Foraging ecology of winter-breeding in New Zealand Timothee Poupart

To cite this version:

Timothee Poupart. Foraging ecology of winter-breeding seabirds in New Zealand. Food and Nu- trition. Université de La Rochelle; Deakin university (Geelong, Australie), 2019. English. ￿NNT : 2019LAROS016￿. ￿tel-02988439￿

HAL Id: tel-02988439 https://tel.archives-ouvertes.fr/tel-02988439 Submitted on 4 Nov 2020

HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Foraging ecology

of winter-breeding seabirds

in New Zealand

By

Timothée Poupart

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

Deakin University (Australia), in cotutelle with Université de La Rochelle (France) école doctorale Euclide,

in collaboration with Te Papa Tongarewa Museum (New Zealand).

Defended the 05th November 2019 at the Centre d’Études Biologiques de Chizé, France

Jury members:

Yan ROPERT-COUDERT President Directeur de Recherche

Centre d’Études Biologiques de Chizé (France)

Jérôme FORT Rapporteur Chargé de Recherche

Université de La Rochelle (France)

Thierry BOULINIER Examinant Directeur de Recherche

Centre d’Écologie Fonctionnelle et Évolutive (Montpellier, France)

Mark JESSOPP Examinant lecturer in zoology

University College Cork (Ireland)

Pierre PISTORIUS Examinant Senior lecturer

Nelson Mandela University (Port Elizabeth, South Africa)

John ARNOULD Supervisor Professor

Deakin University (Melbourne, Australia)

Charles-André BOST Supervisor Directeur de Recherche

Centre d’Études Biologiques de Chizé

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Foraging ecology of winter-breeding seabirds in New Zealand submitted for the degree of Doctor of Philosophy

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Foraging ecology of winter-breeding seabirds in New Zealand submitted for the degree of Doctor of Philosophy

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Abstract

Although the cost of reproduction constrains to breed during spring/summer when food availability peaks, exception exist in seabirds with few engaged in breeding during winter months. How their elevated energy needs can be sustained during a period traditionally reported for food shortage and challenging at-sea conditions is poorly understood. In addition, this unusual breeding phenology is adopted by more species in New Zealand than elsewhere in the world, with a concentration on the South island west coast where several winter breeding species are reported to forage with overlap. Therefore, the objectives of this thesis were to: 1) describe the fine-scale foraging behaviour of winter-breeding species from the west coast of

New Zealand’s South Island, 2) investigate the intrinsic and extrinsic factors driving their foraging, and 3) quantify their niche overlap as they exploit similar areas during elevated energetically demand.

Using bio-logging data (GPS, accelerometer, dive recorder) combined with stable isotopes

(carbon and nitrogen from whole blood), the winter foraging strategies of breeding males and females were investigated in a deep diver (Fiordland penguin Eudyptes pachyrhynchus) and two surface-feeders / shallow divers (Westland petrel Procellaria westlandica and southern

Buller’s Thalassarche b. bulleri). The tracked individuals foraged close to their colony compared to their summer breeding congenerics, using primarily the nearby shelf-slope and neritic waters. Males and females displayed similar foraging behaviour in penguins and petrels, while spatial sexual differences occurred for albatross. All three species encountered prey at a high rate, allowing raising offspring with good success and without higher foraging effort than their summer-breeding congeners.

These findings suggest that winter-breeding species have a phenology matching a winter prey resource on the shelf of the west coast of New Zealand’s South Island. With additional data from literature for little penguin Eudyptula minor and spotted shag Stictocarbo punctatus,

this winter-breeding community showed partial overlap of their foraging niche, but an accumulation of small divergences in home ranges, diving behaviour, temporal pattern of foraging, diet and trophic level is likely to explain their coexistence. Hence, winter-breeding can be a favourable phenology for high-level predators, which exploit shelf-slope and inshore waters undergoing winter mixing that insure fish and persistence through winter. In addition, winter-breeding also allow the matching of chick-fledging period with the spring

(local primary production peak), and before the elevated needs of millions of summer-breeding species back from migration.

Résumé

Bien que le coût énergétique de la reproduction contraigne les animaux à élever leur(s) jeune(s) pendant le pic d’abondance de la ressource alimentaire au printemps et/ou en été, certaines espèces d’oiseaux marins font exception, en se reproduisant pendant les mois d’hiver.

Comment leurs besoins énergétiques élevés peuvent-ils être satisfaits pendant une période traditionnellement décrite par des conditions environnementales difficiles réduisant les ressources alimentaires ? Cette question a été peu étudiée jusqu’à présent. Cette stratégie originale de reproduction hivernale est adoptée en Nouvelle-Zélande par davantage d’espèces qu’ailleurs dans le monde, avec une concentration sur la côte ouest de l’île du Sud. Dans cette région, les aires de distribution des espèces les plus faciles à suivre en mer étaient connues pour présenter un chevauchement spatial.

Dans ce contexte, cette thèse a eu trois objectifs. Tout d’abord, décrire le comportement de recherche alimentaire à fine échelle d’espèces d’oiseaux marins nicheuses en hiver clés du réseau trophique, sur la côte ouest de l’ile du Sud de la Nouvelle-Zélande. Ensuite, examiner les facteurs intrinsèques et extrinsèques déterminant leur comportement de recherche alimentaire. Et enfin, quantifier le recouvrement de leurs niches écologiques sur leur zones d’alimentation durant la période d’élevage du(des) jeune(s).

Nous avons pu étudier la stratégie de recherche alimentaire sur une communauté d’espèces constituée de deux guildes : les oiseaux plongeurs (manchot du Fiordland Eudyptes pachyrhynchus) et les oiseaux de surface (pétrel de Westland Procellaria westlandica, albatros de Buller Thalassarche bulleri bulleri). L’approche s’est basée sur le déploiement de bio- loggers sur les oiseaux (GPS, accéléromètre, enregistreur de plongée) et l’analyse isotopique

(sur le carbone et l’azote) de sang prélevé après leur voyage en mer. Les individus équipés se sont moins éloignés de leur colonie par rapport à leurs espèces congénères nichant en été, et ont utilisé majoritairement les eaux du talus continental et néritiques. Mâles et femelles ont

utilisé des comportements de recherche alimentaire semblables, avec des différences spatiales concernant l’albatros de Buller. Des taux de rencontre de proies élevés ont été enregistrés chez les trois espèces, permettant un élevage du(des) jeune(s) avec un taux de succès élevé, et sans effort supérieur par rapport aux espèces nichant en été.

Ces résultats suggèrent que les espèces d’oiseaux marins nichant en hiver ont une phénologie de la reproduction concordant avec des ressources alimentaire hivernales suffisantes au large de la côte ouest de l’île du Sud en Nouvelle-Zélande. En utilisant des données supplémentaires issues de la littérature, l’étude de ségrégation de niche écologique de ces espèces a été étendue avec l’inclusion du manchot bleu Eudyptula minor et du Cormoran tacheté Stictocarbo punctatus, nichant aussi en hiver sur cette même côte. Cette communauté de cinq espèces a montré un recoupement partiel de leur niche écologique. La ségrégation

écologique est réalisée grâce à un faisceau de divergences sur le plan des déplacements horizontaux, verticaux, de la distribution temporelle de l’activité de recherche alimentaire, du régime alimentaire et de la niche isotopique. Cette ségrégation expliquant la coexistence de cette communauté avienne dans un même habitat.

Par conséquent, la stratégie de reproduction hivernale peut être favorable aux oiseaux marins prédateurs supérieurs, lorsque des processus océanographiques locaux sont favorables.

Sur le plan océanographique, un mélange vertical des eaux attire et garantit la persistance d’espèces proies au cours de l’hiver. En outre, la phénologie hivernale de la reproduction contribue aussi à l’émancipation du poussin au printemps. Ainsi, elle concorde avec le pic local de productivité primaire, en accord avec les prédictions. Ces espèces, présentes en populations modestes, peuvent terminer leur cycle de reproduction hivernal avant que d’autres espèces beaucoup plus abondantes de retour de migration (comme les millions de couples de Puffin fuligineux Puffinus griseus) n’engagent à leur tour leur reproduction estivale.

Preface

The ethical guidelines of Deakin University Ethics Committee and Animal Welfare

Committee Fieldwork protocols, conducted in New Zealand, were approved by the Wildlife

Act Authority for wildlife located on public conservation land and other land (Authorisations numbers 49827-FAU, 26677-FAU, 48714-FAU, 39729-FAU and 39912-FAU).

The present thesis opens with a general introduction to the work in Chapter 1. The core chapters (Chapters 2-5) are data-chapters published (Chapters 2 and 3), submitted (Chapter 4) or in preparation (Chapter 5) for publication in peer-reviewed journals. Lastly, Chapter 6 forms the General Discussion of the main findings of the study.

I am the primary contributor to all aspects of the work presented in this study, and John P.Y

Arnould (my primary supervisor), Susan M. Waugh and Charles A. Bost (my co-supervisors) are co-authors on the resulting publications for providing guidance and assistance in all aspects of this PhD. Akiko Kato provided helpful advices and assistance with acceleration data analysis in Chapters 2, 3 and 4. Karyne M. Rodgers contributed to the stable isotopes analysis conducted at GNS laboratory (Lower Hut, New Zealand) presented in Chapters 2, 3, 4 and 5. Lauren P.

Angel provided assistance with GPS and acceleration data merging in chapter 3. Finally, Colin

M. Miskelly helped for the fieldwork and manuscript editing in Chapters 2 and 3.

Publications arising from this thesis

Chapter 2

Timothée A Poupart, Susan M Waugh, Charles A Bost, Akiko Kato, Colin M Miskelly, Karyne

M Rodgers, John PY Arnould (2019). Foraging ecology of a winter breeder, the Fiordland penguin. Mar Ecol Prog Ser 614:183-197. https://doi.org/10.3354/meps12910

Chapter 3

Timothée A Poupart, Susan M Waugh, Colin M Miskelly, Akiko Kato, Lauren P Angel, Karyne

M Rodgers, John PY Arnould (2019). Fine scale foraging behaviour of southern Buller’s albatross, the only Thalassarche provisioning chicks through winter. Mar Ecol Prog Ser. https://doi.org/10.3354/meps13042

Chapter 4

Timothée A Poupart, Susan M Waugh, Akiko Kato, John PY Arnould (in review). Foraging niche overlap during chick-rearing in the sexually dimorphic Westland petrel. Royal Society

Open Science.

Acknowledgments

My first thanks go to my supervisors, Susan Waugh, John Arnould and Charly Bost. Your personal investment made this PhD project happen and your continued support mentored me during this research journey. Thank you for sharing your time, your knowledge and your passion for wildlife research.

I would like to thank also the Te Papa Tongarewa team and managers (Susan Waugh, Colin

Miskelly, Alan Tennyson, Laura Shepherd, Jean-Claude Stahl, Dale Bailey, Dean Peterson) for their warm welcome on the other side of the world, and their precious support in all kind of situation. I also would like to thank the iwi who allowed us to work in wonderful places: Kati

Waewae, Kati Mahaki, Makawhio Runanga of Ngai Tahu, Ngai Tahu Runaka of Awarua

Runaka, Hokonui Runaka, Oraka Aparima Runaka and Waihopai Runaka.

I would like also to warmly thank the people involved in the fieldwork, who braved the austral winter in tents on Solander island (Susan Waugh, Colin Miskelly, Jean-Claude Stahl,

Laureline Durand, Francois Même), who endured the nocturnal and muddy walks in the

Westland ranges (Leon Berard, Laureline Durand, Francois Meme), and who shared the hut life on Open Bay Island (Aude Boutet, John Arnould, Charly Bost, Susan Waugh, David

Waugh). They not only helped to gather precious data but also to make memorable moments.

The fieldwork would have been impossible without the support of the Department of

Conservation (New Zealand) people involved in the permits establishment and the biosecurity checks, neither without the safe logistic provided by pilots and their staff (Southern Lakes

Helicopter, Haast Heliservices, Fly Fiordland).

Although not directly involved and less apparent in the research outcomes, many people have also helped in one way or another for the completion of this PhD. Listing them without missing any is going to be hard. For instance, I would like to thank the administrative staff at

Deakin, Te Papa, Chizé and La Rochelle: Clorinda Scofield, Jennifer De La Corte Gomez,

Virginie Bernard, and Paco Bustamante for their help with administrative matters.

On the computer side, I am grateful to Higo Jasser and Fawzi Elfaidi, always responsive to sort out computer issues. A PhD with data loggers also require a lot of programing and I am very grateful to all students and researchers who kindly provided some analysis tips at a coffee break or by email: Travis Knox, Lauren Angel, Elodie Camprasse, Grace Sutton, Florian

Orgeret, Clara Péron, Julien Collet, Paul Tixier, Akiko Kato, Karine Delord, Yves Cherel,

David Pinaud.

On the student life side, I would like to thank the flatmates, deskmates and labmates who made this time enjoyable: Aymeric Froment, Liam Plucke, Jack, Paul Tixier, Alizée Meillère,

Andréaz Dupoué, Grace Sutton, Jonathan Botta, Marlenne Rodriguez, Florian Orgeret, Julien

Collet, William Jouanneau, Nathan Pacoureau, Candice Michelot, Alexandre Corbeau,

Christophe Sauser, le jardin, Josie et Michel, Karine Heerah, Joris Laborie, Olivia Hicks,

Baptiste Picard, Sophie Dupont, Ryan and Caryn Reisinger, Juliette Rabdeau, Julie Mestre,

Lucas Torres. In addition, I think about the PhD candidates and post-doc students met previously, who motivated me to follow this way: Jean-Baptiste Thiebot, Sophie Jeudi-de-

Grissac, Laurie Thiers, Samantha Patrick, Alice Carravieri, Benoit Gineste, Jade Vacquié-

Garcia, Sabrina Tartu, Joan Ferrer-Obiol, Antoine Reits, Agnès Lewden, Quentin Schull,

Robin Cristofari, Clément Cornec, Pierre Blévin.

Last but not least, to my parents, sister, the entire family and the friends who trusted my choices and kept being present despite the geographic distance.

I want to dedicate this work to Guy Gérard and John Stevenson.

Table of contents

Chapter 1: General introduction ...... 1 1.1 Foraging and breeding: the essentials of life ...... 1 1.2 foraging ...... 4 1.3 Timing of breeding in seabirds ...... 7 1.4 New Zealand, a hotspot for winter-breeding seabirds ...... 12 1.5 Research objectives and thesis structure ...... 14 Chapter 2: Foraging ecology of a winter breeder, the Fiordland penguin ...... 17 2.1 Abstract ...... 18 2.2 Introduction ...... 19 2.3 Materials and methods ...... 21 2.3.1 Study site and field procedures ...... 21 2.3.2 Data handling and processing ...... 22 2.3.3 Statistical analyses ...... 26 2.4 Results ...... 27 2.4.1 At-sea movements and habitat use ...... 27 2.4.2 Diving behaviour and foraging effort ...... 31 2.4.3 Trophic level and isotopic niche width ...... 36 2.5 Discussion ...... 37 2.5.1 At-sea movements and habitat use ...... 37 2.5.2 Diving behaviour and foraging effort ...... 40 2.5.3 Trophic level and isotopic niche width ...... 41 2.6 Supplementary material ...... 45 Chapter 3: Fine scale foraging behaviour of southern Buller's albatross, the only Thalassarche provisioning chicks through winter ...... 49 3.1 Abstract ...... 50 3.2 Introduction ...... 51 3.3 Materials and methods ...... 54 3.3.1 Study site and field procedures ...... 54 3.3.2 Data handling and processing ...... 55 3.3.3 Statistical analyses ...... 57 3.4 Results ...... 58 3.4.1 At-sea movements and activity budget ...... 58 3.4.2 Foraging behaviour and trophic niche ...... 65 3.5 Discussion ...... 71 3.5.1 At-sea movements and activity budget ...... 71 3.5.2 Foraging behaviour and trophic niche ...... 75 3.6 Supplementary material ...... 79

Chapter 4: Foraging niche overlap during chick-rearing in the sexually dimorphic Westland petrel ...... 83 4.1 Abstract ...... 84 4.2 Introduction ...... 85 4.3 Materials and methods ...... 88 4.3.1 Study site and field procedures ...... 88 4.3.2 Data processing and statistical analyses ...... 89 4.4 Results ...... 93 4.4.1 At-sea movements and activity budgets ...... 93 4.4.2 Fine-scale foraging behaviour ...... 98 4.5 Discussion ...... 102 4.5.1 At-sea movements and activity budget ...... 102 4.5.2 Foraging behaviour and trophic niche ...... 104 4.6 Supplementary material ...... 109 Chapter 5: Niche segregation in New Zealand winter breeding seabirds ...... 113 5.1 Abstract ...... 114 5.2 Introduction ...... 115 5.3 Materials and methods ...... 118 5.3.1 Study sites and field procedures ...... 118 5.3.2 Data processing and statistical analyses ...... 119 5.4 Results ...... 121 5.4.1 At-sea movements...... 121 5.4.2 Temporal pattern of foraging and diving behaviour ...... 124 5.4.3 Diet and isotopic niche ...... 125 5.5 Discussion ...... 128 Chapter 6: General Discussion ...... 132 6.1 Foraging patterns of winter- and summer- breeding species ...... 133 6.2 Marine trophic resource in winter around New Zealand ...... 138 6.3 Relation between winter-foraging and winter-breeding ...... 139 6.4 Perspectives and future research ...... 143 Literature cited ...... 144

List of tables

Table 1-1: Seabird species from temperate and polar regions with part of their breeding cycle occurring in winter, hereafter called winter breeders...... 11

Table 2-1: Logger deployments on Fiordland penguins at Taumaka / Open Bay Island, New Zealand, and their GPS trip metrics according to the breeding stages (Mean ± SE)...... 28

Table 2-2: Summary of the models’ outputs used to assess the trends in foraging trips parameters of breeding Fiordland penguin at Taumaka / Open Bay Island...... 30

Table 2-3: Summary of the diving behaviour of 23 Fiordland penguins (25 trips including 23172 dives) provisioning chicks at Taumaka / Open bay Island, New Zealand...... 33

Table 2-4: Summary of the generalised additive mixed models (GAMMs) outputs used to assess the trends in the diving behaviour of Fiordland penguin provisioning chicks at Taumaka / Open Bay Island...... 34

Table 2-5: Comparison of breeding and foraging parameters among the Eudyptes . .... 39

Table 3-1. Summary of the linear mixed models (LMMs) outputs used to assess the trends in activity budget and foraging trip parameters of breeding southern Buller’s albatross at Hautere/Solander Island...... 61

Table 3-2 : Activity patterns during southern Buller’s albatross foraging trips and associated vectorial dynamic body acceleration (VeDBA) values (mean ± SE) sampled at post-guard stage (n = 26 individuals / 64 trips / 3700 h at sea)...... 64

Table 3-3 : Summary of the models outputs used to assess the trends in foraging behaviour of breeding southern Buller’s albatross at Hautere/Solander Island...... 66

Table 3-4. Isotopic values (whole blood, Mean ± SD) of males and females southern Buller’s provisioning chick at Hautere/Solander island recorded in 2016 and 2017. Their isotopic niche widths are reported for the corrected standard ellipse area (SEAc) and Bayesian standard ellipse area (SEAB)...... 70

Table 3-5. Comparative activity pattern (percentage of time, mean ± SD) of albatrosses tracked with activity-recorder loggers...... 74

Table 4-1 : Logger deployments on Westland petrels and their GPS trip metrics during post- guard stage (mean SE)...... 93

Table 4-2 : Sexual size dimorphism in morphometric measurements of genetically sexed Westland petrels tracked during rearing chick in 2016 and 2017, showed by the Storer’s dimorphism index (SDI = 100 x (mean ♂ – mean ♀)/(mean ♂ + mean ♀) x 0.5)...... 94

Table 4-3 : Summary of the generalised additive mixed models (GAMMs) outputs used to assess the trends in the at-sea behaviour of Westland petrel provisioning chick at Punakaiki, New Zealand...... 96

Table 4-4 : Summary of the generalised additive mixed models (GAMMs) outputs used to assess the oceanographic variables influencing the foraging of Westland petrel provisioning chick at Punakaiki, New Zealand...... 99

Table 4-5: Isotopic values (whole blood, Mean ± SD) of males and females Westland petrels provisioning chick in 2016 and 2017...... 101

Table 5-1: Number of individuals with GPS, dive, acceleration data and blood samples collected during each year of the study...... 122

Table 5-2: Spatial overlap between winter breeding species for home range (kernel 95%) and focal area (kernel 50%, in italic) estimated using Bhattacharyya’s affinity index (0=no overlap, 1=complete overlap)...... 122

Table 5-3: Isotopic values (whole blood, mean SD) of the winter breeding species provisioning chicks off the west coast of New Zealand’s South Island in 2016 and 2017...... 128

List of figures

Figure 1-1: Illustration of the seasonality and the match / mismatch hypothesis using the Great tit Parus major as predator and caterpillars as prey...... 3

Figure 1-2 : Seabird species richness across latitudinal gradient with regards of the breeding phenology...... 9

Figure 2-1 : Fiordland penguins’ foraging trips from Taumaka / Open Bay Island expressed as standardised time spent in area within 0.01° cells during the different breeding stages...... 29

Figure 2-2 : Typical Fiordland penguin dive profile (in blue) along a two-days foraging trip, overlaid with the bathymetry (dotted pattern below) and the period of the day (dawn and dusk represented by light grey shaded areas, night-time by dark grey shaded areas)...... 32

Figure 2-3: Temporal variation of dive parameters calculated on hourly basis, predicted by GAMMs...... 35

Figure 2-4: Isotopic niche of breeding Fiordland penguins (n=53) shown by the 40% standard ellipse areas corrected for sample size (SEAc), represented by breeding stages and years. .... 36

Figure 3-1 : At-sea movements of breeding southern Buller’s albatross (males in orange, females in yellow) during the post-guard stage at Hautere/Solander Island in 2016 and 2017...... 60

Figure 3-2 : Foraging strategies used by southern Buller’s albatrosses over several successive foraging trips...... 63

Figure 3-3 : Temporal distribution of average (mean ± SE) foraging time (orange) and landing rate (blue) during foraging trips of southern Buller’s albatross provisioning chick...... 64

Figure 3-4 : Influence of oceanographic variables on the standardised time spent foraging of southern Buller’s albatross predicted by generalised additive mixed model (GAMM) during post-guard stage at Hautere/Solander Island. The grey area indicates the 95 % confidence interval...... 68

Figure 3-5 : Isotopic niche (from whole blood) of breeding southern Buller’s albatrosses provisioning chick at Hautere/Solander island, represented by the 40 % corrected standard ellipse area (SEAc) ...... 70

Figure 4-1 : At-sea movements of breeding Westland petrel (males in orange, females in yellow) during the post-guard stage, from Punakaiki...... 95

Figure 4-2 : Distribution of the foraging trip durations of chick-rearing Westland petrels. ... 95

Figure 4-3 : Temporal variation of the at-sea time activity budget of Westland petrel...... 97

Figure 4-4 : Relationship between the time spent foraging in area by Westland petrel provisioning chick and influencing oceanographic parameters modelled by generalized additive mixed model (GAMM)...... 100

Figure 4-5: Isotopic values and niche of breeding Westland petrel...... 101

Figure 5-1: Spatial overlap between winter-breeding species on the west coast of New Zealand’s South Island during 2016 (up) and 2017 (below)...... 123

Figure 5-2: Time spent foraging along the time of the day by tracked winter breeding species. The areas in dark grey indicate the night, in light grey the dusk and dawn (nautical twilight)...... 124

Figure 5-3: Comparison of diving range (vertical line), mean dive depth (point) and standard error (horizontal line) for tracked winter breeding species...... 125

Figure 5-4: Dietary overlap among the winter breeding community off the west coast of New Zealand’s South Island represented by non-metric multidimensional scaling (NMDS), with convex hulls (when n > 2 studies) or lines (when n = 2 studies) coloured by species...... 126

Figure 5-5: Isotopic results of winter breeding species provisioning chicks. Individuals’ signatures are shown by the dots, and the isotopic niches by the 40% standard ellipse areas ...... 127

Figure 6-1 : Breeding distribution and colony sizes of summer-breeding New Zealand seabirds...... 135

Figure 6-2: Breeding distribution and colony sizes of winter-breeding New Zealand seabirds. Note the difference of scale in the dots size area compared with the summer-breeding figure...... 136

Chapter 1:

General introduction

1.1 Foraging and breeding: the essentials of life

Any organisms living on Earth undergo the influence of various biotic and abiotic environmental stressors, affecting their physiology and behaviour (Killen et al. 2013). Acting in interaction over time, these ongoing constraints have deleterious impacts on an individual’s inability to cope with them. Thereby, they constitute natural selection pressure (Darwin 1859), limiting population size within the environment’s carrying capacity by different processes.

During an animal life cycle, the early-life mortality reduces the number of young reaching maturity (Daunt et al. 2007, Orgeret et al. 2016). Fully-grown adults still have to survive, and in addition, to compete for mates to engage in breeding attempts (Clutton-Brock 2007). As energy requirements peak for adults engaged in parental care (Hirshfield & Tinkle 1975, Liu et al. 2003), only the fittest will be able to rear healthy offspring. Being successful in survival, growth, investment in reproduction and genome transmission (Pianka 1981) requires qualities to satisfy these energetic needs by acquiring sufficient trophic resources. Wild animals achieve this trophic resource acquisition by an adjusted foraging behaviour, that conditions all the animal activities within their environment, and therefore, plays a key role in their biology

(Hughes 2009).

Among the environmental variations that species have to face annually, seasonality is amongst the most pronounced (Haury et al. 1978). In temperate and polar regions, the cycles of spring, summer, autumn and winter alter drastically both climatic conditions and food availability. Typically, the mild spring and hot summer increases primary production on land and at sea (Cramer et al. 1999, Behrenfeld et al. 2005). In contrast, autumn and winter undergoes a reduction in primary production as temperature and day length decrease. These conditions expose the consumers and their predators higher in the food chain (Daly & Smith Jr

1993) to food restrictions combined with energy stringency (Weathers & Sullivan 1993,

Pravosudov et al. 1999).

Predators can face the harsh winter environmental conditions and food restrictions with different strategies. Mobile species can mitigate these conditions by moving to more favourable areas for wintering (Berger 2004, Alonso et al. 2008, Chapman et al. 2015). However, resident species have to endure the winter conditions with physiological, morphological and/or behavioural adaptations. For instance, antifreeze production (Goddard et al. 1992, Duman

2015), hypo metabolism during hibernation and daily torpor (Heldmaier et al. 2004), insulation for low thermal conductance (Hart 1956), body fat reserves and passive rewarming (Signer et al. 2011), altitude change (Mysterud 1999), increased foraging effort (Systad et al. 2000,

Grémillet et al. 2005), or social grouping (Vincent et al. 1995, Gardner 2004) can be used in response to the severity of conditions. Nonetheless, winter is reported as a challenging period that increases mortality (Jansson et al. 1981, Barrett 1982, Hurst 2007).

Most species cannot afford the cost of reproduction during such challenging periods.

Instead, their energy-demanding activities have to match a trophic resource availability peak

(Lack 1954, Perrins 1970, Cushing 1990, Regular et al. 2014) to be successful. Although partially genetically inherited (Gienapp et al. 2013), population dynamics are primarily synchronized by environmental conditions (Post & Forchhammer 2002, Visser et al. 2009) explaining the seasonal characteristic of breeding (Svensson 1997) and its optimal timing (Lack

1968, Tarwater & Beissinger 2013) occurring usually in spring/summer (Figure 1-1). The selective pressures on parental foraging and on offspring fitness at this time reflect the degree

2 of adaptation of a species to its environment and, thus, are considered major life history traits

(Both & Visser 2005).

Figure 1-1: Illustration of the seasonality and the match / mismatch hypothesis using the Great tit Parus major as predator and caterpillars as prey. Adapted from Durant et al. (2007).

3

This is especially the case for , which have to maintain the highest core body temperature of any endotherm (Nagy 1987) while their size constrains the amount of energy they can store (Calder 1974) and extra mass impairs their flight. With limited body reserves, most of them are considered income breeding species (Jönsson 1997), which have to fuel the cost of reproduction through concomitant foraging. In addition, their central place foraging behaviour (Orians 1979) during reproduction, involves extra-cost from regular commuting movements between foraging areas and nest, according to the chick fasting capacity (Phillips

& Hamer 1999). These constraints strongly differ from those experienced by capital breeding species, which can store body reserves and decouple resource acquisition and utilisation.

Hence, the energy constraint from the competing costs of thermoregulation, energy assimilation, growth and reproduction is a major factor in shaping life history (Zera &

Harshman 2001), and making them more sensitive to real time food availability than other animals.

1.2 Seabird foraging

Birds represent 9,990 species in the world (Chapman 2009), including 359 species relying on marine habitats: the seabirds (Dias et al. 2019). They inhabit all seas and oceans which cover

71 % of the earth’s surface, from which they consume millions of tonnes of prey annually

(Guinet et al. 1996, Furness 2003, Brooke 2004). As major consumers of marine resources, they play an important role in the nutrients and carbon cycles (Huntley et al. 1991). Seabird species are classified in 23 families occupying a wide range of ecological niches, feeding at most trophic levels of the food web (Schreiber 2001). Their prey include passively swimming planktonic and actively swimming nektonic organisms (Haeckel 1890) such as fish, and cephalopods (Cherel & Klages 1998), (Hedd & Gales 2001) and

(Thiebot et al. 2017). Seabirds are visual foragers feeding primarily in the upper ocean photic

4 zone (0 – 200 m deep, where is concentrated) by surface seizing, surface plunging, pursuit plunging, pursuit diving, aerial pursuit or scavenging (Nelson 1979).

Seabirds live in a highly spatio-temporally variable environment, constantly in motion with coupled hydrodynamic and atmospheric processes, that can change the prey availability over short periods of time (Haury et al. 1978). In addition, wet seabirds undergo greater heat loss with thermal conductance decreased by 2 – 5 fold (Kooyman et al. 1976, de Vries & van Eerden

1995) while maintaining an internal body temperature at 39 – 40 °C (Wilson et al. 1992,

Gremillet et al. 1995). Insulated by trapped air between feathers (Grémillet et al. 1998b,

Ponganis 2015), diving species also propel against their own buoyancy to dive (Wilson et al.

1992, Watanuki et al. 2003), increasing their foraging energy costs. Seabirds also differ from many terrestrial birds by a unique array of life history traits such as low fecundity, long lifespan, delayed sexual maturity and senescence (Ricklefs 1998), in association with quasi-exclusive colonial breeding (Siegel-Causey & Kharitonov 1990).

These extreme life history traits, linked to a “K” reproductive strategy (Dobzhansky 1950,

MacArthur & Wilson 1967), show a low energy investment in offspring. Under this strategy, parents facing higher effort or physiological stress favour their own fitness at the expense of the offspring (Sæther et al. 1993, Kidawa et al. 2017, Kloskowski 2019). Conversely, they can lose weight to support the chick provisioning (Croll et al. 1991, Golet et al. 1998); indicating the presence of an energy conflict while breeding (Clark & Ydenberg 1990). Alternating between short and long foraging trips during chick provisioning has been reported to satisfy this trade-off, with long trips dedicated to body maintenance and short trips for maximising chick feeding (Chaurand & Weimerskirch 1994, Ropert-Coudert et al. 2004) or the opposite

(Carpenter-Kling et al. 2017). Their acute cost of reproduction is classically attributed to the heterogeneity and unpredictability of marine prey within their foraging range (Ashmole 1963,

Lack 1968, Dobson & Jouventin 2006). However, some marine features remain predictable at

5 large scale (Weimerskirch 2007) and seabirds can use them as cues to optimize their foraging

(Macarthur & Pianka 1966).

The search for prey can be divided into two phases, the approach and the detection

(Bartumeus & Catalan 2009). The approach starts at the departure from the colony, when individuals can choose to go to a known area from previous experience (Kotzerka et al. 2011,

Regular et al. 2013, Votier et al. 2017), or to follow the direction of returning successful birds

(Davoren et al. 2003, Weimerskirch et al. 2010). Once at sea, these visual predators actively take sensory information all along their trip, not only with their vision, but also from the olfaction (Verheyden & Jouventin 1994, Nevitt et al. 2004). Observational studies have shown the ability of seabirds to sense large-scale environmental gradients that characterise oceanic frontal zones (Pocklington 1979, Kuroda 1991) and bathymetric features (Haney et al. 1995), where the sea surface temperature, and seabird distributions are correlated

(Pakhomov & McQuaid 1996). Indeed, these areas can create favourable conditions under different processes (the ocean triad, Bakun 1996): enrichment, with water mixing increasing the local productivity, concentration, with convergent currents aggregating exogenous prey, and retention, with gyral circulation keeping planktonic item within an area).

With the development of animal-borne data loggers and environment satellite-remote sensing, tracking studies coupled to oceanographic data have advanced our understanding of the complex prey/seabird interaction (Fauchald 2009). The search approach occurs at meso- scale (10 – 100 km) in a moving mosaic of hydrodynamic processes, influencing both prey populations (Haury et al. 1978, Barry & Dayton 1991) and predator movement costs (Wilson et al. 2012, Elliott et al. 2014, Masello et al. 2017). Breeders (e.g. experienced individuals) have been reported to select the edges of geostrophic eddies (Nel et al. 2001, Tew Kai et al.

2009, Bon et al. 2015), frontal activity (Grecian et al. 2018) and internal waves (Haney 1987).

Foraging in these conditions, predators increase their energy gain (Godø et al. 2012, Abrahms

6 et al. 2018). Ephemeral sub meso-scale turbulences (0 – 10 km) locally change the structure of the ecosystem within hours (Lévy et al. 2012) and trigger a refinement of an individual’s approach (Sabarros et al. 2014) to maximise prey detection. The search effort is increased for flying and surface feeding species by horizontal path sinuosity (Fauchald & Tveraa 2003).

Diving species increase their vertical sinuosity, with dive rate (Boyd et al. 1994) and oscillations during the dives (Bost et al. 2007). Ultimately, both techniques increase the time spent by the predator in productive prey patches (Warwick-Evans et al. 2015). In addition, the presence of prey can be revealed by local enhancement with association with conspecifics

(Watanuki et al. 2008, Tremblay et al. 2014, Sutton et al. 2015), interaction with heterospecifics

(Sakamoto et al. 2009b, Wells et al. 2016) as well as fishing vessels (Votier et al. 2013, Collet et al. 2015).

1.3 Timing of breeding in seabirds

Such hierarchical reliance on the water mass properties constrains and helps seabirds to locate food across seasons. While tropical waters have invariable sea surface temperature and low oceanic densities (Johannes 1978), temperate and polar waters alternate seasonally predictable periods of higher temperature and food abundance with periods of lower temperature and food scarcity when net energy losses may occur (Shuter & Post 1990). Despite these food supply variations, temperate and polar regions still host the greatest diversity of seabirds with 257 species (e.g. 74 % of global species, Croxall et al. 2012). A vast majority

(220 species, 489 million individuals) breed with a schedule matching the most favourable time in summer, hereafter called summer-breeding species. For them, a phenological mismatch with prey availability results in reduced breeding success with deleterious demographic consequences (Regehr & Montevecchi 1997, Hipfner 2008). Too early or too late, mismatched breeders and their fledglings would face sub-optimal conditions (Regular et al. 2014) towards the autumn and winter, presenting a number of challenges.

7

At sea, autumn and winter conditions cool the surface temperature (Chiswell 1994), forcing seabirds to increase their metabolism (Bevan & Butler 1992, Croll & McLaren 1993). Colder water also modifies the surface layer stratification (Garner 1969) and deepens the mixed layer

(Condie & Dunn 2006) with structural consequences in the prey field for seabirds (Charrassin

& Bost 2001). With lower primary productivity and higher fish mortality (Crisp 1964), food is expected to be less abundant. More frequent and more powerful storms (Allan et al. 2009) can also depress the foraging success of surface foraging species (Sagar & Sagar 1989). Altogether, these challenging conditions can induce an energetic bottleneck (Fort et al. 2009) affecting individuals by immediate reduction of their immune-competence (Svensson et al. 1998) and survival (Reid 1987, Barbraud & Weimerskirch 2003), and sometimes cause catastrophic wreck events at the population level (Underwood & Stowe 1984, Harris & Wanless 1996,

Jamieson et al. 2016). Winter conditions can also have carry-over effects on seabird fitness, influencing outcomes in the next breeding season (Harrison et al. 2011, Salton et al. 2015).

Hence, most seabird species complete their breeding cycle before winter, which is either avoided by trans-equatorial migrations (González-Solís et al. 2007, Guilford et al. 2009), buffered by longitudinal migrations (Thiebot et al. 2011), or endured by resident species released from demanding activities (Collins et al. 1999, Hedd & Gales 2005).

Paradoxically, a minority of seabird species support breeding duties (e.g. incubation or chick rearing) during winter months, hereafter called winter-breeding species. They occur mainly in the southern hemisphere (Figure 1-2).

8

Figure 1-2 : Seabird species richness across latitudinal gradient with regards of the breeding phenology.

These 34 winter-breeding species (30 million individuals) have part or all of their breeding cycle occurring during the winter months. Hence, this count includes species with different breeding cycles: those starting to breed in summer with an extended breeding cycle through the rest of the year; those breeding asynchronously throughout the year; and those with breeding onset scheduled during the winter season. These winter-breeding species are found among the Procellaridae, Diomedeidae, Phalacrocoracidae, Spheniscidae, Laridae and

Alcidae families (Table 1-1).

9

Family Latin name IUCN Hemisphere Species red list New Zealand of Winter-breeding justification Common name category status (2016) occurrence (2018)

Diomedeidae Black-footed albatross Phoebastria nigripes N Brooding in Jan – Feb (Hyrenbach & Dotson 2003) NT - Short-tailed albatross Phoebastria albatrus N Hatching Dec – Jan + 155 d for fledging VU - Diomedea exulans S Hatching Mar – Apr + 283 d for fledging VU -

Antipodean albatross Diomedea antipodensis S Hatching Mar – Apr + 240 d for fledging EN nationally critical

Amsterdam albatross Diomedea amsterdamensis S Hatching May + 235 d for fledging EN -

Tristan albatross Diomedea dabbenena S Hatching Mar, fledging in Nov (Cuthbert et al. 2004) CR - Diomedea sandfordi S Hatching Jan – Feb + 236 d for fledging (Richdale 1952) EN naturally uncommon

Southern royal albatross Diomedea epomorpha S Hatching Feb – Mar + 236 d for fledging (Tickell 1968) VU naturally uncommon Southern Buller’s albatross Diomedea bulleri bulleri S Hatching Mar – Apr + 167 d for fledging (Sagar 1998) NT naturally uncommon

Phalacrocoracidae Crowned cormorant Phalacrocorax coronatus S Breeds throughout the year (Rand 1960) NT - Little Pied cormorant Microcarbo melanoleucos S Nesting begins Jul – Aug (Taylor 2013) NT - Bank cormorant Phalacrocorax neglectus S Breeding extends from May – Oct (Crawford et al. 1999) EN -

Black-faced cormorant Phalacrocorax fuscescens S Egg laying peak in Jul (Taylor et al. 2012) LC -

Pied cormorant Phalacrocorax varius S Clutches laid in all months (Powlesland 2013) LC recovering Great cormorant Phalacrocorax carbo N, S Clutches laid autumn - winter in New Zealand (Powlesland 2013) LC naturally uncommon

New Zealand king shag Phalacrocorax S Breeding Mar – Sep (Schuckard 1994) VU nationally endangered carunculatus

Spotted shag Stictocarbo punctatus S Egg laying in Aug (Turbott 1956) LC not threatened

Spheniscidae King penguin Aptenodytes patagonicus S Breeding cycle lasting 400 days (Ancel 2013) LC -

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Emperor penguin Aptenodytes forsteri S Breeding cycle lasting 300 days (Ancel 2013) NT -

Gentoo penguin Pygoscelis papua S Northern populations laying in early winter (Bost & Jouventin 1990) LC - Fiordland penguin Eudyptes pachyrhynchus S Egg laying in Jul – Aug (Warham 1974) VU nationally vulnerable

Little penguin Eudyptula minor S Egg laying in Jul – Aug (Heber et al. 2008) LC at risk

African penguin Spheniscus demersus S Nesting May – Sep (Crawford et al. 1999) EN -

Procellariidae Northern giant petrel Macronectes halli S Egg laying in Aug (Marchant and Higgins 1990) LC recovering Bermuda petrel Pterodroma cahow N Egg laying in Dec – Jan (Madeiros et al. 2012) EN -

Atlantic petrel Pterodroma incerta S Egg laying in Jun – Jul (Klages & Cooper 1997) EN - Great-winged petrel Pterodroma macroptera S Egg laying in Jun – Jul (Imber 1976) LC not threatened

Providence petrel Pterodroma solandri S Hatching mid-Jul (Bester et al. 2007) VU -

Westland petrel Procellaria westlandica S Chick-rearing in Aug-Oct (Freeman 1998) EN naturally uncommon Grey petrel Procellaria cinerea S Chick-rearing in May - Jun (Zotier 1990) NT naturally uncommon

Little Puffinus assimilis S Egg laying in Jun – Aug (Booth et al. 2000) LC recovering

Common Pelecanoides urinatrix S Egg laying in Jul – Aug (Marchant & Higgins 1990) LC not threatened

Laridae King gull Larus hartlaubii S Breeding year-round (Williams et al. 1990) LC -

Alcidae Cassin’s Aucklet Ptychoramphus aleuticus N Egg laying in Dec - Jun (Whitworth et al. 2015) NT - Table 1-1: Seabird species from temperate and polar regions with part of their breeding cycle occurring in winter, hereafter called winter breeders. S and N indicate respectively the southern and northern hemisphere. LC, NT, VU, EN and CR stand respectively for Least Concern, Near threatened, Vulnerable, Endangered and Critically endangered.

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1.4 New Zealand, a hotspot for winter-breeding seabirds

One of the 25 world-wide biodiversity hotspots is located in New Zealand (Myers et al.

2000). Originally part of the Gondwana supercontinent, Australia and New Zealand have been separated by the opening of the Tasman Sea (~ 80 Ma years ago, Molnar et al. 1975). Since then, collisional tectonism, crustal thickening and volcanic activity have progressively lifted the land mass and shaped this archipelago (Hicks & Campbell 2012). The surrounding marine environment evolved as well when Tasmania separated from (40 ± 5 Ma ago), creating a cold water flow coming from the South Indian Ocean when seabirds already existed

(Fordyce & Jones 1990, Nelson & Cooke 2001). Subsequently, the Drake Passage opening between Antarctica and South America (30 ± 5 Ma ago) strengthened the presence of oceanic fronts with the Antarctic Circumpolar Current (ACC, Deacon 1982, Orsi et al. 1995, Rintoul et al. 2001). Lately, the Quaternary glacial – interglacial cycles have affected the ice cover on land, the sea level, the current flow and the front’s positions (Darvill et al. 2016).

Currently, the New Zealand archipelago ranges between 29 - 52° S and 166 - 174° E, at the interface of the ACC and the South Pacific gyre. Its surrounding marine realm is characterised by zonal belts of warm, cool and cold surface waters, separated by oceanic fronts marking sharp changes in vertical water structure, temperature, salinity and nutrients: the subtropical front at 43 – 45° S, the front at 50° S and the Polar front at 60° S (Heath 1985).

These fronts and the ACC interact with the submarine relief (Butler et al. 1992) along their way on the great ocean conveyor belt (Broecker 1991). The archipelago, settled by humans with the consecutive arrivals of Polynesian (1280) and European migrants (1769), underwent drastic landscape modification and invasive mammal introductions that caused species extinctions (Wilmshurst et al. 2008).

Despite these losses, New Zealand remains a biodiversity hotspot with high endemism for both terrestrial and marine biodiversity. Indeed, its waters host 56 marine mammal taxa out of

12 the 120 species listed worldwide (Schipper et al. 2008, Baker et al. 2010), and the largest seabird assemblage worldwide with 78 species, including 33 endemic (Croxall et al. 2012).

Whereas winter-breeding occurs in the entire , the winter-breeding species richness differs geographically: 12 species occur in the southern Atlantic sector, against 8 species in the southern Indian sector, and 21 in the southern Pacific sector. New Zealand archipelago stands out for hosting the greatest concentration (17 species), where the highest density occurs on the New Zealand South Island with 10 species.

During winter, most species migrated out the New Zealand waters by trans-equatorial migrations towards the North Pacific (Shaffer et al. 2006), latitudinal migrations towards South

America (Deppe 2012, Rayner et al. 2012) or in Southern Ocean frontal zones (NIWA 2016).

These migrations result in a drop of breeding seabirds numbers from > 43 million individuals in summer to < 3 million in winter (NZ Bird online 2019). How these winter-breeding species are able to sustain the cost of reproduction during the apparent challenging winter, while others species migrate to survive, is poorly understood. Learning about such fundamental biological processes is crucial to understanding the evolutionary costs and benefits of winter-breeding.

Although the nesting sites of winter-breeding species are scattered on New Zealand in coastal areas with phylogeographic partitioning (Rawlence et al. 2014), at sea, several reports indicate some overlap of their foraging range. Particularly, the waters off the west coast of New

Zealand’s South Island are reported to be used by the highest concentration of winter-breeding species. In this area, five species are reported to breed and forage: the Westland petrel

Procellaria westlandica (Freeman et al. 1997, Waugh et al. 2018), the Little penguin Eudyptula minor (Heber et al. 2008), the Fiordland penguin Eudyptes pachyrhynchus (Warham 1974), the southern Buller’s albatross Thalassarche bulleri bulleri (Sagar & Weimerskirch 1996, Stahl &

Sagar 2000a, Stahl & Sagar 2000b) and the Spotted shag Phalacrocorax punctatus (Heather &

Robertson 2000). Diet studies indicate that these species all feed on fish, cephalopod and

13 with common prey taxa (Van Heezik 1989, Freeman 1998, James & Stahl 2000,

Flemming et al. 2013).

1.5 Research objectives and thesis structure

Understanding how New Zealand’s winter-breeding seabird species meet the high food requirements of reproduction (Gremillet et al. 1995) with intra- and inter-specific overlaps is crucial to validate or invalidate the match / mismatch hypothesis during winter. Seasonal variations of the environment usually lead seabirds to increase their foraging effort in response to food depletion (Salamolard & Weimerskirch 1993). For example, the breeding King penguin

Aptenodytes patagonicus feed on myctophid fish during summer, but dive deeper during the winter and shift diet towards squids (Cherel et al. 1996, Charrassin et al. 2002). Hence, we can expect winter-breeding species to forage with more effort than do the summer-breeding species in times of prey availability peak.

The alternative hypothesis could be a match with winter prey resources around New

Zealand, reflecting a particular ecosystem functioning on which winter-breeding seabirds specialised. Besides, predators have to adapt not only to the prey presence, but also to their accessibility, dictated by the environment physical conditions. In this case, the reduced winter day length is expected to constrain these visuals foragers to modify their foraging behaviour

(Kirkwood & Robertson 1997b, Systad et al. 2000, Daunt et al. 2006). In addition, the niche theory (Hutchinson 1959) and the competitive exclusion principle (Hardin 1960), postulate that ecologically similar species are expected to realise niche partitioning to reduce inter-specific competition, allowing species to coexist in sympatry (Macarthur 1958, Pianka 2002). However, there are off the west coast of New Zealand’s South Islands some evidences of temporal, spatial and trophic overlaps.

14

Despite some previous knowledge on the Westland petrel, little penguin, Fiordland penguin and southern Buller’s albatross foraging areas and prey, these species with small populations, concerning (Table 1-1) and living in an environment likely to be substantially affected by global change (Matear et al. 2013), remain poorly known in regards of the biological and ecological factors influencing their foraging behaviour, habitat use and niche segregation in winter.

Therefore, the objectives of this thesis were to: 1) describe the fine-scale foraging behaviour of winter-breeding species from the west coast of New Zealand’s South Island,

2) investigate the intrinsic and extrinsic factors driving their foraging, and 3) quantify their niche overlap as they exploit similar areas during elevated energetically demand.

To achieve these objectives, multi-disciplinary data were obtained from winter-breeding species engaged in reproduction and known to exploit the waters off the west coast of New

Zealand’s South Island. Particularly, information on horizontal at-sea movements, water column usage, activity budget and their related trophic niche were investigated using animal- borne data loggers and blood samples. Fine-scale data were gathered in order to improve the resolution of the knowledge and identify the main factors influencing their foraging behaviour during winter conditions. This thesis is structured with the central chapters reporting specific studies that have been submitted to, or published, in peer-reviewed journals.

Chapter 2 addressed the study objectives on the guild of divers, able to use the water column vertically. Among penguins of the Eudyptes genus, the Fiordland penguin is the only one to breed as early as winter (Warham 1974).

Chapter 3 investigated the guild of the surface feeders, with the study case of the southern

Buller’s albatross, the only Thalassarche among its genus to lay in autumn and to rear its chick entirely through the austral winter.

15

Chapter 4 focused on a Procellariform species able to use both surface feeding and diving, the Westland petrel. When others Procellaria congenerics are undertaking long-distance foraging trips to provision offspring (Péron et al. 2010), this large species stays surprisingly close to the colony with an apparent lack of sexual segregation during the austral winter

(Waugh et al. 2018).

While previous chapters reported species-specific investigations of their foraging behaviour at fine-scale, Chapter 5 was dedicated to include this new knowledge on these endemic and synchronous breeding species, in order to quantify the niche segregation. Additional data from published literature on little penguin and spotted shag were also incorporated in order to assess and quantify potential niche segregation of these winter-breeding seabird community.

Finally, in the General Discussion (Chapter 6), the new insights gained from the preceding chapters were used to discuss the costs benefits of the winter breeding strategy.

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Chapter 2:

Foraging ecology of a winter breeder,

the Fiordland penguin

A version of this chapter has been published as:

Timothée A Poupart, Susan M Waugh, Charles A Bost, Akiko Kato, Colin M Miskelly, Karyne

M Rodgers, John PY Arnould (2019). Foraging ecology of a winter breeder, the Fiordland penguin. Mar Ecol Prog Ser 614:183-197. https://doi.org/10.3354/meps12910

17

2.1 Abstract

Breeding in most species is timed to coincide with the greatest availability of food resources to support the increased energetic needs of reproduction. Correspondingly, the majority (76 %) of seabird species in temperate and polar regions breed in spring/summer, matching the peak in ocean productivity. The Fiordland penguin (Eudyptes pachyrhynchus) is one of the only 34 seabird species worldwide that have part of their breeding cycle during the winter, and its chicks fledge when congeneric Eudyptes species in the same region are only starting to hatch eggs. Little is known of the foraging ecology of this species and the factors that may influence its timing of breeding. In the present study, the foraging behaviour of breeding individuals from

Taumaka / Open Bay Island, New Zealand, was investigated using GPS, dive recorder and tri- axis accelerometer data loggers. A total of 35 (4 males, 31 females) individuals was tracked at sea, revealing extensive use of continental shelf slope (200-1000 m) habitat within 42 ± 5 km of the colony. Individuals foraged mostly during daylight in the epi-pelagic zone (mean modal depth 22 ± 2 m) and prey encounter events occurred in 50 % of dives. Blood isotopic signatures suggest a trophic level indicative of consumption, supporting previous findings that winter-spawning squid are the most important prey type. The results of the present study suggest that a winter-breeding strategy by seabirds can reflect locally abundant prey resources and suitable conditions at the time for breeding.

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2.2 Introduction

The survival of any animal depends on its capacity to match food intake to energy requirements. Throughout the life cycle, energy requirements vary and environmental fluctuations alter food availability. Energetically demanding activities, such as reproduction

(Speakman 2008) are, thus, restricted to favourable times. Income-breeder species fuelling their reproductive investment with current trophic intake (Stearns 1989) have a breeding schedule synchronised with the time of the year giving the best chance of survival to the offspring (Lack 1954, Perrins 1970). This timing is typically a fixed life history trait, and is considered an adaptive evolutionary response to the predominant environmental conditions.

In temperate and polar environments, contrasting seasons throughout the year lead to variability in primary production. At sea, the warmer conditions and longer day-length during spring and summer enhance blooms, which support a cascade of large biomasses in primary and secondary consumers (Bradford-Grieve et al. 1993, Verity & Smetacek 1996) providing an important food resource for pelagic fish and higher predators. In contrast, the primary production is reduced in autumn, with a minimum in winter (Behrenfeld et al. 2005,

Alvain et al. 2008), making this period unfavourable for heterotrophic organisms.

Correspondingly, in temperate and polar latitudes, breeding activities of predators are typically scheduled in spring and summer to coincide with favourable environmental conditions.

Seabirds (359 species, Dias et al. 2019) are among the most numerous marine predators, and play a key role within marine food webs (Brooke 2004). Their colonial breeding and central- place foraging habits, coupled with the increased energetic costs of chick rearing, can lead to a total predator demand of > 200 tons·km-1·year-1 (Murphy 1995) during summer.

Consequently, the timing of reproduction in seabirds is closely linked to the temporal and spatial productivity of oceanic features (Bost et al. 2009) and, correspondingly, the vast majority of polar and temperate seabirds breed in summer (197 species, ca 481 million individuals). In contrast, breeding in winter (i.e. incubation or chick rearing during the winter

19 months) occurs in only 34 species (ca 30 million individuals; Croxall et al 2012).

Winter is considered a period of reduced prey availability and harsh environmental conditions for seabirds (Newton 1998) that induce an energetic bottleneck, often leading to increased mortality (Camphuysen et al. 1999). Correspondingly, most temperate and polar seabirds avoid these negative effects through migration towards more beneficial areas for their non-breeding period (Shaffer et al. 2006, Guilford et al. 2009)). Resident species have to buffer these challenging conditions and compensate for the shorter day length with nocturnal foraging

(Systad et al. 2000, Daunt et al. 2006). Paradoxically, winter-breeding species endure these conditions while experiencing the additional demands of reproduction (Salamolard &

Weimerskirch 1993, Charrassin et al. 2002). Seasonal studies have reported penguins dive longer and deeper in winter than summer (Green et al. 2005), with associated changes in diet, while feeding a chick during winter (Charrassin et al. 2002). However, little is known of the biological and ecological factors influencing winter-breeding or its energetic and reproductive consequences on seabirds (Zotier 1990).

The largest winter-breeding seabird community in the world is found in New Zealand, with

17 species of winter-breeding procellariforms, cormorants and penguins (Croxall et al. 2012).

It includes the Fiordland penguin (Eudyptes pachyrynchus) which is endemic to the coast and offshore islands of the south-west of the South Island. Unique within its genus, the breeding cycle of the species starts during the austral winter (Warham 1974), with egg laying occurring in July/August and the chick-fledging period starts in late spring when congenerics at similar latitudes are just starting to hatch (Garcia-Borboroglu & Boersma 2013). The small population of < 7,000 individuals nests in loose aggregations containing fewer than 10 pairs, dispersed over long stretches of coastline in dense vegetation, overhangs and small caves. This is in contrast to other Eudyptes species, which breed in very large colonies at high nesting densities in open spaces.

Given the apparent challenge of winter breeding and its small population, the Fiordland

20 penguin may experience reduced food availability during reproduction, and may have to compensate for such conditions by increasing its foraging range and expend an increased effort

(e.g. higher dive rate, deeper, longer and anaerobic dives) compared to its seven summer- breeding congenerics. While the diet of Fiordland penguin has been reported to be composed of cephalopods, fish and crustaceans (Van Heezik 1989, 1990), very little is known of its foraging behaviour and the environmental factors influencing foraging in this species (Mattern

2013). Such information is crucial to understanding how the species, which has a Vulnerable conservation status (IUCN, 2018), may respond to environmental variability and (Otley et al. 2018). The objectives of the present study, therefore, were to examine in

Fiordland penguins over the breeding season: 1) at-sea movements and habitat use; 2) diving behaviour and foraging effort; 3) trophic niche level and width; and 4) potential intrinsic and environmental factors influencing these parameters.

2.3 Materials and methods

2.3.1 Study site and field procedures

The study was conducted on Taumaka / Open Bay Island (43.859 °S, 168.885 °E), 4.5 km off the west coast of New Zealand’s South Island (

Figure 2-1). This 20 ha island hosts one of the largest populations of Fiordland penguins with at least 150 breeding pairs (McLean & Russ 1991). Individuals were sampled (once throughout the study) over different breeding stages (incubation, guard and crèche) and over two breeding seasons (2016 and 2017). Individuals were observed from hides as they returned to the island and captured by hand as they walked to, or at, the nest. Once captured, they were fitted with a cloth hood to minimise stress and weighed using a spring scale (± 20 g, Pesola

Ltd, Switzerland).

To determine at-sea movements and marine habitat use, the birds were equipped with a GPS 21 data logger (i-gotU Mobile Action Technology, Inc., Taiwan) accurate to ± 10 m (Morris &

Conner 2017). The device was removed from its original casing to reduce drag effect and sealed in a waterproof heat-shrink tubing (Tyco Electronics, Switzerland). During incubation, model

GT 600 (45x39x13mm, 26.5 g) units were deployed, programmed to sample at 2 min intervals.

During guard and crèche stages, model GT-120 (45x25x12mm, 15 g) units were deployed, programmed to sample at 1 and 2 min intervals, respectively. The data loggers were attached to the mid-line dorsal feathers on the lower back with black waterproof tape (TESA 4651,

Beiersdorf AG, Germany) following Wilson et al. (1997).

To obtain information on diving behaviour, same individuals were simultaneously instrumented during the guard and crèche stages with a dive behaviour/accelerometer data logger (40x15x11 mm, 6.5 g Axy-Depth, Technosmart, Rome, Italy, or 21x13x4 mm, 1.7 g

WACU, MIBE/IPHC, Strasbourg, France) recording depth (± 5 cm) and temperature (± 0.1

°C) every second and tri-axial body acceleration at 25 Hz. In total, attached devices represented ca 1 % of the penguins body mass in air and ca 2.6 % of their cross-sectional surface area and, therefore, are likely to have had negligible impact on the foraging behaviour (Wilson et al.

1986, Agnew et al. 2013). Handling procedures lasted 10-15 min before animals were released near the nest to resume normal behaviours.

After one or two foraging trips to sea, individuals were recaptured and the data loggers were removed. Culmen length and bill depth were measured using Vernier callipers (± 0.1 mm) to sex the birds using a discriminant function previously established at this site (Murie et al. 1991).

A 0.1 mL blood sample was collected by venipuncture of a tarsal vein and stored in 70 % ethanol for later analysis of stable isotopes for trophic niche estimation.

2.3.2 Data handling and processing

The GPS data were processed within the R statistical environment (R Core Team, 2017).

Foraging trips were defined as the time spent at sea between the departure and the return (land- based points removed). A speed filter with a threshold at 8.2 km·h-1, corresponding to the upper 22 range speed of the similar-sized Macaroni penguin Eudyptes chrysolophus (Brown 1987) was applied to remove erroneous locations. The following trip metrics were calculated using the package adehabitatHR (Calenge 2006): the trip duration, total horizontal distance travelled, the mean horizontal speed, the maximum distance from the colony; and compass bearing to the most distal point.

Raw depth data were downloaded from the data loggers and converted using the software

Axy Manager (Technosmart Europe S.r.l., Rome, Italy). Submergences of greater than 1 m depth were considered as dives and were processed within the R software to calculate their parameters (maximum depth, duration, descent and ascent rates, bottom time, post-dive interval) using the package diveMove (Luque, 2007). Maximum depth of successive dives were compared to assess the Intra Depth Zone (IDZ; Tremblay & Cherel 2000). For each individual trip, the proportion of time spent diving and the dive frequency were determined. For individuals providing sufficient data, the behavioural aerobic dive limit (bADL) was estimated from the dive duration and the post-dive interval. As 98 % of post-dive intervals were ≤ 60 s

(and those lasting longer were not related to dive sequences), this threshold was used to investigate the bADL. The bADL was determined from the intersection of quantile regressions fitted on a moving average of 5 successive dives (supplementary Fig S 2-1), to account for oxygen payoff delay (Horning 2012). Lastly, dive data were visually inspected to ascertain dive shape profiles (Wilson et al. 1996). Dive occurrence was investigated in relation to local sunrise, sunset and nautical twilight times (www.timeanddate.com, retrieved for Haast, 10 km east of the colony) in order to describe their temporal distribution (dawn, day, dusk and night).

The foraging effort was assessed from the vertical dive rate (total vertical distance/trip duration, m·h-1).

The acceleration data along the three axis (surge, heave and sway) were analysed within

IGOR Pro software (Wavemetrics Inc., USA, 2000, Version 7) to infer behaviour at each second of the trip. The gravity-related static acceleration, determined by a one second running

23 mean, was subtracted from the raw acceleration (Wilson et al. 2006, Shepard et al. 2008) to calculate Vectorial Dynamic Body Acceleration (VeDBA = √(퐴푥2 + 퐴푦2 + 퐴푧2)), a proxy of whole body activity (Qasem et al. 2012). Assuming that sudden sharp and rapid movements were associated with prey pursuits (Ropert-Coudert et al. 2006, Chimienti et al. 2016), peaks above 0.15 g during dives on a 1s moving average VeDBA were considered to represent Prey

Encounter Events (PEE, supplementary Fig S 2-2) following the method described in Sánchez et al. (2018). Intervals of ≤ 2 s between VeDBA peaks were considered to be related to the same prey item as inspection of the frequency distribution of interval durations revealed a sharp decrease in the number of PEE above this threshold. The PEE were then aligned with the diving behaviour and the interpolated GPS coordinates in order to describe their vertical and spatio- temporal distribution along the foraging trip.

To investigate the important environmental factors driving the Fiordland penguin habitat use, oceanographic variables considered to be influential (Reisinger et al. 2018) were gathered on the penguins foraging area. Remote-sensed sea surface chlorophyll-a concentration was excluded, as it has been reported as an imprecise index to the water column stock of chlorophyll-a in these inshore waters influenced by the coastal run-off (Vincent et al. 1991).

Bathymetry and sea floor slope were obtained from 250 m gridded bathymetry data

(www.niwa.co.nz/our-science/oceans/bathymetry). The daily sea surface temperature (SST) and SST anomaly were obtained at 0.01° resolution (https://coastwatch.pfeg.noaa.gov/). The daily sea surface height (SSH), mixed layer thickness (MLT), salinity (SAL), sea water eastward and northward velocities data were obtained at 0.08 ° resolution

(http://marine.copernicus.eu/). The current speed was calculated with the last as: current speed = √northward velocity 2+ eastward velocity 2. Within square grid cells of

0.01° (ca 1 km2) matching the finest resolution of the oceanographic data, the linearly interpolated GPS tracks at 1 min were converted in a standardised proportion of time spent in area, using the package trip (Sumner 2015). As individuals spend more time where they forage, 24 it is a spatial index of the foraging effort (Péron et al. 2012, Warwick-Evans et al. 2015). The time spent in area values were then spatio-temporally matched with the above oceanographic variables, using the package raster (Hijmans 2016).

The trophic niche of individuals was investigated using the analysis of stable isotopes (SIA) of nitrogen (δ 15N) and carbon (δ 13C), a widely used method to infer the consumer trophic level and quantify its niche within the foodweb (Bearhop et al. 2004). The SIA was conducted on whole blood samples, which reflects the assimilated diet signature with a half-life turnover rate of 12 – 14 d for a penguin of this size (Barquete et al. 2013). Samples were oven-dried for 24 h at 60 °C, ground and 0.5 mg sub-samples loaded into tin capsules. Analyses were conducted at the National Isotope Centre (GNS Science, Lower Hutt, New Zealand) with an elemental analyser (EuroVector, Italy) coupled to a mass spectrometer (Isoprime, England). Isotopic ratios are reported in the δ notation relative to the international standards, the Vienna Pee Dee

Belemnite limestone for carbon and to the atmospheric N2 for nitrogen. Their isotopic deviation was defined as δ(‰) = [(Rs-Rref) /Rref], where Rs is the isotopic ratio measured for the sample

13 and Rref is the reference standard. Internal laboratory standards (Leucine;  C -28.30 ‰ and 

15N +6.54 ‰; EDTA: 13C -31.12 ‰ and  15N +0.58 ‰; Caffeine, δ13C -38.17 1 ‰ and δ15N

-7.82 ‰; Cane sugar 13C -10.33 ‰) calibrated to Primary Reference Materials (RM’s, IAEA-

N1,  15N +0.43 ‰; IAEA-N2,  15N +20.41 ‰; IAEA-CH6, 13C -10.449 ‰; and IAEA-CH7,

13 13 15  C -32.151 ‰) relative to international standards δ CVPDB and δ NAir indicated an analytical precision of ± 0.1 ‰ for 13C and ± 0.2 ‰ for  15N.

The isotopic niche position and width of Fiordland penguins was estimated and compared between breeding stages in a 2D isotopic space, using the ellipse area-based metrics of the

SIBER package (Jackson et al. 2011). The isotopic niche was estimated by the 40 % standard ellipse area corrected for sample size (SEAc) and by the Bayesian standard ellipses areas

5 (SEAB) on 10 replicates, which quantified uncertainty and allowed robust statistical

25 comparisons (Jackson et al. 2011). The niche overlap between stages was quantified by the isotopic area of overlap from the maximum likelihood ellipses for two given stages.

2.3.3 Statistical analyses

All the statistical analyses were conducted within the R software (R Core Team 2017).

Different tests were used to assess the variable normality (Shapiro-Wilk test), variance homogeneity of unbalanced samples (Bartlett test), to look at the distribution between departures and returns times (Wilcoxon test) and their variation between breeding stages

(Kolmogorov-Smirnov tests). The uniformity of range bearings was tested with a Kuiper’s test.

To investigate the variables influencing the foraging behaviour of the instrumented individuals, different mixed models were fitted to account for the hierarchical structure of the tracking data

(Bolker et al. 2009) using individuals as a random factor. Generalized Linear Mixed Models

(GLMMs) were used to investigate the influence of the year, breeding stage and sex

(explanatory variables) on the maximum distance from the colony, mean horizontal speed, trip duration and total horizontal distance travelled (response variables) using the package nlme

(Pinheiro et al. 2014). Allowing non-linear relation between the response variable and its covariables (Wakefield et al. 2009), Generalized Additive Mixed Models (GAMMs) were used to investigate the influence of the year, breeding stage and sex (explanatory variables) on the dive rate, depth, duration, and percentage of anaerobic dives (response variables). The dives temporal autocorrelation was taken in account by an autoregressive component (rho) using the package mgcv (Wood 2004). A GAMM was also used to investigate the influence of the oceanographic variables on the foraging effort index. Prior to modelling, oceanographic variables were scaled and checked for collinearity, with a cut-off criterion of rs = 0.5 for inclusion in the model. GLMs were used to investigate the influence of the year, breeding stage and sex on the isotopic values (δ13C and δ15N).

26

Model selection was based on the Akaike’s Information Criterion corrected for small sample sizes (AICc), ranking all the candidate models using the package MuMIn (Barton 2016). The best-supported model was chosen, or in the case of several candidate models with substantial support (ΔAIC < 4), a model averaging procedure was used to identify the important predictor variables (Burnham et al. 2011) and to select the individual model including them

(Supplementary Table S 2-1). Selected models were validated by examination of the residuals

(Zuur 2009). Variable influence was stated with significance at P < 0.05. Unless otherwise stated, data are presented as Means ± SE.

2.4 Results

2.4.1 At-sea movements and habitat use

Due to logistical constraints, not all stages could be sampled equally in both years of the study. Device malfunctions and loss at sea of some devices meant that complete data sets were not available from all individuals (Table 2-1). Data on at-sea movements were obtained for 35 individuals (37 trips), totalling 1427 h at sea and 22470 filtered locations (27 removed). There was a significant difference between the sexes in the body mass of departing birds, with males weighing 3.4 ± 0.1 kg and females 2.8 ± 0.0 kg (ANOVA, P < 0.001), but not between year or breeding stage. When recaptured, the same birds were weighed with an average mass gain of

44 ± 33 g. Movements from the colony occurred throughout most of the day (01:00 – 22:00 h) with departures occurring mainly before sunrise (67 %), while returns to the colony were spread throughout the afternoon until sunset (70 %). This pattern was consistent across the breeding stages. During incubation, individuals conducted multi-day trips (3 – 5 d), while during the guard stage trips were mostly for a single day (8 – 15 h, 64 %) or shorter multi-day trips (2 d,

36 %). During the crèche stage, all trips consisted of longer multi-day trips (2 – 7 d).

27

Individuals travelled in a non-random direction across breeding stages (Kuiper test, D = 4.5,

P < 0.01), in a northerly direction over a narrow peri-insular shelf (Figure. 1). They reached a maximum distance from the colony of 115 km, making a total home range area of 3877 km2.

Their total horizontal distance travelled ranged from 11-379 km, covered at a mean horizontal speed of 3.1 ± 0.1 km·h-1. The GLMMs indicated an influence of the breeding stage and year on the trips parameters (Table 2-2). The guard stage trips were closer to the colony by 62 ± 11 km, they had trip duration that were shorter by 70 ± 9 h, and the birds travelled shorter horizontal distances by 187 ± 25 km (all P < 0.001). The year 2017 had shorter maximum distance from the colony (17 ± 8 km) compared to 2016. Sex had no influence on trip parameters.

Table 2-1: Logger deployments on Fiordland penguins at Taumaka / Open Bay Island, New Zealand, and their GPS trip metrics according to the breeding stages (Mean ± SE). Incubation Guard Crèche Year 2016 2016 2017 2017 Individuals equipped (n) 4 (3F, 1M) 5 (5F) 21 (20F, 1M) 5(3F, 2M) Body mass (kg) 2.7 ± 0.1 2.8 ± 0.1 3 ± 0.05 3 ± 0.08 Trips recorded (n) 4 5 23 5 Trip duration (h) 101 ± 9 31 ± 4 17 ± 2 106 ± 16 Max. distance from the colony (km) 89 ± 9 42 ± 6 25 ± 3 88 ± 13 Total horizontal distance travelled (km) 250 ± 29 96 ± 13 56 ± 6 254 ± 46 Mean horizontal speed (km·h-1) 2.4 ± 0.07 3.1 ± 0.2 3.3 ± 0.1 2.7 ± 0.1 Trip bearing (°) 8 ± 1.3 350 ± 2 0.01 ± 2.1 30 ± 1.2

At sea, individuals spent most of their time in shelf-slope waters (200 - 1000 m, 68 %), followed by the neritic shelf waters (0 - 200 m, 22.9 %), and the oceanic waters (> 1000 m, 9

%). The sea surface temperature ranged between 11 and 14 °C with an associated temperature anomaly between -0.6 and 1.2 °C. The salinity ranged between 34.6 and 35.2 PSU, the sea surface height between 0.007 and 0.2 m, and the mixed layer depth varied from 10 to 228 m deep. The GAMM modelling revealed that the time spent in area was influenced negatively by

28 the salinity above 35 psu (P < 0.001) and positively by seafloor slope between 0 and 29 ° (P <

0.01, Supplementary Fig S 2-3).

Figure 2-1 : Fiordland penguins’ foraging trips from Taumaka / Open Bay Island expressed as standardised time spent in area within 0.01° cells during the different breeding stages. The study site location (black point) is represented in panel A in regards to the breeding populations’ locations (green points), to the average position of the subtropical front (dashed line), and is framed by a rectangle showing the area plotted in panels B, C and D. The New Zealand islands are shaded in grey and the bathymetry is indicated by the 200 m and 1000 m isobaths. 29

Table 2-2: Summary of the models’ outputs used to assess the trends in foraging trips parameters of breeding Fiordland penguin at Taumaka / Open Bay Island. Significant P value are highlighted in bold.

Model Response variable Predictor Parametric Approximate P value variable coefficients significance of smooth terms Est SE t edf F GLMM Max. distance from the colony Stage (guard) -62.0 11.3 9.1 - - < 0.001 Year (2017) -17.5 8.0 -2.1 - - 0.03 Sex (male) 2.3 9.5 0.2 - - 0.8 GLMM Trip duration Stage (guard) -70.6 9.6 -7.3 - - < 0.001 Year (2017) -13.9 8.8 -1.5 - - 0.1 Sex (male) 13.5 10.5 1.2 - - 0.2 GLMM Max. distance travelled Stage (guard) -187.3 25.2 -7.4 - - < 0.001 Year (2017) -40.6 23.3 -1.7 - - 0.09 Sex (male) 29.7 27.6 1.0 - - 0.2 GAMM Log(time spent in area) Intercept -0.19 0.27 -0.72 - - 0.4 Slope - - - 1 7.1 0.007 Current - - - 6.3 1.9 0.059 Salinity - - - 8.0 6.1 < 0.001

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2.4.2 Diving behaviour and foraging effort

Diving behaviour data were obtained from 23 individuals (25 trips) totalling 970 h at sea and 23,172 dives. Individuals spent 72 ± 2 % of their time at sea submerged, with the number of dives recorded per trip ranging from 253 to 4790, reflecting the variation in trip duration.

Dives were conducted primarily during daylight, not only during the 14 single day trips (98.8

%) but also for the 11 multi-day trips (87.2 %) which included 1-6 successive nights at sea.

Outside of daylight, diving activity was reduced but not absent, with 0.9 % occurring at dawn,

3.8 % at dusk and 7.9 % at night. Dives were epi-pelagic along the trips, characterised by shallow dives in the vicinity of the colony followed by sequences of deeper diving further off- shore (Figure 2-2) with typical V-, U- and irregular U-shaped profiles.

Dive depths (max. 154 m) and duration (max. 206 s) were not normally distributed and so modes were calculated for each trip. Mean modal dive depth across all individuals was 22 ± 2 m, with 35 ± 1 % of dives occurring sequentially within the same IDZ. Mean modal dive duration was 74 ± 11 s and the mean modal post-dive interval of 20 ± 1 s. These dives characteristics led to a dive frequency of 19 ± 2 dive·h-1 and to a mean dive rate of 1141 ± 64 m·h-1 (Table 2-3). Most individuals did not conduct apparent anaerobic dives and the bADL could be calculated for 2 males (155 ± 2 s) during crèche stage, 7 females during guard stage

(146 ± 1 s) and 2 females during crèche stage (154 ± 2 s). No significant difference was found between sexes (t2.1=-2.3, P = 0.13) or breeding stage (t1.4=-1.7, P = 0.26). While only 6 % of the total foraging dives were anaerobic, there was substantial inter-individual variation in their proportions (range 0 - 38%). All these dive parameters varied temporally according to the hour of the day (all P < 0.001, Table 4). At midday, the dive rate increased due to deeper, longer and, hence, more anaerobic dives. Concurrently, individuals encountered fewer prey at this time (Figure 2-3). Breeding stage influenced some dive parameters, with crèche stage increasing the dive rate by 262 ± 107 m.h-1 and the maximum depth by 11 ± 4 m compared to the guard stage. Sex did not influence the dives parameters.

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Figure 2-2 : Typical Fiordland penguin dive profile (in blue) along a two-days foraging trip, overlaid with the bathymetry (dotted pattern below) and the period of the day (dawn and dusk represented by light grey shaded areas, night-time by dark grey shaded areas).

Across all individuals, prey encounter events (PEE) were recorded in 50 ± 2 % of dives.

Within these dives, PEE occurred 1.0 ± 0.1 per dive, primarily during the bottom phase (74.7

%), with the remainder during the descent (13.4 %) and the ascent (11.8 %) phases of dives.

Overall, individuals encountered prey at a rate of 33 ± 3 PEE·h-1 during their foraging trips, without influence of the sex or breeding stage (GLMM, P > 0.05). Based on a linear interpolation of the GPS tracks, the horizontal distance between successive PEE dives was 92

± 15 m. The vertical distribution of the PEE in the water column ranged between 2 and 105 m deep, with a time spent encountering prey positively increasing with depth (Supplementary Fig

S 2-4).

32

Table 2-3: Summary of the diving behaviour of 23 Fiordland penguins (25 trips including 23172 dives) provisioning chicks at Taumaka / Open bay Island, New Zealand. According to their distributions, parameters are summarized by either the mean (normality), the mode (skewed between individuals) or the mean of the modes (skewed within individuals).

Dive parameter Mean/Mode* Mean of the modes SE Range % time spent diving 72 * - 2 44 - 77 Dive frequency (h-1) 23* - 1 14 - 56 Dive rate (m·h-1) 1141 - 64 629 - 1775 Dive depth (m) - 22 2 1 - 56 Duration (s) - 74 11 1 - 182 Post-dive interval (s) - 19 2 12 - 29 Bottom time (s) - 1 0 1 - 1 Descent rate (m·s-1) 0.6 - 0.4 0.2 - 2 Ascent rate (m·s-1) 0.6 - 0.4 0.2 - 2 Anaerobic dives (%) 0 * - 1.7 0 - 38 IDZ dives (%) 35 - 1 37 - 86 Dives with prey encounter events (PEE) (%) 50 - 2 28 – 75 PEE rate (h-1) 33 - 3 13 - 66 Number of PEE within PEE dives (n) 1 - 0.06 1 - 2 Horizontal distance between PEE dives (m) - 92 15 3 - 213

33

Table 2-4: Summary of the generalised additive mixed models (GAMMs) outputs used to assess the trends in the diving behaviour of Fiordland penguin provisioning chicks at Taumaka / Open Bay Island. Significant P value are highlighted in bold.

Response variable Predictor Parametric Approximate P value variable coefficients significance of smooth terms Est SE t Edf F Dive rate Intercept 1051 60 17.4 - - < 0.001 Stage (crèche) 262 107 2.4 - - 0.01 S(hour) - - - 7.2 64.1 < 0.001 Dive depth Intercept 18.9 1.7 11.0 - - < 0.001 Stage (crèche) 11.0 4.1 2.6 - - 0.007 Sex (male) -7.8 4.3 -1.8 - - 0.07 S(hour) - - - 4.4 44.2 < 0.001 Dive duration Intercept 84.4 3.6 23.0 - - < 0.001 Stage (crèche) 9.4 6.3 1.4 - - 0.1 S(hour) - - - 5.0 46.9 < 0.001 % of anaerobic dives Intercept 12 3.7 3.2 - - 0.001 Stage (crèche) 10.4 5.8 1.7 - - 0.07 S(hour) - - - 6.1 22.6 < 0.001 Time spent in PEE Intercept 56.9 32.8 1.7 - - 0.08 Stage (crèche) 163.2 98.6 1.6 - - 0.09 Sex (male) 163.7 98.5 1.6 - - 0.09 S(hour) - - - 7.3 14.6 < 0.001

34

Figure 2-3: Temporal variation of dive parameters calculated on hourly basis, predicted by GAMMs. Points represent the raw data, and blue shaded areas along the curves represent the 95 % confidence interval. Dark grey and light grey areas represent respectively the night-time and the sunset/sunrise time over the study period. Anaerobic dives are reported only for individuals that dived above their bADL.

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2.4.3 Trophic level and isotopic niche width

Stable isotope values of whole blood (Mean ± SD) were -19.8 ± 0.3 ‰ for δ13C and 12.2 ±

0.3 ‰ for δ15N, with an associated C:N ratio of 3.3 ± 0.1. The GLMs indicated that δ15N values were not influenced by year, breeding stage or sex (null model selected). The δ13C values were not influenced by sex, but were significantly reduced by 0.5 ± 0.1 ‰ in 2017 (P < 0.001), and reduced by 0.2 ± 0.1 ‰ during the guard stage (P = 0.01). Therefore, isotopic data from both sexes were pooled together and were clustered by year and breeding stage (Figure 2-4). The

2 2 isotopic niche area during incubation was estimated at SEAc = 0.37 ‰ and SEAB = 0.31 ‰ ,

2 with a high probability of being larger than during the guard stage (in 2016 SEAc = 0.29 ‰ ,

2 2 2 SEAB = 0.20 ‰ in 2016, and SEAc = 0.27 ‰ , SEAB = 0.19 ‰ in 2017) and was statistically

2 2 similar to isotopic niche area during the crèche stage (SEAc = 0.35 ‰ , SEAB = 0.37 ‰ ). All the isotopic niche areas from SEAB overlapped to some extent. In order of importance, the overlap was high between incubation/crèche, incubation/guard 2016, guard 2016/crèche, medium between guard 2017/crèche, and low between guard 2017/crèche, guard 2016/guard

2017 (Supplementary Table S 2-2).

Figure 2-4: Isotopic niche of breeding Fiordland penguins (n=53) shown by the 40% standard ellipse areas corrected for sample size (SEAc), represented by breeding stages and years.

36

2.5 Discussion

With a winter-time breeding phenology, the Fiordland penguin is unique amongst its congenerics. The combined results of the at-sea movement, diving behaviour, prey field estimation and isotopic niche obtained by this present study revealed individuals breeding at

Taumaka / Open Bay Island engaged in short and directional foraging trips towards a close peri-insular shelf slope. During foraging trips, individuals dived within the epi-pelagic zone primarily during the day. Isotopic examination of the trophic niche showed a small niche width that corresponds to a level of a squid-dominated diet. This foraging strategy was consistent between sexes, and only constrained to a shorter distance from the colony during the chick- guard stage by the need for more regular chick feedings. Despite the shorter available daylight hours (11-13 h in winter versus 14-17 h in summer), individuals did not display any detectable compensation by foraging more at night. While winter is considered a period of low food availability for many seabird species, this study revealed individuals encounter prey at a sufficiently high abundance that they do not need to forage at a higher effort than the summer breeding conspecifics.

2.5.1 At-sea movements and habitat use

The early morning departures and the afternoon returns to the colony by Fiordland penguins observed in the present study were consistent with the previous observations on this (Warham

1974) and other penguins species, displaying a typical diurnal pattern consistent with their reliance on ambient light as visual foragers (Wilson et al. 1993, Bost et al. 2002). During the incubation stage, males and females alternated foraging trips until hatching. Whereas females usually assume all the foraging duties in guard stage while males brood the chicks (Warham

1974), the present study found one male alternated guard duties with its female partner. A sexing error is unlikely as both individuals of the pair were instrumented for the study. During the crèche stage, as in other penguin species, both sexes were simultaneously engaged in foraging trips to cope with the high energy demands of larger chicks (Green et al. 2005).

37

The tracked individuals made directional movements which suggest the use of predictable profitable prey areas close to the colony (Barlow & Croxall 2002). In 2016, females foraged further away during the guard stage than in 2017, which could reflect inter-annual variation in the prey distribution (Garthe et al. 2011). Breeding stage influenced the trips parameters, with distance and duration typically reduced during the guard stage, when small offspring need to be provisioned more frequently, while incubation and crèche trips parameters were similarly longer. Despite the presence of sexual size dimorphism and their different reproductive roles, sex did not influence foraging trip parameters in the present study. This is in contrast to that reported in other Eudyptes species where males forage in prolonged trips, further from the colony than females (Barlow & Croxall 2002, Ludynia et al. 2013), enabling preparation for, and in recuperation of, long fasting periods by males associated with the guard stage. However, due to logistical constraints, a sample with equal sex ratios could not be obtained in the present study such that it is possible sex differences in habitat use do exist in Fiordland penguins.

Whereas most Eudyptes recover from the energy deficit of fasting during courtship, egg laying and incubation with trips of long duration to distant oceanic areas (Table 2-5), the

Fiordland penguin from Taumaka / Open Bay Island foraged close to the colony on short trips only. Similarly, during the crèche stage, individuals in the present study supported the higher nutritional requirements of large chicks with foraging trips of shorter duration and closer to the colony than congenerics (Table 2-5). They also foraged mostly over the shelf slope, where their time per grid cell was influenced by the sea-surface salinity and seafloor bathymetry slope.

This is in contrast with its summer-breeding congenerics that use mesoscale (eddies) and sub- mesoscale (filaments) cues to locate favourable foraging conditions in the oceanic environment

(Bon et al. 2015, Whitehead et al. 2016). Instead, Fiordland penguins from Taumaka / Open

Bay Island targeted the adjacent shelf slope, likely to reflect a ready access to favourable waters, where a lower salinity could indicate the areas of mixing (Heath 1985).

38

Table 2-5: Comparison of breeding and foraging parameters among the Eudyptes genus. Data from the present study are shown in italics, others data are from Garcia-Borboroglu and Boersma 2013, excepted for data preceded by superscripts: (1)Morrison 2015, (2)Whitehead 2017, (3)Otley et al. 2018, (4)Booth et al. 2018. The dive rate with an asterix indicate the values calculated per hour underwater, for comparison purpose. Eudyptes penguin species Southern rockhopper Eastern rockhopper Northern Erect-crested Fiordland Snares Macaroni Royal rockhopper

E. chrysocome E. filholi E. moseleyi E. sclateri E. pachyrhynchus E. robustus E. chrysolophus E. schlegeli

Egg laying period November December September - October July –August September- November- October- October October December November

Main prey: Crustaceans Crustaceans Crustaceans NA Cephalopods Crustaceans Crustaceans Crustaceans

Cephalopods Cephalopods Cephalopods Fish

Fish Fish

Habitat, trip duration and Patagonian shelf and Polar frontal zone, peri-insular shelf NA Peri-insular shelf Subtropical Polar frontal zone, Polar frontal range slope shelf slope front shelf zone NA Incubation 0.3 – 22 d 14 d(1) 3 – 5 d 10 ± 2 d 10 - 26 d 19 ± 7 d NA (9 - 190 km) NA (76 - 115 km) 200 km (300-700 km) (415 – 600 km) 11-19 h Guard 15 – 42 h 6 – 67 h(2) 8 – 41 h 34 ± 8 h 4 – 64 h 4 ± 1 d NA (30 km) (1 – 78 km) (11 - 134 km) (121 ± 31 km) (12 – 98 km) (116 km) 12 ± 1 (4) Crèche 27 – 28 h 1 – 336 h(2) 2 – 7 d NA 10 – 277 h 6 ± 3 d NA NA (2 – 420 km) (42 - 111 km) NA (22 – 406 km) (201 km)

Mean dive depth range (m) 14 - 27 48 13 - 18 NA 20 23 15 - 60 32

Dive rate (m/h) 1716* – 2909* 1544* 1530 NA 1141 (=1782*) NA 1205, 1457* NA

Chick fledge duration (d) 66-73 68 63-70 70 74 75 60-70 65

Mean breeding success 0.35 – 0.61 0.47 0.36 NA 0.61(3) 0.41 0.35 0.53

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2.5.2 Diving behaviour and foraging effort

The individuals tracked in the present study started foraging soon after leaving the colony, with no apparent commuting phase, and spent the majority of their time at sea diving. Despite an ability to reach deeper-water prey, predominant aerobic and epi-pelagic dives reflect a prey availability at shallower depths. Diving behaviour varied throughout the day, with the deepest and longest dives occurring in the middle of the day when the rate of prey encounter decreased.

This strongly suggests an adaptation to diel vertically migrating prey (Bost et al. 2002) and is similar to other Eudyptes species where temporal variation in epi-pelagic dives corresponds to vertically migrating prey (Wilson et al. 1997, Tremblay and Cherel 2003, Deagle et al. 2008).

Breeding stage influenced the dive depth and the foraging effort, showing a slight increase during the crèche stage. This is in accordance with the changing energy demands of chick rearing (Green et al. 2009), and similar to that reported for congeneric species (Schiavini &

Rey 2004, Deagle et al. 2008). Within the limited samples sizes of the present study, diving parameters were not influenced by the sex, despite the presence of sexual dimorphism and unequal breeding duties between male and female Fiordland penguins (Warham 1974). This is similar to that observed in Royal/Macaroni penguins (Hull 2000, Deagle et al. 2008) but in contrast to that reported in Rockhopper penguins where females dived to greater depths than males (Ludynia et al. 2013). These contrasted results could potentially reflect site-specific prey accessibility and density-dependence triggering the intra-specific competition (Lewis et al.

2001). Given the unbalanced sex ratio in the present study, further investigations are required to confirm the presence or absence of sex differences in diving behaviour and foraging effort in Fiordland penguins.

Assuming the foraging behaviour of a predator reflects the availability of its prey (Davoren et al. 2003, Wilson et al. 2005, Elliott et al. 2008), the horizontal and vertical spatial distribution of Prey Encounter Events (PEE) observed in the present study suggests a prey that migrates deeper during the day, is uniformly distributed throughout the shelf slope, and is abundant

40 during the breeding period off the west coast of New Zealand’s South Island. The observed

PEE rate (~1 per dive) was low in comparison to that reported in other penguin species

(Watanabe & Takahashi 2013) achieving multiple prey captures per dive associated with small schooling prey. Hence, the results of the present study suggest individuals are likely to have foraged predominantly on less aggregated or solitary larger prey. Future studies using animal- borne cameras are needed to confirm the identity of prey species and the quantification of prey consumption (Watanabe and Takahashi 2013).

2.5.3 Trophic level and isotopic niche width

The δ15N values observed in the present study are similar to that observed in other penguin species in New Zealand inshore waters that are known to have a squid-dominated diet

(Flemming & Van Heezik 2014). This is consistent with the stomach contents of Fiordland penguin previously analysed at Taumaka / Open Bay Island, indicating that squid (ranging in mantle lengths of 20 - 140 mm) represents 71 % of the diet by mass (Van Heezik 1989).

Furthermore, the small isotopic ellipses and the absence of δ15N variation between sexes and breeding stages corroborate, respectively, the low prey diversity and lack of sex difference in stomach contents (Van Heezik 1989). In contrast to the diet shift reported for congenerics when provisioning chicks during the crèche by foraging on shelf (southern and northern rockhopper penguins, Schiavani and Rey 2004, Tremblay and Cherel 2003, Booth et al. 2018), the feeding at similar trophic level by the Fiordland penguin in the present study is likely to reflect a constant prey availability changes off the west coast of New Zealand’s South Island. The δ 13C values, reflecting the carbon source in the food chain with a gradient between inshore–offshore habitats (Hobson et al. 1994), indicated small variations between breeding stages and years.

These isotopic results are also consistent with the GPS trips and dive parameters discussed above. The different time scales between time integration of whole blood isotopes and the duration of the tracked foraging trips complicate their spatio-temporal interpretation, especially

41 in region of such intermittent water mixing processes (Vincent et al. 1991). Future studies should consider analysing the stable isotopes of blood plasma, integrating a shorter period of time (Barquete et al. 2013) to gain in accuracy.

The narrowness of the trophic niche observed in the present study is typical of specialist

Eudyptes species, having little deviation in their stable isotopes values (Cherel et al 2007) and few prey taxa in their stomach contents (Cooper et al. 1990). However, while Eudyptes species rely mostly on crustacean or fish (Cooper et al. 1990), the Fiordland penguin appears to be a squid specialist during the breeding season off the west coast of New Zealand’s South Island

(Van Heezik 1989). This is consistent with the local oceanic conditions, with a weak eastward flow bringing the oligotrophic and iron-limited subtropical waters of the Tasman Sea to this region (Heath 1985, Boyd et al. 1999, Ellwood et al. 2008). Undergoing a mixed layer deepening in winter that recharge the photic zone in nutrients and rising over the peri-insular shelf where intermittent wind-driven coastal upwelling and large river outflows occur (Heath

1985, (Griffiths & Glasby 1985, Young & Foster 1986), these waters have an increased phytoplankton production in winter that peaks in September-October before decreasing in summer (Longhurst 1995, Murphy et al. 2001). Numerous species, including arrow squid

(Nototodarus sloanii) and warty squid (Moroteuthis ingens) which are the main prey of the

Fiordland penguin (Van Heezik 1989), take advantage of these conditions to spawn during winter (Uozumi & Forch 1995). Other fish prey such as sprat (Sprattus antipodum), red cod

(Pseudophycis bachus) or hoki (Macruronus novaezelandiae) also spawn in winter on this shelf

(Coombs & Cordue 1995, Beentjes & Renwick 2001).

The present study found no compelling evidence that Fiordland penguin at Taumaka / Open

Bay Island experience particularly challenging prey availability conditions during their winter breeding period. Instead, the results suggest that Fiordland penguins breeding at this location match their breeding activity to a predictable prey resource, potentially winter spawning squid.

42

This close prey resource is likely to explain the shorter foraging range and similar foraging effort that lead to a high breeding success after a similar chick-rearing period compared to the other Eudyptes species (Table 2-5). However, these apparently favourable foraging conditions are at odds with the low population size and the negative population trend for the species

(Mattern 2013). While introduced predators are known to reduce the breeding success of

Fiordland penguins nesting on the mainland (Mattern 2013, Ellenberg et al. 2015), the results of the present study were obtained on an island free from introduced mammalian predators.

This suggests that the species may experience a local energetic bottleneck at other times of the year, limiting their population growth. For instance, the local availability of squid is known to decrease in summer (Mattlin 1985), when Fiordland penguins shift foraging location towards distant oceanic fronts during the pre-moult trip (Mattern et al. 2018), and are not observed near their breeding sites during the non-breeding period.

It will be necessary to gather further information on the Fiordland penguin’s foraging ecology throughout the annual cycle (Marra et al. 2015) to understand the full range of its ecological requirements and potential threats at sea. This is especially important in view of the reliance on a narrow continental shelf associated with a narrow trophic niche dimension, reflecting a high degree of specialization and little plasticity during the breeding period, which may make this population highly sensitive to environmental perturbations (Laidre et al. 2008).

The present study was conducted in a small proportion of the species’ range, with many populations occurring further south closer to the subtropical front (

Figure 2-1) where individuals are likely to face different marine conditions and are known to have a fish-dominated diet at Codfish Island (Van Heezik 1990). The degree to which the foraging characteristics of this relatively large population of the Fiordland penguin breeding at the study site reflects that of other smaller breeding groups remains to be investigated.

43

Therefore, additional studies are needed across the species’ range to better understand the drivers and consequences of winter breeding.

Other seabird species with long breeding cycles that extend chick rearing into winter (e.g.

King penguin Aptenodytes patagonicus, Charrassin et al. 2002, or Wandering albatross

Diomedea exulans, Salamolard and Weimerskirch 1993) forage in oceanic waters with a higher effort (longer trip durations and greater distances) to rear chicks. In contrast, the present study suggests winter breeding in Fiordland penguins is a strategy to match favourable pelagic conditions. These findings extend the knowledge on species that commence breeding in winter, currently limited to the Emperor penguin Aptenodytes forsteri and gentoo penguin Pygoscelis papua, which are capable of benthic foraging (Rodary et al. 2000, Lescroël and Bost 2005). In addition to taking advantage of a winter resource, the absence of the numerous migratory summer-breeding species during winter could constitute another advantage. More studies involving different winter-breeding seabirds from others parts of the world and considering year-round prey availability are needed to improve our understanding of the evolution of winter breeding. Studies on flying species, more constrained by surface prey availability, would be especially important. Such temporal resource segregation with summer-breeding species is likely to have played a major role in speciation. For instance, this could be the case in the

Eudyptes radiation and the divergence between the summer-breeding Snares penguin and the winter-breeding Fiordland penguin during the Pleistocene (Baker et al. 2006). In addition, the ongoing climate change and anthropogenic impacts on the oceans at a global scale might influence the cost/benefit of the winter-breeding strategy, on which much remains to be discovered.

44

2.6 Supplementary material

Fig S 2-1: Behavioural aerobic dive limit estimation method used for successive dives of Fiordland penguin.

45

(m) Depth

)

g (

Acceleration

1

-

s .

)

g (

VeDBA

Date and time (GMT)

Fig S 2-2: Prey encounter event (PEE) identification based on accelerometry data. On the acceleration axis, green represent the surge (X), blue the sway (Y) and red the heave (Z). The arrows represent the VeDBA peaks above 0.15 g during dive, and the stars the corresponding PEE on the depth axis.

Table S 2-1: Best and most parsimonious models selected explaining the GPS trips and dive parameters trends of the Fiordland penguins breeding at Taumaka / Open Bay Island.

Δ rho Model Response variable Predictor variables Rank AICc weight AIC value GPS trips parameters GLMM Max. distance from the stage + year + sex 1 296.1 0.0 0.8 - colony GLMM Trip duration stage + year + sex 1 302.3 0.0 0.8 - GLMM Max. distance travelled stage + year + sex 1 364.1 0.0 0.9 - GAMM Log(time spent in area) current + salinity + slope 2 12104.3 0.04 0.43 0.02 Dives parameters GAMM Dive rate hour + stage 1 13573.6 0.0 0.45 0.67 GAMM % of anaerobic dives hour + sex + stage 3 3193.2 0.24 0.51 0.58 GAMM Dive depth hour + sex + stage 1 7370.4 0.0 0.33 0.34 GAMM Dive duration hour + stage 1 8834.7 0.0 0.45 0.35 GAMM Time spent in PEE hour 4 4147.5 0.6 0.27 0.25

46

Fig S 2-3: Relationship between the time spent in area by Fiordland penguins (n=35) and influencing oceanographic parameters modelled by GAMM.

Fig S 2-4: Distribution of the prey encounter events within the water column (right) with regards of the dives distribution (left).

47

Table S 2-2: Pairwise comparison between Fiordland penguin Bayesian standard ellipse areas 2 (SEAB) of 1) the probability to be smaller, and separated by a dash, 2) the overlap ratio (‰ , in italics).

Incubation 2016 Guard 2016 Guard 2017 Crèche 2017 Incubation 2016 - 0.30 / 0.41 0.10 / 0.14 0.49 / 0.59 Guard 2016 0.69 / 0.52 - 0.28 / 0.05 0.71 / 0.44 Guard 2017 0.89 / 0.19 0.71 / 0.06 - 0.97 / 0.26 Crèche 2017 0.50 / 0.63 0.28 / 0.37 0.02 / 0.20 -

48

Chapter 3:

Fine scale foraging behaviour of

southern Buller's albatross, the only Thalassarche

provisioning chicks through winter

A version of this chapter has been published as:

Timothée A Poupart, Susan M Waugh, Colin M Miskelly, Akiko Kato, Lauren P Angel, Karyne

M Rodgers, John PY Arnould (2019). Fine scale foraging behaviour of southern Buller’s albatross, the only Thalassarche provisioning chicks through winter. Mar Ecol Prog Ser

625:163-179. https://doi.org/10.3354/meps13042

49

3.1 Abstract

Predators generally time their reproductive events to match the peak in prey resource availability in order to sustain the elevated energy requirement of offspring provisioning.

Consequently, most temperate/polar seabirds breed in spring/summer, including the majority of small albatross species that have short breeding cycles. In contrast, the southern Buller’s albatross Thalassarche bulleri bulleri has a delayed breeding schedule with chick-rearing extending throughout the entire austral winter. In the present study, the fine-scale at-sea movements and trophic niche of chick-rearing southern Buller’s albatross were determined at

Hautere/Solander Island (New Zealand, 46°35′S, 166°54′E) during the 2016 and 2017 chick rearing periods to investigate the winter foraging strategy used during this nominally challenging period. The tracks recorded by 15 males (n = 43) and 11 females (n = 21) revealed that southern Buller’s albatross foraging behaviour accounted for only a small proportion of time at sea, primarily influenced by the time of day. Foraging occurred mainly in the neritic waters of New Zealand’s South Island shelf, with individuals undertaking consistent short trips

(≤ 230 km from colony) or alternating short and long trips up to 1500 km from the colony. Fine scale tracking data revealed males spending more time foraging, during shorter trips than females. Their isotopic niches were small, with overlap between sexes, but with males having higher  15N values than females. Time spent foraging was influenced by both static and dynamic oceanographic variables. These findings suggest that southern Buller’s albatross foraging behaviour, despite having to sustain chick provisioning in winter, is similar to summer-breeding congenerics.

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3.2 Introduction

Trophic resource acquisition, the fundamental process on which all allocation of energy expenditure in an animal’s life depends, vary according to nutritional demand and resource availability in the environment (Boggs 1992). During offspring provisioning, ‘income- breeding’ species increase their nutritional intake to meet the elevated energy requirements of both offspring and self-maintenance. Such demand can be satisfied by matching the timing of reproduction with a period of high food availability (Lack 1968) and altering the time/energy allocation of behaviours (Gittleman & Thompson 1988). Correspondingly, food supply and parental foraging are both selection pressures on individual fitness, shaping the evolution of breeding (Thomas et al. 2001).

The marine environment is highly temporally and spatially dynamic (Stommel 1963). The scale-dependent interactions between oceanographic and biological processes lead to a heterogeneous seascape of productivity and prey (Haury et al. 1978). This complexity is thought to shape the extreme life history traits of marine predators (low offspring production, delayed maturity and long life expectancy (Ashmole 1971). However, predictable seasonal variations occur in polar and temperate regions, with ocean primary productivity and consumers’ biomass rising in spring / summer and decreasing in autumn / winter (Atkinson &

Peck 1990, Behrenfeld et al. 2005). Hence, the breeding schedule of many marine predators in these ecosystems is centred on summer.

During breeding, seabirds become central-place foragers (Orians 1979) and behave to maximise their energy gain from the time-constrained transport of prey between feeding areas and the nest. For the albatrosses, this trade-off is accomplished using dynamic soaring flight powered by the wind (Richardson 2011). This flight allows them to cover considerable distances with minimal energetic cost (Costa & Prince 1987, Jouventin & Weimerskirch 1990,

Bevan et al. 1995) and to maximise their prey encounters (Weimerskirch et al. 2000,

Weimerskirch et al. 2005). Feeding mainly upon cephalopods, fish and crustaceans by surface-

51 seizing (Cherel & Klages 1998), albatrosses are constrained by the availability of prey near the surface. As visual predators, they follow a diel activity pattern, searching in flight and landing on water to feed mainly during the day and become less active at night when they raft on the water surface (Weimerskirch & Wilson 1992, Catry et al. 2004b).

To locate favourable foraging conditions, albatrosses can use different oceanographic cues at meso-scale such as eddies (Nel et al. 2001) and continental shelves (Brothers et al. 1998,

Cherel et al. 2000), that individuals can exploit with environmental specialisation (Bonnet-

Lebrun et al. 2018). In addition, some species can have different foraging strategies between sexes (Shaffer et al. 2001, Phillips et al. 2004, Pereira et al. 2018). Furthermore, the presence of conspecifics (Silverman et al. 2004), marine mammals (Sakamoto et al. 2009b) and fishing vessels (Torres et al. 2011, Collet et al. 2015) has been reported to influence their foraging behaviour, demonstrating their complex interactions with the marine environment.

Large albatrosses (Diomedea spp., 6 - 11 kg body mass) lay an egg in spring/summer, hatching late-summer/early-autumn. The chick is provisioned by both parents during 9 months to reach its fledging size and to become heavier than adults (Weimerskirch & Lys 2000).

During winter, the breeders display an asymmetrical parental investment, reduce the time spent with the chick and increase their proportion of long trips, resulting in a feeding rate decrease while the parents’ body condition increases (Huin et al. 2000, Weimerskirch & Lys 2000). The pairs retaining a chick at this stage have to forage with a greater effort (Salamolard &

Weimerskirch 1993, Shaffer 2004) and will not be able to breed the next year (Tickell 1968,

Jouventin & Dobson 2002).

In contrast, the smaller albatrosses nesting in subantarctic and temperate latitudes (e.g.

Thalassarche and Phoebetria, 2 - 5 kg) breed with a shorter chick- rearing period (4 - 5 months) coinciding with summer - autumn, with one exception. In New Zealand, the endemic Buller’s albatross (T. bulleri) occurs with two genetically distinct subspecies (Wold 2017). The breeding distribution of the northern Buller’s albatross (NBA, T. b. platei) is restricted to the

52

Three Kings (34°S) and the Chatham Islands (43°S) while the southern Buller’s albatross

(SBA, T. b. bulleri) nests at only the Solander (46°S) and the Snares Islands (48°S). Whereas

NBA have a breeding period similar to other Thalassarche species, SBA have a delayed breeding season by 3 months. SBA lays eggs in mid-summer (January), hatches in autumn, and displays the longest chick-rearing period of the genus (167 d, (Sagar & Warham 1998) that forces SBA to sustain chick provisioning through the entire austral winter. Previous studies showed foraging happening around New Zealand and Tasman Sea (Stahl & Sagar 2000a, Stahl

& Sagar 2000b), when these waters undergo cooling and structure change in association with the Antarctic circumpolar ocean-atmosphere system (Garner 1969, White & Cherry 1999).

While breeding constraints are avoided during the austral winter by other small albatrosses, or imply negative carry-over effects for the large Diomedea (Prince et al. 1994b), the small population of winter-breeding SBA (13,625 pairs) can sustain an average breeding success of

70 % with an adult survival rate > 90 % (Sagar et al. 2002, Sagar et al. 2005, Francis & Sagar

2012). Although this near threatened species (IUCN 2019) is subject to environmental changes in its foraging range (Matear et al. 2013) and experienced a recent decline in adult survival

(Francis & Sagar 2012), little is known about its fine-scale foraging behaviour and activity budget. How the SBA parents sustain its chick rearing food requirements is crucial and missing knowledge to understand the species interaction with its environment. Hypothetically, its winter food requirements could be met with greater foraging effort in comparison to others albatrosses, or with adaptation of activities to daylight reduction (9-10 h of daylight per day during SBA chick-rearing against 11-15 h for summer-breeding albatrosses at similar latitude).

Alternately, its food requirements could be met with normal effort thanks to a winter prey resource. The objectives of the present study, therefore, were to determine in SBA during the chick-rearing period: 1) fine-scale at-sea movements and activity budget, 2) foraging behaviour and trophic niche, and 3) influence of sex and environmental factors on foraging behaviour.

53

3.3 Materials and methods

3.3.1 Study site and field procedures

The study was conducted at Hautere/Solander Island (46°35′S, 166°54′E) which hosts 5,280

SBA breeding pairs, e.g. ca 37 % of the entire population (Thompson et al. 2017). Birds from accessible nests of the West Bay area were selected at random during the post-guard stage of the 2016 and 2017 breeding seasons. One adult per nest (n = 20 in May 2016 and n = 19 in July

2017) was captured by hand after having fed its chick and weighed in a cloth bag with a suspension scale (±25 g, Pesola). To monitor their at-sea movements and fine-scale behaviour, individuals were equipped with two data loggers: 1) a GPS (i-gotU model GT–600, Mobile

Action Technology, Taiwan, 45 x 39 x 13 mm) sampling location at 2 min intervals, and 2) a tri-axial accelerometer (GCDC X16-mini, Gulf Coast Data Concepts, USA, 47 x 22 x 9 mm) sampling at 25 Hz. Both devices were encapsulated separately in heat-shrink tubing and attached to the central dorsal feathers with waterproof tape (Tesa 4651, Tesa GmbH, Germany).

For all individuals, the loggers were consistently positioned between the wings, with the accelerometer behind the neck and the GPS lower on the back. The total package weighed 52.8 g (2.1 ± 0.2 % of body mass), a mass reported to have no measurable effect on trip duration

(Sagar & Weimerskirch 1996) and likely to have minimal impact on individual behaviour

(Phillips et al. 2003, Chivers et al. 2016).

Following instrumentation, individuals were returned to the nest to resume normal behaviours. Two days later, nests were visually monitored during local daylight hours and individuals that had returned to provision the chick were recaptured to retrieve the data loggers.

Body mass was recorded at return (during or after chick feeding depending on the individuals) and a 0.1 mL blood sample was obtained by venepuncture of a tarsal vein, for genetic sex determination (Parentage and Animal Genetic Services Centre, Massey University,

Wellington) and for stable isotope analyses. Handling time at capture and recapture did not exceed 15 min.

54

3.3.2 Data handling and processing

The GPS data processed to separate the individuals’ trips and keep the at-sea locations only

(see Chapter 2). The resulting trips were filtered with a cut-off threshold of 110 km·h-1 (Catry et al. 2004a) as stormy conditions occurred during the deployments. Trip metrics (duration, maximum distance from the colony, total distance travelled, average speed) were calculated with the adehabitat HR package (Calenge 2006) and tracks were linearly interpolated to 1 s intervals using the zoo package (Zeileis & Grothendieck 2005). The period of the day (dawn, day, dusk, night) was assigned for each time-location combinations, using the solar elevation with the maptools package (Bivand & Lewin-Koh 2017) and the nautical twilight (i.e. sun 12

° below the horizon) to define dawn and dusk. At night, the illuminated fraction of the moon was retrieved with the lunar package (Lazaridis 2014).

The acceleration data were used to infer the individuals’ behaviour at each second of their trip. To do so, the VeDBA was calculated (see Chapter 2), as well as the body pitch

푥 180 (pitch = 퐴푟푐푡푎푛 ( ) × ( )) using the static component of acceleration (Yoda et al. 1 휋 (푦2+ 푧2)2

2001). Then, a three-step process identified four key behaviours (supplementary Figure S1A): soaring flight, flapping flight, rafting on water and foraging on water. Firstly, time spent flying or on water was determined by travelling speed obtained from the GPS track, with speed <10 km·h-1 defining the time on water (Weimerskirch et al. 2002). Landings were inferred when birds stopped a behaviour in the air to start another on water. Secondly, a K-means clustering conducted on the heave axis data separated the time when the acceleration was steady (non- active bird) from the time when it was variable (active bird), using the Ethographer package

(Sakamoto et al. 2009a). Thirdly, as Thalassarche albatrosses feed predominantly on near surface prey grasped by surface seizing (98% of the feeding observations in (Harper 1987) and can submerge briefly to few meters deep (Prince et al. 1994a), prey encounters are expected to involve a negative body pitch < -20 º (Warwick-Evans et al. 2015) associated with sharp and

55 rapid movement to reach prey from surface. After visual inspection of the data, we used a negative body pitch < -30º on water associated with vectorial dynamic body acceleration peaks

> 1 g (Supplementary Fig S 3-1) during the bout to infer foraging behaviour. The frequency distribution of time between foraging behaviour revealed a sharp decrease for intervals >1 s

(68 % of all intervals <1 s, Supplementary Fig S 3-2) and, hence, this threshold was assumed to represent separate foraging events. As SBA were observed rafting and preening at sea in front of the colony, only trips > 3 km from the colony and including foraging behaviour were considered to be foraging trips.

To investigate the environmental parameters influencing the SBA foraging activity, the foraging trips were expressed as a standardised proportion of time spent foraging in 0.1° x 0.1° grid cells. The relationships between this foraging intensity index and bio-physical oceanographic variables, considered to influence directly or indirectly marine predators and their prey (Reisinger et al. 2018), was analysed with remote-sensed variables. Static- (depth, seafloor slope) and dynamic- (sea-surface wave height, sea-surface temperature, mixed layer depth, sea water velocity, mean sea-surface chorophyll-a concentration, wind speed) oceanographic variables (bathymetry was obtained from GEBCO www.gebco.net and others datasets from Copernicus http://marine.copernicus.eu/, supplementary Table S 3-1) were spatio-temporally overlaid with these cells using the raster package (Hijmans & Van Etten

2016).

Stable isotope analysis of nitrogen (δ15N) and carbon (δ13C), a proxy of the trophic ecology

(Jaeger et al. 2010), was used to infer the trophic level of individuals and quantify their niche width (Bearhop et al. 2004). The whole blood, a tissue integrating the assimilated diet over the

4 – 5 weeks prior to sampling for albatrosses (Ceia et al. 2015), was used to do this analysis and to determine the isotopic niche from ellipses metrics (as explained in Chapter 2).

56

3.3.3 Statistical analyses

All statistical analyses were conducted within the R statistical environment v. 3.4.2 (R Core

Team 2017). Different analysis were conducted on the mass, GPS trip metrics, activity budget, isotopic, and foraging behaviour data according to their respective characteristics. Data normality and variance homogeneity were respectively assessed with Shapiro-Wilk and

Bartlett tests. To compare the individuals’ body mass and mass gain estimation (one data per individual) between sex and year, Wilcoxon – Mann Whitney test and T-test were respectively used. Linear mixed models (LMMs) were used to compare the GPS trip metrics (duration, maximum distance to the colony, total distance travelled and mean trip speed) between sex and year (Table 3-1, Table S 3-2). They were fitted with individual identity as a random effect, to account for the hierarchical structure of tracking data and pseudo replication of repeated measures (Bolker et al. 2009) with the package nlme (Pinheiro et al. 2014). Similar LMMs were also used to investigate the influence of sex, year, period of the day and moon illumination on the birds’ activity budget.

Accounting for repeated measures has not been developed in circular statistics, hence, we selected the first trip of each individual to compare the destination bearings of the trips using a circular ANOVA implemented in the package circular (Agostinelli & Lund 2017). First trip hours of departure from and arrival to the colony were compared between sex and year with

Wilcoxon-Mann Whitney tests. Isotopic results were tested for sex and year potential differences with ANOVA. For foraging behaviour, the geographic distance between foraging periods was modelled with another LMM to investigate the influence of sex, year, period of the day and marine habitat (Table 3-3, Table S 3-2).

Finally, the environmental factors influencing the foraging was investigated using generalised additive mixed models (GAMM) implemented in the package mgcv (Wood 2018): the standardised time spent foraging (% of time spent foraging within a cell relative to the total of time spent foraging during the entire trip) as response variable, and the oceanographic

57 variables as explanatory variables. Prior to modelling, the oceanographic data were scaled and checked to avoid cross-correlation (Péron et al. 2012) with a cut-off of |r2| < 0.5. Model selection, for all LMMs and GAMM, was conducted by candidate models comparison of their

Akaike information criteria (AIC) using the package MuMin (Barton 2016). The best supported model, or by default the most parsimonious model, was identified by a model averaging procedure among the equally supported model with Δ AIC < 4 (Burnham et al. 2011) and retained (supplementary Table S 3-2) after validation based on the examination of residuals

(Zuur et al. 2009). Unless otherwise stated, all data are reported as Mean ± SE.

3.4 Results

3.4.1 At-sea movements and activity budget

GPS data were obtained from 33 individuals / 77 trips, and due to device malfunctions, were reduced for combined GPS and accelerometer foraging trips data to 26 individuals / 64 trips

(15 males / 43 trips, 11 females / 21 trips) totalling 3,700 h at sea. These individuals departed from and returned to the colony mostly during daylight (96 %) with the maximum occurring at

15:00 h. This timing was not significantly different between departures / returns, sex and year

(Wilcoxon tests, W = 2867, 2642, 3112 respectively). Individuals departed with a body mass of 2.65 ± 0.03 kg, without significant difference between sex and year (Wilcoxon tests, W =

89, 93 respectively). At recapture, their mass gain estimation was not significantly different between sex (t test, t18 = - 0.6) but showed a higher value in 2016 with 219 ± 43 g than in 2017 with 32 ± 54 g (t test, t29 = 2.6, P = 0.01).

Foraging trips varied greatly in duration (2 - 315 h) with a skewed distribution towards short duration trips (mode = 3 h). Brief single day trips (2 - 9 h, 26 % of the trips) were undertaken close to the colony (6 – 82 km away) around the narrow peri-insular shelf enclosing this volcanic island (Figure 3-1A). Short overnight trips (12 - 29 h, 27 %) were used to forage further (up to 231 km) off the southwest corner of New Zealand’s South Island, in neritic, shelf-

58 slope and oceanic waters (Figure 3-1B). Multiple-day trips (3 – 14 days, 46 %) reached distant locations (up to 1575 km away) in various regions of the New Zealand and Australian shelves,

Tasman Sea, south Pacific ocean and subantarctic waters (Figure 3-1C). Nearshore coastal habitats were also used by individuals foraging within the channels between the coastal islands of south-eastern Tasmania, Fiordland and Otago Peninsula (Figure 3-1 B and C).

Both sexes in both years conducted the three types of foraging trips, with sample sizes showing independency between these factors (Chi-square test, χ² = 4.3 and χ² = 0.6 respectively). In the same way, the trip direction bearing did not differ significantly between sex or year (circular ANOVA, respectively F1,75 = 1.6 and F1,75 = 0.1). Models investigating the influence of the year and sex on the trips parameters revealed no significant influence for single day and overnight trips, but significant influences for multiple days trips (Table 3-1). Multiple days trips by males had a shorter duration by 54 ± 23 h (P < 0.05), covered shorter total distance by 1565 ± 494 km (P < 0.01) and reached closer maximum distance from the colony by 411 ±

124 km (P < 0.05) compared to females, but travelled at the same mean trip speed. The year influenced only the mean trip speed (Table 3-1), with long trips in 2017 slower by 3.4 ± 1.6 km.h-1 (P < 0.05) than in 2016.

59

Figure 3-1 : At-sea movements of breeding southern Buller’s albatross (males in orange, females in yellow) during the post-guard stage at Hautere/Solander Island in 2016 and 2017. Foraging events are represented by the red dots (when acceleration data was available), land by the shaded grey areas and colony site by the black triangle. The dashed white line represents the average position of the subtropical front (STF), estimated by the 10 °C isotherm (Heath 1985).

60

Table 3-1. Summary of the linear mixed models (LMMs) outputs used to assess the trends in activity budget and foraging trip parameters of breeding southern Buller’s albatross at Hautere/Solander Island. LMMs include individual identity as random effect. Bold figures show the explanatory variables with significant P value.

Response variable Explanatory variables Parametric coefficients P value Est. SE t % time spent rafting on water Intercept 6.9 3.4 2.0 0.04 Sex (male) 4.2 3.4 1.2 0.22 Year (2017) 4.8 3.3 1.4 0.16 Period of the day (day) 6.3 2.3 2.6 < 0.01 Period of the day (dusk) 8.1 2.5 3.2 < 0.01 Period of the day (night) 48.8 2.3 20.3 < 0.001 % nocturnal time spent rafting on water Intercept 32.9 5.5 5.9 < 0.001 % moon illuminated 18.8 7.7 2.4 0.01 Year(2017) -10.5 4.8 -2.1 0.03 % time spent foraging Intercept 0.17 0.04 4.3 < 0.001 Sex (male) 0.13 0.03 3.6 0.001 Year (2017) -0.08 0.03 -2.3 0.02 Period of the day (day) 0.11 0.03 3.03 0.002 Period of the day (dusk) -0.04 0.04 -1.04 0.3 Period of the day (night) -0.02 0.03 -0.5 0.5 Nocturnal landing rate Intercept 1.2 0.1 7.7 < 0.001 Moon illumination 0.2 0.2 0.9 0.3 Year(2017) 0.5 0.1 3.0 0.005 Trip duration (single day) Intercept 2.9 0.8 3.6 0.004 Sex (male) 0.75 0.9 0.8 0.4 Year (2017) 0.5 0.9 0.6 0.5 Trip duration (overnight) Intercept 17.3 3.0 5.7 < 0.001 Sex (male) 4.2 3.1 1.3 0.2 Year (2017) -0.8 2.2 -0.3 0.7 Trip duration (multiple days) Intercept 154.4 21.3 7.2 < 0.001 Sex (male) -54.7 23.2 -2.3 0.02 Year (2017) -8.9 22.6 -0.4 0.6

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Total distance travelled (single day) Intercept 35.8 24.8 1.4 0.1 Sex (male) 22.6 27.9 0.8 0.4 Year (2017) 49.8 27.9 1.7 0.1 Total distance travelled (overnight) Intercept 323.0 96.5 3.3 0.006 Sex (male) -36.5 71.6 -0.5 0.6 Year (2017) -1.6 101.3 -0.01 0.9 Total distance travelled (multiple days) Intercept 3686 452 8.1 < 0.001 Sex (male) -1565 494 -3.1 0.004 Year (2017) -858 484 -1.7 0.08 Max. distance from the colony (single day) Intercept 13.9 11.6 1.1 0.2 Sex (male) 15.3 13.0 1.1 0.2 Year (2017) 7.3 12.7 0.5 0.5 Max. distance from the colony (overnight) Intercept 115.3 27.5 4.1 0.001 Sex (male) -39.8 28.9 -1.3 0.2 Year (2017) -19.3 20.4 -0.9 0.3 Max. distance from the colony (multiple Intercept 738 112 6.5 < 0.001 days) Sex (male) -411 124 -3.3 0.02 Year (2017) 51 122 0.4 0.6 Average trip speed (single day) Intercept 12.7 4.3 2.9 0.01 Sex (male) 9.4 4.8 1.9 0.07 Year (2017) 4.8 4.7 1.0 0.3 Average trip speed (overnight) Intercept 19.2 3.5 5.4 < 0.001 Sex (male) -4.8 3.7 -1.3 0.2 Year (2017) -1.6 2.6 -0.6 0.5 Average trip speed (multiple days) Intercept 23.0 1.4 15.5 < 0.001 Sex (male) -2.3 1.6 -1.4 0.1 Year (2017) -3.4 1.6 -2.1 0.04

When recorded, successive trips indicated the presence of multiple foraging strategies.

Primarily, a dual short-long trip strategy was noted for 14 individuals, alternating one multiple-

day trip with one or several shorter ones towards different areas (Figure 3-2A). Secondarily,

short-term consistency was noted for 4 individuals repeating trips within the same areas (Figure

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3-2B). The remainder (3 individuals) undertook 2 – 3 single day and overnight trips with no clear pattern.

Figure 3-2 : Foraging strategies used by southern Buller’s albatrosses over successive foraging trips, represented with two representative individuals (one in black, one in white). The panel A shows the short / long trips alternation, and panel B the consistency over several trips undertook in the same area. The red triangle shows the colony location.

Individuals spent most of their time at sea in soaring flight (53.3 ± 2.6 %), followed by rafting on water (42.0 ± 2.4 %). Flapping flight represented 4.3 ± 0.5 % of the time and foraging behaviour only 0.30 ± 0.03 %. Birds spent most of their time engaged in behaviours with low vectorial dynamic body acceleration (Table 3-2). LMMs revealed that the percentage of time spent on water was not influenced by the sex or year, but was significantly increased by 48 ±

2 % at night (P < 0.001) at the expense of flying behaviours. Conversely, the proportion of time spent foraging increased by 0.13 ± 0.03 % for males (P = 0.001), increased by 0.11 ± 0.03

% during the day (P < 0.01), and was reduced by 0.08 ± 0.03 % in 2017 (P = 0.02).

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Table 3-2 : Activity patterns during southern Buller’s albatross foraging trips and associated vectorial dynamic body acceleration (VeDBA) values (mean ± SE) sampled at post-guard stage (n = 26 individuals / 64 trips / 3700 h at sea). Bold figures highlight the majority of time in each period of the day.

Behaviour Proportion of time at sea (%) VeDBA.s-1 (g) dawn day dusk night Floating 11.1 ± 0.8 23.5 ± 1.2 17.7 ± 1.0 60.4 ± 1.3 0.16 ± 4.10-5 Soaring flight 85.6 ± 0.9 72.2 ± 1.3 79.7 ± 1.1 38.1 ± 1.3 0.17 ± 5.10-5 Flapping flight 2.9 ± 0.3 3.6 ± 0.2 2.2 ± 0.2 1.1 ± 0.1 0.26 ± 9.10-5 Foraging 0.25 ± 0.02 0.48 ± 0.03 0.22 ± 0.02 0.24 ± 0.008 0.47 ± 2.10-3

Figure 3-3 : Temporal distribution of average (mean ± SE) foraging time (orange) and landing rate (blue) during foraging trips of southern Buller’s albatross provisioning chick. Shaded area represent in light grey the twilight periods (dawn and dusk) and in dark grey the night during the tracking periods. The time of day refers to the New Zealand local time.

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The time spent foraging and the landing rate showed similar trends during a day (Figure

3-3). Individuals displayed an average landings rate of 0.70 ± 0.02.h-1 during their trips, that reached 0.99 ± 0.04.h-1 during daylight and that decreased to 0.61. ± 0.05 h-1 at twilight and to

0.51. ± 0.02 h-1 at night. During night-time recorded through all the moon phases, LMMs showed that the illuminated fraction of the moon had no significant influence on the percentage of time spent foraging and the landing rate, but positively influenced the percentage of time spent flying (P = 0.01, Table 3-1).

3.4.2 Foraging behaviour and trophic niche

During these at-sea movements, a total of 6,658 foraging behaviour events were inferred, between 1 and 551 per trip according to their duration. These foraging events lasted between

1-60 s, with a highly skewed distribution towards short durations (94 % of events < 10 s, mode

= 2 s). They were spread along the entire trip with no clear bias between the outward, central and inward phases of the trips (Figure 3-1).

These foraging events occurred in short periods of activity (bouts), with the time interval skewed towards short values. Inspection of the time interval distribution indicated that events separated by less than 660 s were likely to be clustered within the same foraging period

(Supplementary Fig S 3-3). Applying this threshold, SBA foraging occurred at a rate of 0.44 ±

0.02 periods·h-1 that were separated by a variable geographically distance (in straight line) between 0.09 and 490 km. LMM revealed this distance not significantly influenced by year and sex (Table 3-3).

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Table 3-3 : Summary of the models outputs used to assess the trends in foraging behaviour of breeding southern Buller’s albatross at Hautere/Solander Island. These linear mixed model (LMM) and generalised additive mixed model (GAMM) bit include individual identity as random effect.

Model Response variable Explanatory variable Parametric Approximate P value coefficients significance of smooth terms Est. SE t edf F LMM Interval distance Intercept 47.2 6.4 7.3 - - < 0.001 between foraging events Sex (male) -5.7 3.9 -1.4 - - 0.16 Year (2017) -0.2 3.8 -0.07 - - 0.9 Period of the day (day) 9.9 5.1 1.9 - - 0.05 Period of the day (dusk) 17.2 6.5 2.6 - - 0.009 Period of the day (night) 4.0 5.1 0.7 - - 0.4 Marine habitat (neritic) -35.3 3.9 -8.8 - - < 0.001 Marine habitat (slope) -25.0 4.0 -6.2 - - < 0.001 Marine habitat (bathyal) -15.9 3.9 -1.4 - - 0.1 GAMM Log(standardised time wave height - - - 2.6 2.3 0.06 spent foraging) sea surface temperature - - - 6.1 6.5 < 0.001 mixed layer thickness - - - 4.4 3.6 < 0.01 depth - - - 3.5 6.5 < 0.001 seafloor slope - - - 1.0 11.4 < 0.001

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While individuals spent their overall time at sea in neritic waters (< 200 m, 38.2 %), in slope waters (200 – 1000 m, 36.4 %), in bathyal waters (1000 – 2000 m, 8.0 %) and in abyssal waters

(17.2 %), their time spent foraging was concentrated in neritic waters (47.9 %), followed by slope waters (34.6 %), abyssal waters (10.5 %) and bathyal waters (6.9 %). These marine habitats influenced significantly the geographic distance separating foraging periods (P <

0.001), with greatest distances observed in descending order in abyssal (55 ± 5 km), bathyal

(33 ± 5 km), slope (23 ± 1 km) and neritic waters (14 ± 1 km).

The period of the day also significantly influenced this distance (P < 0.001), being greater by 17 ± 6 km at dusk. Foraging behaviour encompassed a wide range of oceanographic conditions on a sea surface varying in temperature between 9.8 and 20.1 °C, agitated by wind blowing between 0.2 and 17.7 m.s-1, with wave heights between 0.5 – 7.8 m and current speed from 0 to 0.6 m.s-1. The sea-surface chlorophyll-a concentration varied between 0.08 – 3.2 mg.m-3, and the mixed layer depth ranged between 7-202 m.

The GAMM modelling revealed the time spent foraging to be influenced by the five following oceanographic variables (Table 3-1): the mixed layer deepening beyond 50 m had a positive effect while the wave height and the seafloor slope (superior to 2.5 °) had negative effect. The depth increase had a negative effect in neritic and slope waters and a variable effect with large confidence intervals in bathyal and abyssal waters. The sea surface temperature had contrasted effects, positive for cold (10 - 12.5 °C) and hot (17 - 20 °C) temperatures, but negative between these values (Figure 3-4).

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Figure 3-4 : Influence of oceanographic variables on the standardised time spent foraging of southern Buller’s albatross predicted by generalised additive mixed model (GAMM) during post-guard stage at Hautere/Solander Island. The grey area indicates the 95 % confidence interval.

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The isotopic results were grouped with small variation for δ15N and δ13C values (Figure 3-

5). All individuals fed at a high trophic level characterised by δ15N= 14.7 ± 0.3 ‰, with the exception of one individual. This lower outlier (δ15N = 12.8 ‰) was the only individual foraging in subantarctic waters, to -51.2°S (Figure 3-1). Given the isotopic baseline variation between subtropical and subantarctic water masses (Quillfeldt et al. 2005) biasing their comparison, this atypical individual was excluded from further analysis.

15 In subtropical waters, δ N values showed minor differences between sexes (ANOVA, F1,17

= 13.7, P < 0.001) with δ15N = 14.9 ± 0.4 ‰ for males and 14.5 ± 0.2 ‰ for females (mean ±

SD) but not between years. δ13C values showed minor differences between sexes and years

13 (ANOVA, respectively F1,17 = 6.3, P = 0.01 and F1,17 = 9.2, P = 0.004) with δ C = -18.3 ± 0.2

‰ in 2016 and -18.5 ± 0.3 ‰ in 2017 (Table 3-4). Consequently, the isotopic niches were estimated by ellipses for each sexes and years combinations (Figure 3-5).

The ellipses areas ranged from 0.08 to 0.30 ‰2, with differences between groups: females were likely to have smaller ellipse area than males in any year. Within sexes, opposite inter- annual differences occurred with males likely to have a smaller ellipse in 2017, and conversely, females likely to have a smaller ellipse in 2016. The grouped isotopic results generated ellipses overlaps which were, in descending order, greatest for males between years, sexes within year, sexes between years and females between years (Supplementary Table S 3-3).

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Figure 3-5 : Isotopic niche (from whole blood) of breeding southern Buller’s albatrosses provisioning chick at Hautere/Solander island, represented by the 40 % corrected standard ellipse area (SEAc) Individuals’ signatures are shown for males in 2016 by the dark blue squares, for males in 2017 by the light blue triangles, for females in 2016 by the coral squares and for females in 2017 by the red triangles.

Table 3-4. Isotopic values (whole blood, Mean ± SD) of males and females southern Buller’s albatrosses provisioning chick at Hautere/Solander island recorded in 2016 and 2017. Their isotopic niche widths are reported for the corrected standard ellipse area (SEAc) and Bayesian standard ellipse area (SEAB).

13 15 2 2 Year Sex N δ C (‰) δ N (‰) SEAC (‰ ) SEAB (‰ ) TOTAL (- outlier) 40 -18.4 ± 0.2 14.7 ± 0.3 0.29 0.28 2016 male 9 - 18.3 ± 0.2 14.9 ± 0.4 0.30 0.27 2016 female 7 - 18.3 ± 0.1 14.5 ± 0.2 0.12 0.08 2017 female 11 - 18.7 ± 0.2 14.4 ± 0.2 0.17 0.14 2017 male 13 - 18.4 ± 0.2 14.8 ± 0.3 0.26 0.19

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3.5 Discussion

Using two years of GPS, accelerometer, isotopic and oceanographic data, the present study provided fine-scale information on the foraging behaviour and its drivers of chick-rearing SBA during winter. Individuals foraged primarily on the New Zealand South Island peri-insular shelf in neritic and slope waters. Parents alternated long and short foraging trips, including repeated trips within the same area and very brief single-day trips in waters surrounding the colony.

During their trips, their activity budget was typical for albatross and primarily influenced by the period of the day. Foraging behaviour represented only a small proportion of their time, and occurred in short bouts spread during their entire trips, with increased during daytime.

Although males and females shared this foraging strategy in both years, some differences between the sexes occurred. Males were engaged in shorter long trips and spent more time foraging than females. The isotopic results were clustered together and showed only minor variation for δ13C and δ15N between sexes and years. While their foraging effort was comparable to others albatross species, SBA time spent foraging was found influenced by static and dynamic oceanographic variables, e.g. depth, seafloor slope, mixed layer thickness, wave height and sea surface temperature.

3.5.1 At-sea movements and activity budget

The marine areas exploited in the present study are consistent with those previously reported for the species (Sagar & Weimerskirch 1996, Stahl & Sagar 2000a, Stahl & Sagar 2000b,

Torres et al. 2013). However, while previous studies during chick rearing found individuals remaining within a restricted range around the colony (Stahl & Sagar 2000a, Stahl & Sagar

2000b), individuals in the present study covered a wider range that expand the known foraging range of SBA during the post-guard stage. In addition, some individuals were observed to circumnavigate New Zealand South Island and frequent the east coast of the North Island, which is consistent with previous ship-borne observations (Stahl et al. 1998).

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These findings suggest that inter-annual availability in prey distribution may alter the foraging areas of breeding birds. Fine-scale records confirmed the brief, short and long foraging trips described by Stahl et al (2000a). The finer resolution provided by the GPS in the present study also revealed undocumented very short duration foraging trips, within close proximity to the colony. This strategy seems uncommon for far-ranging large and small albatrosses, usually foraging for several days at greater distances from the colony during chick-rearing (Torres et al. 2011, Pereira et al. 2018, Sztukowski et al. 2018, Thiebot et al. 2018).

Despite foraging areas shared between sexes, the shorter and closer foraging trips during post-guard stage undertaken by males contributed to a fine-scale spatial segregation (Pereira et al. 2018) for a species with little sexual dimorphism (Sagar et al. 1998). Shorter trips by males were consistent with earlier observations of the species (Stahl & Sagar 2000b). The tracked individuals displayed some flexibility in their at-sea movements, with usage of different strategies. Alternating between short and long trips is a bimodal strategy observed in many seabirds, and enables parents to maximise food delivery to the chick and restore parental body condition (Chaurand & Weimerskirch 1994, Ropert-Coudert et al. 2004, Brown et al. 2012).

Repeated successive short trips consistently within the same area is a strategy used when the environment is predictable (Weimerskirch 2007).

Using both strategies, SBA at-sea movements appear to be intermediate between the closely related shy albatross (T. cauta), a resident species using year-round predictable areas of the south-east Australian continental shelf (Mason et al. 2018) and migratory congenerics

(Thalassarche) or oceanic species (Diomedea) able to adapt to a wider range of oceanographic conditions. Further tracking data over longer durations with accurate measures of chick provisioning and prey content would be required to fully understand the respective advantages of these foraging strategies by SBA.

During these at-sea movements, the activity budget obtained from fine-scale acceleration data allowed comparison with previous albatross studies that have inferred time spent in flight,

72 on water and landings from GLS wet/dry data loggers. In the present study, SBA flight, landing on water and foraging activities occurred throughout all times of the day and night but were more frequent during the daylight hours. This activity pattern reflects the constraint of available light for these visual predators (Weimerskirch & Wilson 1992) and is typical for albatrosses

(Table 3-5). The SBA activity budget did not differ between the sexes, as reported for other albatross species (Phalan et al. 2007). Their landing rate (index of foraging activity) and proportion of time spent on water was similar to values reported for shelf-specialised black- browed (T. melanophrys) and shy (T. cauta) albatrosses (Weimerskirch & Guionnet 2002,

Hedd 2001, Phalan et al. 2007). In contrast, oceanic species appear more variable, with some displaying higher rates of landings (yellow-nosed T. chlororynchos, wandering D. exulans royal D. epomophora and Amsterdam D. amsterdamensis albatrosses, Weimerskirch &

Guionnet 2002, (Waugh & Weimerskirch 2003), others lower (light-mantled sooty albatross

Phoebetria palpebrata, Weimerskirch & Guionnet 2002), and some with different amounts between day and night (grey-headed albatross, (Catry et al. 2004b). These comparisons suggest that SBA landing rate and proportion of time on water were not increased in response to reduced daylight hours (Systad et al. 2000) compared to summer breeding congenerics.

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Table 3-5. Comparative activity pattern (percentage of time, mean ± SD) of albatrosses tracked with activity-recorder loggers. The number of tracked individuals and their chick-rearing stage (CR) is further indicate when available (G = guard, PG = post-guard). Italic figures in percentage flying column represent the back-calculated figures from the percentage on water reported (100 - percentage). Data are sourced from: (1)(Prince & Francis 1984), (2)(Weimerskirch & Guionnet 2002), (3) (Catry et al. 2004b), (5) (Hedd et al. 2001) and (6)(Kappes et al. 2015).

Species Breeding stage N percentage of daytime percentage of night-time Source flying on water landing.h-1 flying on water landing.h-1 Grey-headed albatross Thalassarche chrysostoma CR 13 84.9 15.1 ± 9 na 50.1 49.9 ± 14.6 na 1 PG 4 84.9 15.1 0.74 38.1 61.9 0.59 2 CR 4 81 ± 16 19 0.99 ± 0.3 6 94 ± 7 0.14 ± 0.1 3 PG 4 85.7 14.3 ± 6 na 9.5 90.5 ± 4 na 4 Black-browed albatross Thalassarche melanophrys PG 6 76.0 24 0.98 32 68 0.67 2 PG 12 78.9 21.1 ± 7 na 30 70.0 ± 6 na 4 Yellow-nosed albatross T. chlororhynchos PG 9 70.0 29.9 1.26 16.6 83.31 0.69 2 Shy albatross T. cauta G 21 73.4 26.6 ± 16 na 53.7 46.3 ± 29 na 5 Dark-mantled sooty albatross Phoebetria fusca G 3 78.1 21.9 0.40 39.2 60.8 0.20 2 Light-mantled sooty albatross P. palpebrata PG 3 78.4 21.6 ± 6 na 42.5 57.5 ± 9 na 4 Wandering albatross Diomedea exulans PG 17 67.5 32.5 ± 12 na 28.9 71.1 ± 18 na 4 Present Southern Buller’s albatross Thalassarche b. bulleri PG 26 75.8 ± 6 23.5 ± 6 0.99 ± 0.0 39.2 ± 6 60.4 ± 6 0.51. ± 0.0 study Laysan albatross Phoebastria immutabilis PG 34 86.8 ± 9 13.2 1.01 ± 0.5 66.8 ± 19 33.2 0.64 ± 0.4 6 Black-footed albatross P. nigripes PG 26 86.9 ± 7 13.1 0.84 ± 0.2 73.0 ± 12 27 0.46 ± 0.1 6

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3.5.2 Foraging behaviour and trophic niche

The location of foraging events from acceleration in the present study provided novel insights into how the species obtains its daily food intake, previously estimated at 750 g.d-1 for similar-sized albatross (Catry et al. 2004b). In space and time, foraging behaviour occurred throughout the trips and at any time of the day, suggesting widely distributed prey in space and time. However, foraging bouts occurred mainly in bursts during periods that were separated in space and time by short intervals. These findings suggest feeding on aggregated and patchy prey, which were variable according the period of the day and the marine habitat (intervals were longer at dusk and in oceanic waters). This patchiness is also consistent with the previously reported opportunistic and localised feeding on prey captured by marine mammals

(Bräger 1998), in interaction with fishing vessels (Torres et al. 2013), or on offal from shearwater harvesting discharged at sea (Waugh et al. 2017) that can represent an alternative food source for SBA during the chick-rearing period.

The quantification of the foraging behaviour showed a reduced nocturnal foraging activity, while mainly rafting on the sea surface, suggests a secondary “sit and wait” foraging technique

(Weimerskirch et al. 1997). The lack of a relationship between moonlight illumination and time spent foraging at night further suggests this strategy may be opportunistic. Such nocturnal foraging in grey-headed albatross (T. chrysostoma) has been reported to lead to smaller meals with prey of higher water content (e.g. salps, jellyfish, (Catry et al. 2004b). Hence, SBA could focus on bioluminescent and vertically migrating prey reaching surface at night such as bioluminescent salps (Swift et al. 1977, Andersen & Sardou 1994), which are reported to be an abundant prey item in SBA diet (James & Stahl 2000). In addition, the quantification of the foraging behaviour revealed a difference between the sexes, with males providing a higher foraging effort than females. In combination with their shorter long trips (and thus, more frequent visits to the chick), these findings are consistent with the asymmetrical parental investment reported in summer-breeding and winter-breeding albatrosses, where males engage

75 more frequently in short trips than females, and deliver more food to the chick (Weimerskirch et al. 1997, Weimerskirch & Lys 2000, Hedd & Gales 2005, Phillips et al. 2017). Therefore, male SBA are likely to be more involved in the chick provisioning during winter than females.

In addition, inter-annual variation occurred with lower time spent foraging in 2017, in association with a lower mass gain estimation and slower foraging trips. These findings suggest a lower food availability in 2017, likely to be related with the inter-annual changes of the marine environment (individuals foraged in waters characterised by sea surface temperatures of 14.9 ± 0.07 °C in 2016 against 13.9 ± 0.04 °C in 2017). However, tracked individuals relied heavily on the shelf and slope waters in both years of the study, a common feature with many summer breeding congenerics: the black-browed (Cherel et al. 2000, Wakefield et al. 2011),

Chatham (Deppe et al. 2014), white-capped (Torres et al. 2011), Shy (Brothers et al. 1998,

Hedd et al. 2001), Indian yellow-nosed (Makhado et al. 2018) and Campbell (Waugh et al.

1999, Sztukowski et al. 2018) albatrosses. In contrast, the grey-headed albatross exploits deeper pelagic waters in association with the polar frontal zone (Waugh et al. 1999, Nel et al.

2001, Catry et al. 2004b).

The higher foraging activity found in neritic waters in the present study suggests the New

Zealand shelf provides a predictable concentrated winter prey resource, which is likely to induce foraging site fidelity (Stzukowski 2018) in SBA. Modelling revealed foraging time was greater on the shelf in areas with shallow depth and gentle seafloor slope, where the mixed layer deepens, with additional influence of sea-surface temperature and wave height. These findings reinforce the reliance by the species on the shelf where dynamic mixing occurs at fine spatio-temporal scale (Vincent et al. 1991) and is likely to influence the availability of SBA prey.

Prey capture rates in pelagic foraging grey-headed albatross were found to not be influenced by wave height (Catry et al. 2004a). In contrast, wave height had a negative influence on time spent foraging by SBA, which happened primarily in neritic waters. This suggests potential

76 different environmental drivers of foraging suitability between pelagic and neritic habitats. For the Tasman Sea, the projected response to climate change predict intensification of currents and increase in eddy activity (Matear et al. 2013). These conditions were found to increase prey encounter rate in oceanic feeding wandering albatrosses, thanks to windier conditions

(Weimerskirch et al. 2012). However, whether increased eddies with windier and higher wave regimes mixing more the upper ocean could positively or negatively impact SBA foraging in different marine habitats needs further research.

The isotopic investigation of the trophic niche corroborated the GPS results obtained in the present study, with δ13C values consistent with subtropical / subantarctic waters signature

(Cherel & Hobson 2007). The δ15N values were also consistent with its diet, constituted by weight from 65 % of fishes, 24 % of salps and 7 % of cephalopods (James & Stahl 2000); as well as with the δ15N values characterizing a fish dominated diet in New Zealand inshore waters

(Flemming & Van Heezik 2014). Despite the SBA generalist diet including 89 prey items from three trophic levels (West & Imber 1986, Cherel & Klages 1998, James & Stahl 2000), its isotopic niche measured in the present study was narrow, suggesting a proportional consumption of similar prey types by individuals. In other albatross species, δ13C and δ15N values display a greater variability (Bugoni et al. 2010, Jaeger et al. 2010) and greater ellipses areas (Jiménez et al. 2017), with no difference between sexes from feathers and blood cell isotope data (Phillips et al. 2011). While the difference of δ15N between sexes in the present study is minor (0.4 ‰), it could relate to the propensity for females to fed more on cephalopods and crustaceans than males (James & Stahl 2000). In addition, while fisheries discards are an important food item of SBA (James & Stahl 2000), a higher δ15N in male blood by 0.6 ‰ was reported for the waved albatross Phoebastria irrorata when male-biased access to fishery discards occurred (Awkerman et al. 2007). Despite limited SBA interaction with fishing vessels being reported during the guard stage at The Snares Islands (Torres et al. 2013), these findings could indicate more interaction happening at Solander during the post-guard stage. Indeed, this

77 period coincides with the Hoki Macruronus novaezelandiae trawling season (New Zealand’s largest trawl fishery), a SBA prey with high energetic value (Schaafsma et al. 2018) that can be targeted to feed the chick. While feeding on fisheries discards can be beneficial for the population (James & Stahl 2000), SBA is also considered to be at “very high risk” of commercial fishing-related mortality (Richard & Abraham 2013). Therefore, further year- round tracking data of both birds and vessels are needed to determine with more accuracy the cost-benefit of this complex interaction.

In summary, the present study revealed that SBA rely heavily on the neritic and slope waters of the New Zealand South Island to provision their chick through the austral winter, but also displayed some variability in foraging strategies, with excursions further into oceanic waters.

During these trips, there was no evidence of increased foraging effort or nocturnal compensation for shorter day length. Instead, a high foraging event rate and activity level were recorded, comparable to that found in summer breeding albatrosses. Hence, foraging conditions on the New Zealand shelf are not only favourable for other albatrosses during summer (Waugh et al. 1999, Thompson et al. 2014), but also during winter for SBA which may benefit from the presence of shoaling and spawning prey (Zeldis 1985, Uozumi & Forch 1995, Daponte et al.

2013). In addition, SBA may benefit of the release of competition with New Zealand summer breeding species. Indeed, millions pairs of petrels, and prions, as well as > 200,000 pairs of Thalassarche (Waugh et al. 2013, Jamieson et al. 2016, Miskelly et al. 2019), authors unpublished data) vacate their colonies in winter and shift for their non-breeding distribution

(Shaffer et al. 2006, Thompson et al. 2014). Therefore, winter foraging off the New Zealand coast seems adapted to the year-round prey availability across the south Pacific basin for this longitudinal migratory species (Stahl & Sagar 2000b).

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3.6 Supplementary material

Table S 3-1: Environmental variables details. Dynamic variables (*) were gathered from Copernicus (http://marine.copernicus.eu/services-portfolio/access-to-products/).

Spatial / Abbreviation description Unit temporal Product resolution DEPTH Ocean depth m 0.008° / - GEBCO SLOPE Ocean floor slope ° 0.083° / - Derivated from DEPTH WAVE* Sea surface wave significant height m 0.083° / 3 hours Global_Analysis_Forecast_Wav_001_027 SST* SST, Sea surface temperature °C 0.083° / daily Global_Analysis_Forecast_PHY_001_024 UCURR* Eastward sea water velocity m.s-1 0.083° / daily Global_Analysis_Forecast_PHY_001_024 VCURR* Northward sea water velocity m.s-1 0.083° / daily Global_Analysis_Forecast_PHY_001_024 CHLA* Mean chlorophyll a concentration mg.m-3 0.5° / weekly Global_Analysis_Forecast_Bio_001_014 UWIND* Eastward 10m wind speed m.s-1 0.25° / 6 hourly Cersat-Glo-Blended_Wind-L4-V5-OBS VWIND* Northward 10m wind speed m.s-1 0.25° / 6 hourly Cersat-Glo-Blended_Wind-L4-V5-OBS

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A

B

Fig S 3-1: Decision tree (A) and example of the method used to assign key behaviours (B) to southern Buller’s albatross during their foraging trips according to their GPS and acceleration data.

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Fig S 3-2: Frequency distribution of the time intervals between foraging behaviour recorded within foraging trips of southern Buller’s albatross.

Fig S 3-3: Frequency distribution of the time intervals between foraging events recorded within foraging trips of southern Buller’s albatross. The red line represents the threshold established by visual inspection of the data.

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Table S 3-2: Best and most parsimonious models selected explaining the GPS trips and time spent foraging trends of southern Buller’s albatross raising chick at Hautere/Solander Island.

Model formula AICc ΔAIC Weight LMM Trip duration ~ sex + year 860 0.0 0.92 Total distance travelled ~ sex + year 1293 0.0 0.99 Maximum distance from the colony ~ sex + year 1066 0.0 0.98 Average speed ~ sex + year 527 0.0 0.36 Interval distance between foraging ~ sex + year + period of day + marine habitat 60382 0.0 0.55 GAMM Log(std_time spent foraging) ~ depth+ mixed layer thickness + seafloor slope 4186 0.0 0.23 + SST + wave

Table S 3-3: Pairwise comparison of 1) the probability to be smaller, and 2) the percentage of

overlap (in italics) between Bayesian standard ellipses areas (SEAB) of breeding southern Buller’s albatrosses provisioning chick at Hautere/Solander Island (New Zealand).

Females 2016 Males 2016 Females 2017 Males 2017 Females 2016 - 0.98 / 21 0.82 / 1.5 0.93 / 18 Males 2016 0.02 / 53 - 0.08 / 1.1 0.23 / 75 Females 2017 0.17 / 2.2 0.91 / 0.6 - 0.76 / 6.5 Males 2017 0.06 / 40 0.76 / 64 0.23 / 40 -

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Chapter 4:

Foraging niche overlap during chick-rearing in the

sexually dimorphic Westland petrel

A version of this chapter has been submitted as:

Timothée A Poupart, Susan M Waugh, Akiko Kato, John PY Arnould (in review). Foraging niche-overlap during chick-rearing in the sexually dimorphic Westland petrel. Roy Soc Open

Sci.

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4.1 Abstract

Most Procellariform seabirds have a pelagic existence, breed in summer when prey availability peaks, and migrate from breeding areas during winter. Additional common features of this group include a dual foraging strategy (short trips for chick-provisioning, long trips for self-maintenance) and sex-specific foraging niches associated with sexual size dimorphism.

The Westland petrel Procellaria westlandica, a New Zealand endemic, is one of only 9.8 % seabirds that breed in winter. Previous findings suggest this large, sexually-dimorphic petrel has a relatively narrow foraging range, displays no evidence of a dual foraging strategy and shares foraging areas between sexes. To investigate further the mechanisms of this unusual strategy, the present study determined the fine-scale at-sea behaviours (GPS and accelerometer data loggers) and trophic niches (stable isotopes of carbon and azote in whole blood) of chick- rearing individuals (16 males, 13 females). All individuals foraged on the peri-insular shelf slope of New Zealand’s South Island western coast in short, unimodal trips. Both sexes displayed a high foraging rate (2.7 events.h-1) without temporal, spatial or isotopic niche segregation. However, slight differences in flying speed and influences of oceanographic variables on time spent foraging were found suggesting minor sexual differences in habitat use.

These findings suggest the presence of a winter prey resource close to the breeding colony sufficiently abundant to satisfy the nutritional needs of breeding without increased foraging effort or intra-specific competition avoidance. Additional data are needed to assess the consistency of foraging niche overlap between the sexes and its reproductive outcomes in view of anticipated environmental changes.

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4.2 Introduction

Seabirds comprise 359 species worldwide (Dias et al. 2019) which play an important role in marine food-webs through top-down control and nutrient cycling. Procellariforms, characterised by their tubular nostrils on the upper mandible, represent the largest proportion of seabirds (128 species) and are responsible of the biggest consumption of marine resources

(~ 24.1 millions tons.year-1, (Brooke 2004). They range in size from the smallest storm-petrel

(wing span 32 cm, body mass 20 g) to the largest albatross (wing span 300 cm, body mass

12,000 g, Prince & Morgan 1987). While their successful adaptive radiation has led

Procellariforms to occupy diverse ecological niches from tropical to polar regions (Warham

1996), they still share common life history traits linked to their unique pelagic life style.

In the open ocean, these species rely on visual and olfactory cues (Abolaffio et al. 2018) to forage on epipelagic fish, squid and crustacean. Within this highly spatio-temporally variable marine environment (Stommel 1963, Haury et al. 1978), prey availability at surface is unpredictable at a fine-scale (Weimerskirch 2007). To maximise prey encounters,

Procellariforms have to prospect wide areas by covering long distances within a large range

(Weimerskirch et al. 2005), and increase path sinuosity when crossing a favourable patch

(Fauchald & Tveraa 2003, Weimerskirch et al. 2007). This energetic constraint is traditionally seen as the cause of their “K” reproductive strategy (MacArthur & Wilson 1967) with delayed sexual maturity, low fecundity, slow growth of a single offspring and long lifespan (Ricklefs

1990). In addition, the seasonal variation in temperate and polar marine environments lead to an increase in ocean productivity during spring/summer and a decrease in autumn/winter

(Behrenfeld et al. 2005). In response to this cyclic pattern, most Procellariforms undertake seasonal migrations during the winter non-breeding period (Phillips et al. 2005, González-Solís et al. 2007) to mitigate or avoid a hostile environment (Furness & Monaghan 1987).

During breeding, food intake in seabirds must increase to satisfy the elevated energy expenditure of reproduction (Croxall & Ricketts 1983, Gremillet et al. 1995, Shaffer et al.

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2003). Breeding adults are constrained to follow a central place foraging strategy due to the need to regularly return to the nest to feed their young (Phillips & Hamer 1999).

Correspondingly, to ensure successful chick-rearing, seabirds mostly breed in summer, when marine prey availability is usually the greatest (Lack 1954, Regular et al. 2014). To maximise energy efficiency of reproduction, albatrosses, petrels and shearwaters can use a dual foraging strategy during chick-rearing. Facilitated by the production of stomach oils (Prince & Morgan

1987), breeding adults of these species alternate several short foraging trips with one long

(Chaurand & Weimerskirch 1994). Short trips (1 – 5 d) undertaken within a small range are dedicated to the provisioning of the chick, while long trips (6 – 29 d) reach distant more productive areas to restore parental body condition (Weimerskirch et al. 1994, Baduini &

Hyrenbach 2003, Cherel et al. 2005). This bimodality in foraging trips can also mediate fluctuations in local food supply (Berlincourt & Arnould 2015).

Another characteristic of Procellariforms is the similarity in plumage characteristics but differences in morphology between the sexes (Granadeiro 1993). Male-biased sexual size dimorphism (SSD) is predominant among species with males being larger in head, bill, wing, tarsus, or tail length and body mass than females (Lorentsen & Røv 1994). Only the storm petrels (Hydrobatidae) display female-biased SSD (Warham 1990, Castro et al. 2013). Size dimorphism in body mass varies from 15-22% in large albatrosses and giant petrels to 6–11% in smaller Procellariforms species (Croxall 1995). This marked SSD induces sex-specific foraging and reproduction costs (Shaffer et al. 2003, Shaffer 2004) often linked throughout the breeding season with sex-specific foraging strategies, involving spatial segregation or habitat specialisation (González‐Solís et al. 2000, Phillips et al. 2007, Pinet et al. 2012, Pereira et al.

2018). Consequently, males and females can potentially be sensitive to different threats

(Gianuca et al. 2017, Cortés et al. 2018).

A few Procellariform species (n = 12) differ from the general reproductive pattern for the order, with a non-breeding period during summer, synchronous egg laying in autumn, and

86 chick-rearing throughout the winter. The unusual phenology of these winter breeders, coupled with challenging access (burrow nesting in remote areas, nocturnal habits), has caused this group remains the least documented petrels (Zotier 1990). One such species is the Westland petrel (Procellaria westlandica), an endemic of New Zealand with a breeding distribution restricted to the west coast of the South Island and classified as endangered (Baker & Coleman

1977, IUCN 2018). Despite a wingspan of 140 cm conferring this flap-glider species with a high flight capability (Ainley et al. 2015), they have a reduced foraging range and shorter trips than other smaller Procellariforms (Freeman et al. 1997, Pollet et al. 2014). In addition, although males are larger than females (SSD of 6 % in body mass, Landers 2011), both sexes appear to forage in the same areas throughout the whole breeding cycle (Waugh et al. 2018).

Furthermore, in contrast to its congenerics (Péron et al. 2010, Zhang et al. 2017), Westland petrels sustain the increased nutritional requirements of chick-provisioning with no indication of bimodality in foraging trip duration (Freeman et al. 2001), Waugh et al. 2018).

There is currently little information on how Westland petrels obtain the nutritional requirements necessary for successful breeding following with a strategy vastly different to that of the majority of Procellariforms. Such knowledge is vital for understanding the potential impacts of environmental variability on this endangered species. This is especially relevant in view of the anticipated shifts in the region’s marine ecosystem in response to global climate change (Matear et al. 2013). The objectives of the present study, therefore, were to examine in chick-rearing male and female Westland petrels: 1) fine-scale spatio-temporal foraging behaviour; 2) the environmental factors influencing their foraging, and 3) their associated isotopic niche.

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4.3 Materials and methods

4.3.1 Study site and field procedures

Fieldwork was conducted in the coastal ranges near Punakaiki, Westland, New Zealand

(42.146°S, 171.341°E). Endemic to this location, an estimated breeding population of 4,000 pairs (ACAP 2011) nest in burrows dug in the broadleaf/podocarp rainforest soil (Wilson &

Coast 2016). Birds from the Scotsman’s Creek study colony were captured in the nest burrow, accessible via artificial inspection hatches, over two years during the post-brood period (11-15

August 2016 and 2017). During their nocturnal attendance at the nest, one adult per burrow was captured (2016 n = 17, 2017 n =15) after having had a chance to feed their chicks (burrows checked every hour). Individuals were weighed in a cloth bag with a suspension scale (± 25 g,

Pesola) and their morphometrics taken (culmen depth, width and length, as well as tarsus length with slide callipers at the nearest 0.1 mm, and wing length with a stopped-rule ± 1 mm).

Individuals were also banded (if not already) with a uniquely-numbered metal band.

The bird was then equipped with a GPS data logger (i-gotU GT-120, Mobile Action

Technology, Taiwan, 45 x 25 x 12 mm, 15 g) sampling location at 5 and 3 min intervals in

2016 and 2017, respectively, with an accuracy of ±10 m (Morris & Conner 2017) to obtain information on its at-sea movements. To obtain behaviour information, individuals were also instrumented with a tri-axial accelerometer data logger sampling at 25 Hz (Axy-Depth,

Technosmart, 40 x 15 x 11 mm, 7 g, also sampling pressure at 1 Hz; or X16-mini, Gulf Coast

Data Concepts, 47 x 22 x 9 mm, 15 g). The GPS and X16-mini data loggers were encapsulated in heat-shrink tubing (Tyco Electronics, Switzerland) and all loggers were attached to the dorsal mid-line feathers (accelerometer between the scapula, GPS anterior to the tail-feathers) using black waterproof tape (Tesa 4651, Beiersdorf AG). The total mass of the data loggers was 28-34 g (2.9 ± 0.3 % of body mass) such that they are likely to have minimal impact on individual behaviour during the short-term deployment (Phillips et al. 2003, Chivers et al.

2016). After instrumentation, individuals were returned to their burrow to resume normal

88 behaviours.

The nest was inspected the following day with a burrowscope (Sextant Technology Limited,

New Zealand) through the natural entrance to confirm the instrumented bird had departed. The burrow entrance was then fitted with a one-way trap door or a wooden stick, to reveal the nocturnal visit of a parent, and checked at night every hour until recapture. Upon recapture, data loggers were removed, the birds were weighed again and a blood sample (0.1 mL) was obtained by venepuncture of a tarsal vein. The blood was immediately stored in 70% ethanol for later genetic sex determination (Parentage and Animal Genetic Services Centre, Massey

University, Wellington) and stable isotope analyses (GNS Science, Lower Hutt, New Zealand).

All handling of birds for procedures lasted <15 min. During the fledging period three months later (November) the burrows were monitored again to count the surviving chicks in order to obtain the breeding success.

4.3.2 Data processing and statistical analyses

The GPS data processed to separate the individuals’ trips and keep the at-sea locations only

(see Chapter 2). Resulting at-sea movements were processed in R statistical environment v

3.4.2 (R Core Team 2017) to remove erroneous locations using a 25 m.s-1 speed filter (Freeman et al. 2010). Foraging trip metrics (duration, maximum distance from the colony, total horizontal distance travelled, average speed) were calculated using the adehabitat HR package

(Calenge 2006). The distribution of the trip duration was assessed for bimodality with calculation of the bimodality coefficient (Pfister et al. 2013) and mode(s) estimation(s) by mixture distribution implemented in the modes package (Deevi & Strategies 2016). At-sea locations were linearly interpolated at 1 s intervals and the maximum convex polygon enclosing trip locations was used to estimate the home range area using the geosphere package (Hijmans

& Van Etten 2016).

Fine-scale activity budgets and spatio-temporal localisation of foraging behaviour were inferred from the acceleration data. Data from the seven birds equipped with Axy-Depth (tri-

89 axial acceleration and pressure) and GPS data loggers were visualised in Igor Pro software v.7

(Wavemetrics Inc., USA, 2000). The pressure was converted to depth (D in m) using the atmospheric pressure (Pa in mBar) as the baseline of measured pressure (Pm) in the relationship

D = 0.01(Pm - Pa), and corrected for surface drift. Given the high sensitivity of the sensor (5 mBar) potentially causing low-pressure variance other than actual diving (Cianchetti-Benedetti et al. 2017), submergences greater to the body length of the bird (0.55 m) were considered as a dive.

The dive depth and the average speed determined from GPS data were then used as references to guide the interpretation of the acceleration signals. The visual inspection of the acceleration data indicated a higher variation in the heave axis during flight (due to wing beats) than when rafting on water (Wilson et al. 2006, Collins et al. 2015). Hence, a spectrum analysis was conducted on the heave axis data using the package Ethographer (Sakamoto et al. 2009a), followed by a K-means clustering (n = 2) in order to separate periods of flapping and non- flapping, and retrieve their characteristics (dominant cycle and amplitude) with the peak tracer function. Using a combination of the dominant cycle and amplitude of flaps, with the heave value and variation associated with air and water, each second of the trip was classified as flapping flight, soaring flight or rafting on water behaviour (Supplementary Fig S 4-1).

The acceleration data were used to infer the individuals’ behaviour at each second of their trip. The dynamic and static components were differentiated to calculate respectively the

VeDBA and the body pitch (see Chapters 2 and 3), while the VeDBA allowed to compare the relative movement costs of each behaviour. The body pitch allowed to define the foraging events when a bird was not flying and displayed a negative body pitch value below -

25°(Warwick-Evans et al. 2015), induced by a downward head movement associated with surface-seizing, surface-diving and pursuit-plunging for prey (Marchant & Higgins 1990). The frequency distribution of the time interval between seconds of foraging behaviour displayed a sharp decrease for intervals > 5 s (Supplementary Fig S 4-3) and, therefore, this threshold was

90 used to separate distinct foraging events.

The acceleration-based method described above identified 91.4 ± 5.2 % of dives detected by pressure data, validating this method for application on the remaining individuals that were instrumented with X16-mini accelerometers. In addition, using the calculated descent rate from dive data individuals (0.84 ± 0.0 m.s-1, Supplementary Fig S 4-2), the dive depth of the X16- mini individuals was estimated from the duration of the dive.

To investigate the oceanographic variables influencing the Westland petrel habitat use, remote-sensed oceanographic variables reported to be influential for Procellariforms

(Reisinger et al. 2018) were gathered on the foraging locations (Supplementary Table S 4-1).

For each tracked individual, the time spent foraging was localised on the interpolated track and converted into a standardised percentage within square grid cells of 0.04 ° (ca 4 km2), matching the most accurate spatio-temporal combination available for oceanographic variables in order to approach real-time at-sea conditions. The resulting standardised time spent foraging in area was then spatio-temporally matched with the oceanographic variables using the package raster

(Hijmans & Van Etten 2016). Stable isotope analyses of nitrogen (δ15N) and carbon (δ13C), proxies of trophic ecology (Jaeger et al. 2010), were used to infer the trophic level of individuals and quantify their niche width (Bearhop et al. 2004). Analysis was conducted on whole blood, as described in Chapter 3.

The effect of mass change on the foraging rate, and the effect of sex and year on body mass, mass change and stable isotope values, were investigated with analysis of variance (ANOVAs).

As the GPS trip metric data included multiple trips by some individuals, the influence of sex and year was investigated with linear mixed models (LMMs). They were performed with individual identity as a random factor to account for their pseudo replication (Bolker et al.

2009) using the nlme package (Pinheiro et al. 2014). Similar LMMs were also conducted on the activity budget (e.g. proportion of time flapping, gliding, rafting on water, foraging). The temporal variation of the activity budget and dive depth throughout the day was further

91 investigated with generalised additive mixed models (GAMMs) using the mgcv package

(Wood 2018). In addition, GAMMs were also used to investigate the influence of the encountered oceanographic parameters on the log-transformed time spent foraging for each sex. Prior to inclusion in the model, oceanographic parameters were scaled and checked for collinearity, with a cut-off criterion of |rs| = 0.5 for inclusion in the model.

Model selection was conducted by comparison of the Akaike Information Criteria (AIC,

Akaike 1974) between candidates models using the MuMin package (Barton 2016). The best supported model (Δ AIC = 0 without other equally supported models having Δ AIC < 4,

Burnham et al. 2011), or by default, the most parsimonious model (constituted by the important explanatory variables identified by model averaging procedure among the equally supported models, Burnham et al. 2011) was retained (Supplementary Table S 4-2). The validation of the retained models was based on the examination of their residuals (Zuur et al. 2009). The isotopic niche quantification was performed using the ellipse-based metrics of the SIBER package

(Jackson et al. 2011), by the standard ellipse area corrected for sample size (SEAc) and

Bayesian standard ellipses area (SEAB). Unless otherwise stated, all data are presented as Mean

± SE.

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4.4 Results

4.4.1 At-sea movements and activity budgets

At-sea movement (GPS) data were obtained from 32 individuals, and due to device

malfunctions, at-sea movements combined with behaviour data were obtained from 29

individuals (16 males / 18 trips, 13 females / 15 trips, Table 4-1) totalling 1,556 h in duration.

Morphometric measurements confirmed a male-biased structural dimorphism (Table 4-2).

However, the body mass at instrumentation (1,250 ± 19 g) did not differ significantly between

sexes and years (ANOVA, P > 0.5 in both cases). At recapture, some individuals gained mass

(+94 ± 15 g, n = 14) and some lost mass (-113 ± 13 g, n = 16). Mass change was not significantly

different between sexes and years (ANOVA, P > 0.2 in both cases).

Table 4-1 : Logger deployments on Westland petrels and their GPS trip metrics during post- guard stage (mean SE). 2016 2017 males females males females Individuals equipped (n) 11 6 7 8 Individuals (trips) with GPS and acceleration data 9 (9) 5 (5) 7 (9) 8 (10) Body mass (kg) 1.25 ± 0.03 1.21 ± 0.02 1.27 ± 0.05 1.25 ± 0.04 Trip duration (h) 46 ± 6 55 ± 16 41 ± 6 60 ± 9 Max. distance from the colony (km) 120 ± 12 106 ± 33 173 ± 28 200 ± 37 Total horizontal distance covered (km) 749 ± 98 677 ± 234 890 ± 155 1276 ± 247 Mean horizontal speed (km.h-1) 16.8 ± 1.0 10.8 ± 1.6 21.7 ± 1.3 19.8 ± 1.2

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Table 4-2 : Sexual size dimorphism in morphometric measurements of genetically sexed Westland petrels tracked during rearing chick in 2016 and 2017, showed by the Storer’s dimorphism index (SDI = 100 x (mean ♂ – mean ♀)/(mean ♂ + mean ♀) x 0.5).

Males ♂ Females ♀ T test result SDI (n=18) (n=14) (P) (%) Culmen depth (mm) 18.2 ± 0.3 16.4 ± 0.2 < 0.001 10.4 Culmen width (mm) 23.6 ± 0.2 22.2 ± 0.3 < 0.01 6.1 Culmen length (mm) 51.1 ± 0.4 48.8 ± 0.4 < 0.001 4.6 Wing length (mm) 392 ± 3 379 ± 2 < 0.01 3.5 Tarsus length (mm) 65.2 ± 0.5 64.0 ± 0.6 0.1 1.8 Mass at deployment (g) 1256 ± 25 1238 ± 28 0.6 1.4

Individuals foraged up to 154 ± 14 km away from the colony over the shelf-slope and submarine canyons off the west coast of New Zealand’s South Island (Figure 4-1). Their trips lasted 50 ± 4 h, covered a total horizontal distance of 920 ± 95 km at an average speed of 18 ±

1 km.h-1 that resulted in a home range size of 36,563 km2 in 2016 and 80,052 km2 in 2017. The distribution of foraging trip durations did not reveal any indication of bimodality and, combined with previously collected data from the same stage of breeding (Waugh et al. 2018), durations showed a bimodality coefficient of 0.38 (suggesting unimodality) with a single mode at 3 days (Figure 4-2). The LMMs revealed no significant influence of year and sex on the total horizontal distance travelled or trip duration. Year of study had a significant influence on the maximum distance from the colony and the average speed, with trips reaching maximum distance greater by 69 ± 28 km (P = 0.02), travelled at speeds 6.7 ± 1.3 km.h-1 faster in 2017

(P < 0.001). Sex had a significant influence only for the average speed, with males travelling faster 3.6 ± 1.3 km.h-1 than females (P = 0.01, Table 4-1).

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Figure 4-1 : At-sea movements of breeding Westland petrel (males in orange, females in yellow) during the post-guard stage, from Punakaiki. The red dots represent the surface foraging and the black dots the dives. On land, the black triangle represent the colony location, and at sea, the black line is the 12 nautical miles boundary of the Territorial Sea.

Figure 4-2 : Distribution of the foraging trip durations of chick-rearing Westland petrels. Data represented in green were gathered during this study (2016 and 2017), data in blue were gathered in 2012 and 2015 (from Waugh et al. 2018), and data in grey represent their addition.

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Individual activity budgets were comprised of 51.4 ± 2.5 % flapping flight, 34.6 ± 2.7 %

rafting on water, 13.7 ± 1.0 % soaring flight and only 0.13 ± 0.01 % of time foraging. These

behaviours had different VeDBA values, highest being for foraging (0.73 ± 0.06 g), followed

in decreasing order by flapping flight (0.39 ± 0.01 g), gliding flight (0.20 ± 0.01 g) and rafting

on water (0.19 ± 0.01 g). The GAMMs revealed that these behaviour proportions all varied

significantly according to the hour of day (P < 0.001). The sex did not significantly influence

the timing of these activities at sea, and significant inter-annual variation occurred only with

rafting on water and flapping flight behaviours which decreased by 13 % and increased by 11

%, respectively, in 2017 (Table 4-3). Rafting on water peaked at the middle of the day, at the

expanse of flapping and gliding flight that both increased at dawn and dusk (Figure 4-3).

Table 4-3 : Summary of the generalised additive mixed models (GAMMs) outputs used to assess the trends in the at-sea behaviour of Westland petrel provisioning chick at Punakaiki, New Zealand. Significant P-values are highlighted in bold.

Response variable Predictor Parametric coefficients Significance P variable of smooth terms Estimate SE t Edf F % foraging Intercept 0.13 0.01 7.0 - - < 0.001 Hour - - - 1.0 14.8 < 0.001 % rafting on water Intercept 43.3 4.5 9.6 - - < 0.001 Hour - - - 8.7 15.2 < 0.001 Year (2017) -13.4 4.9 -2.7 - - 0.006 Sex (Male) -6.0 4.9 -1.2 - - 0.2 % flapping flight Intercept 43.7 4.8 9.0 < 0.001 Hour - - - 8.6 12.6 < 0.001 Year (2017) 11.1 5.3 2.0 0.03 Sex (Male) 4.3 5.3 0.8 0.4 % gliding flight Intercept 14.7 1.0 14.0 - - < 0.001 Hour - - - 7.7 25.4 < 0.001 Dive depth Intercept 1.4 0.1 14.0 - - < 0.001 Year (2017) -0.4 0.1 -2.5 - - 0.01

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Figure 4-3 : Temporal variation of the at-sea time activity budget of Westland petrel. The proportions of behaviours and dive depth are predicted on an hourly basis by generalized additive mixed models (GAMMs). Dark grey and light grey shaded areas correspond to the night-time and sunset/sunrise times during the study period, and shaded areas along the curves represent the 95 % confidence interval.

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4.4.2 Fine-scale foraging behaviour

The foraging behaviour, inferred during a total of 7,348 s (2h), occurred during 4,080 foraging events (between 8 – 399 events per trip, according to their duration). The resulting foraging rates were 2.7 ± 0.2 events.h-1 (range 0.6 – 5.9), equating to 0.16 ± 0.01 events.km-1 travelled (range 0.05 – 0.40). These rates were not significantly influenced by sexes, years, trip duration/travelled distance (null models selected, Supplementary Table S 4-2) or by the mass change of individuals (ANOVA, P= 0.3). The time spent foraging consisted of 66.6 ± 3.1 % surface foraging and 33.4 ± 3.1 % by diving.

Surface foraging events were of brief duration (1.2 ± 0.01 s) and dives (n = 152 recorded, n

= 827 estimated) were characterised by duration of 3.1 ± 0.1 s and depth of 1.3 ± 0.0 m.

Maximum dive duration and depth reached 26 s and 8.6 m, respectively. The GAMM modelling revealed that the proportion of time spent foraging peaked during the first part of the night (P< 0.001) but that the dive depth was not significantly influenced by the time of the day and the sex (Figure 4-3) but by year, with depths shallower by 0.4 ± 0.1 m in 2017 (P =

0.01).

Individuals spent 75.4 % of their foraging time over the peri-insular shelf slope (200 – 1,000 m), and only 13.3 % in bathyal waters (1,000 – 2,000 m), 11.0 % in neritic waters (0 – 200 m) and 0.09 % in abyssal waters (> 2,000 m). Foraging locations were situated above a sea floor slope ranging from 0.02 - 15.00° and where the chlorophyll-a concentration was 0.35 ± 0.01 mg.m-3. The sea surface was characterised by a temperature ranging from 10.6 - 14.1 °C with associated temperature anomalies between -1.8 - 0.9 °C. The sea surface height varied between

-1 0.03 - 0.18 m and was agitated by currents up to 0.3 m·s , waves ranging from 0.6 to 4.8 m, and wind blowing between 2 - 14 m.s-1.

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The GAMMs revealed a significant influence of four oceanographic variables on the time

spent foraging in area, with results differing between sexes (Table 4-4, Figure 4-4). For

females, the time spent foraging in area was negatively influenced by positive temperature

anomalies (P = 0.001) and negatively by sea surface temperature (P < 0.05). For males, it was

positively influenced by wind speed (P < 0.01) and positively influenced by current (P = 0.01).

Table 4-4 : Summary of the generalised additive mixed models (GAMMs) outputs used to assess the oceanographic variables influencing the foraging of Westland petrel provisioning chick at Punakaiki, New Zealand. Significant P-value are highlighted in bold.

Response variable Predictor Parametric coefficients Significance P variable of smooth terms Estimate SE t Edf F Log(time spent foraging) females Intercept 0.32 0.7 0.4 0.6 SLOPE - - - 7.5 2.0 0.02 SST - - - 3.8 2.4 0.05 DEPTH - - - 1.0 0.8 0.04 ASST - - - 2.0 0.8 0.3 Log(time spent foraging) males Intercept 0.5 0.1 2.6 - - 0.007 SLOPE - - - 2.0 2.0 0.1 SST - - - 2.4 0.7 0.5 DEPTH - - - 1.0 3.8 0.05 ASST - - - 2.9 1.0 0.3 WIND - - - 1.0 3.0 0.08 WAVE - - - 5.0 1.7 0.1 CURRENT - - - 1.0 5.7 0.01

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Figure 4-4 : Relationship between the time spent foraging in area by Westland petrel provisioning chick and influencing oceanographic parameters modelled by generalized additive mixed model (GAMM). Shaded areas represent the 95% confidence interval.

Stable isotope values of whole blood (Mean ± SD) were 15.4 ± 0.2 ‰ for δ 15N and at -18.3

± 0.3 ‰ for δ 13C (Table 4-5). These isotopic results showed little variation, and did not significantly change between years or sexes (ANOVA, P ≥ 0.1 in all cases). All values, pooled together to construct the isotopic niche, revealed a small isotopic niche (Figure 4-5) with an

2 2 area estimated at 0.23 ‰ by the SEAC and at 0.21 ‰ by the SEAB. These feeding conditions related to years of medium (2016) and high (2017) fledging success recorded at the colony with

51 % (n=31) and 85 % (n=21), respectively.

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Year Sex N δ 13C (‰) δ 15N (‰)

All individuals 34 -18.3 ± 0.3 15.4 ± 0.2 2016 male 12 - 18.2 ± 0.3 15.5 ± 0.2 2016 female 7 - 18.3 ± 0.3 15.4 ± 0.2

2017 female 8 - 18.3 ± 0.2 15.4 ± 0.2 2017 male 7 - 18.4 ± 0.4 15.5 ± 0.2

Table 4-5: Isotopic values (whole blood, Mean ± SD) of males and females Westland petrels provisioning chick in 2016 and 2017.

Figure 4-5: Isotopic values and niche of breeding Westland petrel. The colours and point shapes indicate the sex and year respectively. The isotopic niche is represented by the 40 % corrected standard ellipse in black.

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4.5 Discussion

Using combined GPS and accelerometer data from adult males and females rearing chicks during two breeding seasons, the present study provided information on the fine-scale foraging behaviour of Westland petrels. The results confirmed the species small foraging area over the shelf slope of New Zealand’s South Island west coast, exploited by relatively short foraging trips unimodal in duration. The acceleration data showed that foraging behaviour was comprised of short and dispersed events, representing a small proportion of their at-sea activity budget. The analysis of movements and isotopic niche did not reveal clear sexual segregation despite their sexual-size dimorphism. However, sexual differences were observed in the influence of oceanographic variables on time spent foraging, suggesting a potential small-scale habitat specialisation. These findings suggest male and female Westland petrels consume the same prey, sufficiently abundant locally during winter to satisfy the nutritional needs of breeding without intra-specific competition avoidance or increased foraging effort compared to summer breeding species.

4.5.1 At-sea movements and activity budget

The present study confirmed and refined the chick-rearing movements of Westland petrels previously reported by at-sea observations (Freeman 1997) and tracking studies (Freeman et al. 2001, Waugh et al. 2018). The species is known to be able to cover 1,351 km.day-1 (Landers et al. 2011b), displayed restricted movements (432 ± 20 km.day-1) during the present study.

This is consistent with previous reports of the species displaying range restriction during chick- rearing period (Waugh 2018), due to the need of regular returns to the nest for feeding the chick

(Phillips & Hamer 1999). However, the small maximum distance to the colony and home range area values recorded in the present study are in contrast with other Procellariforms. For instance, the similar-sized congeneric white-chinned petrel Procellaria aequinoctialis displays much wider movements and exploits an area 8 times bigger in different oceanographic context

(Berrow et al. 2000, Péron et al. 2010, Rollinson et al. 2018). Even smaller Procellariidae and

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Hydrobatidae, species with lower flight capacity, display greater range and exploit a wider area

(Rayner et al. 2008, Freeman et al. 2010, Oppel et al. 2018) than Westland petrel.

In addition to this particular foraging distribution, the Westland petrel at-sea movements were also different to many Procellariforms as a result of the absence of bimodality in their duration (Baduini & Hyrenbach 2003). The alternating of short trips close to the colony with long trips to distant more productive areas, respectively associated with parental mass loss and gain (Weimerskirch et al. 1994, Weimerskirch et al. 2003) is reported to be advantageous to reduce parent-offspring energy conflict (Wischnewski et al. 2019). Both unimodal and dual strategies are reported in shearwaters with unimodality exhibited in high quality habitats and bimodality when parents face low prey availability close to the colony (Navarro et al. 2009,

Riou et al. 2011, Cecere et al. 2014).

Despite the presence of reachable areas of enhanced productivity favourable for

Procellariforms near New Zealand, such as the subtropical front (Rayner et al. 2008, Deppe et al. 2014) and polar frontal zone (Shaffer et al. 2009), individuals in the present study exploited only a small foraging range to sustain their chick-rearing energy requirements. This suggests the shelf slope of New Zealand’s South Island west coast provides the closest reliable prey- rich habitat for the species (Louzao et al. 2011). Nonetheless, both positive and negative mass changes were recorded during foraging trips which could indicate that Westland petrels, despite having unimodal trip durations, potentially alternate the function of these short trips between chick-provisioning and self-maintenance in the same area.

Information on the activity budgets of foraging seabirds provides useful information on their energy expenditure, foraging effort, reproductive costs, prey availability and habitat quality

(Litzow & Piatt 2003, Markones et al. 2010, Linnebjerg et al. 2014, Collins et al. 2016). The tracked individuals in the present study spent the majority of their time at sea in flight, and especially flapping flight, which is consistent with the reported flap-gliding flight of

Procellaria (Ainley 2015). Despite the proximity of the foraging areas, individuals undertook

103 the costly activity of flapping flight (Hicks et al. 2017) to patrol large areas in order to maximise prey encounters, as has also been reported for long-ranging albatrosses (Weimerskirch 2005).

Spending a majority of time in flight searching for prey and little time actually foraging is a common pattern for pelagic Procellariforms such as albatrosses (Weimerskirch & Guionnet

2002), petrels (Rayner et al. 2008) and shearwaters (Shaffer et al. 2009, Matsumoto et al. 2012) that forage on patchy prey (Weimerskirch et al. 2005).

The activity budgets of individuals in the present study were primarily influenced by the time of the day and, to a lesser extent, by the year of study. These findings are consistent with the constraint of available light on these visual foragers influencing their at-sea activities during the day (Phalan 2007), and with the inter-annual variations observed in the species movements.

In 2017, when individuals spent less time on the water and more time in flapping flight, they reached further maximum distances from the colony and at higher speeds. While these findings could have arisen from different at-sea conditions (e.g. wind-speed and/or direction) between the years influencing the energetic costs of movements for foraging seabirds (Wilson 2012,

Elliott 2014), the difference in sea surface temperature (12 °C in 2016, 13 °C in 2017) might have changed prey distribution on New Zealand shelf (Neumann 2001). However, the constant proportion of time spent foraging between years recorded in the present study suggests some behavioural plasticity to compensate for minor variations of the foraging cost, as previously suggested for Westland petrels impaired by carrying extra weight of satellite loggers without adverse effect on adult weight and chick success (Freeman et al. 2001).

4.5.2 Foraging behaviour and trophic niche

The fine-scale movement data, coupled with the acceleration data, gathered in the present study enabled the foraging behaviour of individuals to be accurately determined. During their foraging trips, individuals spent only a small proportion of their time foraging. However, this foraging time was spread out along the tracks with many foraging events that were separated by intervals skewed towards short time. The foraging rate observed in the present study was

104 higher than reported in the Scopoli’s shearwater Calonectris diomedea in the Mediterranean

Sea (1.7 events.h-1, Cianchetti-Benedetti et al. 2017) but similar to the southern Buller’s albatross (Thalassarche b. bulleri , 2.5 events.h-1) which also forages along the west coast of

New Zealand South Island (Poupart et al. 2019). The findings suggest Westland petrels feed on prey patchily distributed throughout the shelf slope, including aggregated prey such as the schooling crustacean Nyctiphanes australis (O'brien 1988) or the scavenging on discards around fishing vessels (Freeman 1998).

The results of the present study also revealed the Westland petrel as a species able to feed at any time of the day or night. While foraging is generally reduced at night for albatrosses and some petrels (Phalan et al. 2007, Shaffer et al. 2009), in the present study it increased during the first hours of darkness. This suggests a pulsed food availability at the beginning of the night, potentially due to the diel vertically migrating prey reaching near surface waters (Lampert

1989). Indeed, previous studies on Westland petrel diet reported feeding upon vertically migrating and bioluminescent species of fish and squid (Imber 1976, Freeman 1998) able to be detected from long range (50 – 100 m, Voss 1985) and representing important biomass on shelf-slope habitat (May & Blaber 1989, Williams & Koslow 1997).

The maximum dive depths recorded in the present study were very close to that previously recorded with capillary-tube maximum depth gauges (Freeman et al. 1997). The mean and maximum dive depths recorded in the present study were shallower than those reported for congenerics, petrels and shearwaters also breeding in the New Zealand region (Rayner et al.

2008, Shaffer et al. 2009, Bell 2016) as well as worldwide (Table 4 in (Rollinson et al. 2014).

Assuming that Westland petrel has comparable diving capacity to the similar-sized white- chinned petrel, the shallow dives recorded in the present study suggest an availability of different prey near surface throughout the day.

The foraging activity observed in the present study was concentrated on the shelf slope near the breeding colony, which receives an eastward flow from the Tasman Sea and undergoes a

105 seasonal winter mixing and intermittent upwelling that sustains the local food web during winter to create a prey rich ecosystem (Koslow et al. 1997, Bradford-Grieve & Livingston

2011). Use of similar habitats was reported for the Westland petrel during its summer non- breeding period in the Humboldt Current system off South America, where at-sea observations were concentrated in waters of 200 – 1000 m depth undergoing upwelling (Spear et al. 2005).

The investigation of the time spent foraging by individuals in the present study in relation to oceanographic variables revealed a significant influence of depth, slope, sea surface temperature and current. Slope was also reported to increase the foraging intensity estimated by kernel density estimate (Waugh et al. 2018), and these findings are consistent with the slope involved in horizontal advection, uplifting and mixing of subsurface waters in the area (Butler et al. 1992).

The δ 13C values observed in the present study are consistent with feeding in subtropical waters (Cherel & Hobson 2007). The δ 15N values confirmed that Westland petrel was feeding at high trophic level (Post 2002) in accordance with the previously described fish-dominated diet of the species (Freeman 1998) and congenerics (Bugoni et al. 2010, Carvalho et al. 2013).

Chick-rearing individuals showed comparable isotopic values in their whole blood to incubating birds and a comparable isotopic niche area, with the exception of the larger SEAC observed in 2015 during a strong El Niño year (Waugh et al. 2018). This is in contrast with smaller Procellariforms that have been found with altered δ 15N over the breeding season

(Cherel et al. 2014). Hence, the Westland petrel seems relying on a narrow trophic resource, which is persistent throughout its breeding cycle during winter.

Lack of sexual segregation

Despite the sexual size dimorphism present in the Westland petrel (males larger than females), there were few differences in the foraging behaviour between the sexes. Both sexes displayed similar at-sea movements, with the only trip parameters that differed being the

106 slightly higher average horizontal flight speed of males, which could relate to their longer wings (Landers et al. 2011a, Table 4-2) due to the close link between wing morphology and flight behaviour (Spear and Ainley 1997). Males and females also used similar foraging areas over the shelf-slope, with both sexes foraging at same rate and during the same time of day.

Their resulting isotopic niches also indicated an absence of sex-specific dietary specialisation.

Together, these results suggest a similar foraging strategy for both sexes, which is consistent with previously reported lack of difference in foraging area estimates (Waugh et al. 2018) and their similar survivorship (Waugh et al. 2015). These findings contrast with observations for many Procellariforms (and other seabirds) which display sex-specific spatial segregation and foraging specialisation reducing intersexual competition (Bearhop et al. 2006, González‐Solís et al. 2007, Phillips et al. 2011, Cleasby et al. 2015).

The only sexual difference associated with foraging in the present study was related to habitat use, with differences in the influence of current, slope and sea surface temperature on the time spent foraging between the sexes. These findings suggest slight sexual differences in fine scale habitat selection, as has been reported during the winter chick-rearing in the wandering albatross Diomedea exulans (Pereira et al. 2018). A lack of spatial segregation as observed in Westland petrels during the pre-laying, incubation and chick-rearing periods

(Waugh 2018), has also been reported in Cory’s shearwater Calonectris diomedea off the west coast of African (Navarro et al. 2009) within a major upwelling zone (Barton et al. 1998).

Under conditions of high habitat quality and prey abundance, both sexes can forage on the same niche without competition, and sexual size dimorphism becomes supported mainly by sexual selection (Serrano‐Meneses & Székely 2006, Navarro et al. 2009). The investigation of the other hypotheses for sexual size dimorphism (e.g. the niche divergence hypothesis, Darwin

1874, Shine 1989) would require further studies on colony attendance, incubation behaviour and chick provisioning by both sexes in Westland petrels to assess their respective reproductive roles (Phillips et al. 2004, Hedd et al. 2014).

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The reliance on the relatively small foraging area identified in the present study could pose problems for the species. The Westland petrel population size is small (ca 4,000 breeding pairs,

(ACAP 2011), and, while breeding pairs have a relatively a high fledging success, its breeding frequency is variable with some adults skipping years between attempts (Waugh et al. 2006).

In addition, the long fledging period for the species, similar to other winter breeding

Procellariforms (Zotier 1990), may reflect the small meal sizes delivered by breeding parents

(Freeman 1998). A single foraging area is likely to increase the sensitivity of a specialized predator to local food shortage (Laidre et al. 2008, Paredes et al. 2012) and, therefore, the

Westland petrel may have a limited ability to adapt to large-scale environmental changes

(Matear et al. 2013). Additional studies are needed to evaluate the consistency of foraging behaviour by both sexes, throughout the annual cycle and under variable environmental conditions (e.g. strong El Nino/La Nina years). Such data would provide insights into potential energy constraints for the species (Fort et al. 2009) and how it may respond to anticipated environmental changes (Oppel et al. 2012).

The foraging area identified in the present study supports the defining of the pelagic important bird area (IBA) and marine protected area (MPA) proposed for Westland petrel

(Forest & Bird 2014, MPI 2015), where the Hoki Macruronus novaezelandiae trawling fishery area coincide with the species foraging areas. Despite an opportunistic usage of fisheries waste by the Westland petrel (Freeman 1998, Freeman & Wilson 2002, Waugh et al. 2018), fine- scale data on the movements of fishing vessels would allow future study to refine the habitat modelling with natural foraging behaviour data only. In addition, the identification of birds’ interactions with fishing vessels is required to better understand their use of this alternative food resource, which may mitigate the variation of their natural prey. Such knowledge would be beneficial for the species, classified “at risk” to bycatch (Richard & Abraham 2013), and which faces other fishing fleets and catch methods during their migration and non-breeding period in South American waters (Landers et al. 2011b, Sato et al. 2016).

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In summary, the results of the present study suggest that male and female Westland petrels

can support the nutritional needs of breeding using similar area, foraging behaviour and trophic

resources. This large foraging niche overlap between sexes does not appear associated with

increased competition and higher foraging effort than in other Procellariforms. Together, with

the lack of a bimodal foraging trip strategy and a relatively restricted foraging range, these

findings indicate that the species has access to a predictable and sufficiently abundant prey on

the shelf slope of New Zealand’s South Island west coast during its winter breeding period.

4.6 Supplementary material

Table S 4-1: Oceanographic data used to model the Westland petrel habitat. DEPTH was downloaded from https://www.niwa.co.nz/our-science/oceans/bathymetry, CHLA and ASST from https://coastwatch.pfeg.noaa.gov/ and the remainders from http://marine.copernicus.eu/

Spatial / temporal ABBREVIATION, description (unit) Product resolution DEPTH, ocean depth (m) 0.01° / - New Zealand Regional Bathymetry 2016 SLOPE, ocean floor slope (°) 0.01° / - derivated from DEPTH ASST, SST anomaly (°C) 0.01° / daily MUR SST Analysis Anomaly v04.1 CHLA, chlorophyll a concentration (mg.m-3) 0.04 / daily Chlorophyll-a, Aqua MODIS, NPP, L3SMI SST, sea surface temperature (°C) 0.08° / hourly Global_Analysis_Forecast_PHY_001_024 SSH, sea surface height (m) 0.08° / hourly Global_Analysis_Forecast_PHY_001_024 CURRENT, sea surface water velocity (m.s-1) 0.08° / hourly Global_Analysis_Forecast_PHY_001_024 WAVE, sea surface wave height (m) 0.08° / 3 h Global_Analysis_Forecast_Wav_001_027 WIND, wind speed (m.s-1) 0.25° / 6 h Cersat_Glo_Blended_Wind_L4_Rep-V6-Obs

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Fig S 4-1: Westland petrel at-sea behaviours inferred from tri-axial acceleration. The average speed and the dive depth, shown in black, are used as reference. The coloured data (heave in blue, body pitch in orange and heave clustering in red and violet) represent the data allowing to identify the following behaviours: (A) the flight versus rafting on water, (B) the flapping versus the gliding flight, and (C) the foraging versus rafting on water.

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Fig S 4-2: Relationship between dive duration and dive depth from Westland petrels. Black dots represent the data from 152 dives, and the line colours the different individuals (n= 5). Shaded areas show the 95 % confidence interval.

Fig S 4-3: Frequency distribution of the time intervals between seconds of foraging behaviour recorded within foraging trips of Westland petrel provisioning chick at Punakaiki, New Zealand.

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Table S 4-2: Best and most parsimonious models based on the corrected Akaike Information Criterion (AICc) explaining the GPS trips parameters, the activity budget and foraging behaviour of Westland petrels rearing chick.

Model Response variable Predictor variable AICc Δ weight Rho AIC GPS trips parameters LMM Total horizontal distance year + sex 530 0.0 0.9 - LMM Trip duration year + sex 330 0.0 0.8 - LMM Maximum distance to the colony year + sex 405 0.0 0.9 - LMM Average speed year + sex 203 0.0 0.9 - Activity budget GAMM % foraging s(hour) + year + sex 349 0.0 0.3 -0.005 GAMM % rafting s(hour) + year + sex 15387 0.0 0.3 0.48 GAMM % flapping s(hour) + year + sex 15259 0.0 0.2 0.58 GAMM % gliding s(hour) + year + sex 13249 0.0 0.2 0.61 Foraging behaviour LMM Foraging rate (time) 0 120 0.0 0.4 - LMM Foraging rate (distance) 0 -52 0.0 0.9 - GAMM Dive depth hour + year + sex 2420 0.0 0.2 0.17

GAMM Log(% time foraging in area)males SST + ASST + WIND + WAVE + 1766 0.7 0.3 0.13 CURRENT + DEPTH + SLOPE

GAMM Log(% time foraging in area)females SST + ASST + DEPTH + SLOPE 1715 0.05 0.2 0.14

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Chapter 5:

Niche segregation in New Zealand winter breeding seabirds

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5.1 Abstract

According to the niche theory and the principle of competitive exclusion, sympatric species should display foraging segregation in order to coexist with distinct niches. Divergence in spatial, temporal habitat use or diet are expected between species and, even more, between guilds, especially during periods of high energetic needs such as reproduction. Combining

GPS, dive recorder, accelerometer and stable isotopes data, this study investigated the horizontal, vertical, temporal and trophic components of the foraging niche within a seabird community engaged in breeding during winter on the west coast of New Zealand’s South

Island. Additional data from literature enabled comparisons of the foraging niche of two guilds encompassing 5 species (diving guild: Fiordland penguin Eudyptes pachyrhynchus, little penguin Eudyptula minor, spotted shag Stictocarbo punctatus; Procellariform surface-feeding guild: southern Buller’s albatross Thalassarche bulleri bulleri and Westland petrel Procellaria westlandica). The results revealed partial overlaps within and between guilds in most of the tested components of the foraging niche, indicating that all these predators exploited similar food resources. However, each species displayed different optimums, as expected from their morphological differences. These findings indicate that foraging niche segregation mechanism was not dominated by single or large differences but, instead, involved a combination of multiple small divergences in all niche components.

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5.2 Introduction

As the ability for a species to persist in an area depends on environmental conditions

(Grinnell 1917), the ecological niche of a species has been conceptualized firstly by a hyper- volume drawn in several dimensions (Hutchinson 1957) representing its bioclimatic envelope.

The functional role of a species within its environment (Elton 1927) interacts with the ongoing fundamental biotic interactions (e.g. mutualism, predation and competition) which can alter the species distribution (Boucher et al. 1982). Hence, the environmental conditions, the biotic interactions and the per-capita effects allowing the persistence of a stable or growing population are used to define the ecological niche of a species (Chase & Leibold 2003).

According to the competitive exclusion principle (Hardin 1960), the coexistence of resource- sharing species imply some displacements of the niche characters to reduce the amount of overlap between competing species (Macarthur 1958). Hence, the realised niche of a species may differ from its theoretical niche (Hutchinson 1959), and this flexibility is mainly driven by the vital need of food acquisition (Gause 1934).

In marine environments, the highly variable conditions lead to spatio-temporal patchiness of productivity at several scales (Haury et al. 1978) which impacts higher trophic levels.

Seabirds are wide-ranging marine predators (359 species, Dias et al. 2019) that occupy diverse habitats, using an array of feeding techniques with associated morphological adaptations

(Nelson 1979). Feeding at all trophic levels, these conspicuous predators display structured spatial communities over large-scale environmental gradients (Pocklington 1979, Ballance et al. 1997) are particularly relevant to investigate the niche partitioning (Pontón-Cevallos et al.

2017).

During their non-breeding period, seabirds display clear ecological segregation by using distinct habitats across wide areas, highlighting the primary role of spatial segregation (Thiebot et al. 2012, Navarro et al. 2015). To breed, philopatric seabirds return to their colonies (Rolland

115 et al. 1998) and become restricted to a central place foraging range (Orians 1979). During this time of elevated energy expenditure, they return regularly to the nest to provision their chicks

(Gremillet et al. 1995, Phillips & Hamer 1999, Collins et al. 2016).

Pelagic species exposed to heterogeneous and fluctuating prey tend to reduce their food uncertainty (Weimerskirch 2007, Bartumeus et al. 2016) by foraging in marine features that aggregate prey (Schneider 1982, Bost et al. 2009). This phenomenon, strengthened by local enhancement (Hoffman et al. 1981, Silverman et al. 2004, Thiebault et al. 2014), concentrates individuals and sympatric species within small areas where they can compete for the same food resource (Sealy 1973, Camphuysen & Webb 1999, Ainley et al. 2009). While some sympatric species may segregate in their breeding phenology (Ramos et al. 2016), species breeding synchronously are exposed to locally increased intra-specific and inter-specific competition around breeding sites (Ballance et al. 2009, Masello et al. 2010, Trevail et al. 2019). High intra- specific competition may induce some Ashmole halo effect (Birt et al. 1987, Elliott et al. 2009,

Oppel et al. 2015). These cumulative constraints lead seabird communities to display their most divergent niche segregation during the chick-rearing period (Afan et al. 2014, Barger et al.

2016), allowing to reduce competition on the same prey resources (Wilson 2010). This occurs through spatial segregation of the foraging areas and diving depth, temporal segregation of the pattern of foraging activity and dietary segregation (Croxall & Prince 1980, Masello et al. 2010,

Rosciano et al. 2016).

With 78 breeding species, New Zealand host the richest assemblage of seabirds in the world

(Croxall et al. 2012). In addition, New Zealand has the highest number of species breeding during the winter months. While these winter-breeding species occur throughout the New

Zealand archipelago, their distribution is concentrated on the west coast of South Island which hosts five species from two guilds. The Fiordland penguin Eudyptes pachyrhynchus (3 kg,

2,500 – 9,900 individuals, BirdLife International 2018a), little penguin Eudyptula minor (1 kg,

> 16,000 pairs, Te Papa Tongarewa Museum seabird unpublished database) and spotted shag 116

Stictocarbo punctatus (1 kg, 10 - 50,000 pairs, Szabo 2017) comprise a guild of diving foragers that on the west coast start laying in winter and achieve fast chick development for fledging in spring (Warham 1974, Fenwick & Browne 1975, Heber et al. 2008). The Westland petrel

Procellaria westlandica (1.5 kg, 7,900 – 13,700 individuals, BirdLife International 2018b) and southern Buller’s albatross Thalassarche bulleri bulleri (2.5 kg, 13,625 pairs, Sagar & Stahl

2005) comprise a Procellariform surface-feeding guild which starts to breed before winter and have a slow chick development during winter but also fledge in spring (Baker & Coleman

1977, Sagar & Warham 1998).

While the foraging niche of sympatric summer-breeding species display important spatial and trophic segregation (Pratte et al. 2017), preliminary single-species studies of winter- breeders in New Zealand suggest a degree of niche overlap, exploiting similar foraging areas off the west coast of New Zealand’s South Island (Stahl & Sagar 2000b, Waugh et al. 2018) with common prey species in their diet (Van Heezik 1989, Freeman 1998, James & Stahl 2000).

Understanding how these winter-breeding seabird species may be able to support temporal, spatial and/or trophic niche overlap during the demanding chick-rearing is important for predicting how this community may respond to environmental variability. However, access to these species is relatively challenging and this has limited their study (Zotier 1990) in comparison to the rapid increase in knowledge of the foraging behaviour of summer-breeding species with the advent of bio-logging technology (Ropert-Coudert et al. 2012). The objectives of the present study, therefore, were to determine in Fiordland penguins, little penguins, spotted shag, Westland petrel and southern Buller’s albatross: 1) their ecological niche in spatial, temporal and trophic dimensions; and 2) the respective overlap to discern their ecological niche segregation within a common restricted range.

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5.3 Materials and methods

5.3.1 Study sites and field procedures

The study area was located on the west coast of New Zealand’s South Island, where a narrow peri-insular shelf is reported to host the foraging areas of several winter-breeding species.

Fieldwork was conducted in 2016 and 2017 during the austral winter/spring. To study their respective foraging niche, the fieldwork on this community was conducted at three locations.

The diving guild was studied on Taumaka/Open Bay Island (43.859°S, 168.885°E). The surface-feeders guild was studied at Punakaiki (42.145°S, 171.340°E) for Westland petrel (the only breeding location of the species) and at Hautere/Solander Island (46.568°S 166.896°E) for the southern Buller’s albatross (one of its two breeding locations, with the Snares Islands).

In order to describe the species spatial requirements and quantify their overlap during chick- rearing period, the at-sea movements of parents were recorded using GPS data loggers. Fine- scale data were recorded with 1, 2, 3 and 5 min sampling intervals depending on the trade-off life-time battery/expected trip length of the species (loggers’ model and attachment method previously presented in the materials and methods section of the chapters 2, 3 and 4). To infer the at-sea behaviours of individuals during their trips, tri-dimensional accelerometer data loggers were also deployed. These acceleration data were recorded at 25 Hz, allowing the reconstruction of the activity budget and the identification of foraging behaviour. As proxy of prey encounter events (Kokubun et al. 2011), the foraging behaviour occurrence in time and space allowed to gain insights in the foraging strategies of the species, and to investigate the temporal segregation of their foraging niche. To compare the diving behaviour of the species, penguin and petrel were equipped with an accelerometer including a pressure sensor, allowing measurement of dive depth each second. Loggers were chosen to represent minimal extra mass and cross-sectional surface area in order to have negligible impact on the individual’s behaviour (Phillips et al. 2003, Agnew et al. 2013, Chivers et al. 2016). At recapture after a foraging trip, the loggers were removed. To investigate the isotopic niche, 0.1 mL of blood was 118 taken from a tarsal vein by venepuncture. Details on instrumentation and handling are presented in Chapters 2, 3 and 4 for each studied species.

At Taumaka/Open Bay Island, the Fiordland penguin, little penguin and spotted shag breed sympatrically. However, complete data collection was possible only on Fiordland penguins due to the inaccessibility of the nests of the two other species. Little penguins were captured away from nests at night for blood sampling only. The at-sea movements, foraging and diving behaviour information on both spotted shag and little penguin were obtained from the literature from previous studies in New Zealand. For little penguin, the maximum foraging distance from the colony reported on the west coast of New Zealand’s South Island was 34 ± 13 km over waters > 150 m deep (Poupart et al. 2017). Little penguin diving behaviour was characterised by mean dive depth at 11 ± 0 m and maximal dive depth at 31 ± 1 m (Chilvers 2019). For spotted shag, the maximum foraging distance from the colony was reported between 2 – 16 km

(Stonehouse 1967). Published data on the diving behaviour of spotted shag are currently unavailable (Ropert-Coudert et al. 2018) but observations of surfacing behaviour suggests mean dive durations of 30 s (Stonehouse 1967). Assuming comparable diving capabilities as the Antarctic blue-eyed shag Phalacrocorax atriceps, such dive duration would correspond to an intermediate dive depth between penguins and Procellariforms at < 21 m (Croxall et al.

1991). Information on the diet of each species was obtained from published studies of stomach contents analysis (Imber 1976, West & Imber 1986, Van Heezik 1989, 1990, Freeman 1998,

James & Stahl 2000, Fraser & Lalas 2004, Lalas et al. 2004, Flemming et al. 2013).

5.3.2 Data processing and statistical analyses

The horizontal component of the species niche was investigated using the processed GPS tracks (as presented in Chapters 2-4). These data were used to calculate their respective home ranges, with the geosphere package (Hijmans & Van Etten 2016), and their spatial utilization distribution (Worton 1989) using the adehabitat package (Calenge 2006). Kernels were computed with 50% and 95% utilization distribution (UD), using smoothing parameter (h) 119 fixed by the hdef method. These kernels were interpreted, respectively, as the core foraging area (50% UD) and the home range (95% UD) of tracked species, from which overlap was quantified by Bhattacharyya’s affinity index (ranging from 0 when no overlap, to 1 when overlap is complete) as recommended for quantifying overall similarity between ranges

(Fieberg & Kochanny 2005).

The vertical component of the species niche was assessed for the Fiordland penguin and

Westland petrel with the dive data retrieved from loggers (as described in Chapters 2 and 4) and published reports for the other species. As Thalassarche albatrosses rarely plunge (Harper

1987), the southern Buller’s albatross diving ability was assumed from the shallow dives recorded in similar-sized congener Thalassarche melanophris (Prince et al. 1994a). The temporal components of the species’ niches were studied with the timing of the foraging behaviour inferred from the tri-axial acceleration data (see Chapters 2-4 for details). The time spent foraging by each species was grouped by hour and the temporal trends compared between species.

Finally, the degree of inter-specific trophic niche partitioning was assessed firstly from summarized information on diet (in a matrix of prey presence-absence for each study and site).

Interspecific difference within the winter-breeding seabird community was investigated by a

Non-metric MultiDimensional Scaling (NMDS, Clarke 1993). The Bray-Curtiss dissimilarity index was used as input in the NMDS, performed with the package vegan (Oksanen et al. 2007).

In addition, isotopic ratio values (δ13C and δ15N) from whole blood were used to determinate the ellipse-based isotopic niche of the species, using the SIBER package (Jackson et al. 2011)

(see details on methods in Chapters 2-4). This ellipse can be interpreted as the core isotopic foraging niche of a population (Polito et al. 2015), and enables comparisons of the trophic level, isotopic niche overlap (from 40% corrected standard area, SEAC) and width differences (from

Bayesian estimates, SEAB) among guilds and unrelated species within a same ecosystem

(Hobson et al. 1994, Cherel & Hobson 2007).

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5.4 Results

5.4.1 At-sea movements

Tracking data were obtained for 33 southern Buller’s albatross, 31 Fiordland penguins and

31 Westland petrels (Table 5-1). GPS data showed restricted home range and core areas along the west coast of New Zealand’s South Island (Figure 5-1) for Fiordland penguin and Westland petrel, characterised by movements with mean maximal distance from the colony of 37 ± 4 km

(max = 107 km) and 154 ± 14 km (max = 315 km), respectively. Only the southern Buller’s albatross displayed an extended home range, with extensions on the east coast of the New

Zealand North and South islands, Tasman Sea and the east coast of Tasmanian. However, its core range was also mainly located along the west coast of the South Island, with movements characterised by maximal distance from the colony of 249 ± 38 km (max = 1575 km). These data corresponded to global home range areas of 1,252,538 km2 for southern Buller’s albatross,

49,540 km2 for Westland petrel, and 4,427 km2 for Fiordland penguin. These home ranges also all encompassed areas situated within 34 km around little penguin colonies and within 16 km around spotted shag colonies home range along the west coast of New Zealand’s South Island

(Figure 5-1).

All tracked species overlapped at sea by variable amounts, with their Bhattacharyya’s affinity index ranging from 0-0.34 for home ranges and 0-0.14 for core areas (Table 5-2). The largest overlap at sea was found between the home range and core areas of southern Buller’s albatross and Westland petrel, breeding 612 km apart. Little overlap was found, and only in home range, between the Fiordland penguin of Taumaka/Open Bay Island and the Westland petrel breeding 285 km apart. The home ranges of little penguin and spotted shag estimated from literature data also showed potential overlap between these two species within 16 km offshore, both in the coastal and inshore environments.

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Table 5-1: Number of individuals with GPS, dive, acceleration data and blood samples collected during each year of the study.

Data collected

GPS Dives 3D Acceleration Whole blood samples 2016 Southern Buller’s albatross 17 - 13 17 Fiordland penguin 5 1 1 10 Little penguin - - - 10 Westland petrel 16 7 14 19 2017 Southern Buller’s albatross 16 - 14 24 Fiordland penguin 26 22 22 43 Little penguin - - - 20 Westland petrel 15 - 15 15

Table 5-2: Spatial overlap between winter breeding species for home range (kernel 95%) and focal area (kernel 50%, in italic) estimated using Bhattacharyya’s affinity index (0=no overlap, 1=complete overlap).

Southern Buller’s albatross Fiordland penguin 2016 Fiordland penguin 0.03 / 0 - Westland petrel 0.26 / 0.09 0 / 0 2017 Fiordland penguin 0.09 / 0 - Westland petrel 0.34/ 0.13 0.14 / 0

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Figure 5-1: Spatial overlap between winter-breeding species on the west coast of New Zealand’s South Island during 2016 (up) and 2017 (below). Plain and dotted lines represent the 50% kernel (core area) and 95% kernel (home range) respectively, in orange for southern Buller’s albatross, green for Westland petrel and red for Fiordland penguin. The triangles on the coast represent other breeding locations known for these species, following the same colours, and in blue for little penguin and black for spotted shag (data from Te Papa Tongarewa Museum unpublished database).

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5.4.2 Temporal pattern of foraging and diving behaviour

In addition to the temporal overlap of their respective breeding schedules, the tracked species also displayed some temporal overlap in the timing of their foraging behaviour at a daily scale. Fiordland penguins foraged mostly (89 %) during daylight hours, whilst the volant species were less dependent on daylight hours for feeding (46 % of the southern Buller’s albatross and 45 % of the Westland petrel foraging times). Little penguin and spotted shag are reported to be diurnal foragers returning to colonies at dusk (Stonehouse 1967, Preston et al.

2008). While there was partial temporal overlap in foraging, these species exhibited differences in their respective temporal trends throughout the day. Fiordland penguin time spent foraging peaked after sunrise at 08:00 h and before sunset at 15:00 h (local time), while southern Buller’s albatross foraging peaked at 10:00 h and Westland petrels foraging peaked in darkness after sunset (21:00 h, Figure 5-2). In addition, foraging activity decreased during solar noon for

Fiordland penguin and southern Buller’s albatross, but not for Westland petrel.

Figure 5-2: Time spent foraging along the time of the day by tracked winter breeding species. The areas in dark grey indicate the night, in light grey the dusk and dawn (nautical twilight).

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Diving behaviour was found to be limited close to the surface for Procellariforms, with deepest dives recorded at 8 m for the Westland petrel, and inferred at 2 m for southern Buller’s albatross (Prince et al. 1994a). Penguins were the species exploiting the greatest part of the water column, with dives recorded as deep as 105 m for the Fiordland penguin and 34 m for the little penguin, while the spotted shag was assumed to exploit shallower waters to a depth of 21m (Figure 5-3).

Figure 5-3: Comparison of diving range (vertical line), mean dive depth (point) and standard error (horizontal line) for tracked winter breeding species.

5.4.3 Diet and isotopic niche

Published information on the diet of the five winter-breeders reported a total of 139 prey items, including 89 prey items for the southern Buller’s albatross, 47 for the Westland petrel,

23 for the little penguin and 22 for the Fiordland penguin. The main consumed prey were fish and cephalopods for all species, with a fish-dominated diet for surface-feeders (Imber 1976,

West & Imber 1986, Freeman 1998, James & Stahl 2000) and cephalopods for divers (Van

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Heezik 1989, 1990, Flemming et al. 2013). Limited available data on the spotted shag diet indicate feeding on planktonic crustaceans and small fish including the Australian anchovy

Engraulis australis (Marchant & Higgins 1990), a prey species commonly consumed by

Westland petrels (Imber 1976). Dietary overlap between the diets of the species comprised a total of 32 common prey items, including 18 cephalopods, 13 fish and 1 crustacean. In order of importance, common prey were found between southern Buller’s albatross and Westland petrel (n = 20), southern Buller’s albatross and Fiordland penguin as well as Fiordland and little penguins (n = 8), southern Buller’s albatross and little penguin (n = 7), Westland petrel and

Fiordland penguin (n = 6), and Westland petrel and little penguin (n = 5). The NMDS ordination showed the largest dissimilarity between southern Buller’s albatross and little penguin diets, while the lowest dissimilarity was found between the diets of the two penguins

(Figure 5-4).

Figure 5-4: Dietary overlap among the winter breeding community off the west coast of New Zealand’s South Island represented by non-metric multidimensional scaling (NMDS), with convex hulls (when n > 2 studies) or lines (when n = 2 studies) coloured by species.

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The isotopic investigation of trophic niche was conducted on blood samples obtained from a total of 158 individuals (Table 5-3), including tracked individuals and additional non-tracked

13 breeders. The guilds differed in their δ C (ANOVA, F3,154=192, P < 0.001) and the species

15 differed in their δ N (ANOVA, F3,154=359, P < 0.001). Their SEAB estimated isotopic niche areas was 1.48 ‰2 for little penguin, 0. 37 ‰2 for Fiordland penguin, 0. 36 ‰2 for southern

2 Buller’s albatross and 0.22 ‰ for Westland petrel. Their SEAC showed no inter-guild overlap, as well as intra-guild for the Procellariforms surface feeders. However, the diving guild of penguins showed maximum likelihood overlap by 40 % (Figure 5-5).

Figure 5-5: Isotopic results of winter breeding species provisioning chicks. Individuals’ signatures are shown by the dots, and the isotopic niches by the 40% standard ellipse areas

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N δ13C (‰) δ15N (‰) Westland petrel 34 -18.3 ± 0.3 15.4 ± 0.2 Southern Buller’s albatross 41 -18.5 ± 0.2 14.6 ± 0.4 Fiordland penguin 53 -19.9 ± 0.3 12.2 ± 0.3 Little penguin 30 -19.8 ± 0.5 12.6 ± 0.8

Table 5-3: Isotopic values (whole blood, mean SD) of the winter breeding species provisioning chicks off the west coast of New Zealand’s South Island in 2016 and 2017.

5.5 Discussion

By combining the information from different tracking devices, associated isotopic results and dietary studies, the present study described for the first time the degree of at-sea overlap during the elevated nutritional needs of chick-rearing within a winter-breeding seabird community. Horizontal, vertical, temporal and trophic axes showed varying partial intra-guild and inter-guild overlaps. Despite no drastic distinctions between these different species, the accumulation of small segregation in all axes is likely to be the mechanism of ecological niche partitioning during the period of chick-rearing for these species.

The niche theory postulates that species with similar ecological requirements display niche segregation to limit competition (Ricklefs & Miller 1999). Thus, large foraging divergences were expected between and within guilds of the winter breeding seabird community of the west coast of New Zealand’s South Island. The results of the present study, conducted on species having small populations, indicated that they all used predominantly the shelf-slope and neritic waters of the west coast of New Zealand’s South Island despite the species-specific difference in body mass, movement costs and distance travelled between swimming and flying species.

These findings are consistent with the foraging areas described in previous single-species studies (Freeman et al. 1997, Stahl & Sagar 2000b, Waugh et al. 2018) and confirm inter- specific overlap at-sea across years. Although species showed some spatial overlap which is

128 likely to be under-estimated, they also displayed spatial differences between guilds, with restricted at-sea horizontal movements by diving guild constrained by high energetically demanding movements (flipper strokes for swimming for penguins, and wing flaps for flying shag, Ropert-Coudert et al. 2006, Hicks et al. 2017). Procellariforms species flying with low cost soaring flight (Sachs et al. 2013) moved further offshore and from their colony. However, they also exploited close areas over the narrow peri-insular shelf that overlapped not only partially between guilds, but also at a higher degree within its guild. The shelf is reported to undergo an enrichment of nutrients during winter, caused by the combination of the flow of oligotrophic waters coming from the Tasman Sea, the intermittent wind-driven upwelling and the mixed-layer deepening (Longhurst 1995, Chiswell et al. 2016).

Due to the logistical and field constraints, the tracking of all species (and in multiple locations for species with a wide range) was not possible in the present study. Consequently, the degree of overlap reported in the present study may be under-estimated. For instance, the breeding range of penguins and shags with many colony locations encompass a wider part of the home range of southern Buller’s albatross and Westland petrel than measured in the present study.

Spatial segregation was also apparent in the vertical axis, with clear intra- and inter-guilds divergences in diving depth. Indeed, Procellariforms are mainly surface-seizers and Westland petrels showed a dives limited at shallow depth only. In contrast, pursuit-divers such as shag and penguins exploited deeper depth, and it is inferred, a deeper depth found for larger species, a finding consistent with the relation depth ~ body size in other penguins (Wilson 2010).

The quantification of foraging behaviour by the accelerometry method allowed accurate comparison of the foraging timing between species. For these visual foragers, general diurnal overlap occurred. However, each tracked species displayed species-specific peaks of foraging time. For instance, the Fiordland penguin foraging peaks after sunrise and before sunset,

129 associated with deeper dives at noon and quasi absence of diving at night. As penguins are visual foragers (Wilson et al. 1993, Bost et al. 2002), this diving pattern is likely to be related to the of some of its prey (Chapter 2). In the same way, albatrosses are reported to be actively searching prey from the air during the day, but mainly using a sit-and- wait technique on water at night (Weimerskirch & Wilson 1992, Catry et al. 2004b). In contrast,

Westland petrel foraging peaks after sunset suggests an active feeding on diel migrating prey moving close to surface at night, which is in accordance with the presence of bioluminescent prey in its diet (Imber 1976, Freeman 1998). The diurnal foraging activity of the little penguin

(Cannell & Cullen 1998) suggest common visual constraint with the Fiordland penguin. While foraging behaviour data are not available for the spotted shag, shags tend to be diurnal, coastal and benthic foragers (Grémillet et al. 1998a).

The largest difference between the two guilds was found in the trophic axis, as expected for guilds with different feeding techniques. Our results showed that the most similar diets existed within guilds, followed by Fiordland penguin – Westland petrel (with a lower number of diet studies) for inter-guild comparisons of diets. The investigation of the isotopic niche from whole blood also emphasized the inter-guild diet segregation, with Procellariforms situated high in the food chain, at the equivalent of one trophic level above the penguins (Post 2002). However, intra-guild isotopic niche overlap revealed contrasted results between penguins and

Procellariforms. Procellariforms species both showed narrow isotopic niche, which did not overlap. In contrast, sympatric penguins had large isotopic niche overlap. The wide isotopic niche of the little penguin overlapped almost entirely the narrower isotopic niche of the

Fiordland penguin, suggesting respectively generalist and specialized diets. However, these results seem in contrast with the high number of prey items found in Procellariforms diets(Freeman 1998), and with the low number of prey items found in the little penguin diet.

Hence, this suggest a complex link between the snapshot information of stomach contents and the assimilated diet over time of the whole blood that needs to be clarified with further study.

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Although the species showed inter- and intra-guild overlap in most the niche axes, this overlap was always partial, and the accumulation of small divergence in several axes with mechanisms comparable than other summer breeding species (Masello et al. 2010, Rosciano et al. 2016, Pratte et al. 2017) lead the species to occupy hyper-volumes more segregated than expected with only one axis. Their coexistence within a same geographical area can also be strengthened by different prey choice, e.g. same prey species of different length (Van Heezik

1990). The present study, reported results from two years with good breeding success (Chapter

4) and additional years with different environmental conditions are required to better understand niche overlap in these species. Indeed, the generalist and specialized species are likely to display variable segregation under changing prey availability (Polito et al. 2015,

Moreno et al. 2016). Such knowledge on niche plasticity is important in perspective of ongoing climate change in the area (Matear et al. 2013).

In summary, the present study indicate that the winter-breeding seabird community of New

Zealand study shows overlapping foraging areas during the chick-rearing period, but with differences in their use of the marine environment in terms of diving depth, preferred time of foraging during the day, prey items and/or size which enables their coexistence. In contrast to other seabirds for which spatial segregation is the main mechanism of niche partitioning

(Navarro et al. 2013, Gulka et al. 2019) , the present study showed at-sea overlap both for sympatric species and distant breeding species, flying hundreds of kilometres to forage in similar areas. These findings suggest that shelf slope and inshore waters off the west coast of

New Zealand’s South Island provide adequate access to a variety of prey during winter and spring, and allow the small populations species of this winter-breeding community to meet their nutritional needs during breeding without intense competition. Under these conditions, winter, a season generally reported as a challenging period elsewhere, may be a favourable time for breeding locally. Indeed, this area is also reported to be heavily exploited by overwintering Cape petrel Daption capense from Antarctica (Delord et al. 2016).

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Chapter 6:

General Discussion

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The ability to meet the elevated food requirements of reproduction is crucial for animal populations, especially for income-breeding species that have to fuel their offspring needs with their own maintenance (Lack 1954). While most seabird species display a breeding phenology matching their prey abundance in spring/summer, a few species are able to breed during winter months (Croxall 1984). How such species can take advantage of a period traditionally reported to be energetically and nutritionally challenging, and how they can avoid inter-specific competition, is poorly documented. Hence, the winter-breeding seabird community on the west coast of the New Zealand’s South Island was studied with the objectives to determine the fine- scale foraging behaviour of two guilds (divers: penguins, surface-feeders: Procellariforms), the environmental and intrinsic factors influencing it, the potential difference in foraging strategy with summer-breeding congenerics, and their niche overlap as they exploit similar areas during the chick-rearing period.

6.1 Foraging patterns of winter- and summer- breeding species

Given the seasonal variation of oceanographic conditions influencing the marine life and the prey field of seabirds (Hipfner 2008, Wells et al. 2008), some differences are reported in the foraging behaviour between summer- and winter-breeding seabirds. For example, the species with protracted breeding seasons spanning a year display seasonal changes in diet and foraging effort. In subpolar regions, King penguins Aptenodytes patagonicus rear chicks at

80% of the adult mass until their growth is interrupted by winter due to irregular feeding and fasting during this season, and they complete growth and fledging the following summer

(Cherel & Le Maho 1985, Croxall & Briggs 1991). While King penguins forage primarily on myctophid fish during summer, their diet becomes dominated in mass by squids in winter

(Cherel et al. 1993, Cherel et al. 1996) when they forage at greater depths (Charrassin & Bost

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2001). Similar seasonal increase in foraging effort have been found in surface-feeding species such as the Wandering albatross Diomedea exulans (Salamolard & Weimerskirch 1993).

In the temperate region of the New Zealand archipelago, winter is milder than in subpolar regions but this area is still strongly influenced by the Antarctic circumpolar ocean-atmosphere system (White & Cherry 1999) and undergoes a sea-surface cooling by 4°C (Garner 1969).

The degree of severity/mildness in climatic conditions and food availability during winter is known to influence directly the survival (Camphuysen et al. 1999, Fort et al. 2009), and indirectly the fitness for the subsequent breeding by carry-over effects, of both resident and migratory species (Saino et al. 2004, Harrison et al. 2011, Salton et al. 2015). The apparent acute costs of reproduction during winter, induced by seasonal changes of the marine environment and reflected in predator responses to prey field changes (Elliott et al. 2008), gives reasons to expect some differences between summer- and winter-breeding foraging behaviour.

Reduced day length, up to 5 h compared to summer at the same location, is also suspected to constraint the foraging of these visual predators (Daunt et al. 2006). In addition, as the seabird survival and breeding success is positively correlated with prey availability (Oro & Furness

2002, Sherley et al. 2013), winter-breeding could also lead to differences in their respective life-history traits (Stearns 1989).

Analysis of the nesting distribution of summer- and winter-breeding species (Figures 6-1 and 6-2) suggest that, as has been observed elsewhere (Newton & Fugler 1989, Bost &

Jouventin 1990, Zotier 1990), winter-breeding species in New Zealand occupy the same breeding range as summer-breeding species but with lower population sizes. However, the wide distribution of winter-breeding species across the New Zealand archipelago is mainly due to the phylogeographic partitioning (Rawlence et al. 2014), except on the west coast of the New

Zealand’s South Island that aggregate winter-breeding species.

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Figure 6-1 : Breeding distribution and colony sizes of summer-breeding New Zealand seabirds.

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Figure 6-2: Breeding distribution and colony sizes of winter-breeding New Zealand seabirds. Note the difference of scale in the dots size area compared with the summer-breeding figure.

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The present study revealed the pelagic winter-breeding species on the west coast of the New

Zealand’s South Island were engaged in foraging trips of short duration within a restricted range in comparison to their summer-breeding congenerics (Chapters 2-4). A similar trend was observed for diving behaviour, with winter-breeders foraging at shallower depths.

Interestingly, identification of foraging events revealed prey encounters were common and widespread over the study zone. The reduced day length did not lead the studied species expanding their foraging activity during low light levels (Systad et al. 2000). Fiordland penguins were found to be almost exclusively diurnal foragers, while nocturnal foraging occurred more regularly for Procellariforms. While large-sized penguins have been reported to rewarm peripheral tissues with blood circulation while resting on the sea surface at night

(Lewden et al. 2017), albatrosses forage opportunistically while resting on the surface at night

(Weimerskirch & Wilson 1992). In contrast, petrels are known to actively forage at night

(Harper 1987, Rayner et al. 2008, Mackley et al. 2011), potentially reflecting their ability to locate vertically migrating prey that include bioluminescent taxa (Schramm 1986). These findings are consistent across guilds and genus (Chapters 2, 3 and 4) and associated with high survival and breeding success (Francis & Sagar 2012, Waugh et al. 2015, Otley et al. 2017).

Contrary to expectations, the present study found no evidence of increased foraging effort, in comparison to that observed in summer-breeding congenerics, due to a winter-breeding schedule. The comparable effort suggests a permissive food availability adequate to sustain the elevated nutritional requirements of breeding activities. Hence, the scheduling of breeding may be more influenced by the predictability and profitability of available resources than fixed seasonal influences (e.g. photoperiod) in these temperate species.

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6.2 Marine trophic resource in winter around New Zealand

The foraging trips of the tracked winter-breeding species in the present study were mostly directional and converged towards the area where the eastward flow of the Tasman Sea waters interact with the peri-insular shelf of the west coast of the New Zealand’s South Island (Heath

1985). This eastward flow divides there into the northward Westland current (4 cm.s-1) and the southward Southland current (30 cm.s-1, Bradford-Grieve & Livingston 2011). In contrast to eastern boundary upwelling systems (California, Iberian/Canary, Humboldt and Benguela currents, (García-Reyes et al. 2015), this oceanic feature does not cause a sustained and strong upwelling (Butler et al. 1992). However, in winter, the sea-surface cooling disrupts the vertical thermal stratification which, in turn, affects the mixed-layer deepening (up to 200 m deep) and its convective overturn (Garner 1969, Sutton et al. 2005). Wind stress induces a coastal flux varying in strength according to the shelf topography and is responsible for the intermittent upwelling plume (Shirtcliffe et al. 1990, Stanton 1995). In addition, the mountainous land mass blocking prevailing westerly winds induces heavy rainfalls, eventually influencing inshore waters with large amounts of freshwater and sediments brought by river outflows (Stanton

1976, Stevens et al. 2019). Together, these mixing processes recharge the iron-limited waters coming from the Tasman Sea over the New Zealand shelf (Ellwood et al. 2013) and constitute the drivers of the ecosystem enrichment (Bradford-Grieve et al. 1993).

Consequently, contrary to most oceanic areas where winter primary productivity is depressed (Alvain et al. 2008), it is locally increased off New Zealand (Longhurst 1998,

Murphy et al. 2001). The Chapter 5 showed that the studied winter-breeding species feed at medium and high trophic level, and therefore, are decoupled from direct primary productivity.

However, the winter and spring primary production aggregates the prey of top predators

(Grémillet et al. 2008, Bost et al. 2009, Sabarros et al. 2014). Despite the lack of prey biomass in the present study, previous reports indicate that mesopelagic fishes, squids and taxa find on the productive shelf off the west coast of New Zealand’s South Island suitable conditions

138 for spawning in winter (Coombs & Cordue 1995, Uozumi & Forch 1995, Daponte et al. 2013).

Vertical diel migration (McClatchie & Dunford 2003), adult aggregation in schools (O'Driscoll

2004) and sometimes terminal spawning (which die-off after reproduction, Jackson &

Mladenov 1994) are different processes that provide predictable and accessible food resources in the epi-pelagic zone / near surface for seabirds, which occur also in winter off the west coast of the New Zealand’s South Island. In addition, this resource is constituted not only by adults preys, but also their larvae hatching and growing fast through winter before their ontogenic descent in summer (Voss 1985, Jackson et al. 2007).

The breeding schedule, foraging behaviour and the niche habitat overlap of the tracked winter-breeding species in the present study are in accordance with this particular ecosystem functioning. The resident species (little penguin) ceases breeding after only one clutch (whereas the species is known to multi-clutch in other parts of its range, Reilly & Cullen 1981, Gales

1985) while the migratory species depart the region in summer, suggesting a potential energetic bottleneck in the region for winter-breeding species following their breeding period.

6.3 Relation between winter-foraging and winter-breeding

The fine-scale description of the foraging behaviour by the seabird winter-breeding community of the west coast of the New Zealand’s South Island, augmented by dietary information from the literature and by an isotopic examination of their trophic niche

(integrating a longer time period than stomach contents), suggest a phenological match between the plankton, the consumers and predator needs, as hypothesized by Cushing (1990). Once the milder conditions of spring arrive, the chicks of winter-breeding species fledge after the peak of primary production has passed (Murphy et al. 2001), and the adults vacate their breeding foraging range. The southern Buller’s albatross and Westland petrel both migrate to South

America (Stahl & Sagar 2000b, Landers et al. 2011b), and the Fiordland penguin descends to

139 subantarctic waters in order to built-up fat reserves for the moult (Mattern et al. 2018). The findings of the present study suggest sufficient food availability for the small populations of the tracked species in the present study. Hence, the foraging cost/benefit ratio as a determining factor for the timing of breeding, among others that have been reported (photoperiod, weather, genetic inheritance, Van Noordwijk et al. 1981, Nelson et al. 1998, Both et al. 2005). Hence, breeding at the right time can encompass a variety of periods during the year, including winter.

This notion can be illustrated by the extreme example of the Emperor penguins Aptenodytes forsteri, which can breed in the cold and darkness of the Antarctic winter as long as they have access to sufficient fish and stock to fuel it (Kirkwood & Robertson 1997a). In European temperate latitudes, winter-breeding also occurs in small rodents during years of acorn and beech mast superabundance (Smyth 1966). This difference between winter season and challenging environmental conditions, mediated by food availability, is also reported for overwintering summer-breeding species. For example, the survival of blue petrel Halobaena caerulea is reduced during winters with sea-surface temperature warmer than average, caused by lower food availability (Barbraud & Weimerskirch 2003).

The number of winter-breeding seabirds species in polar, subantarctic and temperate regions is very limited (Chapter 1), as well as in other animal phyla. However, the existence of this unusual winter-breeding schedule across different genera and geographic locations suggest that winter-breeding can be seen as an evolutionary convergence. According to the local food availability (that can or cannot sustain elevated food requirements) present in the gradient of seasonal environments between polar – subtropical regions, the “right” breeding time reveals the degree of adaptation of a species to its environment (Both & Visser 2005) and is likely to be context-dependent. Hence, winter-breeding schedule is in fact a response to the same constraints as a summer-breeding strategy, and seems to be a life-history trait shaped by profitable conditions at a different season.

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Synchronization in the timing of reproduction has been reported to have an adaptive significance to distribution and predictability of the food supply (Emlen & Demong 1975, Ims

1990). The breeding schedule synchronization observed in Westland petrel, southern Buller’s albatross and Fiordland penguin tracked populations, on top of the inter-specific overlap of their respective breeding schedule (Chapter 1), suggest a reliance on a pulsed winter food resource driving the profitability of the habitat for all seabirds. Too early or too late, a mismatch with this pulse would reduce offspring survival (Lack 1954, Perrins 1970). Given the limited knowledge of the prey species consumed by the seabirds in the present study, further research on diet and, ideally, the abundance of prey at sea, is needed to understand which factors drive such a temporal match.

What has caused winter-foraging and winter-breeding match situation to happen? Two non- exclusive hypothesis could be discussed. Firstly, the original evolution of the New Zealand archipelago, with changing oceanic circulation and land mass evolution, has offered a variety of opportunities to evolve in original ways (Newnham et al. 1999). This panel of environmental conditions has led to a wide species radiation that could explain the variety of strategies in New

Zealand seabirds (Grealy et al. 2017, Rawlence et al. 2017, Rawlence et al. 2019). Indeed, the fossil discoveries testify to a large ancient biodiversity (Mayr et al. 2017), potentially including a ready “winter niche”. Such winter food resources could have been exploited by winter- breeding species even more numerous in the past. These facts also highlight that the current

New Zealand seabirds populations are likely to be a glimpse of the past, since human colonisation and its consequences (e.g. direct predation, mammal introductions) has reduced the species distributions and population sizes (Tennyson & Martinson 2006, Rawlence et al.

2015). For instance, larger seabirds populations, potentially reinforced during the last glacial maximum when subantarctic islands experienced ice cover while New Zealand remained ice- free (Gersonde et al. 2005), would have led to an intense intra- and inter-specific competition.

Hence, a second hypothesis of winter-breeding evolving, driven by competitive exclusion, can

141 be put forward. Indeed, the waters around the South Island of New Zealand host the foraging areas of millions of summer-breeding seabirds, such as the millions pairs of sooty shearwater

Puffinus griseus (Jones 2000, Shaffer et al. 2009, Waugh et al. 2013). Few species with small populations breeding during winter months before the arrival of numerous summer-breeders is a situation common to other places, although involving lower diversity of winter-breeding species (Chapter 1). For example, the Bass Strait in Australia also hosts the black-faced cormorant, common diving petrel and little penguin, which finish breeding when millions of short-tailed shearwater Puffinus carneipes arrive and overlap with their foraging areas

(Berlincourt et al. 2015).

Philopatric seabirds, when displaying breeding asynchrony, can undergo a temporal restriction of their gene flow, eventually leading to speciation (Monteiro & Furness 1998,

Hendry & Day 2005, Rayner et al. 2011). Phylogenetic studies has shown that the closest relative species to Westland petrel, southern Buller’s albatross and Fiordland penguin were respectively the Grey petrel Procellaria cinerea, the Shy albatross Thalassarche cauta (after the northern subspecies Thalassarche bulleri platei) and the Snares penguin Eudyptes robustus

(Penhallurick & Wink 2004, Ksepka et al. 2006, Wold 2017). Divergence in their respective breeding time and specialization on different energy pathways (McCormack et al. 2019) are likely to have played a role in their speciation process.

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6.4 Perspectives and future research

Fine-scale tracking in the present study provided valuable insights in at-sea foraging behaviour by breeding individuals and subtle niche partitioning within a community. The combined use of GPS, accelerometers and diving recorders at a high sampling rate, the location accuracy and temporal match with remote-sensed environmental variables allowed to detail the foraging metrics and to improve the understanding of winter-breeding foraging. However, data on prey abundance and cycles remain limited and the link between winter-prey field and predators’ behaviour at fine-scale remains the most challenging information to get. With the recent development of animal-borne cameras (Sutton et al. 2015, Wells et al. 2016), and of biomimetic sonar (Goulet et al. 2019), predator-prey interactions could be better known in situ for far-ranging and deep-diving species. Such technologies might be a way to fill the gap between the extensive knowledge acquired on large predators, contrasting with the limited understanding of their small prey. In addition to at-sea studies during the winter-breeding season, year-round studies are also needed to identify the most critical times of predator in life cycle context (Marra et al. 2015).

While previous tracking studies have traditionally focused on species-specific studies to respond to conservation needs, multi-species approaches combining guilds and communities are more powerful to identify hot-spots reflecting ecosystem functioning (Block et al. 2011,

Reisinger et al. 2018) and niche partitioning among species (Navarro et al. 2015). In order to expand the understanding of breeding time, prey-predator interaction and niche segregation, future studies should target sympatric summer- and winter-breeding species communities (and including species that has not been tracked yet). Such combination of predators, prey and their environmental conditions would enable an ecosystem-based approach on the marine life adaptations and flexibility. Such knowledge is increasingly needed in order to tackle the challenges arising from ongoing climate change and human footprint and the oceans (Gremillet

& Boulinier 2009, Poloczanska et al. 2013, Halpern et al. 2015).

143

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