9 10.9 29.9 -19.4 3.3 3.1 2.6 T63 SCC 0-0.5g 0.4075 Stomiidae Idiacanthus atlanticus Stomiidae 7.2 9.5 26.6 -18.8 3.7 2.7 2.2 Z1-125 SCC 125 µm 2.89E-06 Zooplankton Bulk Sample Zooplankton 5.4 5.0 23.9 -19.3 4.5 1.4 1.3 Z2-250 SCC 250 µm 2.31E-05 Zooplankton Bulk Sample Zooplankton 8.2 5.2 36.7 -20.3 4.5 1.5 1.3 Z3-500 SCC 500 µm 1.85E-04 Zooplankton Bulk Sample Zooplankton 8.2 6.1 34.8 -19.7 4.2 1.7 1.5 Z4-1000 SCC 1000 µm 0.001481 Zooplankton Bulk Sample Zooplankton 8.0 6.3 36.4 -19.3 4.6 1.8 1.5 Z5-2000 SCC 2000 µm 0.011848 Zooplankton Bulk Sample Zooplankton 9.0 6.1 34.1 -19.9 3.8 1.7 1.5 G138 SWC 01-2g 1.269 Melanocetidae Melanocetus johnsonii Other 10.7 13.0 40.5 -19.0 3.8 4.4 3.6 G139 SWC 01-2g 1.9445 Melanocetidae Melanocetus johnsonii Other 10.8 11.1 41.1 -19.2 3.8 3.9 3.0 C28 SWC 0.5-1g 0.9882 Myctophidae Ceratoscopelus warmingii Myctophidae 12.0 8.5 40.5 -19.7 3.4 3.1 2.3 C29 SWC 01-2g 1.1835 Myctophidae Ceratoscopelus warmingii Myctophidae 12.4 8.7 42.4 -20.6 3.4 3.1 2.4 C30 SWC 01-2g 1.6768 Myctophidae Ceratoscopelus warmingii Myctophidae 12.3 8.5 41.5 -20.3 3.4 3.1 2.3 C33 SWC 01-2g 1.1355 Myctophidae Ceratoscopelus warmingii Myctophidae 12.5 8.8 41.9 -20.6 3.3 3.2 2.4 C34 SWC 0.5-1g 0.92 Myctophidae Ceratoscopelus warmingii Myctophidae 12.0 7.8 42.5 -20.7 3.5 2.9 2.2 C35 SWC 0.5-1g 0.7608 Myctophidae Ceratoscopelus warmingii Myctophidae 11.7 7.8 41.8 -20.4 3.6 2.9 2.2 C36 SWC 0-0.5g 0.2574 Myctophidae Ceratoscopelus warmingii Myctophidae 11.8 7.3 40.6 -20.9 3.4 2.7 2.1 C37 SWC 0-0.5g 0.4002 Myctophidae Ceratoscopelus warmingii Myctophidae 11.9 7.9 41.3 -20.3 3.5 2.9 2.2

133 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs C38 SWC 0-0.5g 0.3445 Myctophidae Ceratoscopelus warmingii Myctophidae 11.3 7.7 41.1 -20.5 3.6 2.9 2.2 C39 SWC 0-0.5g 0.2973 Myctophidae Ceratoscopelus warmingii Myctophidae 11.5 7.5 41.8 -20.7 3.6 2.8 2.1 C40 SWC 0-0.5g 0.4767 Myctophidae Ceratoscopelus warmingii Myctophidae 11.8 8.6 42.6 -19.8 3.6 3.1 2.4 C42 SWC 0-0.5g 0.308 Myctophidae Ceratoscopelus warmingii Myctophidae 11.3 7.5 41.4 -20.3 3.7 2.8 2.1 C43 SWC 0-0.5g 0.4131 Myctophidae Ceratoscopelus warmingii Myctophidae 11.8 7.6 40.0 -20.5 3.4 2.8 2.1 C44 SWC 0-0.5g 0.3232 Myctophidae Ceratoscopelus warmingii Myctophidae 11.4 7.7 38.7 -20.5 3.4 2.9 2.2 C46 SWC 0.5-1g 0.6833 Myctophidae Ceratoscopelus warmingii Myctophidae 12.0 7.1 41.5 -21.1 3.5 2.7 2.0 C47 SWC 0.5-1g 0.8243 Myctophidae Ceratoscopelus warmingii Myctophidae 12.7 8.1 43.7 -20.7 3.4 3.0 2.3 C48 SWC 0.5-1g 0.598 Myctophidae Ceratoscopelus warmingii Myctophidae 13.2 7.9 45.1 -20.5 3.4 2.9 2.2 C49 SWC 0.5-1g 0.5042 Myctophidae Ceratoscopelus warmingii Myctophidae 12.4 8.3 42.4 -20.0 3.4 3.0 2.3 C51 SWC 01-2g 1.344 Myctophidae Ceratoscopelus warmingii Myctophidae 13.4 9.0 45.8 -20.5 3.4 3.2 2.5 C52 SWC 01-2g 1.05 Myctophidae Ceratoscopelus warmingii Myctophidae 13.4 8.6 44.6 -20.1 3.3 3.1 2.4 C53 SWC 02-4g 2.0235 Myctophidae Ceratoscopelus warmingii Myctophidae 13.0 8.7 43.8 -20.0 3.4 3.1 2.4 C54 SWC 01-2g 1.82 Myctophidae Ceratoscopelus warmingii Myctophidae 13.2 9.0 43.9 -20.1 3.3 3.2 2.5 C55 SWC 02-4g 2.1541 Myctophidae Ceratoscopelus warmingii Myctophidae 13.3 9.2 43.9 -20.2 3.3 3.3 2.5 C56 SWC 0.5-1g 0.9555 Myctophidae Ceratoscopelus warmingii Myctophidae 12.6 8.2 43.3 -20.6 3.4 3.0 2.3 C57 SWC 02-4g 2.1867 Myctophidae Ceratoscopelus warmingii Myctophidae 13.7 8.9 45.2 -20.1 3.3 3.2 2.4 C58 SWC 01-2g 1.6025 Myctophidae Ceratoscopelus warmingii Myctophidae 13.1 9.0 44.0 -20.0 3.4 3.2 2.5 C59 SWC 02-4g 2.2335 Myctophidae Ceratoscopelus warmingii Myctophidae 13.2 9.5 44.8 -19.7 3.4 3.4 2.6 C60 SWC 01-2g 1.7749 Myctophidae Ceratoscopelus warmingii Myctophidae 13.7 9.1 45.5 -20.2 3.3 3.3 2.5 C61 SWC 02-4g 2.5491 Myctophidae Ceratoscopelus warmingii Myctophidae 12.9 9.2 42.2 -20.0 3.3 3.3 2.5 C62 SWC 02-4g 2.5424 Myctophidae Ceratoscopelus warmingii Myctophidae 13.3 8.2 44.0 -20.3 3.3 3.0 2.3 C63 SWC 02-4g 2.1635 Myctophidae Ceratoscopelus warmingii Myctophidae 12.7 8.9 43.0 -20.0 3.4 3.2 2.4 C65 SWC 02-4g 2.7891 Myctophidae Ceratoscopelus warmingii Myctophidae 13.1 9.2 44.0 -20.3 3.4 3.3 2.5 C72 SWC 04-8g 4.1192 Myctophidae Ceratoscopelus warmingii Myctophidae 13.0 8.9 43.8 -20.2 3.4 3.2 2.4 C76 SWC 04-8g 4.5982 Myctophidae Ceratoscopelus warmingii Myctophidae 13.1 9.0 44.5 -20.2 3.4 3.2 2.5

134 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs C77 SWC 04-8g 4.4251 Myctophidae Ceratoscopelus warmingii Myctophidae 12.6 9.5 44.6 -20.2 3.5 3.4 2.6 C78 SWC 04-8g 4.2705 Myctophidae Ceratoscopelus warmingii Myctophidae 12.7 8.8 43.1 -20.2 3.4 3.2 2.4 C79 SWC 04-8g 4.9114 Myctophidae Ceratoscopelus warmingii Myctophidae 12.2 10.1 43.5 -20.2 3.6 3.6 2.8 C80 SWC 04-8g 4.525 Myctophidae Ceratoscopelus warmingii Myctophidae 12.6 9.4 42.8 -20.3 3.4 3.4 2.6 G132 SWC 0.5-1g 0.6605 Myctophidae Lampanyctus 1 Myctophidae 12.6 9.8 44.1 -20.3 3.5 3.5 2.7 G133 SWC 0.5-1g 0.9571 Myctophidae Lampanyctus 1 Myctophidae 12.8 10.7 42.1 -19.4 3.3 3.7 2.9 G134 SWC 0.5-1g 0.7273 Myctophidae Lampanyctus 1 Myctophidae 12.0 11.6 41.7 -19.5 3.5 4.0 3.2 G135 SWC 0.5-1g 0.5677 Myctophidae Lampanyctus 1 Myctophidae 12.8 10.2 42.7 -19.8 3.3 3.6 2.8 G136 SWC 0.5-1g 0.9177 Myctophidae Notoscopelus resplendens Myctophidae 12.2 10.5 41.0 -19.4 3.3 3.7 2.9 G137 SWC 0-0.5g 0.3993 Myctophidae Lampanyctus 1 Myctophidae 11.5 11.5 40.9 -19.4 3.6 4.0 3.2 G23 SWC 04-8g 6.4373 Myctophidae Sybolophorus barnardi Myctophidae 31.3 9.9 99.5 -19.7 3.2 3.5 2.7 G24 SWC 04-8g 6.0663 Myctophidae Symbolophorus evermanni Myctophidae 13.4 10.2 42.8 -19.7 3.2 3.6 2.8 G26 SWC 04-8g 7.4926 Myctophidae Sybolophorus barnardi Myctophidae 14.1 10.3 44.1 -19.1 3.1 3.6 2.8 G27 SWC 04-8g 5.1495 Myctophidae Symbolophorus evermanni Myctophidae 13.5 10.3 43.7 -19.9 3.2 3.6 2.8 G38 SWC 08-16g 9.6876 Myctophidae Sybolophorus barnardi Myctophidae 14.7 11.7 45.9 -19.2 3.1 4.0 3.2 G40 SWC 0-0.5g 0.4806 Myctophidae Lampanyctus 1 Myctophidae 11.3 8.6 40.1 -20.2 3.6 3.1 2.4 G43 SWC 0-0.5g 0.3874 Myctophidae Lampanyctus 1 Myctophidae 11.1 9.4 38.4 -19.2 3.5 3.4 2.6 G44 SWC 0-0.5g 0.289 Myctophidae Lampanyctus 1 Myctophidae 11.2 9.0 39.8 -19.9 3.5 3.2 2.5 G46 SWC 0-0.5g 0.2466 Myctophidae Lampanyctus 1 Myctophidae 11.0 8.7 40.5 -19.7 3.7 3.1 2.4 G47 SWC 0-0.5g 0.2122 Myctophidae Lampanyctus 1 Myctophidae 10.5 9.5 42.1 -19.5 4.0 3.4 2.6 G51 SWC 0-0.5g 0.0545 Myctophidae Lampanyctus 1 Myctophidae 11.4 9.3 39.2 -20.1 3.4 3.3 2.5 G52 SWC 08-16g 8.0123 Myctophidae Symbolophorus evermanni Myctophidae 14.3 12.2 45.4 -19.6 3.2 4.2 3.4 G53 SWC 04-8g 5.9653 Myctophidae Lampandena luminosa Myctophidae 12.9 10.2 40.1 -19.3 3.1 3.6 2.8 G54 SWC 04-8g 4.0377 Myctophidae Lampandena luminosa Myctophidae 13.3 11.6 42.1 -19.2 3.2 4.0 3.2 G55 SWC 04-8g 5.4982 Myctophidae Symbolophorus evermanni Myctophidae 14.3 11.4 45.1 -19.3 3.2 3.9 3.1 G62 SWC 0.5-1g 0.5258 Myctophidae Lampanyctus 1 Myctophidae 11.5 9.4 42.4 -19.8 3.7 3.4 2.6

135 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs G76 SWC 08-16g 8.7954 Myctophidae Sybolophorus barnardi Myctophidae 13.9 10.9 44.4 -19.6 3.2 3.8 3.0 G77 SWC 04-8g 7.884 Myctophidae Sybolophorus barnardi Myctophidae 13.3 12.2 42.0 -18.8 3.2 4.2 3.4 G84 SWC 08-16g 11.5858 Myctophidae Sybolophorus barnardi Myctophidae 13.9 11.7 43.4 -19.0 3.1 4.0 3.2 G96 SWC 0.5-1g 0.5922 Myctophidae Lampanyctus 1 Myctophidae 11.9 9.9 40.4 -19.5 3.4 3.5 2.7 G97 SWC 0-0.5g 0.4483 Myctophidae Lampanyctus 1 Myctophidae 10.8 8.7 36.6 -20.3 3.4 3.1 2.4 G98 SWC 0.5-1g 0.5144 Myctophidae Lampanyctus 1 Myctophidae 11.3 10.0 37.0 -25.3 3.3 3.5 2.7 H27 SWC 02-4g 3.6555 Myctophidae Hygophum hygomii Myctophidae 13.7 10.5 43.5 -18.9 3.2 3.7 2.9 H28 SWC 02-4g 3.663 Myctophidae Hygophum hygomii Myctophidae 14.0 10.5 44.5 -19.3 3.2 3.7 2.9 H29 SWC 02-4g 3.4785 Myctophidae Hygophum hygomii Myctophidae 14.1 11.3 45.3 -19.0 3.2 3.9 3.1 H30 SWC 02-4g 2.9544 Myctophidae Hygophum hygomii Myctophidae 13.5 11.3 44.4 -19.2 3.3 3.9 3.1 H31 SWC 02-4g 3.5127 Myctophidae Hygophum hygomii Myctophidae 14.2 11.3 45.3 -19.1 3.2 3.9 3.1 H32 SWC 02-4g 3.3855 Myctophidae Hygophum hygomii Myctophidae 14.0 10.6 44.8 -19.3 3.2 3.7 2.9 H33 SWC 02-4g 3.0622 Myctophidae Hygophum hygomii Myctophidae 14.0 11.5 44.7 -18.9 3.2 4.0 3.2 H34 SWC 02-4g 2.6546 Myctophidae Hygophum hygomii Myctophidae 13.8 11.3 45.0 -19.4 3.3 3.9 3.1 H40 SWC 01-2g 1.9471 Myctophidae Hygophum hygomii Myctophidae 10.6 10.2 35.5 -19.7 3.4 3.6 2.8 H45 SWC 0.5-1g 0.6055 Myctophidae Hygophum hygomii Myctophidae 12.5 8.5 41.0 -20.1 3.3 3.1 2.3 H46 SWC 0-0.5g 0.39 Myctophidae Hygophum hygomii Myctophidae 12.3 8.4 41.1 -20.1 3.3 3.1 2.3 H47 SWC 0.5-1g 0.7343 Myctophidae Hygophum hygomii Myctophidae 13.2 9.3 42.4 -19.3 3.2 3.3 2.5 H48 SWC 0-0.5g 0.2961 Myctophidae Hygophum hygomii Myctophidae 12.3 11.2 41.3 -19.5 3.4 3.9 3.1 H49 SWC 0-0.5g 0.261 Myctophidae Hygophum hygomii Myctophidae 12.0 9.6 40.5 -19.3 3.4 3.4 2.6 H50 SWC 0-0.5g 0.1644 Myctophidae Hygophum hygomii Myctophidae 11.7 7.9 39.8 -20.5 3.4 2.9 2.2 H51 SWC 0-0.5g 0.2757 Myctophidae Hygophum hygomii Myctophidae 11.6 8.8 38.7 -19.7 3.3 3.2 2.4 H52 SWC 0-0.5g 0.2603 Myctophidae Hygophum hygomii Myctophidae 12.0 10.2 40.7 -19.7 3.4 3.6 2.8 H53 SWC 0-0.5g 0.2677 Myctophidae Hygophum hygomii Myctophidae 11.9 8.1 39.6 -20.2 3.3 3.0 2.3 H55 SWC 0-0.5g 0.1442 Myctophidae Hygophum hygomii Myctophidae 11.6 9.2 40.8 -20.0 3.5 3.3 2.5 H56 SWC 04-8g 4.28 Myctophidae Hygophum hygomii Myctophidae 13.4 10.9 42.8 -19.3 3.2 3.8 3.0

136 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs H57 SWC 04-8g 4.2162 Myctophidae Hygophum hygomii Myctophidae 13.3 11.0 41.6 -18.9 3.1 3.8 3.0 H58 SWC 04-8g 4.1728 Myctophidae Hygophum hygomii Myctophidae 13.5 9.8 42.8 -19.1 3.2 3.5 2.7 H60 SWC 04-8g 4.0582 Myctophidae Hygophum hygomii Myctophidae 13.4 11.1 43.1 -19.3 3.2 3.9 3.0 H61 SWC 04-8g 4.3038 Myctophidae Hygophum hygomii Myctophidae 13.0 10.8 41.2 -18.9 3.2 3.8 2.9 H62 SWC 04-8g 4.1359 Myctophidae Hygophum hygomii Myctophidae 13.2 11.2 41.5 -19.3 3.2 3.9 3.1 H63 SWC 04-8g 4.1699 Myctophidae Hygophum hygomii Myctophidae 13.4 11.2 42.4 -19.2 3.2 3.9 3.1 H86 SWC 0.5-1g 0.6456 Myctophidae Hygophum hygomii Myctophidae 11.7 10.4 44.7 -20.1 3.8 3.6 2.8 POM5 SWC NA NA Particulate Organic Matter Bulk Sample POM NA 0.6 NA -20.7 7.9 0.8 0.9 POM6 SWC NA NA Particulate Organic Matter Bulk Sample POM NA 0.8 NA -20.8 8.0 0.8 0.9 POM7 SWC NA NA Particulate Organic Matter Bulk Sample POM NA 3.7 NA -23.2 5.9 1.7 1.4 POM8 SWC NA NA Particulate Organic Matter Bulk Sample POM NA 0.5 NA -20.3 8.2 0.7 0.9 T37 SWC 0.5-1g 0.5175 Stomiidae Astronesthes indicus Stomiidae 12.1 10.2 40.1 -19.1 3.3 3.6 2.8 T38 SWC 01-2g 1.3505 Stomiidae Melanostomias Stomiidae 11.2 13.7 45.3 -18.6 4.0 4.6 3.9 T41 SWC 02-4g 2.7366 Stomiidae Malacosteus australis Stomiidae 8.6 12.3 48.9 -18.5 5.7 4.2 3.4 T42 SWC 0.5-1g 0.5322 Stomiidae Stomias Boa Stomiidae 11.0 9.1 36.4 -19.0 3.3 3.3 2.5 T43 SWC 0-0.5g 0.1963 Stomiidae Idiacanthus atlanticus Stomiidae 9.5 9.2 32.6 -19.5 3.4 3.3 2.5 T44 SWC 0-0.5g 0.2916 Stomiidae Idiacanthus atlanticus Stomiidae 9.4 8.8 32.1 -19.6 3.4 3.2 2.4 T56 SWC 0-0.5g 0.0817 Stomiidae Idiacanthus atlanticus Stomiidae 8.5 8.1 32.6 -20.1 3.8 3.0 2.3 T57 SWC 0-0.5g 0.1271 Stomiidae Idiacanthus atlanticus Stomiidae 8.1 9.3 30.8 -19.5 3.8 3.3 2.5 T58 SWC 0.5-1g 0.7413 Stomiidae Chauliodus sloani Stomiidae 10.9 10.1 37.4 -19.5 3.4 3.6 2.8 T59 SWC 0.5-1g 0.528 Stomiidae Chauliodus sloani Stomiidae 10.1 10.8 34.9 -19.4 3.4 3.8 2.9 T61 SWC 0-0.5g 0.3624 Stomiidae Chauliodus sloani Stomiidae 11.2 10.2 38.1 -19.4 3.4 3.6 2.8 Z10 SWC 2000 µm 0.011848 Zooplankton Bulk Sample Zooplankton 8.0 6.0 31.2 -20.8 3.9 2.4 1.8 Z6 SWC 125 µm 2.89E-06 Zooplankton Bulk Sample Zooplankton 7.0 2.7 32.1 -21.2 4.6 1.4 1.2 Z7 SWC 250 µm 2.31E-05 Zooplankton Bulk Sample Zooplankton 8.1 3.0 35.7 -21.8 4.4 1.5 1.3 Z8 SWC 500 µm 1.85E-04 Zooplankton Bulk Sample Zooplankton 6.5 4.5 26.0 -21.2 4.0 1.9 1.5

137 Chapter 3 – Appendix

Appendix 3C Table 1: Continued ID WM WC Weight Family Species MS %N δ15N %C δ13C C:N TLc TLs Z9 SWC 1000 µm 0.001481 Zooplankton Bulk Sample Zooplankton 7.5 5.5 29.6 -20.9 4.0 2.2 1.7

138