VIABILITY ASSESSMENT OF A RECENTLY REINTRODUCED ELK (CERVUS ELAPHUS)

POPULATION IN ONTARIO, CANADA

A Thesis Submitted to the Committee on Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Faculty of Arts and Science

TRENT UNIVERSITY

Peterborough, Ontario, Canada

© Copyrighted by Terese E. Mcintosh 2012

Environmental and Life Sciences Ph. D. Graduate Program

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1+1 Canada ABSTRACT

VIABILITY ASSESSMENT OF A RECENTLY REINTRODUCED ELK (CERVUS ELAPHUS) POPULATION IN ONTARIO, CANADA

Terese E. Mcintosh

From 1998-2001, 443 elk were translocated from Elk Island National Park, Alberta and released into four primary release areas in Ontario, including Nipissing-French River,

Bancroft-North Hastings, Lake Huron-North Shore, and Lake of the Woods. The objectives of my research were to assess the viability of the reintroduced elk population in

Ontario and investigate management options that encourage demographic growth and stability.

To accurately estimate the size and composition of elk populations in Ontario, a sightability model including the variables elk group size and activity, dominant tree type, percent canopy cover, and percent conifer cover provided increased reliability for estimating elk numbers compared to existing methods. This model may be useful in other areas where elk density is low and sightability is poor due to dense forest cover.

Examination of cause-specific mortality revealed that post-capture myopathy and transportation related injuries were an important immediate cause of death for translocated elk, and should be considered a predictable factor in planning. Analyses of factors influencing survival revealed that method of introduction to the novel landscape and behaviour in the first years following release were important determinants of elk survival.

Prolonged holding time prior to release can improve chances of survival.

Stochastic population models predicted that elk populations in the Bancroft-North

Hastings and Lake Huron-North Shore regions are at relatively low risk of extinction, while those in the Nipissing-French River and Lake of the Woods regions are likely to decline over

ii the next 25 years. Management efforts focused on improving calf survival and recruitment levels comparable to growing elk populations may be effective. Reducing transmission of

Parelaphostrongylus tenuis in the most affected region, Bancroft-North Hastings, is also important and the potential impact of the parasite on eastern elk populations should be monitored.

Finally, although likely not important in the short-term, genetic diversity may be an important factor deterrnining future persistence of elk populations in Ontario. Maintaining positive population growth rates, increasing population size, and maintaining population stability are strategies that favour retention of genetic diversity. Genetic augmentation should also be a consideration in regions with small populations and relatively low rates of population increase.

Key words: elk (Cervus elaphus), Ontario, reintroduction, management, survival, mortality, population viability

ill ACKNOWLEDGEMENTS

Thank you to my advisors, Dr. Rick Rosatte and Dr. Dennis Murray, and committee members Dr. Brad White and Dr. Joe Hamr. This project would not have been possible were it not for your unending patience and support. Furthermore, your teaching and advice has been critical to my continued development as a researcher and scientist.

Thank you to Dr. Chris Davies and Dr. Art Rodgers. Your thoughtful review of my thesis was very much appreciated and, no doubt, helped to strengthen the end product.

Chapter 2 and Chapter 4 of my thesis have been published. While largely my own work, co-authors Dr. R. Rosatte, Dr. D. Murray, Dr. J. Hamr, Dr. D. Campbell, Dr. K.

Welch, Dr. D. Fournier, and Dr. M. Spinato provided valuable input and advice.

This project would not have been possible without the efforts of the other students and field staff working at each of the elk restoration sites across Ontario. In particular, I thank Nancy Dewar, Mark Ryckman, Adelle Yott, Debbie Jenkins, Megan Hazell, Jason

Stevenson, Greg Element, and Arthur Dupius for providing sound data on which to build my work. I also thank the Kenora, Bancroft, Sudbury, and Blind River MNR staff for ongoing technical and logistical support and the Ontario Ministry of Natural Resources

Aviation Services for many safe hours of flying. I also thank keen aerial observers Megan

Hazell, Joe Hamr, Ben Cox, Ivan Filion, Greg Element, Arthur Dupuis, Ken Mills, Jamie

Mills, Kaitlin Byrick, Chris Kyle, John O'Donnell, and Julia Philips.

Thank you to Chris Kyle and Kristyne Wozney for teaching me all I know about genetics and helping me to analyse my data. I appreciate you taking the time to provide much needed direction and guidance.

Funding and support for this project was provided by the Ontario Elk Restoration

Committee, the Ontario Ministry of Natural Resources Wildlife Research and Development

iv Section, the Ontario Federation of Anglers and Hunters, Cambrian College, and the members and organizations of the Ontario Elk Restoration Program.

Finally, I am very grateful for the unwavering support, encouragement, and patience of my family, especially Greg, Eli, Jude and Baby #3. This work is as much yours as it is mine.

v TABLE OF CONTENTS

ABSTRACT OF DISSERTATION ii

ACKNOWLEDGMENTS iv

LIST OF FIGURES viii

LIST OF TABLES ix

CHAPTER 1: INTRODUCTION 1 Elk Population Dynamics 4 Life History Traits of Elk 4 Reproduction 4 Survival 7 Rates of Increase 12 Variability in Rates of Increase and Density Dependence 13 Elk Population Genetics 16 Modelling Elk Population Dynamics 19 Literature Cited 20

CHAPTER 2: DEVELOPMENT OF A SIGHTABILITY MODEL FOR ELK (CERVUS ELAPHUS) RECENTLY REINTRODUCED TO ONTARIO, CANADA 32 Abstract 32 Introduction 33 Study Area 35 Methods 35 Aerial Surveys 35 Data Analysis 37 Results 39 Model Validation 39 Discussion 40 Management Implications 44 Literature Cited 44

CHAPTER 3: PATTERNS OF MORTALITY AND FACTORS INFLUENCING THE SURVIVAL OF ELK (CERVUS ELAPHUS) RECENTLY REINTRODUCED TO ONTARIO, CANADA 51 Abstract 52 Introduction 52 Study Area 55 Methods 56 Animal Capture and Monitoring 56 Assessment of Mortality Factors 57 Survival Estimation and Analysis 57

VI Results 60 Mortality 60 Survival 61 Discussion 63 Management Implications 66 Literature Cited 67

CHAPTER 4: EVIDENCE AND IMPLICATIONS OF PARELAPHOSTRONGYLUS TENUIS INFECTIONS IN ELK (CERVUSELAPHUS) RECENTLY REINTRODUCED TO ONTARIO, CANADA 80 Abstract 80 Casel 81 Case 2 86 Discussion 86 Literature Cited 90

CHAPTER 5: GENETIC VARIABILITY IN AN ELK (CERVUS ELAPHUS) POPULATION RECENTLY REINTRODUCED TO ONTARIO, CANADA 96 Abstract 96 Introduction 97 Study Area 100 Methods 101 Sample Collection and DNA Isolation 101 Statistical Analyses 103 Results 103 Discussion 104 Management Implications 109 Literature Cited 109

CHAPTER 6: POPULATION VIABILITY OF ELK (CERVUS ELAPHUS) RECENTLY REINTRODUCED TO ONTARIO, CANADA 118 Abstract 118 Introduction 119 Study Area 121 Methods 122 Population Estimation 122 Recruitment 123 Survival 124 Population Viability Analysis 125 Results 128 Recruitment 128 Survival 129 Population Viability Analysis 129 Discussion 131 Management Implications 135 Literature Cited 136

vn CHAPTER 7: GENERAL CONCLUSIONS 151 Management Implications 155

Vlll LIST OF FIGURES

Figure 1.1: Historical distribution of elk in a) eastern North America, and b) Ontario, Canada 30

Figure 1.2: Map depicting four elk release sites in Ontario, Canada 1998-2001 31

Figure 3.1: Kaplan- Meier survival rates for elk reintroduced to four release sites in Ontario including Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron-North Shore (LHNS) from 1998-2001. Cumulative time 0 represents the release day into they study rather than calendar time 75

Figure 4.1. Parelaphostrongylus tenuis larvating eggs in the brain meninges of the bull elk (Case 1): (a) degenerate larvae, (b) normal looking larva, (c) larva surrounded by eosinophils. Arrows indicate larvae (a, b) or eosinophils (c). Bar = 20 mm 94

Figure 4.2. Photos of cross sections of brain from the cow elk (Case 2) showing (a) a submature or adult nematode (compatible with P. tenuis) in a cerebral sulcus bar =100 mm; (b) (c) larvating nematode eggs (compatible with P. tenuis) in the meninges (photos by D. Campbell); (b) bar = 50 mm, (c) bar =100 mm 95

Figure 6.1: Distribution of fecal progesterone concentrations in wild elk samples from each release site in Ontario, Canada (2004-2005), where concentrations of 10 [xg/g wet fecal mass were considered not pregnant, >13 jxg/g wet mass indicated pregnancy, and 10-13 p.g/g wet mass was equivocal 143

Figure 6.2: Predicted number (+/- 95% CI) of female elk in the a. NFR, b. BNH, c. LOW, and d. LHNS regions of Ontario, Canada over a 25 year time horizon :.146

Figure 6.3: Cumulative probability of quasi-extinction based on stochastic population projections for female elk in the a. NFR, b., BNH, c. LOW, and d. LHNS regions of Ontario, Canada over a 25 year time horizon. Solid line=30 elk, short dashed line=100 elk, long dashed line=200 elk 147

Figure 6.4: Changes in the cumulative probability of quasi-extinction for female elk released in the LOW region of Ontario, Canada (2000-2001) resulting from increases in the number elk (increases of 10%-100%) released at the site 148

Figure 6.5: Changes in the cumulative probability of quasi-extinction (threshold^ 100) for female elk released in the LOW region of Ontario, Canada (2000-2001) resulting from increases in calf survival (10%-50%) 149

Figure 6.6: Changes in the population growth rate of female elk reintroduced to the BNH region of Ontario, Canada (2000-2001) resulting from a 5%-25% drop in yearling and adult female survival representative of loss related to Parelaphostrongylus tenuis 150

IX LIST OF TABLES

Table 2.1: Candidate sightability models for surveys of elk in Ontario, Canada in March 2004 and 2005. For each logistic regression model I include number of parameters (K), biased- corrected Akaike's Information Criterion (AICc), AlCc difference (A,), AlCc weight (a/), and percent accuracy (n — 49) 48

Table 2.2: Parameter estimates for the best model developed to explain sightability of elk in Ontario, Canada, January 2000 - December 2005 49

Table 2.3: Ontario elk sightability modeP predictions, accuracy, and precision as tested on 12 survey plots in March 2006. I included estimates of the total population based on actual counts (N) and the sightability corrected count (iVA) 50

Table 3.1: Sex and age breakdown of radio-collared elk transported to the Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron- North Shore (LHNS) regions of Ontario from 1998-2001 72

Table 3.2: Description of variables used in analyses of elk survival in Ontario. The first set of models included all elk reintroduced to Ontario, with release site as a categorical variable. The second analysis included more detailed variables reflecting environmental and behavioural characteristics of elk reintroduced to the BNH region of Ontario 73

Table 3.3: Percent cause-specific mortality for elk reintroduced to 4 sites in Ontario, Canada including Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron-North Shore (LHNS) from January 1998-December 2005. Sample sizes are in parentheses 74

Table 3.4: Candidate models for elk survival in four release sites in Ontario, Canada December 1999 to December 2005. For each Andersen-Gill model I include number of parameters (K), Akaike's Information Criterion (AIC), AIC difference (A,), and AIC weight (a/), and goodness-of-fit (P) (n— 404). Only models with <5 A, are provided 76

Table 3.5: Model averaged hazards ratios and unconditional standard errors for the top 6 (<4 A,) models developed to explain survival of elk in Ontario, Canada, December 1999- Decmber2005 77

Table 3.6: Candidate models for elk survival in the BNH region of Ontario, Canada December 1999 to December 2005. For each Andersen-Gill model I include number of parameters (K), Akaike's Information Criterion (AIC), AIC difference (A,), and AIC weight (u>), and goodness-of-fit (P) (n — 116). Only models with <5 A, are provided 78

Table 3.7: Model averaged hazards ratios and unconditional variances for the top 6 (<4 AJ models developed to explain survival of elk released in the BNH region of Ontario, Canada, January 2000-Decmber 2005 79

x Table 5.1: Genetic diversity in the four Ontario elk populations at release, Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake Huron-North Shore (LHNS), and Lake of the Woods (LOW). Sample size (n), expected heterozygosity (Hh), observed heterozygosity (H0), and number of unique alleles (No of Alleles) are reported for each population 116

Table 5.2: Expected heterozygosities (H,J for elk populations in the Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake Huron-North Shore (LHNS), and Lake of the Woods (LOW) regions in Ontario, Canada at 12 microsatellite loci 117

Table 6.1: Age breakdown of female elk reintroduced to Ontario from 1998-2001 142

Table 6.2: Demographic, variables used in stage-based model for female elk released into the NFR, BNH, LOW, and LHNS regions of Ontario, Canada (1998-2001) 144

Table 6.3: Sensitivity and elasticity of vital rates for female elk released into NFR, BNH, LOW, and LHNS regions of Ontario, Canada (1998-2001) 145

XI CHAPTER 1 INTRODUCTION

Reintroduction, defined as an attempt to establish an extirpated species in an area of historical occupation, has become an increasingly common tool in conservation biology; however, despite numerous examples, generalizations remain limited about why reintroduction programs for some species, or in some areas, are successful and others are not (IUCN 2003) Theoretical considerations predict that programs that release greater than

20 animals into the core of their historical distribution, where they can disperse and exploit good quality habitat are most successful (Griffith et al. 1989, Wolfe et al. 1996, Fischer and

Lindenmayer 2000, Komers and Curman 2000). Yet even when these conditions are met, much uncertainty exists as to whether a given reintroduction will be successful. Failures can arise when the original cause of decline or extirpation remains unchanged (Armstrong and

Mclean 1995, Fischer and Lindenmayer 2000), habitat requirements are poorly defined

(Harig and Fausch 2002, Owen-Smith 2002), or novel risks now occur (O'Bryan and

McCullough 1985, Short et al. 1992, Armstrong and Mclean 1995). Critical experiments assessing the viability of reintroduced species are limited, and further advancement is unlikely to occur if studies continue to focus only on the outcome of actual reintroductions that are designed to maximize success rather than gain insight into factors influencing both success and failure.

In North America, large mammals, such as elk (Cervus elaphus), have frequently been the subject of reintroduction attempts (Seddon et al. 2007). Elk are highly valued for consumptive and non-consumptive purposes (Conover 1997, Bunnell et al. 2002) and have been the subject of extensive and intensive restoration efforts in North America (Witmer

1990, Sargeant and Oehler 2007). Although reintroductions have been important for the

1 recovery of elk populations in western North America, they have had limited success in the

east. Since the early 1900's ten eastern states and one province (Ontario) have attempted to

establish free-ranging elk populations through reintroduction (Witmer 1990). However,

eight of the eleven attempts were unsuccessful (Larkin et al. 2003). In general, most of

these reintroduction attempts have not been adequately monitored or evaluated post-release,

thereby prohibiting the identification of factors influencing the success or failure of the

effort (Griffith et al. 1989, Kleiman 1996). Better information is required to improve future reintroduction methodologies and to develop management strategies that encourage population growth and demographic stability in eastern landscapes.

Once native to Ontario, elk (Cervus elaphus) occupied the deciduous forest westward

to 95 degrees longitude, northward to the 47c parallel, and southward to the 34' parallel

(O'Gara and Dundas 2002) (Figure 1.1). However, as was the case across most of North

America, increasing human setdement, as well as demands for meat and agricultural land resulted in the extirpation of these elk during the late 1800s and early 1900s (Ranta 1979,

Witmer 1990, Ceballos and Ehrlich 2002). There have been several previous attempts to

reintroduce elk to the province; mostly notably in the 1930s when elk were reintroduced to

several locations in central Ontario. However, due to concerns regarding the transmission

of the giant liver fluke, Fascioloides magna, to livestock, most of these animals were destroyed

(Kingscote 1950, 1951, Addison 1997). Two small remnant populations managed to survive in the Nipissing-French River area of Ontario, and in 1996 they were estimated to number

approximately 60 animals (Bellhouse and Broadfoot 1998).

In 1997, the Government of Ontario announced a provincial elk restoration initiative, and from 1998 to 2001 a total of 460 elk were translocated from Elk Island

National Park (EINP), Alberta and released into four primary and distinct release areas in

2 Ontario, including Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake

Huron-North Shore (LHNS), and Lake of the Woods (LOW) (Rosatte et al. 2007) (Figure

1.2). Although plans for the restoration of elk in Ontario called for the release of at least 200 elk at each site with a ratio of 2.5 female elk to 1 male elk, concerns regarding the transmission of Chronic Wasting Disease have halted the import of the elk into the province (Rosatte et al. 2007), thereby creating four relatively small and isolated elk populations that are inherently more vulnerable to population decline and extinction. There is therefore a critical need for the development of a methodology in which the future viability of the elk population in Ontario and those at each individual release site can be assessed. Furthermore, there is a need to identify factors important to the success or failure of reintroduction and develop management strategies that encourage short and long-term demographic growth and population stability.

The specific objectives of my research were to i) develop an accurate method of estimating the size and composition of the elk population in Ontario; ii) evaluate the factors determining the survival of elk in Ontario, including an examination of the impacts of meningeal worm, Varelaphostrongylus tenuis; iii) collect empirical data on the level of genetic diversity in the reintroduced elk population; and iv) to create a population model in which the predicted viability of the Ontario elk population could be assessed and management options that encourage demographic growth and stability evaluated. The results of this study can help both researchers and managers to better understand, predict, and possibly mitigate factors affecting the dynamics of the Ontario elk population. Furthermore, the reintroduction of elk into Ontario may be useful for testing basic ecological theory, providing semi-controlled conditions in which community and ecosystem processes can be studied without the loss of complexity. In particular, this study can provide insight into the

3 demographic problems inherent in both small and establishing populations and will aid in identifying the factors influencing the success or failure of new and establishing populations.

ELK POPULATION DYNAMICS

The factors that explain changes in population size are a central theme in ecology, and studies of population dynamics are of great interest for population ecology, wildlife management, and conservation biology (Morris and Doak 2002). Furthermore, population growth and stability are the most important response variables determining the success of any wildlife reintroduction effort. Although a wide variety of factors influence the growth and stability of a population, they can be combined into a limited set of rates that includes the life history of the species, the average environmental conditions, the extrinsic variability in the biotic and abiotic factors influencing a population (environmental stochasticity), and the intrinsic variability caused by small population sizes (demographic stochasticity). This set of processes, in turn, influence the mean and variance of birth and death rates, which ultimately determine the overall growth rate of the population (Morris and Doak 2002).

LIFE HISTORY TRAITS OF ELK

Reproduction

Elk are seasonal breeders whose reproductive strategy is adapted to fluctuations in forage quantity and quality (Sadlier 1987). Female elk aged 3.5 to 7.5 are generally regarded as the most capable breeders and are considered the most important factor in the productivity and growth of an elk population (Flook 1970). Female elk are bred annually during the rutting period (September and October), usually producing a single calf in late

May or early June (Raedeke et al. 2002). It is estimated that in most populations nearly 95% of adult female elk are fertile; however, pregnancy rates between 72% and 90% are typically

4 observed (Raedeke et al. 2002). Pregnancy rates for elk in EINP, Alberta, the source population for the Ontario elk reintroduction, are estimated to be between 80 and 90%

(Rosatte et al. 2003).

Reproduction at an early age is thought to be an important parameter influencing population growth rate for most herbivores with low birth and death rates and long life spans (K-selected) (Cole 1954, McCullough 1979). In most western elk populations, females breed for the first time at age 2.5, with pregnancy rates for yearlings ranging from 0 % to

80% (Flook 1970, Bubenik 1985, Hudson et al. 1991). Although the proportion of yearling females that successfully conceive is highly variable from one population to another and from one year to another (Flook 1970), it is thought to be influenced by individual growth and development, which in turn, is affected by the environment (Wisdom and Cook 2000).

Hudson et al. (1991) suggested that females must achieve 65-70% of their adult body mass before they can successfully reproduce. Correspondingly, several studies have also reported that female calves that experience a difficult winter were less likely to breed as yearlings

(Raedeke et al. 2002). Similarly, Houston (1982) reported that yearling pregnancy rates were negatively correlated with the severity of the previous winter and population density.

The male segment of ungulate populations usually do not affect reproduction rates, provided that sufficient numbers of males are present to breed all mature females (Caughley

1977). The optimal adult male to female ratio for elk reproduction and population growth is difficult to determine and few studies have reported any correlation between the lack of males and declines in calf production. Bubenik (1985) suggested that 25 adult males per 100 adult females would maintain optimal calf production, although Noyes et al. (1996) observed significant population growth with 18 adult males per 100 adult females. Some studies have concluded that as few as 3 to 10 adult males per 100 adult females during the rut could result

5 in population increases (Hines et al. 1985), while others have reported that below a threshold of approximately 10 adult males per 100 adult females, calf production can decline (Freddy

1987). An approximate ratio of 2.5 adult females to 1 adult male was requested to maximize productivity and population growth in Ontario (Rosatte et al. 2007); however, this was not always possible given the age and sex distribution of the elk captured. Actual ratios of adult females to adult males reintroduced to Ontario ranged from 2.1:1 to 4.8:1 for each release site (Rosatte et al. 2007).

Several studies have also suggested that pregnancy rates are lower in elk herds with fewer older aged bulls. Conaway (1952) concluded that yearling males were physiologically capable of fertilization; however, subsequent research has shown that immature, reproductively inexperienced males are less effective breeders than adults (Lincoln 1971,

Hines and Lemos 1979). For example, Hines and Lemos (1979) found that breeding by yearling male elk resulted in a 57% reduction in annual reproduction. Similarly, Noyes et al.

(1996) reported an increase in pregnancy rates from 89% when yearling bulls were the primary sires to 97% when 5-year-old bulls were the primary breeders.

Elk populations that are under stress due to poor habitat conditions or high population density may display lower mean fecundity rates, with elk in the youngest and oldest age category displaying the most pronounced declines (Caughley 1977). Colonizing populations, which are typically not limited by density or habitat constraints, may exhibit higher mean fecundity rates, particularly in the yearling age class (McCorquodale et al. 1988).

On the other hand, there are studies that suggest that reproduction during the initial years of elk restoration may be considerably lower than that observed in established populations

(Larkin et al. 2003). Abortions triggered by stress and injuries related to trapping, handling, and translocation may result in lower calving rates immediately following reintroduction.

6 Also, a prolonged rutting period resulting from breeding dominated by sub-adults or deficient nutritional conditions may result in high calf mortality associated with late parturition (Clutton-Brock et al. 1982, Noyes et al. 1996, Cook et al. 2001). Finally, an individual's ability to find a suitable mate due to low population densities may result in lower reproduction (Allee 1938). Calving rates in elk reintroduced to Kentucky ranged from 53% to 92% in the first two years following their release (Larkin et al. 2002). Post release movements of adult cows to areas devoid of males are thought to have been responsible for the observed difference in calving rates (Larkin et al. 2002).

Survival

As is the case in most wildlife populations, elk mortality during the first year of life is high, with considerable post-natal mortality being reported for most populations (Raedeke et al. 2002). Physiological maturity, body condition, sex, population size, age of the cow, birth date, birth weight, disease, severe environmental conditions, and predation by black bears

(Ursus americanus), coyotes (Cams latrans), and wolves {Cams lupus) are important factors in the survival of sub-adult elk (calves and yearlings) (Raedeke et al. 2002). Combinations of these factors may also have important impacts on calf survival. For example, considerable winter mortality of elk calves can occur when malnutrition operates in concert with disease and heavy parasitic loads (Murie 1951, Raedeke et al. 2002).

Although translocations have occurred through the 1900s, survival data for calves following reintroduction is limited. Calf survival rates for elk in the reintroduced Michigan population were higher than other North American elk populations, averaging 0.90 (0.85-

0.95 CT) in summer months and 0.97 (0.93-1.00 CI) in winter months (Bender et al. 2002).

Similarly, the three years following the reintroduction of elk to Kentucky, survival rates for calves were higher than those from the source populations, averaging 0.92 (0.85-0.99 CI)

7 (Larkin et al. 2003). In both cases, a high nutritional plane, lack of significant predators, and relatively mild winters were thought to have increased calf survival (Bender et al. 2002,

Larkin et al. 2003). Biologists in EINP, Alberta estimate that approximately 60%-70% of adult female elk are with calves each winter.

Ecological theory related to life history strategies suggests that adult stages of survival are the most important for the persistence of long-lived vertebrates such as elk

(Gaillard et al. 1998, Wisdom et al. 2000). Among adult elk in western North America, causes of mortality, in decreasing order of importance, include hunting (both legal and illegal), predation, disease, malnutrition, severe environmental conditions, harassment, and accidents (Taber et al. 1982, Unsworth et al. 1993, Ballard et al. 2000, Raedeke et al. 2002).

Disease, poaching, and depredation removals have been the leading causes of mortality among reintroduced elk in eastern North America (Sevringhaus and Darrow 1976, Eveland et al. 1979, Witmer 1990, Raskevitz et al. 1991, Larkin et al. 2003).

One parasite of potential importance in the survival of elk translocated from Alberta to Ontario is the meningeal worm, Parelaphostrongylus tenuis. Parelaphostrongylus tenuis is a parasite of white-tailed deer of the eastern deciduous forest biome and deciduous/coniferous ecotone of eastern and central North America (Lankester 2001). It is rare or absent in the coastal plains region of the southeastern United States and is absent in western North America. The precise limits, however, of its most westerly distribution are poorly known (Lankester 2001). It has been found in white-tailed deer in western Manitoba and in the United States east of a line projected south from western Minnesota, through central Okalahoma, and into the extreme eastern portions of Texas. The central grasslands, which are less hospitable for required intermediate gastropods, have been identified as a

8 possible barrier that prevented the parasite's movement westward with white-tailed deer

(Lankester 2001).

Naturally occurring disease caused by P. tenuis is rare in white-tailed deer (Eckroade et al. 1970, Prestwood 1970, Lankester 2001); however, this parasite can be devastating to other North American cervids (Anderson 1971). The effects of P. tenuis on cervids other than the white-tailed deer have been described by Anderson et al. (1966), who determined that this parasite caused what is referred to as "moose sickness". Anderson et al. (1966) and

Anderson (1971, 1972) subsequendy demonstrated the pathogenicity of this parasite to other native ungulates and determined experimentally that the meningeal worm is a significant pathogen in elk.

The meningeal worm, however, is probably not as pathogenic in elk as it is in moose and caribou (Anderson et al. 1966), with the severity and outcome of infection being dose dependent (Samuel et al. 1992). A wide spectrum of impacts on elk at both the individual and population level has been reported for meningeal worm. For example Larkin et al.

(2002), concluded that P. tenuis related mortality would likely limit the growth of reintroduced elk populations in Kentucky. Similarly, studies have concluded that this parasite has probably limited the success of past elk reintroductions into eastern North

America (Anderson and Prestwood 1981, Raskevitz et al. 1991, Thorne et al. 2002). On the other hand, populations of elk sympatric with infected white-tailed deer have persisted

(Moran 1973, Woolfe et al. 1977), although individual elk have demonstrated clinical signs of meningeal worm infections (Moran 1973, Woolfe et al. 1977, Olsen and Woolfe 1978, 1979,

Anderson and Prestwood 1981, Devlin and Drake 1989).

9 V&telaphostrongylus tenuis does not occur naturally in Alberta, but is very common in white-tailed deer in Ontario (Lankester 2001). Therefore, the interest in P. tenuis arises from the potential negative impact of this parasite on the success of translocated animals onto

Ontario range. Much of what is known about the relative susceptibility of the various cervids to P. tenuis comes from experimental infections, while measures of the impact on wild populations are scarce, particularly in the case of elk. This parasite is suspected of having played a role in the failure of several elk reintroduction efforts (Sevringhaus and

Darrow 1976, Anderson and Prestwood 1981, Samuel et al. 1992, Larkin et al. 2002, Thorne et al. 2002). Predictions as to the survival of elk translocated on to P. tenuis range are speculative at best, until better long-term population data are available.

Where hunting is prohibited, illegal shooting has been documented as the major source of male mortality in many elk populations. Moran (1973) reported that illegal shooting of elk during the regular white-tailed deer season accounted for the greatest annual known loss of elk in Michigan. During the 1960s and 1970s, illegal shooting was thought to have equaled or exceeded annual calf production, thereby resulting in a population decline in

Michigan (Moran 1973, Bellhouse and Broadfoot 1998). The growth of the elk population in Pennsylvania also has been limited by poaching (Parker 1990).

Wolves and other predators are reported to be influential in limiting or regulating ungulate populations (Gasaway et al. 1992, Messier 1994) and predation is thought to be an important mechanism of elk population regulation in many areas (Kunkel 1997). Due to the limited number of large predators in many parts of eastern North America, predation is generally not considered an important source of mortality for elk reintroduced to the east.

However, the potential for predation by wolves, black bears, and coyotes to play a significant

10 role in the dynamics of elk populations in Ontario exists, particularly in the north where predator densities are relatively high (Bellhouse and Broadfoot 1998).

Although environmental factors, such as snow depth and temperatures that vary geographically and temporally impact elk populations differently, increased mortality of adult male and female elk that enter the winter season in poor condition is generally reported

(Raedeke et al. 2002). For example, cow survival is positively correlated with warmer

January temperatures and negatively with cool May temperatures and low total July precipitation (Sauer and Boyce 1983). Some elk herds may have the ability to respond to increasingly severe environmental conditions by migrating to another area or shifting forage resources. Other herds, however, may not have the capacity or opportunity to move to more hospitable areas and, as a result, may experience higher mortality (Raedeke et al. 2002).

Compared with other sources of mortality, accidental deaths of elk are relatively uncommon. However, recent studies indicate that injury and mortality among rutting bulls may be relatively common (Clutton-Brock et al. 1982, Leslie and Jenkins 1985).

Furthermore, 18% of all mortalities of elk reintroduced to Kentucky were attributed to accidents, including vehicle collision, injury, and drowning, possibly due to inexperience with the novel habitat (Larkin et al. 2003).

Finally, previous studies have reported that adult survival is remarkably constant in ungulate populations despite environmental variations, and that sex seems to be the most important factor accounting for variation in adult survival (Gaillard et al. 1998). In most species of ungulates, adult male survival is both lower and more variable over time than adult female survival (Clutton-Brock et al. 1982, Boer 1988, Jorgenson et al. 1997). Flook (1970) reasoned that adult male elk should suffer higher mortality rates than adult females because

11 bulls require greater annual food intake than do cows, their digestive system is not substantially greater than that of cows, and they use much of their energy during the rut, often entering the winter with diniinished body condition. McCullough (1969) attributed higher mortality in adult males to their greater aggressiveness, range of movement, and to injuries and energy depletion during the rut. Studies of the importance of sex in the survival of reintroduced elk populations remain scarce, with equivocal results often being reported.

Rates of Increase

Estimates of rates of increase, defined as the per capita rate of population growth between two time intervals (Morris and Doak 2002), are essential for efficient wildlife management because they can contribute to the measurement of population viability.

However, data on the growth rate of elk populations following a reintroduction are limited.

Caughley (1970) suggested that populations of ungulates introduced to vacant habitat should closely conform to exponential growth models. Accordingly, McCorquodale et al. (1988) found the rate of increase for a colonizing elk population in central Washington to be as high as 30%. Likewise, the rates of increase for elk introduced to both Washington (Merrill

1987) and California (Gogan and Barrett 1987) were estimated at 34% and 29%, respectively.

Although these data suggest that introduced elk populations have great growth potential in a variety of habitats, they more likely represent the maximum for elk with high first year survival and favourable habitat conditions, and do not reflect the situation when conditions are less ideal (Caughley 1977, Raedeke et al. 2002). According to Moran (1973), elk reintroduced to Michigan grew at rate of approximately 20% for the first 20 years, declining to 13% in later years.

Riney (1964) proposed that populations of ungulates introduced into previously unoccupied areas normally adjust to their new environment with a single irruptive oscillation,

12 followed by a leveling off of numbers, a decline, and a period of relative stability in which the population density generally remains lower than peak density. Irruptive patterns of growth have been reported in several introduced elk populations (Caughley 1970, Larkin

2001). High initial population growth followed by rapid decline has also been reported for other ungulates including reindeer (Scheffer 1951, Klein 1969) and moose (Mech 1966).

Variability in rates of increase and density dependence

Temporal variation in abundance of large herbivores can have widely different sources; however, two different types of stochastic processes are generally recognized: demographic and environmental stochasticity (Lande 1993). Demographic stochasticity results from chance realizations of individual probabilities of death and reproduction in finite populations (Liebhold and Bacompte 2003). As these individual events average out, demographic stochasticity is most important in small populations. In contrast, environmental stochasticity results from a continuous series of random perturbations that similarly affect birth and death rates of all individuals in a population and is important to both small and large populations (Liebhold and Bacompte 2003). Both types of stochasticity can contribute to extinction when populations are at very low numbers (Lande 1993,

Stephan and Wissel 1994, Lande et al. 1998, Fieburg and Ellner 2001).

A variety of negative and positive density-dependent processes have been described for elk populations, including both declines and increases in pregnancy rates, declines in calf survival due to low birth weights, and declines in juvenile survival at high elk densities

(Raedeke et al. 2002). Negative density dependence is a decline in average vital rates as population size increases (Morris and Doak 2002) and theoretical ecology predicts that as population size increases, intraspecific competition for forage increases leading to density- dependent feedback that lowers recruitment as populations approach carrying capacity (K)

13 (Moen 1973, McCullough 1979, Sjether 1997). Juvenile mortality is among the most sensitive responses to increasing population density and several researchers have reported that density dependent recruitment rates in elk are due to changes in fecundity or survival of young, which may be due to lower energy reserves as a result of more dominant individuals excluding calves from high quality forage (Knight 1970, Sauer and Boyce 1983, Gaillard et al,

1998, 2000). Houston (1982) identified undernutrition at high densities and subsequent effects on reproduction, calf birth mass, and survival of calves as critical features in the population growth of the Northern Yellowstone elk herd. Similarly, Sauer and Boyce (1983) and Singer et al. (1997) found that calf survival was negatively correlated with cow census data, suggesting that elk density affects calf survival.

In reintroduced populations, where numbers are generally far below carrying capacity, a phenomenon known as inverse density dependence or the Allee effect may be critically important for population persistence. The Allee effect refers to the correlation of population si2e with per captia growth rate (Boyce 1992, Stephens and Sutherland 1999,

Stephens et al. 2002). In many cases, this pattern of decreasing per capita growth with decreasing density includes negative growth at very low densities resulting in a decline to extinction. The importance of Allee dynamics in extinction has received considerable attention in studies related to the conservation of endangered species (Lande 1988, Boyce

1992, Groom 1998, Courchamp et al. 1999) and recent work indicates that the combined influence of Allee dynamics and stochastic processes may strongly influence success or failure in the establishment of reintroduced species (Larkin et al. 2002).

There are several mechanisms that that can cause this type of inverse density dependence in animal populations, especially at low densities. These mechanisms include failure to locate mates, inbreeding depression, failure to satiate predators, and lack of

14 cooperative feeding (Boyce 1992, Courchamp et al. 1999, Stephens and Sutherland 1999,

Stephens et al. 2002). In models incorporating Allee effects, extinction rates increase dramatically as density declines, and below some density threshold extinction is considered certain (Dennis 1989, Lewis and Kareiva 1993, Veit and Lewis 1996).

In contrast to negative density effects, positive density dependence is an increase in the population growth rate as population size increases (Morris and Doak 2002). Positive density effects may result from improvements in mating success, group defense, or group foraging as density increases (Morris and Doak 2002). In reintroduced populations, where carrying capacity far exceeds population size, positive density dependence may play a role in the irruptive population growth that has been described in the first years following release.

For example, high survival and reproductive rates were observed during the first three years of Kentucky elk reintroduction (Larkin et al. 2003). Similarly, initial rates of increase for a colonizing elk population in Washington approached the practical maximum recorded for elk (McCorquodale et al. 1988).

A variety of density-independent processes also may be important in the growth and regulation of elk populations and a fundamental driver of density independent variation in vital rates in climatic variation (Sjether 1997). For example, Coughenour and Singer (1996) reported that factors important to elk survival, and subsequently population growth and stability, were spring precipitation, forage production, and snow depth. Similarly, Singer et al. 1997 reported strong influences of environmental factors such as winter severity on calf survival.

Finally, the importance of density dependent and density independent processes vary geographically and temporally, and these factors should not be considered mutually exclusive

15 mechanisms of population regulation (Raedeke et al. 2002, Garrott et al. 2003). Recent studies suggest that a combination of density dependence and environmental stochasticity strongly affect the population dynamics of elk (Saether 1997, Gaillard et al. 1998). Food resources, habitat quality, weather, disease and parasites, interspecific competition, predation, human activities and population density all can account for the demographic variation observed among years or among populations (Gaillard et al. 1998). For example, climate tends to punctuate density dependent factors during severe winters and mitigate them in mild winters (Sauer and Boyce 1983). Similarly, early spring green up generally results in cow elk establishing a high nutritional plane during the later stages of gestation, which in turn, increases birth weight and juvenile survival (Merrill and Boyce 1991).

ELK POPULATION GENETICS

The reintroduction of large, free-ranging species is expensive and time-consuming and as such, these populations necessarily start from small initial releases. This raises concerns about the degree to which bottlenecks and effective population size can reduce genetic variability within the population, and the impact on the long-term viability of the population (Masden et al. 2000, Williams et al. 2002). Genetic variation is known to be greatly affected by founder effect (Nei et al. 1975, Wright 1978) and populations originating from a small number of animals are thought to contain less genetic variation than those originating from a larger number (Williams et al. 2002). Furthermore, a lack of genetic variation has been linked to inbreeding effects in several populations (O' Brien et al. 1985), resulting in slower growth as well as reduced fecundity and survival over time (Ralls et al.

1979, Ballou and Ralls 1982, Ralls et al. 1988). The number, origin, and genetic diversity of

16 populations are therefore central points to consider when assessing impacts of reintroductions on genetic diversity and population persistence.

The theoretical 50-500 rule suggests that at least 50 animals are necessary to avoid loss of vigor from inbreeding and at least 500 individuals are needed to avoid the negative effects of genetic drift (Simberloff 1988). These numbers, however, assume that all members of the population are breeding and that breeding between individuals is random.

These assumptions are not valid for elk, as they ignore many important demographic characteristics (Reed et al. 1986, Raedeke et al. 2002). For example, elk are polygamous, young do not reach their prime breeding age for several years, only a portion of breeding aged males and females breed, generations of breeders show considerable overlap, breeding is not random between males and females, and fertility varies among individuals (Lewin

1982, Witmer 1990). The actual population size for elk would, therefore, need to be much larger than the 50-500 rule proposes. Schonewald-Cox (1986) has suggested that an elk population would require 90 breeders (15 male and 75 female) to prevent inbreeding, and

900 breeders (150 male and 750 female) to prevent genetic drift. Further, the 50-500 rule has recently been updated to the 500-5000 rule, in an effort to maintain evolutionary potential in perpetuity (Traill et al. 2010)

Young aged animals and the proportion of males may also have long-term genetic and evolutionary consequences for elk reintroductions. The effective population size can be drastically reduced in populations with a low proportion of males, which may accelerate the loss of genetic variation due to genetic drift, particularly in currently small populations

(Ryman et al. 1981). Sexual selection may also decrease because of less variation in male age and therefore body size. Body size is thought to be an important factor determining the reproductive success of male elk (Andersson 1994), indicating that variation in reproductive

17 success may be lower with less structured size hierarchies. Similarly, a lower proportion of males in the population may decrease the variance in mating success in male elk, thereby creating less intense sexual selection for larger male body size (Saether et al. 2003).

The strength of the relationship between genetic variation and population size is likely to vary between species; however, several life history traits of elk make them a likely candidate for genetic problems. For example, age at sexual maturity (2-4 years), social structure (matriarchal), mating tactics (polygamous), and fecundity (one calf per year) of elk makes them susceptible to genetic problems (Witmer 1990, Raedeke et al. 2002, Lenny

Williams et al. 2002). In particular, loss of allelic diversity due to genetic drift, in association with founder effects or prolonged bottlenecks, is of concern for reintroduced elk.

Moreover, the potential for inbreeding may be increased for reintroduced populations due to the small number of founders and male-biased dispersal (Larkin 2001, Lenny Williams et al.

2002). Additionally, elk populations in Ontario are geographically isolated and the lack of gene flow between the four sub-populations could further affect the amount of variation existing in each sub-population, placing them at a higher risk of extinction.

Although empirical evidence is limited, a small number of founders and geographical isolation are thought to have contributed to the reduced genetic diversity in elk populations reintroduced to the NFR region of Ontario (Polziehn et al. 2000). Similarly elk populations founded by a small number of animals in both California and Pennsylvania reported levels of genetic variation, no unique or few rare alleles, and large genetic distances between the reintroduced herd and the source population (Lenny Williams et al. 2002, Lenny Williams et al. 2004). These studies suggest that the size and rate of population growth following reintroduction can have important genetic consequences for the population (Lenny Williams et al. 2002).

18 MODELING ELK POPULATION DYNAMICS

One of the most powerful and pervasive methods used to address issues related to extinction and risk management of threatened populations is model-based population viability analysis (PVA) (Reed 2002). Broadly defined, PVA is the use of quantitative methods to predict the likely future status of a population or collection of populations of conservation concern (Boyce 1992, Morris and Doak 2002). There are many potential products and uses of PVA, including assessing the extinction risk of a single population, comparing relative extinction risks of two or more populations, identifying key life stages or demographic processes as management targets, determining how many individuals need to be released to establish a new population, and determining how many and which populations are needed to achieve a desired overall likelihood of species persistence (Morris and Doak

2002).

In previous studies, PVA models have been used to address several questions related to elk population dynamics including, population persistence (Larkin 2001), the effects of predation (Mack and Singer 1993), environmental influences (Turner et al. 1994, Cook et al.

2004), and various survival and reproductive outputs (Sauer and Boyce 1983, Smith and

Anderson 1998, Bender et al. 2002). In general, the demography and population dynamics of elk are relatively well resolved and studies of the life history traits of ungulates have concluded that recruitment parameters, including juvenile survival and some measures of fecundity, combine elasticity with high temporal variability, whereas adult survival has the highest elasticity and the lowest temporal variability (Gaillard et al. 1998, Gaillard et al. 2000,

Festa-Bianchet et al. 2003, Gaillard and Yoccoz 2003, Garrott et al. 2003). The most important advancement of knowledge for Ontario's elk population will therefore come from studies focused on understanding the mechanisms responsible for variability of vital rates in

19 these new populations and developing management strategies that encourage long-term demographic growth and stability.

LITERATURE CITED

Addison, E. M. 1997. Liver flukes and translocated elk in Ontario: review and interpretation of facts. Report to Ontario Ministry of Natural Resources, Fish and Wildlife Branch.

Allee, W. C. 1938. The social life of animals. Norton, New York.

Anderson, R. C. 1971. Neurologic disease in reindeer (Rangifer tarandus tarandus) introduced into Ontario. Canadian Journal of Zoology-Revue Canadienne De Zoologie 49:159- 166.

Anderson, R. C. 1972. The ecological relationships of meningeal worm and native cervids in North America. Journal of Wildlife Disease 8:304-310.

Anderson, R. C, Lankester, M.W., and U. R. Strelive. 1966. Further experimental studies of Pneumostrongylus tenuis in cervids. Canadian Journal of Zoology-Revue Canadienne De Zoologie 44:851-861.

Anderson, R. C, and A. K. Prestwood. 1981. Lungworms. Pages 266-317 in W. R. Davidson, F. A. Hayes, V. F. Netties, and F. E. Kellogg, editors. Diseases and parasites of white-tailed deer. Tall Timbers Research Publication, Tallahassee, Florida.

Andersson, M. 1994. Sexual selection. Princeton University Press.

Armstrong, D.P., and LP. McLean. 1995. New Zealand translocations: theory and practice. Pacific Conservation Biology 2:39-54.

BaUard, W. B, Whitlaw, H.A., Wakeling, B.F., Brown, R.L., de Vos, J.C.J., and M. C. Wallace. 2000. Survival of female elk in northern Arizona. Journal of Wildlife Management 64:500-504.

Ballou, J. D., and K. Ralls. 1982. Inbreeding and juvenile mortality in small populations of ungulates: a detailed analysis. Biological Conservation 24:239-272.

Bellhouse, T. J., and J. D. Broadfoot. 1998. Plan for the restoration of elk in Ontario. Ontario Ministry of Natural Resources Report, Toronto, Ontario.

Bender, L. C, Carlson, E., Schmitt, S.M., and J. B. Haufler. 2002. Production and survival of elk (Cervus elaphus) calves in Michigan. American Midland Naturalist 148:163-171.

20 Boer, A. H. 1988. Mortality rate of moose in New Brunswick: a life-table analysis. Journal of Wildlife Management 52:21-25.

Boyce, M. S. 1992. Population viability analysis. Annual Review of Ecological Systems 23:481-506.

Bubenik, A. D. 1985. Reproductive strategies in cervids. Pages 482 in P. F. Fennessy and K. R. Drew, editors. Biology of deer production. The Royal Society of New Zealand Wellington Bulletin 22.

BunneU, S.D., Wolfe, M.L., Branson, M.W., and D.R. Potter. 2002. Recreational use of elk. Pages 701-748 in D. E. Toweill and J. W. Thomas, editors. North American elk: ecology and management. Smithsonian Institute Press, Washington.

Caughley, G. 1970. Eruption of ungulate populations, with emphasis on Himalayan thar in New Zealand. Ecology 51:52-72.

Caughley, G. 1977. Analysis of vertebrate populations. John Wiley and Sons, New York.

Ceballos, G., and P. R. Ehrlich. 2002. Mammal population losses and the extinction crisis. Science 296:904-907.

Clutton-Brock, T. H., F. E. Guinness, and S. D. Albon. 1982. Red deer: behaviour and ecology of two sexes. University of Chicago Press, Chicago.

Cole, L. C 1954. The population consequences of life history phenomena. Quarterly Review of Biology 29:103-137.

Conover, M.R. 1997. Monetary and intangible valuation of deer in the United States. Wildlife Society Bulletin 25:289-305

Conaway, C. 1952. The age of sexual maturity in male elk. Journal of Wildlife Management 16:313-315.

Cook, J. G., Johnson, B.K., Cook, R.C., Riggs, R.A., Delcurto, T., Bryant, L.D., and L. L. Irwin. 2004. Effects of summer-autumn nutrition and parturition date on reproduction and survival of elk. Wildlife Monographs 1-61.

Cook, R. C, Murray, D.L., Cook, J.G., Zager, P., and S. L. Monfort. 2001. Nutritional influences on breeding dynamics of elk. Canadian Journal of Zoology-Revue Canadienne De Zoologie 79:845-853.

Coughenour, M. B., and F. J. Singer. 1996. Elk population processes in Yellowstone National Park under the policy of natural regulation. Ecological Applications 6:573- 593.

Courchamp, F., Clutton-Brock, T.H., and B. T. Grenfell. 1999. Inverse density dependence and the Allee effect. Trends in Ecological Evolution 14:405-410.

21 Dennis, B. 1989. Allee effects: population growth, critical density, and the chance of extinction. Natural Resource Modeling 3:481-538.

Devlin, D., and W. Drake. 1989. Pennsylvania elk census 1989. Pennsylvania Game Commission, Annual unpublished report, Harrisburg, Pennsylvania.

Eckroade, R. J., ZuRhein, G.M., and W. J. Foreyt. 1970. Meningeal worm invasion of the brain of a naturally infected white-tailed deer. Journal of Wildlife Disease 6:430-436.

Eveland, J. F., George, J.L., Hunter, N.B., Forney, D.M., and R. L. Harrison. 1979. A preliminary evaluation of the ecology of the elk in Pennsylvania. Pages 145-151 in M. S. Boyce, Haydon-Wing, L.D., editor. North American elk: ecology, behaviour, and management. University of Wyoming, Laramine.

Festa-Bianchet, M., Gaillard, J.M., and S. D. Cote. 2003. Variable age structure and apparent density dependence in survival of adult ungulates. Journal of Animal Ecology 72:640- 649.

Fieburg, J., and S. P. EILner. 2001. Stochastic matrix models for conservation and management: a comparative review of methods. Ecological Letters 4:244-266.

Fischer, J., and D.B. Lindenmayer. 2000. An assessment of the published results of animal relocations. Biological Conservation 96:1-11.

Flook, D. R. 1970. Causes and implications of an observed sex differential in the survival of wapiti. 11, Canadian Wildlife Services Bulletin Report, Ottawa.

Freddy, D. J. 1987. Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife, Research Report No. 01-03-047, Fort Collins, Colorado.

Gaillard, J. M., and N. G. Yoccoz. 2003. Temporal variation in survival of mammals: A case of environmental canalization? Ecology 84:3294-3306.

Gaillard, J. M., Festa-Bianchet, M., and N. G. Yoccoz. 1998. Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends in Ecological Evolution 13:58-63.

Gaillard, J. M., Festa-Bianchet, M., Yoccoz, N.G., Loison, A., and C. Toigo. 2000. Temporal variation in fitness components and population dynamics of large herbivores. Annual review of Ecology and Systematics 31:367-393.

Garrott, R. A., Eberhardt, L.L., White, P.J., and J. Rotella. 2003. Climate-induced variation in vital rates of an unharvested large-herbivore population. Canadian Journal of Zoology-Revue Canadienne De Zoologie 81:33-45

Gasaway, W. C, Boertje, R.D., Grangaard, D.V., Kellyhouse, D.G., Stephenson, R.O., and D. G. Larson. 1992. The role of predation in limiting moose at low densities in Alaska and Yukon and implications for conservation. Wildlife Monographs 120:59.

22 Gogan, P. J., and R. H. Barrett. 1987. Comparative dynamics of introduced Tule elk populations. Journal of Wildlife Management 51:20-27.

Griffith, B., Scott, J.H., Carpenter, J.W., and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science 245:477-480.

Groom, M. J. 1998. Allee effects limit population viability on an annual plant. American Naturalist 151:487-496.

Harig, A.L., and K.D. Fausch. 2002. Minimum habitat requirements for establishing translocated cutthroat trout populations. Ecological Applications 12:535-551.

Hines, W. W., and J. C. Lemos. 1979. Reproductive performance by two age classes of male Roosevelt elk in southwestern Oregon. Report 8 Oregon Department of Fish and Wildlife Resources, Portland.

Houston, D. B. 1982. The Northern Yellowstone elk: ecology and management. Macmillan Publishing Company, New York, New York, USA.

Hudson, R. J., Kozak, H.M., Adamczewski, J.Z., and C. D. Olson. 1991. Reproductive performance of farmed wapiti (Cervus elaphus nelsoni). Small Ruminant Research 4:19- 28.

IUCN (World Conservation Union). 2003. IUCN/SSC Guidelines for Re-Introductions. Gland, Switzerland.

Jorgenson, J. T., Festa-Bianchet, M., Gaillard, J.M., and W. D. Wishart. 1997. Effects of age, sex, disease, and density on survival of bighorn sheep. Ecology 78:1019-1032.

Kingscote, A. A. 1951. Liver fluke control in the Burwash area. Ontario Veterinary College Report for 1950.

Klein, D. R. 1969. The introduction increase and crash of reindeer on St. Matthew Island. Journal of Wildlife Management 32:350-367.

Kleiman, D. G. 1996. Reintroduction programs. University of Chicago Press, Chicago.

Knight, R. R. 1970. The Sun River elk herd. Wildlife Monographs 23:66.

Komers, P.E., and G.P. Curman. 2000. The effect of demographic characteristics on the success of ungulate reintroductions. Biological Conservation. 93:187-193.

Kunkel, K. E. 1997. Predation by wolves and other large carnivores in northwestern Montana and southeastern British Columbia. Ph.D. University of Montana, Missoula, Montana.

Lande, R. 1988. Genetics and demography in biological conservation. Science 241:1455- 1460.

23 Lande, R. 1993. Risks of population extinction from demographic and environmental stochasticity and random catastrophes. American Naturalist 142:911-927.

Lande, R., Engen, S., and B. E. Saether. 1998. Extinction times in finite metapopulation models with stochastic local dynamics. Oikos 83:383-389.

Lankester, M. W. 2001. Parelaphostrongylus tenuis. Pages 568 in W. M. Samuel, M. J. Pybus, and A. A. Kocan, editors. Parasitic diseases of wild mammals. Iowa State University Press, Iowa.

Larkin, J. L. 2001. Demographic and spatial characterization of a reintroduced elk population. Ph.D. University of Kentucky, Lexington.

Larkin, J.L., Maehr, D.S., Cox, J.J., Bolin, D.C., and M.W. Wichrowski. 2003. Demographic characteristics of a reintroduced elk population in Kentucky. Journal of Wildlife Management 67:467-476.

Larkin, J. L., Maehr, D.S., Cox, J.J., Wichrowski, M.W., and R. D. Crank. 2002. Factors affecting reproduction and population growth in a restored elk Cervus elaphus nelsoni population. Wildlife Biology 8:49-54.

Lenny Williams, C, Thomas, S., Serfaas, L., Cogan, R., and O.E. Rhodes. 2002. Micro satellite variation in the reintroduced Pennsylvania elk herd. Molecular Ecology 11:1299-1310.

Lenny Williams, C, Lungrigan, B., and O.E. Rhodes. 2004. Microsatellite DNA variation in Tule elk. Journal of Wildlife Management 68:109-119.

Leslie, J., D.M., and K J. Jenkins. 1985. Rutting mortality among male Roosevelt elk. Journal of Mammalogy 66:163-164.

Lewin, R. 1982. Red deer illuminate sexual selection. Science 218:1206-1208.

Lewis, M. A., and P. Kareiva. 1993. Allee dynamics and the spread of invading organisms. Theoretical Population Biology 43:141-158.

Liebhold, A., and J. Bacompte. 2003. The Allee effect, stochastic dynamics, and eradication of alien species. Ecology Letters 6:133-140.

Lincoln, G. A. 1971. Puberty in a seasonally breeding male, the red deer stag {Cervus elaphus L.). Journal of Reproductive Fertilization 25:41-54.

Mack, J. A., and F. J. Singer. 1993. Using POP-II models to predict effects of wolf predation and hunter harvests on elk, mule deer, and moose on the Northern Range. Pages 49- 74 in R. S. Cook, editor. Ecological issues on reintroducing wolves into Yellowstone National Park. U.S. National Parks Service Science Monographs 93/22.

24 Masden, T., Olsson, M., Wittzell, H., Stille, B., Gullberg, A., Shine, R., Andersson, S., and H. Tegelstrom. 2000. Population size and genetic diversity in sand lizards (Lacerta agi/is) and adders (Vipera berus). Biological Conservation 94:257-262.

McCorquodale, S. M., Eberhardt, L.L., and L. E. Eberhardt. 1988. Dynamics of a Colonizing Elk Population. Journal of Wildlife Management 52:309-313.

McCullough, D. R. 1969. The Tule elk: Its history, behaviour and ecology. University of California Press, Berkley, California.

McCullough, D. R. 1979. The George River deer her: population ecology of a K-selected species. University of Michigan Press, Ann Arbor.

Mech, L. D. 1966. The wolves of Isle Royal. Fauna of the national parks of the U.S., Faunal Series 7, Washington D.C.

Merrill, E. H., and M. S. Boyce. 1991. Summer range and elk population dynamics in Yellowstone National Park. Pages 263-274 in R. B. Keiter and M. S. Boyce, editors. The greater Yellowstone ecosystem: redefining America's wilderness heritage. Yale University Press, New Haven, Connecticut.

Messier, F. 1994. Ungulate population models with predation: a case study with the North American moose. Ecology 75:478-488.

Moen, A. N. 1973. Wildlife Ecology. W.H. Freeman and Company, San Francisco, California.

Moran, R. J. 1973. The Rocky Mountain elk in Michigan. 267, Michigan Department of Natural Resources, Wildlife Division, Lansing, Michigan.

Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: theory and practice of population viability analysis. Sinauer Associates Inc., Sunderland, Massachusetts.

Morton, E. S. 1987. Reintroduction as a method for studying bird behaviour and ecology. Cambridge University Press, Cambridge.

Murie, O. L. 1951. The elk of North America. Stackpole Co., Harrisburg, Pennsylvania.

Nei, M., Maruyama, T., and R. Chakraborty. 1975. The bottleneck effect and genetic variability in populations. Evolution 29:1-10.

Noyes, J. H.Johnson, B.K., Bryant, L.D., Findholt, S.L., and J. W. Thomas. 1996. Effects of bull age on conception dates and pregnancy rates of cow elk. Journal of Wildlife Management 60:508-517.

O' Brien, S. J., Roelke, M.E., Marker, L., Newman, A., Winkler, C.A., Meltzer, D., Colly, L., EvermannJ.F., Bush, M., and D. E. Wildt. 1985. Genetic basis for species vulnerability in the cheetah. Science 227:1428-1434.

25 O'Bryan, M. K., and D. R. McCullough. 1985. Survival of black-tailed deer following relocation in California. Journal of Wildlife Management 49:115-119.

O'Gara, B. W., and R. G. Dundas. 2002. Distribution: past and present. Pages 67-120 in D. E. Toweill and J. W. Thomas, editors. North American elk: ecology and management. Smithsonian Institute Press, Washington.

Olsen, A., and A. Woolfe. 1978. The development of clinical signs and the population significance of neurological disease in a captive wapiti herd. Journal of Wildlife Disease 14:263-268.

Olsen, A., and A. Woolfe. 1979. A summary of the prevalence of Parelaphostrongylus tenuis in a captive wapiti population. Journal of Wildlife Disease 15:33-35.

Owen-Smith, N. 2002. Adaptive herbivore ecology. From resources to populations in variable environments. Cambridge University Press, Cambridge, UK.

Parker, L. R. 1990. Feasibility assessment for the reintroduction of North American elk, moose, and caribou into Wisconsin. Wisconsin Department of Natural Resources, Bureau of Research, Madison, Wisconsin.

Polziehn, R. O., J. Hamr, F. F. Mallory, and C. Strobeck. 2000. Microsatellite analysis of North American wapiti (Cervus elaphus) populations. Molecular Ecology 9:1561-1576.

Prestwood, A. K. 1970. Neurologic disease in a white-tailed deer massively infected with meningeal worm (Pneumostrongjilus tenuis). Journal of Wildlife Disease 6:84-86.

Raedeke, K. J., J. J. Millspaugh, and P. E. Clark. 2002. Population characteristics. Pages 67- 120 in D. E. Toweill and J. W. Thomas, editors. North American elk: ecology and management. Smithsonian Institute Press, Washington.

Ralls, K., Ballou, J.D., and A. Templeton. 1988. Estimates of lethal equivalents and the cost of inbreeding in mammals. Conservation Biology 2:185-193.

Ralls, K., Brugger, K., and J. D. Ballou. 1979. Inbreeding and juvenile mortality in small populations of ungulates. Science 206:1101-1103.

Ranta, W. B. 1979. Range and habitat relationships of wapiti, Cervus canadensis, in the Nipissing-French River area of Ontario. M.Sc. Carlton University, Ottawa, Ontario.

Raskevitz, R. F., Kocan, A.A., and J. H. Shaw. 1991. Gastropod Availability and Habitat Utilization by Wapiti and White-Tailed Deer Sympatric on Range Enzootic for Meningeal Worm. Journal of Wildlife Disease 27:92-101.

Reed, D. J. 2002. Emerging issues in PVA. Conservation Biology 16:7-19.

26 Riney, T. 1964. The impact of introductions of large herbivores on the tropical environment. International Union for the Conservation of Nature Publications New Series 4:261- 273.

Rosatte, R., J. Hamr, J. Young, I. Filion, and H. Smith. 2007. The restoration of elk {Cervus elaphus) in Ontario, Canada 1998-2005. Restoration Ecology 15:34-43.

Rosatte, R.,J. Young, and J. Hamr. 2003. Ontario elk restoration Program: 1998-2003. unpublished report Elk Restoration Unit, Cambrian College.

Ryman, N., Baccus, R., Reuterwal, C, and M. H. Smith. 1981. Effective population size, generation interval, and potential loss of genetic variability in game species under different hunting regimes. Oikos 36:257-266.

Sadlier, R. M. F. S. 1987. Reproduction of female cervids. Pages 577 in C. M. Wemmer, editor. Biology and management of the Cervidae. Smithsonian Institute Press, Washington, D.C.

Saether, B. E. 1997. Environmental stochasticity and population dynamics of large herbivores: a search for mechanisms. Trends in Ecology and Evolution 12:143-149.

Saether, B. E., Solberg, E.J., and M. Heim. 2003. Effects of altering sex ratio structure on the demography of an isolated moose population. Journal of Wildlife Management 67:455-466.

Samuel, W. M., Pybus, M.J., Welch, D.A., and C. J. Wilke. 1992. Elk as a potential host for meningeal worm: implications for translocation. Journal of Wildlife Management 56:629-639.

Sargeant, G.A., and M.W. Oehler Sr. 2007. Dynamics of newly established elk populations. Journal of Wildlife Management 71:1141-1148.

Sauer, J. R., and M. S. Boyce. 1983. Density Dependence and Survival of Elk in Northwestern Wyoming. Journal of Wildlife Management 47:31-37.

Scheffer, V. B. 1951. The rise and fall of a reindeer herd. Science Monthly 73:356-362.

Schonewald-Cox, C. 1986. Founding populations in conservation. Pages 519 in S. K. Majumdar, F. J. Brenner, and A. F. Rhodes, editors. Endangered and threatened species programs in Pennsylvania and other states. Pennsylvania Academy of Science, Easton.

Seddon, P.J., Armstrong, D.P., and R.F. Maloney. 2007. Developing the science of reintroduction biology. Conservation Biology 21:303-312.

Sevringhaus, C. W., and R. W. Darrow. 1976. Failure of elk to survive in the Adirondacks. New York Fish and Game 23:98-99.

27 Short, J., Bradshaw, S.D., Giles, J., Prince, R.I.T., Wilson, G.R., 1992. Reintroduction of macropods (Marsupiala: Macropodoidea) in Australia — a review. Biological Conservation 62, 189-204.

Simberloff, D. 1988. The contribution of population and community biology to conservation science. Annual Review of Ecology, Evolution and Systematics 19:473- 511.

Singer, F. J., Harting, A., Symonds, K.K., and M. B. Coughenour. 1997. Density dependence, compensation, and environmental effects on elk calf mortality in Yellowstone National Park. Journal of Wildlife Management 61:12-25.

Smith, B. L., and S. H. Anderson. 1998. Juvenile survival and population regulation of the Jackson Elk Herd. Journal of Wildlife Management 62:1036-1045.

Stephan, T., and C. Wissel. 1994. Stochastic extinction models in discrete time. Ecological Modeling 75/76:183-192.

Stephens, P. A., Frey-Roos, F., Arnold, W., and W. J. Sutherland. 2002. Model complexity and population predictions: the alpine marmot as a case study. Journal of Animal Ecology 71:343-361.

Stephens, P. A., and W. J. Sutherland. 1999. Consequences of the Allee effect for behaviour, ecology, and conservation. Trends in Ecological Evolution 14:401-405.

Taber, R. D., Raedeke, K.J., and D. A. McCaughran. 1982. Population characteristics. Pages 698 in J. W. Thomas and D. E. Toweill, editors. Elk of North America: ecology and management. Stackpole Books, Harrisburg, Pennsylvania.

Thorne, E. T., Williams, E.S., Samuel, W.M., and T. P. Kistner. 2002. Diseases and parasites. Pages 351-388 in D. E. Toweill and J. W. Thomas, editors. North American elk: ecology and management. Smithsonian Institute Press, Washington.

Traill, L.W., Brook, B.W., Frankham, R.R., and C.J.A. Bradshaw. 2010. Pragmatic population viability targets in a rapidly changing world. Biological Conservation 143:28-34.

Turner, M. G., Wu, Y.A., Wallace, L.L., Romme, W.H., and A. Brenkert. 1994. Simulating Winter Interactions among Ungulates, Vegetation, and Fire in Northern Yellowstone Park. Ecological Applications 4:472-486.

Unsworth, J. W., Kuck, L., Scott, M.D., and E. O. Garton. 1993. Elk Mortality in the Clearwater Drainage of North central Idaho. Journal of Wildlife Management 57:495-502.

Veit, R. R., and M. A. Lewis. 1996. Dispersal, population growth, and the Allee effect: dynamics of the house finch invasion of eastern North America. American Naturalist 148:255-274.

28 Wisdom, M. J., Mills, L.S., and D. F. Doak. 2000. Life stage simulation analysis: estimating vital rate effects on population growth for conservation. Ecology 81:628-641.

Witmer, G. 1990. Reintroduction of elk in the United States. Journal of the Pennsylvania Academy of Science 64:131-135.

Woolfe, A., Mason, C.A., and D. Kradel. 1977. Prevalence and effects of Parelaphostrongylus tenuis in a captive wapiti herd. Journal of Wildlife Disease 13:149-154.

Wolfe, CM., Griffith, B., Reed, C, and S.A., Temple. 1996. Avian and mammalian reintroductions: update and reanalysis of 1987 survey data. Conservation Biology. 10:1142-1154.

Wright, S. 1978. Evolution and the genetics of populations: variability within and among populations. University of Chicago Press, Chicago.

29 Figure 1.1: Historical distribution of elk in a) eastern North America, and b) Ontario, Canada (adapted from Peterson, R.L. 1966. Mammals of Eastern Canada. Oxford University Press. Toronto, Ontario).

30 Elk Release Areas In Ontario 1998-2001

a 112 5 225 459 JtmSftaers I < i i I i

.^3 >*

OJgifc

Legend! / Q Elfe Release Area

Figure 1.2: Map depicting four elk release sites in Ontario, Canada 1998-2001 (adapted from Ontario Ministry of Natural Resources. 2011. Elk Population Objective Setting Guidelines. Queens Printer, Peterborough, Ontario, Canada. 6pp).

31 CHAPTER 2

DEVELOPMENT OF A SIGHTABILITY MODEL FOR LOW-DENSITY ELK (CERVUS

ELAPHUS) POPULATIONS IN ONTARIO, CANADA1

ABSTRACT

The status of reintroduced elk (Cervus elaphus) populations in Ontario, Canada, is unclear and

there is a need for effective population survey methods that can be applied locally. I sought

to develop a sightability model that could account for both low densities of elk and dense

forest cover in elk release areas in Ontario. Winter aerial survey counts were corrected for

sightability based on radio-collared animals known to be within observable distance of the

aircraft. The multivariate model with the highest small sample Akaike's Information

Criterion (AIC^j weight [wi — 0.427) revealed that elk group size, elk activity, dominant tree

type, percent canopy cover, and percent conifer cover were significant predictors of elk

sightability. The group size effect indicated that odds of sighting an elk increased by 1.223

(95% CI: 1.062 - 1.408) for every additional elk. Standing elk were 15.029 (95% CI: 11.695 -

19.315) times more likely to be observed than were resting elk, and those located in conifer

cover were 0.013 (95% CI: 0.001 - 0.278) times less likely to be sighted than elk in deciduous

cover. Furthermore, elk located in >50% canopy cover and >50% conifer cover were 0.041

(95% CI: 0.003 - 0.619) times and 0.484 (95% CI: 0.024 - 9.721) times less likely to be

sighted than elk in more open habitat, respectively. Variables not associated with sightability

included elk density, number of male elk, dominant tree size, slope and topography, and light

intensity. During model validation, observers detected 79% (113/143) of known elk in any

1 Mcintosh, T.E., Rosatte, R.C., Hamr, J., and D.L. Murray. 2009. Development of a sightability model for low- density elk populations in Ontario, Canada. Journal of Wildlife Management 73: 580-585.

32 given area, and population and sightability model predictions (±90% CI) overlapped with the population estimate, implying that the predictive model was robust. Not surprisingly, large groups of elk in open habitat increased model precision, which highlights difficulties of counting Ontario elk in their northern range, where they are often solitary. Elk population size was overestimated by: i) Lincoln-Petersen hypergeometric maximum likelihood estimator for closed populations and ii) Minta-Mangel bootstrap estimator. I conclude that the model provided increased reliability for estimating elk numbers in Ontario compared to existing methods, and that the estimator may be useful in other areas where elk density is low and sightability is poor due to dense forest cover.

INTRODUCTION

Restoration of extirpated populations has become an increasingly important tool in conservation biology, and the measure of success is whether a self-sustaining population can be established (Fischer and Lindenmayer 2000, Morton 1987). Although restoration efforts have been important for recovery of elk [Cervus elaphus) populations in western North

America, such activities have had limited success in the east. In fact, since the early 1900s

> 10 eastern states and one province (Ontario) have attempted to establish free-ranging elk populations through transplant (Witmer 1990, O'Gara and Dundas 2002). However, many of these attempts were deemed unsuccessful due to low levels of post-release monitoring and management, which has led to uncertainty regarding the status and prognosis of recovering elk populations (Griffith et al. 1989, Kleiman 1996, O'Gara and Dundas 2002).

Better information is required to improve future elk restoration methodology and to develop management strategies that encourage population growth and long-term stability in eastern

North America.

33 Accurate and precise numerical estimates of abundance are essential in determining status of recovering elk populations. Aerial census is currently the most practical and commonly used method for estimating elk numbers, but visibility bias (i.e., not observing all animals on each sampled unit) remains a major cause of underestimation. Indeed, several studies have shown that large proportions of animals are not sighted during surveys, even when they occur in open, flat terrain (Caughley 1977, Samuel et al. 1987). In general, the likelihood of sighting an animal depends on biological factors including group size, habitat, animal behaviour, and snow cover, as well as measurement error due to observer fatigue and experience, search speed, and altitude (Caughley 1974, Noyes et al. 2000, Otten et al. 1993,

Samuel et al. 1987, Unsworth et al. 1990). Visibility bias can be reduced by applying sightability models that standardize controllable factors and measure the influence of factors that cannot be controlled (Caughley 1974, Samuel et al. 1987, Steinhorst and Samuel 1989,

Unsworth et al. 1990).

A variety of models can correct for elk sightability bias and the most commonly used approach (Samuel et al. 1987) corrects for variability in group size and vegetative cover.

However, the Samuel et al. (1987) model does not account for less-important variables including snow cover, search rate, and animal behaviour. Later validation and modification of the model (Unsworth et al. 1990, Unsworth et al. 1998) revealed a need to restrict surveys to periods when group sizes are largest, elk are in open habitats (typically mid-winter), and the ground is snow covered, although Leptich and Zager (1993) cautioned against using the model without site-specific validation (see also Otten et al. 1993, Anderson et al. 1998).

There are 2 major challenges for application of an elk population estimation model specific to Ontario. First, most sightability models have been developed for elk populations at high densities (Noyes et al. 2000), and may not reflect the lower overall density and more

34 solitary nature of animals in Ontario. Second, current sightabihty models do not account for lower visibility of elk in dense eastern forests, which could lead to population underestimation. A locally validated sightabihty model should increase both precision and accuracy of elk population estimates in eastern Canada.

STUDY AREA

Elk were surveyed at 2 elk reintroduction sites including the Nipissing-French River Area

(NFR; 46 ° 12' 23.3" N, 80° 50' 38.1" W) in central Ontario, Canada and the Bancroft-

North Hastings area (BNH; 45° 02' 15" N, 83° 29' 12.7" W) in eastern Ontario, Canada.

The major forest region represented in both areas was the Great Lakes-St. Lawrence forest, a transition zone between northern boreal forest and southern temperate forest (Rowe 1972).

These forests generally contain sugar maple (Acer saccharum), yellow birch (Betula luted), and beech (Fagus grandifolid), as well as mixed softwoods of white (Pinus strobus) and red pine (P. resinosd), trembling aspen (Populus tremuloides), balsam fir {Abies balsamiferd), white birch (Betula papyriferd), and eastern hemlock (Tsuga canadensis; Rowe 1972, Chambers et al. 1997,

Thompson 2000). The glacier-shaped Canadian Shield topography is mosdy rugged with rocky ridges interspersed with numerous lakes (Thompson 2000). Mean maximum snow depth in the NFR and BNH elk release areas averaged 50 cm and 65 cm annually, respectively (Anonymous 2003).

METHODS

Aerial Surveys

Aerial surveys were conducted in the BNH and the NFR study areas during the winters of

2004 -2006. A Bell Long Ranger helicopter with a pilot and 2 observers who were

35 experienced in sighting elk from the air (i.e., training and instruction in aerial survey techniques, as well as participation in previous elk surveys in Ontario) were utilized during surveys. To minimize observer error, the same observers were used, including the pilot, for each survey. Surveys were conducted with complete snow cover on the ground and good weather conditions (i.e., >305 m ceiling). All surveys were completed between 0800 hours and 1700 hours and units were sampled at a standard ground speed (80-100 km/hr) and altitude (50-70 m).

A stratified random sampling system (Caughley 1977) was used, where each area was divided into strata of low and high elk density, based on recent telemetry locations (i.e., <24 hr). Each density unit was further divided into sampling units averaging 16 km2 (Oswald

1998). Each unit was sampled by flying consecutive parallel transects 400 m apart. This spacing produced 0.4-km-wide bands, allowing observers to search each band with similar intensity (Oswald 1998). All crew members, including the pilot, assisted in searching for elk.

When an elk group was observed, the search pattern was interrupted until the location, group size, age and sex class (ad M, ad F, yearling M, and calf), number of radio-collared elk, and group activity (resting, standing) were recorded. Radio-collared elk were identified in located groups by telemetry. Because >50% of elk were radio-collared during the study, it was assumed they represented the population. Habitat variables recorded for each sighted elk group included dominant tree type (conifer, deciduous), percentage canopy cover (<50%,

>50%), percentage conifer cover (<50%, >50%), size class of dominant tree type (sapling, mature), slope and topography (flat, steep), and light intensity (flat, bright). Sightability variables were estimated visually by consensus for an area encompassing all elk plus an estimated 10m perimeter for the location where the group was first sighted. To maintain independence among observations, elk groups containing > 1 elk were treated as one

36 observation. Following the survey, radio-collared elk known to be in the area (i.e., < 24 hr telemetry locations) but missed during the survey, were located by telemetry, noting the same variables described previously.

Data Analysis

Prior to data collection, 20 candidate models were developed based on knowledge of the

Ontario elk population and published information on elk and other ungulate sightability models ( Caughley 1974, Samuel et al. 1987, Unsworth et al. 1990, Otten et al. 1993,

Anderson et al. 1998, Cogan and Diefenbach 1998, Unsworth et al. 1998, McCorquodale

2001; Table 1). For each of the 20 models, I modeled the group detection variable of radio- collared elk in both the BNH and NFR regions, where 0=not detected and l=detected, as a linear function of various combinations of the independent variables (i.e., time of day, group size, sex and age grouping, elk activity, dominant tree type, % canopy cover, % conifer cover, size class of dominant tree type, slope and topography, and light intensity) using logistic regression (SPSS 13.0, SPSS Inc. Chicago, IL). Some of the predictor variables assessed overlapping environmental conditions, so to avoid problems associated with multicollinearity, I analyzed tolerance and variance inflation factors (VIF; Tabacknick and

Fidell 1989). I also examined the condition index and variance proportions for each dimension for evidence of multicollinearity (Tabachnick and Fidell 2001). If an individual variable had an unacceptable tolerance (<2.5) and variance inflation factor (>10), I eliminated it from the model (Tabacknick and Fidell 1989). Additionally, if variables had condition indices <30 combined with >2 variance proportions >0.50,1 eliminated them

(Belsley et al. 1980, Tabachnick and Fidell 2001).

Multimodel inferencing was used to compare models (Burnham and Anderson 2002,

Kuha 2004), with small-sample Akaike's Information Criterion (AIC^ , AIC,. differences (Ai),

37 and AIC^.weights (w) guiding model selection (Burnham and Anderson 2002). I considered the model with Ai =0 to best fit the data, whereas I considered those with Ai >10 to have no support; I considered models with Ai <2 to have substantial support (Burnham and

Anderson 2002).

The number of elk at each site and in the population were estimated using the sightability-adjustment method of Steinhorst and Samuel (1989), with independent variables related to probability of observing an elk group in the best model used as correction factors to estimate total number of elk in the study area (Steinhorst and Samuel 1989). To validate the sightability model, I used surveys flown in 2004 and 2005 {n — 49) to develop the model, and a survey flown in BNH in 2006 («=12) served for validation. I derived population estimates with 90% confidence intervals (Sofroniou and Hutcheson 2002), representing sightability variance (error associated with the correction factor applied to each group) and model variance (error in estimating sightability probabilities during model development;

Steinhorst and Samuel 1989). Furthermore, because the sightability model was developed based on radio-collared animals, validation worked to test both the ability of the model to estimate abundance and the proportion and evenness of radio-collared individuals in the population. To assess model accuracy and compare estimates derived from the model to those derived from previously used methods, I also estimated total number of elk in the study area using the Lincoln-Petersen hypergeometric maximum likelihood estimator for closed populations (Chapman 1951) and the Minta-Mangel bootstrap estimator (Minta and

Mangel 1989). I made mark-resight population estimates using the program NOREMARK

(White 1996).

38 RESULTS

Tolerance statistics ranged from 0.304 to 0.834 and VIF ranged from 1.213 to 3.287 for all variables under consideration, therefore I considered multicollinearity acceptably low and eliminated no variables. Furthermore, no dimension had a condition index <30 combined with >2 variance proportions >0.50, meeting criteria for non-multicollinearity.

The multivariate model with the highest AIQ weight (model 1, A, = 0, wt — 0.427) revealed that elk group size (£V,= 0.86), elk activity f^jv,— 0.66), dominant tree type Q^ —

0.99), percent canopy cover Q>V.= 0.97), and percent conifer cover QV/= 0.86) together were significant predictors of elk sightability (Table 2.1). More specifically, the group size effect indicated that odds of sighting an elk increased by 1.223 (95% CI: 1.062 - 1.408) for every additional elk. Standing elk were 15.029 (95% CI: 11.695-19.315) times more likely to be observed than those that were resting, and those located in conifer cover were 0.013

(95% CI: 0.001 - 0.278) times less likely to be sighted than elk in deciduous cover.

Furthermore, elk located in >50% canopy cover and >50% conifer cover were 0.041 (95%

CI: 0.003 - 0.619) times and 0.484 (95% CI: 0.024 - 9.721) times less likely to be sighted than elk in more open habitat, respectively (Table 2.2). There was little support for the other

models I tested (AAICf >3) and the collective weight of evidence from the modeling exercise

indicated that elk density QjVj — 0.24), number of male elk (^jvt — 0.10), dominant tree size

QjVj— 0.21), slope Qjv,— 0.05), and light intensity (X«/,-= 0.006) were not related to elk sightability (Table 2.1).

Model Validation

Elk surveys were conducted during 2006 to validate the sightability model, with a census of

12 plots flown and observers recording 79% (113/143) of known elk (both radio-collared and uncollared elk) in the study area. I found that 90% confidence intervals for the

39 sightability corrected population estimate overlapped with the known number of radio- collared elk. The model slightly underestimated the known elk population (143), predicting that 141 elk (90% CI: 82 - 201) were present, with a relative error of 1.3%. I derived the most precise estimates from surveys of large groups of elk in more open habitats as this allowed for rriinirnal model correction of observed data (Table 2.3). For example, relative errors ranged from 1.5% for a group of 10 elk that I estimated to number 9.8, to 200% for a group of 2 elk estimated to number 6. Indeed, model correction was greatest when elk density was low and vegetation cover was high.

Mark-resight techniques tended to overestimate the size of a population relative to its actual size. Both the Lincoln-Petersen hypergeometric maximum likelihood technique

(161; 90% CI: 140-197) and the Minta-Mangel bootstrap technique (162; 90% CI: 140-197) estimated the population to be 13% higher than the known population size. However, both the number of known elk and the sightability-corrected estimates were included within the

90% confidence intervals of the mark-resight estimators.

DISCUSSION

The best-fit sightability model for winter helicopter counts of elk in Ontario indicated that group size, activity status, dominant tree type, percent canopy cover, and percent conifer cover were the primary factors influencing sightability. These results are similar to models developed from other studies of elk (Otten et al. 1993, Samuel et al. 1987, Anderson et al.

1998, Cogan and Diefenbach 1998, Unsworth et al. 1998), mule deer {Odocoiks hemionus;

Ackerman 1988, Unsworth et al. 1998), moose {Alces alces; Anderson and Lindzey 1996), bighorn sheep (Ovis canadensis; Bodie et al. 1995), and waterfowl (Smith et al. 1995).

However, I found that group size was an important predictor of sightability in the north-

40 eastern range and thus should be included in population estimation exercises where elk densities are low. This is of particular importance in reintroduced populations, where number of founders tends to be low and population growth is used as a metric of reintroduction success. Group size was also an important variable in sightability models developed by Samuel et al. (1987) and Cogan and Diefenbach (1998). However, Otten et al.

(1993) did not find group size to be important, reporting that low variation in group size might have reduced the importance of this variable in their study.

An important criticism of sightability models for estimating elk populations is that effects of undercounting group sizes have not been addressed rigorously (Cogan and

Diefenbach 1998). Cogan and Diefenbach (1998) suggest that undercounting elk in groups caused negatively-biased population estimates, and although I did not verify that I accurately counted individual elk, Cogan and Diefenbach (1998) considered all elk within 45 m as comprising a group. In contrast, I defined an elk group as any cohesive unit where behavior and distance were consistent with grouping, rather than distance as the only factor determining group membership. Including behavior as a component of group membership should limit potential undercounting of elk numbers in the low-density population.

Elk activity status (standing, resting) has not been found to influence ungulate sightability in other studies (Samuel et al. 1987, Bodie et al. 1995, Anderson and Lindzey

1996); however, surveys in Ontario may be more sensitive to movement because of dense habitat and increased difficulty in sighting animals. Sightability models developed for elk in summer conditions report that elk activity plays an important role in the ability to see elk

(Anderson et al. 1998), likely because lack of snow makes elk detection more difficult.

Furthermore, activity was thought to be important in sighting mule deer in winter models

(Unsworfh et al. 1998). Flights over large groups of elk likely would elicit some degree of

41 activity and thereby increase detection success, but in smaller groups, the ability to hide under cover and thus remain undetected should increase. /

When validating the model, the most precise population estimates resulted from surveys of large groups of elk in more open habitats, which allowed for rninimal model correction of observed data. Model correction was greatest when elk group size was low and vegetation cover was high, which suggests that model accuracy and precision are sensitive to observations with low detection probabilities and demonstrates the importance of maximizing sightability of elk within the constraints of the survey protocol. This idea is supported by Unsworth et al. (1990) and Samuel et al. (1987), where 95% confidence intervals dropped from 22% to 7% of the estimate when the proportion of detected elk increased from 71% to 93%. My 90% confidence intervals associated with the estimated number of elk in each plot were wide, likely because the average rate of detection in the study area was low (67-79%). However, the population estimate was within 2 elk of the known population, indicating that the model was accurate.

The limitation of my model is that probability of seeing an elk must be >0 to apply the correction factor. If part of the population has zero probability of being seen, then no correction factor can be developed to estimate that portion of the population. Zero detection probability may occur in survey plots where only one or 2 elk are present and thus the sightability model may in fact underestimate populations of elk at very low densities.

This problem requires further investigation, as it is important to detect biologically significant population changes (10-20%) in founding and small populations. There were

<200 elk in the core range of each of the BNH and NFR regions during the early 2000's

(Rosatte et al. 2007), and underestimation of only 20 to 40 animals could be misleading to managers. Regardless, by better surveying elk at low densities and heavy forest cover, my

42 sightability model accounted for animals that might otherwise be missed and yielded an increased level of certainty in elk population estimates. These improvements over the existing mark-resight method of censusing elk populations in Ontario are crucial for managers to detect meaningful changes in elk population numbers over time, and to assess success of the reintroduction effort. Furthermore, because a large portion of the Ontario elk population is radio-collared, mark-resight population estimates should be possible for the next several years without additional marking efforts. The combination of mark-resight techniques, along with population estimates derived from application of the sightability model should give managers a good indication of the population status, thereby allowing for best management practices.

Ideally, aerial survey estimators should be accurate, precise, cost effective and repeatable to facilitate timely management decisions (Gasaway et al. 1985, Anderson and

Lindzey 1996). Mark-resight estimators have suggested modest increases or decreases (i.e.,

> 10%) in the Ontario elk populations during the 6 years since the last release (Rosatte et al.

2007). Furthermore, estimates of recruitment have been low, likely in part reflecting poor sightability during aerial surveys. The locally-validated sightability model that was developed in this study, the first for elk in eastern Canada, accounted for both low densities of elk and dense forest cover in elk release areas in Ontario. The model should aid in the detection of meaningful changes in the elk populations, thereby allowing for better management towards growth and long-term stability. Furthermore, following validation, this model may be applicable to the remaining reintroduced elk herds in Ontario and those elsewhere in eastern

North America.

43 Management Implications

The locally-validated model provided increased reliability for estimating elk numbers in Ontario compared to existing methods (i.e., mark-resight models), and with local validation, the estimator may be useful in other areas where elk density is low and sightability is poor due to dense forest cover. To maximize sightability and overall accuracy of the model, I recommend conducting the survey when detection rates are highest, elk are more gregarious, and with rigorous standardization of the survey protocol (i.e., search speed, altitude, aircraft type, observer experience, weather conditions).

LITERATURE CITED

Ackerman, B. B. 1988. Visibility bias of mule deer aerial census procedures in southeast Idaho. Dissertation, University of Idaho. Moscow, USA.

Anderson, C. R., and F. G. Lindzey. 1996. Moose sightability model developed from helicopter surveys. Wildlife Society Bulletin 24:247-259.

Anderson, C. R., Moody, D.S., Smith, B.L., Lindzey, F.G., and R. P. Lanka. 1998. Development and evaluation of sightability models for summer elk surveys. Journal of Wildlife Management 62:1055-1066.

Anonymous. 2003. Canadian climate normals 1981-2003. Environment Canada, Atmospheric Environment Service Report. Ottawa, Ontario, Canada.

Belsley, D. A., Kuh, E., and R.E. Welsch. 1980. Regression diagnostics: Identifying influential data and sources of collinearity. Wiley, New York, New York, USA.

Bodie, W. L., Garton, E.O., Taylor, E.R., and M. McCoy. 1995. A sightability model for bighorn sheep in canyon habitats. Journal of Wildlife Management 59:832-840.

Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer, New York, New York, USA.

Caughley, G. 1974. Bias in aerial survey. Journal of Wildlife Management 38:921-933.

Caughley, G. 1977. Sampling in aerial survey. Journal of Wildlife Management 41:605-615.

44 Chambers, B. A., Naylor, B.J., Nieppola, J., Merchant, B., and P. Uhlig. 1997. Field guide to forest ecosystems in central Ontario. South Central Region Science and Technology Report FG-01. Toronto, Ontario, Canada.

Chapman, D. G. 1951. Some properties of the hypergeometric distribution with applications to zoological sample censuses. University of California Publication in Statistics 1:131- 160.

Cogan, R. D., and D. R. Diefenbach. 1998. Effect of undercounting and model selection on a sightability-adjustment estimator for elk. Journal of Wildlife Management 62:269- 279. Fischer, J., and D. B. Lindenmayer. 2000. An assessment of the published results of animal relocations. Biological Conservation 96:1-11.

Gasaway, W. C, Bubois, S.D., and S. L. Harbo. 1985. Biases in aerial transect surveys for moose during May and June. Journal of Wildlife Management 49:777-784.

Griffith, B.J., Scott, M., Carpenter, J.W., and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science 245:477-480.

Kleiman, D. G. 1996. Reintroduction programs. Pages 297-305 in Kleiman D. G., Allen M. E., Thompson K. V., Lumpkin S., editors. Wild mammals in captivity: principles and techniques. University of Chicago Press, Chicago, Illinois, USA.

Kuha, J. 2004. AIC and BIC: Comparisons of assumptions and performance. Sociological Methods and Research 33:188-229.

Leptich, D. J., and P. Zager. 1993. Couer d'Alene elk ecology project, study II: elk sightability models. Job completion report W-160-R-20. Idaho Department of Fish and Game Report. Boise, USA.

McCorquodale, S. M. 2001. Sex-specific bias in helicopter surveys of elk: sightability and dispersion effects. Journal of Wildlife Management 65:216-225.

Minta, S., and M. Mangel. 1989. A simple population estimate based on simulation for capture-recapture and capture-resight data. Ecology 70:1738-1751.

Morton, E. S. 1987. Reintroduction as a method for studying bird behaviour and ecology. Pages 165-173 in Jordan W. R., Gilpin M. E., Aber J. D., editors. Restoration ecology: a synthetic approach to ecological research. Cambridge University Press, Cambridge, United Kingdom.

Noyes, J. H., Johnson, B.K., Riggs, R.A., Schlegel, M.W., and V. L. Coggins. 2000. Assessing aerial survey methods to estimate elk populations: a case study. Wildlife Society Bulletin 28:636-642.

45 O'Gara, B. W., and R. G. Dundas. 2002. Distribution: past and present. Pages 67-120 in Toweill D. E., Thomas J. W., editors. North American elk: ecology and management. Smithsonian Institute Press, Washington, D.C., USA.

Oswald, K. 1998. Moose aerial observation manual. Ontario Ministry of Natural Resources. Northeast Science and Technology Report. 008. Toronto, Ontario, Canada.

Otten, M. R. M., Haufler, J.B., Winterstein, S.R., and L. C. Bender. 1993. An aerial censusing procedure for elk in Michigan. Wildlife Society Bulletin 21:73-80.

Rosatte, R., Hamr, J., Young, J., Filion, I., and H. Smith. 2007. The restoration of elk {Cervus elaphus) in Ontario, Canada 1998-2005. Restoration Ecology 15:34-43.

Rowe,J. S. 1972. Forest regions of Canada. Canadian Forest Service Publication Report. 1300. Ottawa, Ontario, Canada.

Samuel, M. D., Garton, E.O., Schlegel, M.W., and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in north central Idaho. Journal of Wildlife Management 51:622- 630.

Smith, D. R., Reinecke, K.J., Conroy, M.J., Brown, M.W., and J. R. Nassar. 1995. Factors affecting visibility rate of waterfowl surveys in the Mississippi Alluvial Valley. Journal of Wildlife Management 59:515-527.

Sofroniou, N-, and G. D. Hutcheson. 2002. Confidence intervals for the predictions of logistic regression in the presence and absence of a variance-covariance matrix. Understanding Statistics 1:3-18.

Steinhorst, R. K., and M. D. Samuel. 1989. Sightabihty adjustment methods for aerial surveys of wildlife populations. Biometrics 45:415-425.

Tabachnick, B. G. and L.S. Fidell 2001. Using multivariate statistics: Fourth edition. Allyn & Bacon, New York, New York, USA.

Thompson, I. D. 2000. Forest vegetation of Ontario: factors influencing landscape change. Pages 336 in Perera A. H., Euler D. L., Thompson I. D., editors. Ecology of a managed terrestrial landscape: patterns and processes of forested landscapes in Ontario. University of British Columbia Press, Vancouver, Canada.

Unsworth, J. W., Kuck, L., and E. O. Garton. 1990. Elk sightabihty model validation at the national bison range, Montana. Wildlife Society Bulletin 18:113-115.

Unsworth, J. W., Leban, F.A., Leptich, D.J., Garton, E.O., and P. Zager. 1998. Aerial Survey: User's Manual, 3rd Edition (Electornic). Idaho Department of Fish and Game, Boise, USA.

46 White, G. C. 1996. Program NOREMARK Software Reference Manual. Colorado State University Report. Fort Collins, USA.

Witmer, G. 1990. Reintroduction of elk in the United States. Journal of the Pennsylvania Academy of Science 64:131-135.

47 Table 2.1: Candidate sightability models for surveys of elk in Ontario, Canada in March 2004 and 2005. For each logistic regression model I include number of parameters (K), biased-corrected Akaike's Information Criterion (AICc), AlCc difference (A), AIC<: weight (w), and percent accuracy in = 49). Model description K AICc w. Accuracy GS + ACT + DTT + CC + CON 35.714 0.000 0.427 89.8

GS+DTT+CC 4 38.955 3.240 0.084 79.6

DEN+ACT+GS+DDT+DTS+CC+CON 8 39.483 3.769 0.065 91.

GS + DTT + DTS + CC + CON 39.713 3.999 0.058 85.7

DEN+ACT+DTT+CC+CON 39.726 4.012 0.057 85.7

GS+ACT+ME+DTT+CC+CON 7 40.518 4.803 0.039 87i

7 DTT+CC+CON 40.613 4.898 0.037 83.7

DEN+ACT+GS+DTT+CC+CON 7 40.844 5.129 0.033 85.7

DEN+GS+DTT+CC 41.136 5.421 0.028 83.7

10 DEN+ACT+GS+ME+DTT+DTS+CC+CON 41.276 5.562 0.026 89i

11 GS+DTT+CC+CON 41.372 5.657 0.025 79.6

12 GS+DTT+DTS+CC+CON+SLO 7 41.491 5.776 0.024 85.7

13 GS+ME+DTT 41.791 6.076 0.020 87.8

14 DTT+DTS+CC+CON 41.888 6.173 0.019 85.7

15 DEN+DTT+CC+CON 41.987 6.272 0.019 81.6

16 DTT+DTS+CC+CON+SLO 43.093 7.379 0.011 85.7

17 GS+DTT 43.630 7.916 0.008 83.7

18 DEN+GS+DTT+CC+CON 43.651 7.937 0.008 83.7

19 GS+ACT+ME+DTT+DTS+CC+CON+SLO+LI 10 44.311 8.596 0.006 89.8

20 DEN+ACT+GS+ME+DTT+DTS+CC+CON+SLO 10 44.374 8.659 0.006 91.8

"Abbreviations: DEN = density of elk in survey area, ACT = elk activity, GS = elk group size, ME = no. of M elk, DTT = dominant tree type, DTS = dominant tree size, CC = % canopy cover, CON = % conifer cover, SLO = slope, LI — light intensity b % accuracy refers to % of surveys that correctly classified by the specified model.

48 Table 2.2: Parameter estimates for the best model developed to explain sightability of elk in Ontario, Canada, January 2000 - December 2005.

95% CI

Parameter Estimate SE Odds ratio Upper Lower

Elk group size 0.201 0.072 1.223 1.062 1.408

Elk activity (standing) 2.710 0.128 15.029 11.695 19.315

Dominant tree type (conifer) -4.377 0.142 0.013 0.009 0.017

Canopy cover (>50%) -3.191 0.129 0.041 0.032 0.053

Conifer cover (>50%) -0.726 0.138 0.484 0.369 0.634

Constant 4.174 0.159

49 Table 2.3: Ontario elk sightabiHty modeF predictions, accuracy, and precision as tested on 12 survey plots in March 2006. I included estimates of the total population based on actual counts (N) and the sightabiHty corrected count (NA).

Correction Survey No. of elk Relative

factor N b plot seen N error (%) 90% CI

Lower Upper

1 18 0.963 20 18.7 -6.6 14.9 22.5

2 7 0.996 8 7.0 -12.1 4.6 9.4

3 1 0.197 4 5.1 26.9 0.0 11.4

4 10 0.723 15 13.8 -7.7 7.2 19.5

5 1 0.197 2 5.1 153.7 0.0 10.8

6 2 0.140 9 14.2 58.3 9.7 18.8

7 1 0.166 2 6.0 200.4 0.0 10.6

8 10 0.992 11 10.1 -8.4 6.3 13.8

9 5 0.960 6 5.2 -16.4 0.6 9.8

10 9 0.914 10 9.8 -1.5 5.3 14.4

11 3 0.914 4 3.3 -17.9 0.0 7.9

12 46 0.701 52 42.8 -17.7 33.3 52.2

Total no. of elk 143 141 -1.3 82 201

a Logistic regression model contained elk group size, elk activity, dominant tree type, canopy cover, and conifer cover. b I estimated 90% confidence intervals following Sofroniou and Hutcheson (2002)

50 CHAPTER 3

PATTERNS OF MORTALITY AND FACTORS INFLUENCING THE SURVIVAL OF ELK (CERVUS

ELAPHUS) RECENTLY REINTRODUCED TO ONTARIO, CANADA

ABSTRACT

Wildlife reintroductions provide a rare opportunity to study the factors that influence

survival in establishing populations, which may differ from those that influence established populations. This study examined both patterns of mortality and determinants of survival among

elk released in four distinct release sites in Ontario, Canada (1998-2005). I predicted that:: i) elk located in release sites closer to the core of the historic range of elk in Ontario would have higher

survival, ii) survival would increase as an animal's time and experience on the landscape increased,

and iii) survival rates would decline as animals moved farther away from the release site. During

the study 443 elk were radio-collared and released; 218 mortalities were documented across the 4 release sites. Predation by wolves was the most important proximate cause of mortality (27%),

followed by accidents (21%), death due to injuries sustained during translocation and/or post

capture myopathy (20%), emaciation (10%), poaching (10%), and infection with the parasite

P.tenuis (2%). Overall, the annual survival of elk across Ontario ranged from 0.45 (0.37-0.53) to

0.81 (0.66-0.90), with rates being lowest in the years following a release (i.e., 1998, 1999, 2000,

2001) and highest in the final years of the study (2003, 2004, 2005), likely due to immediate deaths

from post-capture myopathy and transportation related injuries, as well as lack of familiarity with novel habitat and mortality risk in the year following release. Model averaged hazards lend further support to the risk associated with the method of introduction to the novel landscape and behaviour in the first year following release. The most important factor influencing elk survival was length of holding period, with elk released after limited holding (<10 days) being 23.3 (95% CI:

51 20.404— 26.077) times less likely to survive than those held longer periods. Further, an analysis restricted to the Bancroft-North Hastings release area revealed higher risk among animals with large home ranges (1.09, 95% CI: 0.648-1.132), and those with south/south-west movements

(1.001, 95% CI: 0.638-1.336). The results of this study suggest that mortality caused by post- capture myopathy and transportation related injuries is an important immediate cause of death for translocated elk, and that following translocation, the method of introduction to the novel landscape and behaviour in the first year following release need careful consideration via soft- release and appropriate release areas.

INTRODUCTION

Variation in survival can play a substantive role in the population dynamics of large ungulates (Sasther 1997, Loison and Langvatin 1998, Gaillard et al. 1998, Sasther et al. 2007), and the complexities of animal population change cannot be fully understood unless factors influencing survival are elucidated. In general, studies have shown that large ungulates tend to follow a U- shaped pattern of age-specific mortality, with high mortality rates associated with juveniles, low mortality during prime adulthood, and increasing rates of mortality associated with senescence

(Caughley 1966, Fowler 1987, Loison et al. 1999, Festa-Bianchet et al. 2003). Given this well recognized pattern, it is clear that the role of age in mortality risk and cause of death must be considered in any assessment of ungulate population demography. Further, research efforts should identify factors that influence deviation from the general pattern, and in turn, contribute to population change.

Mechanisms affecting the variation in survival of large ungulates are relatively well understood. Indeed, many studies have shown that patterns of numerical change are fuelled by a combination of stochastic environmental variation and density dependent mortality (Sasther 1997,

52 Gaillard et al 1998, Coulson et al. 2000, 2001). In turn, ungulate mortality is often driven by a variety of factors including food availability and habitat quality (Bender et al. 2008), climate

(Garrott et al. 2003), disease and parasites (Murray et al. 2006), predation (Kunkel and Pletscher

1999), population density (Stewart et al. 2005), and harvest (Ballard et al. 2000), and each has been shown, at least to some degree, to account for annual variability in survival rates (Gaillard et al.

1998).

Wildlife reintroductions provide a rare opportunity to study the factors that influence survival in establishing populations, which may differ from those that influence established populations. A common feature of many wildlife reintroductions seems to be a high loss of animals immediately following release (Griffith et al. 1989). While persistence largely depends on good habitat conditions, establishment of a new group of individuals depends on the short-term local survival of released individuals (Armstrong and Seddon 2007). Short-term post-release survival is thus a crucial parameter for measuring the success of new and reintroduced populations.

Released animals may experience variable survival rates depending on the age of individuals and cohort size, where an overall increase in survival is related to the total number of animals released and, in particular, the number of animals released in cohorts with traditionally higher survival rates (i.e., adult females) (Griffith et al. 1989, Wolf et al. 1998, Fischer and Lindenmayer

2000, Sarrazin and Legendre 2000). Allee and in- or out-breeding effects (Jaimison et al. 2007,

Somers et al, 2008) also may be important, where larger founding populations are less likely to succumb to extinction either through demographic stochasticity or from maladaptive traits.

Furthermore, social and ecological familiarity with the landscape also may encourage higher survival as animals are able to disperse and exploit good quality habitat (Armstrong and Craig

1995, Stamps and Swaisgood 2007, Haydon et al. 2008). Pre- and post- release experience may be similarly important, as the ability of translocated animals to cope with novel environments has

53 been related to pre- and post- experience with both habitat and mortality risks (Frair et al. 2007).

Finally, factors such as release site fidelity, dispersal behaviour, and soft vs. hard release methodology may be related to social and ecological familiarity with the landscape and can also play a critical role in variation of survival (Eastridge and Clark 2001, Haydon et al. 2008, Ryckman et al, 2009, Yott et al. 2010).

Hypotheses for reintroduction success generally include large combinations of socio- ecological predictors based on their theoretical relationship with survival (Linklater at al. 2011).

Here I present results from an analysis of causes of mortality and determinants of survival among elk released into Ontario, Canada, across four distinct release sites in the province; three release areas are on the periphery of the historical range of elk in Ontario. I predicted that: i) release sites would differ in terms of survival rates experienced by locally-released elk, with those animals released farther from the core of their historic range experiencing increase risk due to marginal habitat and higher predator densities, ii) survival rate variability would be largely influenced by an animal's time and experience on the landscape, with animals new to the landscape experiencing higher mortality from novel habitat and mortality risks, and iii) variability in survival rates would be influenced by distance from the release site, with recently-released animals having increased risk compared to those with more experience (e.g., length of time on the landscape). I considered that assessment of mortality determinants in reintroduced elk will be relevant to understanding the status and prognosis of recovering ungulate populations in the periphery of their native range, as well as inform on the development of successful reintroduction methodology for ungulate recovery programs.

54 STUDY AREA

The four elk reintroduction sites extend through Ontario, from Lake of the Woods (LOW;

49° 15' N, 93° 43' W) in the northwest, Lake Huron-North Shore (LHNS; 46° 26' N, 83° 6' W) and

Nipissing-French River (NFR; 46 ° 12' N, 80° 50' W) in the central part of the province, and

Bancroft-North Hastings (BNH; 45° 02' N, 83° 29' W) in south-eastern Ontario. Three of the release sites, LOW, NFR, and LHNS are located in the northern periphery of the historic range of elk in Ontario, while the BNH release is considered to be within the core historic range

(Hutchinson et al. 1997). Pair-wise distance between release sites ranges from 250 km to 1200km, therefore each site is considered as distinct. The major forest region represented in three of the four elk release sites (BNH, NFR, LHNS) is the Great Lakes-St. Lawrence forest, a transition zone between northern boreal forest and southern temperate forest (Rowe 1972). These forests generally contain sugar maple (Acer saccharum), yellow birch {Betula luted), and beech QFagus grandifolid), as well as mixed softwoods of white (Pinus strobus) and red pine (P. resinosd), trembling aspen (Populus tremuloides), balsam fir {Abies balsamiferd), white birch (Betulapapyriferd), and eastern hemlock (Tsuga canadensis; Rowe 1972, Chambers et al. 1997, Thompson 2000). The Boreal Forest

Region encompassed the LOW elk release site at the northern periphery of the historic elk range, and was dominated by coniferous trees including black spruce (Picea mariand), white spruce {Picea glaucd), and balsam fir (Abies balsamed) (Rowe 1972). Climate variability among areas includes a latitudinal temperature gradient, as well as a precipitation gradient from northwest to southeast

(Anonymous 2003). Mean maximum snow depth in all elk release areas averages between 50 and

65 cm annually (Anonymous 2003); however, spring green-up generally occurs one month earlier

(mid to late April) in the more southern elk release site (i.e., BNH) (Hutchinson et al. 1997).

Potential competitors to elk in the areas include white-tailed deer (Odocoileus virginianus) and moose

(Alces alces), whereas predators include wolves (Canis lupus, Canis lycaon), coyotes (Canis latrans) and

55 black bears (JJrsus americanus). Deer density is higher in the south (Hutchinson et al. 1997) while the densities of wolves and black bears is higher in the NFR and LOW areas (Bellhouse and

Rosatte 2005; Rosatte et al. 2007). Finally, human densities vary among the release areas with relatively low densities in the LOW, NFR, and LHNS release sites (1 person/1.6 km2), compared to much higher densities (15-19 per 1.6 km2) in the BNH region (Hutchinson et al. 1997).

METHODS

Animal Capture and Monitoring

From 1998 to 2001, 460 elk were transported from Elk Island National Park, Alberta, to 4 release sites in Ontario (Rosatte et al. 2007) (Table 3.1). Field monitoring of released elk began immediately following release (February/March 1998, 1999, 2000, and 2001) and continued through to the end of the study period in December 2005. All released elk were fitted with mortality\motion sensitive VHF radio-collars (Model LMRT-4; Lotek Engineering Inc.,

Newmarket, Ontario), except 30 of 60 animals released in 2000 in LOW, that were not collared.

Overall, the majority of marked animals were adult female (68.6%), followed by adult males

(20.9%), yearling females (3.9%), yearling males (3.1%), juvenile males (1.7%) and juvenile females

(1.6%). Radio-collars were replaced opportunistically throughout the study period, both on released animals and a small number of those born in Ontario. The percent of the estimated elk population on a given site that was radio-collared during the study period ranged between 25% and

97% in BNH (n=120), 56% and 100% in NFR (n=177), 50% and 71% in LOW (n=73), and 75% and 100% (n-50) in LHNS. Elk reintroduced to the BNH and LHNS were located weekly, whereas those released in NFR and LOW were located bi-weekly. Both ground and aerial telemetry techniques were regularly used for survival monitoring and cause of death assessment.

56 Assessment of Mortality Factors

Causes of elk mortality were interpreted on the basis of animal behavior prior to death (i.e., behavior indicating meningeal \Parelaphostrongylus tenuis\ worm infection) (Anderson and Lankester

1974) and ground-tracking and assessing the carcass as soon as possible after receiving a mortality signal. Physical evidence, such as sign of other species (i.e., predator tracks, scat) and condition of the remains were used to determine the cause of death (White and Garrott 1990). In cases where cause of death was difficult to determine, a veterinary pathologist (Canadian Cooperative Wildlife

Health Centre; University of Guelph) determined cause of death via necropsy.

The proximate cause of death was classified into categories based on evidence at the death site and ancillary information from carcass necropsy. Cause of death for elk in Ontario included: predation, illegal hunting, accidental death (vehicle collision, injury, drowning), emaciation, probable meningeal worm, death within one month of release resulting from transport injuries and/or post capture myopathy, and unknown (i.e., no clear evidence of cause of death, but in most cases predation, vehicle collision, drowning, and poaching were ruled out). A total of 17 elk were excluded from this analysis as they died during capture, handling, transportation, or in holding pens, and were never released onto the Ontario landscape (n=443).

Survival Estimation and Analysis

A staggered-entry Kaplan-Meier (Pollock et al. 1989) was used to estimate study period and annual survival rates for elk at each of the 4 Ontario release sites (n=443). To further investigate determinants of elk survival, Andersen-Gill hazards models were developed based on knowledge of the Ontario elk populations and published information on factors influencing elk and ungulate survival. Variables representing: i) the four elk release sites in Ontario (NFR, BNH, LOW, and

LHNS), ii) time in years (1998-2005) and biological seasons: parturition and lactation (1 May- 31

57 August), rutting period (1 September — 30 November), winter pregnancy (1 December — 31 April) were made available for inclusion. Year and season were also made available through a set of dummy variables representing year or season individually. Other variables under consideration as possible determinants of elk survival included iii) demographic characteristics (gender and age as dummy variables isolating adults and calves), and iv) length of holding period prior to release (<10 days, 11-20 days, 30-60 days, >90 days). Given the importance of sex and age in the survival of ungulates, two-way interaction terms between sex, age, and time variables (year of study and elk season) were also examined in the model to see if model fit improved (Hosmer and Lemeshow

1999) (Table 3.2). All elk released in Ontario between 1998 and 2001 were included in this analysis

(n=404) with the exception of 56 elk who were thought to have died from transport-related injuries and/or post-capture myopathy. These animals were excluded from this analysis to better characterize determinants of survival on the Ontario landscape in the absence of the effects of capture and transportation.

Detailed data for several environmental and behavioural factors thought to be important for elk were not available for all release sites in Ontario. Accordingly, a second series of models that included a more detailed set of variables complete for 116 elk released in the BNH region were used. Models included all the variables described above as well as spatially-explicit behavioural and environmental variables including maximum annual distance from release site, average annual direction from release site, size of annual 95 % fixed kernel home range, herd membership representing established herd member or solitary animal (based on radio-telemetry and observation), habitat variables (water, human settlement, sand/gravel/mine tailings/bedrock, forest depletion cuts, forest, wetlands agriculture/pasture/abandoned fields) associated with the annual 95% fixed kernel home range estimate for each subject, and average annual proximity (in km) to known elk and white-tailed-deer feeding locations (proxy measure for "P. tenuis exposure)

58 (Table 3.2). Habitat variables were derived from the Ontario Land Cover database, which is a province-wide classification system using multispectral LANDSAT thematic mapper images collected between 1999 and 2002 (Spectranalysis 2004). The spatial resolution of the classification data is 0.5 hectares and overall accuracy ranges from 85 to 95%, depending on the land cover type

(Spectranalysis 2004). Arc View 3.2 was used for all Geographic Information System analyses, including estimation of 95% fixed kernel home ranges for elk, which were calculated using the

Home Range Extension for Arc View. Again, given the importance of sex and age in the survival of ungulates, two-way interaction between sex, age, and time variables in the model (year of study and season) were also examined to see if model fit improved (Hosmer and Lemeshow 1999).

An a priori suite of 20 candidate models for all elk released in Ontario and 25 candidate models for elk released in the BNH regions were developed based on the understanding of the

Ontario elk population and published information on elk survival. For each of the models, determinants of elk survival were assessed using Andersen-Gill (AG) hazard models (Fleming and

Harrington 1991, Andersen et al. 1993). Following this method, survival was expressed in terms of the hazard function, where a hazard ratio > 1 indicated a decrease in survival as the predictor variable increased, while a hazard ratio < 1 indicated an increase in survival as the absolute of the predictor variable increased. When the 95% confidence interval around the hazard ratio included

1,1 assumed either no relationship between the mortality rate and the predictor, or that the estimate had low precision (Johnson et al. 2004).

Some of the predictor variables assessed overlapping environmental and behavioural conditions. To avoid problems associated with multicollinearity, I analyzed tolerance and variance inflation factors (VIF; Tabacknick and Fidell 1989). Tolerance statistics ranged from 0.447 to 1.326 and VIF ranged from 2.213 to 5.287 for all variables under consideration, therefore I considered multicollinearity acceptably low and did not eliminate any variables from the analysis.

59 Andersen-Gill models are based on the assumption of proportional hazards, as are their more common counter-parts, Cox Proportional Hazards models. To test the assumption of hazard proportionality, scaled Schonfeld residuals versus survival times were plotted and a chi-square

significance test was examined for the resulting correlation (Therneau and Grambsch 2000). The

assumption of proportional hazards was met for all models, thus proportionality of hazard was

assumed.

Andersen-Gill models were compared using standard model selection and multimodel inferencing procedures (Burnham and Anderson 2002). For all candidate models Akaike's

Information Criterion (AIC), AIC differences (Ai), and AIC weights (w,) were calculated to guide model selection, and I considered the model with Ai =0 to best fit the data and those with Ai >10

to have no support; Ai <2 indicated substantial support whereas Ai between 2 and 4 indicated marginal support (Burnham and Anderson 2002). If more than one model was considered plausible, model averaging techniques were used to more accurately include model selection uncertainty directly into the elk hazards (Burnham and Anderson 2002). The relative importance

of each individual variable was also examined by surnming AIC weights (w,) across all models that

contained the variable of interest (Burnham and Anderson 2002).

RESULTS

Mortality

A total of 218 mortalities of elk were documented for 443 released elk across the 4 Ontario release

areas between February/March 1998 and December 2005. Overall mortality for all elk released in

Ontario was 49%, ranging from a low of 19% in the LHNS region to a high of 85% in the NFR region (Table 3.3). Predation by wolves and possibly black bears was the most important proximate cause of mortality (27%), largely owing to comparatively high mortality in the NFR

60 region where 38% of all mortalities were attributed to predation. No mortalities in the LHNS region were attributed to predation, while only 3% and 8% of mortalities were attributed to predation in the BNH and LOW regions, respectively. Accidents, including vehicle collision, injury and drowning, were the cause of death for 21% of all elk in Ontario, followed by death within one month of release due to injuries sustained during translocation and/or post capture myopathy

(20%), emaciation (10%), poaching (10%), and infection with the parasite P.tenuis (2%). Only elk in the BNH, where white-tailed deer densities are high and winter feeding is common, experienced deaths attributed to P.tenuis. An additional 19% of elk in this study died from unknown causes.

Survival

Survival of 443 individual elk was monitored across the 4 Ontario release areas for an average of

899 ±13 (SE) days per animal. During the study period, the survival rate for all elk was 0.50 (0.41-

0.62), whereas across each of the four release areas survival ranged from 0.45 (0.37-0.53) in NFR,

0.54 (0.45-0.63) in BNH, 0.62 (0.49-0.782) in LOW and 0.81 (0.66-0.90) in LHNS (Figure 3.1).

Annual survival rates for all released elk were highest in the final year of this study, 2005, with a small but steady increase observed during the years 2003-2005. Annual survival rates for elk released in the NFR regions ranged from a high of 0.96 (0.60-0.98) in 2005 to a low of 0.49 (0.39-

0.59) in 2001, whereas for elk released in the BNH region annual survival rates ranged from a high of 0.80 (0.69-0.88) in 2005 to a low of 0.59 (0.48-0.68) in 2002. For elk released in the LOW region, annual survival rates ranged from a high of 0.87 (0.45-0.98) in 2005 to 0.57 (0.42-0.69) in

2002, while for those elk released in LHNS, annual survival rates ranged from a high of 0.98 (0.95-

0.99) in 2005 to a low of 0.80 (0.66-0.89) in 2003.

Andersen-Gill hazard models for all elk released in Ontario (excluding censors, n=404) revealed 6 candidates with substantial support (Ai <4) (Table 3.4). These top 6 models represented

0.96 of the available model weight and variables representing length of holding time Q^w, — 0.822)

61 and year of study (^jvt — 0.797) had the most collective weight of evidence, followed by season

= = (Y>;.= 0.766), sex (£u>,-= 0.295), age (T>,- 0.181), and the interaction term age*year (Y>; 0.173).

Because my analysis revealed 6 highly-plausible models (i.e., Ai <4), model-averaged hazard estimates indicated that animals subject to limited holding (<10 days) prior to release were 23.3

(95% CI: 20.404— 26.077) times less likely to survive than those who were held longer prior to release (>11 days) (Table 2.5). Year of study, elk season, sex, age, and the interaction term age*year also were associated with higher elk hazards; however, these variables tended to have a smaller effect on elk mortality risk. More specifically, model-averaged hazard estimates indicated that elk were less likely to survive in the year immediately following release (0.478; 95% CI: 0.359-0.0.598).

Elk were also less likely to survive during the winter months December-April (0.591; 95% CI:

0.358-0.822). Sex and age also influenced survival with male elk (0.240; 95% CI: 0.035-0.444) and calves (0.769; 95% CI: 0.726-0.810) experiencing higher rates of survival. Finally, the interaction term of age*year revealed that adult elk experienced lower rates of survival in the year immediately following release (1.835; 95% CI: 0.030-3.267) (Table 3.5).

To further investigate the factors influencing elk survival, a second set of models based on variables that were complete for animals released in BNH (n=112) were evaluated. Six candidate models were considered to have substantial support (Ai <4), and included variables representing size of annual home range (^JV;= 0.998) and direction from release site (Y>_,= 0.922), followed by year of study (Y>.= 0.722), percentage of agricultural land in the home range (Y>/~ 0.559),

percentage of human settlement in the home range (^jfj— 0.505), interaction term age*year (Y>; =

0.447) and the interaction term sex*age (Y>/~ 0.371) (Table 3.6). More specifically, model- averaged estimates of elk hazards for the top 6 models revealed that elk with comparatively large annual home ranges were 1.09 (95% CI: 0.648-1.132), times less likely to survive than those with smaller home ranges (Table 3.7). As well, elk whose average direction was south/south-west of

62 the release site were 1.001 (95% CI: 0.638-1.336) times less likely to survive than those that dispersed in other directions. Year of study, percentage of agricultural land in the home range, percentage of human setdement in the home range, and interaction terms age*year and sex*age also were associated with higher elk hazards, however, these variables had a small effect on elk survival and a lower weight of evidence. Notably, elk were less likely to survive in the year immediately following release (0.490; 95% CI: 0.306-0.674). The risk of mortality was also higher for elk whose home range consisted of higher proportions of agricultural land (0.548; 95% CI:

0.211-0.886) and human setdement (0.187; 95% CI: 0.011-0.364). Finally, the interaction term age*year (0.919; 95% CI: 0.554-1.522) and the interaction term sex*age (0.899; 95% CI: 0.333-

2.421) also were associated with higher elk hazards, with adult female elk experiencing lower rates of survival, especially in the year immediately following release (Table 3.7).

DISCUSSION

Although the main causes of mortality and mechanisms responsible for variation in survival of large ungulates are relatively well understood, deviation from general patterns is expected for new and establishing populations that are exposed to a different habitat and novel mortality risks.

Overall, my study revealed that survival of elk was low compared to established populations, but was similar to rates reported for reintroduced or establishing populations (Raedeke et al. 2002;

Larkin et al. 2003; Muller et al. 2004). As I anticipated, the lowest annual survival rates were generally recorded in the year immediately following release, largely owing to death from post capture myopathy and/or transport related injuries; however, factors associated with inexperience or unfamiliarity with the Ontario landscape, such as high rates of predation, accidental death, and poaching were also important causes of death in the years immediately following release. These results are similar to those reported for elk reintroduced to the core of their historic range in

63 Kentucky, where 49% of all mortalities were attributed to capture injuries (Larkin et al. 2003), with the remaining related to accidents (18%) and movement outside the restoration zone (4%).

The analyses of the mechanisms responsible for elk survival in Ontario garnered further support for the hypothesis that survival rates would increase as an animal's time and experience on the landscape increased. Indeed, both holding time and year of study were strong predictors of elk survival in Ontario. Increasingly, the method of release is recognized as an important factor in the success of wildlife reintroductions, with soft release involving holding animals through an acclimation period being beneficial (Maloney et al. 2006, Bright and Morris 1994, Haydon et al.

2008, Yott et al. 2010). For example, high release site fidelity, social cohesion and relatively high survival rates of Tule elk reintroduced to California were attributed to holding animals in small pens for 3-6 months prior to release on the landscape (Gogan and Barrett 1998).

In Ontario, the length of time elk were held prior to release varied from 112 days in the

LHNS region to some animals experiencing no acclimation in BNH region following an escape/release from the enclosure the day they were placed in the holding pen. The relationship between holding time and survival for Ontario elk may be related to increasing site fidelity and social cohesion for animals experiencing a soft release. For a reintroduced species, a balance of dispersal and coalescence generally determines the distribution of animals across the landscape

(Haydon et al. 2008), and elk survival is generally higher for those in groups (Raedeke, et al. 2002).

Therefore, survival may, in part, depend on the coalescence process limiting widespread dispersal across the landscape and the establishment of an effective group structure within the release area

(Haydon et al. 2008).

For elk released in the BNH region of Ontario, elk hazards increased with size of the animals' home range. Following release in a novel environment animals often experience a dispersive phase in which they rapidly emigrate from the point of origin, possibly to explore the

64 novel landscape and to find good quality habitat (Haydon et al. 2008, Fryxell et al. 2008). Dispersal also may be influenced by the proximity of other animals, as was the case relative to elk farms in the LOW, BNH, and LHNS regions of Ontario where recently-released elk were drawn (Mcintosh

2003, Ryckman 2008). Dispersal of elk in the NFR region may also have been influenced by the existing wild elk population, a remnant group from a reintroduction attempt in the 1930's.

Alternatively, elk may have dispersed to more suitable habitat and high quality forage conferring lower risk, although this scenario is unlikely because the BNH elk release site was located in the core of the historic elk release site in Ontario, and habitat quality and forage availability was presumably high.

In this study, elk that moved in a southward direction also experienced lower survival than those that moved in a more northerly direction. Due to restricted elk habitat availability in southern Ontario, southward movements may reflect searching for better quality habitat near the core of their historic range in agricultural areas, where elk can easily obtain high quality forage.

Although southern regions may provide better elk habitat than some of the actual release areas, increased proximity to anthropogenic activities at lower latitudes likely increased mortality caused by humans. Indeed, the highest rates of vehicle collisions and illegal hunting of elk were recorded in the BNH region - the most southerly and most densely-populated region of the current elk range in Ontario (Hutchinson et al. 1997; OMNR 2010). Studies elsewhere also indicate that human-caused mortality is generally important for recovering ungulate populations, especially those with low predator densities. For example, among elk released in both Kentucky and

Tennessee, vehicle collisions and poaching were among the most important causes of death

(Larkin et al. 2003, MuUer et al. 2004).

Finally, I anticipated that elk located in release sites closer to the core of the historic range of elk in Ontario would have higher survival, as habitat quality would be high and predator density

65 low (Hutchinson et al. 1997). Although, elk in the NFR and BNH regions had slightly lower overall survival rates compared to those in the LOW and LHNS regions, release site was not a significant predictor of survival. These results are unexpected given the disparity in habitat features and locations of the sites (Hutchinson et al. 1997). My results may be explained by the fact that although the main causes of mortality differed for each release site (i.e., predation was the leading cause of death for elk released in the NFR and LOW release area, while vehicle collisions and poaching were the leading causes of death for elk in the BNH region), overall mortality rates were similar across all 4 release sites.

Management Implications

My results provide an extensive analysis of causes of mortality and determinants of survival in 4 distinct populations of elk recently reintroduced to Ontario, and reveal clear patterns of increased mortality risk that can inform elk population restoration and management, as well as reintroduction methodologies for wildlife recovery programs. First, the results indicate that post-capture myopathy and transportation-related injuries can be an important cause of mortality during the initial stage of a wildlife reintroduction project and should be considered a predictable factor to incorporate into planning. Investigation into methods that work to minimize the effects capture and transportation related deaths, such as improved capture and care techniques, are recommended as the establishment of a new group of individuals often depends on short-term local survival of released individuals (Armstrong and Seddon 2007). The results of this study also suggest that survival of elk is largely influenced by the method of introduction to the novel landscape and behaviour in the first year following release. Therefore, actions such as holding animals in an enclosure prior to release can mitigate disruption of natural group structure and provide acclimation and familiarity to the novel environment. Finally, the negative effect of proximity to humans implies that release sites further from human settlement, coupled with efforts

66 to minimize dispersal away from the carefully chosen release site can improve the chances of population persistence.

LITERATURE CITED

Andersen, P.K., Borgan, 0, Gill, R.D., and N. Keiding. 1993. Statistical models based on counting processes. Springer-Verlag, New York, New York, USA.

Anderson, R.C., and M.W. Lankester. 1974. Infectious and parasitic diseases and arthropod pests of moose in North America. Naturaliste Canada 101:23-50.

Anonymous. 2003. Canadian climate normals 1981-2003. Environment Canada, Atmospheric Environment Service Report. Ottawa, Ontario, Canada.

Armstrong, D. P. and J. L. Craig. 1995. Effectsfof familiarity on the outcome of translocations: a test using saddlebacks Phiksturnus carunculatus rufusater. Biological Conservation 71: 133-141.

Armstrong, D.P., and P.J. Seddon. 2007. Directions in reintroduction biology. Trends in Ecology and Evolution23:20-25.

Ballard, W.B., Whitlaw, H.A., Wakeling, B.F., Brown, R.L., DeVos, J.C., and M.C. Wallace. 2000. Survival of female elk in northern Arizona. Journal of Wildlife Management 64:500-504.

Belsley, D. A., Kuh, E., and R.E. Welsch. 1980. Regression diagnostics: Identifying influential data and sources of collinearity. Wiley, New York, New York, USA.

Bender, L.C., Lomas, L.A., and J.B. Browning. 2007. Condition, survival and cause-specific mortality of adult female mule deer in north-central New Mexico. Journal of Wildlife Management 71:1118-1124.

Bright, P.W. and P.A. Morris. 1994. Animal translocation for conservation: performance of dormice in relation to release methods, origin and season. Journal of Applied Ecology 31:699-708.

Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer, New York, New York, USA.

Caughley, G. 1966. Mortality patterns in mammals. Ecology 47:906-918.

Caughley, G. 1977. Analysis of vertebrate populations. Wiley, London, UK.

Caughley, G, and L.C. Birch. 1971. Rate of Increase. Journal of Wildlife Management 35:658-663.

67 Chambers, B. A., Naylor, B.J., Nieppola, J., Merchant, B., and P. Uhlig. 1997. Field guide to forest ecosystems in central Ontario. South Central Region Science and Technology Report FG- 01. Toronto, Ontario, Canada.

Coulson, T., Catchpole, E.A., Albon, S.D., Morgan, J.T., Pemberton, J.M., Clutton-Brock, T.H., Crawley, M.J., and B.T. Grenfell. 2001. Age, sex, density winter weather and population crashes in Soay sheep. Science 292:1528-1531.

Coulson, T., Milner-Gulknd, E.J., and T.H. Clutton-Brock. 2000. The relative roles of density and climatic variation on population dynamics and fecundity rates in three contrasting ungulate species. Proceedings of the Royal Society of London, Series B 267:1771-1779.

Eastridge, R., andJ.D. Clark. 2001. Evaluation of two soft-release techniques to reintroduce black bears. Wildlife Society Bulletin 29:1163-1174.

Fischer, J. and D.B. Lindenmayer. 2000. A review of relocation as a conservation management tool. Biological Conservation 96, 1-11.

Flemrning, T., and D. Harrington. 1991. Counting processes and survival analysis. John Wiley and Sons, New York, New York, USA.

Fowler, C.W. 1987. A review of density dependence in populations of large animals. Current Mammalogy 1:401 -441.

Frair, J.L., Merrill, E.H., Allen, J.R., and M.S. Boyce. 2007. Know thy enemy: Experience effects elk translocation success in risky landscapes. Journal of Wildlife Management 71:541-554.

Fryxell, J.M., Hazell, M., Borger, L., Dalziel, B.D., Haydon, D.T., Morales, J.M., Mcintosh, T., and R.C. Rosatte. 2008. Multiple movement models by large herbivores and multiple spatiotemporal scales. Proceedings of the National Academy of Sciences. 105:19114-19119.

Gaillard, J.M., Festa-Bianchet, M., and N.G. Yoccoz. 1998. Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends in Ecology and Evolution 13:58-63.

Garrott, R.A., and Eberhardt, L.L., White, P.J., and J. Rotella. 2003. Climate-induced variation in vital rates of an unharvested large herbivore population. Canadian Journal of Zoology 81:33-45.

Griffith, B., Scott, J.M., Carpenter, J.W., and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science. 245:477-480.

68 Gogan, P., and R. Barrett. 1988. Lessons in management from a translocation of Tule elk. Pps. 275-285 In: Translocation of Wild Animals. Eds. L. Nielsen and R. Brown. Wisconsin Humane Society.

Haydon, D.T., Morales, J.M., Yott, A., Jenkins, D.A., Rosatte, R., and J.M. Fryxell. 2008. Socially informed random walks: incorporating group dynamics into models of population spread and growth. Proceedings of the Royal Society B. 275:1101-1109.

Hosmer, D.W., and S. Lemeshow. 1999. Applied survival analysis. John Wiley and Sons. New York, New York, USA.

Hutchinson, B.C, Ranta, W.B., Fraser, B.C., and J. Quirouette. 1997. Determining the most suitable areas for elk restoration in Ontario, Canada. Unpubl. 21pp.

Johnson, C.J., Boyce, M.S., Schwartz, C.C., and M.A. Haroldson. 2004. Modelling survival: application of the Andersen-Gill model to Yellowstone grizzly bears. Journal of Wildlife Management 68:966-978.

Jamieson, I. G., Tracy, L. N., Fletcher, D., & Armstrong, D. P. (2007). Moderate inbreeding depression in a reintroduced population of North Island robins. Animal Conservation, 10, 95-102.

Larkin, J.L., Maehr, D.S., Cox, J.J., Bolin, D.C., and M.W. Wichrowski. 2003. Demographic characteristics of a reintroduced elk population in Kentucky. Journal of Wildlife Management 67:467-476.

Linklater, W.L, Adcock, A., du Preez, P., Swaisgood, R.R., Law, P.R., Knight, M.H., Gedir, J.V., and G.I.H Kerley. 2011. Guidelines for large herbivore translocation simplified: black rhinoceros case study. Journal of Applied Ecology 48:493-502. Loison, A. and R. Langvatn. 1998. Short- and long-term effects of winter and spring weather on growth and survival of red deer in Norway. Oecologia 116:489-500.

Loison, A., Festa-Bianchet, M., Gaillard, J.M., Jorgenson, J.T., and J.M. Jullien. 1999. Age- specific survival in five populations of ungulates: evidence of senescence. Ecology 80:2539-2554.

Kunkel, K. and D.H. Pletscher. 1999. Species-specific population dynamics of cervids in a multipredator ecosystem. Journal of Wildlife Management 63:1082-1093.

Mcintosh, T. 2003. Movements, survival and habitat use by elk (Cervus elaphus) reintroduced to northwestern Ontario. MSc Thesis. Lakehead University, Thunder Bay, Ontario.

Moran, R.J., 1973. The Rocky Mountain elk in Michigan: Research and Development Report No. 267. Michigan Department of Natural Resources, Lansing, Michigan.

Muller, L., Kindall, J., Lupardus, J., and S. Bennett. 2004. Tennessee elk restoration project Tennessee Wildlife Resources Agency Report. Knoxville, Tennessee, USA.

69 Murray, D.L, Cox, E.W., Ballard, W.B., Whitlaw, H.A., Lenarz, M.S., Custer, T.W., Barnet, T., and T.K. Fuller. 2006. Pathogens, nutritional deficiency, and climatic influences on a declining moose population. Wildlife Monographs 166:1-30.

Molony, S.E., Dowding, C.V., Baker, P.J., Cuthill, I.C., and S. Harris. 2006. The effect of translocation and temporary captivity on wildlife rehabilitation success: an experimental study using European hedgehogs (Erinaceus europaeus). Biological Conservation 130:530—537.

Owen-Smith, N. 2003. Foraging behaviour, habitat suitability and translocations success, with special reference to large mammalian herbivores. Pages 93-109 in M. Festa- Bianchet, editor, Animal behaviour and wildlife conservation. Island Press, Washington D.C., USA.

Raedeke, K.J., Millspaugh, J.J., and P.E. Clark. 2002. Population Characteristics. In D.E. Toweill and J.W. Thomas Eds. North American Elk: Ecology and Management. Smithsonian Institution Press, Washington, USA.

Rosatte, R., Hamr, J., Young, J., Filion, I., and H. Smith. 2007. The restoration of elk [Cervus elaphus) in Ontario, Canada 1998-2005. Restoration Ecology 15:34-43.

Rowe, J. S. 1972. Forest regions of Canada. Canadian Forest Service Publication Report. 1300. Ottawa, Ontario, Canada.

Ryckman, M.J., Rosatte, R.C., Mcintosh, T., Hamr, J., and D.Jenkins. 2007. Post release dispersal of reintroduced elk [Cervus elaphus) in Ontario, Canada. Restoration Ecology 18:173-180.

Sa^ther, B.E. 1997. Environmental stochasticity and population dynamics of large herbivores: a search for mechanisms. Trends in Ecology and Evolution 3:91-95.

Sasfher, B.E., Engen, S., Solberg, E.J., and M. Heim. 2007. Estimating the growth of a newly established moose population using reproductive value. Ecography 30:417-421.

Sarrazin, F., and S. Legendre. 2000. Demographic approach to releasing adult versus young in reintroductions. Conservation Biology 14:488-500.

Somers MJ, Graf JA, Szykman M, Slotow R, Gusset M (2008) Dynamics of a small re­ introduced population of endangered wild dogs over 25 years: Allee effects and the implications of sociality for conservation. Oecologia 158:239—247.

Spectranalysis Inc. 2004. Introduction to the Ontario Land Cover Database Second Edition (2000): Outline of production methodology and description of 27 land cover classes. Report to Natural Resources Information Branch, Ontario Ministry of Natural Resources, Peterborough, Ontario.

Stamps, J.A. and R.R. Swaisgood. 2007. Someplace like home: experience, habitat selection and conservation biology. Applied Animal Behaviour Science 102: 392-409.

70 Stewart, K.M., Bowyer R.T., Dick, B.L.Johnson, B.K., andJ.G. Kie. 2005. Density dependent effects on physical condition and reproduction in North American elk: an experimental test. Oecologia 143:85-93.

Tabachnick, B. G. and L.S. Fidell 2001. Using multivariate statistics: Fourth edition. Allyn & Bacon, New York, New York, USA.

Therneau, T.M. and P.M. Grambsch. 2000. Modelling survival data. Springer-Verlag, New York, New York, USA.

Thompson, I. D. 2000. Forest vegetation of Ontario: factors influencing landscape change. Pages 336 in Perera A. H., Euler D. L., Thompson I. D., editors. Ecology of a managed terrestrial landscape: patterns and processes of forested landscapes in Ontario. University of British Columbia Press, Vancouver, Canada.

White, G.C., and R.A. Garrott. 1990. Analysis of Wildlife Radio-Tracking Data. Academic Press, San Diego.

Wolf, CM., Garland, T.G., and B. Griffiths. 1998. Predictors of avian and mammalian translocation success: reanalysis with phylogenetically independent contrasts. Biological Conservation. 86:243-255.

Yott, A., Rosatte, R., Schaefer, J.A., Hamr, J., and J. Fryxell. 2010. Movement and spread of a founding population of reintroduced elk {Cervus elaphus) in Ontario, Canada. Restoration Ecology. 19:70-77.

71 Table 3.1: Sex and age breakdown of radio-collared elk transported to the Nipis sing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron-North Shore (LHNS) regions of Ontario from 1998 to 2001.

Release Date Adults Yearlings Calves site Males Females Males Females Males Females NFR Mar. 1998 14 34 na na 0 0 NFR Jan. 1999 7 42 na na 6 14 NFR Mar. 2000 0 15 na na 7 13 NFR Feb.2001 0 10 na na 7 8 BNH Jan. 2000 10 32 4 4 10 10 BNH Jan. 2001 8 18 5 2 6 11 LOW Jan. 2000 5 15 na na 4 6 LOW Feb.2001 7 15 5 3 8 5 LHNS Dec. 2000 4 27 4 4 8 3

Total 45 208 18 13 56 70 Note: A total of 12 animals were radio-collared in Ontario following release (5 in BNH & 7 in NFR) In 2002 5 elk were relocated from LHNS to NFR due to nuisance

72 Table 3.2: Description of variables used in analyses of elk survival in Ontario. The first set of models included all elk reintroduced to Ontario, with release site as a categorical variable. The second analysis included more detailed variables reflecting environmental and behavioural characteristics of elk reintroduced to the BNH region of Ontario.

Variable Description and coding system Demographic Gender Gender (female—1) Age class Dummy variable representing age class (adult= 1, juvenile — 2)

Temporal Season Dummy variable representing each season of the study (Dec-Apr-1, May-Aug—2, Sept-Nov-3) Year Dummy variables representing each year of the study

Behavioural Distance from release site a Annual average distance form the release site Direction from release site a Annuals average direction from the release site Annual home range size a 95% fixed kernel home range size (m2) a z Herd member Dummy variable representing established herd member or solitary animal (herd = 1)

Habitat Habitat type a Proportions of 7 habitat types identified by Ontario Land Sat images (water, settlement/infrastructure, sand/gravel/mine tailings/bedrock, forest depletion cuts, forest, wetlands agriculture/pasture/abandoned fields)

Anthropogenic Holding period Length of holding period prior to release (<10 days=l, 11-20 days=2, 30-60 days=3, >90 days=4) Release site Dummy variable representing the 4 elk release sites in Ontario (BNH=1, NFR=2, LOW=3, LHNS=4) Feeding sites a Dummy variable representing elk in close proximity to feeding sites (feeding=l); proxy measure for PJenuis exposure a available only for elk released in the BNH region of Ontario (i.e., model population)

73 Table 3.3: Percent cause-specific mortality for elk reintroduced to 4 sites in Ontario, Canada including Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron-North Shore (LHNS) from January 1998 to December 2005. Sample sizes are in parentheses.

Release Release Total mortality Transport Emaciation Predation Poaching Accident P.tenuis Unknown site Year injuries/ post-capture myopathy NFR 1998 70 (28/40) 46 (13) 0 35 (9) 4(1) 12(3) 0 8(2)

NFR 1999 85 (56/66) 23 (13) 32 (14) 18 (18) 0 16(7) 0 9(4)

NFR 2000 54 (19/35) 0 5(1) 58 (11) 0 37(7) 0 0

NFR 2001 57 (13/23) 15(2) 0 46(6) 0 38(5) 0 0

BNH 2000 53 (37/70) 22(8) 13(4) 6(2) 16(5) 26 (8) 3(1) 29(9)

BNH 2001 46 (23/50) 0 0 9(2) 26(6) 13(3) 13(3) 39(9)

LOW 2000 50 (15/30) 0 0 20(3) 27 (4) 20(3) 0 33(5)

LOW 2001 42 (18/43) 33(6) 0 18(3) 6(1) 18(3) 0 29(5)

LHNS 2001 19 (9/47) 11 (1) 0 0 22(2) 22(2) 0 44(4)

All 98-01 49 (218/443) 20 (43) 10 (19) 27 (54) 10 (19) 21 (41) 2(4) 19 (38)

Note: Total mortality is accumulated mortality for radio-collared elk from release year to December 31st, 2005. IZlk that died prior to release (i.e., at E1NP, m transport, in holding pens) were eliminated from the analyses (n=17)

74 Figure 3.1: Kaplan- Meier survival rates for elk reintroduced to four release sites in Ontario including Nipissing-French River (NFR), Bancroft-North Hastings (BNH), Lake of the Woods (LOW) and Lake Huron-North Shore (LHNS) from 1998-2001. Cumulative time 0 represents the release day into the study rather than calendar time.

o o

co S To E LO "55 o LU "ro > o CO

£8 CO

o o o 1000 2000 300C Cummulative time (days) NFR BNH LHNS — LOW

75 Table 3.4: Candidate models for elk survival in four release sites in Ontario, Canada December 1999 to December 2005. For each Andersen-Gill model I include number of parameters (K), Akaike's Information Criterion (AIC), AIC difference (A,), AIC weight (IP), and goodness-of-fit (P) (a— 404). Only models with <5 A, are provided.

Model description K AIC A w, x2 P

1 season + year of study + holding time 44 1420.11420.15 00 0.290 78.05 <0.001

2 year of study + holding time 3 1420.60 0.45 0.231 75.60 <0.001

3 sex + age + elk season + year of study + 5 1420.623 0.48 0.176 78.39 <0.001 age*year 4 season + year of study 3 1421.15 1.000 0.169 75.04 <0.001

5 Sex + season + year of study + holding 5 1421.23 1.08 0.123 78.97 <0.001 time 6 Sex + age + season + year of study + 6 1421.86 1.71 0.033 80.34 <0.001 holding time 7 Age + season + release area + year of 6 1424.52 4.37 0.026 81.68 0.0023 study + holding time 8 Sex + age + season + release area + year 7 1424.98 4.83 0.010 83.22 0.0047 of study + holding time

76 Table 3.5: Model averaged hazards ratios and unconditional standard errors for the top 6 (<4 A,) models developed to explain survival of elk in Ontario, Canada, December 1999- Decmber 2005.

95% CI

Parameter Hazard Ratio SE Upper Lower

Season 0.591 0.119 0.822 0.358

Year of study 0.478 0.061 0.598 0.359

Holding time 23.248 1.451 26.077 20.404

Sex 0.240 0.105 0.444 0.035

Age 0.769 0.021 0.810 0.726

Age*year 1.835 0.540 3.267 0.030

77 Table 3.6: Candidate models for elk survival in the BNH region of Ontario, Canada December 1999 to December 2005. For each Andersen-Gill model I include number of parameters (K), Akaike's Information Criterion (AIC), AIC difference (A,), AIC weight {w), and goodness-of-fit (P) {n— 116). Only models with <5 A, are provided.

Model description K AIC A, w, X2 P

L year of study + direction from release site 5 146.011 0~000 0386 25.28 <0.001 +agriculture + home range size I year of study + direction from release site+ 5 147.818 1-806 0.157 24.42 <0.001 setdement+ home range size * year of study + direction from release site + 6 148.153 2.142 0.132 26.19 <0.001 settlement + agriculture + home range size 1 year of study + direction from release site + 4 148.933 2.922 0.090 21.41 <0.001 home range size j year of study+direction from release site + 6 148.959 2.939 0.089 25.39 0.001 agriculture+ home range size + age*year > year of study+ direction from release site + 6 149.012 3.001 0.086 25.43 0.001 agriculture+ home range size + sex*age

78 Table 3.7: Model averaged hazards ratios and unconditional variances for the top 6 (<4 A,) models developed to explain survival of elk released in the BNH region of Ontario, Canada, January 2000-Decmber 2005.

95% CI

Parameter Hazard Ratio SE Upper - Lower

Year of study 0.490 0.094 0.674 0.306

Direction from release site 1.001 0.178 1.336 0.638

Agriculture 0.548 0.173 0.886 0.211

Settlement 0.187 0.091 0.364 0.011

Home range size 1.09 0.181 1.132 0.648

Age*Year 0.919 0.237 1.522 0.554

Sex*Age 0.899 0.455 2.421 0.333

79 CHAPTER 4

EVIDENCE AND IMPLICATIONS OF PARELAPHOSTRONGYLUS TENUIS INFECTION IN A

FREE RANGING ELK (CERVUS ELAPHUS) POPULATION IN SOUTHERN ONTARIO,

CANADA2

ABSTRACT

Parelaphostrongylus tenuis is one of the most pathogenic nematodes of cervids such as elk, moose, and caribou, often causing severe neurological disease and death. During 2000 and

2001, 120 elk (Cervus elaphus), were transported from Elk Island National Park, Alberta, and released in the Bancroft, Ontario area. This was part of a larger restoration project in which

443 elk were released in 4 areas of Ontario during 1998-2001 (Rosatte et al. 2002). All but one of the Bancroft area released elk were radio-collared and ear-tagged prior to release. This provided a means for monitoring the location of released elk, as well as their progeny that were born in Ontario. During 2000-2005, 42 elk that died in southern Ontario were collected opportunistically to determine their state of health, body condition, and to determine in some cases, the cause of death. Post-mortems on 42 elk yielded four classes of animals at their time of death: i) elk that were probably exposed to P. tenuis and developed inflammatory lesions in the brain but were in good condition, ii) elk with clinical syndrome due to P. tenuis infection, had neurological signs, and were in an emaciated state, iii) elk without evidence of P. tenuis infection, and iv) animals in which infection was not assessed, due to unsuitability or unavailability of brain tissue for examination. Of the 42 elk that had succumbed due to a variety of reasons (found dead, illegally shot, collisions with vehicles,

Mcintosh, Terese, E., Rosatte, Richard, C, Campbell, Douglas, Welch, Kate, Fournier, Dominique, and Maria Spinato. 2007. Evidence oiParelaphostronglus tenuis infection in free ranging elk populations in Southern Ontario Canada. Canadian Journal of Veterinary Medicine 48:1146-1154.

80 drowning, hit by a train), 13 died too soon following release (1-5 months) to have become infected with P. tenuis (i.e. the elk originated in Alberta where apparently there is no P. tenuis in wild deer or elk). Of the 29 that survived longer than 6 months post release, 17 (59%) had lesions in the brain compatible with P. tenuis infection. Greater numbers of females had lesions than males (p< 0.025; Chi Square=5.04); however, no differences with respect to the age of elk and occurrence of lesions was found (9 elk were < 2 yrs of age and 8 elk were > 3 yrs of age) (p=0.7, Chi square = 0.15). The sex/age composition of the 17 elk that had lesions was: 35% (6/17) cows >3 yrs; 12% (2/17) 2 yr old cows; 24% (4/17) yearling cows;

12% (2/17) bulls > 3 yrs; 6% (1/17) 2 yr old bulls; and 12% (2/17) yearling bulls. Of the 11 elk that were not suspect for P. tenuis, 27% were adult cows, 27% were adult bulls, 36% were yearling bulls and 1 was a male calf. None of the 13 elk that died 1-5 months post release had any evidence of P. tenuis infection.

CASEI

During 2003/2004, a group of about 30-40 elk consisting of animals transported from Elk Island National Park (EINP, Alberta and their offspring that had been born in

Ontario were observed frequenting the area of Hartsmere, Ontario (approximately 44° 5 N,

77° 30 W, about 30 km east of Bancroft, Ontario). During October and November, 2004, a resident reported seeing a sick yearling bull elk in this group. During December 2004, the animal later left the group, became solitary, and began to frequent a near-by barn.

Eventually, the animal stayed continuously at the barn prompting the resident to provide feed, particularly alfalfa. Clinical signs exhibited by the yearling bull elk included a loss of fear of humans, ataxia, loss of balance, and a drooping head. Moreover, the elk had left the

Hartsmere elk group, which is an abnormal behaviour for a social animal such as an elk, and

81 it remained solitary near the barn since December 2004. Based on the observed clinical signs a tentative diagnosis of P. tenuis infection was made and it was decided to attempt to acquire a blood sample from the animal for the purpose of immunodiagnosis.

On January 11, 2005 (-17° C ambient temperature), the P. tenuis suspect yearling bull elk was immobilized with an intramuscular injection of 500 mg of Telazole (tiletamine hydrochloride and zolazepam hydrochloride, Fort Dodge Animal Health, Fort Dodge, Iowa) and 300 mg of AnaSed (xylazine hydrochloride, Vet-A-Mix, Shenandoah, Iowa). The elk was estimated to weigh 150-200 kg. As the elk had no fear of humans and was approachable, the drugs were administered intramuscularly in the right upper hind limb area via a 5 cc sterile syringe (Burron Medical Products, Bethlehem, Pennsylvania, USA) and 22g (4 cm) needle (Terumo, Belgium) attached to jab stick (an 80 cm section of copper tubing which contained a wooden dowel to apply pressure to the syringe plunger). After the animal was immobilized, 8 ml of blood was collected from the jugular vein into 2 lOcc sterile Vacutainer blood collection tubes containing EDTA (Becton Dickinson, Franklin Lakes, New Jersey,

USA) and 20g (4cm) sterile Vacutainer needles (Becton Dickinson, Franklin Lakes, New

Jersey, USA). The elk was also fitted with a VHF (148.402 Mhz) radio-collar (Lotek

Engineering, Newmarket, Ontario, Canada) and ear-tagged (#139, Flex-Lok, Ketchum

Manufacturing, Ottawa, Ontario, Canada) for future identification. When processing was complete, the elk was administered an intramuscular injection (right hind limb) of 12 mg of

Yobine (yohimbine hydrochloride, Lloyd Laboratories, Shenandoah, Iowa, USA) as an antagonist to speed up recovery from the effects of xylazine. The elk recovered fully. The blood sample was later centrifuged at 2000 RPM for 15 minutes and a 4 ml plasma sample was collected using a pipette and stored in two 2 ml sterile plastic microtubes (Sarstedt,

82 Germany) at -12 C. The frozen sample was shipped one week later by courier to the Prairie

Diagnostic Services laboratory in Regina, Saskatchewan.

The blood plasma sample was tested for the presence of antibodies against P. tenuis using an enzyme-linked immunosorbent assay (ELISA) as described by Ogunremi et al.

(2002a). The S/P ratio of an ELISA test performed on the bull elk sample on February, 4,

2005, was 0.986 which translates to an ELISA index of 98.6 units, cut off — 45.0 units, indicating the bull elk was exposed to P. tenuis. Validation of the ELISA test in elk has yielded a sensitivity of 100% (n=12) and a specificity of 97% (n=579) (manuscript in preparation).

Although field infected elk rarely pass enough P.- tenuis first-stage larvae to make fecal examination a reliable diagnostic test (Pybus et al. 1989), nevertheless an attempt was made to recover larvae from the feces of the P. tenuis-suspect bull elk using the Baermann technique. Fecal samples were collected at the location of the bull elk on February 18, 2005 and screened for P. tenuis larvae using the Baermann-beaker technique (Forrester and

Lankester 1997) at Trent University, Peterborough, Ontario, as well as at the Regina laboratory of the Prairie Diagnostic Services, Inc., Saskatchewan. No P. tenuis larva was detected in the feces of the bull elk using this technique however, the samples were positive for the lungworm, Dictyocaulus sp. Historical observations indicate that larval shedding is typically inconsistent or undetectable in P. tenuis-infected elk (Anderson et al. 1966; Welch et al. 1991). More recently, out of 4 elk inoculated with 6-20 L3, 2 larvae were recovered from only 1 animal that shed larvae and only on day 202 post exposure despite meticulous examination of feces two times a week (Ogunremi et al. 2002a).

Between February and May 2005, the Bancroft bull elk intermittently showed the same neurological signs but had deteriorated by June 1, 2005. Because of concerns about

83 the safety of motorists due to the elk's proximity to the road, and to prevent further undue suffering of the animal, a decision was made to euthanize. At this time, a second blood sample was collected and the plasma again tested positive for P. tenuis. Postmortem examination findings included: meningoencephalomyelitis, characterized by moderate to severe perivascular cuffing of eosinophils, lymphocytes, plasma cells, and macrophages in the brain and spinal cord. Four sections of degenerate larvae (Figure 4.1a), and one of a normal-looking larva (Figure 4.1b) were present in the meninges of the brain. All larvae were surrounded by mononuclear cells and in addition two of the degenerate sections were closely associated with eosinophils (1 and 5 eosinophils; Figure 4.1c). The larvae had the same features as the ones earlier found in the histopathological sections of P. tenuis-infected elk brain (Carpenter et al. 1973). Areas of haemorrhages were observed in the white matter of the spinal cord and brain. Hemosiderin granules were present inside macrophages and extraceUularly in the brain and spinal cord sections. In the lungs, an adult female worm with eggs (85 x 45 urn) was recovered. There was severe pulmonary congestion and infiltration of inflammatory cells particularly eosinophils, macrophages and lymphocytes. The CNS and pulmonary lesions are attributable to P. tenuis and Dictyocaulus, respectively. While serological cross-reactivity has been observed between Dictyocaulus-intected elk and WTD sera and the somatic antigens of P. tenuis (Bienek et al. 1998; Ogunremi et al. 2002a), no such cross- reactivity was observed against the ES products of P. tenuisUi (Ogunremi et al. 1999, 2002a).

Specificity of the P. tenuisELISA was found to be 97.2% (95% confidence interval, = 95.8 -

98.6%) among 579 elk sourced from P. tenuis-£ree areas where the prevalence of Dictyocaulus can be expected to be at least 12% (Kingscote et al. 1987; Pybus 1990). Based on the above specificity estimate and a test sensitivity of 100% (n — 12; manuscript under preparation), it

84 is reasonable to conclude that the ELISA test using larval ES products, provides a specific and sensitive detection of P. tenuis-exiposed elk.

The brain of the elk was tested for rabies by the fluorescent antibody test but was negative. Chronic wasting disease (CWD) is a cause of neurological signs in elk. As in P. tenuis infections, elk affected with CWD show abnormal head posture and loss of fear of humans. Excessive salivation is not a common finding in P. tenuis-inkcted elk, and was not observed in this bull elk; however, it is commonly seen in animals terminally sick with CWD

(Rourke et al. 1999; Williams and Young 1992; Thorne et al. 2002). Importantly, none of the pathognomonic signs of CWD, namely spongiform degeneration of grey matter neuropil, intraneuronal vacuolation, and astrocytic hypertrophy and hyperplasia (Williams and Young

1992; Spraker et al. 2002) was observed in the brain of this animal. Meningitis and encephalitis, which are notably absent in CWD infections (Williams and Young 1992) were both observed in this elk. Trace mineral deficiency, particularly of copper, resulting in ataxia has been reported in red deer which is conspecific with elk [Cervus elaphus subsp). However, the effects of copper deficiency are remarkably different from that of P. tenuis infection as follows: there are accompanying skeletal deformities (Gogan et al. 1988; Audige et al. 1995), usually many animals in the same social group are affected and thus, the use of the term enzootic ataxia to describe the neurological syndrome caused by copper deficiency (Audige et al. 1995); the main CNS pathology is neural demyelination (Terlecki et al. 1964). In a recent report, intensive behavioural observations over a period of 14 years of 100 radio- collared elk belonging to different age and gender classes failed to reveal any neurological signs other than those due to P. tenuis infection in Michigan (Bender et al. 2005).

85 CASE 2

During the first two weeks of September 2005, a yearling (1 Vz yrs) cow elk, located near the area utilized by the above bull elk, was observed by residents as having mobility problems (slow, stumbling, unstable movements), had no fear of humans, and remained in an approximate 10m x 40m area. On September 14, 2005, the cow elk was observed and photographed in the same area. However, on September 15, 2005, she was found dead, the apparent victim of predation by wild canids (Cams sp). The suspected cause of death was confirmed during post-mortem at the CCWHC, Guelph. Histology revealed an adult nematode, compatible with P. tenuis, in a cerebral sulcus, and larvating nematode eggs

(compatible with P. tenuis) in the meninges (in tissue as well as blood vessels) (Figure 4.2).

The larvae had evoked an inflammatory response. Blood serum samples collected post­ mortem revealed a positive P. tenuis ELISA S/P ratio of 1.04 and 0.72 (104 and 72 ELISA units).

DISCUSSION

Parelaphostrongylus tenuis, also known as meningeal worm or brain worm, is one of the most pathogenic nematodes of cervids such as elk, moose [Alces alces), and caribou (Rangifer tarandus caribou). It can cause severe neurological disease and death in species such as elk and has probably limited the success of previous elk restorations in eastern North America

(Lankester 2001; Pybus et al. 1989; Raskevitz et al. 1991). However, this parasite rarely causes serious disease in white-tailed deer, the definitive host in Ontario, as deer and P. tenuis have co-evolved (Lankester 2001). As well, some re-introduced elk herds have persisted on the same range as P. tenuis infected white-tailed deer (Samuel et al. 1992).

86 It was postulated during 2003/04, that elk restored to the Bancroft, Ontario, area may have been acquiring P. tenuis infections from deer in the Hartsmere area as brain lesions possibly due to parasite migration were found in elk during post-mortems at the Canadian

Cooperative Wildlife Health Centre (CCWHC), Guelph, Ontario. This is reminiscent of other jurisdictions where P. tenuis is enzootic and elk have been re-introduced. Carpenter et al. (1973) detected lesions and P. tenuis larvae, in the meninges of elk sampled in Oklahoma.

Woolf et al. (1977), found lesions present in the brain of 37 animals infected with P. tenuis in

Pennsylvania, although only 11 clinical cases were observed among all 87 elk examined

(Olsen and Woolf 1979). As well, Carpenter et al. (1973), detected lesions and P. tenuis larvae, in the meninges of elk sampled in Oklahoma. Since the re-introduction of elk into Ontario, larval or adult meningeal worms have not been found in necropsied elk until now, and despite the strong suspicion of elk acquiring and dying of P. tenuis, a confirmatory diagnosis could not be made until the P. tenuis ELISA became available (Ogunremi et al. 2002a).

It seems reasonable to conclude that the source of P. tenuis infection for the elk was via ingestion of infected gastropods that acquired their infections via consumption of, or penetration by, P. tenuis larvae shed in the feces of white-tailed deer. The bull elk is known to have wintered during 2003/04 in the yarding areas east of Bancroft (Bellhouse and Rosatte

2005), where a high density of WTD is found, and most of their fecal samples, 82%, have dorsal-spined larvae, presumably of P. tenuis (Mcintosh 2003). Furthermore, the infected bull elk likely spent the summer/fall of 2004 in the same general area as the other members of its social group as determined by radio-telemetry (Mcintosh, unpublished). In a previous study in Minnesota, P. tenuis larvae found in gastropods had reached the infective 3rd stage by July -

October (Lankester and Petersen 1996), but only a small proportion of the gastropods were expected to be infected. For instance, 1 % of gastropods were found to be infected with P.

87 tenuis m Algonquin Park, Ontario, north of the Hartsmere area (Lankester 1967). Thus, the elk probably acquired the infection in the vicinity of the deer yarding areas during the summer/fall of 2004.

The severity and outcome of the P. tenuis infection in cervids such as elk is correlated with the infective dose of larvae. Significant doses of > 125 3r stage larvae can result in neurological symptoms and death. Elk receiving moderate numbers (25-75) of larvae developed neurological signs, some died and some shed larvae. However, elk that were exposed to small numbers of larvae (15) did not develop clinical signs or shed larvae (Samuel et al. 1992). Thus, the ingestion of low doses of larvae may in part explain the survival of some eastern elk populations. The impact of P. tenuis on the Bancroft elk population will most likely be related to the prevalence of P. tenuis in deer populations, range overlap between deer and elk, the abundance and type of gastropods found on deer and elk range, the number of P. tenuis- infected gastropods that elk ingest, the age of elk at infection, the amount of damage caused by worms within the central nervous system, and the ability of elk to survive low level infections of P. tenuis.

Other studies have noted clinical signs in elk due to P. tenuis infection similar to this study, however, those diagnoses were made post-mortem. Meningeal worms were found post-mortem in the brains of elk in Oklahoma that exhibited signs prior to death such as ataxia and circling (Carpenter et al. 1973). In Pennsylvania, Woolf et al. (1977) observed clinical signs in captive elk including ataxia, circling, tameness, and head/neck tilt, confirmed post-mortem to be infected with P. tenuis. Neurological signs in Michigan elk were also attributed to P. tenuis infection (Lankester 2001). It should also be noted that Woolf et al.

(1977) found that although there was a high prevalence of P. tenuis infected elk on a preserve

88 in Pennsylvania, many did not exhibit any clinical signs. Thus clinical signs only, may not be a reliable estimate of the true prevalence of P. tenuis in a wild elk population.

Olsen and Woolf (1979) and Woolf et al. (1977) found a higher prevalence of P. tenuis infections in yearling and 2.5 yr old elk (60%) than in calves and elk older than 3.5 yrs

(25%) in a preserve in Pennsylvania. More recendy, Larkin et al. (2003) showed that 73% of elk dying of P. tenuis in Kentucky were < 3 yr old. In this study, only 53% of wild elk sampled in the Bancroft, Ontario, suspected of being infected with P. tenuis were <2.5 years of age (of those, 35% were yearlings). As noted by Woolf et al. (1977), a high prevalence of

P. tenuis in younger-aged elk could affect the productivity of the herd and limit population growth over the long term. The true impact of P. tenuis remains to be seen in Ontario, as elk were only recently (2000/2001) introduced to the Bancroft area. However, in Michigan, P. tenuis only accounted for 3% of elk mortalities, much lower than mortality due to harvesting

(58%), illegal kills (22%), other diseases (7%) and malnutrition (4%) (Bender et al. 2005).

In the past, the only technique available for the detection of P. tenuis in live hosts was the Baermann funnel technique, which relies on the recovery of 1st stage larvae in the feces of infected animals. The more efficacious modified technique described by

Forrester and Lankester (1997) may lead to the recovery of onlyl3% of P. tenuis larvae present in feces. The probability of recovery of larvae from infected elk using these techniques is low as elk only intermittently shed low numbers of 1st stage larvae in feces

(Lankester 2001; Welch et al. 1991; Ogunremi et al. 2002a). This may be related to the fact that field infected elk may only harbour a few (1-3) adult worms (Carpenter et al.

1973). As well, unisexual infections may be present in infected animals making larval shedding impossible (Slomke et al. 1995). Furthermore, worms may die or the elk may die before infections become patent (Lankester 2001). Thus, the newly developed P.

89 tenuis ELISA is useful for detecting meningeal worm infections in animals such as elk that usually harbour few of the parasites. The ELISA is expected to be a useful wildlife management tool in Ontario for monitoring the prevalence of P. tenuis in elk as well as other ungulates such as moose (Ogunremi et al. 2002b).

To my knowledge, this is the first documentation of an ante-mortem P. tenuis infection in an individual free ranging elk in the wild. The potential impact of P. tenuis on restored eastern elk populations needs to be taken seriously by wildlife mangers as failures of previous introduction attempts have been attributed to P. tenuis infections (Severinghaus and

Darrow 1976). Other observations that P. tenuis was responsible for reduced growth and mortalities in elk populations in Pennsylvania and Kentucky, respectively (Eveland et al.

1979; Larkin et al. 2003) are important and relevant. Given the observations reported in this study, it would not be prudent to transport elk from eastern North America to the west, where P. tenuis is currendy absent {see Lankester (2001) for a map of the current range of P. tenuis).

LITERATURE CITED

Anderson, R. C, Lankester, M.W., and U. R. Strelive. 1966. Further experimental studies of Pneumostrongylus tenuis in cervids. Canadian Journal of Zoology 41: 851 - 861.

Audige, L., Wilson, P.R., Morris, R.S., and G. W. Davidson. 1995. Osteochondrosis, skeletal abnormalities and enzootic ataxia associated with copper deficiency in a farmed red deer (Cervus elaphus) herd. New Zealand Veterinary Journal 43: 70 — 76.

Bellhouse, T., and R. Rosatte. 2005. Assessment of the potential for negative interaction between re-introduced elk {Cervus elaphus) and resident white-tailed deer (Odocoileus virginianus) in their wintering areas in Ontario, Canada. Mammalia 69 (1): 35-56.

Bender, L., Schmitt, S., Carlson, E., Haufler, J., and D. Beyer Jr. 2005. Mortality of rocky mountain elk in Michigan due to meningeal worm. Journal of Wildlife Diseases 41: 134-140.

90 Bienek, D.R., Neumann, N.F., Samuel, W.M., and M. Belosivic. 1998. Meningeal worm evokes a heterogenous immune response in elk. Journal of Wildlife Diseases 34:334-341.

Carpenter, J. W., Jordan, H.E., and B. C. Ward. 1973. Neurologic disease in wapiti naturally infected with meningeal worms. Journal of Wildlife Diseases 9: 148-153.

Eveland, J., George, J., Hunter, N., Forney, D., and R. Harrison. 1979. A preliminary evaluation of the ecology of the elk in Pennsylvania. In North American Elk: ecology behaviour and management. M. Boyce and L. Hay den (eds). University of Wyoming, Laramie, pp. 145-151.

Forrester, S., and M. Lankester. 1997. Extracting protostrongylid nematode larvae from ungulate feces. Journal of Wildlife Diseases 33: 511-516.

Gogan, P. J P., Jessup, D.A., and R. H. Barrett. 1988. Antler anomalies in tule elk. Journal of Wildlife Diseases 24: 656-662.

Kingscote, B. F., Yates, W.D., and G. B. Tiffin. 1987. Diseases of wapiti utilizing cattle range in south-western Alberta. Journal of Wildlife Diseases 23:86-91.

Lankester, M. 1967. Gastropods as intermediate hosts of Pneumostrongylus tenuis Dougherty, of white-tailed deer. Thesis. University of Guelph, Guelph, Ontario.

Lankester, M. 2001. Extra pulmonary lungworms of cervids. In Parasitic diseases of wild mammals, W. M. Samuel, M. J. Pybus and A. A. Kocan (eds.).Iowa State University Press, Ames, Iowa, pp. 228-278.

Lankester, M., and W. Peterson. 1996. The possible importance of wintering yards in the transmission oiParelaphostrongj/lus tenuis to white-tailed deer and moose. Journal of Wildlife Diseases 32: 31-38.

Larkin, J. L., Alexy, K.A., Bolin, D.C., Maeher, D.S., Cox, J.J., Wichroski, M.W., and N. W. Seward. 2003. Meningeal worm in a reintroduced elk population in Kentucky. Journal of Wildlife Diseases 39: 588-592.

Mcintosh, T. 2003. Movements, survival and habitat use by elk (Cervus elaphus) reintroduced to northwestern Ontario. Thesis, Lakehead University, Thunder Bay, Ontario, Canada.

Ogunremi, O., Lankester, M., Loran, S., and A Gajadhar. 1999. Evaluation of excretory-secretory products and somatic worm antigens for the serodiagnosis of experimental Parelaphostrongylus tenuis infection in white-tailed deer. Journal of Veterinary Diagnostic Investigation 11: 515-521.

91 Ogunremi, O., Lankester, M.W., and A. Gajadhar. 2002a. Immunuodiagnosis of experimental Parelaphostrongylus tenuis infection in elk. The Canadian Journal of Veterinary Research 66: 1-7.

Ogunremi, O. A, Lankester, M.W., Dergousoff, S.J., and A. Gajadhar. 2002b. Detection of anti-Pare/apbostron^y/us tenuis antibodies in experimentally infected and free-ranging moose {Alces alces). Journal of Wildlife Diseases 38: 796-803.

Olsen, A., and A. Woolf. 1979. A summary of the prevalence of Parelaphostrongylus tenuis in a captive wapiti population. Journal of Wildlife Diseases 15: 33-35.

O'Rourke, K. I., Besser, T.E., Miller, M.W., Cline, T.F., Spraker, T.R.Jenny, A.L., Wild, M.A., and G. L. Zebarth.1999. PrP genotypes of captive and free-ranging rocky mountain elk (Cervus elaphus nelsoni) with chronic wasting disease. Journal of General Virology 80: 2765-2769.

Pybus, M. J. 1990. Survey of hepatic and pulmonary helminths of wild cervids in Alberta, Canada. Journal of Wildlife Diseases 26: 453-459

Pybus, M., Samuel, W., and V. Crichton. 1989. Identification of dorsal spined larvae from free-ranging wapiti [Cervus elaphus} in south-western Manitoba. Journal of Wildlife Diseases 25: 291-293.

Raskevitz, R., Kocan, A., and J. Shaw. 1991. Gastropod availability and habitat utilization by wapiti and white-tailed deer sympatric on range enzootic for meningeal worm. Journal of Wildlife Diseases 27: 92-101.

Rosatte, R., Hamr, J., Ranta, B., Young, J., and N. Cool. 2002. Elk restoration in Ontario, Canada: Infectious disease management strategy, 1998-2001. Annals of the New York Academy of Sciences 969: 358-363.

Samuel, W., Pybus, M., Welch, D., and C. Wilke. 1992. Elk as a potential for meningeal worm: implications for translocation. Journal of Wildlife Management 56: 629-639.

Severinghaus, C, and R. Darrow. 1976. Failure of elk to survive in the Adirondacks. New York Fish and Game Journal 23: 98-99.

Slomke, A., Lankester, M., and W. Peterson. 1995. Infrapopulation dynamics of Parelaphostrongylus tenuis in white-tailed deer. Journal of Wildlife Diseases 31: 125- 135.

Spraker, T. R., Zink, R.R., Cummings, B.A., Sigurdson, C.J., Miller, M.W., and K. I. O'Rourke. 2002. Distribution of protease-resistant prion protein and spongiform encephalopathy in free ranging mule deer (Odocoileus hemionus) with chronic wasting disease. Veterinary Pathology 39: 546-556.

Terlecki, S., Done, J.T., and F. G. Clegg. 1964. Enzootic ataxia of red deer. British Veterinary Journal 120: 311-321.

92 Thome, T., Williams, E., Samuel, W., and T. Kistner. 2002. Diseases and Parasites. In North American elk, ecology and management. Pp 351-387. D. Toweill and J. W. Thomas editors. Smithsonian Institution Press, Washington.

Welch, D. A., Pybus, M.J., Samuel, W.M., and C. J. Wilke. 1991. Reliability of fecal examination for detecting infections of meningeal worm in elk. Wildlife Society Bulletin 19: 326-331.

Williams, E. S. and S. Younge. 1992. Spongiform encephalopathies in cervidae. Revue scientifique et technique 11:551-567.

Woolf, A., Mason, C, and D. Kradel. 1977. Prevalence and effects of Parelaphostrongylus tenuis in a captive wapiti population. Journal of Wildlife Diseases 13: 149-154.

93 Figure 4.1. Varelaphostrongylus tenuis larvating eggs in the brain meninges of the bull elk (Case 1) (a) degenerate larvae, (b) normal looking larva, (c) larva surrounded by eosinophils. Arrows indicate larvae (a, b) or eosinophils (c) Bar = 20 mm.

ff< r*l&

•m* % * jf % »f» w * % I.

r St .!> *V * fc

•;*'.'€>,

'jw

94 Figure 4.2. Photos of cross sections of brain from the cow elk (Case 2) showing (a) a submature or adult nematode (compatible with P. tenuis) in a cerebral sulcus bar =100 mm; (b) (c) larvating nematode eggs (compatible with P. tenuis) in the meninges (photos by D. Campbell); (b) bar = 50 mm, (c) bar =100 mm.

95 CHAPTER 5

GENETIC VARIABILITY IN AN ELK (CERVUS ELAPHUS) POPULATION RECENTLY

REINTRODUCED TO ONTARIO, CANADA

ABSTRACT

Reintroduction is an increasingly common tool for restoring wildlife populations; however, there are potential genetic consequences. Understanding the genetic structure of these populations and maintaining adequate genetic diversity is important for long-term restoration success. In this study, insights are presented into the genetic diversity at the time of release, for four relatively small elk populations reintroduced to isolated and distinct locations in Ontario, Canada. The results of the study show that across all four populations of elk, no significant deviations from Hardy-Weinberg expectations were detected. The overall number of alleles detected per locus ranged from 1 to 12, with the average number of alleles per locus observed within the four elk populations ranging from 2.83 (1.034) in the

LHNS region to 3.83 (1.03) in the BNH region. Unique alleles were detected in each of the 4

Ontario elk populations. Further, there were no marked differences in genetic variation between the source population, EINP, and the four Ontario elk populations, indicating no bottlenecks. Starting from a population of 120 individuals and expanding rapidly to an estimate of 426-647 (95% CI) individuals in 2008, elk released in the BNH region are likely to maintain or improve their genetic diversity over the long-term. Elk released in the NFR and LOW regions have experienced population decline since release (NFR = from 172 elk to an estimated 128-149 95% CI individuals in 2008; LOW = from 104 elk to an estimated

25-35 95% CI individuals in 2008) and may face genetic consequences such as reduced diversity and lower fitness due to extended bottlenecks. Similarly, elk released in the LHNS

96 region may also experience founder effects and reduced allelic richness as only 47 individuals were released into this isolated region of the province, the number of alleles per locus was the lowest among the four populations, and population growth to date has been moderate

(estimated 80-100 individuals in 2009). Genetic restoration by augmenting these populations with further elk translocations could help to avoid the consequences of reduced genetic diversity. Continued monitoring of the genetic diversity in each of the elk release sites, in particular those elk that were born in Ontario, is recommended to further elucidate the impact of restoration strategies and post-restoration management on the retention of genetic variability in the Ontario elk populations.

INTRODUCTION

Reintroductions frequently have been used to reestablish extirpated wildlife populations to areas of suitable habitat within their historic range. In general, the successful establishment of a reintroduced population depends on many factors including the total number of animals released, the habitat quality of the release site, the location of the release site in relation to the historical range of the species, and the biological characteristics of the species (Griffith et al. 1989, Wolf et al. 1996, Wolf et al. 1998). While the initial establishment of a demographically viable population is essential for restoration success, the long-term viability of the population may depend on the maintenance of sufficient levels of genetic variability (Frankham and Ralls 1998).

The reintroduction of large, free-ranging species such as elk provides an opportunity to consider the influence of reintroduction methodologies and management actions on genetic variability. Reintroduced elk populations face many of the constraints typical in other wildlife reintroduction efforts, including small initial population sizes (e.g., Lenny-

97 Williams et al. 2002, Mock et al. 2004, Stephen et al. 2005), small number of founders

(Griffith et al. 1989, Wolf et al. 1998), and relative isolation from other wild populations

(e.g., Maudet et al. 2002). Each raises concerns about the degree to which bottlenecks and effective population size can reduce genetic variability within the population, and the overall impact on the long-term viability of the population (Fitzsimmons et al. 1997, Masden et al.

2000, Lenny-Williams et al. 2002, Mock et al. 2004).

Genetic variation is known to be greatly affected by founder effect (Nei et al. 1975,

Wright 1978) and populations originating from a small number of animals are thought to contain less genetic variation than those initiated from a larger number (Lenny-Williams et al. 2002). When a few individuals establish a new population, the genetic constitution of the new population depends on the genetics of the founders. If founders are not representative of the source population, or if only a few founders are involved, the new population may be a biased representation of the larger gene pool from which it came and may have lower overall genetic diversity (Haliburton 2004). This may be particularly important in wildlife reintroductions, where a small number of individuals are often used to establish the new population. Bottlenecks have been reported in several reintroduced elk populations originating from a small number of founders (Lenny Williams et al. 2002, 2004).

Over the longer-term, a lack of genetic variation has also been linked to inbreeding effects in several populations (Zachos et al. 2007), resulting in slower growth, reduced fecundity and survival over time, and loss of evolutionary potential (Ralls et al. 1979; Ballou and Ralls 1982; Ralls et al. 1988; Slate et al. 2000; Reed and Frankham 2003). In addition, a harem-breeding system and matriarchal social structure could make reintroduced elk populations particularly susceptible to losing genetic variability over the longer term through direct reductions in the effective size of a population (Clutton-Brock et al. 1988).

98 Once native to Ontario, elk (Cervus elaphus) were extirpated in the late 1800s due to increasing demands for meat and agricultural land (Ranta 1979,-Witmer 1990, Ceballos and

Ehrlich 2002). There have been several previous attempts to reintroduce elk to the province. Most notably elk were reintroduced to several locations in central Ontario during the 1930s. However, due to concerns regarding the transmission of the giant liver fluke

(Fasrioloides magna) to livestock, most of these animals were destroyed (Kingscote 1950, 1951,

Addison 1997). Two small remnant populations have managed to survive in the Nipissing-

French River area of Ontario, and in 1996 they were estimated to number approximately 60 animals (Bellhouse and Broadfoot 1998).

In 1997, the Government of Ontario announced a provincial elk restoration initiative, and from 1998 to 2001 a total of 443 elk (Cervus elaphus) (Rosatte et al. 2007) were translocated from Elk Island National Park (EINP), Alberta and released into four primary release areas in Ontario, including 172 elk in Nipissing-French River (NFR), 120 elk in

Bancroft/North Hastings (BNH), 47 elk in Lake Huron-North Shore (LHNS), and 104 elk

Lake of the Woods (LOW) (Rosatte et al. 2007). Although plans for the restoration of elk in

Ontario called for the release of at least 200 female elk at each site, concerns regarding the transmission of Chronic Wasting Disease have halted the import of the elk into the province

(Rosatte et al. 2007), thereby creating four relatively small and isolated elk populations.

Here I present insights into the genetic diversity of four relatively small elk populations recently reintroduced to isolated and distinct locations in Ontario, Canada. The specific objectives were to i) provide baseline data by determining the level of genetic diversity in each of the four elk populations in Ontario, ii) examine differences in genetic diversity, if any, between the four Ontario elk populations and the source population at

EINP, and ii) using theoretical considerations and previous studies, to speculate on the

99 possible impact of the level of diversity and the probability of long-term population persistence at each of the four elk release sites.

STUDY AREA

The four elk reintroduction sites extend through Ontario, from Lake of the Woods

(LOW; 49° 15' N, 93° 43' W) in the north-west, Lake Huron-North Shore (LHNS; 46° 26'

N, 83° 6' W) and Nipissing-French River (NFR; 46 ° 12' N, 80° 50' W) in the central part of the province, and Bancroft-North Hastings (BNH; 45° 02' N, 83° 29' W) in south-eastern

Ontario. Each elk population is geographically isolated from each other, and with the exception of elk in the NFR region who were reintroduced among a remnant population of elk present in the area since the 1930s, they are isolated from all other wild populations.

Pair-wise distances range from 250km to 1200 km. The major forest region represented in three of the four elk release sites (BNH, NFR, LHNS) is the Great Lakes-St. Lawrence

forest, a transition zone between northern boreal forest and southern temperate forest

(Rowe 1972). These forests generally contain sugar maple (Acer saccharum), yellow birch

(Betula luted), and beech (Fagus grandifolid), as well as mixed softwoods of white (Pinus strobus) and red pine (P. resinosd), trembling aspen (Populus tremuloides), balsam fir (Abies balsamiferd), white birch (Betulapapyriferd), and eastern hemlock (Tsuga canadensis; Rowe 1972, Chambers et al. 1997, Thompson 2000). The Boreal Forest Region encompassed the LOW elk release site at the northern periphery of the historic elk range, and was dominated by coniferous trees including black spruce (Picea mariand), white spruce (Piceaglaucd), and balsam fir (Abies

balsamed) (Rowe 1972). Climate variability among areas includes a latitudinal temperature gradient, as well as a precipitation gradient from northwest to southeast (Anonymous 2003).

Mean maximum snow depth in all elk release areas averages between 50 and 65 cm annually

(Anonymous 2003); however, spring green-up generally occurs one month earlier (mid to

100 late April) in the more southern elk release site (i.e., BNH) (Hutchinson et al. 1997).

Potential competitors to elk in the areas include white-tailed deer (Odocoikus virginianus) and moose (Alces alces), whereas predators include wolves (Canis lupus, Canis lycaon), coyotes (Canis latrans) and black bears (Ursus americanus). Deer density is higher in the south (Hutchinson et al. 1997) while the densities of wolves and black bears is higher in the NFR and LOW areas

(Bellhouse and Rosatte 2005; Rosatte et al. 2007). Finally, human densities vary among the release areas with relatively low densities in the LOW, NFR, and LHNS release sites (1 person/1.6 km2), compared to much higher densities (15-19 per 1.6 km2) in the BNH region

(Hutchinson et al. 1997).

METHODS

Sample Collection and DNA Isolation

Elk Island National Park, Alberta was the source of elk for Ontario's most recent reintroduction from 1998 to 2001. Blood samples from all elk (n=443) transported and subsequendy released in Ontario were collected during trapping and handling in Elk Island

National Park (December 1998, 1999, 2000, and 2001). Blood samples were drawn from captured elk using procedures approved by the Ontario Ministry of Natural Resources

Animal Care Committee. Blood samples were collected into serum separator tubes (SST), designed to separate serum from the blood clot by centrifugation using an inert thixotropic gel with a specific gravity of 1.04 (Young and Bermes 1994). Following centrifugation, blood samples were stored at -20°C.

For DNA extractions from blood, samples were thawed and as much of the thixotropic gel as possible was removed from the SST tube (Siafakas et al. 1995). Equal volumes of blood and 2x lysis buffer (Applied Biosystems: 4 M urea, 0.2 M sodium chloride,

101 0.5% n-lauroyl sarcosine, 10 mM CDTA [1,2-cyclohexanediaminetetraacetic acid], 100 mM

Tris-HCl pH 8.0), as well as 40ul of Proteinase-K (20.0 mg/mL, >600.0 U/mLlOO |TL)

(Qiagen), were incubated in a water bath at 65°C for one hour. After one hour, a second

40ul of Proteinase-K was added to each sample. Samples were then incubated at 37°C overnight. Following incubation, a Qiagen QIAamp isolation kit for blood extraction protocol was used (Sambrook et al. 1989).

Muscle tissue and hair samples were collected opportunistically from elk that died following release in Ontario. A total of 40 samples (NFR=20; BNH=16; LOW 4) were obtained for this study. Samples were collected in the field as soon as possible following death and stored at -20 C until DNA extraction. Following the addition of lx lysis buffer and Proteinase-K digestion for at least 24 hours, DNA was extracted from small pieces of elk muscle tissue with the Qiagen QIAamp tissue isolation kit, according to manufacturer's instructions.

The quality and size assessment of DNA extracted from all samples was examined prior to amplification using agarose gel electrophoresis. The quantity of DNA extracted from all samples was also assessed using a fluorometer and confirmed by conducting a nuclear plateau of DNA following polymerase chain reaction (PCR) amplification.

Microsatellite loci were selected for inclusion in this study based on potential variability, amplification efficacy, and application in previous studies of elk populations.

Polymerase chain reaction was used to amplify extracted DNA at the following 12 dinucleotide (CA/GT) microsatellite loci: BM1009, BM4108, BM4208, BM1225, BM4513,

IGF, AF102257, BL42, BM848, AF102246, BM415, BM5004 (Bishop et al. 1994;

Kirkpatrick et al. 1992; Iannuzzi et al. 2001; Merredith et al. 2004). Negative controls were run with each set of reactions to detect polymerase chain reaction contamination and lane-

102 to-lane leakage during allele scoring. Polymerase chain reaction products were electrophoresed using 6% acrylamide gels and an ABI 377 DNA automated sequencer

(Applied Biosystems). GENESCAN software was used to extract and track gel lanes, and

GENOTYPER 2.5 software (Applied Biosystems, Foster City) was used to size alleles.

Data used to examine differences in genetic diversity between the four Ontario elk populations and those of the source population, EINP, were obtained from Polziehn et al.

2000.

Statistical Analysis

All 4 populations of elk reintroduced to Ontario were tested for departures from Hardy-

Weinburg equilibrium at each locus and for linkage disequilibrium between pairs of loci using Fisher's Exact Test in GENEPOP 3.4 (Raymond and Rousset 1995a). Average

numbers of alleles per locus, unique alleles, expected heterozygosities (Hr, unbiased for

sample size) and observed heterozygosities (H()) at each locus and across all loci were also calculated for each population in Ontario using Cervus version 2.0 (Marshall et al. 1998).

Statistical comparisons of mean HL (arc-sine transformed) and mean Allelic richness between the four elk populations were made using 2-tailed, paired t-tests. Given that each elk population in Ontario represents a sub-sample of the much larger elk population in

EINP, Alberta, differences in per locus allele frequency distributions between the four elk populations and the source population, EINP, Alberta, were investigated with Fisher's exact test calculated using GENEPOP 3.4 (Raymond and Rousset 1995a, 1995b).

RESULTS

Complete genotypes at 12 loci were determined from 233 individual elk. Measures of genetic diversity were calculated from observed allele distribution and patterns of genetic

103 diversity did not differ among the four elk populations reintroduced to Ontario. Across all populations no significant deviations from Hardy-Weinberg expectations were detected

(Table 1 and 2). The overall number of alleles detected per locus ranged from 3 (BL 42) to 8

(BM 1009 and AF102257). The average number of alleles per locus observed within the four elk populations ranged from 2.83 in the LHNS region and 3.83 in the BNH region.

Unique alleles were detected in each of the four elk populations. The average expected heterozygosity for a locus ranged from 17% to 66%, and average expected heterozygosities within each population ranged from 46% to 53% (Table 1 and 2). There were no marked differences in genetic variation between the source population, EINP, and the four Ontario elk populations.

DISCUSSION

Wildlife restoration practitioners have long recognized that the starting pool of genetic variation is a critical element in the persistence, resilience, and stability of a population (Young and Clarke 2000). Although the source population may have relatively high levels of genetic diversity, those animals selected for translocation may not be representative. This may be of particular concern for animals such as elk, which are generally gregarious and often reside in close familial groups. The results of this study show that litde genetic diversity seems to have been lost during the translocation of elk from EINP to four release sites in Ontario indicating no bottlenecks. Indeed, there was no marked difference in genetic variation between the source population (EINP) and each of four reintroduced populations. This is also suggested by the overlapping distribution of genotypes from the larger elk population in EINP, which in turn hints at a generally low level of diversity for the species as a whole. A low level of genetic diversity is consistent with the observation of few

104 alleles in many microsatellite loci surveyed in North American elk (Talbot et al. 1996, Wilson et al, 1997, Roed and Midthjell 1999, Polziehn et al. 2000, Lenny-Wiffiams et al. 2002).

However, microsatellite variability in Ontario elk does appear to be greater than what has been observed for other species such as bison (Wilson and Strobeck 1999), moose (Broders et al. 2000), and caribou (Zitdau et al. 2000).

The strength of the relationship between genetic variation and population size is likely to vary between species; however, several life history traits of elk make them a likely candidate for genetic problems (e.g., sexual maturity at 2 to 4 years, matriarchal social structure, polygamous mating tactics, and fecundity of one calf per year) (Witmer 1990,

Raedeke et al. 2002, Lenny-Williams et al. 2002). In particular, loss of allelic diversity due to genetic drift, in association with founder effects or prolonged botdenecks, is of concern for reintroduced elk (Lenny-Williams et al. 2002). Moreover, the potential for inbreeding may be increased for reintroduced populations due to the small number of founders and male- biased dispersal (Larkin 2001, Lenny-Williams et al. 2002). Additionally, elk populations in

Ontario are geographically isolated, with no observed immigration between the herds. The lack of gene flow between the four sub-populations could further affect the amount of variation existing in each sub-population, placing them at a higher risk of extinction.

In order to speculate on the long-term influence of genetic diversity on elk populations in Ontario, the number and growth of the population are central points to consider. The theoretical 50-500 rule suggests that at least 50 animals are necessary to avoid loss of vigour from inbreeding and at least 500 individuals are needed to avoid the negative effects of genetic drift (Simberloff 1988). These numbers, however, assume that all members of the population are breeding and that breeding between individuals is random.

These assumptions are not valid for elk, as they ignore many important demographic

105 characteristics (Reed et al. 1986, Raedeke et al. 2002). For example, elk are polygamous, young do not reach their prime breeding age for several years, only a portion of breeding aged males and females breed, generations of breeders show considerable overlap, breeding is not random between males and females, and fertility varies between individuals (Lewin

1982, Witmer 1990). The actual population size for elk would, therefore, need to be much larger than the 50-500 rule proposes. Schonewald-Cox (1986) has suggested that an elk population would require 90 breeders (15 male and 75 female) to prevent inbreeding, and

900 breeders (150 male and 750 female) to prevent genetic drift. This population size has yet to be reached for any elk population in Ontario and if predictions are realized, only the

BNH elk population shows the potential to achieve these numbers and avoid the negative effects of inbreeding and genetic drift (Mcintosh unpublished). Elk released in the NFR and

LOW regions have experienced population decline since release (NFR = from 172 elk to an estimated 128-149 individuals in 2008; LOW = from 104 elk to an estimated 25-30 individuals in 2008) and may face genetic consequences such as reduced diversity and lower fitness due to extended bottlenecks (Rosatte pers. comm.). Similarly, elk released in the

LHNS region may also experience founder effects and reduced allelic richness as only 47 individuals were released into this isolated region of the province, the number of alleles per locus was the lowest among the four populations, and population growth to date has been moderate (estimated 80-100 individuals in 2009) (Rosatte pers. comm.).

In addition to the number and growth of the population, long-term genetic health may be influenced by the relative isolation of the herds. Over time, random changes in allelic frequency due to genetic drift may cause the elk populations to differentiate and, in the absence of mutation and migration, smaller populations will loose alleles, in particular rare ones, or become fixed for alleles much sooner than large populations would (Hart and Clark

106 1997; Luikart et al. 1998a, b). Although empirical evidence is limited, a small number of founders and slow population growth in combination with geographical isolation are thought to have contributed to the reduced genetic diversity in elk populations reintroduced to the NFR region of Ontario (Polziehn et al. 2000). Similarly, elk populations founded by a small number of animals that experienced a prolonged bottleneck in both California and

Pennsylvania reported low levels of genetic variation, no unique or few rare alleles, and large genetic distances between the reintroduced herd and the source population (Lenny-Williams et al. 2002, Lenny-Williams et al. 2004).

In contrast, a population of elk reintroduced to Custer State Park, South Dakota, was founded by a relatively large number of animals (n=125) and increased rapidly to approximately 300 individuals in three years (Millsapugh and Brundige 1996). The lower intensity and short duration of the population bottleneck due to rapid herd recovery is reflected in higher levels and patterns of genetic variability in this herd. Elk reintroduced to the BNH region of Ontario have followed a similar pattern, with a relatively large founding population (n=120) and rapid population growth in following years (2008 population estimate 426-647 individuals) (Ontario Ministry of Natural Resources 2010). This population may, therefore, maintain genetic diversity similar to the source population of

EINP, Alberta.

Young animals and the proportion of males may also have long-term genetic and evolutionary consequences for elk reintroductions, especially in the case of a bottleneck.

The effective population size can be drastically reduced in populations with a low proportion of males, which may accelerate the loss of genetic variation due to genetic drift, particularly in currently small populations (Ryman et al. 1981, Lenny-Williams et al. 2002). Sexual selection may also decrease because of less variation in male age and therefore body size.

107 Body size is thought to be an important factor determining the reproductive success of male elk (Andersson 1994), indicating that variation in reproductive success may be lower with less structured size hierarchies. Similarly, a lower proportion of males in the population may decrease the variance in mating success in male elk, thereby creating less intense sexual selection for larger male body size (Saether et al. 2003). Furthermore, strong matriarchal lineages combined with a polygamous mating system can result in reduced heterozygosity and under a severe botdeneck, it is possible that females may mate with younger aged males giving rise.to first order inbreeding (Lenny-Williams et al. 2002). Genetic analysis of elk born in Ontario following release is recommended to further elucidate the impacts of demography on the genetic diversity of elk in Ontario.

Evidence is mounting that small, isolated populations suffering from inbreeding depression may be amenable to genetic restoration (Ingvarsson 2001; Tallmon et al. 2004;

Hedrick 2005). Increased fitness in natural populations of adders (Vipera berus, Madsen et al. 1996), and prairie chickens (Tympanuchus cupido, Westermeier et al. 1998) was reported after immigrants bred with local populations. In these cases only low levels of immigration were necessary to derive a benefit; indeed, genetic restoration of a wolf population (Canis lupus, Vila et al. 2003) occurred as a result of one immigrant. To lessen the risk of extinction associated with isolated, reintroduced populations, conservation practitioners may therefore choose to genetically augment populations with in situ translocations or ex situ captive bred animals to initiate genetic restoration. This type of genetic restoration may be an important consideration for elk populations in Ontario, specifically those in the NFR, LOW, and

LHNS regions that currendy have small populations and relatively slow rates of increase.

108 Management Implications

The widespread use of translocations for conserving small or endangered populations and the recognized importance of rnaintairung genetic variability from long-term population viability (Frankham and Ralls 1998; Saccheri et al. 1998) underscores the importance of understanding factors that influence the retention of genetic variability in translocated populations. Maintaining positive population growth rates, increasing population size, and rnaintaining population stability are all strategies that favour the retention of genetic variability in restored populations. It may be possible to maximise post­ release population growth and population size by releasing relatively large numbers of animals (>50) and encouraging rapid population growth in the years following release

(Lenny-Williams et al. 2002). Continued monitoring of genetic variability in the Ontario elk populations will help to further elucidate the impacts of the restoration attempt and the impact of restoration strategies and post-restoration management on the retention of genetic variability in Ontario elk populations.

LITERATURE CITED

Addison, E. M. 1997. Liver flukes and translocated elk in Ontario: review and interpretation of facts. Report to Ontario Ministry of Natural Resources, Fish and Wildlife Branch.

Andersson, M. 1994. Sexual selection. Princeton University Press.

Anonymous. 2003. Canadian climate normals 1981-2003. Environment Canada, Atmospheric Environment Service Report. Ottawa, Ontario, Canada.

Ballou, J. D., and K. Ralls. 1982. Inbreeding and juvenile mortality in small populations of ungulates: a detailed analysis. Biological Conservation 24:239-272.

Bellhouse, T. J., and J. D. Broadfoot. 1998. Plan for the restoration of elk in Ontario. Ontario Ministry of Natural Resources Report, Toronto, Ontario.

109 Bellhouse, T. and R. C. Rosatte. 2005. Assessment of the potential for negative interaction between re-introduced elk (Cervus elaphus) and resident white-tailed deer (Odocoileus virginianus) in their wintering areas in Ontario, Canada. Mammalia 69: 35-56.

Bishop, M. D., Kappes, S.M., and J. W. Keele. 1994. A genetic linkage map of cattle. Genetics 136:619-639.

Bou2at, J.L., Cheng, H.H., Lewin, H.A., Westmeier, R.L., Brawn, J.D., and K.N. Paige. 1998. Genetic evaluation of a demographic bottleneck in the Greater Prairie Chicken. Conservation Biology. 12:836-843.

Broders, H.G., Mahoney, S.P., Montevecchi, W.A., and W.S. Davidson. 2000. Population genetic structure and the effect of founder events on the genetic variability of moose, A.kes, alces, in Canada. Journal of Molecular Ecology 8:1309-1316.

Buchanan, E C, and A. M. Crawford. 1992. Ovine dinucleotide repeat polymorphism at the MAF209 locus. Animal Genetics 23: 183.

Ceballos, G. and Ehrlich, P.R. 2002. Mammal population losses and the extinction crisis. Science. 296: 904-907.

Chambers, B. A., Naylor, B.J., Nieppola, J., Merchant, B., and P. Uhlig. 1997. Field guide to forest ecosystems in central Ontario. South Central Region Science and Technology Report FG-01. Toronto, Ontario, Canada.

Clutton-Brock, T. H., Guinness, F.E., and S. D. Albon. 1982. Red deer: behaviour and ecology of two sexes. University of Chicago Press, Chicago.

Fitzsimmons, N.N., Buskirk, S.W., and M.H. Smith. 1997. Genetic changes in reintroduced Rocky Mountain bighorn sheep populations. Journal of Wildlife Management. 61:863-872.

Frair, J.L., Merrill, E.H., Allen, J.R., M.S. Boyce. 2007. Know thy enemy: experience effects translocation success in risky landscapes. Journal of Wildlife Management 74:123— 140.

Frankham, R. and K. Ralls. 1998. Conservation biology: inbreeding leads to extinction. Nature. 392:441-442.

Griffith, B., Scott, J.M., Carpenter, J.W., and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science. 245:477-480.

Haliburton, R. 2004. Introduction to population genetics. Pearson Education., Upper Saddle River, NJ, USA.

Hard, D.L., and A.G. Clark. 1997. Principles of Population Genetics. Sinauer Associates, Inc. Sunderland, MA.

110 Hedrick, P.W. 2005. "Genetic restoration": a more comprehensive perspective than "genetic rescue." Trends in Ecology and Evolution 20: 109.

Hutchinson, B.C, Ranta, W.B., Fraser, B.C., and J. Quirouette. 1997. Determining the most suitable areas for elk restoration in Ontario, Canada. Unpubl. 21pp. lannuzzi L, Di Meo G.P, Hayes H., Perucatti A., Incarnato D., et al. 2001. FISH-mapping of 31 type I loci (Texas markers) to river buffalo chromosomes. Chromosome Research 9: 339-342.

Ingvarsson, P.K. 2001. Restoration of genetic variation lost — the genetic rescue hypothesis. Trend in Ecology and Evoloutionl6:62-63.

Kingscote, A.A. 1950. Liver rot (fascioloidiasis) in ruminants. Canadian Journal of Comparative Medicine and Veterinary Science 14:203-208.

Kingscote, A.A. 1951. Liver fluke control in the Burwash area. Ontario Veterinary College Report for 1950.

Kirkpatrick, B. W. 1992. Detection of a three allele single-strand-conformational- polymorphism (SSCP) in the fourth intron of the bovine growth hormone gene. Animal Genetics 23:179-181.

Larkin, J. L. 2001. Demographic and spatial characterization of a reintroduced elk population. Ph.D. University of Kentucky, Lexington.

Lenny Williams, C, Thomas, S., Serfaas, L., Cogan, R., and O.E. Rhodes. 2002. MicrosateUite variation in the reintroduced Pennsylvania elk herd. Molecular Ecology 11:1299-1310.

Lenny Williams, C, Lungrigan, B., and O.E. Rhodes. 2004. MicrosateUite DNA variation in Tule elk. Journal of WUdUfe Management 68:109-119.

Lewin, R. 1982. Red deer iUuminate sexual selection. Science 218:1206-1208.

Luikart, G., AUendorf, F.W., Cornuet, J.M., and W.B. Sherwin. 1998a. Distortion of aUele frequency distributions provides a test for recent population bottlenecks. Journal of Heredity 89:238-247.

Luikart, G., Sherwin, W.B., Steele, B.M., and F.W. AUendorf. 1998b. Usefulness of molecular markers for detecting population bottlenecks via monitoring genetic change. Molecular Ecology 7:963-974.

MarshaU, TC, Slate, J, Kruuk, LEB & Pemberton, JM (1998) Statistical confidence for likelihood-based paternity inference in natural populations. Molecular Ecology 7: 639-655.

Ill Masden, T., M. Olsson, H. Wittzell, B. Stille, A. Gullberg, R. Shine, S. Andersson, and H. Tegelstrom. 2000. Population size and genetic diversity in sand lizards (Lacerta agilis) and adders {Vipera berus). Biological Conservation 94:257-262.

Maudet, C, Miller, C, Bassano, B., Breitenmose-Wursten, C, Gauthier, D., Obexer-Ruff, G., Michaellet, J., Taberlet, P., and G. Luikart. 2002. Microsatellite DNA and recent statistical methods in wildlife conservation management: applications in Alpine ibex [Capra ibex (ibex)]. Molecular Ecology. 11:421-436.

Merredith, E.P., Rodzen, J.A., Levine, K.F. andJ.D. Banks. 2004.Characterization of an additional 14 microsatellite loci in California elk {Cervus elaphus) for use in forensic and population applications. Conservation Genetics 6:151-153.

Millspaugh, J., and G. Brundige. 1996. History and management of Custer State Park elk. South Dakota. Conservation Digest 63:5-9.

Mock, K.E., Rhodes, E.K., and E.O. Rhodes Jr. 2004. Assessing loss of genetic diversity due to translocation: long-term case histories in Merriam's turkey (Meleagris gallapavo merriami). Conservation Genetics 5:631-645.

Nei, M., Maruyama, M., and R. Chakraborty. 1975. The bottleneck effect and genetic variability in populations. Evolution. 29:1-10.

Ontario Ministry of Natural Resources. 2010. Backgrounder on Elk in Ontario. Queens Press, Toronto, Ontario.

Polziehn, R.O., Hamr, J., Mallory, F.F., and Strobeck, C. 1998. Phylogenetic status ofNorth American wapiti (Cervus elaphus) subspecies. Canadian Journal of Zoology 76: 998 1010.

Polziehn, R.O., Hamr, J., Mallory, F.F., and Strobeck, C. 2000. Microsatellite analysis of North American wapiti (Cervus elaphus) populations. Molecular Ecology. 9: 1561-1576.

Raedeke, K. J., Millspaugh, J.J., and P. E. Clark. 2002. Population characteristics. Pages 67- 120 in D. E. Toweill and J. W. Thomas, editors. North American elk: ecology and management. Smithsonian Institute Press, Washington.

Ralls, K., Ballou, J.D., and A. Templeton. 1988. Estimates of lethal equivalents and the cost of inbreeding in mammals. Conservation Biology 2:185-193.

Ralls, K., Brugger, K., and J. D. Ballou. 1979. Inbreeding and juvenile mortality in small populations of ungulates. Science 206:1101-1103.

Ranta, W. B. 1979. Range and habitat relationships of wapiti, Cervus canadensis, in the Nipissing-French River area of Ontario. M.Sc. Carlton University, Ottawa, Ontario.

112 Raymond M., and F., Rousset. 1995a. An exact test for population differentiation. Evolution 49:1280-1283.

Raymond M., and F. Rousset.. 1995b. Genepop (version 1.2), population genetics software for exact tests and ecumenicism. Journal of Heredity 86:248-249.

Reed, D.H. and R. Frankham. 2003. Correlation between fitness and genetic diversity. Conservation Biology 17:230-237.

Reed, J. M., Doerr, P.D., and W. J.R. 1986. Determining the minimum population sizes for birds and mammals. Wildlife Society Bulletin 14:255-261.

Roed, K.H. and L. Midthjell. 1999. Microsatellites in reindeer, Rangifer tarandus, and their use in other cervids. Molecular Ecology 7:1771-1788.

Rosatte, R., Hamr, J., Young, J., Filion, I., and H. Smith. 2007. The restoration of elk (Cervus elaphus) in Ontario, Canada 1998-2005. Restoration Ecology 15:34-43.

Rowe, J. S. 1972. Forest regions of Canada. Canadian Forest Service Publication Report. 1300. Ottawa, Ontario, Canada.

Ryman, N., Baccus, R., Reuterwal, C, and M. H. Smith. 1981. Effective population size, generation interval, and potential loss of genetic variability in game species under different hunting regimes. Oikos 36:257-266.

Sasther, B. E., Solberg, E.J., and M. Heim. 2003. Effects of altering sex ratio structure on the demography of an isolated moose population. Journal of Wildlife Management 67:455-466.

Sambrook J., Fritsch E.F. and Maniatis T. 1989. Molecular Cloning: A Laboratory Manual. CSH Laboratory Press. Cold Springs Harbor, NY.

Saccheri, M., Kuussaari, M., Kankare, M., Vikman, P., Fortelius, W., and I Hanski. 1998. Inbreeding and extinction in a butterfly metapopulation. Nature 392:491-494.

Schonewald-Cox, C. 1986. Founding populations in conservation: problems and characteristics of small populations. In Endangered and threatened species programs in Pennsylvania and other states: causes, issues, and management. Edited by S.K. Mujamdar, FJ. Brenner, and A.F. Rhoads. Pennsylvania Academy of Science, Easton, Pennsylvania, pp. 1-19.

Siafakas, N., Burnett, L., Bennetts, B., and Proos, A. 1995. Nonenzymatic extraction of DNA from blood collected into serum separator tubes. Clinical Chemistry 41: 1045- 1046.

Simberloff, D. 1988. The contribution of population and community biology to conservation science. Annual Review of Ecology, Evolution and Systematics 19:473- 511.

113 Slate, J., Kruuk, L.E.B., MarchaU, T.C., Pemberton, J.M., and T.H. Clutton-Brock. 2000. Inbreeding depression influences lifetime breeding success in a wild population of red deer (Cervus elaphus). Proceedings of the Royal Society of London: Part B, 267:1657-1662.

Stephen, C.L., Whittaker, D.G., Gillis, D., Cox, L.L., and O.E. Rhodes Jr. 2005. Genetic consequences of reintroductions: an example from Oregon pronghorn antelope (Antilocapra americand). Journal of Wildlife Management 69:1463-1474.

Talbot, J., Haigh, J., and Y. Tlante. 1996. A parentage evaluation test in North American elk (wapiti) using microsatellites of ovine and bovine origin. Animal Genetics 27:117- 119.

Tallmon D.A., Luikart G., R.S. Waples. 2004. The alluring simplicity and complex reality of genetic rescue. Trends in Ecology and Evolution 19:489-496.

Thompson, I. D. 2000. Forest vegetation of Ontario: factors influencing landscape change. Pages 336 in Perera A. H., Euler D. L., Thompson I. D., editors. Ecology of a managed terrestrial landscape: patterns and processes of forested landscapes in Ontario. University of British Columbia Press, Vancouver, Canada.

Westermeier, R.L., Brawn, J.D., Simpson, S.A., Esker, T.L., Jansen, R.W., Walk, J.W., Kershner, E.L., Bouzat, J.L., and K.N. Paige. 1998. Tracking the long-term decline and recovery of an isolated population. Science 5394:1695-1698.

Wilson, G.A., Stronbeck, C, Wu, L., and Coffin, J.W. 1997. Characterization of microsatellite loci in caribou, Rangfer tarandus, and their use in other artiodactyls. Molecular Ecology 6: 697-699.

Witrner, G. 1990. Reintroduction of elk in the United States. Journal of the Pennsylvania Academy of Science 64:131-135.

Wolf, CM., Griffiths, B., Reed, C, and S.A. Temple. 1996. Avian and mammalian translocations: update and reanalysis of 1987 survey data. Conservation Biology 10: 1142-1154.

Wolf, CM., Garland, T.G., and B. Griffiths. 1998. Predictors of avian and mammalian translocation success: reanalysis with phylogenetically independent contrasts. Biological Conservation 86:243-255.

Wright, S. 1978. Evolution and the genetics of populations. Vol. 4. Variability within and among natural populations. University of Chicago Press. Chicago.

Vila, C, Sundqvist, A.K., Flagstad, O., Seddon, J., Bjornerfeldt, S., Kojola, I., Casulli, A., Sand, H., Wabakken, P., H. Ellegren. 2003. Rescue of a severely botdenecked wolf (Cams lupus) population by a single immigrant. Proceedings of the Royal. Society of London B 270: 91-97.

114 Young, A.G., and G.M. Clarke eds. 2000. Genetics, demography, and viability of fragmented populations. Cambridge University Press, Cambridge, UK.

Young, D.S. and Bermes, E.W. Jr. 1994. Specimen collection and processing — sources of biological variation. In: Tietz textbook of clinical chemistry. Edited by C.A. Burtis and E.R. Ashwood. WB Saunders. Philadelphia, pp. 58-101.

Zachos, F.E., Althoff, C, Steynitz, Y.V., Eckert, I., and G.B. Hartl. 2007. Genetic analysis of an isolated red deer (Cervus elaphus) population showing signs of inbreeding depression. European Journal of Wildlife Management.53:61-67.

Zitdau (McFarlane), K., Coffin, J., Farnell, R., Kuzyk, G., and C. Strobeck. 2000. Genetic relationships of three Yukon caribou herds determined by DNA typing. Rangifer, Special Issue No. 12:59-62.

115 Table 5.1: Genetic diversity in the four Ontario elk populations at release, Nipis sing-French River (NFR), Bancroft-North Hastings (BNH), Lake Huron-North Shore (LHNS), and Lake of the Woods (LOW). Sample size (n), expected heterozygosity (HJ, observed heterozygosity (H0), and number of unique alleles (No of Alleles) are reported for each population.

Population n HE (SD) H0 (SD) No Alleles (SD) NFR 49 0.5273 (0.0243) 0.4382 (0.0206) 3.42 (1.00) BNH 95 0.4900 (0.0316) 0.4670 (0.0150) 3.83 (1.03) LNHS 33 0.4841 (0.0377) 0.4555 (0.0259) 2.83 (1.03) LOW 55 0.4677 (0.0364) 0.4081 (0.0194) 3.33 (0.98)

116 Table 5.2: Expected heterozygosities (HjJ for elk populations in the Nipis sing-French River (NFR), Bancroft-North Hastings (BNH), Lake Huron-North Shore (LHNS), and Lake of the Woods (LOW) regions in Ontario, Canada at 12 microsatellite loci.

Locus NFR BNH LNHS LOW BM1009 0.4778 0.5028 0.496 0.5166 BM4107 0.6156 0.6076 0.5874 0.6053 BM4208 0.534 0.2356 0.1678 0.2762 BM1225 0.6581 0.6441 0.6471 0.627 BM4513 0.3671 0.3552 0.3212 0.1873 IGF 0.5018 0.4859 0.4667 0.4283 AF102257 0.5018 0.4935 0.5476 0.4486 BL42 0.4513 0.4634 0.4513 0.4986 BM848 0.4941 0.4651 0.5273 0.4904 AF102246 0.5293 0.513 0.5732 0.5003 BM415 0.6564 0.5657 0.5706 0.4734 BM5004 0.5406 0.5479 0.4528 0.5603

117 CHAPTER 6

POPULATION VIABILITY OF ELK (CERVUS ELAPHUS) RECENTLY REINTRODUCED TO

ONTARIO, CANADA

ABSTRACT

Stochastic population models for elk {Cervus elaphus) reintroduced to four regions of Ontario were developed to examine possible population trajectories and efficacy of hypothetical management strategies. Stage-based population matrices for the female segment of the population were assembled using demographic parameters estimated from a field study, including annual survival rates determined via telemetry and productivity rates obtained from radioimmunoassay of feces for progesterone. Variability in survival and productivity was accounted for by adding a variance component corresponding to the observed inter-annual variability in stage-specific survival and pregnancy rates. Population projections revealed that for the Lake Huron-North Shore and Bancroft-North Hastings release areas, elk were at low risk of quasi-extinction (n=30), whereas populations in the Nipissing-French River and Lake of the Woods regions were likely to decline substantially during the projected 25-year time horizon. Variation in projected population trajectories among elk release sites likely can be attributed to site-specific effects of forage, predation, and climate on calf survival and recruitment. The models indicate that addition of more elk in the areas undergoing population decline would not appreciably change the population trajectory or extinction risk.

However, management efforts focused direcdy at improving calf survival and recruitment to levels comparable to growing elk populations may be effective; these efforts could include winter feeding programs and/or predator control. Finally, using Bancroft/North Hastings as a model population to evaluate the impacts of Parelaphostrongylus tenuis on a reintroduced

118 elk population, reductions of 5-20% in annual survival of yearling and adult elk likely would not cause the population to decline, although >25% decline in survival could be unsustainable. In addition, P. tenuis may limit elk population recovery in release sites where white-tailed deer populations are high.

INTRODUCTION

Reintroduction of animal populations into areas of historical occupation has become an increasingly important tool in conservation biology and is often accomplished via transplant of animals from current to historical range (IUCN 2003). Although the measure of recovery success is whether a self sustaining population can be established, the results of transplant efforts have often been equivocal (Witmer 1990). A variety of factors have contributed to past failures, including poor release protocols and small sample sizes, inadequate post-release monitoring and management, and the paucity of prognosticative exercises in assessing viability of recovering populations (Wolfe et al. 1996) . It follows that acquisition of reliable demographic estimates from the released population and their analysis in a population projection framework is essential to determining likelihood of growth and viability of reintroduced populations under a variety of environmental conditions and management scenarios.

Elk (Cervus elaphus) reintroduction has a long history in eastern North America, filled with both successes and failures. Prior to 1990 there were at least 7 attempts to restore elk to eastern North America, but long-term, successful establishment of free ranging elk populations only occurred in Pennsylvania and Michigan (Witmer 1990, Larkin et al. 2003).

Although these successes have contributed greatly to the formally scant knowledge of elk

119 ecology in eastern North America, detailed information about the necessary elements of a successful elk reintroduction and the processes by which success was achieved remains limited.

Elk were formerly native to Ontario and occupied the deciduous forest covering much of south-central Ontario (O'Gara and Dundas 2002). However, increasing human settlement, as well as demands for meat and agricultural land, resulted in the extirpation of elk in Ontario during the late 1800s and early 1900s (Ranta 1979, Witmer 1990, Ceballos and

Ehrlich 2002). Since that time, there have been several attempts to transplant elk to the province, but due to concerns regarding transmission of the parasite Vascioloides magna, most of these animals were destroyed before the population was fully established (Addison 1997).

Two small remnant populations managed to survive a transplant occurring in the 1930's, and in 1996 the free-ranging elk population in Ontario was estimated at approximately 60 animals (Bellhouse and Broadfoot 1998).

From 1998 to 2001, a total of 460 elk {Cervus elaphus) were transplanted from Elk

Island National Park (EINP), Alberta, and placed in holding pens in four release areas spaced broadly across Ontario (Rosatte et al. 2007). A total of 443 elk were released from the pens following variable holding periods. Each of the 4 release areas (Nipissing-French

River (NFR), Bancroft/North Hastings (BNH), Lake Huron-North Shore (LHNS), and

Lake of the Woods (LOW) were also targeted for additional releases of up to 200 female elk in subsequent years; however, in 2002 concerns regarding the transmission of Chronic

Wasting Disease halted further transplants into the province (Rosatte et al. 2007).

Consequently, there are currendy 4 relatively small and isolated elk populations in Ontario; because such populations tend to be subject to high inherent vulnerability to stochastic events (see Griffith et al. 1998, Caughley 1994), there is a need to assess status and prognosis

120 for each. Furthermore, marginal habitat at the periphery of their former range, high predator densities, and high prevalence of the parasite Parelaphostrongylus tenuis, may limit the growth of the elk populations in Ontario. Indeed, factors important to the success or failure of the recovery effort should be explored so as to inform management strategies encouraging population persistence (Komers and Curman 2000; Steury and Murray 2004).

STUDY AREA

The four elk reintroduction sites extend through Ontario, from Lake of the Woods

(LOW; 49° 15' N, 93° 43' W) in the northwest, Lake Huron-North Shore (LHNS; 46° 26' N,

83° 6' W) and Nipissing-French River (NFR; 46 ° 12' N, 80° 50' W) in the central part of the province, and Bancroft-North Hastings (BNH; 45° 02' N, 83° 29' W) in south-eastern

Ontario. Three of the release sites, LOW, NFR, and LHNS are located in the northern periphery of the historic range of elk in Ontario, while the BNH release is considered to be within the core historic range (Hutchinson et al. 1997). Pair-wise distance between release sites ranges from 250 km to 1200km, therefore each site is considered as distinct. The major

forest region represented in three of the four elk release sites (BNH, NFR, LHNS) is the

Great Lakes-St. Lawrence forest, a transition zone between northern boreal forest and southern temperate forest (Rowe 1972). These forests generally contain sugar maple (Acer saccharum), yellow birch (Betu/a luted), and beech (Fagusgrandifolid), as well as mixed softwoods of white (Pinus strobus) and red pine (P. resinosd), trembling aspen (Populus tremuloides), balsam fir (Abies balsamiferd), white birch (Betu/a papjriferd), and eastern hemlock (Tsuga canadensis;

Rowe 1972, Chambers et al. 1997, Thompson 2000). The Boreal Forest Region encompassed the LOW elk release site at the northern periphery of the historic elk range,

121 and was dominated by coniferous trees including black spruce (Picea mariand), white spruce

(Picea glaucd), and balsam fir [Abies balsamed) (Rowe 1972). Climate variability between areas includes a latitudinal temperature gradient, as well as a precipitation gradient from northwest to southeast (Anonymous 2003). Mean maximum snow depth in all elk release areas averages between 50 and 65 cm annually; however, spring green-up generally occurs one month earlier (mid to late April) in the more southern elk release site (i.e., BNH)

(Hutchinson et al. 1997). Potential competitors to elk in the areas include white-tailed deer

(Odocoi/eus virginianus) and moose (Alces alces), whereas predators include wolves (Canis lupus,

Canis lycaon), coyotes {Canis latrans) and black bears (Ursus americanus). Deer density is higher in the south (Hutchinson et al. 1997) while the density of wolves and black bears is higher in the NFR and LOW areas (Rosatte et al. 2003). Finally, human densities vary among the release areas with relatively low densities in the LOW, NFR, and LHNS release sites (1 person/1.6 km2), compared to much higher densities (15-19 per 1.6 km2) in the BNH region

(Hutchinson et al. 1997).

METHODS

Population Estimation

From 1998 to 2001 a total of 315 female elk were translocated from Elk Island National

Park, Alberta to four release sites in Ontario (Rosatte et al. 2007). Since release, elk populations at each of the release sites were surveyed annually (1998-2005), with aerial classification by age class and gender (Mcintosh et al. 2009). Because the majority of elk released in Ontario were radio-collared, elk population estimates were calculated annually using the Lincoln-Petersen estimator for closed populations (Chapman 1951). The number

122 of elk released in each site was used as the population vector in each model (Table 6.1), whereas subsequent population estimates (1999-2005) were used to validate results from the demographic-based population projections.

Recruitment

I evaluated productivity for reintroduced elk by assaying progestagen (P4) concentration in fecal samples collected during late gestation (March-April) (White et al. 1995). Fecal samples were collected during routine ground monitoring of radio-collared animals by locating recently-used feeding/bedding sites and collecting 8-10 pellets from individual pellet groups.

In roughly 75% of fecal collections, pellets were collected from known animals (i.e., females observed defecating); once a known animal was sampled, I sought to exclude further sampling of that individual during the year. In cases where fresh pellets were collected but individual identity was not known, fecal pellet size was used to exclude both adult male and young elk (i.e., calves) from the sample (see Christianson and Creel 2008, Maccracken and

Vanballenberghe 1987, Khan and Goyal 1993). Yearling elk could not be distinguished by measuring pellet length, but preliminary model exploration for the Ontario populations revealed low sensitivity to production levels in this particular cohort (T. Mcintosh, unpublished data).

Sample preparation and assay conditions followed standard protocol at the

Reproductive Physiology Laboratory, Metropolitan Toronto Zoo, Toronto, Ontario, Canada

(Brown et al 2002). The lower threshold for pregnancy was determined by assaying progesterone levels among 30 captive female elk at the zoo, known not to be pregnant during spring 2005. Both the lower and upper threshold was explored among free-ranging animals by opportunistically verifying the presence/absence of a calf among 15 free-ranging females shortly post-partum (see Murray et al. 2006) during spring 2005 and 2006. Because

123 neonatal calves could have died prior to field verification (i.e., observations were made 1-8 weeks after the calving period), I could not discount post-partum calf mortality and thus the

field vaUdation of progesterone levels is a liberal test of the threshold. However, preliminary model exploration for the population revealed relatively low sensitivity to productivity levels

for all cohorts (T. Mcintosh, unpublished data).

Following pregnancy evaluation based on established thresholds, inter-annual variation was assessed for each release site using chi-squared tests; in the absence of yearly effects, pregnancy rates were averaged across years for inclusion in deterministic population projection matrices.

Survival

Field monitoring of elk reintroduced to Ontario began immediately following their release (January 1998, February/March 1999, 2000, and 2001) and continued through to the

end of December 2005. All released elk were fitted with mortality\motion sensitive VHF radio-collars (Model LMRT-4; Lotek Engineering Inc., Newmarket, Ontario), except 30 of

60 animals released in 2000 in LOW, that were not collared. Opportunistically throughout

the study period collars were replaced on both released animals and a small number of those born in Ontario. The percent of the estimated elk population on a given site that was radio-

collared during the study period ranged between 25-97% in BNH (n=77), 56-100% in NFR

(n=139), 50-71% in LOW (n=65), and 75-100% (n=34) in LHNS. Elk reintroduced to the

BNH and LHNS were relocated weekly, whereas those released in NFR and LOW were relocated bi-weekly. Both ground and aerial telemetry techniques were regularly used for

survival monitoring and cause of death assessment.

Staggered-entry Kaplan-Meier (Pollock et al. 1989) was used to estimate stage-

specific (i.e., calves, yearlings, adults) annual survival rates for each release area. Using log-

124 rank tests, preliminary analyses revealed that adult female elk survival was significantly lower in the BNH, NFR, and LOW regions in the year following each release (BNH 5£2=3.48, df=5, P=0.013; NFR x2=2.59, df=7, P=0.006; LOW x2=2.92, df=5,P=0.027). This was largely attributed to high levels of post capture myopathy and transportation-related injuries.

Therefore, female elk dying within three months of release were censored from the analyses.

Survival was averaged across years for each release site and included in the subsequent population matrices (NFR=8 years, BNH=6 years, LOW = 6 years, LHNS=5 years). Inter- annual variation in survival was assessed for each release site using chi-squared tests (Pollock et al.1989); in the absence of yearly effects, survival rates were averaged across years for inclusion in deterministic population projection matrices.

Survival estimates for yearling females were based on data following each of the 9 elk releases (BNH=2 releases, NFR=4 releases, LOW=2 releases, LHNS=1 release). Although the sample size for yearly elk was low, preliminary model exploration for the Ontario elk populations revealed low sensitivity to yearling survival (T. Mcintosh, unpublished data).

For sites with more than one release, survival results were averaged across years after using log-rank tests to discount significant yearly variation (NFR, BNH, LOW). Elk calves born in

Ontario were not radio-collared; therefore, a direct measure of calf survival was not available and instead I used number of elk known to be pregnant from fecal progestagen concentrations versus the number of calves counted during the following winter

(February/March) calf surveys (Merrill 1987, Coughenour and Singer 1996); the difference between ratios approximated calf mortality rate during the interval.

Population Viability Analysis

Vital rate estimates from my field study were used to parameterize both deterministic and stochastic models describing elk population growth. Due to geographic isolation of

125 each elk population (> 200 km), I reasonably assumed population closure, developing separate projection models for each of the four elk release sites. Models were based on the stage-specific Lefkovitch transition matrix (Lefkovitch 1965, Caswell 2001) for the female segment of the population, where the dominant eigenvalue represents the finite growth rate

(A,) of the population (Morris and Doak 2002).

I parameterized models using female stage-specific survival and fecundity rates, with the assumption that the sex ratio at birth was parity. Sensitivity and elasticity analyses were exclusively deterministic, serving to evaluate the response of X to variability in each non-zero element of the transition matrix (Caswell 2001, Morris and Doak 2002). I considered high matrix sensitivity/elasticity to a particular vital rate as warranting additional attention to specific parameters for future management (Morris and Doak 2002).

For deterministic analyses, I assumed that elk vital rates remained unchanged during the study period (Taylor 1995, Boyce 2001). Stochasticity was then added to simulations by adding a variance component corresponding to the observed inter-annual variability in stage- specific survival and pregnancy rates. Simulation exercises assumed density-independent population growth, which is appropriate with an expanding population of recently-released individuals (Sargent and Oehler 2007). Monte Carlo simulations (Akcakaya et al. 1999) were carried out with 1000 replications and for 25 year time horizons. Following the population projections, linear regression of projected population size on years was used to determine the stochastic growth rate for each population (Caswell 2001, Morris and Doak 2002).

Simulations were conducted using PopTools Version 3.0.6 (CSIRO, Canberra, Australia).

Many species experience reduced growth at low densities (Allee 1938; Dennis 1989).

Such Allee effects can have important consequences for both population viability and

126 conservation of small and reintroduced populations. Therefore, matrix elements in the models were made a function of the total population size, whereby quasi extinction thresholds of 30, 100, and 200 elk were set. The quasi-extinction thresholds also served to determine the conditional time to extinction (Dennis et al. 1991, Morris and Doak 2002). If the population dropped below the quasi-extinction threshold, ecological and Allee effects were assumed to contribute to an extinction vortex. A beginning threshold of 30 animals was selected based on the long-term persistence of an estimated 30 elk in the NFR area of

Ontario (Bellhouse and Broadfoot 1998) and the persistence of elk populations in both

Michigan and Pennsylvania with < 30 animals (Moran 1973, Eveland et al. 1979).

Subsequent thresholds of 100 and 200 animals at each site were selected to reflect recovery goals for the populations (Rosatte et al. 2007).

Identification of the most effective population management strategies should be based on the relative contribution of vital rates to growth of the population and the ability to manage change in vital rates (Nichols and Hines 2002). I explored demographic outcomes of several management options by adjusting both matrix elements and population vectors in the model. More specifically, I sought to determine implications of releasing more elk in those areas where A<1. Accordingly, the initial population size in the reference model (i.e., number of female elk released in each site in past years minus those censored) was increased by 10%, 30%, 50%, and 100%. Comparisons of the cumulative probability of quasi- extinction (fhreshold= 100) were then conducted between the reference model (i.e., model with current population demographics) and those with a hypothetical increase in the number of elk released. Similarly, matrix elements that potentially could be influenced by management, such as increased survival of adults, yearlings, and calves, were altered and the

127 subsequent cumulative probability of quasi-extinction (threshold—100) was compared to that of the reference model (Murray et al. 2006, Morris and Doak 2002).

The parasite Parelaphostrongylus tenuis is considered to be an important source of population limitation in the BNH elk population, with 59% of elk mortalities (n=29) showing evidence of P. tenuis infection after only a limited exposure on the landscape

(Mcintosh et al. 2007). Accordingly, yearling and adult female survival was reduced by 5% increments to explore the potential demographic impact of this parasite on elk populations.

RESULTS

Recruitment

Elk pregnancy status assessment indicated that fecal P4 concentrations fell into 3 groups, each with widely separated confidence intervals with little or no overlap. In the study, concentrations of <10 [J-g/g wet fecal mass were considered not pregnant, >13 p.g/g wet mass indicated pregnancy, and 10-13 |J.g/g wet mass was equivocal (Figure 6.1). For captive elk that were known not to be pregnant (n=30), the lower threshold provided 100%

correct correspondence with a mean P4 concentration of 5.90 + 1.33. Validation of the results through field observations largely corroborated the pregnancy status assessment. For

cows known to have a calf during May-June, pregnancy detection via P4 assay was 87%

(n=15), with a mean P4 concentration of 6.19 + 1.85 SD. Thus, I surmise that the establishment of the lower pregnancy thresholds, coupled with my field validation exercise provided reasonable accuracy for pregnancy status assessment.

Application of progesterone thresholds for fecal samples collected in 2004 revealed that overall, 22% of cows (n=151) were not pregnant, 65% were pregnant, and the

128 remainder were inconclusive. During 2005, 26% (n^ 116) were considered not pregnant,

56% were pregnant, and the remainder were inconclusive. No inter-annual variation in pregnancy status was detected in any area; however, pregnancy rates were notably different between release sites, with rates being highest in LHNS (77%; n=26), followed by lower rates in BNH (63%; n=181), NFR (62%; n=24) and LOW (40%; n=40) (Table 6.2).

Survival

During January 1998-December 2005, Survival was monitored for 315 radio-collared

elk, with most animals in the study being adult females (66%), followed by female calves

(22%), and female yearlings (12%); the mean duration of monitoring was 897 +10 days per individual (n=315). Log rank tests indicated that annual survival rates differed among release sites for female yearlings (% =1.36, df=3 P=0.02), while no difference was detected

for adult females (% =1.34, df=3, P=0.56). Annual survival rates for yearling females aged

<2 years were highest for animals in the LHNS release (0.90; 0.82-0.98 95% CI), followed by

those in BNH (0.87; 0.81-0.93), LOW (0.73; 0.65-0.81), and NFR (0.60; 0.55-0.65). Adult

female survival averaged as high as 0.95 (0.88-0.99) in LHNS, followed by BNH (0.90; 0.84-

0.96), NFR (0.84; 0.77-0.88), and LOW (0.82; 0.75-0.89). Finally, female calves differed markedly in their annual survival rates, with rates highest for those in BNH (0.67), followed by LHNS (0.45), in LOW (0.30) and NFR (0.29) (Table 6.2). No inter-annual variation in

survival was detected in any area.

Population Viability Analysis

Stochastic simulations derived from the demographic models indicated that populations in LHNS (A=1.175; 1.065-1.285, 95% CI) and BNH (A=1.165; 1.032 -1.299)

should increase during the next 25 years, while those in LOW (A=0.972; 0.652-1.047) and

129 NFR (A=0.969; 0.935-1.003) are likely to face a steady decline (Table 6.2, Figure 6.2). In the short term (2003-2005), these predictions are qualitatively supported by annual population surveys indicating that elk populations increased by 1.2% and 1.3% in the LHNS and BNH regions, respectively, and declined by 23% and 56% in the NFR and LOW regions, respectively (Rosatte et al. 2007). Sensitivity and elasticity analysis indicated that the most important demographic parameter influencing the population growth rate in each release area was adult female survival, with 79% of the sensitivity and 69% of the elasticity attributed to contribution from this stage class. Calf survival was also important with 69% of the sensitivity and 53% of the elasticity attributed to this stage class, followed by yearling survival, adult and yearling recruitment rates, which were markedly lower (Table 6.3).

Results of stochastic population projections indicated a relatively low risk of quasi- extinction (thresholds= 30, 100, and 200 elk) for elk released in LNHS and BNH, and higher risk for elk released in the LOW and NFR (Figure 6.3). For elk released in both LHNS and

BNH, stochastic population projections gave a probability of quasi-extinction ~0 based on all extinction thresholds under consideration (up to 200 females in the population). In the

LOW region, stochastic simulation indicated that the population will constitute < 100 females of all ages through 25 years, and the risk of breaching the 30 female threshold was

0.119 after 25 years. In the NFR region, population projection indicated that although there is ~0 chance of the elk population declining <30 females, the risk of declining <100 females increased from 0 to 0.93, and the population would not reach the 200 female goal in the 25 year time horizon.

Using elk released in LOW as a model of a declining elk population in Ontario, it appears that increasing numbers of elk via further translocation would not appreciably change the risk of extinction (Figure 6.4). Even when the number of elk released in LOW

130 was increased by 100%, the risk of quasi-extinction (threshold=100 animals) remained high at 0.85 after the 25 year time horizon. Management strategies focused on increasing survival of adult and yearling females would likely increase overall growth rate of the population; however, current survival estimates are high, even in areas where the population is declining, and may be difficult to improve upon. In contrast, variation in the survival rate of elk calves in LOW to target levels (i.e. 0.45) dramatically decreased the risk of quasi extinction, producing a stable growth rate with only a 30% increase in calf survival (A= 1.005 CI= 0.921-

1.089; threshold n=100) and an increasing population after a 50% increase in calf survival

(A=1.025 CI= 0.971-1.079). Indeed, the cumulative probability of quasi-extinction following a 50% increase in calf survival decreased from 1 to 0 over the 25 year time horizon (Figure

6.5).

Finally, simulations designed to model the impacts oiPJenms on elk released in BNH indicated that reductions of 5-20% in annual survival of yearling and adult elk would not cause the population to decline (5% loss A= 1.126 [0.98-1.272], 10% loss A= 1.086

[CI=0.941-1.232], 15% loss A= 1.050 [CI=0.904-1.196], 20% loss A= 1.006 [CI=0.86-

1.152]). However, a reduction of 25% in the annual survival of both yearling and adult females would result in a negative growth rate (A= 0.984;[CI= 0.938-1.033]), likely resulting in a slow population decline (Figure 6.6).

DISCUSSION

In theory, newly-established populations should provide insight about maximum rates of numerical increase achieved when animals are released from limitation of resources

131 (Caughley and Birch 1971, Howell et al. 2003, Larkin et al. 2003). These rates of increase are expected to vary as a result of environmental influences (Caughley and Birch 1971, Caughley

1978) and have long been considered the best statistic for assessing success or failure of newly established populations (Morris and Doak 2002). Studies of both colonizing and introduced elk populations have reported annual rate of increase to be as high as 34-36%

(Murphy 1963, Gogan and Barrett 1987, McCorquodale et al. 1988). Similarly, elk reintroduced to Kentucky, Pennsylvania, and Michigan have demonstrated high survival and reproductive rates, characteristic of colonizing ungulate populations (Larkin et at. 2002,

Winner 1990), and presumably leading to high population growth rates. Recent studies also have suggested that population dynamics of large herbivores are strongly affected by stochastic environmental variation (Saether 1997). Indeed, there are a wide variety of factors accounting for demographic variability and the long-term persistence of a population

(Gaillard et al. 1998).

In this context, spatial variation in rates of increase among elk populations in

Ontario can be attributed to local environmental influences (Gogan and Barrett 1978,

Raedeke et al. 2002). Elk released into both LHNS and BNH experienced steady growth over the last 5-6 years and there are currendy several thriving sub-herds across the landscape

(Rosatte et al. 2007). For example, locally abundant forage (often from agricultural feed and winter white-tailed deer feeding sites), as well as mild winter environments and low predator densities likely have contributed to the relatively high rates of increase among LHNS and

BNH areas. Furthermore, the BNH site in particular is located in the core of the historic range of elk in Ontario, where in theory, one would expect a high likelihood of population growth and persistence (see Griffith et al. 1989, Wolfe et al. 1996).

132 The predicted numerical decline in both NFR and LOW elk populations is consistent with observations showing that elk numbers have failed to increase in the years following the reintroduction in those areas (Rosatte et al. 2007). These trends likely reflect higher adult and yearling mortality resulting from high predation rates in NFR and high predation and poaching rates in LOW (Rosatte et al. 2007). Also, the estimated calf survival rates in both regions were among the lowest reported for elk populations in North America

(Moran 1973, Bender et al. 2002, Myers 1999, Smith and Anderson 1998), again likely owing to high predation rates by both wolves and black bears. Furthermore, LOW in particular is on the northern periphery of the historic range of elk in Ontario, where overall habitat quality is likely marginal. Similarly, the NFR region is outside the core of historical elk range, where predator densities are high and quality forage seems limited.

For most long-lived species, rate of increase is sensitive to changes in adult female survival; however, survival rates of adult females typically have a narrow range of natural variation (Gaillard et al. 1998, Eberhardt 2002). Sensitivity and elasticity analyses indicated that in all elk release sites in Ontario, growth of the recovering population is primarily influenced by changes in adult female survival, followed by calf survival, yearling survival, adult fecundity, and yearling fecundity. Although management strategies focused on increasing survival of adult females likely would increase overall growth rate of the population over the long-term, current survival estimates are relatively high and unlikely to be subject to further increase. Research and management focused on improving survival of calves, however, would be more effective (Gaillard et al. 2000). Indeed, variation in survival rate of elk calves in areas where the population is declining (i.e., LOW and NFR) to levels experienced by the other Ontario populations dramatically reduced the risk of quasi extinction. Possible efforts to improve calf survival in these regions could include

133 establishment of a supplemental feeding program during the winter months and/or predator control around the release sites. However, the potential impact of these measures on elk population recovery remains complex and likely would require extensive efforts that may be more long-term than is reasonably expected.

Multiple releases have been required to establish elk in many of the cases of successful reintroduction (e.g., Pennsylvania, Kentucky) (Witmer 1990). Therefore, future management strategies in Ontario may involve the translocation of additional elk to each of the four release sites. In this study, the model predicted that in cases where elk populations were declining (i.e. LOW and NFR), addition of more elk would not appreciably reduce the risk of extinction. Therefore, Allee effects are unlikely to contribute to population decline and management of calf survival rates should provide a better avenue for improving population demographics.

Another important issue in predicting success or failure of reintroduction is the management of disease and parasites, and one parasite of concern for elk in Ontario is P. tenuis, which may become particularly prevalent in BNH due to high white-tailed deer densities and winter feeding by local residents. From 2000 to 2005, 59% of elk mortalities in BNH showed evidence of P. tenuis infection (Mcintosh et al. 2007). Moreover, 82% of white-tailed deer (the primary host pf P. tenuis) apparently had larval P. tenuis present in their feces (Mcintosh, 2003). Although given the short time on the landscape and the more recent trend in winter feeding which congregates both elk and white-tailed deer, the full impact of P. tenuis on elk in Ontario remains to be fully revealed. I modeled potential impacts of the parasite by reducing survival rates among population projections. It is clear that small reductions (5%-20%) in the survival of adult and yearling female elk beyond what has been experienced in the BNH region would result in a depressed growth rate. However,

134 reduction of 25% in the annual survival of both yearling and adult females would produce a negative growth rate, resulting in a slow population decline. Therefore, the potential impact of P. tenuis on restored eastern elk populations needs to be taken seriously by wildlife mangers. Failures of previous introduction attempts have been attributed to P. tenuis infections (Severinghaus and Darrow 1976), and other observations that P. tenuis was responsible for reduced growth and mortalities in elk populations are common (Eveland et al. 1979; Larkin et al, 2003).

In general, the number of individuals that are released during reintroductions is small. This means that founding groups are susceptible to the same dangers of increased extinction risks as small natural populations, including environmental fluctuations, demographic stochasticity, and inbreeding. Therefore, to achieve the highest probability of success, a primary goal of reintroduction should be to maintain the population above a critical density, below which the population will likely experience an unrecoverable decline.

Research has suggested that a minimum of 15 male and 75 female elk are needed to avoid inbreeding problems, while 150 male and 750 female elk are needed to avoid genetic drift

(Schonewald-Cox 1986). Projections indicate that elk released in both the LHNS and BNH regions will reach this target, while those in the NFR and LOW areas will likely fall short, thereby exacerbating the potential for extinction at these sites.

Management Implications

The results of my study demonstrate the need for reliable demographic estimates following a reintroduction and the importance of analysis in a population projection framework for determining the likelihood of growth and viability under a variety of environmental conditions and management scenarios. Indeed, the relatively simple population models employed in this study accurately describe both the growth and decline of

135 elk populations recently reintroduced to Ontario. The model and parameter estimates are likely to be useful for management planning for elk in Ontario; however, model projections are sensitive to the compounding effects of small changes in parameters and the close fit of the models to past population estimates does not imply the ability to make equally accurate estimates long-term. Model projections will be most useful for comparing hypothetical management scenarios and examining the factors important to the viability of elk populations reintroduced to Ontario in the short-term (i.e. 2-10 years). Vital rates should continue to be monitored and the population projections refined in each of the release sites to assure the continued relevance of the results.

Literature Cited

Akcakaya, H.R., Burgman, M.A., and L. Ginzburg. 1999. Applied population ecology. Sinauer, Sunderland, Massachusetts, USA.

Anonymous. 2003. Canadian climate normals 1981-2003. Environment Canada, Atmospheric Environment Service Report. Ottawa, Ontario, Canada.

Allee, W. C. 1938. The social life of animals. Norton, New York.

Beissinger, S.R. and M.I. Westphal. 1998. On the use of demographic models of population viability in endangered species management. Journal of Wildlife Management 62:821- 841.

Bellhouse, T. J., and J. D. Broadfoot. 1998. Plan for the restoration of elk in Ontario. Ontario Ministry of Natural Resources Report, Toronto, Ontario.

Bender, L. C, E. Carlson, S. M. Schmitt, and J. B. Haufler. 2002. Production and survival of elk (Cervus elaphus) calves in Michigan. American Midland Naturalist 148:163-171.

Boyce, M.S. 2001. Population viability analysis: Development, interpretation, and application. Pages 123-136 in T.M. Schenk and A.B. Franklin, editors. Modelling in natural resource management. Island, Washington, D.C., USA.

Bronson, F.H. 1989. Mammalian Reproductive Biology. Chicago University Press, Chicago, Illinois, USA.

136 Brook, B.W., O'Grady, J.J., Chapman, A.P., Burgman, M.A., Akcakaya, J.R., and R. Frankham. 2000. Predictive accuracy of population viability analysis in conservation biology. Nature 404:385-387.

Brown, J., Walker, S., and K. Steinman. 2002. Endocrine manual for reproductive assessment of domestic and non-domestic species. Conservation and Research Centre, Smithsonian's National Zoological Park, Front Royal Virginia.

Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation. Sinauer, Sunderland, Massachusetts, USA.

Caughley, G. 1994. Directions in conservation biology. Journal of Animal Ecology 63:215- 244.

Caughley, G. 1978. Analysis of vertebrate populations. John Wiley and Sons, Chichester, United Kingdom.

Caughley , G. and L.C. Birch. 1971. Rate of increase. Journal of Wildlife Management 35:658-663.

Chambers, B. A., Naylor, B.J., Nieppola, J., Merchant, B., and P. Uhlig. 1997. Field guide to forest ecosystems in central Ontario. South Central Region Science and Technology Report FG-01. Toronto, Ontario, Canada.

Chapman, D. G. 1951. Some properties of the hypergeometric distribution with applications to zoological sample censuses. University of California Publication in Statistics 1:131-

Christianson, D. and Creel, S. 2008. Risk effects in elk: sex-specific responses in grazing and browsing due to predation risk from wolves. Behavioural Ecology 19:1258-1266.

Coughenour, M.B. and F.J. Singer. 1996. Elk population processes in Yellowstone National Park under the policy of natural regulation. Ecological Applications 6:573-593.

Cross, P.C. and S.R. Beissinger. 2001. Using logistic regression to analyse the sensitivity of PVA models: a comparison of methods based on African wild dog models. Conservation Biology 16:258-261.

Dennis, B. 1989. Allee effects: population growth, critical density, and the chance of extinction. Natural Resource Modeling 3:481-538.

Dennis, B., Munholland, P.L., and, J.M. Scott. 1991. Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61:115-143.

Eberhardt, L.L. 2002. A paradigm for population analysis of long-lived vertebrates. Ecology 83:2841-2854.

137 Eveland, J. F., J. L. George, N. B. Hunter, D. M. Forney, and R. L. Harrison. 1979. A preliminary evaluation of the ecology of the elk in Pennsylvania. Pages 145-151 in M. S. Boyce, Haydon-Wing, L.D., editor. North American elk: ecology, behaviour, and management. University of Wyoming, Laramine.

Flook, D.R. 1970. Causes and implication of an observed sex differential in the survival of wapiti. Canadian Wildlife Service Bulletin Report Series 11, Ottawa, Ontario, Canada.

Franklin, I. R. 1980. Evolutionary change in small populations. In: M..E. Soule' and B. A. Wilcox (ed.) Conservation Biology: an Evolutionary-Ecological Perspective, p 135. Sinauer , Sunderland, Massachusetts, USA.

Galliard, J.M., Festa-Bianchet, M., and N.G. Yoccuz. 1998. Population dynamics of large herbivores: variable recruitment with constant adult survival. Trends in Ecology and Evolution 13:58-63.

Gaillard, J. M., Festa-Bianchet, M., Yoccoz, N.G., Loison, A., and C. Toigo. 2000. Temporal variation in fitness components and population dynamics of large herbivores. Annual review of Ecology and Systematics 31:367-393.

Gogan, P.J.P. and R.H.B. Barrett. 1987. Comparative dynamics of reintroduced elk populations. Journal of Wildlife Management 51:20-27.

Griffith, B., J. M. Scott, J. W. Carpenter, and C. Reed. 1989. Translocation as a species conservation tool: status and strategy. Science 245:477-480.

Howell, J.A., Brooks, G.C., Semenoff-Iving, M., and C. Greene. 2002. Population dynamics of tule elk at Point Reyes National Seashore, California. Journal of Wildlife Management 66: 478-490.

Hutchinson, B. C, W. B. Ranta, D. W. McKenney, V. E. Bower, H.J. Bosveld, J. Quiroulette, and B. C. Fraser. 1997. Determining the most suitable areas for elk restoration in Ontario, Canada.

IUCN (World Conservation Union). 2003. The re-introduction of species. Gland, Switzerland.

Khan I, Goyal SP. 1993. Fecal pellet measurements of manipur browantlered deer with respect to sex and age classes. Zoo Biology 12:561—565.

Komers, P.E. and GP. Curman. 2000. The effect of demographic characteristics on the success of ungulate populations. Biological Conservation 93:187-193.

Larkin, J. L., D. S. Maehr, J. J. Cox, D. C. Bolin, and M. W. Wichrowski. 2003. Demographic characteristics of a reintroduced elk population in Kentucky. Journal of Wildlife Management 67:467-476.

138 Larkin, J. L., D. S. Maehr, J. J. Cox, M. W. Wichrowski, and R. D. Crank. 2002. Factors affecting reproduction and population growth in a restored elk Cervus elaphus nelsoni population. Wildlife Biology 8:49-54.

Maccracken JG, Vanballenberghe V. 1987. Age related and sex related differences in fecal pellet dimensions of moose. Journal of Wildlife Management 51:360—364.

McCorquodale, S.M., Eberhardt, L.L., and L.E. Eberhardt. 1988. Dynamics of a colonizing elk population. Journal of Wildlife Management 52:309-313.

Mcintosh, T. E. 2003. Movements, survival and habitat use by elk {Cervus elaphus} reintroduced to northwestern Ontario. MSc Thesis, Lakehead University, Thunder Bay, Ontario.

Mcintosh, T.E., Rosatte, R.C., Hamr, J., and D.L. Murray. 2009. Development of a sightability model for low-density elk populations in Ontario, Canada. Journal of Wildlife Management 73:580-585.

Mcintosh, T. Rosatte, R., Campbell, D., Welch, K., Fournier, D., Spinato, M., and O. Ogunremi. 2007. Evidence of Parelaphostrongylus tenuis infections in free ranging elk {Cervus elaphus) in southern Ontario. Canadian Veterinary Journal 48:1146-1154.

Meretsky, V., Snyder, N., Beissinger, S., Clendenen, D. and Wiley, J. 2000. Demography of the California condor: Implications for Re-establishment. Conservation Biology 14: 957-967.

Merrill, E.H. 1987. Population dynamics and habitat ecology of elk in the Mount St. Helens blast zone. Ph.D. Dissertation, University of Washington, Seatde, USA.

Minta, S., and M. Mangel. 1989. A simple population estimate based on simulation for capture-recapture and capture-resight data. Ecology 70:1738-1751.

Moran, R. J. 1973. The Rocky Mountain elk in Michigan. 267, Michigan Department of Natural Resources, Wildlife Division, Lansing, Michigan.

Morris, W.F. and D.F. Doak. 2002. Quantitative Conservation Biology. Sinauer, Sunderland Massachusetts, USA.

Murphy, D.A. 1963. A captive elk herd in Mississippi. Journal of Wildlife Management 27:411-414.

Murray, D.L., Cox, E.W., BaUard, W.B., Whitlaw, H.A., Lenarz, M.S., Custer, T.W., Barnett, T., and T.K. Fuller. 2006. Pathogens, nutritional deficiency, and climate influences on a declining moose population. Wildlife Monographs 166:1-30.

139 Myers, W. D. 1999. An assessment of elk population trends and habitat use with special reference to agricultural damage zones in the northern Blue Mountains of Washington. Final Report, Washington Department Fish and Wildlife, Olympia. 172 P-

Nelson, L.J. and J.M. Peek. 1982. Effects of survival and fecundity on rate of increase of elk. Journal of Wildlife Management 46:535-540.

Nichols, J.D. andJ.E. Hines. 2002. Approaches for the direct estimation of A, and demographic contribution to A, using capture-recapture data. Journal of Applied Statistics 29:539-568.

Pollock, K.H., Winterstein, S.R., Bunck, CM. and P.D. Curtis. 1989. Survival analysis in telemetry studies: the staggered-entry design. Journal of Wildlife Management 53:7- 15.

Raedeke, K.J., Millspaugh, J.J., and P.E. Clark. 2002. Population characteristics. Pages 448- 491. in D.E. Toweill and J.W. Thomas, editors. North American elk: ecology and management. Wildlife Management Institute, Washington, D.C., USA.

Raifhel, J.D., Kauffman, M.J., and D.H. Pletscher. 2007. Impact of spatial and temporal variation in calf survival on growth of elk populations. Journal of Wildlife Management 71:795-803.

Reed, J.M., Mills, L.S., Dunning, J.B., Menges, E.S., McKelvey, K.S., Fry, R., Beissinger,S.R., Anstett, M.C. and P. Miller. 2002. Emerging issues in population viability analysis. Conservation Biology 16:7-19.

Rosatte, R., J. Hamr, J. Young, I. Filion, and H. Smith. 2007. The restoration of elk (Cervus elaphus) in Ontario, Canada 1998-2005. Restoration Ecology 15:34-43.

Rowe, J. S. 1972. Forest regions of Canada. Canadian Forest Service Publication Report. 1300. Ottawa, Ontario, Canada.

Sargent, G.A. and M.W. Oehler, Sr. 2007. Dynamics of newly established elk populations. Journal of Wildlife Management 71:1141-1148.

Sarrizan, F. and Legendre, S. 2000. Demographic approach to releasing adults versus young in reintroductions. Conservation Biology 14:488-500.

Schonewald-Cox, C. 1986. Founding populations in conservation. Pages 519 in S. K. Majumdar, F. J. Brenner, and A. F. Rhodes, editors. Endangered and threatened species programs in Pennsylvania and other states. Pennsylvania Academy of Science, Easton.

Sevringhaus, C. W., and R. W. Darrow. 1976. Failure of elk to survive in the Adirondacks. New York Fish and Game 23:98-99.

140 Smith, B. L., and S. H. Anderson. 1998. Juvenile survival and population regulation of the Jackson Elk Herd. Journal of Wildlife Management 62:1036-1045.

Taylor, B.L. 1995. The reliability of using population viability analysis for risk classification of species. Conservation Biology 9:551-558.

Thompson, I. D. 2000. Forest vegetation of Ontario: factors influencing landscape change. Pages 336 in Perera A. H., Euler D. L., Thompson I. D., editors. Ecology of a managed terrestrial landscape: patterns and processes of forested landscapes in Ontario. University of British Columbia Press, Vancouver, Canada.

White, G.C. 2000. Population viability analysis. Pages 288-331 in L Boitani and T.K. Fuller editors. Research techniques in animal ecology: controversies and consequences. Columbia University, New York, New York, USA.

White, P. J., R. A. Garrott, J. F. Kirkpatrick, and E. V. Berkeley. 1995. Diagnosing pregnancy in free-ranging elk using fecal steroid metabolites. Journal of Wildlife Diseases 31:514-522.

Witmer G. 1990. Reintroduction of elk in the United States. Journal of the Pennsylvania Academy of Science 64:131-135.

Wolfe, CM., Griffith, B., Reed, C, Temple, S.A. 1996. Avian and mammalian rein traductions: update and reanalysis of 1987 survey data. Conservation Biology 10:1142-1154.

141 Table 6.1: Age breakdown of female elk reintroduced to Ontario from 1998 to 2001.

Release site* Date Adults Yearlings Call NFR Mar. 1998 33 Na 0 NFR Jan. 1999 42 Na 13 NFR Mar. 2000 20 Na 13 NFR Feb. 2001 10 Na 8 BNH Jan. 2000 32 4 10 BNH Jan.2001 18 2 11 LOW Jan. 2000 32 1 6 LOW Feb. 2001 15 6 5 LHNS Dec. 2000 27 4 3 Total 229 17 69* *Nipissing-French River=NFR, Bancroft/North Hastings=BNH, Lake of the Woods=LOW Lake Huron-North Shore=LHNS * sex unknown for one calf

142 01 00 ro 4-* c

<10 10-13 >13

PdG ug/g

Figure 6.1: Distribution of fecal progesterone concentrations in wild elk sampled from each release site in Ontario, Canada (2004-2005), where concentrations of 10 [xg/g wet fecal mass were considered not pregnant, >13 ug/g wet mass indicated pregnancy, and 10-13 ^g/g wet mass was equivocal.

143 Table 6.2: Demographic variables used in stage-based model for female elk released into the NFR, BNH, LOW, and LHNS regions of Ontario, Canada (1998-2001).

Estimate Matrix Element NFR BNH LOW LHNS Adult survival 0.839 (±0.04) 0.899 (±0.06) 0.822 (±0.07) 0.950 (±0.08) Yearling survival 0.600 (±0.05) 0.865 (±0.06) 0.731 (±0.08) 0.899 (+0.08) Calf survival 0.290 0.67 0.300 0.45 Adult 0.699 0.626 0.650 0.77 productivity ^ 0.969 (0.935- 1.165 (1.032- 0.972 (0.652- 1.175 (1.065- 1.003) 1.298) 1.047) 1.299) Elk release sites; Nipissing-French River=NFR, Bancroft/North Hastings=BNH, Lake of the Woods=LOW, Lake Huron- North Shore=LHNS Note: All matrix elements were estimated directly from data collected from radio-collared elk in each for the four release sites in Ontario. Yearling productivity was assumed to be 0. PreHminary sensitivity analyses demonstrated that yearling productivity contributes little to the growth rates of the 4 elk populations and assays of progestagen (P4) concentration in fecal samples could not discern the contribution of yearling elk, and were therefore captured in the estimated rate for adult females.

144 Table 6.3: Sensitivity and elasticity of vital rates for female elk released into NFR, BNH, LOW, and LHNS regions of Ontario, Canada (1998-2001).

Sensitivity Elasticity Matrix Element NFR BNH LOW LHNS NFR BNH LOW LHNS Adult survival 0.789 0.686 0.764 0.723 0.683 0.529 0.645 0.584 Yearling survival 0.146 0.292 0.177 0.212 0.106 0.158 0.118 0.139 Calf survival 0.353 0.273 0.383 0.362 0.106 0.158 0.118 0.139 Adult productivity 0.170 0.212 0.157 0.181 0.106 0.158 0.118 0.139 Elk release sites; Nipissing-French River=NFR, Bancroft/h rth Hastings=BNH, Lake of the Woods=LOW, Lake Huron-North Shore=LHNS

145 180 5000 b 160 4500 /*^ 4000 140 z 5- 35CO ~"* 120 01 0) N £ 3000 (/» 100 c § 2500 o *- 80 y s? ^ re £ 2000 -? a. j/^ <* 60 §• 15C0 OoL 40 °" 1000 _^^ -

20 500 ^SKC^^^^ ~~ -si-<- «5*Hf=^ •2MB- «» -—«=* 0 1 1 1 1 1 1 1 I 1 ! 1— I ' 0 riii 1 I 1 1 1 III 1 • t 1 1 1 1 1 i i i ]I 5 13 17 21 25 1 I) 9 13 17 21 25

Years Years

4000 d 3500

3000 2 2500 N / C 0 2000 JS 3 1500 ! Q. a P 30 0 a. 1000 20 500 10 C3 E»B»—SfflSS=J n i ™* 0 i 13 17 21 1 5 9 13 17 21 25 Years Years

Figure 6.2: Predicted number (+/- 95% CI) of female elk in the a. N R, b. BNH, c. LOW, and d. LHNS regions of Ontario, Canada over a 25 year time horizon.

146 a> Cumulative probability of quasi Cumulative probability of quasi II extinction extinction

pr pr. o Cumulative probability of quasi £j To3 Cumulative probability of quasi- N' O extinction O extinction PS ppppppppp p ooooooooo OHNJUisUlijlvjixiiD o pt. CJh-if^JUJ^LnCTI-^JCXJ^iJI—* 0 PS >T3 r H ro' n C Un J O o _--- PS 0> 1 pr - • o r? U3 1 B - - - '

pr n ------rti r" OJ pr at

re P I—* o o re F no o" i—* a. p pr ro G- CL =3 O O o- o II TO >• O la es - 10% Increase .a o a. --30% Increase OJ — 50% Increase _ro E —• 10O% Increase (—»

13 17 21 25

Years

Figure 6.4: Changes in the cumulative probability of quasi-extinction for female elk released in the LOW region of Ontario, Canada (2000-2001) resulting from increases in the number of elk (increases of 10%-100%) released at the site.

148 1 • 0.9 3 o \ •"*•«. o 0.8 --^ rH ^ ;>- II 0.7 •*—» O Y- 15 -C 0.6 TO O) O 0.5 10% Increase £3. •*-*c 0.4 o •=> <=^ <=> <= 30% Increase TO 0.3 50% Increase E 0.2 3 0.1

0 Ill' '1 i i ) ]L 5 9 13 17 21 25

Years

Note: 10% increase in calf survival = 0.33, 30% increase in calf survival = 0.39, 50% increase in calf survival = 0.45

Figure 6.5: Changes in the cumulative probability of quasi-extinction (fhreshold=100) for female elk released in the LOW region of Ontario, Canada (2000-2001) resulting from increases in calf survival (10%-50%).

149 1400 1200

jg 1O00

800 5% Loss 10% Loss 600 • 15% Loss 400 Populatio n • 20% Loss 200 •25% Loss U*-2_ 0 13 17 21 25

Years

Figure 6.6: Changes in the population growth rate of female elk reintroduced to the BNH region of Ontario, Canada (2000-2001), resulting from a 5%-25% drop in yearling and adult female survival representative of loss related to Varelaphostrongylus tenuis.

150 CHAPTER 7

CONCLUSIONS

The reintroduction of a free-ranging elk population to Ontario provided the unique opportunity to study the ecology of elk and test basic ecological theory in a semi-controlled environment in which community and ecosystem processes could be studied without the loss of complexity. The results of this study provided insights to help both researchers and managers to better understand, predict, and possibly mitigate factors affecting the dynamics of the recently reintroduced Ontario elk population and better understand the demographic problems inherent in new and establishing populations. The specific objectives of my research were to i) develop an accurate method of estimating the size and composition of the elk populations in Ontario; ii) evaluate patterns of mortality and factors related to survival of elk in Ontario, including an examination of the impacts of meningeal worm,

Parelaphostrongylus tenuis; iii) collect empirical data on the level of genetic diversity in the reintroduced elk population; and iv) create a population model in which the predicted viability of the Ontario elk population could be assessed and management options that encourage demographic growth and stability evaluated.

A first step in the development of any wildlife monitoring program is the establishment of an effective means of assessing population size. The locally-validated sightability model developed in this study, the first for elk in eastern Canada, accounted for both low densities of elk and dense forest cover in elk release areas in Ontario. The model should aid in the detection of meaningful changes in the four distinct elk populations in

Ontario, thereby allowing for better management towards population growth and long-term stability. Furthermore, following validation, this model may be applicable to other jurisdictions in eastern North America, including populations of elk reintroduced to the Lake

151 of the Woods and Lake Huron-North Shore regions of Ontario, where elk densities are low and forest cover is high. To maximize sightability and overall accuracy of the model, I recommend conducting the survey when detection rates are highest, elk are more gregarious, and with rigorous standardization of the survey protocol (i.e., search speed, altitude, aircraft type, observer experience, weather conditions).

Although the factors influencing mortality and survival are relatively well understood for established populations, less information is known about new and establishing populations, including those recently reintroduced to a novel landscape. My results reveal clear patterns of increased mortality risk that can inform elk population restoration and management, as well as reintroduction methodologies for wildlife recovery programs. The results indicate that post-capture myopathy and transportation-related injuries can be an important cause of mortality during the initial stage of a wildlife reintroduction project and should be considered a predictable factor to incorporate into planning. Investigation into methods that work to minimize the effects of capture and transportation related deaths, such as improved capture, care and transportation techniques, are recommended as the establishment of a new group of individuals often depends on short-term local survival of released individuals. The results also suggest that survival of elk is largely influenced by the method of introduction to the novel landscape and behaviour in the first year following release. Therefore, actions such as holding animals in an enclosure prior to release can mitigate disruption of natural group structure and provide acclimation and familiarity to the novel environment. Finally, the negative effect of proximity to humans implies that release sites further from human settlement, coupled with efforts to rninimize dispersal from the carefully chosen release site can improve the chances of population persistence.

152 Another important issue in predicting success or failure of reintroduction is the management of disease and parasites. One parasite of concern for elk in Ontario is

Pare/aphostrongy/us tenuis which has been detected in the Bancroft-North Hastings region and may become particularly prevalent here due to high white-tailed deer densities and winter feeding by local residents. From 2000 to 2005, 59% of reviewed elk mortalities in Bancroft-

North Hastings showed evidence of P. tenuis infection. Moreover, 82% of white-tailed deer, the primary host pf P. tenuis, apparently had larval P. tenuis present in their feces. Although given the short time on the landscape and the more recent trend in winter feeding which congregates both elk and white-tailed deer, the full impact of P. tenuis on elk in Ontario remains to be fully revealed. Modelling clearly indicated that small reductions (5%-20%) in the survival of adult and yearling female elk beyond what has been experienced in the BNH region would result in a depressed growth rate. However, reduction of 25% in the annual survival of both yearling and adult females would produce a negative growth rate, resulting in a slow population decline. Therefore, the potential impact of P. tenuis on restored eastern elk populations needs to be taken seriously by wildlife mangers. Continued monitoring of cause-specific mortality is recommended, as is reducing or limiting the number of feeding sites where white-tailed-deer and elk are brought into unnaturally close contact.

Although likely less important for short-term population persistence, genetic diversity may be a critical factor determining the long-term persistence of elk populations in

Ontario. The results of my study show that across all four populations of elk, no significant deviations from Hardy-Weinberg expectations were detected, the overall number of alleles detected per locus ranged from 1 to 12, unique alleles were detected in each population and there were no marked differences in genetic variation between the source population and the four Ontario elk populations at the time of release. Starting from a population of 120

153 individuals and expanding rapidly to an estimate of 426-647 individuals in 2008, elk released in the Bancroft-North Hastings region are likely to maintain or improve their genetic diversity over the long-term. Elk released in the Nipissing-French River (n= 172) and Lake of the Woods (n=104) regions have experienced population decline since release and may face genetic consequences such as reduced diversity, lower fitness, and possible extirpation due to extended bottlenecks. Similarly, elk released in the Lake Huron-North Shore region may also experience long-term genetic decline as only 47 individuals were released into this isolated region of the province, the number of alleles per locus was the lowest among the four populations, and population growth to date been moderate (estimated 80-100 individuals in 2009). Genetic restoration by augmenting these populations with further elk translocations could help to avoid the possible consequences of reduced genetic diversity.

Continued, long-term monitoring of the genetic diversity in each of the elk release sites, in particular those elk that were born in Ontario is recommended to further elucidate the impact of restoration strategies and post-restoration management on the retention of genetic variability in the Ontario elk populations.

Finally, stochastic population models for elk [Cervus elaphus) reintroduced to four release sites in Ontario were developed to examine possible population trajectories and efficacy of hypothetical future management strategies. Population projections revealed that for the Lake Huron-North Shore and Bancroft-North Hastings release areas, elk were at low risk of quasi-extinction, whereas populations in the Nipissing-French River and Lake of the

Woods regions were likely to decline substantially during the projected 25-year time horizon.

Variation in projected population trajectories among elk release sites likely can be attributed to site-specific effects of forage, predation, and climate on calf survival and recruitment. The models indicate that addition of more elk in the areas undergoing population decline would

154 not appreciably change the population trajectory or extinction risk. However, management efforts focused direcdy at improving calf survival and recruitment to levels comparable to growing elk populations may be effective; these efforts could include winter feeding programs during severe winters and/or predator control. Finally, using Bancroft-North

Hastings as a model population to evaluate the impacts of Parelaphostrongylus tenuis on a reintroduced elk population, reductions of 5-20% in annual survival of yearling and adult elk likely would not cause the population to decline, although >25% decline in survival could be unsustainable.

In conclusion, the ecosystems in which wildlife populations are managed are dynamic and continued monitoring and future research is vital to the understanding of elk populations in Ontario, as well as new and establishing wildlife populations elsewhere. Just as other researchers have concluded, the results of this study demonstrate the importance of continued monitoring to assess patterns of mortality, factors influencing the survival of elk, and the growth rate of elk populations. By integrating these findings, managers will be able to develop effective strategies for the conservation of elk in Ontario and, more broadly, strategies important for new and establishing wildlife populations.

MANAGEMENT IMPLICATIONS

Based on the results of my study, several recommendations can be made that will help managers continue to accurately assess the viability of elk populations in Ontario and to develop management strategies that encourage demographic growth and stability. The results of my study may also be useful in improving reintroduction methodologies and increasing the chance of success for future reintroduction efforts.

155 To accurately assess the viability of elk recently reintroduced to Ontario, regular numerical estimates of abundance, as well as continued monitoring and assessment of vital rates such as survival, fecundity, and population growth should be continued for all elk populations in Ontario. These data can be used to assess the current status of each elk population, as well as update stochastic population models that examine possible population trajectories and the efficacy of hypothetical management strategies. This may be of particular importance in the Lake of the Woods and Nippising French regions of Ontario, where current models indicate probable declines over the next 25 years. Management efforts focused directly on improving calf survival and recruitment levels comparable to growing elk populations may be effective in these regions and should be further explored.

The potential impact of P. tenuis on elk populations in Ontario should be taken seriously by managers and monitoring of the prevalence, frequency and impact of the parasite is recommended. This may be of particular importance in the Bancroft-North

Hastings region, where the greatest impact of the parasite has been seen. Further, efforts to reduce feeding sites where white-tailed deer, the primary host for P. tenuis, and elk are brought into unnaturally close contact are recommended to reduce transmission of the parasite.

Finally, although the genetic diversity present in the 4 Ontario elk populations is likely not important in the short-term, it may be an important factor determining the persistence of elk populations in Ontario in the future. Efforts to maintain positive population growth rates and maintain population stability are recommended. As well, genetic augmentation should be considered to avoid bottlenecks and founder effects in those regions that currently have small populations and slow rates of increase. In the long-term,

156 monitoring of genetic diversity of the Ontario elk population is recommended to assess genetic changes in the populations are they become established in Ontario.

Based on the results of my study several recommendations related to improving reintroduction methodologies and increasing the chance of success for future reintroduction efforts can be made. First, mortality caused by post-capture myopathy and transportation- related injuries can be an important immediate cause of death for translocated animals and should be considered a predictable factor that is incorporated into translocation planning.

Second, the results of my study indicated that survival was influenced by the method of introduction to the landscape and behaviour in the first year following release. Action such as prolonged holding time in an enclosure following release can mitigate disruption of natural group structure and provide acclimation and familiarity to the novel environment which can improve rates of survival. Finally, release sites farther from human settlement, coupled with efforts to minimize dispersal for a carefully chosen release site can improve the

survival of translocated animals.

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