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The foraging ecology of Glausous Gulls preying on the eggs and chicks of Thick-billed Murres Gilchrist, H. Grant 1995

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THE FORAGING ECOLOGY OF GLAUCOUS GULLS PREYING ON THE EGGS AND CHICKS OF THICK-BILLED  MURRES  by H. GRANT GILCHRIST  Honors B.Sc., Trent University, 1990  A THESIS SUBMHthD IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES DEPARTMENT OF ZOOLOGY  We accept this thesis as conforming to the required standard  NIVERSITY OF BRITISH COLUMBIA September 1995 © H. Grant Gilchrist, 1995  In presenting this thesis in  partial  fulfilment of the requirements for an advanced  degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission.  (Signature)  Department of The University of British Columbia Vancouver, Canada Date  DE-6 (2/88)  °  ABSTRACT The glaucous gull (Larus hyperboreus) is a generalist predator with a circumpolar distribution. It commonly depredates the eggs and chicks of birds nesting in the Arctic, and often breeds in association with colonial nesting waterfowl and seabirds. The aim of this thesis was to examine how environmental factors constrained the ability of glaucous gulls to depredate cliff-nesting thick-billed murres (Uria lomvia), and to determine whether these constraints vary through time, in space, or between individuals. I also wanted to determine how changes in gull foraging constraints could affect the impact of gulls on murre reproductive success and population dynamics. This study was conducted from 1990-1992 at a murre colony on Coats Island, Canada, and in 1993 at colonies in the Upernavik region of Greenland. Based upon results from egg placement experiments and field observations of predation, gull foraging success was constrained by high murre nesting densities, collective murre defence, and the accessibility of narrow cliff ledges. However, windy conditions enhanced the ability of gulls to overcome these constraints. Wind improved the aerial maneuverability of gulls, and enabled gulls to reach weakly-defended narrow ledges and avoid contact with murres during attack. Murre defence on narrow cliff ledges was less effective because murres had difficulty turning to face attacking gulls without dislodging their own eggs and chicks. Gull search activity, attack activity, and predation rates were strongly correlated with windy conditions. Consequently, the impact of gull predation on murre reproductive failure, which ranged from 0% to 21% depending on nest type, was determined largely by wind. Under calm wind conditions, adult gulls were often inactive and they rarely fed their chicks. This inactivity may reflect the reluctance of gulls to forage on foot, because although this was the most successful attack mode, it also incurred the greatest contact with defending murres. Alternatively, gulls could have been responding to the varying energetic demands determined by changing weather conditions, so that the danger of injury while foraging did not influence mode selection or periods of foraging activity. I explored these two alternatives using a dynamic II  simulation model which integrated field data and energetic estimates of gull foraging behaviour. The model suggested that the first explanation, which was based upon energy considerations alone, was not sufficient to explain gull foraging inactivity under calm wind conditions. However, the model supported the idea that gulls were sensitive to risk of injury, and that they should select low-danger foraging modes that provide low energetic gains. The model also revealed that gulls can afford to use foraging modes that yield low energetic gains relative to more productive and dangerous ones (e.g. scavenging vs. foraging on foot under calm conditions), because even poor foraging modes are sufficient to meet their energetic demands under most circumstances. I predicted that a decline in the density of nesting murres should enhance the ability of gulls to overcome the constraints of calm wind conditions, cliff ledge accessibility, and prey defence. Thus, murre colony declines should increase the impact of gull predation on murre reproduction. To examine the impact of gull predation at declining thick-billed murre colonies, I compared gull foraging mode selection, predation rates, and murre nest site selection at Coats Island, N.W.T., with that at declining murre colonies found near Upernavik Greenland. I found that gulls at declining colonies foraged on broad cliff ledges and were less constrained by calm wind conditions, apparently because population declines increased the availability of low nesting density ledges where gulls could maneuver on foot and attack murres with little risk of injury. Perhaps because of this, predation rates at declining murre colonies were consistently higher than at the stable Coats colony, particularly at low wind speeds.  111  TABLE OF CONTENTS Abstract  ii  Table of Contents  iv  List of Tables  vii  List of Figures  viii  Acknowledgments  x  Chapter 1: Introduction  1 1 3 4 5 9  Predator foraging behaviour Study sites Ecology of the glaucous gull Glaucous gull ecology at Coats Island Aims of this thesis Chapter 2: Effects of murre nest density, cliff ledge width, and wind on predation by gulls Introduction Methods Study area and species Egg placement experiments Behavioural observations Statistical analysis Results Nesting density Ledge width Wind speed Vulnerability of eggs relative to timing of laying Discussion Constraints on gull foraging efficiency Consequences of predation for thick-billed murres Chapter 3: Wind and prey nest sites as foraging constraints on an avian predator, the glaucous gull Introduction Methods Study area and species Behavioural observations Gull gliding-flight dynamics Effects of gull predation on murre reproductive success Statistical analysis iv  10 10 11 12 12 13 14 16 16 16 20 22 26 26 28 30 30 31 31 32 33 33 34  Results Murre colony structure and environment Gull search activity Gull attack rates Gull attack selectivity relative to murre nest site characteristics Gull predation rates Gull attack success Wind and gull maneuverability in flight Murre responses to gull attack Path diagram Colony-level effects of gull predation on seasonal murre reproduction Discussion Wind: a foraging constraint for glaucous gulls depredating murres The currency of glaucous gull foraging decisions Population level consequences of gull foraging behaviour for murres Conclusions Chapter 4:  Foraging mode selection of glaucous gulls provisioning young: consequences of a danger-reward trade-off mediated by wind?  Introduction Methods Study site and species interactions Field studies of gull foraging behaviour Dynamic optimization model Brood energy dynamics Model assumptions concerning provisioning Weather conditions Metabolic rate estimates Limits of chick fat stores Flight energetics Energy consumption Foraging mode energetic s and danger of contact with murres Modeling risk of fatal injury Results and Discussion Foraging mode selection with no risk of injury Foraging mode selection with risk of injury Comparisons with field data of gull foraging behaviour Further predictions Conclusions Chapter 5:  Effects of glaucous gull predation at declining thick-billed murre colonies: An inter-colony comparison  Introduction Methods Study sites Gull foraging behaviour and predation rates Numerical response of glaucous gulls to murre colony declines V  36 36 36 41 41 41 46 51 51 53 57 59 59 61 63 64  65 65 67 67 67 68 69 74 76 76 80 82 83 84 89 90 90 90 94 101 102 104 104 105 105 107 107  Murre nest site selection and breeding density Results Gull foraging mode selection, attack activity, and predation rates Numerical response of glaucous gulls to murre colony declines Murre nest site selection Discussion Gull foraging behaviour and predation rates Numerical response of glaucous gulls to murre colony declines Murre nest site distribution at declining colonies: a consequence of gull predation? Population-level effects of gull foraging behaviour: multiple-stable states? Conclusions Appendix I  108 109 109 112 115 117 117 118 119 121 123 124 125  Chapter 6: Conclusions Thesis synthesis Comparisons with other studies of gull foraging ecology From Larus to leo: identifying future research directions  125 126 132 134  Literature cited  vi  LIST OF TABLES page Table 2.1  Description of attack modes of gulls and murre responses to attack.  15  Table 2.2  Murre responses to gull attacks in relation to cliff ledge width.  19  Table 2.3  Gull attack techniques in relation to cliff ledge width.  21  Table 2.4  Murre response to gull attacks in relation to timing of murre egg laying.  25  Table 3.1  General linear models of factors affecting rates of aerial search by gulls.  40  Table 3.2  General linear models of factors affecting gull attack activity.  42  Table 3.3  Analysis of covariance of factors affecting rates of gull attack in relation to murre nest site characteristics.  43  Table 3.4  General linear model of factors affecting gull predation rates.  47  Table 3.5  Multiple logistic regression of factors affecting gull attack success.  49  Table 3.6  a) General linear model of factors affecting murre response to gull attack, and b) multiple logistic regression of factors affecting the probability that a gull was struck by murres during attack.  54  Table 4.1  Probability of wind conditions in the future in relation to the wind conditions in the current time interval  72  Table 4.2  Estimates of Resting Metabolic Rates for a glaucous gull adult and chick in relation to weather conditions  81  Table 4.3  Proportion of gull foraging time devoted to flight in relation to wind  85  Table 4.4  Parameter estimates of glaucous gull foraging mode energetics and risk of injury in relation to wind conditions  87  Table 6.1  A review of studies examining the foraging ecology of gulls  vii  127  LIST OF FIGURES page Figure 2.1 Survival of exposed murre eggs in relation to thick-billed murre nesting densities.  17  Figure 2.2 Survival of exposed murre eggs in relation to cliff ledge width.  18  Figure 2.3 Survival of exposed murre eggs in relation to wind speed.  23  Figure 2.4 Survival of exposed murre eggs in relation to timing of murre egg laying.  24  Figure 3.1 Wind conditions in relation to date at Coats Island.  37  Figure 3.2 Examples of glaucous gull aerial search activity in relation to wind and time of day.  38  Figure 3.3 Attack activity of glaucous gulls in relation to wind and murre nest site characteristics.  44  Figure 3.4 Glaucous gull predation rates in relation to date and year.  45  Figure 3.5 Predation rates of murre eggs and chicks in relation to wind, murre nest site characteristics, and year.  48  Figure 3.6 Glaucous gull attack success in relation to wind speed and year.  50  Figure 3.7 a) Glaucous gull foraging patrol duration over murre breeding areas in relation to wind, and b) gull attack-hover duration in relation to wind.  52  Figure 3.8 Path analysis of the interactions between factors affecting gull predation rates and risk of contact with murres during attack.  55  Figure 3.9 Proportion of murre eggs and chicks lost to gull predation in relation to murre nest type  58  Figure 4.1 Survival function of gull brood in relation to energy stores.  70  Figure 4.2 Dynamic model predictions of gull foraging mode selection under calm conditions in relation to time, brood energy stores, and risk of injury.  91  Figure 4.3 Dynamic model predictions of gull foraging mode selection under windy conditions in relation to time, brood energy stores, and risk of injury.  92  Figure 4.4 Individual variation in attack mode selection in relation to wind conditions.  96  Figure 4.5 Time budgets of aerial foraging specialists, and pedal foraging specialists in relation to wind conditions.  99  viii  Figure 5.1 Wind conditions at Coats Island and Kingittoq murre colonies.  106  Figure 5.2 Attack mode selection of glaucous gulls in relation to wind conditions and colony identity.  110  Figure 5.3 Glaucous gull attack activity in relation to cliff ledge width, wind speed and colony identity.  111  Figure 5.4 Gull predation rates in relation to wind speed and colony identity.  113  Figure 5.5 The relationship between gull numbers and murre colony size  114  Figure 5.6 Murre nesting characteristics in relation to the magnitude of declines at three Arctic murre colonies.  116  ix  ACKNOWLEDGMENTS from the support and input of many people, and I greatly This study benefited would like to take this opportunity to thank them. Most notably, I thank my supervisors Jamie Smith and Tony Gaston who generously provided support and encouragement throughout this project, and who contributed many ideas during the field work and write-up stages. Both Jamie and Tony were great supervisors, and I feel very fortunate to have studied with them. They struck a balance of involvement with this research while at the same time allowing me to make key decisions relating to the work (for better or worse). They also tempered my overly optimistic approach to field work with questions like, “ what will you do if that doesn’t work?” at opportune times (i.e. prior to plane departure). I would also like to thank Erica Nol for introducing me to both Jamie and Tony. I also greatly appreciate the input of my other research committee members Tony Sinclair, Ron Ydenberg, and David Jones, and also Carl Walters. They encouraged me to integrate a sound understanding of an organism’s Natural History with theoretical ideas. I particularly thank Ron Ydenberg for our many conversations and his substantial contributions to chapter 4. At the University of British Columbia, I was also fortunate to be surrounded by a dynamic and friendly group in the “Smith Lab” consisting of Lance Barret-Lenard, Fiona Schmiegelow, Linda Dupuis, Dave Westcott, Wesley Hochachka, David Ward, Arnon Lotem, Alice Cassidy, Victoria Campbell, and Christine Adkins. I benefited especially from my discussions with David Ward, Arnon, and Wesley. Thanks also to Christine Adkins for helping me translate gull behaviour into Quick Basic. While on Coats Island, I was fortunate to share my summers and bear encounters with Leah deForest, Garry Donaldson, David Andrews, David Noble, Don Crol, Mark Hiphner, Marco Passeri, Paul Prior, and Thomas Alogut. The experiences we shared on Coats have been the basis for many long-lasting friendships. I especially thank “the gull guys”, Thomas Alogut, Marco Passeri and Paul Prior for their assistance and tireless commitment to this work. While in the Canadian arctic, I also thank Bob Longworth and Lyne Paplinski of the Iqaluit Research Center for their logistical support and Carribean weather reports over the radio. For the research conducted in Greenland, I thank the Greenland Home Rule Government, Henning Thing, and the community and Mayor of Upernavik for their assistance and permission to work in the Upernavik region. I would also like to thank Kaj Kampp, Jamie Smith, Tony Gaston, David Nettleship, Vernon Byrd, David Nysewander, William Sydeman, and Daniel Roby for helping me reach Greenland. I also appreciate the assistance and companionship of Gabanguak Bidstrup, Thomas Alogut, and Tara Gilchrist while in the field. This project was funded by the Canada Life Assurance Co., World Wildlife Fund Canada, the American National Fish and Wildlife Foundation, the John K. Cooper Memorial Trust, the Erickson Memorial Scholarship, the Hull Group, Sierra Designs Canada, Mountain Equipment Co-op, Sigma Xi Research Support Fund, the Canadian Wildlife Service (Student Research Support Program to H.G.G. and operating grants to Anthony J. Gaston), Natural Sciences and Engineering Research Council of Canada (grant to James N. M. Smith and student support for H.G.G.), the University of British Columbia Graduate Fellowship, the Northern Studies Trust Program, and the Science Institute of the Northwest Territories. Finally, I would like to acknowledge the support of my family, Tara Gilchrist, Nancy and Brian, Susan and Cohn, and my parents Hugh and Myirea Gilchrist who helped me in so many ways. I am especially grateful to my parents for encouraging me to pursue my interest in nature and for not pushing the more practical “architecture career path” too hard. Finally, I thank my wife Tara for her tremendous support and patience, particularly during our times apart. x  1  CHAPTER 1 INTRODUCTION  When I was young, I used to lie in the grass on summer afternoons to watch the aerial acrobatics of a kingbird (Tyrannus tyrannus) catching insects. I was amazed at how easily it could fly up from its perch to snatch insects out of the air. On one of these days, a dense fog rolled over the countryside and the kingbird rarely moved; its feathers fluffed out against the dampness. As I was about to leave, I noticed a Cooper’s hawk (Accipiter cooperii) suddenly appear out of the fog in a grey blur as it dived towards the kingbird on the fence. The kingbird climbed vertically into the air to avoid the attack, and the hawk followed effortlessly. At the peak of its climb the kingbird dived straight back to the ground and at the last second, pulled up to glide neatly through the wire fence with the hawk in close pursuit. The hawk rocketed through the fence in a puff of feathers, and tumbled lifelessly into the grass on the other side; one of its wings shorn off by the wire. The kingbird re-appeared out of the grass and returned silently to its perch in the fog. Early observations like this convinced me that foraging and anti-predator behaviour are critical components of an animal’s life history, and also important influences on the interactions between species in the wild. Even predators like the Cooper’s hawk face constraints and risks when foraging, and in the most extreme cases, foraging decisions can cause crippling injury or even death (as above). As I continued to study biology, I often found it useful to examine foraging behaviour from an economic perspective (Stephens and Krebs 1986). Early foraging studies used the premise that animals should select foraging strategies which maximize their net energetic gain. However, the simplicity of these early models obscured critical factors that affect foraging decisions in the wild (learning, changing physiological states, predation risk, risk of injury during attack; Real and Caraco 1986; Lima and Dill 1986; Mangel and Clark 1986). More recent foraging studies have attempted to identify factors that constrain the abilities of animals to maximize net energetic gain. Rather than asking, “do animals behave  2 optimally?’, foraging theory now considers why animals often select foraging strategies that do not yield the highest energetic gain (Dill 1986; Stephens 1990; Ward 1990). For example, foragers often appear to minimize mortality risks while foraging, so that a trade-off exists between immediate energetic gain and risks of mortality (Lima and Dill 1986). For predators like the Cooper’s hawk, foraging can be dangerous if prey fight back (physically or behaviourally), or if larger predators prey on them while they hunt (Curio 1974). In the first case, the value of attacking a prey should decrease as the danger of injury during attack increases, because an animal should rarely jeopardize its current and future reproduction for a small immediate increment in fitness (Clark 1994). The relative costs and benefits of alternative foraging decisions should also vary with: 1) the availability of prey, 2) the dangers associated with subduing prey, 3) environmental conditions, and 4) the energetic state of the predator. Consequently, the impacts of predators on prey should also be dynamic. Only a few field-studies of vertebrate predator-prey interactions have quantified how changes in the foraging constraints of predators influence the behaviour and population dynamics of predators and prey (Werner et al. 1981; Spear 1993; Young 1993; Goss-Custard Ct  al. 1995).  Young (1993) identified several environmental factors which determined the  impact of south polar skuas (Catharacta niaccorinicki) on the reproductive success of Adelie penguins (Pygoscelis adeliae). The ability of skuas to take penguin chicks increased in windy conditions because wind increased their ability to avoid the defensive attacks of adult penguins. Late in the breeding season, penguin chicks also grew too large for skuas to kill, and this placed skuas in an energetic bottleneck at a critical time in their own chicks development. In addition, heavy ice conditions at sea affected the availability of alternative food sources and this affected the value of foraging at the penguin colony for skuas, and the risks skuas were willing to take when attacking penguins. These examples illustrate how seemingly unimportant environmental factors can interact to influence predator foraging behaviour, and consequently, the impact of predators on prey populations.  3 Interactions between changing environmental conditions and predator foraging constraints like those described above, may affect the ability of glaucous gulls (Larus hyperboreus) to prey on the eggs and chicks of colonial nesting thick-billed murres (Uria lomvia). These topics are examined further in the chapters that follow using egg placement experiments, behavioural observations, and computer simulations.  Study sites I studied the predator-prey interaction between glaucous gulls and thick-billed murres breeding on Coats Island, N.W.T. Canada (1990-1992), and in the Upernavik region of north west Greenland (1993). The Coats Island murre colony has expanded since the 1970?s, whereas the Upernavik murre colonies have experienced severe population declines due to a commercial hunt conducted by the local community between 1970 and 1985 (Kampp et al. 1994). The stability of the cliff at the Coats colony permitted safe access with climbing equipment and un-obstructed views of the birds. In addition, 3 factors permitted me to study an avian predator-prey system in unusual detail: 1) the numbers of birds present at the colony (ca. 32000 breeding pairs of murres, 13-16 breeding pairs of glaucous gulls), 2) my close proximity to the birds allowed me to study many predator-prey interactions at close range and in a degree of detail that is rarely possible in the wild, and 3) several of the physical and environmental factors that affected these interactions were easily quantified (e.g. cliff ledge structure, wind speed). A further benefit of the field site was that other recent research on the reproductive ecology of the thick-billed murre at Coats Island (Noble 1990; deForest 1993), provided me with insights into this predator-prey system that I could not have achieved alone.  4 Ecology of the glaucous gull DISTRIBUTION  -  The glaucous gull is the second largest of all gull species. It is a  generalist predator with a circumpolar distribution. In North America, it is widely distributed in arctic regions and breeds along coasts from northern Alaska to Baffin Island, and Labrador. In the Atlantic, it is replaced by the greater black-backed gull (Larus marinus) below Labrador. In the Pacific, it is replaced by the glaucous-winged gull (Larus glaucascens) in the Aleutian Islands and in British Columbia. Glaucous gulls from the eastern Arctic winter in the Maritime regions of Canada, southern Greenland, and rarely on the Great Lakes. Gulls that breed in the western Arctic and Alaska winter along the west coast of North America as far south as northern California. NESTING BEHAVIOUR  -  Glaucous gulls use a variety of nesting habitats. Like many  other Arctic bird species, glaucous gulls select nest sites that are inaccessible to Arctic foxes (Alopex lagopus). They may nest on coastal islands and cliffs (Manning et al. 1956; Gaston et al. 1985), on islands in freshwater lakes near coasts (Martin and Moitoret 1986), and on sandy islets at river mouths (Sage 1974). In the Canadian and Greenland Arctic, glaucous gulls also nest on inaccessible cliffs in association with colonies of black-legged kittiwakes (Rissa brevirostris), thick-billed murres (Uria lomvia), and Iceland gulls (Larus glaucoides). The density of breeding glaucous gulls ranges from single nests spaced kilometers apart over flat tundra, to colonies of more than 100 breeding pairs on small islands or cliffs (Johnson and Herter, 1989). The selection and distribution of glaucous gull nests likely reflects an interaction between limited nest sites that are inaccessible to foxes, and of the availability of foraging opportunities needed for successful reproduction. For example, at Digges Island, Quebec, Canada, all glaucous gulls nest on a cliff that is inaccessible to foxes (Gaston et al. 1985). Some gull nests are scattered within a thick-billed murre colony, and the owners of these nests forage primarily on murre eggs and chicks (Gaston et al., 1985). In contrast, the gulls nesting at a colony of approximately 40 pairs near the upper margin of the murre colony apparently feed at distant shorelines and on the open  5 ocean. These gulls do not maintain feeding areas around their nests, and consequently, their nests are spaced only meters apart within the gull colony (Gaston et al., 1985). A similar dichotomy (i.e. where seabird-feeding specialists maintain territories and generalists nest colonially), apparently occurs among glaucous gulls at most other seabird colonies in the eastern Canadian and Greenland Arctic (Gaston and Nettleship, pers corn., and pers. obs.), and among some other gull species (Spear 1994; Watanuki 1993; Nettleship 1972). DIET DURING THE BREEDING SEASON  -  Glaucous gulls are omnivores, although animal  material predominates in the diet of most individuals. Major categories of food during the breeding season include: 1) marine invertebrates from the intertidal zone, 2) bird eggs and chicks, especially of colonial-nesting waterfowl and seabird species, 3) invertebrates and fish from rivers, 4) carrion, especially items washed up on shore or present on the sea ice, 4) small mammals, especially lemmings where they occur, 5) human refuse at community garbage dumps or fish plants, and 6) food items pirated from other foraging birds (Ingolfsson, 1976; Gaston and Nettleship 1981; Strang 1982; Johnson and Herter 1989; Barry and Barry 1990). One of these food categories may predominate in the diet of some individuals. For example, some glaucous gulls nest within seabird or waterfowl colonies and prey primarily on the eggs and chicks of these other species (Gaston and Nettleship 1981). However, it appears that most glaucous gulls in the Arctic have a more varied diet, and that these specialized gulls form a small portion of the entire breeding population (Barry and Barry 1990).  Glaucous gull ecology at Coats Island NESTING BEHAVIOUR AN]) REPRODUCTIVE TIIvIING  -  Glaucous gulls arrive at Coats  Island during the first and second weeks of May, which is several weeks prior to the arrival of thick-billed murres at the colony. At this time, land-fast ice typically extends for over 50 km from shore and the tundra of the island is largely snow-covered. Snow squalls occur frequently in May and well into early June. Gulls construct their nests out of plant material which they collect from ridges that have been blown free of snow. At Coats Island, gull nests  6 are constructed on cliff ledges and are spaced widely apart (>35 meters between most nests). This nesting distribution reflects the fact that breeding pairs defend feeding territories within the murre colony, and prevent other gulls from establishing nests in these territories by direct attacks. Banding of gulls has shown that breeding pairs at Coats Island are philopatric to both their mates and to specific nesting ledges between years. This nesting distribution is unlike that observed in most other gull species, which typically nest colonially and commute to distant food sources (e.g. Siegel-Causey and Hunt 1981; Sibly and McCleery 1983; Pugesek and Wood 1992; Spear 1993). The number of glaucous gulls that have bred at the Coats Island murre colony since 1986, when researchers began to visit the colony regularly, has ranged from 12 to 16 pairs. A further 3 to 5 non-breeding glaucous gulls are usually present. Thick-billed murres begin to arrive at the cliff sporadically and briefly in early June. The early attendance patterns of murres appears to be determined largely by weather and the distances they must travel to open water. During bad weather, murres often abandon the colony and return to sea until weather conditions improve. In rare years where open water occurs close to shore, murres will return to the colony one to two weeks earlier in the year. The peak of murre egg laying typically falls between the 24th and 26th of June, which coincides with the hatching of most glaucous gull chicks. One factor that influences glaucous gull reproductive success is the weather that coincides with hatching period of gull chicks. Hatching chicks may be susceptible to exposure during wet and windy weather, because brooding adults sometimes stand up off their eggs when hatching is taking place. Once chicks have hatched, however, they are brooded more consistently, and are less vulnerable to the effects of wind and rain. During late June, July and August, glaucous gull chicks remain on cliff nesting ledges. If chicks accidentally fall to lower ledges during this time, they are either killed outright by breeding murres, or are forced by murres to leap to the ocean where they eventually die. Gull chicks fledge during the third and fourth weeks of August, so that most gull chicks have left the cliff prior to the peak of murre chick departures. Gull chicks remain in the area  7 around the colony and are sometimes attended by their parents at this time. Thus, breeding glaucous gulls spend approximately four months of the year at the Coats Island colony. Although very little is known about their migration pathways, it is likely that the glaucous gulls of Coats Island spend the winter in southern Greenland or Newfoundland, Canada. FORAGING OPPORTUNII1ES DURING BREEDING  -  When gulls first arrive at Coats island  in early May, foraging opportunities may be limited. They have poor access to the open ocean, and murres are absent from the colony. Examination of samples of regurgitated pellets (n=32) during May and early June revealed that gulls scavenge seal species (F. phocidae) and walrus (Odobenus rosmarus) carcasses on the sea ice. Coats Island supports a resident caribou herd (Rangfer tarundus) which experiences mass die-offs on a five to eight year cycle. The carcasses from these winter die-offs, however, are mostly consumed by Arctic foxes prior to the arrival of breeding glaucous gulls. An exception to this occurred in 1991, when two caribou fell to their deaths at the colony and were covered by drifting snow and glaucous gulls scavenged these carcasses for several weeks in May and June. In June, Arctic foxes provide gulls with scavenging opportunities on the sea ice below the colony. Murres often fall to the ice during intra-specific fights and when departing from the colony in calm winds. Murres are rarely killed by the fall, but remain on the ice and are often unable to take flight. During calm wind conditions, it was common to see 10 to 20 murres stranded on the ice below the colony. Arctic foxes often killed these murres in quick succession, so that several carcasses remained to be scavenged by glaucous gulls. Following the break-up of the sea ice in late June, murres are no longer accessible to foxes and this food source no longer exists for gulls. Once murres begin to lay in late June, glaucous gulls concentrate much of their foraging effort on stealing murre eggs. Observations of predation events, of food items provided to chicks, and the analysis of pellets regurgitated on nesting ledges (GG, unpublished data),  8 indicated that murre eggs and chicks make up >85% of gull diet in July and August. This is the period of the breeding season that is the focus of this thesis. Murre eggs and chicks are a highly profitable food for glaucous gulls for the following reasons. First, murre colonies provide gulls with a dependable and predictable energy source for 2 and one half months during the breeding season. Second, adult gulls can almost forage and guard their chicks simultaneously, because they can hunt within feeding territories near their nest. As a result, glaucous gull chicks are sometimes left alone at the nest at a very early age while both parents forage in the vicinity. This contrasts with the situation in most colonialnesting gull species, where one member of a pair must be present at the nest to defend their chicks against cannibalistic conspecifics (Pierotti and Annett 1991 a). A further benefit to gulls breeding in association with murres is that glaucous gulls can kill and easily ingest murre chicks throughout the breeding season. In some other avian predator-prey systems, prey can grow too large for the predator to kill them (e.g. skuas and adelie penguin chicks, Young 1994; Glaucous gulls preying on snow goose goslings, Keith Hobson, C.W.S. personal communication.). In summary, the diet of breeding glaucous gulls at Coats island is apparently less diverse than the diets of glaucous gulls nesting elsewhere in the Arctic, and also less diverse than the diets of most other large gull species nesting in temperature regions. Glaucous gulls in the western Arctic have a diverse diet which can include rodents, intertidal organisms, scavenged carcasses, mollusks, fish, and waterfowl eggs (see references above). Gulls in more temperate regions have a similarly diverse diet and may supplement natural prey with human refuse during the breeding season (Siegel-Causey and Hunt 1981; Sibly and McCleery 1985; Pierotti and Annett 1986; Spear 1993). Coats Island supports no rodent species or Inuit communities. The shores near the murre colony at Coats Island also support few intertidal organisms, apparently due to scouring by sea ice. As a result, glaucous gulls that breed at the Coats Island murre colony feed primarily on murre eggs and chicks, fish at sea, and rarely on scavenged carcasses. Thus, the foraging opportunities for breeding gulls at Coats Island are largely  9 determined by weather and ice conditions around the colony, and the reproductive timing of murres.  Aims of this thesis  My objectives were to examine the foraging behaviour of glaucous gulls preying on the eggs and chicks of thick-billed murres, and to determine their impacts on murre reproductive success. Specifically, I studied how environmental factors constrain the ability of glaucous gulls to attack murres, and if these constraints varied through time, in space, or between individuals. I also considered the impact of gulls on the reproductive success and population dynamics of murres. In chapter 2, I describe an experiment in which I placed murre eggs in the colony and monitored their fate in relation to cliff ledge characteristics, murre nesting density, gull attack mode, and wind conditions. In chapter 3, I examine the hypothesis that gull foraging activity and predation rates are positively correlated with windy conditions. In chapter 4, I present a detailed energy budget of gull foraging activities and integrate this with field data of gull foraging behaviour using a dynamic model. I use this model to test the hypothesis that danger of injury during attack is the main factor influencing the selection of foraging mode by gulls. Chapters 3 and 4 generated the prediction that decreased murre nesting densities decrease the risk of injury for gulls, thereby enhancing their foraging efficiency. Consequently, the impact of glaucous gulls on the reproductive success of thick-billed murres should increase following any perturbation that decreases murre nesting densities. In chapter 5, I test a prediction of this hypothesis, that glaucous gull predation should be greater at a heavily-harvested and declining murre colony (Upernavik in northwest Greenland), than at Coats Island, N.W.T., Canada. In chapter 6, I briefly summarize the thesis and identify the need for further research on mortality risks taken by top predators.  10  CHAPTER 2 EFFECTS OF MURRE NEST DENSITY, CLIFF LEDGE WIDTH, AND WIND ON PREDATION BY GULLS  Predation strongly influences the reproductive behaviour of colonial-breeding birds (Wittenberger and Hunt 1985; Burger and Gochfeld, 1994).  Nesting in groups may provide  benefits through increased vigilance, predator swamping, and group defence (Burger and Gochfeld, 1994). Among seabirds, the effectiveness of predator mobbing may increase with group size and nesting density as neighbours defend nest sites collectively (Birkhead 1977; Siegel-Causey and Hunt 1981; Spear and Andersson 1989; Spear 1993). It may also vary over the course of the breeding season, being most effective when most birds in a group have young (Andersson et al. 1980). Colony structure and topography may also influence predator foraging efficiency because nest site characteristics, such as burrow depth, cliff ledge width, and ledge slope vary within seabird colonies and can affect the accessibility of nest sites to avian predators (Nettleship 1972), and the ability of prey to defend themselves (Siegel-Causey and Hunt 1981; Young 1994). Therefore, the impact of avian predation is a function of how predator foraging constraints vary in space and time, and how predators overcome these constraints. Glaucous gulls, Larus hyperboreus, are generalist predators that often breed in association with waterfowl or seabird colonies (Portenko 1989; Johnson and Herter 1989; Barry and Barry 1989). They commonly prey on thick-billed murre, Uria lomvia, eggs and chicks at colonies in the Arctic (Gaston and Nettleship 1981). Thick-billed murres breed in dense colonies on exposed cliff ledges, and the principle habitat features affecting their reproduction include the slope and width of cliff ledges, the numbers of adjacent rock walls, and the number of breeding neighbours (Gaston and Nettleship 1981). Murres that nest on the interior of dense groups on broad cliff ledges experience the highest reproductive success  11 (Gaston and Nettleship 1981; Birkhead et al. 1985; Birkhead and Nettleship 1986; deForest 1993), perhaps because they are most successful in avoiding gull predation. In this chapter, I identify some of the foraging constraints of glaucous gulls and examine whether they vary spatially or temporally. I also explore how the dynamics of gull foraging constraints affect the vulnerability of murre nest types. I placed eggs experimentally in the murre colony and monitored their fate in relation to cliff ledge width, murre nesting density, timing of murre egg-laying, murre defence, gull foraging mode, and wind conditions. Based upon previous observations of gull foraging, I predicted that: 1) exposed eggs placed in high density nesting areas would survive longer than those in low density areas due to collective defence by murres, 2) that eggs placed on narrow ledges would survive significantly longer than those on broad ledges because the large body size of glaucous gulls, 1.8-2.1 kg, makes it difficult for them to forage on narrow ledges, and 3) that eggs placed early in the breeding season would survive for a shorter period than eggs placed following the peak in murre laying.  METHODS Study Area and Species The study was conducted at a thick-billed murre colony on Coats Island, Northwest Territories, Canada (62°30’N, 83°OOW) in 1990, 1991, and 1992. Thick-billed murres bred on a vertical cliff up to 65 meters above the sea. Since 1984, 1500-2500 murre chicks have been banded each year with metal and colour bands, establishing a sample of birds of known age. Glaucous gulls nested on ledges within the murre colony or occasionally on turf immediately above the murres. Glaucous gulls were the primary predators at the Coats Island colony, and murre eggs and chicks made up >85% of gull diet for both adults and chicks. Prior to the onset of laying by murres, gulls fed on the carcasses of murre, ringed seal, Phoca hispida, and caribou, Rangifer tarundus, present on the sea ice below the colony cliffs.  12 Egg placement experiments In 1990, 1991, and 1992 I placed large chicken eggs painted to mimic murre eggs in the murre colony in several sites and monitored their survival in relation to time of day, gull attack technique, murre defence, murre reproductive synchrony, and weather conditions. In preliminary studies, experimental eggs were taken readily by gulls and occasionally incubated by murres. In 1991, I also used genuine murre eggs taken as part of a study examining thickbilled murre reproductive success (deForest 1993). In all studies, eggs were placed by climbing down into the colony from above using fixed ropes. Murres often left nesting ledges in response to the disturbance caused during egg placement, but usually returned within 5 minutes. Climbing equipment allowed me to move slowly and methodically within the colony, and I was able to avoid significant egg dislodgment.  Further, I remained above study plots and deterred gulls from taking exposed  eggs until murres had returned to their nest sites. I began to record the survival time of experimental eggs after I left the cliff face and entered an observation blind. The survival of experimental eggs was monitored continuously for the first four hours after placement, and checked hourly thereafter. Eggs that survived beyond twenty-four hours, were then checked every three hours. I terminated the experiment after 72 hours, and assumed that surviving eggs were either invisible or inaccessible to gulls. In 1990 and 1991, I tested the effects of nesting density and ledge width on the predation of experimental murre eggs. Eggs were placed in four situations: 1) broad ledges with high murre nesting density; 2) broad ledges with low nesting density; 3) narrow ledges with high density; and 4) narrow ledges with low density. High density ledges had >80% of their area occupied by breeding murres, whereas low density ledges had <40% of their area occupied. The nesting density of ledges was assessed by eye using a 15-45 power spotting scope and with the aid of photographs of nesting ledges. Broad ledges supported more than one row of breeding sites, whereas narrow ledges supported only one row.  13 In 1991, I tested the effects of wind speed on the accessibility of narrow ledges to gulls. I conducted the experiment following the peak of murre laying at which time >80% of murres had eggs. Two eggs were placed on each of fourteen narrow, low-density murre nest sites. One egg was placed under windy conditions (>15 km/h), while the other was placed on the same site under calm conditions (<5 km/h). I then compared the survival times of the eggs under the two regimes. Wind speed categories were based upon a 15 km/h wind threshold above which glaucous gulls could glide without flapping their wings. This threshold was determined from behavioural observations in the field and from data on flight dynamics of large gulls (Pennycuick 1987). Wind speed was measured to ± 1 km/h using a Weather-pro Digitar anemometer mounted 1.5 m from the cliff face. If the wind conditions changed during the first four hours of the experiment (e.g., from calm to windy), the trial was abandoned. I predicted that eggs placed under calm conditions would survive longer than those placed under windy conditions due to the increased maneuverability of gulls in strong winds. In 1992, I used thick-billed murre eggs to test the effect of laying synchrony on egg predation. For these trials, eggs were placed only when wind speeds were >15 km/hr. I placed eggs on broad (N=6) and narrow (N=6) ledges about a week before the peak of egg laying (< 17% of pairs with eggs). These placements were repeated on the same sites 12 days later at which time >82% of the pairs had eggs. Survival times were then compared. Laying synchrony was monitored as part of a project examining the reproductive biology of thickbilled murres (deForest 1993). I predicted that eggs placed at the beginning of the laying period would survive for a shorter time, because birds not yet incubating their own eggs should not contribute to group defence during gull attack.  Behavioural Observations After egg placement, I observed gull foraging activity from blinds and recorded the attack methods used, classifying them as shown in Table 2.1. In addition, I recorded whether eggs were removed successfully or dropped during the attempt. I also recorded the response of the  14 murres during attacks by gulls (Table 2.1). When more than one murre responded to an attack, I often recorded several types of behaviour simultaneously.  Statistical Analysis The survival of eggs relative to ledge width and murre nesting density was compared using the Kolmogorov-Smirnov goodness of fit test. The survival of eggs placed on the same nest sites under two different conditions of both wind speed and numbers of neighbors with eggs were compared using the Wilcoxon matched-pairs test. The defensive responses of individual murres nesting on the same ledge could not be considered independent. In fact, it is likely that the response of an individual murre to a gull attack depends on the behaviour of its neighbours (Birkhead 1977). For each gull attack, I randomly selected the response of one individual next to the egg for analysis of the effects of ledge width on murre defence behaviour. For my analysis I used the following categories of murre defensive response (see Table 2.1-a): 1) no defence = flush or no response, 2) moderate defence  =  orient, and 3) strong defence = lunge. Finally, I used log-likelihood ratio (G) tests to  examine differences in weak, moderate, and strong murre defence behaviour relative to ledge width and laying date. I also compared the attack techniques of gulls using a G-test, with the William’s correction for continuity applied because of small sample sizes (Sokal and Rohlf 1981).  15  Table 2.1. a) Attack modes of gulls, and b) murre response to gull attack. Description  Behaviour  Gull stands on murre nesting ledge, head lowered; lunges into nesting group of murres to take egg Aerial lunge Gull flying along colony cliff drops into nesting murres to steal egg Hover harass Gull flying along colony cliff stops to hover next to murre nest sites; gull then maneuvers into nest site to steal egg without landing  a) Stand lunge  b) No response Orient  Murres on nesting ledge do not alter behaviour during gull attack Murres elongate their necks and direct their beaks towards attacking gull  Flush Lunge  Murres suddenly fly from nesting ledge avoiding contact with gull Murre runs towards attacking gull standing on ledge; in response to aerial attack, murre drops from ledge and attempts to strike hovering gull  16 RESULTS Nesting Density Of the 77 experimental eggs that disappeared (n=92), 48 (66%) were taken within the first four hours and only 15 of a total of 92 eggs (16.3%) survived for 72 hours. I saw gulls take 58 (75.3%) of the 77 disappearing eggs. As predicted, eggs placed on ledges with high nesting densities remained for significantly longer than eggs placed under low-density conditions regardless of ledge width (Fig. 2.1). Group defence by murres was important in preventing gulls from reaching exposed eggs because gulls tried to avoid strikes from nearby murres. On ledges with high nesting densities, murres collectively defended exposed eggs by lunging at or striking gulls as gulls tried repeatedly, and often unsuccessfully, to reach exposed eggs. On ledges with low nesting densities, gulls could walk among incubating birds while taking eggs. As predicted, gulls abandoned foraging attempts more frequently under high nesting density conditions (11 of 25 of high density attempts, 9 of 37 low density attempts; Gadj4.37,  dfl, P<O.05).  Experimental eggs may also have been hidden under incubating birds in high nesting density conditions. I considered that eggs were concealed when I could not see them from several different vantage points on the cliff, and gulls did not investigate them when foraging in their vicinity. Of the 15 eggs that survived to the end of the observation period (3 days), 5 (33%) were concealed by neighbouring murres under high density nesting conditions.  Ledge Width  Although nearly twice the number of eggs disappeared from broad ledges within the first eight hours (Fig. 2.2), I found no statistically significant differences in the survival time of eggs placed on narrow vs. broad ledges in 1990 (Fig. 2.2), contradicting my prediction. Murre responses to gull attack, however, did vary significantly with ledge width.  Murres on  broad ledges responded more often to gull attacks with orient and lunge behaviours (Table 2.1;  17  Figure 2.1 Survival of exposed murre eggs in relation to thick-billed murre nesting densities (low murre nesting density black; high murre nesting density white). Kolmorgorov -  -  Smirnov two-sample test, P<0.001). Wind conditions >10 km/h.  100  80  C Ci)  60  -  (15 C,)  c,)  )  w  40  20  0 500  1000  1500  2000  Survival time (mm)  2500  >3000  18  Figure 2.2 Survival of exposed murre eggs in relation to cliff ledge width (broad ledge  -  black; narrow ledge -white). Kolmorgorov-Smirnov two sample test, P=0.483. Wind conditions> 10 km/h.  100  80 C  ci) -  Ce  60  Cl) 40  20  0  I  I  I  H 1000  1500  -H 2000  Time (mm)  2500  >  3000  19  Table 2.2 Murre responses to gull attacks in relation to cliff ledge width. Each observation relates to a randomly selected murre situated next to the experimental egg.  Ledge width Narrow  Broad  11  3  Flush  6  5  Orient  14  17  Lunge  2  9  Murre response  No response  20 G=8.41 dJ2, P<0.025), and were more successful in repelling gulls (15 of 34 cases on broad vs. 9 of 43 cases on narrow ledges;  53 , 6 . 4 Gadj=  dfl, P<0.05). Typically, murres on narrow  ledges only contributed to the defence of immediately adjacent nest sites even at high densities. Murres on narrow ledges also had difficulty turning on their sites to defend against attacking gulls without dislodging their own eggs. On broad ledges, birds moved tightly together and turned to face gulls that were attacking on foot. Murres in the interior of groups on broad ledges often extended their heads over the birds situated on the edge and attempted to strike advancing gulls. In this way, several tiers of murres contributed to the defence of neighbours and of exposed eggs on broad ledges. Some individual murres on broad ledges also walked between the gull and the group, and then lunged at the gull, forcing it from the ledge. Observations of banded murres revealed that these murres were often the mates of incubating birds (5 of 12 cases involving banded birds). However non-breeders ( 3 of 12) also contributed to defence. Gull attack behaviour also varied with ledge width (G=23.22, dfr2, P<0.001). Gulls typically made aerial attacks on narrow ledges, wheras they frequently landed on broad ledges to make their attacks (Table 2.3). Aerial attacks were so rapid that gulls often failed to grip eggs firmly before flying off. Consequently, gulls dropped eggs taken from narrow ledges 3 l, df1, P<0.07). 7 . 3 times as often (13 of 39) as eggs from broad ledges (2 of 19; Gadj While gulls were attacking on broad ledges, eggs sometimes rolled out onto unoccupied areas of the ledge beyond the reach of defending murres. This allowed gulls to pick up eggs more slowly, to make several attempts if necessary, and even in some cases, to ingest eggs whole before leaving the ledge.  Wind Speed In 1990, I did not find a significant difference in the survival of eggs placed on narrow and broad ledges. I therefore performed egg placements under windy conditions (>15 km/hour) and found that gulls could reach narrow ledges using gliding flight. In 1991, I found  21  Table 2.3 Gull attack techniques on eggs placed experimentally in relation to cliff ledge width.  Ledge width Attack technique  Narrow  Broad  Stand Lunge  4  18  Hover Harass  27  6  Aerial lunge  12  10  22 that eggs placed under calm conditions on narrow, low nesting-density ledges survived significantly longer than those placed on the same sites under windy conditions (Wilcoxon’s signed-ranks test, paired comparisons, N=l4, Z2.88, P<0.00l). When it was windy, nearly 90% of the eggs were taken within the first two hours, almost twice the percentage taken under calm conditions during that period (Fig. 2.3).  Vulnerability relative to timing oflaying Eggs placed during the peak of murre egg laying survived significantly longer than those placed on the same sites at the beginning of the laying period (Fig. 2.4; Wilcoxon’s signed ranks test, paired comparisons, N=12, Z=2.81, P<0.025). All of the eggs were placed under moderate wind conditions. Early in the laying period non-incubating birds often flushed when attacked leaving experimental eggs exposed and incubating birds vulnerable to attack (Table 2.4), although these differences in murre behaviour were not statistically significant in relation to timing of laying  5 , 5 . 2 (Gadj=  dJ2, P< 0.5, one-tailed). However, there was insufficient  power to reject the null hypothesis convincingly (1 -/3 = 0.381). The idea that murres were more aggressive in their defence against gulls once most individuals were on eggs is supported by the fact that murres repelled 3 times as many attacks following the peak in murre laying (9 of 23, or 39% of gull attacks post peak; 2 of 23, or 13% of attacks prior to the peak; 6 , 7 . 3 Gadj  df=1, P<0.03, one-tailed).  23  Figure  2.3 Survival of exposed murre eggs in relation to wind (windy,> 15km/h, black;  calm, <5km/h, white). Wilcoxon’s signed ranks test, paired comparisons, n=14, Z=2.88, P<o.o1.  100  80  C  ci)  60  cts •1C,)  C) C)  w  40  20  jEl 1  300  400  Survival time (mm)  500  >  600  24  Figure 2.4 Survival of exposed murre eggs in relation to the timing of murre laying (early black; late white). Wilcoxons signed ranks test, paired comparisons, n=12, Z=2.81. -  P<0.01. Wind conditions> 10 km/h.  100  80  C  60  -  (‘5  .4-  CO  3) C)  uJ  20  0 100  200  300  400  Time (mm)  500  >  600  25  Table 2.4 Murre responses during gull attacks in relation to timing of murre egg laying. Each observation is based upon one randomly selected murre situated next to the experimental egg.  Timing relative to laying peak Prior  Post  None  2  3  Flush  9  Orient  7  Lunge  2  5 17 4  Murre response  26 DISCUSSION Constraints on gullforaging efficiency Many colonial seabirds exhibit greater reproductive success at high nesting densities (Burger and Gochfeld 1994). Predator swamping, increased vigilance, and increased communal defence may explain this phenomenon (Wittenberger and Hunt 1985; Burger and Gochfeld 1994). Birkhead (1977) and Spear (1993) found that common murres which nested on the periphery of groups were more vulnerable to gull attack and egg loss. I found that the greater survival of thick-billed murre eggs at high nesting-densities was due largely to the ability of murres in dense groups to strike gulls during attack. I found that gulls typically stood on the edge of nesting groups and harassed the outermost birds even when attempting to steal eggs from the center of large groups. Gulls often abandoned these attempts after being struck on the face and neck by the beaks of incubating birds. In contrast, gulls that foraged on ledges with low nesting densities walked between brooding murres and often took murre eggs without being struck by defending murres. Siegel-Causey and Hunt (1981) found that glaucous-winged gulls, Larus glaucescens, preferred to attack nests on level ground when foraging in a colony of pelagic, Phalacrocorax pelagicus, and double-crested cormorants, P. auritus. Gulls were more likely to get struck by defending cormorants when they foraged on steep terrain. In this study, colony topography and cliff ledge width also influenced predation on exposed eggs. When brooding, murres typically faced into the cliff and away from most gull attacks. Murre defence against gulls was less effective on narrow ledges, apparently because murres had difficulty turning to face attacking gulls without dislodging their own eggs. Consequently, murres on narrow ledges could defend only their immediate neighbours, and most murres on narrow ledges defended experimental eggs weakly. In contrast, most murres on broad ledges turned to face gulls attacking on foot. Birds nesting in the interior of large groups typically extended their heads over the birds situated on the edge and contributed to group defence. Finally, more non-  27 breeding murres were present on broad than on narrow ledges (Noble 1990), and they sometimes defended against attacking gulls. Spear and Anderson (1989) concluded that wind affected the success of common ravens, Corvus corax, attacking colonial-nesting yellow-footed gulls, Larus livens. They noted that ravens attacked only during 25-40 km/hr winds, and suggested that increased maneuverability of ravens under these conditions enhanced their ability to avoid defensive mobbing by gulls (Spear and Anderson 1989). Similarly, south polar skuas (Catharacta maccormicki) were more successful under moderate winds when stealing the chicks of Adelie penguins (Pygoscelis adeliae), apparently because wind increased their ability to out-maneuver defending penguins (Young 1993). In my study, wind influenced the ability of glaucous gulls to reach eggs on narrow ledges and avoid contact with murre during attack. Gulls reached weaklydefended eggs on narrow ledges when wind conditions enabled them to maneuver over to nest sites. Gulls apparently faced lower risks of getting struck by defending murres when attacking nest sites on narrow ledges under windy conditions, and consequently, they were able to remove eggs more readily from these sites. Surprisingly, wind effects have rarely been discussed in previous studies of avian predation within seabird colonies (Spear and Andersson 1989; Young 1994; Thiel and Sommer, 1994). In several studies, gulls and skuas, Cartharacta sp., foraged primarily on foot in low nesting-density areas on broad cliff ledges or on level ground (Birkhead 1977; Furness 1981; Watanuki 1982; Watanuki 1983; Spear 1993).  In contrast, the thick-billed  murre colony that I studied is currently expanding so most broad ledges were densely occupied by murres (Gaston et al. 1993). Thus, the aerial foraging of gulls recorded in this study reflected the lack of broad ledges with low nesting densities where gulls could forage on foot, and that wind enabled gulls to reach narrow ledges where murre defence was less effective.  28 Consequences of gull predation for thick-billed murres The ability of glaucous gulls to take experimental eggs was greatly reduced by group defence of murres nesting at high densities. Eggs on the edge of a group were taken much more quickly than those in the interior. Despite this generality, several other notable factors influenced the effectiveness of murre group defence. At Coats Island, communal defence by murres also depended on laying synchrony. Eggs placed before the peak of murre egg laying were quickly taken even in high-density areas. Non-incubating murres often bolted from ledges when attacked, leaving experimental eggs vulnerable to gulls. Following the peak of laying, gulls were more likely to be repelled by murres when attempting to take eggs. These results support the contention that individuals without young should abandon the group and avoid contact with the predator (Anderson et al. 1980). I conclude that the first murre eggs laid on a nesting ledge experience greater risk of predation because group defence is not firmly established early in the breeding season. Gulls used windy conditions to reach narrow ledges and avoid contact with murres during attack. However, for birds nesting in the center of high-density groups, wind had no effect because these sites were well defended regardless of wind conditions. Thus, the vulnerability of murre nest sites to gulls is partly determined by group defence, and partly by the position of nest sites in relation to prevailing winds. Based upon these findings, I rank the vulnerability of thick-billed murre nest sites at Coats Island from high to low as follows: 1) low density edge sites on broad ledges; 2) low density sites on narrow ledges; 3) high density sites on narrow ledges; and 4) high density sites on broad ledges. I conclude that low density sites on broad ledges are most vulnerable because gulls could reach these sites on foot regardless of wind conditions. Nest sites on narrow ledges are typically inaccessible during calm wind conditions (<15 km/hour). However, wind speeds often exceed 15 km/h for several hours on most days at the Coats Island colony (deForest 1993). Finally, gulls have difficulty reaching sites on high density broad ledges due to group defence, regardless of wind conditions. These findings provide a  29 mechanism to explain the results of Birkhead and Nettleship (1986) and of deForest (1993) who found that thick-billed murre reproductive success was lowest on broad, low density ledges, intermediate on narrow ledges, and greatest on broad, high-density ledges.  30  CHAPTER 3 WiND AND PREY NEST SITES AS FORAGING CONSTRAINTS ON AN AVIAN PREDATOR, THE GLAUCOUS GULL  Predation is a major force influencing population dynamics, community structure, and prey behaviour (Zaret 1980; Taylor 1984; Sih 1989). The influence of predators on their prey is often a function of changes in the environment (e.g. diet switching in response to changes in prey availability; reviewed in Sinclair 1989; Newton 1993).  Consequently, it is of interest to  quantify how predators respond to changes in their foraging constraints, and how these dynamics influence prey populations (Werner et al. 1981; Erlinger, 1989; Cooper 1990; Mills and Shenk 1992; Spear 1993; Goss-Custard et al. 1995). It has been useful to examine predator foraging behaviour from an economic perspective (Stephens and Krebs 1986). For example, the most appropriate foraging strategy for a predator is to maximize the trade-off between energetic reward and risk of injury while foraging, rather than to maximize net energy gain alone (Stein 1977; Pettifor 1990). Thus, the value of attacking prey should decrease as the danger of injury during attack increases for the predator. The trade-off between energetic gain and risk of injury may be particularly important among avian predators which forage within seabird colonies, and who face the group antipredator defences of their prey. The risk of injury while foraging, and the ability of avian predators to overcome these dangers, may be influenced by colony topography, changes in prey nesting densities, and weather conditions (ch. 2 and references therein). Glaucous gulls are common predators of thick-billed murre eggs and chicks in the Arctic. Thick-billed murres breed in dense colonies on exposed cliff ledges, and they defend themselves collectively against gull attack (Gaston and Nettleship 1981). In chapter 2, I showed that glaucous gulls are constrained by narrow cliff ledge width, murre nesting-density, and murre defence when they attack exposed murre eggs. Windy conditions enhance the ability of gulls to overcome these foraging constraints (ch. 2). However, these conclusions are  31 limited to the conditions simulated by the egg placement experiments, because murres likely defend their own eggs differently than experimental eggs. In this chapter, I examine the constraints of gulls foraging on naturally occurring murre eggs and chicks using multivariate statistical models. I also examine the affects of wind in greater detail to determine if wind influences the choice of tactics by gulls and their foraging success. I expected that foraging activity of gulls and predation rates would be positively correlated with windy conditions. Finally, I explore how wind speed and gull foraging behaviour interact to affect the vulnerability of murre nest types using a model which integrates data on predation rates and seasonal wind conditions.  METHODS Study area and species This study was conducted at a thick-billed murre colony on the north eastern tip of Coats Island, Northwest Territories, Canada (62°30’N, 83°OOW) during 1990-92. For further details, see chapters 1 and 2. There was considerable variation in the types nesting ledges and in the density of breeding murres within the colony. I classified 5 nest site characteristics: 1) broad ledge sites high nesting-densities, 2) broad ledge sites at low densities, 3) narrow ledge sites with high densities, 4) narrow ledge sites in low densities, and 5) crevice sites. I defined these site characteristics following Gaston and Nettleship (1981): 1) broad ledges could support two or more rows of breeding birds, whereas narrow ledges supported only one row, 2) high density sites had 3 neighbours on broad ledges and 2 neighbours on narrow ledges. Crevice sites were located under rock overhangs, in crevices, or within rock piles. The proportion of the types was determined by photographing study plots from the cliff at a distance of approximately 20-30 meters. Murres were counted from 15x25 cm black and white prints. The number of breeding pairs was estimated by multiplying the total number of birds present on the cliff by a correction factor of 0.75 (see Nettleship 1976, for further details).  32  Behavioural observations Gull foraging behaviour was monitored from blinds on the cliff face. Study plots extended  Ca.  40 meters from the base of the blinds, and from the sea to the cliff top. Gulls  appeared unaffected by my presence once I was inside a blind. Aerial search activity of gulls was monitored by recording the number of ffight patrols made by gulls over the study plots during half-hour time intervals. Gulls flying close to the cliff face with their head directed towards brooding/incubating murres were considered to be patrolling. This distinct head posture made foraging patrols easily distinguishable from other flight behaviours (e.g. travel to and from the nest). The number of attacks made during each 30 mm. observation period was monitored. I considered that an attack had occurred if a gull made an aggressive advance towards brooding murres either on foot or from the air.  For each gull attack, I recorded the attack behaviour  (aerial or pedal), nest site characteristics of the murres attacked (cliff ledge width and nesting density), murre defensive response (do nothing, flush from ledge avoiding gull, oriented beak towards gull, lunge at gull), and outcome (food item taken or not). Attack and patrol rates were monitored in relation to date, time of day, wind conditions, visibility, and the number of murres present on the study plots. Murre numbers on study plots included both breeders and non-breeders. Wind was monitored with a Digitar anemometer mounted 1.5 from the cliff. Visibility was recorded as clear (no fog), light fog (40m < visibility  <  80 m), and dense fog (visibility <40m). Because visibility, wind conditions, and  murre attendance varied on a fine time scale, I chose 30 minutes as the duration of behavioural observation intervals. I examined the vulnerability of gulls to injury in two ways: first, I videotaped gull attacks; second, I used a gull model made of Styrofoam and plastered paper. The gull model was introduced into brooding murres from the edge of nesting groups using an extendible 4 cm diameter pole to mimic natural attacks. With both methods, the location where murres struck  33 the heads of gulls, and the source of the defensive strikes (i.e. the individual being attacked or its immediate neighbours) was recorded. The influence of wind on aerial maneuverability was examined by timing the duration of gull attack hovers and foraging patrols in relation to wind conditions on the cliff face. A hover was defined as a gull trying to maintain its position next to a murre nest site during aerial attack. Patrols were timed with a digital stopwatch as birds passed over the study plots through a defined field of view (i.e. a 50 m x 40 m area of cliff). Patrols in which gulls made attacks were not included in the analysis of patrol durations.  Gull gliding-flight dynamics I caught nine gulls, either on nesting ledges or at bait stations on the sea ice, by using padded leg-hold traps. I measured the body mass, wing length, and wing area of each bird, following the procedures outlined by Pennycuick (1989). I used these morphological measurements in Pennycuick’s gliding-flight model (Pennycuick 1989) to estimate the minimum air velocities at which glaucous gulls could glide.  Effects of gull predation on murre reproductive success Previous experimental work suggested that gull predation was influenced by the width of murre nesting ledges, murre nesting density, and wind conditions (ch. 2 and references therein). Thus, I estimated the proportion of murre eggs and chicks lost to gulls annually as follows:  Ni=YZP(Tj*T)  (1)  100 1 is the proportion of eggs that were originally laid which were taken from type i nest where N sites (e.g. broad ledge, high murre nesting-density); T is the total number of daylight foraging hours available to gulls in a breeding season at Coats Island (i.e. from the onset of murre egg-  34 laying to murre chick departure); T is the proportion of T hours at wind speedj; and P  is  the predation rate (eggs taken! 1000 nest sites! hour) from nests of type i at wind speedj.  Statistical analysis  I used General Linear Modeling (SYSTAT, 1989) to explore factors affecting aerial search activity, gull attack rates, and predation rates. For each model, condition indices and tolerance diagnostics were examined to identify co-linearity among the variables (Systat 1989; Kleinbaum et al. 1988). If severe co-linearity existed between two variables, models were re run and the variables were included in separate models. In cases where several variables were examined together, I did not conduct full factorial analyses. Instead, I included only a subset of possible interactions which were selected after screening models and examining interaction plots (JMP software, SAS Institute), and from my previous knowledge of the system (ch. 2). Rates of gull attack and predation in relation to murre nest site characteristics were expressed as attacks! half hour! 1000 nest sites. I applied arcsine square-root transformations on rate data of search activity, attack frequency, and predation prior to analyses (Sokal and Rohlf 1981). I used logistic regression analysis to examine factors influencing gull attack success, and the factors affecting the probability that a gull was struck by a murre during an attack, because both were binary variables. To test for the significance of the independent variable (or variables) I used the likelihood ratio statistic (Kleinbaum et al. 1988).  If year had a  significant influence on pooled data, models were derived for each year separately. Some of the behavioural data was collected during consecutive half hours of observation. To test if these data were independent, I conducted a time series analysis (Systat 1989) and found that aerial search activity was indeed strongly auto-correlated for up to 2 and one half hours. I therefore analyzed a subset of the original data in which one 30 minute period was extracted from each 21!2 observation period. For the analysis which examined factors affecting attack success, each attack was considered to be an independent event. Although I was sampling gulls repeatedly, I was also studying all members of the gull population at Coats  35 Island roughly equally. Thus, the variation in the ANOVA is actually the population-wide variation over the course of the summer, rather than the variation of a limited sample. Following the above analyses, I constructed a path diagram to illustrate how environmental factors interacted with gull predation rates. The strengths of these influences were estimated by the standardized coefficients generated from the general linear models. To permit comparisons between factors analyzed with general linear models, ANCOVA, and logistic models, I re-ran the ANCOVAS and logistic analyses using multiple linear regression specifically for the variables included in the path diagram.  36 RESULTS Colony structure and environment There was considerable variation in the structure of cliff ledges and the density of nesting murres within the Coats Island colony. Of the murres nesting on the study plots, about half nested on broad ledges in high-density groups (Mean  =  47% ± 2.3 SE; n  =  5 murre count  plots). Approximately 25.0% (± 1.1) and 8.1% (± 0.78) of breeding pairs nested on narrow ledges under high and low nesting densities respectively. A further 17.7% (±1.5) nested on broad ledges under low nesting-density conditions. These included birds nesting alone or on the edge of large groups. A further 5% (±1.2) of murres nested in crevices or caves. The last proportion may be too low because these sites were difficult to count. Winds were frequently >40 1cm/h in 1990, and rarely exceeded 30 km/h in 1991 and 1992. Significantly stronger winds occurred in 1990 than in 1990-9 1 (90-91,t= 4.986, df=44, P<0.00l; 1990-92: t=5.34, df= 44, P= 0.001), however wind speeds in 1991 and 1992 were similar  (t  =0.973, df =97, P=0.33). As a result, most of my behavioural observations were  conducted under calm (<10 km/h) or moderate (10-40 kmlh)wind conditions in 1991 and 1992 (Fig 3.1). Extended calm periods (>3 days at <10 km/h) occurred each summer, and were typically accompanied by warm temperatures (15-25°C).  Gull search activity Aerial search activity was reduced under calm wind conditions in all years (Fig. 3.2, Table 3.1, a-c). Date had a significant influence on search activity in all years, and there was a statistically significant interaction between date and wind conditions in 1990 (Table 3.1, a-c). This reflected daily fluctuations in wind speed.  37 Figure 3.1. Wind conditions in relation to date at Coats Island. 100  1990 80  60  40  20  0 10 0  -c 2  60  V 0) 0)  40  30  20  40  50  90  80  70  60  1991  Co  V  20  0 10  30  20  40  50  70  60  80  90  60  1992 40  -  20.i\ / L I  0  60  20  Date (June 1  Day 1)  —  I  70  —  I  I  80  90  38  Figure 3.2. Examples of glaucous gull aerial search activity in relation to wind conditions and time of day. Each figure represents three days of gull foraging activity. Solid horizontal bars within each figure represent wind conditions above 10 km/h; open horizontal bars represent wind conditions equal to, or below 10 km/h. Vertical bars represent periods of night when gulls could not forage.  ____ ___________  39  6O_  60-  2  Time (half h)  -  6O  40  General linear models of factors affecting rates of aerial search by gulls (patrols/half hour) as affected by five variates in (a) 1990, (b) 1991, and (c) 1992. Murre attendance was not monitored in 1990. Terms with more than one component, separated by a dot, indicate interactions between the component terms. t-values for single terms were calculated after interaction terms were dropped from the model. See methods for  Table 3.1.  transformations conducted prior to the analysis and further rationale. Coefficient  Term 65 F 1 , Model (a) 5  Date Time  =  SE  t-value  P-value  44.7, 63.7% of variance explained 0.011 0.033 0.000 0.000  3.028  0.003  0.814  0.417  Wind  0.643  0.206  3.117  0.002  Wind change Wind* date  0.017  0.026  0.643  0.521  0.001 -0.001 28.0, 27.6% of variance explained 0.009 -0.031  -2.533  0.020  -3.571  <0.001  95 F 3 , Model (b) 5  Date Time  -0.001  0.001  -2.774  0.006  Wind  1.009  0.089  11.338  <0.001  -0.041  0.020  -2.007  0.045  0.002 -0.002 Murre attendance 638 = 30.1, 19.7% of variance explained , 5 Model (c) F 0.010 -0.010 Date  -1.022  0.308  -1.019  <0.001  Wind change  Time  -0.000  0.000  -2.490  0.013  Wind  0.458  0.051  9.017  <0.001  Wind change  0.016  0.017  0.940  0.348  -0.004  0.00 1  -3.030  0.003  Murre attendance  41 Gull attack activity In all years, attack rate was positively correlated with both aerial search activity and wind conditions (Table 3.2 a-b). Wind conditions and aerial search activity contributed significantly to the models when included independently or together. Changes in wind conditions between observation periods had a significant influence in the calm years of 1991 and 1992 but not in the generally windy year of 1990, indicating that gulls responded more strongly to increases in wind during calm years. Year, date, time of day, and visibility did not affect attack rate.  Gull attack selectivity and murre nest site characteristics Because nesting ledge structure and murre nesting density varied within the Coats Island murre colony (see above), I examined how gulls selected for nest sites and in relation to wind 76 F (Table 3.3). Wind conditions had the strongest influence on rates of attack (ANcovA, 1 674.54, P <0.001). As wind increased, gulls attacked a higher proportion of nest sites on narrow ledges, apparently because wind enhanced their ability to reach these sites (Fig. 3.3, see below). Consequently, there was a strong interaction between wind conditions and the 676 (F 6 , width of cliff ledges attacked 1  =  176.48, P  >  0.001). Cliff ledge width alone had only a  16676 = 4.02, P = 0.045). Murre nesting-density had a strong weak influence on attack rates (F 676 (F 6 , and negative effect on attack rates 1  =  207.83, P <0.001). Gulls thus attacked areas of  low murre nesting-densities selectively (Fig. 3.3, see below). In summary, attack rates and the types of nest sites attacked by gulls were detennined largely by moderate to high winds, which enabled gulls to reach low nesting-density sites on narrow ledges from the air.  Gull predation rates Year (199 1-1992), date, time of day, and murre attendance had no detectable influence on predation rates. There were also no apparent seasonal trends in predation rates (Fig. 3.4). Instead, predation rates varied sharply over a few days, largely in response to changing wind  42  General linear models of factors affecting rates of gull attack activity (attacks/half hour) in (a) 1990, and (b) 199 1-1992 combined. Murre attendance was not monitored in 1990. Year (b), date, and time were not significant and are not reported. Search and attack rates were arcsine transformed prior to analysis.  Table 3.2.  Coefficient  Term  SE  100.7, 75.0% of variance explained 0.034 0.178 Wind 0.010 0.001 Wind change 0.037 0.363 Aerial search rate  t-value  P-value  65 F 1 , (a) Model 4  , 1033= 80.7, 38.7% of variance explained 8 (b) Model F 0.050 0.103 Wind 0.004 0.014 Wind change 0.000 -0.00 1 Murre attendance 0.019 0.196 Aerialsearchrate  5.303  <0.001  0.030  0.976  9.791  <0.001  2.076  0.038  3.392  0.001  -2.695  0.007  10.203  <0.001  43  Table 3.3. Analysis of covariance of factors influencing rates of gull attack in relation to murre nest site characteristics. Variables separated by a (*) refer to interaction terms. Attack rate data were arcsine transformed prior to analysis.  F  493.12  674.54  1  493.12 2.94  2.94  4.02  <0.001 0.045  1  151.93  151.93  207.83  <0.001  2  129.01  129.01  176.48  <0.001  2  0.11  0.11  0.15  0.695  6676  4880.47  0.73  df  SS  Wind  1  Cliff ledge width Murrenestingdensity Ledge width* wind Ledge width Error  *  nesting density  P  MS  Source  44 Figure 3.3 Attack activity of glaucous gulls in relation to wind and murre nest types. 4low 0----  3  -  1990  Broad high  J T  Narrow low Narrow high  2-  1  // T  0 0  30  20  10  2  T  1991  0  // 1  .1  /4_%_,  ::;:::i.I 30  1992  3’O  Wind speed (km/h)  45  Figure 3.4. Glaucous gull predation rates in relation to date and year. 12  1990 10  I  8  I  6 Cl,  h..  I  ••wIf .q  ‘iiH  0  I  10 C  IIH  I  o o o  20  I  40  30  50  70  60  80  90  8  1991 .1  Cl)  6  0  o C;) 0) 0) CD  riiI  I  ri  7!3i  I’ t 1  2  •‘,  :.  10  20  1992  0 6  4  11 :.fI  * 2  .1!  /  .  .4 \ ...  0 0  10  20  IIV\  I’  I’  IT  I  I  30  40  Date (June 1  50  =  /  \?.J •  I  60  70  Day 1)  80  90  46  conditions. Wind alone had a positive influence in 1990 but not in the generally calm years of 1992 and 1991 (Table 3.4 a,b). Predation within the colony was determined by murre nest site characteristics and by wind speed. Nest sites on narrow ledges experienced higher rates of predation when wind speeds increased above 10 km/h (Fig. 3.5). This was predicted based upon the previous result that narrow ledges experienced higher rates of attack under windy conditions. Consequently, there was a significant interaction between narrow cliff ledge width and wind conditions in all years (Table 3.4 a,b). Therefore, predation rates closely reflected the influence that wind conditions had on the selection of murre nest sites that were attacked.  Gull attack success In approximately 21% of 2407 gull attacks, an egg or chick was taken. Attack success depended strongly on attack technique (Table 3.5). Attacks made on foot succeeded more often (308 of 671, 46%) than aerial attacks (191 of 1736, 11%). Attack success was negatively related to attack rate and wind speed (Table 3.5), because high attack rates occurred during windy conditions when the less successful aerial attacks predominated. Attack success was positively correlated with low murre nesting-densities and with weak defensive responses by murres (Table 3.5). Cliff ledge width did not influence attack success, and contrary to prediction, there was no detectable interaction between ledge width and murre defensive response. Fog and the attendance of non-breeding murres had no influence on attack success. In summary, high predation rates observed under windy conditions resulted from high attack rates and not from an increase in attack success.  47  Table 3.4. General linear model for predation rates (eggs-chicks taken! half hour) in (a) 1990, and (b) 1991-1992 combined. Murre attendance was not monitored in 1990. Terms with more than one component, separated by a (*), indicate interactions between the component terms. The effects of year (b), time of day, visibility, and previous conditions were not significant and are not reported. t-values for single terms were calculated after interaction terms were dropped from the model. See Methods for transformations conducted prior to the analysis and further rationale.  Coefficient  Term  12.96, 27.7% of variance explained, P 0.006 0.018 0.039 -0.027 Aerial search rate  210 , 6 (a) Model F Wind  t-value  SE  =  <  P-value  0.001 3.007  0.003  -0.699  0.485  Attackratebroadledges  0.167  0.095  1.761  0.080  Attackratenarrowledges Wind * broad ledges  0.176  0.070  2.527  0.012  -0.002  0.004  -0.436  0.664  0.006  0.003  2.4 10  0.0 17  -0.433  0.665 0.960  Wind  *  narrow ledges  1120 = 47.1, 22.9% of variance explained, P , 7 (b) Model F 0.006 -0.003 Wind <0.00 1 <0.00 1 Murre attendance 0.004 0.020 Aerialsearchrate Attackratebroadledges Attack rate narrow ledges Wind  *  broad ledges  Wind  *  narrow ledges  <  0.001 0.050 5.575  <0.001 <0.001  0.051 0.004  0.011 0.0 12  4.759 0.328  -0.004  0.003  -1.229  0.2 19  0.009  0.003  2.583  0.0 10  0.743  48  Figure 3.5. Predation rates in relation to wind, murre nest types, and year 0.6  0.4  Co  ci  .1  Co  0.2  4-  0 ci C  0 0 0  0.0 0  a -c  10  30  20  0.6  1991  ‘4-  -c C  ci)  0.4  4-  c,) c,) a) C,)  ci)  4-.  0.2  C 0 t3  a)  0.0 0  ci  10  20  0.6  30  1992  0.4  0.2  0.0 0  10  20  Wind speed (km/h)  30  49  Table 3.5. Multiple logistic regression model of factors affecting gull attack success (eggs chicks taken! attack). The effects of year, time of day, and interactions were not significant and are not reported.  Estimate  Term Model 2 x [13, 12551 Wind speed  =  103.3, P  <  SE  2 value X  P -value  0.001  -0.034  0.014  6.21  0.013  Attackrate  -0.104  0.031  11.55  <0.001  Murre attendance Pedal attack techniques  -0.003  0.002  0.02  0.879  0.701  0.105  44.50  <0.001  Broadcliffledgewidth Low murre nesting density  -0.003  0.138  0.00  0.971  0.506  0.265  3.63  0.051  1.368  0.4 18  10.76  0.001  Low murre defensive response  50  Figure 3.6 Glaucous gull attack success in relation to wind speed and year. Error bars represent 1 Standard Error.  U.b  1990  0.3  0  00 C  0 0.6-  30  20  10  U)  1991  -  4—  c,) ci) Cl)  0.3-  0 Ct  0.0 0.6  I  10  0  I  •  •  30  20  -  1992  0.3  -  00  ii.  0  10  20  Wind speed (km/ h)  30  51  Wind and gull maneuverability in flight I examined the duration of search patrols and attack hovers under various wind conditions. Aerial searching by gulls consisted of two distinct components: the patrol where gulls flew into the wind along the cliff searching for prey; and the return, where gulls circled back over the ocean flying with the wind. Search patrol duration increased significantly with wind speed (r 2 = 0.61, P <0.001; log transformed) because stronger head winds reduced gliding speeds (Fig. 3.7a). This likely increased their ability to locate exposed or poorly guarded murre eggs and chicks. 2 = 0.14, P < 0.002; linear Hover duration during attacks also increased with wind speed (r regression with data weighted by their variance, Fig.3.7b).  Wind conditions above 10 km/h  enabled gulls to maintain their position next to nesting ledges without flapping their wings (static-glide). Interestingly, the threshold wind speed above which gulls could static-glide was lower than that predicted by Pennycuick’s gliding model (Fig. 3.7b). I suggest that this difference occurred because gulls used updrafts that were not be measured by the anemometer.  Murre responses to gull attack During attack, murres typically attempted to strike gulls with their beaks. Gulls attacked brooding murres head-first, and this exposed their head and eyes to contact with defending murres. Video analysis of gull attacks and experiments with gull models indicated that the greatest danger to gulls came from neighbours of intended victims. This occurred because the attacked murres typically struck at the beak of the gull, whereas its neighbours to either side could strike the head and eyes of the attacker. It is likely because of these risks of being struck that gulls avoided large groups of murres and preferentially attacked murres nesting alone or on the periphery of nesting groups. I used general linear modeling to explore how the width of nesting ledges, murre nesting-  52  Figure 3.7. a) Glaucous gull foraging patrol duration over murre breeding areas in relation to wind speed, and b) glaucous gull hover duration in relation to wind speed for gulls attacking murres from the air. The predicted line in figure b represents the wind speed at which glaucous gulls are predicted to glide generated by a ifight dynamics model (Pennycuick 1989), whereas the observed line is the wind speed threshold at which gulls were observed to glide while foraging at Coats Island.  50  a)  C,) 0  .  ci)  Co  40  0  $ 30  . I •  V  0 4-  20  0 0) C 0)  I  .  ..  •.•  : :  10  0  LL  .  •  C  0  •  • •  •  I  1j •$I  11  •I.  •1.I• 30  20  10  0  .  ••  40  ci)  LH  U)  C  30  0  D  20  -  ci > 0  .  -c  -  0 44-  •  •I  •  ••  •  I_..I. 0  •  .  •• .  10  0  predicted  observed I I.  b)  U) C.)  •Z  L  .  I  I  . •  .  I  •  .  . . •.  •  •  •  ••  •. •  !  10  Wind speed (km/h)  ••  •  .  •  •.  •  20  30  53 density, wind speed, and gull attack technique affected murre defence. The strongest murre response was found on broad cliff ledges (Table 3.6), because murres on broad ledges were more likely to strike gulls than murres on narrow ledges. Gulls attacking on foot were struck more often than gulls attacking from the air (Table 3.6), and consequently, wind conditions had a significantly negative influence on murre response (Table 3.6). In summary, gulls that attacked narrow ledges from the air under windy conditions were least likely to get struck by defending murres.  Path diagram I summarized the interactions of the various factors affecting gull predation rates using a path diagram which integrated the above analyses (Figure 3.8). Wind had a strong positive influence on aerial attack technique, and both search and attack activity. Both search and attack activity had a positive influence on predation rates of murre eggs and chicks. Aerial attack had a weak negative influence on attack success, which reflects that attacks in flight were less successful than attacks made on foot. However, a benefit of aerial attacks for gulls was the negative affect they had on the effectiveness of murre defence, and presumably, the danger of injury for gulls. Therefore, wind facilitated the use of aerial attacks which had a low probability of success when compared with attacks made on foot, but which also were associated with low probabilities of contact with murres during attack.  54  Table 3.6. (a) General linear model for factors influencing the level of murre response to gull attack, and (b) multiple logistic regression model for probability that gull was struck by murres during attack. Murre response data for all three years were combined for analysis because they did not differ by year. All possible interactions were initially included and none contributed a significant effect. The effects of year, and time were not significant and are not reported.  Estimate  Term  SE  t  -  value  (a) Model F [6, 1292] = 79.17, 17.5% of variance explained, P <0.001 10.09 0.006 -0.024 Wind speed 0.066 0.086 1.67 Pedal attack techniques 37.12 0.055 0.339 Broad cliff ledge width 0.22 0.104 Low murre nesting density -0.049 4.04 0.076 0.153 Successful attack (b) Model  x [6, 1294] = 2  P -value  0.001 0.196 <0.001 0.637 0.046  84.12, 17.8% of variance explained, P <0.001 -0.026  0.022  1.37  0.242  0.856  0.159  28.86  <0.001  0.655  0.200  10.71  0.011  Low murre nesting density -0.3 13 0.001 Murre attendance  0.161 0.002  1.04 0.23  0.308 0.63 1  0.307  0.160  3.66  0.055  Wind speed Pedal attack techniques Broadcliffledgewidth  Successful gull attack  55  Figure 3.8. Path diagram illustrating the relationships between factors affecting gull predation rates. Solid arrows represent the direction of influences tested with multiple linear regression. Shaded arrows indicate an absence of data, although an interaction likely occurred. Values above arrows refer to the standardized regression coefficients between. The sizes of coefficients indicates the magnitudes of influences, and these can be compared throughout the path diagram. The signs of the coefficients indicate whether factors had negative or positive influences on each other. Arrows without a coefficient indicate an absence of significant influence, however negative or positive signs of the non-significant coefficients are included for reference.  AERIALATTTACK TECHNIQUE  +0.186  ATTACK ACTIVITY  SEARCH ACTIVITY  +0.621  -0.162  NARROW LEDGES ATTACKED  MURRE NuMBERS-  +ve  ye  —  -  -ye  PREDATION RATE  +ve  ATTACK SUCCESS  -0211  LEVEL OF MURRE DEFENCE  +ve  +0.761  RISK OF INJURY FOR GULLS  NESTING DENSITY  L1  57  Colony-level effects of gull predation on niurre reproduction Murre nest sites varied in their vulnerability to gull predation. Although newst sites on narrow ledges experienced frequent predation at moderate wind speeds (Fig 3.5), calm wind conditions restricted the ability of gulls to reach these nest sites. Therefore, nest sites on narrow ledges suffered intermediate levels of predation over the total breeding season (Fig. 3.9). Murres that nested at high densities on broad ledges could defend themselves effectively against attack regardless of wind conditions. In contrast, murres in low-density areas on broad cliff ledges suffered the highest levels of egg and chick loss because these sites were accessible to gulls during all wind conditions. Thus, broad ledges supported both the safest (interior) and most vulnerable (edge) nest sites within the colony (Fig. 3.9). These results are robust because there were no strong seasonal differences in attack rate, attack success, or predation rate over the course of the breeding season.  58  Figure 3.9. Estimates of the proportion of murre eggs that were originally laid which were taken by glaucous gulls during an entire breeding season at Coats Island. Reproductive failure due to predation is presented in relation to murre nest site characteristics (e.g, BH= broad cliff ledge width, high murre nesting-density; BL=broad cliff ledge, low nesting density; NH=narrow ledge, high density; NL=narrow ledge, low density; CAVE=crevice nest site). For further definitions of murre nest site characteristics, see Methods.  20 C,) D  c,) 0  .4.4-  U)  0  C,)  c,) c,) ci) 15  10  C  0  0  0  2 cL  0 BROAD HIGH  BROAD LOW  NARROW HIGH  NARROW LOW  Nest site characteristics  CAVE  59  DISCUSSION Wind: a foraging constraintfor glaucous gulls preying on thick-billed murre eggs and chicks Glaucous gull foraging activity and predation rates were higher under windy conditions. Typically, gulls patrolled the murre colony when wind conditions exceeded 10 km/h. What advantages could account for the strong interaction between wind and aerial foraging by gulls? First, gulls flew into the wind when searching, and higher winds slowed their rate of search. Foraging patrols over nesting murres took twice as long under windy conditions than under calm conditions (Fig 3.7a). This likely increased the ability of gulls to locate exposed or poorly guarded murre eggs because slower search speeds typically increase the likelihood that a forager detects concealed food items (Norberg 1977; Gendron and Staddon 1983; Bell 1991). Second, wind also increased the ability of gulls to attack vulnerable eggs and chicks once they had been detected. Under low winds (<10km/h), gulls had difficulty hovering next to murre nest sites (Fig. 3.8b), and they typically had to circle over the ocean to maintain their flight speed before returning to make an attack. Under these circumstances, gulls often could not relocate the vulnerable sites after circling. In contrast, gulls could maintain their position next to murre nest sites during attack under windy conditions (Fig. 2.8b). Indeed, I occasionally observed gulls gliding backwards under windy conditions to take eggs that they had initially passed over. Thus, windy conditions enabled gulls to make rapid and effective attacks almost immediately after prey were detected. This is important because, in most cases, eggs and chicks were only exposed to gulls briefly while an adult murre preened or an incubation change-over took place between brooding murres. Third, and perhaps most importantly, windy conditions allowed gulls to reach poorly defended, and difficult to land on, nest sites. Murre defence was weak on narrow ledges because most murres on narrow ledges faced into the cliff, and could not turn readily to face gulls without dislodging their eggs and chicks. Consequently, murres on narrow ledges could  60 only defend their immediate neighbours. In addition, most gull attacks at narrow ledges were swift and from the air. In contrast, murres on broad ledges could turn to face gulls that were attacking on foot. Murres on broad ledges could also act collectively to defend their neighbours (see also Birkhead 1977; ch. 2). I therefore conclude that windy conditions enabled gulls to overcome constraints imposed by both colony topography and prey defence and thus reach narrow ledges where murre defence was ineffective. Other avian predators use wind to enhance their foraging success (Rudolph 1981, American kestrels; Spear and Andersson 1989, common ravens; Haney and Lee 1993, gulls at sea; Theil and Sommer 1994, herring and greater black-backed gulls; Young 1994, south polar skuas). However, not all aerial foragers are efficient in high winds because wind interferes with prey detection and pursuit in other systems. In these cases, the benefits gained by increased maneuverability and lower energetic search costs during flight in winds are not sufficient to increase the net foraging efficiency of the predator. For example, the foraging ability of ospreys, Pandion haleaetus, and some terns, Sterna sp., decreases during windy conditions despite increased maneuverability, longer hovering bouts, and more time spent gliding. The surface turbulence on water created by wind interferes with their ability to locate prey (Dunn 1973; Grubb 1977; Taylor 1983; Machmer and Ydenberg 1990). Wind may also increase the maneuverability of avian prey and their ability to escape predation or kleptoparasitism (Amat and Aguilera 1990). Wind and poor weather may also decrease the activity of prey, and in turn, the probability that predators detect them (Mearns and Newton 1988). Based upon these considerations and my findings, I predict that wind should enhance the foraging efficiency of avian predators when: 1) aerial maneuverability increases the accessibility to prey and/or the likelihood of successful attack, 2) the energetic costs of search and attack during flight dramatically influence the net profitability of prey, and 3) wind does not greatly enhance the ability of prey to escape or avoid detection.  61 The currency of glaucous guilforaging decisions A basic theoretical premise of behavioural ecology is that animals select behavioural strategies that maximize fitness. In practice, indirect ‘currencies’ for estimating fitness are derived from the natural histories of foraging animals and the constraints facing them (Sibly and McCleery 1985; Mangel and Clark 1986; McNamara and Houston 1990). For example, classical foraging theory predicts that animals should select foraging strategies that maximize their net energetic gain while foraging (Stephens and Krebs 1986). This could occur either through maximizing the rate of energy gain or the efficiency with which it is obtained, and there is considerable evidence that both strategies occur in the wild (reviewed in Ydenberg et al. 1994). In my system however, glaucous gulls appeared to do neither of these things. Most gulls were inactive for extended periods of time during calm wind conditions at Coats Island (<10km/h; Figs. 3.2, 3.3). Once windy conditions returned, however, gulls which had been loitering at the colony began to forage immediately which suggests that they had been waiting for wind conditions to increase. This is surprising since adult gulls were surrounded by their prey, and attacks made on foot under calm conditions were highly successful. Although there were several benefits from aerial foraging under windy conditions (see above), these benefits cannot explain both the foraging inactivity of gulls under calm conditions, and their reluctance to forage on foot.  -  The foraging inactivity of gulls could simply have been a response to changes in their energetic requirements under different weather conditions. For example, during calm conditions the thermal maintenance requirements for glaucous gulls would be low (Gabrielsen and Mehlum 1984). Under windy conditions, gulls might need to increase their forging activity to meet their higher energetic requirements due to higher rates of heat loss. However, three factors suggest that this does not explain foraging inactivity of gulls under calm wind conditions. First, gulls occasionally left the colony to forage at sea under calm conditions. This strategy yields less energy than could be obtained from a single murre egg obtained by foraging on foot (Spear 1993; ch. 4). Second, under windy conditions gulls foraged primarily  62 on the wing although this probably incurred higher energetic costs (Wiens 1984), and was accompanied by lower attack success (11%) compared with gulls foraging on foot (43%). Finally, gull chicks actively begged and harassed adults during calm conditions and this activity appeared to intensify as calm conditions persisted (pers. obs.). Collectively, these results suggest that gulls were not satiated during calm conditions, and that they selected foraging modes which did not yield the highest net energetic gains even when foraging conditions improved. I therefore suggest that energetic considerations alone are insufficient to explain glaucous gull foraging behaviour at Coats Island. Foraging theory has recognized that environmental constraints often force foragers away from the strategy that maximizes net energetic gain (McNamara and Houston 1986; Mangel and Clark 1986; Lima and Dill 1990; Dill 1986). For example, prey may minimize their exposure to mortality risks while foraging (e.g. predation), and this may lower their foraging efficiency (Lima and Dill 1990). For predators, injury while foraging often results from prey fighting back (Curio 1974). Although these injuries are rarely fatal, the potential loss of fitness for the predator is great. Among glaucous gulls, the risks of eye injury associated with foraging on foot could reduce the fitness value of foraging on foot under calm conditions. I propose that a tradeoff between energetic gain and risk of injury while foraging explains the reluctance of gulls to forage on foot, and consequently, the reduced foraging activity observed under calm conditions. Sutherland and Moss (1985) predict such a foraging strategy in systems where, 1) poor foraging conditions are short-lived relative to the energy reserves of foragers and their dependent young (e.g. the duration of calm wind conditions), 2) the forager is highly successful once conditions improve, 3) the energetic value of a food item is large (here, 714 kJ/ murre egg; Spear 1993), and 4) the mortality risks associated with improved conditions are low (e.g. the ability to reach poorly defended narrow ledges on the wing).  Therefore, waiting for  improved foraging conditions could be an appropriate foraging strategy for glaucous gulls at Coats Island, particularly considering their long lifespan and the limited contribution of a  63 In summary, I suggest that glaucous gull foraging behaviour at Coats Island reflects a trade-off between the dangers of injury while foraging at the colony (which is generated by murre defence) and the energetic gain of captunng a murre egg or chick. This tradeoff appears to be mediated by wind conditions, which alter the reward/danger ratio of alternative foraging decisions. Tests of these conclusions requires a closer examination of foraging energetics and risk of contact with murres. I explore these issues further in chapter 4.  Population-level consequences of guilforaging behaviourfor murres Glaucous gulls preyed on murre eggs and chicks throughout the breeding season, and their foraging activity and predation rates were positively correlated with windy conditions. Wind also influenced the characteristics of the murre nest sites that were attacked by gulls. Consequently, the level of gull predation was both a function of wind conditions over the course of the breeding season, and of predation rates in relation to nest site characteristics. By integrating data on wind conditions at Coats Island and gull predation rates relative to wind conditions, I calculated the proportion of eggs and chicks lost to gulls in relation to murre nest site characteristics using equation 1. From this, I ranked the vulnerability of murre nest sites to gull predation from high to low as follows: 1) low-density edge sites on broad ledges; 2) lowdensity sites on narrow ledges; 3) high density sites on narrow ledges; 4) high-density sites on broad ledges; and 5) crevice nest sites. Under both actual (this study) and simulated predation (ch. 2), these rankings are the same. My findings also partly explain the results of Birkhead and Nettleship (1986) and of deForest (1993) who found that thick-billed murre reproductive success was lowest on broad, low nesting-density ledges, intermediate on narrow ledges, and greatest on broad, high-density ledges. However, reproductive failure due to gull predation at Coats cannot account for all of the egg and chick loss experienced by murres. By integrating data on murre reproductive success collected during the years of this study at Coats Island (deForest 1993), with the results presented in Figure 3.9, I estimate that gulls accounted for 0% (crevice), 13% (broad-high),  64 21% (broad-low), 13% (narrow-high), and 18% (narrow-low) of murre reproductive failure at each of these nest sites. Murre nest site characteristics could also affect the likelihood that eggs and chicks are dislodged during incubation change-overs between members of a breeding pair or during fights between neighbours (Birkhead 1977; deForest 1993). Despite these low annual predation rates, my results illustrate how avian predation selects for murres to nest at high densities. The predation rate at low-density nest sites on broad cliff ledges was 6 times greater than at similar sites at high nesting-densities. From this, I predict that colony-wide predation rates should increase at murre colonies if the proportion of birds nesting at low densities in open, level habitat increases. Avian predators would be less constrained by both calm wind conditions and by group defence if they could forage on foot under low risk of contact regardless of wind conditions. If this occurred, avian predation could slow the expansion or colonization of new seabird nesting areas in open habitat (e.g. Johnson 1938; Spear 1993), or steepen declines in populations that are decreasing. I explore these issues further below in chapter 5.  Conclusions In this study, windy conditions allowed gulls to overcome constraints imposed by colony topography and prey defence. Both attack activity and predation rates were positively correlated with windy conditions. Consequently, the impact that predation had on murre reproductive success, which ranged from 0% to 21% of murre reproductive failure depending on murre nest types, was determined largely by wind conditions and the accessibility of murre nest sites to gulls. I suggest that a decline in the density of nesting murres could enhance the ability of gulls to overcome the constraints of calm wind conditions, cliff ledge accessibility, and prey defences.  65  CHAPTER 4 FORAGING MODE SELECTION OF GLAUCOUS GULLS PROVISIONING YOUNG: A DANGER-REWARD TRADE-OFF MEDIATED BY WIND?  Life history theory is based on the assumption that trade-offs exist between various activities in an organism’s life. For example, the risks and energy allocation associated with present reproduction may reduce an organism’s ability to reproduce in the future (Williams 1966). Trade-offs between the advantages and disadvantages of particular levels of reproductive expenditure may affect many life-history characteristics, including the age of sexual maturity, survival rate, brood size, reproductive frequency, and short-term investment in young. Among organisms with parental care, provisioning can add to the cost of reproduction or reduce the probability of adult survival (Drent and Daan 1980; Reznick 1985; Nur 1988; Hochachka 1990). Provisioning could increase energetic demands on the parent, thus increasing risks of adult mortality or reducing energy available for future reproduction (e.g. Dijkstra et al. 1990; Beauchamp et al. 1991). It could also increase the exposure of the parent to predation (e.g. Harfenist and Ydenberg 1995). Thus, parents may be in conflict with their offspring about the optimal level of provisioning to be maintained (Ydenberg 1994). The provisioning choices of top predators could also be influenced by the risk of injury while foraging as a direct result of prey fighting back (Curio 1974). Risk of injury could increase if predators were forced to make more kills, or to switch to a more dangerous prey to meet the energetic demands of their young. Under risk of injury, the provisioning strategy which maximizes the energetic contribution to young might not be the one that maximizes lifetime reproductive success for the adult. Further, the relative costs and benefits of these foraging decisions should vary with 1) changes in the availability of prey, 2) the risks associated with subduing prey, and 3) the energetic state of the offspring. Applying a lifehistory framework could provide insight into whether variation in foraging behaviour within a  66 predator population is caused by evolutionary trade-offs between present and future reproduction (e.g. Sibly and McCleery 1985; Dijkstra et al. 1990; Pierotti and Annet 1991). The glaucous gull, Larus hyperboreus, is well suited for a study of these topics. At Coats Island, Northwest Territories, Canada, glaucous gulls prey on the eggs and chicks of colonial cliff-nesting thick-billed murres, Uria lomvia, and they use several foraging modes when doing so. In general, the most successful foraging modes incur the greatest contact with defending murres so that a trade-off may exist between energetic gain and risk of injury (ch. 3). Weather conditions at the murre colony may also influence this trade-off. Wind improves the aerial maneuverability of gulls which in turn increases their ability to reach murre nesting ledges and avoid contact with murres during attack (ch. 2, 3). At Coats Island, breeding gulls are often inactive for extended periods of time under calm wind conditions (ch. 3). During such periods of inactivity, their chicks are rarely provisioned. In chapter 3, I suggested that this foraging inactivity is the response of adult gulls to the dangers of foraging under calm wind conditions which is generated by murre defence. Thus, foraging inactivity under calm conditions may reflect a conflict between parent and offspring in which the adult ensures its survival and future reproduction at the expense of its current brood. An alternative explanation is that gulls are simply responding to the varying energetic demands determined by changing weather conditions, and that danger of injury while foraging is unrelated to foraging inactivity. In this chapter, I present a dynamic optimization model of gull foraging mode selection which explores these two alternatives in the context of life history theory.  In this  model, the optimal decision for the adult gull is to choose the foraging mode that maximizes the trade-off between current brood survival (via provisioning), and the risk of fatal injury while foraging. The model integrates field data on gull foraging mode selection with energetic parameters obtained from the literature, to explore the above alternatives. I compare the model’s predictions with field data on gull time budgets, and discuss how these predictions explain patterns of individual variation observed among wild gulls.  67  METHODS Study site and species interactions The field component of this study was conducted at a thick-billed murre colony located on Coats Island. See chapters 2 and 3 for further details. Though the diet of breeding gulls and their chicks at Coats Island was made up mostly of murre eggs and chicks (90%), gulls occasionally fed at sea. Trips to sea typically exceeded three hours duration. Food resources inland from the colony were limited because Coats Island has no rodents, and carrion on the tundra was quickly consumed by Arctic foxes (Alopex lagopus). No waterfowl colonies existed near the murre colony. Gulls depredated murre eggs and chicks throughout the breeding season. Early in the season, members of gull breeding pairs took turns foraging away from the nest so that one adult was always present with the chicks. After 2 weeks, gull chicks were often left unattended while both parents foraged. Members of a pair did not forage together nor did they attack murres cooperatively. Gulls attacked murres on foot or from the air, and in general, attacks made on foot were most successful (ch. 3). Attacks on foot also incurred the greatest risk of contact with murres during attack because the presence of a gull standing on a nesting ledge afforded murres the time to establish a collective defence (ch. 2, 3).  Field studies ofguilforaging behaviour Gull attack modes were studied among the general gull population. From blinds, I observed predation attempts and monitored the frequency of each attack mode, the probability of their success, and the frequency that the gulls were struck by defending murres during each attack (for further details, see ch. 3). In 1992, 8 glaucous gulls were captured using padded leg-hold traps and each was individually marked with acrylic paint The attack mode repertoire, attack rate, and attack success of each bird was monitored. The length of time each gull devoted to the following  68 activities was also studied: 1) at the nest ledge; 2) loitering near but not on the nest ledge; 3) absent from colony; 4) foraging on foot; 5) aerial foraging; and 6) scavenging at the colony. Foraging behaviour and time allocation were studied in relation to two wind speed categories: calm < 5 km/h and windy> 10 km/h. Above 10 km/h gulls could search the colony using gliding flight and were able to reach narrow murre breeding ledges (ch. 2, 3). Preliminary analysis of attack mode selection indicated that 2 of 8 birds (terrnedfoot specialists), attacked murres predominantly on foot regardless of wind conditions. Thus, I partitioned time budget data so that aerial and foot specialists were analyzed separately.  Dynamic optimization model The following assumptions describe interactions of gulls and murres at Coats Island which were incorporated into the dynamic optimization model. Several of these assumptions were identified through experimentation and behavioural observation in the field (ch. 2, 3). Aspects of gull energetics not studied at Coats Island were taken from the literature. Assumptions concerning model parameters are introduced here, and further details of parameter values are provided below. The dynamic model simulates the foraging mode selection of an adult gull responding to changes in both the energy stores of its chicks and to wind conditions. The brood obtains energy through provisioning from the adult. Adult gulls choose between the following foraging modes: 1) do nothing and loiter at the colony, 2) attack murres by foraging on foot, 3)  attack murres using flapping ifight attack modes, 4) attack murres using gliding flight  modes, 5) scavenge at the colony, and 6) leave the colony to forage at sea. The gull cannot use the gliding flight foraging mode during calm wind conditions (w=0, wind speed <5 km/h) due to the limitations of flight dynamics (Pennycuick 1987, 1989; ch. 2, 3). However, when wind speed exceeds 10 km/h (w=1), all foraging modes are available to the gull. In the model, adult gulls select a foraging mode at the start of each hour interval (t =  1,2,3 ...7). Each foraging mode (i) carries with it a wind-dependent probability of  69 successfully obtaining a food item in each period t (2), and an energetic cost for the adult (q,) measured in U/h. Each foraging mode also carries with it a survival probability c,, so the risk of fatal injury to the adult during the interval is, 1-c,.  Brood energy dynamics The energy reserves of the brood in period t is x(t). The gross energetic gain that is available to the brood (/3j is a function of the energetic value of the food item () multiplied by the metabolizable assimilation efficiency of the food type,  *  =  J3j. Assuming a  delivery of /3 the energy status in the next period is,  3 1 x(t÷l)=x(t)+/  (1)  w 1 -ow-p  and if no delivery, (2)  x(t+1)=x(t)-8 -p  is the energy requirement of the adult  where 8 is the brood metabolic costs at rest, and q, using foraging mode i during that time period.  /3 8, and q, are all dependent on wind ,  status w, and /3 and p are also dependent on i. Energy status evolves in this way until the final time period T, at which time brood success can be assessed. Survival of nestlings to breeding S (x(1)) depends on energy reserves x(t) (Fig. 4.1. The adult terminal fitness (F) depends on the success of the brood and also on adult survival. If the adult survives to the end of the terminal period T, fitness is assessed as,  F (x, w, I)  =  S (x (7))  [w=O or 1]  Fitness is assessed at the end of each foraging interval. Wind conditions are set at the beginning of each interval, following which, the gull is able to make its foraging mode  (3)  70  Figure 4.1 Brood success S (x) as a function of energy reserves x at time t Smax is the maximum number of chicks that can survive to breed (3). The Xmin is the minimum reserves a 3 chick brood can carry (986 kJ), and xmax is the maximum reserves (14985 kJ).  S(x(T))=Smax  *  x(7) x(7)  x  -  -  Xmin+  Smax  Cl,  3 ci, ci; 0  >,  2: Cl)  V ci) 4-, C.) C) 0.  w  0 0  5000  10000  Brood energy reserves  Xmin  15000 x (7)  2000  71 decision. Wind conditions change from interval to interval according to the Markov process defined in Table 4.1. At the end of the penultimate period T- 1, the adult still has one period to forage, during which it may deliver J3 to the brood, or during which it may die with probability 1Wind conditions during T- 1 are w. If it is calm (w=0) during period T, the adult’s expected fitness at the start of the final period is,  [ *] + 1 [CL  *,2  *F(X+/31w_3w  0,1)]  + *f(x_& *(1) ) [cQ 1  0,1)]  If it is windy (w= 1) during period T, the adult’s expected fitness at the start of the final period is,  [(1CL)*oJ  + 1 [CL  *,2, *F(x+f3_& -p ,, 1,7)] 1 +  1 [cL  *  *F(x_3 Piw’ 1,1)] (1_2L, ) 1  In either case, the adult chooses foraging mode i (at the start of the final period T, after it knows w) to maximize the appropriate expression above. The expected fitness at the end of the penultimate period T -1 depends on the probability of calm or windy conditions in the next period provided in Table 4.1. We can use these probabilities to derive the expected fitness at the end of each period as,  72  Table 4.1 The probability of wind conditions in the next time period in relation to wind conditions in the current time period.  Next period  Calm  (t +  1)  Windy  Calm  q=O.8  l-q  Windy  ‘-p  8 p=o.  Current Period t  73  F(x, 1,  t)  =  max  { [(1- cq)  *  (4a)  0]  +  [ (p)*cj*.a,l*F(X+5_3(1)q,(1),1,t+1)] + [(1-p)  *  cj  *  *  F(x-f-—8(o)- q(O),O,  t+  1)]  + [(p)  *  yj  *  (1  -)) * F (x —5(1)-q (1), 1, 1  t+  1)]  + l [(1p)*j ) *F(x_o(o)(o),0,t+1)]} 1 *(  A similar fitness algorithm is derived when wind conditions in the current time step are calm  (w = 0), and given the probabilities that the wind would increase (1 -q) or stay calm (q) in the next time period.  F (x, 0,  t)  =  max  { [(1- cq)  *  (4b)  0]  + [(1q)*j  *F(x+f3_8(1)(1),  l,t+ 1)]  F(x +J3—ö(o)-q (o), 0, 1  t+  + [(q)  *  *  *  1)]  + [(1q)*oj *(1  l,t+ 1)]  + [(q)  *  *  (1  *  F (x  —  (0)  - (0), 0, t + 1)]  }  The model was implemented as described in Mangel and Clark (1986) by beginning with the terminal time period T (equation 3), and iterating backwards using equations 4a and 4b.  74 Model assumptions concerning provisioning The gull being modeled was assumed to provide half the energetic requirements to its brood of three chicks. Behavioural observations at Coats Island indicated that members of a pair contributed roughly equally to the provisioning of chicks. In some other gull species, males typically contribute more to provisioning than females (Watanuki 1989; Pyle et al. 1991). The model also assumed that the adult could accurately assess the energetic state of the brood during each hourly time step, and that the adult delivered food items during the hour in which it was obtained. Observations in the field indicated that this latter assumption was generally the case. The model assumed that following a successful prey capture, the adult provisioned the brood with the energy gained minus its own energetic requirements for that hour (q). Thus, the adult was assumed to maintain its own energy balance while provisioning, so that the model did not follow the energetic state of the adult. This simplification allowed me to develop a tractable model which considered two states: chick energy stores x(t), and wind conditions w(t). However, this approach assumed that provisioning strategies were independent of the energetic state of the adult. This simplification has important implications for studies of provisioning strategies (Ydenberg 1994), and it therefore warrants further elaboration. The perceived value of a food item and the costs a forager is prepared to pay to obtain it, may differ if the food is for the foragers own consumption or for delivery to its young (Ydenberg 1994). In most cases, the interplay between the energetic states of both adult and young in studies of provisioning should be considered. This is particularly true if the forager is constrained by time or energy limitations, because as a forager approaches a time or energy boundary it may alter its provisioning strategies, foraging strategies, or both (Ydenberg et al. 1994). However, I suggest that adult glaucous gulls have few time or energy constraints in relation to the time scales considered by this model.  75 Gulls at Coats Island have up to 20 hours of daylight in which to forage during the period of the breeding season that this model considers. Further, gulls raise their young surrounded by their primary food, so that the time between prey capture and delivery to the brood is negligible. Indeed, gulls often take eggs and chicks from murres who share their own nesting ledges. Considering the number of attacks that gulls can make in a day, the high probability of their success, and the negligible travel time while searching for prey and delivering prey to chicks, it seems unlikely that gulls are constrained by foraging time. I also assume that adult gulls at Coats Island are not constrained energetically. The distances traveled while searching for prey are small, and the energy obtained from a single prey item is high relative to the energetic requirements of both foraging and maintenance (see below). For example, I estimate that a gull using the flapping flight mode for over 6 hours, could still achieve a positive energy balance for itself if it obtained a single murre egg during that time (i.e. a prey capture rate actually lower than that observed in the wild, see below). Further, large gulls typically carry fat stores during the breeding season which can easily maintain them through short term periods of poor foraging conditions similar to those considered by this model (Spaans 1971; Coulson et al 1983; Sibly and McCleery 1985). Therefore, it is reasonable to assume that adult glaucous gulls generally maintain a constant energetic state by assimilating portions of the prey that they deliver to their young. If the energetic state of the parent is constant, short-term provisioning strategies should be more greatly influenced by the energetic state of the young, or by other factors influencing adult fitness (e.g. risk of injury while foraging). The model therefore concentrates on two parameters: 1) the energetic state of the chicks, which, due to their dependence on their parents, their smaller energy stores, and their higher thermal conductance, are more likely to be affected by poor foraging conditions; and 2) the risk of fatal injury for the adult while foraging.  76 Weather conditions Wind conditions at the Coats Island colony ranged between 0 and 70 km/h throughout the breeding season. However, wind conditions were usually moderate and ranged between 0 to 25 km/h (ch. 3). This model considered the period of the breeding season when gulls preyed on murre eggs and when gull chicks were approximately 900g (half their final mass of 1800g). During this period (early July), snow storms occurred occasionally and temperatures regularly fell below 2°C at night, i.e. below the thermal neutral zone of adult glaucous gulls (2°C, Gabrielsen and Mehlum 1984).  Metabolic rate estimates There are two basic approaches to studying avian energetics in the field. The first is to calculate total gross energy intake and compare it with estimates of Field Metabolic Rate (1MR),  which is the total energy cost that a wild animal pays during the course of a day  (Nagy 1987). Estimates of the FMR are typically derived using the doubly-labeled water technique (Nagy 1987; Birt-Friesen et al. 1989). With this method, the relative energetic costs of each activity are typically not partitioned (e.g. flight, brooding young, walking). The second approach is to compare total daily gross energy intake with estimated expenditures of each of the activities performed during the day (Tarboton 1978). In this case, most activities are given costs as multiples of the Basal Metabolic Rate (BMR) while the energetics of flight are usually derived from flight dynamics models (Gabrielsen et al. 1987). BMR  can be defined as the rate of energy used by animals at rest and in a fasting condition,  and at an ambient temperature at which little or no extra heat is required for the maintenance of body temperature (Kendeigh 1970). BMR may be estimated from either allometric equations based on mass (Tarboton 1978), from studies using metabolic chambers or doubly labeled water techniques (Gabrielsen and Mehlum 1984), or by combinations of these methods (Weathers et al. 1984; Birt-Friesen et al. 1989).  I applied the BMR approach for  two reasons. First, data existed for the BMR for glaucous gulls and other high latitude  77 seabirds existed (Birt-Friesen et. a!. 1989; Ellis 1984; Gabrielsen and Mehium 1984). Secondly, I could simulate foraging mode decisions and the energetic state of adults and chicks on a fine time scale, which permitted me to compare output of the model with field data on gull foraging behaviour. I estimated the basal metabolic rate (BMR, kJ day-’) of adult glaucous gulls (mean weight = 171 5g) using the allometric equation of Ellis (1981) for seabirds: BMR  =  (5)  381.8 M° 721  where M is the mass of the bird measured in kilograms (kg) and BMR is measured in kJ/day. This equation predicts a BMR of approximately 563 kJ day-’ or 23.5 kJIh for adult glaucous gulls. I adjusted this estimate by +20% to account for discrepancies observed between allometric predictions of BMR for seabirds and the results of metabolic chamber studies of glaucous gulls (Gabrielsen and Mehlum 1981). These high levels of BMR have been attributed to a latitudinal gradient in which high-latitude seabirds are thought to maintain higher metabolic rates to mediate the effects of their cold environment (Ellis 1984; Gabrielsen and Mehium 1984; Gabrielsen et al. 1987; Klaassen 1988). Following this adjustment, I 1 for adult glaucous gulls. I assumed that estimated a BMR of 675.6 kJ day-’ or 28.2 kJIhthe Resting Metabolic Rate at the nest was 1.9 xBMR or 53.6 kJ/h for adults. This multiple of BMR was the energetic expenditure of adult black-legged kittiwakes (Rissa tridactyla) nesting on exposed cliffs in the arctic (Gabrielsen et al. 1987) and closely approximates the value 2.13 xBMR for northern seabirds at rest (Birt-Friesen et al. 1989) and 1.9 xBMR for herring gulls at rest (Baudinette and Schmidt-Nielsen 1974). I estimated the BMR of a 0.9kg glaucous gull chick as 16.9 kJ/h using the adjusted Ellis (1981) allometric equation for seabirds (see above). I also assumed that glaucous gull chicks had higher RMRs than the value estimated for adults (RMR = 1 .9x BMR or 32.3 kJ/h) due the additional requirements of growth.  I calculated the energetic cost for growth (Etis; kJ/g)  using the equations, 1= E,  m  ) +1  —  m  )t  (6)  78 where etis is the energy density of body tissue of the chick (kJ/g), t is age of the chick in days, and m is mass of the chick in grams (following Klaassen 1988). The costs for the ) were calculated from the production costs (Et; kJIg) assuming 5 synthesis of body tissue (E  a synthesis efficiency of 75% (Ricklefs 1974): (7)  = 1.25 3 E  Energy density of tissue was estimated from the linear function of Drent et al. (1992) which was derived by plotting the energy density of body tissue from gull and tern chicks at a given weight against the final asymptotic mass of each species. Thus, for a 900g glaucous gull chick at half asymptotic mass, the energy density of tissue was estimated to be 8.3 kJ/g. From the logistic growth curve of glaucous gull chicks at Coats Island (Gilchrist unpub. data), chicks gained approximately 19g per day at this time. These values, when entered into the equations above, provide an energetic estimate for growth of 9.1 U/h. When added to previously calculated values of RMR for glaucous gull chicks (RMR  l.9x BMR or 32.3 kJ/h,  see above), the energetic requirement estimated for growth was 23% of the total energy expenditure. This is close to the energetic requirements for growth of other non-passerine species at half asymptotic weight (as a proportion of total energy expenditure: 20-36% for herring gull chicks, Dunn 1980; 15-22% for Arctic terns, Klaassen 1988; 27-33% for longeared owls, Wijnandts 1984). When maintenance metabolism and growth were combined, I estimated that a 900g glaucous gull chick had a RMR of approximately 41.4 kJ/hour under neutral thermal conditions. Reviews of avian energy budget studies have emphasized the importance of evaluating the influence of environmental conditions on metabolic rates (Weathers et al 1984; Webster and Weathers 1988). During the night on Coats Island, the energy used by adults and chicks consisted of resting metabolism plus additional thermoregulatory requirements. The additional metabolic heat production at night (Enignt kJIg.h.°C) was estimated using the equations:  79 Enigh: =  Cn  *  (Tb  -  Tamb)  -  (8)  BMR  where Cn is the thermal conductance of the bird (kJIg.h.°C),  Tb  is the body temperature,  and Tarn is the ambient temperature (Lasiewski et al. 1967; Weathers et al. 1984). Due to the differences expected in body temperature and thermal conductance between adults and chicks, I calculated thermal costs for each separately. Under conditions where ambient nightime temperature was -2°C, adult body temperature was assumed to be 39.6°C (Gabrielsen and Mehium 1984), adult mass was 1800g, and the thermal conductance was 0.0004984 kJ/g.h.°C (0.0248 ml 02 /g.h.°C following the conversion 0.020 1 kJ/ml 02; Gabrielsen and Mehlum 1984), I calculate that adults required an additional 7.4 kJfh for thermal maintenance during the night (14% above daytime RMRs at thermal-neutral temperatures). At -8°C I calculated that adults would require 12.5kJIh above their RIvIR at ,  thermal neutral temperatures. I assumed that chick thermal conductance was 0.0006977 kJIg.h.°C (40% less efficient than adults; Klaassen 1994), and that chick body temperature was 41.3°C (4% higher than adults, Wijnandts 1984). At -2°C, I calculated that chicks (900g) required an additional 10.2 kJ/h for thermal maintenance during the night (24.6% above daytime RMRs) assuming that they were not brooded by their parents. This value rose to 14.1 kJ/h for chicks at Tamb= -8°C. Most gull nest ledges on Coats Island were exposed and supported no vegetation. Thus, nesting ledges provided little protection from the wind for either adults or chicks. Relatively few investigations have examined the influence of wind on convective heat loss from birds, and those that have, have generally concentrated on passerines in a laboratory setting (Webster and Weathers 1988). Energetic studies under laboratory conditions have shown that wind increases the convective heat loss from birds at air temperatures below and within the thermal-neutral zone, and that wind also has greater effects at lower air temperatures (Gessaman 1972; Goldstein 1983; Webster and Weathers 1988). I applied the equations of Goldstein (1983) which predict the metabolic rate of a bird at any wind speed  80 10 crit). These calculations occur in two steps. First, below the lower critical temperature (T the energetic expenditure in relation to temperature is calculated, 66 b = .0092M  (Tamb  (9a)  0 Crit) .32 -Ti  where b is in watts (W), M is mass in grams, and Ta and Tiowcrjt are in oC. The second step involves the equation, RMR =  (9b)  a + (b) (“Ju)  where RMR is known for the temperature of interest, u is the wind velocity in mis, and a is the Y-intercept. When the values for RMR, b and u, are known for a given temperature, a ,  can be calculated (Goldstein 1983). For an adult glaucous gull of mass 1715g at -2°C in wind conditions of 0.O6mls where RMR =53.6kJ?h, b =1.954, and “Ju= ‘J0.06, a will equal 14.4. These values can then be substituted back into equation 8b, to calculate values for other wind speeds at -2°C (for details see, Goldstein 1983). Thus, for an adult gull at -2°C in wind conditions of 25km/h, the RMR was estimated to be 61.2 kJ/h. The thermoregulation requirements for chicks were calculated in the same way but I assumed that chicks had a higher lower critical temperature than adults (Tk = 6°C rather than 2°C). These 0 equations can only estimate the change in thermoregulatory costs below T,  The  influence of wind within the thermal-neutral zone was estimated as 1.1 x and 1.1 5x RMR for adults and chicks respectively (Wijnandts 1984). Metabolic rate estimates are summarized in Table 4.1.  Limits of chickfat stores  Energy stores are the nutrients accumulated by an animal which help it to survive periods of energy shortage. Energy can be stored as fat, carbohydrate, or protein (vander Meer and Piersma 1994). However, protein is viewed as an energy store used only in emergencies because it typically constitutes the tissue necessary for normal functioning (references in vander Meer and Piersma 1994). I therefore assumed that fat was the most  critical energy store. The maximum and minimum fat stores carried by glaucous gull chicks  81  Table 4.2 Estimates of Resting Metabolic Rates (RMR; kJ/h) for a glaucous gull adult (171 5g) and chick (900g) in relation to weather conditions. Weather categories refer to the conditions simulated in the model. See Methods further details.  Chick  Adult Weather*  Day  Night  Day  Night  Calm  53.6  61.2  41.4  51.6  Windy  56.0  77.9  47.6  65.2  Storm  77.9  86.6  65.2  72.1  *  Calm  <  5 km/h; Windy  =  25 km/h; Storm-day  =  -2C, 25 km/h; Storm-night= -8C, 25km/h.  82 were estimated based upon the fat stores found in other gull species (i.e. as a proportion of total body mass). The fat stores of adult lesser black-backed gulls (Larusfuscus) ranged from 1-12% of total body mass (Sibly et al. 1987). Similarly, the range in weights of herring gulls over a year was approximately 9% of upper body mass (Coulson et al. 1983). Herring gulls in northern England maintained fat stores which ranged between 62-lO6g or 611% of body mass (Sibly and McCleery 1985). Based upon these findings, I estimated that the upper limit of fat stores that a gull chick could carry (x,) was 15% of total body mass (135g). This proportion is higher than for adult gulls because chicks are not constrained by the low weight requirements of flight. In the model, a three chick brood with an average mass of 900g could thus carry a maximum of 405g of fat or 14985 Id of energy given an assimilation efficiency of 37.7-39.7 kJg of lipid reserve (Johnston 1970). The lower minimum fat store  (Xmin)  was estimated as 3% of body mass, or 342 U per chick. I made  the simplifying assumption that fat stores were depleted linearly during fasting; this is nearly the case among fasting herring gulls (Spaans 1971). Thus, a three chick brood that entered a fasting period with maximum stores  (xmax)  could survive for approximately 4.5 days under  calm thermal-neutral conditions given my estimates of RMR (Table 4.1).  Flight energetics  The cost of level flapping flight was estimated using the equation provided by Pennycuick (1989): 2(spv)+o.5pv SbCdb+l.2Pamj+E+Pjb} (10) *g) / Cf= 1.1 [l.2(M 2  where M is body mass in kilograms (=1.75 1 ± 0.23 kg n =9 birds), g is acceleration due ,  , Sd = wind disc area in square meters, p = air density at sea level, v = mis ) to gravity (9.8 2 airspeed (mis), Sb body frontal area (in square meters), Cdb = drag coefficient of the body, Pam  is the absolute minimum power (JIs), E = metabolic efficiency, 0.23; Pennycuick 1989),  ). The cost of flight in mechanical units (W) was 723 and jb = basal metabolic rate (3.73M°  then converted to its metabolic equivalent (kJIh). A 1715g glaucous gull flying at its  83 maximum range speed (the velocity at which maximum distance is traveled per unit power, Pennycuick 1989) using flapping flight predicted an energy expenditure of 29.6 W or 106.6 kJ/h under calm wind conditions (Pennycuick 1989). This estimate closely approximates the 108 kJ/h predicted from the equation, logy =l.80+0.679logx  (11)  which was derived from activity-specific doubly labeled water studies of six northern seabird species foraging at sea (Birt-Friesen et al. 1989). The minimum power velocity (Vmp=the velocity at which flapping flight is most energy efficient) was calculated as 23.5 W or 84.6 kJIh given the above morphology. I estimated that gliding required approximately 2.1 xBMR, which is roughly equivalent to estimates of power required to support the body mass of birds on outstretched wings (Pennycuick 1989). This multiple of BMR is similar to 2.4 xBMR measured for herring gulls gliding in a wind tunnel (Baudinette and Schmidt-Nielsen 1974) and for free-ranging herring gulls whose heart rates when gliding were 1 .3x their heart rates at rest (i.e. RMR; Kanwisher et al. 1978). This provides and estimate of 64.4 kJ/h when gliding for a 1715g glaucous gull. The energetic cost of hovering was estimated as lix BMR for a gull hovering under calm wind conditions.  Energy consumption I estimated the rate of gross energetic gain ingested (GET) for each foraging mode by monitoring the rate at which individually marked birds obtained food items (e.g. eggs, fish). Thick-billed murre eggs at Coats Island average iOOg wet weight (deForest 1993). Most egg contents are ingested by glaucous gulls once the shell had been cracked with the bill. I estimated, however, that gulls spilled approximately 1 5g from most eggs. The energy 1 wet weight (Spear 1992) content of fresh common murre eggs (Uria aalge) is 9.08 kJgwhich provides 771.8 kJ. I applied this same value to thick-billed murre eggs and then assumed a digestive assimilation efficiency of 0.85 for fresh eggs (Dunn 1976; Spear 1993;  84 Young 1994). Gulls also scavenged discarded fish (mean mass 11 g wet weight) and abandoned murre eggs at the colony, and I estimate that scavenged fish yielded a gross energetic value of approximately 4.4 kJg (Dunn 1976; Fumess 1981; Spear 1993; Young 1994). I assume a lower digestive assimilation efficiency of 0.70 for scavenged material (Young 1994).  Foraging mode energetics and risk ofcontact with murres The hourly energetics of each foraging mode i, reflected the number and characteristics of the attacks that occurred, their probability of success  (A), the metabolizable energy gained  (/3), and the energetic costs of the search and attack activities for the adult during that time (q). As discussed below, these values often varied with wind conditions. Adult gulls often loitered on or near their nesting ledges and were assumed to lose energy at their daytime RMR of 53.6 kJh and 56 kJ/h during calm and windy conditions respectively (Table 4.1). When adults were inactive, chicks were not provisioned and were also assumed to lose energy at their daytime RMR (Table 4.1). The energetic costs of the stand foraging mode included both the costs of standing activity during search and attack, and the short exploratory flights between murre nesting ledges (Table 4.2). Kanwisher et al. (1978) found that the heart rates of herring gulls increased by approximately 20% during aggressive interactions between conspecifics. A similar physiological response likely occurs among glaucous gulls attacking thick-billed murres. Thus, I assumed that persistent attacks made on foot required 1.2 xRMR. During each hour of stand foraging, glaucous gulls often visited several murre ledges. The flights between ledges amounted to approximately 10 mm of flight each hour under windy conditions (Table 4.2). I combined the estimated costs of both standing (53.6 kJfh) and flight (84.6 kJ/h calm, flapping; 64.9 kJIh windy, gliding) and integrated these with the time allocated to each of these activities per hour. This provided an overall energetic estimate of 55.6 kJIh and 58.1 kJ/h under calm and windy conditions respectively. While stand  85  Table 4.3 Proportion of foraging time devoted to flight in relation to foraging mode and wind conditions (a) calm <5 km/h, b)> 10 km/h).  % Total foraging time Foraging mode  b)  *  x (SE)  x (SE)  Hovering x (SE)  (2.1)  2 (0.2)  0 (0.0)  14  (3.6)  4 (0.6)  2 (0.3)  Flapping flight mode Gliding flight mode#  85  (8.5)  8 (1.7)  6 (1.3)  --  --  --  --  Stand foraging Scavenge atcolony Flapping flight mode*  4  (1.3)  0 (0.0)  3  (0.7)  10 (2.1) 6 (1.1)  --  --  5  (0.2)  Gliding flight mode #  Gliding  6  Standforaging Scavengeatcolony  a)  Flapping  Gulls could  --  --  --  91 (5.6)  not patrol the colony using gliding flight under calm conditions  Gulls rarely used flapping flight during windy conditions at the colony  3 (1.9) --  --  4 (2.0)  86 foraging, marked individuals had a mean attack rate of approximately 4 attacks/h (± 2.6; 8.2h). For gulls in the general population, each stand attack had a 46% chance of success (ch. 3), so that for each hour of stand foraging activity, gulls had approximately a 1.8 chance of successfully obtaining a single egg (i.e. 0.9 probability of obtaining two items). Gulls had a 0.32 probability of being severely struck by defending murres during each attack so that gulls were typically struck on average 1.3 times each hour while foraging (Table 4.4). Wind conditions did not influence these probabilities. The energetic costs of scavenging on foot included foraging on foot and short flights between cliff ledges, and I estimate an energetic cost of 67.7 kJ/h and 62.8 kJ/h during calm and windy conditions respectively. This is similar to the energy requirements of the stand foraging mode minus the costs of attack. However, scavenging gulls took more short flights within the colony (Table 4.2). At Coats Island, scavenging held a 0.6 probability of a gull finding a single food item during one hour of foraging activity (n=4.8 h). The ratio of food items obtained while scavenging by the general gull population was approximately 8 fish for each murre egg ingested. This yielded a mean energetic gain of 61 U/item when scavenging. However, scavenging held little risk from murre contact because most searching activity occurred at the base of cliffs or on large ledges free of nesting murres where colony debris collected. Wind did not alter these probabilities for scavenging gulls. The energetic costs of the flapping-flight foraging mode included the flight costs of aerial search patrols and of hovering aerial attack. I assumed that gulls were flying at their minimum power velocity rather than their maximum range velocity when foraging at the colony. A slow and energy-efficient flight speed is expected for birds searching for concealed prey in a localized area (Gendron and Staddon 1983), and it was obvious that patrolling glaucous gulls flew more slowly than gulls flying to their nest or out to sea. The ffight energetics model of Pennycuick (1989) estimated an energetic expenditure of 84.6 kJfhour for a 1715g glaucous gull flying at its minimum power velocity under calm wind conditions. Aerial attacks under calm conditions required that the gull hovered next to the  171 f LI  0.45 FD  652 e  0.40  0.9997 1.0000 VAR  0.5 0.0 FD FD, LI  0.9999  0.2 62.8  61 s  0.40  67.2 151 .2#  0.9990  1.3 58.1  652 e  0.80  ----  1.0000 0.0  108.0#  171 f  0.45  ----  $ DAE = Digestive Assimilation Efficiency (e=murre egg; s=scavenged material; f=arctic cod) # Estimated based upon allometric equations of northern seabirds foraging at sea (Birt-Friesen et al. 1990) @ FD = Field data; U=Literaure; VAR=Variable in the model  c) Source’  Gliding flight Trip to sea  Flapping flight  b) Stand foraging Scavenge at colony  Trip to sea  ----  0.9995 0.9  89.8  652 e  0.55  Flapping flight  Gliding flight  0.9999  0.2  62.7  61 s  (prob./hour)  (Prob. of contlh)  0.40  (kJ/h)  0.9990  ) 5 DAE  1.3  *  55.6  (kJ/food item  Survival ()  Murre contact  652e  (Prob. of two items/h)  Energetic cost (q,)  0.80  mode (i)  Gros energetic gain (j3)  a) Stand foraging Scavenge at colony  Foraging  Foraging success (A)  Table 4.4 Parameter estimates of glaucous gull foraging mode energetics and danger in relation to wind conditions (a) calm; b) windy; c) source of estimate. Murre contact refers to the probability of a gull being seriously struck by murres during one hour of foraging activity.  88 murre nest site. These hovering attacks were rarely maintained for more than six seconds under calm conditions (ch. 3). Individually marked gulls had a mean attack rate of 6 attacks/h (± 3.4; n=2.67h) using flapping-ifight under calm conditions. In the general gull population, flapping ifight attacks had a 0.19 probability of success and a 0.16 probability that the gull was struck by defending murres (w=572). Thus, for each hour of flapping flight foraging activity, gulls had a 0.55 probability of successfully obtaining two food items and a 0.9 probability of serious contact with defending murres (Table 4.3). Under windy conditions, gulls rarely used the flapping flight mode and I therefore had insufficient data to estimate these values for windy conditions (Table 4.3). The energetic costs of the gliding-flight foraging mode under windy conditions included the flight costs of search patrols and of aerial attack. However, under windy conditions, gulls glided almost continuously, even when attacking murres. I estimated that gliding foraging required 64.4 kJIh for a 1715g gull (2.1 xBMR). Individual gulls had a mean attack rate of 11 attacks/h (± 5.6; n=6.7 foraging hours). Each attack had a 0.08 probability of success and a 0.049 probability of being struck by defending murres (n=1551). Thus, for each hour of gliding flight foraging activity, gulls had a 0.85 probability of success and a .054 probability of contact with defending murres (Table 4.3). Gulls could not glide extensively when patrolling under calm wind conditions due to the constraints of flight dynamics (Pennycuick 1989; ch. 3), so gliding was excluded from the model as a foraging option for gulls during calm conditions (Table 4.3). The energetic gains and costs of glaucous gulls foraging at sea are uncertain. Little is known about the distribution of fish at sea around Coats Island or how the availability of fish for gulls varies with season, ice, or weather conditions. Based upon observations of regurgitations to chicks and of crop contents, gulls foraged primarily on Arctic cod (Boreogadus saida ) when at sea. Foraging trips averaged three hours away from the colony(± 1.3; 42 trips; n=8 birds). I used equation 10, to obtain an estimate of 108 kJ/h under calm wind conditions for a 171 5g gull. During windy conditions, the cost of foraging  89 at sea was 40% higher for black-legged kittiwakes in the Arctic (Gabrielsen et al. 1987) and I use this value for glaucous gulls. Young (1994) found that the foraging success of skuas at sea in Antarctica was not influenced by strong gales. Similarly, I found that glaucous gulls returned consistently with large fish loads regardless of weather conditions at sea. I therefore assume that the probability of a gull finding fish during a trip to sea was 0.9 regardless of wind. The prey load obtained from a trip to sea was estimated as 137 grams of Arctic cod. This load is approximately 8% of gull body mass which is consistent with fish loads of other large gull and skua species (Furness and Hislop 1981; Spear 1993; Young 1994). This yields a gross energetic gain of 171.1 id/h for a three hour foraging trip assuming that the gull was successful (Table 4.3).  Modeling risk offatal injury In this model, the probability of contact with murres while foraging (Table 4.3) was used as an index by which foraging modes could be ranked in terms of danger. Thus, the stand foraging mode held the highest degree of risk of fatal injury; scavenging and foraging at sea the least (Table 4.3). Tn the model, the parameter c was varied so that adult foraging mode selection could be estimated in the presence or absence of risk of fatal injury. Thus, when the model was run with no risk (i.e. x=1), gulls were assumed to select foraging modes that simply maximized the rate of net energetic gain. As risk increased (CL<l), the model selected the foraging mode which maximized expected fitness by maximizing the trade-off between the survival of the current brood (via provisioning) and the adult.  90 RESULTS AND DISCUSSION  Foraging mode selection with no risk of injury To model foraging mode selection under no risk of injury, o was set to one. Thus, the optimal foraging mode was selected based upon energy considerations alone. Under calm wind conditions, the model selected the stand foraging mode which provided the most reliable and sizable energetic gains per hour. Alternative foraging modes such as flapping flight, foraging at sea, and scavenging were not selected (Fig. 4.2b). Under windy conditions with no risk of injury, the gull also selected the stand foraging mode only (Fig. 4.3a). Other potential foraging modes which included gliding, scavenging and trips to sea were not selected. The model predicted that foraging activity under windy conditions should occur at chick energetic states higher than predicted for calm conditions. In other words, gulls would be expected to forage more and maintain their broods at higher energetic states under windy conditions, simply because the costs of thermoregulation are higher under windy conditions (Table 4.2). To summarize, if all foraging modes held little risk of injury so that foraging decisions were based upon energy considerations alone (c=l), gulls should select the stand foraging mode regardless of wind conditions (Fig. 4.2b, 4.3b). Thus, foraging mode should not vary with changing wind conditions, even though energetic demands are higher during windy conditions (Table 4.2). However, most gulls did vary their foraging mode selection as wind conditions changed (ch. 3). Thus, changes in gull foraging patterns observed under varying wind conditions were not simply the response of gulls to changing energetic demands imposed by weather.  Foraging mode selection with risk of injury Thick-billed murres aggressively defend themselves against gull attack, and although I  never witnessed a fatality of an adult gull, it was not uncommon to observe gulls with bloodied faces and legs following aggressive interactions with murres. Further,  ________________  91 Figure 4.2 a, b Gull foraging mode selection under calm wind conditions in relation to time, brood energy reserves, and risk of injury (a) no risk, b) risk). Hyphenated strategies refer to mixed foraging strategies. DO NOTHING = Inactivity; SCAV=Scavenge; SEA=Forage at sea; STAND = Forage on foot; FL = Foraging using flapping flight. -  night RISK  x max  a)  DO NOTHING  DO NOTHING  SCAV DO NOTHING  SCAV DO NOTHING  -  /  -  J.  SEA  FL  C’)  ci)  ci) Cl) ci)  x mm  STAND  STAND  >  c,)  x max  NO RISK b)  ci) C)  -c C-)  DO NOTHING  STAND  x mm T  Time (hours)  92  Figure 4.3 a, b Gull foraging mode selection under windy conditions in relation to time, brood energy reserves, and risk of injury (a) no risk, b) risk). Hyphenated strategies refer to mixed foraging strategies. DO NOTHING = Inactivity; SCAV=Scavenge; SEA=Forage at sea; STAND = Forage on foot at colony; FL = Foraging using flapping flight at colony; GLIDE = Glide foraging at colony. -  RISK  xmax  I  xmin  NO RISK  x max  x mm T  Time (hours)  93 several fully-grown gull chicks were blinded and killed when they fell into densely occupied murre nesting ledges (Donaldson, pers. comm.), so the potential of fatal injury exists. This model was built to explore whether this potential was high enough among adult gulls to influence their foraging activity and provisioning strategies. To simulate foraging mode selection under risk of injury, the probability that gulls would survive an attack (x) was lowered to reflect the relative risks of contact associated with each foraging mode (see Methods). Therefore, the optimal foraging mode was selected based upon both the energetic gain for the brood, and potential risk of injury for the adult while foraging. This generated predictions that were in sharp contrast to the foraging decisions made under energy considerations alone. Under calm wind conditions with danger, the model predicted that gulls should select a variety of foraging modes depending on the energetic state of their brood (Fig. 4.2a). For broods with high energy stores during calm conditions, gulls should do nothing or scavenge at the colony (Table 4.4). At brood energy stores below 50% of maximum reserves  (Xmax),  the model predicted that gulls should leave the murre colony to forage at sea. However, scavenging and trips to sea both yield lower net energetic gains compared to flapping-flight or stand foraging at the colony (Table 4.4). Under windy conditions, the model predicted that gulls should switch to the gliding flight foraging mode for brood states 8% xmax <x(t) <65%  Xmax  (Fig. 4.2a). Trips to sea  and scavenging are not selected. Under low brood energy stores (x(t) <8%  xmax),  the stand  foraging mode is selected. However, this should be rare under windy conditions, because gliding-flight yields energetic gains sufficient to meet the energetic demands of the brood (compare Tables 4.2 and 4.4). In summary, the model predicts that gulls foraging under risk of injury should not select modes which maximize rates of net energetic gain unless brood energy stores fall to near-critical levels. This prediction holds for both wind conditions and is in sharp contrast to the provisioning strategies predicted for gulls foraging under low risk of injury (see above).  94  Comparisons with field data of guilforaging behaviour The model generated two distinct foraging strategies based upon the degree of danger associated with foraging mode decisions. Further, these two strategies were marked by strong differences in the effects that wind had on them. Under low risk of injury, the model predicted that gulls should select the stand foraging mode regardless of wind conditions. In contrast, gulls foraging under risk of injury are predicted to spend a greater amount of time at sea or fasting under calm conditions, and much of their time glide-foraging during windy conditions. How do these predictions compare with observations of glaucous gulls foraging in the wild? To address this question, I studied the affects that sudden wind change had on foraging mode selection of gulls in the wild. In the context of the dynamic model, gulls move from one decision array to another following a wind change (Figs. 4.2 a,b and 4.3 a,b). For example, if wind increased, the model predicted that gulls foraging under risk should switch synchronously from loitering, scavenging, or foraging at sea to the gliding flight mode if their broods fell below 60% of Xmax (Fig. 4.2a to 4.3a). Similarly, if gulls were foraging using gliding flight and the wind dropped below 10 km/h, a synchronous switch to inactivity, scavenging, or absenteeism from the colony is expected. In contrast, the model predicts that gulls foraging under low danger should not switch foraging modes with a wind change, because stand foraging is always preferred (Fig. 4.2b and 4.3b). On 6 occasions during the years of this study, my assistants and I monitored gull foraging activity continuously for several days in relation to wind conditions. As predicted, both aerial search and attack activity increased immediately when wind conditions increased following extended periods of calm (ch. 3). During calm conditions, attacks made on foot or from flight were initially infrequent. As calm conditions persisted beyond 14 hours, attack frequency using flapping flight or stand foraging modes gradually increased. The model suggested that this gradual increase in foraging activity would be expected if parents were  95 responding to the worsening energetic states of their chicks. To test this prediction more rigorously requires that adult foraging decisions, chick energetic state, and wind conditions are monitored simultaneously. This is a challenging undertaking because it requires that the adults that are captured and marked also nest on accessible cliff ledges. More importantly, it requires that the energetic states of chicks are monitored on a fine time scale in a way that minimizes disturbance to both gull chicks and the murres nesting around them. This work was beyond the scope of this thesis.  Although the foraging behaviour of the general gull population was similar to that predicted for gulls foraging under danger, marked individual variation existed among gulls (Figs. 4.4, B l-B6). The majority of marked birds (6 of 8) exhibited a diverse foragingmode repertoire which included inactivity, scavenging, trips to sea, and both stand and aerial foraging. Their attack mode selection also varied with wind conditions, so that aerial attacks predominated under windy conditions. In contrast, 2 of 8 birds showed a consistent preference for stand attack modes regardless of wind conditions (Fig. 4.4 B 1, B2). I observed that these two gulls attacked murres by pulling them off their nest sites by the wing or tail, and they usually did this without being struck by murres. Thus, these gulls used an attack technique which apparently decreased the risks associated with foraging on foot. As predicted by the model, the time allocated to foraging among such foot specialists did not vary significantly with wind conditions (Fig. 4.5), while aerial specialists spent significantly more time away from the colony under calm conditions, and significantly more time foraging on the wing at the colony under windy conditions (Fig. 4.5). These patterns of foraging behaviour are in general qualitative agreement to the two foraging mode patterns predicted by the model. Thus, individual variation observed within this gull population could be partly explained by the differences in how individuals respond to the risk of injury while attacking murres. Among avian predators breeding at seabird colonies, some individuals commonly travel further for small energetic rewards compared to the resources available to them at  96  Attack mode selection of 6 glaucous gulls (Bird 1 Bird 6), in relation to  Figure 4.4  -  wind conditions (calm <5 km/h; windy> 10 km/h). Attack modes include: 1- stand foraging; 2 aerial lunge; 3 pull murre off site while standing; 4 drop into murres from -  -  -  above; 5 ascend aerially from the ocean and lunge into murres; 6 hover harass from flight; -  -  7 descend aerially from the ocean and lunge into murres; 8 pull murre off site from flight; -  -  9 circle and hover harass from flight; 10- descend from above and harass. Note that birds, -  B 1 and B2 attacked murres using stand foraging modes regardless of wind conditions.  ________________________  97  100’  100’  —  B1 WIND  Bi CALM 75’  75.  50  50’  25  25’  0’  0’  —  1  2  3  4  5  6  7  8  9  —  1  10  2  3  4  5  6  7  8  B2 CALM (  10  100’  100’ C.)  9  B2 WIND  75.  75.  50’  50’  25’  25’  0 0. 0 0’  0•  —.  1  2  3  4  5  6  7  8  100’  9  83 CALM  75.  50’  50’  25’  25’  r,fl  ..  2  3  4  5  6  3  4  5  6  7  8  9  10  83 WIND  7  0’  -  1  2  100’  75.  0’  .  —  1  10  7  8  9  10  Foraging mode  1  2  3  4  5  6  7  8  9  10  98  100’-  100  B4WIND  B4CALM  75  75.  50  50’ 25-  on...  .fl  1  6  345  2  7  8  910  B6WIND  75.  75.  50-  50’  25-  25-  0  0-— 1  .  .  2  3  4  5  El  ri 6  7  8  100-  01  10  9  85 CALM  75  50  50’  25-  25 —  1  2  3  4  5  6  7  8  100  75  0-  6  86 CALM  C 0 0  3  -___  5  100-  100•  ‘€  2  1  78910  4  9  10  B5 WIND  —  r—i  6  7  F1r,  .  2  3  4  5  6  7  8  9  10  1  Foraging mode  2  3  4  5  8  9  10  99  Figure 4.5 Gull time budgets in relation to wind conditions and foraging mode specialization. (*) refers to a significant difference in the time devoted to an activity under windy and calm conditions (t-test, paired comparisons, P<O.05).  2 a-  0 0.  C 0  ‘6  -o  0)  4-  a) E  0’  20  40  60  80  Tr  AERIAL  LOllER  STAND FOR AERIAL. FOR  z= 1 flra..  Behavioural categories  ABSENT  -r  *  0  20  40  60  80  T  STAND  STAND FOR AERIAL FOR  Behavioural categories  LOllER  J]j ABSENT  T  D  CALM WIND  C  C  101 colonies (e.g. Southern and Southern 1984; Watanuki 1989, 1991; Spear 1992; Young 1994). This again suggests that the economics of alternative foraging behaviours differ between individuals. For some individuals, high risk of injury while foraging at the colony could increase the relative benefits of foraging elsewhere. A danger-reward trade-off may also explain why large males are typically the individuals who specialize on seabird prey (Parsons 1971; Watanuki 1989; Watanuki 1991; Spear 1993). Being large may dilute the risk of injury during attack. However, there is also likely a correlation between low risk of injury, killing ability, and the ability to ingest large seabird prey; all of which may increase with bill size (Harris and Jones 1969; Watanuki 1989). Although risk of injury is just one factor influencing foraging strategies of avian predators, my findings suggest that it contributes to the behavioural variation observed among individuals foraging in the wild.  Further predictions  Why do most gulls at Coats Island forage under the constraints of murre defence and calm wind conditions while a minority appear to be able to obtain murre eggs and chicks at will? A similar dichotomy exists in other avian predator populations (Watanuki 1991; Spear 1992; Young 1994). Perhaps the reward-danger ratio of foraging modes change as individuals improve their foraging performance with experience. For example, learning the subtleties of attack could help glaucous gulls overcome murre defenses more efficiently, and this would enhance the profitability of the more productive but risky modes (e.g. foraging on foot). The time and experience probably required to learn how to overcome prey defences probably ensures that individuals within a long-lived population differ in their foraging abilities at any given time (Fig. 4.4). For example, it is likely that young glaucous gulls forage under greater risk than adults when preying on murres. If this is true, the model predicts that young birds should use a variety of foraging modes under both calm and windy conditions (Fig. 4. la, 4.2a). Thus, young birds should use modes which carry low risk of injury and low energetic gains (e.g. scavenging, foraging at sea, gliding flight). If learning  102 occurs, foraging mode repertoire of individuals should shrink with age as they become more adept at attacking murres. In fact, the oldest and most experienced gulls should forage almost exclusively on foot (Fig. 2a, 2b), and consequently, escape the constraint of calm wind conditions (ch. 2, 3). Therefore, learning to improve foraging efficiency could enable glaucous gulls to increase their reproductive success without necessarily increasing the costs of reproduction. An improvement in foraging efficiency has been invoked to explain how older gulls can achieve higher reproductive success without increasing their energetic expenditure (Reid 1988; Pugesek and Wood, 1992; Pugesek 1995). My model also generated predictions on how gulls might differ in their foraging success and mode selection at colonies with lower inherent risks. At Coats Island during the years of this study, the colony was increasing in size so that murres were nesting at very high densities. Indeed, most cliff ledges were completely occupied by brooding murres and the risk of contact with murres when foraging on foot was high (ch. 2, 3). If a murre colony were to decline suddenly following a perturbation (e.g. oil spill, gill-netting by-catch, or an era of over-hunting), murre nesting densities on ledges and/or the proportion of ledge area occupied by brooding murres would decline (Birkhead 1977). Under both circumstances, gulls should overcome murre defences more easily (Spear 1992; Siegel-Causey and Hunt 1981; ch. 2, 3). If this occurred, the model predicts that a higher proportion of gulls would forage on foot and thereby overcome the constraints of calm wind conditions, colony topography, and murre defence (ch. 2, 3). Consequently, the proportion of murre eggs and young lost to avian predation should increase during and following colony declines. I explore these issues further in chapter 5.  Conclusions My aim in this chapter was to integrate field data and energetic estimates of gull foraging behaviour to explore the influence that mortality risks have on the foraging and provisioning strategies of glaucous gulls. Previous field studies indicated that gull foraging  103 activity, foraging mode selection, and provisioning are strongly affected by wind (ch. 2, 3). There are at least two possible explanations for this. First, an increase in foraging activity during windy conditions may occur because gulls require more energy to maintain themselves and their young due to higher thermoregulatory costs. Alternatively, a trade-off may exist between the risk of injury and energetic gain while foraging, and perhaps windy conditions improve the economics of this trade-off in favor of gulls. The model suggests that the first explanation, which is based upon energy considerations alone, is not sufficient to explain the observed patterns of foraging activity. However, the model supports the idea that glaucous gulls are very sensitive to risk of injury while foraging. Gulls at Coats Island face higher risks of contact with murres when foraging under calm wind conditions (ch. 2, 3), and this dynamic model predicts that under calm conditions, gulls should select low-danger modes that provide low to moderate energetic gains (e.g. do nothing, scavenge, forage at sea). A general feature of the results is that gulls can afford to use foraging modes that yield low energetic gains relative to more productive and dangerous ones, because even poor foraging modes are sufficient to meet their energetic demands under most circumstances. In addition, poor foraging conditions in the wild (i.e. calm wind conditions) are usually short-term in relation to the energy stores that are typically maintained by large gulls (Spaans 1971; Coulson et al. 1883; Sibly and McCleery 1985).  104  CHAPTER 5 EFFECTS OF GLAUCOUS GULL PREDATION AT DECLINING THICK-BILLED MLJRRE COLONIES: AN INTER-COLONY COMPARISON  Many prey species have evolved adaptations which decrease their profitability as prey by increasing the risks of injury for the predators attacking them (e.g. toxicity, defensive weapons, aggressive group defense; Edmunds 1974; Endler 1986; Sih 1989). Thus, the value of a prey should increase for a predator as the risk of injury for the predator declines. Consequently, if the effectiveness of a prey’s defence depends on large group size, (e.g. dolphins, Norris and Dohl 1980; muskox, Gray 1974), predators may have an increasing impact on prey numbers as prey populations decline. Such predator-prey dynamics may apply to colonial-nesting seabirds that breed in association with avian predators. The effectiveness of group defense often increases with nesting density (Hatch 1970; Birkhead 1977; Gotmark and Andersson 1984), and avian predators respond to the dangers generated by these defensive behaviours (Spear and Anderson 1989; Spear 1993; Young 1994; Thiel and Sommer 1994). For example, gulls (Larus sp.) are highly selective when attacking the nest sites of cliff-nesting murres (Uria sp.). They avoid dense nesting aggregations and preferentially attack birds nesting alone or on the edge of groups, apparently because they can forage without being struck by defending neighbours (Birkhead 1977; Spear 1993; ch. 2, 3). Because most avian predators do not attack seabirds nesting at high densities, most of a breeding colony is typically safe from predation (Spear 1993; Young 1994). Consequently, avian predation has only a minor impact on seabird reproduction at most colonies (Siegel-Causey and Hunt 1981; Spear 1993; Young 1994; ch. 2, 3). If nesting densities of seabirds declined however, predation should have a greater impact on seabird reproduction because avian predators could overcome the constraint of group prey defence (ch. 2, 3). This prediction has conservation implications for the recovery of heavily harvested. seabird colonies, or those reduced in size by natural catastrophes.  105 To examine the relative impacts of avian predation at increasing and declining seabird colonies, I compared glaucous-gull (Larus hyperboreus) predation at thick-billed murre (Uria lomvia) colonies in the Canadian and Greenland Arctic. Glaucous gulls are the primary avian predator of thick-billed murre eggs and young in the Arctic. I compared gull predation rates, foraging behaviour, and thick-billed murre nest site selection at an expanding colony (Coats Island, Canada) with declining colonies in the Upernavik region of Greenland. These comparisons tested: 1) if gulls were more successful when stealing eggs and young at declining colonies, 2) if murre nesting densities and group structure on breeding ledges were altered as colonies declined, and 3) how/if the number of breeding gulls changed at declining colonies.  METHODS Study sites I worked at two field sites. The first was at the north eastern tip of Coats Island, Northwest Territories, Canada (1990-1992). See chapter 1 and 2 for further details. The second site was in the southern Upernavik region of Greenland at the Kingittoq (5625 breeding pairs) and Timmiak (175 breeding pairs) colonies. I carried out behavioural observations of gulls and murres at Kingittoq, and visited Timmiak once to census the colony. A commercial harvest of murres by the community of Upernavik in the 1980’s substantially reduced the murre populations at these colonies (Evans 1984; Kampp et al. 1994). Although this commercial hunt ceased in 1988, these colonies have not recovered and hunting for personal use continues in the early spring (Falk and Durinck 1992; pers. obs.). At both study sites, weather conditions were generally moderate during my studies and wind conditions were often below 10 km/h (Fig. 5.1), and periods of calm conditions (>2 days), commonly occurred.  106 Figure 5.1 Wind conditions at Coats Island (1990-1992) and Kingittoq (1993) colonies.  50 King ittoq  40  30  20  a) E 4-  10•  0 4-.  ct5 G) Co  00-4  -  0 0  J  5-9  10-14  15-19  I  20-24  >25  50  Coats 40  30  20  10•  0• 0-4  5-9  10-14  15-19  Wind speed (km/h)  20-24  >25  107 Gullforaging behaviour and predation rates Behavioural observations of gull-murre interactions were carried out daily from concealment from blinds at Coats Island (1990-92) and from behind rocks at Kingittoq (1993). For each gull attack, I recorded the following: 1) gull foraging mode (aerial flapping flight, aerial gliding ifight, stand foraging); 2) murre nest site characteristics (narrow ledge high nesting density, narrow ledge low density, broad ledge high density, broad ledge low density, and cave/crevice), and 3) outcome of the attack (egg/chick taken or not). See chapters 2 and 3 for definitions of nest sites and foraging modes, and other details relating to methodology. Wind conditions on the cliff were monitored with a computerized Digitar anemometer at Coats, and a hand-held anemometer at Kingittoq. I used analysis of covariance to explore factors affecting foraging mode selection by gulls at Coats and Kingittoq colonies. Colony location (Coats vs. Kingittoq), wind conditions (continuous variable), and the interaction colony x wind were included in the model. I analyzed the stand foraging mode only because stand and aerial proportional data were not independent (i.e. they both combined to make 100%). I used analysis of covariance to examine factors influencing gull attack activity. Colony identity, ledge width, wind conditions, colony x ledge width, and colony x wind were included in the model. All proportional and rate data were arcsine transformed prior to analysis.  The population-level response of glaucous gulls to murre population declines Predator foraging efficiency and reproductive success may fall as a predator’s primary prey decline (Sinclair 1989). Consequently, the impact of glaucous gull predation should remain constant regardless of colony state assuming that the numbers of gulls present at murre colonies declined in parallel. However, it is more likely that gull numbers would decline more slowly than those of murres, particularly if colony declines increased the vulnerability of murre nest sites to predation. If this were true, a higher ratio of gulls to murres would be predicted at declining colonies over the short term.  108 I studied the numerical relationship between glaucous gull numbers and murre colony size using photographs of the number of gulls present at Coats and the Upernavik colonies, and using information of gull and murre numbers in the literature (App. I). I used analysis of covariance to examine the numerical relationship between gull and murre numbers in relation to colony state (stable at Coats vs. declining at Upernavik). Colony state, murre numbers, and the interaction between colony state and murre numbers were included in the model. Numbers of gulls and murres were log-transformed prior to analysis.  Murre nest site selection and breeding density I photographed each colony from the sea during mid July and then counted the murres on the cliff face from black and white prints. The numbers of birds present on the cliff were multiplied by a correction factor of .75 to estimate the number of breeding pairs (following Nettleship 1976). From these photographs, I also quantified the proportion of murres breeding on the various nest types. For definitions and characteristics of murre nest site characteristics, see ch. 2. I examined how the magnitude of colony decline, nest site characteristics, and the interaction between colony state influenced the use of each type of nest site using ANCOVA (i.e. the proportion of each colony nesting on each nest type). Because only 4 of the 5 proportions could be considered independent, I only included 3 of the 5 characteristics in the model to maintain independence (cave, broad high density, and narrow high density).  109 RESULTS Gullforaging mode selection, attack activity, and predation rates Gulls at Coats and Kingittoq used different foraging modes (Fig. 5.2 a, b; ANCOVA, F 6 =  11.6, P  0.014). Gulls at Kingittoq frequently attacked murres on broad ledges on foot  even under windy conditions (Fig. 5.2b). However, the proportion of aerial attacks by gulls at Kingittoq increased with wind speed (5.2a), which implies that gulls still benefited from foraging on the wing. In contrast, gulls at Coats Island mostly attacked from the air even during calm conditions (Fig. 5.2). Therefore, the greatest differences in foraging modes between gulls at the two colonies occurred at low wind speeds (<10 km/h). The influence of wind, however, was not quite significant (F 1,6  5.5, P  =  0.057).  Gull attacks were more frequent at Kingittoq colony, particularly under calm conditions (Fig. 5.3a). Gulls at Kingittoq attacked murres on broader ledges than gulls at Coats Island at all wind speeds. At Coats Island, broad ledges were densely occupied by murres and there were few opportunities for gulls to forage on foot (ch. 3). Instead, gulls at Coats relied heavily on aerial attacks (Fig. 5.2). Consequently, gull attack activity and foraging success increased with wind speed at Coats Island (Fig. 5.3) when windy conditions increased their aerial maneuverability and enabled them to attack weakly defended narrow ledges (ch. 3). Thus, 55 F attack activity was significantly influenced by wind (ANCOVA, 1 ledge width (F  1,3455  16.28, P <0.001), and colony identity (F  =  16.15, P  13455 =  <  13.59, P  0.001), =  0.001). There was also a significant interaction between colony identity and ledge (F  =  6.88, P =009), which supports the idea that gulls attacked different ledge types at the two colonies. The idea that risk of contact with murres varied between the two colonies is also supported by the observation that gulls at Kingittoq ingested eggs on the nesting ledges, while gulls at Coats typically carried murre eggs to un-occupied ledges above the colony.  To  summarize, attack activity at Kingittoq was consistently higher than at Coats, particularly under calm wind conditions when gulls at Kingittoq could forage on foot on broad ledges.  110  Figure 5.2 Attack mode selection of glaucous gulls in relation to wind conditions and colony (a) Aerial foraging, b) Stand foraging).  100  a)  -  -  0  -  --  .- -  0  ..--  80  .  0- -  60 .$...  /  40•  1• 20  ----0”  -  *  Coats Island Kingittoq  C)  00  •  I  I  30  20  10  D  100 b) C  80  60•fr  —  40-  ..0.  20-  -...-...--.. • -.  - 0’ -  •0  00  I  •  10  Wind speed (km/h)  I  20  30  111 Figure 5.3 Glaucous gull attack activity in relation to cliff ledge width (a) broad, b) narrow), wind speed, and colony (i.e. Coats Island, Canada, and Kingittoq, Greenland). Values are off-set for clarity. 0.5  0.4  0.3 U)  0.2  E 0 0 0  0.1  -c -c  0.0 0  Cl)  10  20  30  10  20  30  -  C-) -I.4-  a5  0.5  > > C)  0.4  -  C) 4— 4-  0.3  c 0.2  0.1  0.0 0  Wind speed (km/h)  112 Predation rates at Kingittoq were consistently higher than at Coats Island although they were more similar under higher wind speeds (Fig. 5.4). This is expected because gull foraging behaviour and attack rates were most similar at higher wind conditions (see above). Thus, the greatest differences in predation rates between the two colonies occurred at low wind speeds, 1 and predation rates were significantly influenced by wind (ANCOVA, F  1436 =  17.82, P =  0.001). Although mean predation rates were more than twice as high at Kingittoq than at Coats (Fig. 5.4), no significant colony effect was detected (F  11436 =  2.45, P =0.13).  In summary, gulls at Kingittoq had consistently higher attack rates and were less constrained by calm wind conditions, apparently because they could forage on foot on broad ledges regardless of wind conditions. Consequently, gull predation rates at Kingittoq were higher than at Coats Island during calm wind conditions..  Numerical response ofglaucous gull populations to murre colony declines A review of the literature suggests that there is a consistent numerical relationship between the number of breeding predatory gulls and murre colony size at stable colonies (open symbols, Fig. 5.5, Appendix I). As predicted, the number of glaucous gulls present at the declining Upernavik colonies exceeded the observed relationship (Fig. 5.5). Consequently, both murre numbers (F  1,16 =  15.97, P =0.001) and colony location (F 1,16  =  17.01, P  =0.001) had a significant influence on the numbers of gulls present at murre colonies. These results imply that a time lag exists in the population response of glaucous gulls to murre population declines. Although the 8 pairs of breeding glaucous gulls at Kingittoq foraged almost exclusively on murre eggs and chicks, it is unlikely that the other declining murre colonies entirely supported the numbers of gulls that were present. This is particularly true at the Kingittoq, Upernavik, and Timmiak colonies where high proportions of murres bred on nest sites  113  Figure 5.4 Gull predation rates in relation to wind speed and colony (i.e. Coats Island Canada and Kingittoq, Greenland). Sample sizes for each value refer to the number of half hours of observation at each wind speed. Values are off-set for clarity.  0.12 ----0--  Co  Coats Island  a) I  D  0.10  2 0  0 0  0.08  21  -c U)  a) C  153 0.04-  127  a) 0.02-  0.00  0  I  I  I  5  10  15  Wind speed (km/h)  20  25  30  114  Figure 5.5 The relationship between numbers of predatory gulls, murre colony size, and  murre colony state (i.e.Upernavk region vs. other stable or increasing murre colonies).  Other murre colonies • Upernavik region murre colonies  O  1000•  I 0  o• O  10-  .0  0 I  0 1100  I  I  I  1000  10000  100000  Murres (breeding prs)  1000000  115  that were inaccessible to gulls (see below). It is likely that some of the gulls at Upemavik were generalists who foraged at sea, on fish offal from the Upernavik fishing fleet, or at a garbage dump (10-25 km away).  The extent to which these gulls exploited the other Upernavik  colonies requires further study of their foraging behaviour and diet (e.g. analysis of pellet contents at nest sites).  Murre nest site selection Murres selected different nest sites at Coats, Kingittoq, and Timrniak. At Coats Island, most cliff ledges were densely occupied so that most murres nested at high densities on broad cliff ledges (Fig. 5.6). At the Kingittoq colony, murres were more evenly distributed over the cliff face and fewer of them nested at high densities on broad ledges as I predicted (Fig. 5.6). Guano stains on the cliff clearly indicated that empty ledges had once been occupied by murres, and this was confirmed through interviews with local Inuit. At Kingittoq, and contrary to expectation, few birds nested on broad ledges under low nesting-densities. Instead, most murres nested on narrow cliff ledges. At the Tinmiiak colony, which had experienced the greatest declines, murres nested almost exclusively on narrow ledges at high densities or in crevices (Fig. 5.6). Collectively, these results suggest that as colonies declined, murres moved from broad ledges to narrow ledges or caves. This is supported by a significant interaction between colony state and nest site characteristics (ANCOVA, F  1,6 =  11.6, P  =  0.014).  116  Figure 5.6 The % of murres nesting under 5 nest types (BH=broad ledge, high murre nesting density; NL=narrow ledge, low density; NH-narrow ledge, high density; BH=broad ledge, high density; CAVE=cave or crevice nest site), at Coats Island, Kingittoq, and Tinimiak colonies.  80  • COATS  70 > C 0 0 C)  Q KINGI1TOQ  60  TIMMIAK  50  a) 40  S 0  30 20 10 0 BL  NL  NH  BH  Nest site characteristics  CAVE  117  DISCUSSION Guliforaging behaviour and pre&ztion rates Many seabirds must nest at high densities as a defence against avian nest predators (Burger and Gochfeld 1994). Among murres, high nesting densities are particularly important on broad cliff ledges where gulls can forage on foot regardless of wind conditions (Birkhead 1977; Spear 1993; chapters 2, 3). My inter-colony comparison showed that gulls at the declining Kingittoq colony foraged more often on broad ledges and were less constrained by calm wind conditions, perhaps because population declines increased the availability of lownesting density ledges where gulls could maneuver on foot and attack murres with little risk of injury. This is supported by the observation that gulls at Kingittoq ingested eggs on the nesting ledges, while gulls at Coats typically carried murre eggs to un-occupied ledges above the colony. The ability of gulls to forage routinely on foot during calm conditions likely increases annual predation rates at colonies, because calm conditions typically restrict the ability of gulls to reach murre nest sites at stable colonies (ch. 2, 3). Indeed, at Coats Island calm periods coincided with, 1) greater absenteeism of gulls from the murre colony (ch. 3, 2) a higher proportion of fish provisioned to gull chicks (a food resource of lower caloric value than seabird chicks or eggs; Pierotti and Annet 1991; Watanuki 1992), and 3) gull chick weight loss at most nests (Gilchrist, unpubi.). Thus, the ability of gulls at Kingittoq to forage effectively on broad cliff ledges regardless of wind should enhance their chick’s growth, and hence, their reproductive success. This could help maintain high gull numbers at colonies despite murre colony declines (discussed further below). To summarize, changes in the nesting structure of colonies may influence the economics of gull foraging behaviour, and this suggests that colony declines resulting from human induced mortality of murres can alter natural predator-prey relationships at colonies.  118 Response of gulls populations to murre colony declines As predicted, the number of gulls per 1000 murre pairs present at colonies in the Upernavik region was higher than at stable murre colonies found elsewhere in Arctic and temperate regions. This result may reflect the ability of gulls to escape both the constraints of calm wind conditions and the reduced effectiveness of murre group defence. Both of these factors could enhance adult survival and reproductive success of gulls. However, the high number of gulls present at even the smallest colonies (where few murres were accessible, see below), implies that gulls in the Upernavik region also utilized food sources at sea, or in the community of Upernavik. The murre colonies closest to the community of Upernavik have suffered the greatest declines (Kampp et al. 1994), and are also nearest to alternative food sources for gulls (e.g. garbage dump, fish plant). These alternative food sources may maintain high gull numbers even as murre colonies decline. Consequently, an interaction may exist between the proximity of a murre colony to a human community, hunting intensity, and the numbers of predatory gulls present. These interactions will likely ensure that gulls will be maintained at high numbers at Upernavik and will continue to depress murre reproductive success, affect nest site selection, and perhaps prevent the re-colonization of abandoned nesting ledges. The effects of gull predation at declining murre colonies may also be complicated by feeding territoriality within colonies. Territoriality of seabird predators occurs among skuas, Catharacta sp. (Andersson 1976; Trilimich 1978; Furness 1981; Young 1994), western gulls, L. occidentalis, (Spear 1993), and slaty-backed gulls, L. schistisagus (Watanuki 1992). At the Coats Island murre colony, I also found that glaucous gulls defended feeding territories (Gilchrist, in prep.). Further, the distribution of glaucous gull nests at other Arctic colonies (Gaston, pers. corn.), as well as the consistent numerical relationship observed between gulls and murres (Fig 5.5), suggests that feeding territoriality is a widespread phenomenon in this species.  119 If I assume that the dynamics of glaucous gull territoriality are governed by constraints similar to those of raptors (Village 1982; Janes 1984; Temeles 1987; Finck 1990), I predict the following: if thick-billed murres move from broad, low nesting-density ledges to inaccessible nest sites during population declines (see Results and discussion below), glaucous gull territories should expand during colony declines. In general, declining colonies should eventually be occupied by fewer gulls that specialize on murres once murres have made the transition to inaccessible nest sites.  Murre nest site distribution at declining colonies: a consequence ofgull predation? Murres nested on different types of sites at the three colonies, after the availability of the nest types had been controlled for. At Kingittoq, a smaller proportion of murres bred on available broad ledges compared to Coats. At a colony near extinction, a greater proportion of murres bred on narrow ledges or in caves inaccessible to gulls. These results suggest that during the population declines at these colonies, murres had moved from broad ledges to narrow ledge or cave nest sites. Gull predation may explain the levels of reproductive failure on broad ledges required to establish the odd pattern of nest distribution observed at the Upernavik colonies. Because the Upernavik region colonies have experienced heavy hunting mortality in recent decades (Evans 1984; Evans and Nettleship 1985), it seems reasonable to assume that the sizes of breeding groups on nesting ledges decreased within the colony as murres were removed from the breeding population. Similar nesting patterns have been observed at other murre colonies following rapid population declines (Johnson 1938; Birkhead 1977; Ainley and Boekelhede 1990). If this occurred at Upernavik, it is likely that a greater proportion of birds would have nested on the periphery of breeding groups (i.e. a greater circumference to area ratio) where they would have been more vulnerable to gull attack (Birkhead 1977; Spear 1993; ch. 2, 3). More importantly, larger unoccupied areas on broad cliff ledges would have increased the accessibility of murre nest sites to gulls foraging on foot (Spear 1993; ch. 2). If  120 these processes occurred during the Upernavik population declines, the predator refuge provided by high nesting densities may have broken down and murres nesting on broad ledges would have experienced higher predation rates. Under these conditions, birds on broad ledges would be predicted to eventually abandon their nest sites and prospect for new ones. Assuming that these dynamics are correct, why did displaced murres not converge to fill up a small number of broad ledges after abandoning high-predation areas? If they had, the Kingittoq colony would have consisted of a mosaic of empty and high nesting-density broad cliff ledges. In this situation, even a small number of murres could have established a refuge against predation by maintaining some high nesting-density areas within the colony where gulls could not land to forage on foot. It is likely that prospecting murres at the declining colonies could not improve their nest site by recruiting to other broad ledges, because their new nest sites would likely be positioned on the edge of small groups as well. Thus, their new sites would also be vulnerable to predation. Further, the potential for others to join the group would be low because other prospectors would be thinly distributed over the cliff (due to population declines), and would likely be philopatric to their original nesting areas (Gaston and Nettleship 1981; Noble 1991). Thus, a synchronous colonization of a broad ledge would not likely occur unless there were many prospectors, or if a structural refuge provided some initial protection from gull attack (e.g. rock overhang, loose rock).  Consequently, prospectors would be expected to  consistently abandon broad ledges until they were attracted to the remaining nest sites within the colony that were relatively free from predation (i.e. narrow ledges or caves). If this process continued, the majority of birds would eventually nest on sites inaccessible to gulls (Timmiak, Fig. 5.6). Consequently, the per capita predation rate would be predicted to be lowest at the colonies that had experienced the greatest declines. I propose that this pattern of prospecting and nest site selection, driven largely by murres attempting to avoid gull predation and harassment, would result in the nesting distribution observed at the Upernavik area colonies and elsewhere (Johnson, 1938; Birkhead 1977; Ainley  121 and Boekeihede 1990). The nest distribution at the Upernavik colonies also suggests that gulls alone cannot force a murre colony to extinction, because the structural refuges on the cliff ensure that not all nest sites are accessible to gulls.  Population level effects ofguilforaging behaviour: multiple-stable states? Once seabird population declines have occurred, can predation of eggs and young hold colonies at low numbers once sources of adult mortality have been removed? In other words, are there multiple stable states among seabird populations in which avian predation has only a slight influence on the prey population at high densities, whereas at low densities predators can hold the population permanently below the level at which resources become limiting (review Sinclair 1989; Newton 1993)? For predators to maintain stable prey densities, theory suggests that the following criteria must be met: 1) that the predators involved are generalists which can switch rapidly between alternative food sources as prey numbers change; 2) an ample supply of alternative prey exists to maintain a high predator population; 3) that prey occur in a patchy habitat with predator refuges so that prey cannot be forced to extinction by predation; 4) variation in the vulnerability of individual prey and the hunting skills of individual predators; and 5) that predation varies proportionally with prey density which may be determined by intra specific interactions among the predators themselves, e.g. interference or territoriality (Sinclair 1989; Newton 1993). All of these requirements appear to be met at the Upemavik colonies (see above), which suggests that gulls should be able to maintain murre colonies at low numbers following a population decline. Despite this, data from a limited number of sites (Birkhead 1977; Hatchwell 1992; Ainley and Boekethede 1990), and computer simulations based upon thick-billed murre population parameters obtained in the Canadian Arctic (Gilchrist, in prep) suggest that in general, gulls cannot hold murre populations at low levels indefinitely once sources of adult mortality have been removed. There are at least two possible explanations for this.  122 First, the pattern of nest site selection during colony recovery may enhance the rate at which murres can overcome high levels of egg and chick predation by gulls. During recovery, new recruits to the colony are predicted to join high-density nesting areas to breed, and in doing so, re-establish high-density areas more quickly than if nest sites were selected randomly. This pattern is in contrast to the distribution of nest sites predicted during the colony declines when birds were removed randomly from the breeding population (e.g. shot or oiled at sea). Also during the declines, high philopatry by established breeders to their poor sites would likely prolong the time over which a large portion of the colony nested on sites vulnerable to gulls. Therefore, I predict that per capita predation would be lower during colony recovery than during decline for a given population size. This prediction has implications for seabird colony monitoring because it suggests that the status of a colony at a given population size can only be assessed when current census data are integrated with historical information. A second and related explanation regarding colony recovery in the presence of avian predators considers the relationship between structural habitat refuges, recruitment of young to the colony, and the re-establishment of high-nesting density areas. In general, predation on the eggs and chicks of birds is much less likely to affect subsequent breeding numbers than is predation on the adults themselves, particularly among long-lived species such as the thickbilled murre (Newton 1993). Therefore, it is important to consider that glaucous gulls lower the effective breeding population by limiting the habitat where murres can reproduce successfully, rather than through the direct mortality of breeding adults. As well, at most declining colonies a breeding population is maintained in structural refuges (Birkhead 1977; Ainley and Boekelhede 1990; this study). It appears that members of these remnant breeding populations can often produce enough offspring in their lifetime to eventually re-establish high nesting-densities in open habitat (Birkhead 1977, Hatchwell 1991; Ainley and Boekelhede 1990). This assumes that there is high philopatry to the natal colony and that offspring return to breed even after initial reproductive failures, and both of these assumptions appear to be met with murres (Gaston and Nettleship 1981; Noble 1991; deForest 1992). Therefore, I suggest  123 that a gradual increase in a breeding population could modify the breeding habitat of murres favorably and eventually enable them to escape high levels of predation. This could explain the recovery of murre colonies in the presence of gull predation following initial population declines (Birkhead 1977; Hatchwell and Birkhead 1991; Ainley and Boekelhede 1990). These findings also suggest that a colony could be held at a low population equilibrium by predators if other sources of adult mortality continued to erode the breeding population and/or the recruits returning to breed at their natal colony. This appears to be the situation at the southern Upernavik colonies where these colonies continue to persist at low numbers with no indication of recovery, despite the cessation of the summer commercial hunt (Kampp et al. 1994; pers. obs.).  Conclusions My findings illustrate how seemingly unimportant details of predator-prey interactions can have practical consequences. In this system the interactions between wind speed, cliff ledge accessibility, and risk of injury for the predator while forging, varied with prey population size. Consequently, human-induced changes in murre numbers appeared to alter the natural predator-prey dynamics at murre breeding colonies, and the perhaps increased the impact of predation on murre reproductive success. These findings could be relevant to other ecological systems where the economics of predator foraging decisions are partly determined by the risk of injury established through group prey defence.  124  Appendix I. Numbers of predatory gulls in relation to murre colony size (expressed as breeding pairs). Gulls present in the vicinity of colonies which did not feed primarily on murre eggs and chicks were excluded. GULLS*  LOCATION  2a Icefjord, Spitsbergen 19 a Bear Island, Norway Akpatok Island North, Can., 1985 138 a Akpatok Island South, Can., 1985 61 a 22 a Coats Island, Canada, 1990 85 a Diggs Island, Canada, 1985 21 a Hantch Island, Canada 70 a Minarettes, Canada, 1985 40 a Prince Leopold east, Canada, 1981 50 a Halduyt Island, Greenland 5 a Greenland Islands, Carey 50 a Saunders Island, Greenland 50 a Parker Snow Bay, Greenland 50 a Agpat Agpai, Greenland a 19936 Greenland, Agparssuit, Upernavik Kingigtoq general, Greenland, 1993 20 a Timmiakulussuiot, Greenland, 1993 16 a 30 a Appatsiaat, Greenland, 1993 60 a Bezymyannaya Bay, Russia, 1956 8b SE Farallon Island, U.S.A. -  -  -  MURRES@ CENSUS#  750 a 52 500 a 450 000 a 200 000 a 30 000 a 180 000 a 50 000 a 133 000 a 70 000 a 28 000 a 5 000 a 107 000 a 38 000 a 36 000 a 350 a 7500 a 200 a 320 a 180 000 a 4 500 b  ii ii ii ii i i ii ii i iii iii iii iii iii ii ii ii ii iii i  SOURCE  Pennycuick 1956 Williams 1975 Chapdelaine, pers corn., 1994 Chapdelaine, pers corn., 1994 Gilchrist and Gaston, unpub Gaston et a!. 1985; pers corn. 1994 Gaston, pers corn., 1994 Gaston and Smith, 1985 Gaston & Nettleship 1981 Kampp 1990; pers. corn. 1994 Kampp 1990; pers. corn. 1994 Kampp 1990; pers. corn. 1994 Kampp 1990; pers. corn. 1994 Kampp 1990; pers. corn. 1994 this study this study this study this study Uperski, 1956 Spear 1993  a) glaucous gull, Larus hyperboreus, b) western gull, Larus @ a) thick-billed murre,Uria lornvia, b) common murre, Uria aalge. # i) detailed census with gull behaviour! diet information, ii) detailed census of both species, iii) estimate of at least one species *  125  CHAPTER 6 CONCLUSIONS Thesis synthesis In chapter 2, I presented one of the first experimental studies to examine the foraging constraints of an avian predator in the wild. I found that the foraging ability of glaucous gulls was constrained by narrow cliff ledge width, high murre nesting densities, and group defence. My results confirm descriptive behavioural studies of other avian predators foraging at seabird colonies (Watanuki 1989; Spear 1993; Young 1994). However, I found that glaucous gulls could overcome these foraging constraints using wind conditions which enabled them to reach weakly-defended nest sites on narrow ledges. Thus, the foraging constraints affecting glaucous gulls were not constant, but varied with wind conditions. In chapter 3,1 conducted observations of gulls preying on the eggs and chicks of naturally occurring murre eggs and chicks and found that gull foraging activity and predation rates were positively correlated with wind speed. Using a model which integrated field data on gull predation rates and wind conditions, I found that the vulnerability of murre nest sites was a function of both colony topography and seasonal wind conditions. In chapters 3 and 4, I concluded that a trade-off existed between energetic gain and risk of injury to the foraging gulls, and that this trade-off was mediated by wind.  Although I never  witnessed an adult gull being killed by murres, I did observe adult gulls being injured by the defensive strikes of murres. I suggest that the potential for injury during attack altered the relative costs and benefits of foraging decisions. For example, although foraging on foot under calm wind conditions yielded the greatest rewards for gulls, it also incurred the greatest risk of contact with defending murres. Consequently, gulls preferred to forage aerially during windy conditions, although aerial attacks were much less successful than attacks made on foot. In the most extreme response to this trade-off, gulls were inactive during calm conditions (Fig. 3.2), perhaps because they were waiting for the wind to increase and for foraging conditions to  126 improve. To my knowledge, this is the first field study to support the theoretical prediction of Sutherland and Moss (1985), that foraging inactivity among top predators is influenced by the dangers and rewards of current foraging conditions, rather than simply being a result of predator satiation. In chapter 5, I tested the prediction that gull predation should increase following any perturbation that decreases murre nesting densities. Although previous seabird studies have discussed this possibility (Johnson 1938; Birkhead 1977; Ainley and Boekeihede 1990), my study is among the first to quantify this influence and to examine why it occurs. I found that gulls at declining colonies in Greenland foraged on broad ledges and were less constrained by calm wind conditions, apparently because population declines increased the availability of low nesting-density ledges where gulls could attack murres on foot regardless of wind conditions. Consequently, predation rates at the declining Upernavik murre colonies were higher during calm wind conditions compared to the Coats Island colony. I suggest that the effects of predators on their prey may be particularly among prey species who rely on group defence to avoid predation.  Comparisons with other gull foraging studies I now compare and contrast my results with other studies that have examined the foraging ecology of large gulls, and to identify topics that warrant further research (Table 6.1). Few studies of gulls have examined how risk of injury while foraging influences gull foraging behaviour, although several studies have identified prey defence as an important constraint on gull foraging efficiency. Most studies to date have emphasized the effects of gull predation on the reproductive success of prey, or have identified factors that affect diet selection (e.g. trade offs between foragingtime allocation and nest defence). Of those studies that have focused specifically on attack behaviour, several have found, as I did, that windy conditions enhance gull foraging efficiency. There are too few studies, however, to determine whether the effect  127  Table 6.1. A review of studies examining the foraging ecology of 7 species of large gull during the breeding season. %POP refers to the proportion of the population that specialized on a specific food item. FT refers to gulls that maintained feeding territories. SUBSTR refers to the slope and other habitat characteristics where gulls were foraging. WIND refers to studies that detected significant wind effects on gull foraging efficiency. Question marks refer to topics that were not examined in the research. In studies where two foraging behaviours occurred within a single gull population, each strategy is described separately and they share the same literature source.  diet selection of gulls.  ? shoreline  yes: diet ?  scavenge  garbage, fish, ? seabird eggs.  ?  low Arctic L. marinus Greater black-backed  diet selection. inter-specific competition.  ? shoreline  yes: diet ?  searching on foot  ?  intertidal, shellfish.  ?  low Arctic coastal  L. hyperboreus  Schamel 1977 pred. effects on prey.  no island, flat.  yes: for. behav.  prey defence prey concealed  predation on foot  waterfowl eggs, fish.  territorial dispersed FT  low Arctic  L. hyperboreus  Gaston et al., 1985 ?  shoreline ?  ?  yes  cliff  ?  pred. effects on prey.  Ingolfsson 1976  Ingolfsson 1976  Gaston et al., 1985  Strang 1976  prey defence, topography.  100%  fish, intertidal.  colonial  low Arctic coastal  ?  gull foraging and breeding ecology.  ?  Barry and Barry, 1990  this study  SOURCE  tundra, coasts.  diet selection, seasonal var. in diet.  foraging mode, energy-injury trade-offs.  STUDY FOCUS  ?  predation aerial, on foot.  seabird eggs.  territorial dispersed Fr?  low Arctic coastal  L. hyperboreus  >70%  ?  yes  WIND EFFECT  ?  ?  wat. eggs, fish.  territorial dispersed FT  Arctic coastal  L hyperboreus  cliff  SUBSTR.  shoreline, tundra, sea,  yes: for. behav.  INDIVD VAR.  yes: diet  ?  ?  ?  rodents, colonial, solitary fish, or wat. eggs.  low Arctic coastal  Glaucous  L. hyperboreus  prey defense, topography, wind.  predation aerial, on foot.  >90%  seabird eggs, fish.  territorial dispersed FT  low Arctic coastal  L. hyperboreus  FACTORS AFF. FOR.  % POP FORAGE MODE  DIET  NEST BEHAV.  REGION  SPECIES  colonial  fish.  seabird eggs, 30% fish.  colonial  temperate coastal  L argentatus Herring pIll  70%  island, flat  sea, shorelines ?  7  ? 7 7  yes  yes  prey defence, wind,  at sea, shorelines.  island, sloped,  predation, aerial,  at sea  garbage, fish.  colonial  99%  yes: for. prey defence behav. topography intra-spec comp.  predation aerial, on foot.  1%  seabird eggs, fish.  territorial FT  temperate coastal  L occidentalis Western Il  pred. effects on prey, wind effects.  Theil and Sommer, 1994.  Theil and Sommer, 1994.  Spear 1993  pred. for. behav. Spear 1993 and effects on prey.  Watanuki 1983, 1989, 1992 gull for. behav. individ. diff. in diet.  yes: diet, island, for. behav. sloped.  prey defence topography  predation, aerial,  ?  seabird eggs.  colonial  L. schistisagus temperate Slaty-backed pill  Pugesek 1992 gull reprod. strategies.  ?  ?  0%  “inland lakes”  colonial  temperate coastal  L. Californicus California gull  Siegel-Causey and Hunt 1985.  ?  ?  ?  ?  at sea  ?  garbage, fish  colonial  Siegel-Causey and Hunt 1985.  pred. effects on prey, pred. for. constraints.  no  island, flat and sloped,  ?  prey defence, topography, eagle dist.  predation on foot  seabird eggs, fish.  colonial  Johnson 1938  pred. effects on prey.  ?  flat island  yes: for. behav.  prey defence, human dist.  predation aerial, on foot.  L glaucascens temperate Glaucous-winged coastal  ?  seabird eggs  territorial dispersed FT?  temperate coastal  L. rnarinus  ‘-  ?  prey defence, wind,  yes shorelines open water  waterfowl chicks.  predation, aerial,  ?  ?  low arctic  L. argenratus  ..  .  Pierotti and Annett, trade-offs: 1991. diet selection and nest guarding.  distant shores, dumps at colony  yes: diet  time away from nest. topography.  45% L. on foot. intertidal 23% 4’ on foot garbage seabird adults 9% ij aerial  coloniaL, various habitats.  temperate  L. argentatus  1991. diet selection and nest guarding.  agriculture shorelines  diet  variation in prey avail,  on foot.  earthworms, intertidal,  Sibly and McCleery  factors affecting Mendenhall and Mime, 1985. prey survival  trade-offs:  ?  distant garb.  yes:  temporal  scavenge,  ?  garbage,  colonial  temperate  L. argentatus  Southern and Southern, 1984  ?  distant garb. dump  ?  ?  garbage, fish  colonial  temperate  ?  Southern and Southern, 1984.  96%  pred. for. behav. and effects on prey.  ?  island, flat.  yes  prey defence  4%  predation aerial, on foot.  seabird eggs, fish.  colonial Fr?  temperate  L argentatus  C  131 of wind is related to the topography of the habitat as I have suggested (e.g. gulls that forage on foot in level habitat may be less reliant on wind than gulls that forage in cliff habitat; Ch. 2, 3). I now consider topics that warrant further study. Gulls are well-suited for comparative studies because they have been extensively studied in the wild, and they have extremely diverse diets, and nesting and foraging behaviours. By comparing the reproductive and foraging ecology of gull species, it should be possible to explore how foraging behaviour and environmental constraints interact to influence the evolution and maintenance of coloniality. For example, my literature review showed that two distinct foraging strategies often occur among gull populations that breed near avian prey (e.g. waterfowl or seabird colonies). These populations can be divided into ‘specialist predators’ which feed primarily on eggs and chicks, and ‘generalists’ who have a varied diet. Nest site selection by gulls within a population appears to be related to these foraging strategies (Table 6.1). Gulls that commute to distant foraging sites typically nest colonially. In contrast, the nests of predator-specialists are typically dispersed because these gulls often maintain feeding territories around their nests. It would be interesting to study the costs and benefits of these two foraging strategies, and to explore why both are maintained within a population. I suggest that predation on seabird or waterfowl eggs by specialists is typically the most profitable foraging strategy for 3 reasons. First, gulls that nest colonially and commute to foraging sites must balance foraging opportunities with the risk that their chicks may be killed by conspecifics in their absence (Pierotti and Annett 1991; Sibly and McCleery 1991). This risk appears to be reduced for predator-specialists because they forage near their nest, and often exclude other gulls from the area (Spear 1993; this study). Second, travel to distant food sources likely decreases the net profitability of prey, which in turn, may decrease chick growth and reproductive success (Sibly and McCleery 1991). Third, birds that commute to sea or to intertidal areas typically forage on unpredictable (e.g. fish) and less profitable prey (e.g. intertidal organisms) when compared with seabird prey (Watanuki 1992; Theil and Sommer 1994; Southern and Southern 1984; this study; but see Pierotti and Annett 1991).  132 Despite the benefits for gulls of specializing on seabird or waterfowl prey, predatorspecialists often make up a small proportion of gull populations (Table 6.1). Perhaps competitive exclusion by territoriality restricts most individuals within a population from accessing the most profitable prey. However, little is known about how individual gulls within a population become specialized.  From this, I identify a need for researchers to study  how foraging specialists come to occur in a gull population, whether the ratio of generalists to specialists remains stable during environmental change, and whether competitive exclusion within a population prevents more individuals from adopting a specialized diet.  From Lw-us to Leo: the need to examine mortality risks among top predators It is difficult to quantify the mortality risks of decisions made by animals in the wild. Given the consequences, it is not surprising that fatal outcomes are rarely observed. Nevertheless, mortality risks influence the costs and benefits of behavioural decisions in the wild. For example, prey appear to be sensitive to both the dangers associated with behavioural alternatives, and to environmental factors that may alter the degree of danger (Milinski and Heller 1978; Lima 1986; Lima and Dill 1990; Sih 1989; Ydenberg 1994). Although many top predators face mortality risks while foraging, little attention has been devoted to how these dangers influence their behaviour (Stein 1977; Pettifor 1990; Merav et al. 1991). It is likely that the trade-off between energetic gain and risk of injury that I found among glaucous gulls depredating murres, is common among top predators. For example, the largest and most energetically valuable prey are often the most dangerous to attack. Indeed, it is common for some predators to “test” the defensive abilities of their large prey before attempting to make a kill (lions, Schaller 1972; wolves, Mech 1970; hyaenas, 1990). The trade-off between energetic gain and risk of injury while foraging could affect several aspects of predator behaviour, and in many cases this has been over-looked. For example, several authors have concluded that the average group size of African lions (Panther leo) is larger than required to capture and subdue even large prey (reviewed in Packer 1986;  133 Mangel and Clark 1988). Several explanations have been invoked to explain “larger than optimal’ pride size. Large prides may have a lower variance in daily food intake (Caraco 1981), increased mating success (Caraco and Wolf 1975), or be able to maintain larger feeding territories. However, to my knowledge, no one has considered that individuals that forage as part of a larger pride face less risk of injury when subduing prey. Given the frequency with which lions hunt (every few days), their potential longevity (10-15 years), and the size and defensive abilities of their large prey, it seems reasonable that reduced mortality risks while hunting could out-weigh the energetic costs of sharing prey among more individuals. 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