Trophic-based analyses of the Scotia Sea ecosystem with an examination of the effects of some data limitations and uncertainties Sarah Collings Doctor of Philosophy University of York Biology September 2015 Abstract The Scotia Sea is a sub-region of the Southern Ocean with a unique biological operation, including high rates of primary production, high abundances of Antarctic krill, and a diverse community of land-breeding predators. Trophic interactions link all species in an ecosystem into a network known as the food web. Theoretical analyses of trophic food webs, which are parameterised using diet composition data, offer useful tools to explore food web structure and operation. However, limitations in diet data can cause uncertainty in subsequent food web analyses. Therefore, this thesis had two aims: (i) to provide ecological insight into the Scotia Sea food web using theoretical analyses; and (ii) to identify, explore and ameliorate for the effects of some data limitations on these analyses. Therefore, in Chapter 2, I collated a set of diet composition data for consumers in the Scotia Sea, and highlighted its strengths and limitations. In Chapters 3 and 4, I constructed food web analyses to draw ecological insight into the Scotia Sea food web. I indicated the robustness of these conclusions to some of the assumptions I used to construct them. Finally, in Chapter 5, I constructed a probabilistic model of a penguin encountering prey to investigate changes in trophic interactions caused by the spatial and temporal variability of their prey. I show that natural variabilities, such as the spatial aggregation of prey into swarms, can explain observed foraging outcomes for this predator. Pressures caused by anthropogenically-driven changes to the earth's climate may alter the community structure in the Scotia Sea. Furthermore, activities by commercial fisheries who operate in the Scotia Sea are increasing, which may impact on the food web. This thesis offers a baseline analysis of the Scotia Sea food web, which will be useful to assess changes to the ecosystem caused by future, external pressures. 2 Contents Abstract 2 Contents 3 List of tables 9 List of figures 11 Acknowledgements 15 Authors declaration 17 1 Introduction 18 1.1 Placing the research in the wider context . 18 1.2 Introduction to the Scotia Sea . 19 1.3 Trophic interactions and food webs . 19 1.4 The Scotia Sea food web . 21 1.5 Uncertainties in food web analysis . 23 1.6 Thesis structure and aims . 25 2 Diet composition of Scotia Sea consumers: a new data set to facilitate food web analyses 29 Diet composition of Scotia Sea consumers: a new data set to facilitate food web analyses . 29 2.1 Introduction . 30 2.2 Methods . 32 2.2.1 Data set format . 32 2.2.2 Summary of the data . 35 2.3 Results . 37 2.3.1 Temporal and spatial spread of the data set . 37 2.3.2 Summary of species groups . 37 2.4 Discussion . 49 2.4.1 Spatial spread of the Scotia Sea data set . 49 2.4.2 Temporal spread of the Scotia Sea data set . 50 2.4.3 Taxonomic coverage of Scotia Sea predators . 50 2.4.3.1 Land-breeding predators and cetaceans . 50 3 2.4.3.2 Cephalopods and fish . 51 2.4.3.3 Benthos and zooplankton . 52 2.4.4 Diet metrics . 53 2.4.5 Taxonomic resolution of prey . 53 2.5 Conclusion . 53 3 System-level properties for the Scotia Sea food web and the importance of taxonomic resolution of species 55 Abstract . 55 3.1 Introduction . 56 3.2 Methodology . 58 3.2.1 Food web matrix definition . 58 3.2.2 Scotia Sea food web matrix . 58 3.2.3 Closure groups . 59 3.2.3.1 Definition . 59 3.2.3.2 Assessing the effects of closure groups . 60 3.2.4 Network properties . 61 3.2.4.1 Binary topological properties . 61 3.2.4.2 Quantitative topological properties . 67 3.2.5 Aggregating species in a food web matrix . 73 3.2.6 Sensitivity analysis . 74 3.2.6.1 SA1: Structural biases of closure groups . 74 3.2.6.2 SA2: Using species-resolved data only, from the Scotia Sea data set . 74 3.3 Results . 75 3.3.1 Effects of closure groups on network properties . 75 3.3.2 Effects of aggregating species in the Scotia Sea food web matrix on network properties . 77 3.3.3 Sensitivity analysis . 78 3.3.3.1 SA1: Structural biases of closure groups . 78 3.3.3.2 SA2: Using species-resolved data only, from the Scotia Sea data set . 78 3.4 Discussion . 80 3.4.1 Scotia Sea network properties . 80 3.4.1.1 Linkage complexity . 81 3.4.1.2 The trophic positions of species . 83 3.4.1.3 Diversity of trophic interactions . 83 4 3.4.2 Binary versus quantitative properties . 84 3.4.3 Closure groups . 85 3.4.4 Limitations and further work . 86 3.5 Conclusion . 87 4 A mass-balanced model to estimate production of species in the Scotia Sea food web 89 Abstract . 89 4.1 Introduction . 90 4.2 Methods . 92 4.2.1 The Reduced Production Model . 92 4.2.2 Scotia Sea functional groups . 95 4.2.3 Parameterising the RPM . 99 4.2.3.1 Diet matrix . 99 4.2.3.2 Production estimate . 109 4.2.3.3 Efficiency estimates . 110 4.2.4 Sensitivity and uncertainty analyses . 115 4.3 Results . 116 4.3.1 Baseline production estimates . 116 4.3.2 Sensitivity analysis . 117 4.3.3 Uncertainty analysis . 121 4.4 Discussion . 123 4.4.1 Summary of the sensitivity and uncertainty analyses . 123 4.4.2 Primary production . 124 4.4.3 Zooplankton and benthos . 125 4.4.4 Fish and cephalopods . 126 4.4.5 Apex and land-breeding predators . 127 4.4.6 Caveats and future work . 128 4.5 Conclusion . 129 5 The importance of swarming prey and their intra-annual variability for the foraging outcomes of a predator 131 Abstract . 131 5.1 Introduction . 132 5.1.1 Chapter motivation: the importance of detailed interactions . 132 5.1.2 Overview of macaroni penguin ecology . 133 5.1.3 Individual-based stochastic encounter modelling . 134 5 5.1.4 Aims . 134 5.2 Methods . 135 5.2.1 Macaroni penguin (Eudyptes chrysolophus): biology and model con- straints . 135 5.2.2 Modelling a penguin's foraging trip . 136 5.2.2.1 Model 1: both prey are randomly distributed . 136 5.2.2.2 Model 2: krill form swarms . 138 5.2.2.3 Parameter values . 140 5.2.3 Forage trip simulations . 140 5.2.4 Krill recruitment and penguin breeding success . 142 5.2.5 Can the spatial aggregations of krill into swarms explain observed patterns in the diet composition of macaroni penguins? . 142 5.2.6 How does biological complexity affect foraging? . 143 5.2.6.1 ABC1: A predator encountering a krill swarm may leave the swarm before satiation . 143 5.2.6.2 ABC2: Handling time of prey . 144 5.2.6.3 ABC3: Alternate prey also form swarms . 144 5.2.7 Do prey which form swarms have different energetic costs than non- swarming prey? . 145 5.2.8 How does the timing and strength of krill recruitment during the brood phase affect foraging success? . 145 5.3 Results . 146 5.3.1 Forage trip outcomes: random versus swarming krill . 146 5.3.2 How does biological complexity affect foraging? . 147 5.3.2.1 ABC1: A penguin can leave a.