Birds of Prey and Grouse in Finland, Do Avian Predators Limit Or Regulate

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A 509 OULU 2008 A 509

UNIVERSITY OF OULU P.O. Box 7500 FI-90014 UNIVERSITY OF OULU FINLAND ACTA UNIVERSITATIS OULUENSIS ACTA UNIVERSITATIS OULUENSIS ACTA A

SERIES EDITORS SCIENTIAE RERUM Vitali Reif NATURALIUM VitaliReif ASCIENTIAE RERUM NATURALIUM Professor Mikko Siponen BIRDS OF PREY AND BHUMANIORA GROUSE IN FINLAND Professor Harri Mantila DO AVIAN PREDATORS LIMIT OR CTECHNICA Professor Hannu Heusala REGULATE THEIR PREY NUMBERS?

DMEDICA Professor Olli Vuolteenaho

ESCIENTIAE RERUM SOCIALIUM Senior Researcher Eila Estola

FSCRIPTA ACADEMICA Information officer Tiina Pistokoski

GOECONOMICA Senior Lecturer Seppo Eriksson

EDITOR IN CHIEF Professor Olli Vuolteenaho EDITORIAL SECRETARY Publications Editor Kirsti Nurkkala FACULTY OF SCIENCE, DEPARTMENT OF BIOLOGY, UNIVERSITY OF OULU ISBN 978-951-42-8804-3 (Paperback) ISBN 978-951-42-8805-0 (PDF) ISSN 0355-3191 (Print) ISSN 1796-220X (Online)

ACTA UNIVERSITATIS OULUENSIS A Scientiae Rerum Naturalium 509

VITALI REIF

BIRDS OF PREY AND GROUSE IN FINLAND Do avian predators limit or regulate their prey numbers?

Academic dissertation to be presented, with the assent of the Faculty of Science of the University of Oulu, for public defence in Kuusamonsali (Auditorium YB210), Linnanmaa, on June 7th, 2008, at 12 noon

Supervised by Doctor Risto Tornberg

Reviewed by Professor Steve Redpath Doctor Jari Valkama

ISBN 978-951-42-8804-3 (Paperback) ISBN 978-951-42-8805-0 (PDF) http://herkules.oulu.fi/isbn9789514288050/ ISSN 0355-3191 (Printed) ISSN 1796-220X (Online) http://herkules.oulu.fi/issn03553191/

Cover design Raimo Ahonen

OULU UNIVERSITY PRESS OULU 2008 Reif, Vitali, Birds of prey and grouse in Finland. Do avian predators limit or regulate their prey numbers? Faculty of Science, Department of Biology, University of Oulu, P.O.Box 3000, FI-90014 University of Oulu, Finland Acta Univ. Oul. A 509, 2008 Oulu, Finland

Abstract Relationships between predators and prey may affect population dynamics of both parties. Predators may also serve as a link between populations of different prey, e.g., small game and small mammals. I used available data on the diet and reproduction of birds of prey (mainly common buzzards Buteo buteo and goshawks Accipiter gentilis) and video surveillance of their nests, as well as multiannual data on numbers of grouse and small mammals for studying food habits and population dynamics of raptors and their links with population fluctuations of voles and grouse (capercaillie Tetrao urogallus, black grouse Tetrao tetrix and hazel grouse Bonasa bonasia) in western Finland during 1980–1990s when grouse and vole numbers fluctuated in regular cycles. Microtus voles were the main prey of the buzzards which partly switched their diet to small game (juvenile grouse and hares) in years when vole numbers declined. The nesting rate of buzzards also correlated with vole abundance, but the productivity rate and brood size tended to lag behind the vole cycle. This mismatch between the buzzards' functional and numerical responses resulted in a fairly small impact of buzzards on juvenile grouse, which did not correlate with vole density. The productivity of goshawks followed the fluctuations of grouse density closely whereas the occupancy rate of goshawk territories did so with a two-year lag. The annual numerical ratio of goshawk to grouse was inversely related to grouse density, suggesting that this predator may be a destabilising factor for grouse population dynamics. However, the goshawks' kill rate of grouse showed no clear relations to grouse density. In June–July, these birds of prey (including hen harriers Circus cyaneus) usually killed a relatively small number of grouse chicks. Losses to raptors constituted up to one quarter of grouse juvenile mortality during the two months. We did not find a strong effect of avian predators on grouse juvenile mortality. In boreal forests, predators and other factors of grouse mortality do not operate as one, and there is probably no single factor responsible for the reproductive success of grouse.

Keywords: birds of prey, functional response, grouse, numerical response, population dynamics, predation, small mammals

To my parents, for their patience 6 Acknowledgements

This work started when Risto Tornberg kindly invited a complete stranger, who was interested in studying the ecology of birds of prey, to work with him (and, apparently, to share the office) on the basis of receiving a single email. A long time has passed since then (much longer than we both expected), but I still hope that Risto does not regret his decision too much. In Risto, I have enjoyed having not only the most benevolent supervisor one can ever imagine, but also a sociable office companion with whom to debate a great variety of subjects reaching far beyond animal ecology — from history to modern day politics. Risto is the person who introduced me to Finnish nature and culture and has always been ready to help in any imaginable everyday situation (not to mention translations from Finnish). In addition, I am convinced that the dinners of grouse stew were not the least important factor in helping me to appreciate better the preferences of goshawks and buzzards. I am profoundly grateful to him for such openness and trust, for his optimism and belief in the success of my work (which extended much farther than my own confidence), and last but not least for the luxurious chair that he ceded to me and that really saved my back during the countless hours in front of the computer. My arrival in Finland would not have been possible without the kind help of Mikko Mönkkönen (which I, unfortunately, have not had a chance to pay back). I would also like to thank Mikko for his bicycle that made my acquaintance with the town easy and comfortable from the very first day in Oulu (not many newcomers to this bicycle paradise enjoy such conditions). I would never have been able to even plan a study like this without the huge mass of data which I had the privilege of using: statistics and biological reports on raptors and their prey collected over the years by various people. During this work I had the honour of cooperating with one of the top ecologists, Erkki Korpimäki (University of Turku), who gave me some general guidelines, kindly shared his records of long-term trapping of small mammals and was never tired of editing countless versions of my manuscripts (I imagine how loose they must have been in the beginning…). This was an invaluable learning experience. The initial stimulus for this project was the unique data on the diet and nesting of birds of prey which were collected in western Finland over some twenty years by Sven Jungell. These data became the keystone of my study. Sven’s nest data contain almost 3000 records (arranged into an electronic

7 database by Sakari Mykrä), and anyone familiar with raptor biology will be impressed with the amount of hard field work that was carried out by this devoted ornithologist. I thank Kauko Huhtala for allowing me to analyse his “raptor” data, and Matti Suopajärvi, Kalevi Tunturi, Pentti and Markku Hukkanen, and Mikko Viitanen for letting me use “their” nests for video surveillance. I also thank Matti for accommodating me with my caravan for a few weeks in his parking lot in Tornio, and Kalevi for his assistance in the field. I thank Jari Ylönen (the Experimental Zoo, University of Oulu) and Juhani Itämies (the Zoological Museum, University of Oulu) for technical and financial support in the ”video” project. Pekka Helle (Finnish Game and Fisheries Research Institute) provided me with a variety of unpublished information about grouse. I am indebted to numerous hunters who walk hundreds of kilometres every year counting grouse; without the efforts of all these people who remained anonymous to me, this study would not be possible. I extend warm thanks to Matti Rauman, who never refused to fix any item of gear at any time of the day or to make another connector or cable for me, and to Kai Niemelä, who put a great deal of effort into continuously upgrading my computer and providing me with the software updates I required. I am grateful to Jari Oksanen and Seppo Rytkönen for advising me on data analysis, to Esa Hohtola for giving me friendly advice on anything of which I was uncertain, and to Minna Vanhatalo for always finding time to write me another certificate or reference, and sorting out the academic bureaucracy. I also thank the heads of the Zoological Museum — Juhani Itämies, Mikko Mönkkönen and Jouni Aspi — for allowing me to work in the museum premises. I am indebted to Jukka Forsman, Jari Valkama and Steve Redpath for reviewing and commenting on this thesis. Jukka also helped me to improve one of my first grant applications, which was the key factor for its success. I owe my greatest gratitude to Vladimir Tumanov, who reviewed most of the texts presented in this thesis in order to ensure that others would really understand what I meant. If my English has improved a little over these years, it is thanks to him. Through the years of work on the thesis, my research was funded — brick by brick — with grants and scholarships from the Centre for International Mobility of the Finnish Ministry of Education, the Jenny and Antti Wihuri Foundation, the Foundation of the Finnish Association for Nature Conservation, the Ella and Georg Ehrnrooth Foundation, the Environmental Graduate School EnviroNet (my

8 special thanks to Riitta Kamula) and the Faculty of Science of the University of Oulu. I am also grateful to the Faculty for the travel grants that allowed me to attend several scientific meetings and a summer school — a valuable experience for a young researcher. My interest in avian predators, which eventually brought me to Finland, was aroused at the beginning of my studies at Moscow State Pedagogical University by my first supervisor, Vladimir Galushin, whose encouragement I continued to feel throughout this research, and by my field tutors, Alexey Kostin (MSPU) and Andrey Kuznetsov (Darwin Nature Reserve). These scientists (and friends) opened up for me the fascinating world of birds of prey, for which I am deeply grateful. I am grateful to Pasi Reunanen and Edu Belda for pleasant company indoors and outdoors during my early days in Oulu, and for giving me shelter when I did not have a place to stay. I also thank my fellow Ph.D. students at the Department of Biology, who did not refuse to join me for a chat over a cup of coffee, and all those people who greeted me in the corridors of the University (even though I could not always remember your names). My appreciation also goes to all my friends and relatives in Finland, Russia and around the globe for their moral support, transmitted by verbal means or via those intangible threads whose presence we always feel, even when we are doubtful about their existence. I am indebted to my beloved parents, Zaituna and Edgar, for their encouragement and patience. I owe them my interest in biology: they definitely gave me the right books to read. Finally, my loving thanks to Zdravka, who is simply a part of my life, for everlasting support and tolerance.

Oulu, May 2008 Vitali Reif

9 10 List of original papers

This thesis is based on the following articles, which are referred to in the text by their Roman numerals:

I Reif V, Tornberg R, Jungell S & Korpimäki E (2001) Diet variation of common buzzards in Finland supports the alternative prey hypothesis. Ecography 24: 267–274. II Reif V, Jungell S, Korpimäki E, Tornberg R & Mykrä S (2004) Numerical response of common buzzards and predation rate of main and alternative prey under fluctuating food conditions. Annales Zoologici Fennici 41: 599–607. III Tornberg R, Korpimäki E, Jungell S & Reif V (2005) Delayed numerical response of goshawks to population fluctuations of forest grouse. Oikos 111: 408–415. (Erratum: same authors (2006) Oikos 113: 572). IV Reif V, Tornberg R & Huhtala K (2004) Juvenile grouse in the diet of some raptors. Journal of Raptor Research 38: 243–249. V Reif V & Tornberg R (2006) Using time-lapse digital video recording for a nesting study of birds of prey. European Journal of Wildlife Research 52: 251–258. VI Tornberg R & Reif V (2007) Assessing the diet of birds of prey: a comparison of prey items found in nests and images. Ornis Fennica 84: 21–31. VII Reif V, Tornberg R & Korpimäki E (2008) Factors explaining forest grouse mortality: predation impacts of raptors, vole abundance or weather conditions? Manuscript.

11 12 Contents

Abstract Acknowledgements 7 List of original papers 11 Contents 13 1 Introduction 15 1.1 Avian predators and prey: a general view ...... 15 1.2 Mutual influence of predators and prey ...... 17 1.3 Grouse, voles and birds of prey in the north ...... 19 1.4 Juvenile grouse as common prey for several raptor species ...... 21 1.5 Biases in raptor diet data...... 22 1.6 Aims and steps of the study ...... 22 2 Material and methods 27 2.1 General approach ...... 27 2.2 Study area...... 27 2.3 The main study species ...... 28 2.3.1 The common buzzard (Buteo buteo) ...... 28 2.3.2 The goshawk (Accipiter gentilis)...... 28 2.3.3 Grouse ...... 29 2.4 Raptor nesting data...... 31 2.5 Raptor diet...... 31 2.6 Data on prey in field and weather ...... 32 2.7 Data handling and analysis...... 33 3 Results and discussion 35 3.1 Responses of a vole-based migratory predator — the common buzzard...... 35 3.1.1 Functional response (I)...... 35 3.1.2 Numerical response (II)...... 36 3.1.3 Total response and predation impact on grouse (VII)...... 37 3.2 Generalist resident predator — the goshawk (III)...... 39 3.3 How raptors share juvenile grouse by size (IV)...... 40 3.4 Prey remains in nests and in images (V, VI) ...... 41 3.5 Total impact of avian predators on populations of grouse (VII) ...... 43 3.5.1 Kill rate, impact and role of raptors in grouse juvenile mortality ...... 43 3.5.2 Potential impact...... 47

13 3.5.3 Problems of the approach, sensitivity of the model and reliability of the results...... 47 4 Concluding remarks 51 References 53 Original papers 65

14 1 Introduction

This study relates how birds of prey eat grouse — forest gallinaceous birds. Grouse have always had a distinct place among other game, and their importance in Finnish hunting culture cannot be overestimated (Ludwig 2007). Although being relatively well-studied animals, grouse still attract much attention of scientists and game managers. This may be because prey, as a victim, traditionally elicits more sympathy than predators. However, in the 20th century birds of prey also became “prey” — victims of humans. This image, in turn, affected the course of many studies which considered “the case” mostly from the position of the predator. My study is an attempt to look at the problem as in a court of law — from both sides or “points of view,” i.e., predator and prey.

1.1 Avian predators and prey: a general view

Relationships between predators and their prey is, perhaps, one of the most fascinating subjects in animal ecology. The “match point” — the predator’s attack on prey — is usually a momentary event that has quite clear consequences for the individuals involved. However, the result of this confrontation is, on the one hand, the outcome of long evolution and, on the other hand, a key for the long- term success of both predator and prey populations, as well as a driving factor for their further respective adaptations. Through evolution, predator and prey species have evolved mutual adaptations not only in morphology and behaviour, but also on the population level. These adaptations enable the general stability of these species in the long term despite short- or even long-term numerical fluctuations (Seger 1992). Indeed, except for a few known cases (e.g. small islands), in nature predators usually do not drive prey populations to extinction. Predator-prey relationships are a topical issue in both game management and animal ecology. Among predators, birds of prey have always been the subject of particular attention among hunters and gamekeepers — primarily because of their visibility. Their detrimental effect on populations of small game was suspected especially in the view of the dramatic decline in the numbers of small game in the 20th century and led to mass legal and illegal persecution of raptors (Newton 1979). Nowadays the killing of raptors and the destruction of their nests is still common even in countries where birds of prey enjoy legal protection (e.g. Byholm & Nikula 2007).

15 The effect of raptor predation on domestic and game animals was the objective of even early studies on raptor diet (e.g. Fisher 1893, McAtee 1935, Craighead & Craighead 1956). Several studies demonstrated that predators take mostly the so-called “doomed surplus” of prey populations, i.e. individuals that fail to obtain territory, are weakened, suffer an injury or happen to be vulnerable to predation because of unusual appearance (e.g. unusual coloration) (e.g. Jenkins et al. 1964). Therefore, it was assumed that predators can affect prey populations sensibly only in cases when the latter are themselves under some unfavourable conditions (e.g. extreme weather) (Errington 1946, 1956, 1967). Some other studies also concluded that raptors’ impact on small game is usually not considerable (e.g. Galushin 1970, Kenward et al. 2001). Such findings perhaps helped to save some species of raptors from extinction because these investigations served as scientific grounds in campaigns against the mass persecution of birds of prey, which had seriously diminished the animals' numbers in many countries in the 20th century (Newton 1979). On the other hand, there is a number of facts indicating that predators in general and birds of prey in particular can in certain circumstances constitute a serious mortality factor for prey animals (Kenward et al. 1981, Lindén & Wikman 1983, Erlinge et al. 1984, Widén 1987, Willebrand 1988, Keith & Rusch 1989, Klemola et al. 1997, 2000, Smith & Willebrand 1999, Norrdahl & Korpimäki 2000, Thirgood et al. 2000, Tornberg 2001, see also review in Valkama et al. 2005). In fact, results of these studies do not contradict the “Errington’ view” in general, but rather expand it and demonstrate that “special conditions” occur in nature more often than it was believed before. Therefore, predators may have a more far-reaching effect on prey populations than just a temporary decrease in numbers. Although predator-prey systems can remain stable even in heavily anthropogenically altered habitats (Craighead & Craighead 1956), as the proportion of intact natural biotic communities is sweepingly vanishing from the face of the Earth (currently they occupy not more that 15% of Europe, Hannah et al. 1994), this stability is not so obvious anymore. Intensively managed European forests may be more suitable for some species but less so for others. For example, given the extensive clear-cutting in Finland, numerous young forests can support large populations of moose (Alces alces) and roe deer (Capreolus capreolus) that are currently controlled there only by hunters. This is because the numbers of these animals' natural predators (bears Ursus arctos, wolves Canis lupus and lynx Lynx lynx) are far too low (e.g. Luoma 2002, Helle & Wikman 2007). At the same

16 time, quickly cultivated and highly fragmented pine forests with scarce underbrush are suitable for voles and thus attract their predators, but they may not provide enough cover for grouse to avoid these predators (Henttonen 1989, Storaas et al. 1999, Kurki et al. 2000). Therefore, even though many of the predator-prey systems have been studied before, the constantly changing environment (including climate change) does not justify previous views. Besides, different mechanisms may be operating in different geographical locations.

1.2 Mutual influence of predators and prey

The results of interaction between predator and prey populations are usually measured by the response (numerical and functional) of predator to prey abundance on one hand, and by the impact of predators on their prey on the other (Solomon 1949, Pech et al. 1995). In theory, the effect of predators on their prey may be of two types: limiting and regulating (Sinclair & Pech 1996). The limiting role implies that a population of predators hunts prey at a rate independent of prey density. This rate can be stable or variable depending on abundance of other prey and variations in predator numbers. If a predator population is able to catch a constant number of prey individuals, then its impact will be higher when prey density is low, and lower when numbers of prey increase. Regulation is based on density-dependence in the predator-prey relationships, i.e. predation should increase with the density of the prey and vice versa. In this way a predator potentially would be able to stabilise the density of its prey, exercising higher pressure on a large prey population and allowing it to recover when its density drops (Solomon 1971, Korpimäki 1993, Murdoch 1994). Therefore, if one is interested in the effect of predators on prey, the primary question that should be studied is the dependence of predation on prey numbers (Redpath & Thirgood 1999). However, populations of predators and prey both depend on many other factors, such as weather, the availability of other food and the presence of other predators. Therefore, the detection of density-dependence in natural ecosystems is difficult (Newton 1998). The most basic reaction of predators to change in prey abundance is change in predator diet — the functional response. The shape (or type) of functional response potentially determines the impact on a given prey population (Crawley 1992, Redpath & Thirgood 1999). Functional response, in turn, defines changes in the numbers of the predators, i.e. numerical response (Keith et al. 1977). Traditionally, predators are divided into two main groups: generalists and

17 specialists (Andersson & Erlinge 1977). When the numbers of certain abundant prey (like voles) fluctuate, generalists predators respond mainly functionally — through changes in the diet. Specialists, on the other hand, respond mainly numerically — via migrations and changes in the reproduction rates (Crawley 1992). Theoretically, generalist predators should have a stabilising effect on prey population dynamics because they can switch to other prey when main prey populations are depleted. Specialists, on the other hand, have no choice but to hunt their prey as long as possible and may therefore depress it to very low numbers (Hanski et al. 1991, Crawley 1992). However, truly narrow specialisation of a predator species on a single prey species is a rare phenomenon. In nature predators form a continuum between these two extreme types where they can change their roles depending on a given food situation (e.g. Formozov 1934, Andersson & Erlinge 1977, Korpimäki & Krebs 1996). In addition to functional response, the type of a predator’s numerical response may also define its effect on prey populations. If numerical response is delayed, the effect may become destabilising because a high number of predators may fall upon a scarce population of prey (e.g. Murdoch & Oaten 1975, Hanski et al. 1993, Korpimäki & Krebs 1996). A predator’s response depends also on its residential status. Residents are more attached to their nesting and hunting grounds than migrants. As a result, a time lag in numerical response is more common among resident predators (Keith et al. 1977, Korpimäki et al. 1991, Rohner 1995, but see Kjellander & Nordström 2003). To sum up, resident specialists should have a destabilising effect on prey population dynamics, whereas the effect of migrant generalists should be the opposite. Although a time lag in numerical response occurs typically among mammalian specialist predators (Korpimäki et al. 1991, Korpimäki & Krebs 1996), it has also been found in raptors, e.g. the great-horned owl (Bubo virginianus) and the goshawk (Accipiter gentilis) in relation to snowshoe hares (Lepus americanus) in North America (Keith et al. 1977, Doyle & Smith 1994, 1995), the gyrfalcon (Falco rusticolus) in relation to the ptarmigan (Lagopus mutus) in Iceland (a rare case of narrow specialisation) (Nielsen 1999) and the goshawk in Finland in relation to forest grouse species (Huhtala & Sulkava 1981, Sulkava et al. 1994, Tornberg 2001). Among predators, avian ones are the most versatile tacticians. By virtue of their ability to fly, birds of prey can swiftly respond to variations in the abundance of prey not only by shifting their diet (functional response), but also by locally

18 switching hunting grounds or long-distance migration (numerical response) (Galushin 1974, Korpimäki 1994). When prey density falls, depending on the tightness of ties with one or several prey species (i.e. the level of specialisation), predators may shift to other relatively easy and nutritious prey for maximizing energy gain or, if there is no such prey available, expand their diet spectrum (Pyke 1984, Stephens & Krebs 1986, Crawley & Krebs 1992). When none of these options is available, predators emigrate to another area (or starve). Conversely, when the numbers of certain prey increase somewhere (e.g. lemmings or voles during years of their extremely high density), many predators are able to specialise on this ‘super-abundant’ resource and are attracted to the area (Andersson & Erlinge 1977, Gilg et al. 2006). This leads to synchronous fluctuations of predator and prey numbers (Galushin 1974, Korpimäki 1985, 1994, Korpimäki & Norrdahl 1991b).

1.3 Grouse, voles and birds of prey in the north

Cyclic fluctuations of herbivores (microtine rodents and small game) in northern latitudes is a well-known but still intriguing phenomenon (Elton 1942, Siivonen 1948, 1957, Chitty 1950, Korpimäki 1984, 1994, Hansson & Henttonen 1989, Krebs 1996, Krebs et al. 2001, Gilg et al. 2006). Several hypotheses have been put forward to explain the regular synchronous cycles of grouse and particularly their synchrony with cycles of small mammals, but still none of them is currently accepted as the ultimate one (Moss & Watson 2001). Natural populations can be affected by abiotic factors, like weather or even lunar (Siivonen & Koskimies 1955) and solar (Sinclair & Gosline 1997) cycles, as well as by such biotic factors as food and predators. Cycles of small game and small mammals may be caused by herbivore-plant interaction (e.g. Haukioja et al. 1983, Krebs 1996, Selås 1997). Berry crops — the main food of adult and growing young grouse — can be affected by weather conditions (temperature), which may also impact grouse breeding success directly (e.g. Siivonen 1957, Semenov-Tian-Shansky 1959). Precipitation and temperature in the first weeks of life or shortly before hatching has been found to be important for chick survival among various grouse species in Scotland (Moss 1986, Summers et al. 2004), Norway (Steen et al. 1988, Wegge & Kastdalen 2007) and central Finland (Ludwig et al. 2006). Cycles may be also caused by variations in the grouse reproduction rate that could result from changes in population structure (Lindén 1989).

19 Other hypotheses allot the main role to predators operating together with other factors. Hagen (1952) and Lack (1954) suggested that the regional synchrony of voles and small game may be explained by varying impacts of generalist predators subsisting on both of these prey types. This theory (later called the Alternative Prey Hypothesis, hereafter APH) predicts that predators, hunting fluctuating populations of small mammals (voles), increase their density in good vole years and shift their diet to small game in years when vole populations decrease (Angelstam et al. 1984). Most generalist predators that feed on small mammals are relatively small, and therefore, alternative prey should not be very big either. In boreal forests, chicks of grouse and juvenile of hares (Lepus spp.), typical r-selected species with large broods, represent such prey. The existence of periodic synchronous fluctuations among vole and small game populations in Norway, central and northern Sweden and northern Finland appear to support the APH (Hörnfeldt 1978, Angelstam et al. 1985, Small et al. 1993, see also Kjellander & Nordström 2003). Some experimental evidence has also been found, however, mainly with respect to mammalian predators (Lindström et al. 1987, Marcström et al. 1988). With respect to avian predators, Korpimäki et al. (1990) found that among-year variations in the diet composition of eagle owls (Bubo bubo) and Ural owls (Strix uralensis) in western Finland fulfilled the main postulates of APH. As far as grouse are concerned, the numerical response of their predators may or may not be consistent with the functional one. If numerical and functional responses are consistent, generalist predators exert the highest impact on alternative prey in years when abundance of main prey decreases, as predicted by the APH (Angelstam et al. 1984). During such years, generalist predators should shift their diet to alternative prey (mainly young and eggs). Having a high population density that has increased in response to a peak in the main prey, these predators may considerably break the reproductive success of alternative prey. The second possibility has been described by the Shared Predation Hypothesis (hereafter SPH, Norrdahl & Korpimäki 2000) which states that in the years of high abundance of main prey, predators increase their numbers and may considerably affect alternative prey at the same time given the high likelihood of predator-prey encounters (see also Wegge & Storaas 1990, Selås 2001). A review of north European avian and mammalian predators' diet composition indicates that among the birds of prey in Finland, the common buzzard (Buteo buteo) and the rough-legged buzzard (Buteo lagopus), along with the eagle owl and the Ural owl, are potentially able to switch from small

20 mammals to small game (Korpimäki et al. 1990, Korpimäki & Norrdahl 1997). Since the southern limit of the rough-legged buzzard’s range does not usually extend beyond Lapland (Forsman 1993), for juvenile grouse in western Finland the common buzzard is the most “dangerous” predator among the diurnal vole- eating birds of prey. The only previous study of buzzard diet in Finland (Suomus 1952) revealed that this species fed on both small mammals and grouse, but how its diet and numbers changed depending on fluctuations of vole density was not clear. Another grouse predator in boreal forests is the goshawk, a powerful generalist predator. It has been found that the goshawk can specialise on grouse (especially in winter) which may account for more than half of the predator's diet in Fennoscandia (Sulkava S 1964, Widén 1987, Tornberg 1997, Tornberg & Colpaert 2001). Therefore, in relation to grouse, the common buzzard is a vole- based migrating generalist while the goshawk is a grouse-based resident generalist. In this study I have mainly considered predation of these two raptor species. I was particularly interested in the combined predation impact of such predators on fluctuating populations of grouse.

1.4 Juvenile grouse as common prey for several raptor species

Besides buzzards and goshawks, juvenile grouse are common prey for some other birds of prey species. Some of them kill grouse chicks on a regular basis while others catch them mainly as subsidiary prey. Among the diurnal raptors in western Finland, there are four species that may hunt grouse chicks frequently: the goshawk (Tornberg 1997), the sparrowhawk (Accipiter nisus) (Sulkava P 1964), the common buzzard (Suomus 1952, I) and the hen harrier (Circus cyaneus) (Redpath & Thirgood 1999). These raptors differ in size and hunting abilities. Given the variations in the hatching time and growth rates of different grouse species, chicks of different sizes can be found in the forest during raptors’ nesting season, and the size range of these chicks also changes constantly through the summer (IV). Various species of juvenile grouse are difficult to distinguish from one another, and therefore, they are usually pooled together in analyses of raptor diets (e.g. Tornberg 1997). Thus, possible differences in the impact on different grouse species, as well as their discriminating importance for raptors, may be masked. Our study of grouse chick size in the diet of four raptors (IV) was aimed to resolve this issue.

21 1.5 Biases in raptor diet data

Most raptor diet studies (including our own presented here — I, IV, VII) are based on data obtained by collecting food remains and regurgitated pellets from nests (reviews in Marti et al. 1993, Korpimäki & Marti 1995). However, direct methods for studying raptor diet (observations from a hide, video and movie surveys, feeding experiments) indicate that such data can be biased for various reasons, e.g., remains of large prey may be easier to discover than remains of small prey; small prey may be simply digested completely; and finally, not all kills may be delivered to the nest (Sonerud 1992, Rutz 2003). Therefore, it is generally thought that large prey tend to be overrepresented while small prey are underrepresented in food remains (e.g. Sulkava S 1964, Mersmann et al. 1992, Redpath et al. 2001, Rutz 2003, Lewis et al. 2004). On the other hand, some studies have shown that remains and pellets may still yield results similar to ones obtained by direct methods (see Collopy 1983, Simmons et al. 1991). Thus, although comparisons between different methods for studying the diet of raptors exist, we have found no previous analyses of possible bias in relation to prey size, species or method. Such bias, however, may affect implications stemming from such data because importance of some prey may be estimated incorrectly. Therefore, we undertook a special study for evaluating the reliability of our diet data (V, VI).

1.6 Aims and steps of the study

The main goal of the present study was the estimation of raptor predation impact on grouse reproduction. It was achieved by several steps which involved analysing the functional and numerical responses of raptors, a close look at juvenile grouse in their diet and an experimental test of data reliability. Most of the study is concentrated on a retrospective time period (1980–1990s) when the numbers of grouse and voles both fluctuated in regular cycles1. First, we analysed the functional responses of the common buzzard to regular fluctuations of its food resource — small mammals (I). We aimed to define the buzzard’s main and alternative prey in our study area and to find out how the buzzard’s diet niche changes when the numbers of voles drop. We were especially

1 In the middle of the 1990s the visible regularity of the fluctuations was disturbed, and although voles later returned to regular oscillations with a three-year cycle (Korpimäki et al. 2005), grouse did not (Helle et al. 2002, Ranta et al. 2004). 22 interested in the degree of the buzzard’s diet shift to juvenile grouse in the years of low vole abundance, i.e., whether the buzzard predation can potentially be an important mortality factor for grouse. Then we examined the numerical response of the buzzard population (II). Besides the general parameters of the buzzard's reproductive success, we studied in particular the dependence of numerical response on the vole cycle. We expected to find immediate numerical response to varying vole numbers as usually observed in vole-eating birds of prey. In the third paper, we describe the numerical response of a sympatric goshawk population to fluctuations of grouse density (III). In this study we aimed to check whether the goshawks have a lagging response to grouse and can therefore significantly affect a declining grouse population — a condition for predation-induced prey cycles. In our fourth study, we examine the size of juvenile grouse in the diet of several raptor species (IV). We generally aimed to explore how different raptors share this common food resource and tried to evaluate relative importance of chicks among different grouse species in the diet of raptors, as well as differences in their vulnerability to predation by these raptors. In the fifth and sixth papers, we describe an experimental study involving video and film surveillance of goshawk and buzzard nests aimed at testing the reliability of raptor diet data (V, VI). We compared two methods — direct (observations and film/video surveillance) and indirect (examination of prey remains) — using our own data together with material from five other studies (VI). Furthermore, we tested a digital video recorder as a tool for nest observations and developed a procedure for its use (V). Despite of increasing number of studies employing remote photography, we found no special guide to this kind of equipment and methods, and important technical details are often skipped in research papers. Therefore, after passing a trial-and-error process, we decided to review the techniques used in today’s nest studies as well as the most essential properties of image recording equipment and to summarize our experience in a separate paper (V). In the last stage of the study (VII), we summarise the findings of the previous papers and, using additional data from published, as well as unpublished sources, calculate the actual values characterizing the way in which the summer predation of raptors affects grouse (Fig. 1). In order to obtain a more complete picture of grouse predation by diurnal raptors, we used available data on the hen harrier and

23 calculated its approximate impact on grouse as well. We also attempted to analyse the effect of raptor predation on the mortality of juvenile grouse. The role of the author of this thesis in the papers was as follow: analysis of electronic databases related to diet and nesting of raptors (I, II, III, VII), statistical and/or graphical analysis (I, II, IV, VII), geo-information analysis (II, III), video surveillance of nests, collection of prey remains and analysis of video data (V, VI), identification and measurements of prey remains (IV, VI), building up the predation model (VII), writing the manuscripts (I, II, IV–VII). R. Tornberg identified most of the prey remains (I, VI, VII), analysed data (III, VI, VII), wrote the paper III, provided essential assistance in the fieldwork and made available his previously collected data (V, VI) and played a key role in the creation and editing of papers (I–IV, VI, VII). Most of the original raptor diet and nesting data used in this study were collected by S. Jungell (I–IV, VII) and K. Huhtala (IV, VII). E. Korpimäki provided the data on vole trapping and closely edited papers I, II, III and VII. The other assistance and sources of other data are referred to and acknowledged in the papers.

24 • Food requirements of adult raptors • Numeric proportion • Food requirements of juvenile raptors of juvenile grouse • Density of active raptor nests (II, III) in the diet of raptors • Mean numbers of young per raptor nest (II, III) (I, VII)

Weight proportion • Total consumption of juv. grouse of raptors in the diet of raptors

• Average weight of juv. grouse Weight of juv. grouse in the diet of raptors (IV) in the diet of raptors

• No. of grouse females in the diet of raptors (I, VII)

No. of juv. grouse lost to raptors

Fig. 1. Simplified diagram of a model for evaluating raptor predation on grouse. The original input data are marked with bullets. The numbers of studies where respective data were obtained are indicated. The sources for the other data are listed in VII: Appendix 1.

26 2 Material and methods

2.1 General approach

For studying the effect of predation, one needs to know, on one hand, the numbers of prey killed by predators during a certain time period and, on the other hand, the numbers of prey present in the same area during the same time. Inasmuch as the numbers of killed prey can rarely be counted directly in a relatively large area (e.g. Craighead & Craighead 1956, Gilg et al. 2006), they are usually estimated indirectly using the number of predators, their diet composition and food requirements (e.g. Ryszkowski et al. 1971, Keith et al. 1977, Lindén & Wikman 1983, Korpimäki & Norrdahl 1991b) (Fig. 1). When raptor predation during the nesting season is in question, the number of nests and young are of primary interest. In this study, I had a unique opportunity to use data collected over a long period by professional, as well as amateur biologists and hunters, including materials processed by the Finnish Game and Fishery Research Institute.

2.2 Study area

The area from which the most of the data (I, II, III, VII) originate and for which the main results (the values of predation impact, VII) were obtained, is located in western Finland in the Southern Ostrobothnia region (III: fig. 1). The diet materials for the analysis of young grouse size in raptor diet (IV) came also from the nearby Central Ostrobothnia region, as well as from the areas of the cities Oulu and Kuusamo. The video observations (V, VI) were made in the north-west part of the Oulu province and in southern Lapland (in the vicinity of the towns Kemi and Tornio). The Ostrobothnia–Oulu–Tornio region represents coastal lowland with small creeks, rivers and ditches. About half of the area is covered by woodlands with interspersed peat bogs (most of which are drained); the rest are cultivated fields. The forests are intensively managed and chiefly dominated by Scotch pine (Pinus sylvestris) mixed with Norway spruce (Picea excelsa) and white birch (Betula pubescens). The area of Kuusamo is rolling country with numerous small and large lakes. Coniferous forests comprise more than 70% of the area, with fewer bogs and fields than in Oulu and Ostrobothnia.

27 2.3 The main study species

2.3.1 The common buzzard (Buteo buteo)

Being one of the most common European raptors, the common buzzard (hereafter buzzard) justifies its name quite well. The buzzard is a medium-size raptor from the family of Accipitridae, with males weighing about 690 g and females — 860 g (Cramp & Simmons 1980). Its distribution range covers forest and forest-steppe belts of Europe and Asia. The buzzard is a year-round resident in southern and central Europe but migratory in the north where it is present only during nesting time. From wintering grounds buzzards arrive in Finland in March–April, and autumn migration starts in August (Forsman 1993). Buzzards nest in most parts of Finland, excluding northern Lapland (Väisänen et al. 1998), and typically prefer fragmented landscapes with a high proportion of arable and logged lands. (There are two subspecies of buzzards in Finland: Buteo buteo buteo and Buteo buteo vulpinus; the latter occurs mostly in eastern parts of the country.) The numbers of buzzards in Finland have declined during the last 20 years (J. Valkama, pers. comm.). The mean nesting density of buzzards in our main study area in western Finland was 4.8 territorial pairs per 100 km2. The usual clutch size is 2–4 eggs which are incubated for 33–38 days. Chicks hatch in the end of May — beginning of June. The young leave nests at the age of 6–7 weeks and become independent after a further 40–55 days (Cramp & Simmons 1980, Forsman 1993). The buzzard is a versatile predator that can utilise many different types of small and medium-sized prey and specialise on some of them depending on abundance levels. However, in most areas of Europe the basis of the bird's diet consists of small mammals (voles and shrews) (I). Buzzards track down their prey by perching, soaring and even walking (Cramp & Simmons 1980).

2.3.2 The goshawk (Accipiter gentilis)

The goshawk is a powerful resident forest predator. Goshawks are larger than buzzards: mean male weight is 860 g and female — 1410 g (Cramp & Simmons 1980). It inhabits the forest zone of North America, Europe and Asia (Kenward 2006). Most of Finland's territory is included in the goshawk’s range where its nesting is limited by the timberline in the north (Forsman 1993, Väisänen et al.

28 1998). Although preferring mature forest, goshawks nest in various types of habitats and even in big cities. The mean nesting density of goshawks in our main study area was 3.6 pairs/100 km2. Goshawks start nesting there in March–April. The clutch contains 3–4 eggs and incubation lasts 35–38 days. Chicks hatch in the end of May — beginning of June and leave nests after 35–42 days, in mid July. The young become independent after two more months and may perform long dispersal migrations (Kenward 2006). In Finland, the goshawk diet includes a great variety of different prey types where pigeons, passerines and gallinaceous (mainly grouse) birds prevail in summer, and hares, red squirrels, rats and grouse — in winter (Tornberg 1997, Tornberg & Colpaert 2001). The goshawk is the only predator in the boreal forests of the Palearctic that can specialise on forest grouse. The latter's proportion in the goshawk's diet can account for more than 50% (Sulkava S 1964, Widén 1987, Tornberg & Sulkava 1991, Tornberg 1997, Tornberg & Colpaert 2001). Some pairs, depending on the location of their nests, can also specialise on pigeons, crows, gulls or ducks (Tornberg, unpubl.). Goshawks can catch prey in flight; however, the “sit and wait” technique (attacks from nests, branches and the ground) is the most common hunting method (Cramp & Simmons 1980, Kenward 1982, Widén 1984, Tornberg, unpubl.).

2.3.3 Grouse

There are four species of forest grouse (Tetraonidae) in Finland: the capercaillie (Tetrao urogallus), the black grouse (Tetrao tetrix), the hazel grouse (Bonasa bonasia) and the willow grouse (Lagopus lagopus). The density of the willow grouse was generally very low in our study area; therefore, it was omitted from the analysis. Grouse are one of the most important game species which has a high cultural and, in some places, economic value. The capercaillie is the largest grouse and is also characterized by the greatest degree of sexual dimorphism (adult male mean weight is 4100 g and female 1800 g), followed by the black grouse (1255 g and 910 g, respectively) and the hazel grouse (both sexes weigh about 400 g) (Dement'ev & Gladkov 1952, Cramp & Simmons 1980). These grouse species are sympatric to a great extent, occupying mostly the northern or mountain parts of the Palearctic, with the hazel grouse extending further to the east than the other two species (Johnsgard 1983). Their preferred habitats, however, are different. The capercaillie of the European boreal zone is

29 usually associated with continuous old-growth coniferous and mixed forests, usually avoiding young, light and fragmented forests. Starting from the 18th century, the destruction of the capercaillie's preferred habitats (along with hunting) has been the main reason for its disappearance or decline in most regions where the bird used to range (Storch 2000, 2001). The black grouse is generally a more common and numerous species than the capercaillie in Fennoscandia and Central Europe, but in European Russia the situation is mostly the opposite (Borchtchevski 2007). It is an ecotone species and therefore benefits from forest fragmentation (Ludwig 2007). The hazel grouse prefer relatively intact spruce or mixed forests, and their numbers are comparable to those of capercaillie. All grouse are resident birds but may perform regional movements (Dement'ev & Gladkov 1952, Cramp & Simmons 1980). In Russia, the abundance of all grouse species was found to relate negatively to human population density and open habitats — natural as well as agricultural (Borchtchevski 2007). In Finland, the mean clutch size of capercaillie, black grouse and hazel grouse is 7, 8 and 9 eggs, respectively (Pynnönen 1954, Rajala 1974, Marjakangas & Törmälä 1997). Chicks of capercaillie and black grouse hatch in the middle of June, and chicks of hazel grouse — in the last ten days of the same month. Grouse are nidifugous birds: the chicks move away from the nest and follow the hen very soon after hatching. Chick mortality is very high: usually less than one third survive until autumn (Lindén 1981, Willebrand 1988, Wegge & Kastdalen 2007). The food of adult grouse consists of pine (capercaillie, black grouse) and spruce (hazel grouse) needle (in winter), catkins of birch (Betula spp.) and alder (Alnus spp.), leaves, buds, seeds and berries (juniper Juniperus communis, blueberry Vaccinium myrtillus, as well as lingonberry Vaccinium vitis-idaea). Chicks in early life feed on invertebrates (spiders, ants, caterpillars) (Dement'ev & Gladkov 1952, Cramp & Simmons 1980). The numbers of Finnish forest grouse have been constantly declining in the past hundred years. Until the beginning of the 1990s, the numbers of grouse in Finland were fluctuating in regular and synchronous six- to seven-year cycles (Helle et al. 2002) that where synchronous over large areas (Ranta et al. 1995). The cycle length in Finland was longer than the one found in western Fennoscandia (3–4 years) (Angelstam et al. 1985, Small et al. 1993) but shorter than in North America and Siberia (10–11 years) (Keith et al. 1977, Keith & Rusch 1989, Beshkarev et al. 1994, Boutin et al. 1995). Our study period covers two last peaks — in 1980 and 1989 (III: fig. 2).

30 2.4 Raptor nesting data

The data on the nesting of raptors was collected between 1977 and 1996 in Southern Ostrobothnia by S. Jungell. He continuously investigated the area surrounding the town of Jeppo for nests of raptors, owl and ravens. He gradually extended the search range and built a number of artificial nests. The database contains 2921 records (nest-years), the majority of which are for nests of the goshawk (924) and the common buzzard (852). The following information concerning the nests was recorded: species, state of the nest/territory (unoccupied, decorated but not used, occupied — defined by observations of incubating birds) and breeding success (number of fledglings). Based on this data the following criteria for breeding parameters were calculated for each year: territory occupancy rate (proportion of occupied territories), nesting rate (proportion of occupied territories where nesting was initiated), proportion of successful nests, population productivity rate (number of fledglings per occupied territory) and average brood size (II, III). Additional information on raptors’ breeding used in the study was taken from the data of the Ringing Centre of the Finnish Museum of Natural History, Helsinki university (raptor-grid, Saurola 1986 and unpubl.) and Suomenselän linnut, a periodical of Suomenselkä Ornithological Society.

2.5 Raptor diet

Most of the diet data used in this study is based on food remains and pellets collected by S. Jungell from the nests of common buzzards and goshawks between 1984 and 1993 in Southern Ostrobothnia (I, II, VII). The identification of prey remains was done by R. Tornberg using reference material from the Zoological Museum at the University of Oulu. For estimations of raptor predation (VII), weight proportions of prey in the diet were used; therefore, they are mentioned in the results along with numerical proportions. I analysed the size of juvenile grouse in the diet of goshawks, common buzzards, sparrowhawks and hen harriers (IV) by measuring grouse humeri found in prey remains. In addition to the data described above, I used prey remains collected in different years between 1966–2003 in Central Ostrobothnia (by K. Huhtala), Oulu (by R. Tornberg) and Kuusamo (by J. Mäkelä) (collections of prey remains of the Zoological Museum, University of Oulu). These data were used also later as one of the key components for the model of predation impact (VII).

31 Additional material was collected with video surveillance equipment and a compact movie camera: the prey delivered to the nests were identified based on images and collected remains with subsequent comparison of the results (V, VI). The video recordings were done at the nests of goshawk, common buzzards and rough-legged buzzards in 2002–2005; the movie camera was used at goshawk and buzzard nests in 2002. This material was complemented with data taken from films shot by R. Tornberg at goshawk nests in 1989–1990. We used a portable digital video recorder equipped with a hard disc drive, and a colour CCD camera with a manual zoom lens — typical equipment for security surveillance. The camera was usually fixed on a branch above or next to the nest in the same tree. The system was powered by car batteries and could record in time-lapse mode (approx. 2 images per second) autonomously for two to four days. The recordings were viewed with a TV-set or a computer, and the images with prey were saved on a video tape or as graphic files in a computer. The exact time of each delivery was registered. (See V for a detailed description of the method and equipment.) The nests were surveyed for about four days in one or two sessions. Our sampling pattern covered about 2/3 of the goshawk nestling period (from hatching to fledging) and the second part of the buzzard nestling period. The movie camera used at one goshawk and one common buzzard nests took one shot per 80 sec in automatic mode for several days; these data were analysed separately from video data (see the details in VI). The total duration of video records amounted to 1303 hrs. The video records registered 123 prey deliveries to the goshawk nests and 102 deliveries to the common buzzard nests. The video and film images together revealed 336 prey items delivered to the nests, and remains of 161 prey items were collected from the nests (some data had to be omitted later from the analysis).

2.6 Data on prey in field and weather

The abundance of small mammals (voles, mice and shrews) in the corresponding years was estimated based on trapping data collected by E. Korpimäki and co- workers in Kauhava (15–20 km south of the main study area; III: fig. 1). Small mammals were trapped in May and September with metal mouse snap-traps in two sites separated by ca. 14 km. Main types of habitats (a cultivated field, an abandoned field, a spruce forest and a pine forest) were sampled during four-day trapping sessions. Water voles (Arvicola terrestris) were trapped with metal rat

32 snap-traps along large ditches and creeks (the main habitat of water voles there). The density index was calculated as the mean number of animals trapped per 100 trap nights for the two sites. (See Korpimäki & Norrdahl 1991a, Korpimäki et al. 1991, Norrdahl & Korpimäki 2002 for more details.) The data on grouse numbers and reproduction were obtained from the published and unpublished data of the Finnish Game and Fisheries Research Institute, as well as from various publications (see VII: Appendix 1). Adult and young grouse are counted across the whole country during annual wildlife censuses that are carried out by hunters, usually in August, in triangular 12-km permanent routes (until 1988 — in linear routes) (Rajala 1966, Lindén et al. 1989). We derived the numbers of grouse in June from the August data of the previous year (VII). The weather data were taken from monthly surveys of the Finnish Meteorology Institute at the Kruunpyy weather station located at the northern edge of the main study area.

2.7 Data handling and analysis

The database was processed with MS Excel spreadsheet programme. For statistical analysis SPSS and R packages were used. The spatial information (location of the nests) was analysed with geographical information systems MapInfo (MapInfo Corporation) and Ranges V (Anatrack Ltd., see Kenward & Hodder 1996). Since the area where raptor nests were sought and checked was constantly expanding (especially until the mid-1980s), we selected a permanent core area for calculating nest density for each year, which would reflect the dynamics of populations but not of the researcher's efforts. We delineated an area including 50% of known nests using harmonic mean analysis (Dixon & Chapman 1980) in Ranges V. Such areas were selected separately for buzzard and goshawk populations (II, III). Thereafter, for each year the numbers of nests and young were counted within these areas using MapInfo. These selected data were used also for kill rate calculations (VII).

34 3 Results and discussion

3.1 Responses of a vole-based migratory predator — the common buzzard

3.1.1 Functional response (I)

The diet of common buzzards in western Finland consisted of 42 prey species, the most frequent prey (17%) being voles of the genus Microtus (the field vole M. agrestis and the sibling vole M. rossiameridionalis) and water voles (15%), followed by the adder (Vipera berus; 6%), juvenile hares (Lepus spp.) and grouse, bank voles (Clethrionomys glareolus) and common shrews (Sorex araneus) (about 4% each). Small mammals are the buzzard's most common prey also in most places of Europe where the diet of this raptor has been studied (Suomus 1952, Pinowski & Ryszkowski 1962, Likhopeck 1970, Rockenbauch 1975, Brüll 1984, Goszczyński & Piłatowski 1986, Spidsø & Selås 1988, Selås 2001). In Poland and Great Britain lagomorphs and birds are the main buzzard food (Jędrzejewski et al. 1994, Graham et al. 1995, Swann & Etheridge 1995). The obvious importance of water voles distinguished buzzard diet in our study area as previously a high proportion of these mammals was noticed in buzzard diet only in Estonia (Randla 1976). In our study area water voles are also important alternative prey for some other vole-eating raptors — kestrels (Falco tinnunculus), as well as short-eared (Asio flammeus) and long-eared (A. otus) owls (Korpimäki & Norrdahl 1991b). In northern Europe voles are a highly variable food resource (e.g. Hansson & Henttonen 1985), and their density fluctuations are usually reflected in the diet of buzzards (Suomus 1952, Spidsø & Selås 1988, Selås 2001). We found the food niche of buzzards broadened when the abundance of Microtus voles in the field decreased suggesting that these voles indeed were the main prey. Therefore, buzzard functional and numerical responses were measured in relation to fluctuations of vole density. The widening of the food niche in response to diminished abundance of the main food resource was previously observed in buzzards (Likhopeck 1970, Jędrzejewski et al. 1994) and other raptors (Korpimäki 1987).

35 Small game species — grouse and young hares — were an important group of buzzard prey, especially when expressed in weight proportion (48%). Although the specialisation of individual buzzard pairs on gallinaceous birds (mostly hazel grouse) even in good vole years was noted in the north-western Urals (Donaurov 1948, Neifeld 2005), grouse as the most numerous bird prey of buzzards distinguishes Finnish buzzards from other European populations. More than half of grouse discovered in food remains from buzzard nests were juvenile. In the years when voles were scarce, the proportion of grouse (and particularly the numbers of their chicks) in buzzard diet increased up to 12% (I: fig. 2). However, these variations did not relate to fluctuations of grouse field density and correlated (negatively) only with vole abundance. Therefore, grouse were the “classical” alternative prey for common buzzards, fulfilling the postulates of the APH (Angelstam et al. 1984). These findings indicate that common buzzards were potentially capable of reducing the reproductive success of grouse in the years of low vole density. Similar “diet tactics” — switching to small game in poor vole years — were observed in this region among Ural owls and eagle owls (Korpimäki et al. 1990). It should be noted that between-year variations in the diet is a coarse-scale estimation of functional response. In some years, the density of voles increased or decreased drastically between the spring and autumn censuses (Korpimäki & Norrdahl 1991a). Such serious changes in the abundance of small mammals usually cause immediate functional responses of many vole and lemming predators (e.g. Korpimäki et al. 1991, Gilg et al. 2006) and are most likely also reflected in the diet of buzzards through the summer, but the methods used in this study cannot detect such fine-scale response.

3.1.2 Numerical response (II)

We found most parameters of numerical response (nesting and reproduction rates) in this buzzard population to be highly variable. Twenty-six to fifty-seven percent of known territories were occupied in various years, and nesting was initiated in 40% to 85% of them. On average, 85% of active nests were successful. The population produced on average 1.7 fledglings per nesting pair, or 2.2 per successful pairs. These values of nesting success are higher than usually observed in Central Europe, Great Britain and Norway (Mebs 1964, Tubbs 1967, Picozzi & Weir 1974, Rockenbauch 1975, Spidsø & Selås 1988, Jędrzejewski et al. 1994, Swann & Etheridge 1995, Goszczyński 1997).

36 Like its diet (I), the buzzard's nesting and reproduction were closely tied to the abundance of voles during the time period when cycles still occurred. The nesting and productivity rate of buzzards correlated with the abundance of Microtus voles in spring. However, in some years declines in vole numbers did not seem to have an immediate effect for the buzzard's productivity rate and average brood size as these parameters of numerical response tended to remain relatively high (II: figs. 1 and 2). Thus, the numerical response of buzzards supported the APH only partly. The productivity of vole-hunting kestrels and several owl species in the same area was much more closely connected to Microtus vole density (Korpimäki & Sulkava 1987, Korpimäki & Norrdahl 1991b, Korpimäki 1994). Individual buzzard nests had a relatively stable average success rate despite variations in the nesting success rate of the whole population. That is, if a pair was able to initiate a nesting attempt, it was likely to rear at least one fledgling, but in years of food scarcity (low vole density) few pairs attempted to breed. This indicates that the common buzzard is a more versatile predator than most vole specialists. Including more prey species in the bird's diet (widening of the food niche; I) enables its successful nesting even in poor vole years (Mebs 1964). The competition for nest sites with goshawks may be another factor that could “distort” the numerical response of buzzards. Goshawks are resident and larger predators; they therefore have an advantage in occupying nest sites and have been found to influence the buzzard's breeding parameters in our study area (Hakkarainen et al. 2004).

3.1.3 Total response and predation impact on grouse (VII)

According to our estimations, in June–July of 1984–1993 buzzards caused the death of 70–128 (mean 102) juvenile and 12–38 (mean 23) adult grouse per 100 km2 (VII). Surprisingly, the kill rate of grouse did not vary as much as could be expected on the basis of large fluctuations in the abundance of the buzzard's main prey — Microtus voles (Fig. 2). The kill rate of juvenile grouse did not correlate with the field density of Microtus voles (although the kill rate increased during the two years when vole numbers declined), or with the density of grouse. These kill rate values resulted in a fairly small impact of buzzards on juvenile grouse, which varied from 1.4% to 4.0% (2.7% on average) and did not correlate with the vole index either.

6 80

2 5 60 4 50

3 40

30 2 20 Vole and grouse indices grouse and Vole

Killedgrouse, ind./km juv. 1 10

0 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 Years harrier buzzard goshawk juv. grouse density vole density

Fig. 2. Numbers of juveniles of three grouse species killed by goshawks, buzzards and harriers (bars). The means of spring and autumn total vole indices and estimated density of juvenile grouse in June are indicated (lines).

The lack of coherence between functional and numerical responses resulted in buzzard’s predation impact on grouse being not clearly depended on vole cycles. Thus, our results indicate that the diet switching of a single predator from small mammals to juvenile grouse (I) may not lead to a considerable limiting effect for grouse populations when not supported by immediate numerical response (II). On the other hand, we still did not find any support for the SPH (Norrdahl & Korpimäki 2000, Selås 2001) as buzzard predation on grouse did not generally increase in peak vole years (Fig. 2). The values of the buzzard's total impact on grouse are quite close (or slightly higher) to those found by Galushin (1970) in the central part of European Russia. In Britain, buzzard predation impact on released pheasants was found to be

38 exceeding 10%, but this was due to sparse vegetation that made the hunting conditions favourable for buzzards (Kenward et al. 2001).

3.2 Generalist resident predator — the goshawk (III)

The summer diet of goshawks in western Finland was generally based on birds, mainly corvine (the hooded crow Corvus cornix, the magpie Pica pica and the jay Garrulus glandarius) and grouse (juvenile and adult). Mammalian prey were chiefly the red squirrel (Sciurus vulgaris) and hares (Lepus spp.). The proportion of juvenile grouse constituted on average 4.7% (or 4.4% by weight), and the total grouse proportion was 25% (40% by weight) of prey (VII). We, however, did not find a clearly-shaped functional response to variations in grouse numbers (cf. Redpath & Thirgood 1999). This indicates that in summer the goshawk is an opportunistic predator and does not rely solely on grouse. We found that the productivity of the goshawk tracked the density of grouse, but the occupancy rate of goshawk territories followed grouse fluctuations with a two-year lag (III). The annual numerical ratio of goshawk to grouse was inversely related to grouse density so that goshawk numbers were four times higher at low than at high densities of grouse (III: fig. 6, Erratum). Selås & Kålås (2007) reasonably argued that the two-year time lag which we found in the occupancy rate could be not a response to fluctuations of grouse numbers, but a result of high mountain hare numbers (Lepus timidus). The latter is important winter prey that could allow more goshawk females to breed. Nevertheless, according to observations made during a period of 18 years, a high proportion of occupied goshawk territories corresponded twice to years of declining or low phases of grouse cycles (III: fig. 3). Therefore, as far as grouse are concerned, goshawks indeed had a lagging response, and the cause of this lag does not matter for the impact of goshawk predation on grouse. Delayed density-dependence in predator-prey relationships may lead to oscillations of prey numbers (Murdoch & Oaten 1975, Korpimäki & Krebs 1996, Moss & Watson 2001). The time lag in the numerical response and the inverse relation of the predator-prey ratio to grouse density suggest that goshawks may be a destabilising factor for grouse populations, especially during low phases of the latter's cycles. A similar situation was observed in relationships between the gyrfalcon and the ptarmigan in Iceland (Nielsen 1999). The negative correlation between the goshawk occupancy rate and the average proportion of juveniles in autumnal grouse populations seemed to support our supposition. However, the

39 goshawk kill rate of grouse showed no clear relations to grouse density (VII: fig. 4). The heaviest impact was on black grouse juveniles (6% mean, 11% max) and adults (9% mean, 18% max; VII: table 3). The highest value of the kill rate fell at the peak of grouse cycles (Fig. 2), leading to a relatively low mean predation impact. Of the three grouse species together, the goshawks killed on average 3.7% juveniles and 5.9% adults. As in the case of the buzzard, these findings indicate that the effects of functional and numerical responses for goshawk predation impact on grouse do not necessary facilitate each other.

3.3 How raptors share juvenile grouse by size (IV)

The analysis of prey remains from the nest sites of goshawks, common buzzards, hen harriers and sparrowhawks indicated that the sizes of grouse chicks were significantly different in the catch of these raptors: the goshawk took larger chicks than did other species (IV: fig. 2). The largest grouse chicks were found in goshawk nests and the smallest in sparrowhawk nests. The mass of the raptor female accounts for these differences in terms of stepwise linear regression (IV: table 2). Females are probably mostly responsible for hunting juvenile grouse because the latter are relatively large- or medium-sized prey for these raptors. The analysed prey remains were accumulated in the nests mostly at the end of the nestling period when females hunt actively. We performed visual graphical comparisons of juvenile grouse sizes found in raptor nests with the sizes of four grouse species according to their growth curves (obtained from literature sources), taking into account the approximate time when the young leave nests, i.e., when the prey remains were presumably accumulated in the nests — close to fledging time (IV: figs. 2 and 3). These figures indicated a large overlap in the sizes of juvenile grouse that were preyed upon by the four raptor species. Therefore, it is not possible to identify the species of grouse chicks based on their humeri size and the date of finding. We could see that the growth of juvenile grouse most likely conditioned the increase of their size in the goshawk diet during the post-fledging period (when young leave the nest and stay around but are still fed by parents) as compared to the late-nestling time (IV: fig. 3a). Such graphical analysis enables the determination of the time period when juvenile grouse can be hunted by different raptors. We compared the minimal and maximal size of juvenile grouse in the diet of each raptor with growth curves of grouse (IV: fig. 3). The overlap of these figures gave an estimate of the size and

40 age when young grouse are in danger of being hunted by all of these predators (IV: fig. 4). The young of larger grouse reach this size at an earlier age but then soon escape the size “suitable” for predation by smaller raptors (the sparrowhawk and the hen harrier). On the other hand, chicks of smaller grouse reach this size at an older age and remain vulnerable to predation by all these raptors during a longer period (IV: fig. 4). The growth of juvenile grouse makes them an increasingly more profitable food item through the summer, which may explain the increase of their proportion in goshawk diet from 7% in June to 41% in August, as found in the Oulu area (Tornberg 1997). Although these findings do not allow one to deduce the kind of strong implications that would be based on statistical analysis, they do help us to understand in general terms the structure of raptor predation on juvenile grouse. The findings demonstrate, on the one hand, how birds of prey share a common food resource, and, on the other hand, that the predation risk for grouse chicks is not constant throughout the time of their development. Juvenile mortality in grouse was found to be the highest during the first weeks of life and was mostly attributed to carnivore predation (also probably because birds of prey are more difficult to identify as predators) (Kastdalen & Wegge 1991, Park et al. 2002, Wegge & Kastdalen 2007). We suggest, therefore, that with the growth of the chicks, raptor predation becomes increasingly more important.

3.4 Prey remains in nests and in images (V, VI)

The comparison of images produced by video records and movie films with collected prey remains revealed that in general small prey were (expectedly) underestimated in food remains as compared to large prey. However, the categories “large” and “small” were not absolute and depended on the raptor species. Grouse chicks are relatively large prey for buzzards and were overestimated in prey remains, but for goshawks they are small or medium-sized prey and were slightly underrepresented in the remains (VI). This relativity of size may explain the difference between the characteristics of juvenile grouse remains in common buzzard and rough-legged buzzard nests (overestimation) (Suomus 1952, Pasanen & Sulkava 1971) and in goshawk nests (underestimation) (Sulkava S 1964). The volume of prey species or type in raptor diet also affected their representation in the diet data. A comparison of data (including literature sources) collected by direct (video recording/filming and observations from a hide) and

41 indirect methods for studying raptor diet (collection of prey remains) indicate that prey species delivered to the nest in small amounts may be overrated, but prey delivered in large amounts will most likely be underestimated in food remains. For prey delivered to the nest in a proportion of around 10–30%, depending on the weight class, remains are likely to give fairly reliable estimates whereas a higher proportion will most likely be underestimated in the remains, and a lower proportion may be overestimated. Therefore, we concluded that indirect methods may give fairly reliable results when the diet of raptors is diverse, and no prey species or category prevails excessively. However, if the studied species specialises on a certain prey, a direct method should be applied (VI). This finding indicates that the proportion of juvenile grouse in buzzard nests may be also overestimated in prey remains given the underestimation of the most numerous buzzard prey — small mammals, especially during good vole years. Another aim of the study was to test procedures for the use of digital recording equipment. Young grouse were fairly easily distinguishable in video images because of their relatively long and lightly feathered tarsus, but we were usually unable to identify them according to species. Thirty-two percent of the prey items delivered during our video surveillance sessions were identified according to species or genus, 31% — according to family and 15% — according to class (VI). These results indicate that current digital video recorders (DVRs) designed for security surveillance systems (V) may not be suitable for studies aimed at the accurate (species level) identification of raptor prey since conventional (analogue) time-lapse video recorders seems to obtain more detailed images (e.g. Rogers et al. 2005, Smithers et al. 2005). However, advances in digital technology (see Pierce & Pobprasert 2007 for one of the most recent examples of its use in an ornithological study) will certainly enable the use of DVRs for detailed observations of prey in the near future. Young and adult hawks demonstrated full tolerance to the camera next to their nest, and our study caused no nesting failures. Although we were unable to make any conclusions regarding the influence of the study on the further nesting of buzzards because the number of their nests varied between the years of the study (probably depending on vole abundance), many goshawk nests were occupied in the following years after the surveillance. Our experience of using digital video equipment indicates that it is an efficient, relatively cheap and non- intrusive tool for long, detailed observations of various aspects of nesting biology. This equipment enables good quantitative and size assessment of delivered prey

42 and can provide details of animal behaviour that are difficult to obtain by other means (V). (For example, we observed on video images the fall of the youngest chick of a rough-legged buzzard from a relatively small nest when it was pushed out by an older sibling.) Although the image quality may not always be sufficient for reliable prey identification, technical surveys are somewhat more efficient in the identification of prey brought to the nest as compared to observations from a hide (VI). Our detailed description of the method and its pitfalls (V) can be used as a manual for similar studies.

3.5 Total impact of avian predators on populations of grouse (VII)

3.5.1 Kill rate, impact and role of raptors in grouse juvenile mortality

Our results indicate that in June–July, birds of prey usually killed a relatively small amount of grouse chicks. The mean values of their predation impact for 10 years from 1984 to 1993 did not exceed 11%, and the maximal impact reached 18% for hazel grouse and 16% for black grouse (Fig. 3, Table 1). Totally nesting goshawks, common buzzards and hen harriers were killing 5 to 15% (on average, 8%) of juvenile capercaillie, black grouse and hazel grouse put together. These losses to raptors made up 7–24% of grouse juvenile mortality during two months (VII: table 2). Juveniles of black grouse were under the heaviest predation pressure, followed by hazel grouse (Fig. 3). Among the adult grouse, hazel grouse suffered from the heaviest predation impact (Table 1). The goshawk was the main “grouse killer” among these raptors, but in some years common buzzards and hen harriers were catching more grouse chicks than were goshawks (Fig. 2). Among black and hazel grouse more chicks perished as a result of raptors’ killing grouse hens, while in the case of capercaillie chicks, direct elimination was a more important cause of mortality (VII: table 2). In terms of the General Linear Models, the negative effects of factors related to weather and vole abundance account for the high proportion (60%) of variation in juvenile mortality of three grouse species, whereas the raptor predation rate indicated only marginally significant negative effects. Together these results point towards mammalian predators (acting in accordance with the APH) as the main factor influencing grouse population dynamics during the summer.

43 Table 1. Average (with standard errors) and maximum impacts (in %) of raptors on juveniles, adults and the whole populations of capercaillie, black grouse and hazel grouse during June–July in 1984–1993. (The impact on capercaillie and black grouse does not account adult males.)

Grouse Goshawk Common buzzard Hen harrier Total species mean s.e. max mean s.e. max mean s.e. max mean s.e. max Capercaillie juv. 2.5 0.5 5.2 1.2 0.2 2.2 1.3 0.6 6.8 5.1 0.8 10.5 ad. 3.4 0.7 6.4 — — — — — — 3.4 0.7 6.4 total 1.8 0.3 3.7 0.9 0.2 1.6 0.9 0.4 4.8 3.6 0.6 7.4 Black grouse juv. 6.0 0.9 11.1 3.7 0.4 6.2 1.2 0.6 6.0 10.9 1.0 15.9 ad. 9.3 1.6 18.2 3.5 0.6 6.8 — — — 12.8 1.3 16.1 total 6.2 0.9 10.7 3.2 0.4 5.5 0.9 0.4 4.4 9.8 0.9 14.2 Hazel grouse juv. 2.7 0.9 10.2 2.3 0.2 3.9 3.6 1.2 12.1 8.6 1.6 17.7 ad. 4.4 1.4 16.2 2.5 0.3 4.0 7.9 2.6 21.7 14.9 3.2 29.7 total 2.6 0.9 9.6 2.4 0.2 4.0 3.5 0.8 9.0 8.5 1.3 15.9

Although a direct comparison of our results with other studies is difficult because of different time scales, raptor predation impact on grouse in western Finland seems to be at a similar level or slightly lower than in other places within the boreal zone of Fennoscandia and Russia. However, this impact varies strongly among species depending on their abundance (Lindén & Wikman 1983, Widén 1987, Borchtchevski 1993, Tornberg 2001VII). In North America (in more southern latitudes — in Alberta, Manitoba, Wisconsin) predation impact on the ruffed grouse (Bonasa umbellus) seems to be lower, but the relative role of raptors (mainly the goshawk and the great horned owl) is greater as compared to mammalian predators (Rusch & Keith 1971, Rusch et al. 1978, 1989, Small et al. 1991). There are only few studies where raptor predation impact on grouse chicks has been considered. In the area of Oulu (200 km northward from our study area), Tornberg (2001) found that during the nesting season the predation impact of goshawks on combined grouse chick numbers was 7%, which is close to the maximum corresponding value in our study. In the Scottish moors, predation of hen harriers on chicks of red grouse (Lagopus lagopus scoticus) can be quite high: harriers removed 28% of hatchlings during the first two months, which was the main cause of grouse mortality (see also Redpath 1991, Thirgood et al. 2000).

44 20 30

2 18 25 16

14 20 12

10 15

8 index Vole 10 6 4 5 2

Impact, %, and grouse density, ind./km grouse density, %, and Impact, 0 0 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 Years capercaillie black grouse hazel grouse average index

Fig. 3. Annual variation in the pooled predatory impact of goshawks, buzzards and harriers on juveniles of three grouse species (bars) and mean vole index (line).

However, Picozzi (1978) found harrier predation impact on red grouse chicks to be 7%, which is close to the maximum values of harrier impact on all grouse chicks in our study. Proportion of red grouse chicks killed by harriers was higher when grouse density was low (Redpath 1991). According to the APH, the kill rate of juvenile grouse by vole-based generalist predators (in our case — buzzards and harriers) should be higher in years when small mammals are scarce (Hagen 1952, Lack 1954, Angelstam et al. 1984, Small et al. 1993). We found that the abundance of small mammals had a significant negative relationship with chick mortality (VII: table 4, fig. 8). However, the combined kill rate of grouse by buzzards and harriers peaked during only one of the decline phases of vole cycles (Fig. 2). Interestingly, that the kill rate of juvenile grouse by three raptors together indeed amplified in the years when vole numbers dropped, but these increases had different reasons. In one year the increases had to do with harrier predation, and in two other years — with the goshawk. In none of these cases did buzzard predation play any visible role (Fig. 2). Furthermore, contrary to our expectation, buzzard and harrier kill rates of

45 grouse were not coordinated. Given the limitations of available data, harriers’ predation was analysed only approximately. However, this mismatch between two vole-based predators questions the possibility of using any of them as an indicator of the way the whole vole-predator guild operates, at least without a special study. Whereas the effect of goshawks on grouse population dynamics may be destabilising (III), the effects of vole-eating buzzards and harriers, even if they do not coincide, seem to be the opposite (Hanski et al. 1991). This may be the reason why the total effect of avian predators on grouse mortality was not clearly distinguished. The high kill rates of grouse in 1986 coincided with a peak density of stoats (Mustela erminea) and least weasels (M. nivalis), as well as a high proportion of grouse in the diet of red foxes in our study area (Korpimäki et al. 1991, Dell’Arte et al. 2007). The low numbers of voles in this year could force these predators to search for alternative prey, including chicks of grouse (Korpimäki et al. 1991). Carnivores were found to be responsible for 2/3 of the total predation loss of capercaillie chicks in Norway (Kastdalen & Wegge 1991, Wegge & Kastdalen 2007). In an experimental study in northern Sweden, red foxes and pine martens (Martes martes) have been shown to be the key predator species that influence grouse breeding success (Marcström et al. 1988). The abundance of foxes and martens affected grouse breeding success in Finland as well (Kurki et al. 1997, Kauhala et al. 2000, Kauhala & Helle 2002). Furthermore, APH-type predation may have been enhanced by forest fragmentation creating grassy habitats suitable for field voles and their predators (Henttonen 1989), which leads to increased densities of these predators and losses of grouse broods to mammalian predators (Storaas et al. 1999, Kurki et al. 2000, but see Borchtchevski et al. 2003). Our evidence for increased mortality of juvenile grouse in the years of declining vole numbers and unfavourable weather conditions (VII) is mostly correlative. Therefore, we cannot exclude the possibility of the influence stemming from some external factor affecting both voles and grouse, e.g., plant food availability (Selås 1997, 2003). On the other hand, unfavourable weather conditions can also make grouse chicks more vulnerable to mammalian and avian predators (Kastdalen & Wegge 1989, Wegge & Kastdalen 2007, Ludwig 2007), which may be supported by our results.

46 3.5.2 Potential impact

As the kill rate did not show a clear relationship to grouse density, we cannot rule out the possibility that the highest kill rates of these raptors may coincide with one another, as well as with the lowest grouse density. This is specially so since the numerical response of goshawks followed grouse numbers with a time lag, and goshawk-to-grouse ratio was negatively related to grouse density (III). Therefore, we modelled such a situation by comparing the highest kill rate and the lowest density of grouse occurring during the studied years. In this case the pooled raptor predation impact on three species of juvenile grouse would amount to 25% while the highest potential impact of these raptors would be 13% for the capercaillie, 20% for the black grouse and 30% for the hazel grouse. These values probably closely indicate the highest potential impact that diurnal raptors can have on juvenile grouse in our study area. Although we do not know whether such a situation ever the case, the possibility of such high impact by only three species of raptors may indicate that predators together may be one among other impulse factors for population perturbations of grouse (Kaitala et al. 1996). However, currently there is no clear answer as to whether these values are really “high enough.”

3.5.3 Problems of the approach, sensitivity of the model and reliability of the results

Most of the parameters used for the estimation of predation impact (Fig. 1, VII) are variable in nature. Furthermore, some of them come from distinct (though close) areas. We were unable to take into account all these variations and had to use mean values instead. However, we attempted to test the sensitivity of the model's final results to variations in some of the input data by increasing or decreasing these data by 10% and measuring the corresponding change in the predation impact. The strongest effect was induced by the change in the numbers of female grouse in spring (the average change of the impact value among the three grouse species was +14% and −6.5%), followed by a change in the average density of territories occupied by all raptors (−10% and +10% change of the predation impact value, respectively). The corresponding changes of the impact were similar for all grouse species (VII: fig. 7). We also checked the effect of juvenile grouse species allocation in the diet since in the model this was done approximately (VII: appendix 1). When the

47 proportion of capercaillie chicks among all juvenile grouse in the diet of goshawks was changed from 30% to 40% or 20% (at the cost of respective change in the proportion of black grouse while keeping the proportion of hazel grouse constant), the value of the goshawk's impact on juvenile capercaillie changed from 2.5% to 2.8% or 2.3%, respectively. The effect for the other grouse species was even smaller (VII: fig. 7). The reliability of the diet data elicits a major concern because these data were estimated based on prey remains that may give a biased image of raptor diet (VI). However, our comparison of data from video/movie camera surveillance and collected prey remains suggests that prey remains give quite a correct picture of real proportions among different kinds of prey, unless a given raptor is specialises on one prey (VI). Because small mammals clearly prevail in the diet of common buzzards (at one of the nests we observed 21 prey, most of which being voles, delivered during just one day), we attempted to evaluate the influence of this possible bias on our final results. Based on the difference between the numbers of grouse specimens found in nests and observed in film and video images (VI), we calculated correction coefficients and applied them to the original diet data of raptors. The ensuing values of predation impact changed by 1–2%, i.e., even less than suggested by the sensitivity analysis which tests a 10% change in the diet proportion (VII: fig. 7). Therefore, we surmise that possible bias in diet data would not have a strong influence on the final results. There are, however, some other potential biases that could not be controlled in this study. First of all, we shall admit that without an estimation of the non- breeding part in a raptor population (floaters), it is not possible to have a reliable evaluation of a given species' numerical response (Rohner 1996, Hunt 1998, Newton & Rothery 2001). Besides, it should be remembered that the abundance of grouse was not estimated exactly within the area where the raptor populations were studied. Instead, data for the whole province of Vaasa was taken. Such data may be more suitable for analysis of large-scale population dynamics. Furthermore, the estimations of grouse population size and the proportion of juveniles based on hunter counts may be randomly biased (Hörnell-Willebrand et al. 2006). Intra-guild predation (impact of one grouse predator species on another) (e.g. Milonoff 1994) was not addressed in our study; neither was the predation of eagle and Ural owls that inhabit our study area and can catch grouse chicks, especially in poor vole years (Korpimäki et al. 1990, Korpimäki & Norrdahl 1997).

48 The above-mentioned reflections led us to the conclusion that the chosen approach for the evaluation of the role of avian predation in grouse population dynamics might have been not the best possible one. In the absence of precise information on all aspects of ecology and population dynamics of both predator and prey from one and the same area and given the limitations of the available data, a more productive approach, perhaps, would be modelling grouse population dynamics and including predation in the model as one of the factors. Based on grouse population dynamics, the losses to predators in such model could be compared with our estimations of grouse kill rates by raptors.

50 4 Concluding remarks

In this study, it has been demonstrated that juvenile grouse are an important food resource for several species of raptors, constituting primary or alternative prey. A vole-based generalist predator, such as the common buzzard, switched its diet from voles to small game, and its nesting performance also depended on vole numbers. However, the final effect on grouse of common buzzard predation was insignificant in relation to numbers of juvenile grouse. Thus, the real effect of switching to alternative prey may not necessary be much detrimental for the prey population because functional and numerical responses do not always enhance each other in terms of total response. Furthermore, the final effects of different vole predators on grouse may not be in phase. This finding illustrates that predation pressure cannot be assessed only on the basis of functional or numerical responses separately. Goshawk predation, on the other hand, may be an important factor for the survival of juvenile grouse and, potentially, for their population dynamics since the goshawk's numerical response lagged behind fluctuations of grouse numbers. However, although total raptor predation impact indicated a negative effect on juvenile grouse mortality, we did not find strong evidence of regulation in this predator-prey system. In boreal forests, the factors of grouse mortality do not operate as one, and there is no single power that could be responsible for cycles in grouse populations. Nevertheless, fur-bearing predators are probably a more important factor determining grouse numbers in the autumn than birds of prey. Therefore, a special study would be needed in order to estimate how well responses of all grouse predators are coordinated. The regular cycles of Finnish grouse populations disappeared in the middle of the 1980s while visible cycles vanished in the mid-1990s (Helle et al. 2002, Ranta et al. 2004). Unfortunately, the existing raptor data from our study area do not cover the following period; therefore, we cannot check possible changes in raptor diet and nesting during this perturbation. The number of assumptions and the averaging of the original data in our model, as well as the relatively small time scale of the present study, do not allow us to take these results as ultimate ones. However, we believe that they still may closely indicate the processes occurring in nature. The effect of predation on the reproductive success of grouse was found to be an important factor in the bird's long-term population dynamics (Ludwig 2007). Our study demonstrates how birds of prey may contribute to integrated predation.

51 These results should be tested by a close look at grouse population dynamics with the presence and absence of predators. Inasmuch as an experimental study with total predator removal is not likely in light of possible political (ethical) and economical reasons, there is a need for a comprehensive model of grouse population dynamics which would be based inter alia on the results presented here. Furthermore, an integrated study of prey and predators in relatively small natural refuges (or refuges created by forestry) may shed more light on their interaction.

52 References

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64 Original papers

The published papers reprinted with kind permissions from Wiley-Blackwell Publishing (I, III), Finnish Zoological and Botanical Publishing Board (II), The Raptor Research Foundation, Inc. (IV), Springer Science+Business Media (V) and BirdLife Finland (VI).

Original publications are not included in the electronic version of the dissertation.

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ACTA UNIVERSITATIS OULUENSIS SERIES

492. Siira, Antti (2007) Mixed-stock exploitation of Atlantic salmon (Salmo salar L.) and seal-induced damage in the coastal trap-net fishery of the Gulf of Bothnia. Challenges and potential solutions 493. Donnini, Serena (2007) Computing free energies of protein-ligand association 494. Syrjänen, Anna-Liisa (2007) Lay participatory design: A way to develop information technology and activity together 495. Partanen, Sari (2007) Recent spatiotemporal changes and main determinants of aquatic macrophyte vegetation in large lakes in Finland 496. Vuoti, Sauli (2007) Syntheses and catalytic properties of palladium (II) complexes of various new aryl and aryl alkyl phosphane ligands 497. Alaviuhkola, Terhi (2007) Aromatic borate anions and thiophene derivatives for sensor applications 498. Törn, Anne (2007) Sustainability of nature-based tourism 499. Autio, Kaija (2007) Characterization of 3-hydroxyacyl-ACP dehydratase of mitochondrial fatty acid synthesis in yeast, humans and trypanosomes 500. Raunio, Janne (2008) The use of Chironomid Pupal Exuvial Technique (CPET) in freshwater biomonitoring: applications for boreal rivers and lakes 501. Paasivaara, Antti (2008) Space use, habitat selection and reproductive output of breeding common goldeneye (Bucephala clangula) 502. Asikkala, Janne (2008) Application of ionic liquids and microwave activation in selected organic reactions 503. Rinta-aho, Marko (2008) On monomial exponential sums in certain index 2 cases and their connections to coding theory 504. Sallinen, Pirkko (2008) Myocardial infarction. Aspects relating to endogenous and exogenous melatonin and cardiac contractility 505. Xin, Weidong (2008) Continuum electrostatics of biomolecular systems 506. Pyhäjärvi, Tanja (2008) Roles of demography and natural selection in molecular evolution of trees, focus on Pinus sylvestris 507. Kinnunen, Aulis (2008) A Palaeoproterozoic high-sulphidation epithermal gold deposit at Orivesi, southern Finland 508. Alahuhta, Markus (2008) Protein crystallography of triosephosphate isomerases: functional and protein engineering studies

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